ObjectiveTo evaluate the anti-inflammatory activity of the novel magnolol ester derivative YW and to investigate its effects on chondrocyte senescence and preliminary mechanisms. MethodsMagnolol and p-methylbenzoic acid were used as raw materials to synthesize the magnolol ester derivative YW （Molecular Formula： C₂₆H₂₄O₃， Molecular Weight： 384.17， HPLC Purity >96%） via DCC/DMAP-catalyzed esterification. Cytotoxicity was assessed using the CCK-8 assay. A lipopolysaccharide （LPS）-induced RAW264.7 macrophage activation model and an interleukin-1β （IL-1β）-induced rat primary chondrocyte model were established. The release and mRNA expression of inflammatory factors including nitric oxide （NO）， IL-1β， tumor necrosis factor-alpha （TNF-α）， and IL-6 were detected by enzyme-linked immunosorbent assay （ELISA）， Griess reagent method， and quantitative real-time PCR （RT-qPCR）. The expression of senescence markers such as inducible nitric oxide synthase （iNOS）， pro-interleukin-1β （pro-IL-1β）， lysine acetyltransferase 7 （KAT7）， cyclin-dependent kinase inhibitor 1A （p21）， and cyclin-dependent kinase inhibitor 2A （p16）， as well as proteins related to chondrocyte extracellular matrix synthesis and catabolism， were analyzed by Western blot （WB）. Molecular docking was performed using Discovery Studio 2019 to validate target binding. ResultsYW exhibited no significant cytotoxicity at concentrations ≤20 μmol/L. YW concentration-dependently inhibited LPS-induced macrophage inflammatory cytokine release， significantly downregulated iNOS， Pro-IL-1β protein， and inflammatory cytokine mRNA expression （P<0.01）. YW stably bound to KAT7 protein （binding energy： -94.2 kcal/mol）； YW downregulated KAT7 and aging marker protein expression in naturally aged and IL-1β-induced chondrocyte models （P<0.01）； YW regulated chondrocyte matrix synthesis and catabolic protein expression in IL-1β-induced chondrocytes （P<0.01）. ConclusionYW inhibits macrophage activation and inflammatory cytokine release while downregulating KAT7 and senescence marker protein expression in chondrocytes， thereby blocking chondrocyte senescence.

ObjectiveTo investigate the association between endothelin receptor type A gene （EDNRA） and congenital bilateral absence of the vas deferens （CBAVD）. MethodsThis case-control study consisted of 124 subjects with CBAVD and 100 fertile controls.Two single nucleotide polymorphisms （SNPs： rs5335 and rs1801708） in the EDNRA gene were genotyped via PCR， PCR-RFLP analysis， and direct sequencing. ResultsNo significant differences existed between EDNRA polymorphisms and CBAVD phenotype （rs1801708： P=0.220 2， 0.163 2； rs5335： P=0.805 8， 0.818 6）. However， the rs1801708-rs5335 haplotype AG was notably associated with an increased risk of CBAVD （P=0.008 6， OR=2.178， 95% CI： 1.207-3.929）. A significantly protective effect of rs1801708-rs5335 haplotype GG on CBAVD （P=0.038 5， OR= 0.671， 95% CI： 0.460-0.980） was observed. After Bonferroni correction， the result for haplotype A-G remained significant （P =0.008 6<0.012 5）， while haplotype G-G was not significant. ConclusionThe rs1801708-rs5335 AG haplotype of EDNRA is a potential risk factor for CBAVD development in Han Chinese.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

To address the growing challenge of an increasing number of elderly lung cancer patients amidst China's aging population and to fill the gap in quality control standards for surgical treatment in this special population, this study aimed to develop a standardized surgical evaluation system for elderly lung cancer patients tailored to China's national conditions. The system was established through a literature review, integrated the pathophysiological characteristics of elderly patients, and was constructed following review, feedback, and revision by experts from multiple thoracic surgery centers. Employing a 100-point scoring system, it comprises three primary domains: physical infrastructure and geriatric adaptability foundational conditions (10 points); management level and perioperative care models (20 points); and technical proficiency and clinical outcomes (70 points). The system places a strong emphasis on geriatric adaptability, proposing specific, quantifiable indicators for age-friendly facility modifications, control of elderly-specific complications, multidisciplinary collaboration, and standardized perioperative management. It provides a convenient and measurable assessment tool for quality control in the surgical treatment of elderly lung cancer in China, which is expected to promote the standardization and homogenization of diagnosis and treatment.

