Is polyethylene glycol loxenatide 100 μg the preferred glucagon-like peptide-1 receptor agonist for type 2 diabetes mellitus? A meta-analysis and trial sequential analysis

OBJECTIVE

This study aimed to systematically evaluate the efficacy, safety and optimal dose of polyethylene glycol loxenatide (PEX168) for treating type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

Clinical trials of PEX168 for T2DM were identified in 8 databases, with a build time limit of January 2023. Included studies were subjected to meta-analysis and trial sequential analysis (TSA).

RESULTS

On the efficacy endpoint, the meta-analysis showed that PEX168 100 μg significantly reduced 0.86% glycated hemoglobin type A1c (HbA1c) (MD -0.86, 95% CI -1.02 - -0.70,  p<0.00001), 1.11 mmol/L fasting plasma glucose (FPG) (MD -1.11, 95% CI -1.49 - -0.74, p<0.00001) and 1.91 mmol/L 2h postprandial glucose (PPG) (MD -1.91, 95% CI -3.35 - -0.46, p=0.01) compared with placebo. The TSA showed that all these benefits were conclusive. On safety endpoints, total adverse events (AEs), gastrointestinal (GI) AEs, serious AEs, and hypoglycemia were comparable to placebo for PEX168 100 μg (p>0.05). In the dose comparison, the HbA1c, FPG, and 2h PPG of PEX168 200 μg were comparable to 100 μg (p>0.05), while GI AEs were significantly higher than 100 μg (RR=2.84, 95% CI 1.64-4.93,  p=0.0002).

CONCLUSIONS

PEX168 100 μg can significantly lower blood glucose and does not increase the risk of total AEs, GI AEs, and hypoglycemia, which may be a preferred glucagon-like peptide-1 receptor agonist for type 2 diabetes mellitus.

Loss of CD20 expression as a mechanism of resistance to mosunetuzumab in relapsed/refractory B-cell lymphomas

ABSTRACT

CD20 is an established therapeutic target in B-cell malignancies. The CD20 × CD3 bispecific antibody mosunetuzumab has significant efficacy in B-cell non-Hodgkin lymphomas (NHLs). Because target antigen loss is a recognized mechanism of resistance, we evaluated CD20 expression relative to clinical response in patients with relapsed and/or refractory NHL in the phase 1/2 GO29781 trial investigating mosunetuzumab monotherapy. CD20 was studied using immunohistochemistry (IHC), RNA sequencing, and whole-exome sequencing performed centrally in biopsy specimens collected before treatment at predose, during treatment, or upon progression. Before treatment, most patients exhibited a high proportion of tumor cells expressing CD20; however, in 16 of 293 patients (5.5%) the proportion was <10%. Analyses of paired biopsy specimens from patients on treatment revealed that CD20 levels were maintained in 29 of 30 patients (97%) vs at progression, where CD20 loss was observed in 11 of 32 patients (34%). Reduced transcription or acquisition of truncating mutations explained most but not all cases of CD20 loss. In vitro modeling confirmed the effects of CD20 variants identified in clinical samples on reduction of CD20 expression and missense mutations in the extracellular domain that could block mosunetuzumab binding. This study expands the knowledge about the occurrence of target antigen loss after anti-CD20 therapeutics to include CD20-targeting bispecific antibodies and elucidates mechanisms of reduced CD20 expression at disease progression that may be generalizable to other anti-CD20 targeting agents. These results also confirm the utility of readily available IHC staining for CD20 as a tool to inform clinical decisions. This trial was registered at www.ClinicalTrials.gov as #NCT02500407.

[Play the "combo fist" in the diagnosis and treatment of advanced gastric cancer]

The incidence of gastric cancer ranks fifth among malignant tumors worldwide, with the fourth highest mortality rate. A noteworthy characteristic of our country is the high prevalence of advanced-stage patients of approximately 40%. Advanced-stage gastric cancer carries an unfavorable prognosis with median survival of around one year. Diagnosis methods for advanced-stage gastric cancer (such as laparoscopic exploration, molecular profiling, and artificial intelligence) are still being continuously improved, while chemotherapy remains the primary treatment. With the rapid development of medical science, the role of surgical intervention in advanced-stage gastric cancer is becoming increasingly prominent. Therefore, as gastric tumor surgeons, we should consider how to use a combination of treatments, including surgery, chemotherapy, targeted therapy, immunotherapy, and interventional therapy, based on different pathological stages and the heterogeneity of tumors. With a multidisciplinary approach involving experts from various fields, we can collectively improve the survival rate and quality of life for advanced-stage patients. This article provides a brief overview of the current advances in the diagnosis and treatment of advanced-stage gastric cancer, and discusses therapeutic decision primarily from the perspective of surgeons.

Germline cell de novo mutations and potential effects of inflammation on germline cell genome stability

Uncontrolled pathogenic genome mutations in germline cells might impair adult fertility, lead to birth defects or even affect the adaptability of a species. Understanding the sources of DNA damage, as well as the features of damage response in germline cells are the overarching tasks to reduce the mutations in germline cells. With the accumulation of human genome data and genetic reports, genome variants formed in germline cells are being extensively explored. However, the sources of DNA damage, the damage repair mechanisms, and the effects of DNA damage or mutations on the development of germline cells are still unclear. Besides exogenous triggers of DNA damage such as irradiation and genotoxic chemicals, endogenous exposure to inflammation may also contribute to the genome instability of germline cells. In this review, we summarized the features of de novo mutations and the specific DNA damage responses in germline cells and explored the possible roles of inflammation on the genome stability of germline cells.

Lactiplantibacillus plantarum and faecal microbiota transplantation can improve colitis in mice by affecting gut microbiota and metabolomics

Gut microbiota may have therapeutic effects on inflammatory bowel disease (IBD). Regulating intestinal microbiota through Lactiplantibacillus plantarum (L. plantarum) and faecal microbiota transplantation (FMT) is a novel approach to treating IBD. This study aimed to explore the effect of L. plantarum and FMT pretreatment in alleviating colitis in mice. Five groups of mice (n = 6 per group) were included: CON group, DSS group (dextran sodium sulphate-induced colitis mice), LP-DSS pretreatment group (colitis mice were given strain L. plantarum and 5% DSS), DSS-FMT group (mice pretreated with faecal microbiota transplantation were given 5% DSS), and LP-FMT pretreatment group (mice pretreated with faecal microbiota transplantation and L. plantarum were given 5% DSS). Serum metabolites and intestinal microbiota were analysed by 16S rRNA sequencing liquid chromatography-mass spectrometry (LC-MS). The results demonstrated that L. plantarum and FMT improved gut microbiota in mice by increasing Firmicutes and decreasing the Bacteroidetes. In the serum metabolomics analysis, there were 11 differential metabolites in the DSS-FMT and LP-FMT pretreatment groups, and these differential metabolites were mainly glycerophospholipids and sphingolipids. It is worth noting that Lachnospira and Lactobacillus were positively associated with 8 differential metabolites. These results suggest that L. plantarum and FMT can regulate intestinal microorganisms and serum metabolomics to alleviate inflammation.

SDA-Net: Self-distillation driven deformable attentive aggregation network for thyroid nodule identification in ultrasound images

Early detection and accurate identification of thyroid nodules are the major challenges in controlling and treating thyroid cancer that can be difficult even for expert physicians. Currently, many computer-aided diagnosis (CAD) systems have been developed to assist this clinical process. However, most of these systems are unable to well capture geometrically diverse thyroid nodule representations from ultrasound images with subtle and various characteristic differences, resulting in suboptimal diagnosis and lack of clinical interpretability, which may affect their credibility in the clinic. In this context, a novel end-to-end network equipped with a deformable attention network and a distillation-driven interaction aggregation module (DIAM) is developed for thyroid nodule identification. The deformable attention network learns to identify discriminative features of nodules under the guidance of the deformable attention module (DAM) and an online class activation mapping (CAM) mechanism and suggests the location of diagnostic features to provide interpretable predictions. DIAM is designed to take advantage of the complementarities of adjacent layers, thus enhancing the representation capabilities of aggregated features; driven by an efficient self-distillation mechanism, the identification process is complemented with more multi-scale semantic information to calibrate the diagnosis results. Experimental results on a large dataset with varying nodule appearances show that the proposed network can achieve competitive performance in nodule diagnosis and provide interpretability suitable for clinical needs.

