Metabolic associated fatty liver disease (MAFLD) is fundamentally driven by an imbalance in hepatic fatty-acid flux: the influx of fatty acids exceeds the liver’s capacity for disposal, resulting in excessive hepatic lipid accumulation, predominantly in the form of triglycerides (TGs). The occurrence and progression of MAFLD depend on disordered regulation across multiple metabolic steps, including fatty-acid uptake, de novo lipogenesis (DNL), fatty-acid oxidation (FAO), and very low-density lipoprotein (VLDL) export. Forkhead box protein O1 (FOXO1) is a key transcriptional regulator within the hepatic network coordinating glucose and lipid metabolism. Under metabolic stress and insulin resistance (IR), FOXO1 expression is frequently increased, whereas its inhibitory phosphorylation is reduced. These changes enhance FOXO1 nuclear localization and transcriptional activity, thereby reprogramming the expression of genes related to metabolism in the liver. Because hepatic lipid deposition is the central pathological feature of MAFLD, the functional status of FOXO1 directly influences hepatic lipid homeostasis. Growing evidence suggests that FOXO1 can exert bidirectional, environment-dependent effects on hepatic lipid accumulation; however, the molecular basis for this functional switch remains incompletely understood. This review systematically summarizes the biological functions and regulatory mechanisms of FOXO1 and its roles in hepatic lipid metabolism, with a particular focus on its crosstalk with insulin signaling. FOXO1 expression is shaped by RNA modifications and epigenetic regulation mediated by non-coding RNAs. Its transcriptional output is precisely governed by post-translational modifications—such as phosphorylation and acetylation—as well as by coordinated nucleocytoplasmic shuttling. Notably, these regulatory patterns vary markedly across nutritional states, degrees of insulin resistance, and stages of disease. In the fed state, insulin/IGF-1 signaling activates the PI3K-AKT pathway, promoting the inhibitory phosphorylation of FOXO1 and facilitating additional modifications, including acetylation, methylation, and ubiquitination. Together, these events drive FOXO1 export from the nucleus and dampen its transcriptional activity, suppressing gluconeogenesis and constraining lipogenic programs. Conversely, during fasting or when insulin signaling is weakened, FOXO1 inhibition is relieved. FOXO1 accumulates in the nucleus, binds to DNA, and regulates the transcription of downstream target genes. Mechanistically, FOXO1 can aggravate hepatic lipid accumulation by activating genes involved in TG synthesis while repressing FAO-related pathways, thereby favoring storage over oxidation. However, under specific conditions, FOXO1 may also alleviate the hepatic lipid burden by promoting TG hydrolysis and enhancing VLDL secretion, thereby reducing the net hepatic lipid load. In addition, lipotoxic signals mediated by ceramides and diacylglycerols (Cer/DAG) activate atypical protein kinase C (aPKC), further exacerbating the disruption of the AKT-FOXO1 axis. This vicious cycle ultimately produces a metabolic paradox in which increased hepatic glucose output coexists with persistent, insulin-independent lipogenesis, accelerating MAFLD progression. Importantly, FOXO1 regulation is not uniform: during early metabolic overload, insulin-mediated suppression may remain effective, whereas in advanced insulin resistance, the loss of AKT control permits sustained FOXO1 activity. Such stage-dependent dynamics may help explain why FOXO1 can either promote steatosis or, in certain contexts, support programs that facilitate lipid turnover. Accordingly, interventions should be liver-specific and tuned to the disease stage, aiming to curb maladaptive FOXO1 signaling while preserving its capacity to promote triglyceride hydrolysis and VLDL secretion when advantageous. Overall, this review offers an important perspective on MAFLD pathogenesis, emphasizing FOXO1 as a potential therapeutic target and providing a theoretical basis for developing liver-specific, disease-course-dependent precision interventions.