This study aimed to investigate the mechanism of liquiritin (LQ) in the improvement of ventricular remodeling (VR) after acute myocardial infarction (AMI). Molecular docking was used to predict the binding affinity of liquiritin to thioredoxin-interacting protein (TXNIP). After 2 weeks of modeling, the rats were randomly divided into a model group, a low-dose liquiritin group (20 mg/kg LQ), and a high-dose liquiritin group (40 mg/kg LQ). Liquiritin was administered by gavage once a day, and the sham group and model group were given the same volume of 0.5% sodium carboxymethylcellulose (CMC-Na), with intervention of 4 consecutive weeks. Echocardiography was employed to detect the cardiac function, HE staining was used to observe cardiological changes, ELISA was used to detect the activity of serum creatine kinase-MB (CK-MB) activity, and the colorimetric method was adopted to detect serum malondialdehyde (MDA), total superoxide dismutase (T-SOD) and catalase (CAT) activities. RT-qPCR was used to detect the gene expressions of TXNIP, thioredoxin (TRX) and NACHT, LRR, and PYD domains-containing protein 3(NLRP3). Western blot was used to detect the protein expressions of TXNIP, TRX and NLRP3 in rat myocardial tissue. Molecular docking results showed that liquiritin had a good binding affinity to TNXIP target. After 20 and 40 mg/kg liquiritin intervention, the levels of ejection fraction (EF) and fractional shortening (FS) were significantly increased (P<0.01), and the levels of LVIDs, LVIDd, LVESV, and LVEDV were decreased (P<0.01). The myocardial structure was significantly improved, the cell arrangement tended to be regular, and the area of inflammatory cell infiltration and necrosis was reduced. Liquiritin significantly reduced the level of CK-MB (P<0.01), decreased the activity of MDA, and increased the activities of CAT and T-SOD (P<0.01). Liquiritin effectively inhibited the overexpression of TXNIP and NLRP3 genes and proteins, and enhanced the expression of TRX genes and proteins in the myocardial tissues of AMI rats. In conclusion, liquiritin has a regulatory effect on the TXNIP/TRX signaling pathway, inhibits the activation of the NLRP3 inflammasome, and thus improves ventricular remodeling after acute myocardial infarction.

Short-chain fatty acids （SCFA） are the main metabolic products generated by the fermentation of dietary fiber by gut microbiota. Studies have shown that SCFA not only play a role in energy metabolism， but also act as important signaling molecules， exhibiting a significant potential in alleviating liver and pancreatic fibrosis. The core mechanism of SCFA mainly involves the regulation of various key signaling pathways by activating G protein-coupled receptors and inhibiting the activity of histone deacetylase， thereby suppressing the activation and proliferation of hepatic stellate cell （HSC） and pancreatic stellate cell （PSC）， which is a key link in fibrosis formation. In addition， SCFA can effectively alleviate tissue inflammation response， improve intestinal barrier function， and regulate gut microbiota balance， thus indirectly preventing the process of fibrosis mediated by the “gut-liver/pancreas axis”. Compared with the research on SCFA in liver fibrosis， studies on their role in pancreatic fibrosis are limited. Given that HSC and PSC are highly homologous， the transcription factors and proteins that have been confirmed in liver fibrosis-related studies are also similarly expressed in PSC， suggesting that they may also influence the activation of PSC. This article systematically summarizes the recent advances in the research on SCFA in alleviating liver and pancreatic fibrosis， in order to provide new perspectives for exploring the mechanism of pancreatic fibrosis and developing related interventional strategies.

