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

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

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.

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.

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.

Irritable bowel syndrome(IBS)is a prevalent functional gastrointestinal disorder characterized by a complex etiology involving multiple interacting factors.Accumulating evidence in recent years has indicated that intestinal barrier dysfunction may play a crucial role in the pathogenesis of IBS.This review systematically ex-amines the impact of intestinal barrier dysfunction on IBS,analyzing its associations with the mechanical,im-mune,chemical,and microbial components of the gut barrier,as well as current clinical treatment approaches.Moreover,this paper highlights the potential of intestinal barrier repair mechanisms as therapeutic targets,which may provide novel insights and directions for understanding the underlying pathophysiological mechanisms and de-veloping effective interventions for IBS.

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(d 18∶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 phos-photransferase 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.

Objective To 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.Methods A 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.Results Compared 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).Conclusion ACA-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.

The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic 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 work-flow,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 mu-tations to predict their impact on binding affinity to the targets.The results showed that multiple mu-tations 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.