A lung disease diagnosis algorithm based on 2D spectral features of ultrasound RF signals

Lung diseases are commonly diagnosed based on clinical pathological indications criteria and radiological imaging tools (e.g., X-rays and CT). During a pandemic like COVID-19, the use of ultrasound imaging devices has broadened for emergency examinations by taking their unique advantages such as portability, real-time detection, easy operation and no radiation. This provides a rapid, safe, and cost-effective imaging modality for screening lung diseases. However, the current pulmonary ultrasound diagnosis mainly relies on the subjective assessments of sonographers, which has high requirements for the operator's professional ability and clinical experience. In this study, we proposed an objective and quantifiable algorithm for the diagnosis of lung diseases that utilizes two-dimensional (2D) spectral features of ultrasound radiofrequency (RF) signals. The ultrasound data samples consisted of a set of RF signal frames, which were collected by professional sonographers. In each case, a region of interest of uniform size was delineated along the pleural line. The standard deviation curve of the 2D spatial spectrum was calculated and smoothed. A linear fit was applied to the high-frequency segment of the processed data curve, and the slope of the fitted line was defined as the frequency spectrum standard deviation slope (FSSDS). Based on the current data, the method exhibited a superior diagnostic sensitivity of 98% and an accuracy of 91% for the identification of lung diseases. The area under the curve obtained by the current method exceeded the results obtained that interpreted by professional sonographers, which indicated that the current method could provide strong support for the clinical ultrasound diagnosis of lung diseases.

Comparison of the diagnostic effectiveness of ultrasound imaging coupled with three mathematical models for discriminating thyroid nodules

BACKGROUND

The overlapping nature of thyroid lesions visualized on ultrasound (US) images could result in misdiagnosis and missed diagnoses in clinical practice.

PURPOSE

To compare the diagnostic effectiveness of US coupled with three mathematical models, namely logistic regression (Logistics), partial least-squares discriminant analysis (PLS-DA), and support vector machine (SVM), in discriminating between malignant and benign thyroid nodules.

MATERIAL AND METHODS

A total of 588 thyroid nodules (287 benign and 301 malignant) were collected, among which 80% were utilized for constructing the mathematical models and the remaining 20% were used for internal validation. In addition, an external validation cohort comprising 160 nodules (80 benign and 80 malignant) was employed to validate the accuracy of these mathematical models.

RESULTS

Our study demonstrated that all three models exhibited effective predictive capabilities for distinguishing between benign and malignant nodules, whose diagnostic effectiveness surpassed that of the TI-RADS classification, particularly in terms of true negative diagnoses. SVM achieved a higher diagnostic rate for malignant thyroid nodules (93.8%) compared to Logistics (91.5%) and PLS-DA (91.6%). PLS-DA exhibited higher diagnostic rates for benign thyroid nodules (91.9%) compared to Logistics (86.7%) and SVM (88.7%). Both the area under the receiver operating characteristic curve (AUC) values of PLS-DA (0.917) and SVM (0.913) were higher than that of Logistics (0.891).

CONCLUSION

Our findings indicate that SVM had significantly higher rates of true positive diagnoses and PLS-DA exhibited significantly higher rates of true negative diagnoses. All three models outperformed the TI-RADS classification in discriminating between malignant and benign thyroid nodules.

Self-supplying Cu2+ and H2O2 synergistically enhancing disulfiram-mediated melanoma chemotherapy

Disulfiram (DSF) can target and kill cancer cells by disrupting cellular degradation of extruded proteins and has therefore received particular attention for its tumor chemotherapeutic potential. However, the uncontrollable Cu2+/DSF ratio reduces the efficacy of DSF-mediated chemotherapy. Herein, self-supplying Cu2+ and oxidative stress synergistically enhanced DSF-mediated chemotherapy is proposed for melanoma-based on PVP-coated CuO2 nanodots (CPNDs). Once ingested, DSF is broken down to diethyldithiocarbamate (DTC), which is delivered into a tumor via the circulation. Under the acidic tumor microenvironment, CPNDs produce sufficient Cu2+ and H2O2. DTC readily chelates Cu2+ ions to generate CuET, which shows antitumor efficacy. CuET-mediated chemotherapy can be enhanced by H2O2. Sufficient Cu2+ generation can guarantee the maximum efficacy of DSF-mediated chemotherapy. Furthermore, released Cu2+ can be reduced to Cu+ by glutathione (GSH) and O2- in tumor cells, and Cu+ can react with H2O2 to generate toxic hydroxyl radicals (·OH) via a Fenton-like reaction, promoting the efficacy of CuET. Therefore, this study hypothesizes that employing CPNDs instead of Cu2+ ions could enhance DSF-mediated melanoma chemotherapy, providing a simple but efficient strategy for achieving chemotherapeutic efficacy.

[Imaging risk factors for postoperative cerebral infarction in adults with ischemic Moyamoya disease]

Objective: To investigate the imaging factors associated with postoperative cerebral infarction in adult patients aged 18 and above with ischemic Moyamoya disease. Methods: The clinical data of adult patients who underwent surgeries for ischemic Moyamoya disease in the Department of Neurosurgery at Peking University International Hospital from October 2015 to October 2020 were retrospectively analyzed. Of the 239 patients, 120 were male and 119 were female, with ages ranging from 18 to 63 (41.7±10.3) years. A total of 239 patients(290 cases) underwent direct and indirect combined revascularization (CR).Gender, age, surgical side, preoperative transient ischemic attack (TIA), presence of old cerebral infarction, and imaging features were compared between the patients with (48 cases) and without (242 cases) cerebral infarction within 1 week after surgery. Multivariate logistic binary regression model was used to analyze the imaging risk factors of postoperative cerebral infarction. Results: Cerebral infarction occurred in 48 cases(16.5%) among the 290 CR group within 1 week after surgery. The proportion of patients with TIA, old cerebral infarction, ICA stenosis, A1 segment stenosis, M1 segment stenosis, abnormal posterior cerebral artery (PCA), and unstable compensation before CR in the cerebral infarction group was higher than that in the non-cerebral infarction group (P<0.05).Preoperative TIA (OR=4.514, 95%CI: 1.920-10.611), old cerebral infarction (OR=2.856,95%CI:1.176-6.936), A1 stenosis (OR=7.027,95%CI:1.877-26.308), M1 stenosis (OR=6.968,95%CI:2.162-22.459), abnormal PCA (OR=4.114,95%CI:1.330-12.728)and unstable compensation (OR=4.488,95%CI:1.194-16.865) were risk factors for cerebral infarction after CR surgery (all P<0.05). Conclusion: Among the imaging factors, TIA, old cerebral infarction, A1 stenosis, M1 stenosis, abnormal PCA and unstable compensation were risk factors for cerebral infarction in adult patients with ischemic Moyamoya disease treated by combined revascularization.

Disturbance of mitochondrial dynamics in myocardium of broilers with pulmonary hypertension syndrome

1. The following study investigated the relationship between pulmonary hypertension syndrome (PHS) and mitochondrial dynamics in broiler cardiomyocytes.2. An animal model for PHS was established by injecting broiler chickens with CM-32 cellulose particles. Broiler myocardial cells were cultured under hypoxic conditions to establish an in vitro model. The ascites heart index, histomorphology, mitochondrial ultrastructure, and mitochondrial dynamic-related gene and protein expression were evaluated.3. The myocardial fibres from PHS broilers had wider spaces and were wavy and twisted and the number of mitochondria increased. Compared with the control group, the gene and protein expression levels were decreased for Opa1, Mfn1, and Mfn2 in the myocardium of PHS broilers. The gene and protein expression was significantly increased for Drp1 and Mff.4. This study showed that PHS in broilers may cause myocardial mitochondrial dysfunction, specifically by diminishing mitochondrial fusion and enhancing fission, causing disturbances in the mitochondrial dynamics of the heart.

