Detection of lung cancer through SERS analysis of serum

Early detection and postoperative assessment are crucial for improving overall survival among lung cancer patients. Here, we report a non-invasive technique that integrates Raman spectroscopy with machine learning for the detection of lung cancer. The study encompassed 88 postoperative lung cancer patients, 73 non-surgical lung cancer patients, and 68 healthy subjects. The primary aim was to explore variations in serum metabolism across these cohorts. Comparative analysis of average Raman spectra was conducted, while principal component analysis was employed for data visualization. Subsequently, the augmented dataset was used to train convolutional neural networks (CNN) and Resnet models, leading to the development of a diagnostic framework. The CNN model exhibited superior performance, as verified by the receiver operating characteristic curve. Notably, postoperative patients demonstrated an increased likelihood of recurrence, emphasizing the crucial need for continuous postoperative monitoring. In summary, the integration of Raman spectroscopy with CNN-based classification shows potential for early detection and postoperative assessment of lung cancer.

An Anthropomorphic Diagnosis System of Pulmonary Nodules using Weak Annotation-Based Deep Learning

Purpose

To develop an anthropomorphic diagnosis system of pulmonary nodules (PN) based on Deep learning (DL) that is trained by weak annotation data and has comparable performance to full-annotation based diagnosis systems.

Methods

The proposed system uses deep learning (DL) models to classify PNs (benign vs. malignant) with weak annotations, which eliminates the need for time-consuming and labor-intensive manual annotations of PNs. Moreover, the PN classification networks, augmented with handcrafted shape features acquired through the ball-scale transform technique, demonstrate capability to differentiate PNs with diverse labels, including pure ground-glass opacities, part-solid nodules, and solid nodules.

Results

The experiments were conducted on two lung CT datasets: (1) public LIDC-IDRI dataset with 1,018 subjects, (2) In-house dataset with 2740 subjects. Through 5-fold cross-validation on two datasets, the system achieved the following results: (1) an Area Under Curve (AUC) of 0.938 for PN localization and an AUC of 0.912 for PN differential diagnosis on the LIDC-IDRI dataset of 814 testing cases, (2) an AUC of 0.943 for PN localization and an AUC of 0.815 for PN differential diagnosis on the in-house dataset of 822 testing cases. These results demonstrate comparable performance to full annotation-based diagnosis systems.

Conclusions

Our system can efficiently localize and differentially diagnose PNs even in resource-limited environments with good robustness across different grade and morphology sub-groups in the presence of deviations due to the size, shape, and texture of the nodule, indicating its potential for future clinical translation.

Summary

An anthropomorphic diagnosis system of pulmonary nodules (PN) based on deep learning and weak annotation was found to achieve comparable performance to full-annotation dataset-based diagnosis systems, significantly reducing the time and the cost associated with the annotation.

Key Points

A fully automatic system for the diagnosis of PN in CT scans using a suitable deep learning model and weak annotations was developed to achieve comparable performance (AUC = 0.938 for PN localization, AUC = 0.912 for PN differential diagnosis) with the full-annotation based deep learning models, reducing around 30%∼80% of annotation time for the experts.The integration of the hand-crafted feature acquired from human experts (natural intelligence) into the deep learning networks and the fusion of the classification results of multi-scale networks can efficiently improve the PN classification performance across different diameters and sub-groups of the nodule.

Determination of Spin-Parity Quantum Numbers of X(2370) as 0^{-+} from J/ψ→γK_{S}^{0}K_{S}^{0}η^{'}

Based on (10087±44)×10^{6}  J/ψ events collected with the BESIII detector, a partial wave analysis of the decay J/ψ→γK_{S}^{0}K_{S}^{0}η^{'} is performed. The mass and width of the X(2370) are measured to be 2395±11(stat)_{-94}^{+26}(syst)  MeV/c^{2} and 188_{-17}^{+18}(stat)_{-33}^{+124}(syst)  MeV, respectively. The corresponding product branching fraction is B[J/ψ→γX(2370)]×B[X(2370)→f_{0}(980)η^{'}]×B[f_{0}(980)→K_{S}^{0}K_{S}^{0}]=(1.31±0.22(stat)_{-0.84}^{+2.85}(syst))×10^{-5}. The statistical significance of the X(2370) is greater than 11.7σ and the spin parity is determined to be 0^{-+} for the first time. The measured mass and spin parity of the X(2370) are consistent with the predictions of the lightest pseudoscalar glueball.

Crosstalk between Exercise and Immunotherapy: Current Understanding and Future Directions

Accumulated evidence highlights that exercise can modulate multiple cytokines, influencing transcriptional pathways, and reprogramming certain metabolic processes, ultimately promoting antitumor immunity and enhancing the efficacy of immune checkpoint inhibitors in cancer patients. Exploring the mechanisms behind this will, for one thing, help us uncover key factors and pathways in exercise-assisted cancer immunotherapy, offering more possibilities for future treatment methods. For another, it will support the development of more personalized and effective exercise prescriptions, thereby improving the prognosis of cancer patients.

Transcriptomic analysis reveals the inhibitory effect of beta-sitosterol on proliferation of bovine preadipocytes

Fat deposition affects beef quantity and quality via preadipocyte proliferation. Beta-sitosterol, a natural small molecular compound, has various functions, such as anti-inflammation, antibacterial, and anticancer properties. The mechanism of action of Beta-sitosterol on bovine preadipocytes remains unclear. This study, based on RNA-seq, reveals the impact of Beta -sitosterol on the proliferation of bovine preadipocytes. Compared to the control group, Beta-sitosterol demonstrated a more pronounced inhibitory effect on cell proliferation after 48 hours of treatment than after 24 hours, as evidenced by the results of EdU staining and flow cytometry. RNA-seq and Western Blot analyses further substantiated these findings. Our results suggest that the impact of Beta-sitosterol on the proliferation of bovine preadipocytes is not significant after a 24-hour treatment. It is only after extending the treatment time to 48 hours that Beta-sitosterol may induce cell cycle arrest at the G2/M phase by suppressing the expression of CCNB1, thereby inhibiting the proliferation of bovine preadipocytes.

Construction of a three-dimensional inflammation model of human bronchial epithelial cells BEAS-2B by using the self-assembling D-form peptide Sciobio-Ⅲ

Human bronchial epithelial cells in the airway system, as the primary barrier between humans and the surrounding environment, assume a crucial function in orchestrating the processes of airway inflammation. Target to develop a new three-dimensional (3D) inflammatory model to airway system, and here we report a strategy by using self-assembling D-form peptide to cover the process. By testing physicochemical properties and biocompatibility of Sciobio-Ⅲ, we confirmed that it can rapidly self-assembles under the trigger of ions to form a 3D nanonetwork-like scaffold, which supports 3D cell culture including the cell strains like BEAS-2B cells. Subsequently, inflammation model was established by lipopolysaccharide (LPS), the expression of some markers of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), and interleukin-8 (IL-8), the levels of relevant inflammatory factors were measured by RT-qPCR and the secretion profile of inflammatory cytokines by ELISA, are obtained the quite difference effects in 2D and 3D microenvironment, which suggested Sciobio-Ⅲ hydrogel is an ideal scaffold that create the microenvironment for 3D cell culture. Here we are success to establish a 3D inflammation model for airway system. This innovative model allows for rapid and accurate evaluation of drug metabolism and toxicological side effects, hope to use in drug screening for airway inflammatory diseases and beyond.

