Recent studies have identified a missense mutation in the β1-receptor (ADRB1-A187V) that exerts a pronounced impact on human sleep, with a noted decrease in protein abundance in vivo. The administration of β-blockers is frequently associated with sleep disturbances in clinical settings. In this study, we assessed the influence of various β-blockers on sleep within mouse models. Our findings indicated that β-blockers could induce varying degrees of arousal, sleep disruption, and a decrease in REMS (rapid eye movement sleep). We examined the dose-dependent effects of metoprolol and nebivolol on both sleep and cardiac functionality in both wild-type and Adrb1-A187V mutant mice. Our data suggested that, in contrast to cardiac effects, higher doses of metoprolol are required to have noted impact on sleep. No genotype effect was observed with metoprolol in terms of sleep or cardiac function. In contrast, the mutant mice demonstrated increased sensitivity to nebivolol, which exacerbated sleep fragmentation and impeded the onset of REMS. This study is expected to provide some reference for minimizing the occurrence of sleep disorders and reducing the adverse reactions of drugs to the greatest extent.

Patients suffering from nerve injury often experience exacerbated pain responses and complain of memory deficits. The dorsal hippocampus (dHPC), a well-defined region responsible for learning and memory, displays maladaptive plasticity upon injury, which is assumed to underlie pain hypersensitivity and cognitive deficits. However, much attention has thus far been paid to intracellular mechanisms of plasticity rather than extracellular alterations that might trigger and facilitate intracellular changes. Emerging evidence has shown that nerve injury alters the microarchitecture of the extracellular matrix (ECM) and decreases ECM rigidity in the dHPC. Despite this, it remains elusive which element of the ECM in the dHPC is affected and how it contributes to neuropathic pain and comorbid cognitive deficits. Laminin, a key element of the ECM, consists of α-, β-, and γ-chains and has been implicated in several pathophysiological processes. Here, we showed that peripheral nerve injury downregulates laminin β1 (LAMB1) in the dHPC. Silencing of hippocampal LAMB1 exacerbates pain sensitivity and induces cognitive dysfunction. Further mechanistic analysis revealed that loss of hippocampal LAMB1 causes dysregulated Src/NR2A signaling cascades via interaction with integrin β1, leading to decreased Ca²⁺ levels in pyramidal neurons, which in turn orchestrates structural and functional plasticity and eventually results in exaggerated pain responses and cognitive deficits. In this study, we shed new light on the functional capability of hippocampal ECM LAMB1 in the modulation of neuropathic pain and comorbid cognitive deficits, and reveal a mechanism that conveys extracellular alterations to intracellular plasticity. Moreover, we identified hippocampal LAMB1/integrin β1 signaling as a potential therapeutic target for the treatment of neuropathic pain and related memory loss.
Animals ; Laminin/genetics* ; Hippocampus/metabolism* ; Neuralgia/metabolism* ; Cognitive Dysfunction/etiology* ; Male ; Peripheral Nerve Injuries/metabolism* ; Extracellular Matrix/metabolism* ; Integrin beta1/metabolism* ; Pyramidal Cells/metabolism* ; Signal Transduction

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

OBJECTIVE: Cancer remains a significant global health challenge, necessitating the development of effective treatment approaches. Developing synergistic therapy can provide a highly promising strategy for anti-cancer treatment through combining the benefits of various mechanisms. METHODS: In this study, we developed a synergistic strategy for chemo-photothermal therapy by constructing nanocomposites using gold nanorods (GNRs) and tetrahedral framework nucleic acids (tFNA) loaded with the anti-tumor drug doxorubicin (DOX). RESULTS: Our in vitro studies have systematically clarified the anti-cancer behaviors of tFNA-DOX@GNR nanocomposites, characterized by their enhanced cellular uptake and proficient lysosomal escape capabilities. It was found that the key role of tFNA-DOX@GNR nanocomposites in tumor ablation is primarily due to their capacity to induce cytotoxicity in tumor cells via a photothermal effect, which generates instantaneous high temperatures. This mechanism introduces various responses in tumor cells, facilitated by the thermal effect and the integrated chemotherapeutic action of DOX. These reactions include the induction of endoplasmic reticulum stress, characterized by elevated reactive oxygen species levels, the promotion of apoptotic cell death, and the suppression of tumor cell proliferation. CONCLUSION This work exhibits the potential of synergistic therapy utilizing nanocomposites for cancer treatment and offers a promising avenue for future therapeutic strategies.
Doxorubicin/chemistry* ; Gold/chemistry* ; Nanotubes/chemistry* ; Humans ; Nanocomposites/chemistry* ; Cell Line, Tumor ; Nucleic Acids/chemistry* ; Antibiotics, Antineoplastic/pharmacology* ; Antineoplastic Agents/administration & dosage*

