Association of composite dietary antioxidant index with mortality in adults with hypertension: evidence from NHANES.

Objective: The objective of this study is to assess the correlation between composite dietary antioxidant index (CDAI) with all-cause mortality and cause-specific mortality in adults with hypertension. Methods: The cohort study comprised adult participants with hypertension from the NHANES database, spanning 9 cycles from 2001 to 2018. Follow-up was conducted until December 31, 2019. Multi-variable Cox regression analysis was utilized to ascertain hazard ratios (HR) and their corresponding 95% confidence intervals, evaluating the relationship between CDAI and the risks of all-cause and cause-specific mortality. To further investigate the association between CDAI and mortality rates in adults with hypertension, Kaplan-Meier survival curves, restricted cubic splines (RCS), subgroup analyses and sensitivity analyses were employed. Results: The analysis included 16,713 adults with hypertension (mean age 56.93 ± 0.23 years, 8,327 [49.61%] male). During the mean follow-up time 102.11 ± 1.22 months, with 3,908 (18.08%) all-cause mortality occurred, 1,082 (4.84%) cardiovascular mortality and 833 (3.80%) cancer mortality. Compared to the lowest quartile of CDAI, the weighted multivariate hazard ratios of participants in the highest quartile was 0.77 (95% CI, 0.68-0.87) for all-cause mortality, 0.83 (95% CI, 0.67-1.04) for cardiovascular mortality, and 0.64 (95% CI, 0.50-0.82) for cancer mortality. RCS analysis demonstrated a nonlinear association of CDAI with all-cause and cancer mortality, and a linear association between CDAI and cardiovascular mortality. The results were robust in subgroup analyses and sensitivity analyses. Conclusion: Higher CDAI is associated with reduced all-cause mortality, cardiovascular mortality, and cancer mortality in hypertensive adults. Our findings highlight the importance of an antioxidant diet in improving outcomes in adults with hypertension.

Revisiting Race and the Benefit of RAS Blockade in Heart Failure: A Meta-Analysis of Randomized Clinical Trials.

Importance: Concerns have arisen that renin-angiotensin system (RAS) blockers are less effective in Black patients than non-Black patients with heart failure and reduced ejection fraction (HFrEF). Objective: To determine whether the effects of RAS blockers on cardiovascular outcomes differ between Black patients and non-Black patients with HFrEF. Data Sources: MEDLINE and Embase databases through December 31, 2023. Study Selection: Randomized trials investigating the effect of RAS blockers on cardiovascular outcomes in adults with HFrEF that enrolled Black and non-Black patients. Data Extraction and Synthesis: Individual-participant data were extracted following Preferred Reporting Items for Systematic Reviews and Meta-analyses Independent Personal Data (PRISMA-IPD) reporting guidelines. Effects were estimated using a mixed-effects model using a 1-stage approach. Main Outcome and Measure: The primary outcome was first hospitalization for HF or cardiovascular death. Results: The primary analysis, based on the 3 placebo-controlled RAS inhibitor monotherapy trials, included 8825 patients (9.9% Black). Rates of death and hospitalization for HF were substantially higher in Black than non-Black patients. The hazard ratio (HR) for RAS blockade vs placebo for the primary composite was 0.84 (95% CI, 0.69-1.03) in Black patients and 0.73 (95% CI, 0.67-0.79) in non-Black patients (P for interaction = .14). The HR for first HF hospitalization was 0.89 (95% CI, 0.70-1.13) in Black patients and 0.62 (95% CI, 0.56-0.69) in non-Black patients (P for interaction = .006). Conversely, the corresponding HRs for cardiovascular death were 0.83 (95% CI, 0.65-1.07) and 0.84 (95% CI, 0.77-0.93), respectively (P for interaction = .99). For total hospitalizations for HF and cardiovascular deaths, the corresponding rate ratios were 0.82 (95% CI, 0.66-1.02) and 0.72 (95% CI, 0.66-0.80), respectively (P for interaction = .27). The supportive analyses including the 2 trials adding an angiotensin receptor blocker to background angiotensin-converting enzyme inhibitor treatment (n = 16 383) gave consistent findings. Conclusions and Relevance: The mortality benefit from RAS blockade was similar in Black and non-Black patients. Despite the smaller relative risk reduction in hospitalization for HF with RAS blockade in Black patients, the absolute benefit in Black patients was comparable with non-Black patients because of the greater incidence of this outcome in Black patients.

