Diabetic Nephropathy (DN) is the leading cause of end-stage renal disease (ESRD) globally, representing a major global health burden with limited disease-modifying therapies. Podocyte injury serves as the core pathological hallmark of DN, and conventional treatments targeting metabolic disorders or hemodynamic abnormalities fail to reverse the progressive decline of renal function. Accumulating evidence over the past decade has established that high glucose-induced podocyte pyroptosis—a pro-inflammatory form of programmed cell death—is a key driving force in DN progression. Its core molecular mechanism hinges on the activation of the TXNIP-NLRP3 inflammasome axis. Under sustained hyperglycemic conditions, excessive reactive oxygen species (ROS) are generated via pathways including the polyol pathway, advanced glycation end products (AGEs) accumulation, and mitochondrial dysfunction. Concurrently, methylglyoxal (a glucose metabolite) mediates post-translational modification of thioredoxin-interacting protein (TXNIP). These events collectively trigger the dissociation of TXNIP from thioredoxin (TRX), a redox-regulating protein. The free TXNIP then translocates to the mitochondria, where it binds to The NACHT, LRR, and PYD domain-containing protein 3 (NLRP3) and promotes inflammasome assembly. This assembly activates cysteine-aspartic acid protease 1 (caspase-1), which cleaves Gasdermin D (GSDMD) to generate its N-terminal fragment (GSDMD-NT). GSDMD-NT oligomerizes to form membrane pores, leading to podocyte swelling, rupture, and the release of pro-inflammatory cytokines interleukin-1β (IL-1β) and interleukin-18 (IL-18). These cytokines amplify local inflammatory responses, induce mesangial cell proliferation, and accelerate extracellular matrix deposition, ultimately exacerbating glomerulosclerosis. MCC950, a highly selective NLRP3 inhibitor, exerts its therapeutic effects through a multi-layered mechanism: it binds to the NACHT domain (NAIP, CIITA, HET-E and TP1 domain) of NLRP3 with nanomolar affinity, forming hydrogen bonds with key residues (Lys-42 and Asp-166) within the ATP-hydrolysis pocket to block ATP hydrolysis, thereby locking NLRP3 in an inactive conformational state. Additionally, MCC950 interferes with the protein-protein interaction between TXNIP and NLRP3 and regulates mitochondrial homeostasis to reduce ROS production. Preclinical studies have demonstrated that MCC950 dose-dependently reduces proteinuria, restores the expression of podocyte-specific markers (nephrin and Wilms tumor 1 protein, WT1), and alleviates podocyte foot process fusion and glomerulosclerosis in both streptozotocin (STZ)-induced type 1 diabetic models (characterized by absolute insulin deficiency) and db/db type 2 diabetic models (driven by insulin resistance). However, discrepancies in therapeutic outcomes exist across different models—some studies report exacerbated renal inflammation and fibrosis in STZ-induced models—which may stem from differences in disease pathogenesis, intervention timing (early vs. mid-stage disease), and dosing duration. Despite its promising preclinical efficacy, MCC950 faces significant translational challenges, including low oral bioavailability, insufficient podocyte targeting, potential hepatotoxicity, and drug-drug interactions with statins (commonly prescribed to diabetic patients for cardiovascular risk management). Furthermore, off-target effects such as the inhibition of carbonic anhydrase 2 have been identified, raising concerns about its safety profile. Nevertheless, its unique mechanism of action—directly blocking podocyte pyroptosis by targeting the TXNIP-NLRP3 axis—endows it with substantial translational value. In the future, strategies to overcome these barriers are expected to advance its clinical application: targeted delivery via nanocarriers (e.g., PLGA-PEG nanoparticles or nephrin antibody-conjugated systems) to enhance renal accumulation and podocyte specificity; precise patient stratification based on biomarkers such as serum IL-18 and renal TXNIP/NLRP3 expression to identify “inflammatory-phenotype” DN patients most likely to benefit; and combination therapy with sodium-glucose cotransporter 2 (SGLT2) inhibitors—whose metabolic benefits synergize with MCC950’s anti-inflammatory effects. These approaches hold great potential to break through clinical translation bottlenecks, offering a novel, precise anti-inflammatory treatment option for DN and addressing an unmet clinical need for therapies targeting the inflammatory underpinnings of the disease.

