ObjectiveTo elucidate the potential mechanisms by which the classic prescription Anmeidan alleviates cognitive impairment in insomnia model rats through metabolic profiling. MethodsA total of 60 SD rats were randomly divided into six groups： blank group， model group， low-， medium-， and high-dose Anmeidan groups， and the Suvorexant group， with 10 rats in each group. Except for the blank group， the insomnia model was established in all other groups via intraperitoneal injection of para-chlorophenylalanine. The Suvorexant group was administered Suvorexant solution （30 mg·kg^-1·d^-1） by gavage， while the low-， medium-， and high-dose Anmeidan groups received Anmeidan decoction （4.55， 9.09， 18.18 g·kg^-1·d^-1） by gavage. The blank group received an equivalent volume of normal saline. The open field test was used to assess spatial exploration and anxiety/depressive-like behaviors in rats. Serum levels of epidermal growth factor （EGF）， brain-derived neurotrophic factor （BDNF）， and vasoactive intestinal peptide （VIP） were measured using enzyme-linked immunosorbent assay （ELISA）. Untargeted metabolomics was employed to identify differential metabolites in rat serum， and systematic biological methods were applied to analyze the potential targets and pathways of Anmeidan. ResultsCompared to the blank group， the model group exhibited significant reductions in total distance traveled， average speed， number of entries into the central area， time spent in the central area， and frequency of upright events （P<0.01）， along with significant decreases in VIP， EGF， and BDNF levels （P<0.05，P<0.01）. A total of 100 differential metabolites were identified between the model and blank groups. Compared to the model group， the low-， medium-， and high-dose Anmeidan groups showed significant increases in total distance traveled， average speed， number of entries into the central area， time spent in the central area， and frequency of upright events （P<0.05，P<0.01）， as well as a significant increase in VIP levels （P<0.05，P<0.01）. Anmeidan significantly reversed abnormal changes in 67 metabolites compared to the model group. A combined analysis identified 134 potential targets of Anmeidan， with network topology analysis suggesting that Caspase-3， B-cell lymphoma 2 （Bcl-2）， nuclear transcription factor-κB （NF-κB）， interleukin-1β （IL-1β）， interleukin-2 （IL-2）， matrix metalloproteinase-9 （MMP-9）， and Toll-like receptor 4 （TLR4）， among others， may serve as key targets of Anmeidan. Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway analysis revealed major enriched pathways， including the cyclic adenosine monophosphate （cAMP） signaling pathway， hypoxia inducible factor-1 （HIF-1） signaling pathway， and IL-17 signaling pathway. ConclusionThis study demonstrates that Anmeidan can recalibrate abnormal metabolic profiles in insomnia model rats to mitigate cognitive impairment， with its mechanisms of action potentially involving the regulation of immune-inflammatory responses， energy metabolism， and apoptosis-related pathways.

OBJECTIVE To investigate the efficacy and safety of ropivacaine combined with oxycodone for the analgesia of iliac fascia nerve block in patients undergoing hip replacement. METHODS Sixty-six patients who underwent hip replacement at the Central Hospital of Enshi Tujia and Miao Autonomous Prefecture from October 2023 to April 2024 were selected and randomly divided into observation group and control group， with 33 cases in each group. Before induction of anesthesia， ultrasound-guided iliac fascial nerve block was performed. Patients in the observation group were treated with 0.33% ropivacaine+0.1 mg/kg oxycodone injection mixture 30 mL， and patients in the control group were treated with 0.33% ropivacaine injection 30 mL. The time of first postoperative rescue analgesia， 24 h postoperative analgesic drug consumption， sensory block and motor block effective and maintenance time， satisfaction degree， numerical rating scale （NRS） pain score， Ramsay sedation score， muscle strength score， heart rate （HR）， mean arterial pressure （MAP）， oxygen saturation（SpO2）， sleep score， anxiety score， and the occurrence of adverse reactions in the two groups were all recorded. RESULTS Compared with the control group， the first rescue analgesia time after operation was significantly prolonged in the observation group， and 24 h postoperative analgesic drug consumption after operation decreased； the effective time of sensory block was significantly shortened， and the maintenance time of sensory block was significantly prolonged， and the satisfaction score was higher； the NRS pain score after iliac fascia nerve block was lower， HR and MAP were lower， and the anxiety score and sleep score 24 and 48 h after operation were lower （P＜0.05）. In terms of safety， patients in both groups had adverse reactions after operation， such as hypertension， nausea， vomiting， and dizziness， but there was no significant difference in the incidence of adverse reactions between the two groups （P＞0.05）. CONCLUSIONS Oxycodone combined with ropivacaine shows good efficacy and safety for iliac fascial nerve block analgesia in patients undergoing hip replacement， can significantly prolong the analgesic time of ropivacaine， reduce postoperative analgesic drug consumption， improve the sleep quality of patients， and promote the rapid recovery of patients.

