The functional realization of proteins and other biological macromolecules depends on conformational dynamics and allosteric regulation, and elucidating their molecular mechanisms is an important foundation for understanding life processes. Molecular dynamics simulations are a powerful tool for investigating conformational evolution at the atomic level. However, traditional methods are limited by simulation timescales and high free-energy barriers, making it difficult to effectively capture rare conformations and their transition pathways. As a result, the development of enhanced sampling techniques has become key to overcoming this bottleneck. As a classical enhanced sampling technique, metadynamics suffers from several shortcomings, including strong dependence on collective variables and significant errors caused by bias potential accumulation. This article reviews three major improvement strategies. The first combines stochastic resetting with metadynamics, using trajectory-resetting mechanisms to improve sampling efficiency while avoiding the difficulty of optimizing collective variables. The second, SinkMeta, employs a “sinking” bias effect to enable efficient exploration of specific regions and paths. The third, OPES-based hybrid methods, improve the stability of free-energy estimation by optimizing the target distribution or the way the bias is constructed. These methods provide new ideas for characterizing free-energy landscapes and studying conformational transitions in complex biological systems, while also promoting the continued development of enhanced sampling methodologies.

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is higher among individuals with inflammatory bowel disease (IBD) than in the general population. Emerging evidence indicates that the development of MASLD in patients with IBD may occur independently of traditional metabolic risk factors, suggesting a unique pathophysiological mechanism distinct from conventional MASLD pathways. Bile acids (BAs), which act as critical signaling molecules in enterohepatic circulation, play an essential role in maintaining gastrointestinal homeostasis through bidirectional gut–liver axis communication. These molecules are increasingly recognized as pivotal regulators in the progression of both MASLD and IBD. While previous studies have characterized the dynamics of BA in blood or fecal samples under both conditions, a comprehensive understanding of their metabolic profiles and the associated interactions within the gut–liver axis is still lacking. This review synthesizes current evidence from studies employing BA metabolomics to investigate IBD and MASLD. By focusing on BA signatures, we summarize conserved alterations between these two conditions and their potential mechanisms of disease progression. Our review advances understanding of BA-mediated pathways in IBD and MASLD, providing a foundation for assessing their roles in contributing to the pathogenesis of MASLD in patients with IBD.

Objective To reveal the scientific output and trends in pulmonary nodules/early-stage lung cancer prediction models. Methods Publications on predictive models of pulmonary nodules/early lung cancer between January 1, 2002 and June 3, 2023 were retrieved and extracted from CNKI, Wanfang, VIP and Web of Science database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze the hotspots and theme trends. Results A marked increase in the number of publications related to pulmonary nodules/early-stage lung cancer prediction models was observed. A total of 12581 authors from 2711 institutions in 64 countries/regions published 2139 documents in 566 academic journals in English. A total of 282 articles from 1256 authors were published in 176 journals in Chinese. The Chinese and English journals which published the most pulmonary nodules/early-stage lung cancer prediction model-related papers were Journal of Clinical Radiology and Frontiers in Oncology, respectively. Chest was the most frequently cited journal. China and the United States were the leading countries in the field of pulmonary nodules/early-stage lung cancer prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that multi-omics, nomogram, machine learning and artificial intelligence were the current focus of research. Conclusion Over the last two decades, research on risk-prediction models for pulmonary nodules/early-stage lung cancer has attracted increasing attention. Prognosis, machine learning, artificial intelligence, nomogram, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of pulmonary nodules/early-stage lung cancer prediction models. More high-quality future studies should be conducted to validate the efficacy and safety of pulmonary nodules/early-stage lung cancer prediction models further and reduce the global burden of lung cancer.

