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This study retrospectively collected clinical data from 480 patients with connective tissue diseases (CTDs) at Nanjing First Hospital between August 2019 and December 2023 to develop and validate a multi-classification machine learning (ML) model for assessing depression risk. Addressing the limitations of traditional assessment tools, six ML models were constructed using univariate analysis and the LASSO algorithm, with the categorical boosting (Catboost) model emerging as the best performer, demonstrating strong predictive ability across different depression severity levels (none_F1 = 0.879, mild_F1 = 0.627, moderate and severe_F1 = 0.588). Additionally, the study provided an interpretation of the best-performing model using SHAP and developed a user-friendly R Shiny application ( https://macnomogram.shinyapps.io/Catboost/ ) to facilitate clinical use. The findings suggest that the Catboost model represents a significant advancement in assessing depression risk among CTD patients, highlighting the potential of ML in enhancing mental health management for this patient population.

Aneurysmal subarachnoid hemorrhage (aSAH) is a significant cause of morbidity and mortality throughout the world. Dynamic nomogram to predict the prognosis of elderly aSAH patients after endovascular coiling has not been reported. Thus, we aimed to develop a clinically useful dynamic nomogram to predict the risk of 6-month unfavorable outcome in elderly aSAH patients after endovascular coiling. We conducted a retrospective study including 209 elderly patients admitted to the People's Hospital of Hunan Province for aSAH from January 2016 to June 2021. The main outcome measure was 6-month unfavorable outcome (mRS ≥ 3). We used multivariable logistic regression analysis and forwarded stepwise regression to select variables to generate the nomogram. We assessed the discriminative performance using the area under the curve (AUC) of receiver-operating characteristic and the risk prediction model's calibration using the Hosmer-Lemeshow goodness-of-fit test. The decision curve analysis (DCA) and the clinical impact curve (CIC) were used to measure the clinical utility of the nomogram. The cohort's median age was 70 (interquartile range: 68-74) years and 133 (36.4%) had unfavorable outcomes. Age, using a ventilator, white blood cell count, and complicated with cerebral infarction were predictors of 6-month unfavorable outcome. The AUC of the nomogram was 0.882 and the Hosmer-Lemeshow goodness-of-fit test showed good calibration of the nomogram ( = 0.3717). Besides, the excellent clinical utility and applicability of the nomogram had been indicated by DCA and CIC. The eventual value of unfavorable outcome risk could be calculated through the dynamic nomogram. This study is the first visual dynamic online nomogram that accurately predicts the risk of 6-month unfavorable outcome in elderly aSAH patients after endovascular coiling. Clinicians can effectively improve interventions by taking targeted interventions based on the scores of different items on the nomogram for each variable.

Background This study aimed to predict metastasis risk and identify prognostic factors of gastrointestinal signet ring cell carcinoma (SRCC) using data from the SEER database, the largest cancer dataset in North America. Methods Data were obtained from the SEER database, covering 17 cancer registries from 2004 to 2020. Demographic and clinical data included sex, age, race, tumor location, size, pathological grade, stage, overall survival time, and treatment modalities. Statistical analyses were conducted using SPSS and R software. Propensity Score Matching (PSM) ensured comparable baseline characteristics between gastric cancer (GC) and colorectal cancer (CRC) groups. LASSO regression analysis identified predictors of metastasis, leading to the construction of predictive models using the lrm function in R. Nomograms were visualized with the “rms” package and assessed via ROC curves, calibration curves, and decision curve analysis (DCA). Cox regression analyses identified prognostic indicators for overall survival (OS), and Kaplan–Meier curves compared OS between high-risk and low-risk groups. Results From 2004 to 2020, 7680 SRCC patients were identified, including 4980 GC and 2700 CRC patients. CRC patients were older and had larger tumors, higher staging, and worse differentiation. Nomograms demonstrated good discriminative ability, with AUCs of 0.704 and 0.694 for GC, and 0.694 and 0.701 for CRC in training and validation cohorts, respectively. The DCA curve indicates that this predictive model has a high gain in predicting metastasis and OS. Conclusions The nomograms effectively predicted metastasis risk and OS in metastatic SRCC patients, offering clinical utility in stratifying patients and guiding treatment decisions, thereby enhancing personalized treatment approaches.