ObjectiveTo investigate the lower limb muscle synergy patterns during jumping in patients after anterior cruciate ligament reconstruction (ACLR). MethodsFrom March to November, 2022, 23 patients after ACLR were enrolled as observation group, and 24 healthy ones matched in height, body mass and exercise level were recruited as control group at Wuhan Sports University. Surface electromyography (sEMG) data of lower limb muscles were collected during a single-leg vertical jump task. Non-negative matrix factorization was applied for synergy analysis. The number of synergies, variance accounted for, synergy structure (muscle weight) and activation coefficient were extracted. ResultsThree types of muscle synergy patterns were identified on the affected side and contralateral side of the observation group, and the control group. For Synergy 1, the weight of biceps femoris was higher on both the affected and contralateral sides than in the control group (P < 0.01); the weight of semitendinosus was higher on the affected side than on the contralateral side (P < 0.05). For Synergy 2, the weight of lateral gastrocnemius and soleus were higher on both sides of the observation group than in the control group (P < 0.05). For Synergy 3, the weight of gluteus maximus was lower on the affected side than on the contralateral side and in the control group (P < 0.05); the weight of tibialis anterior was higher on the affected side than on the contralateral side and in the control group (P < 0.001); the weight of vastus lateralis was lower on the contralateral side than on the affected side and in the control group (P < 0.001). In the observation group, the peak activation time and stop time of Synergy 3 were delayed bilaterally (P < 0.05). ConclusionPatients after ACLR exhibit altered structural and temporal characteristics of lower limb muscle synergy during jump task. The hamstrings show increased participation during the pre-activation phase, and calf muscles undertake more stabilizing functions during the landing phase.

Hemoglobin (Hb) concentration is a key clinical biomarker for diagnosing and managing anemia, ischemic stroke, perioperative blood loss, and chronic diseases such as renal failure. Traditional venous blood sampling remains the gold standard due to its high accuracy, but its invasive nature limits frequent testing, real time monitoring, and large scale screening. This has driven growing interest in non-invasive Hb detection technologies over the past decade. Among these, optical methods are the most promising because of their safety, potential for continuous monitoring, and compatibility with portable or wearable devices. This paper systematically reviews major advances in optical non invasive Hb detection from the last ten years. We focus on near-infrared spectroscopy branches—photoplethysmography (PPG) and dynamic spectrum (DS)—and also cover color analysis/RGB imaging, Raman spectroscopy, and photoacoustic spectroscopy. For each technology, we explain its detection principles, analyze advantages and limitations, and summarize optimization strategies reported in recent literature. PPG, based on pulsatile blood volume changes, underpins many commercial continuous monitors. However, its accuracy is constrained by motion artifacts, individual physiological variations (e.g., skin tone, tissue thickness), and low AC signal to noise ratio. In contrast, DS—an advanced derivative of PPG—uses a differential principle to extract absorbance changes between systolic and diastolic peaks. This theoretically eliminates interference from static tissues (skin, bone, venous blood) and common mode noise (e.g., ambient light), positioning DS as a more robust framework for high precision Hb quantification. Beyond spectral methods, color analysis/RGB imaging offers a hardware minimalist approach. By analyzing images of vascular rich, thin tissues (e.g., conjunctiva, nail beds, palms), it enables Hb estimation using smartphone cameras. Recent advances have shifted from manual RGB feature extraction to deep learning models and spectral super resolution that reconstruct hyperspectral data from RGB inputs, significantly improving screening accuracy. Our academic perspective emphasizes critical and integrative analysis. We highlight persistent challenges that hinder clinical translation: profound individual biological variability (skin optics, microvascular architecture), sensitivity to measurement conditions (pressure, ambient light), and a lack of standardized validation protocols and multi center trials. A central thesis is that no single optical method is universally superior; each involves trade offs between accuracy, complexity, cost, and practicality. Looking forward, we posit that the next performance leap will come from multimodal information fusion—combining PPG, electrocardiogram (ECG), bioimpedance, or different optical modalities to compensate for individual differences and environmental noise. AI and deep learning are essential not only for image analysis but also for automated, end to end feature extraction from complex waveforms like PPG sequences. Advancing hardware (tunable lasers, quantum dot LEDs, novel sensor designs) is crucial to improve signal fidelity and portability. Finally, we advocate for clinical scenario specific optimization and rigorous standardized evaluation frameworks to gain regulatory approval (e.g., FDA, NMPA) and achieve widespread clinical acceptance. In conclusion, this review synthesizes a decade of progress. Optical non-invasive Hb detection has evolved from proof of concept studies to emerging products and validated screening tools, but the journey toward reliable, clinic ready quantitative devices continues. The convergence of smarter algorithms, fused sensing modalities, and focused clinical validation offers the most promising path to transform this potential into routine medical practice, ultimately enabling personalized, continuous, and accessible hematological management.

