Stringent Selection Research Articles

Intelligent Manufacturing and Green Innovation—Evidence from China’s Listed Manufacturing Firms

The realization of intelligent and green manufacturing represents two core challenges currently faced by manufacturing enterprises. The “Intelligent Manufacturing Pilot Demonstration List” issued by the Ministry of Industry and Information Technology (MIIT) of the People’s Republic of China provides a sample of firms that have undergone stringent selection processes, demonstrating secure and controllable technological capabilities, with no intellectual property disputes. Using data from manufacturing firms listed on the Shanghai and Shenzhen stock exchanges from 2011 to 2020, we identify those that implemented intelligent manufacturing based on the aforementioned pilot list from 2015 to 2019 as the treatment group and the remaining firms as the control group to investigate whether intelligent manufacturing increases the number of green patent applications. The findings indicate that the implementation of intelligent manufacturing significantly increases green patent applications by 3.676% through three main pathways: reducing the level of financing constraints, improving resource utilization efficiency, and increasing R&D investment. Heterogeneity analysis reveals that state-owned enterprises exhibit a significantly stronger promotion effect on green innovation post-implementation of intelligent manufacturing compared to non-state-owned enterprises, with enterprises in the western region demonstrating the most pronounced enhancement in green innovation. Based on these findings, we propose corresponding recommendations from the perspectives of policy support and enterprise strategy.

Exploring Potential Diagnostic Biomarkers for Mechanical Asphyxia in the Heart Based on Proteomics Technology

Mechanical asphyxia presents a challenging diagnostic issue in forensic medicine due to its often covert nature, and the signs visible during an autopsy are usually not specific. Despite some progress in understanding hypoxia’s effects, traditional methods’ inherent limitations might overlook new biomarkers in mechanical asphyxia. This study employed 4D-DIA proteomics to explore the protein expression profiles of cardiac samples under conditions of mechanical asphyxia. Proteomic analysis identified 271 and 371 differentially expressed proteins in the strangulation and suffocation groups, respectively, compared to the control group. Seventy-eight differentially expressed proteins were identified across different mechanical asphyxia groups compared to the control group. GO and KEGG analysis showed enrichment in pathways, including complement and coagulation cascades, cAMP and cGMP-PKG signaling pathways, inflammatory mediator regulation of TRP channels, and phagosomes. Through stringent selection based on protein interactions, ALKBH5, NAA10, and CLPB were identified as potential diagnostic biomarkers. ALKBH5 showed increased expression in asphyxia models, while NAA10 and CLPB were downregulated; these biomarker changes were validated in both animal models and human cardiac samples. This study highlights the potential of proteomics in discovering reliable biomarkers, which can enhance the specificity of mechanical asphyxia diagnosis in forensic practice, provide new insights into the pathophysiological mechanisms of mechanical asphyxia, and offer new perspectives for diagnosing mechanical asphyxia.

Triangular titanium implants for sacroiliac joint fusion.

The sacroiliac joint (SIJ) is a common source of chronic low back pain. Published cohorts have reported favorable outcomes after SIJ fusion. We report the 12-month follow-up from SIJ fusion of the so far largest single-center and single-surgeon group. Over 15,000 outpatients were evaluated for chronic low back and leg pain, of whom 3,477 underwent SIJ blocks. 541 patients were stringently selected to undergo SIJ fusion with triangular titanium implants (TTI). 483 patients had a follow-up of 12 months. Patients were seen every 3 months and completed visual analog scale (VAS) and Oswestry Disability Index (ODI) ratings. Mean age of all patients was 61 years, and the majority (65%) were women. 44% had undergone prior lumbar fusion and 10% had a spinal cord stimulator (SCS) in place at the time of SIJ surgery. 26% underwent non-simultaneous bilateral SI joint fusion. At 12 months, the proportion of patients with clinically important improvements in pain (≥ 2 points) was very high (100%). The proportion with substantial improvement (≥ 4 points) was 98%. Similarly, improvement in ODI was high, with nearly 99% having an improvement of≥ 15 points by month 12. The proportions of patients with VAS ≤ 2 or ODI ≤ 15 was also high (92.8% and 48.9%). In our clinical practice, SIJ fusion with TTI produces significant improvement in pain and disability. The most important factor for achieving these clinical results may be the very stringent multistep selection of patients for surgery, which is described in detail, as well as the highly standardized and streamlined surgical procedure and the particular postoperative management.