This work examines the impact of ice habit models on snowfall rate (SFR) derived from space‐borne passive microwave observations. SFR retrieval is highly sensitive to ice habit assumptions. Comparisons of the SFRs based on Cloud Profiling Radar, ERA5, and National Oceanic and Atmospheric Administration Stage IV indicate that dense and sphere‐like particles tend to overestimate SFR, whereas most non‐spherical particles underestimate it. SFR biases differ by more than 200% between the most extreme cases. Although several ice habits perform well globally, an optimal choice of ice habit is environmentally dependent: A hollow bullet rosette works well in moist and warm conditions, whereas a solid ice sphere excels in cold and dry conditions. A machine learning model integrates multiple ice habits into the SFR algorithm by adjusting their contributions based on environmental conditions. This multi‐ice habit approach improves statistical metrics by ∼10% overall (by 40% in deep clouds) compared to a single ice habit method.

Increasing evidence suggests that circular RNAs (circRNAs) play critical roles in various pathophysiological activities. However, the role of circRNAs in inflammatory bowel disease (IBD) remains unclear. Here we report the potential roles of hsa_circRNA_103765 in regulating cell apoptosis induced by TNF-α in Crohn’s disease (CD). We identify that CircRNA_103765 expression was significantly upregulated in peripheral blood mononuclear cells (PBMCs) of patients with active IBD. A positive correlation with TNF-α significantly enhanced circRNA_103765 expression in CD, which was significantly reversed by anti-TNF-α mAb (infliximab) treatment. In vitro experiments showed that TNF-α could induce the expression of circRNA_103765, which was cell apoptosis dependent, while silencing of circRNA_103765 could protect human intestinal epithelial cells (IECs) from TNF-α-induced apoptosis. In addition, circRNA_103765 acted as a molecular sponge to adsorb the miR-30 family and impair the negative regulation of Delta-like ligand 4 (DLL4). Collectively, CircRNA_103765 is a novel important regulator of the pathogenesis of IBD via sponging miR-30 family-mediated DLL4 expression changes. Blockade of circRNA_103765 could serve as a novel approach for the treatment of IBD patients.

Radiotherapy is widely used in cancer treatment in both curative and palliative care due to its good safety profile and broad clinical availability. It not only directly destroys tumor cells by damaging their DNA but also plays a critical immunomodulatory role, making it a potential combination partner for immunotherapy. Radiotherapy-induced immune effects are complex. They could enhance antitumor immunity by releasing tumor antigens but also promote tumor immune evasion by adaptively regulating immunosuppressive molecules, such as phagocytosis checkpoints. However, the effects of radiotherapy on phagocytosis checkpoints are not fully elaborated compared to T cell-associated immune checkpoints. Phagocytosis checkpoints are regulated by a series of receptor-ligand binding molecules, respectively on the tumor cells and phagocytes, which mediate pro-phagocytosis or anti-phagocytosis signals, modulate tumor antigen presentation, and further determine the infiltration of tumor-specific cytotoxic T cells in the tumor microenvironment. Radiotherapy regulates the different phagocytosis checkpoints on the tumor cells and phagocytes to modulate phagocytic clearance and reshape the irradiated tumor microenvironment. Therefore, radiotherapy in combination with phagocytosis checkpoints-associated immunotherapy can be a promising antitumor approach by considering the type, dose, and sequence of this combinatory regimen as well as the biomarkers for patient selection. This review attempts to summarize the cross-effects of radiotherapy and phagocytosis checkpoints and their combination strategies to enhance the efficiency of radiotherapy and improve the survival of cancer patients. Opportunities built on the roles of the phagocytosis checkpoint in radiotherapy are duly warranted.

Background As an important vegetable crop, cultivated lettuce is grown worldwide and a great variety of agronomic traits have been preserved within germplasm collections. The mechanisms underlying these phenotypic variations remain to be elucidated in association with sequence variations. Compared with single nucleotide polymorphisms, structural variations (SVs) that have more impacts on gene functions remain largely uncharacterized in the lettuce genome. Results Here, we produced a comprehensive SV set for 333 wild and cultivated lettuce accessions. Comparison of SV frequencies showed that the SVs prevalent in L. sativa affected the genes enriched in carbohydrate derivative catabolic and secondary metabolic processes. Genome-wide association analysis of seven agronomic traits uncovered potentially causal SVs associated with seed coat color and leaf anthocyanin content. Conclusion Our work characterized a great abundance of SVs in the lettuce genome, and provides a valuable genomic resource for future lettuce breeding.