Osteoarthritis (OA), a highly prevalent degenerative joint disease worldwide, is defined by articular cartilage degradation, abnormal bone remodeling, and persistent chronic inflammation. It severely compromises patients’ quality of life, and currently, there is no radical cure. Abnormal mechanical stress is widely regarded as a core driver of OA pathogenesis, and the exploration of mechanical signal perception and transduction mechanisms has become crucial for deciphering OA’s pathophysiological processes. Piezo1, a key mechanosensitive cation channel belonging to the Piezo protein family, has recently gained significant attention due to its pivotal role in mediating cellular responses to mechanical stimuli in joint tissues. This review systematically examines Piezo1’s expression patterns, regulatory mechanisms, and pathological functions in OA, with a particular focus on its dual roles in modulating chondrocyte homeostasis and bone metabolism disorders, while also delving into the underlying molecular signaling pathways and potential therapeutic implications. Piezo1, consisting of approximately 2 500 amino acids and forming a unique trimeric propeller-like structure, is widely expressed in chondrocytes, osteocytes, mesenchymal stem cells, and synovial cells. It exhibits permeability to cations such as Ca²⁺, K⁺, and Na⁺, and directly responds to membrane tension changes induced by mechanical stimuli like fluid shear stress and mechanical overload. In OA patients and animal models, Piezo1 expression is significantly upregulated, especially in cartilage regions subjected to abnormal mechanical stress (e.g., human temporomandibular joint cartilage). This overexpression is closely associated with aggravated cartilage degeneration, increased chondrocyte apoptosis, accelerated cellular senescence, and intensified inflammatory responses. Mechanical overload and pro-inflammatory cytokines (e.g., IL-1β) are key inducers of Piezo1 upregulation: IL-1β activates the PI3K/AKT/mTOR signaling pathway to enhance Piezo1 expression, forming a pathogenic positive feedback loop that inhibits chondrocyte autophagy, promotes apoptosis, and further accelerates joint degeneration. Mechanistically, Piezo1 mediates OA progression through multiple interconnected pathways. When activated by mechanical stress, Piezo1 triggers excessive Ca²⁺ influx, leading to endoplasmic reticulum stress (ERS) and mitochondrial dysfunction, which directly induce chondrocyte apoptosis. This process involves the activation of downstream signaling cascades such as cGAS-STING and YAP-MMP13/ADAMTS5. YAP, a transcriptional regulator, upregulates the expression of matrix metalloproteinase 13 (MMP13) and aggrecanase (ADAMTS5), thereby accelerating cartilage matrix degradation. Additionally, Piezo1-driven Ca²⁺ overload promotes the accumulation of reactive oxygen species (ROS) and upregulates senescence markers (p16 and p21), accelerating chondrocyte senescence via the p38MAPK and NF-κB pathways. Senescent chondrocytes secrete senescence-associated secretory phenotype (SASP) factors (e.g., IL-6, IL-1β), further amplifying joint inflammation. In terms of bone metabolism, Piezo1 maintains joint homeostasis by promoting the differentiation of fibrocartilage stem cells into chondrocytes and balancing bone formation and resorption through regulating the FoxC1/YAP axis and RANKL/OPG ratio. Therapeutically, targeting Piezo1 shows promising potential. Preclinical studies have demonstrated that Piezo1 inhibitors (e.g., GsMTx4) can reduce joint damage and alleviate pain in OA mice. Simultaneously, siRNA-mediated co-silencing of Piezo1 and TRPV4 (another mechanosensitive channel) decreases intracellular Ca²⁺ concentration, inhibits chondrocyte apoptosis, and promotes cartilage repair. Conditional knockout of Piezo1 using Gdf5-Cre transgenic mice alleviates cartilage degeneration in post-traumatic OA models by downregulating MMP13 and ADAMTS5 expression. Despite existing challenges, such as off-target effects of inhibitors, inefficient local drug delivery, and interindividual genetic variability, strategies like developing selective Piezo1 antagonists, optimizing targeted nanocarriers, and combining Piezo1-targeted therapy with physical therapy provide viable avenues for clinical translation. The authors propose that Piezo1 serves as a critical therapeutic target for OA, and future research should focus on deciphering its context-dependent regulatory networks, developing tissue-specific intervention strategies, and validating their efficacy and safety in clinical trials to address the unmet medical needs of OA patients.

