A neural algorithm for computing bipartite matchings.

Finding optimal bipartite matchings-e.g., matching medical students to hospitals for residency, items to buyers in an auction, or papers to reviewers for peer review-is a fundamental combinatorial optimization problem. We found a distributed algorithm for computing matchings by studying the development of the neuromuscular circuit. The neuromuscular circuit can be viewed as a bipartite graph formed between motor neurons and muscle fibers. In newborn animals, neurons and fibers are densely connected, but after development, each fiber is typically matched (i.e., connected) to exactly one neuron. We cast this synaptic pruning process as a distributed matching (or assignment) algorithm, where motor neurons "compete" with each other to "win" muscle fibers. We show that this algorithm is simple to implement, theoretically sound, and effective in practice when evaluated on real-world bipartite matching problems. Thus, insights from the development of neural circuits can inform the design of algorithms for fundamental computational problems.

Regulatory T and CXCR3+ Circulating Tfh Cells Concordantly Shape the Neutralizing Antibody Responses in Individuals Who Have Recovered from Mild COVID-19.

Regulatory T (Treg) cells are involved in the antiviral immune response in patients with coronavirus disease 2019 (COVID-19); however, whether Treg cells are involved in the neutralizing antibody (nAb) response remains unclear. Here, we found that individuals who recovered from mild but not severe COVID-19 had significantly greater frequencies of Treg cells and lower frequencies of CXCR3+ circulating T follicular helper (cTfh) cells than healthy controls. Furthermore, the frequencies of Treg and CXCR3+ cTfh cells were negatively and positively correlated with the nAb responses, respectively, and Treg cells was inversely associated with CXCR3+ cTfh cells in individuals who recovered from mild COVID-19 but not in those with severe disease. Mechanistically, Treg cells inhibited memory B-cell differentiation and antibody production by limiting the activation and proliferation of cTfh cells, especially CXCR3+ cTfh cells, and functional molecule expression. This study provides novel insight showing that mild COVID-19 elicits concerted nAb responses, which are shaped by both Treg and Tfh cells.

Oncological and reproductive outcomes of endometrial atypical hyperplasia and endometrial cancer patients undergoing conservative therapy with hysteroscopic resection: A systematic review and meta-analysis.

INTRODUCTION: Our objective was to conduct a systematic review and meta-analysis of studies evaluating the oncological and reproductive outcomes of patients with endometrial atypical hyperplasia (AH) and endometrioid endometrial cancer (EEC) undergoing conservative therapy with hysteroscopic resection (HR). MATERIAL AND METHODS: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement for systematic reviews and meta-analyses. The study strictly followed the methodological framework proposed by the Cochrane Handbook and was retrospectively registered in PROSPERO (CRD42023469986). Searches were conducted in PubMed, Embase, and the Cochrane Library, from inception to October 10, 2023. A checklist based on items of the Newcastle-Ottawa Scale and the Methodological Index for Non-randomized Studies was used for quality assessment. The primary end points for this meta-analysis were complete response (CR), pregnancy, and live birth rates following HR-based therapy in patients with EEC or AH. The secondary end point was the recurrence rate (RR). RESULTS: Twenty-one articles involving 407 patients with clinical stage IA, low or intermediate grade, EEC, and 444 patients with AH managed with HR-based conservative treatment were included for this systematic review. CR to HR-based conservative therapy was achieved in 88.6% of patients with EEC and 97.0% of patients with AH. Of these, 30.6% and 24.2%, respectively, had live births. The overall pooled disease RR was 18.3% and 10.8% in patients with EEC and AH, respectively. Further subset analyses revealed that EEC patients with body mass index (BMI) ≤28 kg/m2 had higher CR rates as well as higher chances of pregnancy and live birth (91.6% CR, 32.9% pregnancy, 31.1% live birth) compared with patients with BMI >28 kg/m2 (86.4% CR, 28.4% pregnancy, 23.0% live birth). The HR followed by oral progestogen subgroup had higher CR rates and higher chances of pregnancy and live birth (91.8% CR, 36.3% pregnancy, 28.2% live birth) than the HR followed by the levonorgestrel intrauterine system subgroup (82.5% CR, 25.3% pregnancy, 16.3% live birth). CONCLUSIONS: Hysteroscopic resection followed by progestins appears to be a promising choice for fertility-sparing treatment in young patients with AH and EEC, with effective and safe responses. The live birth rate remains to be improved by providing medical guidance and encouragement.