Ferroptosis plays important roles both in normal physiology and multiple human diseases. It is well known that selenoprotein named glutathione peroxidase 4 (GPX4) is a crucial regulator for ferroptosis. However, it remains unknown whether other selenoproteins responsible for the regulation of ferroptosis, particularly in gut diseases. In this study, it is observed that Selenoprotein I (Selenoi) prevents ferroptosis by maintaining ether lipids homeostasis. Specific deletion of Selenoi in intestinal epithelial cells induced the occurrence of ferroptosis, leading to impaired intestinal regeneration and compromised colonic tumor growth. Mechanistically, Selenoi deficiency causes a remarkable decrease in ether‐linked phosphatidylethanolamine (ePE) and a marked increase in ether‐linked phosphatidylcholine (ePC). The imbalance of ePE and ePC results in the upregulation of phospholipase A2, group IIA (Pla2g2a) and group V (Pla2g5), as well as arachidonate‐15‐lipoxygenase (Alox15), which give rise to excessive lipid peroxidation. Knockdown of PLA2G2A, PLA2G5, or ALOX15 can reverse the ferroptosis phenotypes, suggesting that they are downstream effectors of SELENOI. Strikingly, GPX4 overexpression cannot rescue the ferroptosis phenotypes of SELENOI‐knockdown cells, while SELENOI overexpression can partially rescue GPX4‐knockdown‐induced ferroptosis. It suggests that SELENOI prevents ferroptosis independent of GPX4. Taken together, these findings strongly support the notion that SELENOI functions as a novel suppressor of ferroptosis during colitis and colon tumorigenesis. Specific deletion of Selenoi in intestinal epithelial cells induces the occurrence of ferroptosis, leading to impaired intestinal regeneration and compromised colonic tumor growth. Mechanistically, Selenoi deficiency causes a remarkable decrease in ether‐linked phosphatidylethanolamine (ePE) and a marked increase in ether‐linked phosphatidylcholine (ePC). The imbalance of ePE and ePC results in excessive lipid peroxidation.

Flower-like cobalt–molybdenum mixed-oxide microspheres (CoMo-FMs) with hierarchical architecture were successfully synthesized via a hydrothermal process and subsequent calcination step. The characterization results show that CoMo-FMs were assembled from ultrathin mesoporous nanosheets with thicknesses of around 4.0 nm, providing the composite with a large pore volume and a massive surface area. The synthesized CoMo-FMs were employed as catalysts for the aerobic oxidative desulfurization (AODS) of fuel, and the reaction results show that the optimal catalyst (CoMo-FM-2) demonstrated an outstanding catalytic performance. Over CoMo-FM-2, various thiophenic sulfides could be effective removed at 80–110 °C under an atmospheric pressure, and a complete conversion of sulfides could be achieved in at least six consecutive cycles without a detectable change in chemical compositions. Further, the catalytic mechanism was explored by conducting systemic radical trapping and transformation experiments, and the excellent catalytic performance for CoMo-FMs should be mainly due to the synergistic effect of Mo and Co elements.

To develop high-performance soy protein-based adhesives, this study employed a phenol-glyoxal precondensate as a crosslinking agent and optimized the hot-pressing process parameters for plywood through orthogonal experiments, exploring its feasibility for application in wood-based panel manufacturing. Electrospray ionization mass spectrometry (ESI-MS) and nuclear magnetic resonance (13C-NMR) analyses revealed the self-polymerization behavior of glyoxal and its condensation reaction pathway with phenol under acidic conditions, confirming that cyclic ether intermediates were predominant. Using boiling water-resistant bond strength as the evaluation index, orthogonal experiments were conducted to optimize hot-pressing temperature, pressure, time, and glue spread amount. The results demonstrated that hot-pressing temperature exerted the greatest influence on performance, with the optimal conditions being 170 °C, 1.4 MPa, 1.0 min/mm, and 330 g/m2. The crosslinking agent enhanced the compactness and water resistance of the adhesive layer through multi-site covalent bonding, hydrogen bond entanglement, and π-π stacking, providing a reference for the industrial application of bio-based adhesives.