Targeted degradation of LRG1 to attenuate renal fibrosis.

Leucine-rich α-2 glycoprotein 1 (LRG1), a secreted glycoprotein, has been identified as significantly upregulated in renal fibrosis, potentially exacerbating the condition by enhancing TGF-ß-Smad3-dependent signaling pathways. Herein, utilizing our developed LRG1-targeting peptide for LRG1 recruitment and lenalidomide for E3 ubiquitin ligase engagement, we developed an advanced proteolysis targeting chimera, ETTAC-2, specifically designed for LRG1 degradation. Our cellular degradation assays validated that ETTAC-2 effectively degraded LRG1 through a proteasome-dependent mechanism, achieving half-maximal degradation at a concentration of 8.38 µM. Furthermore, anti-fibrotic experiments conducted both in vitro and in vivo revealed that ETTAC-2 efficiently induced LRG1 degradation in fibrotic kidneys. This action effectively inhibited the TGF-ß-Smad3 signaling pathway and diminished the secretion of fibrosis-associated proteins, consequently attenuating the progression of renal fibrosis. Our study highlights the pivotal role of LRG1 in renal fibrosis and positions ETTAC-2 as a promising therapeutic candidate for targeted LRG1 intervention.

Syntheses, crystal structure, and photoelectric properties of two selenoantimonates A-Zn-Sb-Se (A = Rb and Cs).

Metal chalcogenides, as a new class of semiconductor materials, have a broad range of applications in synthetic chemistry due to their rich structures and excellent properties. We have synthesized two selenoantimonates A4Zn2Sb2Se7 [A = Rb(1), Cs(2)] under solvothermal conditions in the visible region using a band gap optimization strategy with alkali metals as structure-directing agents. Compounds 1 and 2 have a two-dimensional layered structure consisting of charge-balanced Rb+(1) or Cs+(2) cations and [Zn2Sb2Se7]4- anions with novel 20-membered rings (20-MR) [Zn6Sb4Se10] with an aperture of 5.6949 × 13.7741 Å2 formed in the middle. Furthermore, we have investigated the crystal structure, band gap, photoelectronic properties, and energy band structure.

Methyltransferase Like-3-Mediated N6-Methyladenosine Modification of Long Noncoding RNA Hepatocyte Nuclear Factor 1a Antisense RNA 1/Hepatocyte Nuclear Factor 4a Antisense RNA 1 Regulates Cytochrome P450 Enzyme Expression.

Interindividual variations in the expression and activity of cytochrome P450 enzymes (CYPs) led to lower therapeutic efficacy or adverse drug events. We previously demonstrated that CYPs are regulated by the long noncoding RNAs (lncRNAs) hepatocyte nuclear factor 1a antisense RNA 1 (HNF1A-AS1) and HNF4A-AS1 via transcription factors (TFs) including hepatocyte nuclear factor 1a (HNF1A), hepatocyte nuclear factor 4a (HNF4A), and pregnane X receptor (PXR). However, the upstream mechanisms regulating HNF1A-AS1 and HNF4A-AS1 are poorly understood. N6-methyladenosine (m6A) is a prevalent epitranscriptomic modification in mammalian RNA. Therefore, the aim of this study was to investigate whether m6A modification regulates the expression of HNF1A-AS1 and HNF4A-AS1 and affects CYP expression in HepG2 and Huh7 cells. The methyltransferase-like 3 (METTL3) inhibitor, STM2457, significantly suppressed the expression of HNF1A-AS1 and induced HNF4A-AS1 expression. Consistent with this, a loss-of-function assay of METTL3 in the cell lines resulted in the downregulation of HNF1A-AS1 and its downstream HNF1A, PXR, and CYPs at the RNA level, as well as the downregulation of some CYPs proteins, and upregulation of HNF4A-AS1. The results of gain-of-function experiments showed the opposite trend. Mechanistically, subsequent RNA stability experiments confirmed that METTL3 affected the stability of both lncRNAs, but in opposite ways; that is, METTL3 reduced HNF1A-AS1 stability and increased HNF4A-AS1 stability. Rescue experiments confirmed that the regulation of METTL3 on TFs and CYPs may require the involvement of these two lncRNAs. Altogether, our study demonstrates that METTL3 is involved in TFs-mediated CYP expression by affecting HNF1A-AS1/HNF4A-AS1 stability. SIGNIFICANCE STATEMENT: Although the impact of long noncoding RNAs (lncRNAs) including hepatocyte nuclear factor 1a antisense RNA 1 (HNF1A-AS1) and hepatocyte nuclear factor 4a antisense RNA 1 (HNF4A-AS1) on the downstream transcription factor (TF) and cytochrome P450 enzyme (CYP) expression is well studied, the upstream regulation of these two lncRNAs by methyltransferase-like 3 (METTL3) remains unexplored. This study reveals that METTL3 is involved in the regulation of lncRNA-TF-CYP expression by affecting the stability of HNF1A-AS1 and HNF4A-AS1 in HepG2 and Huh7 cells.

