OBJECTIVE To provide valuable insights for the adjustment of anti-infectious regimens， identification of adverse reactions， and individualized pharmaceutical care in patients with critically severe scrub typhus. METHODS Clinical pharmacists actively participated in the pharmaceutical care process for a patient with severe scrub typhus leading to mixed shock undergoing continuous renal replacement therapy and extracorporeal membrane oxygenation. Initially， the patient received meropenem （1 g， q12 h， ivdrip）， in combination with doxycycline （0.1 g， q12 h， po）， which was later switched to meropenem （1 g， q8 h， ivdrip） along with omacycline （100 mg， qd， ivdrip） due to impaired gastrointestinal function. However， as the patient’s condition progressively deteriorated and the infection became uncontrolled， the clinical pharmacists recommended that the clinicians adjust the anti-infective regimen to meropenem （2 g， q8 h， ivdrip） combined with tigecycline （100 mg for first dose； 50 mg， q12 h for maintenance； ivdrip）. The clinicians followed the advice of the clinical pharmacists. After treatment， the patient’s symptoms exhibited significant improvement， accompanied by a notable decrease in inflammatory markers， indicating that the infection had been successfully controlled. However， due to continuously increasing bilirubin levels， in order to reduce the risk of drug-induced liver injury， the clinicians changed tigecycline to azithromycin （0.5 g， qd， ivdrip） following the recommendation of the clinical pharmacists. RESULTS Ultimately， metagenomic next-generation sequencing of the bronchoalveolar lavage fluid and blood specimens indicated that Orientia tsutsugamushi had been completely eradicated in the patient. CONCLUSIONS Tigecycline may be a viable therapeutic choice for patients with severe scrub typhus. In the context of critically ill patients with scrub typhus， combining tigecycline with azithromycin might potentially enhance the efficacy in eliminating Orientia tsutsugamushi.

Objective To report the diagnosis of a canine distemper virus outbreak among a colony of cynomolgus monkeys at an experimental monkey farm in 2019. MethodsA total of 46 samples were collected from 21 diseased cynomolgus monkeys (exhibiting symptoms such as facial rash, skin scurf, runny nose, and diarrhea) and from one deceased monkey at an experimental monkey breeding farm in South China in late 2019, including serum, skin rash swabs, and anticoagulated whole blood, liver, lung, and skin tissues were submitted for testing. All submitted samples were tested for canine distemper virus gene fragments using real-time quantitative PCR, while immunohistochemical staining was performed to detect canine distemper virus nucleoprotein in lung tissues. The skin tissue of the deceased monkey was ground and sieved. The filtrate was inoculated into a monolayer MDCK cell line for virus isolation. Then, whole-genome sequencing was performed to identify the isolated virus. The Clustal Omega tool was used to align and analyze the homology of different Asian canine distemper virus isolates. A phylogenetic tree was constructed, followed by genetic evolutionary analysis. ResultsClinical retrospective analysis revealed that the diseased cynomolgus monkeys exhibited symptoms similar to those observed in cynomolgus monkeys infected with measles virus. Necropsy findings showed red lesions in the lungs and significant hemorrhage in the colonic mucosa. Real-time quantitative PCR detected canine distemper virus nucleic acid in the serum, skin rash swabs of the infected monkeys, and various tissue samples of the deceased monkey, all of which tested positive. Calculation based on the standard curve formula indicated the viral load was highest in the skin tissue. Immunohistochemical staining of the deceased monkey's lung tissue demonstrated aggregation of CDV nucleoprotein in alveolar epithelial cells, bronchi, and bronchioles. A CDV strain was isolated from the skin tissue of the deceased monkey. Phylogenetic analysis indicated that this strain shares the closest relationship (98.86%) with the Asian-1 type canine distemper virus strain CDV/dog/HCM/33/140816, previously identified in dogs in Vietnam. ConclusionBased on comprehensive analysis of clinical symptoms, nucleic acid detection, viral protein immunohistochemistry, and whole-genome sequencing results, the diagnosis confirms that the cynomolgus monkeys in this facility are infected with canine distemper virus. It is recommended to include canine distemper virus as a routine surveillance target in captive monkey populations. Additionally, this study provides a foundation for further research on the molecular biological characteristics of canine distemper virus.