Serum Magnesium Levels Are Negatively Associated with Obesity and Abdominal Obesity in Type 2 Diabetes Mellitus: A Real-World Study.

Background: There remains controversy over the relationship between serum magnesium levels and obesity in type 2 diabetes mellitus (T2DM). Therefore, the aim of this study was to assess whether there is any association of serum magnesium levels with obesity and abdominal obesity in T2DM. Methods: This cross-sectional, real-world study was conducted in 8,010 patients with T2DM, which were stratified into quintiles according to serum magnesium levels. The clinical characteristics and the prevalence of obesity and abdominal obesity were compared across serum magnesium quintiles in T2DM. Regression analyses were used to evaluate the relationship of serum magnesium with obesity and abdominal obesity in T2DM (clinical trial registration number: ChiCTR1800015893). Results: After adjustment for age, sex, and duration of diabetes, the prevalence of obesity and abdominal obesity was significantly declined across magnesium quintiles (obesity: 51.3%, 50.8%, 48.9%, 45.3%, and 43.8%, respectively, P<0.001 for trend; abdominal obesity: 71.5%, 70.5%, 68.2%, 66.4%, and 64.5%, respectively, P=0.001 for trend). After controlling for confounders, there were clearly negative associations of serum magnesium levels and quintiles with obesity and abdominal obesity in T2DM. Moreover, C-reactive protein partly mediates the effect of serum magnesium on obesity and abdominal obesity (P=0.016 and P=0.004, respectively). Conclusion: The significantly negative relationship between serum magnesium and the risk of obesity and abdominal obesity was observed in T2DM. Furthermore, the independently negative association of serum magnesium with obesity may be explained by its anti-inflammatory functions. Serum magnesium levels may be applied to assess the risk of obesity and abdominal obesity in T2DM.

Assessing the safety of bedaquiline: insight from adverse event reporting system analysis.

Background: The development and marketing of Bedaquiline (BDQ) represent significant advancements in treating tuberculosis, particularly multidrug-resistant forms. However, comprehensive research into BDQ's real-world safety remains limited. Purpose: We obtained BDQ related adverse event (AE) information from the US Food and Drug Administration's Adverse Event Reporting System (FAERS) to assess its safety and inform drug usage. Methods: The AE data for BDQ from 2012 Q4 to 2023 Q3 was collected and standardized. Disproportionality analysis, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Multi-item Gamma Poisson Shrinker (MGPS), and Bayesian Confidence Propagation Neural Network (BCPNN) was used to quantify signals of BDQ-related AEs. Logistic regression was used to analyze the individual data of hepatotoxicity and drug-induced liver injury, and multiple linear regression models were established. Additionally, network pharmacology was employed to identify the potential biological mechanisms of BDQ-induced liver injury. Results: We identified 2017 case reports directly related to BDQ. Our analysis identified 341 Preferred Terms (PTs) characterizing these AEs across 27 System Organ Classes (SOC). An important discovery was the identification of AEs associated with ear and labyrinth disorders, which had not been documented in the drug's official leaflet before. Subgroup analysis revealed a negative correlation between BDQ-related liver injury and females (OR: 0.4, 95%CI: 0.3-0.6). In addition, via network pharmacology approach, a total of 76 potential targets for BDQ related liver injury were predicted, and 11 core target genes were selected based on the characterization of protein-protein interactions. The pathway linked to BDQ-induced liver injury was identified, and it was determined that the PI3K-Akt signaling pathway contained the highest number of associated genes. Conclusion: The analysis of the FAERS database revealed adverse events linked to BDQ, prompting the use of a network pharmacology approach to study the potential molecular mechanism of BDQ-induced liver injury. These findings emphasized the significance of drug safety and offered understanding into the mechanisms behind BDQ-induced liver injury. BDQ demonstrated distinct advantages, including reduced incidence of certain adverse events compared to traditional treatments such as injectable agents and second-line drugs. However, it is important to acknowledge the limitations of this analysis, including potential underreporting and confounding factors. This study provides valuable insights into the safety of BDQ and its role in the management of MDR-TB, emphasizing the need for continued surveillance and monitoring to ensure its safe and effective use.