In this study, lipopolysaccharide(LPS), ovalbumin(OVA), and compound 48/80(C48/80) were administered to establish non-infectious pneumonia models under simulated clinical conditions, and the correlation between their pathological characteristics and traditional Chinese medicine(TCM) syndromes was compared, providing the basis for the selection of appropriate animal models for TCM efficacy evaluation. An acute pneumonia model was established by nasal instillation of LPS combined with intraperitoneal injection for intensive stimulation. Three doses of OVA mixed with aluminum hydroxide adjuvant were injected intraperitoneally on days one, three, and five and OVA was administered via endotracheal drip for excitation on days 14-18 to establish an OVA-induced allergic pneumonia model. A single intravenous injection of three doses of C48/80 was adopted to establish a C48/80-induced pneumonia model. By detecting the changes in peripheral blood leukocyte classification, lung tissue and plasma cytokines, immunoglobulins(Ig), histamine levels, and arachidonic acid metabolites, the multi-dimensional analysis was carried out based on pathological evaluation. The results showed that the three models could cause pulmonary edema, increased wet weight in the lung, and obvious exudative inflammation in lung tissue pathology, especially for LPS. A number of pyrogenic cytokines, inclading interleukin(IL)-6, interferon(IFN)-γ, IL-1β, and IL-4 were significantly elevated in the LPS pneumonia model. Significantly increased levels of prostacyclin analogs such as prostaglandin E2(PGE2) and PGD2, which cause increased vascular permeability, and neutrophils in peripheral blood were significantly elevated. The model could partly reflect the clinical characteristics of phlegm heat accumulating in the lung or dampness toxin obstructing the lung. The OVA model showed that the sensitization mediators IgE and leukotriene E4(LTE4) were increased, and the anti-inflammatory prostacyclin 6-keto-PGF2α was decreased. Immune cells(lymphocytes and monocytes) were decreased, and inflammatory cells(neutrophils and basophils) were increased, reflecting the characteristics of "deficiency", "phlegm", or "dampness". Lymphocytes, monocytes, and basophils were significantly increased in the C48/80 model. The phenotype of the model was that the content of histamine, a large number of prostacyclins(6-keto-PGE1, PGF2α, 15-keto-PGF2α, 6-keto-PGF1α, 13,14-D-15-keto-PGE2, PGD2, PGE2, and PGH2), LTE4, and 5-hydroxyeicosatetraenoic acid(5S-HETE) was significantly increased, and these indicators were associated with vascular expansion and increased vascular permeability. The pyrogenic inflammatory cytokines were not increased. The C48/80 model reflected the characteristics of cold and damp accumulation. In the study, three non-infectious pneumonia models were constructed. The LPS model exhibited neutrophil infiltration and elevated inflammatory factors, which was suitable for the efficacy study of TCM for clearing heat, detoxifying, removing dampness, and eliminating phlegm. The OVA model, which took allergic inflammation as an index, was suitable for the efficacy study of Yiqi Gubiao formulas. The C48/80 model exhibited increased vasoactive substances(histamine, PGs, and LTE4), which was suitable for the efficacy study and evaluation of TCM for warming the lung, dispersing cold, drying dampness, and resolving phlegm. The study provides a theoretical basis for model selection for the efficacy evaluation of TCM in the treatment of pneumonia.
Animals ; Disease Models, Animal ; Mice ; Pneumonia/genetics* ; Medicine, Chinese Traditional ; Male ; Humans ; Cytokines/immunology* ; Female ; Lipopolysaccharides/adverse effects* ; Lung/drug effects* ; Drugs, Chinese Herbal ; Ovalbumin ; Mice, Inbred BALB C