Design of eco-friendly antifreeze peptides as novel inhibitors of gas-hydration kinetics.

In this study, peptides designed using fragments of an antifreeze protein (AFP) from the freeze-tolerant insect Tenebrio molitor, TmAFP, were evaluated as inhibitors of clathrate hydrate formation. It was found that these peptides exhibit inhibitory effects by both direct and indirect mechanisms. The direct mechanism involves the displacement of methane molecules by hydrophobic methyl groups from threonine residues, preventing their diffusion to the hydrate surface. The indirect mechanism is characterized by the formation of cylindrical gas bubbles, the morphology of which reduces the pressure difference at the bubble interface, thereby slowing methane transport. The transfer of methane to the hydrate interface is primarily dominated by gas bubbles in the presence of antifreeze peptides. Spherical bubbles facilitate methane migration and potentially accelerate hydrate formation; conversely, the promotion of a cylindrical bubble morphology by two of the designed systems was found to mitigate this effect, leading to slower methane transport and reduced hydrate growth. These findings provide valuable guidance for the design of effective peptide-based inhibitors of natural-gas hydrate formation with potential applications in the energy and environmental sectors.

A Self-Catalytic NO/O2 Gas-Releasing Nanozyme for Radiotherapy Sensitization through Vascular Normalization and Hypoxia Relief.

Radiotherapy (RT), essential for treating various cancers, faces challenges from tumor hypoxia, which induces radioresistance. A tumor-targeted "prosthetic-Arginine" coassembled nanozyme system, engineered to catalytically generate nitric oxide (NO) and oxygen (O2) in the tumor microenvironment (TME), overcoming hypoxia and enhancing radiosensitivity is presented. This system integrates the prosthetic heme of nitric oxide synthase (NOS) and catalase (CAT) with NO-donating Fmoc-protected Arginine and Ru3+ ions, creating HRRu nanozymes that merge NOS and CAT functionalities. Surface modification with human heavy chain ferritin (HFn) improves the targeting ability of nanozymes (HRRu-HFn) to tumor tissues. In the TME, strategic arginine incorporation within the nanozyme allows autonomous O2 and NO release, triggered by endogenous hydrogen peroxide, elevating NO and O2 levels to normalize vasculature and improve blood perfusion, thus mitigating hypoxia. Employing the intrinsic O2-transporting ability of heme, HRRu-HFn nanozymes also deliver O2 directly to the tumor site. Utilizing esophageal squamous cell carcinoma as a tumor model, the studies reveal that the synergistic functions of NO and O2 production, alongside targeted delivery, enable the HRRu-HFn nanozymes to combat tumor hypoxia and potentiate radiotherapy. This HRRu-HFn nanozyme based approach holds the potential to reduce the radiation dose required and minimize side effects associated with conventional radiotherapy.