Automated Cytometric Gating with Human-Level Performance Using Bivariate Segmentation.

Recent advances in cytometry technology have enabled high-throughput data collection with multiple single-cell protein expression measurements. The significant biological and technical variance between samples in cytometry has long posed a formidable challenge during the gating process, especially for the initial gates which deal with unpredictable events, such as debris and technical artifacts. Even with the same experimental machine and protocol, the target population, as well as the cell population that needs to be excluded, may vary across different measurements. To address this challenge and mitigate the labor-intensive manual gating process, we propose a deep learning framework UNITO to rigorously identify the hierarchical cytometric subpopulations. The UNITO framework transformed a cell-level classification task into an image-based semantic segmentation problem. For reproducibility purposes, the framework was applied to three independent cohorts and successfully detected initial gates that were required to identify single cellular events as well as subsequent cell gates. We validated the UNITO framework by comparing its results with previous automated methods and the consensus of at least four experienced immunologists. UNITO outperformed existing automated methods and differed from human consensus by no more than each individual human. Most critically, UNITO framework functions as a fully automated pipeline after training and does not require human hints or prior knowledge. Unlike existing multi-channel classification or clustering pipelines, UNITO can reproduce a similar contour compared to manual gating for each intermediate gating to achieve better interpretability and provide post hoc visual inspection. Beyond acting as a pioneering framework that uses image segmentation to do auto-gating, UNITO gives a fast and interpretable way to assign the cell subtype membership, and the speed of UNITO will not be impacted by the number of cells from each sample. The pre-gating and gating inference takes approximately 2 minutes for each sample using our pre-defined 9 gates system, and it can also adapt to any sequential prediction with different configurations.

Multiple instance learning for eosinophil quantification of sinonasal histopathology images: A hierarchical determination on whole slide images.

KEY POINTS: We proposed a hierarchical framework including an unsupervised candidate image selection and a weakly supervised patch image detection based on multiple instance learning (MIL) to effectively estimate eosinophil quantities in tissue samples from whole slide images. MIL is an innovative approach that can help deal with the variability in cell distribution detection and enable automated eosinophil quantification from sinonasal histopathological images with a high degree of accuracy. The study lays the foundation for further research and development in the field of automated histopathological image analysis, and validation on more extensive and diverse datasets will contribute to real-world application.

[Transcriptomic characteristics analysis of bone from chronic osteomyelitis].

OBJECTIVE: To explore the molecular mechanism of chronic osteomyelitis and to clarify the role of MAPK signal pathway in the pathogenesis of chronic osteomyelitis, by collecting and analyzing the transcriptional information of bone tissue in patients with chronic osteomyelitis. METHODS: Four cases of traumatic osteomyelitis in limbs from June 2019 to June 2020 were selected, and the samples of necrotic osteonecrosis from chronic osteomyelitis (necrotic group), and normal bone tissue (control group) were collected. Transcriptome information was collected by Illumina Hiseq Xten high throughput sequencing platform, and the gene expression in bone tissue was calculated by FPKM. The differentially expressed genes were screened by comparing the transcripts of the Necrotic group and control group. Genes were enriched by GO and KEGG. MAP3K7 and NFATC1 were selected as differential targets in the verification experiments, by using rat osteomyelitis animal model and immunohistochemical analysis. RESULTS: A total of 5548 differentially expressed genes were obtained by high throughput sequencing by comparing the necrotic group and control group, including 2701 up-regulated and 2847 down-regulated genes. The genes enriched in MAPK pathway and osteoclast differentiation pathway were screened, the common genes expressed in both MAPK and osteoclast differentiation pathway were (inhibitor of nuclear factor κ subunit Beta, IκBKß), (mitogen-activated protein kinase 7, MAP3K7), (nuclear factor of activated t cells 1, NFATC1) and (nuclear factor Kappa B subunit 2, NFκB2). In rat osteomyelitis model, MAP3K7 and NFATC1 were highly expressed in bone marrow and injured bone tissue. CONCLUSION: Based on the transcriptome analysis, the MAPK signaling and osteoclast differentiation pathways were closely related to chronic osteomyelitis, and the key genes IκBKß, MAP3K7, NFATC1, NFκB2 might be new targets for clinical diagnosis and therapy of chronic osteomyelitis.