CCNE1 is a predictive and immunotherapeutic indicator in various cancers including UCEC: a pan-cancer analysis.

BACKGROUND: CCNE1 plays an important oncogenic role in several tumors, especially high-stage serous ovarian cancer and endometrial cancer. Nevertheless, the fundamental function of CCNE1 has not been explored in multiple cancers. Therefore, bioinformatics analyses of pan-cancer datasets were carried out to explore how CCNE1 regulates tumorigenesis. METHODS: A variety of online tools and cancer databases, including GEPIA2, SangerBox, LinkedOmics and cBioPortal, were applied to investigate the expression of CCNE1 across cancers. The pan-cancer datasets were used to search for links between CCNE1 expression and prognosis, DNA methylation, m6A level, genetic alterations, CCNE1-related genes, and tumor immunity. We verified that CCNE1 has biological functions in UCEC cell lines using CCK-8, EdU, and Transwell assays. RESULTS: In patients with different tumor types, a high mRNA expression level of CCNE1 was related to a poor prognosis. Genes related to CCNE1 were connected to the cell cycle, metabolism, and DNA damage repair, according to GO and KEGG enrichment analyses. Genetic alterations of CCNE1, including duplications and deep mutations, have been observed in various cancers. Immune analysis revealed that CCNE1 had a strong correlation with TMB, MSI, neoantigen, and ICP in a variety of tumor types, and this correlation may have an impact on the sensitivity of various cancers to immunotherapy. CCK-8, EdU and Transwell assays suggested that CCNE1 knockdown can suppress UCEC cell proliferation, migration and invasion. CONCLUSION: Our study demonstrated that CCNE1 is upregulated in multiple cancers in the TCGA database and may be a promising predictive biomarker for the immunotherapy response in some types of cancers. Moreover, CCNE1 knockdown can suppress the proliferation, migration and invasion of UCEC cells.

Pan-cancer analysis combined with experiments predicts CTHRC1 as a therapeutic target for human cancers.

BACKGROUND: The function of collagen triple helix repeat containing 1 (CTHRC1) as an oncogene has been reported in a growing number of publications. Bioinformatics methods represent a beneficial approach to examine the mechanism and function of the CTHRC1 gene in the disease process of cancers from a pan-cancer perspective. METHODS: In this study, using the online databases UCSC, NCBI, HPA, TIMER2, Oncomine, GEPIA, UALCAN, cBioPortal, COSMIC, MEXPRESS, STRING, CCLE, LinkedOmics, GTEx, TCGA, CGGA, and SangerBox, we focused on the relationship between CTHRC1 and tumorigenesis, progression, methylation, immunity, and prognosis. qPCR was used to detect CTHRC1 expression in glioma tissues and cell lines. RESULTS: The pan-cancer analysis showed that CTHRC1 was overexpressed in most tumors, and a significant correlation was observed between CTHRC1 expression and the prognosis of patients with cancer. CTHRC1 genetic alterations occur in diverse tumors and are associated with tumor progression. Levels of CTHRC1 promoter methylation were decreased in most cancer tissues compared with normal tissues. In addition, CTHRC1 coordinated the activity of ICP genes through diverse signal transduction pathways, was also associated with immune cell infiltration and the tumor microenvironment, and potentially represented a promising immunotherapy target. We identified CTHRC1-related genes across cancers using the GEPIA2 tool. The single-gene GO analysis of CTHRC1 across cancers showed that it was involved in some signaling pathways and biological processes, such as the Wnt signaling pathway, cell migration, and positive regulation of protein binding. The expression and function of CTHRC1 were also further verified in glioma tissues and cell lines. CONCLUSIONS: CTHRC1 is overexpressed in various cancer types and functions as an important oncogene that may promote tumorigenesis and development through different mechanisms. CTHRC1 may represent an important therapeutic target for human cancers.

Pan-cancer evaluation of gene expression and somatic alteration data for cancer prognosis prediction.