Diabetic Nephropathy (DN) is the leading cause of end-stage renal disease (ESRD) globally, representing a major global health burden with limited disease-modifying therapies. Podocyte injury serves as the core pathological hallmark of DN, and conventional treatments targeting metabolic disorders or hemodynamic abnormalities fail to reverse the progressive decline of renal function. Accumulating evidence over the past decade has established that high glucose-induced podocyte pyroptosis—a pro-inflammatory form of programmed cell death—is a key driving force in DN progression. Its core molecular mechanism hinges on the activation of the TXNIP-NLRP3 inflammasome axis. Under sustained hyperglycemic conditions, excessive reactive oxygen species (ROS) are generated via pathways including the polyol pathway, advanced glycation end products (AGEs) accumulation, and mitochondrial dysfunction. Concurrently, methylglyoxal (a glucose metabolite) mediates post-translational modification of thioredoxin-interacting protein (TXNIP). These events collectively trigger the dissociation of TXNIP from thioredoxin (TRX), a redox-regulating protein. The free TXNIP then translocates to the mitochondria, where it binds to The NACHT, LRR, and PYD domain-containing protein 3 (NLRP3) and promotes inflammasome assembly. This assembly activates cysteine-aspartic acid protease 1 (caspase-1), which cleaves Gasdermin D (GSDMD) to generate its N-terminal fragment (GSDMD-NT). GSDMD-NT oligomerizes to form membrane pores, leading to podocyte swelling, rupture, and the release of pro-inflammatory cytokines interleukin-1β (IL-1β) and interleukin-18 (IL-18). These cytokines amplify local inflammatory responses, induce mesangial cell proliferation, and accelerate extracellular matrix deposition, ultimately exacerbating glomerulosclerosis. MCC950, a highly selective NLRP3 inhibitor, exerts its therapeutic effects through a multi-layered mechanism: it binds to the NACHT domain (NAIP, CIITA, HET-E and TP1 domain) of NLRP3 with nanomolar affinity, forming hydrogen bonds with key residues (Lys-42 and Asp-166) within the ATP-hydrolysis pocket to block ATP hydrolysis, thereby locking NLRP3 in an inactive conformational state. Additionally, MCC950 interferes with the protein-protein interaction between TXNIP and NLRP3 and regulates mitochondrial homeostasis to reduce ROS production. Preclinical studies have demonstrated that MCC950 dose-dependently reduces proteinuria, restores the expression of podocyte-specific markers (nephrin and Wilms tumor 1 protein, WT1), and alleviates podocyte foot process fusion and glomerulosclerosis in both streptozotocin (STZ)-induced type 1 diabetic models (characterized by absolute insulin deficiency) and db/db type 2 diabetic models (driven by insulin resistance). However, discrepancies in therapeutic outcomes exist across different models—some studies report exacerbated renal inflammation and fibrosis in STZ-induced models—which may stem from differences in disease pathogenesis, intervention timing (early vs. mid-stage disease), and dosing duration. Despite its promising preclinical efficacy, MCC950 faces significant translational challenges, including low oral bioavailability, insufficient podocyte targeting, potential hepatotoxicity, and drug-drug interactions with statins (commonly prescribed to diabetic patients for cardiovascular risk management). Furthermore, off-target effects such as the inhibition of carbonic anhydrase 2 have been identified, raising concerns about its safety profile. Nevertheless, its unique mechanism of action—directly blocking podocyte pyroptosis by targeting the TXNIP-NLRP3 axis—endows it with substantial translational value. In the future, strategies to overcome these barriers are expected to advance its clinical application: targeted delivery via nanocarriers (e.g., PLGA-PEG nanoparticles or nephrin antibody-conjugated systems) to enhance renal accumulation and podocyte specificity; precise patient stratification based on biomarkers such as serum IL-18 and renal TXNIP/NLRP3 expression to identify “inflammatory-phenotype” DN patients most likely to benefit; and combination therapy with sodium-glucose cotransporter 2 (SGLT2) inhibitors—whose metabolic benefits synergize with MCC950’s anti-inflammatory effects. These approaches hold great potential to break through clinical translation bottlenecks, offering a novel, precise anti-inflammatory treatment option for DN and addressing an unmet clinical need for therapies targeting the inflammatory underpinnings of the disease.