Incomplete debridement of chronic osteomyelitis is the main factor leading to recurrence. For the treatment of chronic osteomyelitis, the complete elimination of the source of infection is the key to preventing recurrence. This process includes not only the complete removal of infected lesions, dead bone, accreted scar tissue and granulation tissue, but also the elimination of dead space and improved local blood circulation. In these steps, debridement is a core procedure, and judging the scope of debridement is the premise of whether it could be completely debridement. This article systematically reviewed the application of different imaging techniques in evaluating the scope of chronic osteomyelitis infection, and discusses its future development trend. Although traditional plain X-ray film could preliminarily indicate osteomyelitis, it is difficult to determine the infection scope. CT scan has the function of accurate anatomic localization, which is important for preoperative assessment of the scope of bone infection, but the recognition of soft tissue information is limited. MRI, with its high sensitivity, clearly distinguishes between infected bone and soft tissue, which plays an important role in the evaluation of soft tissue infection, but may overestimate the extent of bone infection. Nuclide techniques such as 18F-FDG PET/CT and SPECT/CT show great potential for accurately assessing the extent of infection before surgery. In the future, by optimizing the combination of different imaging technologies, combining clinical symptoms, intraoperative conditions and pathological results, and developing an image analysis platform based on artificial intelligence, it will be able to more accurately assess the scope of infection, provide more effective and personalized treatment plans for patients with chronic osteomyelitis, enhance treatment effects, and significantly improve quality of life of patients.
Humans ; Osteomyelitis/diagnosis* ; Chronic Disease ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed

Objective To investigate the weight loss efficacy and mechanisms of oligopeptide-herbal medicine composite,and to provide new approaches for obesity treatment.Methods Twenty-three SPF female SD rats were randomly divided into control group(n=3)and modeling group(n=20).The control group was fed an ordinary diet for 6 consecutive weeks,and the modeling group was fed a high-fat diet for 6 consecutive weeks to establish a simple obesity rat model.After successful modeling,the modeling group was randomly divided into model group(n=10)and treatment group(n=10).The treatment group started anoint-and-massage therapy with oligopeptide-herbal medicine composite(3 g per rat per time,once a day,20 min each time),which was recorded as day 1.The control group and model group were not treated with oligopeptide-herbal medicine composite but received the same massage,and continued to be fed ordinary feed and high-fat feed respectively.Ten rats in the model group and ten in the treatment group were each divided into 3 groups,with 3,3,and 4 rats in each group.On days 3,6,and 9 after treatment,the rats in the three groups were weighed and cardiac blood collection was performed after isoflurane respiratory anesthesia.After euthanasia by cardiac bloodletting,abdominal subcutaneous adipose tissue(aSAT)and perirenal white adipose tissue(pWAT)samples were collected and weighed.Serum triglycerides(TG)and high-density lipoprotein cholesterol(HDL-C)levels were measured.Image J software was used to measure aSAT thickness and the diameter and area of perirenal white adipocytes and abdominal subcutaneous adipocytes.Immunofluorescence technique was used to observe the number of telocytes(TCs),cell junctions and exosomes per unit area of aSAT.Transmission electron microscopy was used to measure the length of telopodes(Tps)of dermal and subcutaneous TCs in abdominal skin,and to observe the distribution of exosome vesicles,rough endoplasmic reticulum,mitochondria,and cell junctions.Results Compared with the control group,the body weight of rats in the modeling group increased significantly(P＜0.05).Compared with the control group,rats in the model group showed a significant increase in serum TG level,a significant decrease in HDL-C level,and a significant increase in pWAT mass(all P＜0.05).Compared with the model group,the treatment group showed a significantly increased rate of body weight reduction,significantly decreased pWAT mass,significantly decreased serum TG level,and significantly increased HDL-C level(all P＜0.05).Compared with the model group,the treatment group showed significant reductions in aSAT thickness,as well as cell diameter and area in both aSAT and pWAT(all P＜0.05).Compared with the model group,the treatment group showed significantly increased number of TCs per unit area of aSAT,number of exosomes from TCs in aSAT,and Tps length(all P＜0.05).The treatment group showed an increasing trend in the numbers of mitochondria,rough endoplasmic reticulum,and cell junctions in TCs.Conclusion Oligopeptide-herbal medicine composite applied via anoint-and-massage therapy effectively improves obesity-related symptoms such as dyslipidemia and fat accumulation in obese rats by regulating TCs and their intercellular communication.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Objective To investigate the weight loss efficacy and mechanisms of oligopeptide-herbal medicine composite,and to provide new approaches for obesity treatment.Methods Twenty-three SPF female SD rats were randomly divided into control group(n=3)and modeling group(n=20).The control group was fed an ordinary diet for 6 consecutive weeks,and the modeling group was fed a high-fat diet for 6 consecutive weeks to establish a simple obesity rat model.After successful modeling,the modeling group was randomly divided into model group(n=10)and treatment group(n=10).The treatment group started anoint-and-massage therapy with oligopeptide-herbal medicine composite(3 g per rat per time,once a day,20 min each time),which was recorded as day 1.The control group and model group were not treated with oligopeptide-herbal medicine composite but received the same massage,and continued to be fed ordinary feed and high-fat feed respectively.Ten rats in the model group and ten in the treatment group were each divided into 3 groups,with 3,3,and 4 rats in each group.On days 3,6,and 9 after treatment,the rats in the three groups were weighed and cardiac blood collection was performed after isoflurane respiratory anesthesia.After euthanasia by cardiac bloodletting,abdominal subcutaneous adipose tissue(aSAT)and perirenal white adipose tissue(pWAT)samples were collected and weighed.Serum triglycerides(TG)and high-density lipoprotein cholesterol(HDL-C)levels were measured.Image J software was used to measure aSAT thickness and the diameter and area of perirenal white adipocytes and abdominal subcutaneous adipocytes.Immunofluorescence technique was used to observe the number of telocytes(TCs),cell junctions and exosomes per unit area of aSAT.Transmission electron microscopy was used to measure the length of telopodes(Tps)of dermal and subcutaneous TCs in abdominal skin,and to observe the distribution of exosome vesicles,rough endoplasmic reticulum,mitochondria,and cell junctions.Results Compared with the control group,the body weight of rats in the modeling group increased significantly(P＜0.05).Compared with the control group,rats in the model group showed a significant increase in serum TG level,a significant decrease in HDL-C level,and a significant increase in pWAT mass(all P＜0.05).Compared with the model group,the treatment group showed a significantly increased rate of body weight reduction,significantly decreased pWAT mass,significantly decreased serum TG level,and significantly increased HDL-C level(all P＜0.05).Compared with the model group,the treatment group showed significant reductions in aSAT thickness,as well as cell diameter and area in both aSAT and pWAT(all P＜0.05).Compared with the model group,the treatment group showed significantly increased number of TCs per unit area of aSAT,number of exosomes from TCs in aSAT,and Tps length(all P＜0.05).The treatment group showed an increasing trend in the numbers of mitochondria,rough endoplasmic reticulum,and cell junctions in TCs.Conclusion Oligopeptide-herbal medicine composite applied via anoint-and-massage therapy effectively improves obesity-related symptoms such as dyslipidemia and fat accumulation in obese rats by regulating TCs and their intercellular communication.