BACKGROUND: Over the past decades, approaches for diagnosing and treating cancer have seen significant improvement. However, the variability of patient and tumor characteristics has limited progress on methods for prognosis prediction. The development of high-throughput omics technologies now provides multiple approaches for characterizing tumors. Although a large number of published studies have focused on integration of multi-omics data and use of pathway-level models for cancer prognosis prediction, there still exists a gap of knowledge regarding the prognostic landscape across multi-omics data for multiple cancer types using both gene-level and pathway-level predictors. METHODS: In this study, we systematically evaluated three often available types of omics data (gene expression, copy number variation and somatic point mutation) covering both DNA-level and RNA-level features. We evaluated the landscape of predictive performance of these three omics modalities for 33 cancer types in the TCGA using a Lasso or Group Lasso-penalized Cox model and either gene or pathway level predictors. RESULTS: We constructed the prognostic landscape using three types of omics data for 33 cancer types on both the gene and pathway levels. Based on this landscape, we found that predictive performance is cancer type dependent and we also highlighted the cancer types and omics modalities that support the most accurate prognostic models. In general, models estimated on gene expression data provide the best predictive performance on either gene or pathway level and adding copy number variation or somatic point mutation data to gene expression data does not improve predictive performance, with some exceptional cohorts including low grade glioma and thyroid cancer. In general, pathway-level models have better interpretative performance, higher stability and smaller model size across multiple cancer types and omics data types relative to gene-level models. CONCLUSIONS: Based on this landscape and comprehensively comparison, models estimated on gene expression data provide the best predictive performance on either gene or pathway level. Pathway-level models have better interpretative performance, higher stability and smaller model size relative to gene-level models.

Cancer prognosis prediction using somatic point mutation and copy number variation data: a comparison of gene-level and pathway-based models.

BACKGROUND: Genomic profiling of solid human tumors by projects such as The Cancer Genome Atlas (TCGA) has provided important information regarding the somatic alterations that drive cancer progression and patient survival. Although researchers have successfully leveraged TCGA data to build prognostic models, most efforts have focused on specific cancer types and a targeted set of gene-level predictors. Less is known about the prognostic ability of pathway-level variables in a pan-cancer setting. To address these limitations, we systematically evaluated and compared the prognostic ability of somatic point mutation (SPM) and copy number variation (CNV) data, gene-level and pathway-level models for a diverse set of TCGA cancer types and predictive modeling approaches. RESULTS: We evaluated gene-level and pathway-level penalized Cox proportional hazards models using SPM and CNV data for 29 different TCGA cohorts. We measured predictive accuracy as the concordance index for predicting survival outcomes. Our comprehensive analysis suggests that the use of pathway-level predictors did not offer superior predictive power relative to gene-level models for all cancer types but had the advantages of robustness and parsimony. We identified a set of cohorts for which somatic alterations could not predict prognosis, and a unique cohort LGG, for which SPM data was more predictive than CNV data and the predictive accuracy is good for all model types. We found that the pathway-level predictors provide superior interpretative value and that there is often a serious collinearity issue for the gene-level models while pathway-level models avoided this issue. CONCLUSION: Our comprehensive analysis suggests that when using somatic alterations data for cancer prognosis prediction, pathway-level models are more interpretable, stable and parsimonious compared to gene-level models. Pathway-level models also avoid the issue of collinearity, which can be serious for gene-level somatic alterations. The prognostic power of somatic alterations is highly variable across different cancer types and we have identified a set of cohorts for which somatic alterations could not predict prognosis. In general, CNV data predicts prognosis better than SPM data with the exception of the LGG cohort.

Comparison of pathway and gene-level models for cancer prognosis prediction.

BACKGROUND: Cancer prognosis prediction is valuable for patients and clinicians because it allows them to appropriately manage care. A promising direction for improving the performance and interpretation of expression-based predictive models involves the aggregation of gene-level data into biological pathways. While many studies have used pathway-level predictors for cancer survival analysis, a comprehensive comparison of pathway-level and gene-level prognostic models has not been performed. To address this gap, we characterized the performance of penalized Cox proportional hazard models built using either pathway- or gene-level predictors for the cancers profiled in The Cancer Genome Atlas (TCGA) and pathways from the Molecular Signatures Database (MSigDB). RESULTS: When analyzing TCGA data, we found that pathway-level models are more parsimonious, more robust, more computationally efficient and easier to interpret than gene-level models with similar predictive performance. For example, both pathway-level and gene-level models have an average Cox concordance index of ~ 0.85 for the TCGA glioma cohort, however, the gene-level model has twice as many predictors on average, the predictor composition is less stable across cross-validation folds and estimation takes 40 times as long as compared to the pathway-level model. When the complex correlation structure of the data is broken by permutation, the pathway-level model has greater predictive performance while still retaining superior interpretative power, robustness, parsimony and computational efficiency relative to the gene-level models. For example, the average concordance index of the pathway-level model increases to 0.88 while the gene-level model falls to 0.56 for the TCGA glioma cohort using survival times simulated from uncorrelated gene expression data. CONCLUSION: The results of this study show that when the correlations among gene expression values are low, pathway-level analyses can yield better predictive performance, greater interpretative power, more robust models and less computational cost relative to a gene-level model. When correlations among genes are high, a pathway-level analysis provides equivalent predictive power compared to a gene-level analysis while retaining the advantages of interpretability, robustness and computational efficiency.