Performance Optimization and Fault-Tolerance of Highly Dynamic Systems Via Q-Learning With an Incrementally Attached Controller Gain System

High-performance and reliable control of systems that are highly dynamic and open-loop unstable is challenging but of considerable practical interest. Thus, this article investigates the performance optimization and fault tolerance of highly dynamic systems. First, an incremental control structure is proposed, where a controller gain system is attached to the predesigned controller, and by reconfiguring the controller gain system, the performance can be equivalently optimized as configuring the predesigned one. The incremental attachment of the controller gain system does not modify the existing control system, and it can be easily attached via various communication channels. Second, a structure integrating fault-tolerance strategy and hardware redundancy is proposed. Under this structure, command fusion and fault-tolerance strategies are developed where the control commands from different control units are optimally fused, and each control unit can be reconfigured w.r.t. the performance of the other ones. Furthermore, Q -learning algorithms are developed to realize the proposed structures and strategies in real-time model-freely. As such, varying operational conditions of the highly dynamic system can be tackled. Finally, the proposed structures and algorithms are validated case by case to show their effectiveness.

Impacts of Combining Pulsed Low Dose Rate Radiotherapy (PLDR) and Anti-PD-1 Antibody on Tumor Growth and Its Mechanism for Lung Cancer in Mice

PURPOSE/OBJECTIVE(S)

As an emerging anti-tumor strategy, Immunotherapies has been approved for the treatment of a variety of tumors. Recent data suggest that the efficacy of radiotherapy in various cancers can be augmented when combined with immune checkpoint blockade. Then, pulsed low dose rate radiotherapy (PLDR) is a new radiotherapy segmentation method. Therefore, this study investigated the inhibitory effect of PLDR combined with anti-PD-1 antibody on lung cancer in mice and its impact on tumor immune microenvironment.

MATERIALS/METHODS

By transplanting murine LLC cells into the right leg of C57BL/6 mice with immune activity, a transplanted subcutaneous tumor model was established. The mice were randomly divided into five groups: control, conventional radiotherapy (RT)±anti-PD-1 antibody (mAb),PLDR±anti-PD-1 antibody (mAb). RT was delivered as a dose of 5 × 2 Gy whereas PLDR involved delivering a dose of 2 Gy as 10 pulses of 0.2 Gy, each 3 minutes apart and lasting for 5 days. Anti-PD-1 antibody and isotype control were administered intraperitoneally once every three days at a dose of 5mg/kg, three times in total. The tumor, blood and tumor-draining lymph nodes (TDLNs) were harvested after treatment, and a single cell suspension was prepared for flow cytometry to analyze the changes in the immune microenvironment of the tumor tissue, the expression of PD-L1. PD-1 and the activated systemic immune response; Finally, this study explored a mechanism able to explain the observed synergy of combined therapy.

RESULTS

PLDR combined with anti-PD-1 antibody can better inhibit the growth of tumor than RT,PLDR and RT combined group. Survival analysis demonstrated a statistically significant advantage for PLDR+anti-PD-1 than other groups. Median survival with PLDR+anti-PD-1mAb was 63d compared with 54d with RT+anti-PD-1mAb,41d with RT and 40d with PLDR and 33 with control. Meanwhile both RT and PLDR induced up-regulation of PD-L1 expression on tumor surface and PD-1 expression on lymphocytes. Then, the frequency of CD4+,CD8+T cells were higher in the PLDR combined treatment group in tumor blood and draining lymph nodes, and synergistically reduce the local accumulation of tumor-infiltrating myeloid-derived suppressor cells (MDSCs) than others. Finally, the main reason for the better tumor inhibition effect of PLDR combined group is that it upgrades the number and activity of CD8+T cells in tumor.

CONCLUSION

PLDR combined with anti-PD-1 antibody can result in better tumor growth inhibition and significantly delay the survival time of mice, which was mainly through the cytotoxic T cell-dependent mechanism, meanwhile increasing the infiltration of CD4 + and CD8 +T-cells in tissues.

Analysis of prognostic factors for vocal fold leukoplakia based on 344 cases at a two-year follow up

OBJECTIVE

To evaluate risk factors for poor prognosis in vocal fold leukoplakia.

METHODS

Clinical data were collected for 344 patients with vocal fold leukoplakia who received surgical treatment in our otolaryngology department from October 2010 to June 2019. Univariate and multivariate logistic regression analyses of the relevant factors were conducted.

RESULTS

Among the 344 patients, 98 exhibited recurrence and 30 underwent a malignant change. Multivariate logistic regression analysis showed that size of the lesion (p = 0.03, odds ratio = 2.14), form of the lesion under white light (p < 0.001), surgical method (p < 0.001, odds ratio = 0.28) and pathological type (p < 0.001) were independent factors that affected the recurrence of vocal fold leukoplakia. In both univariate and multivariate analyses, the sole independent risk factor for malignant transformation of vocal fold leukoplakia was pathological type (p < 0.001).

CONCLUSION

The outlook for vocal fold leukoplakia depends on several clinical factors, especially pathological type. The more severe the pathological type, the more likely it is to recur or become cancerous.

Distributed Adaptive-Neural Finite-Time Consensus Control for Stochastic Nonlinear Multiagent Systems Subject to Saturated Inputs

In this article, the problem of distributed finite-time consensus control for a class of stochastic nonlinear multiagent systems (MASs) (with directed graph communication) in the presence of unknown dynamics of agents, stochastic perturbations, external disturbances (mismatched and matched), and input saturation nonlinearities is addressed and studied. By combining the backstepping control method, the command filter technique, a finite-time auxiliary system, and artificial neural networks, innovative control inputs are designed and proposed such that outputs of follower agents converge to the output of the leader agent within a finite time. Radial-basis function neural networks (RBFNNs) are employed to approximate unknown dynamics, stochastic perturbations, and external disturbances. To overcome the complexity explosion problem of the conventional backstepping method, a novel finite-time command filter approach is proposed. Then, to deal with the destructive effects of input saturation nonlinearities, the finite-time auxiliary system is designed and developed. By mathematical analysis, it is proven that the mentioned MAS (injected by the proposed control inputs) is semiglobally finite-time stable in probability (SGFSP) and all consensus tracking errors converge to a small neighborhood of the zero during a finite time. Finally, a numerical simulation onto a group of four single-link robot manipulators is carried out to illustrate the effectiveness of the suggested control scheme.

Mosunetuzumab monotherapy is active and tolerable in patients with relapsed/refractory diffuse large B-cell lymphoma

As part of a phase 1 or 2 study, this single-arm expansion cohort established the efficacy and safety of mosunetuzumab monotherapy in patients with relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) (received ≥2 previous lines of therapy). Intravenous mosunetuzumab was administered with cycle (C) 1 step-up dosing for cytokine release syndrome (CRS) mitigation: C1 day (D) 1: 1 mg; C1D8 2 mg; C1D15 and C2D1: 60 mg; C3 + D1: 30 mg. Hospitalization was not mandatory. Patients with complete response (CR) completed treatment after C8; those with partial response or stable disease continued treatment for a total of 17 cycles. The primary end point was CR rate (best response), assessed against a historical control CR rate (20%) by independent review facility. Eighty-eight patients (73.9% de novo DLBCL; 26.1% transformed follicular lymphoma) were enrolled; all had received previous anthracycline and anti-CD20 therapy. Overall response and CR rates were 42.0% (95% confidence interval [CI], 31.6-53.1) and 23.9% (95% CI, 15.4-34.1), respectively; CR rate did not reach statistical significance vs the historical control (P = .36). Median time to first response was 1.4 months. Median progression-free survival was 3.2 months (95% CI, 2.2-5.3). The CR rate in 26 patients who received previous chimeric antigen receptor T-cell (CAR-T) therapy was 12%. CRS was one of the most common adverse events (26.1% of patients); predominantly grade 1 to 2 and primarily in C1. Four patients (4.5%) discontinued mosunetuzumab owing to adverse events. Mosunetuzumab demonstrated notable efficacy and a manageable safety profile in patients with R/R DLBCL, including those previously treated with CAR-Ts. This trial was registered at www.clinicaltrials.gov as #NCT02500407.

