[The efficacy and safety of immunotherapy combined with chemotherapy neoadjuvant in locally advanced resectable hypopharyngeal squamous cell carcinoma]

Objective: To explore the efficacy and safety of immunoneoadjuvant therapy with pembrolizumab combined with chemotherapy in locally advanced resectable hypopharyngeal squamous cell carcinoma patients. Methods: This study was a prospective, single arm, single center clinical study that was opened for enrollment in April 2021. Patients who met the inclusion criteria at the Cancer Hospital of the Chinese Academy of Medical Sciences were treated with neoadjuvant therapy of pembrolizumab combined with cisplatin and paclitaxel, and after treatments, received surgery and postoperative adjuvant therapy. The main endpoint of this study was postoperative pathological complete response (pCR), and other observations included adverse reactions and long-term prognoses of patients after neoadjuvant therapy. Results: By September 2023, a total of 23 patients who underwent neoadjuvant therapy and surgery were enrolled in the study and all patients were males aged 49-74 years. All patients were locally advanced stage, including 3 patients in stage Ⅲ and 20 patients in stage Ⅳ. There were 12 cases of primary lesions with posterior ring involvement accompanied by fixation of one vocal cord and 20 cases of regional lymph node metastases classified as N2. Eighteen cases received a two cycle regimen and 5 cases received a three cycle regimen for neoadjuvant therapy. The postoperative pCR rate was 26.1% (6/23), with no surgical delay caused by adverse drug reactions. The laryngeal preservation rate was 87.0% (20/23). Pharyngeal fistula was the main surgical complication, with an incidence of 21.7% (5/23). The median follow-up time was 15 months, and 3 patients experienced local recurrence. Conclusions: The immunoneoadjuvant therapy of pembrolizumab combined with chemotherapy has a high pCR rate in locally advanced resectable hypopharyngeal squamous cell carcinoma, with increased laryngeal preservation rate and no significant impact on surgical safety.

Study of the f_{0}(980) and f_{0}(500) Scalar Mesons through the Decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}

Using e^{+}e^{-} collision data corresponding to an integrated luminosity of 7.33  fb^{-1} recorded by the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, we present an analysis of the decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}, where the D_{s}^{+} is produced via the process e^{+}e^{-}→D_{s}^{*±}D_{s}^{∓}. We observe the f_{0}(980) in the π^{+}π^{-} system and the branching fraction of the decay D_{s}^{+}→f_{0}(980)e^{+}ν_{e} with f_{0}(980)→π^{+}π^{-} measured to be (1.72±0.13_{stat}±0.10_{syst})×10^{-3}, where the uncertainties are statistical and systematic, respectively. The dynamics of the D_{s}^{+}→f_{0}(980)e^{+}ν_{e} decay are studied with the simple pole parametrization of the hadronic form factor and the Flatté formula describing the f_{0}(980) in the differential decay rate, and the product of the form factor f_{+}^{f_{0}}(0) and the c→s Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| is determined for the first time to be f_{+}^{f_{0}}(0)|V_{cs}|=0.504±0.017_{stat}±0.035_{syst}. Furthermore, the decay D_{s}^{+}→f_{0}(500)e^{+}ν_{e} is searched for the first time but no signal is found. The upper limit on the branching fraction of D_{s}^{+}→f_{0}(500)e^{+}ν_{e}, f_{0}(500)→π^{+}π^{-} decay is set to be 3.3×10^{-4} at 90% confidence level.

[The predictive value of dynamic changes of neutrophil/lymphocyte ratio (NLR) combined with the model of end-stage liver disease (MELD) score in patients with acute-on-chronic hepatitis B liver failure]

Objective: To determine the predictive value of dynamic changes of neutrophil/lymphocyte ratio (NLR) combined with the model of end-stage liver disease (MELD) score in patients with acute-on-chronic hepatitis B liver failure. Methods: Patients with acute-on-chronic hepatitis B liver failure who were hospitalized in the Department of Hepatology of Qilu Hospital of Shandong University from January 2010 to July 2023 were retrospectively enrolled. According to the clinical outcomes of patients within 30 days of admission, they were divided into the survival group and the death group. The dynamic changes in NLR and initial values on day 3, 5, 8, and 12 in two groups were analyzed for the diagnostic value of 30-day prognosis in patients with acute-on-chronic hepatitis B liver failure. Logistic regression analysis and machine learning XGBoost algorithm were used to evaluate the risk factors influencing the prognosis of patients at 30 days. Receiver operating characteristic(ROC) curve was used to evaluate the diagnostic value of NLR and initial value change combined with MELD score on day 12 of admission in patients with chronic acute hepatitis B liver failure. Results: A total of 243 patients were enrolled in the study, including 145 patients in the survival group [115 males, 30 females, aged 25-74 (47±11)] and 98 patients in the death group [80 males, 18 females, aged 22-80 (49±13) ]. The median initial NLR of survival group and death group were 3.5 (2.1, 5.3) and 4.9 (2.9, 8.3), respectively, and the difference was statistically significant (P=0.003). The variation of NLR from the initial value on day 3, 5, 8, and 12 in the survival group [1.6 (0, 4.3), 1.9 (-0.2, 4.1), 2.0 (-0.1, 4.3) and 2.9 (0.3, 7.0), respectively] were lower than that in the death group [3.2 (0.9, 7.5), 5.1 (1.8, 7.6), 5.8 (2.0, 10.6) and 9.6 (3.5, 16.4), respectively] (all P<0.001). Logistic regression multivariate analysis showed that the changes in NLR on the 12th day and initial value (OR=1.07,95%CI:1.01-1.14, P=0.014), the changes in NLR on the 3rd day and initial value (OR=2.71, 95%CI: 1.32-5.55, P=0.007), the initial value of NLR (OR=1.18,95%CI:1.01-1.37,P=0.035) and fibrinogen (OR=0.21,95%CI:0.05-0.96,P=0.044) were related factors for death within 30 days. Machine learning XGBoost algorithm showed that the weight of the change between the NLR on the 12th day and the initial value was the highest. The area under the ROC curve of the combined MELD score was 0.812 (95%CI: 0.728-0.895), the specificity was 67.78%, and the sensitivity was 82.35%. Conclusion: Dynamic change of NLR combined with MELD score has high predictive value for the short-term prognosis of patients with acute-on-chronic hepatitis B liver failure.

[Surgical treatment and prognosis analysis of hilar cholangiocarcinoma]

Objective: To investigate the surgical treatment effect and prognostic factors of hilar cholangiocarcinoma. Methods: This is an ambispective cohort study. From August 2005 to December 2022,data of 510 patients who diagnosed with hilar cholangiocarcinoma and underwent surgical resection at the Hepatobiliary Center of the First Affiliated Hospital of Nanjing Medical University were retrospectively collected. In the cohort,there were 324 males and 186 females,with an age of (M (IQR)) 63(13)years (range:25 to 85 years). The liver function at admission was Child-Pugh A (343 cases,67.3%) and Child-Pugh B (167 cases,32.7%). Three hundred and seventy-two(72.9%) patients had jaundice symptoms and the median total bilirubin was 126.3(197.6) μmol/L(range: 5.4 to 722.8 μmol/L) at admission. Two hundred and fourty-seven cases (48.4%) were treated with percutaneous transhepatic cholangial drainage or endoscopic nasobiliary drainage before operation. The median bilirubin level in the drainage group decreased from 186.4 μmol/L to 85.5 μmol/L before operation. Multivariate Logistic regression was used to identify the influencing factors for R0 resection,and Cox regression was used to construct multivariate prediction models for overall survival(OS) and disease-free survival(DFS). Results: Among 510 patients who underwent surgical resection,Bismuth-Corlett type Ⅲ-Ⅳ patients accounted for 71.8%,among which 86.1% (315/366) underwent hemi-hepatectomy,while 81.9% (118/144) underwent extrahepatic biliary duct resection alone in Bismuch-Corlett type Ⅰ-Ⅱ patients. The median OS time was 22.8 months, and the OS rates at 1-,3-,5-and 10-year were 72.2%,35.6%,24.8% and 11.0%,respectively. The median DFS time was 15.2 months,and the DFS rates was 66.0%,32.4%,20.9% and 11.0%,respectively. The R0 resection rate was 64.5% (329/510), and the OS rates of patients with R0 resection at 1-,3-,5-and 10-year were 82.5%, 48.6%, 34.4%, 15.2%,respectively. The morbidity of Clavien-Dindo grade Ⅲ-Ⅴ complications was 26.1%(133/510) and the 30-day mortality was 4.3% (22/510). Multivariate Logistic regression indicated that Bismuth-Corlett type Ⅰ-Ⅲ (P=0.009), hemi-hepatectomy and extended resection (P=0.001),T1 and T2 patients without vascular invasion (T2 vs. T1:OR=1.43 (0.61-3.35),P=0.413;T3 vs. T1:OR=2.57 (1.03-6.41), P=0.010;T4 vs. T1, OR=3.77 (1.37-10.38), P<0.01) were more likely to obtain R0 resection. Preoperative bilirubin,Child-Pugh grade,tumor size,surgical margin,T stage,N stage,nerve infiltration and Edmondson grade were independent prognostic factors for OS and DFS of hilar cholangiocarcinoma patients without distant metastasis. Conclusions: Radical surgical resection is necessary to prolong the long-term survival of hilar cholangiocarcinoma patients. Hemi-hepatectomy and extended resection,regional lymph node dissection and combined vascular resection if necessary,can improve R0 resection rate.

Exhalomics as a noninvasive method for assessing rumen fermentation in dairy cows: Can exhaled-breath metabolomics replace rumen sampling?

Previously, we used secondary electrospray ionization-mass spectrometry (SESI-MS) to investigate the diurnal patterns and signal intensities of exhaled (EX) volatile fatty acids (VFA) of dairy cows. The current study aimed to validate the potential of an exhalomics approach for evaluating rumen fermentation. The experiment was conducted in a switchback design, with 3 periods of 9 d each, including 7 d for adaptation and 2 d for sampling. Four rumen-cannulated original Swiss Brown (Braunvieh) cows were randomly assigned to 1 of 2 diet sequences (ABA or BAB): (A) low starch (LS; 6.31% starch on a dry matter basis) and (B) high starch (HS; 16.2% starch on a dry matter basis). Feeding was once per day at 0830 h. Exhalome (with the GreenFeed System), and rumen samples were collected 8 times to represent every 3 h of a day, and EX-VFA and ruminal (RM)-VFA were analyzed using SESI-MS and HPLC, respectively. Furthermore, the VFA concentration in the gas phase (HR-VFA) was predicted based on RM-VFA and Henry's Law (HR) constants. No interactions were identified between the types of diets (HS vs. LS) and the measurement methods on daily average VFA profiles (RM vs. EX or HR vs. EX), suggesting a consistent performance among the methods. Additionally, when the 3-h interval VFA data from HS and LS diets were analyzed separately, no interactions were observed between methods and time of day, indicating that the relative daily pattern of VFA molar proportions was similar regardless of the VFA measurement method used. The results revealed that the levels of acetate sharply increased immediately after feeding, trailed by an increase in the acetate:propionate ratio and a steady increase for propionate (2 h after feeding the HS diet, 4 h for LS), and butyrate. This change was more pronounced for the HS diet than the LS diet. However, there was no overall diet effect on the VFA molar proportions, although the measurement methods affected the molar proportions. Furthermore, we observed a strong positive correlation between the levels of RM and EX acetate for both diets (HS: r = 0.84; LS: r = 0.85), RM and EX propionate (r = 0.74), and RM and EX acetate:propionate ratio (r = 0.80). Both EX-VFA and RM-VFA exhibited similar responses to feeding and dietary treatments, suggesting that EX-VFA could serve as a useful proxy for characterizing RM-VFA molar proportions to evaluate rumen fermentation. Similar relationships were observed between RM-VFA and HR-VFA. In conclusion, this study underscores the potential of exhalomics as a reliable approach for assessing rumen fermentation. Moving forward, research should further explore the depth of exhalomics in ruminant studies to provide a comprehensive insight into rumen fermentation metabolites, especially across diverse dietary conditions.

Observation of D^{+}→K_{S}^{0}a_{0}(980)^{+} in the Amplitude Analysis of D^{+}→K_{S}^{0}π^{+}η

We perform for the first time an amplitude analysis of the decay D^{+}→K_{S}^{0}π^{+}η and report the observation of the decay D^{+}→K_{S}^{0}a_{0}(980)^{+} using 2.93  fb^{-1} of e^{+}e^{-} collision data taken at a center-of-mass energy of 3.773 GeV with the BESIII detector. As the only W-annihilation-free decay among D to a_{0}(980) pseudoscalar, D^{+}→K_{S}^{0}a_{0}(980)^{+} is the ideal decay in extracting the contributions of the W-emission amplitudes involving a_{0}(980) and to study the final-state interactions. The absolute branching fraction of D^{+}→K_{S}^{0}π^{+}η is measured to be (1.27±0.04_{stat}±0.03_{syst})%. The branching fractions of intermediate processes D^{+}→K_{S}^{0}a_{0}(980)^{+} with a_{0}(980)^{+}→π^{+}η and D^{+}→π^{+}K[over ¯]_{0}^{*}(1430)^{0} with K[over ¯]_{0}^{*}(1430)^{0}→K_{S}^{0}η are measured to be (1.33±0.05_{stat}±0.04_{syst})% and (0.14±0.03_{stat}±0.01_{syst})%, respectively.