Objective To report the diagnosis of a canine distemper virus outbreak among a colony of cynomolgus monkeys at an experimental monkey farm in 2019. MethodsA total of 46 samples were collected from 21 diseased cynomolgus monkeys (exhibiting symptoms such as facial rash, skin scurf, runny nose, and diarrhea) and from one deceased monkey at an experimental monkey breeding farm in South China in late 2019, including serum, skin rash swabs, and anticoagulated whole blood, liver, lung, and skin tissues were submitted for testing. All submitted samples were tested for canine distemper virus gene fragments using real-time quantitative PCR, while immunohistochemical staining was performed to detect canine distemper virus nucleoprotein in lung tissues. The skin tissue of the deceased monkey was ground and sieved. The filtrate was inoculated into a monolayer MDCK cell line for virus isolation. Then, whole-genome sequencing was performed to identify the isolated virus. The Clustal Omega tool was used to align and analyze the homology of different Asian canine distemper virus isolates. A phylogenetic tree was constructed, followed by genetic evolutionary analysis. ResultsClinical retrospective analysis revealed that the diseased cynomolgus monkeys exhibited symptoms similar to those observed in cynomolgus monkeys infected with measles virus. Necropsy findings showed red lesions in the lungs and significant hemorrhage in the colonic mucosa. Real-time quantitative PCR detected canine distemper virus nucleic acid in the serum, skin rash swabs of the infected monkeys, and various tissue samples of the deceased monkey, all of which tested positive. Calculation based on the standard curve formula indicated the viral load was highest in the skin tissue. Immunohistochemical staining of the deceased monkey's lung tissue demonstrated aggregation of CDV nucleoprotein in alveolar epithelial cells, bronchi, and bronchioles. A CDV strain was isolated from the skin tissue of the deceased monkey. Phylogenetic analysis indicated that this strain shares the closest relationship (98.86%) with the Asian-1 type canine distemper virus strain CDV/dog/HCM/33/140816, previously identified in dogs in Vietnam. ConclusionBased on comprehensive analysis of clinical symptoms, nucleic acid detection, viral protein immunohistochemistry, and whole-genome sequencing results, the diagnosis confirms that the cynomolgus monkeys in this facility are infected with canine distemper virus. It is recommended to include canine distemper virus as a routine surveillance target in captive monkey populations. Additionally, this study provides a foundation for further research on the molecular biological characteristics of canine distemper virus.

OBJECTIVE To analyze the influencing factors of voriconazole trough concentration and adverse drug reactions （ADR） in renal transplant recipients. METHODS Data from inpatients who received voriconazole and therapeutic drug monitoring in our hospital between January 2022 and August 2023 were retrospectively analyzed. Patients were divided into renal transplant group and non-renal transplant group based on transplantation status. A 1∶1 propensity score matching （PSM） method was used to balance differences in baselines between the two groups. Voriconazole trough concentrations， target attainment rate， clinical efficacy， and ADR were compared between the two groups. Multiple linear regression （backward） was used to analyze the factors influencing voriconazole trough concentrations in the renal transplant group. Univariate analysis and binary Logistic regression were used to identify independent risk factors for ADR in the renal transplant group. RESULTS After PSM， 48 patients were included in each group. There were no statistically significant differences in the mean voriconazole trough concentration， target attainment rate or efficacy rate between the two groups （P＞0.05）. The total incidence of ADR was significantly higher in the renal transplant group than in the non-renal transplant group （P＜0.05）. Multiple linear regression analysis showed that age， average daily dose， pulmonary infection， total bilirubin during medication， day-1 loading dose， use of the original drug， concomitant immunosuppressant use， and the occurrence of ADR were factors influencing voriconazole trough concentration in renal transplant patients （P＜0.05）. Binary Logistic regression analysis showed that abnormal direct bilirubin during medication [OR＝7.747， 95%CI （1.334， 45.005）， P＝0.023] was an independent risk factor for ADR in renal transplant patients receiving voriconazole. CONCLUSIONS Age， average daily dose， pulmonary infection， use of the original drug， day-1 loading dose， total bilirubin during medication， concomitant immunosuppressant use， and the occurrence of ADR are the factors influencing voriconazole trough concentration in renal transplant patients. Furthermore， patients with abnormal direct bilirubin during medication are more susceptible to ADR.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