A novel ESIPT fluorescent probe for early detection and assessment of ferroptosis-mediated acute kidney injury via peroxynitrite fluctuation.

BACKGROUND: Acute kidney injury (AKI) poses a severe risk to public health, mostly manifested by damage and death of renal tubular epithelial cells. However, routine blood examination, a conventional approach for clinical detection of AKI, is not available for identifying early-stage AKI. Plenty of reported methods were lack of early biomarkers and real time evaluation tools, which resulted in a vital challenge for early diagnosis of AKI. Therefore, developing novel probes for early detection and assessment of AKI is exceedingly crucial. RESULTS: Based on ESIPT mechanism, a new fluorescent probe (MEO-NO) with 2-(2'-hydroxyphenyl) benzothiazole (HBT) derivatives as fluorophore has been synthesized for dynamic imaging peroxynitrite (ONOO-) levels in ferroptosis-mediated AKI. Upon the addition of ONOO-, MEO-NO exhibited obvious fluorescence changes, a significant Stokes shift (130 nm) and rapid response (approximately 45 s), and featured exceptional sensitivity (LOD = 7.28 nM) as well as high selectivity from the competitive species at physiological pH. In addition, MEO-NO was conducive to the biological depth imaging ONOO- in cells, zebrafish, and mice. Importantly, MEO-NO could monitor ONOO- levels during sorafenib-induced ferroptosis and CP-induced AKI. With the assistance of MEO-NO, we successfully visualized and tracked ONOO- variations for early detection and assessment of ferroptosis-mediated AKI in cells, zebrafish and mice models. SIGNIFICANCE AND NOVELTY: Benefiting from the superior performance of MEO-NO, experimental results further demonstrated that the levels of ONOO- was overexpressed during ferroptosis-mediated AKI in cells, zebrafish, and mice models. The developed novel probe MEO-NO provided a strong visualization tool for imagining ONOO-, which might be a potential method for the prevention, diagnosis, and treatment of ferroptosis-mediated AKI.

Mineralocorticoid Receptor Antagonists in Patients With Heart Failure and Impaired Renal Function.

BACKGROUND: Kidney dysfunction often leads to reluctance to start or continue life-saving heart failure (HF) therapy. OBJECTIVES: This study sought to examine the efficacy and safety of mineralocorticoid receptor antagonists (MRAs) in patients with HF with reduced ejection fraction experiencing significant kidney dysfunction. METHODS: We pooled individual patient data from the RALES (Randomized Aldactone Evaluation Study) and EMPHASIS-HF (Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure) trials. The association between MRA treatment and outcomes was assessed according to whether the estimated glomerular filtration rate (eGFR) declined to <30 mL/min/1.73 m2 or not. The primary outcome was cardiovascular death or HF hospitalization. RESULTS: Among 4,355 patients included, 295 (6.8%) experienced a deterioration of eGFR after randomization to <30 mL/min/1.73 m2. These patients had more impaired baseline cardiac and kidney function (eGFR 47.3 ± 13.4 mL/min/1.73 m2 vs 70.5 ± 21.8 mL/min/1.73 m2) and had a higher risk of the primary outcome than patients without eGFR deterioration (HR: 2.49; 95% CI: 2.01-3.08; P < 0.001). However, the risk reduction in the primary outcome with MRA therapy was similar in those who experienced a decrease in eGFR to <30 mL/min/1.73 m2 (HR: 0.65; 95% CI: 0.43-0.99) compared with those who did not (HR: 0.63; 95% CI: 0.56-0.71) (Pinteraction = 0.87). In patients with a decrease in eGFR to <30 mL/min/1.73 m2, 21 fewer individuals (per 100 person-years) experienced the primary outcome with MRA treatment, vs placebo, compared with an excess of 3 more patients with severe hyperkalemia (>6.0 mmol/L). CONCLUSIONS: Because patients experiencing a decrease in eGFR to <30 mL/min/1.73 m2 are at very high risk, the absolute risk reduction with an MRA in these patients is large and this decline in eGFR should not automatically lead to treatment discontinuation.