Study of High-Transverse-Momentum Higgs Boson Production in Association with a Vector Boson in the qqbb Final State with the ATLAS Detector

This Letter presents the first study of Higgs boson production in association with a vector boson (V=W or Z) in the fully hadronic qqbb final state using data recorded by the ATLAS detector at the LHC in proton-proton collisions at sqrt[s]=13  TeV and corresponding to an integrated luminosity of 137  fb^{-1}. The vector bosons and Higgs bosons are each reconstructed as large-radius jets and tagged using jet substructure techniques. Dedicated tagging algorithms exploiting b-tagging properties are used to identify jets consistent with Higgs bosons decaying into bb[over ¯]. Dominant backgrounds from multijet production are determined directly from the data, and a likelihood fit to the jet mass distribution of Higgs boson candidates is used to extract the number of signal events. The VH production cross section is measured inclusively and differentially in several ranges of Higgs boson transverse momentum: 250-450, 450-650, and greater than 650 GeV. The inclusive signal yield relative to the standard model expectation is observed to be μ=1.4_{-0.9}^{+1.0} and the corresponding cross section is 3.1±1.3(stat)_{-1.4}^{+1.8}(syst)  pb.

[Pathogenetic analysis of transfusion-related acute lung injury caused by human leukocytes antigen antibody against human leukocyte antigen]

From September 2019 to October 2020, pathogenetic analysis of three patients clinically diagnosed as transfusion-related acute lung injury (TRALI) caused by human leukocyte antibodies was conducted by Guangzhou Blood Centre, including 2 males and 1 female, aged 56, 50 and 20 years old, respectively. Solid phase agglutination, anti-human globulin test and flow cytometry method were used to detect the presence of antibodies against patients. Sequencing-based human leukocyte antigen (HLA-SBT) typing technique was used to detect the human leukocyte antigen (HLA) genotypes of patients. Lifecodes single antigen class Ⅰ/Ⅱ kit (LSA-Ⅰ/Ⅱ) were used to detect the specificity of HLA-class Ⅰ and class Ⅱ antibodies in donor blood by Luminex 200 liquid suspension chip system. The HLA specific antibodies and corresponding epitopes in donors were also analyzed. The results showed that　HLA class Ⅰ or class Ⅱ specific antibodies against TRALI patients were detected in the blood donors. The plasma of donor 3 received by patient 1 contained antibodies against the patient's HLA-DRB1*09∶01 antigen, and the epitopes mediating the antibody reaction of the donor and recipient were 70R, 31I, 70QA. There were antibodies against the HLA-A*11∶02, HLA-A*11∶01, DRB1*12∶02, and DRB1*09∶01 antigens of patient 2 in the plasma of donor 4, and the associated antigenic epitopes were 151AHA, 57V, and 16Y. Antibodies against the HLA-DRB1*14∶04, DRB1*11∶01, and DPB1*05∶01 antigens of patient 3 were present in the plasma of donor 6 and donor 7, and the associated epitopes were 96HK, 140TV, 13SE, and 111K.　Three cases of TRALI were confirmed to be caused by HLA antibodies through laboratory analysis, and human leukocyte antibody detection should be paid attention in clinically suspected cases of TRALI, and targeted diagnosis and treatment should be given.

[Ophthalmic surgical robot-assisted retinal puncture and injection for submacular hemorrhage caused by polypoid choroidal vasculopathy: a case report]

A 65-year-old man presented with decreased visual acuity in the left eye for 1 month. The diagnosis of hemorrhagic retinal detachment (submacular hemorrhage), which was caused by idiopathic polypoid choroidal vasculopathy, was confirmed by the ultra-wide-angle fundus examination, optical coherence tomography, and B-ultrasound. A vitrectomy combined with an ophthalmic surgical robot-assisted retinal puncture and injection was performed. The recombinant tissue plasminogen activator was injected accurately by the ophthalmic surgical robot between the retinal nerve epithelium and retinal pigment epithelium through a micro-injection needle. During the 2-month follow-up, the subretinal hemorrhage was significantly regressive, the visual acuity of the left eye was improved from hand movement to 0.1, and no other complications were observed.

Measurement of the Centrality Dependence of the Dijet Yield in p+Pb Collisions at sqrt[s_{NN}]=8.16 TeV with the ATLAS Detector

ATLAS measured the centrality dependence of the dijet yield using 165  nb^{-1} of p+Pb data collected at sqrt[s_{NN}]=8.16  TeV in 2016. The event centrality, which reflects the p+Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R_{CP}, is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R_{CP} shows a scaling with the Bjorken x of the parton originating from the proton, x_{p}, while no such trend is observed as a function of x_{Pb}. This analysis provides unique input to understanding the role of small proton spatial configurations in p+Pb collisions by covering parton momentum fractions from the valence region down to x_{p}∼10^{-3} and x_{Pb}∼4×10^{-4}.

Preoperative Contrast-Enhanced Ultrasound Predicts Microvascular Invasion in Hepatocellular Carcinoma as Accurately as Contrast-Enhanced MR

OBJECTIVES

Both contrast-enhanced ultrasound (CEUS) and contrast-enhanced magnetic resonance (CEMR) are important imaging methods for hepatocellular carcinoma (HCC). This study aimed to establish a model using preoperative CEUS parameters to predict microvascular invasion (MVI) in HCC, and compare its predictive efficiency with that of CEMR model.

METHODS

A total of 93 patients with HCC (39 cases in MVI positive group and 54 cases in MVI negative group) who underwent surgery in our hospital from January 2020 to June 2021 were retrospectively analyzed. Their clinical and imaging data were collected to establish CEUS and CEMR models for predicting MVI. The predictive efficiencies of both models were compared.

RESULTS

By the univariate and multivariate regression analyses of patients' clinical information, preoperative CEUS static and dynamic images, we found that serrated edge and time to peak were independent predictors of MVI. The CEUS prediction model achieved a sensitivity of 92.3%, a specificity of 83.3%, and an accuracy of 84.6% (Az: 0.934). By analyzing the clinical and CEMR information, we found that tumor morphology, fast-in and fast-out, peritumoral enhancement, and capsule were independent predictors of MVI. The CEMR prediction model achieved a sensitivity of 97.4%, a specificity of 77.8%, and an accuracy of 83.2% (Az: 0.900). The combination of the two models achieved a sensitivity of 84.6%, a specificity of 87.0%, and an accuracy of 86.2% (Az: 0.884). There was no significant statistical difference in the areas under the ROC curve of the three models.

CONCLUSION

The CEUS model and the CEMR model have similar predictive efficiencies for MVI of HCC. CEUS is also an effective method to predict MVI before operation.

Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13 TeV with the ATLAS Detector

Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140  fb^{-1} of pp collisions at sqrt[s]=13  TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e,μ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.

Thrombin injection under B-flow and ultrasound guidance: A safe and effective treatment of pseudoaneurysms

PURPOSE

To evaluate the method of thrombin injection under B-flow and ultrasound guidance (BUGTI) for the treatment of pseudoaneurysms.

MATERIALS AND METHODS

Twenty-one patients suffering from pseudoaneurysm (PSA) were retrospectively reviewed at the First Affiliated Hospital of Nanjing Medical University in Nanjing, China, from January 2018 to August 2019. The patients were treated using an ultrasound-guided injection of thrombin (500 IU/mL) combined with B-mode blood flow imaging (B-flow). The information on the PSA, including the size of the arterial rupture and sac, flow rate, thrombin dose, and treatment outcome, was recorded during the procedure. Follow-up evaluation was performed at 1, 3, and 6 months after the treatment. Pearson's correlation analysis was performed among the characteristics of PSA and the dose of thrombin.

RESULT

The age of patients ranged from 34 to 80 years and averaged 62.8 years. The maximum cross-sectional area of PSA ranged from 208 to 1148 mm2. All patients were treated with thrombin injections. The dose of thrombin ranged from 300 to 1667 IU. No reperfusions were detected at follow-up 6 months, and the BUGTI treatment was successful in all 21 cases. Pearson's correlation analysis demonstrated that the dose of thrombin was positively correlated with the width (r = 0.449, p < .05) and maximum cross-sectional area (r = 0.504, p < .05) of PSA.

CONCLUSION

Thrombin injection under B-flow and ultrasound guidance is a rapid and effective treatment for PSA. Additionally, the sac size could be used to estimate the dose of thrombin.

Predictors of High Cardiovascular Risk Among Nonobese Patients with Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease in a Chinese Population

Purpose

This study aims to investigate cardiovascular risk factors in nonobese patients with type 2 diabetes (T2DM) and non-alcoholic fatty liver disease (NAFLD) and to determine whether they might be used to predict high-risk individuals effectively.

