OBJECTIVE To investigate the effects of subanesthetic dose of esketamine on postoperative anxiety and recovery in patients undergoing laparoscopic cholecystectomy. METHODS A total of 200 patients scheduled for laparoscopic cholecystectomy at Suzhou Ninth Hospital Affiliated to Soochow University from January 2023 to December 2024 were randomly assigned to control group （n＝100） and observation group （n＝100）. One minute before the initiation of anesthesia， patients in the control group received intravenous injections of Propofol emulsion injection， Sufentanil citrate injection， and Succinylcholine chloride injection. On this basis， patients in the observation group received an intravenous injection of Esketamine hydrochloride injection. The anxiety status of patients in both groups was compared， along with their general intraoperative conditions （including sufentanil dosage， duration of pneumoperitoneum， operative time， anesthesia time， and extubation time）， postoperative recovery， incidence of adverse reactions， and the need for dezocine rescue analgesia. Heart rate and mean arterial pressure， entropy index （state entropy and response entropy）， inflammatory marker levels [interleukin-6 （IL-6） and C-reactive protein （CRP）]， numerical rating scale （NRS） for pain intensity were compared between the two groups at different time points. RESULTS No significant differences were found between the two groups in pneumoperitoneum duration， operative time， anesthesia time，extubation time， incidence of postoperative dry mouth， entropy index or length of stay in the post-anesthesia care unit （P＞0.05）. Compared with the control group， the observation group showed significantly lower postoperative STAI-S scores， reduced intraoperative sufentanil consumption， decreased incidence of postoperative nausea， vomiting， and shivering， the need for dezocine rescue analgesia， as well as lower plasma IL-6 and CRP levels at 24 h after surgery， and NRS （P＜0.05）. The heart rate and mean arterial pressure of patients in the observation group at the start of surgery， end of surgery， and during extubation were all significantly higher than those in the control group （P＜0.05）. CONCLUSIONS Subanesthetic dose of esketamine can effectively alleviate postoperative anxiety， reduce intraoperative opioid consumption， suppress postoperative inflammatory response， relieve postoperative pain， and promote recovery in patients undergoing laparoscopic cholecystectomy.

ObjectiveTo evaluate the therapeutic effects of modified Banxia Xiexintang（MBXT） on polycystic ovary syndrome with insulin resistance（PCOS-IR） rats and reveal its potential mechanisms based on the integrated analysis of transcriptomics and metabolomics. MethodsFemale SD rats were selected， and a PCOS-IR model was established by intragastric administration of letrozole combined with a high-fat diet for 21 days. The modeled rats were randomly divided into the model group， MBXT low-， medium-， and high-dose groups（6.62， 13.23， 26.46 g·kg^-1）， and metformin group（0.158 g·kg^-1）， with a normal group set up separately. After 14 days of administration， the estrous cycle was observed， ovarian morphology was examined by hematoxylin-eosin（HE） staining， and the levels of testosterone（T）， estradiol（E₂）， follicle-stimulating hormone（FSH）， and luteinizing hormone（LH） in serum were detected by enzyme-linked immunosorbent assay（ELISA）. Serum metabolites and ovarian tissue gene expression were detected using ultra-performance liquid chromatography-quadrupole-electrostatic orbitrap mass spectrometry（UPLC-Q-Orbitrap-MS） and RNA-Seq technology， respectively， followed by multi-omics integrated analysis. ResultsPharmacodynamic findings revealed that all MBXT dose groups could reversed abnormal estrous cycles in PCOS-IR rats， improve polycystic ovarian lesions， and normalize dysregulated serum hormone levels（T， LH， E₂， FS， P<0.05， P<0.01）. Metabolomic analysis revealed that compared with the model group， MBXT reversed 278 differential metabolites such as estrone and S-formylglutathione， mainly involving pathways such as steroid hormone biosynthesis， glutathione metabolism， and lipid peroxidation regulation. Transcriptomic analysis identified 434 differentially expressed genes， and enrichment analysis revealed that MBXT significantly regulated lipid peroxidation defense systems， including glutathione metabolism， peroxisome function， and fatty acid metabolism， thereby intervening in ferroptosis processes. It also engaged in inflammation-related pathways such as the chemokine signaling pathway. Integrated analysis revealed that both metabolomics and transcriptomics co-enriched metabolic pathways associated with ferroptosis and fatty acid metabolism. And key Hub genes［such as Ras-related C3 botulinum toxin substrate 2 gene（Rac2） and Fas ligand gene（Faslg）］ showed significant correlations with differential metabolites. ConclusionMBXT can effectively ameliorate reproductive dysfunction and metabolic disorders in PCOS-IR rats. Its mechanism may be related to remodeling the immune-metabolism network， particularly by regulating MHC-mediated immune responses， inhibiting local ovarian ferroptosis， and enhancing steroid hormone synthesis pathways.