Observation of Significant Flavor-SU(3) Breaking in the Kaon Wave Function at 12<Q^{2}<25 GeV^{2} and Discovery of the Charmless Decay ψ(3770)→K_{S}^{0}K_{L}^{0}

We present cross sections for the reaction e^{+}e^{-}→K_{S}^{0}K_{L}^{0} at center-of-mass energies ranging from 3.51 to 4.95 GeV using data samples collected in the BESIII experiment, corresponding to a total integrated luminosity of 26.5  fb^{-1}. The ratio of neutral-to-charged kaon form factors at large momentum transfers (12 Collapse

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Affiliation(s)

M Ablikim Institute of High Energy Physics, Beijing 100049, People's Republic of China
M N Achasov Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
P Adlarson Uppsala University, Box 516, SE-75120 Uppsala, Sweden
X C Ai Zhengzhou University, Zhengzhou 450001, People's Republic of China
R Aliberti Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
A Amoroso University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
M R An Liaoning Normal University, Dalian 116029, People's Republic of China
Q An State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Bai Southeast University, Nanjing 211100, People's Republic of China
O Bakina Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
I Balossino INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
Y Ban Peking University, Beijing 100871, People's Republic of China
H-R Bao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
V Batozskaya Institute of High Energy Physics, Beijing 100049, People's Republic of China National Centre for Nuclear Research, Warsaw 02-093, Poland
K Begzsuren Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
N Berger Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
M Berlowski National Centre for Nuclear Research, Warsaw 02-093, Poland
M Bertani INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
D Bettoni INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
F Bianchi University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
E Bianco University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
A Bortone University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
I Boyko Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
R A Briere Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
A Brueggemann University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
H Cai Wuhan University, Wuhan 430072, People's Republic of China
X Cai Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
A Calcaterra INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
G F Cao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
N Cao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S A Cetin Turkish Accelerator Center Particle Factory Group, Istinye University, 34010 Istanbul, Turkey
J F Chang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
T T Chang Xinyang Normal University, Xinyang 464000, People's Republic of China
W L Chang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G R Che Nankai University, Tianjin 300071, People's Republic of China
G Chelkov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
C Chen Nankai University, Tianjin 300071, People's Republic of China
Chao Chen Soochow University, Suzhou 215006, People's Republic of China
G Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China
H S Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M L Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S J Chen Nanjing University, Nanjing 210093, People's Republic of China
S L Chen North China Electric Power University, Beijing 102206, People's Republic of China
S M Chen Tsinghua University, Beijing 100084, People's Republic of China
T Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X R Chen Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y B Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Q Chen Jilin University, Changchun 130012, People's Republic of China
Z J Chen Hunan University, Changsha 410082, People's Republic of China
S K Choi Chung-Ang University, Seoul, 06974, Republic of Korea
X Chu Nankai University, Tianjin 300071, People's Republic of China
G Cibinetto INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
S C Coen Bochum Ruhr-University, D-44780 Bochum, Germany
F Cossio INFN, I-10125, Turin, Italy
J J Cui Shandong University, Jinan 250100, People's Republic of China
H L Dai Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J P Dai Yunnan University, Kunming 650500, People's Republic of China
A Dbeyssi Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
R E de Boer Bochum Ruhr-University, D-44780 Bochum, Germany
D Dedovich Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Z Y Deng Institute of High Energy Physics, Beijing 100049, People's Republic of China
A Denig Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
I Denysenko Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
M Destefanis University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
F De Mori University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
B Ding Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Jinan, Jinan 250022, People's Republic of China
X X Ding Peking University, Beijing 100871, People's Republic of China
Y Ding Liaoning University, Shenyang 110036, People's Republic of China
Y Ding Jilin University, Changchun 130012, People's Republic of China
J Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L Y Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M Y Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Dong Wuhan University, Wuhan 430072, People's Republic of China
M C Du Institute of High Energy Physics, Beijing 100049, People's Republic of China
S X Du Zhengzhou University, Zhengzhou 450001, People's Republic of China
Z H Duan Nanjing University, Nanjing 210093, People's Republic of China
P Egorov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Y H Fan North China Electric Power University, Beijing 102206, People's Republic of China
J Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
S S Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W X Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Q Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
R Farinelli INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
L Fava University of Eastern Piedmont, I-15121 Alessandria, Italy INFN, I-10125, Turin, Italy
F Feldbauer Bochum Ruhr-University, D-44780 Bochum, Germany
G Felici INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
C Q Feng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J H Feng Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
K Fischer University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
M Fritsch Bochum Ruhr-University, D-44780 Bochum, Germany
C D Fu Institute of High Energy Physics, Beijing 100049, People's Republic of China
J L Fu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y W Fu Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Gao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y N Gao Peking University, Beijing 100871, People's Republic of China
Yang Gao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
S Garbolino INFN, I-10125, Turin, Italy
I Garzia INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
P T Ge Wuhan University, Wuhan 430072, People's Republic of China
Z W Ge Nanjing University, Nanjing 210093, People's Republic of China
C Geng Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
E M Gersabeck University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
A Gilman University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
K Goetzen GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
L Gong Liaoning University, Shenyang 110036, People's Republic of China
W X Gong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W Gradl Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
S Gramigna INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
M Greco University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
M H Gu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y T Gu Guangxi University, Nanning 530004, People's Republic of China
C Y Guan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z L Guan Henan University of Technology, Zhengzhou 450001, People's Republic of China
A Q Guo Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L B Guo Nanjing Normal University, Nanjing 210023, People's Republic of China
M J Guo Shandong University, Jinan 250100, People's Republic of China
R P Guo Shandong Normal University, Jinan 250014, People's Republic of China
Y P Guo Fudan University, Shanghai 200433, People's Republic of China
A Guskov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
J Gutierrez Indiana University, Bloomington, Indiana 47405, USA
T T Han Institute of High Energy Physics, Beijing 100049, People's Republic of China
W Y Han Liaoning Normal University, Dalian 116029, People's Republic of China
X Q Hao Henan Normal University, Xinxiang 453007, People's Republic of China
F A Harris University of Hawaii, Honolulu, Hawaii 96822, USA
K K He Soochow University, Suzhou 215006, People's Republic of China
K L He Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F H H Heinsius Bochum Ruhr-University, D-44780 Bochum, Germany
C H Heinz Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y K Heng Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C Herold Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
T Holtmann Bochum Ruhr-University, D-44780 Bochum, Germany
P C Hong Fudan University, Shanghai 200433, People's Republic of China
G Y Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y R Hou University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z L Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China
B Y Hu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H M Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J F Hu South China Normal University, Guangzhou 510006, People's Republic of China
T Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China
G S Huang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
K X Huang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
L Q Huang Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Huang Shandong University, Jinan 250100, People's Republic of China
Y P Huang Institute of High Energy Physics, Beijing 100049, People's Republic of China
T Hussain University of the Punjab, Lahore-54590, Pakistan
N Hüsken Indiana University, Bloomington, Indiana 47405, USA Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
N In der Wiesche University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
M Irshad State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J Jackson Indiana University, Bloomington, Indiana 47405, USA
S Jaeger Bochum Ruhr-University, D-44780 Bochum, Germany
S Janchiv Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
J H Jeong Chung-Ang University, Seoul, 06974, Republic of Korea
Q Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q P Ji Henan Normal University, Xinxiang 453007, People's Republic of China
X B Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X L Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Y Ji Shandong University, Jinan 250100, People's Republic of China
X Q Jia Shandong University, Jinan 250100, People's Republic of China
Z K Jia State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H J Jiang Wuhan University, Wuhan 430072, People's Republic of China
P C Jiang Peking University, Beijing 100871, People's Republic of China
S S Jiang Liaoning Normal University, Dalian 116029, People's Republic of China
T J Jiang Hangzhou Normal University, Hangzhou 310036, People's Republic of China
X S Jiang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y Jiang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J B Jiao Shandong University, Jinan 250100, People's Republic of China
Z Jiao Huangshan College, Huangshan 245000, People's Republic of China
S Jin Nanjing University, Nanjing 210093, People's Republic of China
Y Jin University of Jinan, Jinan 250022, People's Republic of China
M Q Jing Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X M Jing University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Johansson Uppsala University, Box 516, SE-75120 Uppsala, Sweden
X Kui Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Kabana Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica 1000000, Chile
N Kalantar-Nayestanaki University of Groningen, NL-9747 AA Groningen, The Netherlands
X L Kang China University of Geosciences, Wuhan 430074, People's Republic of China
X S Kang Liaoning University, Shenyang 110036, People's Republic of China
M Kavatsyuk University of Groningen, NL-9747 AA Groningen, The Netherlands
B C Ke Zhengzhou University, Zhengzhou 450001, People's Republic of China
V Khachatryan Indiana University, Bloomington, Indiana 47405, USA
A Khoukaz University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
R Kiuchi Institute of High Energy Physics, Beijing 100049, People's Republic of China
R Kliemt GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
O B Kolcu Turkish Accelerator Center Particle Factory Group, Istinye University, 34010 Istanbul, Turkey
B Kopf Bochum Ruhr-University, D-44780 Bochum, Germany
M Kuessner Bochum Ruhr-University, D-44780 Bochum, Germany
A Kupsc National Centre for Nuclear Research, Warsaw 02-093, Poland Uppsala University, Box 516, SE-75120 Uppsala, Sweden
W Kühn Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
J J Lane University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
P Larin Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
A Lavania Indian Institute of Technology Madras, Chennai 600036, India
L Lavezzi University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
T T Lei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Z H Lei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H Leithoff Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
M Lellmann Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
T Lenz Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
C Li Qufu Normal University, Qufu 273165, People's Republic of China
C Li Nankai University, Tianjin 300071, People's Republic of China
C H Li Liaoning Normal University, Dalian 116029, People's Republic of China
Cheng Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
D M Li Zhengzhou University, Zhengzhou 450001, People's Republic of China
F Li Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
G Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H B Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H J Li Henan Normal University, Xinxiang 453007, People's Republic of China
H N Li South China Normal University, Guangzhou 510006, People's Republic of China
Hui Li Nankai University, Tianjin 300071, People's Republic of China
J R Li Tsinghua University, Beijing 100084, People's Republic of China
J S Li Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
J W Li Shandong University, Jinan 250100, People's Republic of China
Ke Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
L J Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L K Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
Lei Li Renmin University of China, Beijing 100872, People's Republic of China
M H Li Nankai University, Tianjin 300071, People's Republic of China
P R Li Lanzhou University, Lanzhou 730000, People's Republic of China
Q X Li Shandong University, Jinan 250100, People's Republic of China
S X Li Fudan University, Shanghai 200433, People's Republic of China
T Li Shandong University, Jinan 250100, People's Republic of China
W D Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W G Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
X H Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X L Li Shandong University, Jinan 250100, People's Republic of China
Xiaoyu Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y G Li Peking University, Beijing 100871, People's Republic of China
Z J Li Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Z X Li Guangxi University, Nanning 530004, People's Republic of China
C Liang Nanjing University, Nanjing 210093, People's Republic of China
H Liang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H Liang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y F Liang Sichuan University, Chengdu 610064, People's Republic of China
Y T Liang Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G R Liao Guangxi Normal University, Guilin 541004, People's Republic of China
L Z Liao Shandong University, Jinan 250100, People's Republic of China
Y P Liao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J Libby Indian Institute of Technology Madras, Chennai 600036, India
A Limphirat Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
D X Lin Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Lin Institute of High Energy Physics, Beijing 100049, People's Republic of China
B J Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
B X Liu Wuhan University, Wuhan 430072, People's Republic of China
C Liu Jilin University, Changchun 130012, People's Republic of China
C X Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
F H Liu Shanxi University, Taiyuan 030006, People's Republic of China
Fang Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Feng Liu Central China Normal University, Wuhan 430079, People's Republic of China
G M Liu South China Normal University, Guangzhou 510006, People's Republic of China
H Liu Lanzhou University, Lanzhou 730000, People's Republic of China
H B Liu Guangxi University, Nanning 530004, People's Republic of China
H M Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Huanhuan Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Huihui Liu Henan University of Science and Technology, Luoyang 471003, People's Republic of China
J B Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J Y Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
K Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
K Y Liu Liaoning University, Shenyang 110036, People's Republic of China
Ke Liu Henan University of Technology, Zhengzhou 450001, People's Republic of China
L Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
L C Liu Nankai University, Tianjin 300071, People's Republic of China
Lu Liu Nankai University, Tianjin 300071, People's Republic of China
M H Liu Fudan University, Shanghai 200433, People's Republic of China
P L Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q Liu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S B Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
T Liu Fudan University, Shanghai 200433, People's Republic of China
W K Liu Nankai University, Tianjin 300071, People's Republic of China
W M Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Liu Lanzhou University, Lanzhou 730000, People's Republic of China
Y Liu Lanzhou University, Lanzhou 730000, People's Republic of China
Y Liu Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y B Liu Nankai University, Tianjin 300071, People's Republic of China
Z A Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z Q Liu Shandong University, Jinan 250100, People's Republic of China
X C Lou Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F X Lu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H J Lu Huangshan College, Huangshan 245000, People's Republic of China
J G Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
X L Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Lu Central South University, Changsha 410083, People's Republic of China
Y P Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Z H Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C L Luo Nanjing Normal University, Nanjing 210023, People's Republic of China
M X Luo Zhejiang University, Hangzhou 310027, People's Republic of China
T Luo Fudan University, Shanghai 200433, People's Republic of China
X L Luo Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
X R Lyu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y F Lyu Nankai University, Tianjin 300071, People's Republic of China
F C Ma Liaoning University, Shenyang 110036, People's Republic of China
H Ma Yunnan University, Kunming 650500, People's Republic of China
H L Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China
J L Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L L Ma Shandong University, Jinan 250100, People's Republic of China
M M Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q M Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China
R Q Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Ma Peking University, Beijing 100871, People's Republic of China
Y M Ma Institute of Modern Physics, Lanzhou 730000, People's Republic of China
F E Maas Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
M Maggiora University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
S Malde University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
Q A Malik University of the Punjab, Lahore-54590, Pakistan
A Mangoni INFN Sezione di Perugia, I-06100 Perugia, Italy
Y J Mao Peking University, Beijing 100871, People's Republic of China
Z P Mao Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Marcello University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
Z X Meng University of Jinan, Jinan 250022, People's Republic of China
J G Messchendorp GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany University of Groningen, NL-9747 AA Groningen, The Netherlands
G Mezzadri INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
H Miao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T J Min Nanjing University, Nanjing 210093, People's Republic of China
R E Mitchell Indiana University, Bloomington, Indiana 47405, USA
X H Mo Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B Moses Indiana University, Bloomington, Indiana 47405, USA
N Yu Muchnoi Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
J Muskalla Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y Nefedov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
F Nerling Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
I B Nikolaev Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
Z Ning Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
S Nisar COMSATS University Islamabad, Lahore Campus, Defence Road, Off Raiwind Road, 54000 Lahore, Pakistan
Q L Niu Lanzhou University, Lanzhou 730000, People's Republic of China
W D Niu Soochow University, Suzhou 215006, People's Republic of China
Y Niu Shandong University, Jinan 250100, People's Republic of China
S L Olsen University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q Ouyang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Pacetti INFN Sezione di Perugia, I-06100 Perugia, Italy University of Perugia, I-06100 Perugia, Italy
X Pan Soochow University, Suzhou 215006, People's Republic of China
Y Pan Southeast University, Nanjing 211100, People's Republic of China
A Pathak Jilin University, Changchun 130012, People's Republic of China
P Patteri INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
Y P Pei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
M Pelizaeus Bochum Ruhr-University, D-44780 Bochum, Germany
H P Peng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Y Peng Lanzhou University, Lanzhou 730000, People's Republic of China
K Peters GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
J L Ping Nanjing Normal University, Nanjing 210023, People's Republic of China
R G Ping Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Plura Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
V Prasad Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica 1000000, Chile
F Z Qi Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Qi State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H R Qi Tsinghua University, Beijing 100084, People's Republic of China
M Qi Nanjing University, Nanjing 210093, People's Republic of China
T Y Qi Fudan University, Shanghai 200433, People's Republic of China
S Qian Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W B Qian University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C F Qiao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J J Qin University of South China, Hengyang 421001, People's Republic of China
L Q Qin Guangxi Normal University, Guilin 541004, People's Republic of China
X S Qin Shandong University, Jinan 250100, People's Republic of China
Z H Qin Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J F Qiu Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Q Qu Tsinghua University, Beijing 100084, People's Republic of China
C F Redmer Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
K J Ren Liaoning Normal University, Dalian 116029, People's Republic of China
A Rivetti INFN, I-10125, Turin, Italy
M Rolo INFN, I-10125, Turin, Italy
G Rong Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Ch Rosner Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
S N Ruan Nankai University, Tianjin 300071, People's Republic of China
N Salone National Centre for Nuclear Research, Warsaw 02-093, Poland
A Sarantsev Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Y Schelhaas Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
K Schoenning Uppsala University, Box 516, SE-75120 Uppsala, Sweden
M Scodeggio INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
K Y Shan Fudan University, Shanghai 200433, People's Republic of China
W Shan Hunan Normal University, Changsha 410081, People's Republic of China
X Y Shan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J F Shangguan Soochow University, Suzhou 215006, People's Republic of China
L G Shao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M Shao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C P Shen Fudan University, Shanghai 200433, People's Republic of China
H F Shen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W H Shen University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Shen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B A Shi University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H C Shi State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J L Shi Fudan University, Shanghai 200433, People's Republic of China
J Y Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q Q Shi Soochow University, Suzhou 215006, People's Republic of China
R S Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J J Song Henan Normal University, Xinxiang 453007, People's Republic of China
T Z Song Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
W M Song Institute of High Energy Physics, Beijing 100049, People's Republic of China Jilin University, Changchun 130012, People's Republic of China
Y J Song Fudan University, Shanghai 200433, People's Republic of China
Y X Song Peking University, Beijing 100871, People's Republic of China
S Sosio University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
S Spataro University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
F Stieler Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y J Su University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G B Sun Wuhan University, Wuhan 430072, People's Republic of China
G X Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Sun University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H K Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
J F Sun Henan Normal University, Xinxiang 453007, People's Republic of China
K Sun Tsinghua University, Beijing 100084, People's Republic of China
L Sun Wuhan University, Wuhan 430072, People's Republic of China
S S Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Sun Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
W Y Sun Jilin University, Changchun 130012, People's Republic of China
Y Sun China University of Geosciences, Wuhan 430074, People's Republic of China
Y J Sun State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Z Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z T Sun Shandong University, Jinan 250100, People's Republic of China
Y X Tan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C J Tang Sichuan University, Chengdu 610064, People's Republic of China
G Y Tang Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Tang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Y A Tang Wuhan University, Wuhan 430072, People's Republic of China
L Y Tao University of South China, Hengyang 421001, People's Republic of China
Q T Tao Hunan University, Changsha 410082, People's Republic of China
M Tat University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
J X Teng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
V Thoren Uppsala University, Box 516, SE-75120 Uppsala, Sweden
W H Tian Shanxi Normal University, Linfen 041004, People's Republic of China
W H Tian Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Y Tian Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z F Tian Wuhan University, Wuhan 430072, People's Republic of China
I Uman Near East University, Nicosia, North Cyprus, 99138, Mersin 10, Turkey
Y Wan Soochow University, Suzhou 215006, People's Republic of China
S J Wang Shandong University, Jinan 250100, People's Republic of China
B Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
B L Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Bo Wang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C W Wang Nanjing University, Nanjing 210093, People's Republic of China
D Y Wang Peking University, Beijing 100871, People's Republic of China
F Wang University of South China, Hengyang 421001, People's Republic of China
H J Wang Lanzhou University, Lanzhou 730000, People's Republic of China
J P Wang Shandong University, Jinan 250100, People's Republic of China
K Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L L Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
M Wang Shandong University, Jinan 250100, People's Republic of China
Meng Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
N Y Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Wang Fudan University, Shanghai 200433, People's Republic of China
S Wang Lanzhou University, Lanzhou 730000, People's Republic of China
T Wang Fudan University, Shanghai 200433, People's Republic of China
T J Wang Nankai University, Tianjin 300071, People's Republic of China
W Wang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
W Wang University of South China, Hengyang 421001, People's Republic of China
W P Wang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Wang Peking University, Beijing 100871, People's Republic of China
X F Wang Lanzhou University, Lanzhou 730000, People's Republic of China
X J Wang Liaoning Normal University, Dalian 116029, People's Republic of China
X L Wang Fudan University, Shanghai 200433, People's Republic of China
Y Wang Tsinghua University, Beijing 100084, People's Republic of China
Y D Wang North China Electric Power University, Beijing 102206, People's Republic of China
Y F Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y L Wang Henan Normal University, Xinxiang 453007, People's Republic of China
Y N Wang North China Electric Power University, Beijing 102206, People's Republic of China
Y Q Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Yaqian Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China Hebei University, Baoding 071002, People's Republic of China
Yi Wang Tsinghua University, Beijing 100084, People's Republic of China
Z Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Z L Wang University of South China, Hengyang 421001, People's Republic of China
Z Y Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Ziyi Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
D Wei University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
D H Wei Guangxi Normal University, Guilin 541004, People's Republic of China
F Weidner University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
S P Wen Institute of High Energy Physics, Beijing 100049, People's Republic of China
C W Wenzel Bochum Ruhr-University, D-44780 Bochum, Germany
U Wiedner Bochum Ruhr-University, D-44780 Bochum, Germany
G Wilkinson University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
M Wolke Uppsala University, Box 516, SE-75120 Uppsala, Sweden
L Wollenberg Bochum Ruhr-University, D-44780 Bochum, Germany
C Wu Liaoning Normal University, Dalian 116029, People's Republic of China
J F Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China China Center of Advanced Science and Technology, Beijing 100190, People's Republic of China
L H Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China
L J Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Wu Fudan University, Shanghai 200433, People's Republic of China
X H Wu Jilin University, Changchun 130012, People's Republic of China
Y Wu University of Science and Technology of China, Hefei 230026, People's Republic of China
Y H Wu Soochow University, Suzhou 215006, People's Republic of China
Y J Wu Institute of Modern Physics, Lanzhou 730000, People's Republic of China
Z Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L Xia State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X M Xian Liaoning Normal University, Dalian 116029, People's Republic of China
T Xiang Peking University, Beijing 100871, People's Republic of China
D Xiao Lanzhou University, Lanzhou 730000, People's Republic of China
G Y Xiao Nanjing University, Nanjing 210093, People's Republic of China
S Y Xiao Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y L Xiao Fudan University, Shanghai 200433, People's Republic of China
Z J Xiao Nanjing Normal University, Nanjing 210023, People's Republic of China
C Xie Nanjing University, Nanjing 210093, People's Republic of China
X H Xie Peking University, Beijing 100871, People's Republic of China
Y Xie Shandong University, Jinan 250100, People's Republic of China
Y G Xie Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y H Xie Central China Normal University, Wuhan 430079, People's Republic of China
Z P Xie State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
T Y Xing Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C F Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C J Xu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
G F Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Y Xu University of Jinan, Jinan 250022, People's Republic of China
Q J Xu Hangzhou Normal University, Hangzhou 310036, People's Republic of China
Q N Xu Inner Mongolia University, Hohhot 010021, People's Republic of China
W Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China
W L Xu University of Jinan, Jinan 250022, People's Republic of China
X P Xu Soochow University, Suzhou 215006, People's Republic of China
Y C Xu Yantai University, Yantai 264005, People's Republic of China
Z P Xu Nanjing University, Nanjing 210093, People's Republic of China
Z S Xu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F Yan Fudan University, Shanghai 200433, People's Republic of China
L Yan Fudan University, Shanghai 200433, People's Republic of China
W B Yan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
W C Yan Zhengzhou University, Zhengzhou 450001, People's Republic of China
X Q Yan Institute of High Energy Physics, Beijing 100049, People's Republic of China
H J Yang Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
H L Yang Jilin University, Changchun 130012, People's Republic of China
H X Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Tao Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Yang Fudan University, Shanghai 200433, People's Republic of China
Y F Yang Nankai University, Tianjin 300071, People's Republic of China
Y X Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Yifan Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z W Yang Lanzhou University, Lanzhou 730000, People's Republic of China
Z P Yao Shandong University, Jinan 250100, People's Republic of China
M Ye Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
M H Ye China Center of Advanced Science and Technology, Beijing 100190, People's Republic of China
J H Yin Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z Y You Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
B X Yu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C X Yu Nankai University, Tianjin 300071, People's Republic of China
G Yu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J S Yu Hunan University, Changsha 410082, People's Republic of China
T Yu University of South China, Hengyang 421001, People's Republic of China
X D Yu Peking University, Beijing 100871, People's Republic of China
C Z Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L Yuan Beihang University, Beijing 100191, People's Republic of China
S C Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z Y Yuan Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
C X Yue Liaoning Normal University, Dalian 116029, People's Republic of China
A A Zafar University of the Punjab, Lahore-54590, Pakistan
F R Zeng Shandong University, Jinan 250100, People's Republic of China
S H Zeng University of South China, Hengyang 421001, People's Republic of China
X Zeng Fudan University, Shanghai 200433, People's Republic of China
Y Zeng Hunan University, Changsha 410082, People's Republic of China
Y J Zeng Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Zhai Jilin University, Changchun 130012, People's Republic of China
Y C Zhai Shandong University, Jinan 250100, People's Republic of China
Y H Zhan Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
A Q Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B L Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B X Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
D H Zhang Nankai University, Tianjin 300071, People's Republic of China
G Y Zhang Henan Normal University, Xinxiang 453007, People's Republic of China
H Zhang University of Science and Technology of China, Hefei 230026, People's Republic of China
H C Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H H Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H H Zhang Jilin University, Changchun 130012, People's Republic of China
H Q Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H Y Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
J Zhang Zhengzhou University, Zhengzhou 450001, People's Republic of China
J J Zhang Shanxi Normal University, Linfen 041004, People's Republic of China
J L Zhang Henan University, Kaifeng 475004, People's Republic of China
J Q Zhang Nanjing Normal University, Nanjing 210023, People's Republic of China
J W Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J X Zhang Lanzhou University, Lanzhou 730000, People's Republic of China
J Y Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Z Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Jianyu Zhang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L M Zhang Tsinghua University, Beijing 100084, People's Republic of China
L Q Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Lei Zhang Nanjing University, Nanjing 210093, People's Republic of China
P Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q Y Zhang Liaoning Normal University, Dalian 116029, People's Republic of China Zhengzhou University, Zhengzhou 450001, People's Republic of China
Shuihan Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Shulei Zhang Hunan University, Changsha 410082, People's Republic of China
X D Zhang North China Electric Power University, Beijing 102206, People's Republic of China
X M Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
X Y Zhang Shandong University, Jinan 250100, People's Republic of China
Y Zhang University of South China, Hengyang 421001, People's Republic of China
Y Zhang University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
Y T Zhang Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y H Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Yan Zhang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Yao Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z D Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z H Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z L Zhang Jilin University, Changchun 130012, People's Republic of China
Z Y Zhang Nankai University, Tianjin 300071, People's Republic of China
Z Y Zhang Wuhan University, Wuhan 430072, People's Republic of China
G Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Y Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J Z Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Lei Zhao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Ling Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China
M G Zhao Nankai University, Tianjin 300071, People's Republic of China
R P Zhao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S J Zhao Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y B Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y X Zhao Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z G Zhao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
A Zhemchugov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
B Zheng University of South China, Hengyang 421001, People's Republic of China
J P Zheng Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W J Zheng Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y H Zheng University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B Zhong Nanjing Normal University, Nanjing 210023, People's Republic of China
X Zhong Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H Zhou Shandong University, Jinan 250100, People's Republic of China
L P Zhou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Zhou Wuhan University, Wuhan 430072, People's Republic of China
X K Zhou Central China Normal University, Wuhan 430079, People's Republic of China
X R Zhou State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Y Zhou Liaoning Normal University, Dalian 116029, People's Republic of China
Y Z Zhou Fudan University, Shanghai 200433, People's Republic of China
J Zhu Nankai University, Tianjin 300071, People's Republic of China
K Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China
K J Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L Zhu Jilin University, Changchun 130012, People's Republic of China
L X Zhu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S H Zhu University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
S Q Zhu Nanjing University, Nanjing 210093, People's Republic of China
T J Zhu Fudan University, Shanghai 200433, People's Republic of China
W J Zhu Fudan University, Shanghai 200433, People's Republic of China
Y C Zhu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Z A Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J H Zou Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Zu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China

