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.

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.

OBJECTIVES: As early as the Apollo 11 mission, astronauts experienced ocular, skin, and upper airway irritation after lunar dust (LD) was brought into the return cabin, drawing attention to its potential biological toxicity. However, the biological effects of LD exposure through the digestive system remain poorly understood. This study aimed to evaluate the impact of digestive exposure to lunar dust simulant (LDS) on gut microbiota and on the intestine, liver, kidney, lung, and bone in mice. METHODS: Eight-week-old female C57BL/6J mice were used. LDS was used as a substitute for lunar dust, and Shaanxi loess was used as Earth dust (ED). Mice were randomly divided into a phosphate buffered saline (PBS) group, an ED group (500 mg/kg), and a LDS group (500 mg/kg), with assessments at days 7, 14, and 28. Mice were gavaged once every 3 days, with body weight recorded before each gavage. At sacrifice, fecal samples were analyzed by 16S ribosomal RNA (rRNA) sequencing; inflammatory cytokine expression [interleukin (IL)-1β, IL-6, and tumor necrosis factor alpha (TNF-α)] in intestinal, liver, and lung tissues was measured by real-time reverse transcription PCR (real-time RT-PCR); hematoxylin and eosin (HE) staining was performed on lung, liver, and intestinal tissues; Periodic acid-Schiff (PAS) staining was used to assess the integrity of the intestinal mucus barrier, and immunohistochemical staining was performed to evaluate the expression of mucin-2 (MUC2). Serum biochemical tests assessed hepatic and renal function. Femoral bone mass was analyzed by micro-computed tomography (micro-CT); osteoblasts and osteoclasts were assessed by osteocalcin (OCN) and tartrate-resistant acid phosphatase (TRAP) staining. Bone marrow immune cell subsets were analyzed by flow cytometry. RESULTS: At day 10, weight gain was slowed in ED and LDS groups. At days 22 and 28, body weight in both ED and LDS groups was significantly lower than controls (both P<0.05). LDS exposure increased microbial species richness and diversity at day 7. Compared with the PBS and ED groups, mice in the LDS group showed increased relative abundance of Deferribacterota, Desulfobacterota, and Campylobacterota, and decreased Firmicutes, with increased Helicobacter typhlonius and reduced Lactobacillus johnsonii and Lactobacillusmurinus. HE and PAS staining of the colon showed that mucosal structural disruption and goblet cell loss were more severe in the LDS group. In addition, immunohistochemistry revealed a significant downregulation of MUC2 expression in this group (P<0.05). No obvious pathological alterations were observed in liver HE staining among the 3 groups, and none of the groups exhibited notable hepatic or renal dysfunction. HE staining of the lungs in the ED and LDS groups showed increased perivascular inflammatory cell infiltration (both P<0.05). CONCLUSIONS LDS exposure via the digestive route induces gut dysbiosis, intestinal barrier disruption, pulmonary inflammation, bone loss, and bone marrow immune imbalance. These findings indicate that LD exposure poses potential health risks during future lunar missions. Targeted restoration of beneficial gut microbiota may represent a promising strategy to mitigate LD-related health hazards.
Animals ; Dust ; Mice ; Mice, Inbred C57BL ; Dysbiosis/etiology* ; Female ; Gastrointestinal Microbiome/drug effects* ; Moon ; Liver/metabolism* ; Digestive System/microbiology* ; Lung/metabolism* ; Kidney