OBJECTIVE: Varied acupoint selections represent a potential cause of the uncertainty surrounding the efficacy of acupuncture for knee osteoarthritis (OA). Skin temperature, a guiding factor for acupoint selection, may help to address this issue. This study explored thermal sensitization of acupoints used for the treatment of knee OA. METHODS: This cross-sectional case-control study enrolled cases aged 45-75 years with symptomatic knee OA and age- and gender-matched non-knee OA controls in a 1:1 ratio. All participants underwent infrared thermographic imaging. The primary outcome was the relative skin temperature of acupoint (STA), and the secondary outcome was the absolute STA of 11 acupoints. The Z test was used to compare the relative and absolute STAs between the groups. Principal component analysis was used to extract the common factors (CFs, acupoint cluster) in the STAs. A general linear model was used to identify factors affecting the STA in the knee OA cases. For the group comparisons of relative STA, P < 0.0045 (adjusted for 11 acupoints through Bonferroni correction) was considered to indicate statistical significance. For other analyses, P < 0.05 was used as the threshold for statistical significance. RESULTS: The analysis included 308 participants, consisting of 151 cases (mean age: [64.58 ± 6.67] years; male: 25.83%; mean body mass index: [25.70 ± 3.16] kg/m²) and 157 controls (mean age: [63.37 ± 5.96] years; male: 26.11%; mean body mass index: [24.47 ± 2.84] kg/m²). The relative STAs of ST34 (P = 0.0001), EX-LE2 (P < 0.0001), EX-LE5 (P = 0.0006), SP10 (P < 0.0001), BL40 (P = 0.0012) and GB39 (P = 0.0037) were higher in the knee OA group. No difference was found in the STAs of ST35, ST36, SP9, GB33 and GB34. Four CFs were identified for relative STA in both groups. The acupoints within each CF were consistent between the groups. The mean values of the relative STAs across each CF were higher in the knee OA group. In the knee OA cases, no factors were observed to affect the relative STA, while age and gender were found to affect the absolute STA. CONCLUSION Among patients with knee OA, thermal sensitization occurs in the acupoints of the lower extremity, exhibiting localized and regional thermal consistencies. The thermally sensitized acupoints that we identified in this study, ST34, SP10, EX-LE2, EX-LE5, GB39 and BL40, may be good choices for the acupuncture treatment of knee OA. Please cite this article as: Tu JF, Wang XZ, Yan SY, Wang YR, Yang JW, Shi GX, Zhang WZ, Jing LN, Yang LS, Liu DH, Wang LQ, Mi BH. Thermal sensitization of acupoints in patients with knee osteoarthritis: A cross-sectional case-control study. J Integr Med. 2025; 23(3): 289-296.
Humans ; Osteoarthritis, Knee/physiopathology* ; Male ; Cross-Sectional Studies ; Middle Aged ; Female ; Acupuncture Points ; Case-Control Studies ; Aged ; Skin Temperature ; Acupuncture Therapy

Objective:To investigate the relationship between different states of cardiac function and their changes during the course of diabetic foot ulcers(DFU), and to evaluate their impact on patient prognosis.Methods:A retrospective analysis was conducted on 194 DFU patients who were rehospitalized at approximately 3-month intervals. Basic clinical data and cardiac function-related indicators were collected at baseline and follow-up. Patients were followed until death or until November 10, 2024. Outcomes including ulcer healing, recurrence, minor amputation, and death were recorded. Logistic regression models were used to analyze the effects of cardiac function status and its changes on these four outcomes. Results:After treatment, the proportion of patients with NYHA class Ⅱ-Ⅲ decreased significantly from 33.5% at baseline to 21.6%( P=0.009). Serum N-terminal pro-B-type natriuretic peptide(NT-proBNP) level also decreased after treatment compared with baseline [635.85(59.83, 453.28) pg/mL vs 728.67(81.48, 696.15) pg/mL, P=0.055]. Serum NT-proBNP level was significantly higher in the death group compared to the survival group( P=0.002). The proportion of DFU patients with baseline NYHA class Ⅱ-Ⅲ was significantly higher than that in those with class Ⅰ( P=0.012). Regression analysis showed that an improvement in NT-proBNP levels was associated with a lower risk of DFU recurrence( OR=0.378, 95% CI 0.183-0.779, P=0.008), and improvement in NYHA class was associated with a lower mortality risk( OR=0.074, 95% CI 0.020-0.275, P<0.001). Conclusion:Cardiac function status and its changes during the treatment of DFU patients have strong prognostic implications, particularly in predicting the risk of recurrence and death outcomes.

