A 4D single-cell protein atlas of transcription factors delineates spatiotemporal patterning during embryogenesis.

Complex biological processes such as embryogenesis require precise coordination of cell differentiation programs across both space and time. Using protein-fusion fluorescent reporters and four-dimensional live imaging, we present a protein expression atlas of transcription factors (TFs) mapped onto developmental cell lineages during Caenorhabditis elegans embryogenesis, at single-cell resolution. This atlas reveals a spatiotemporal combinatorial code of TF expression, and a cascade of lineage-specific, tissue-specific and time-specific TFs that specify developmental states. The atlas uncovers regulators of embryogenesis, including an unexpected role of a skin specifier in neurogenesis and the critical function of an uncharacterized TF in convergent muscle differentiation. At the systems level, the atlas provides an opportunity to model cell state-fate relationships, revealing a lineage-dependent state diversity within functionally related cells and a winding trajectory of developmental state progression. Collectively, this single-cell protein atlas represents a valuable resource for elucidating metazoan embryogenesis at the molecular and systems levels.

Associations between Chinese visceral adiposity index and risks of all-cause and cause-specific mortality: A population-based cohort study.

AIM: To determine the associations between the Chinese visceral adiposity index (CVAI) and the risks of all-cause and cause-specific mortality. MATERIALS AND METHODS: A total of 3 916 214 Chinese adults were enrolled in a nationwide population cohort covering all 31 provinces of mainland China. The CVAI was calculated based on age, body mass index, waist circumference, and triglyceride and high-density lipoprotein cholesterol concentrations. We used a Cox proportional hazards regression model to determine the hazard ratios and 95% confidence intervals (CIs) for risk of mortality associated with different CVAI levels. RESULTS: The median follow-up duration was 3.8 years. A total of 86 158 deaths (34 867 cardiovascular disease [CVD] deaths, 29 884 cancer deaths, and 21 407 deaths due to other causes) were identified. In general, after adjusting for potential confounding factors, a U-shaped relationship between CVAI and all-cause mortality was observed by restricted cubic spline (RCS). Compared with participants in CVAI quartile 1, those in CVAI quartile 4 had a 23.0% (95% CI 20.0%-25.0%) lower risk of cancer death, but a 23.0% (95% CI 19.0-27.0) higher risk of CVD death. In subgroup analysis, a J-shaped and inverted U-shaped relationship for all-cause mortality and cancer mortality was observed in the group aged < 60 years. CONCLUSIONS: The CVAI, an accessible indicator reflecting visceral obesity among Chinese adults, has predictive value for all-cause, CVD, and cancer mortality risks. Moreover, the CVAI carries significance in the field of health economics and secondary prevention. In the future, it could be used for early screening purposes.

Enhancing identification performance of cognitive impairment high-risk based on a semi-supervised learning method.

BACKGROUND: Cognitive assessment plays a pivotal role in the early detection of cognitive impairment, particularly in the prevention and management of cognitive diseases such as Alzheimer's and Lewy body dementia. Large-scale screening relies heavily on cognitive assessment scales as primary tools, with some low sensitivity and others expensive. Despite significant progress in machine learning for cognitive function assessment, its application in this particular screening domain remains underexplored, often requiring labor-intensive expert annotations. AIMS: This paper introduces a semi-supervised learning algorithm based on pseudo-label with putback (SS-PP), aiming to enhance model efficiency in predicting the high risk of cognitive impairment (HR-CI) by utilizing the distribution of unlabeled samples. DATA: The study involved 189 labeled samples and 215,078 unlabeled samples from real world. A semi-supervised classification algorithm was designed and evaluated by comparison with supervised methods composed by 14 traditional machine-learning methods and other advanced semi-supervised algorithms. RESULTS: The optimal SS-PP model, based on GBDT, achieved an AUC of 0.947. Comparative analysis with supervised learning models and semi-supervised methods demonstrated an average AUC improvement of 8% and state-of-art performance, repectively. CONCLUSION: This study pioneers the exploration of utilizing limited labeled data for HR-CI predictions and evaluates the benefits of incorporating physical examination data, holding significant implications for the development of cost-effective strategies in relevant healthcare domains.

Interferon-Gamma-Inducible Protein 16 Inhibits Hepatocellular Carcinoma via Interferon Regulatory Factor 3 on Chemosensitivity.