Microbiome and lung cancer: carcinogenic mechanisms, early cancer diagnosis, and promising microbial therapies

Microbiomes in the lung, gut, and oral cavity are correlated with lung cancer initiation and progression. While correlations have been preliminarily established in earlier studies, delving into microbe-mediated carcinogenic mechanisms will extend our understanding from correlation to causation. Building upon the causative relationships between microbiome and lung cancer, a novel concept of microbial biomarkers has emerged, mainly encompassing cancer-specific bacteria and circulating microbiome DNA. They might function as noninvasive liquid biopsy techniques for lung cancer early detection. Furthermore, potential microbial therapies have displayed initial efficacy in lung cancer treatment, providing multiple avenues for therapeutic intervention. Herein, we will discuss the molecular mechanisms and signaling pathways through which microbes influence lung cancer initiation and development. Additionally, we will summarize recent findings on microbial biomarkers as a member of tumor liquid biopsy techniques and provide an overview of the latest advances in various microbe-assisted/mediated therapeutic approaches for lung cancer.

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

Key Words Collapse

MESH Headings Collapse

Grants Collapse

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

Collapse

Engineering Self-Assembling Peptide Hydrogel to Enhance the Capacity of Dendritic Cells to Activate In Vivo T-Cell Immunity

The efficacy of the dendritic cell (DC) has failed to meet expectations thus far, and crucial problems such as the immature state of DCs, low targeting efficiency, insufficient number of dendritic cells, and microenvironment are still the current focus. To address these problems, we developed two self-assembling peptides, RLDI and RQDT, that mimic extracellular matrix (ECM). These peptides can be self-assembled into highly ordered three-dimensional nanofiber scaffold structures, where RLDI can form gelation immediately. In addition, we found that RLDI and RQDT enhance the biological function of DCs, including releasing antigens sustainably, adhering to DCs, promoting the maturation of DCs, and increasing the ability of DC antigen presentation. Moreover, peptide hydrogel-based DC treatment significantly achieved prophylactic and treatment effects on colon cancer. These results have certain implications for the design of new broad-spectrum vaccines in the future.

Rapid in situ mutation detection in extracellular vesicle-DNA

A PCR- and sequencing-free mutation detection assay facilitates cancer diagnosis and reduces over-reliance on specialized equipment. This benefit was highlighted during the pandemic when high demand for viral nucleic acid testing often sidelined mutation analysis. This shift led to substantial challenges for patients on targeted therapy in tracking mutations. Here, we report a 30-minute DNA mutation detection technique using Cas12a-loaded liposomes in a microplate reader, a fundamental laboratory tool. CRISPR-Cas12a complex and fluorescence-quenching (FQ) probes are introduced into tumor-derived extracellular vesicles (EV) through membrane fusion. When CRISPR-RNA hybridizes with the DNA target, activated Cas12a can trans-cleave FQ probes, resulting in fluorescence signals for the quantification of DNA mutation. Future advancements in multiplex and high-throughput mutation detection using this assay will streamline self-diagnosis and treatment monitoring at home.

Preparation, Structural Identification, and Screening of Egg-Derived Peptides with Facilitating Alcohol Metabolism Activity

The aim of this study was to obtain egg-derived peptides with facilitating alcohol metabolism (EPs) by enzymolysis, to identify their structures, and screen small polypeptides with higher activity by molecular docking. The optimum conditions for preparing EPs with facilitating alcohol metabolism were obtained by a single factor experiment, adding 2% Protamex and performing enzymolysis for 3 h with a liquid-material ratio of 35:1. The dose-response relationship experiment showed that 800 mg/kg·bw EPs played a better role in facilitating alcohol metabolism. EPs contained 40% hydrophobic amino acids (HAA), including 9.24% Leu. Eighty-four peptides were identified by HPLC-MS/MS and four peptides with potential activation of alcohol dehydrogenase were further selected by molecular docking. The tetrapeptide Trp-Ile-Val-Asp (WIVD) with the highest binding energy reached -7.16 kcal/mol. These findings suggest that egg is a good source for the preparation of peptides with facilitating alcohol metabolism activity.

Chimeric nanobody-decorated liposomes by self-assembly

Liposomes as drug vehicles have advantages, such as payload protection, tunable carrying capacity and improved biodistribution. However, due to the dysfunction of targeting moieties and payload loss during preparation, immunoliposomes have yet to be favoured in commercial manufacturing. Here we report a chemical modification-free biophysical approach for producing immunoliposomes in one step through the self-assembly of a chimeric nanobody (cNB) into liposome bilayers. cNB consists of a nanobody against human epidermal growth factor receptor 2 (HER2), a flexible peptide linker and a hydrophobic single transmembrane domain. We determined that 64% of therapeutic compounds can be encapsulated into 100-nm liposomes, and up to 2,500 cNBs can be anchored on liposomal membranes without steric hindrance under facile conditions. Subsequently, we demonstrate that drug-loaded immunoliposomes increase cytotoxicity on HER2-overexpressing cancer cell lines by 10- to 20-fold, inhibit the growth of xenograft tumours by 3.4-fold and improve survival by more than twofold.

Selenium- and/or Zinc-Enriched Egg Diet Improves Oxidative Damage and Regulates Gut Microbiota in D-Gal-Induced Aging Mice

Eggs, with their high nutritional value, are great carriers for enriching nutrients. In this study, selenium- and/or zinc-enriched eggs (SZE) were obtained and their effects on ameliorating oxidative stress injury, alleviating cognitive impairment, and maintaining intestinal flora balance in a D-gal-induced aging mice model were investigated. As determined by the Y-maze test, SZE restored the learning and memory abilities and increased the Ach level and AChE activity of aging mice (p < 0.05). Meanwhile, supplementation of low-dose SZE increased antioxidant levels and decreased inflammation levels (p < 0.05). High-dose SZE increased anti-inflammatory levels but were less effective than low dose. Additionally, SZE maintained the intestinal flora balance and significantly increased the ratio of Firmicutes and Bacteroidota. Blautia, as a probiotic, was negatively correlated with pro-inflammatory factors and positively correlated with antioxidant levels (p < 0.05). These results suggest that SZE might improve organ damage and cognitive function by attenuating oxidative stress and inflammatory response and maintaining healthy gut flora.

MYC expression and fatty acid oxidation in EGFR-TKI acquired resistance

This report expands on our previous research, highlighting a unique inverse correlation between MYC expression in tumor cells and immune cells during the development of EGFR-TKI resistance. It is observed that MYC expression and fatty acid oxidation (FAO) metabolism in tissue-resident memory (TRM) CD8 + T cells are significantly impaired. These findings offer new insights into the mechanisms of TKI resistance. Although the study is preliminary, it suggests caution when interpreting the effectiveness of MYC inhibitors in reversing TKI resistance, especially when immune factors are not considered.

Giant magnetocaloric effect in spin supersolid candidate Na2BaCo(PO4)2

Supersolid, an exotic quantum state of matter that consists of particles forming an incompressible solid structure while simultaneously showing superfluidity of zero viscosity1, is one of the long-standing pursuits in fundamental research2,3. Although the initial report of 4He supersolid turned out to be an artefact4, this intriguing quantum matter has inspired enthusiastic investigations into ultracold quantum gases5-8. Nevertheless, the realization of supersolidity in condensed matter remains elusive. Here we find evidence for a quantum magnetic analogue of supersolid-the spin supersolid-in the recently synthesized triangular-lattice antiferromagnet Na2BaCo(PO4)2 (ref. 9). Notably, a giant magnetocaloric effect related to the spin supersolidity is observed in the demagnetization cooling process, manifesting itself as two prominent valley-like regimes, with the lowest temperature attaining below 100 mK. Not only is there an experimentally determined series of critical fields but the demagnetization cooling profile also shows excellent agreement with the theoretical simulations with an easy-axis Heisenberg model. Neutron diffractions also successfully locate the proposed spin supersolid phases by revealing the coexistence of three-sublattice spin solid order and interlayer incommensurability indicative of the spin superfluidity. Thus, our results reveal a strong entropic effect of the spin supersolid phase in a frustrated quantum magnet and open up a viable and promising avenue for applications in sub-kelvin refrigeration, especially in the context of persistent concerns about helium shortages10,11.