Objective:To construct a thyroid nodule segmentation model using ultrasound dynamic images and explore its potential for assisting in the screening of thyroid nodules.Methods:A total of 126 patients with thyroid nodules（comprising 150 nodules）who were diagnosed and treated at Xuzhou Cancer Hospital from April 2024 to December 2024 were prospectively enrolled. Two-dimensional ultrasound was performed to capture short-axis and long-axis video images of thyroid nodules，forming a dynamic ultrasound image dataset. The dataset was divided into training，validation，and test sets in a ratio of 6∶1∶3. After the training loss curve converged，the model that performed well on the validation set was selected for testing. Three-fold cross-validation was employed for training and testing. All 300 ultrasound videos were divided into three subsets. In each experiment，two subsets were used as the training set，and one subset was used as the test set to evaluate the model's generalization ability. A collaborative spatiotemporal diffusion model was established based on the dynamic trends and tissue texture details of thyroid nodules. Six widely used segmentation metrics were employed to evaluate the model's application capabilities.Results:The study included 126 patients with 150 thyroid nodules，300 dynamic ultrasound images，and video lengths of 3-4 seconds per nodule，resulting in 12 312 segmented images. The size of the thyroid nodules was（10.7 ± 10.6）mm（transverse diameter）×（8.4 ± 6.3）mm（anteroposterior diameter）. Among the nodules，62（41.3%）had clear boundaries，while 88（58.7%）had indistinct boundaries；61（40.7%）exhibited regular shapes，while 89（59.3%）were irregular；66（44.0%）had a taller-than-wide aspect ratio；and 70（46.7%）showed microcalcifications. The collaborative diffusion model based on dynamic ultrasound image segmentation achieved the following scores：a Jaccard score of（69.22 ± 0.03）%，a Dice score of（79.16 ± 0.18）%，a Precision score of（86.70 ± 0.17）%，a Recall score of（77.82 ± 0.04）%，an Sα score of（85.26 ± 0.01）%，and an Eθmn score of（90.58 ± 0.17）%. Compared to other models，this model demonstrated significant improvements across all evaluation metrics，achieving the highest values in each metric with increments of over 8% and 1%，respectively. Conclusions:The collaborative diffusion model with a dynamic controller，constructed based on dynamic ultrasound images of thyroid nodules，demonstrates excellent performance in ultrasound image segmentation. It improves the accuracy of thyroid nodule screening，thereby providing a valuable auxiliary diagnostic tool for clinical practice.

Objective To development and validate a predictive model for distinguishing between malignant pleural effusion(MPE)and benign pleural effusion(BPE).Methods A total of 428 patients diagnosed with pleural effusion(PE)and hospitalized at the First Hospital of Huai'an Affiliated to Nanjing Medical University from July 2020 to May 2022 were selected.The patients were divided into BPE group(211 cases)and MPE group(217 cases)according to diagnostic criteria.The basic information and clinical data of these patients were collected.Boruta method was used for univariate screening,followed by multivariate Logistic regression to construct a basic nomogram model.Bootstrap method was used for internal validation to evaluate the performance of the nomogram,including dis-crimination,accuracy,and clinical applicability.Results The model included 8 key variables:dyspnea,chest pain,general symp-toms,X-ray/CT with malignant tumor features,serum carcinoembryonic antigen,serum neuron-specific enolase,pleural lactate dehy-drogenase,and pleural carcinoembryonic antigen.Internal validation showed that the area under the receiver operating characteristic curve(AUCROC)of the model was 0.933(95%confidence interval:0.912-0.954),with good accuracy(P＞0.05).Decision curve a-nalysis(DCA)indicated that this predictive model for predicting MPE risk had a significant net benefit when the probability threshold exceeded 1%.Conclusion The constructed prediction model could effectively distinguish between MPE and BPE.

Uric acid is the end product of purine metabolism in the human body. In recent years, the role of uric acid in female fertility and assisted reproductive technology (ART) has gained increasing attention. Dysregulation of uric acid metabolism can lead to hyperuricemia (HUA). HUA is not only closely related to metabolic syndrome and cardiovascular diseases but may also adversely affect female fertility by influencing ovarian function and embryos development. In this review, we explored the role of uric acid in female fertility, including its association with female subfertility, infertility, adverse pregnancy outcomes and metabolic syndrome, as well as its potential impact on ART like in vitro fertilization-embryo transfer and intracytoplasmic sperm injection. Further studies are needed to clarify the threshold and clinical intervention value of uric acid levels in women of childbearing age, providing a basis for reproductive health counseling and personalized pregnancy assistance for HUA patients of childbearing age.