Abnormal synaptic plasticity is an early pathological feature of Alzheimer disease (AD). Synaptic damage and dysfunction initiate neuronal degeneration and death, ultimately leading to cognitive impairment. Traditional Chinese medicine (TCM) can effectively ameliorate cognitive dysfunction through multitarget regulation of synaptic plasticity. This review summarizes the mechanisms by which TCM, including active components, single herbs, and classical formulas, modulates synaptic plasticity, offering new insights for future research and clinical applications. Relevant experimental studies published between 2020 and 2024 were retrieved from major databases, including China National Knowledge Infrastructure, the National Science and Technology Library, Wanfang Data, Elsevier, ScienceDirect, PubMed, SpringerLink, and Web of Science. Network pharmacology and bioinformatics approaches were used to predict the therapeutic effects and mechanisms of TCM on AD-related synaptic plasticity. In total, 15 TCM single herbs and 11 TCM formulas were identified as enhancing AD-related synaptic plasticity. Additionally, 15 active ingredients targeting synaptic plasticity in AD were retrieved from TCM databases over the past decade. This review provides novel perspectives and strategic directions for future AD research and therapeutic development.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Flap transplantation is a critical surgical strategy for the reconstruction of tissue defects caused by trauma, tumor resection, and congenital malformations, and its survival rate directly determines surgical efficacy and patient prognosis. Following transplantation, flaps inevitably undergo ischemia-reperfusion (I/R) injury, during which oxidative stress, inflammatory responses, and metabolic disturbances are intricately intertwined, ultimately leading to cellular injury and tissue necrosis. Recent studies have demonstrated that multiple forms of programmed cell death—including apoptosis, pyroptosis, ferroptosis, necroptosis, and PANoptosis—play central roles in flap I/R injury. The extensive crosstalk and molecular interactions among these pathways form a highly complex cell death network. Specifically, apoptosis is mediated by the imbalance of Bcl-2 family proteins and the activation of cysteine-dependent aspartate-specific protease (caspase) cascades; pyroptosis is driven by the NLRP3-caspase-1-GSDMD axis, resulting in membrane pore formation and the release of pro-inflammatory cytokines; ferroptosis is characterized by iron-dependent lipid peroxidation and dysfunction of glutathione peroxidase 4 (GPX4); necroptosis is triggered by the receptor-interacting serine/threonine-protein kinase 1 (RIPK1)-RIPK3-MLKL signaling complex, leading to membrane rupture; and PANoptosis represents an integrated form of inflammatory cell death that coordinates multiple death pathways. Importantly, these forms of programmed cell death are not independent but are interconnected through extensive signaling crosstalk. Key regulatory molecules, including caspase-8, reactive oxygen species (ROS), nuclear factor-κB (NF-κB), and nuclear factor erythroid 2-related factor 2 (Nrf2), collectively modulate the dynamic balance among these pathways. Therefore, the multidimensional interplay and spatiotemporal dynamics of programmed cell death constitute a fundamental pathological basis of flap I/R injury. This review systematically summarizes the latest advances in the mechanisms and interactions of various programmed cell death pathways in flap I/R injury, aiming to elucidate the underlying regulatory network. These insights may provide novel theoretical foundations for optimizing flap protection strategies, improving flap survival, and promoting tissue repair.

Objective: This study aimed to evaluate the prognostic value of [ 18F]ALF-NOTA-FAPI-04 PET/CT-derived parameters, including the maximum standardized uptake value (SUVmax), FAPI-avid tumor volume (FTV), and total lesion FAP expression (TLF), in patients with recurrent gastric cancer undergoing combined chemoimmunotherapy. We sought to establish a noninvasive imaging biomarker framework to optimize patient stratification and therapeutic decision-making. Materials and Methods: This retrospective cohort study analyzed 51 patients with recurrent gastric cancer who received programmed cell death protein 1 (PD-1) inhibitors combined with chemotherapy after gastrectomy. All patients underwent [ 18F]ALF-NOTA-FAPI-04 PET/CT within 14 days of chemoimmunotherapy. Semi-quantitative parameters (SUVmax, FTV, and TLF) were derived using semi-automated tumor segmentation. The primary endpoint of this study was the assessment of the clinical efficacy of chemoimmunotherapy, categorized as a durable or nondurable clinical benefit. The secondary endpoints included progression-free survival (PFS) and overall survival (OS). In a subgroup of 16 patients who underwent sequential [ 18F]FDG PET/CT within seven days of [ 18F]ALF-NOTA-FAPI-04 PET/CT, tracer uptake values were compared between the two PET/CT examinations. Results: 51 patients were included. The median PFS and OS were 7 and 10 months, respectively. Durable clinical benefit (DCB) was observed in 30 patients and showed significantly lower SUVmax, FTV, and TLF values than non-DCB. TLF demonstrated the highest diagnostic accuracy for DCB (area under the receiver operating characteristic curve [AUC] = 0.80). Multivariable analysis identified TLF ≥ 188.88 SUVbw·cm 3 as an independent factor associated with PFS (hazard ratio [HR] = 7.29, P = 0.001) and FTV ≥ 44.17 cm 3 as an independent factor associated with OS (HR = 5.16, P = 0.010). In the subgroup analysis of 16 patients, semi-quantitative analysis demonstrated consistently higher values of [ 18F]ALF-NOTA-FAPI-04-derived parameters than [ 18F]FDG-derived parameters (all P < 0.001). Conclusion [ 18F]ALF-NOTA-FAPI-04 PET/CT may be a useful imaging tool for predicting clinical outcomes in patients with recurrent gastric cancer undergoing treatment with PD-1 inhibitors and chemotherapy.