The Antitumor Impact of Combining Hepatic Artery Ligation With Copper Chelators for Liver Cancer

Background

Hepatocellular carcinoma (HCC) is one of the main cancer-related mortality worldwide. Thus, there is a constant search for improvement in treatment strategies to enhance the prognosis of this malignancy. The study aims to investigate the combined antitumor activity of ammonium tetrathiomolybdate (TM, copper chelator) combined with hepatic artery ligation (HAL) for liver cancer.

Methods

A total of 40 Sprague-Dawley (SD) rats bearing hepatic tumors were randomly divided into four groups: the control group without any treatment (control), HAL only (HAL), given TM by gavage (TM), and given TM combined with HAL (HAL + TM). The concentrations of serum copper were measured at the predetermined time points. Tumor growth rate, overall survival (OS), expression of hypoxia-inducible factor-1α (HIF-1α), vascular endothelial growth factor (VEGF), and microvessel density (MVD), as determined by immunohistochemical examination, were compared.

Results

HAL treatment transiently could elevate alanine transaminase (ALT) and aspartate transaminase (AST) but resumed to baseline within 1 week. Serum copper was significantly increased in tumor-bearing animals over time. The values of serum copper in the three treatment groups were significantly lower than those in the control group at different time points, with the lowest values observed in the TM group (P < .05). The average tumor size was 30.33 ± 2.58, 20.83 ± 2.93, 16.80 ± 3.84, and 10.88 ± 1.08 mm in the control, HAL, TM, and HAL + TM groups, respectively (HAL + TM vs other groups, all P < .05). In addition, the expression levels of HIF-1α, VEGF, and MVD were significantly lower in the HAL + TM group than those in the other groups (P < .05). The OS of rats in the combined groups was significantly prolonged combined to the other groups (P < .05), with survival time of 19.1 ± 0.64, 25.4 ± 1.24, 25.3 ± 1.78, and 29.9 ± 2.22 days in the control, HAL, TM, and HAL + TM groups, respectively.

Conclusion

These findings suggest that combined treatment with TM and HAL holds great potential for liver cancer treatment by reducing tumor hypoxia and angiogenesis. The observed results indicate that these combinations may offer a novel target and strategy for interventional therapy of liver cancer.

Untangling the web of intratumor microbiota in lung cancer

Microbes are pivotal in contemporary cancer research, influencing various biological behaviors in cancer. The previous notion that the lung was sterile has been destabilized by the discovery of microbiota in the lower airway and lung, even within tumor tissues. Advances of biotechnology enable the association between intratumor microbiota and lung cancer to be revealed. Nonetheless, the origin and tumorigenicity of intratumor microbiota in lung cancer still remain implicit. Additionally, accumulating evidence indicates that intratumor microbiota might serve as an emerging biomarker for cancer diagnosis, prognosis, and even a therapeutic target across multiple cancer types, including lung cancer. However, research on intratumor microbiota's role in lung cancer is still nascent and warrants more profound exploration. Herein, this paper provides an extensive review of recent advancements in the following fields, including 1) established and emerging biotechnologies utilized to study intratumor microbiota in lung cancer, 2) causation between intratumor microbiota and lung cancer from the perspectives of translocation, cancerogenesis and metastasis, 3) potential application of intratumor microbiota as a novel biomarker for lung cancer diagnosis and prognosis, and 4) promising lung cancer therapies via regulating intratumor microbiota. Moreover, this review addresses the limitations, challenges, and future prospects of studies focused on intratumor microbiota in lung cancer.

Q-TWiST analysis of survival benefits with brigatinib versus crizotinib in patients with anaplastic lymphoma kinase-positive non-small cell lung cancer based on results of the ALTA-1L trial

OBJECTIVES

The ALTA-1L phase 3 open-label trial demonstrated increased progression-free survival (PFS) with brigatinib versus crizotinib in patients with anaplastic lymphoma kinase-positive (ALK-positive) locally advanced or metastatic non-small cell lung cancer (NSCLC) previously untreated with ALK-targeted therapy. This post-hoc analysis of data from the ALTA-1L trial used the quality-adjusted (QA) time without symptoms of disease or toxicity (Q-TWiST) methodology to compare the QA survival benefit of brigatinib versus crizotinib in this patient population.

PATIENTS AND METHODS

The Q-TWiST analysis was performed using final (January 29, 2021) individual patient-level blinded independent review committee (BIRC)- and investigator-assessed survival data for brigatinib (n = 137) and crizotinib (n = 138) in adult patients (N = 275) with ALK-positive locally advanced or metastatic NSCLC previously untreated with ALK-targeted therapy. Q-TWiST was compared between the two treatments. Subgroup analyses were performed in patients stratified by various clinicopathological characteristics, including presence or absence of brain metastases at baseline.

RESULTS

Brigatinib was associated with significantly longer time without symptoms of disease or toxicity (P < 0.001) than crizotinib, with significantly greater Q-TWiST (mean [SE] months: BIRC-assessed, 28.2 [1.2] versus 25.1 [1.1], P = 0.045; investigator-assessed, 28.5 [1.2] versus 24.8 [1.1], P = 0.018). Relative gains in Q-TWiST with brigatinib compared to crizotinib were clinically meaningful (BIRC-assessed, 10.4%; investigator-assessed, 12.3%). Patients with brain metastases at baseline receiving brigatinib had significantly greater Q-TWiST (mean [SE] months: BIRC-assessed, 29.0 [1.9] versus 19.0 [1.9], P = 0.0001) than those receiving crizotinib.

CONCLUSION

First-line brigatinib treatment was associated with significant and clinically meaningful gains in Q-TWiST compared to crizotinib in patients with ALK-positive locally advanced or metastatic NSCLC, supporting the results of the ALTA-1L trial and brigatinib as a safe and effective first-line treatment for ALK-positive NSCLC.

Analysis of the Influencing Factors of Delirium after PCI for Acute Myocardial Infarction and its Impact on the Quality of Life of Patients

Objective

Delirium is a common and serious issue in patients recovering from percutaneous coronary intervention (PCI). It can lead to longer hospital stays, increased mortality, and decreased quality of life. This study aims to investigate different nursing interventions to improve care for post-PCI patients by reducing the incidence and duration of delirium.

Methods

Between December 2021 and April 2023, we enrolled patients who underwent PCI surgery for acute myocardial infarction at our hospital as study participants. Utilizing a clinical randomized controlled trial design, we allocated these patients randomly into either the intervention group or the control group. The control group received conventional nursing care, while the intervention group received routine nursing care augmented by family visit nursing care, encompassing emotional support, education, and enhanced communication with family members. Upon the completion of all intervention measures, we assessed the incidence of delirium in post-PCI patients using the Richmond Agitation Sedation Scale (RASS) and the ICU Ambiguity Assessment Method for the Intensive Care Unit (CAM-ICU). Furthermore, we evaluated the patients' quality of life using the US Medical Bureau's Quality of Life Health Survey (SF-36).