Numerical simulation and experimental investigation of coating influence on extrusion tap wear.

In order to improve the service life of extrusion taps and reduce their wear, this paper adopted the coating-simulation technology to investigate the influence laws of tool coating type and coating thickness on extrusion torque, extrusion temperature and wear amount. The validity of the numerical simulation results is confirmed through internal thread extrusion experiments. The results showed that the extrusion torque and extrusion temperature of single-layer coating and composite coating showed a tendency of decreasing and then increasing with the increase of the coating thickness; the extrusion torque and extrusion temperature of the double-layer coating increased with the increase of the coating thickness; the wear amount of the three types of coatings increased with the increase of the coating thickness. The TiAlN single coating demonstrates the most pronounced impact on decreasing extrusion torque and temperature (3.82 N·m and 88.4 °C), resulting in a smooth extrusion process. The TiAlN-TiAlN double coating exhibits the lowest wear amount of 0.076 mm. The utilization of numerical simulation proves to be a dependable approach for evaluating the efficacy of tool coatings, and reasonable selection of coating type and thickness can effectively reduce the extrusion torque, extrusion temperature and wear amount.

SGLT-2 inhibitors are beneficial in reducing the risk of thyroid cancer: findings from a Mendelian randomization study.

OBJECTIVE: Previous studies have investigated the association between diabetes medications and thyroid cancer, but the results have not been conclusive. This study used a Mendelian randomization approach to investigate the causal relationship between diabetes medications and thyroid cancer (TC). METHODS: Exposures were six major diabetes medications target, while outcomes were TC and its differentiated forms, including papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC). Mendelian randomization was conducted using IVW, MR-Egger, and weighted median methods. Tests for heterogeneity, horizontal pleiotropy, and leave-one-out were also performed. RESULTS: In European populations, SGLT2 inhibitors were significantly negatively associated with TC (OR 0.051, 95% CI 0.006-0.465, P = 0.0082) as well as PTC (OR 0.034, 95% CI 0.003-0.411, P = 0.0079), while no correlation was found with FTC. These findings remained consistent even after applying the Bonferroni correction. CONCLUSIONS: The evidence suggests that SGLT2 inhibitors could be potential therapeutic targets for TC, especially for PTC, in European populations. However, further large-scale randomized controlled trials are necessary to verify their ability to reduce the risk of and treat these types of cancer.

An artificial intelligence tool to assess the risk of severe mental distress among college students in terms of demographics, eating habits, lifestyles, and sport habits: an externally validated study using machine learning.

BACKGROUND: Precisely estimating the probability of mental health challenges among college students is pivotal for facilitating timely intervention and preventative measures. However, to date, no specific artificial intelligence (AI) models have been reported to effectively forecast severe mental distress. This study aimed to develop and validate an advanced AI tool for predicting the likelihood of severe mental distress in college students. METHODS: A total of 2088 college students from five universities were enrolled in this study. Participants were randomly divided into a training group (80%) and a validation group (20%). Various machine learning models, including logistic regression (LR), extreme gradient boosting machine (eXGBM), decision tree (DT), k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM), were employed and trained in this study. Model performance was evaluated using 11 metrics, and the highest scoring model was selected. In addition, external validation was conducted on 751 participants from three universities. The AI tool was then deployed as a web-based AI application. RESULTS: Among the models developed, the eXGBM model achieved the highest area under the curve (AUC) value of 0.932 (95% CI: 0.911-0.949), closely followed by RF with an AUC of 0.927 (95% CI: 0.905-0.943). The eXGBM model demonstrated superior performance in accuracy (0.850), precision (0.824), recall (0.890), specificity (0.810), F1 score (0.856), Brier score (0.103), log loss (0.326), and discrimination slope (0.598). The eXGBM model also received the highest score of 60 based on the evaluation scoring system, while RF achieved a score of 49. The scores of LR, DT, and SVM were only 19, 32, and 36, respectively. External validation yielded an impressive AUC value of 0.918. CONCLUSIONS: The AI tool demonstrates promising predictive performance for identifying college students at risk of severe mental distress. It has the potential to guide intervention strategies and support early identification and preventive measures.

