ObjectiveBased on the theory of "spleen governing transportation and transformation"， this study investigates the efficacy of Atractylodis Macrocephalae Rhizoma processed with Aurantii Fructus Immaturus juice（AMR-AFI） in improving slow-transit constipation（STC）， as well as the synergistic regulatory mechanism involving the microbiota-metabolism axis， thereby elucidating the scientific basis of its processing theory. MethodsAnimals were randomly divided into the control group， model group， positive drug（mosapride） group（3 mg·kg^-1）， and low-， medium-， and high-dose groups of AMR-AFI（3.9， 7.8， 15.6 g·kg^-1）. Except for the control group， the remaining five groups were induced with STC using loperamide hydrochloride. Following modeling， interventions were administered. All groups received continuous administration for 15 d， during which fecal samples， colon tissue， and serum were collected. Constipation improvement was assessed by measuring fecal moisture content and small intestinal propulsion rate， histological morphology of colonic tissue was observed via hematoxylin-eosin（HE） staining， and the levels of interleukin（IL）-6， tumor necrosis factor（TNF）-α， and IL-2 in serum were detected using enzyme-linked immunosorbent assay（ELISA）. Furthermore， the microbial community structure in mouse feces was analyzed by 16S rRNA sequencing， while transcriptomic sequencing was employed to screen differentially expressed genes in colonic tissue， followed by gene ontology（GO） and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analyses. Finally， Spearman correlation analysis was conducted to explore the association between differential microbiota and differential genes. ResultsCompared with the control group， the intestinal propulsion rate and fecal moisture content in the model group were significantly decreased（P<0.01）， while serum levels of IL-6， TNF-α， and IL-2 were significantly elevated（P<0.01）. HE staining showed damage and shedding of colonic mucosal epithelial cells， along with a reduction in goblet cells in the model group. In comparison with the model group， all treatment groups improved the pathological state of the colonic mucosa to varying degrees and reduced serum levels of IL-6， TNF-α， and IL-2（P<0.01）. Among these， the high-dose group of AMR-AFI significantly increased the intestinal propulsion rate and fecal moisture content of rats（P<0.05， P<0.01）. Further transcriptomic analysis revealed that a total of 104 differentially expressed genes were identified from comparisons between the model group and the control group， as well as between the model group and the high-dose group of AMR-AFI. These genes were mainly enriched in pathways closely related to STC pathogenesis， such as arachidonic acid metabolism and aldosterone-regulated sodium reabsorption. 16S rRNA sequencing results indicated that AMR-AFI reversed the structural imbalance of the gut microbiota in model mice， increased species richness， downregulated the relative abundance of pro-inflammatory bacteria such as Parasutterella， and enriched beneficial and butyrate-producing bacteria， including Lachnospiraceae_NK4A136_group， Ruminococcaceae， and Lachnospiraceae. Spearman correlation analysis further showed that the beneficial bacteria enriched in the AMR-AFI group were negatively correlated with genes involved in the arachidonic acid metabolic pathway and positively correlated with genes in the aldosterone-regulated sodium reabsorption pathway. In contrast， pro-inflammatory bacteria in the model group exhibited the opposite correlation trends. ConclusionAMR-AFI can effectively exert synergistic therapeutic effects on STC by regulating intestinal microbiota， arachidonic acid-mediated inflammatory metabolism， and aldosterone-regulated water-salt balance pathways.