AIM: To investigate the mechanism of Hexue Mingmu Tablets(HXMMT)in improving diabetic retinopathy(DR)based on transcriptomics.METHODS: Zebrafish DR models were established by 3-day glucose induction(130 mmol/L)starting at 3 days post-fertilization(dpf). Larvae were randomized into four groups: control group(CG; aquaculture water), model group(MG; 130 mmol/L glucose), low-dose HXMMT treatment group(L-HX; 130 mmol/L glucose +7.5 mg/L HXMMT), and high-dose HXMMT treatment group(H-HX; 130 mmol/L glucose +75 mg/L HXMMT), with a 3-day intervention period until 6 dpf. The area and length of eyes, and body length of zebrafish were observed by stereomicroscopy, retinal morphology was observed by hematoxylin-eosin staining(HE), and retinal vessel diameter was observed under fluorescence microscope. Differentially expressed genes(DEGs)were identified by RNA-sequencing(RNA-seq)technology to further elucidate the molecular mechanism of HXMMT in improving DR in zebrafish, and the sequencing accuracy was validated through quantitative real-time polymerase chain reaction(qRT-PCR).RESULTS: HE staining demonstrated that the intervention with HXMMT significantly improved the disordered cell arrangement, widened gaps, and thickened inner nuclear layer(INL)in ganglion cell layer GCL); retinal vascular diameter quantification revealed that the retinal vessel diameter of the MG significantly increased compared with the CG, and it was significantly changed after the intervention of HXMMT, with significant efficacy in the H-HX(P<0.05); transcriptomics profiling identified 1 470 reversed DEGs, predominantly enriched in the AMPK signaling pathway, FoxO signaling pathway, retinal developmental processes, and tight junction regulation. Technical validation confirmed strong correlation between qRT-PCR and RNA-seq data(R2=0.8571, P<0.05).CONCLUSION: HXMMT may improve retinal vascular microcirculation disorders in DR by regulating core targets including vsx1, pde6c, arr3a, plk1, fbp1b, foxo1a, pcna, and cdk1, as well as synergistically modulating processes such as retinal development in camera-type eyes, visual perception, microtubule cytoskeletal organization, tight junctions, and the AMPK signaling pathway, Foxo signaling pathway.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

This study aimed to explore the molecular mechanism of rubioncolin C(RuC) in inhibiting gastric cancer(GC). AGS and MGC803 cell lines were selected as cellular models. After treating the cells with RuC at different concentrations, the effects of RuC on the proliferation ability of GC cells were assessed using the CCK-8 method, real-time cellular analysis(RTCA), and colony formation assays. Transmission electron microscopy was used to observe subcellular structural changes. Immunofluorescence was applied to detect LC3 fluorescent foci. Acridine orange staining was used to evaluate the state of intracellular lysosomes. Western blot was employed to detect the expression of autophagy-related proteins LC3Ⅱ, P62, and lysosomal cathepsin D(CTSD). The SuperPred online tool was used to predict the target proteins that bound to RuC, and molecular docking analysis was conducted to identify the interaction sites between RuC and CTSD. The drug affinity responsive target stability(DARTS) assay was performed to detect the direct binding interaction between RuC and CTSD. The results showed that RuC significantly inhibited the proliferation and colony formation of GC cells at low concentrations, with 24-hour half-maximal inhibitory concentrations(IC_(50)) of 3.422 and 2.697 μmol·L~(-1) for AGS and MGC803 cells, respectively. After 24 hours of treatment with RuC at concentrations of 1, 2, and 3 μmol·L~(-1), the colony formation rates for AGS cells were 61.0%±1.5%, 28.0%±0.5%, and 18.2%±0.5%, respectively, while the rates for MGC803 cells were 56.0%±0.5%, 23.3%±1.0%, and 11.8%±1.0%, all of which were significantly reduced. Transmission electron microscopy revealed that RuC promoted an increase in autophagosome formation in GC cells. Immunofluorescence detection showed that LC3 fluorescent foci of GC cells increased with the increase in RuC dose. RuC up-regulated the expression of autophagy-related proteins LC3Ⅱ and P62 in GC cells. Acridine orange staining indicated that RuC altered the acidic environment of lysosomes. SuperPred online prediction identified CTSD as a potential target protein of RuC. Western blot analysis revealed that RuC induced the up-regulation of the inactive precursor of CTSD in GC cells. CTSD activity assays indicated that RuC reduced the activity of CTSD. Molecular docking simulations found that RuC bound to the substrate-binding region of CTSD, forming hydrogen bonds with the Tyr205 and Asp231 residues. Microscale thermophoresis and DARTS assays further confirmed that RuC directly bound to CTSD. In summary, RuC inhibits lysosomal activity by targeting and down-regulating the expression of CTSD, thereby inducing autophagosome accumulation in GC cells.
Humans ; Stomach Neoplasms/enzymology* ; Cathepsin D/chemistry* ; Cell Line, Tumor ; Molecular Docking Simulation ; Cell Proliferation/drug effects* ; Autophagosomes/metabolism* ; Autophagy/drug effects*