Result

Significant differences were observed in Richmond Agitation Sedation Scale (RASS) scores at 24 and 48 hours post-PCI, favoring the intervention group (P < .05). The intervention group also exhibited a lower incidence of delirium at 24 hours (P < .05) and a significantly shorter delirium duration (P < .05). While baseline quality of life scores did not differ significantly between the groups, post-intervention, the intervention group demonstrated significantly higher quality of life scores. These results underscore the positive impact of combined nursing interventions on sedation levels, delirium incidence and duration, and overall quality of life for post-PCI patients.

Conclusion

The combined approach of routine nursing care and home visit interventions significantly reduced delirium incidence and duration in post-PCI patients. This personalized care strategy emphasizes patient well-being and is indicative of a broader shift towards individualized healthcare. It highlights the potential for enhanced patient outcomes and improved quality of life in the context of post-PCI patient management.

[Observation on the efficacy of different targets low-frequency repetitive transcranial magnetic stimulation for the treatment of tremor-dominant subtypes of Parkinson's disease]

Objective: To analyze the efficacy of different targets low-frequency repetitive transcranial magnetic stimulation (rTMS) for the treatment of tremor Parkinson's disease(PD). Method: A total of 82 patients with primary PD who were admitted to the Department of Neurology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from April 1, 2020 to March 31, 2021 were prospectively collected. According to the clinical characteristics of major movement disorders, 82 patients with tremor type (TD) were selected to enroll.The patients were randomly divided into 3 groups at a 1∶1∶1 ratio according to the randomized coding sequence of the trial: the primary motor cortex (M1) group with 26 cases, the cerebellum group with 26 cases and the dual-site (M1, cerebellum) group with 30 cases. All patients were treated with 1 Hz low-frequency stimulation of the corresponding target once a day for 5 days a week for 2 weeks, a total of 10 times; The dosage remained unchanged during the treatment for all groups. Before and after 2 weeks' treatment, the patients were assessed with the Unified PD Rating Scale (UPDRS) and PD Quality of Life Questionnaire-39 (PDQ-39) without medication. Cortical excitability, namely transcranial magnetic stimulation motor evoked potential (TMS-MEP), [including resting motor threshold (rMT) and active motor threshold (aMT) examinations], timed up and go (TUG) and electromyographic tremor were conducted. Result: There were 82 patients, 39 males and 43 females, with an average age of (67±8) years. Before the treatment, there was no statistically significant difference in the evaluation indicators among the three groups (all P>0.05). After the treatment, the differences of the UPDRS-Ⅲ score [(38.9±2.5) vs (29.2±3.6) ], UPDRS tremor score [(23.7±2.1) vs (14.6±3.1) ], TUG time [(44.8±3.1) s vs (33.7±4.1) s], tremor amplitude [(480±126) μV vs (276±94) μV], PDQ-39 score [(51±13) vs (45±13) ], rMT [(36±17)% vs (43±13)%], and aMT [(26±16)% vs (31±12)%] were statistically significant (all P<0.01) from those before the treatment. There was no statistical difference in the above factors between the M1 group and cerebellum group (all P>0.05). There was no statistically significant difference in tremor peak frequency among the three groups before and after the treatment (all P>0.05). Conclusions: Dual-site low-frequency rTMS can improve PD tremor, while M1 or cerebellar low-frequency rTMS does not significantly improve PD tremor. Its mechanism may be to improve PD tremor symptoms by regulating cortical excitability.

Detection, survival, and persistence of Staphylococcus capitis NRCS-A in neonatal units in England

BACKGROUND

The multidrug-resistant Staphylococcus capitis clone, NRCS-A, is increasingly associated with late-onset sepsis in low birthweight newborns in neonatal intensive care units (NICUs) in England and globally. Understanding where this bacterium survives and persists within the NICU environment is key to developing and implementing effective control measures.

AIM

To investigate the potential for S. capitis to colonize surfaces within NICUs.

METHODS

Surface swabs were collected from four NICUs with and without known NRCS-A colonizations/infections present at the time of sampling. Samples were cultured and S. capitis isolates analysed via whole-genome sequencing. Survival of NRCS-A on plastic surfaces was assessed over time and compared to that of non-NRCS-A isolates. The bactericidal activity of commonly used chemical disinfectants against S. capitis was assessed.

FINDINGS

Of 173 surfaces sampled, 40 (21.1%) harboured S. capitis with 30 isolates (75%) being NRCS-A. Whereas S. capitis was recovered from surfaces across the NICU, the NRCS-A clone was rarely recovered from outside the immediate neonatal bedspace. Incubators and other bedside equipment were contaminated with NRCS-A regardless of clinical case detection. In the absence of cleaning, S. capitis was able to survive for three days with minimal losses in viability (<0.5 log10 reduction). Sodium troclosene and a QAC-based detergent/disinfectant reduced S. capitis to below detectable levels.

CONCLUSION

S. capitis NRCS-A can be readily recovered from the NICU environment, even in units with no recent reported clinical cases of S. capitis infection, highlighting a need for appropriate national guidance on cleaning within the neonatal care environment.

Byproducts of Sesame Oil Extraction: Composition, Function, and Comprehensive Utilization

Sesame is principally used to generate oil, which is produced by chemical refining or pressing. Sesame meal, as a main byproduct of sesame oil extraction, is usually discarded, causing resource waste and economic loss. Sesame meal is rich in sesame protein and three types of sesame lignans (sesamin, sesamolin, and sesamol). Sesame protein extracted via a physical method and an enzymic method has balanced amino acid composition and is an important protein source, and thus it is often added to animal feed and used as a human dietary supplement. Extracted sesame lignan exhibits multiple biological activities such as antihypertensive, anticancer, and cholesterol-lowering activities, and therefore it is used to improve the oxidative stability of oils. This review summarizes the extraction methods, functional activities, and comprehensive utilization of four active substances (sesame protein, sesamin, sesamolin, and sesamol) in sesame meal with the aim to provide theoretical guidance for the maximum utilization of sesame meal.

Bioinspired engineering of fusogen and targeting moiety equipped nanovesicles

Cell-derived small extracellular vesicles have been exploited as potent drug vehicles. However, significant challenges hamper their clinical translation, including inefficient cytosolic delivery, poor target-specificity, low yield, and inconsistency in production. Here, we report a bioinspired material, engineered fusogen and targeting moiety co-functionalized cell-derived nanovesicle (CNV) called eFT-CNV, as a drug vehicle. We show that universal eFT-CNVs can be produced by extrusion of genetically modified donor cells with high yield and consistency. We demonstrate that bioinspired eFT-CNVs can efficiently and selectively bind to targets and trigger membrane fusion, fulfilling endo-lysosomal escape and cytosolic drug delivery. We find that, compared to counterparts, eFT-CNVs significantly improve the treatment efficacy of drugs acting on cytosolic targets. We believe that our bioinspired eFT-CNVs will be promising and powerful tools for nanomedicine and precision medicine.

Establishment and validation of nomograms for predicting survival of lung invasive adenocarcinoma based on the level of pathological differentiation: a SEER cohort-based analysis

Background

The pathological differentiation of invasive adenocarcinoma (IAC) has been linked closely with epidemiological characteristics and clinical prognosis. However, the current models cannot accurately predict IAC outcomes and the role of pathological differentiation is confused. This study aimed to establish differentiation-specific nomograms to explore the effect of IAC pathological differentiation on overall survival (OS) and cancer-specific survival (CSS).