[Methylation in Promoter Region of SLC6A2 Gene in Heart Failure Patients and Its Correlation with Qi Deficiency/Blood Stasis Syndrome].

OBJECTIVE: To explore the methylation status in promoter region of norepinephrine transporter gene (NET, SLC6A2) in heart failure ( HF) patients and its correlation with qi deficiency/blood stasis syndrome (QDS/BSS). METHODS: Thirty-six patients with heart failure (NYHA classification III to IV) were recruited in the study (as the heart failure group) and their scores of QDS/BSS were evaluated. Besides, a healthy elderly group (30 cases) and a healthy youth group (30 cases) were also set up. They were recruited from Physical Examination Center of Fujian Provincial Hospital. Pyrosequencing was applied to detect the methylation in promoter region of SLC6A2 gene, and the total methylation index (MTI) of CpG island was calculated. The correlation between the methylation status in promoter region of SLC6A2 and scores of QDS/BSS was assessed using Pearson and Partial analyses. Risk factors were screened and adjusted using Logistic regression. RESULTS: By one-factor analysis of variance, the total MTI in the HF group (219.72% ± 54.03%) was obviously higher than that in the healthy elderly group (194.47% ± 34.92%) and the healthy youth group (161.60% ± 41.11%) (all P < 0.05). Meanwhile, the total MTI was higher in the healthy elderly group than in the healthy youth group (P < 0.01). By covariance analysis , after controlling age and BMI, the total MTI was higher in the HF group than in the healthy elderly group (P = 0.041), while it was higher in the healthy elderly group than in the healthy youth group (P = 0.016). Age was found to play an essential role in affecting MTI of SLC6A2 gene promoter region among the 3 groups (F = 16.447, P = 0.01). The total MTI was quite lower in the healthy youth group. Results of Partial correlation analysis showed MTI was positively correlated with scores of qi deficiency and blood stasis respectively (r = 0.494 and 0.419 respectively, both P < 0.05). Logistic regression analysis showed after adjusting confounding factors, the relative risk (OR value) of total MTI of SLC6A2 gene in promoter region was 1.038 (95% CI, 1.006 to 1.071, P = 0.020). CONCLUSIONS: Abnormally elevated methylation of the promoter region of SLC6A2 gene is one of risk factors for HF. In addition, the degree of methylation of the promoter region of SLC6A2 gene was positively correlated with the severity of QDS/BSS.

Relationship between Renying pulse augmentation index and Cunkou pulse condition in different blood pressure groups.