Identification of the central tolerance checkpoint for autoreactive proteinase 3+ B cells in human bone marrow

Major target antigens of ANCA-associated vasculitis (AAV) are myeloperoxidase (MPO) and proteinase 3 (PR3). High-affinity MPO- and PR3-ANCA immunoglobulins are produced by antigen-experienced, class-switched autoreactive B cells. To prevent autoreactivity, B cells are subjected to several self-tolerance checkpoints, from the early immature stages in the bone marrow (BM), collectively called “central tolerance”, to late mature stages, collectively called “peripheral tolerance”; the latter was recently elucidated for autoreactive PR3+ B cells.Here we investigated central tolerance controlling immature PR3+B cells in the BM before their migration into the periphery as transitional B cells. We applied an established flow cytometry-based method using labeled recombinant PR3 (rPR3) to identify the PR3+B cells to compare the phenotype of PR3+B cells in paired samples of BM mononuclear cells (BMMC) and peripheral blood mononuclear cells (PBMC) of non-vasculitis controls (No-AAV), and PBMC of patients with PR3-ANCA-associated vasculitis (PR3-AAV).We observed that the proportion of PR3+B cells within BMMC was higher (median [IQR]; 1.98 % [1.77–2.75]) than within PBMC of No-AAV (0.9 % [0.63–1.44], p < 0.01 by paired comparison) and similar to their proportion within PBMC of patients with PR3-AAV (1.82 % [1.66–3.21]; p > 0.05). Within CD24++CD38++ B cells, the subset of B cell migrating from BM to the periphery, BMMC contained a greater proportion of PR3+B cells as compared to PBMC in No-AAV (3.35 % [1.99–4.92] versus 1.23 % [0.62–1.55], p < 0.01), showing different surface markers of maturation (i.e. higher proportion of CD27−CD10+ and lower expression of CD21, IgD, IgM). Importantly, we observed a significant decline of the PR3+ fraction from the immature subset (IgD−IgM+; 2.80 % [1.23–4.02]) to the early transitional subset (IgD+IgM+; 1.76 % [0.96–2.68], p < 0.01) in BMMC, while no significant reduction was observed between the early transitional of BMMC and the transitional compartment of PBMC in No-AAV (1.26 % [0.62–1.56], p > 0.05).In conclusion, to prevent PR3-related autoimmunity, autoreactive PR3+B cells pass a stringent selection in the BM, and their removal by central tolerance checkpoint activity occurs mainly between T1-like/immature to T2-like/early transitional B cells of BMMC.

Oncological outcomes of organ-sparing cystectomy versus standard radical cystectomy in male patients diagnosed with bladder cancer.

To compare the oncological outcomes between standard radical cystectomy (SRC) and organ-sparing cystectomy (OSC) in male patients diagnosed with bladder cancer. Patients with stage Ta-T3 bladder cancer who underwent OSC or SRC were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. The association between preoperative factors and the implementation of OSC was analyzed using logistic regression. Propensity score matching (PSM) was employed to balance baseline characteristics between the two groups. Patients' overall survival (OS) and cancer-specific survival (CSS) were estimated using the Kaplan-Meier method. Subgroup analyses based on the T stage were also conducted. A total of 7264 patients were included, with 96.8% (7033 patients) receiving SRC and 3.2% (231 patients) receiving OSC. Patients with higher T stages and high-grade tumors were less likely to undergo OSC. After PSM, OSC was associated with significantly worse OS and CSS than SRC. Subgroup analysis revealed that OSC did not lead to worse OS and CSS in non-muscle invasive bladder cancer and T2 stage patients, but it resulted in significantly worse outcomes in T3 stage patients. Our study indicates that OSC is associated with poorer oncological outcomes compared to SRC, particularly in patients with advanced-stage tumors. These findings suggest the need for stringent selection criteria for OSC in bladder cancer patients. Given the negative impact on prognosis, stage T3 should potentially be considered a contraindication for OSC. Further evidence is required to confirm these assertions.