Histone deacetylase complexes: Structure, regulation and function.

Histone deacetylases (HDACs) are key epigenetic regulators, and transcriptional complexes with deacetylase function are among the epigenetic corepressor complexes in the nucleus that target the epigenome. HDAC-bearing corepressor complexes such as the Sin3 complex, NuRD complex, CoREST complex, and SMRT/NCoR complex are common in biological systems. These complexes activate the otherwise inactive HDACs in a solitary state. HDAC complexes play vital roles in the regulation of key biological processes such as transcription, replication, and DNA repair. Moreover, deregulated HDAC complex function is implicated in human diseases including cancer. Therapeutic strategies targeting HDAC complexes are being sought actively. Thus, illustration of the nature and composition of HDAC complexes is vital to understanding the molecular basis of their functions under physiologic and pathologic conditions, and for designing targeted therapies. This review presents key aspects of large multiprotein HDAC-bearing complexes including their structure, function, regulatory mechanisms, implication in disease development, and role in therapeutics.

ClusterMatch aligns single-cell RNA-sequencing data at the multi-scale cluster level via stable matching.

MOTIVATION: Unsupervised clustering of single-cell RNA sequencing (scRNA-seq) data holds the promise of characterizing known and novel cell type in various biological and clinical contexts. However, intrinsic multi-scale clustering resolutions poses challenges to deal with multiple sources of variability in the high-dimensional and noisy data. RESULTS: We present ClusterMatch, a stable match optimization model to align scRNA-seq data at the cluster level. In one hand, ClusterMatch leverages the mutual correspondence by canonical correlation analysis and multi-scale Louvain clustering algorithms to identify cluster with optimized resolutions. In the other hand, it utilizes stable matching framework to align scRNA-seq data in the latent space while maintaining interpretability with overlapped marker gene set. Through extensive experiments, we demonstrate the efficacy of ClusterMatch in data integration, cell type annotation, and cross-species/timepoint alignment scenarios. Our results show ClusterMatch's ability to utilize both global and local information of scRNA-seq data, sets the appropriate resolution of multi-scale clustering, and offers interpretability by utilizing marker genes. AVAILABILITY AND IMPLEMENTATION: The code of ClusterMatch software is freely available at https://github.com/AMSSwanglab/ClusterMatch.

Metabolomics reveals dysregulated all-trans retinoic acid and polyunsaturated fatty acid metabolism contribute to PXR-induced hepatic steatosis in mice.

Activation of pregnane X receptor (PXR) by xenobiotics has been associated with metabolic diseases. This study aimed to reveal the impact of PXR activation on hepatic metabolome and explore novel mechanisms underlying PXR-mediated lipid metabolism disorder in the liver. Wild-type and PXR-deficient male C57BL/6 mice were used as in vivo models, and hepatic steatosis was induced by pregnenolone-16α-carbonitrile, a typical rodent PXR agonist. Metabolomic analysis of liver tissues showed that PXR activation led to significant changes in metabolites involved in multiple metabolic pathways previously reported, including lipid metabolism, energy homeostasis, and amino acid metabolism. Moreover, the level of hepatic all-trans retinoic acid (ATRA), the main active metabolite of vitamin A, was significantly increased by PXR activation, and genes involved in ATRA metabolism exhibited differential expression following PXR activation or deficiency. Consistent with previous research, the expression of downstream target genes of peroxisome proliferator-activated receptor α (PPARα) was decreased. Analysis of fatty acids by Gas Chromatography-Mass Spectrometer further revealed changes in polyunsaturated fatty acid metabolism upon PXR activation, suggesting inhibition of PPARα activity. Taken together, our findings reveal a novel metabolomic signature of hepatic steatosis induced by PXR activation in mice.