OBJECTIVE: To investigate the effect of manual acupuncture manipulations (MAMs) on subcutaneous muscle tissue, by developing quantitative models of "lifting and thrusting" and "twisting and rotating", based on machine learning techniques. METHODS: A depth camera was used to capture the acupuncture operator's hand movements during "lifting and thrusting" and "twisting and rotating" of needle. Simultaneously, the ultrasound imaging was employed to record the muscle tissue responses of the participants. Amplitude and angular features were extracted from the movement data of operators, and muscle fascicle slope features were derived from the data of ultrasound images. The dynamic time warping barycenter averaging algorithm was adopted to align the dual-source data. Various machine learning techniques were applied to build quantitative models, and the performance of each model was compared. The most optimal model was further analyzed for its interpretability. RESULTS: Among the quantitative models built for the two types of MAMs, the random forest model demonstrated the best performance. For the quantitative model of the "lifting and thrusting" technique, the coefficient of determination (R²) was 0.825. For the "twisting and rotating" technique, R² reached 0.872. CONCLUSION Machine learning can be used to effectively develop the models and quantify the effects of MAMs on subcutaneous muscle tissue. It provides a new perspective to understand the mechanism of acupuncture therapy and lays a foundation for optimizing acupuncture technology and designing personalized treatment regimen in the future.
Humans ; Acupuncture Therapy/methods* ; Machine Learning ; Male ; Adult ; Female ; Subcutaneous Tissue/diagnostic imaging* ; Young Adult

Retrieving keyframes most relevant to text from small intestine videos with given labels can efficiently and accurately locate pathological regions. However, training directly on raw video data is extremely slow, while learning visual representations from image-text datasets leads to computational inconsistency. To tackle this challenge, a small bowel video keyframe retrieval based on multi-modal contrastive learning (KRCL) is proposed. This framework fully utilizes textual information from video category labels to learn video features closely related to text, while modeling temporal information within a pretrained image-text model. It transfers knowledge learned from image-text multimodal models to the video domain, enabling interaction among medical videos, images, and text data. Experimental results on the hyper-spectral and Kvasir dataset for gastrointestinal disease detection (Hyper-Kvasir) and the Microsoft Research video-to-text (MSR-VTT) retrieval dataset demonstrate the effectiveness and robustness of KRCL, with the proposed method achieving state-of-the-art performance across nearly all evaluation metrics.
Humans ; Video Recording ; Intestine, Small/diagnostic imaging* ; Machine Learning ; Image Processing, Computer-Assisted/methods* ; Algorithms

AIM: To investigate the effect of adalimumab combined with dexamethasone intravitreal implant in the treatment of refractory non-infectious uveitis macular edema(UME).METHODS: A total of 92 cases(131 eyes)of refractory non-infectious UME patients admitted to our hospital from January 2020 to January 2022 were selected and randomly divided into control group, with 46 cases(63 eyes)treated with dexamethasone intravitreal implant and observation group, with 46 cases(68 eyes)treated with adalimumab subcutaneous injection combined with dexamethasone intravitreal implant. The best corrected visual acuity(BCVA), central retinal thickness(CRT), vitreous opacity and Th17/Treg cytokines were measured before and after treatment, and the occurrence of adverse reactions was recorded.RESULTS: Totally 3 cases(4 eyes)were lost to follow-up. After treatment for 1, 3, 6 and 12 mo, BCVA was improved in both groups compared with that before treatment, and CRT, vitreous opacity score, serum interleukin(IL)-17 and IL-22 levels were decreased compared with those before treatment, and serum transforming growth factor-β(TGF-β)and IL-10 levels were increased compared with those before treatment. BCVA in the observation group was better than that in the control group, and CRT, vitreous opacity score, serum IL-17 and IL-22 levels were lower than those in the control group, and serum TGF-β and IL-10 levels were higher than those in the control group(all P<0.05). During treatment and follow-up, no serious adverse reactions occurred in both groups.CONCLUSION: Adalimumab combined with dexamethasone intravitreal implants in the treatment of refractory non-infectious UME can significantly subside the macular edema, reduce vitreous opacity and improve visual acuity.