Bibliometric analysis of intestinal microbiota in diabetic nephropathy

OBJECTIVE

The purpose of this study is to use bibliometrics to explore the research overview and research hotspots.

MATERIALS AND METHODS

The relevant literature on intestinal flora and diabetic nephropathy in the Web of Science Core Collection was sorted out, and VOSviewer, CiteSpace, Scimago Graphica and other software were used to conduct data visualization analysis on the number of publications, countries, institutions, journals, authors, keywords and citations.

RESULTS

A total of 124 relevant literatures were included. From 2015 to 2022, the number of published papers increased every year. The countries, institutions and journals that published the most articles in this field are China, Isfahan University Medical Science and Frontiers in Pharmacology. Liu Bicheng and Mirlohi Maryam are the authors with the most published articles in this field. The main keywords of research in this field are obesity, inflammation, oxidative stress, indoxyl sulfate, short-chain fatty acids (SCFAs) and Chinese herbal medicine.

CONCLUSIONS

This is the first bibliometric analysis of diabetic nephropathy and gut microbiota, reporting hot spots and emerging trends. Obesity, inflammation, oxidative stress, indoxyl sulfate, SCFAs and Chinese herbal medicine are the main keywords of current research, and SCFAs and Chinese herbal medicine may be the hotspots of future research.

Efficacy and safety of iguratimod combined with methylprednisolone for primary Sjögren's syndrome: a meta-analysis and trial sequential analysis

OBJECTIVE

The purpose of this study is to evaluate the combination of iguratimod (IGU) and methylprednisolone (MP) for the efficacy and safety of primary Sjögren's syndrome (pSS) by a meta-analysis and a trial sequential analysis (TSA).

MATERIALS AND METHODS

Clinical studies of IGU combined with MP for pSS were searched through eight databases. Revman 5.3 and TSA 0.9.5.10 Beta were used for the meta-analysis and TSA.

RESULTS

In terms of efficacy endpoints, compared with "HCQ+MP" group, "IGU+MP" group decreased erythrocyte sedimentation rate (ESR) [mean difference (MD)=-5.15, 95% confidence interval (CI)=(-7.37, -2.93), p<0.0001], immunoglobulin G (IgG) [MD=-3.38, 95% CI=(-4.13, -2.64), p<0.00001], immunoglobulin M (IgM) [MD=-0.64, 95% CI=(-1.19, -0.09), p=0.02], Immunoglobulin A (IgA) [MD=-1.16, 95% CI=(-1.92, -0.39), p=0.003], EULAR Sjögren's Syndrome Disease Activity Index (ESSDAI) [MD=-1.62, 95% CI=(-2.07, -1.17), p<0.0001], EULAR Sjögren's Syndrome Patient Reported Index (ESSPRI) [MD=-2.07, 95% CI=(-2.54, -1.59), p<0.0001], increase platelet (PLT) [MD=13.21, 95% CI=(9.77,16.65), p<0.00001], and improve Schirmer I test (SIT) [MD=1.86, 95% CI=(1.40, 2.32), p<0.0001]. TSA presented that these benefits observed with the current information volume were all conclusive, except for IgM. In terms of safety endpoints, the total adverse event rates (AEs), leucopenia, gastrointestinal (GI) AEs, skin diseases, and liver dysfunction of the "IGU+MP" group and the "HCQ+MP" group were comparable. And TSA indicated that the results need to be confirmed by additional studies. Harbord regression showed no publication bias (p=0.986).

CONCLUSIONS

IGU combined with MP effectively attenuates autoimmune responses (IgG, IgM, IgA), reduces clinical symptoms and disease activity (ESR, PLT, ESSPRI, ESSDAI), and improves the exocrine gland functional status (SIT) in patients with pSS. IGU combined with MP does not increase the risk of adverse events, which means that IGU combined with MP may be a safe and effective strategy for the treatment of pSS and has value for further research exploration.

Is tirzepatide 15 mg the preferred treatment strategy for type 2 diabetes? A meta-analysis and trial-sequence-analysis

OBJECTIVE

The study aims to evaluate tirzepatide's efficacy and safety in treating type 2 diabetes by meta-analysis and trial-sequential-analysis (TSA).

MATERIALS AND METHODS

Eight databases were searched for clinical trials on tirzepatide for type 2 diabetes with a time limit of November 2022. Revman5.3 and TSA 0.9.5.10 Beta were selected for meta-analysis and TSA.

RESULTS

Compared with placebo, the meta-analysis demonstrated that tirzepatide 15 mg reduced hemoglobin-type-A1C (HbA1c) (p<0.00001), fasting-serum-glucose (FSG) (p<0.00001), and weight (p<0.00001). Compared with insulin, tirzepatide 15 mg reduced HbA1c (p<0.00001), FSG (p<0.00007), and weight (p<0.00001). Compared with glucagon-like-peptide-1 receptor-agonist (GLP-1 RA), tirzepatide 15 mg reduced HbA1c (p=0.00004), FSG (p=0.001), and weight (p<0.00001). In safety endpoints, the meta-analysis revealed that adverse events (AEs) of placebo, insulin and GLP-1 RA were comparable to tirzepatide 15 mg. The total AEs (p=0.02) and gastrointestinal (GI) AEs (p=0.03) were higher in tirzepatide 15 mg than in the placebo, while hypoglycemia (<54 mg/dl) was comparable. The major adverse cardiovascular events-4 (MACE-4) (p=0.03) and hypoglycemia (<54 mg/dl) (p<0.00001) of tirzepatide 15 mg were lower when compared to insulin, while total AEs (p=0.03) were increased. Compared with GLP-1 RA, tirzepatide 15 mg was comparable in safety endpoints in total AEs and GI AEs, while hypoglycemia (<54 mg/dl) (p=0.04) was higher. TSA indicated that HgA1c, FSG, and weight benefits were conclusive. In safety endpoints, only MACE-4 and hypoglycemia (<54 mg/dl) of Tirzepatide 15 mg vs. Insulin were conclusive. Harbord regression of AEs suggested no evident publication bias (p=0.618).

CONCLUSIONS

Tirzepatide 15 mg reduced HbA1c and weight more effectively than placebo, insulin, and GLP-1 RA. Total AEs were higher than placebo and insulin but comparable to GLP-1 RA. Tirzepatide 15 mg is a kind of optimal strategy to treat type 2 diabetes. However, there is a need to focus on GI AEs.

Observer-Based Fault-Tolerant Finite-Time Control of Nonlinear Multiagent Systems

In this article, an adaptive neural containment control for a class of nonlinear multiagent systems considering actuator faults is introduced. By using the general approximation property of neural networks, a neuro-adaptive observer is designed to estimate unmeasured states. In addition, in order to reduce the computational burden, a novel event-triggered control law is designed. Furthermore, the finite-time performance function is presented to improve the transient and steady-state performance of the synchronization error. Utilizing the Lyapunov stability theory, it will be shown that the closed-loop system is cooperatively semiglobally uniformly ultimately bounded (CSGUUB), and the followers' outputs reach the convex hull constructed by the leaders. Moreover, it is shown that the containment errors are limited to the prescribed level in a finite time. Eventually, a simulation example is presented to corroborate the capability of the proposed scheme.