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Combined Strategies Enable Highly Selective Light Olefins and -Xylene Production on Single Catalyst Bed

Achieving multiple high-value-added chemical production through novel reaction processes and shape-selective catalytic strategy is the key to realizing efficient low-carbon catalytic processes. In this work, a methanol-toluene coreaction system was developed, and combined control strategies of reaction pathway guidance and shape-selective catalysis were applied for the successful production of light olefins and para-xylene on single HZSM-5 catalyst bed. Cofeeding toluene additionally provides reactive and flowing aromatic hydrocarbon pool species that change the dominant reaction pathway in the complex network of the methanol reaction on HZSM-5 and promote the formation of ethylene. For the first time, the key reaction intermediates methylmethylenecyclodiene are directly captured and identified by experimental and theoretical techniques. This helps to propose the catalytic cycle for the dominant generation of ethylene and, more importantly, enriches the methanol-to-hydrocarbons (MTH) chemistry and hydrocarbon pool mechanism. Furthermore, 0.4HZSM-5@S-1-CLD, an optimized HZSM-5 catalyst modified by the silicalite-1 epitaxial growth followed by silanization approach, realizes highly selective production of light olefins (especially ethylene) and para-xylene, while excellent reactant activity is maintained. This highly efficient coreaction route gives an important leading significance in synthesizing the raw materials for the polyolefin and polyester industries. The establishment of the combined control strategies provides a model for the joint production of multiple target chemicals in complex catalytic processes.

Investigation of the ΔI=1/2 Rule and Test of CP Symmetry through the Measurement of Decay Asymmetry Parameters in Ξ^{-} Decays

Using (10087±44)×10^{6}  J/ψ events collected with the BESIII detector, numerous Ξ^{-} and Λ decay asymmetry parameters are simultaneously determined from the process J/ψ→Ξ^{-}Ξ[over ¯]^{+}→Λ(pπ^{-})π^{-}Λ[over ¯](n[over ¯]π^{0})π^{+} and its charge-conjugate channel. The precisions of α_{Λ0} for Λ→nπ^{0} and α[over ¯]_{Λ0} for Λ[over ¯]→n[over ¯]π^{0} compared to world averages are improved by factors of 4 and 1.7, respectively. The ratio of decay asymmetry parameters of Λ→nπ^{0} to that of Λ→pπ^{-}, ⟨α_{Λ0}⟩/⟨α_{Λ-}⟩, is determined to be 0.873±0.012_{-0.010}^{+0.011}, where the first and the second uncertainties are statistical and systematic, respectively. The ratio is smaller than unity more than 5σ, which signifies the existence of the ΔI=3/2 transition in Λ for the first time. Besides, we test for CP symmetry in Ξ^{-}→Λπ^{-} and in Λ→nπ^{0} with the best precision to date.