ObjectiveBased on the theory of "spleen governing transportation and transformation"， this study investigates the efficacy of Atractylodis Macrocephalae Rhizoma processed with Aurantii Fructus Immaturus juice（AMR-AFI） in improving slow-transit constipation（STC）， as well as the synergistic regulatory mechanism involving the microbiota-metabolism axis， thereby elucidating the scientific basis of its processing theory. MethodsAnimals were randomly divided into the control group， model group， positive drug（mosapride） group（3 mg·kg^-1）， and low-， medium-， and high-dose groups of AMR-AFI（3.9， 7.8， 15.6 g·kg^-1）. Except for the control group， the remaining five groups were induced with STC using loperamide hydrochloride. Following modeling， interventions were administered. All groups received continuous administration for 15 d， during which fecal samples， colon tissue， and serum were collected. Constipation improvement was assessed by measuring fecal moisture content and small intestinal propulsion rate， histological morphology of colonic tissue was observed via hematoxylin-eosin（HE） staining， and the levels of interleukin（IL）-6， tumor necrosis factor（TNF）-α， and IL-2 in serum were detected using enzyme-linked immunosorbent assay（ELISA）. Furthermore， the microbial community structure in mouse feces was analyzed by 16S rRNA sequencing， while transcriptomic sequencing was employed to screen differentially expressed genes in colonic tissue， followed by gene ontology（GO） and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analyses. Finally， Spearman correlation analysis was conducted to explore the association between differential microbiota and differential genes. ResultsCompared with the control group， the intestinal propulsion rate and fecal moisture content in the model group were significantly decreased（P<0.01）， while serum levels of IL-6， TNF-α， and IL-2 were significantly elevated（P<0.01）. HE staining showed damage and shedding of colonic mucosal epithelial cells， along with a reduction in goblet cells in the model group. In comparison with the model group， all treatment groups improved the pathological state of the colonic mucosa to varying degrees and reduced serum levels of IL-6， TNF-α， and IL-2（P<0.01）. Among these， the high-dose group of AMR-AFI significantly increased the intestinal propulsion rate and fecal moisture content of rats（P<0.05， P<0.01）. Further transcriptomic analysis revealed that a total of 104 differentially expressed genes were identified from comparisons between the model group and the control group， as well as between the model group and the high-dose group of AMR-AFI. These genes were mainly enriched in pathways closely related to STC pathogenesis， such as arachidonic acid metabolism and aldosterone-regulated sodium reabsorption. 16S rRNA sequencing results indicated that AMR-AFI reversed the structural imbalance of the gut microbiota in model mice， increased species richness， downregulated the relative abundance of pro-inflammatory bacteria such as Parasutterella， and enriched beneficial and butyrate-producing bacteria， including Lachnospiraceae_NK4A136_group， Ruminococcaceae， and Lachnospiraceae. Spearman correlation analysis further showed that the beneficial bacteria enriched in the AMR-AFI group were negatively correlated with genes involved in the arachidonic acid metabolic pathway and positively correlated with genes in the aldosterone-regulated sodium reabsorption pathway. In contrast， pro-inflammatory bacteria in the model group exhibited the opposite correlation trends. ConclusionAMR-AFI can effectively exert synergistic therapeutic effects on STC by regulating intestinal microbiota， arachidonic acid-mediated inflammatory metabolism， and aldosterone-regulated water-salt balance pathways.

Viruses constitute a significant group of pathogens that have caused numerous fatalities and substantial economic losses in recent years, particularly with the emergence of coronaviruses. While the impact of SARS-CoV-2 appears to be diminishing in daily life, only a limited number of drugs have received approval or emergency use authorization for its treatment. Given the high mutation rate of viral genomes, host-directed agents (HDAs) have emerged as a preferred choice due to their broad applicability and lasting effectiveness. In contrast to direct-acting antivirals (DAAs), HDAs offer several advantages, including broad-spectrum antiviral activities, potential efficacy against future emerging viruses, and a lower likelihood of inducing drug resistance. In our review article, we have synthesized known host-directed antiviral targets that span diverse cellular pathways and mechanisms, shedding light on the intricate interplay between host cells and viruses. Additionally, we have provided a brief overview of the development of HDAs based on these targets. We aim for this comprehensive analysis to offer valuable perspectives and insights that can guide future antiviral research and drug development efforts.

Lumbosacral radiculopathy refers to the pain syndrome caused by inflammation or mechanical compression of the lumbar nerve root, mainly manifested as low back pain, and radiating to the lower limbs in cutaneous mode, which can be accompanied by numbness, paresthesia, tingling, muscle weakness and loss of specific reflexes and other symptoms, which not only bring physical pain and life inconvenience to the patients, but also bring huge economic burden to the social medical care. Selective nerve root block(SNRB), as a safe, effective, low-cost, precise and minimally invasive clinical technique, can accurately intervene in specific nerve roots and quickly relieve pain symptoms by reducing inflammation and improving the surrounding environment of nerves. However, there are still many challenges and controversies in practice, such as precise targeting requirements, drug selection, potential risks and complications, and differences in efficacy among different patient populations. The purpose of this review is to systematically review and analyze the existing research results on SNRB, so as to provide useful reference and guidance for the further development of this field.