The Impact of Psychiatric Diagnoses on Patient-reported Satisfaction and Quality of Life in Postmastectomy Breast Reconstruction

OBJECTIVE

The purpose of this study was to determine the prevalence of psychiatric diagnoses among a sample of breast reconstruction patients and measure the association between these diagnoses and reconstruction-related, patient-reported outcomes.

BACKGROUND

The impact of psychiatric disorders in conjunction with breast cancer diagnosis, treatment, and reconstruction have the potential to cause significant patient distress but remains not well understood.

METHODS

A retrospective review of postmastectomy breast reconstruction patients from 2007 to 2018 at Memorial Sloan Kettering Cancer Center was conducted. Patient demographics, comorbidities, cancer characteristics, psychiatric diagnoses, and BREAST-Q Reconstruction Module scores (measuring satisfaction with breast, well-being of the chest, psychosocial, and sexual well-being) at postoperative years 1 to 3 were examined. Mixed-effects models and cross-sectional linear regressions were conducted to measure the effect of psychiatric diagnostic class type and number on scores.

RESULTS

Of 7414 total patients, 50.1% had at least 1 psychiatric diagnosis. Patients with any psychiatric diagnoses before reconstruction had significantly lower BREAST-Q scores for all domains at all time points. Anxiety (50%) and depression (27.6%) disorders were the most prevalent and had the greatest impact on BREAST-Q scores. Patients with a greater number of psychiatric diagnostic classes had significantly worse patient-reported outcomes compared with patients with no psychiatric diagnosis. Psychosocial (β: -7.29; 95% confidence interval: -8.67, -5.91), and sexual well-being (β: -7.99; 95% confidence interval: -9.57, -6.40) were most sensitive to the impact of psychiatric diagnoses.

CONCLUSIONS

Mental health status is associated with psychosocial and sexual well-being after breast reconstruction surgery as measured with the BREAST-Q. Future research will need to determine what interventions (eg, screening, early referral) can help improve outcomes for breast cancer patients with psychiatric disorders undergoing breast reconstruction.

Breast Surgical Oncology Epidemiologic Research: A Guide and Comparison of Four National Databases

BACKGROUND

National databases are a rich source of epidemiologic data for breast surgical oncology research. However, these databases differ in the demographic, surgical, and oncologic variables provided. This study aimed to compare the strengths and limitations of four national databases in the context of breast surgical oncology research.

METHODS

The study comprised a descriptive analysis of four national databases (the National Surgical Quality Improvement Program [NSQIP], the Nationwide Inpatient Sample [NIS], the Surveillance, Epidemiology and End Results [SEER] program, and the National Cancer Database [NCDB]) to assess their strengths and limitations in the context of breast surgical oncology. The study assessed the data available in each database for female patients with a breast cancer diagnosis between 2007 and 2017, and compared patient age, ethnicity, and race distributions.

RESULTS

Data from 3.9 million female patients were examined, with most patients being between 60 and 69 years of age, non-Hispanic, and white. Age, ethnicity, and race distributions were similar in the databases. The NSQIP includes data on operative details, comorbidities, and postoperative outcomes. The NIS provides health services and inpatient utilization information, but does not evaluate outpatient procedures. The SEER program provides population-based oncologic detail including stage, histology, and neoadjuvant/adjuvant treatment. The NCDB offers hospital-based oncologic information and the largest population in the study period, with approximately 2.5 million breast cancer patients.

CONCLUSION

Epidemiologic datasets offer tremendous potential for the examination of oncologic breast surgery, with each database providing unique data useful for addressing different epidemiologic questions. Understanding the strengths and limitations of each database creates a more efficient and productive research environment.

Systems-based digital twins to help characterize clinical dose-response and propose predictive biomarkers in a Phase I study of bispecific antibody, mosunetuzumab, in NHL

Phase I oncology clinical trials often comprise a limited number of patients representing different disease subtypes who are divided into cohorts receiving treatment(s) at different dosing levels and schedules. Here, we leverage a previously developed quantitative systems pharmacology model of the anti-CD20/CD3 T-cell engaging bispecific antibody, mosunetuzumab, to account for different dosing regimens and patient heterogeneity in the phase I study to inform clinical dose/exposure-response relationships and to identify biological determinants of clinical response. We developed a novel workflow to generate digital twins for each patient, which together form a virtual population (VPOP) that represented variability in biological, pharmacological, and tumor-related parameters from the phase I trial. Simulations based on the VPOP predict that an increase in mosunetuzumab exposure increases the proportion of digital twins with at least a 50% reduction in tumor size by day 42. Simulations also predict a left-shift of the exposure-response in patients diagnosed with indolent compared to aggressive non-Hodgkin's lymphoma (NHL) subtype; this increased sensitivity in indolent NHL was attributed to the lower inferred values of tumor proliferation rate and baseline T-cell infiltration in the corresponding digital twins. Notably, the inferred digital twin parameters from clinical responders and nonresponders show that the potential biological difference that can influence response include tumor parameters (tumor size, proliferation rate, and baseline T-cell infiltration) and parameters defining the effect of mosunetuzumab on T-cell activation and B-cell killing. Finally, the model simulations suggest intratumor expansion of pre-existing T-cells, rather than an influx of systemically expanded T-cells, underlies the antitumor activity of mosunetuzumab.

Analysis of factors affecting testicular spermatogenesis capacity by using the tissue transcriptome data from GTEx

In human, endo- or exogeneous factors might alter the cellular composition, the endocrine and inflammatory micro-environments and the metabolic balance in testis. These factors will further impair the testicular spermatogenesis capacity and alter the transcriptome of testis. Conversely, it should be possible that the alteration of the transcriptomes in testes be used as an indicator to evaluate the testicular spermatogenesis capacity and to predict the causing factors. In this study, using the transcriptome data of human testes and whole blood which were collected by the genotype-tissue expression project (GTEx), we analyzed the transcriptome differences in human testes and explored those factors that affecting spermatogenesis. As a result, testes were clustered into five clusters according to their transcriptomic features, and each cluster of testes was evaluated as having different spermatogenesis capacity. High rank genes of each cluster and the differentially expressed genes in lower functional testes were analyzed. Transcripts in whole blood which may be associated with testis function were also analyzed by the correlation test. As a result, factors such as immune response, oxygen transport, thyrotropin, prostaglandin and tridecapeptide neurotensin were found associated with spermatogenesis. These results revealed multiple clues about the spermatogenesis regulation in testis and provided potential targets to improve the fertility of men in clinic.

Epigallocatechin gallate improves the quality of diabetic oocytes

BACKGROUND

Maternal diabetes compromises the quality and developmental potential of oocytes. Therefore, it is important to study how to ameliorate the adverse effects of diabetes on oocyte quality. Epigallocatechin gallate (EGCG) has a variety of physiological activities, including anti-inflammatory, antioxidant, and anti-diabetes. In the present study, we evaluated the effect of EGCG on the maturation of diabetic oocytes in vitro.

OBJECTIVE

Investigating the role of EGCG in restoring the adverse effects of diabetes on oocyte quality.

METHODS

Diabetes mouse model was established by a single injection of streptozotocin (STZ). Oocytes were collected and matured in vitro with/without EGCG in M16 medium.

RESULTS

Compared with control, diabetic oocytes have a higher frequency of spindle defects and chromosome misalignment, but EGCG effectively reduces the incidence of oocytes with abnormal spindle assembly and chromosome mismatches. Moreover, the abnormal mitochondrial membrane potential (MMP) of diabetic oocytes is significantly alleviated by EGCG, and the reduced expression of genes regulating mitochondrial fusion (Mfn1 and Mfn2) and fission (Drp1) in diabetic oocytes is significantly increased while EGCG is added. EGCG also decreases the higher level of reactive oxygen species (ROS) in diabetic oocytes that may be regulated by the increased expression of superoxide dismutase 1 (Sod1) and superoxide dismutase 2 (Sod2). EGCG can also reduce the DNA damage of diabetic oocytes.

CONCLUSIONS

Our results suggest that EGCG, at least partially, improve the quality of diabetic oocytes.