General Fabrication of Robust Alloyed Metal Anodes for High-Performance Metal Batteries.

Revitalizing metal anodes for rechargeable batteries confronts challenges such as dendrite formation, limited cyclicity, and suboptimal energy density. Despite various efforts, a practical fabrication method for dendrite-free metal anodes remains unavailable. Herein, focusing on Li as exemplar, a general strategy is reported to enhance reversibility of the metal anodes by forming alloyed metals, which is achieved by induction heating of 3D substrate, lithiophilic metals, and Li within tens of seconds. It is demonstrated that preferred alloying interactions between substrates and lithiophilic metals created a lithiophilic metal-rich region adjacent to the substrate, serving as ultrastable lithiophilic host to guide dendrite-free deposition, particularly during prolonged high-capacity cycling. Simultaneously, an alloying between lithiophilic metals and Li creates a Li-rich region adjacent to electrolyte that reduces nucleation overpotential and constitutes favorable electrolyte-Li interface. The resultant composite Li anodes paired with high areal loading LiNi0.8Co0.1Mn0.1O2 cathodes achieve superior cycling stability and remarkable energy density above 1200 Wh L-1 (excluding packaging). Furthermore, this approach shows broader applicability to other metal anodes plagued by dendrite-related challenges, such as Na and Zn. Overall, this work paves the way for development of commercially viable metal-based batteries that offer a combination of safety, high energy density, and durability.

Effect of anterior segment structure on vault and position after implantable collamer lens implantation.

PURPOSE: To evaluate the effect of anterior-segment structure on vault and position after implantable collamer lens (ICL) implantation using ultrasound biomicroscopy. METHODS: The retrospective case-control study included insufficient vault eyes (<250 µm), ideal vault eyes (250-750 µm), and excessive vault eyes (>750 µm). The preoperative biometric parameters of the anterior-segment structure and basic data between the three groups were analyzed using one-way analysis of variance. RESULTS: There were significant differences ( P < 0.05) between the three groups in maximum ciliary body thickness (CBT max ), iris-zonule distance (IZD), and trabecular-ciliary angle (TCA). The vault gradually decreased as CBT max decreased and TCA increased. In the pairwise comparison, the CBT max comparison between the insufficient vault (<250 µm) group and the excessive vault (>750 µm) group was statistically significant ( P = 0.024, 95% CI: -0.17-0.017 µm); the TCA comparison between the insufficient vault (<250 µm) group and the excessive vault (>750 µm) group was statistically significant ( P = 0.005, 95% CI: 1.78°-12.15°); The IZD comparison between the insufficient vault (<250 µm) group and the excessive vault (>750 µm) group was statistically significant ( P = 0.037, 95% CI: 0.0027-0.1119 µm). The analysis of 284 ICL haptics locations showed that there were 16.67%, 32.69%, and 70.83% haptics located in the ciliary sulcus in three groups, respectively. CONCLUSION: The vault and ICL haptics position are related to anterior-segment structure. A thinner and posteriorly positioned ciliary body would increase the risk of low vault and fewer ICL haptics located in the ciliary sulcus after ICL implantation. This provides guidance for the selection of the ICL size and placement position before surgery.

Federated Learning With Only Positive Labels by Exploring Label Correlations.

