This study aims to explore the pharmacodynamic material basis of Jinbei Oral Liquid(JBOL) against idiopathic pulmonary fibrosis(IPF) based on serum pharmacochemistry and network pharmacology. The ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technology was employed to analyze and identify the components absorbed into rat blood after oral administration of JBOL. Combined with network pharmacology, the study explored the pharmacodynamic material basis and potential mechanism of JBOL against IPF through protein-protein interaction(PPI) network construction, "component-target-pathway" analysis, Gene Ontology(GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. First, a total of 114 compounds were rapidly identified in JBOL extract according to the exact relative molecular mass, fragment ions, and other information of the compounds with the use of reference substances and a self-built compound database. Second, on this basis, 70 prototype components in blood were recognized by comparing blank serum with drug-containing serum samples, including 28 flavonoids, 25 organic acids, 4 saponins, 4 alkaloids, and 9 others. Finally, using these components absorbed into blood as candidates, the study obtained 212 potential targets of JBOL against IPF. The anti-IPF mechanism might involve the action of active ingredients such as glycyrrhetinic acid, cryptotanshinone, salvianolic acid B, and forsythoside A on core targets like AKT1, TNF, and ALB and thereby the regulation of multiple signaling pathways including PI3K/AKT, HIF-1, and TNF. In conclusion, JBOL exerts the anti-IPF effect through multiple components, targets, and pathways. The results would provide a reference for further study on pharmacodynamic material basis and pharmacological mechanism of JBOL.
Drugs, Chinese Herbal/pharmacokinetics* ; Animals ; Tandem Mass Spectrometry ; Network Pharmacology ; Rats ; Chromatography, High Pressure Liquid ; Rats, Sprague-Dawley ; Male ; Idiopathic Pulmonary Fibrosis/metabolism* ; Humans ; Administration, Oral ; Protein Interaction Maps/drug effects* ; Signal Transduction/drug effects*

Osteoarthritis （OA） and stroke are common clinical diseases that reduce patients' quality of life and place a burden on families and society. Ruyi Zhenbaowan， a classic prescription in Tibetan medicine， have the functions of clearing heat， awakening the brain and opening orifices， relaxing tendons and promoting meridian circulation， and eliminating yellow water. Clinically， they are used to treat osteoarthritis， post-stroke sequelae， neuropathic pain， and other related conditions. Modern pharmacological studies have demonstrated their anti-inflammatory， analgesic， and nerve-repairing effects. However， current research remains insufficient regarding the appropriate indications， timing， and efficacy of this medicine in treating relevant diseases. To enhance clinicians' understanding of this medicine and promote its standardized and rational clinical use， a panel of national experts， including clinical specialists， Tibetan medicine practitioners， pharmacologists， and methodologists， formulated this consensus based on clinical experience and evidence-based practice. The Cochrane systematic review framework， the Grading of Recommendations Assessment， Development and Evaluation （GRADE） system， and the nominal group method were employed to generate seven graded recommendations and 19 consensus-based suggestions. These recommendations clearly define the key points in the clinical application of Ruyi Zhenbaowan， including therapeutic indications， dosage and administration， treatment duration， and medication safety. The consensus specifically addresses the clinical efficacy， appropriate timing of administration， dosage strategies， treatment cycles， and combination medication strategies for treating osteoarthritis and stroke and provides an overview of safety considerations. The aim is to provide standardized guidance for hospitals and healthcare institutions nationwide to ensure the rational application of Ruyi Zhenbaowan in the treatment of osteoarthritis and stroke， reduce medication-related risks， and further leverage its clinical advantages. This consensus has been approved and issued by the China Association of Chinese Medicine， with the standard number GS/CACM 369-2024.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

China is facing the double burden of high incidence of lung cancer and tuberculosis epidemic. Lung cancer combined with tuberculosis has a high incidence and complexity in clinical practice. High-risk groups include immunocompromised people, long-term smokers and people with a history of tuberculosis. The coexistence of the two diseases not only increases the difficulty of diagnosis and treatment decision-making, but also increases the risk of treatment-related adverse reactions and drug interactions. The guideline was developed by Committee of Integrated Rehabilitation for Lung Cancer, Chinese Anti-Cancer Association; Chinese and Western Integrated Lung Cancer Committee of Chinese Anti-Cancer Association; Society of Tuberculosis, Chinese Medical Association, aiming to standardize the diagnosis and treatment of lung cancer complicated with pulmonary tuberculosis. The guideline emphasizes the core position of combined diagnosis of multimodal imaging, etiology and pathology. It is proposed that anti-tuberculosis and anti-tumor treatment should be coordinated under the framework of multidisciplinary team, and drug interactions and timing optimization should be paid attention to. For surgical treatment, minimally invasive resection combined with systematic lymph node dissection is recommended after infection control. Systemic therapy requires individualized risk stratification and dynamic monitoring of efficacy and adverse reactions. Based on evidence-based medicine and Chinese clinical practice, combined with the accessibility of drugs and technologies, this guideline proposes a whole-process management pathway covering screening, diagnosis, treatment and follow-up, in order to improve the prognosis and quality of life of patients.