The effectiveness of sacral lateral branch radiofrequency neurotomy for posterior sacroiliac joint complex pain in patients selected by dual sacral lateral branch blocks; A real-world cohort study

BackgroundPrevious study of spinal neurotomy procedures indicates that stringent block selection improves outcomes. However, this pattern is not established for sacral lateral branch radiofrequency neurotomy (SLBRFN). Few SLBRFN studies have used stringent block selection criteria such as ≥80 % pain reduction following dual sacral lateral branch blocks (SLBB). ObjectiveEvaluate the effectiveness of SLBRFN in patients with ≥80 % pain relief following dual SLBBs. MethodsRetrospective single-arm cohort study of consecutive patients from two Canadian musculoskeletal and pain clinics who underwent first-time SLBRFN after report of ≥80 % pain relief following dual diagnostic SLBBs. Patients were identified by electronic medical record query between 2016 and 2022. The primary outcome was the proportion of individuals with a ≥50 % reduction in the numeric pain rating scale (NPRS) score three months after SLBRFN. Secondary outcomes included the proportion of responders achieving the minimal clinically important difference (MCID) on the pain disability quality-of-life questionnaire (PDQQ), and the duration and mean percentage of pain relief among those with recurrent symptoms after a successful SLBRFN. ResultsOf the 70 participants included, 32 (45.7 %; 95 % CI = 34.6–57.3) reported a ≥50 % reduction in NPRS, and 35 (50.0 %; 95 % CI = 38.6–61.4) achieved the MCID on the PDQQ at 3-months. Among the 17 patients who reported a return of symptoms, the mean duration of relief was 8.0 ± 3.5 months, and the mean percentage of pain relief was 77.9 % ± 16.4 %. Logistic regression models revealed that the use of multi-tined RF probes and lower patient BMI were associated with treatment success. Discussion/conclusionSLBRFN reduced pain and disability in approximately 50 % of patients at 3 months when selected using relatively restrictive selection criteria. Treatment success was associated with multi-tined RF probe type and lower patient BMI. Larger prospective studies assessing long-term outcomes are needed to further evaluate the impact of different selection criteria and techniques on SLBRFN effectiveness.

How the Structure of Signaling Regulation Evolves: Insights from an Evolutionary Model.

To remain responsive to environmental changes, signaling pathways attenuate their activity with negative feedback loops (NFLs), where proteins produced upon stimulation downregulate the response. NFLs function both upstream of signaling to reduce input and downstream to reduce output. Unlike upstream NFLs, downstream NFLs directly regulate gene expression without the involvement of intermediate proteins. Thus, we hypothesized that downstream NFLs evolve under more stringent selection than upstream NFLs. Indeed, genes encoding downstream NFLs exhibit a slower evolutionary rate than upstream genes. Such differences in selective pressures could result in the robust evolution of downstream NFLs while making the evolution of upstream NFLs more sensitive to changes in signaling proteins and stimuli. Here, we test these assumptions within the context of immune signaling. Our minimal model of immune signaling predicts robust evolution of downstream NFLs to changes in model parameters. This is consistent with their critical role in regulating signaling and the conservative rate of evolution. Furthermore, we show that the number of signaling steps needed to activate a downstream NFL is influenced by the cost of signaling. Our model predicts that upstream NFLs are more likely to evolve under a shorter half-life of signaling proteins, absence of host-pathogen co-evolution, and a high infection rate. Although it has been proposed that NFLs evolve to reduce the cost of signaling, we show that a high cost does not necessarily predict the evolution of upstream NFLs. The insights from our model have broad implications for understanding the evolution of regulatory mechanisms across signaling pathways.