Methods

The data of eligible IAC patients between 1975 and 2019 were collected from the Surveillance, Epidemiology, and End Results (SEER) database, and randomly divided in a ratio of 7:3 into a training cohort and a validation cohort. The associations between pathological differentiation and other clinical characteristics were evaluated using chi-squared test. The OS and CSS analyses were performed using the Kaplan-Meier estimator, and the log-rank test was used for nonparametric group comparisons. Multivariate survival analysis was performed using a Cox proportional hazards regression model. The discrimination, calibration, and clinical performance of nomograms were assessed by area under receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA).

Results

A total of 4,418 IAC patients (1,001 high-differentiation, 1,866 moderate-differentiation, and 1,551 low-differentiation) were identified. Seven risk factors [age, sex, race, tumor-node-metastasis (TNM) stage, tumor size, marital status, and surgery] were screened to construct differentiation-specific nomograms. Subgroup analyses showed that disparate pathological differentiation played distinct roles in prognosis, especially in patients with older age, white race, and higher TNM stage. The AUC of nomograms for OS and CSS in the training cohort were 0.817 and 0.835, while in the validation cohort were 0.784 and 0.813. The calibration curves showed good conformity between the prediction of the nomograms and the actual observations. DCA results indicated that these nomogram models could be used as a supplement to the prediction of the TNM stage.

Conclusions

Pathological differentiation should be considered as an independent risk factor for OS and CSS of IAC. Differentiation-specific nomogram models with good discrimination and calibration capacity were developed in the study to predict the OS and CSS in 1-, 3- and 5-year, which could be used predict prognosis and select appropriate treatment options.

[Analysis of 7 cases of pediatric acute myeloid leukemia with DEK-NUP214 fusion gene]

Objective: To investigate the clinical features, treatment regime, and outcome of pediatric acute myeloid leukemia (AML) with DEK-NUP214 fusion gene. Methods: The clinical data, genetic and molecular results, treatment process and survival status of 7 cases of DEK-NUP214 fusion gene positive AML children admitted to the Pediatric Blood Diseases Center of Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences from May 2015 to February 2022 were analyzed retrospectively. Results: DEK-NUP214 fusion gene positive AML accounted for 1.02% (7/683) of pediatric AML diagnosed in the same period, with 4 males and 3 females. The age of disease onset was 8.2 (7.5, 9.5) years. The blast percentage in bone marrow was 0.275 (0.225, 0.480), and 6 cases were M5 by FAB classification. Pathological hematopoiesis was observed in all cases except for one whose bone marrow morphology was unknown. Three cases carried FLT3-ITD mutations, 4 cases carried NRAS mutations, and 2 cases carried KRAS mutations. After diagnosis, 4 cases received IAE induction regimen (idarubicin, cytarabine and etoposide), 1 case received MAE induction regimen (mitoxantrone, cytarabine and etoposide), 1 case received DAH induction regimen (daunorubicin, cytarabine and homoharringtonine) and 1 case received DAE induction regimen (daunorubicin, cytarabine and etoposide). Complete remission was achieved in 3 cases after one course of induction. Four cases who did not achieved complete remission received CAG (aclarubicin, cytarabine and granulocyte colony-stimulating factor), IAH (idarubicin, cytarabine and homoharringtonine), CAG combined with cladribine, and HAG (homoharringtonine, cytarabine and granulocyte colony-stimulating factor) combined with cladribine reinduction therapy, respectively, all 4 cases reached complete remission. Six patients received hematopoietic stem cell transplantation (HSCT) after 1-2 sessions of intensive consolidation treatment, except that one case was lost to follow-up after complete remission. The time from diagnosis to HSCT was 143 (121, 174) days. Before HSCT, one case was positive for flow cytometry minimal residual disease and 3 cases were positive for DEK-NUP214 fusion gene. Three cases accepted haploid donors, 2 cases accepted unrelated cord blood donors, and 1 case accepted matched sibling donor. The follow-up time was 20.4 (12.9, 53.1) months, the overall survival and event free survival rates were all 100%. Conclusions: Pediatric AML with DEK-NUP214 fusion gene is a unique and rare subtype, often diagnosed in relatively older children. The disease is characterized with a low blast percentage in bone marrow, significant pathological hematopoiesis and a high mutation rate in FLT3-ITD and RAS genes. Low remission rate by chemotherapy only and very high recurrence rate indicate its high malignancy and poor prognosis. Early HSCT after the first complete remission can improve its prognosis.

Capsaicin: A Novel Approach to the Treatment of Functional Dyspepsia

Capsaicin, the principal spicy component of red pepper, shows numerous bioactivities these years. Based on the results of past studies, capsaicin may have potential effects on the treatment of functional dyspepsia (FD). However, most studies mainly investigate functional dyspepsia-treatment effects of capsaicin by discussing the relationship between capsaicin and transient receptor potential vanilloid type 1 (TRPV1). In fact, capsaicin may relieve the symptoms of FD in various ways. These effects involve desensitizing C nociceptive fibers, regulating kinds of neurotransmitters, counteracting viruses and inflammation, balancing the gut microbiota, inhibiting the secretion of gastric acid, and reducing oxidative stress damage. A full understanding of these mechanisms will help further development and utilization of capsaicin in food and medical fields.

Low-threshold random lasers based on the DCM-DEG gain system with graphene nanosheets

In this article, low-threshold random lasers based on DCM-DEG (DD) gain system with graphene nanosheets are studied. The experiment results show that the threshold of random lasers reduces rapidly when an appropriate amount of graphene nanosheets is added in DD solution. Meanwhile, the quantity and quality of random lasing modes raise significantly. We discussed the potential reasons why the graphene nanosheets can strengthen the sample's random lasing. And, the influence of the graphene nanosheet concentration on the radiation characteristics of random lasers is further studied. When the concentration of graphene nanosheets is 0.088wt%, the lasing threshold of DD samples with graphene nanosheets (GDD) is only about 31.8% of the lasing threshold of DD samples, and the quality of random lasing modes is five times higher than that of the DD sample. To further reduce the lasing threshold, the gold (Au) nanoparticles are added in the mixed solution to form the GDD solution with Au nanoparticles (GGDD). The results show that the lasing threshold of the GGDD sample is about 7.73 µJ/pulse, which is 5.2% of the lasing threshold of the DD sample. This experiment provides a new method to study low-threshold and high-quality random lasers based on graphene.

N6-methyladenosine regulators are potential prognostic biomarkers for multiple myeloma

N6-methyladenosine (m6A) regulators play an important role in tumorigenesis; however, their role in multiple myeloma (MM) remains unknown. This study aimed to create an m6A RNA regulators prognostic signature for MM patients. We integrated data from the Multiple Myeloma Research Foundation CoMMpass Study and the Genotype-Tissue Expression database to analyze gene expression profiles of 21 m6A regulators. Consistent clustering analysis was used to identify the clusters of patients with MM having different clinical outcomes. Gene distribution was analyzed using principal component analysis. Next, we generated an mRNA gene signature of m6A regulators using a multivariate logistic regression model with least absolute shrinkage and selection operator. The expressions of m6A regulators, except FMR1, were significantly different in MM samples compared with those in normal samples. The KIAA1429, HNRNPC, FTO, and WTAP expression levels were dramatically downregulated in tumor samples, whereas those of other signatures were remarkably upregulated. Three clusters of patients with MM were identified, and significant differences were found in terms of overall survival (p = .024). A prognostic two-gene signature (KIAA1429 and HNRNPA2B1) was constructed, which had a good prognostic significance using the ROC method (AUC = 0.792). Moreover, the risk score correlated with the infiltration immune cells. In addition, KEGG pathway analysis showed that 16 pathways were dramatically enriched. The m6A signature might be a novel biomarker for predicting the prognosis of patients with MM (p = .002). Our study is the first to explore the potential application value of m6A in MM. These findings may enhance the understanding of the functional organization of m6A in MM and provide new insights into the treatment of MM patients.

