Metabolic-associated fatty liver disease (MAFLD) and osteoporosis (OP) are two very common metabolic diseases. A growing body of experimental evidence supports a pathophysiological link between MAFLD and OP. MAFLD is often associated with the development of OP. Rutaecarpine (RUT) is one of the main active components of Chinese medicine Euodiae Fructus. Our previous studies have demonstrated that RUT has lipid-lowering, anti-inflammatory and anti-atherosclerotic effects, and can improve the OP of rats. However, whether RUT can improve both fatty liver and OP symptoms of MAFLD mice at the same time remains to be investigated. In this study, we used C57BL/6 mice fed a high-fat diet (HFD) for 4 months to construct a MAFLD model, and gave the mice a low dose (5 mg·kg^-1) and a high dose (15 mg·kg^-1) of RUT by gavage for 4 weeks. The effects of RUT on liver steatosis and bone metabolism were then evaluated at the end of the experiment [this experiment was approved by the Experimental Animal Ethics Committee of Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences (approval number: IMB-20190124D₃03)]. The results showed that RUT treatment significantly reduced hepatic steatosis and lipid accumulation, and significantly reduced bone loss and promoted bone formation. In summary, this study shows that RUT has an effect of improving fatty liver and OP in MAFLD mice.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

Background::China is one of the countries with the largest burden of gastrointestinal and liver diseases (GILD) in the world. The GILD constitutes various causes of mortality and disability. The study aimed to investigate the trend of GILD in China using the Global Burden of Diseases Study 2019 (GBD 2019) data resources from 1990 to 2019.Methods::The data on the age-standardized mortality rates (ASMR) and disability-adjusted life years (DALYs) for GILD in China from 1990 to 2019 were collected from the GBD 2019 data resources. Furthermore, the ranking of the main causes of deaths and DALYs, as well as the trends of ASMR, DALYs, years of life lost (YLLs), and years of life lost due to disability (YLDs) per 1,000,000 in GILD were reported.Results::The ASMR and DALYs for stomach cancer, liver cancer, and esophageal cancer, which ranked top three among the GILDs from 1990 to 2019, were gradually decreasing. Significant decreases in the ASMR and DALYs were found in diarrheal diseases and acute hepatitis (A, E, and C). However, noteworthy increases were found in those of colon and rectum cancer (CRC) and pancreatic cancer. Trend of DALYs, mortality, and YLLs rates for most of GILD were decreasing from 1990 to 2019, except the burden of CRC and pancreatic cancer with an increasing trend. The DALYs, mortality and YLLs of most GILD diseases showed decreasing trends from 1990 to 2019, except the burden of CRC and pancreatic cancer with an increasing trends.Conclusions::The result of the GBD 2019 showed that the rates of most GILDs decreased in China; however, gastrointestinal and liver cancer, such as stomach cancer still held the top ranking. Furthermore, the shift from infectious diseases to non-communicable causes among GILD burden is occurring.

Objective To explore early postoperative gait characteristics and clinical outcomes after total knee arthroplasty(TKA).Methods From February 2023 to July 2023,26 patients with unilateral knee osteoarthritis(KOA)were treated with TKA,including 4 males and 22 females,aged from 57 to 85 years old with an average of(67.58±6.49)years old;body mass in-dex(BMI)ranged from 18.83 to 38.28 kg·m-2 with an average of(26.43±4.15)kg·m-2;14 patients on the left side,12 pa-tients on the right side;according to Kellgren-Lawrence(K-L)classification,6 patients with grade Ⅲ and 20 patients with grade Ⅳ;the courses of disease ranged from 1 to 14 years with an average of(5.54±3.29)years.Images and videos of standing up and walking,walking side shot,squatting and supine kneeling were taken with smart phones before operation and 6 weeks after operation.The human posture estimation framework OpenPose were used to analyze stride frequency,step length,step length,step speed,active knee knee bending angle,stride length,double support phase time,as well as maximum hip flexion angle and maximum knee bending angle on squatting position.Western Ontario and McMaster Universities(WOMAC)arthritis index and Knee Society Score(KSS)were used to evaluate clinical efficacy of knee joint.Results All patients were followed up for 5 to 7 weeks with an average of(6.00±0.57)weeks.The total score of WOMAC decreased from(64.85±11.54)before op-eration to(45.81±7.91)at 6 weeks after operation(P＜0.001).The total KSS was increased from(101.19±9.58)before opera-tion to(125.50±10.32)at 6 weeks after operation(P＜0.001).The gait speed,stride frequency and stride length of the affected side before operation were(0.32±0.10)m·s-1,(96.35±24.18)steps·min-1,(0.72±0.14)m,respectively;and increased to(0.48±0.11)m·s 1,(104.20±22.53)steps·min-1,(0.79±0.10)m at 6 weeks after operation(P＜0.05).The lower limb support time and active knee bending angle decreased from(0.31±0.38)sand(125.21±11.64)° before operation to(0.11±0.04)s and(120.01±13.35)° at 6 weeks after operation(P＜0.05).Eleven patients could able to complete squat before operation,13 patients could able to complete at 6 weeks after operation,and 9 patients could able to complete both before operation and 6 weeks after operation.In 9 patients,the maximum bending angle of crouching position was increased from 76.29° to 124.11° before operation to 91.35° to 134.12° at 6 weeks after operation,and the maximum bending angle of hip was increased from 103.70° to 147.25° before operation to 118.61° to 149.48° at 6 weeks after operation.Conclusion Gait analysis technology based on artificial intelligence image recognition is a safe and effective method to quantitatively identify the changes of pa-tients'gait.Knee pain of KOA was relieved and the function was improved,the supporting ability of the affected limb was im-proved after TKA,and the patient's stride frequency,stride length and stride speed were improved,and the overall movement rhythm of both lower limbs are more coordinated.