Epigenetic silencing of BEND4, a novel DNA damage repair gene, is a synthetic lethal marker for ATM inhibitor in pancreatic cancer.

Synthetic lethality is a novel model for cancer therapy. To understand the function and mechanism of BEN domain-containing protein 4 (BEND4) in pancreatic cancer, eight cell lines and a total of 492 cases of pancreatic neoplasia samples were included in this study. Methylation-specific polymerase chain reaction, CRISPR/Cas9, immunoprecipitation assay, comet assay, and xenograft mouse model were used. BEND4 is a new member of the BEN domain family. The expression of BEND4 is regulated by promoter region methylation. It is methylated in 58.1% (176/303) of pancreatic ductal adenocarcinoma (PDAC), 33.3% (14/42) of intraductal papillary mucinous neoplasm, 31.0% (13/42) of pancreatic neuroendocrine tumor, 14.3% (3/21) of mucinous cystic neoplasm, 4.3% (2/47) of solid pseudopapillary neoplasm, and 2.7% (1/37) of serous cystic neoplasm. BEND4 methylation is significantly associated with late-onset PDAC (> 50 years, P < 0.01) and tumor differentiation (P < 0.0001), and methylation of BEND4 is an independent poor prognostic marker (P < 0.01) in PDAC. Furthermore, BEND4 plays tumor-suppressive roles in vitro and in vivo. Mechanistically, BEND4 involves non-homologous end joining signaling by interacting with Ku80 and promotes DNA damage repair. Loss of BEND4 increased the sensitivity of PDAC cells to ATM inhibitor. Collectively, the present study revealed an uncharacterized tumor suppressor BEND4 and indicated that methylation of BEND4 may serve as a potential synthetic lethal marker for ATM inhibitor in PDAC treatment.

Morphological and molecular data reveal Cerrenacaulinicystidiata sp. nov. and Polyporusminutissimus sp. nov. in Polyporales from Asia.

Two new species of Polyporales, Cerrenacaulinicystidiata and Polyporusminutissimus, are illustrated and described on the basis of morphological studies and phylogenetic analyses from southern China and Vietnam. C.caulinicystidiata is characterized by annual, resupinate, sometimes effused-reflexed basidiocarps, greyish orange to brownish orange pore surface, irregular pores (3-8 per mm), a trimitic hyphal system, pyriform to ventricose cystidia, and subglobose basidiospores 3.2-4.5 × 2.8-3.5 µm in size. P.minutissimus is characterized by annual, solitary, fan-shaped with a depressed center or infundibuliform basidiocarps, obvious black stipe, cream to buff yellow pileal surface with glabrous, occasionally zonate and radially aligned stripes, angular pores (6-9 per mm), a dimitic hyphal system, and cylindrical basidiospores, 5-9.2 × 2.2-4 µm. Detailed descriptions and illustrations of the two new species are provided. The differences between the two new species and their morphologically similar and phylogenetically related species are discussed.

Incarvine C and its analogues inhibit the formation of cell cytoskeleton by targeting Rac1.