Objective: To investigate the molecular mechanism of Syk in phagocytosis induced by CD36 antibodies. Methods: In vitro, two CD36 monoclonal antibodies, GZ1 (IgG2a) and GZ4 (IgG1), at different concentrations were co-incubated with platelets from CD36-positive blood donors, and the affinity of the antibodies for platelets was assessed using flow cytometry. CD36 positive platelets from donors were labeled with Red-SE. The GZ1 and GZ4 antibodies were added together with dye-labeled platelets to peripheral blood from blood donors for phagocytosis experiments. The expression of the Spleen Tyrosine Kinase (Syk), P-Syk, P38 MAPK and P-P38 were detected using Western blot(WB). In the in vitro phagocytosis inhibition assay, Fcγ receptor (FcγR) antibodies or Syk inhibitor (R406) were pre-incubated with monocytes prior to performing the phagocytosis experiment. In vivo experiments were performed using female C57BL/6J mice. R406 was administered via intraperitoneal injection, followed by tail vein infusion of GZ1 or GZ4 antibodies. Additionally, a treatment group was set up in which the antibodies were infused first, followed by administration of R406. Changes in platelet counts were analyzed using a blood routine analyzer, and antibody binding to platelets was detected by flow cytometry. Results: GZ1 had higher affinity for CD36positive platelets than GZ4. The phagocytosis rate induced by GZ1 was significantly higher than that of GZ4 [(42.12±2.25)% vs (16.25±6.45)%, P<0.001]. Moreover, GZ1-mediated platelet phagocytosis mainly depends on FcγRⅠ of monocytes, while GZ4-mediated platelet phagocytosis mainly relies on FcγRⅡ of monocytes. WB results showed that the GZ1 group significantly upregulated the expression of Syk and phosphorylated Syk (P-Syk), and induced phosphorylation of the downstream P38 MAPK signaling pathway. Pretreatment of monocytes with R406 inhibited the phagocytosis of antibodyopsonized platelets by monocytes. After injecting GZ1 or GZ4 antibodies into C57BL/6 female mice through the tail vein, GZ1 mAbs had a stronger binding rate to the platelets compared with GZ4 mAbs, leading to a significant decrease in platelet count. After pre-injecting R406 into mice, the platelet count reduction in both the GZ1 and GZ4 groups was alleviated, and the binding rate of antibodies to platelets was also significantly reduced. However, administration of R406 after antibody injection failed to prevent the decrease in platelet counts in mice. Conclusion: This study indicates that Syk plays an important role in the phagocytosis of anti-CD36 opsonized platelets by monocytes/macrophages and is closely associated with the activation of the P38 MAPK signaling pathway.

Objective Exploring genetic differences among geographic strains of Anopheles sinensis in China. Methods Based on the mitochondrial cytochrome oxidase subunit I(COⅠ )and ribosomal the second internal transcribed spacer(ITS2), genetic distance analyses were conducted on An. sinensis samples collected nationwide. Results Genetic differentiation was observed within An. sinensis geographic strains, primarily reflected in the genetic distances of COⅠ sequences, with some distances between samples exceeding those between closely related species. However, ITS2 sequences showed relatively low levels of differentiation within geographic strains. No significant separation was observed, and gene exchange exhibited a random pattern among geographic strains. Conclusions Significant differences in genetic distance were observed among An. sinensis samples, along with evidence of interspecific continuity among sibling species. For the identification of closely related species using wild-collected Anopheles mosquitoes samples, reliance solely on commonly used barcodes such as COⅠ and ITS2 may be insufficient. Additional molecular markers, including COⅡ and D3 gene fragments, should also be considered. Caution should be exercised when using COⅠ genes to identify cryptic species, especially within Anopheles mosquitoes.

In the context of burgeoning economic trade, there has been a remarkable increase in the number of ships travelling between domestic and international ports. Inbound and outbound cargo ships, cruise liners, ferries, and other types of vessels have emerged as critical vehicles for the dispersal of vector organisms and the spread of infectious disease agents. Public health concerns associated with these vessels represent a significant threat to human welfare. In this paper, we comprehensively review the hazards posed by vector organisms on ships, the latest advances in prevention and control strategies, and proposes appropriate countermeasures. The aim is to provide effective guidance for the prevention and control of public health security issues caused by ship-borne vector organisms.