SDMT: Spatial Dependence Multi-Task Transformer Network for 3D Knee MRI Segmentation and Landmark Localization

Knee segmentation and landmark localization from 3D MRI are two significant tasks for diagnosis and treatment of knee diseases. With the development of deep learning, Convolutional Neural Network (CNN) based methods have become the mainstream. However, the existing CNN methods are mostly single-task methods. Due to the complex structure of bone, cartilage and ligament in the knee, it is challenging to complete the segmentation or landmark localization alone. And establishing independent models for all tasks will bring difficulties for surgeon's clinical using. In this paper, a Spatial Dependence Multi-task Transformer (SDMT) network is proposed for 3D knee MRI segmentation and landmark localization. We use a shared encoder for feature extraction, then SDMT utilizes the spatial dependence of segmentation results and landmark position to mutually promote the two tasks. Specifically, SDMT adds spatial encoding to the features, and a task hybrided multi-head attention mechanism is designed, in which the attention heads are divided into the inter-task attention head and the intra-task attention head. The two attention head deal with the spatial dependence between two tasks and correlation within the single task, respectively. Finally, we design a dynamic weight multi-task loss function to balance the training process of two task. The proposed method is validated on our 3D knee MRI multi-task datasets. Dice can reach 83.91% in the segmentation task, and MRE can reach 2.12 mm in the landmark localization task, it is competitive and superior over other state-of-the-art single-task methods.

Inheritance of perturbed methylation and metabolism caused by uterine malnutrition via oocytes

BACKGROUND

Undernourishment in utero has deleterious effects on the metabolism of offspring, but the mechanism of the transgenerational transmission of metabolic disorders is not well known. In the present study, we found that undernourishment in utero resulted in metabolic disorders of female F1 and F2 in mouse model.

RESULTS

Undernutrition in utero induced metabolic disorders of F1 females, which was transmitted to F2 females. The global methylation in oocytes of F1 exposed to undernutrition in utero was decreased compared with the control. KEGG analysis showed that genes with differential methylation regions (DMRs) in promoters were significantly enriched in metabolic pathways. The altered methylation of some DMRs in F1 oocytes located at the promoters of metabolic-related genes were partially observed in F2 tissues, and the expressions of these genes were also changed. Meanwhile, the abnormal DNA methylation of the validated DMRs in F1 oocytes was also observed in F2 oocytes.

CONCLUSIONS

These results indicate that DNA methylation may mediate the transgenerational inheritance of metabolic disorders induced by undernourishment in utero via female germline.

MsgeCNN: Multiscale geometric embedded convolutional neural network for ONFH segmentation and grading

BACKGROUND

The incidence of osteonecrosis of the femoral head (ONFH) is increasing gradually, rapid and accurate grading of ONFH is critical. The existing Steinberg staging criteria grades ONFH according to the proportion of necrosis area to femoral head area.

PURPOSE

In the clinical practice, the necrosis region and femoral head region are mainly estimated by the observation and experience of doctor. This paper proposes a two-stage segmentation and grading framework, which can be used to segment the femoral head and necrosis, as well as to diagnosis.

METHODS

The core of the proposed two-stage framework is the multiscale geometric embedded convolutional neural network (MsgeCNN), which integrates geometric information into the training process and accurately segments the femoral head region. Then, the necrosis regions are segmented by the adaptive threshold method taking femoral head as the background. The area and proportion of the two are calculated to determine the grade.

RESULTS

The accuracy of the proposed MsgeCNN for femoral head segmentation is 97.73%, sensitivity is 91.17%, specificity is 99.40%, dice score is 93.34%. And the segmentation performance is better than the existing five segmentation algorithms. The diagnostic accuracy of the overall framework is 90.80%.

CONCLUSIONS

The proposed framework can accurately segment the femoral head region and the necrosis region. The area, proportion, and other pathological information of the framework output provide auxiliary strategies for subsequent clinical treatment.

Protocatechuic Acid Delays Postovulatory Oocyte Ageing in Mouse

SCOPE

Tea is a popular beverage worldwide and has many health functions. Protocatechuic acid (PCA) is an important bioactive component of tea and has benefit to health. In some cases, oocytes after ovulation may miss the optimal fertilization time and enter a postovulatory ageing process. Therefore, to investigate the role of PCA in delaying oocyte ageing is aimed.

METHODS AND RESULTS

Metaphase II (MII) oocytes aged in vitro are randomly divided into three groups: control, aged, and aged + PCA. PCA treatment (30 µM) reduces the fragmentation rate and the incidence of abnormal spindle morphology and chromosome misalignment of oocytes aged 24 h in vitro. The mitochondrial dysfunction of aged oocytes, such as decreased mitochondrial membrane potential and excessive accumulation of reactive oxygen (ROS), is also alleviated by PCA. PCA also delays apoptosis of aged oocytes, and improves the sperm binding capacity. Otherwise, aged oocytes treated with PCA have a higher fertilization rate and blastocyst rate compared with untreated aged oocytes in vitro.

CONCLUSION

PCA is an important bioactive ingredient of tea that improves aged oocyte quality, suggesting that PCA is available to improve the quality of aged oocytes in vitro.

Epigallocatechin gallate improves meiosis maturation against Diazinon exposure in porcine oocytes

Diazinon (DZN) is a refractory organophosphorus pesticide (OP) in the surrounding environment due to its overuse in agriculture. The antioxidant activity of Epigallocatechin gallate (EGCG) from green tea is at least 100 times greater than that of vitamin C. This study aimed to study the effects of DZN on the meiotic maturation of porcine oocytes, as well as the protective roles of EGCG. Firstly, the effects of DZN and EGCG on meiotic nuclear maturation of porcine oocytes were detected, and then embryonic development was investigated by chemical parthenogenetic activation. Next, the spindle assembly, mitochondrial membrane potential (MMP), reactive oxygen species (ROS), DNA damage, and finally the early apoptosis of oocytes were examined by immunofluorescence staining. The results revealed that DZN exposure significantly reduced the quality of porcine oocytes, such as failure of nuclear and cytoplasmic maturation, evidenced by abnormal spindle assembly, disordered chromosome alignment, low MMP, observably increased ROS, severe DNA damage, and early apoptosis. Appropriate EGCG could significantly reduce all these defects caused by DZN. In conclusion, EGCG can help prevent the harm that DZN exposure can do. These findings offer convincing support for enhancing the oocyte quality from EGCG through daily ordinary beverages.

An Integrated Multitasking Intelligent Bearing Fault Diagnosis Scheme Based on Representation Learning Under Imbalanced Sample Condition

Accurate bearing fault diagnosis is of great significance of the safety and reliability of rotary mechanical system. In practice, the sample proportion between faulty data and healthy data in rotating mechanical system is imbalanced. Furthermore, there are commonalities between the bearing fault detection, classification, and identification tasks. Based on these observations, this article proposes a novel integrated multitasking intelligent bearing fault diagnosis scheme with the aid of representation learning under imbalanced sample condition, which realizes bearing fault detection, classification, and unknown fault identification. Specifically, in the unsupervised condition, a bearing fault detection approach based on modified denoising autoencoder (DAE) with self-attention mechanism for bottleneck layer (MDAE-SAMB) is proposed in the integrated scheme, which only uses the healthy data for training. The self-attention mechanism is introduced into the neurons in the bottleneck layer, which can assign different weights to the neurons in the bottleneck layer. Moreover, the transfer learning based on representation learning is proposed for few-shot fault classification. Only a few fault samples are used for offline training, and high-accuracy online bearing fault classification is achieved. Finally, according to the known fault data, the unknown bearing faults can be effectively identified. A bearing dataset generated by rotor dynamics experiment rig (RDER) and a public bearing dataset demonstrates the applicability of the proposed integrated fault diagnosis scheme.

Ensemble of convolutional neural networks and multilayer perceptron for the diagnosis of mild cognitive impairment and Alzheimer's disease

BACKGROUND

Structural magnetic resonance imaging (sMRI) can provide morphological information about the structure and function of the brain in the same scanning process. It has been widely used in the diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI).