ObjectiveTo investigate the mechanism of modified Banxia Xiexintang（MBXT） in improving ovarian dysfunction in polycystic ovary syndrome with insulin resistance（PCOS-IR） rats by inhibiting ferroptosis through the adenosine monophosphate（AMP）-activated protein kinase（AMPK）/fatty acid synthase（FASN）/glutathione peroxidase 4（GPX4） signaling pathway. MethodsSeventy-six female SD rats were randomly divided into a normal group（n=13） and a modeling group（n=63）. The modeling group established a PCOS-IR model by intragastric administration of letrozole combined with a high-fat diet for 21 days. After successful modeling， these rats were randomly divided into the model group， MBXT low-， medium-， and high-dose groups（6.62， 13.23， 26.46 g·kg^-1）， metformin group（0.158 g·kg^-1）， and high-dose of MBXT combined with ferroptosis inducer Erastin group（15 mg·kg^-1）， with 10 rats in each group. After 14 days of intervention， ovarian pathological morphology was observed by hematoxylin-eosin（HE） staining， the mitochondrial ultrastructure of granulosa cells was observed by transmission electron microscopy（TEM）， ovarian reactive oxygen species（ROS） levels were detected by dihydroethidium（DHE） probe， biochemical methods were used to detect Fe²⁺， malondialdehyde（MDA）， glutathione（GSH） and other indicators in ovarian tissues， serum sex hormone and insulin levels were measured by enzyme-linked immunosorbent assay（ELISA）， and the protein expressions of AMPK， FASN， acyl-CoA synthetase long-chain family member 4（ACSL4）， GPX4， and solute carrier family 7 member 11（SLC7A11） in ovarian tissues were detected by Western blot. ResultsCompared with the normal group， the model group showed polycystic changes in the ovaries， with atrophy of mitochondria in granulosa cells and increased membrane density. Serum levels of testosterone（T）， luteinizing hormone（LH）， and insulin were significantly increased（P<0.01）. The levels of ROS， MDA， 4-hydroxynonenal（4-HNE）， and Fe²⁺ in ovarian tissues were significantly elevated（P<0.01）， while adenosine triphosphate（ATP）， GSH， and reduced nicotinamide adenine dinucleotide phosphate （NADPH） levels were significantly decreased（P<0.01）. The phosphorylation levels of AMPK and acetyl-CoA carboxylase （ACC）， as well as the protein expressions of SLC7A11， GPX4， and ferroptosis suppressor protein 1（FSP1） were significantly downregulated（P<0.01）， whereas the expressions of FASN， ACSL4， and nuclear receptor coactivator 4（NCOA4） were significantly upregulated（P<0.01）. Compared with the model group， MBXT intervention at various doses improved the above pathological changes and biochemical indicators in a dose-dependent manner， with the high-dose group showing the most significant effect（P<0.01）. Compared with the MBXT high-dose group， the high-dose of MBXT combined with ferroptosis inducer Erastin group restored ovarian ferroptosis characteristics in rats， with increased ROS and lipid peroxidation products， and altered expressions of key proteins（P<0.05， P<0.01）. ConclusionMBXT can effectively improve ovarian function and metabolic disorders in PCOS-IR rats. Its mechanism may be related to activating the AMPK/ACC signaling pathway， downregulating FASN and ACSL4 to reduce lipid peroxidation substrates， and restoring glucose-6-phosphate dehydrogenase/phosphoglycerate dehydrogenase（G6PD/PHGDH） metabolic flux to enhance the GPX4/FSP1 antioxidant defense system， thereby inhibiting ferroptosis in ovarian granulosa cells.

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.

We report a case of a female farmer from the Yichang suburb, aged 68 years, who had been suffering from the infection for 3 years and had a history of seeking medical treatment at a community hospital and receiving blood transfusions. Her hemoglobin was as low as 28 g/L during this visit, and she had been ill for a long time with severe anemia. Routine stool examination revealed hookworm eggs. After active treatment, the patient recovered and was discharged from the hospital.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Poloxamer， as a non-ionic surfactant， exhibits a unique triblock [polyethylene oxide-poly （propylene oxide）-polyethylene oxide] structure， which endows it with broad application potential in various fields， including solid dispersion technology， nanotechnology， gel technology， biologics， gene engineering and 3D printing. As a carrier， it enhances the solubility and bioavailability of poorly soluble drugs. In the field of nanotechnology， it serves as a stabilizer etc.， enriching preparation methods. In gel technology， its self-assembly behavior and thermosensitive properties facilitate controlled drug release. In biologics， it improves targeting efficiency and reduces side effects. In gene engineering， it enhances delivery efficiency and expression levels. In 3D printing， it provides novel strategies for precise drug release control and the production of high-quality biological products. As a versatile material， poloxamer holds promising prospects in the pharmaceutical field.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.