Patients and Methods

This cross-sectional study included 245 nonobese patients with T2DM who underwent FibroTouch in the National Metabolic Management Center of the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University from January 2021 to December 2022. All individuals were divided into NAFLD and non-NAFLD groups. Patients with NAFLD were further grouped by UAP tertiles (T1, T2 and T3). We created a Cardiovascular Score (total scale: 0-5 points; ≥3 points was defined as high-risk individual) based on baPWV, carotid ultrasound, and urinary microalbumin creatinine ratio (UA/CR) to assess the risk of cardiovascular disease in non-obese T2DM patients with NAFLD. Risk factors were evaluated using univariate and multivariate analysis. The performance of risk factors was compared according to the area under the receiver operating characteristic (ROC) curve.

Results

Atherogenic index of plasma (AIP), atherosclerosis index (AI), prevalence of hypertension, body mass index (BMI) and homeostatic model assessment of insulin resistance (HOMA-IR) were higher in the NAFLD group compared to the non-NAFLD group. In T3 group, AIP, AI, BMI and HOMA-IR were higher than those of T1 group. Multivariate logistic regression showed that age, systolic blood pressure, low-density lipoprotein-cholesterol (LDL-C) and AIP were risk factors for cardiovascular disease among nonobese patients with T2DM and NAFLD. The area under the ROC curve for age, systolic blood pressure, LDL-C and AIP were 0.705, 0.688, 0.738 and 0.642, respectively. The area under the ROC curve was 0.895 when combining them.

Conclusion

Age, systolic blood pressure, AIP and LDL-C are all independent risk factors for cardiovascular disease in non-obese individuals with T2DM and NAFLD, which can be combined to identify high-risk populations and carry out intervention.

Observation of WZγ Production in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

This Letter reports the observation of WZγ production and a measurement of its cross section using 140.1±1.2  fb^{-1} of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. The WZγ production cross section, with both the W and Z bosons decaying leptonically, pp→WZγ→ℓ^{'}^{±}νℓ^{+}ℓ^{-}γ (ℓ^{(^{'})}=e, μ), is measured in a fiducial phase-space region defined such that the leptons and the photon have high transverse momentum and the photon is isolated. The cross section is found to be 2.01±0.30(stat)±0.16(syst)  fb. The corresponding standard model predicted cross section calculated at next-to-leading order in perturbative quantum chromodynamics and at leading order in the electroweak coupling constant is 1.50±0.06  fb. The observed significance of the WZγ signal is 6.3σ, compared with an expected significance of 5.0σ.

Role of Cisplatin in Inducing Acute Kidney Injury and Pyroptosis in Mice via the Exosome miR-122/ELAVL1 Regulatory Axis

Although cisplatin is an effective chemotherapy drug for the treatment of various cancers, its clinical use is limited due to its side effects, especially nephrotoxicity. Unfortunately, acute kidney injury (AKI) caused by cisplatin remains one of the main challenges in effective cancer treatment. Evidence increasingly suggests that renal inflammation and pyroptotic inflammatory cell death of renal tubular epithelial cells (RTECs) mainly determine the progression and outcome of cisplatin-induced AKI. However, it is not clear how cisplatin regulates the pyroptosis of RTECs cells in AKI. The current study aimed to determine the regulation mechanism of AKI induced by cisplatin. We used cisplatin to induce AKI in vivo. We performed H&E staining of mouse kidney tissue sections and evaluated serological indicators of kidney injury (including blood urea nitrogen (BUN), serum creatinine, and tumor necrosis factor-alpha (TNF-alpha)). We used immunohistochemistry and western blot to detect the important substrate protein gasdermin D (GSDMD) and key target caspase-1 of pyroptosis, respectively. Cisplatin induced mouse AKI and RTECs pyroptosis. HK2 cell-derived exosomes treated with cisplatin influenced pyroptosis of the surrounding HK2 cells. Cisplatin-treated HK2 cells exosome-derived miR-122 regulated pyroptosis in the surrounding cells. Exosome-derived miR-122 affected cisplatin-induced AKI and HK2 cells pyroptosis by regulating the expression of embryonic lethal abnormal vision (ELAVL1). These results suggest that exosome miR-122 inhibited pyroptosis and AKI by targeting ELAVL1 under cisplatin treatment, and this offers a potential target for the treatment of AKI.

Combined Measurement of the Higgs Boson Mass from the H→γγ and H→ZZ^{*}→4ℓ Decay Channels with the ATLAS Detector Using sqrt[s]=7, 8, and 13 TeV pp Collision Data

A measurement of the mass of the Higgs boson combining the H→ZZ^{*}→4ℓ and H→γγ decay channels is presented. The result is based on 140  fb^{-1} of proton-proton collision data collected by the ATLAS detector during LHC run 2 at a center-of-mass energy of 13 TeV combined with the run 1 ATLAS mass measurement, performed at center-of-mass energies of 7 and 8 TeV, yielding a Higgs boson mass of 125.11±0.09(stat)±0.06(syst)=125.11±0.11  GeV. This corresponds to a 0.09% precision achieved on this fundamental parameter of the Standard Model of particle physics.

Search for Dark Photons in Rare Z Boson Decays with the ATLAS Detector

A search for events with a dark photon produced in association with a dark Higgs boson via rare decays of the standard model Z boson is presented, using 139  fb^{-1} of sqrt[s]=13  TeV proton-proton collision data recorded by the ATLAS detector at the Large Hadron Collider. The dark boson decays into a pair of dark photons, and at least two of the three dark photons must each decay into a pair of electrons or muons, resulting in at least two same-flavor opposite-charge lepton pairs in the final state. The data are found to be consistent with the background prediction, and upper limits are set on the dark photon's coupling to the dark Higgs boson times the kinetic mixing between the standard model photon and the dark photon, α_{D}ϵ^{2}, in the dark photon mass range of [5, 40] GeV except for the ϒ mass window [8.8, 11.1] GeV. This search explores new parameter space not previously excluded by other experiments.

The Correlation Between Leg Muscle Mass Index and Non-Alcoholic Fatty Liver Disease in Patients with Type 2 Diabetes Mellitus

Objective

To analyze the relationship between leg skeletal muscle mass index (LSMI) and non-alcoholic fatty liver disease (NAFLD) in patients with type 2 diabetes mellitus (T2DM) and the ability of LSMI to predict NAFLD.

Methods

Two hundred patients with T2DM and NAFLD treated at Changzhou Second People's Hospital Affiliated with Nanjing Medical University and the National Metabolic Management Center from June 2022 to June 2023 were divided into four LSMI quartiles. The clinical information from the four patient groups was compared, and the relationship between type 2 diabetes and LSMI and NAFLD was examined. We used receiver operating characteristic curves to determine how well the LSMI predicts NAFLD in T2DM.

Results

The lowest quartile (Q1) had a higher prevalence of NAFLD than group Q4 (P < 0.05). LSMI was negatively associated with body mass index, LS, CAP, and other markers (P < 0.05). Receiver operating characteristic curve analysis LSMI predicted NAFLD with an ideal critical value of 0.64 and an area under the curve of 70.9%. The combined predictive value of the LSMI and the appendicular skeletal muscle mass index was more significant.

Conclusion

Reduced LSMI is associated with NAFLD.

Decreased serum musclin concentration is independently associated with the high prevalence of sarcopenia in Chinese middle-elderly patients with type 2 diabetes mellitus

INTRODUCTION AND AIMS

Sarcopenia is a complication of diabetes mellitus, which can increase hospitalization and lead to poor outcomes. The present study investigated the relationship between the serum musclin concentration and the sarcopenia morbidity in Chinese middle-elderly patients with type 2 diabetes mellitus.

METHODS

We recruited 220 patients with type 2 diabetes mellitus, all of whom completed gait speed, handgrip strength tests, and whole-body dual-energy x-ray measurements to calculate the appendicular skeletal muscle mass index (ASMI). The patients were divided into sarcopenia (n = 110) and non-sarcopenia groups (n = 110). The serum musclin concentration was measured using an enzyme-linked immunosorbent assay.