Pristimerin, which is one of the compounds present in Celastraceae and Hippocrateaceae, has antitumor effects. However, its mechanism of action in esophageal squamous cell carcinoma (ESCC) remains unclear. This study aims to investigate the efficacy and mechanism of pristimerin on ESCC in vitro and in vivo. The inhibitory effect of pristimerin on cell growth was assessed using trypan blue exclusion and colony formation assays. Cell apoptosis was evaluated by flow cytometry. Gene and protein expressions were analyzed through quantitative reverse transcription-polymerase chain reaction (qRT-PCR), Western blotting, and immunohistochemistry. RNA sequencing (RNA-Seq) was employed to identify significantly differentially expressed genes (DEGs). Cell transfection and RNA interference assays were utilized to examine the role of key proteins in pristimerin?s effect. Xenograft models were established to evaluate the antitumor efficiency of pristimerin in vivo. Pristimerin inhibited cell growth and induced apoptosis in ESCC cells. Upregulation of Noxa was crucial for pristimerin-induced apoptosis. Pristimerin activated the Forkhead box O3a (FoxO3a) signaling pathway and triggered FoxO3a recruitment to the Noxa promoter, leading to Noxa transcription. Blocking FoxO3a reversed pristimerin-induced Noxa upregulation and cell apoptosis. Pristimerin treatment suppressed xenograft tumors in nude mice, but these effects were largely negated in Noxa-KO tumors. Furthermore, the chemosensitization effects of pristimerin in vitro and in vivo were mediated by Noxa. This study demonstrates that pristimerin exerts an antitumor effect on ESCC by inducing AKT/FoxO3a-mediated Noxa upregulation. These findings suggest that pristimerin may serve as a potent anticancer agent for ESCC treatment.
Forkhead Box Protein O3/genetics* ; Humans ; Apoptosis/drug effects* ; Esophageal Squamous Cell Carcinoma/physiopathology* ; Esophageal Neoplasms/physiopathology* ; Pentacyclic Triterpenes ; Animals ; Cell Line, Tumor ; Proto-Oncogene Proteins c-bcl-2/genetics* ; Mice ; Signal Transduction/drug effects* ; Mice, Nude ; Cell Proliferation/drug effects* ; Triterpenes/pharmacology* ; Xenograft Model Antitumor Assays ; Mice, Inbred BALB C ; Male ; Gene Expression Regulation, Neoplastic/drug effects*

The nucleotide binding oligomerization domain like receptor protein 3(NLRP3)inflamma-some is an intracellular polymeric protein complex that plays an important role in inflammation and immune response.In recent years,the study of NLRP3 inflammasome in hematological malignancies has become a hot topic.Leukemia is a large group of clonal hematologic malignancies that affect the maturation and/or prolifer-ation of bone marrow or lymphocytes.More and more studies have shown that NLRP3 inflammatory micro-molecules are involved in the occurrence and development of leukemia,and it is expected to become an impor-tant therapeutic target for leukemia in the future.In this review,the structure,biological function,activation pathway of NLRP3 inflammasome and its relationship with different types of leukemia were reviewed,and its potential application in the treatment of leukemia was discussed.