Federated learning (FL) aims to collaboratively learn a model by using the data from multiple users under privacy constraints. In this article, we study the multilabel classification (MLC) problem under the FL setting, where trivial solution and extremely poor performance may be obtained, especially when only positive data with respect to a single class label is provided for each client. This issue can be addressed by adding a specially designed regularizer on the server side. Although effective sometimes, the label correlations are simply ignored and thus suboptimal performance may be obtained. Besides, it is expensive and unsafe to exchange user's private embeddings between server and clients frequently, especially when training model in the contrastive way. To remedy these drawbacks, we propose a novel and generic method termed federated averaging (FedAvg) by exploring label correlations (FedALCs). Specifically, FedALC estimates the label correlations in the class embedding learning for different label pairs and utilizes it to improve the model training. To further improve the safety and also reduce the communication overhead, we propose a variant to learn fixed class embedding for each client, so that the server and clients only need to exchange class embeddings once. Extensive experiments on multiple popular datasets demonstrate that our FedALC can significantly outperform the existing counterparts.

Leonurus japonicus Houtt. modulates neuronal apoptosis in intracerebral hemorrhage: Insights from network pharmacology and molecular docking.

ETHNOPHARMACOLOGICAL RELEVANCE: Leonurus japonicus Houtt. (Labiatae), commonly known as Chinese motherwort, is a herbaceous flowering plant that is native to Asia. It is widely acknowledged in traditional medicine for its diuretic, hypoglycemic, antiepileptic properties and neuroprotection. Currently, Leonurus japonicus (Leo) is included in the Pharmacopoeia of the People's Republic of China. Traditional Chinese Medicine (TCM) recognizes Leo for its myriad pharmacological attributes, but its efficacy against ICH-induced neuronal apoptosis is unclear. AIMS OF THE STUDY: This study aimed to identify the potential targets and regulatory mechanisms of Leo in alleviating neuronal apoptosis after ICH. MATERIALS AND METHODS: The study employed network pharmacology, UPLC-Q-TOF-MS technique, molecular docking, pharmacodynamic studies, western blotting, and immunofluorescence techniques to explore its potential mechanisms. RESULTS: Leo was found to assist hematoma absorption, thus improving the neurological outlook in an ICH mouse model. Importantly, molecular docking highlighted JAK as Leo's potential therapeutic target in ICH scenarios. Further experimental evidence demonstrated that Leo adjusts JAK1 and STAT1 phosphorylation, curbing Bax while augmenting Bcl-2 expression. CONCLUSION: Leo showcases potential in mitigating neuronal apoptosis post-ICH, predominantly via the JAK/STAT mechanism.

Robust Offloading for Edge Computing-Assisted Sensing and Communication Systems: A Deep Reinforcement Learning Approach.

In this paper, we consider an integrated sensing, communication, and computation (ISCC) system to alleviate the spectrum congestion and computation burden problem. Specifically, while serving communication users, a base station (BS) actively engages in sensing targets and collaborates seamlessly with the edge server to concurrently process the acquired sensing data for efficient target recognition. A significant challenge in edge computing systems arises from the inherent uncertainty in computations, mainly stemming from the unpredictable complexity of tasks. With this consideration, we address the computation uncertainty by formulating a robust communication and computing resource allocation problem in ISCC systems. The primary goal of the system is to minimize total energy consumption while adhering to perception and delay constraints. This is achieved through the optimization of transmit beamforming, offloading ratio, and computing resource allocation, effectively managing the trade-offs between local execution and edge computing. To overcome this challenge, we employ a Markov decision process (MDP) in conjunction with the proximal policy optimization (PPO) algorithm, establishing an adaptive learning strategy. The proposed algorithm stands out for its rapid training speed, ensuring compliance with latency requirements for perception and computation in applications. Simulation results highlight its robustness and effectiveness within ISCC systems compared to baseline approaches.

Oxidative Dissolution Process of Sphalerite in Fe2(SO4)3-O3 System: Implications for Heavy Metals Removal and Recovery.