Ras-related C3 botulinum toxin substrate 1 (Rac1) has emerged as a key regulator in the treatment of cancer metastasis because of its involvement in the formation of cell plate pseudopods and effects on cell migration. In this study, we found that incarvine C, a natural product isolated from Incarvillea sinensis, and its seven analogues exhibited antitumour activity by inhibiting cell cytoskeleton formation, with moderate cytotoxicity. Accordingly, these compounds inhibited the cytoskeleton-mediated migration and invasion of MDA-MB-231 cells, with inhibition rates ranging from 37.30 % to 69.72 % and 51.27 % to 70.90 % in vitro, respectively. Moreover, they induced G2/M phase cell cycle arrest in MDA-MB-231 cells. A pull-down assay revealed that the interaction between Rac1 and its downstream effector protein PAK1 was inhibited by these compounds and that the compound Ano-6 exhibited substantial activity, with an inhibition rate of more than 90 %. Molecular docking showed that incarvine C and its analogues could bind to the nucleotide-binding pocket of Rac1, maintaining high levels of inactivated Rac1. As Ano-6 exhibited significant activity in vitro, its anti-cancer activity was tested in vivo. Four weeks of oral treatment with Ano-6 was well-tolerated in mice, and it induced a potential anti-tumour response in xenografts of MDA-MB-231 cells. Further studies demonstrated that Ano-6 was enriched in tumour tissues after 2 h of administration and induced an increase in the number of dead tumour cells. In summary, these findings not only reveal the mechanism of incarvine C but also provide a new molecular template for Rac1 inhibitors and identify a promising candidate for breast cancer treatment.

Comprehensive Urinary Proteome Profiling Analysis Identifies Diagnosis and Relapse Surveillance Biomarkers for Bladder Cancer.

Bladder cancer (BCa) is the predominant malignancy of the urinary system. Herein, a comprehensive urine proteomic feature was initially established for the noninvasive diagnosis and recurrence monitoring of bladder cancer. 279 cases (63 primary BCa, 87 nontumor controls (NT), 73 relapsed BCa (BCR), and 56 nonrelapsed BCa (BCNR)) were collected to screen urinary protein biomarkers. 4761 and 3668 proteins were qualified and quantified by DDA and sequential window acquisition of all theoretical mass spectra (SWATH-MS) analysis in two discovery sets, respectively. Upregulated proteins were validated by multiple reaction monitoring (MRM) in two independent combined sets. Using the multi-support vector machine-recursive feature elimination (mSVM-RFE) algorithm, a model comprising 13 proteins exhibited good performance between BCa and NT with an AUC of 0.821 (95% CI: 0.675-0.967), 90.9% sensitivity (95% CI: 72.7-100%), and 73.3% specificity (95% CI: 53.3-93.3%) in the diagnosis test set. Meanwhile, an 11-marker classifier significantly distinguished BCR from BCNR with 75.0% sensitivity (95% CI: 50.0-100%), 81.8% specificity (95% CI: 54.5-100%), and an AUC of 0.784 (95% CI: 0.609-0.959) in the test cohort for relapse surveillance. Notably, six proteins (SPR, AK1, CD2AP, ADGRF1, GMPS, and C8A) of 24 markers were newly reported. This paper reveals novel urinary protein biomarkers for BCa and offers new theoretical insights into the pathogenesis of bladder cancer (data identifier PXD044896).

Evaluation of Depression and Its Correlates in Terms of Demographics, Eating Habits, and Exercises Among University Students: A Multicenter Cross-Sectional Analysis.