OBJECTIVES: To study the molecular mechanisms of LDH-loaded si-NEAT1 for regulating paclitaxel resistance and tumor-associated macrophage (TAM) polarization in breast cancer. METHODS: qRT-PCR and Western blotting were used to detect the expression of lncRNA NEAT1, miR-133b, and PD-L1 in breast cancer SKBR3 cells and paclitaxel-resistant SKBR3 cells (SKBR3-PR). The effects of transfection with si-NEAT1 and miR-133b mimics on MRP, MCRP and PD-L1 expressions and cell proliferation, migration and apoptosis were investigated using qRT-PCR, Western blotting, scratch and Transwell assays, and flow cytometry. Rescue experiments were conducted using si-NEAT1 and miR-133b inhibitor. Human THP-1 macrophages were cultured in the presence of conditioned media (CM) derived from SKBR3 and SKBR3-PR cells with or with si-NEAT1 transfection for comparison of IL-4-induced macrophage polarization by detecting the surface markers. LDH@si-NEAT1 nanocarriers were constructed, and their effects on MRP, MCRP and PD-L1 expressions and cell behaviors of the tumor cells were examined. THP-1 cells were treated with the CM from LDH@si-NEAT1-treated tumor cells, and the changes in their polarization were assessed. RESULTS: SKBR3-PR cells showered significantly upregulated NEAT1 and PD-L1 expressions and lowered miR-133b expression as compared with their parental cells. Transfection with si-NEAT1 and miR-133b mimics inhibited viability, promoted apoptosis and enhanced MRP and BCRP expressions in SKBR3-PR cells. NEAT1 knockdown obvious upregulated miR-133b and downregulated PD-L1, MRP and BCRP expressions. The CM from SKBR3-PR cells obviously promoted M2 polarization of THP-1 macrophages, which was significantly inhibited by CM from si-NEAT1-transfected cells. Treatment with LDH@si-NEAT1 effectively inhibited migration and invasion, promoted apoptosis, and reduced MRP, BCRP and PD-L1 expressions in the tumor cells. The CM from LDH@si-NEAT1-treated SKBR3-PR cells significantly downregulated Arg-1, CD163, IL-10, and PD-L1 and upregulated miR-133b expression in THP-1 macrophages. CONCLUSIONS LDH@si-NEAT1 reduces paclitaxel resistance of breast cancer cells and inhibits TAM polarization by targeting the miR-133b/PD-L1 axis.
Humans ; MicroRNAs/genetics* ; RNA, Long Noncoding/genetics* ; Paclitaxel/pharmacology* ; Breast Neoplasms/metabolism* ; Drug Resistance, Neoplasm ; B7-H1 Antigen/metabolism* ; Cell Line, Tumor ; Female ; Tumor-Associated Macrophages ; Apoptosis ; Cell Proliferation ; Macrophages ; Cell Movement

Aim To observe the interventional effects of Polygala fallax Hemsl.(PFH)on diabetic kidney disease(DKD)rats and the regulatory mechanism of ferroptosis.Methods Thirty-six SD rats were ran-domly divided into the control group,DKD group,fer-rostatin-1(Fer-1)group,PFH-L group,PFH-M group,and PFH-H group,with six rats in each group.Model-ing was induced by a one-time intraperitoneal injection of 35 mg·kg-1 streptozocin(STZ)in combination with high-sugar and high-fat feed.Ferrostatin-1(25μmol·kg-1)was injected intraperitoneally in Fer-1 group.The PFH-L,PFH-M,and PFH-H groups were gavaged with 50,100 and 200 mg·kg-1 of alcoholic extracts of PFH respectively,and the control and DKD groups were gavaged with an equal volume of distilled water once a day for eight weeks.At the end of drug administration,blood glucose,24h-UP,BUN and Scr levels were measured in each group of rats.HE stai-ning and Masson staining were used to observe renal histopathological changes.ELISA was employed to de-termine the levels of total iron,MDA and GSH activity.IHC was used to observe the expression of Nrf2,SLC7A11,and GPX4 in renal tissues.Western blot was used to detect the protein expression of COL1A1,α-SMA,TGF-,FTH-1,TFR-1,Nrf2,SLC7A1 1,GPX4,in renal tissues.RT-qPCR was used to detect the ex-pression levels of Nrf2,SLC7A11,GPX4 mRNA in re-nal tissues.Results Compared with the control group,blood glucose,24h-UP,BUN,Scr increased(P＜0.05);glomerular volume increased,tubular dilata-tion and collagen fiber deposition were obvious;total i-ron,MDA content increased and GSH activity de-creased(P＜0.05);there was increased protein ex-pression of COL1A1,α-SMA,TGF-β,TFR-1 and de-creased protein expression of FTH-1(P＜0.01);there was decreased mRNA and protein expression of Nrf2,SLC7A11,GPX4 in DKD group rats(P＜0.01).Compared with the DKD group,blood glucose,24h-UP,BUN and Scr decreased(P＜0.05);renal tissue le-sions were significantly reduced;total iron and MDA content decreased,and GSH activity increased(P＜0.05);COL1A1,α-SMA,TGF-β,and TFR-1 protein expression decreased and FTH-1 protein expression in-creased(P＜0.05,P＜0.01);Nrf2,SLC7A11,GPX4 mRNA and protein expression increased in Fer-1 and PFH dose groups(P＜0.05,P＜0.01).Conclusions PFH attenuates renal histopathological injury in DKD rats,and the mechanism may be related to the regula-tion of the Nrf2/SLC7A11/GPX4 signaling pathway.