BACKGROUND AND AIM: Previous reports have suggested IFI16 as a tumor suppressor in hepatocellular carcinoma (HC). Nonetheless, the biological significance of IFI16 and its mechanism concerning resistance to cisplatin (DDP) in HC requires further exploration. METHODS: Samples of tumor and corresponding para-carcinoma tissues were acquired from patients with HC. Furthermore, DDP-resistant cell lines of HC, specifically HCC, Huh7 and Hepatoblastoma, HepG3, were generated by gradually increasing the concentration of DDP. Cell apoptosis and DNA damage were evaluated by utilizing flow cytometry assay and TUNEL staining. The interaction between IFI16 and interferon regulatory factor 3 (IRF3) proteins were analyzed using Co-Immunoprecipitation (Co-IP) assay. In vivo assays were conducted by establishing HC subcutaneous xenograft tumor models. RESULTS: The study found a reduction in IFI16 expression in both HC tissues and DDP-resistant HC cell lines. The binding of IFI16 to IRF3 regulated DNA damage-associated markers in vitro. Overexpression of IFI16 heightened the susceptibility of DDP-induced apoptosis and DNA damage, which was counteracted by IRF3 knockdown, while strengthened by IRF3 overexpression. Moreover, overexpression of IFI16 diminished in vivo DDP-resistant HC tumorigenicity. CONCLUSION: In summary, our findings suggest that IFI16 serves as a tumor suppressor in HC by promoting DNA damage via its interaction with IRF3, thereby reversing DDP resistance.

Comparative Proteome and Cis-Regulatory Element Analysis Reveals Specific Molecular Pathways Conserved in Dog and Human Brains.

Brain development and function are governed by precisely regulated protein expressions in different regions. To date, multiregional brain proteomes have been systematically analyzed only for adult human and mouse brains. To understand the underpinnings of brain development and function, we generated proteomes from six regions of the postnatal brain at three developmental stages of domestic dogs (Canis familiaris), which are special among animals in terms of their remarkable human-like social cognitive abilities. Quantitative analysis of the spatiotemporal proteomes identified region-enriched synapse types at different developmental stages and differential myelination progression in different brain regions. Through integrative analysis of inter-regional expression patterns of orthologous proteins and genome-wide cis-regulatory element frequencies, we found that proteins related with myelination and hippocampus were highly correlated between dog and human but not between mouse and human, although mouse is phylogenetically closer to human. Moreover, the global expression patterns of neurodegenerative disease and autism spectrum disorder-associated proteins in dog brain more resemble human brain than in mouse brain. The high similarity of myelination and hippocampus-related pathways in dog and human at both proteomic and genetic levels may contribute to their shared social cognitive abilities. The inter-regional expression patterns of disease-associated proteins in the brain of different species provide important information to guide mechanistic and translational study using appropriate animal models.

Community screening for dementia among older adults in China: a machine learning-based strategy.

BACKGROUND: Dementia is a leading cause of disability in people older than 65 years worldwide. However, diagnosing dementia in its earliest symptomatic stages remains challenging. This study combined specific questions from the AD8 scale with comprehensive health-related characteristics, and used machine learning (ML) to construct diagnostic models of cognitive impairment (CI). METHODS: The study was based on the Shenzhen Healthy Ageing Research (SHARE) project, and we recruited 823 participants aged 65 years and older, who completed a comprehensive health assessment and cognitive function assessments. Permutation importance was used to select features. Five ML models using BalanceCascade were applied to predict CI: a support vector machine (SVM), multilayer perceptron (MLP), AdaBoost, gradient boosting decision tree (GBDT), and logistic regression (LR). An AD8 score ≥ 2 was used to define CI as a baseline. SHapley Additive exPlanations (SHAP) values were used to interpret the results of ML models. RESULTS: The first and sixth items of AD8, platelets, waist circumference, body mass index, carcinoembryonic antigens, age, serum uric acid, white blood cells, abnormal electrocardiogram, heart rate, and sex were selected as predictive features. Compared to the baseline (AUC = 0.65), the MLP showed the highest performance (AUC: 0.83 ± 0.04), followed by AdaBoost (AUC: 0.80 ± 0.04), SVM (AUC: 0.78 ± 0.04), GBDT (0.76 ± 0.04). Furthermore, the accuracy, sensitivity and specificity of four ML models were higher than the baseline. SHAP summary plots based on MLP showed the most influential feature on model decision for positive CI prediction was female sex, followed by older age and lower waist circumference. CONCLUSIONS: The diagnostic models of CI applying ML, especially the MLP, were substantially more effective than the traditional AD8 scale with a score of ≥ 2 points. Our findings may provide new ideas for community dementia screening and to promote such screening while minimizing medical and health resources.