Observation of D_{s}^{+}→η^{'}μ^{+}ν_{μ}, Precision Test of Lepton Flavor Universality with D_{s}^{+}→η^{(')}l^{+}ν_{l}, and First Measurements of D_{s}^{+}→η^{(')}μ^{+}ν_{μ} Decay Dynamics

By analyzing 7.33  fb^{-1} of e^{+}e^{-} annihilation data collected at center-of-mass energies between 4.128 and 4.226 GeV with the BESIII detector, we report the observation of the semileptonic decay D_{s}^{+}→η^{'}μ^{+}ν_{μ}, with a statistical significance larger than 10σ, and the measurements of the D_{s}^{+}→ημ^{+}ν_{μ} and D_{s}^{+}→η^{'}μ^{+}ν_{μ} decay dynamics for the first time. The branching fractions of D_{s}^{+}→ημ^{+}ν_{μ} and D_{s}^{+}→η^{'}μ^{+}ν_{μ} are determined to be (2.235±0.051_{stat}±0.052_{syst})% and (0.801±0.055_{stat}±0.028_{syst})%, respectively, with precision improved by factors of 6.0 and 6.6 compared to the previous best measurements. Combined with the results for the decays D_{s}^{+}→ηe^{+}ν_{e} and D_{s}^{+}→η^{'}e^{+}ν_{e}, the ratios of the decay widths are examined both inclusively and in several ℓ^{+}ν_{ℓ} four-momentum transfer ranges. No evidence for lepton flavor universality violation is found within the current statistics. The products of the hadronic form factors f_{+,0}^{η^{(')}}(0) and the c→s Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| are determined. The results based on the two-parameter series expansion are f_{+,0}^{η}(0)|V_{cs}|=0.452±0.010_{stat}±0.007_{syst} and f_{+,0}^{η^{'}}(0)|V_{cs}|=0.504±0.037_{stat}±0.012_{syst}, which help to constrain present models on f_{+,0}^{η^{(')}}(0). The forward-backward asymmetries are determined to be ⟨A_{FB}^{η}⟩=-0.059±0.031_{stat}±0.005_{syst} and ⟨A_{FB}^{η^{'}}⟩=-0.064±0.079_{stat}±0.006_{syst} for the first time, which are consistent with the theoretical calculation.

Dietary supplementation of vitamin D3 and calcium partially recover the compromised time budget and circadian rhythm of lying behavior in lactating cows under heat stress

Heat stress (HS) impedes cattle behavior and performance and is an animal comfort and welfare issue. The objective of this study was to characterize the time budget and circadian rhythm of lying behavior in dairy cows during HS and to assess the effect of dietary supplementation of vitamin D3 and Ca. Twelve multiparous Holstein cows (42.2 ± 5.6 kg milk/d; 83 ± 27 d in milk) housed in tiestalls were used in a split-plot design with the concentration of dietary vitamin E and Se as main plots (LESe: 11.1 IU/kg and 0.55 mg/kg, and HESe: 223 IU/kg and 1.8 mg/kg, respectively). Within each plot cows were randomly assigned to (1) HS with low concentrations of vitamin D3 and Ca (HS, 1,012 IU/kg and 0.73%, respectively), (2) HS with high concentrations of vitamin D3 and Ca (HS+D3/Ca; 3,764 IU/kg and 0.97%, respectively), or (3) thermoneutral pair-fed (TNPF) with low concentrations of vitamin D3 and Ca (1,012 IU/kg and 0.73%, respectively) in a Latin square design with 14-d periods and 7-d washouts. Lying behavior was measured with HOBO Loggers in 15-min intervals. Overall, cows in HS spent less time lying per day relative to TNPF from d 7 to 14. Daily lying time was positively correlated with milk yield, energy-corrected milk yield, and feed efficiency, and was negatively correlated with rectal temperature, respiratory rate, fecal calprotectin, tumor necrosis factor-α, and C-reactive protein. A treatment by time interaction was observed for lying behavior: the time spent lying was lesser for cows in HS than in TNPF in the early morning (0000-0600 h) and in the night (1800-2400 h). The circadian rhythm of lying behavior was characterized by fitting a cosine function of time into linear mixed model. Daily rhythmicity of lying was detected for cows in TNPF and HS+D3/Ca, whereas only a tendency in HS cows was observed. Cows in TNPF had the highest mesor (the average level of diurnal fluctuations; 34.2 min/h) and amplitude (the distance between the peak and mesor; 17.9 min/h). Both the mesor and amplitude were higher in HS+D3/Ca relative to HS (26.6 vs. 25.2 min/h and 3.91 min/h vs. 2.18 min/h, respectively). The acrophase (time of the peak) of lying time in TNPF, HS, and HS+D3/Ca were 0028, 0152, and 0054 h, respectively. Lastly, a continuous increase in daily lying time in TNPF was observed during the first 4 d of the experimental period in which DMI was gradually restricted, suggesting that intake restrictions may shift feeding behavior and introduce biases in the behavior of animals. In conclusion, lying behavior was compromised in dairy cows under HS, characterizing reduced daily lying time and disrupted circadian rhythms, and the compromised lying behavior can be partially restored by supplementation of vitamin D3 and Ca. Further research may be required for a more suitable model to study behavior of cows under HS.

Spleen-dedicated stiffness measurement performed well to rule out high-risk varices in HBV-related hepatocellular carcinoma: Screening for high-risk varices in HCC

BACKGROUND

Esophagogastroduodenoscopy (EGD) is required to screen for high-risk varices (HRV) in patients with hepatocellular carcinoma (HCC), especially since overall survival rates have dramatically improved with new systemic therapies.

AIM

To assess the Baveno VI and Baveno VII algorithms' ability to rule out HRV in hepatitis B virus (HBV)-related HCC METHODS: We prospectively enrolled consecutive patients with HBV related, compensated cirrhosis and newly diagnosed HCC who underwent liver stiffness measurement, spleen stiffness measurement (SSM) using a 100-Hz shear wave frequency, and EGD.

RESULTS

From September 2021 to August 2023, we enrolled 219 patients with HCC, with 107 (48.9%) Barcelona Clinic Liver Cancer (BCLC) A, 28 (12.8%) BCLC B and 84 (38.3%) BCLC C, respectively. HRV prevalence was 28.8% (63/219). Baveno VI criteria safely (HRV missing rate, 3.2%) avoided 27.4% unnecessary EGDs, while the Baveno VII algorithm avoided 49.3% with HRV missing rate at 7.9% (5/63). The SSM ≤40 kPa avoided 47.5% of EGDs safely (HRV missing rate, 4.8%), significantly better than the Baveno VI criteria (p < 0.001) and comparable to the Baveno VII algorithm (p = 0.390). The SSM ≤40 kPa safely avoided EGDs in patient subgroups within Milan criteria, with portal vein tumour thrombosis or BCLC B/C or candidates for systemic therapy.

CONCLUSIONS

We validated that the SSM ≤40 kPa using a 100-Hz probe could safely eliminate more unnecessary EGDs than the Baveno VI criteria in patients with HBV-related HCC. However, the efficacy of the Baveno VII algorithm in patients with HCC requires further investigation.

Determination of the Σ^{+} Timelike Electromagnetic Form Factors

Based on data samples collected with the BESIII detector at the BEPCII collider, the process e^{+}e^{-}→Σ^{+}Σ[over ¯]^{-} is studied at center-of-mass energies sqrt[s]=2.3960, 2.6454, and 2.9000 GeV. Using a fully differential angular description of the final state particles, both the relative magnitude and phase information of the Σ^{+} electromagnetic form factors in the timelike region are extracted. The relative phase between the electric and magnetic form factors is determined to be sinΔΦ=-0.67±0.29(stat)±0.18(syst) at sqrt[s]=2.3960  GeV, ΔΦ=55°±19°(stat)±14°(syst) at sqrt[s]=2.6454  GeV, and 78°±22°(stat)±9°(syst) at sqrt[s]=2.9000  GeV. For the first time, the phase of the hyperon electromagnetic form factors is explored in a wide range of four-momentum transfer. The evolution of the phase along with four-momentum transfer is an important input for understanding its asymptotic behavior and the dynamics of baryons.

Evaluation of an artificial intelligence-based clinical trial matching system in Chinese patients with hepatocellular carcinoma: a retrospective study

BACKGROUND

Artificial intelligence (AI)-assisted clinical trial screening is a promising prospect, although previous matching systems were developed in English, and relevant studies have only been conducted in Western countries. Therefore, we evaluated an AI-based clinical trial matching system (CTMS) that extracts medical data from the electronic health record system and matches them to clinical trials automatically.

METHODS

This study included 1,053 consecutive inpatients primarily diagnosed with hepatocellular carcinoma who were referred to the liver tumor center of an academic medical center in China between January and December 2019. The eligibility criteria extracted from two clinical trials, patient attributes, and gold standard were decided manually. We evaluated the performance of the CTMS against the established gold standard by measuring the accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and run time required.

RESULTS

The manual reviewers demonstrated acceptable interrater reliability (Cohen's kappa 0.65-0.88). The performance results for the CTMS were as follows: accuracy, 92.9-98.0%; sensitivity, 51.9-83.5%; specificity, 99.0-99.1%; PPV, 75.7-85.1%; and NPV, 97.4-98.9%. The time required for eligibility determination by the CTMS and manual reviewers was 2 and 150 h, respectively.

CONCLUSIONS

We found that the CTMS is particularly reliable in excluding ineligible patients in a significantly reduced amount of time. The CTMS excluded ineligible patients for clinical trials with good performance, reducing 98.7% of the work time. Thus, such AI-based systems with natural language processing and machine learning have potential utility in Chinese clinical trials.

Effectiveness of dyadic interventions among cancer dyads: An overview of systematic reviews and meta-analyses

AIMS AND OBJECTIVE

To summarize evidence from systematic reviews (SRs)/meta-analyses (MAs) regarding the impact of dyadic interventions delivered to both members of a cancer dyad, including a cancer patient and caregiver (e.g. family caregiver, intimate partner).

DESIGN

This overview of SRs was conducted in accordance with the preferred reporting items for overviews of reviews statement.

METHODS

A comprehensive search of multiple databases, including PubMed, Cochrane Library, Embase, CINAHL, Web of Science, China National Knowledge Infrastructure and Wan Fang. The methodological and reporting quality of SRs and MAs was assessed using the Assessing the Methodological Quality of Systematic Reviews 2. The quality of the included SRs/MAs was evaluated using the Grades of Recommendations, Assessment, Development and Evaluation approach.

RESULTS

Eighteen SRs/MAs undertook quantitative synthesis to assess the impact of dyadic interventions on cancer dyads. Both the credibility of the SRs/MAs and the evidence quality of the outcome measures were below satisfactory standards. Prior SRs/MAs revealed several limitations such as lack of pre-published protocols or research objectives, failure to report excluded studies and insufficient details on funding sources for individual studies.

CONCLUSIONS

Dyadic interventions may prove advantageous for the physical health and dyadic adjustment of cancer dyads. Nevertheless, the reported results of dyadic interventions on the psychological health of patient-caregiver dyads affected by cancer are inconsistent. Thus, rigorous and comprehensive studies are requisite to establish reliable evidence for conclusive determinations.

RELEVANCE TO CLINICAL PRACTICE

The findings of this overview can guide healthcare practitioners when considering the use of dyadic interventions for cancer dyads. Moreover, these findings have the potential to enhance the integration of these approaches into clinical practice.

PATIENT OR PUBLIC CONTRIBUTION

Our paper presents an overview of systematic reviews, and therefore, such specific details may not be relevant to our study.

First Measurement of the Decay Asymmetry in the Pure W-Boson-Exchange Decay Λ_{c}^{+}→Ξ^{0}K^{+}

Based on 4.4  fb^{-1} of e^{+}e^{-} annihilation data collected at the center-of-mass energies between 4.60 and 4.70 GeV with the BESIII detector at the BEPCII collider, the pure W-boson-exchange decay Λ_{c}^{+}→Ξ^{0}K^{+} is studied with a full angular analysis. The corresponding decay asymmetry is measured for the first time to be α_{Ξ^{0}K^{+}}=0.01±0.16(stat)±0.03(syst). This result reflects the noninterference effect between the S- and P-wave amplitudes. The phase shift between S- and P-wave amplitudes has two solutions, which are δ_{p}-δ_{s}=-1.55±0.25(stat)±0.05(syst)  rad or 1.59±0.25(stat)±0.05(syst)  rad.

Circ_MAPK9 promotes STAT3 and LDHA expression by silencing miR-642b-3p and affects the progression of hepatocellular carcinoma

BACKGROUND

Aberrant expression and activation of circular RNAs (circRNAs) are closely associated with various cancers. The role of circ_MAPK9 (hsa_circ_0001566) in cancer progression remains unknown. This study aims to investigate the function, mechanism and clinical significance of circ_MAPK9 in hepatocellular carcinoma (HCC).

METHODS

Circ_MAPK9 expression on the microarray of tumor from clinical HCC patients was detected by in situ hybridization (ISH). Circ_MAPK9 knockdown was achieved with siRNAs in SMMC-7721 and SK-Hep1 HCC cell lines. The biological function of circ_MAPK9 was verified in vitro by CCK8 test, colony formation assay, transwell assay, PI-Annexin V staining, and in vivo by xenograft tumor in nude mice. Fluorescent in situ hybridization (FISH), subcellular fractionation assay, a dual-luciferase reporter assay and rescue experiments were employed for further mechanistic investigation.

RESULTS

The expression of circ_MAPK9 was significantly up-regulated in HCC tissues and cells, which was found to be associated with poor prognosis. Patients with high expression of circ_MAPK9 had a shorter overall survival and disease-free survival in comparison to those with low circ_MAPK9 expression. Functional assays showed that circ_MAPK9 knockdown suppressed cellular proliferation, migration, invasion and tumor growth in vivo, and promoted apoptosis in HCC cells. Moreover, we found that circ_MAPK9 knockdown could inhibit aerobic glycolysis by decreasing the production of adenosine triphosphate (ATP) and lactic acid, which was mediated by lactate dehydrogenase (LDHA). Mechanistically, circ_MAPK9 functioned as ceRNA via sponging miR-642b-3p and alleviated the inhibitory effect of miR-642b-3p on its target signal transducer and activator of transcription 3 (STAT3) and LDHA, thereby leading to STAT3 activation and LDHA expression.

CONCLUSIONS

Circ_MAPK9, as an oncogene, promotes HCC growth and metastasis through miR-642b-3p/STAT3-LDHA axis. Circ_MAPK9 could serve as a potential biomarker for HCC poor prognosis and diagnosis.

Genomic epidemiological investigation of an outbreak of Serratia marcescens neurosurgical site infections associated with contaminated haircutting toolkits in a hospital barber shop

BACKGROUND

Nine surgical site infections caused by Serratia marcescens were diagnosed in neurosurgical patients in a 3500-bed hospital between 2nd February and 6th April 2022.

OBJECTIVE

To trace the source of infections caused by S. marcescens to expedite termination of the outbreak and prevent future epidemics.

METHODS

A review of all surgical procedures and cultures yielding S. marcescens since February 2022 was conducted. Samples were collected from patients and environmental sources. S. marcescens isolates were characterized by antibiotic susceptibility testing. Whole-genome sequencing (WGS) was used to investigate genetic relationships. Resistance genes, virulence genes and plasmid replicons were identified.