MicroRNAs(miRNAs)are small non-coding RNAs that are closely associated with the occur-rence and progression of tumors and other diseases.However,miRNAs require high-sensitivity and high-specificity detection due to their low abundance,high sequence homology,and rapid degradation.The RNA-cleaving deoxyribozyme(RCD)is a functional single-stranded DNA molecule that enables specific cleavage of substrates to release miRNAs that can be recycled with the assistance of metal ions,prompting cyclic signal amplification.Recently,developing new methods based on RCD catalytic amplification for miRNA high-sensitivity detection has become the focus of researchers.Based on combing with the various new technologies and materials in miRNA biosensors,this study classifies and reviews the new methods for detecting miRNAs based on deoxyribozyme catalytic amplification developed in recent years.We sepa-rate these miRNA detection strategies into three categories:RCDs combined with DNA self-assembly,i-sothermal amplification,and nanomaterials.We explore the basic principles of each approach,the latest research advancements,and application scenarios in biomedical sensors and medical detection.This re-view provides a foundation and reference for further research of highly sensitive and accurate miRNA de-tection strategies.

Objective:To develop and evaluate a nomogram prediction model for the 3-month mortality risk of patients with sepsis-associated acute kidney injury (S-AKI).Methods:Based on the American Medical Information Mart for Intensive Care-Ⅳ (MIMIC-Ⅳ), clinical data of S-AKI patients from 2008 to 2021 were collected.Initially, 58 relevant predictive factors were included, with all-cause mortality within 3 months as the outcome event. The data were divided into training and testing sets at a 7∶3 ratio. In the training set, univariate Logistic regression analysis was used for preliminary variable screening. Multicollinearity analysis, Lasso regression, and random forest algorithm were employed for variable selection, combined with the clinical application value of variables, to establish a multivariable Logistic regression model, visualized using a nomogram. In the testing set, the predictive value of the model was evaluated through internal validation. The receiver operator characteristic curve (ROC curve) was drawn, and the area under the curve (AUC) was calculated to evaluate the discrimination of nomogram model and Oxford acute severity of illness score (OASIS), sequential organ failure assessment (SOFA), and systemic inflammatory response syndrome score (SIRS). The calibration curve was used to evaluate the calibration, and decision curve analysis (DCA) was performed to assess the net benefit at different probability thresholds.Results:Based on the survival status at 3 months after diagnosis, patients were divided into 7?768 (68.54%) survivors and 3?566 (31.46%) death. In the training set, after multiple screenings, 7 variables were finally included in the nomogram model: Logistic organ dysfunction system (LODS), Charlson comorbidity index, urine output, international normalized ratio (INR), respiratory support mode, blood urea nitrogen, and age. Internal validation in the testing set showed that the AUC of nomogram model was 0.81 [95% confidence interval (95% CI) was 0.80-0.82], higher than the OASIS score's 0.70 (95% CI was 0.69-0.71) and significantly higher than the SOFA score's 0.57 (95% CI was 0.56-0.58) and SIRS score's 0.56 (95% CI was 0.55-0.57), indicating good discrimination. The calibration curve demonstrated that the nomogram model's calibration was better than the OASIS, SOFA, and SIRS scores. The DCA curve suggested that the nomogram model's clinical net benefit was better than the OASIS, SOFA, and SIRS scores at different probability thresholds. Conclusions:A nomogram prediction model for the 3-month mortality risk of S-AKI patients, based on clinical big data from MIMIC-Ⅳ and including seven variables, demonstrates good discriminative ability and calibration, providing an effective new tool for assessing the prognosis of S-AKI patients.