Chemically Induced Activity Recovery of Isolated Lithium in Anode-free Lithium Metal Batteries.

The anode-free lithium metal battery is considered to be an excellent candidate for the new generation energy storage system because of its higher energy density and safety than the traditional lithium metal battery. However, the continuous generation of SEI or isolated Li hinders its practical application. In general, the isolated Li is considered electrochemically inactive because it loses electrical connection with the current collector. Here we show an abnormal phenomenon that the lost capacity appears to be recovered after cycles when the isolated Li reconnects with a deposited Li metal layer. The isolated Li reconnection is ascribed to the chemical induction of the block copolymer coating. The migration of Li+ is affected by the electron delocalization and the electron cloud density of the polymer, which determine the conversion direction of Li+. Based on the mechanism, we propose a strategy to slow down the capacity decay of the anode-free lithium metal battery.

Single-cell dynamics of chromatin activity during cell lineage differentiation in Caenorhabditis elegans embryos.

Elucidating the chromatin dynamics that orchestrate embryogenesis is a fundamental question in developmental biology. Here, we exploit position effects on expression as an indicator of chromatin activity and infer the chromatin activity landscape in every lineaged cell during Caenorhabditis elegans early embryogenesis. Systems-level analyses reveal that chromatin activity distinguishes cellular states and correlates with fate patterning in the early embryos. As cell lineage unfolds, chromatin activity diversifies in a lineage-dependent manner, with switch-like changes accompanying anterior-posterior fate asymmetry and characteristic landscapes being established in different cell lineages. Upon tissue differentiation, cellular chromatin from distinct lineages converges according to tissue types but retains stable memories of lineage history, contributing to intra-tissue cell heterogeneity. However, the chromatin landscapes of cells organized in a left-right symmetric pattern are predetermined to be analogous in early progenitors so as to pre-set equivalent states. Finally, genome-wide analysis identifies many regions exhibiting concordant chromatin activity changes that mediate the co-regulation of functionally related genes during differentiation. Collectively, our study reveals the developmental and genomic dynamics of chromatin activity at the single-cell level.

Glycoprotein α-Subunit of Glucosidase II (GIIα) is a novel prognostic biomarker correlated with unfavorable outcome of urothelial carcinoma.

BACKGROUND: Urothelial carcinoma (UC) is among the most prevalent malignancies. The muscle-invasive bladder cancer (MIBC) shows an invasive feature and has poor prognosis, while the non-muscle invasive bladder cancer (NMIBC) shows a better prognosis as compared with the MIBC. However, a significant proportion (10%-30%) of NMIBC cases progress to MIBC. Identification of efficient biomarkers for the prediction of the course of UC remains challenging nowadays. Recently, there is an emerging study showed that post-translational modifications (PTMs) by glycosylation is an important process correlated with tumor angiogenesis, invasion and metastasis. Herein, we reported a data-driven discovery and experimental validation of GANAB, a key regulator of glycosylation, as a novel prognostic marker in UC. METHODS: In the present study, we conducted immunohistochemistry (IHC) assay to evaluate the correlation between the expression levels of GANAB protein and the prognosis of UC in our cohort of 107 samples using whole slide image (WSI) analysis. In vitro experiments using RNAi were also conducted to investigate the biological functions of GANAB in UC cell lines. RESULTS: We observed that positive GANAB protein expression was significantly correlated with poor prognosis of UC in our cohort, with p-value of 0.0017 in Log-rank test. Notably, tumor cells at the invasive front of the tumor margin showed stronger GANAB expression than the tumor cells inside the tumor body in UCs. We further validated that the elevated expression levels of GANAB were significantly correlated with high grade tumors (p-values of 1.72 × 10-10), advanced stages (6.47 × 10-6), and elevated in luminal molecular subtypes. Moreover, knocking-down GANAB using RNAi in UM-UC-3 and T24 cells inhibited cell proliferation and migration in vitro. Knockdown of GANAB resulted in cell cycle arrest at G1 phase. We demonstrated that GANAB mediated HIF1A and ATF6 transcriptional activation in the ER stress signaling, and regulated the gene expression of cell cycle-related transcriptional factors E2F7 and FOXM1. CONCLUSIONS: The elevated expression of GANAB is a novel indicator of poorer prognosis of UC. Our data suggests that GANAB is not only a new and promising prognostic biomarker for UC, but also may provide important cues for the development of PTM-based therapeutics for UC treatment.

