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Drug discovery focused on target proteins has been a successful strategy, but many diseases and biological processes lack obvious targets to enable such approaches. Here, to overcome this challenge, we describe a deep learning–based efficacy prediction system (DLEPS) that identifies drug candidates using a change in the gene expression profile in the diseased state as input. DLEPS was trained using chemically induced changes in transcriptional profiles from the L1000 project. We found that the changes in transcriptional profiles for previously unexamined molecules were predicted with a Pearson correlation coefficient of 0.74. We examined three disorders and experimentally tested the top drug candidates in mouse disease models. Validation showed that perillen, chikusetsusaponin IV and trametinib confer disease-relevant impacts against obesity, hyperuricemia and nonalcoholic steatohepatitis, respectively. DLEPS can generate insights into pathogenic mechanisms, and we demonstrate that the MEK–ERK signaling pathway is a target for developing agents against nonalcoholic steatohepatitis. Our findings suggest that DLEPS is an effective tool for drug repurposing and discovery. Drug discovery based on transcriptional profiling does not require knowledge of protein targets.

Multi-sensor integrated navigation technology has been applied to the indoor navigation and positioning of robots. For the problems of a low navigation accuracy and error accumulation, for mobile robots with a single sensor, an indoor mobile robot positioning method based on a visual and inertial sensor combination is presented in this paper. First, the visual sensor (Kinect) is used to obtain the color image and the depth image, and feature matching is performed by the improved scale-invariant feature transform (SIFT) algorithm. Then, the absolute orientation algorithm is used to calculate the rotation matrix and translation vector of a robot in two consecutive frames of images. An inertial measurement unit (IMU) has the advantages of high frequency updating and rapid, accurate positioning, and can compensate for the Kinect speed and lack of precision. Three-dimensional data, such as acceleration, angular velocity, magnetic field strength, and temperature data, can be obtained in real-time with an IMU. The data obtained by the visual sensor is loosely combined with that obtained by the IMU, that is, the differences in the positions and attitudes of the two sensor outputs are optimally combined by the adaptive fade-out extended Kalman filter to estimate the errors. Finally, several experiments show that this method can significantly improve the accuracy of the indoor positioning of the mobile robots based on the visual and inertial sensors.

Background Chronic obstructive pulmonary disease (COPD) patients face elevated perioperative risks, yet evidence-based guidelines for preoperative hemoglobin optimization in non-cardiac surgery remain undefined. This study investigated the association between preoperative hemoglobin levels and postoperative outcomes in the high-risk population, with emphasis on nonlinear dynamics and clinically actionable thresholds. Methods In this retrospective cohort study, 346 COPD patients undergoing non-cardiac surgery were analyzed. Multivariable regression models (adjusted for demographics, comorbidities, and surgical factors) evaluated the association of hemoglobin and length of stay (LOS), mortality, and other complications. Restricted cubic splines and threshold analysis characterized nonlinear relationships, while subgroup analysis and sensitivity analysis assessed effect heterogeneity. Results For every 1 g/L increase in Hemoglobin, LOS was shortened by 0.09 days (95% CI −0.15 ~ −0.04; P  = 0.001) and mortality was decreased by 9% (OR = 0.92; 95% CI 0.86 ~ 0.98; P  = 0.013). Moderate/Severe anemia (Hb < 90 g/L) increased mortality 23-fold (OR = 23.42; 95% CI 1.8 ~ 304.23; P  = 0.013) and postoperative delirium (POD) risk ninefold (OR = 9.27; 95% CI 1.77 ~ 48.53; P  = 0.02). There was a non-linear relationship between Hemoglobin and LOS/POD. Subgroup analysis and forest plots indicated heterogeneity in the inverse hemoglobin-LOS association. Sensitivity analysis showed the effect of anemia on LOS was significant in the elderly (OR = 5.19, 95% CI −1.1 ~ 11.49; P  = 0.007) and pulmonary hypertension subgroup (OR = 6.88, 95% CI 2.33 ~ 11.43; P  < 0.001). Conclusion Preoperative hemoglobin optimization may be particularly beneficial for COPD patients undergoing non-cardiac surgery, with effects potentially more pronounced in elderly patients or those with pulmonary hypertension. However, our study was underpowered to confirm subgroup-specific effects due to sample size limitations. Future research should prioritize these high-risk subgroups for targeted preoperative optimization trials.