Background: University students are a vulnerable population prone to mental health challenges. This study aimed to investigate depression and its associated factors among university students in terms of demographics, eating habits, and exercises. Methods: A total of 2891 university students from three universities participated in this study between January 2024 and February 2024. An online survey questionnaire was distributed using a snow-ball strategy. The survey collected demographic, lifestyle, and psychological data, including depression and anxiety scores using the PHQ-9 and GAD-7 screening tools. Subgroup analysis was conducted according to sport frequency and sport type using Chi-square test for qualitative data and t-test for quantitative data. Multiple linear regression analysis was performed to identify risk factors for depression. Results: A total of 44.2% and 39.5% of the participants reported symptoms of depression and anxiety, respectively. Significant differences were observed in various characteristics across different sport frequency groups, with participants with higher sport frequency tending to have less depression (P<0.001) and anxiety (P<0.001) symptoms. As the frequency of weekly exercise increased, anxiety and depression scores gradually decreased. The mean PHQ-9 and GAD-7 scores were highest in the group with no sports and lowest in the group with a sport frequency of 3-4 times per week (P<0.001). Additionally, once exercise frequency reached 5 times per week or more, anxiety and depression scores no longer decreased. Subgroup analysis based on sport type revealed that participants engaging in specific sports, such as basketball, tennis, dance, and running, had lower depression (P<0.001) and anxiety (P<0.001) scores compared to the overall average. Based on multiple linear regression analysis, married status (P=0.036), enjoying barbecue food (P<0.001), prolonged sedentary time (P=0.001), experiencing stress events (P<0.001), and electronic device usage time (P<0.001) were positively associated with depression scores, while loving eating vegetables (P=0.007), a relatively longer sport time (P=0.005), a higher exercise frequency (P=0.064), and no chronic disease (P<0.001) were negatively associated with depression scores. Conclusion: This study highlights the importance of a healthy lifestyle, including regular exercise, limited exposure to electronic screens, and a balanced diet, in preventing and mitigating depression among university students. This study also suggests that exercising 3-4 times a week is associated with the lowest levels of anxiety and depression. Activities such as basketball, tennis, dance, and running are effective in alleviating these mental health issues through regular exercise.

Prognostic predictive value of urothelial carcinoma of the bladder after TURBT based on multiphase CT radiomics.

OBJECTIVE: To investigate multiphase computed tomography (CT) radiomics-based combined with clinical factors to predict overall survival (OS) in patients with bladder urothelial carcinoma (BLCA) who underwent transurethral resection of bladder tumor (TURBT). METHODS: Data were retrospectively collected from 114 patients with primary BLCA from February 2016 to February 2018. The regions of interest (ROIs) of the plain, arterial, and venous phase images were manually segmented. The Cox regression algorithm was used to establish 3 basic models for the plain phase (PP), arterial phase (AP), and venous phase (VP) and 2 combination models (AP + VP and PP + AP + VP). The highest-performing radiomics model was selected to calculate the radiomics score (Rad-score), and independent risk factors affecting patients' OS were analyzed using Cox regression. The Rad-score and clinical risk factors were combined to construct a joint model and draw a visualized nomogram. RESULTS: The combined model of PP + AP + VP showed the best performance with the Akaike Information Criterion (AIC) and Consistency Index (C-index) in the test group of 130.48 and 0.779, respectively. A combined model constructed with two independent risk factors (age and Ki-67 expression status) in combination with the Rad-score outperformed the radiomics model alone; AIC and C-index in the test group were 115.74 and 0.840, respectively. The calibration curves showed good agreement between the predicted probabilities of the joint model and the actual (p < 0.05). The decision curve showed that the joint model had good clinical application value within a large range of threshold probabilities. CONCLUSION: This new model can be used to predict the OS of patients with BLCA who underwent TURBT.

Structure-Guided Design of Ferritin-Platinum Prodrugs for Targeted Therapy of Esophageal Squamous Cell Carcinoma.

Due to its intrinsic tumor-targeting attribute, limited immunogenicity, and cage architecture, ferritin emerges as a highly promising nanocarrier for targeted drug delivery. In the effort to develop ferritin cage-encapsulated cisplatin (CDDP) as a therapeutic agent, we found unexpectedly that the encapsulation led to inactivation of the drug. Guided by the structural information, we deciphered the interactions between ferritin cages and CDDP, and we proposed a potential mechanism responsible for attenuating the antitumor efficacy of CDDP encapsulated within the cage. Six platinum prodrugs were then designed to avoid the inactivation. The antitumor activities of these ferritin-platinum prodrug complexes were then evaluated in cells of esophageal squamous cell carcinoma (ESCC). Compared with free CDDP, the complexes were more effective in delivering and retaining platinum in the cells, leading to increased DNA damage and enhanced cytotoxic action. They also exhibited improved pharmacokinetics and stronger antitumor activities in mice bearing ESCC cell-derived xenografts as well as patient-derived xenografts. The successful encapsulation also illustrates the critical significance of comprehending the interactions between small molecular drugs and ferritin cages for the development of precision-engineered nanocarriers.

