ObjectiveTo investigate the impact of anticentromere antibody （ACA） on the clinical features and prognosis of patients with primary biliary cholangitis （PBC） by comparing clinical classification， ursodeoxycholic acid （UDCA） response， GLOBE score， and UK-PBC score between ACA-positive PBC patients and ACA-negative PBC patients. MethodsA total of 749 patients who were admitted to Beijing Ditan Hospital， Capital Medical University， from August 2013 to December 2022 and were diagnosed with PBC were enrolled and divided into ACA-positive group with 147 patients and ACA-negative group with 602 patients. According to their conditions on admission， the two groups were compared in terms of the distribution of clinical types， i.e.， chronic progression-type PBC， portal hypertension-type PBC， and standard jaundice/liver failure-type PBC. There were 261 patients with complete data after 1-year follow-up， among whom there were 53 patients with positive ACA and 208 with negative ACA. A statistical analysis was performed， and propensity score matching was performed based on sex and age at a ratio of 1∶2. The two groups were compared in terms of 1-year UDCA response rate， GLOBE score， and UK-PBC score before and after matching. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. ResultsCompared with the ACA-negative group， the ACA-positive group had a significantly higher age （61.28±10.35 years vs 56.74±12.17 years， t=4.164， P<0.001）， a significantly higher proportion of female patients （93.9% vs 77.6%， χ²=20.221， P<0.001）， a significantly higher proportion of patients with portal hypertension （48.3% vs 27.6%， χ²=23.289， P<0.001）， and a significantly lower proportion of patients with jaundice/liver failure （24.5% vs 38.5%， χ²=10.205， P<0.001）. After 1-year follow-up， for the 261 PBC patients with complete data， there was no significant difference in UDCA response rate before propensity score matching between the ACA-positive group and the ACA-negative group （41.5% vs 41.8%， P>0.05）， and there was a significant difference in the proportion of patients with a GLOBE score of >0.3 between the ACA-positive group and the ACA-negative group （92.5% vs 80.3%， χ²=3.935， P=0.047）. There were 53 patients in the ACA-positive group and 106 patients in the ACA-negative group after propensity score matching， and there were no significant differences between the two groups in UDCA response rate， GLOBE score， and UK-PBC score （all P>0.05）. ConclusionACA-positive patients tend to have an older age， with a higher proportion of female patients or patients with portal hypertension， while there is a relatively low proportion of patients with jaundice/liver failure. Positive ACA has no significant impact on UDCA response rate， GLOBE score， and UK-PBC score.

Neurodegenerative diseases (NDDs) are a group of heterogeneous neurological disorders that can cause progressive loss of neurons in the central nervous system or peripheral nervous system, resulting in a decline in motor function. Motion capture, as a high-precision and high-resolution technology for capturing human motion data, drives NDDs motor assessment to effectively extract kinematic features and thus assess the patient's motor ability or disease severity. This paper focuses on the recent research progress in motor assessment of NDDs driven by motion capture data. Based on a brief introduction of NDDs motor assessment datasets, we categorized the assessment methods into three types according to the way of feature extraction and processing: NDDs motor assessment methods based on statistical analysis, machine learning and deep learning. Then, we comparatively analyzed the technical points and characteristics of the three types of methods from the aspects of data composition, data preprocessing, assessment methods, assessment purposes and effects. Finally, we discussed and prospected the development trends of NDDs motor assessment.
Humans ; Neurodegenerative Diseases/diagnosis* ; Machine Learning ; Biomechanical Phenomena ; Deep Learning ; Motion ; Motion Capture

Dry eye disease (DED) is a prevalent and intractable ocular disease induced by a variety of causes. Elevated sphingomyelin (SM) levels and pro-inflammatory cytokines were detected on the ocular surface of DED patients, particularly in the meibomian glands. Sphingomyelin synthase 2 (SMS2), one of the proteins involved in SM synthesis, would light a novel way of developing a DED therapy strategy. Herein, we report the design and optimization of a series of novel thiophene carboxamide derivatives to afford 14l with an improved highly potent inhibitory activity on SM synthesis (IC_{50, SMS2} = 28 nmol/L). Moreover, 14l exhibited a notable protective effect of anti-inflammation and anti-apoptosis on human corneal epithelial cells (HCEC) under TNF-α-hyperosmotic stress conditions in vitro, with an acceptable ocular specific distribution (corneas and meibomian glands) and pharmacokinetics (PK) profiles (t _{1/2, cornea} = 1.11 h; t _{1/2, meibomian glands} = 4.32 h) in rats. Furthermore, 14l alleviated the dry eye symptoms including corneal fluorescein staining scores and tear secretion in a dose-dependent manner in mice. Mechanically, 14l reduced the mRNA expression of Tnf-α, Il-1β and Mmp-9 in corneas, as well as the proportion of very long chain SM in meibomian glands. Our findings provide a new strategy for DED therapy based on selective SMS2 inhibitors.