Hierarchical Aggregation for Numerical Data under Local Differential Privacy

The proposal of local differential privacy solves the problem that the data collector must be trusted in centralized differential privacy models. The statistical analysis of numerical data under local differential privacy has been widely studied by many scholars. However, in real-world scenarios, numerical data from the same category but in different ranges frequently require different levels of privacy protection. We propose a hierarchical aggregation framework for numerical data under local differential privacy. In this framework, the privacy data in different ranges are assigned different privacy levels and then disturbed hierarchically and locally. After receiving users' data, the aggregator perturbs the privacy data again to convert the low-level data into high-level data to increase the privacy data at each privacy level so as to improve the accuracy of the statistical analysis. Through theoretical analysis, it was proved that this framework meets the requirements of local differential privacy and that its final mean estimation result is unbiased. The proposed framework is combined with mini-batch stochastic gradient descent to complete the linear regression task. Sufficient experiments both on synthetic datasets and real datasets show that the framework has a higher accuracy than the existing methods in both mean estimation and mini-batch stochastic gradient descent experiments.

The role of lipid metabolic reprogramming in tumor microenvironment

Metabolic reprogramming is one of the most important hallmarks of malignant tumors. Specifically, lipid metabolic reprogramming has marked impacts on cancer progression and therapeutic response by remodeling the tumor microenvironment (TME). In the past few decades, immunotherapy has revolutionized the treatment landscape for advanced cancers. Lipid metabolic reprogramming plays pivotal role in regulating the immune microenvironment and response to cancer immunotherapy. Here, we systematically reviewed the characteristics, mechanism, and role of lipid metabolic reprogramming in tumor and immune cells in the TME, appraised the effects of various cell death modes (specifically ferroptosis) on lipid metabolism, and summarized the antitumor therapies targeting lipid metabolism. Overall, lipid metabolic reprogramming has profound effects on cancer immunotherapy by regulating the immune microenvironment; therefore, targeting lipid metabolic reprogramming may lead to the development of innovative clinical applications including sensitizing immunotherapy.

Single-cell transcriptional profiling uncovers the association between EOMES+CD8+ T cells and acquired EGFR-TKI resistance

Acquired resistance to tyrosine kinase inhibitors (TKIs) is reportedly inevitable in lung cancers harboring epidermal growth factor receptor (EGFR) mutations, emphasizing the need for novel approaches to predict EGFR-TKI resistance for clinical monitoring and patient management. This study identified a significant increase in eomesodermin (EOMES)+CD8+ T cells in the TKI-resistant patients, which was correlated with poor survival. The increase in EOMES+CD8+ T cells was further confirmed in both tissue samples and peripheral blood of patients with TKIs resistance. The integrated analysis of pseudotime and Gene set variation showed that the increase in EOMES+CD8+ T cells may be attributed to TRM T cell conversion and metabolic reprogramming. Overall, this work suggested an association between the increased number of EOMES+CD8+ T cells and acquired TKI drug resistance, supporting the utility of EOMES+CD8+ T cells as a biomarker for TKI treatment response.

CT-guided percutaneous microwave ablation for pulmonary metastases from colorectal cancer: Prognosis analyses based on the origin of the primary tumor

BACKGROUND

Microwave ablation (MWA) is becoming an effective therapy for inoperable pulmonary metastases from colorectal cancer (CRC). However, it is unclear whether the primary tumor location affects survival after MWA.

OBJECTIVE

This study aims to investigate the survival outcomes and prognostic factors of MWA based on different primary origins between colon and rectal cancer.

METHODS

Patients who underwent MWA for pulmonary metastases from 2014 to 2021 were reviewed. Differences in survival outcomes between colon and rectal cancer were analyzed with the Kaplan-Meier method and log-rank tests. The prognostic factors between groups were then evaluated by univariable and multivariable Cox regression analyses.

RESULTS

A total of 118 patients with 154 pulmonary metastases from CRC were treated in 140 MWA sessions. Rectal cancer had a higher proportion with seventy (59.32% ) than colon cancer with forty-eight (40.68% ). The average maximum diameter of pulmonary metastases from rectal cancer (1.09 cm) was greater than that of colon cancer (0.89 cm; p = 0.026). The median follow-up was 18.53 months (range 1.10 - 60.63 months). The disease-free survival (DFS) and overall survival (OS) in colon and rectal cancer groups were 25.97 vs 11.90 months (p = 0.405), and 60.63 vs 53.87 months (p = 0.149), respectively. Multivariate analyses showed that only age was an independent prognostic factor in patients with rectal cancer (HR = 3.70, 95% CI: 1.28 - 10.72, p = 0.023), while none in colon cancer.

CONCLUSIONS

Primary CRC location has no impact on survival for patients with pulmonary metastases after MWA, while a disparate prognostic factor exists between colon and rectal cancer.

Short- and long-term outcomes of laparoscopic versus open pelvic exenteration for locally advanced rectal cancer: a single-center propensity score matching analysis

BACKGROUND

Research on short-term outcomes and long-term oncological results of laparoscopic pelvic exenteration (LPE) for locally advanced rectal cancer (LARC) is still limited. The purpose of this study was to compare the outcomes of LPE and open pelvic exenteration (OPE).

METHODS

Between January 2010 and December 2019, consecutive LARC patients who underwent radical pelvic exenteration at Peking University First Hospital were enrolled. Groups were matched at a 1:1 ratio using propensity score matching. The primary endpoints were 3 year overall survival (OS) and disease-free survival (DFS). The secondary endpoints were postoperative short-term outcomes.

RESULTS

There were 144 patients (68 males and 76 females, median age 58.5 [range 27.0-86.0] years). After matching, patients were stratified into LPE (n = 48) and OPE (n = 48) groups (LPE: 24 males and 24 females, median age 57.0 [range 27.0-81.0] years; OPE: 26 males and 22 females, median age 58.0[range 36.0-80.0] years). There were no significant differences on baseline data between the two groups. Compared with the OPE group, the LPE group had a significantly lower estimated blood loss (200 vs 500 ml, p = 0.003), less overall postoperative complications (12/48 vs 25/48, p = 0.006), less surgical site infection (8/48 vs 20/48, p = 0.007), shorter length of stay (12 vs. 15 days, p = 0.005), but similar operative time (344 vs. 360 min, p = 0.493). The pathological R0 resection rate (98.0% vs. 93.7%, p = 0.610), 3 year local recurrence (18.4% vs. 23.5, p = 0.140), 3 year OS (74.6% vs. 65.5%, p = 0.290) and 3-year DFS (60.0% vs. 50.3%, p = 0.208) were similar between the two groups. Shorter distance from anal verge (HR = 0.92, p = 0.042), (y) pT4b (HR = 2.45, p = 0.023), (y)pN1-2 (HR = 2.42, p = 0.004) and positive CRM (HR = 6.23, p = 0.004) were independent prognostic risks for 3 year DFS.

CONCLUSIONS

LPE can be performed safely and has certain short-term advantages over OPE, most notably less blood loss and surgical site infection. However, LPE does not improve long-term oncological outcomes.

Developing mRNA signatures as a novel prognostic biomarker predicting high risk multiple myeloma

Background

Multiple myeloma (MM) remains an essentially incurable disease. This study aimed to establish a predictive model for estimating prognosis in newly diagnosed MM based on gene expression profiles.