Alzheimer's disease(AD)is a chronic neurodegenerative disease that severely affects the quality of life of the elderly.Its main pathological features include the deposition of β-amyloid protein to form senile plaques,neurofibrillary tangles caused by abnormal phosphorylation of tau pro-tein,as well as extensive neuronal loss and synaptic dysfunction.In recent years,mesenchymal stem cells(MSCs)and their exosomes(MSC-Exos)have attracted extensive attention due to their poten-tial in the treatment of neurodegenerative diseases.MSCs possess multidirectional differentiation po-tential,immunomodulatory capacity,and significant neuroprotective and repair effects.As an impor-tant signaling mediator of MSCs,MSC-Exos are a type of nanoscale double-layer membrane-structured vesicles secreted by MSCs,capable of carrying and delivering various bioactive substances.MSCs and their derived MSC-Exos have demonstrated good safety and efficacy in the treatment of AD.This arti-cle systematically reviewed the basic and translational research progress on MSCs and MSC-Exos in the treatment of AD in recent years.

Objective To analyze the clinical manifestations and epidemiological characteristics of influenza in Hubei. Methods Pharyngeal swab specimens from 16,500 patients with suspected influenza infection admitted to our hospital from January 2020 to December 2022 were selected. Viral detection and serotyping were performed by fluorescence quantitative polymerase chain reaction. Furthermore, the epidemiological and clinical data of patients were collected to analyze the clinical features and epidemiological characteristics of influenza viruses. Results A total of 16 500 clinical specimens were tested in this study, with a positive detection rate of 16.27% (2 684/16 500). The positive detection rate was 5.10% (862/16 500) for influenza A virus, 10.13% (1 672/16 500) for influenza B virus and 0.91% (150/16 500) for mixed influenza. The positive detection rate of influenza viruses was on the rise from 2020 to 2022 , reaching 18.43% in 2022. Seasonal distribution analysis denoted that the highest positive detection rates were observed in spring (18.23%) and winter (19.72%), with statistical difference (P<0.05). In terms of age distribution, patients<12 years (19.14%) had the highest positive detection rate, followed by those >60 years (17.71%), with statistical difference (P<0.05). From 2020 to 2022, the positive detection rate of influenza virus was 16.89% in males, which was higher than 15.63% in females (P<0.05). The main clinical symptoms were fever (86.89%) and cough (80.27%) for influenza A virus infections, cough (92.52%) and fever (86.06%) for influenza B virus infections, and cough (94.00%), fever (88.00%) and runny nose (86.00%) for mixed infections. Conclusion The influenza B viruses are the leading cause of influenza in Hubei from 2020 to 2022, and the infection demonstrates an increasing annual trend, with a high prevalence in winter and spring. Furthermore, children and the elderly are high-risk populations, and clinical manifestions are mainly cough and fever.

Objective To establish an artificial intelligence (AI)-assisted platform for detection of parasite eggs, and to evaluate its detection efficiency and accuracy, so as to provide technical supports for elimination of parasitic diseases. Methods A total of 1 003 slides of Enterobius vermicularis, horkworm, Trichuris trichiura, Clonorchis sinensis, Taenia, Ascaris lumbricoides, Schistosoma japonicum, Paragonimus westermani and Fasciolopsis buski eggs were collected, and converted into digital images with an automatated scanning microscope to create a dataset. Based on the Object Detection platform on the Baidu Easy DL model, an AI-assisted platform for detection of parasite eggs was created through procedures of uploading, labeling, training, evaluation and optimization. Then, 70% of the datasets were randomly selected for model training, and the precision, recall and average accuracy were calculated to evaluate the effectiveness of platform for recognition of parasite eggs. In addition, the platform was deployed on the computer and smart phone terminals for use. Results An AI-assisted platform for detection of parasite eggs was successfully created. If the platform was deployed using the public cloud application programming interface (API), the average accuracy, precision and recall of the platform were 93.42%, 92.55% and 89.32% for recognition of parasite eggs. If the platform was deployed using the offline software development kit (SDK), the average accuracy, precision and recall of the platform were 92.97%, 94.78% and 87.63% for recognition of parasite eggs. In addition, the precision of the platform was 97.00% and 96.23% for identification of Taenia and C. sinensis eggs, respectively. Conclusions The AI-assisted platform for detection of parasite eggs has been successfully created, which is high in the accuracy for recognition of parasite eggs and convenient in use. This platform may provide a powerful technical support for parasitic disease diagnosis.