The identification and optimization of mutations in nanobodies are crucial for enhancing their therapeutic potential in disease prevention and control. However, this process is often complex and time-consuming, which limit its widespread application in practice. In this study, we developed a workflow, named Evolutionary-Nanobody (EvoNB), to predict key mutation sites of nanobodies by combining protein language models (PLMs) and molecular dynamic (MD) simulations. By fine-tuning the ESM2 model on a large-scale nanobody dataset, the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced. The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies. Additionally, we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations. MD simulations analyzed the energy changes caused by these mutations to predict their impact on binding affinity to the targets. The results showed that multiple mutations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target, further validating the potential of this workflow for designing and optimizing nanobody mutations. Additionally, sequence-based predictions are generally less dependent on structural absence, allowing them to be more easily integrated with tools for structural predictions, such as AlphaFold 3. Through mutation prediction and systematic analysis of key sites, we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes. The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

Cantharidin (CTD), a natural compound used to treat multiple tumors in the clinic setting, has been limited due to acute kidney injury (AKI). However, the major cause of AKI and its underlying mechanism remain to be elucidated. Serum creatinine (SCr) and blood urea nitrogen (BUN) were detected through pathological evaluation after CTD (1.5 mg/kg) oral gavage in mice in 3 days. Kidney lipidomics based on ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to investigate lipids disorder after CTD exposure in mice. Then, spatial metabolomics based on matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) was used to detect the kidney spatial distribution of lipids. Integrative analysis was performed to reveal the spatial lipid disorder mechanism and verify key lipids in vitro. The results showed that the levels of SCr and BUN were increased, and tubular necrosis was observed in mouse kidneys, resulting in acute tubular necrosis (ATN) in CTD-induced AKI. Then, lipidomics results revealed that after CTD exposure, 232 differential lipid metabolites and 11 pathways including glycerophospholipid (GP) and sphingolipid (SL) metabolism were disrupted. Spatial metabolomics revealed that 55 spatial differential lipid metabolites and nine metabolic pathways were disturbed. Subsequently, integrative analysis found that GP metabolism was stimulated in the renal cortex and medulla, whereas SL metabolism was inhibited in the renal cortex. Up-regulated lysophosphatidylcholine (LysoPC) (18:2(9Z,12Z)), LysoPC (16:0/0:0), glycerophosphocholine, and down-regulated sphingomyelin (SM) (d18:0/16:0), SM (d18:1/24:0), and SM (d42:1) were key differential lipids. Among them, LysoPC (16:0/0:0) was increased in the CTD group at 1.1196 μg/mL, which aggravated CTD-induced ATN in human kidney-2 (HK-2) cells. LysoPC acyltransferase was inhibited and choline phosphotransferase 1 (CEPT1) was activated after CTD intervention in mice and in HK-2 cells. CTD induces ATN, resulting in AKI, by activating GP metabolism and inhibiting SL metabolism in the renal cortex and medulla, LysoPC (16:0/0:0), LysoPC acyltransferase, and CEPT1 may be the therapeutic targets.

Lirispirolides A-L (1-12), twelve novel sesquiterpene-monoterpene heterodimers featuring distinctive carbon skeletons, were isolated from the branches and leaves of Chinese tulip tree [Liriodendron chinense (L. chinense)], a rare medicinal and ornamental plant endemic to China. The structural elucidation was accomplished through comprehensive spectroscopic analyses, quantum-chemical calculations, and X-ray crystallography. These heterodimers exhibit a characteristic 2-oxaspiro[4.5]decan-1-one structural motif, biosynthetically formed through intermolecular [4 + 2]-cycloaddition between a germacrane-type sesquiterpene and an ocimene-type monoterpene. The majority of the isolated compounds demonstrated significant anti-neuroinflammatory effects in lipopolysaccharide (LPS)-induced BV-2 microglial cells by reducing the production of pro-inflammatory mediators, specifically tumor necrosis factor-α (TNF-α) and nitric oxide (NO). Further investigation revealed that the lirispirolides' inhibition of NO release correlated with decreased messenger ribonucleic acid (mRNA) expression of inducible NO synthase (iNOS).
Sesquiterpenes/isolation & purification* ; Anti-Inflammatory Agents/isolation & purification* ; Animals ; Mice ; Tumor Necrosis Factor-alpha/genetics* ; Nitric Oxide/immunology* ; Microglia/immunology* ; Molecular Structure ; Liriodendron/chemistry* ; Monoterpenes/isolation & purification* ; Plants, Medicinal/chemistry* ; Cell Line ; Lipopolysaccharides ; Nitric Oxide Synthase Type II/immunology* ; Plant Extracts/pharmacology* ; China