Methods

RNA-seq data were downloaded from the Multiple Myeloma Research Foundation (MMRF) CoMMpass Study and the Genotype-Tissue Expression (GTEx) databases. Weighted gene coexpression network analysis (WGCNA) and protein-protein interaction network analysis were performed to identify hub genes. Enrichment analysis was also conducted. Patients were randomly split into training (70%) and validation (30%) datasets to build a prognostic scoring model based on the least absolute shrinkage and selection operator (LASSO). CIBERSORT was applied to estimate the proportion of 22 immune cells in the microenvironment. Drug sensitivity was analyzed using the OncoPredict algorithm.

Results

A total of 860 newly diagnosed MM samples and 444 normal counterparts were screened as the datasets. WGCNA was applied to analyze the RNA-seq data of 1589 intersecting genes between differentially expressed genes and prognostic genes. The blue module in the PPI networks was analyzed with Cytoscape, and 10 hub genes were identified using the MCODE plug-in. A three-gene (TTK, GINS1, and NCAPG) prognostic model was constructed. This risk model showed remarkable prognostic value. CIBERSORT assessment revealed the risk model to be correlated with activated memory CD4 T cells, M0 macrophages, M1 macrophages, eosinophils, activated dendritic cells, and activated mast cells. Furthermore, based on OncoPredict, high-risk MM patients were sensitive to eight drugs.

Conclusions

We identified and constructed a three-gene-based prognostic model, which may provide new and in-depth insights into the treatment of MM patients.

[Effects of mechanical tension on the formation of hypertrophic scars in rabbit ears and transforming growth factor-β1/Smad signaling pathway]

Objective: To explore the effects of mechanical tension on the formation of hypertrophic scars in rabbit ears and transforming growth factor-β1 (TGF-β1)/Smad signaling pathway. Methods: The experimental research method was adopted. Six New Zealand white rabbits, male or female, aged 3-5 months were used and 5 full-thickness skin defect wounds were made on the ventral surface of each rabbit ear. The appearance of all rabbit ear wounds was observed on post surgery day (PSD) 0 (immediately), 7, 14, 21, and 28. On PSD 28, the scar formation rate was calculated. Three mature scars in the left ear of each rabbit were included in tension group and the arch was continuously expanded with a spiral expander. Three mature scars in the right ear of each rabbit were included in sham tension group and only the spiral expander was sutured without expansion. There were 18 scars in each group. After mechanical tension treatment (hereinafter referred to as treatment) for 40 days, the color and texture of scar tissue in the two groups were observed. On treatment day 40, the scar elevation index (SEI) was observed and calculated; the histology was observed after hematoxylin eosin staining, and the collagen morphology was observed after Masson staining; mRNA expressions of TGF-β1, Smad3, collagen Ⅰ, collagen Ⅲ, and α-smooth muscle actin (α-SMA) in scar tissue were detected by real-time fluorescence quantitative reverse transcription polymerase chain reaction; and the protein expressions of TGF-β1, collagen Ⅰ, collagen Ⅲ, and α-SMA, and phosphorylation level of Smad3 in scar tissue were detected by Western blotting. The number of samples of each group in the experiments was 3. Data were statistically analyzed with independent sample t test. Results: On PSD 0, 5 fresh wounds were formed on all the rabbit ears; on PSD 7, the wounds were scabbed; on PSD 14, most of the wounds were epithelialized; on PSD 21, all the wounds were epithelialized; on PSD 28, obvious hypertrophic scars were formed. The scar formation rate was 75% (45/60) on PSD 28. On treatment day 40, the scar tissue of rabbit ears in tension group was more prominent than that in sham tension group, the scar tissue was harder and the color was more ruddy; the SEI of the scar tissue of rabbit ears in tension group (2.02±0.08) was significantly higher than 1.70±0.08 in sham tension group (t=5.07, P<0.01). On treatment day 40, compared with those in sham tension group, the stratum corneum of scar tissue became thicker, and a large number of new capillaries, inflammatory cells, and fibroblasts were observed in the dermis, and collagen was more disordered, with nodular or swirling distribution in the scar tissue of rabbit ears in tension group. On treatment day 40, the mRNA expressions of TGF-β1, Smad3, collagen Ⅰ, collagen Ⅲ, and α-SMA in the scar tissue of rabbit ears in tension group were respectively 1.81±0.25, 5.71±0.82, 7.86±0.56, 4.35±0.28, and 5.89±0.47, which were significantly higher than 1.00±0.08, 1.00±0.12, 1.00±0.13, 1.00±0.14, and 1.00±0.14 in sham tension group (with t values of 5.36, 9.82, 20.60, 18.26, and 17.13, respectively, all P<0.01); the protein expressions of TGF-β1, collagen Ⅰ, collagen Ⅲ, and α-SMA, and phosphorylation level of Smad3 in the scar tissue of rabbit ears in tension group were respectively 0.865±0.050, 0.895±0.042, 0.972±0.027, 1.012±0.057, and 0.968±0.087, which were significantly higher than 0.657±0.050, 0.271±0.029, 0.631±0.027, 0.418±0.023, and 0.511±0.035 in sham tension group (with t values of 5.08, 21.27, 15.55, 16.70, and 8.40, respectively, all P<0.01). Conclusions: Mechanical tension can inhibit the regression of hypertrophic scars in rabbit ears through stimulating the hyperplasia of scars, inhibiting the normal arrangement of dermal collagen fibers, and intensifying the deposition of collagen fibers, and the mechanism may be related to the activation of TGF-β1/Smad signaling pathway by mechanical tension.

A Self-Assembling Peptide as a Model for Detection of Colorectal Cancer

Patient-derived organoid (PDO) models have been widely used in precision medicine. The inability to standardize organoid creation in pre-clinical models has become apparent. The common mouse-derived extracellular matrix can no longer meet the requirements for the establishment of PDO models. Therefore, in order to develop effective methods for 3D cultures of organoids, we designed a self-assembling peptide, namely DRF3, which can be self-assembled into ordered fibrous scaffold structures. Here, we used the co-assembly of self-assembling peptide (SAP) and collagen type I, fibronectin, and laminin (SAP-Matrix) to co-simulate the extracellular matrix, which significantly reduced the culture time of PDO, improved the culture efficiency, and increased the self-assembly ability of cells. Compared with the results from the 2D cell line, the PDO showed a more significant expression of cancer-related genes. During organoid self-assembly, the expression of cancer-related genes is increased. These findings provide a theoretical basis for the establishment of precision molecular modeling platforms in the future.

Bta-miR-493 Inhibits Bovine Preadipocytes Differentiation by Targeting BMPR1A via the TGFβ/BMP and p38MAPK Signaling Pathways

Fat deposition significantly impacts the meat yield and the meat quality of beef cattle, which is closely associated with the preadipocyte proliferation and differentiation. Bta-miR-493 is expressed differentially in the backfat of Qinchuan cattle of various ages, and it may be involved in the fat accumulation of beef cattle. However, the role and functional mechanism of bta-miR-493 in fat deposition are still unclear. Tissue-specific expression analysis showed that the level of bta-miR-493 was moderately abundant in the adipose tissues of beef cattle. Moreover, the expression of bta-miR-493 in perirenal fat, subcutaneous fat, and longissimus dorsi muscle of Japanese black cattle was significantly higher than that in Qinchuan cattle. EdU staining, cell counting assay, and Oil Red O staining indicated that bta-miR-493 promoted the proliferation of bovine preadipocytes but inhibited their differentiation. The dual luciferase assay and transcriptomic analysis confirmed that bone morphogenetic protein receptor 1A (BMPR1A) is a target gene of bta-miR-493. Moreover, rescue experiments showed that bta-miR-493 could promote bovine preadipocyte proliferation but inhibit their differentiation by targeting BMPR1A via the TGFβ/BMP and p38MAPK signaling pathways. Overall, our findings revealed a bta-miR-493-BMPR1A-TGFβ/BMP/p38MAPK regulatory axis that will serve as a theoretical foundation for the molecular breeding of beef cattle with high intramuscular fat deposition.