OBJECTIVES: Due to prolonged exposure to cosmic radiation and meteorite impacts, lunar surface dust forms nanoscale angular particles with strong electrostatic adsorption properties. These dust particles pose potential inhalation risks, yet their pulmonary toxicological mechanisms remain unclear. Given the need for dust exposure protection in future lunar base construction and resource development, this study established an acute exposure model using lunar soil simulant (LSS) and used Earth soil (ES; Loess from Shaanxi, China) as a comparison to investigate lung injury mechanisms. METHODS: C57BL/6 mice were randomly assigned to 3 groups: Phosphate buffered saline (PBS), LSS, and ES, with 5 to 7 mice per group. Mice in the LSS and ES groups received a single intratracheal instillation to induce acute inhalation exposure. Body weight was monitored for 28 days. Mice were euthanized at days 3, 7, 14, and 28 post-exposure, and peripheral blood, bronchoalveolar lavage fluid (BALF), and lung tissues were collected. Immune cell subsets in BALF were analyzed using flow cytometry. Hematoxylin-eosin (HE) staining assessed lung structure and inflammation; periodic acid-Schiff (PAS) staining evaluated airway mucus secretion; Masson staining examined collagen deposition. Real-time reverse transcription PCR (real-time RT-PCR) was used to measure the mRNA expression of inflammatory cytokines (IL-1β, IL-6, and TNF-α) and epithelial barrier genes (Occludin, Cadherin-1, and Zo-1). Lung tissues at day 7 were subjected to transcriptomic sequencing, followed by immune infiltration and pathway enrichment analyses to determine immunoregulatory mechanisms. RESULTS: Body weight in the ES group progressively declined after day 18 (all P<0.05), while the LSS group showed no significant changes compared with the control group. HE staining showed both LSS and ES induced inflammatory cell infiltration around airways and vasculature, which persisted for 28 days but gradually lessened over time. PAS staining revealed marked mucus hypersecretion in the LSS group at day 3, followed by gradual recovery; no significant mucus changes were observed in the ES group. Masson staining indicated no obvious pulmonary fibrosis in either group within 28 days. Real-time RT-PCR demonstrated significant upregulation of IL-1β and TNF-α in both LSS and ES groups, peaking on day 7, accompanied by downregulation of epithelial barrier genes (Occludin, Cadherin-1, and Zo-1)(all P<0.05). Transcriptomic analysis showed that both LSS and ES activated chemokine-related pathways and enriched leukocyte migration and neutrophil recruitment pathways. Further validation revealed upregulation of CXCL2 and MMP12 in the LSS group, whereas CXCL3 and MMP12 were predominantly elevated in the ES group. CONCLUSIONS Both LSS and ES can induce sustained lung injury and neutrophil infiltration in mice, though the underlying molecular mechanisms differ. Compared with ES, exposure to LSS additionally triggers a transient eosinophilic response, suggesting that lunar dust particles possess stronger immunostimulatory potential and higher biological toxicity.
Animals ; Mice ; Mice, Inbred C57BL ; Soil ; Lung Injury/etiology* ; Dust ; Bronchoalveolar Lavage Fluid ; Moon ; Lung/pathology* ; Inhalation Exposure/adverse effects* ; Male