PURPOSE

To capture the anatomical changes in the brain caused by AD/MCI, deep learning-based MRI image analysis methods have been proposed in recent years. However, it is observed that the performance of most existing methods is limited as they only construct a single type of deep network and ignore the significance of other clinical information.

METHODS

To make up for these defects, an ensemble framework that incorporates three types of dedicatedly-designed convolutional neural networks (CNNs) and a multilayer perceptron (MLP) network is proposed, where three CNNs with entropy-based multi-instance learning pooling layers have more reliable feature selection abilities. The dedicatedly-designed base classifiers can make use of the heterogeneous data, and empower the framework with enhanced diversity and robustness. In particular, to consider the interactions among the base classifiers, a novel multi-head self-attention voting scheme is designed. Moreover, considering the chance that MCI can be transformed to AD, the proposed framework is designed to diagnose AD and predict MCI conversion simultaneously, with the aid of the transfer learning technique.

RESULTS

For performance evaluation and comparison, extensive experiments are conducted on the public dataset of the Alzheimer's Disease Neuroimaging Initiative (ADNI). The results show that the proposed ensemble framework provides superior performance under most of the evaluation metrics. Especially, the proposed framework achieves state-of-the-art diagnostic accuracy (98.61% for the AD diagnosis task, and 84.49% for the MCI conversion prediction task).

CONCLUSIONS

These promising results demonstrate the proposed ensemble framework can accurately diagnose AD patients and predict the conversion of MCI patients, which has the potential of clinical practice for diagnosing AD and MCI.

SQSTM1 and its MAP1LC3B-binding domain induce forced mitophagy to degrade mitochondrial carryover during mitochondrial replacement therapy

Mitophagy is a process that selectively degrades mitochondria in cells, and it involves a series of signaling events. Our recent paper shows that the ectopic expression of SQSTM1 and its MAP1LC3B-binding domain (Binding) at the mitochondrial outer membrane, can directly cause mitophagy. To distinguish this mitophagy from others, we called it forced mitophagy. Further results show that the forced mitophagy can degrade half of the mitochondria and their DNA in HeLa cells and mouse embryos. Meanwhile, there are no apparent effects on mitochondrial membrane potential (MMP), reactive oxygen species (ROS), mitosis and embryo development. Thus, the forced mitophagy was examined to selectively degrade mitochondrial carryover in the nuclear donor embryos' mitochondria by pre-labeling with Binding before mitochondrial replacement therapy (MRT). The results show that the forced mitophagy can reduce mitochondrial carryover from an average of 4% to 0.09% compared to the controls in mouse embryos and tissues. In addition, the offspring from MRT mice show negligible effects on growth, reproduction, exercise and behavior. Furthermore, results from human tri-pronuclear embryos show that the forced mitophagy results in undetectable mitochondrial carryover in 77% of embryos following MRT. Therefore, forced mitophagy is efficient and safe for degrading mitochondrial carryover in MRT.

Pregnancy rate and reproductive hormones in humpback whale blubber: Dominant form of progesterone differs during pregnancy

To better understand reproductive physiology of humpback whales Megaptera novaeangliae that reside in Hawai'i and Alaska, enzyme immunoassays were validated for both progesterone and testosterone in free-ranging and stranded animals (n = 185 biopsies). Concentrations were analyzed between different depths of large segments of blubber taken from skin to muscle layers of stranded female (n = 2, 1 pregnant, 1 non-pregnant) and male (n = 1) whales. Additionally, progesterone metabolites were identified between pregnant (n = 1) and non-pregnant (n = 3) females using high pressure liquid chromatography (HPLC). Progesterone concentrations were compared between juvenile (i.e., sexually immature), lactating, and pregnant females, and male whales, and pregnancy rates of sexually mature females were calculated. Based on replicate samples from ship struck animals collected at 7 depth locations, blubber containing the highest concentration of progesterone was located 1 cm below the skin for females, and the highest concentration of testosterone was in the skin layer of one male whale. HPLC of blubber samples of pregnant and non-pregnant females contain different immunoreactive progesterone metabolites, with the non-pregnant female eluate comprised of a more polar, and possibly conjugated, form of progesterone than the pregnant female. In females, concentrations of progesterone were highest in the blubber of pregnant (n = 28, 28.6 ± 6.9 ng/g), followed by lactating (n = 16, 0.9 ± 0.1 ng/g), and female juvenile (n = 5, 1.0 ± 0.2 ng/g) whales. Progesterone concentrations in male (n = 24, 0.6 ng/g ± 0.1 ng/g) tissues were the lowest all groups, and not different from lactating or juvenile females. Estimated summer season pregnancy rate among sexually mature females from the Hawai'i stock of humpback whales was 0.562 (95 % confidence interval 0.528-0.605). For lactating females, the year-round pregnancy rate was 0.243 (0.09-0.59), and varies depending on the threshold of progesterone assumed for pregnancy in the range between 3.1 and 28.5 ng/g. Our results demonstrate the synergistic value added when combining immunoreactive assays, HPLC, and long-term sighting histories to further knowledge of humpback whale reproductive physiology.

Application of SYNTAX and its Derivative Scores in the Selection of Revascularization Strategies for Complex Coronary Heart Disease

Complex coronary heart disease (CHD) has become a hot spot in medicine due to its complex coronary anatomy, variable clinical factors, difficult hemodynamic reconstruction, and limited effect of conservative drug treatment. Identifying complex CHD and selecting optimal treatment methods have become more scientific as revascularization technology has improved, and coronary risk stratification scores have been introduced. SYNTAX and its derivative scores are decision-making tools that quantitatively describe the characteristics of coronary lesions in patients based on their complexity and severity. The SYNTAX and its derivative scores could assist clinicians in rationalizing the selection of hemodynamic reconstruction treatment strategies, and have demon-strated outstanding value in evaluating the prognosis of patients with complex CHD undergoing revascularization treatment. The authors in this article summary the practical application of SYNTAX and its derivative scores in complex CHD in order to deepen the understanding of the relationship between the choice of different revascularization strategies and SYNTAX and its derived scores in complex CHD and provide a further reference for clinical treatment of complex CHD.

Quo vadis artificial intelligence?

The study of artificial intelligence (AI) has been a continuous endeavor of scientists and engineers for over 65 years. The simple contention is that human-created machines can do more than just labor-intensive work; they can develop human-like intelligence. Being aware or not, AI has penetrated into our daily lives, playing novel roles in industry, healthcare, transportation, education, and many more areas that are close to the general public. AI is believed to be one of the major drives to change socio-economical lives. In another aspect, AI contributes to the advancement of state-of-the-art technologies in many fields of study, as helpful tools for groundbreaking research. However, the prosperity of AI as we witness today was not established smoothly. During the past decades, AI has struggled through historical stages with several winters. Therefore, at this juncture, to enlighten future development, it is time to discuss the past, present, and have an outlook on AI. In this article, we will discuss from a historical perspective how challenges were faced on the path of revolution of both the AI tools and the AI systems. Especially, in addition to the technical development of AI in the short to mid-term, thoughts and insights are also presented regarding the symbiotic relationship of AI and humans in the long run.

In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response

Response to immunotherapies can be variable and unpredictable. Pathology-based phenotyping of tumors into ‘hot’ and ‘cold’ is static, relying solely on T-cell infiltration in single-time single-site biopsies, resulting in suboptimal treatment response prediction. Dynamic vascular events (tumor angiogenesis, leukocyte trafficking) within tumor immune microenvironment (TiME) also influence anti-tumor immunity and treatment response. Here, we report dynamic cellular-level TiME phenotyping in vivo that combines inflammation profiles with vascular features through non-invasive reflectance confocal microscopic imaging. In skin cancer patients, we demonstrate three main TiME phenotypes that correlate with gene and protein expression, and response to toll-like receptor agonist immune-therapy. Notably, phenotypes with high inflammation associate with immunostimulatory signatures and those with high vasculature with angiogenic and endothelial anergy signatures. Moreover, phenotypes with high inflammation and low vasculature demonstrate the best treatment response. This non-invasive in vivo phenotyping approach integrating dynamic vasculature with inflammation serves as a reliable predictor of response to topical immune-therapy in patients.