Objective To explore the echocardiographic features of critically ill patients with infection, and to evaluate the predictive value of echocardiographic parameters for 28-day mortality and myocardial injury. Methods Using a single-center prospective cohort design, 120 critically ill patients with infection admitted to the Intensive Care Unit, Jinshan Hospital of Fudan University from January 2024 to January 2025 were enrolled consecutively. According to the severity of infection, patients were divided into the sepsis group (n＝75) and the non-sepsis group (n＝45). Cox proportional hazards models and modified Poisson regression were used to analyze risk factors of 28-day all-cause mortality and myocardial injury. Kaplan-Meier survival curve and log-rank test were used to assess prognosis differences among patients with different ultrasound parameters. ROC curve and area under the curve (AUC) were applied to evaluate the predictive performance of ultrasound parameters, and restricted cubic spline (RCS) model was used to explore nonlinear relationships. Results The E/e′ ratio was significantly higher in the sepsis group than in the non-sepsis group (P＜0.001), while left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS) were lower in the sepsis group (P＜0.05). The Cox proportional hazards model found no association between ultrasound parameters and 28-day all-cause mortality. Modified Poisson regression showed that, after adjusting for confounding factors, elevated E/e′ was an independent risk factor of myocardial injury (RR＝1.12, 95% CI 1.07–1.17, P＜0.001). Survival analysis demonstrated that patients with E/e′ ＞10.9 had lower 28-day survival rates (P＝0.02), and the AUC for E/e′ predicting myocardial injury was 0.835. RCS analysis suggested a nonlinear relationship between E/e′ and myocardial injury risk (P＜0.001). Conclusions E/e′, LVEF, and LVFS have no significant predictive value for 28-day mortality risk in critically ill patients with infections. Elevated E/e′ is an independent risk factor of myocardial injury in such patients, with a nonlinear relationship.

OBJECTIVE To investigate the prevalence and influencing factors of potentially inappropriate medication （PIM） among the elderly in nursing homes in Urumqi based on three PIM screening tools， and to compare the applicability of different tools. METHODS A cross-sectional study design was adopted. Elderly individuals from six nursing homes in Urumqi were selected as the research subjects from May 2021 to September 2023. Demographic characteristics， disease burden and medication records of the elderly were collected. PIM screening was performed using the Chinese PIM criteria （2024 edition）， the American Geriatrics Society （AGS） Beers criteria （2023 edition）， and the Screening Tool of Older Person’S Prescriptions（STOPP）/Screening Tool to Alert to Right Treatment（START） （2023 edition）. Fleiss’s Kappa test was used to assess the consistency among the three screening tools， and multivariate Logistic regression was used to analyze the influencing factors of PIM. RESULTS The prevalence of PIM screened by the Chinese PIM criteria was 47.4% （323/682）， by the AGS Beers criteria was 43.4% （296/682）， and by the STOPP criteria was 50.9% （347/682）. The consistency among the three screening tools was low （Fleiss’s Kappa＝0.12， P ＜0.001）. Multivariate Logistic regression analysis showed that all three screening tools indicated that polypharmacy， aspirin use and psychotropic drug use were independent risk factors for PIM among elderly in nursing houses （all OR＞1， P ＜0.05）. CONCLUSIONS The prevalence of PIM among the elderly in nursing homes in Urumqi is relatively high. Polypharmacy， aspirin use and psychotropic drug use are common independent risk factors for PIM. There are differences in screening results among the three tools with low consistency. The Chinese PIM criteria can serve as a first-line tool for PIM screening in nursing homes.