Nitrofurantoin(NFT)is a nitrofuran antibiotic commonly used as a veterinary drug to treat bacterial infections in animals.However,due to the low solubility and bioaccumulation properties,NFT is prone to leave excessive residues in animal-derived foods and water systems,posing serious threats to human health and ecosystems.Therefore,there is an urgent need to develop an efficient and rapid detection method for NFT.In this work,nitrogen-doped carbon nanomaterials with unique bowl-like structures(N-CNBs)were synthesized via a hydrothermal-carbonization method.The morphology,surface structure,and specific surface area of N-CNBs were characterized using transmission electron microscopy(TEM),scanning electron microscopy(SEM),and X-ray photoelectron spectroscopy(XPS).The N-CNB modified glassy carbon electrode(N-CNB/GCE)was prepared,and the electrochemical test revealed that the N-CNB/GCE exhibited higher conductivity and larger electrochemical active surface area compared to bare GCE and nitrogen-doped hollow carbon nanosphere-modified electrode(N-HCNS/GCE).Additionally,the N-CNB/GCE demonstrated superior electrocatalytic activity toward NFT.An NFT electrochemical sensor was constructed based on N-CNB/GCE.The detection conditions of the sensor were optimized,and differential pulse voltammetry(DPV)was employed for NFT detection under optimal experimental conditions.The established NFT electrochemical sensor had a wide linear range of 0.4-500 μmol/L,a low detection limit(S/N=3)of 0.015 μmol/L and high selectivity,with excellent stability and reproducibility.The practical feasibility of this sensor was confirmed by analysis of NFT in milk and tap water samples,with spiked recoveries ranging from 94.2%to 108.9%.

Objective To explore the effect of life reconstruction training on anxiety and depression among individuals with chronic spinal cord injury(SCI)and their caregivers,and to analyze the influencing factors.Methods A total of 216 SCI patients and 79 caregivers who participated in life reconstruction training were recruited from the Hope House for SCI individuals in Shanghai Yangzhi Rehabilitation Hospital from May,2017 to Octo-ber,2019.They were assessed with Self-Rating Anxiety Scale(SAS)and Self-Rating Depression Scale(SDS)be-fore and after intervention.Results After intervention,the scores of SAS and SDS decreased(P<0.05)in both SCI patients and their caregivers.SAS scores were more likely to reduce in SCI patients who suffered anxiety at admission(OR=2.315,95%CI 1.328 to 4.033,P=0.003)and their caregivers(OR=3.632,95%CI 1.270 to 10.390,P=0.016),as well as non-agricultural-registered SCI patients(OR=1.908,95%CI 1.074 to 3.391,P=0.028).Being unmarried,having an injury duration≥21 years,injury due to disease,and having depression at admission significantly promoted the reduction in SDS scores among SCI patients(P<0.05).Caregivers with a junior-high-school education or less were more likely to experience reductions in scores of SAS and SDS compared with those with higher education(P<0.05).Caregivers with five to 15 years of caregiving experience achieved more anxiety reduction(OR=7.155,95%CI 1.806 to 28.342,P=0.005).Conclusion Life reconstruction training is effective on anxiety and depression among individuals with chronic SCI and their caregivers.It is recommended to prioritize anxiety interventions for patients with rural household registra-tion in China,along with depression management for the married/divorced/widowed individuals,with<21 years since injury,and trauma-induced lesions.For caregivers,it is needed to focus to anxiety and depression in better-educated individuals,as well as anxiety in those with either<5 or≥15 years of caregiving experience.

Objective To explore the effect of life reconstruction training on anxiety and depression among individuals with chronic spinal cord injury(SCI)and their caregivers,and to analyze the influencing factors.Methods A total of 216 SCI patients and 79 caregivers who participated in life reconstruction training were recruited from the Hope House for SCI individuals in Shanghai Yangzhi Rehabilitation Hospital from May,2017 to Octo-ber,2019.They were assessed with Self-Rating Anxiety Scale(SAS)and Self-Rating Depression Scale(SDS)be-fore and after intervention.Results After intervention,the scores of SAS and SDS decreased(P<0.05)in both SCI patients and their caregivers.SAS scores were more likely to reduce in SCI patients who suffered anxiety at admission(OR=2.315,95%CI 1.328 to 4.033,P=0.003)and their caregivers(OR=3.632,95%CI 1.270 to 10.390,P=0.016),as well as non-agricultural-registered SCI patients(OR=1.908,95%CI 1.074 to 3.391,P=0.028).Being unmarried,having an injury duration≥21 years,injury due to disease,and having depression at admission significantly promoted the reduction in SDS scores among SCI patients(P<0.05).Caregivers with a junior-high-school education or less were more likely to experience reductions in scores of SAS and SDS compared with those with higher education(P<0.05).Caregivers with five to 15 years of caregiving experience achieved more anxiety reduction(OR=7.155,95%CI 1.806 to 28.342,P=0.005).Conclusion Life reconstruction training is effective on anxiety and depression among individuals with chronic SCI and their caregivers.It is recommended to prioritize anxiety interventions for patients with rural household registra-tion in China,along with depression management for the married/divorced/widowed individuals,with<21 years since injury,and trauma-induced lesions.For caregivers,it is needed to focus to anxiety and depression in better-educated individuals,as well as anxiety in those with either<5 or≥15 years of caregiving experience.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.