Objective:To construct logistic regression, decision tree, and neural network models to predict pressure injury in neurocritically ill patients using machine learning algorithms, and compare the predictive performance of the three models.Methods:The clinical data of 341 neurocritically ill patients who received treatment in the Department of Neurosurgery at The First Affiliated Hospital of Wenzhou Medical University from May 2020 to February 2023 were collected retrospectively. The patients were randomly divided into a training set and a testing set in a 7:3 ratio. Univariate and multivariate analyses were conducted based on the clinical data from the training set. According to the results of the multivariate analysis, logistic regression, decision tree, and neural network models were constructed. The predictive performance of the three models was validated and compared using receiver operating characteristic curve analysis.Results:Among the 341 patients, 35 developed pressure injury (a total of 40 occurrences), with an incidence rate of 10.26%. Multivariate analysis indicated that incontinence ( OR = 47.32, 95% CI: 1.360-1 647.700), decreased albumin levels ( OR = 0.56, 95% CI: 0.360-0.870), increased sensory ability ( OR = 0.00, 95% CI: 0.000-0.190), and increased mobility ( OR = 0.03, 95% CI: 0.000-0.390) were independent risk factors for pressure injury in neurocritically ill patients (all P < 0.05). Based on these independent risk factors, logistic regression, decision tree, and neural network models were constructed. Receiver operating characteristic curve analysis revealed that the area under the curve for the three models was 0.987 (95% CI: 0.941-0.999), 0.945 (95% CI: 0.881-0.980), and 0.908 (95% CI: 0.834-0.956), respectively. These results suggest that all three models exhibited high predictive performance for pressure injury in neurocritically ill patients, with the logistic regression model showing a significantly greater area under the curve than the neural network model. Conclusions:The occurrence of pressure injury in neurocritically ill patients is closely related to incontinence, albumin levels, sensory ability, and mobility. Constructing predictive models using machine learning algorithms can provide valuable insights for the early prevention and management of pressure injury in neurocritically ill patients.

Objective:To explore latent categories of decent work perception among nurses in tuberculosis wards and analyze their influencing factors.Methods:Convenience sampling was used to select tuberculosis ward nurses from 13 general or specialized hospitals in China in July 2024 for the study. General Information Questionnaire, Decent Work Perception Scale (DWPS), Work-Family Support Scale, and Connor-Davidson Resilience Scale were used to survey the tuberculosis ward nurses. Mplus 8.3 software was used for latent profile analysis of decent work perception of nurses in tuberculosis wards. Unordered multicategorical Logistic regression was used to explore the factors influencing the latent categories of decent work perception for nurses in tuberculosis wards.Results:A total of 920 questionnaires were distributed, and 833 valid questionnaires were recovered, with a valid recovery rate of 90.54%. The mean DWPS item score of 833 tuberculosis ward nurses was [3.44 (2.94, 3.88) ]. Decent work perceptions of tuberculosis ward nurses were classified into three latent categories, namely, low decent perception-low occupational recognition type (15.61%, 130/833), medium decent perception-moderate occupational recognition type (50.54%, 421/833), and high decent perception-high occupational recognition type (33.85%, 282/833). Unordered multicategorical Logistic regression analysis revealed that organizational support, psychological resilience, job title, monthly income, hospital class, and number of monthly night shifts were the influencing factors of latent categories of decent work perception among nurses in tuberculosis wards.Conclusions:The decent work perception of nurses in tuberculosis wards is at a medium level. Nursing managers should focus on nurses with low decent perception-low occupational recognition and manage and support nurses according to the characteristics and influencing factors of different categories.

As the global population ages and cancer diagnostic and treatment technologies improve, the number of elderly cancer survivors continues to increase, and their complex care needs challenge the traditional mono-disciplinary care model. This paper explores the dilemmas of implementing a long-term care system and suggestions for future research through a comprehensive overview of the care needs of elderly cancer survivors and the progress of interdisciplinary research, with the aim of providing a theoretical basis and practical reference for improving the long-term care system and enhancing patients' quality of life.