INTRODUCTION: Ultrasonography (US) is the current standard of care for imaging surveillance in patients at risk of hepatocellular carcinoma (HCC). Magnetic resonance imaging (MRI) has been explored as an alternative, given the higher sensitivity of MRI, although this comes at a higher cost. We performed a cost-effective analysis comparing US and dual-sequence non-contrast-enhanced MRI (NCEMRI) for HCC surveillance in the local setting. METHODS: Cost-effectiveness analysis of no surveillance, US surveillance and NCEMRI surveillance was performed using Markov modelling and microsimulation. At-risk patient cohort was simulated and followed up for 40 years to estimate the patients' disease status, direct medical costs and effectiveness. Quality-adjusted life years (QALYs) and incremental cost-effectiveness ratio were calculated. RESULTS: Exactly 482,000 patients with an average age of 40 years were simulated and followed up for 40 years. The average total costs and QALYs for the three scenarios - no surveillance, US surveillance and NCEMRI surveillance - were SGD 1,193/7.460 QALYs, SGD 8,099/11.195 QALYs and SGD 9,720/11.366 QALYs, respectively. CONCLUSION Despite NCEMRI having a superior diagnostic accuracy, it is a less cost-effective strategy than US for HCC surveillance in the general at-risk population. Future local cost-effectiveness analyses should include stratifying surveillance methods with a variety of imaging techniques (US, NCEMRI, contrast-enhanced MRI) based on patients' risk profiles.
Humans ; Adult ; Carcinoma, Hepatocellular/diagnostic imaging* ; Liver Neoplasms/diagnostic imaging* ; Cost-Effectiveness Analysis ; Cost-Benefit Analysis ; Quality-Adjusted Life Years ; Magnetic Resonance Imaging/methods*

Objective To investigate the factors that lead to diffuse chorioretinal atrophy(DCA)in patients with high myopia(HM)and to establish a prediction model.Methods In this retrospective case-control study,a total of 169 HM patients(338 eyes)admitted to the Department of Ophthalmology,Harbin 242 Hospital from October 2018 to October 2022 were selected.All patients underwent comprehensive ophthalmic examination at the time of inclusion.The incidence of DCA was evaluated according to the International Photographic Classification and Grading System for myopic maculopa-thy,and the risk factors of DCA in HM patients were analyzed by multivariate Logistic regression.The predictive model of DCA in HM patients was established by the receiver operating characteristic curve(ROC)based on risk factors,and the calibration degree of the predictive model was tested by Hosmer-Lemeshow(H-L).Results Among the 169 patients,34 patients were divided into the DCA group,and 135 patients were divided into the non-DCA group;there were statistically significant differences in age and gender distribution between the two groups(both P＜0.05).The axial length(AL),pat-tern standard deviation(PSD),positive rate of carbonic anhydrase 2(CAII)antibody in the DCA group were higher than those in the non-DCA group,while the best corrected visual acuity(BCVA),mean defect(MD)of the visual field,spheri-cal equivalent(SE),deep retinal microvessel density(MVD)and serum 25-hydroxyvitamin D[25(OH)D]were lower than those in the non-DCA group(all P＜0.05).Older age,longer AL and positive CAII antibody were the risk factors for DCA in HM patients(all P＜0.05),while greater deep retinal MVD and higher 25(OH)D were the protective factors(both P＜0.05).ROC analysis showed that the area under the curve of the prediction model for DCA in HM patients was 0.864(95％CI:0.802-0.911,P＜0.001),and the sensitivity and specificity were 85.29％and 88.15％,respectively.According to the H-L test,the prediction model for DCA in HM patients was relatively consistent with the actual results(P＞0.05).Con-clusion The occurrence of DCA in HM patients is affected by age,AL,CAII antibody,deep retinal MVD and 25(OH)D level,and a prediction model established based on the above factors can predict the risk of DCA well.