Association of the serum transaminase with mortality among the US elderly population.

BACKGROUND AND AIM: Considering the inconsistent findings of research into the associations between serum levels of liver enzymes (alanine aminotransferase [ALT], aspartate aminotransferase [AST], and gamma-glutamyltransferase [GGT]) and mortality among elderly people, we aimed to investigate the associations of ALT, AST, GGT, and De-Ritis ratio (DRR, defined as AST/ALT) and all-cause or cause-specific mortality among the US elderly people using National Health and Nutrition Examination Surveys data. METHODS: We included 6415 elderly participants (≥ 65 years). Exclusion criteria included positive test for hepatitis B virus, hepatitis C virus, and human immunodeficiency virus infection at baseline. Multivariable-adjusted Cox regression models calculating hazard ratios (HR) and 95% confidence intervals were developed for each of the liver enzyme measures. RESULTS: All-cause cumulative mortality was 33.8%, of which 23.8% were cardiovascular disease (CVD) deaths, 15.6% were cancer deaths, and 60.6% were other cause deaths. Adjusted Cox models found increased all-cause mortality risk for low ALT (HR: 1.70), low AST (HR: 1.13), high GGT (HR: 1.25), and high DRR (HR: 1.68). Low ALT and high DRR predicted CVD mortality. Low ALT (HR: 1.91), low AST (HR: 1.16), high GGT (HR: 1.40), and high DRR (HR: 1.76) predicted other cause mortality. CONCLUSIONS: Low ALT and high DRR were associated with increased CVD and cancer mortality. All serum liver enzyme measures were associated with all-cause mortality and other cause mortality in the US elderly population. Further studies may validate these findings in other elderly populations.

The 980 nm diode laser treatment for non-muscle-invasive bladder tumor with en bloc technique: single-center experience.

BACKGROUND: Transurethral resection of the bladder tumor (TURBT) is one of the most established urological procedures for the treatment of the primary non-muscle-invasive bladder cancer (NMIBC). The aim of the study is to evaluate the efficacy and safety of 980 nm diode laser as a treatment for primary NMIBC. METHODS: Eighty-eight patients with NMIBC were treated by en bloc transurethral resection with 980 nm diode laser, and 76 patients were treated by plasmakinetic transurethral resection from May 2016 to July 2019 at the Department of Urology, Tangdu Hospital, Air Force Medical University. The clinical data were collected and compared between the two groups. RESULTS: The bladder irrigation time was shortened in 980 nm diode laser group compared to that of plasmakinetic transurethral resection group (4.1 ± 0.6 vs 13.1 ± 3.1 h, p < 0.001). A total of 13.2% (10/76) patients experienced obturator nerve reflex, and 5.3% (4/76) experienced delayed bleeding in plasmakinetic transurethral resection group, while no obturator nerve reflex and delayed bleeding cases were observed in 980 nm diode laser group (p < 0.05). The postoperative catheterization and hospitalization time showed no significant difference between the two groups. The median follow-up time was 27 months (13-38 months). No significant difference in the recurrence rate was observed between the two groups. CONCLUSIONS: The 980 nm diode laser is an effective and safe tool in transurethral resection of NMIBC using en bloc technique. It has less perioperative complications and shortened bladder irrigation time.

An improved RIME optimization algorithm for lung cancer image segmentation.