RESULTS

The serum musclin concentration was significantly lower in the sarcopenia group (712.82 pg/mL) than in the non-sarcopenia group (922.53 pg/mL). The serum musclin concentration positively correlated with the whole-body skeletal mass (r = 0.230; P = 0.001). Sarcopenia morbidity declined as the quartile of serum musclin concentration increased (P = 0.001), and a negative correlation was observed between the serum musclin concentration and the prevalence of sarcopenia (odds ratio = 0.998, P = 0.001). The correlation remained when quartiles were considered.

CONCLUSIONS

The serum musclin concentration is an independent protective factor for sarcopenia in Chinese middle-elderly patients with type 2 diabetes mellitus.

The effect of sedentary time on cardiovascular disease risk in middle-aged and elderly patients with type 2 diabetes mellitus

Sedentary lifestyle has become quite prevalent lately, and it has been associated with cardiovascular diseases (CVDs). CVD is a primary cause of premature death in patients with type 2 diabetes mellitus (T2DM). Some studies have focused on the association between sedentary behavior and blood glucose among T2DM patients. However, the occurrence and development of CVD involves many factors, such as blood glucose, blood lipid and so on. Therefore, we comprehensively examined the association of sedentary time with overall CVD risk and various metabolic risk factors in T2DM patients. A total of 775 middle-aged and elderly patients with T2DM were assessed. Framingham risk equation was employed to assess their overall CVD risk, while the sedentary time was self-reported. Demographic data and anthropometric and cardiac metabolic indicators were separately analyzed for both genders. The median age of the respondents was 55 (range: 45-75) years, and 39.23% were women. The overall risk of CVD in women was lower than that in men. Linear regression analysis revealed that sedentary time was significantly positively correlated with overall CVD risk and triglyceride level, but not with diastolic blood pressure and glycosylated hemoglobin and high-density lipoprotein cholesterol (HDL-C) levels. However, the correlation of sedentary time with fasting blood glucose level, body mass index, total cholesterol, and low-density lipoprotein cholesterol was only detected in women. In middle-aged and elderly patients with T2DM, prolonged sedentary time may increase the triglyceride levels and the overall risk of CVD. The adverse effects of sedentary time on fasting blood glucose, body mass index, total cholesterol, and low-density lipoprotein cholesterol may exhibit sex-based differences, as they were detected only in women.

Observation of Single-Top-Quark Production in Association with a Photon Using the ATLAS Detector

This Letter reports the observation of single top quarks produced together with a photon, which directly probes the electroweak coupling of the top quark. The analysis uses 139  fb^{-1} of 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider. Requiring a photon with transverse momentum larger than 20 GeV and within the detector acceptance, the fiducial cross section is measured to be 688±23(stat) _{-71}^{+75}(syst)  fb, to be compared with the standard model prediction of 515_{-42}^{+36}  fb at next-to-leading order in QCD.

Measurement of Suppression of Large-Radius Jets and Its Dependence on Substructure in Pb+Pb Collisions at sqrt[s_{NN}]=5.02 TeV with the ATLAS Detector

This letter presents a measurement of the nuclear modification factor of large-radius jets in sqrt[s_{NN}]=5.02  TeV Pb+Pb collisions by the ATLAS experiment. The measurement is performed using 1.72  nb^{-1} and 257  pb^{-1} of Pb+Pb and pp data, respectively. The large-radius jets are reconstructed with the anti-k_{t} algorithm using a radius parameter of R=1.0, by reclustering anti-k_{t} R=0.2 jets, and are measured over the transverse momentum (p_{T}) kinematic range of 158 Collapse

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Measurement of the Sensitivity of Two-Particle Correlations in pp Collisions to the Presence of Hard Scatterings

A key open question in the study of multiparticle production in high-energy pp collisions is the relationship between the "ridge"-i.e., the observed azimuthal correlations between particles in the underlying event that extend over all rapidities-and hard or semihard scattering processes. In particular, it is not known whether jets or their soft fragments are correlated with particles in the underlying event. To address this question, two-particle correlations are measured in pp collisions at sqrt[s]=13  TeV using data collected by the ATLAS experiment at the LHC, with an integrated luminosity of 15.8  pb^{-1}, in two different configurations. In the first case, charged particles associated with jets are excluded from the correlation analysis, while in the second case, correlations are measured between particles within jets and charged particles from the underlying event. Second-order flow coefficients, v_{2}, are presented as a function of event multiplicity and transverse momentum. These measurements show that excluding particles associated with jets does not affect the measured correlations. Moreover, particles associated with jets do not exhibit any significant azimuthal correlations with the underlying event, ruling out hard processes contributing to the ridge.

Observation of an Excess of Dicharmonium Events in the Four-Muon Final State with the ATLAS Detector

A search is made for potential ccc[over ¯]c[over ¯] tetraquarks decaying into a pair of charmonium states in the four muon final state using proton-proton collision data at sqrt[s]=13  TeV, corresponding to an integrated luminosity of 140  fb^{-1} recorded by the ATLAS experiment at LHC. Two decay channels, J/ψ+J/ψ→4μ and J/ψ+ψ(2S)→4μ, are studied. Backgrounds are estimated based on a hybrid approach involving Monte Carlo simulations and data-driven methods. Statistically significant excesses with respect to backgrounds dominated by the single parton scattering are seen in the di-J/ψ channel consistent with a narrow resonance at 6.9 GeV and a broader structure at lower mass. A statistically significant excess is also seen in the J/ψ+ψ(2S) channel. The fitted masses and decay widths of the structures are reported.

Observation of the γγ→ττ Process in Pb+Pb Collisions and Constraints on the τ-Lepton Anomalous Magnetic Moment with the ATLAS Detector

This Letter reports the observation of τ-lepton-pair production in ultraperipheral lead-lead collisions Pb+Pb→Pb(γγ→ττ)Pb and constraints on the τ-lepton anomalous magnetic moment a_{τ}. The dataset corresponds to an integrated luminosity of 1.44  nb^{-1} of LHC Pb+Pb collisions at sqrt[s_{NN}]=5.02  TeV recorded by the ATLAS experiment in 2018. Selected events contain one muon from a τ-lepton decay, an electron or charged-particle track(s) from the other τ-lepton decay, little additional central-detector activity, and no forward neutrons. The γγ→ττ process is observed in Pb+Pb collisions with a significance exceeding 5 standard deviations and a signal strength of μ_{ττ}=1.03_{-0.05}^{+0.06} assuming the standard model value for a_{τ}. To measure a_{τ}, a template fit to the muon transverse-momentum distribution from τ-lepton candidates is performed, using a dimuon (γγ→μμ) control sample to constrain systematic uncertainties. The observed 95% confidence-level interval for a_{τ} is -0.057 Collapse

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Dose Painting Radiotherapy Guided by Diffusion-Weighted Magnetic Resonance vs. 18F-FDG-PET/CT in Locoregionally Advanced Nasopharyngeal Carcinoma: A Randomized, Controlled Clinical Trial

PURPOSE/OBJECTIVE(S)

This phase II randomized controlled trial aimed at comparing the efficacy and toxicity of diffusion-weighted magnetic resonance imaging (DWI)-guided dose painting radiotherapy (DP-RT), FDG-PET/CT-guided DP-RT, and conventional MRI-based radiotherapy (RT) in locoregionally advanced nasopharyngeal carcinoma (NPC).

MATERIALS/METHODS

A total of 330 patients with stage III-IVa NPC disease were randomly assigned in a 1:1:1 ratio to receive induction chemotherapy followed by concurrent chemoradiotherapy by DWI-guided DP-RT (group A, n = 110), FDG-PET/CT-guided DP-RT (group B, n = 110), or conventional MRI-based RT (group C, n = 110). All patients received volumetric modulated arc therapy (VMAT). In group A, subvolume GTVnx-DWI (gross tumor volume of nasopharynx in DWI) was defined as the areas within the GTVnx (gross tumor volume of nasopharynx) with an apparent diffusion coefficient (ADC) below the mean ADC (ADC < mean). In group B, subvolume GTVnx-PET (gross tumor volume of nasopharynx in PET images) was defined within GTVnx as the SUV50%max isocontour. The doses to GTVnx-DWI in group A and GTVnx-PET in group B were escalated to 75.2 Gy/32 fx in patients with T1-2 disease and to 77.55 Gy/33 fx in those with T3-4 disease in 2.35 Gy per fraction. In group C, planning gross tumor volume of nasopharynx (PGTVnx) was irradiated at 70.4 to 72.6 Gy/32 to 33 fx in 2.2 Gy per fraction. This trial is registered with chictr.org.cn (ChiCTR2200057476).