MaMoReS: A Robust Tool for Evaluating Supply Chain Resilience Through Systematic Literature and Network Analysis

Nowadays, disruptive events pose significant threats to organizations, making resilience a critical focus. Evaluating supply chain resilience is essential to avoid escalating disruptions. However, the literature on this topic is fragmented, and the assessment of resilience remains an open gap due to the lack of a clear definition of the dimensions and elements for its evaluation. To fill this gap, this study integrates a systematic literature review (SLR) and a systematic literature network analysis (SLNA) to propose a MAturity MOdel for REsilient Supply Chains (MaMoReS). Through content analysis and stringent selection of 15 resilience maturity models (ResMMs) via SLR, along with an SLNA on 6,474 sources, this method defines dimensions and sub-dimensions. The proposed MaMoReS is framed around five levels and five dimensions: risk management, agility, flexibility and adaptability, redundancy and robustness, transparency and visibility, and collaboration and relationships. The MaMoReS is applied to two case studies, pinpointing the practicality of the MaMoReS for measuring the resilience maturity level of the two companies along with their dimensions and sub-dimensions scoring. Thus, the MaMoReS can be used as an assessment tool by supply chain managers and researchers to evaluate the resilience of a supply chain.

Serological profile of voluntary blood donors in a blood bank of tertiary health care centre- An institution-based study

Background: The safe transfusion of blood facilities is an essential component of an efficient, excellent healthcare sector. Unsafe blood transfusions can be a cause of transfusion-transmitted infections and can be lethal. The present study was conducted to find out the seroprevalence of HBsAg, HCV, HIV, malarial parasites, and syphilis in voluntary blood donors in a tertiary care center. Materials and methods: This prospective study was conducted at the blood bank of the Shri Mahant Indiresh Hospital, Dehradun. 16413 samples from all blood donations were screened for HBsAg, HCV, HIV 1 and 2, malaria, and syphilis. Samples were collected in vacutainers at the time of blood donation and screened for HIV 1and2, HBsAg, and HCV using the fourth-generation enzyme-linked immunosorbent assay technique. Syphilis was tested by Treponema antibodies using the VITROS Syphilis TPA Reagent Pack. Malaria was tested by pan malaria card, monoclonal anti-pan specific parasite lactate dehydrogenase antibody conjugated to colloidal gold, and another monoclonal anti-pan specific parasite lactate dehydrogenase antibody immobilized on a nitrocellulose strip in a thin line. Results: Out of 16413 blood donors 342(2.1%) were found to be seropositive and 16071 (97.9%) were found to be seronegative. The total number of donors, who were found positive for HBsAg/Anti HCV was 1 (0.3%). Out of the seropositive cases, HBsAg, HCV, HIV, and Syphilis infections constituted 28.9%, 27.5, 14.6, and 28.7% cases respectively. Conclusions: There is a need for the development and implementation of stringent donor selection and sensitive screening tests to reduce the risk of acquiring transfusion-transmitted illnesses.

Maximizing genetic gains across agronomic and consumer preference traits in St. Augustinegrass breeding

AbstractCombining large multi‐environment trial (MET) datasets to decide which genotypes to move forward in the breeding process can be challenging, especially when dealing with negatively correlated traits. The use of a selection index has long been identified as an effective strategy in these situations. However, the method has found limited application in turfgrass breeding. The objective of this study was to use MET data for St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] breeding lines evaluated across the southern United States to compare genetic gains achieved with the additive additive genetic index (AI) versus the turf performance index (TPI) incorporating agronomic as well as consumer preference traits. The use of either selection index produced more positive genetic gains across traits than direct selection even in the presence of negative correlations. However, the higher genetic gains obtained with AI versus TPI indicate that the use of an index that weighs traits according to their importance is a better approach for selection. Moreover, under a more stringent selection intensity, none of the best lines identified with AI would have been selected with TPI emphasizing the importance of choosing selection criteria that provide a more nuanced ranking of lines. Additionally, higher heritability values and gains from selection were obtained for turfgrass quality under stress (drought and shade) than under normal conditions indicating that selection under stress environments might be more efficient. Most of the evaluated St. Augustinegrass lines outperformed the checks, further supporting the value of cross‐institutional breeding collaborations.