OBJECTIVE: To explore the relationship between Renying pulse (carotid) augmentation index (AI) and Cunkou pulse condition in different blood pressure groups, and the clinical significance of Renying and Cunkou pulse parameters to reflect vascular function. METHODS: Eighty-six patients with essential hypertension (EH) and 52 individuals with normal blood pressure (control group) between September 2010 and January 2012 were included in this study. Renying pulse AI was examined by a new diagnostic tool (ALOKA ProSound Alpha 10)--wave intensity (WI) that is calculated as the product of the derivatives of the simultaneously recorded blood pressure changes (dP/dt) and blood-flow-velocity changes (dU/dt), while Cunkou pulse condition was detected by DDMX-100 Pulse Apparatus in both EH and control groups. A multifactorial correlation analysis was performed for data analysis. RESULTS: After adjusting for potential confounding variables, in the EH group, AI was positively correlated with t5, w2/t (r(t5) = 0.225, P < 0.05; r(w2/t) = 0.230, P < 0.05) and negatively correlated with h5, h5/h1 and w2 (r(h5) = -0.393, P < 0.01; r(h5)/h1) = -0.444, P < 0.01; r(w2) = -0.389, P < 0.01). In the control group, AI was positively correlated with t3, t4, t5 and w1 (r(t3) = 0.595, P < 0.01; r(t4) = 0.292, P < 0.05; r(t5) = 0.318, P < 0.05; r(w1) = 0.541, P < 0.01) and negatively correlated with h1, h2, h3, Ad and A (r(h1) = -0.368, P < 0.05; r(h2) = -0.330, P < 0.05; r(h3) = -0.327, P < 0.05; rAd = -0.322, P < 0.05; rA = -0.410, P < 0.01). In the total sample group (EH plus control group, n = 138), AI was positively correlated with t, t5, w1 and w2t (r(t) = 0.257, P < 0.01; r(t5) = 0.266, P < 0.01; r(w1) = 0.184, P < 0.05; r(w2/t) = 0.210, P < 0.05) and negatively correlated with h5, h5/h1, w2 and Ad (r(h5) = -0.230, P < 0.01; r(h5/h1) = -0.218, P < 0.05; r(w2) = -0.267, P < 0.01; rAd = -0.246, P < 0.01). Multiple linear regression analysis was carried out to model the relationship (F = 7.887, P < 0.001). CONCLUSION: Renying pulse AI can effectively predict arterial stiffness in synchrony with the manifestations of Cunkou pulse in elderly patients with hypertension. Cunkou pulse apparatus is a valuable tool for evaluating AI in clinical practice. The close correlations reported above reflect the holistic concept of Traditional Chinese Medicine.

Stabilizing Interlayer Repulsion in Layered Sodium-Ion Oxide Cathodes via Hierarchical Layer Modification.

Layered sodium-ion oxides hold considerable promise in achieving high-performance sodium-ion batteries. However, the notorious phase transformation during charging, attributed to increased O2-─O2- repulsion, results in substantial performance decay. Here, a hierarchical layer modification strategy is proposed to stabilize interlayer repulsion. During desodiation, migrated Li+ from the transition metal layer and anchored Ca2+ in sodium sites maintain the cationic content within the sodium layer. Meanwhile, partial oxygen substitution by fluorine and the involvement of oxygen in redox reactions increase the average valence of the oxygen layer. This sustained cation presence and elevated anion valence collectively mitigate increasing O2-─O2- repulsion during sodium extraction, enabling the Na0.61Ca0.05[Li0.1Ni0.23Mn0.67]O1.95F0.05 (NCLNMOF) cathode to retain a pure P2-type structure across a wide voltage range. Unexpected insights reveal the interplay between different doping elements: the robust Li─F bonds and Ca2+ steric effects suppressing Li+ loss. The NCLNMOF electrode exhibits 82.5% capacity retention after 1000 cycles and a high-rate capability of 94 mAh g-1 at 1600 mA g-1, demonstrating the efficacy of hierarchical layer modification for high-performance layered oxide cathodes.

TOP2A modulates signaling via the AKT/mTOR pathway to promote ovarian cancer cell proliferation.

Ovarian cancer (OC) is a form of gynecological malignancy that is associated with worse patient outcomes than any other cancer of the female reproductive tract. Topoisomerase II α (TOP2A) is commonly regarded as an oncogene that is associated with malignant disease progression in a variety of cancers, its mechanistic functions in OC have yet to be firmly established. We explored the role of TOP2A in OC through online databases, clinical samples, in vitro and in vivo experiments. And initial analyses of public databases revealed high OC-related TOP2A expression in patient samples that was related to poorer prognosis. This was confirmed by clinical samples in which TOP2A expression was elevated in OC relative to healthy tissue. Kaplan-Meier analyses further suggested that higher TOP2A expression levels were correlated with worse prognosis in OC patients. In vitro, TOP2A knockdown resulted in the inhibition of OC cell proliferation, with cells entering G1 phase arrest and undergoing consequent apoptotic death. In rescue assays, TOP2A was confirmed to regulate cell proliferation and cell cycle through AKT/mTOR pathway activity. Mouse model experiments further affirmed the key role that TOP2A plays as a driver of OC cell proliferation. These data provide strong evidence supporting TOP2A as an oncogenic mediator and prognostic biomarker related to OC progression and poor outcomes. At the mechanistic level, TOP2A can control tumor cell growth via AKT/mTOR pathway modulation. These preliminary results provide a foundation for future research seeking to explore the utility of TOP2A inhibitor-based combination treatment regimens in platinum-resistant recurrent OC patients.