Objective: Patients with severe symptomatic aortic stenosis are assessed for coronary artery disease (CAD) prior to transcatheter aortic valve implantation (TAVI) with treatment implications. Invasive coronary angiography (ICA) is the recommended modality but is associated with peri-procedural complications. Integrating machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) into existing TAVI-planning CT protocol may aid exclusion of significant CAD and thus avoiding ICA in selected patients. Materials and Methods: A single-center, retrospective study was conducted, 41 TAVI candidates with both TAVI-planning CT and ICA performed were analyzed. CT datasets were evaluated by a ML-based CT-FFR software. Beta-blocker and nitroglycerin were not administered in these patients. The primary outcome was to identify significant CAD. The diagnostic performance of CT-FFR was compared against ICA. Results: On per-patient level, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy were 89%, 94%, 80%, 97% and 93%, respectively. On per-vessel level, the sensitivity, specificity, PPV, NPV and diagnostic accuracy were 75%, 94%, 67%, 96% and 92%, respectively. The area under the receiver operative characteristics curve per individual coronary vessels yielded overall 0.90 (95% confidence interval 85%–95%). ICA may be avoided in up to 80% of patients if CT-FFR results were negative. Conclusion ML-based CT-FFR can provide accurate screening capabilities for significant CAD thus avoiding ICA. Its integration to existing TAVI-planning CT is feasible with the potential of improving the safety and efficiency of pre-TAVI CAD assessment.

Objectives: . Endotype-based interventions have shown promise in the treatment of patients with obstructive sleep apnea, and upper airway surgery is a key therapeutic option. However, responses to surgery vary among patients with obstructive sleep apnea. This study aims to examine changes in endotypic traits following upper airway surgery and to explore their association with surgical outcomes. Methods: . We prospectively recruited 25 patients with obstructive sleep apnea who visited a single sleep center for upper airway surgery. These patients underwent polysomnographic studies both before and after surgical intervention. During non-rapid eye movement and rapid eye movement sleep, we estimated endotypic traits—including collapsibility (Vpassive), arousal threshold, loop gain, and upper airway compensation—with the phenotyping using polysomnography method. Based on improvements in the apnea-hypopnea index, patients were classified as either responders or non-responders. We compared the preoperative endotypic traits between these groups using Mann-Whitney tests. Additionally, we compared changes in endotypic traits pre- and post-surgery between responders and non-responders using generalized linear mixed models. Results: . We identified 12 responders and 13 non-responders. Compared to non-responders, responders exhibited improved collapsibility during rapid eye movement sleep (22.3 vs. −8.2%eupnea in Vpassive, P=0.01), and their arousal threshold decreased during non-rapid eye movement sleep (−22.4%eupnea, P=0.02). No endotypic trait predicted surgical response; however, the apnea-hypopnea index during rapid eye movement sleep was higher among responders than non-responders (51.8/hr vs. 34.4/hr, P=0.05). Conclusion . Upper airway surgery significantly reduced collapsibility during rapid eye movement sleep in responders. The target pathology for upper airway surgery is a compromised upper airway during rapid eye movement sleep.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

BACKGROUND:The plantarflexor weakness is a common muscle defect in patients with spastic cerebral palsy and Charcot-Marie-Tooth,which clinically manifests abnormal gaits,and the relationship between plantarflexor weakness and abnormal gaits is unclear. OBJECTIVE:To explore the biomechanical behavior of the lower limb under the action of a single factor of plantarflexor weakness to reveal the mechanism of abnormal gait induced by plantarflexor weakness and to provide guidance for the rehabilitation training of patients with plantarflexor weakness. METHODS:A predictive framework of musculoskeletal multibody dynamics in the sagittal plane was established based on OpenSim Moco to predict lower limb joint angles and muscle activation changes during walking in normal subjects.The validity of the framework was verified by combining the inverse kinematics and electromyogram activation time of the experimental data.Reduced isometric muscle forces were used to model plantarflexor weakness and to compare predicted lower extremity joint angles,joint moments,and muscle energy expenditure with normal subjects to analyze the effects of plantarflexor weakness on lower extremity biomechanics. RESULTS AND CONCLUSION:(1)The Moco-based prediction framework realistically predicted the biomechanical changes of the lower limbs during walking in normal subjects(joint angles:normalized correlation coefficient≥0.73,root mean square error≤7.10°).