Lung cancer is a prevalent form of cancer worldwide, necessitating early and accurate diagnosis for successful treatment. Within medical imaging processing, image segmentation plays a vital role in medical diagnosis. This study applies swarm intelligence algorithms to segment lung cancer pathological images at three levels. The original algorithm incorporates the Whales' search prey mechanism and a random mutation strategy, resulting in an improved version named WDRIME, which aims to enhance convergence speed and avoid local optima (LO). Additionally, the study introduces a multilevel image segmentation method for lung cancer based on the improved algorithm. WDRIME's performance is showcased by comparing it to the state-of-the-art algorithms in IEEE CEC2014. To design a framework for lung cancer image segmentation, this paper combines the WDRIME algorithm with the multilevel segmentation method. Evaluation of the segmentation results employs metrics such as PSNR, SSIM, and FSIM. Overall, the analysis confirms that the proposed algorithm supersedes others regarding convergence speed and accuracy. This model signifies a high-quality segmentation method and offers practical support for in-depth exploration of lung cancer pathological images.

Fenofibrate inhibits MOXD1 and PDZK1IP1 expression and improves lipid deposition and inflammation in mice with alcoholic fatty liver.

AIMS: Alcoholic liver disease (ALD) can develop into cirrhosis and hepatocellular carcinoma but no specific drugs are available. Fenofibrate is therapeutically effective in ALD, however, the exact mechanism remains unknown. We explored the hub genes of ALD and the role of fenofibrate in ALD. MAIN METHODS: The hub genes of ALD were screened by bioinformatics method, and their functional enrichment, signalling pathways, target genes and their correlation with immune microenvironment and pathogenic genes were analysed. We also analysed the binding affinity of fenofibrate to proteins of hub genes using molecular docking techniques, and the effects on hub gene expression, lipid deposition, oxidative stress and inflammation in the liver of National Institute on Alcohol Abuse and Alcoholism (NIAAA) model mice. The regulatory effects of fenofibrate on MOXD1 and PDZK1P1 were investigated after gene silencing of peroxisome proliferator-activated receptor-α (Ppar-α). KEY FINDINGS: Hub genes identified, including monooxygenase DBH-like 1 (MOXD1), PDZK1-interacting protein 1 (PDZK1IP1) and solute carrier 51 ß (SLC51B), are highly predictive for ALD. Hepatic MOXD1 and PDZK1IP1 expression was elevated in patients with ALD and NIAAA model mice, with no significant difference in SLC51B expression between the groups. Fenofibrate binds tightly to MOXD1 and PDZK1IP1, inhibits their hepatic expression independently of PPAR-α signalling, and ameliorates lipid deposition, oxidative stress and inflammatory responses in NIAAA model mice. SIGNIFICANCE: MOXD1 and PDZK1IP1 are key genes in ALD progression; fenofibrate improves liver damage in NIAAA model mice by downregulating their expression. Our findings provide insight for improving diagnostic and therapeutic strategies for ALD.

Themes and trends in marathon performance research: a comprehensive bibliometric analysis from 2009 to 2023.

Background: When marathon runners break the 2-h barrier at the finishing line, it attracts global attention. This study is aimed to conduct a bibliometric analysis of publications in the field of marathon running, analyze relevant research contributors, and visualize the historical trends of marathon performance research over the past 15 years. Methods: On 8 December 2023, we extracted high-quality publication data from the Web of Science Core Collection spanning from 1 January 2009 to 30 November 2023. We conducted bibliometric analysis and research history visualization using the R language packages biblioshiny, VOSviewer, and CiteSpace. Results: A total of 1,057 studies were published by 3,947 authors from 1,566 institutions across 63 countries/regions. USA has the highest publication and citation volume, while, the University of Zurich being the most prolific research institution. Keywords analysis revealed several hotspots in marathon research over the past 3 years: (1) physiology of the elite marathon runners, (2) elite marathon training intensity and pacing strategies, (3) nutritional strategies for elite marathon runners, (4) age and sex differences in marathon performance, (5) recovery of inflammatory response and muscle damage. Conclusion: This study presents the first comprehensive bibliometric analysis of marathon performance research over the past 15 years. It unveils the key contributors to marathon performance research, visually represents the historical developments in the field, and highlights the recent topical frontiers. The findings of this study will guide future research by identifying potential hotspots and frontiers.

Pulmonary Tuberculosis Notification Rate Within Shenzhen, China, 2010-2019: Spatial-Temporal Analysis.