BACKGROUND: Growing evidence suggests that long non-coding RNAs (lncRNAs) exert pivotal roles in fostering chemoresistance across diverse tumors. Nevertheless, the precise involvement of lncRNAs in modulating chemoresistance within the context of gallbladder cancer (GBC) remains obscure. This study aimed to uncover how lncRNAs regulate chemoresistance in gallbladder cancer, offering potential targets to overcome drug resistance. METHODS: To elucidate the relationship between gemcitabine sensitivity and small nucleolar RNA host gene 1 ( SNHG1 ) expression, we utilized publicly available GBC databases, GBC tissues from Renji Hospital collected between January 2017 and December 2019, as well as GBC cell lines. The assessment of SNHG1, miR-23b-3p, and phosphatase and tensin homolog (PTEN) expression was performed using in situ  hybridization, quantitative real-time polymerase chain reaction, and western blotting. The cell counting kit-8 (CCK-8) assay was used to quantify the cell viability. Furthermore, a GBC xenograft model was employed to evaluate the impact of SNHG1 on the therapeutic efficacy of gemcitabine. Receiver operating characteristic (ROC) curve analyses were executed to assess the specificity and sensitivity of SNHG1. RESULTS: Our analyses revealed an inverse correlation between the lncRNA SNHG1 and gemcitabine resistance across genomics of drug sensitivity in cancer (GDSC) and Gene Expression Omnibus (GEO) datasets, GBC cell lines, and patients. Gain-of-function investigations underscored that SNHG1 heightened the gemcitabine sensitivity of GBC cells in both in vitro and in vivo  settings. Mechanistic explorations illuminated that SNHG1 could activate PTEN -a commonly suppressed tumor suppressor gene in cancers-thereby curbing the development of gemcitabine resistance in GBC cells. Notably, microRNA (miRNA) target prediction algorithms unveiled the presence of miR-23b-3p binding sites within SNHG1 and the 3'-untranslated region (UTR) of PTEN . Moreover, SNHG1 acted as a sponge for miR-23b-3p, competitively binding to the 3'-UTR of PTEN , thereby amplifying PTEN expression and heightening the susceptibility of GBC cells to gemcitabine. CONCLUSION The SNHG1/miR-23b-3p/PTEN axis emerges as a pivotal regulator of gemcitabine sensitivity in GBC cells, holding potential as a promising therapeutic target for managing GBC patients.
Humans ; Deoxycytidine/pharmacology* ; PTEN Phosphohydrolase/genetics* ; Gemcitabine ; RNA, Long Noncoding/metabolism* ; MicroRNAs/genetics* ; Gallbladder Neoplasms/genetics* ; Cell Line, Tumor ; Animals ; Mice ; Drug Resistance, Neoplasm/genetics* ; Mice, Nude ; Antimetabolites, Antineoplastic ; Gene Expression Regulation, Neoplastic

The rupture of carotid vulnerable plaques is the core pathological basis for major cardiovascular and cerebrovascular events. However， the insufficient alignment between existing animal models and the clinical disease and syndrome characteristics of traditional Chinese and western medicine has limited research progress. In this study， biomedical databases in China and abroad were systematically searched， and the modeling mechanisms and evaluation systems of carotid vulnerable plaque animal models were systematically assessed based on diagnostic criteria of both traditional Chinese and western medicine. Analysis of the clinical correspondence indicated that existing animal models can be categorized into four types： simple high-fat diet， surgical induction combined with high-fat feeding， genetic engineering combined with high-fat feeding， and drug induction combined with high-fat feeding. Among these， the compound strategy of surgical induction combined with high-fat feeding has become the current mainstream approach， showing good concordance with western medicine. The study found that the double balloon injury rabbit model and the ApoE^-/- mouse carotid artery tandem constriction combined with high-fat feeding model demonstrated a high degree of clinical correspondence with both traditional Chinese and western medicine in terms of vulnerable plaque imaging and pathological features. Nevertheless， existing models still face significant technical limitations in faithfully simulating plaque pathology and in translating findings to clinical applications. To address these challenges， integrating complex comorbidity mechanism construction， multimodal dynamic mechanism monitoring， and collaborative evaluation systems of traditional Chinese and western medicine could enable the development of highly concordant carotid vulnerable plaque disease-syndrome combination animal models. Such models would provide a reproducible experimental platform for targeted drug development to regulate plaque stability and for individualized precision treatment， as well as a theoretical basis for innovation in clinical diagnostic and therapeutic strategies.

The expert consensus on the clinical treatment of herpes zoster with fire needling was developed, and the commonly used fire needling treatment scheme verified by clinical research was selected to form a standardized diagnosis and treatment scheme for acute herpes zoster and postherpetic neuralgia (PHN), so as to answer the core problems in clinical application. The consensus focuses on patients with herpes zoster, and forms recommendations for 9 key clinical issues, covering simple fire needling and TCM comprehensive therapy based on fire needling, including fire needling combined with cupping, fire needling combined with Chinese herb, fire needling combined with cupping and Chinese herb, fire needling combined with filiform needling, fire needling combined with moxibustion, and provides specific recommendations and operational guidelines for various therapies.
Humans ; Herpes Zoster/therapy* ; Acupuncture Therapy/instrumentation* ; Consensus ; Clinical Protocols

To introduce and analyze guideline terminology related to clinical question formulation, evidence retrieval and appraisal, and recommendation development.