The Association Between Non-High-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratio With Psoriasis: A Cross-Sectional Survey and Genetic Approach.

This study utilised NHANES data from 2003 to 2006 and 2009 to 2014 to explore the association between the non-high-density lipoprotein to high-density lipoprotein cholesterol ratio (NHHR) and psoriasis. A total of 15 437 U.S.

Dynamic multi-omics profiling of islet and gut hormonal secretion and peripheral crosstalk in response to various nutrient loads.

Postprandial metabolism is a complex and dynamic process involving diverse biomolecules, with islet and gut hormones playing crucial roles. However, how these hormones interact with biomolecules after nutrient intake and coordinate with peripheral insulin resistance (IR) remains elusive. This study characterizes postprandial multi-omics dynamics under mixed meals and four distinct macronutrient loads, investigating hormone secretion patterns, associated responsive molecules, and their relationships with IR.

Association of Glucagon-Like Peptide-1 Receptor Agonists With Cancer Risk in Older Adults With Type 2 Diabetes.

Objective: The real-world evidence on the association between glucagon-like peptide-1 receptor agonists (GLP-1RAs) and cancer risk remains limited and mixed.

Methods: In 2013-2020 national Medicare claims data, we included cancer-naïve patients with type 2 diabetes (T2D). We identified those who initiated GLP-1 RA, sodium-glucose cotransporter 2 inhibitor (SGLT2i), or dipeptidyl peptidase 4 inhibitor (DPP4i) and conducted 1:1 propensity score matching for confounding adjustment.

Gene-Smoking Interaction in Insulin Sensitivity and β-Cell Function Among Normal Glucose Tolerance Individuals.

Objective: To identify genetic loci that exhibit potential interactions with smoking status on insulin sensitivity and islet β-cell function within normal glucose tolerance (NGT) populations.

Methods: All participants underwent an OGTT to confirm NGT status, followed by assessments of insulin sensitivity and β-cell function. Analyses were performed in NGT participants from Nanjing (N = 4808) and Jurong (N = 508) for discovery and validation, respectively.

Variational temporal deconfounder network for individualized treatment effect estimation with longitudinal observational data.

Objective: By leveraging real-world electronic health record (EHR) data, this study set out to estimate individualized treatment effects (ITE) in longitudinal observational settings to advance personalized medicine, addressing key challenges that are often observed in real-world clinical scenarios and pose statistical challenges, including hidden confounding and dynamic treatment regimens.

Methods: We propose the Variational Temporal Deconfounder Network (VTDNet), a novel framework designed to account for time-varying hidden confounding using a variational recurrent transformer-based autoencoder. Specifically, VTDNet comprises three critical components: a temporal Encoder-Decoder structure to capture hidden representation, a Treatment Block that captures interdependencies among multiple treatments, and a Potential Outcome Block that predicts both factual and counterfactual outcomes.

Deciphering the prognostic value and immunotherapeutic strategy of aggrephagy in melanoma: Integrating single-cell sequencing and machine learning.

This study aimed to investigate the role of aggrephagy in cutaneous melanoma (CM) and explore its potential as a biomarker for prognosis and therapeutic targeting. We utilized single-cell sequencing technology and machine learning algorithms to analyze melanoma transcriptome data from the TCGA database and validated our findings using 3 independent datasets from the GEO database. By employing enrichment scoring in single-cell sequencing, we identified characteristic expression patterns of different cell types involved in aggrephagy and constructed an aggrephagy-related signature (ARS).

Mechanistic insights into adipose-derived stem cells and exosomes in ischemia-reperfusion injury repair: from shared pathways to organ-specific therapeutics.

Ischemia-reperfusion injury (IRI) has become a significant challenge for clinical treatment due to the complex multi-mechanism pathological cascade response, including oxidative stress, inflammatory bursts, and programmed cell death. Adipose-derived stem cells (ADSCs) and their exosomes (ADSCs-exosomes) are emerging as a breakthrough therapeutic strategy to reverse IRI, owing to their multi-target synergistic effects. This review systematically analyzes the two major repair modes of ADSCs and ADSCs-exosomes: the "common protection" mechanism, which includes anti-inflammatory, anti-oxidative, and anti-apoptotic effects through paracrine regulation of miRNAs targeting the NF-κB/NRF2/β-catenin signaling axis; and precision repair, which is achieved through organ-specific targets, including hepatic mitochondrial dynamics and pyroptosis inhibition, cardiac macrophage polarization and neutrophil clearance, renal anti-fibrosis and erythropoietin (EPO) activation, as well as brain iron death regulation and microglial remodeling.