RESULTS

Group A and B showed significant higher complete response (CR) rates than group C (100%, 100%, and 96.4% for group A, B and C, respectively, p = 0.036). In groups A, B and C, the 1-year local recurrence-free survival (LRFS) rates were 100%, 100%, and 94.5%, respectively (p = 0.002). The 1-year disease-free survival (DFS) rates were 100%, 99.1%, and 92.7%, respectively (p = 0.001). The 1-year distant metastasis-free survival (DMFS) rates were 100%, 99.1%, and 93.6%, respectively (p = 0.004). The 1-year overall survival (OS) rates were 100%, 100%, and 95.4%, respectively (p = 0.006). Group A and B had significantly higher 1-year LRFS, DFS, DMFS, and OS than those in group C. No significant differences were observed in LRFS, DFS, DMFS and OS between group A and B. Group B (PET/CT group) had a higher incidence of grade 3-4 acute ototoxicity (3.6%) than group A (0%) and group C (0%, p = 0.036). No significant differences in other grade 3-4 acute adverse events and late toxic effects were observed among the three groups, and no patient had grade 5 toxicities. Multivariate analysis showed that dose painting (DWI-guided DP-RT and PET/CT-guided DP-RT vs conventional MRI-based RT) was associated with improved LRFS, DFS, DMFS and OS.

CONCLUSION

Both DWI-guided DP-RT and PET/CT-guided DP-RT plus chemotherapy are associated with improved LRFS, DFS, DMFS and OS compared with conventional MRI-based RT among patients with locoregionally advanced NPC. DWI-guided DP-RT does not increase toxicities, but PET/CT-guided DP-RT has higher incidence of acute ototoxicity.

Deep Learning-Based Multi-Modality Segmentation of Primary Gross Tumor Volume in CT and MRI for Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

The delineation of primary gross tumor volume (GTV) of nasopharyngeal carcinoma (NPC) is an essential step for radiotherapy planning. In clinical practice, radiation oncologists manually delineate the GTV in planning CT with the help of diagnostic MRI. This is because NPC tumors are closely adjacent to many important anatomic structures, and CT and MRI provide complementary strength to accurately determine the tumor extension boundary. Manual delineation is time-consuming with the potential registration errors between MRI and CT decreasing the delineation accuracy. In this study, we propose a fully automated GTV segmentation method based on CT and MRI by first aligning MRI to CT, and then, segmenting the GTV using a multi-modality deep learning model.

MATERIALS/METHODS

We collected 104 nasopharyngeal carcinoma patients with both planning CT and diagnostic MRI scans (T1 & T2 phases). An experienced radiation oncologists manually delineated the GTV, which was further examined by another senior radiation oncologist. Then, a coarse to fine cross-modality registration from MRI to CT was conducted as follows: (1) A rigid transformation was performed on MRI to roughly align MRI to CT with similar anatomic position. (2) Then, the region of interest (RoI) on both CT and rigid-transformed MRI were cropped. (3) A leading cross-modality deformable registration algorithm, named DEEDS, was applied on the cropped MRI and CT RoIs to find an accurate local alignment. Next, using CT and registered MRI as the combined input, a multi-modality deep segmentation network based on nnUNet was trained to generate the GTV prediction. 20% patients were randomly selected as the unseen testing set to quantitatively evaluate the performance.

RESULTS

The quantitative NPC GTV segmentation performance is summarized in Table 1. The deep segmentation model using CT alone achieved reasonable high performance with 76.6% Dice score and 1.34mm average surface distance (ASD). When both CT and registered MRI were used, the segmentation model further improved the performance by 0.9% Dice score increase and 11% relative ASD error reduction, demonstrating the complementary strength of CT and MRI in determining NPC GTV. Notably, the achieved 77.5% Dice score and 1.19mm ASD by the multimodality model is among the top performing results reported in recent automatic NPC GTV segmentation using either CT or MRI modality.

CONCLUSION

We developed a fully automated multi-modal deep-learning model for NPC GTV segmentation. The developed model can segment the NPC GTV in high accuracy. With further optimization and validation, this automated model has potential to standardize the NPC GTV segmentation and significantly decrease the workload of radiation oncologists in clinical practice.

Efficacy and Toxicity of Different Target Volume Delineations of Radiotherapy Based on the Updated RTOG/NRG and EORTC Guidelines in Patients with High Grade Glioma: A Randomized, Controlled Clinical Trial

PURPOSE/OBJECTIVE(S)

Postoperative radiotherapy with concomitant and adjuvant temozolomide (TMZ) is the standard of care for newly diagnosed high grade glioma, but the optimal method for target volume delineations for intensity modulated radiation therapy (IMRT) is still unclear. We hypothesized that compared with the EORTC guidelines, IMRT based on the updated RTOG/NRG guidelines was equally effective, without increasing toxicities for patients with high-grade glioma. The purpose of this randomized phase 2 study was to compare the efficacy and toxicity of IMRT based on different target volume delineations (updated RTOG/NRG versus EORTC guidelines) with concomitant and adjuvant TMZ for patients with high grade glioma.

MATERIALS/METHODS

A total of 302 patients with newly diagnosed high-grade glioma (WHO grade 3-4) were randomly assigned (1:1) to receive postoperative IMRT based on either updated RTOG/NRG guidelines (RTOG/NRG group, n = 151) or EORTC guideline (EORTC group, n = 151), with concomitant and adjuvant TMZ. In the RTOG/NRG group, an initial volume consisting of enhancement, postoperative cavity, plus surrounding edema (or fluid-attenuated inversion recovery [FLAIR] abnormality defined by magnetic resonance imaging [MRI]) and a 2-cm margin received 46 Gy in 23 fractions followed by a boost of 14 Gy in 7 fractions to the area of enhancement plus the cavity and a 2-cm margin. In the EORTC group, a single planning volume was used to deliver 60 Gy in 30 fractions to the area of enhancement and the cavity with a 2-cm margin. The primary end point was overall survival (OS). Secondary end points included progression-free survival (PFS) and toxicities associated with each treatment.

RESULTS

No statistically significant differences were observed between groups for 1-year OS (71.8% for RTOG/NRG group and 69.9% for EORTC group, respectively; P = 0.759) or 1-year PFS (46.7% for RTOG/NRG group and 43.6% for EORTC group, respectively; P = 0.674). Efficacy did not differ by MGMT methylation status. There were no differences in grade 3-4 toxicities (leukopenia, lymphopenia, neutropenia, thrombocytopenia, fatigue, nausea and vomiting) between the two groups. No grade 5 toxicities were observed in both groups. Multivariate analyses showed that tumor MGMT status (methylated vs unmethylated) and WHO grade (grade 3 vs grade 4) were associated with OS and PFS. However, radiation type (RTOG/NRG group vs EORTC), sex, age, and Karnofsky scale did not significantly influence OS or PFS.

CONCLUSION

Compared with EORTC guidelines for postoperative radiotherapy, IMRT based on RTOG/NRG guidelines was equally effective, without increasing toxicities for patients with high-grade glioma. This trial is registered with chictr.org.cn, number ChiCTR2100046667.

Homeostatic Balance of Gut Microbiota in Head and Neck Squamous Cell Carcinoma Patients during Radiotherapy

PURPOSE/OBJECTIVE(S)

Radiotherapy is the major treatment for head and neck squamous cell carcinoma (HNSCC). Oral microbiota changes have been described before. However, gut microbiota changes in HNSCC patients who received local radiotherapy remain unclear. We aim to investigate the dynamic change of gut microbiota composition in HNSCC patients undergoing radiotherapy and to construct the radiotherapy related gut microbiota database in HNSCC patients.

MATERIALS/METHODS

We enrolled 47 HNSCC patients who scheduled with radiotherapy solely. Intensity-modulated radiotherapy (IMRT) was the standard radiotherapy technique for all the enrolled patients. The field was irradiated with a total dose of 60-66Gy in 30-33 fractions. Fecal pellets were collected at three time points. Bacterial genomic DNA was isolated using magnetic beads and then analyzed by the Illumina MiSeq Sequencing System based on the V3-V4 hypervariable regions of the 16S rRNA gene.