Systematic review of Janus kinases inhibitors for rheumatoid arthritis: methodology, reporting, and quality of evidence evaluation.

To evaluate the methodological, reporting and evidence quality of systematic reviews or meta-analyses of Janus kinases (JAK) inhibitors for the treatment of rheumatoid arthritis (RA). Our study systematically retrieved reviews from various databases, spanning from inception to June 2024. Two evaluators independently assessed the methodological, reporting, and evidence quality of each review using the AMSTAR-2 and PRIAMA2020 tools. The evidence quality was evaluated according to GRADE criteria. Six aspects were evaluated: publication year, study type, homogeneity, risk of publication bias, AMSTAR-2 methodology, and PRIAMA2020 reporting quality. Excel 2016 facilitated conversion of scores into radar plots. Following stringent selection criteria, a total of 18 relevant studies were identified. The AMSTAR-2 scores ranged from 4 to 13 points, with five studies rated as low quality and the remaining 13 as critically low quality. All studies encompassed populations, interventions, controls, and outcome measures, demonstrating commendable integrity. However, there is room for improvement in study protocol development and registration, comprehensive search strategies, inclusion and exclusion criteria, conflict of interest disclosure, and discussion of heterogeneity. PRIAMA2020 assessments ranged from 14.5 to 21 points, with two studies scoring below 15 points due to increased bias risk from data transformation and sensitivity analysis. Notably, all reviews (100%) adhered to PRIAMA2020 guidelines for certain items but none met all criteria. GRADE evaluation included 446 outcome measures, with 158 of moderate, 156 of low, and 132 of very low quality, indicating JAK inhibitors is effective in improving RA. According to radar chart, the average rank score was 13.13. One study achieved a balanced score across all dimensions, while 11 exceeded the average, five showed significant differences in PRIAMA2020 scores, and four in AMSTAR two scores. Despite summarizing the efficacy and safety of JAK inhibitors in treating RA, the included studies exhibited poor methodological and reporting quality, along with low-quality evidence overall. Therefore, caution is warranted among decision-makers regarding the use of JAK inhibitors in RA treatment. Urgent requirements include high-quality, multicenter studies investigating JAK inhibitors for RA. https://www.crd.york.ac.uk/PROSPERO, identifier 413415.

Influence of vitamin D in orthodontic tooth movement-a systematic review and meta-analysis of randomized controlled trials in humans.

Orchestration of tooth movement necessitates an equilibrium of bone synthesis and resorption. Vitamin D, through receptor-mediated actions, regulates the differentiation and maturation of osteoblasts and also induces osteoclastogenesis, maintaining this equilibrium. To analyze the impact of vitamin D in orthodontic tooth movement (OTM). A comprehensive exploration of the existing literature was conducted by systematic search through seven e-databases. The criteria for inclusion were established using the PICO format: Orthodontic patients treated with fixed appliance (P), administered with vitamin D3 (I), collated with appropriate control groups (C), with tooth movement as the primary outcome and root resorption, anchorage loss, gingival crevicular fluid (GCF) volume, pain perception, and alveolar bone density as the secondary outcome (O). After an extensive database search, 251 articles were obtained. Six articles were chosen following a stringent selection using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The critical appraisal of randomized control trials (RCTs) involved the meticulous application of the RoB 2 tool. The quantitative synthesis incorporated a subset of six articles only. In the meta-analysis investigating the influence of vitamin D on OTM, a notable disparity was evident between the vitamin D and control groups. Specifically, the standardized mean difference (SMD) stood at 1.43, accompanied by a 95% confidence interval (CI) ranging from 0.691 to 2.169 (P = .00154). For root resorption, the SMD was recorded at -0.51, with a 95% CI spanning from -3.051 to 2.031 (P = .11). The rate of tooth movement was enhanced by systemic and local administration of vitamin D. However, the inadequacy of available data is a hindrance in determining conclusively the impact of vitamin D on the extent of root resorption. The resolution of this quandary needs future human studies devoted toward investigating the influence of vitamin D in the realms of OTM and associated root resorption, thereby providing a definitive elucidation. Prospero- CRD42023491783.