Analytical Validation of a Telomerase Reverse Transcriptase (TERT) Promoter Mutation Assay.

CONTEXT: Telomerase reverse transcriptase (TERT) promoter-mutated thyroid cancers are associated with a decreased rate of disease-free and disease-specific survival. High-quality analytical validation of a diagnostic test promotes confidence in the results that inform clinical decision-making. OBJECTIVE: This work aimed to demonstrate the analytical validation of the Afirma TERT promoter mutation assay. METHODS: TERT promoter C228T and C250T variant detection in genomic DNA (gDNA) was analyzed by assessing variable DNA input and the limit of detection (LOD) of variant allele frequency (VAF). The negative and positive percentage agreement (NPA and PPA) of the Afirma TERT test was examined against a reference primer pair as was the analytical specificity from potential interfering substances (RNA and blood gDNA). Further, the intrarun, interrun, and interlaboratory reproducibility of the assay were tested. RESULTS: The Afirma TERT test is tolerant to variation in DNA input amount (7-13 ng) and can detect expected positive TERT promoter variants down to 5% VAF LOD at 7 ng DNA input with greater than 95% sensitivity. Both NPA and PPA were 100% against the reference primer pair. The test remains accurate in the presence of 20% RNA or 80% blood gDNA for an average patient sample that typically has 30% VAF. The test also demonstrated a 100% confirmation rate when compared with an external next-generation sequencing-based reference assay executed in a non-Veracyte laboratory. CONCLUSION: The analytical robustness and reproducibility of the Afirma TERT test support its routine clinical use among thyroid nodules with indeterminate cytology that are Afirma Genomic Sequencing Classifier suspicious or among Bethesda V/VI nodules.

SARS-CoV-2 spike-reactive naïve B cells and pre-existing memory B cells contribute to antibody responses in unexposed individuals after vaccination.

Introduction: Since December 2019, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has presented considerable public health challenges. Multiple vaccines have been used to induce neutralizing antibodies (nAbs) and memory B-cell responses against the viral spike (S) glycoprotein, and many essential epitopes have been defined. Previous reports have identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike-reactive naïve B cells and preexisting memory B cells in unexposed individuals. However, the role of these spike-reactive B cells in vaccine-induced immunity remains unknown. Methods: To elucidate the characteristics of preexisting SARS-CoV-2 S-reactive B cells as well as their maturation after antigen encounter, we assessed the relationship of spike-reactive B cells before and after vaccination in unexposed human individuals. We further characterized the sequence identity, targeting domain, broad-spectrum binding activity and neutralizing activity of these SARS-CoV-2 S-reactive B cells by isolating monoclonal antibodies (mAbs) from these B cells. Results: The frequencies of both spike-reactive naïve B cells and preexisting memory B cells before vaccination correlated with the frequencies of spike-reactive memory B cells after vaccination. Isolated mAbs from spike-reactive naïve B cells before vaccination had fewer somatic hypermutations (SHMs) than mAbs isolated from spike-reactive memory B cells before and after vaccination, but bound SARS-CoV-2 spike in vitro. Intriguingly, these germline-like mAbs possessed broad binding profiles for SARS-CoV-2 and its variants, although with low or no neutralizing capacity. According to tracking of the evolution of IGHV4-4/IGKV3-20 lineage antibodies from a single donor, the lineage underwent SHMs and developed increased binding activity after vaccination. Discussion: Our findings suggest that spike-reactive naïve B cells can be expanded and matured by vaccination and cocontribute to vaccine-elicited antibody responses with preexisting memory B cells. Selectively and precisely targeting spike-reactive B cells by rational antigen design may provide a novel strategy for next-generation SARS-CoV-2 vaccine development.

Broad cross neutralizing antibodies against sarbecoviruses generated by SARS-CoV-2 infection and vaccination in humans.