RESULTS

S. marcescens was isolated from patients' puncture fluid, cerebrospinal fluid and other secretions, and was also cultured from the barbers' haircutting tools, including leather knives, slicker scrapers and razors. In total, 15 isolates were obtained from patients and eight isolates were obtained from haircutting tools. All isolates exhibited identical antibiotic resistance patterns. WGS revealed close clustering among the 23 isolates which differed significantly from previous strains. Three resistance genes and nine virulence-associated genes were detected in all isolates, and 19 of 23 isolates harboured an MOBP-type plasmid. The results confirmed an outbreak of S. marcescens, which was traced to contaminated haircutting tools in the hospital barber shop. The outbreak ended after extensive reinforcement of infection control procedures and re-education of the barbers.

CONCLUSIONS

These results highlight the risk of postoperative infections related to pre-operative skin preparation, and demonstrate the value of next-generation sequencing tools to expedite outbreak investigations.

Test of CP Symmetry in Hyperon to Neutron Decays

The quantum entangled J/ψ→Σ^{+}Σ[over ¯]^{-} pairs from (1.0087±0.0044)×10^{10}  J/ψ events taken by the BESIII detector are used to study the nonleptonic two-body weak decays Σ^{+}→nπ^{+} and Σ[over ¯]^{-}→n[over ¯]π^{-}. The CP-odd weak decay parameters of the decays Σ^{+}→nπ^{+} (α_{+}) and Σ[over ¯]^{-}→n[over ¯]π^{-} (α[over ¯]_{-}) are determined to be 0.0481±0.0031_{stat}±0.0019_{syst} and -0.0565±0.0047_{stat}±0.0022_{syst}, respectively. The decay parameter α[over ¯]_{-} is measured for the first time, and the accuracy of α_{+} is improved by a factor of 4 compared to the previous results. The simultaneously determined decay parameters allow the first precision CP symmetry test for any hyperon decay with a neutron in the final state with the measurement of A_{CP}=(α_{+}+α[over ¯]_{-})/(α_{+}-α[over ¯]_{-})=-0.080±0.052_{stat}±0.028_{syst}. Assuming CP conservation, the average decay parameter is determined as ⟨α_{+}⟩=(α_{+}-α[over ¯]_{-})/2=-0.0506±0.0026_{stat}±0.0019_{syst}, while the ratios α_{+}/α_{0} and α[over ¯]_{-}/α[over ¯]_{0} are -0.0490±0.0032_{stat}±0.0021_{syst} and -0.0571±0.0053_{stat}±0.0032_{syst}, where α_{0} and α[over ¯]_{0} are the decay parameters of the decays Σ^{+}→pπ^{0} and Σ[over ¯]^{-}→p[over ¯]π^{0}, respectively.

Measurement of Energy-Dependent Pair-Production Cross Section and Electromagnetic Form Factors of a Charmed Baryon

We study the process e^{+}e^{-}→Λ_{c}^{+}Λ[over ¯]_{c}^{-} at twelve center-of-mass energies from 4.6119 to 4.9509 GeV using data samples collected by the BESIII detector at the BEPCII collider. The Born cross sections and effective form factors (|G_{eff}|) are determined with unprecedented precision after combining the single and double-tag methods based on the decay process Λ_{c}^{+}→pK^{-}π^{+}. Flat cross sections around 4.63 GeV are obtained and no indication of the resonant structure Y(4630), as reported by Belle, is found. In addition, no oscillatory behavior is discerned in the |G_{eff}| energy dependence of Λ_{c}^{+}, in contrast to what is seen for the proton and neutron cases. Analyzing the cross section together with the polar-angle distribution of the Λ_{c}^{+} baryon at each energy point, the moduli of electric and magnetic form factors (|G_{E}| and |G_{M}|) are extracted and separated. For the first time, the energy dependence of the form factor ratio |G_{E}/G_{M}| is observed, which can be well described by an oscillatory function.

Clinical utility of repeat fetal echocardiography in congenital heart disease

OBJECTIVES

To investigate the utility of repeat fetal echocardiography (FE) following a diagnosis of structural congenital heart disease (CHD) on the initial FE. We evaluated how often changes in management and counseling occurred based on subsequent FE findings and sought to determine which types of CHD were more likely to have changes in management and/or counseling based on repeat FE.

METHODS

This was a retrospective review of all patients who presented to our center between January 2012 and January 2019 and who had more than one FE performed for structural CHD. We reviewed consultation notes to determine whether management or counseling had changed based on FE findings at follow-up visits. Management variables included a change in location or mode of delivery, plan for atrial septostomy, initiation of prostaglandin infusion, umbilical line placement and planned admission location (nursery vs neonatal intensive care unit). We defined a counseling change as any of the above changes in management as well as any meaningful refinements in the cardiac diagnosis that led to a change in the overall prognosis or future management. Initial diagnoses were grouped into anatomically/hemodynamically relevant subgroups. Fisher's exact test was used to assess the relationship between the initial diagnosis and changes in management. Post-hoc pairwise comparisons were performed using Dunnett's test.

RESULTS

Between January 2012 and January 2019, 267 patients underwent 534 follow-up FE assessments performed for structural CHD. Management change based on repeat FE occurred in 41/267 (15.4%) cases. A change in management was associated with the diagnosis made at the initial visit (P < 0.001). The proportion of cases with a management change was highest among those with an initial diagnosis of pulmonary valve abnormality/non-critical pulmonary stenosis (4/11 (36.4%)), followed by balanced atrioventricular canal (AVC) defect (5/17 (29.4%)) and left ventricular outflow tract obstruction/aortic valve abnormality or coarctation/interrupted aortic arch (19/68 (27.9%)). No management change occurred in fetuses diagnosed with isolated ventricular septal defect (VSD), truncus arteriosus, pulmonary vein anomaly or isolated arch sidedness/branching abnormality. Compared to those with a VSD, management was significantly more likely to be changed in fetuses with a balanced AVC defect (P = 0.025) and left heart lesions (P = 0.002). Right heart lesions showed a trend towards an increased incidence of management change (P = 0.05). A counseling change based on repeat FE occurred in 108/267 (40.4%) cases. The proportion of cases with a counseling change was highest among those with an initial diagnosis of pulmonary valve abnormality/non-critical pulmonary stenosis (8/11 (72.7%)) and hypoplastic left heart syndrome/critical aortic stenosis (5/9 (55.6%)).

CONCLUSIONS

The clinical utility of follow-up FE is associated with the type of CHD diagnosed. Follow-up FE led to changes in management in several types of CHD, most commonly in cases with an initial diagnosis of right and left outflow obstructive lesions and balanced AVC defect. When developing programmatic protocols for the frequency of FE assessments, the type of CHD should be a major determinant, but additional studies are required to reach a consensus on how often serial FE should be performed for each type of CHD. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

MRI-based radiomics analysis of bladder cancer: prediction of pathological grade and histological variant

AIM

To develop magnetic resonance imaging (MRI)-based radiomics models for the prediction of the pathological grade and histological variant of bladder cancer.

MATERIALS AND METHODS

A total of 227 patients who underwent bladder MRI and had histopathologically confirmed grades and variants were included retrospectively from January 2017 to March 2022. They were assigned to a training set (n=131) and a testing set (n=96) based on the MRI system. MRI-based radiomics features were extracted from manually segmented volumes of interest from high-b-value DWI images and ADC maps. The radiomics models were trained with all possible pipelines in the training set. One optimal model was selected using the fivefold cross-validation method and verified by the testing set according to the pathological results. Univariate and multivariate analyses were performed to identify the significant clinical and imaging factors for developing clinical-radiomics models.

RESULTS

The radiomics model for grade prediction had area under the curve (AUC) values of 0.784, 0.786, and 0.733 in the training, cross-validation, and testing sets, respectively. The radiomics model for variant prediction had AUC values of 0.748, 0.757, and 0.789 in the training, cross-validation, and testing sets, respectively. The performance of the clinical-radiomics model was significantly improved compared with the radiomics models alone for the total dataset (AUC for grade: 0.846 versus 0.756; AUC for variant: 0.810 versus 0.757, p<0.05).

CONCLUSION

MRI-based radiomics models could be used to predict the pathological grade and histological variants of bladder cancer with relatively good performance.

[Safety of the strategy of minimizing intestinal resection during surgery for pelvic radiation- induced terminal small intestinal stenosis]

Objective: To investigate the efficacy of strategies for minimizing small bowel resection during surgery for pelvic radiation-induced terminal small intestinal stenosis in preventing postoperative complications such as anastomotic leakage and short bowel syndrome. Methods: This was a retrospective cohort study. There are two subtypes of chronic radiation enteritis (CRE) with combined intestinal stenosis and intestinal obstruction: (1) Type I: terminal ileal lesions with a normal ileal segment of 2-20 cm between the ileal lesion and ileocecal junction; and (2) Type II: the lesion is located in the small bowel at a distance from the ileocecal region, usually accompanied by extensive damage to the bowel segments outside the lesion. The indications for minimal bowel resection are as follows: (1) diagnosis of Type I small bowel CRE; (2) absence of radiological evidence of rectosigmoid damage; and (3) absence of colonic obstruction. The contraindications are: (1) stenotic, penetrating lesions of the distal cecum; (2) emergency surgery; (3) recurrence of malignant tumor or history of radiotherapy for recurrent malignant tumor; (4) interval between radiotherapy and surgery <6 months; and (5) history of preoperative small bowel resection or abdominal chemotherapy. Case data of 40 patients with Type I CRE who met the above criteria and had undergone minimal bowel resection between April 2017 and December 2019 were retrospectively analyzed (minimal bowel resection group; including 13 patients from Jinling Hospital, 16 from the Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, and 11 from the Affiliated Hospital of Xuzhou Medical University). Forty patients with Type I CRE who had undergone resection of intestinal stenosis lesions and the ileocecal region between October 2015 and March 2017 were included as historical controls (conventional resection group; all from Jinling Hospital). The specific strategy for minimal bowel resection was one-stage partial ileal resection+ileo anastomosis+protective small bowel stoma. In contrast, conventional resection comprised ileocecal resection+ileocecal-ascending colon anastomosis. Postoperative complications, intraoperative and postoperative recovery, and changes in postoperative quality of life were analyzed in both groups. The severity of postoperative complications was assessed by Clavien-Dindo and the Comprehensive Complication Index (CCI). Karnofsky performance scores (KPS) were used to evaluate the quality of life of patients in the two groups preoperatively and postoperatively. The higher the KPS score, the better the quality of life. Results: Baseline patient characteristics did not differ significantly between the two groups (P>0.05). Compared with the conventional resection group, the length of small bowel resected in the minimal bowel resection group (51 [20-200] cm vs. 91 [60-200] cm, Z=5.653, P<0.001), duration of postoperative total enteral nutrition [9 (3-18) days vs. 12 (4-50) days, Z=2.172, P=0.030], and duration of postoperative hospital stay [17 (9-24) days vs 29 (13-57) days, Z=6.424, P<0.001] were shorter; all of these differences are statistically significant. The overall incidence of postoperative complications was lower in the minimal bowel resection group than in the conventional resection group [20.0% (8/40) vs. 70.0% (28/40), χ2=19.967, P<0.001], These comprised short bowel syndrome [5.0% (2/40) vs. 25.0% (10/40), χ2=6.274, P=0.012], anastomotic leakage or fistula [2.5% (1/40) vs. 22.5% (9/40), χ2=7.314, P=0.014], and pleural effusion [7.5% (3/40) vs. 25.0% (10/40), χ2=4.500, P=0.034], all of which occurred less often in the minimal bowel resection than conventional resection group. The CCI index was also lower in the minimal bowel resection group than in the conventional resection group [CCI>40: 2.5% (1/40) vs. 12.5% (5/40), Z=18.451, P<0.001]. KPS scores were higher in the minimal bowel resection group 1 and 3 months postoperatively than they had been 1 day preoperatively (79.9±4.7 vs. 75.3±4.1, 86.2±4.8 vs. 75.3±4.1, both P<0.05). In the minimal bowel resection group, seven patients were satisfied with their current quality of life and refused to undergo stoma reduction at follow-up and one deferred stoma reduction because of rectal bleeding. The remaining 32 patients underwent stoma reduction 3 to 12 months after surgery, 26 of whom underwent ileo-cecal anastomosis. The remaining six underwent resection of the stoma and anastomosis of the ileum to the ascending colon. Conclusions: The strategy of minimal small bowel resection in patients with radiation-induced bowel injuries reduces the length of resected small bowel, decreases the risk and severity of postoperative complications, and is associated with a better prognosis and quality of life than conventional resection.

Molecular-scale characterization of groundwater treatment sludge from around the world: Implications for potential arsenic recovery

Iron (Fe)-based treatment methods are widely applied to remove carcinogenic arsenic (As) from drinking water, but generate toxic As-laden Fe (oxyhydr)oxide waste that has traditionally been ignored for resource recovery by the water sector. However, the European Commission recently classified As as a Critical Raw Material (CRM), thus providing new incentives to re-think As-laden groundwater treatment sludge. Before As recovery techniques can be developed for groundwater treatment waste, detailed information on its structure and composition is essential. To this end, we comprehensively characterized sludge generated from a variety of As-rich groundwater treatment plants in different geographic regions by combining a suite of macroscopic measurements, such as total digestions, leaching tests and BET surface area with molecular-scale solid-phase analysis by Fe and As K-edge X-ray absorption spectroscopy (XAS). We found that the As mass fraction of all samples ranged from ∼200-1200 mg As/kg (dry weight) and the phosphorous (P) content reached ∼0.5-2 mass%. Notably, our results indicated that the influent As level was a poor predictor of the As sludge content, with the highest As mass fractions (940-1200 mg As/kg) measured in sludge generated from treating low groundwater As levels (1.1-22 µg/L). The Fe K-edge XAS data revealed that all samples consisted of nanoscale Fe(III) precipitates with less structural order than ferrihydrite, which is consistent with their high BET surface area (up to >250 m2/g) and large As and P mass fractions. The As K-edge XAS data indicated As was present in all samples predominantly as As(V) bound to Fe(III) precipitates in the binuclear-corner sharing (2C) geometry. Overall, the similar structure and composition of all samples implies that As recovery methods optimized for one type of Fe-based treatment sludge can be applied to many groundwater treatment sludges. Our work provides a critical foundation for further research to develop resource recovery methods for As-rich waste.