Septic cardiomyopathy (SCM) arises as a consequence of sepsis-associated cardiovascular dysfunction, for which there is currently no specific targeted therapy available. Previous studies have demonstrated the beneficial therapeutic effect of berberine (BBR) on SCM; however, the underlying mechanisms of action remain unclear. The objective of this is to elucidate how BBR alleviates SCM. Septic cardiomyopathy rat model was established by performing cecal ligation and puncture (CLP), while a cardiomyocyte injury model was provoked in H9C2 cells using lipopolysaccharide (LPS). Cardiac function was assessed through echocardiography, and myocardial histopathology was examined with hematoxylin-eosin (HE) staining. Cardiomyocyte viability was determined through Cell Counting Kit-8 (CCK8) assay, and measurement of ATP levels was done with an ATP assay kit. Mitochondrial ultrastructure was observed using transmission electron microscopy. Real-time polymerase chain reaction (RT-PCR) and Western blotting were employed to analyze the expression of Notch1 signaling pathway components and downstream molecules in myocardial tissues and cells. , BBR markedly improved symptoms and cardiac function in SCM rats, leading to enhanced ATP content, and ameliorated mitochondrial structure. Additionally, BBR increased Notch1 protein expression in myocardial tissue of the rats. , BBR elevated the survival rates of H9C2 cell, improved mitochondrial morphology, and raised ATP levels. The mRNA expression of Notch1, Hes1, and Hes2, and Notch1 protein expression was upregulated by BBR. While these effects were reversed upon inhibiting the Notch1 signaling pathway. BBR improves septic cardiomyopathy by modulating Notch1 signaling to protect myocardial mitochondria.

Background The dried root of Inula helenium L., known as Inulae Radix in Mongolian medicine, is a widely used heat-clearing plant drug within the Asteraceae family. Alantolactone (ATL), a compound derived from Inulae Radix, is a sesquiterpene lactone with a range of biological activities. However, there is a lack of studies investigating its effectiveness in the treatment of hypertension. The aim of this study is to explore the regulatory effect of alantolactone on blood pressure and its underlying mechanism. Methods and results Network pharmacology analysis suggested that ATL had a potential therapeutic effect on hypertension induced by angiotensin II (Ang II). Subsequently, the results of animal experiments demonstrated that ATL could suppress the increase in blood pressure caused by Ang II. Vascular ring experiments indicated that ATL could inhibit the vascular contractions induced by Ang II, Phenylephrine, and Ca 2 ⁺. Further experiments demonstrated that ATL could inhibit the calcium influx induced by Ang II and increase the expression of pMLC2. Molecular docking experiments showed that ATL had a high binding affinity with L-type Voltage-gated Calcium Channels (VGCC), and vascular ring experiments indicated that ATL could significantly inhibit the vascular contractions caused by the agonists of L-type VGCC. In addition, we also observed that ATL had an ameliorative effect on the vascular remodeling induced by Ang II. Conclusions ATL exerted an antihypertensive effect by inhibiting the activation of L-type VGCC and reducing calcium influx.

Immune-mediated glomerulonephritis represents a diverse group of kidney disorders caused by dysregulated immune responses and constitutes a major contributor to chronic kidney disease. Its pathogenesis can be conceptualized as a three-step cascade: aberrant activation of innate immunity through pattern-recognition receptors, inflammasome complexes, and complement pathways; adaptive immune dysregulation characterized by imbalanced B- and T-cell responses and the production of pathogenic autoantibodies; and terminal effector injury involving complement-mediated damage and progressive fibrosis. This narrative review summarizes current advances in anti-inflammatory biologics that intervene at these critical points across a broad spectrum of entities, including IgA nephropathy (IgAN), membranous nephropathy (MN), lupus nephritis (LN), focal segmental glomerulosclerosis (FSGS), minimal change nephropathy (MCN), anti-glomerular basement membrane (anti-GBM) disease, ANCA-associated vasculitis (AAV), and C3 glomerulopathy (C3G). Therapies including cytokine inhibitors targeting TNF-α or IL-6, B-cell-depleting antibodies such as anti-CD20, plasma cell-directed agents, and complement blockers against C5 or Factor B have demonstrated clinical benefits in IgAN, MN, and LN, where evidence from randomized controlled trials supports their efficacy in reducing proteinuria and preserving renal function. For other entities such as FSGS, MCN, anti-GBM disease, and C3G, the evidence remains preliminary, based largely on case reports, preclinical models, or early-phase trials. Despite therapeutic advances, challenges persist regarding efficacy variability, infection risks, and financial burden. Future research aims to achieve precision therapy through multi-omics-based stratification, next-generation biologics such as bispecific antibodies and gene therapies, and optimized drug delivery systems, steering immune-mediated glomerulonephritis management toward truly disease-modifying treatment.