OBJECTIVE To explore the differences in the clinical laboratory test indexes between the patients with two different TCM syndrome types of eczema(dampness-heat infiltration type and non-dampness-heat infiltration type)and observe the distribution and drug resistance rate of pathogens isolated from the skin lesions so as to pro-vide bases for syndrome differentiation and reasonable use of antibiotics.METHODS A total of 180 patients with eczema who were positive for bacterial culture of skin secretions and were treated in Beijing Hospital of Traditional Chinese Medicine from Jan.2021 to Dec.2023 were enrolled in the study and were divided into the dampness-heat infiltration group with 134 cases and the non-dampness-heat infiltration group with 46 cases.The data of clini-cal laboratory test indexes were collected from the two groups of patients,the secretion specimens were sampled from the skin lesion sites,the isolated pathogens were identified by VITEK 2 Compact automatic microorganism analysis system,and the drug susceptibility testing was performed.RESULTS The direct bilirubin level of the dampness-heat infiltration group was(3.99±1.62)umol/L,higher than(3.46±1.12)umol/L of the non-damp-ness-heat infiltration group(P＜0.05),but both were in the normal range;there were no significant differences in other test indexes between the two groups.Totally 180 strains of pathogens were isolated from the 180 patients with eczema,156(86.67％)of which were gram-positive bacteria;Staphylococcus aureus(98 strains),Staphy-lococcus epidermidis(29 strains)and Staphylococcus haemolyticus(15 strains)were the predominant species of the gram-positive bacteria.The gram-negative bacteria accounted for 12.22％(22 strains).The drug resistance rate of the S.aureus strains to penicillin was up to 82.65％,and the isolation rate of methicillin-resistant Staphy-lococcus aureus(MRSA)was 12.24％(12/98);the drug resistance rates of the S.epidermidis strains to penicil-lin and erythromycin were 75.86％,and the drug resistance rate of the S.haemolyticus strains to erythromycin was 100.00％.CONCLUSIONS The gram-positive bacteria(dominated by the S.aureus)are dominant among the pathogens isolated from the skin lesion specimens of the eczema patients and are highly resistant to penicillin and erythromycin.The isolation rate of MRSA is relatuvely low.There is limited clinical significant difference in the direct bilirubin between the two groups.It is necessary to further explore more reliable indexes for syndrome dif-ferentiation.

Objective To establish a classification tree model for non-alcoholic fatty liver disease(NAFLD)among aircrews,screen for influencing factors of NAFLD,so as to provide scientific basis for prevention and intervention decisions for NAFLD.Methods Aircrews who underwent recuperation at a sanatorium from January 2019 to December 2023 were selected as the research objects.Their annual physical examination data were collected and the NAFLD detection rate was calculated.Age,body mass index(BMI),blood pressure,waist circumference,blood routine,biochemistry indexes,and thyroid function were incorporated,and a NAFLD risk model was constructed using classification regression tree method.The predictive performance of the NAFLD classification tree model was evaluated through model misclassification matrix,risk statistics,and receiver operating characteristic curve.Results A total of 4088 aircrews were included in the study,and NAFLD was detected in 380 persons(380/4088,9.30%).The NAFLD model consisted of three layers,and five explanatory variables affecting the onset of NAFLD were extracted,including BMI,triglycerides(TG),high-density lipoprotein cholesterol(HDL-C),alanine aminotransferase(ALT),and total bilirubin(TBIL).BMI was located at the top of the classification tree and was the most important risk factor for NAFLD in aircrews.The area under the curve(AUC)of the model was 0.853.The predictive accuracy of NAFLD was 90.9%,indicating that the model has good accuracy and fitting effect.Conclusion In this study,the detection rate of NAFLD in aircrews was 9.30%.BMI,TG,HDL-C,ALT,and TBIL are risk factors for the onset of NAFLD.NAFLD is mainly related to weight gain and lipid metabolism disorders caused by unhealthy lifestyles.