OBJECTIVE To establish and verify the risk prediction models for postoperative multidrug-resistant or-ganisms(MDROs)infections in the liver transplantation patients based on the machine learning algorithms so as to provide bases for identification of the population at high risk of postoperative MDROs infections.METHODS The liver transplantation patients who were retrospectively collected from intensive care Ⅳ database(MIMIC-Ⅳ)and eICU collaborative research database(eICU)were recruited as the research subjects,meanwhile,the patients who underwent liver transplantation in the First Hospital of Shanxi Medical University from Jan.2021 to Jul.2024 were assigned as the external verification group.The variables were selected by Lasso regression,and the models were established based on 7 types of machine learning algorithms such as extreme gradient boosting algorithm and random forest.The predictive performances of the models were evaluated by comparing the areas under receiver operating characteristic(ROC)curves and the accuracy,the characteristic variables were interpreted by Shapley additive explanations(SHAP),and the risk prediction calculator was established.RESULTS A total of 637 pa-tients were finally enrolled in the study,and the incidence of postoperative MDROs infections was 35.79％.Total-ly 15 variables were finally selected for construction of the model.The area under the receiver operating character-istic curve of XGBoost model was 0.82 for the internal test set,0.78 for the external test set;the predictive per-formance of XGBoost model was better than that of the rest of 6 models.SHAP algorithm indicated that the top 5 important predictive factors were as follows:hepatic encephalopathy,length of intensive care unit(ICU)stay,albumin,model of end-stage liver disease(MELD)and total length of hospital stay.CONCLUSION The risk pre-diction models that are established based on the machine learning algorithms have remarkable effect on prediction of the postoperative MDROs infections and can accurately identify the liver transplantation patients at high risk of postoperative MDROs infections,which may provide guidance for the identification of high-risk population and the development of prevention and treatment measures for infections.