BACKGROUND: Pulmonary tuberculosis (PTB) is a chronic communicable disease of major public health and social concern. Although spatial-temporal analysis has been widely used to describe distribution characteristics and transmission patterns, few studies have revealed the changes in the small-scale clustering of PTB at the street level. OBJECTIVE: The aim of this study was to analyze the temporal and spatial distribution characteristics and clusters of PTB at the street level in the Shenzhen municipality of China to provide a reference for PTB prevention and control. METHODS: Data of reported PTB cases in Shenzhen from January 2010 to December 2019 were extracted from the China Information System for Disease Control and Prevention to describe the epidemiological characteristics. Time-series, spatial-autocorrelation, and spatial-temporal scanning analyses were performed to identify the spatial and temporal patterns and high-risk areas at the street level. RESULTS: A total of 58,122 PTB cases from 2010 to 2019 were notified in Shenzhen. The annual notification rate of PTB decreased significantly from 64.97 per 100,000 population in 2010 to 43.43 per 100,000 population in 2019. PTB cases exhibited seasonal variations with peaks in late spring and summer each year. The PTB notification rate was nonrandomly distributed and spatially clustered with a Moran I value of 0.134 (P=.02). One most-likely cluster and 10 secondary clusters were detected, and the most-likely clustering area was centered at Nanshan Street of Nanshan District covering 6 streets, with the clustering time spanning from January 2010 to November 2012. CONCLUSIONS: This study identified seasonal patterns and spatial-temporal clusters of PTB cases at the street level in the Shenzhen municipality of China. Resources should be prioritized to the identified high-risk areas for PTB prevention and control.

PAX2 mediated upregulation of ESPL1 contributes to cisplatin resistance in bladder cancer through activating the JAK2/STAT3 pathway.

Extra spindle-polar body like 1 (ESPL1) is associated with the development of a variety of cancers, including bladder cancer, and is closely related to chemoresistance. In this study, we aimed to reveal the role of ESPL1 in bladder cancer progression and cisplatin (DDP) resistance. First, ESPL1 was found to be highly expressed in tumor tissues and cells of bladder cancer, and more highly expressed in cisplatin resistant tumor tissues or cells. The binding of PAX2 in ESPL1 promoter region was predicted by Jaspar database and verified by Ch-IP analysis and the luciferase reporter gene assay. Next, cisplatin-resistant T24 cells (T24/DDP) were established and transfected with ESPL1 siRNA (si-ESPL1) or overexpression vector (pcDNA-ESPL1) or co-transfected with PAX2 siRNA (si-PAX2) or overexpression vector (pcDNA-PAX2), and then treated with DDP or AG490, an inhibitor of JAK2. The results showed that silencing ESPL1 significantly reduced T24/DDP cell viability, colony formation and invasion, enhanced sensitivity to DDP, and induced cell apoptosis. Silencing PAX2 decreased ESPL1 expression, enhanced sensitivity to DDP, and induced apoptosis of T24/DDP cells, and inhibited activation of JAK2/STAT3 pathway. Overexpressing ESPL1 reversed the effect of PAX2 silencing on T24/DDP cells, while AG490 counteracted the reversal effect of overexpressing ESPL1. Finally, a xenograft tumor model was established and found that silencing ESPL1 or DDP treatment inhibited tumor growth, while silencing ESPL1 combined with DDP treatment had the best effect. In summary, this study suggested that PAX2-mediated ESPL1 transcriptional activation enhanced cisplatin resistance in bladder cancer by activating JAK2/STAT3 pathway.

Vacuolar H+-ATPase determines daughter cell fates through asymmetric segregation of the nucleosome remodeling and deacetylase complex.

Asymmetric cell divisions (ACDs) generate two daughter cells with identical genetic information but distinct cell fates through epigenetic mechanisms. However, the process of partitioning different epigenetic information into daughter cells remains unclear. Here, we demonstrate that the nucleosome remodeling and deacetylase (NuRD) complex is asymmetrically segregated into the surviving daughter cell rather than the apoptotic one during ACDs in Caenorhabditis elegans. The absence of NuRD triggers apoptosis via the EGL-1-CED-9-CED-4-CED-3 pathway, while an ectopic gain of NuRD enables apoptotic daughter cells to survive. We identify the vacuolar H+-adenosine triphosphatase (V-ATPase) complex as a crucial regulator of NuRD's asymmetric segregation. V-ATPase interacts with NuRD and is asymmetrically segregated into the surviving daughter cell. Inhibition of V-ATPase disrupts cytosolic pH asymmetry and NuRD asymmetry. We suggest that asymmetric segregation of V-ATPase may cause distinct acidification levels in the two daughter cells, enabling asymmetric epigenetic inheritance that specifies their respective life-versus-death fates.