Standard assessment of immune infiltration of biopsies is not sufficient to accurately predict response to immunotherapy. Here, the authors show that reflectance confocal microscopy can be used to quantify dynamic vasculature and inflammatory features to better predict treatment response in skin cancers.

1-Nitropyrene exposure induces mitochondria dysfunction and impairs oocyte maturation in mice

Oocyte quality is essential for a successful pregnancy. 1-Nitropyrene (1-NP) is a widely distributed pollutant in the environment and is well-known for its mutagenicity and carcinogenicity. However, whether 1-NP has toxic effects on mammalian oocyte quality remains unknown. In the present study, we focused on the effect of 1-NP on oocyte maturation using mouse oocytes as an in vitro model. Our study showed that 1-NP exposure disrupted the meiotic spindle assembly and caused chromosome misalignment, further impaired first polar body extrusion, and significantly decreased the fertilization capability in mouse oocytes. Further investigation showed that the mitochondrial membrane potential (MMP) and ATP levels were decreased, and the expression of genes encoding components of the mitochondrial respiratory chain was inhibited in 1-NP exposed oocytes. Meanwhile, 1-NP exposure increased the levels of reactive oxygen species (ROS), inhibited the expression of genes encoding antioxidant enzymes, and increased the frequency of early apoptotic oocytes. Overall, our data suggest that 1-NP exposure disrupts mitochondrial function and intracellular redox balance, ultimately impairing oocyte maturation. These findings reveal the adverse effect of 1-NP exposure on oocyte quality.

MSFR-Net: Multi-modality and single-modality feature recalibration network for brain tumor segmentation

BACKGROUND

Accurate and automated brain tumor segmentation from multi-modality MR images plays a significant role in tumor treatment. However, the existing approaches mainly focus on the fusion of multi-modality while ignoring the correlation between single-modality and tumor sub-components. For example, T2-weighted images show good visualization of edema, and T1-contrast images have a good contrast between enhancing tumor core and necrosis. In the actual clinical process, professional physicians also label tumors according to these characteristics. We design a method for brain tumors segmentation that utilizes both multi-modality fusion and single-modality characteristics.

METHODS

A multi-modality and single-modality feature recalibration network (MSFR-Net) is proposed for brain tumor segmentation from MR images. Specifically, multi-modality information and single-modality information are assigned to independent pathways. Multi-modality network explicitly learn the relationship between all modalities and all tumor sub-components. Single-modality network learn the relationship between single-modality and its highly correlated tumor sub-components. Then, a dual recalibration module (DRM) is designed to connect the parallel single-modality network and multi-modality network at multiple stages. The function of the DRM is to unify the two types of features into the same feature space.

RESULTS

Experiments on BraTS 2015 dataset and BraTS 2018 dataset show that the proposed method is competitive and superior to other state-of-the-art methods. The proposed method achieved the segmentation results with dice coefficients of 0.86 and hausdorff distance of 4.82 on BraTS 2018 dataset, with dice coefficients of 0.80, positive predictive value of 0.76 and sensitivity of 0.78 on BraTS 2015 dataset.

CONCLUSIONS

This work combines the manual labeling process of doctors and introduces the correlation between single-modality and the tumor sub-components into the segmentation network. The method improves the segmentation performance of brain tumors and can be applied in the clinical practice. The code of the proposed method is available at: https://github.com/xiangQAQ/MSFR-Net. This article is protected by copyright. All rights reserved.

Templated Insertions Are Associated Specifically with BRCA2 Deficiency and Overall Survival in Advanced Ovarian Cancer

Cancer cells defective in homologous recombination (HR) are responsive to DNA-crosslinking chemotherapies, PARP inhibitors, and inhibitors of polymerase theta (Pol θ), a key mediator of the backup pathway alternative end-joining. Such cancers include those with pathogenic biallelic alterations in core HR genes and another cohort of cases that exhibit sensitivity to the same agents and harbor genomic hallmarks of HR deficiency (HRD). These HRD signatures include a single-base substitution pattern, large rearrangements, characteristic tandem duplications, and small deletions. Here, we used what is now known about the backup pathway alternative end-joining (Alt-EJ) through the key factor Pol θ to design and test novel signatures of polymerase theta-mediated (TMEJ) repair. We generated two novel signatures; a signature composed of small deletions with microhomology and another consisting of small, templated insertions (TINS). We find that TINS consistent with TMEJ repair are highly specific to tumors with pathogenic biallelic mutations in BRCA2 and that high TINS genomic signature content in advanced ovarian cancers associate with overall survival following treatment with platinum agents. In addition, the combination of TINS with other HRD metrics significantly improves the association of platinum sensitivity with survival compared with current state-of-the-art signatures.

IMPLICATIONS

Small, templated insertions indicative of theta-mediated end-joining likely can be used in conjunction with other HRD mutational signatures as a prognostic tool for patient response to therapies targeting HR deficiency.

Explainable multi-instance and multi-task learning for COVID-19 diagnosis and lesion segmentation in CT images

Coronavirus Disease 2019 (COVID-19) still presents a pandemic trend globally. Detecting infected individuals and analyzing their status can provide patients with proper healthcare while protecting the normal population. Chest CT (computed tomography) is an effective tool for screening of COVID-19. It displays detailed pathology-related information. To achieve automated COVID-19 diagnosis and lung CT image segmentation, convolutional neural networks (CNNs) have become mainstream methods. However, most of the previous works consider automated diagnosis and image segmentation as two independent tasks, in which some focus on lung fields segmentation and the others focus on single-lesion segmentation. Moreover, lack of clinical explainability is a common problem for CNN-based methods. In such context, we develop a multi-task learning framework in which the diagnosis of COVID-19 and multi-lesion recognition (segmentation of CT images) are achieved simultaneously. The core of the proposed framework is an explainable multi-instance multi-task network. The network learns task-related features adaptively with learnable weights, and gives explicable diagnosis results by suggesting local CT images with lesions as additional evidence. Then, severity assessment of COVID-19 and lesion quantification are performed to analyze patient status. Extensive experimental results on real-world datasets show that the proposed framework outperforms all the compared approaches for COVID-19 diagnosis and multi-lesion segmentation.

A proteomic atlas of atherosclerosis: regional proteomic signatures for plaque inflammation and calcification

Funding Acknowledgements

Type of funding sources: Foundation. Main funding source(s): This study was mainly supported from the British Heart Foundation (BHF) supporting Prof. Manuel Mayr as a Chair Holder (CH/16/3/32406) with BHF programme grant support (RG/16/14/32397) and Dr. Theofilatos with BHF programm grant support (G/20/10387).

Background

Using proteomics, we strove to reveal novel molecular subtypes of human atherosclerotic lesions, study their associations with histology and imaging and relate them to long-term cardiovascular outcomes.

Methods

219 samples were obtained from 120 patients undergoing carotid endarterectomy. Sequential protein extraction was combined with multiplexed, discovery proteomics. Parallel reaction monitoring for 135 proteins was deployed for targeted validation. A combination of statistical, bioinformatics and machine learning methods was used to perform differential expression, network, pathway enrichment analysis and train and evaluate prognostic models.