Multidimensional Pancreatic Islet β-cell Function (PIF) Assessment Improves Predictive Effect of Diabetes Risk Scores.

Aims/hypothesis: Comprehensive assessment of pancreatic islet β-cell function (PIF) is crucial for diabetes management. We proposed a multidimensional, relative quantification system for PIF measurement.

Methods: Our novel approach evaluates PIF using three dimensions: stationary-baseline (PIF-S), load-peak (PIF-L), and accelerated-slope (PIF-A).

Photonic Interfaces: an Innovative Wearable Sensing Solution for Continuous Monitoring of Human Motion and Physiological Signals.

Flexible integrated photonic sensors are gaining prominence in intelligent wearable sensing due to their compact size, exceptional sensitivity, rapid response, robust immunity to electromagnetic interference, and the capability to enable parallel sensing through optical multiplexing. However, integrating these sensors for practical applications, such as monitoring human motions and physiological activities together, remains a significant challenge. Herein, it is presented an innovative fully packaged integrated photonic wearable sensor, which features a delicately designed flexible necklace-shaped microring resonator (MRR), along with a pair of grating couplers (GCs) coupled to a fiber array (FA).

Effects of Different Modified Biochars on Growth of and Corresponding Transcriptome Analysis.

Modified biochar can effectively improve the quality and environment of coastal saline-alkali soil, but its effects on the growth and development of halophytes and its mechanism are still unclear. This study systematically evaluated the growth-promoting effects and preliminary mechanisms of HPO-modified biochar (HBC) and HPO-kaolinite-biochar composite (HBCK) on the economically important halophyte . The results demonstrated that the application of HBC/HBCK significantly enhanced plant growth, resulting in increases of over 55% in plant height and greater than 100% in biomass relative to the control.

Complementary Rhizosphere Microbial Strategies Drive Functional Specialization in Coastal Halophyte Succession: Differential Adaptation of and to Saline-Alkali Stress.

While rhizosphere microbiome functions in saline soils are well documented, complementary microbial strategies between pioneer and late-successional halophytes remain unexplored. Here, we used 16S rRNA sequencing and FAPROTAX functional prediction to compare the rhizosphere bacterial communities of two key halophytes- and -in a reclaimed coastal wetland. The results demonstrate that both plants significantly restructured microbial communities through convergent enrichment of stress-tolerant taxa (, , , and ) while suppressing sulfur-oxidizing bacteria ( and ).

Solving a class of resource allocation problem under dynamic constraints: A predefined-time distributed optimization scheme.

In this paper, a predefined-time distributed optimization algorithm is designed to solve the resource allocation problem (RAP) with dynamic constraints. This algorithm updates auxiliary variables in real time through a distributed approach and allocates resources to each node based on dynamic constraints. Its advantages include ensuring all nodes quickly converge to the optimal value within a predefined time, thereby enhancing algorithm efficiency.

stGuide advances label transfer in spatial transcriptomics through attention-based supervised graph representation learning.

The growing availability of spatial transcriptomics data offers key resources for annotating query datasets using reference datasets. However, batch effects, unbalanced reference annotations, and tissue heterogeneity pose significant challenges to alignment analysis. Here, we present stGuide, an attention-based supervised graph learning model designed for cross-slice alignment and efficient label transfer from reference to query datasets.

Exploring the influencing factors of abdominal aortic calcification events in chronic kidney disease (CKD) and non-CKD patients based on interpretable machine learning methods.

Background: Calcification is prevalent in CKD patients, with abdominal aortic calcification (AAC) being a strong predictor of coronary calcification. We aimed to identify key calcification factors in CKD and non-CKD populations using machine learning models.

Methods: Data from the National Health and Nutrition Examination Survey (NHANES), including demographics, blood and urine tests, and AAC scores, were analyzed using machine learning models.

Optimizing Strategy for Lung Cancer Screening: From Risk Prediction to Clinical Decision Support.

Purpose: Low-dose computed tomography (LDCT) screening is effective in reducing lung cancer mortality by detecting the disease at earlier, more treatable stages. However, high false-positive rates and the associated risks of subsequent invasive diagnostic procedures present significant challenges. This study proposes an advanced pipeline that integrates machine learning (ML) and causal inference techniques to optimize lung cancer screening decisions.

Telitacicept and Tacrolimus Synergy in Managing Refractory Primary Membranous Nephropathy: Case Insights.