Spin Excitation Spectra of Anisotropic Spin-1/2 Triangular Lattice Heisenberg Antiferromagnets

Investigation of dynamical excitations is difficult but crucial to the understanding of many exotic quantum phenomena discovered in quantum materials. This is particularly true for highly frustrated quantum antiferromagnets whose dynamical properties deviate strongly from theoretical predictions made based on the spin-wave or other approximations. Here, we present a large-scale numerical calculation on the dynamical correlation functions of spin-1/2 triangular Heisenberg model using a state-of-the-art tensor network renormalization group method. The calculated results allow us to gain for the first time a comprehensive picture on the nature of spin excitation spectra in this highly frustrated quantum system. It provides a quantitative account for all the key features of the dynamical spectra disclosed by inelastic neutron scattering measurements for Ba_{3}CoSb_{2}O_{9}, revealing the importance of the interplay between low- and high-energy excitations and its renormalization effect to the low-energy magnon bands and high-energy continuums. We identify the longitudinal Higgs modes in the intermediate-energy scale and predict the energy and momentum dependence of spectral functions along the three principal axes that can be verified by polarized neutron scattering experiments. Furthermore, we find that the spin excitation spectra weakly depend on the anisotropic ratio of the antiferromagnetic interaction.

Identification of adenoid subtype characterized with immune-escaped phenotype in lung squamous carcinoma based on transcriptomics

Non-small cell lung cancer (NSCLC) is a heterogeneous disease, and its demarcation contributes to various therapeutic outcomes. However, a small subset of tumors shows different molecular features that are in contradiction with pathological classification. Unsupervised clustering was performed to subtype NSCLC using the transcriptome data from the TCGA database. Next, immune microenvironment features of lung adenocarcinoma (LUAD), lung squamous carcinoma (LUSC), and lung adenoid squamous carcinoma (LASC) were characterized. In addition, diagnostic biomarkers to demarcate LASC among LUSC were screened using weighted gene co-expression network analysis (WGCNA) and validated by the in-house cohort. LASC was identified as a novel subtype with adenoid transcriptomic features in LUSC, which exhibited the most immuno-escaped phenotype among all NSCLC subtypes. In addition, FOLR1 was identified as a biomarker for LASC discrimination using the WGCNA analysis, and its diagnostic value was validated by the in-house cohort. Moreover, FOLR1 was related to immuno-escaped tumors in LUSC but not in LUAD. Overall, we proposed a novel typing strategy in NSCLC and identified FOLR1 as a biomarker for LASC discrimination.

Second Primary Malignancy Risk in Multiple Myeloma from 1975 to 2018

As the survival times for multiple myeloma (MM) patients continue to extend, the risk of a second primary malignancy (SPM) among MM survivors has become a topic of increasing concern within the medical community. The Surveillance, Epidemiology, and End Results (SEER) 9 Registry Database was used to evaluate the risk and survival of SPM among MM survivors from 1975 to 2018. The standardized incidence ratio (SIR), absolute excess risk (AER), and cumulative incidence (CMI) of SPM for MM risk were calculated. Survival and the CMI were estimated by using hazard ratios (HRs). Subgroup analyses were performed according to race, sex, age, time of myeloma diagnosis, and the SPM site. A total of 43,825 cases were recorded with the initial diagnosis of MM from 1975 to 2018. A total of 3101 (7.1%) patients developed 3407 SPMs. Solid tumors were decreased in patients with MM (SIR = 0.93; 95% CI = 0.90–0.97) compared to the general population, whereas the risk of hematological malignancy was increased (SIR = 1.90; 95% CI = 1.72–2.10). Taking death as a competing event, the CMI of SPM in the whole population was 7.38% at 10 years (6.11% solid and 1.27% hematologic). Factors associated with SPM occurrence were age, sex, race, and time of MM diagnosis. The survival of SPM patients from MM diagnosis was longer than that of patients without SPM (HR = 0.67, 95% CI = 0.58–0.63). The median survival time was 17 months from SPM diagnosis and 34 months from MM diagnosis (HR = 1.4, 95% CI = 1.35–1.46). Age, race, and sex were important factors for the risk of SPM. Site- and time-specific surveillance strategies should be recommended to monitor SPM in high-risk MM patients.

Extruded small extracellular vesicles: splinters of circulating tumour cells may promote cancer metastasis?

We speculate ruptured circulating tumour cells (CTC) in capillaries could release a large number of small extracellular vesicle-like vesicles, namely mechanically extruded sEV (sEVme), which can encapsulate chromosomal DNA fragments. These sEVme have similar physicochemical properties compared to small extracellular vesicles spontaneously secreted by living cells (sEVss), and thus sEVme and sEVss cannot be effectively distinguished based on their size or membrane protein markers. Meanwhile, these sEVme derived from CTC inherit oncogenic payloads, deliver cargo through the bloodstream to recipient cells, and thus may promote cancer metastasis. The validation of this speculation could facilitate our understanding of EV biogenesis and cancer pathology. The potential finding will also provide a theoretical foundation for burgeoning liquid biopsy using DNA fragments derived from harvested sEV.

Comparison of suspected and confirmed internal EVD-related infections: a prospective multi-centre U.K. observational study

Background

Diagnosis of internal external ventricular drain (EVD)-related infections (iERI) is an area of diagnostic difficulty. Empiric treatment is often initiated on clinical suspicion. There is limited guidance around antimicrobial management of confirmed versus suspected iERI.

Methods

Data on patients requiring EVD insertion were collected from 21 neurosurgical units in the United Kingdom from 2014 to 2015. Confirmed iERI was defined as clinical suspicion of infection with positive cerebrospinal fluid (CSF) culture and/or Gram stain. Cerebrospinal fluid, blood, and clinical parameters and antimicrobial management were compared between the 2 groups. Mortality and Modified Rankin Scores were compared at 30 days post-EVD insertion.

Results

Internal EVD-related infection was suspected after 46 of 495 EVD insertions (9.3%), more common after an emergency insertion. Twenty-six of 46 were confirmed iERIs, mostly due to Staphylococci (16 of 26). When confirmed and suspected infections were compared, there were no differences in CSF white cell counts or glucose concentrations, nor peripheral blood white cell counts or C-reactive protein concentrations. The incidence of fever, meningism, and seizures was also similar, although altered consciousness was more common in people with confirmed iERI. Broad-spectrum antimicrobial usage was prevalent in both groups with no difference in median duration of therapy (10 days [interquartile range {IQR}, 7–24.5] for confirmed cases and 9.5 days [IQR, 5.75–14] for suspected, P = 0.3). Despite comparable baseline characteristics, suspected iERI was associated with lower mortality and better neurological outcomes.

Conclusions

Suspected iERI could represent sterile inflammation or lower bacterial load leading to false-negative cultures. There is a need for improved microbiology diagnostics and biomarkers of bacterial infection to permit accurate discrimination and improve antimicrobial stewardship.