Results

Our extensive proteomics analysis from the core and periphery of plaques doubled the coverage of the plaque proteome compared to the largest proteomics study on atherosclerosis thus far. Plaque inflammation and calcification signatures were inversely correlated and validated with targeted proteomics. The inflammation signature was enriched with neutrophil-derived proteins, including calprotectin (S100A8/9) and myeloperoxidase. The calcification signature contained fetuin-A, osteopontin, and gamma-carboxylated proteins. Sex differences in the proteome of atherosclerosis were explained by a higher proportion of calcified plaques in women. Single-cell RNA sequencing data attributed the inflammation signature predominantly to neutrophils and macrophages and the calcification signature to smooth muscle cells, except for certain plasma proteins that were not expressed but retained in the plaque, i.e., fetuin-A. Echogenic lesions reflect the collagen content and calcification of plaque but carotid Duplex ultrasound fails to capture the extent of inflammatory protein changes in symptomatic plaques. Applying dimensionality reduction and machine learning on the proteomics data defined 4 distinct plaque phenotypes and revealed key protein signatures linked to smooth muscle cell content, plaque calcification and structural extracellular matrix, which improved the 9-year prognostic AUC by 25% compared to ultrasound and histology. A biosignature of four proteins (CNN1, PROC, SERPH, and CSPG2) independently predicted the progression of atherosclerosis and cardiovascular mortality with an AUC of 75%

Conclusion

We combined discovery and targeted proteomics with network reconstruction and clustering techniques to provide molecular insights into protein changes in atherosclerotic plaques. The application of proteomics and machine learning techniques revealed distinct clusters of plaques that inform on disease progression and future adverse cardiovascular events.

Analysis of a Trend Reversal in US Lumpectomy Rates From 2005 Through 2017 Using 3 Nationwide Data Sets

Importance

Rates of lumpectomy for breast cancer management in the United States previously declined in favor of more aggressive surgical options, such as mastectomy and contralateral prophylactic mastectomy (CPM).

Objective

To evaluate longitudinal trends in the rates of lumpectomy and mastectomy, including unilateral mastectomy vs CPM rates, and to determine characteristics associated with current surgical practice using 3 national data sets.

Design and Setting

Data from the National Surgical Quality Improvement Program (NSQIP), Surveillance, Epidemiology, and End Results (SEER) program, and National Cancer Database (NCDB) were examined to evaluate trends in lumpectomy and mastectomy rates from 2005 through 2017. Mastectomy rates were also evaluated with a focus on CPM. Longitudinal trends were analyzed using the Cochran-Armitage test for trend. Multivariate logistic regression models were performed on the NCDB data set to identify predictors of lumpectomy and CPM.

Results

A study sample of 3 467 645 female surgical breast cancer patients was analyzed. Lumpectomy rates reached a nadir between 2010 and 2013, with a significant increase thereafter. Conversely, in comparison with lumpectomy rates, overall mastectomy rates declined significantly starting in 2013. Cochran-Armitage trend tests demonstrated an annual decrease in lumpectomy rates of 1.31% (95% CI, 1.30%-1.32%), 0.07% (95% CI, 0.01%-0.12%), and 0.15% (95% CI, 0.15%-0.16%) for NSQIP, SEER, and NCDB, respectively, from 2005 to 2013 (P < .001, P = .01, and P < .001, respectively). From 2013 to 2017, the annual increase in lumpectomy rates was 0.96% (95% CI, 0.95%-0.98%), 1.60% (95% CI, 1.59%-1.62%), and 1.66% (95% CI, 1.65%-1.67%) for NSQIP, SEER, and NCDB, respectively (all P < .001). Comparisons of specific mastectomy types showed that unilateral mastectomy and CPM rates stabilized after 2013, with unilateral mastectomy rates remaining higher than CPM rates throughout the entire time period.

Conclusions

This observational longitudinal analysis indicated a trend reversal with an increase in lumpectomy rates since 2013 and an associated decline in mastectomies. The steady increase in CPM rates from 2005 to 2013 has since stabilized. The reasons for the recent reversal in trends are likely multifactorial. Further qualitative and quantitative research is required to understand the factors driving these recent practice changes and their associations with patient-reported outcomes.

Characterization of CD20 expression loss as a mechanism of resistance to mosunetuzumab in patients with relapsed/refractory B-cell non-Hodgkin lymphomas

7526

Background: Mosunetuzumab (M) is a bispecific antibody targeting CD20 and CD3 that redirects T cells to engage and eliminate malignant B cells being developed for relapsed or refractory (R/R) B-cell non-Hodgkin lymphomas (B-NHL). CD20 is an optimal target, with uniform expression across B-NHL histologies and minimal receptor turnover. We characterized CD20 loss as a potential mechanism of resistance to M in patients (pts) on a Phase I/II trial (NCT02500407) receiving M monotherapy for the treatment (tx) of R/R B-NHL. Methods: Pts with R/R B-NHL received M intravenously in 3-week cycles, for eight to 17 cycles depending on tumor response. At baseline (BL), biomarker-evaluable (archival or fresh) biopsies were collected from 293 pts. Biopsies from 62 pts were collected at additional time points during tx with M and/or at disease progression (PD). The proportion of CD20+ and PAX5+ tumor cells was determined by immunohistochemistry (IHC) using dual-staining with anti-CD20 (clone L26, VENTANA) and anti-PAX5 (clone DAK-PAX5, DAKO) antibodies. Expression of MS4A1, the gene encoding CD20 , was measured by RNA-sequencing (RNA-seq); MS4A1 mutation profiling was performed by whole exome sequencing (WES). Levels of CD20 expression were assessed relative to response rates. Correlative analyses were performed and assessed centrally (IHC, RNA-seq, and WES) and locally (IHC). Results: CD20 levels were consistently high ( > 75% CD20+PAX5+ cells) in the majority of BL biopsies and generally comparable across histologies (FL, DLBCL, tFL, MCL, and RT). BL CD20 loss (≤5% CD20+PAX5+ cells) was seen in 16/293 pts (5.5%), more commonly in aggressive NHL, and responses to M were not seen in these pts. Among 62 pts with BL and on-tx/at-PD biopsies, BL CD20 levels were ≤5% in 7/62 pts (11%) (6/7 pts [86%] progressed before completing Cycle 2). CD20 levels were maintained in on-tx biopsies from 23/24 pts (96%). At PD, biopsies showed CD20 loss in 7/26 pts (27%). For five pts with BL, on-tx and at-PD biopsies, all pts maintained CD20 while on-tx and 1/5 pts (20%) had CD20 loss at PD. There was no clear association between CD20 reduction and histology. Data from 185 BL biopsies showed generally concordant levels of CD20 gene and protein expression (r = 0.72). In 10/185 pts (5%), MS4A1 was expressed without detectable CD20 protein expression; DNA sequencing revealed novel mutations in MS4A1, including mutations leading to truncation of the protein. CD20 transmembrane and extra-cellular domain mutations were also observed but do not block CD20 expression. Conclusions: In pts with R/R B-NHL treated with M, low BL CD20 expression is associated with lack of response to M. During M tx, loss of tumor cell expression of CD20 is one mechanism of acquired resistance; however, CD20 expression is maintained in most pts with PD, implying alternative mechanisms for acquired M resistance. Clinical trial information: NCT02500407.

MEIOK21 regulates oocyte quantity and quality via modulating meiotic recombination

The reproductive life span of females is largely determined by the number and quality of oocytes. Previously, we identified MEIOK21 as a meiotic recombination regulator required for male fertility. Here, we characterize the important roles of MEIOK21 in regulating female meiosis and oocyte number and quality. MEIOK21 localizes at recombination sites as a component of recombination bridges in oogenesis like in spermatogenesis. Meiok21^-/- female mice show subfertility. Consistently, the size of the primordial follicle pool in Meiok21^-/- females is only ~40% of wild-type females because a great number of oocytes with defects in meiotic recombination and/or synapsis are eliminated. Furthermore, the numbers of primordial and growing follicles show a more marked decrease in an age-dependent manner compared with wild-type females. Further analysis shows Meiok21^-/- oocytes also have reduced rates of germinal vesicle breakdown and the first polar body extrusion when cultured in vitro, indicating poor oocyte quality. Additionally, Meiok21^-/- oocytes have more chromosomes bearing a single distally localized crossover (chiasmata), suggesting a possible defect in crossover maturation. Taken together, our findings indicate critical roles for MEIOK21 in ensuring the number and quality of oocytes in the follicles.