The outbreaks of severe acute respiratory syndrome coronavirus (SARS-CoV-1), Middle East respiratory syndrome coronavirus (MERS-CoV), and SARS-CoV-2 highlight the need for countermeasures to prevent future coronavirus pandemics. Given the unpredictable nature of spillover events, preparing antibodies with broad coronavirus-neutralizing activity is an ideal proactive strategy. Here, we investigated whether SARS-CoV-2 infection and vaccination could provide cross-neutralizing antibodies (nAbs) against zoonotic sarbecoviruses. We evaluated the cross-neutralizing profiles of plasma and monoclonal antibodies constructed from B cells from coronavirus disease 2019 (COVID-19) convalescents and vaccine recipients; against sarbecoviruses originating from bats, civets, and pangolins; and against SARS-CoV-1 and SARS-CoV-2. We found that the majority of individuals with natural infection and vaccination elicited broad nAb responses to most tested sarbecoviruses, particularly to clade 1b viruses, but exhibited very low cross-neutralization to SARS-CoV-1 in both natural infection and vaccination, and vaccination boosters significantly augmented the magnitude and breadth of nAbs to sarbecoviruses. Of the nAbs, several exhibited neutralization activity against multiple sarbecoviruses by targeting the spike receptor-binding domain (RBD) and competing with angiotensin-converting enzyme 2 (ACE2) binding. SCM12-61 demonstrated exceptional potency, with half-maximal inhibitory concentration (IC50) values of 0.001-0.091 µg/mL against tested sarbecoviruses; while VSM9-12 exhibited remarkable cross-neutralizing breadth against sarbecoviruses and SARS-CoV-2 Omicron subvariants, highlighting the potential of these two nAbs in combating sarbecoviruses and SARS-CoV-2 Omicron subvariants. Collectively, our findings suggest that vaccination with an ancestral SARS-CoV-2 vaccine, in combination with broad nAbs against sarbecoviruses, may provide a countermeasure for preventing further sarbecovirus outbreaks in humans.

An investigation of the antidepressant action of xiaoyaosan in rats using ultra performance liquid chromatography-mass spectrometry combined with metabonomics.

A rapid, highly sensitive, and selective method was applied in a non-invasive way to investigate the antidepressant action of Xiaoyaosan (XYS) using ultra performance liquid chromatography-mass spectrometry (UPLC-MS) and chemometrics. Many significantly altered metabolites were used to explain the mechanism. Venlafaxine HCl and fluoxetine HCl were used as chemical positive control drugs with a relatively clear mechanism of action to evaluate the efficiency and to predict the mechanism of action of XYS. Urine obtained from rats subjected to chronic unpredictable mild stress (CUMS) was analyzed by UPLC-MS. Distinct changes in the pattern of metabolites in the rat urine after CUMS production and drug intervention were observed using partial least squares-discriminant analysis. The results of behavioral tests and multivariate analysis showed that CUMS was successfully reproduced, and a moderate-dose XYS produced significant therapeutic effects in the rodent model, equivalent to those of the positive control drugs, venlafaxine HCl and fluoxetine HCl. Metabolites with significant changes induced by CUMS were identified, and 17 biomarker candidates for stress and drug intervention were identified. The therapeutic effect of XYS on depression may involve regulation of the dysfunctions of energy metabolism, amino acid metabolism, and gut microflora changes. Metabonomic methods are valuable tools for measuring efficacy and mechanisms of action in the study of traditional Chinese medicines.

Compound AC1Q3QWB upregulates CDKN1A and SOX17 by interrupting the HOTAIR-EZH2 interaction and enhances the efficacy of tazemetostat in endometrial cancer.

Endometrial cancer (EC) is a common malignancy of the female reproductive system, with an escalating incidence. Recurrent/metastatic EC presents a poor prognosis. The interaction between the long non-coding RNA (lncRNA) HOTAIR and the polycomb repressive complex 2 (PRC2) induces abnormal silencing of tumor suppressor genes, exerting a pivotal role in tumorigenesis. We have previously discovered AC1Q3QWB (AQB), a small-molecule compound targeting HOTAIR-EZH2 interaction. In the present study, we unveil that AQB selectively hampers the interaction between HOTAIR and EZH2 within EC cells, thus reversing the epigenetic suppression of tumor suppressor genes. Furthermore, our findings demonstrate AQB's synergistic effect with tazemetostat (TAZ), an EZH2 inhibitor, significantly boosting the expression of CDKN1A and SOX17. This, in turn, induces cell cycle arrest and impedes EC cell proliferation, migration, and invasion. In vivo experiments further validate AQB's potential by enhancing TAZ's anti-tumor efficacy at lower doses. Our results advocate AQB, a recently discovered small-molecule inhibitor, as a promising agent against EC cells. When combined with TAZ, it offers a novel therapeutic strategy for EC treatment.