Metal sulfides in waste rocks and tailings are susceptible to serious soil and water contamination due to the generation of acid mine drainage (AMD) during stockpiling. The hydrometallurgical process is one of the most essential heavy metal remediation technologies through harmless disposal and resource utilization of the waste sulfides. However, atmospheric hydrometallurgy of sulfides still faces great challenges due to low leaching efficiency and high cost. In this work, we proposed a cooperative leaching system (Fe2(SO4)3-O3) and investigated the oxidative dissolution process of sphalerite (ZnS). Under the optimal conditions, the extracted zinc reached 97.8%. Reactive oxygen species (ROS) (·OH, 1O2 and ·O2-) were identified in the radical quenching experiments. The dissolution of sphalerite did not show passivation due to the ozone's capability to oxidize the sulfur in sphalerite to sulfate. In addition, stirring rate, O3 inlet concentration, and Fe2(SO4)3 concentration had a significant effect on the dissolution of sphalerite. Meanwhile, the apparent activation energy was 24.11 kJ/mol based on kinetic fitting, which indicated that the controlling step of the reaction was mainly a diffusion process. This work demonstrated the cooperative effect of sphalerite leaching in the O3-Fe2(SO4)3 system and provided a theoretical reference for efficient and atmospheric dissolution of sphalerite.

Multiplexed Serum Biomarkers to Discriminate Nonviable and Ectopic Pregnancy.

OBJECTIVE: The use of multiplexed biomarkers may improve the diagnosis of normal and abnormal early pregnancies. In this study we assessed 24 markers with multiple machine learning-based methodologies to evaluate combinations of top candidates to develop a multiplexed prediction model for identification of 1) viability and 2) location of an early pregnancy. DESIGN: A nested case-control design evaluating the predictive ability and discrimination of biomarkers in patients at risk of early pregnancy failure in the first trimester to classify viability and location SUBJECTS: 218 individuals with a symptomatic (pain and/or bleeding) early pregnancy: 75 with an ongoing intrauterine gestation, 68 ectopic pregnancies, and 75 miscarriages. INTERVENTIONS: Serum values of 24 biomarkers were assessed in the same patients. Multiple machine learning-based methodologies to evaluate combinations of these top candidates to develop a multiplexed prediction model for identification of 1) a nonviable pregnancy (ongoing intrauterine pregnancy vs miscarriage or ectopic pregnancy) and 2) an ectopic pregnancy (ectopic pregnancy vs ongoing intrauterine pregnancy or miscarriage). MAIN OUTCOME MEASURES: The predicted classification by each model was compared to actual diagnosis and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), conclusive classification, and accuracy were calculated. RESULTS: Models using classification regression tree analysis using three markers (PSG3, CG-Alpha and PAPPA) were able to predict a maximum sensitivity 93.3%, a maximum specificity 98.6%. The model with the highest accuracy was 97.4% (with 70.2% receiving classification). Models using an overlapping group of three markers (sFLT, PSG3 and TFP12) achieved a maximum sensitivity of 98.5%. and a maximum specificity of 95.3%. The model with the highest accuracy was 94.4% (with 65.6% receiving classification). When the models were used simultaneously the conclusive classification increased to 72.7% with an accuracy 95.9%. The predictive ability of the biomarkers random forest produced similar test characteristics when using 11 predictive markers. CONCLUSION: We have demonstrated a pool of biomarkers from divergent biological pathways that can be used to classify individuals with potential early pregnancy loss. The biomarkers CG-Alpha, PAPPA and PSG3 can be used to predict viability and sFLT, TPFI2 and PSG3 can be used to predict pregnancy location.

Acetyl-CoA metabolic accumulation promotes hepatocellular carcinoma metastasis via enhancing CXCL1-dependent infiltration of tumor-associated neutrophils.

High levels of acetyl-CoA are considered a key metabolic feature of metastatic cancers. However, the impacts of acetyl-CoA metabolic accumulation on cancer microenvironment remodeling are poorly understood. In this study, using human hepatocellular carcinoma (HCC) tissues and orthotopic xenograft models, we found a close association between high acetyl-CoA levels in HCCs, increased infiltration of tumor-associated neutrophils (TANs) in the cancer microenvironment and HCC metastasis. Cytokine microarray and enzyme-linked immunosorbent assays (ELISA) revealed the crucial role of the chemokine (C-X-C motif) ligand 1(CXCL1). Mechanistically, acetyl-CoA accumulation induces H3 acetylation-dependent upregulation of CXCL1 gene expression. CXCL1 recruits TANs, leads to neutrophil extracellular traps (NETs) formation and promotes HCC metastasis. Collectively, our work linked the accumulation of acetyl-CoA in HCC cells and TANs infiltration, and revealed that the CXCL1-CXC receptor 2 (CXCR2)-TANs-NETs axis is a potential target for HCCs with high acetyl-CoA levels.