RESULTS

A total of 194 genera which belonged to 27 phyla were found in 141 samples. Increased abundance of microbiota in diversity and richness was observed in mid-radiotherapy group. Moreover, Bacteroides, Blautia, and Phascolarctobacterium were three main genera in all three groups and the mid-radiotherapy group had the highest relative abundance of Phascolarctobacterium. What's more, most significantly altered bacteria shared the same variation pattern which was increased in mid-radiotherapy while decreased to the almost same level of as pre-radiotherapy in post-radiotherapy group.

CONCLUSION

Local radiotherapy can affect the composition of the gut microbiota in HNSCC patients during the mid-term of radiotherapy. However, self-stabilized ability maintained the gut microbiota homeostasis in the end.

Deep Learning for Automatic Prediction of Lymph Node Station Metastasis in Esophageal Cancer Patients from Contrast-Enhanced CT

PURPOSE/OBJECTIVE(S)

The diagnosis of lymph node (LN) metastasis in computed tomography (CT) is an essential yet challenging task in esophageal cancer staging and treatment planning. Although criteria (e.g., RECIST, morphological/texture features) are proposed to predict LN metastasis, the diagnostic accuracy remains low with sensitivity <50% and specificity <75%, as reported in previous studies. Deep learning (DL) has the potential to address this issue by learning from large-scale labeled data. However, due to the practical surgery procedure in lymph node dissection, it is difficult to pair the metastasis of individual LN reported in the pathology report to the LN instance found in the CT image. Hence, in this study, we first use pathology reports to determine the LNS metastasis, then develop a multiple instance deep learning (MIDL) model to predict lymph node station (LNS) metastasis.

MATERIALS/METHODS

We collected 1200 esophageal cancer patients with preoperative contrast-enhanced CT before surgery. A recently developed automatic mediastinal LNS segmentation model was first applied to segment LNS of 1 to 8 based on the IASLC protocol. For each LNS, the local CT region of interest (ROI) was cropped to generate a station-wise CT patch, where the LNS was labeled as metastatic if at least one metastatic LN was indicated in the pathology report. Using the station-wise CT patch and LNS label, we train a 3D MIDL model, MobileNetV3, to predict LNS metastasis. To better provide the LN position priors in MIDL, LN instances (with a short axis >4mm) were also segmented using an automatic LN detection algorithm and were added to the MIDL model as an auxiliary input. Five-fold cross-validation was conducted to evaluate the MIDL performance.

RESULTS

The MIDL model's performance is summarized in Table 1. The MIDL model incorporating an additional LN instance mask demonstrated a superior overall AUC of 0.7539, surpassing the model without the LN mask input by 2.93%. The specificity was evaluated at a threshold resulting in a recall of 0.7, and the best model outperformed the CT input model in terms of specificity by 2.11%. This highlights the value of including the LN position prior to the MIDL model. Notably, when a threshold was set to result in a specificity of 75%, the best MIDL model demonstrated a significantly higher recall compared to the previously reported clinical diagnostic recall (39.7% vs. 63.21%).

CONCLUSION

We developed a MIDL classification model to predict LNS metastasis using CT scans of 1200 patients. Our findings suggest that the MIDL model can substantially improve LNS metastasis prediction and has the potential to play an essential role in cancer staging, treatment planning, and prognostic analysis.

Anatomy-Guided Deep Learning Model for Accurate and Robust Gross Tumor Volume Segmentation in Lung Cancer Radiation Therapy

PURPOSE/OBJECTIVE(S)

In lung cancer radiation therapy, clinicians must outline the gross tumor volume (GTV) precisely on the planning computed tomography (pCT) for accurate radiation dose delivery. However, due to the limited contrast between tumor and normal tissues in lung parenchyma, accurate delineation of tumor boundaries is difficult leading to large inter-observer variation. In this study, we develop an anatomy-guided lung GTV deep segmentation model using a training cohort of multi-center datasets. The quantitative segmentation performance is evaluated on an independent dataset, where the inter-observer delineation variation is also assessed.

MATERIALS/METHODS

We collected and curated four publicly available lung datasets with GTV annotations (Lung-PET-CT-Dx, LIDC-IDRI, NSCLC-Radiogenomics and RIDER-CT) for deep learning model development. A total of 871 CT scans of patients, who were diagnosed with T1-T4 NSCLC, were available for training after data curation. The GTV annotations of primary tumor were examined and edited by two experienced radiation oncologists following the RTOG 1106 protocol. An anatomy-guided deep learning model was proposed, which consisted two deep networks. The first deep network used CT scan as input and segmented 4 anatomic organs (airway, heart, pulmonary artery and pulmonary vein), while the second deep network took both CT scan and these pre-segmented 4 organs as input and segmented the lung GTV. With the help of anatomic priors from 4 pre-segmented organs, the second deep network could more easily locate the GTV. We used nnUNet as the deep segmentation network. For evaluation, we used NSCLC-Radiomics as the testing dataset, which contains 20 CT scans each annotated by 5 radiation oncologists. The auto-segmented GTV were compared against each of the manual GTV reference. Inter-observer variation was also assessed using the 5 manual GTV references.

RESULTS

The proposed anatomic-guided lung GTV segmentation model achieved a mean Dice score of 82.4% and 95% Hausdorff distance (HD95) of 6.9mm when averaged cross 20 patients and 5 GTV references (Table 1), which outperformed the basic deep GTV segmentation model by markedly reducing 19.4% HD95 error. The performance of proposed model was also comparable to the inter-observer variation (Dice score: 82.4% vs. 81.9%, HD95 6.9 vs. 6.4mm), indicating that our model had similar reproducibility as human observers.

CONCLUSION

We developed and tested an anatomy-guided deep learning model for segmenting GTV in NSCLC patients. The model achieves high quantitative segmentation performance, which is comparable to the human observer variation. It can be potentially used in radiotherapy practice to improve GTV delineation consistency and reduce workloads of radiation oncologists.

Comparison of the diagnostic efficacy of mathematical models in distinguishing ultrasound imaging of breast nodules

This study compared the diagnostic efficiency of benign and malignant breast nodules using ultrasonographic characteristics coupled with several machine-learning models, including logistic regression (Logistics), partial least squares discriminant analysis (PLS-DA), linear support vector machine (Linear SVM), linear discriminant analysis (LDA), K-nearest neighbor (KNN), artificial neural network (ANN) and random forest (RF). The clinical information and ultrasonographic characteristics of 926 female patients undergoing breast nodule surgery were collected and their relationships were analyzed using Pearson's correlation. The stepwise regression method was used for variable selection and the Monte Carlo cross-validation method was used to randomly divide these nodule cases into training and prediction sets. Our results showed that six independent variables could be used for building models, including age, background echotexture, shape, calcification, resistance index, and axillary lymph node. In the prediction set, Linear SVM had the highest diagnosis rate of benign nodules (0.881), and Logistics, ANN and LDA had the highest diagnosis rate of malignant nodules (0.910~0.912). The area under the ROC curve (AUC) of Linear SVM was the highest (0.890), followed by ANN (0.883), LDA (0.880), Logistics (0.878), RF (0.874), PLS-DA (0.866), and KNN (0.855), all of which were better than that of individual variances. On the whole, the diagnostic efficacy of Linear SVM was better than other methods.

Strong Constraints on Jet Quenching in Centrality-Dependent p+Pb Collisions at 5.02 TeV from ATLAS

Jet quenching is the process of color-charged partons losing energy via interactions with quark-gluon plasma droplets created in heavy-ion collisions. The collective expansion of such droplets is well described by viscous hydrodynamics. Similar evidence of collectivity is consistently observed in smaller collision systems, including pp and p+Pb collisions. In contrast, while jet quenching is observed in Pb+Pb collisions, no evidence has been found in these small systems to date, raising fundamental questions about the nature of the system created in these collisions. The ATLAS experiment at the Large Hadron Collider has measured the yield of charged hadrons correlated with reconstructed jets in 0.36  nb^{-1} of p+Pb and 3.6  pb^{-1} of pp collisions at 5.02 TeV. The yields of charged hadrons with p_{T}^{ch}>0.5  GeV near and opposite in azimuth to jets with p_{T}^{jet}>30 or 60 GeV, and the ratios of these yields between p+Pb and pp collisions, I_{pPb}, are reported. The collision centrality of p+Pb events is categorized by the energy deposited by forward neutrons from the struck nucleus. The I_{pPb} values are consistent with unity within a few percent for hadrons with p_{T}^{ch}>4  GeV at all centralities. These data provide new, strong constraints that preclude almost any parton energy loss in central p+Pb collisions.