Determination of Spin-Parity Quantum Numbers for the Narrow Structure near the pΛ[over ¯] Threshold in e^{+}e^{-}→pK^{-}Λ[over ¯]+c.c

A narrow structure in the pΛ[over ¯] system near the mass threshold, named as X(2085), is observed in the process e^{+}e^{-}→pK^{-}Λ[over ¯] with a statistical significance greater than 20σ. Its spin and parity are determined for the first time to be J^{P}=1^{+} in an amplitude analysis, with a statistical significance greater than 5σ over other quantum numbers (0^{-},1^{-} and 2^{+}). The pole positions of X(2085) are measured to be M_{pole}=(2084_{-2}^{+4}±9)  MeV and Γ_{pole}=(58_{-3}^{+4}±25)  MeV, where the first uncertainties are statistical and the second ones are systematic. The analysis is based on the study of the process e^{+}e^{-}→pK^{-}Λ[over ¯] and uses the data samples collected with the BESIII detector at the center-of-mass energies sqrt[s]=4.008, 4.178, 4.226, 4.258, 4.416, and 4.682 GeV with a total integrated luminosity of 8.35  fb^{-1}.

Measurement of Ultra-High-Energy Diffuse Gamma-Ray Emission of the Galactic Plane from 10 TeV to 1 PeV with LHAASO-KM2A

The diffuse Galactic γ-ray emission, mainly produced via interactions between cosmic rays and the interstellar medium and/or radiation field, is a very important probe of the distribution, propagation, and interaction of cosmic rays in the Milky Way. In this Letter, we report the measurements of diffuse γ rays from the Galactic plane between 10 TeV and 1 PeV energies, with the square kilometer array of the Large High Altitude Air Shower Observatory (LHAASO). Diffuse emissions from the inner (15°10  TeV). The energy spectrum in the inner Galaxy regions can be described by a power-law function with an index of -2.99±0.04, which is different from the curved spectrum as expected from hadronic interactions between locally measured cosmic rays and the line-of-sight integrated gas content. Furthermore, the measured flux is higher by a factor of ∼3 than the prediction. A similar spectrum with an index of -2.99±0.07 is found in the outer Galaxy region, and the absolute flux for 10≲E≲60  TeV is again higher than the prediction for hadronic cosmic ray interactions. The latitude distributions of the diffuse emission are consistent with the gas distribution, while the longitude distributions show clear deviation from the gas distribution. The LHAASO measurements imply that either additional emission sources exist or cosmic ray intensities have spatial variations.

Precise Measurement of the e^{+}e^{-}→D_{s}^{*+}D_{s}^{*-} Cross Sections at Center-of-Mass Energies from Threshold to 4.95 GeV

The process e^{+}e^{-}→D_{s}^{*+}D_{s}^{*-} is studied with a semi-inclusive method using data samples at center-of-mass energies from threshold to 4.95 GeV collected with the BESIII detector operating at the Beijing Electron Positron Collider. The Born cross sections of the process are measured for the first time with high precision in this energy region. Two resonance structures are observed in the energy-dependent cross sections around 4.2 and 4.4 GeV. By fitting the cross sections with a coherent sum of three Breit-Wigner amplitudes and one phase-space amplitude, the two significant structures are assigned masses of (4186.8±8.7±30) and (4414.6±3.4±6.1)  MeV/c^{2}, widths of (55±15±53) and (122.5±7.5±8.1)  MeV, where the first errors are statistical and the second ones are systematic. The inclusion of a third Breit-Wigner amplitude is necessary to describe a structure around 4.79 GeV.

[Research and reflection on the diversified method system of multi-stages and multi-scenarios surveillance and early warning of infectious diseases]

With the outbreak of infectious diseases, more and more attention has been paid to surveillance and early warning work. Timely and accurate monitoring data is the basis of infectious diseases prevention and control. Effective early warning methods for infectious diseases can improve the timeliness and sensitivity of early warning work. This paper briefly introduces the intelligent early warning model of infectious diseases, summarizes the emerging surveillance and early warning methods of infectious diseases, and seeks the possibility of diversified surveillance and early warning in different epidemic stages and different outbreak scenarios of infectious diseases. This paper puts forward the idea of constructing a diversified method system of infectious diseases surveillance and early warning based on multi-stages and multi-scenarios and discusses the future development trend of infectious diseases surveillance and early warning, in order to provide reference for improving the construction level of infectious diseases surveillance and early warning system in China.

First Experimental Study of the Purely Leptonic Decay D_{s}^{*+}→e^{+}ν_{e}

Using 7.33  fb^{-1} of e^{+}e^{-} collision data taken with the BESIII detector at the BEPCII collider, we report the first experimental study of the purely leptonic decay D_{s}^{*+}→e^{+}ν_{e}. Our data contain a signal of this decay with a statistical significance of 2.9σ. The branching fraction of D_{s}^{*+}→e^{+}ν_{e} is measured to be (2.1_{-0.9_{stat}}^{+1.2}±0.2_{syst})×10^{-5}, corresponding to an upper limit of 4.0×10^{-5} at the 90% confidence level. Taking the total width of the D_{s}^{*+} [(0.070±0.028)  keV] predicted with the radiative D_{s}^{*+} decay from the lattice QCD calculation as input, the decay constant of the D_{s}^{*+} is determined to be f_{D_{s}^{*+}}=(214_{-46_{stat}}^{+61}±44_{syst})  MeV, corresponding to an upper limit of 354 MeV at the 90% confidence level.

Initial Report of Boswellia Serrata for Management of Cerebral Radiation Necrosis after Stereotactic Radiosurgery for Brain Metastases

PURPOSE/OBJECTIVE(S)

Radiation necrosis (RN) is a concerning late toxicity after radiation therapy (RT) for brain metastases. Oral corticosteroids are the mainstay of management; however, they are not optimal for long-term use given multiple side effects and drug interactions, particularly with the emergence of immunotherapy for several cancers. Boswellia serrata (BS) is an over-the-counter supplement used for its anti-inflammatory properties and has been recently shown to reduce cerebral edema after brain RT. We evaluated the response rates with BS in a series of patients with brain metastases treated with stereotactic radiosurgery (SRS) who developed RN.

MATERIALS/METHODS

We included patients who developed RN after SRS for brain metastases at our institution from 2020-2022 and were treated with BS. Patients were prescribed over the counter BS 4.2-4.5g daily in divided doses. Follow-up MRI imaging was obtained every 2-3 months after starting BS. Response was assessed using Response Assessment in Neuro-Oncology (RANO) criteria. Primary endpoint was ≥25% decrease in edema volume on T2-FLAIR MRI from baseline. Patients were censored if they had tumor progression or repeat RT to necrotic area, or death. Kaplan-Meier curves were used for survival estimates.

RESULTS

A total of 50 patients received BS for Grade 1-3 CTCAE v5.0 RN (G1 = 11, G2 = 36, and G3 = 3). Median age was 62.8 years (range 36.9 - 50) and median RT dose was 24 Gy in 3 fractions. Median time to RN after SRS was 10 months(m). Median follow-up after starting BS was 6m and 40 patients had at least 1 follow up MRI available to evaluate response. The best response was complete response (CR) in 15% patients and partial response (PR) in 40% while 35% had stable disease (SD) and 10% had progressive disease. Median time to CR was 9m (6-12m) and PR was 6m (3-12m). Percentage of patients who had any response (CR or PR) at 3, 6, 9 and 12 months was 25%, 60%, 43% and 50%, respectively. 56% patients had symptomatic RN, of which 35.7% had improvement in symptoms with BS alone, while 64% required steroid use. Overall, median duration of response in patients with CR, PR or SD was 7.5m(range 2-31m). Salvage treatment for RN was steroids (33), surgery (4), Bevacizumab (5) or hyperbaric oxygen therapy (1). No patients had any CTCAE grade 3 or higher toxicities. 3 patients (6%) had any side-effects all of whom had Grade 1-2 gastrointestinal intolerance or diarrhea. 2 patients stopped treatment due to enrolment on an immunotherapy clinical trial. Overall, 39 patients remained on BS at last follow-up or death.

CONCLUSION

We observed >50% response rates with use of BS in our cohort of patients with Grade 1-3 RN after SRS. More than 1/3rd patients with symptomatic RN were able to avoid long-term steroid use. BS is an easily available over-the-counter drug that appears to be a safe and promising treatment option for RN, and can potentially decrease steroid dependence in these patients, reducing the risk of several side-effects. Further prospective studies to compare Boswellia with placebo is warranted.

Exhaled volatile fatty acids, ruminal methane emission, and their diurnal patterns in lactating dairy cows

To date, the commonly used methods to assess rumen fermentation are invasive. Exhaled breath contains hundreds of volatile organic compounds (VOC) that can reflect animal physiological processes. In the present study, for the first time, we aimed to use a noninvasive metabolomics approach based on high-resolution mass spectrometry to identify rumen fermentation parameters in dairy cows. Enteric methane (CH4) production from 7 lactating cows was measured 8 times over 3 consecutive days using the GreenFeed system (C-Lock Technology Inc.). Simultaneously, exhalome samples were collected in Tedlar gas sampling bags and analyzed offline using a secondary electrospray ionization high-resolution mass spectrometry system. In total, 1,298 features were detected, among them targeted exhaled volatile fatty acids (eVFA; i.e., acetate, propionate, butyrate), which were putatively annotated using their exact mass-to-charge ratio. The intensity of eVFA, in particular acetate, increased immediately after feeding and followed a similar pattern to that observed for ruminal CH4 production. The average total eVFA concentration was 35.5 count per second (CPS), and among the individual eVFA, acetate had the greatest concentration, averaging 21.3 CPS, followed by propionate at 11.5 CPS, and butyrate at 2.67 CPS. Further, exhaled acetate was on average the most abundant of the individual eVFA at around 59.3%, followed by 32.5 and 7.9% of the total eVFA for propionate and butyrate, respectively. This corresponds well with the previously reported proportions of these VFA in the rumen. The diurnal patterns of ruminal CH4 emission and individual eVFA were characterized using a linear mixed model with cosine function fit. The model characterized similar diurnal patterns for eVFA and ruminal CH4 and H2 production. Regarding the diurnal patterns of eVFA, the phase (time of peak) of butyrate occurred first, followed by that of acetate and propionate. Importantly, the phase of total eVFA occurred around 1 h before that of ruminal CH4. This corresponds well with existing data on the relationship between rumen VFA production and CH4 formation. Results from the present study revealed a great potential to assess the rumen fermentation of dairy cows using exhaled metabolites as a noninvasive proxy for rumen VFA. Further validation, with comparisons to rumen fluid, and establishment of the proposed method are required.

Results of a Multi-institutional Randomized Phase 3 Trial of Parotid-Sparing Whole Brain Radiotherapy

PURPOSE/OBJECTIVE(S)

Observational studies have reported that xerostomia is common after conventional whole brain radiotherapy (WBRT) and associated with parotid dose. In this multi-institutional, single-blind randomized controlled trial, we hypothesized that patient-reported xerostomia is reduced in patients randomized to parotid-sparing vs. standard WBRT fields.

MATERIALS/METHODS

Between 2018 and 2021, patients receiving conventional WBRT (30-35 Gy in 10-15 fractions) for any diagnosis were enrolled at 3 academic institutions. Patients were randomized between standard WBRT fields covering the C1 vertebra with no prospective parotid delineation (control) vs. parotid-sparing fields without C1 coverage (experimental). Patients completed the University of Michigan Xerostomia Questionnaire (Scored 0-100, higher is worse) at baseline, EndRT, 2 weeks, 1 month, 3 months, and 6 months. Patients were excluded from toxicity analyses if baseline xerostomia score was >50 or if they did not complete any post-baseline questionnaires. The primary endpoint was proportion of patients with ≥15 point absolute increase in xerostomia score from baseline to 1 month; 108 patients were needed for an 80% power to detect a 22% absolute difference (1-sided significance of 0.05). The secondary endpoint was the rate of marginal failures.

RESULTS

The study closed early after 56 patients were randomized. Median survival was 4.6 months. 46 patients (23 in each arm) were eligible for analysis. Mean parotid dose was 17 vs. 10 Gy in the standard vs. parotid-sparing arms, respectively. The table below shows mean xerostomia score and proportion of patients with ≥15 increase in xerostomia score at each time point. There was no difference in the proportion of patients experiencing ≥15 increase in xerostomia score at 1 month, though there was a trend toward lower xerostomia score at 1 month in patients randomized to parotid-sparing fields (p = 0.07, Table). Xerostomia rates were also significantly improved in the parotid-sparing arm at EndRT (p = 0.03), but no longer-term difference was observed with greater attrition at 3 and 6 months. On linear regression, there was a trend toward association between mean parotid dose and xerostomia score at 1 month (p = 0.06). There were no reported marginal failures in either arm.

CONCLUSION

Parotid-sparing without coverage of the C1 vertebra appears safe and may meaningfully reduce acute xerostomia in patients with limited life expectancy who are candidates for conventional WBRT, although the study was underpowered to detect a significant difference at 1 month.

Safety and Efficacy of Stereotactic Radiosurgery with Concurrent Targeted Systemic Therapy for Brain Metastases

PURPOSE/OBJECTIVE(S)

Data describing the safety and efficacy of central nervous system (CNS)-active targeted systemic therapies in combination with stereotactic radiosurgery (SRS, 1 fraction) and/or radiotherapy (SRT, 3-5 fractions) for brain metastases are emerging but limited. We report rates of local and intracranial failure and radiation necrosis in patients receiving CNS-active targeted systemic therapy and SRS/SRT.

MATERIALS/METHODS

We retrospectively identified patients with intact brain metastases at two institutions from 2009-2022 who were treated with SRS/SRT and CNS-active targeted systemic therapy in any sequence. Patients were followed for a minimum of 3 months after SRS/SRT with brain MRI. Patients typically stopped the targeted agent 2-4 days prior to radiation and resumed 2-4 days after. Targeted therapies included inhibitors of ALK/ROS1 (Alectinib, Ceritinib, Crizotinib, Lorlatinib), EGFR (Afatinib, Erlotinib, Gefitinib, Osimertinib), BRAF (Dabrafenib, Encorafenib, Vemurafenib), MEK (Binimetinib, Trametinib), CDK 4/6 (Abemaciclib, Palbociclib, Ribociclib), HER2 (Afatinib, Lapatinib, Neratinib, Pertuzumab, Trastuzumab, T-DM1, T-DXd, Tucatinib), KRAS (Adagrasib and Sotorasib), PARP (Niraparib, Olaparib), VEGF(R) (Axitinib, Bevacizumab, Ramucirumab), and less-selective tyrosine (receptor) kinase inhibitors (Bosutinib, Brigatinib, Entrectinib, Lenvatinib, Pazopanib, Sorafenib, Sunitinib). Local failure (LF) and radiation necrosis were determined radiographically with clinical impression (grade 2 (symptomatic) or higher (G2+)) and compared between different systemic agents.

RESULTS

The study included 95 patients with 310 metastases (SRS 246, SRT 64 metastases). Most common primary histologies were non-small cell lung cancer (36% 34/95), breast cancer (28% 27/95), and melanoma (16% 15/95). Overall survival at 1 and 2 years was 80% (76/95) and 55% (52/95), respectively. Median follow-up was 16.6 (range 3-91) months. Median tumor size was 7mm (range 1-75mm). Median number of brain metastases per patient was 2.5 (range 1-12). The G2+ radiation necrosis rate was 5.8% (18/310) while the LF rate was 9.7% (30/310) per metastasis. There was no significant difference in G2+ radiation necrosis by class of targeted therapy. Sixty-two percent (59/95) of patients experienced distant intracranial failure. Median intracranial progression free survival (PFS) was 8.0 (range 0.4-61.4) months.