SARS-CoV-2 spike-specific TFH cells exhibit unique responses in infected and vaccinated individuals.

Long-term humoral immunity to SARS-CoV-2 is essential for preventing reinfection. The production of neutralizing antibody (nAb) and B cell differentiation are tightly regulated by T follicular help (TFH) cells. However, the longevity and functional role of TFH cell subsets in COVID-19 convalescents and vaccine recipients remain poorly defined. Here, we show that SARS-CoV-2 infection and inactivated vaccine elicited both spike-specific CXCR3+ TFH cell and CXCR3- TFH cell responses, which showed distinct response patterns. Spike-specific CXCR3+ TFH cells exhibit a dominant and more durable response than CXCR3- TFH cells that positively correlated with antibody responses. A third booster dose preferentially expands the spike-specific CXCR3+ TFH cell subset induced by two doses of inactivated vaccine, contributing to antibody maturation and potency. Functionally, spike-specific CXCR3+ TFH cells have a greater ability to induce spike-specific antibody secreting cells (ASCs) differentiation compared to spike-specific CXCR3- TFH cells. In conclusion, the persistent and functional role of spike-specific CXCR3+ TFH cells following SARS-CoV-2 infection and vaccination may play an important role in antibody maintenance and recall response, thereby conferring long-term protection. The findings from this study will inform the development of SARS-CoV-2 vaccines aiming to induce long-term protective immune memory.

Real-World Performance of the Afirma Genomic Sequencing Classifier (GSC)-A Meta-analysis.

CONTEXT: The Afirma® GSC aids in risk stratifying indeterminate thyroid nodule cytology (ITN). The 2018 GSC validation study (VS) reported a sensitivity (SN) of 91%, specificity (SP) of 68%, positive predictive value (PPV) of 47%, and negative predictive value (NPV) of 96%. Since then, 13 independent real-world (RW) postvalidation studies have been published. OBJECTIVE: This study's objective is to compare the RW GSC performance to the VS metrics. METHODS: Rules and assumptions applying to this analysis include: (1) At least 1 patient with molecular benign results must have surgery for that study to be included in SN, SP, and NPV analyses. (2) Molecular benign results without surgical histology are considered true negatives (TN) (as are molecular benign results with benign surgical histology). (3) Unoperated patients with suspicious results are either excluded from analysis (observed PPV [oPPV] and observed SP [oSP]) or assumed histology negatives (false positives; conservative PPV [cPPV] and conservative SP [cSP]) 4. Noninvasive follicular thyroid neoplasm with papillary-like nuclear features is considered malignant. RESULTS: In RW studies, the GSC demonstrates a SN, oSP, oPPV, and NPV of 97%, 88%, 65%, 99% respectively, and conservative RW performance showed cSP of 80% and cPPV of 49%, all significantly higher than the VS except for SN and cPPV. There was also a higher benign call rate (BCR) of 67% in RW studies compared to 54% in the VS (P < 0.05). CONCLUSION: RW data for the Afirma GSC demonstrates significantly better oSP and oPPV performance than the VS, indicating an increased yield of cancers for resected GSC suspicious nodules. The higher BCR likely increases the overall rate of clinical observation in lieu of surgery.

Indoor Passive Visual Positioning by CNN-Based Pedestrian Detection.

Indoor positioning applications are developing at a rapid pace; active visual positioning is one method that is applicable to mobile platforms. Other methods include Wi-Fi, CSI, and PDR approaches; however, their positioning accuracy usually cannot achieve the positioning performance of the active visual method. Active visual users, however, must take a photo to obtain location information, raising confidentiality and privacy issues. To address these concerns, we propose a solution for passive visual positioning based on pedestrian detection and projection transformation. This method consists of three steps: pretreatment, pedestrian detection, and pose estimation. Pretreatment includes camera calibration and camera installation. In pedestrian detection, features are extracted by deep convolutional neural networks using neighboring frame detection results and the map information as the region of interest attention model (RIAM). Pose estimation computes accurate localization results through projection transformation (PT). This system relies on security cameras installed in non-private areas so that pedestrians do not have to take photos. Experiments were conducted in a hall about 100 square meters in size, with 41 test-points for the localization experiment. The results show that the positioning error was 0.48 m (RMSE) and the 90% error was 0.73 m. Therefore, the proposed passive visual method delivers high positioning performance.