Search for Heavy Neutral Leptons in Decays of W Bosons Using a Dilepton Displaced Vertex in sqrt[s]=13 TeV pp Collisions with the ATLAS Detector

A search for a long-lived, heavy neutral lepton (N) in 139  fb^{-1} of sqrt[s]=13  TeV pp collision data collected by the ATLAS detector at the Large Hadron Collider is reported. The N is produced via W→Nμ or W→Ne and decays into two charged leptons and a neutrino, forming a displaced vertex. The N mass is used to discriminate between signal and background. No signal is observed, and limits are set on the squared mixing parameters of the N with the left-handed neutrino states for the N mass range 3  GeV Collapse

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Test of CP Invariance in Higgs Boson Vector-Boson-Fusion Production Using the H→γγ Channel with the ATLAS Detector

A test of CP invariance in Higgs boson production via vector-boson fusion has been performed in the H→γγ channel using 139  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV collected by the ATLAS detector at the LHC. The optimal observable method is used to probe the CP structure of interactions between the Higgs boson and electroweak gauge bosons, as described by an effective field theory. No sign of CP violation is observed in the data. Constraints are set on the parameters describing the strength of the CP-odd component in the coupling between the Higgs boson and the electroweak gauge bosons in two effective field theory bases: d[over ˜] in the HISZ basis and c_{HW[over ˜]} in the Warsaw basis. The results presented are the most stringent constraints on CP violation in the coupling between Higgs and weak bosons. The 95% C.L. constraint on d[over ˜] is derived for the first time and the 95% C.L. constraint on c_{HW[over ˜]} has been improved by a factor of 5 compared to the previous measurement.

Association between time in range 70-180 mg/dl in early stage and severity with in patients acute pancreatitis

BACKGROUND

It is not well understood whether glucose control in the early stage of acute pancreatitis(AP) is related to outcome. This study aimed to investigate the association between blood glucose time in range (TIR) of 70-180 mg/dL in the first 72 h(h) on admission and the progression of AP.

METHODS

Individuals admitted with AP to the Gastroenterology Department of the Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University between January 2017 and December 2021 were included and retrospectively evaluated. The percentage of TIR between 70 and 180 mg/dL in the first 72 h was calculated. According to the progress of AP at discharge, patients were divided into mild pancreatitis(MAP), and moderately severe acute pancreatitis (MSAP), or severe acute pancreatitis (SAP) groups. We examined the association between TIR or TIR ≥ 70% and AP severity using logistic regression models stratified by a glycosylated hemoglobin (HbA1c) level of 6.5%. Receiver operating characteristic (ROC) curves were generated to assess the ability of the TIR to predict MSAP or SAP.

RESULTS

A total of 298 individuals were included, of whom 35 developed MSAP or SAP. Logistic regression analyses indicated that TIR was independently associated with the incidence of more serious AP (odds ratio [OR] = 0.962, 95% CI = 0.941-0.983, p = 0.001). This association remained significant in individuals with HbA1c levels ≤ 6.5% (OR = 0.928, 95% CI = 0.888-0.969, p = 0.001). A TIR ≥ 70% was independently associated with reduced severity only in people with well-antecedent controls (OR = 0.238; 95% CI = 0.071-0.802; p = 0.020). TIR was not powerful enough to predict the severity of AP in both patients with poor antecedent glucose control (AUC = 0.641) or with HbA1c < 6.5% (AUC = 0.668).

CONCLUSIONS

TIR was independently associated with severity in patients with AP, particularly those with good antecedent glucose control.

An integrated radiomics nomogram based on conventional ultrasound improves discriminability between fibroadenoma and pure mucinous carcinoma in breast

Objective

To evaluate the ability of integrated radiomics nomogram based on ultrasound images to distinguish between breast fibroadenoma (FA) and pure mucinous carcinoma (P-MC).

Methods

One hundred seventy patients with FA or P-MC (120 in the training set and 50 in the test set) with definite pathological confirmation were retrospectively enrolled. Four hundred sixty-four radiomics features were extracted from conventional ultrasound (CUS) images, and radiomics score (Radscore) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Different models were developed by a support vector machine (SVM), and the diagnostic performance of the different models was assessed and validated. A comparison of the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) was performed to evaluate the incremental value of the different models.

Results

Finally, 11 radiomics features were selected, and then Radscore was developed based on them, which was higher in P-MC in both cohorts. In the test group, the clinic + CUS + radiomics (Clin + CUS + Radscore) model achieved a significantly higher area under the curve (AUC) value (AUC = 0.86, 95% CI, 0.733-0.942) when compared with the clinic + radiomics (Clin + Radscore) (AUC = 0.76, 95% CI, 0.618-0.869, P > 0.05), clinic + CUS (Clin + CUS) (AUC = 0.76, 95% CI, 0.618-0.869, P< 0.05), Clin (AUC = 0.74, 95% CI, 0.600-0.854, P< 0.05), and Radscore (AUC = 0.64, 95% CI, 0.492-0.771, P< 0.05) models, respectively. The calibration curve and DCA also suggested excellent clinical value of the combined nomogram.

Conclusion

The combined Clin + CUS + Radscore model may help improve the differentiation of FA from P-MC.

Association Between Intestinal Prevotella copri Abundance and Glycemic Fluctuation in Patients with Brittle Diabetes

Objective

Previous studies have demonstrated an association between gut microbiota composition and non-brittle type 2 diabetes (NBT2DM) pathogenesis. However, little is known about the correlation between the abundance of intestinal Prevotella copri and glycemic fluctuations in patients with brittle diabetes mellitus (BDM). In this context, we conducted a case-control study of BDM patients and patients with NBT2DM, aiming to determine and analyze the relationship between the abundance of intestinal Prevotella copri and glycemic fluctuations in patients with BDM.

Research Design and methods

We performed a metagenomic analysis of the gut microbiome obtained from fecal samples of 10 BDM patients, and compared their microbial composition and function to NBT2DM patients (1:1 ratio). Then further collected data including age, sex, BMI, glycated hemoglobin (HbA1c), blood lipids, and alpha diversity of the gut microbiota, which were comparable between the BDM and NBT2DM patients by t-test.

Results

A significant difference existed in the beta diversity of the gut microbiota between the two groups (PCoA, R² = 0.254, P = 0.0001). The phylum-level abundance of Bacteroidetes in the gut microbiota of the BDM patients was significantly lower, by 24.9% (P = 0.001), than that of the NBT2DM patients. At the gene level, the abundance of Prevotella copri was obviously reduced, Correlation analysis showed that the Prevotella copri abundance was inversely correlated to the standard deviation of blood glucose (SDBG) (r = -0.477, P = 0.034). Quantitative PCR confirmed that the abundance of Prevotella copri in the BDM patients in the validation cohort was significantly lower than that in NBT2DM patients, and was negatively correlated with SDBG (r = -0.318, P = 0.043). Glycemic variability in BDM was inversely correlated with the abundance of intestinal Prevotella copri.

Conclusion

The decreased abundance of Prevotella copri in patients with BDM may be associated with glycemic fluctuation.

The role of ultrasound quantitative parameters in the assessment of acute radiodermatitis after breast-conserving surgery

This study aimed to assess the severity of acute radiodermatitis (ARD) by ultrasound quantitative parameters and to try to identify the influencing factors of skin toxicity. A total of 55 patients who underwent radiotherapy after unilateral breast-conserving surgery (BCS) were included in the study. The irradiated side of the breast was used as the research object and the quantitative ultrasound parameters (skin thickness, shear wave elasticity) were evaluated before radiotherapy, every week during radiotherapy. Two weeks after radiotherapy, the patients were divided into two groups, according to the World Health Organization scoring standard: mild (0-2 grade) and severe (3-4 grade). The differences in the parameters between the groups and the changes during radiotherapy were compared, and the relationship between these parameters and the severity of ARD was analyzed. In addition, some clinical factors that may affect ARD were also included in our study. Ninety-eight percent of patients developed different degrees of ARD, and Group 2 accounted for ~31%. At the end of 5 weeks of radiotherapy, the difference in thickness between the two groups was statistically significant (P < 0.05). There was no significant change in the elastic modulus of breast skin between the two groups (P > 0.05). Body mass index >25 kg/m2, breast thickness ≥18 mm, skin basic elastic modulus <23 kPa and skin thickness increment >0.3 mm were considered to be associated with severe skin reactions (P < 0.05). Ultrasound can be a useful tool for the non-invasive and objective assessment of skin changes during radiotherapy, documenting quantitative changes in the skin of breast cancer patients following BCS undergoing radiotherapy.