Transcriptome-wide 1-methyladenosine functional profiling of messenger RNA and long non-coding RNA in bladder cancer.

Introduction: Post-transcriptional RNA modifications are crucial regulators of tumor development and progression. In many biological processes, N1-methyladenosine (m1A) plays a key role. However, little is known about the links between chemical modifications of messenger RNAs (mRNAs) and long noncoding RNAs (lncRNAs) and their function in bladder cancer (BLCA). Methods: Methylated RNA immunoprecipitation sequencing and RNA sequencing were performed to profile mRNA and lncRNA m1A methylation and expression in BLCA cells, with or without stable knockdown of the m1A methyltransferase tRNA methyltransferase 61A (TRMT61A). Results: The analysis of differentially methylated gene sites identified 16,941 peaks, 6,698 mRNAs, and 10,243 lncRNAs in the two groups. Gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses of the differentially methylated and expressed transcripts showed that m1A-regulated transcripts were mainly related to protein binding and signaling pathways in cancer. In addition, the differentially genes were identified that were also differentially m1A-modified and identified 14 mRNAs and 19 lncRNAs. Next, these mRNAs and lncRNAs were used to construct a lncRNA-microRNA-mRNA competing endogenous RNA network, which included 118 miRNAs, 15 lncRNAs, and 8 mRNAs. Finally, the m1A-modified transcripts, SCN2B and ENST00000536140, which are highly expressed in BLCA tissues, were associated with decreased overall patient survival. Discussion: This study revealed substantially different amounts and distributions of m1A in BLCA after TRMT61A knockdown and predicted cellular functions in which m1A may be involved, providing evidence that implicates m1A mRNA and lncRNA epitranscriptomic regulation in BLCA tumorigenesis and progression.

An Artificial Intelligence Platform to Stratify the Risk of Experiencing Sleep Disturbance in University Students After Analyzing Psychological Health, Lifestyle, and Sports: A Multicenter Externally Validated Study.

Background: Sleep problems are prevalent among university students, yet there is a lack of effective models to assess the risk of sleep disturbance. Artificial intelligence (AI) provides an opportunity to develop a platform for evaluating the risk. This study aims to develop and validate an AI platform to stratify the risk of experiencing sleep disturbance for university students. Methods: A total of 2243 university students were included, with 1882 students from five universities comprising the model derivation group and 361 students from two additional universities forming the external validation group. Six machine learning techniques, including extreme gradient boosting machine (eXGBM), decision tree (DT), k-nearest neighbor (KNN), random forest (RF), neural network (NN), and support vector machine (SVM), were employed to train models using the same set of features. The models' prediction performance was assessed based on discrimination and calibration, and feature importance was determined using Shapley Additive exPlanations (SHAP) analysis. Results: The prevalence of sleep disturbance was 44.69% in the model derivation group and 49.58% in the external validation group. Among the developed models, eXGBM exhibited superior performance, surpassing other models in metrics such as area under the curve (0.779, 95% CI: 0.728-0.830), accuracy (0.710), precision (0.737), F1 score (0.692), Brier score (0.193), and log loss (0.569). Calibration and decision curve analyses demonstrated favorable calibration ability and clinical net benefits, respectively. SHAP analysis identified five key features: stress score, severity of depression, vegetable consumption, age, and sedentary time. The AI platform was made available online at https://sleepdisturbancestudents-xakgzwectsw85cagdgkax9.streamlit.app/, enabling users to calculate individualized risk of sleep disturbance. Conclusion: Sleep disturbance is prevalent among university students. This study presents an AI model capable of identifying students at high risk for sleep disturbance. The AI platform offers a valuable resource to guide interventions and improve sleep outcomes for university students.