BACKGROUND Refractory primary membranous nephropathy (pMN), characterized by persistent proteinuria despite immunosuppressive therapy, is frequently associated with phospholipase A2 receptor (PLA2R) antibodies. Recent advancements have emphasized the effectiveness of biological agents, particularly the novel recombinant fusion protein telitacicept, in treating this condition. However, only a limited number of published studies have reported the use of telitacicept in pMN treatment.

Impact of Hormone Receptor Status and HER2 Expression on Neoadjuvant Targeted Therapy Response in HER2-Positive Breast Cancer: A Multicenter Retrospective Study.

Previous studies indicate that HER2 protein expression and hormone receptor (HoR) status affect the sensitivity of HER2-positive breast cancer to neoadjuvant therapy, but it is unclear if sensitivity varies among subgroups defined by HER2 and HoR status. We examined 2 cohorts of patients, aged 18 to 80 years, with HER2-positive early breast cancer who underwent neoadjuvant therapy followed by surgery between January 1, 2009, and December 31, 2022: cohort 1 included 2648 patients, and cohort 2 had 141 patients with RNA expression data. Patients were divided into 4 groups based on immunohistochemical HER2 and HoR status: HER2(3+)/HoR-, HER2(3+)/HoR+, HER2(2+)/HoR-, and HER2(2+)/HoR+.

Combining multi-omics analysis with machine learning to uncover novel molecular subtypes, prognostic markers, and insights into immunotherapy for melanoma.

Background: Melanoma (SKCM) is an extremely aggressive form of cancer, characterized by high mortality rates, frequent metastasis, and limited treatment options. Our study aims to identify key target genes and enhance the diagnostic accuracy of melanoma prognosis by employing multi-omics analysis and machine learning techniques, ultimately leading to the development of novel therapeutic strategies.

Methods: We obtained and processed transcriptomic data, including RNA expression profiles, methylation microarray data, gene mutation data, and clinical information, from the TCGA dataset using multi-omics analysis and machine learning techniques.

Single-cell RNA sequencing reveals a new mechanism of endothelial cell heterogeneity and healing in diabetic foot ulcers.

Diabetic foot ulcers (DFU) are a common and severe complication among diabetic patients, posing a significant burden on patients' quality of life and healthcare systems due to their high incidence, amputation rates, and mortality. This study utilized single-cell RNA sequencing technology to deeply analyze the cellular heterogeneity of the skin on the feet ofDFU patients and the transcriptomic characteristics of endothelial cells, aiming to identify key cell populations and genes associated with the healing and progression of DFU. The study found that endothelial cells from DFU patients exhibited significant transcriptomic differences under various conditions, particularly in signaling pathways related to inflammatory responses and angiogenesis.

NIR-triggering cobalt single-atom enzyme switches off-to-on for boosting the interactive dynamic effects of multimodal phototherapy.

Noninvasive phototherapy with functional preservation is considered to be a promising cancer therapeutic method. However, the clinical application of tumor phototherapy is severely restrained by the lack of appropriate multimodal phototherapy agents exhibiting an ideal tissue penetration depth to maximize the antitumor efficiency as well as to maintain important tissue functions. Herein, an innovative near-infrared ray (NIR)-triggered photodynamic-photocatalytic-photothermal therapy (PDT-PCT-PTT) agent based on an atomically dispersed cobalt single-atom enzyme (Co-SAE) anchored on hollow N-doped carbon sphere (HNCS) has been strategically developed.

Fine Tuning of Hybridized Local and Charge-Transfer Excited States and Luminescence in Carbazole/Benzothiadiazole Isomeric Emitters by Varying Linking Mode.

Hybridized local and charge-transfer (HLCT) type emitters can harvest triplet excitons for light emission via high-lying reverse intersystem crossing (hRISC), showing great potential for application in organic light-emitting diodes (OLEDs). Herein, two isomeric emitters NPC3BTD and NPC2BTD were developed by linking two 9-phenyl-9H-carbazole (NPC) donors onto the central benzo[c][1,2,5]thiadiazole (BTD) acceptor. By tuning the linkage from 3-site to 2-site of carbazole ring, the D-A dihedral angle was decreased, then the HOMO delocalization and CT/LE content ratio in HLCT excited states were reduced, thus NPC2BTD revealed fluorescence hypsochromic shift by 30 nm to green region.

Recent advances in adipose-derived mesenchymal stem cell-derived exosomes for regulating macrophage polarization.

Adipose-derived mesenchymal stem cells (ADSCs) exhibit superior immunomodulatory properties and have broad therapeutic applications. They induce macrophage M2 polarization for anti-inflammatory responses. Exosomes derived from ADSCs (ADSC-EXOs) exhibit biological functions similar to those of ADSCs but can circumvent the limitations associated with cellular injection therapies.