OBJECTIVE: To explore the toxicological mechanism of drug-induced liver injury(DILI) in rats induced by cantharidin(CTD). METHODS: SD rats were exposed to different doses of CTD(0.061 4, 0.092 1, 0.184 1 mg·kg−1) by oral gavage for 28 d. Liver index and serum liver function indictors were detected. HE staining was used to evaluate the pathological changes of liver. Then the proteins in endoplasmic reticulum stress(ERS), autophagy, and apoptosis-pathway were detected by Western blotting. RESULTS: The liver index was increased in CTD groups. The ALT, AST, LDH, ALP and T-Bil were increased by CTD with a dose-dependent manner. Disrupted hepatic architecture and dilatation of central vein were observed after CTD intervention. The protein expression levels of GRP78, CHOP, ATF4, Beclin-1, LC3, Caspase-3, Caspase-8, and Bax/Bcl-2 were increased after CTD intervention. Molecular docking results revealed that GRP78, ATF4, and Beclin-1 could directly interconnect with CTD. CONCLUSION CTD can activate ERS, autophagy and synergistically inducing downstream apoptosis in rat, providing a novel insight into the mechanism of CTD-induced DILI.

Objective To explore the feasibility of automating the measurement of abduction angle after total hip arthroplasty(THA)on postoperative radiographs by using deep learning algorithms.Methods The data were retrospectively collected.A total of 381 cases were used to develop deep learning model.Two radiologists annotated the key points on the images(lateral-superior point and medial-inferior point of acetabular cups,tear drops).The data was split into training dataset(304 cases),tuning dataset(38 cases),and test dataset(39 cases).A 2D U-net model was trained to segment the key points and the abduction angle were automatically meas-ured.After development of the model,an external validation dataset was collected(143 cases).Dice similarity coefficient(DSC)and mean absolute error(MAE)were used to evaluate the prediction efficiency of the model in the test dataset and the external validation dataset.Bland-Altman test was used to analyze the agreement between the abduction angle measured automatically by the model and the physician measurement.Results The DSC were 0.870-0.905 and 0.690-0.750 in the test dataset and the external validation dataset,and the corresponding MAE were 0.311-0.561 and 0.951-1.310.For the result of Bland-Altman analysis,only 6.52％(3/46)and 2.08％(3/144)of the abduction angle measurements in the test dataset and external validation dataset were outside the 95％limit of agreement(LoA).In the qualitative evaluation of the abduc-tion angle,the agreement of the model with the physician were 97.8％and 90.3％in the test dataset and the external validation dataset.Conclusion It is feasible to use deep learning algorithms to automatically measure the abduction angle after THA on X-ray images,achieving similar accuracy to that of physician.

This paper provided a comprehensive review of the concept, current situation and influencing factors of survivors returning to work after hematopoietic stem cell transplantation, both in domestic and international contexts. The research analyzed and elaborates on four aspects of individual factors, disease-related factors, occupational factors, and social support, in order to provide references for constructing an intervention program for the return to work of hematopoietic stem cell transplantation survivors based on the cultural background in China.

Objective:To understand the current status of financial toxicity in patients with heart failure and the factors affecting it, and to provide ideas for making personalized and informed decisions.Methods:Using a scoping review methodological framework, PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, VIP, Wanfang, and SinoMed Databases were searched and screened for relevant literature on financial toxicity in patients with heart failure, with a timeframe of January 1, 2014-October 31, 2023, respectively. Relevant literature was identified based on inclusion and exclusion criteria, and data were extracted, collected, summarized, and the findings were reported.Results:Ten literatures that met the inclusion and exclusion criteria were identified. The results showed 5 cross-sectional surveys, 2 qualitative studies, and 1 each of reviews, mixed studies and commentaries. Heart failure patients generally faced high levels of financial toxicity, the incidence and severity of patient financial toxicity varied somewhat between study outcomes. Factors influencing financial toxicity in heart failure patients included age, education level, family income level, discussion of medical costs with physicians, type of insurance the patient had, and occupational status.Conclusions:In the future, we can develop and apply a specialized assessment tool for financial toxicity in heart failure patients in China, further explore the factors affecting financial toxicity in heart failure patients, and formulate personalized treatment plans and financial support strategies for patients according to the influencing factors, so as to reduce the impact of financial toxicity on heart failure patients.