CONCLUSION

Although heterogeneous, patients treated with SRS/SRT and ongoing CNS-active targeted systemic therapies have on average >6 month intracranial PFS and little evidence of significant toxicity. We observed <6% G2+ radiation necrosis for this cohort, and no particular class of agent was associated with a significantly higher rate of G2+ radiation necrosis.

Integration of Multiparameter MRI into Conventional Pretreatment Risk Factors to Predict Adverse Features after Radical Prostatectomy

PURPOSE/OBJECTIVE(S)

The purpose of this study was to Integration of Multiparameter MRI into conventional pretreatment risk factors to develop nomogram for the prediction of adverse features (i.e., positive margin (PM) or extra-prostatic extension (EPE)) indicated for postoperative radiotherapy in patients with prostate cancer.

MATERIALS/METHODS

We analyzed 203 histologically proven prostate cancer patients underwent preoperative 3T multiparametric MRI including high b value (0, 1500 s/mm2) diffusion-weighted imaging between 2019 and 2022 at our hospital. Patients with a history of neoadjuvant hormonal therapy, or patients whose surgeon's experience was ≤3 years were excluded. Age, surgical technique, serum PSA level, PSA density, clinical T stage, and biopsy Gleason score were clinical predictors. MRI parameters include prostate volume, tumor size, ECE score, seminal vesicle invasion score, tumor location (apex, peripheral region, or bladder neck), apparent diffusion coefficient (ADC), tumor contact length (TCL), PI-RADS score. Predictors were used in nomograms developed from multivariable logistic regression analysis to estimate the probability of positive margin (PM) or extra-prostatic extension (EPE) after RP. The nomogram's predictive accuracy and discriminative ability were determined by the concordance index with calibration and receiver operating characteristic (ROC) curves.

RESULTS

(1) Patient characters: Table 1 lists the MRI characteristics of the patients. Median PSA level is 17.6ng/ml. All patients received extra-fascial resection. 44% of the patients underwent robotic surgery. 24% of the patients had positive margins. In 226 patients who was clinically confined to the prostate, 100 (44%) had a postoperative pathological upgrade of pT3a or above. 46 (29%) of the 158 patients with biopsy grade group (GG)1 was confirmed GG3-5 after RP.

CONCLUSION

Using mpMRI parameters and clinicopathological information, we produced nomograms that may accurately predict adverse Features that are indications for postoperative radiotherapy after RP, which may help individualize treatment decision-making.

Using Proteome Microarray and Gene Expression Omnibus Database to Screen Tumour-Associated Antigens to Construct the Optimal Diagnostic Model of Oesophageal Squamous Cell Carcinoma

AIMS

Autoantibodies against tumour-associated antigens (TAAs) are promising biomarkers for early immunodiagnosis of cancers. This study was designed to screen and verify autoantibodies against TAAs in sera as diagnostic biomarkers for oesophageal squamous cell carcinoma (ESCC).

MATERIALS AND METHODS

The customised proteome microarray based on cancer driver genes and the Gene Expression Omnibus database were used to identify potential TAAs. The expression levels of the corresponding autoantibodies in serum samples obtained from 243 ESCC patients and 243 healthy controls were investigated by enzyme-linked immunosorbent assay (ELISA). In total, 486 serum samples were randomly divided into the training set and the validation set in the ratio of 2:1. Logistic regression analysis, recursive partition analysis and support vector machine were performed to establish different diagnostic models.

RESULTS

Five and nine candidate TAAs were screened out by proteome microarray and bioinformatics analysis, respectively. Among these 14 anti-TAAs autoantibodies, the expression level of nine (p53, PTEN, GNA11, SRSF2, CXCL8, MMP1, MSH6, LAMC2 and SLC2A1) anti-TAAs autoantibodies in the cancer patient group was higher than that in the healthy control group based on the results from ELISA. In the three constructed models, a logistic regression model including four anti-TAA autoantibodies (p53, SLC2A1, GNA11 and MMP1) was considered to be the optimal diagnosis model. The sensitivity and specificity of the model in the training set and the validation set were 70.4%, 72.8% and 67.9%, 67.9%, respectively. The area under the receiver operating characteristic curve for detecting early patients in the training set and the validation set were 0.84 and 0.85, respectively.

CONCLUSIONS

This approach to screen novel TAAs is feasible, and the model including four autoantibodies could pave the way for the diagnosis of ESCC.

Threshold of 25(OH)D and consequently adjusted parathyroid hormone reference intervals: data mining for relationship between vitamin D and parathyroid hormone

PURPOSE

By recruiting reference population, we aimed to (1): estimate the 25(OH)D threshold that maximally inhibits the PTH, which can be defined as the cutoff value for vitamin D sufficiency; (2) establish the PTH reference interval (RI) in population with sufficient vitamin D.

METHODS

Study data were retrieved from LIS (Laboratory Information Management System) under literature suggested criteria, and outliers were excluded using Tukey fence method. Locally weighted regression (LOESS) and segmented regression (SR) were conducted to estimate the threshold of 25(OH)D. Multivariate linear regression was performed to evaluate the associations between PTH concentration and variables including 25(OH)D, gender, age, estimated glomerular filtration rate (EGFR), body mass index (BMI), albumin-adjusted serum calcium (aCa), serum phosphate(P), serum magnesium(Mg), and blood collection season. Z test was adopted to evaluate whether the reference interval should be stratified by determinants such as age and gender.

RESULTS

A total of 64,979 apparently healthy subjects were recruited in this study, with median (Q1, Q3) 25(OH)D of 45.33 (36.15, 57.50) nmol/L and median (Q1, Q3) PTH of 42.19 (34.24, 52.20) ng/L. The segmented regression determined the 25(OH)D threshold of 55 nmol/L above which PTH would somewhat plateau and of 22 nmol/L below which PTH would rise steeply. Multivariate linear regression suggested that gender, EGFR, and BMI were independently associated with PTH concentrations. The PTH RI was calculated as 22.17-72.72 ng/L for subjects with 25(OH)D ≥ 55 nmol/L with no necessity of stratification according to gender, age, menopausal status nor season.

CONCLUSION

This study reported 25(OH)D thresholds of vitamin D sufficiency at 55 nmol/L and vitamin D deficiency at 22 nmol/L, and consequently established PTH RIs in subjects with sufficient vitamin D for northern China population for the first time.

A Single Institution Experience of a Biweekly Head and Neck Contouring Peer Review

PURPOSE/OBJECTIVE(S)

Due to the complexity of head and neck radiotherapy, a single weekly chart rounds session is insufficient to review contours. A dedicated biweekly review of all head and neck contours (prior to treatment planning) that can fully assess images and targets can lead to better patient outcomes. A full review of all head and neck contours also increases the number of contours that resident physicians can observe.

MATERIALS/METHODS

In total, 38 consecutive patients treated between August 2022 and December 2022 were analyzed in a biweekly head and neck contouring peer review. Three head and neck faculty radiation oncologists and four resident physicians participated. An allotted 30-minute time was granted per review session. Changes were tracked and stratified by whether physician contours underwent no changes/minor changes/major changes. Other metrics including re-irradiation status and attendance were noted.

RESULTS

An average of 1.65 patients were discussed per review. Given the allotted time, on average this allowed for up to 18 minutes of discussion per patient. In contrast, our departmental chart rounds session is allotted 1 hour for 40+ patients to be discussed (1.5 minutes per patient). Overall, 10/38 patients underwent minor changes (26.3%) to contour structures and 1 patient underwent a major change (2.6%). Four patients (10.5%) were re-irradiation cases CONCLUSION: A dedicated biweekly half hour review session is both feasible and practical. Additional discussion of head and neck contours helps to implement improvements into a patient's treatment plan. Additional discussion and debate for primary and re-irradiation also increases the number of cases that a training resident physician can observe.

Feasibility of Omitting Contralateral Neck Irradiation in Patients with Node-Negative Sinonasal Squamous Cell Carcinoma Crossing the Midline

PURPOSE/OBJECTIVE(S)

This study aims to analyze the nodal target volume in patients with node-negative SNSCC crossing the midline.

MATERIALS/METHODS

One hundred and four patients with node-negative advanced sinonasal squamous cell carcinoma (SNSCC) crossing the midline were included. Survival rates were estimated and compared between treatment groups.

RESULTS

Sixty-four patients received contralateral ENI (contralateral ENI group), while forty patients did not (non-contralateral ENI group). The median follow-up time was 89.99 and 95.01 months in the contralateral and non-contralateral ENI groups, respectively. At 5 years, the regional relapse-free survival and contralateral regional relapse-free survival were 57.68% vs. 55.83% (p = 0.372), and 57.68% vs. 61.62% (p = 0.541), in contralateral ENI group vs. non-contralateral ENI group, respectively. Five-year overall survival, local relapse-free survival, and distant metastasis-free survival were similar in the two groups (all p > 0.05).

CONCLUSION

In patients with node-negative SNSCC crossing the midline, omission of contralateral ENI did not affect regional control and survival outcomes on the premise of receiving ipsilateral ENI covering at least levels Ib and II.

Attitudes and Barriers to Planned Family Building among Professionals and Trainees in Radiation Oncology

PURPOSE/OBJECTIVE(S)

The timing of residency training often coincides with peak biological fertility. However, family building is frequently deferred and may lead to unanticipated infertility. The attitudes and barriers to family planning are not well described among medical professionals and trainees in radiation oncology (RO).

MATERIALS/METHODS

The Society for Women in Radiation Oncology (SWRO) conducted an electronic survey among practicing physicians, physicists, and residents between January and February 2023, using email and social media as recruitment tools. The survey questions queried demographics, family planning, fertility. Frequencies of responses were summarized using descriptive statistics.

RESULTS

On interim analysis, 147 responses were collected; 123 (89.8%) were SWRO members. Gender identities reported were female (136, 93.2%), male (7, 4.8%), nonbinary or gender diverse (2, 1.4%), and transgender female (1, 0.7%). 95 (64.6%) respondents were age 35 or younger. The majority were practicing physicians (72, 49.0%) followed by RO residents (45, 30.6%), medical physicists (17, 11.6%), medical students, (5, 3.4%), and medical physics residents (4, 2.7%). Most respondents agreed that their reproductive timeline had been impacted by medical training (106, 76.3%). Of those who deferred parenthood due to training or career, 40 (36.7%) were dissatisfied with their choice and 33 (30.2%) were satisfied. 129 (92.8%) reported not receiving any information about fertility preservation during training. Only 65 (47.4%) felt they had a mentor with whom they could approach to discuss family planning. Overall, 84 (60.4%) expressed concern about their fertility and 34 (24.5%) had previously undergone fertility testing. 16 (11.5%) completed at least one cycle of elective fertility preservation and 12 (8.6%) were planning to do so. 39 (28.1%) had considered elective fertility preservation but not pursued it, while 65 (46.8%) had not considered it. Among those two groups, the common reported barriers to accessing fertility services were financial burden (n = 28, 28.6%), lack of awareness of available options (n = 12, 12.2%), difficulty accessing fertility services (n = 6, 6.1%), and difficulty finding time during training (n = 4, 4.1%). Insurance coverage for elective fertility preservation was fully or partially covered by insurance for 12 (8.8%), not covered for 53 (38.7%), and 72 (52.6%) were uncertain of their coverage.

CONCLUSION

The study highlights the impact of training on family building plans of medical professionals in RO. Despite high levels of concern about fertility, few respondents received education about fertility options in training and a limited number had access to mentors to discuss this issue. Significant barriers exist to accessing fertility services, including knowledge gaps about insurance coverage, highlighting a need for further exploration of these barriers and advocacy for improved family planning support for those in RO who desire it.

Neurologic Events and Outcomes in Patients Receiving Proton and Photon Reirradiation for High Grade Non-Codeleted Gliomas

PURPOSE/OBJECTIVE(S)

Patients undergoing reirradiation (ReRT) for high grade glioma are at risk for tumor progression, pseudoprogression, and radiation necrosis. We investigated factors associated with neurologic events and disease control after re-irradiation with protons and photons at a single academic center.

MATERIALS/METHODS

We reviewed records and MRIs of patients receiving scanning beam proton (since center opening in 2016) and photon (since 2015) reirradiation in ≥10 fractions for grade 3 anaplastic astrocytoma (AA) and grade 4 glioblastoma (GBM), excluding 1p19q co-deleted oligodendrogliomas and extensive multifocal/leptomeningeal disease. The primary endpoint was time from ReRT to ≥ grade 2 pseudoprogression or radiation necrosis (PsP/RN, grade 2: moderate symptoms requiring outpatient steroids/bevacizumab, grade 3: severe symptoms leading to admission or surgical intervention). Dose was converted to EQD2 using a/b = 3. Cox proportional hazards model was used to calculate survival and time to PsP/RN.

RESULTS

A total of 53 patients were included (26 protons, 27 photons, median KPS 80). Patients receiving protons had more favorable features. Compared to the photons, the proton group was younger (48 vs. 58) and more likely to have AA (46% vs. 22%) and resection within 3 months (42% vs 26%). The proton group also had a longer interval from prior RT (57 vs. 39 months) and were less likely to receive bevacizumab at reRT (15% vs. 59%). CTV was 130 cc for protons vs 99 cc for photons, and most had active disease at time of ReRT identified on planning MRI (76% protons, 85% photons). Median OS was 10.5 months (14.1 months protons, 8.1 months photons), with time from initial RT the only significant factor on multivariate analysis. Median PFS was 9.4 months (9.8 months protons, 6.2 months photons). 9 patients (18%) had ≥ grade 3 PsP/RN (8 proton, 1 photon) and 21 patients (41%) had ≥ grade 2 PsP/RN (16 proton, 5 photon). Grade 3 events included 1 seizure (photon group), 1 hemorrhage, 1 thalamic stroke, 1 shunt placement, 1 re-resection, and PSP4 4 PsP/RN requiring admission. Protons were associated shorter time to ≥ grade 2 PsP/RN (4 months vs. not reached, p = 0.027). When accounting for bevacizumab use at time of reRT, the association between protons and PsP/RN lost significance but there remained a trend (grade 2, p = 0.095, HR 2.4; grade 3, p = 0.105, HR 5.8). CTV, MGMT status, EQD2, and interval from prior RT were not associated with PsP/RN.

CONCLUSION

High grade neurologic events were common in patients with predominantly active, unresected high grade gliomas receiving ReRT. Though ascertainment and survival bias are significant limitations, pseudoprogression and necrosis appeared to be more prominent in patients receiving protons. These results contribute to ongoing efforts to both optimize ReRT for high grade glioma and investigate biologic effects of proton therapy.