(2)The musculoskeletal model used a small stride support phase to increase the"heel-walking"gait during plantarflexor weakness.When the plantarflexor weakness reached 80%,the muscle energy expenditure was 5.691 4 J/kg/m,and the maximum activation levels of the gastrocnemius and soleus muscles were 0.72 and 0.53,which might cause the plantarflexor weakness patients to be more prone to fatigue when walking.(3)Muscle energy expenditure was significantly higher when the weakness of plantarflexors exceeded 40%,and the joint angles and moments of the lower limbs deteriorated significantly when the weakness of plantarflexors exceeded 60%,suggesting that there may be a"threshold"for the effect of plantarflexor weakness on gait,which may correspond to the point at which health care professionals should intervene in the clinical setting.

Episodic memory, our ability to recall past experiences, is supported by structures in the medial temporal lobe (MTL) particularly the hippocampus, and its interactions with fronto-parietal brain regions. Understanding how these brain regions coordinate to encode, consolidate, and retrieve episodic memories remains a fundamental question in cognitive neuroscience. Non-invasive brain stimulation (NIBS) methods, especially transcranial magnetic stimulation (TMS), have advanced episodic memory research beyond traditional lesion studies and neuroimaging by enabling causal investigations through targeted magnetic stimulation to specific brain regions. This review begins by delineating the evolving understanding of episodic memory from both psychological and neurobiological perspectives and discusses the brain networks supporting episodic memory processes. Then, we review studies that employed TMS to modulate episodic memory, with the aim of identifying potential cortical regions that could be used as stimulation sites to modulate episodic memory networks. We conclude with the implications and prospects of using NIBS to understand episodic memory mechanisms.
Humans ; Memory, Episodic ; Transcranial Magnetic Stimulation/methods* ; Brain/physiology* ; Nerve Net/physiology* ; Mental Recall/physiology* ; Neural Pathways/physiology*

OBJECTIVES: To develop and validate a preoperative clinical-radiomics model for predicting overall survival (OS) and disease-free survival (DFS) in patients with extrahepatic cholangiocarcinoma (eCCA) undergoing radical resection. METHODS: In this retrospective study, consecutive patients with pathologically-confirmed eCCA who underwent radical resection at our institution from 2015 to 2022 were included. The patients were divided into a training cohort and a validation cohort according to the chronological order of their CT examinations. Least absolute shrinkage and selection operator (LASSO)-Cox regression was employed to select predictive radiomic features and clinical variables. The selected features and variables were incorporated into a Cox regression model. Model performance for 1-year OS and DFS prediction was assessed using calibration curves, area under receiver operating characteristic curve (AUC), and concordance index (C-index). RESULTS: This study included 123 patients (mean age 64.0 ± 8.4 years, 85 males/38 females), with 86 in the training cohort and 37 in the validation cohort. The OS-predicting model included four clinical variables and four radiomic features. It achieved a training cohort AUC of 0.858 (C-index = 0.800) and a validation cohort AUC of 0.649 (C-index = 0.605). The DFS-predicting model included four clinical variables and four other radiomic features. It achieved a training cohort AUC of 0.830 (C-index = 0.760) and a validation cohort AUC of 0.717 (C-index = 0.616). CONCLUSIONS The preoperative clinical-radiomics models show promise as a tool for predicting 1-year OS and DFS in eCCA patients after radical surgery.