Combined therapy for hepatocellular carcinoma includes local therapy and systemic therapy.It is often used as preoperative neoadjuvant therapy and translational therapy.Preoperative treatment strategy should be based on preoperative diagnosis,especially imaging evaluation,pathological evaluation,multidisci-plinary discussion and scientific treatment endpoint selection.This article focuses on the relationship be-tween imaging evaluation and postoperative pathological evaluation,hoping to provide help for improving the scientific decision-making of preoperative treatment.

Background/Aims: Activation of the cold receptor, transient receptor potential melastatin 8 (TRPM8) by menthol inhibits esophageal secondary peristalsis in healthy adults. Ineffective esophageal motility (IEM) is common. This study is to evaluate the effects of acute infusion of menthol on esophageal peristalsis in patients with IEM. Methods: Twenty patients with IEM (males 11, mean age 36) were studied for esophageal peristalsis using high-resolution manometry. All participant had primary peristalsis performed with 10 water swallows and secondary peristalsis generated with 10 rapid air injections of 20 mL via mid-esophageal infusion port. Two different sessions by randomly performing acute administration of placebo or menthol (3 mM) were used for testing their effects on esophageal peristalsis. Results: Menthol infusion had no effects on distal contractile integral (P = 0.471), distal latency (P = 0.58), or complete peristalsis (P = 0.251). Menthol infusion did not change basal lower esophageal sphincter pressure (P = 0.321), esophagogastric junction contractile integral (P = 0.758), or integrated relaxation pressure (P = 0.375) of primary peristalsis, but reduced upper esophageal sphincter pressure (P = 0.037). Infusion of menthol significantly reduced the frequency of secondary peristalsis for air injects of 20 mL (P = 0.002), but did not affect distal contractile integral of secondary peristalsis for air injections of 20 mL. Conclusion This work has suggested that activation of TRPM8 by menthol can attenuate mechanosensitivity of secondary peristalsis in response to rapid air distension regardless of the presence of IEM.

Objective:To investigate the risk factors affecting the prognosis of penile cancer after surgery.Methods:We retrospectively analyzed the clinical data on 112 cases of penile cancer treated in Weifang People's Hospital from January 2013 to De-cember 2023.Using the Kaplan-Meier survival curve,χ2 test,Fisher's exact test,and univariate and multivariate Cox risk regression analyses,we compared the clinical characteristics among different groups,and determined the independent prognostic risk factors for cancer-specific survival(CSS)of the patients.Results:The 1-,3-and 5-year CSS rates of the penile cancer patients were 78.2%,66.1% and 63.7%,respectively.Kaplan-Meier analysis indicated a significant correlation of a higher neutrophil-to-lymphocyte ratio(NLR)with a lower CSS rate(P<0.001).Multivariate Cox regression analysis showed high NLR(HR=2.6;95% CI:1.031-6.558;P=0.043)to be an independent risk factor for CSS.Conclusion:Preoperative NLR is an independent risk factor for the prognosis of penile cancer.In addition,older age,farmer or worker occupation,lower education,preoperative lymphocyte-to-monocyte ratio(LMR)≤2.81,preoperative fibrinogen(FIB)≥3.41 g/L,advanced tumor stage and tumor differentiation are associated with the poor prognosis the malignancy.

Objective To design lower limb motor detection system based on the computer vision and human key point detection neural network model to realize non-contact measurement of the lower limb motor.Methods Firstly,a motion data acquisition platform was built to acquire the lower limb motor images,and to extract the 2D image coordinates of the key points of the lower limb in each frame based on the OpenPose neural network model.Secondly,the spatial coordinates of the key points were determined based on the computer vision algorithm with the position information of the visual sensors in the motion data acquisition platform,so as to analyze the lower limb motor in three-dimensional space.Finally,the data compu-tation of the system in case of different motion speeds was discussed with cycling as an example and the motion data simulta-neously collected by the motion capture system as references.Results The Pearson's correlation coefficients of the data computed by the system and the data obtained by the motion capture system were 0.950,0.917,and 0.828 at cycling speeds of 0.8,1.3,and 2.1 m/s,respectively,which were all within the strong correlation range.Conclusion The system developed indicates the lower limb motor,and thus can be used for the lower limb motion detection.[Chinese Medical Equipment Journal,2024,45(2):22-27]