Quantitative evaluation of gastrocnemius medialis mass in patients with chronic heart failure by gray-scale ultrasound and shear wave elastography

Objective

To assess the usefulness of gray-scale ultrasound (US) and shear wave elastography (SWE) in assessing the condition of the skeletal muscles in patients with chronic heart failure (CHF).

Methods

We prospectively compared 20 patients with clinically diagnosed CHF and a control population of 20 normal volunteers. The gastrocnemius medialis (GM) of each individual in the rest and the contraction position was assessed using gray-scale US and SWE. The quantitative US parameters including the fascicle length (FL), pinnation angle (PA), echo intensity (EI), and Young's modulus of the muscle were measured.

Results

In the CHF group compared with the control group, in the rest position, there was a significant difference in EI, PA, and FL of the GM (P &lt; 0.001), but no statistically significant difference in Young's modulus values (P &gt; 0.05); however, in the contraction position, all parameters were statistically different between the two groups (P &lt; 0.001). In the different subgroups of the CHF group grouped according to New York Heart Association staging (NYHA) or left ventricular ejection fraction (LVEF), there were no significant differences in ultrasound parameters in the rest position. However, during the contraction of GM, the smaller the FL and Young's modulus, the larger the PA and EI with the increase of NYHA grade or the decrease of LVEF (P &lt; 0.001).

Conclusion

The gray-scale US and SWE can provide an objective assessment of skeletal muscle status for CHF patients and are expected to be used to guide their early rehabilitation training and improve their prognosis.

Comparison of an online versus conventional multidisciplinary collaborative weight loss programme in type 2 diabetes mellitus: A randomized controlled trial

AIM

The aim of this study was to examine the effect of an online multidisciplinary weight loss management programme.

METHODS

Between July 2016 and July 2017 this randomized controlled trial recruited patients in Nanjing, China who were living with type 2 diabetes mellitus and who were obese or overweight and randomized them to online versus conventional groups. All participants were managed by a multidisciplinary team. The experimental group was managed using the Why Wait WeChat Platform for Weight Reduction Management.

RESULTS

There were 55 and 52 participants in the online and conventional groups, respectively. The decreases in fasting blood glucose (-4.26 vs. -2.99 mmol/L), 2-h postprandial blood glucose (-4.48 vs. -2.68 mmol/L) and glycated haemoglobin (-22.11 vs. -6.21 mmol/mol) were more pronounced in the online compared to conventional group (all P < 0.05). After the intervention, self-management ability parameters, including diet control, foot care and total score, were improved in the online group compared with the conventional group, as well as all indexes of quality of life (all P < 0.05).

CONCLUSION

The online multidisciplinary weight loss management programme improved blood glucose in obese or overweight patients living with type 2 diabetes mellitus. Self-management ability parameters (including diet control, foot care and total score) and quality of life were improved in the online group compared with the conventional group.

Serum Pentosidine is Associated with Cardiac Dysfunction and Atherosclerosis in T2DM

AIM

The purpose of this paper is to investigate the relationship between serum pentosidine levels and cardiac function and vascular disease in diabetic patients, and to provide a new reference indicator for the early detection of diabetic cardiovascular complications.

MATERIALS AND METHODS

This was a cross-sectional study. One hundred and twenty-two patients with type 2 diabetes were grouped by LVEF quartiles to compare the differences between their clinical data and serum pentosidine levels. Also, the correlation between serum pentosidine and clinical indicators was assessed. The effect of serum pentosidine on cardiac function and vascular stiffness was analyzed by multiple stepwise regression.

RESULTS

Serum pentosidine levels were higher in patients with LVEF ≤57%. Serum pentosidine levels were positively correlated with waist-to-hip ratio, hemoglobin, AIP, baPWV, LVESD, and ARD, and negatively correlated with LVEF. Low serum pentosidine was associated with increased LVESD; high pentosidine was significantly associated with increased ARD, high AIP and high baPWV.

CONCLUSION

The results suggest that serum pentosidine, a member of AGEs, may reflect cardiac remodeling and dysfunction as well as atherosclerosis.

Development and validation of nomograms by radiomic features on ultrasound imaging for predicting overall survival in patients with primary nodal diffuse large B-cell lymphoma

Objectives

To develop and validate a nomogram to predict the overall survival (OS) of patients with primary nodal diffuse large B-cell lymphoma(N-DLBCL) based on radiomic features and clinical features.

Materials and methods

A retrospective analysis was performed on 145 patients confirmed with N-DLBCL and they were randomly assigned to training set(n=78), internal validation set(n=33), external validation set(n=34). First, a clinical model (model 1) was established according to clinical features and ultrasound (US) results. Then, based on the radiomics features extracted from conventional ultrasound images, a radiomic signature was constructed (model 2), and the radiomics score (Rad-Score) was calculated. Finally, a comprehensive model was established (model 3) combined with Rad-score and clinical features. Receiver operating characteristic (ROC) curves were employed to evaluate the performance of model 1, model 2 and model 3. Based on model 3, we plotted a nomogram. Calibration curves were used to test the effectiveness of the nomogram, and decision curve analysis (DCA) was used to asset the nomogram in clinical use.

Results

According to multivariate analysis, 3 clinical features and Rad-score were finally selected to construct the model 3, which showed better predictive value for OS in patients with N-DLBCL than mode 1 and model 2 in training (AUC,0. 891 vs. 0.779 vs.0.756), internal validation (AUC, 0.868 vs. 0.713, vs.0.756) and external validation (AUC, 914 vs. 0.866, vs.0.789) sets. Decision curve analysis demonstrated that the nomogram based on model 3 was more clinically useful than the other two models.

Conclusion

The developed nomogram is a useful tool for precisely analyzing the prognosis of N-DLBCL patients, which could help clinicians in making personalized survival predictions and assessing individualized clinical options.

Higher BMI and lower femoral neck strength in males with type 2 diabetes mellitus and normal bone mineral density

BACKGROUND

Type 2 diabetes mellitus (T2DM) and osteoporosis are two age-associated diseases. Body mass index (BMI) is positively associated with osteoporosis or osteopenia in T2DM population. Bone mineral density does not necessarily reflect the alterations in bone microarchitecture. Our aims were to investigate the relationship between BMI and femoral neck strength in males with T2DM and normal range of bone mineral density (BMD).

METHODS

This study enrolled 115 males (median age 53.3 years) with T2DM and normal BMD. Femoral neck strength indexes, including compression strength index (CSI), bending strength index (BSI), impact strength index (ISI), were calculated by parameters generated from Dual-energy X-ray absorptiometry software. Pearson correlation analysis was performed to evaluate the relationships between BMI and femoral neck strength variables.

RESULTS

Compared with T2DM-normal weight group, T2DM-overweight group and T2DM-obesity group had a higher femur neck and total femur BMDs. Cross sectional moment of inertia (CSMI), cross sectional area (CSA), section modulus (SM) were significantly higher (all p<0.05), and buckling ratio (BR) (6.35±2.08 vs 7.18±1.71) was lower in T2DM-obesity group than in T2DM-normal weight group. Compared with T2DM-normal weight group, CSI (all p<0.001), BSI (all p<0.001), ISI (all p<0.001) were significantly reduced in T2DM-obesity and T2DM-overweight groups. Pearson correlation analysis indicated that BMI was negatively correlated with CSI (r= - 0.457, p<0.001), BSI(r = -0.397, p<0.001), ISI (r = - 0.414, p<0.001).

CONCLUSIONS

Higher BMI is associated with lower femoral neck strength in males with T2DM and normal BMD. It implies that femoral neck fracture risk increases in obese and diabetic males, despite their high bone density.