Humans ; Male ; Female ; Retrospective Studies ; Middle Aged ; Cholangiocarcinoma/mortality* ; Prognosis ; Bile Duct Neoplasms/mortality* ; Tomography, X-Ray Computed/methods* ; Aged ; Radiomics

Objective:To develop and validate a deep learning-based multimodal model integrating clinical and radiomic features for predicting acute kidney injury（AKI）risk after partial nephrectomy.Methods:A retrospective analysis was conducted on 416 patients who underwent partial nephrectomy at Zhongshan Hospital，Fudan University from January 2023 to January 2025. The cohort included 100 AKI patients［defined by a ≥ 25% reduction in postoperative evaluated glomerular filtration rate（eGFR）within 48 hours sustained for >24 hours］and 316 non-AKI patients（1∶3 ratio，randomly matched with 16 additional cases for redundancy）. Clinical and radiomic features were extracted from preoperative contrast-enhanced CT scans using PyRadiomics. Demographics included 259 males and 158 females，with a median age of 57（49，65）years，body mass index of（24.1 ± 3.3）kg/m2，preoperative eGFR of（88.5 ± 18.3）ml/（min·1.73 m2），postoperative eGFR（48-hour）of（76.0 ± 21.9）ml/（min·1.73 m2），Zhongshan Score（ZSscore）of 7.34 ± 2.01，and R.E.N.A.L. score of 7.50 ± 1.71. All tumors were T 1a stage. Patients were divided into training（n = 312）and test（n = 104）sets（3∶1 ratio）. A clinical model was constructed via multivariate logistic regression，while radiomic and combined（clinical + radiomic）models utilized an artificial neural network（ANN）with 1 input layer，5 hidden layers，1 output layer，and 10 5 training epochs. Model performance was evaluated by using receiver operating characteristic（ROC）curves and area under the curve（AUC），and was compared to the Martini model. Feature contributions were interpreted via SHapley Additive exPlanations（SHAP）. Results:In the test set，the results of multivariate logistic regression showed that patient’s weight，preoperative eGFR，R.E.N.A.L. score，surgical approach，and operation time were risk factors for AKI（ P < 0.05）. The AUC of the clinical feature prediction model constructed based on the above factors was 0.852（95% CI 0.775?0.929）. In the test set，the AUC of the Martini model was 0.725（95% CI 0.565?0.791）. The radiomic model，trained on 1 315 imaging features，achieved an AUC of 0.898（95% CI 0.804?0.993）with 94.2%（98/104）accuracy. The combined clinical and radiomic model，integrating 1 315 radiomic features and clinical features，demonstrated superior performance with an AUC of 0.946（95% CI 0.887?1.000）and 96.2%（100/104）accuracy，outperforming both the clinical model（ P = 0.03）and the Martini model（ P < 0.01）. SHAP analysis identified the top five predictors in the combined model：ZSscore（SHAP value：0.78），long-run low gray-level emphasis（SHAP value：0.61），run-length non-uniformity（SHAP value：0.58），size-zone non-uniformity（SHAP value：0.46），and gray-level co-occurrence matrix joint energy（SHAP value：0.36）. Conclusions:The deep learning-based multimodal model integrating clinical and radiomic features accurately predicts AKI risk after partial nephrectomy，offering a novel strategy for preoperative risk stratification and personalized intervention.