NL13, a novel curcumin analogue and polo like kinase 4 inhibitor, induces cell cycle arrest and apoptosis in prostate cancer models.

BACKGROUND AND PURPOSE: Prostate cancer remains a major public health burden worldwide. Polo like kinase 4 (PLK4) has emerged as a promising therapeutic target in prostate cancer due to its key roles in cell cycle regulation and tumour progression. This study aims to develop and characterize the novel curcumin analogue NL13 as a potential therapeutic agent and PLK4 inhibitor against prostate cancer. EXPERIMENTAL APPROACH: NL13 was synthesized and its effects were evaluated in prostate cancer cells and mouse xenograft models. Kinome screening and molecular modelling identified PLK4 as the primary target. Antiproliferative and proapoptotic mechanisms were explored via cell cycle, apoptosis, gene and protein analyses. KEY RESULTS: Compared with curcumin, NL13 exhibited much greater potency in inhibiting PC3 (IC50, 3.51 µM vs. 35.45 µM) and DU145 (IC50, 2.53 µM vs. 29.35 µM) prostate cancer cells viability and PLK4 kinase activity (2.32 µM vs. 246.88 µM). NL13 induced G2/M cell cycle arrest through CCNB1/CDK1 down-regulation and triggered apoptosis via caspase-9/caspase-3 cleavage. These effects were mediated by PLK4 inhibition, which led to the inactivation of the AKT signalling pathway. In mice, NL13 significantly inhibited tumour growth and modulated molecular markers consistent with in vitro findings, including decreased p-AKT and increased cleaved caspase-9/3. CONCLUSION AND IMPLICATIONS: NL13, a novel PLK4-targeted curcumin analogue, exerts promising anticancer properties against prostate cancer by disrupting the PLK4-AKT-CCNB1/CDK1 and apoptosis pathways. NL13 represents a promising new agent for prostate cancer therapy.

Integrating multi-task and cost-sensitive learning for predicting mortality risk of chronic diseases in the elderly using real-world data.

BACKGROUND AND OBJECTIVE: Real-world data encompass population diversity, enabling insights into chronic disease mortality risk among the elderly. Deep learning excels on large datasets, offering promise for real-world data. However, current models focus on single diseases, neglecting comorbidities prevalent in patients. Moreover, mortality is infrequent compared to illness, causing extreme class imbalance that impedes reliable prediction. We aim to develop a deep learning framework that accurately forecasts mortality risk from real-world data by addressing comorbidities and class imbalance. METHODS: We integrated multi-task and cost-sensitive learning, developing an enhanced deep neural network architecture that extends multi-task learning to predict mortality risk across multiple chronic diseases. Each patient cohort with a chronic disease was assigned to a separate task, with shared lower-level parameters capturing inter-disease complexities through distinct top-level networks. Cost-sensitive functions were incorporated to ensure learning of positive class characteristics for each task and achieve accurate prediction of the risk of death from multiple chronic diseases. RESULTS: Our study covers 15 prevalent chronic diseases and is experimented with real-world data from 482,145 patients (including 9,516 deaths) in Shenzhen, China. The proposed model is compared with six models including three machine learning models: logistic regression, XGBoost, and CatBoost, and three state-of-the-art deep learning models: 1D-CNN, TabNet, and Saint. The experimental results show that, compared with the other compared algorithms, MTL-CSDNN has better prediction results on the test set (ACC=0.99, REC=0.99, PRAUC=0.97, MCC=0.98, G-means = 0.98). CONCLUSIONS: Our method provides valuable insights into leveraging real-world data for precise multi-disease mortality risk prediction, offering potential applications in optimizing chronic disease management, enhancing well-being, and reducing healthcare costs for the elderly population.