The impact of social media on guideline-concordant cervical cancer-screening: insights from a national survey

OBJECTIVES

Cervical cancer is one of the leading causes of cancer mortality in women, yet routine screenings lead to early detection and sometimes even prevention. Screening is an effective way to prevent cervical cancer, and it has been implemented in many countries and regions worldwide, especially in developed countries. However, the incidence of cervical cancer remains a public health problem due to screening disparities in the population. Social media engagement and overloading of online health information may be the cause of this disparity.

STUDY DESIGN

Cross-sectional study.

METHODS

Data from the Health Information National Trends Survey (a national survey conducted by the National Cancer Institute) was used to characterise cervical cancer screening into two dimensions; namely, high-frequency screening and guideline-concordant screening. The differences between these two screening frequency behaviours were compared by applying ordered logistic regression and binary logistic regression, and the mechanisms of guideline-concordant screening were explored.

RESULTS

The factors influencing high-frequency screening and guideline-concordant screening were different. Only self-efficacy (odds ratio [OR] = 1.16; 95% confidence interval [CI] = 0.98, 1.37) had a significant positive association with the high-frequency screening behaviour. Social media engagement (OR = 0.57; 95% CI = 0.33, 0.96) was shown to have a significant negative impact on guideline-concordant screening. A theory-based mechanism of screening behaviour found that traditional health perception factors no longer influence guideline-concordant screening behaviour, whereas environmental factors (e.g., social media) significantly reduce guideline-concordant screening behaviour.

CONCLUSIONS

The results from this study indicate that while the internet has become the main channel through which women acquire health resources, and social media has become a main platform for people to obtain health information, online information cannot guide people to engage in appropriate healthy behaviours. Overloading of online health information and the digital divide may lead to excessive screening. Consequently, it is important to address the screening disparity caused by health behaviours as a result of environmental factors and the digital divide.

[The clinical practice and consideration for donor liver expansion]

Liver transplantation is the most effective method to address end-stage liver disease. However, there is a huge imbalance between organ supply and demand in China. Recently,effective expansion of the donor liver has become a hot research direction in academia. Authors' group comprehensively integrates domestic and foreign evidence-based medical evidence, the latest academic outcomes and clinical experience. Based on the innovative viewshed of crossfusion between biomedical engineering and medicine, author group systematically elaborate in the main strategies for expanding the liver donor pool, including the multichannel expansion of marginal donor liver,multidimensional innovation of technologies in transplant surgery and diversified exploration of alternative resources of organs. The author group aims to promote the construction of a large cohort,the integration of big data,and the output of high quality research,achieving innovative theory and clinical translation in organ transplantation,thus promoting the higher quality development of liver transplantation in China.

The Society for Women in Radiation Oncology: Where are We Five Years Later?

PURPOSE/OBJECTIVE(S)

The Society for Women in Radiation Oncology (SWRO) was founded in 2017 with a mission to promote representation and gender equity in the field of radiation oncology (RO). SWRO members include faculty and trainee radiation oncologists and medical physicists. We aim to assess the current experiences of SWRO members using a comprehensive survey of gender-related workforce issues we developed. Data was used to establish a 5-year benchmark.

MATERIALS/METHODS

From January to February 2023, an anonymous survey was distributed to current SWRO members. Questions included demographics, family planning/fertility issues, perceptions of the field, and membership needs. Descriptive statistics were used to summarize frequencies of the multiple-choice items on the survey.

RESULTS

On interim analysis, 115 of 680 (17%) completed the survey from 11 countries, 81% of which reside in the US. 55% were faculty physicians, 26% resident physicians, 10% faculty physicists, and 3% physics residents. The majority were female (97%) and either married or in a domestic partnership (74%). 47% reported having at least one child, and 26% reported that they or their partner became pregnant during residency. Length of leave was impacted by residents' desire to complete residency training on schedule. 53% felt RO was perceived as family-friendly, but much fewer (17%) agreed that it is. After clinical responsibilities (70%), insufficient mentorship was cited as the second most common limitation to professional productivity (35%). 48% reported being somewhat or extremely satisfied with current mentorship availability at their institution, while 56% reported being similarly satisfied with the mentorship available within the field. 69% reported seeking or having sought female mentorship outside of their institution. Unwanted sexual comments, attention, or advances by superiors or colleagues was reported by 38% of respondents. Additionally, 72% either agreed or strongly agreed that SWRO membership and participation were a valuable use of their time, with the top three reasons for joining being networking opportunities, mentorship opportunities, and increasing the visibility of women and gender minorities in RO. Suggested improvements included increasing female physics representation and advocacy, and physics-related events, as well as providing opportunities for members to socialize and interact.

CONCLUSION

This study provides an update on the experiences of women and gender minorities in the field of RO since the creation of SWRO in 2017. The study highlights ongoing targets for improvement such as gender-based obstacles, opportunity for additional education and advocacy, support of family-friendly culture shifts, mentorship, and increased physics inclusion and advocacy. These findings support the need for organizations such as SWRO to continue to promote representation and gender equity in RO.

Host response of Nicotiana benthamiana to the parasitism of five populations of root-lesion nematode, Pratylenchus coffeae, from China

In a recent survey of nematodes associated with tobacco in Shandong, China, the root-lesion nematode Pratylenchus coffeae was identified using a combination of morphology and molecular techniques. This nematode species is a serious parasite that damages a variety of plant species. The model plant benthi, Nicotiana benthamiana, is frequently used to study plant-disease interactions. However, it is not known whether this plant species is a host of P. coffeae. The objectives of this study were to evaluate the parasitism and pathogenicity of five populations of the root-lesion nematode P. coffeae on N. benthamiana.N. benthamiana seedlings with the same growth status were chosen and inoculated with 1,000 nematodes per pot. At 60 days after inoculation, the reproductive factors (Rf = final population densities (Pf)/initial population densities (Pi)) for P. coffeae in the rhizosphere of N. benthamiana were all more than 1, suggesting that N. benthamiana was a good host plant for P. coffeae.Nicotiana. benthamiana infected by P. coffeae showed weak growth, decreased tillering, high root reduction, and noticeable brown spots on the roots. Thus, we determined that the model plant N. benthamiana can be used to study plant-P. coffeae interactions.

Search for Λ[over ¯]-Λ Baryon-Number-Violating Oscillations in the Decay J/ψ→pK^{-}Λ[over ¯]+c.c

We report on the first search for Λ[over ¯]-Λ oscillations in the decay J/ψ→pK^{-}Λ[over ¯]+c.c. by analyzing 1.31×10^{9}  J/ψ events accumulated with the BESIII detector at the BEPCII collider. The J/ψ events are produced using e^{+}e^{-} collisions at a center of mass energy sqrt[s]=3.097  GeV. No evidence for hyperon oscillations is observed. The upper limit for the oscillation rate of Λ[over ¯] to Λ hyperons is determined to be P(Λ)=[B(J/ψ→pK^{-}Λ+c.c.)/B(J/ψ→pK^{-}Λ[over ¯]+c.c.)]<4.4×10^{-6} corresponding to an oscillation parameter δm_{ΛΛ[over ¯]} of less than 3.8×10^{-18}  GeV at the 90% confidence level.

[Effect of hollow compression screw internal fixation in treating McCrory-Bladin type Ⅱ lateral process fracture of the talus: open versus arthroscopy surgery]

In order to explore the clinical efficacy of hollow compression screw internal fixation in the treatment of lateral process fracture of the talus under open surgery versus arthroscopy procedure, a retrospective cohort study was conducted to analyze the clinical data of 33 patients with lateral process fracture of the talus admitted to Xuzhou Central Hospital from January 2019 to December 2021. There were 19 males (19 feet) and 14 females (14 feet), aged 18 to 50 years, with an average age of (32.2±9.3) years. According to the modified McCrory-Bladin classification, all patients were classified as type Ⅱ. Based on the different surgical methods, the patients were divided into the arthroscopy group (21 cases, treated with double-tunnel subtalar arthroscopy combined with hollow compression screw internal fixation) and the open group (12 cases, treated with open reduction and internal fixation with hollow compression screw). The operation time was observed and the surgical effects were evaluated using the visual analogue scale (VAS) of pain, the American Orthopedic Foot and Ankle Society (AOFAS) ankle-hindfoot score, the Foot Function Index (FFI), and the Foot and Ankle Ability Measure (FAAM), which includes the FAAM-ADL (activity of daily living subscale) and the FAAM-S (sport subscale). All the patients of the two groups achieved stage Ⅰ wound healing. On the first day after the operation, the mean VAS score of the arthroscopy group was 2.4±0.7, which was significantly lower than that of the open group (3.4±1.6) (P=0.020). No significant difference was observed in terms of the follow-up time, operation time and AOFAS score between the two groups (all P>0.05). The FFI score of the arthroscopy group was significantly lower than that of the open group, and the FAAM-ADL and FAAM-S scores were significantly higher than those in the open group (all P<0.05). Two cases of dorsal foot numbness occurred in the open group after the operation, and the incidence of complications was not significantly different from that of the arthroscopy group (P=0.054). For McCrory-Bladin type Ⅱ lateral process fracture of the talus, the use of compression screw internal fixation could achieve reliable results, however, compared to open surgery, arthroscopy procedure obtained mini trauma and better functions.

[A randomized controlled study on the long-term efficacy of intra-cervical lymphatic immunotherapy for adult allergic rhinitis]

Objective: To determine the long-term efficacy and safety of intra-cervical lymphatic immunotherapy (ICLIT) for adult allergic rhinitis (AR) by comparing it with subcutaneous immunotherapy (SCIT). Methods: A total of 100 adult AR patients with dust mite allergy in Department of Otorhinolaryngology, First People's Hospital of Foshan from Feb 2018 to Dec 2019 were randomly divided into two groups, 50 in SCIT group [including 42 males and 8 females, aging (32.55±9.72) years] and 50 in ICLIT group [including 45 males and 5 females, aging (31.33±9.84) years]. The changes in total symptom score (total system score, TSS), nasal symptom score (total nasal symptom score, TNSS), eye symptom score (total ocular scoring system, TOSS), drug score (total medication score, TMS), and quality of life score of the two groups of patients were evaluated before and after treatment, and the adverse reactions of all patients during the treatment period were recorded. The changes in the level of dust mite specific IgE (sIgE) in the serum were evaluated. GraphPad Prism 9.0 software was used for statistical analysis. Results: In the SCIT group, 38 patients completed treatment and follow-up, with a dropout rate of 24%. In the ICLIT group, 48 patients completed treatment and follow-up, with a dropout rate of only 4%. The scores of TSS, TNSS, TOSS, TMS, and quality of life in the ICLIT group before treatment were 32.1±3.0, 27.3±3.1, 4.8±2.8, 2.3±0.9, and 68.1±28.7, respectively; After 36 months of treatment, the scores were 21.8±11.4, 18.1±9.4, 3.7±2.9, 1.3±1.1, and 36.0±26.7, respectively, which were significantly lower than those before treatment (all P<0.001). After 36 months of treatment, the TSS of the ICLIT group improved by 10.3±11.2 compared to before, while the TSS of the SCIT group improved significantly by 21.9±11.0 compared to before, with statistically significant differences between the groups (P<0.001). No serious systemic adverse reactions occurred in both groups of patients. Conclusions: ICLIT treatment for adult AR has long-term efficacy, high safety, and high compliance, but its long-term efficacy is not as good as SCIT. ICLIT can be considered as a new complementary option for AR immunotherapy.

[Effects of tibial second toe free flap bridged with blood flow and nerve in the treatment of severe flexion contracture of the proximal interphalangeal joint]

Objective: To investigate the effects of tibial second toe free flap bridged with blood flow and nerve in the treatment of severe flexion contracture of the proximal interphalangeal joint. Methods: A retrospective observational study was conducted. From March 2013 to October 2019, 9 patients with severe flexion contracture (type Ⅲ) of the proximal interphalangeal joint after trauma operation, conforming to the inclusion criteria, were hospitalized in Suzhou Ruihua Orthopaedic Hospital, including 5 males and 4 females, aged from 17 to 62 years. After the contracture tissue affecting the extension of the proximal interphalangeal joint was cut off, and the scar tissue was resected, the size of the volar wound near the proximal interphalangeal joint in extended position was 2.0 cm×1.0 cm-2.5 cm×1.5 cm, with the length of proper digital artery and nerve defect being 1.0-1.5 cm. A free flap of the same size as the wound was cut from the tibial side of the second toe and transplanted to repair the wound, and the defective proper digital artery and nerve was repaired by bridging with the tibial proper plantar digital artery and nerve of about 1.5 cm in length. The full-thickness skin graft was taken from the proximal tibial side of the lower leg to repair the wound at flap donor site. The wound at skin graft donor site was sutured directly. The survival of flap and skin graft was observed after operation. The patients were followed up, and at the last follow-up, the recovery of the affected finger and the second toe, including the donor and recipient areas were observed, the two-point discrimination distances of the flap repaired site and the pulp of the affected finger were observed and measured at the same time, the blood flow patency of bridged vessel of the affected finger was examined by Allen test, and the function of the proximal interphalangeal joint of the affected finger was evaluated according to Chinese Medical Association's standard for the range of motion of proximal interphalangeal joint. Results: The flaps and skin grafts survived smoothly after operation. The follow-up after operation lasted for 5 to 22 months, with a mean of 10 months. At the last follow-up, the flap repaired site had good shape, good color and texture, with the two-point discrimination distance being 9-12 mm, and the two-point discrimination distance of the pulp of the affected finger was 6-10 mm; the Allen test results of the affected fingers were all negative (i.e., the bridged vessels had good blood flow patency), with no recurrence of flexion contracture, and the function of the proximal interphalangeal joint was evaluated as excellent; the skin graft area of the second toe was not ruptured but was a little pigmented, and the flexion and extension activities of toe were good. Conclusions: The tibial second toe free flap bridged with blood flow and nerve has reliable therapeutic effect in the treatment of severe flexion contracture of the proximal interphalangeal joint, and the color and texture of the flap repaired area are good. Bridging to repair the severely contracted proper digital artery and nerve is beneficial to improve the blood supply of the finger body and rebuild the sensation.

[Membrane anatomy in right colon cancer: definition and identification of mesocolic completeness]

Complete mesocolic excision (CME) and D3 resection of right colon cancer have been widely implemented, but the definition and identification of the completeness of the mesentery have not been fully agreed, especially the dorsal and medial borders. In this paper, we proposed the dorsal fascia of the colonic mesentery as the dorsal border of the mesocolon and the line connecting the roots of the ileocolic artery and the middle colic artery (ICA-MCA line) as the medial border of the CME by systematically studying the relationship between the mesentery and the mesenteric bed from the theory of membrane anatomy, combined with surgical experience and in-depth review of ontogenetic anatomy. We also proposed the visible "superior mesenteric vein notch" and "middle colic artery triangle" on surgical specimens as identifiers of mesocolic completeness.