Metabolic Characteristics of Gut Microbiota and Insomnia: Evidence from a Mendelian Randomization Analysis.

Insomnia is a common sleep disorder that significantly impacts individuals' sleep quality and daily life. Recent studies have suggested that gut microbiota may influence sleep through various metabolic pathways. This study aims to explore the causal relationships between the abundance of gut microbiota metabolic pathways and insomnia using Mendelian randomization (MR) analysis. This two-sample MR study used genetic data from the OpenGWAS database (205 gut bacterial pathway abundance) and the FinnGen database (insomnia-related data). We identified single nucleotide polymorphisms (SNPs) associated with gut bacterial pathway abundance as instrumental variables (IVs) and ensured their validity through stringent selection criteria and quality control measures. The primary analysis employed the inverse variance-weighted (IVW) method, supplemented by other MR methods, to estimate causal effects. The MR analysis revealed significant positive causal effects of specific carbohydrate, amino acid, and nucleotide metabolism pathways on insomnia. Key pathways, such as gluconeogenesis pathway (GLUCONEO.PWY) and TCA cycle VII acetate producers (PWY.7254), showed positive associations with insomnia (B > 0, p < 0.05). Conversely, pathways like hexitol fermentation to lactate, formate, ethanol and acetate pathway (P461.PWY) exhibited negative causal effects (B < 0, p < 0.05). Multivariable MR analysis confirmed the independent causal effects of these pathways (p < 0.05). Sensitivity analyses indicated no significant pleiotropy or heterogeneity, ensuring the robustness of the results. This study identifies specific gut microbiota metabolic pathways that play critical roles in the development of insomnia. These findings provide new insights into the biological mechanisms underlying insomnia and suggest potential targets for therapeutic interventions. Future research should further validate these causal relationships and explore how modulating gut microbiota or its metabolic products can effectively improve insomnia symptoms, leading to more personalized and precise treatment strategies.

Next-generation AMA1-based plasmids for enhanced heterologous expression in filamentous fungi.

Episomal AMA1-based plasmids are increasingly used for expressing biosynthetic pathways and CRISPR/Cas systems in filamentous fungi cell factories due to their high transformation efficiency and multicopy nature. However, the gene expression from AMA1 plasmids has been observed to be highly heterogeneous in growing mycelia. To overcome this limitation, here we developed next-generation AMA1-based plasmids that ensure homogeneous and strong expression. We achieved this by evaluating various degradation tags fused to the auxotrophic marker gene on the AMA1 plasmid, which introduces a more stringent selection pressure throughout multicellular fungal growth. With these improved plasmids, we observed in Aspergillus nidulans a 5-fold increase in the expression of a fluorescent reporter, a doubling in the efficiency of a CRISPRa system for genome mining, and a up to a 10-fold increase in the production of heterologous natural product metabolites. This strategy has the potential to be applied to diverse filamentous fungi.

Low platelet to high-density lipoprotein ratio predicts poor short-term prognosis in hepatitis B-related acute-on-chronic liver failure

BackgroundAcute-on-chronic liver failure (ACLF) is characterized by a systemic inflammatory response, predominantly associated with hepatitis B virus in the Asia-Pacific region, with a high short-term mortality rate. The platelet to high-density lipoprotein ratio (PHR) has been used to predict the prognosis of patients with various inflammatory diseases. We aim to is to use the PHR to predict the short-term prognosis of patients with HBV-ACLF.MethodIn this study, we retrospectively analyzed clinical data from 270 HBV-ACLF patients. Using logistic regression, we identified independent risk factors for short-term mortality and developed a prognostic model. This model was then validated, compared, and its clinical utility assessed via decision curve analysis (DCA).ResultsAmong the 270 HBV-ACLF patients, 98 patients died within 28 days. The deceased group exhibited a higher proportion of severe hepatic encephalopathy and ascites. Additionally, there was a statistically significant difference (P = 0.046) in the novel inflammation scoring system, PHR, between the two groups. Following stringent variable selection, PHR was identified as a predictive factor for short-term mortality in HBV-ACLF patients using logistic regression analysis (OR: 0.835 (0.756–0.999), P = 0.009), and it exhibited a synergistic effect with certain traditional scores. The prognostic model constructed based on PHR demonstrated a superior ability to predict short-term mortality compared to traditional scores such as Child-Turcotte-Pugh (AUC: 0.889). Evaluation using calibration curves and decision curve analysis (DCA) suggested its practical utility.ConclusionPHR can predict short-term mortality in patients, with a low PHR upon admission being associated with an increased risk of death.