Identification of (apo)lipoprotein subclasses causally underpinning atherosclerosis may lead to identification of novel drug targets for treatment of atherosclerotic cardiovascular disease (ASCVD). In this study, observational and genetic associations between (apo)lipoprotein profile and carotid intima‐media thickness‐assessed atherosclerosis, and risks of coronary artery disease (CAD) and ischemic stroke (IS) are assessed, using data from the UK Biobank study, with further exploration of potential drug target for these two ASCVD subtypes through multi‐omics analysis integrating genetic, transcriptomic, and proteomic data. Cholesteryl ester content in medium high‐density lipoprotein causally protective of atherosclerosis is identified, plus a target gene, PSRC1, with therapeutic potential for CAD, but not IS, supported by consistent evidence from multi‐omics layers of data, which also reveals that such therapeutic potential may be through downregulation of circulating proteins including TRP1, GRNs, and Pla2g12b, and upregulation of Neo1. The results provide strong evidence as well as mechanistic clues of PSRC1’s therapeutic potential for CAD. Lipid content in medium high‐density lipoprotein (HDL) particles, particularly cholesteryl esters, is identified as causally protective of atherosclerosis, and further ASCVD. Evidence from multi‐omics layers of data consistently supports PSRC1 with therapeutic potential for coronary artery disease (CAD), but not ischemic stroke. This study also provides mechanistic clues of PSRC1’s therapeutic potential through its downstream proteins.

The forgotten topological index of a (molecule) graph is the sum of cubes of all its vertex degrees, which plays a significant role in measuring the branching of the carbon atom skeleton. It is meaningful and difficult to explore sufficient conditions for a given graph keeping certain properties in graph theory. In this paper, we mainly explore sufficient conditions in terms of the forgotten topological index for a graph to be ℓ-connected, ℓ-deficient, ℓ-Hamiltonian and ℓ−-independent, respectively. The conditions cannot be dropped.

Podocyte injury is a central driver of proteinuria and progressive kidney dysfunction. Although podocytes are continuously exposed to diverse stressors in both physiological and pathological contexts, the dynamic processes underlying their adaptation and eventual failure remain poorly defined. Here, we performed integrative single-nucleus RNA sequencing of kidney tissues from patients with six types of representative chronic glomerulonephritis, capturing a spectrum of podocyte injury states. We identified distinct podocyte subpopulations and reconstructed a dynamic trajectory characterized by an initial adaptive activation followed by progressive functional decline. Integration with time-resolved transcriptomics identified 778 candidate genes associated with podocyte stress responses. To distinguish putative functional drivers from secondary transcriptional changes, we integrated these candidates with a genome-wide CRISPR-Cas9 knockout screen, prioritizing genes required for podocyte survival under stress conditions. Subsequent siRNA-mediated validation of five representative candidates-BST1, TALDO1, ATP6V1E1, PPP2R1A and CHL1-showed that knockdown of these genes significantly compromised cell viability and accelerated apoptosis, highlighting a coordinated survival network spanning metabolic regulation, autophagy, and cytoskeletal stability. Our findings define a dynamic framework of podocyte stress adaptation and failure, and suggest that targeting stress-response pathways may prolong podocyte survival, thereby extending the therapeutic window for intervention in chronic kidney disease.

Abstract In the contaminated soil, the plants are often threatened by pollutants, reducing the efficiency of phytoremediation. Plant growth–promoting rhizobacteria (PGPR) screened from plant rhizosphere can alleviate this phenomenon. Juncus effusus (J. effusus) has good effects on the remediation of heavy metal pollution but rarely used in soil research. This study aims to determine how PGPR affects the process of the remediation on pyrene-Ni-contaminated soil by J. effusus. PGPR was combined with J. effusus to strengthen the phytoremediation efficiency. The pot experiments were used to investigate the influences of inoculation PGPR on physiological conditions, soil enzyme activity, pyrene, and Ni enrichment ability. PGPR could promote J. effusus growth and nutrient absorption. PGPR was beneficial to promoted soil dehydrogenase activities and pyrene degradation rate in soil. Pyrene degradation rate were 97.3% and 97.1% in pyrene-contaminated soil and pyrene-Ni-contaminated soil, respectively. After inoculation with PGPR, the Ni content in roots of Ni contaminated soil increased from 69.5 to 111.5 mg kg−1, and that of pyrene-Ni-contaminated soil increased from 92.9 to 123.4 mg kg−1. Furthermore, PGPR could promote the chemical morphology transformation of Ni and improved the content of exchangeable Ni in soil significantly. The results showed that PGPR could alleviate the stress of pyrene and Ni on J. effusus, and have a good effect on the remediation of pyrene-Ni in contaminated soil. Further study should focus on the mechanism of PGPR to reduce toxicity of pyrene and Ni to J. effusus.