Robotic gastrectomy was reliable option for overweight patients with gastric cancer: a propensity score matching study.

BACKGROUND: The role of minimally invasive surgery using robotics versus laparoscopy in resectable gastric cancer patients with a high body mass index (BMI) remains controversial. METHODS: A total of 482 gastric adenocarcinoma patients with BMI ≥ 25 kg/m2 who underwent minimally invasive radical gastrectomy between August 2016 and December 2019 were retrospectively analyzed, including 109 cases in the robotic gastrectomy (RG) group and 321 cases in the laparoscopic gastrectomy (LG) group. Propensity score matching (PSM) with a 1:1 ratio was performed, and the perioperative outcomes, lymph node dissection, and 3-year overall survival (OS) and disease-free survival (DFS) rates were compared. RESULTS: After PSM, 109 patients were included in each of the RG and LG groups, with balanced baseline characteristics. Compared with the LG group, the RG group had similar intraoperative estimated blood loss [median (IQR) 30 (20-50) vs. 35 (30-59) mL, median difference (95%CI) - 5 (- 10 to 0)], postoperative complications [13.8% vs. 18.3%, OR (95%CI) 0.71 (0.342 to 1.473)], postoperative recovery, total harvested lymph nodes [(34.25 ± 13.43 vs. 35.44 ± 14.12, mean difference (95%CI) - 1.19 (- 4.871 to 2.485)] and textbook outcomes [(81.7% vs. 76.1%, OR (95%CI) 1.39 (0.724 to 2.684)]. Among pathological stage II-III patients receiving chemotherapy, the initiation of adjuvant chemotherapy in the RG group was similar to that in the LG group [median (IQR): 28 (25.5-32.5) vs. 32 (27-38.5) days, median difference (95%CI) - 3 (- 6 to 0)]. The 3-year OS (RG vs. LG: 80.7% vs. 81.7%, HR = 1.048, 95%CI 0.591 to 1.857) and DFS (78% vs. 76.1%, HR = 0.996, 95%CI 0.584 to 1.698) were comparable between the two groups. CONCLUSION: RG conferred comparable lymph node dissection, postoperative recovery, and oncologic outcomes in a selected cohort of patients with BMI ≥ 25 kg/m2.

Establishing and Validating an Innovative Focal Adhesion-Linked Gene Signature for Enhanced Prognostic Assessment in Endometrial Cancer.

Studies have highlighted the significant role of focal adhesion signaling in cancer. Nevertheless, its specific involvement in the pathogenesis of endometrial cancer and its clinical significance remains uncertain. We analyzed TCGA-UCEC and GSE119041 datasets with corresponding clinical data to investigate focal adhesion-related gene expression and their clinical significance. A signature, "FA-riskScore," was developed using LASSO regression in the TCGA cohort and validated in the GSE dataset. The FA-riskScore was compared with four existing models in terms of their prediction performance. We employed univariate and multivariate Cox regression analyses towards FA-riskScore to assess its independent prognostic value. A prognostic evaluation nomogram based on our model and clinical indexes was established subsequently. Biological and immune differences between high- and low-risk groups were explored through functional enrichment, PPI network analysis, mutation mining, TME evaluation, and single-cell analysis. Sensitivity tests on commonly targeted drugs were performed on both groups, and Connectivity MAP identified potentially effective molecules for high-risk patients. qRT-PCR validated the expressions of FA-riskScore genes. FA-riskScore, based on FN1, RELN, PARVG, and PTEN, indicated a poorer prognosis for high-risk patients. Compared with published models, FA-riskScore achieved better and more stable performance. High-risk groups exhibited a more challenging TME and suppressive immune status. qRT-PCR showed differential expression in FN1, RELN, and PTEN. Connectivity MAP analysis suggested that BU-239, potassium-canrenoate, and tubocurarine are effective for high-risk patients. This study introduces a novel prognostic model for endometrial cancer and offers insights into focal adhesion's role in cancer pathogenesis.