TCR-Engineered T Cells Directed against Ropporin-1 Constitute a Safe and Effective Treatment for Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) has an urgent need for new therapies. We discovered Ropporin-1 (ROPN1) as a target to treat TNBC with T cells. ROPN1 showed high and homogenous expression in 90% of primary and metastatic TNBC but not in healthy tissues. Human leukocyte antigen-A2-binding peptides were detected via immunopeptidomics and predictions and used to retrieve T-cell receptors (TCR) from naïve repertoires. Following gene introduction into T cells and stringent selection, we retrieved a highly specific TCR directed against the epitope FLYTYIAKV that did not recognize noncognate epitopes from alternative source proteins. Notably, this TCR-mediated killing of three-dimensional (3D) tumoroids in vitro and tumor cells in vivo and outperformed standard-of-care drugs. Finally, the T-cell product expressing this TCR and manufactured using a clinical protocol fulfilled standard safety and efficacy assays. Collectively, we have identified and preclinically validated ROPN1 as a target and anti-ROPN1 TCR T cells as a treatment for the vast majority of patients with TNBC. Significance: Metastatic TNBC has a dismal prognosis. This study discovers Ropporin-1 as a target for T-cell therapy for most patients. The selected TCR is highly specific and sensitive in advanced models, and preclinical testing shows that the T-cell product expressing this TCR, manufactured according to good manufacturing practice, has favorable safety and potency.

Prediction of sepsis mortality in ICU patients using machine learning methods

ProblemSepsis, a life-threatening condition, accounts for the deaths of millions of people worldwide. Accurate prediction of sepsis outcomes is crucial for effective treatment and management. Previous studies have utilized machine learning for prognosis, but have limitations in feature sets and model interpretability.AimThis study aims to develop a machine learning model that enhances prediction accuracy for sepsis outcomes using a reduced set of features, thereby addressing the limitations of previous studies and enhancing model interpretability.MethodsThis study analyzes intensive care patient outcomes using the MIMIC-IV database, focusing on adult sepsis cases. Employing the latest data extraction tools, such as Google BigQuery, and following stringent selection criteria, we selected 38 features in this study. This selection is also informed by a comprehensive literature review and clinical expertise. Data preprocessing included handling missing values, regrouping categorical variables, and using the Synthetic Minority Over-sampling Technique (SMOTE) to balance the data. We evaluated several machine learning models: Decision Trees, Gradient Boosting, XGBoost, LightGBM, Multilayer Perceptrons (MLP), Support Vector Machines (SVM), and Random Forest. The Sequential Halving and Classification (SHAC) algorithm was used for hyperparameter tuning, and both train-test split and cross-validation methodologies were employed for performance and computational efficiency.ResultsThe Random Forest model was the most effective, achieving an area under the receiver operating characteristic curve (AUROC) of 0.94 with a confidence interval of ±0.01. This significantly outperformed other models and set a new benchmark in the literature. The model also provided detailed insights into the importance of various clinical features, with the Sequential Organ Failure Assessment (SOFA) score and average urine output being highly predictive. SHAP (Shapley Additive Explanations) analysis further enhanced the model’s interpretability, offering a clearer understanding of feature impacts.ConclusionThis study demonstrates significant improvements in predicting sepsis outcomes using a Random Forest model, supported by advanced machine learning techniques and thorough data preprocessing. Our approach provided detailed insights into the key clinical features impacting sepsis mortality, making the model both highly accurate and interpretable. By enhancing the model’s practical utility in clinical settings, we offer a valuable tool for healthcare professionals to make data-driven decisions, ultimately aiming to minimize sepsis-induced fatalities.

Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets

BackgroundReproducibility is a major concern in biomedical studies, and existing publication guidelines do not solve the problem. Batch effects and quality imbalances between groups of biological samples are major factors hampering reproducibility. Yet, the latter is rarely considered in the scientific literature.ResultsOur analysis uses 40 clinically relevant RNA-seq datasets to quantify the impact of quality imbalance between groups of samples on the reproducibility of gene expression studies. High-quality imbalance is frequent (14 datasets; 35%), and hundreds of quality markers are present in more than 50% of the datasets. Enrichment analysis suggests common stress-driven effects among the low-quality samples and highlights a complementary role of transcription factors and miRNAs to regulate stress response. Preliminary ChIP-seq results show similar trends. Quality imbalance has an impact on the number of differential genes derived by comparing control to disease samples (the higher the imbalance, the higher the number of genes), on the proportion of quality markers in top differential genes (the higher the imbalance, the higher the proportion; up to 22%) and on the proportion of known disease genes in top differential genes (the higher the imbalance, the lower the proportion). We show that removing outliers based on their quality score improves the resulting downstream analysis.ConclusionsThanks to a stringent selection of well-designed datasets, we demonstrate that quality imbalance between groups of samples can significantly reduce the relevance of differential genes, consequently reducing reproducibility between studies. Appropriate experimental design and analysis methods can substantially reduce the problem.

FUS-Mediated Inhibition of Myogenesis Elicited by Suppressing TNNT1 Production.

Myogenesis is a highly orchestrated process whereby muscle precursor cells, myoblasts, develop into muscle fibers to form skeletal muscle during embryogenesis and regenerate adult muscle. Here, we studied the RNA-binding protein FUS (fused in sarcoma), which has been implicated in muscular and neuromuscular pathologies but is poorly characterized in myogenesis. Given that FUS levels declined in human and mouse models of skeletal myogenesis, and that silencing FUS enhanced myogenesis, we hypothesized that FUS might be a repressor of myogenic differentiation. Interestingly, overexpression of FUS delayed myogenesis, accompanied by slower production of muscle differentiation markers. To identify the mechanisms through which FUS inhibits myogenesis, we uncovered RNA targets of FUS by ribonucleoprotein immunoprecipitation (RIP) followed by RNA-sequencing (RNA-seq) analysis. Stringent selection of the bound transcripts uncovered Tnnt1 mRNA, encoding troponin T1 (TNNT1), as a major effector of FUS influence on myogenesis. We found that in myoblasts, FUSretained Tnnt1 mRNA in the nucleus, preventing TNNT1 expression; however, reduction of FUS during myogenesis or by silencing FUS released Tnnt1 mRNA for export to the cytoplasm, enabling TNNT1 translation and promoting myogenesis. We propose that FUS inhibits myogenesis by suppressing TNNT1 expression through a mechanism of nuclear Tnnt1 mRNA retention.

Evaluating in vivo approaches for studying the roles of thymic DCs in T cell development in mice.

T cells express an enormous repertoire of T cell receptors, enabling them to recognize any potential antigen. This large repertoire undergoes stringent selections in the thymus, where receptors that react to self- or non-danger-associated- antigens are purged. We know that thymic tolerance depends on signals and antigens presented by the thymic antigen presenting cells, but we still do not understand precisely how many of these cells actually contribute to tolerance. This is especially true for thymic dendritic cells (DC), which are composed of diverse subpopulations that are derived from different progenitors. Although the importance of thymic DCs has long been known, the functions of specific DC subsets have been difficult to untangle. There remains insufficient systematic characterization of the ontogeny and phenotype of thymic APCs in general. As a result, validated experimental models for studying thymic DCs are limited. Recent technological advancement, such as multi-omics analyses, has enabled new insights into thymic DC biology. These recent findings indicate a need to re-evaluate the current tools used to study the function of these cells within the thymus. This review will discuss how thymic DC subpopulations can be defined, the models that have been used to assess functions in the thymus, and models developed for other settings that can be potentially used for studying thymic DCs.