BACKGROUND:The phosphatidylinositol 3-kinase/protein kinase(PI3K/AKT)signaling pathway plays a pivotal role in regulating osteoclast activation,which is essential for maintaining bone homeostasis.Bone destruction in osteoarticular tuberculosis is caused by aberrant osteoclastogenesis induced by Mycobacterium tuberculosis infection.However,the role of the PI3K signaling pathway in Mycobacterium tuberculosis-induced aberrant osteoclastogenesis remains unclear. OBJECTIVE:To investigate the effects and mechanisms of the PI3K/AKT signaling pathway inhibitor BYL-719 on aberrant osteoclastogenesis induced by Mycobacterium tuberculosis. METHODS:RAW264.7 cells were infected with bovine Mycobacterium tuberculosis bacillus calmette-cuerin vaccine,and Ag85B was used for cellular immunofluorescence staining.The cell counting kit-8 assay was employed to determine the safe concentration of BYL-719.There were four groups in the experiment:blank control group,BYL-719 group,BCG group,and BCG+BYL-719 group.Under the induction of receptor activator of nuclear factor kappa-B ligand,the effects of BYL-719 on post-infection osteoclast differentiation and fusion were explored through tartrate-resistant acid phosphatase staining and phalloidin staining.RT-PCR and western blot were used to detect the expression of osteoclast-related genes and proteins,and further investigate the mechanism of action. RESULTS AND CONCLUSION:Immunofluorescence staining showed that RAW264.7 cells phagocytosed Mycobacterium tuberculosis.Cell counting kit-8 data indicated that 40 nmol/L BYL-719 was non-toxic to cells.Tartrate-resistant acid phosphatase staining and phalloidin staining showed that BYL-719 inhibited the generation and fusion ability of osteoclasts following infection.RT-PCR and western blot results also indicated that BYL-719 suppressed the upregulation of osteoclast-specific genes(including c-Fos,NFATc1,matrix metalloproteinase 9,and CtsK)induced by Mycobacterium tuberculosis infection(P<0.05).Western blot and immunofluorescence staining revealed that BYL-719 inhibited excessive osteoclast differentiation induced by Mycobacterium tuberculosis by downregulating the expression of IκBα-p65.To conclude,BYL-719 inhibits aberrant osteoclastogenesis induced by Mycobacterium tuberculosis through the downregulation of IκBα/p65.Therefore,the IκBα/p65 signaling pathway is a potential therapeutic target for osteoarticular tuberculosis,and BYL-719 holds potential value for the preventing and amelioration of bone destruction in osteoarticular tuberculosis.BYL-719 has the potential to prevent and ameliorate bone destruction in osteoarticular tuberculosis.

italic>Artemisia argyi is a traditional Chinese medicine in China, which is used as medicine with its leaves. The leaves of A. argyi mainly contain flavonoids, phenolic acids, volatile oils and other compounds, and have a variety of pharmacological activities. AP2/ERF transcription factors are abundant in plants and are mainly involved in plant growth and development, abiotic stress response and secondary metabolite biosynthesis regulation. However, there are few reports on the AP2/ERF gene family and its functions in A. argyi. In this study, we systematically identified the AP2/ERF gene family in A. argyi genome, and analyzed its phylogenetic tree, protein physicochemical properties, subcellular localization, conserved motifs, promoter elements, and expression patterns. The results showed that a total of 204 AP2/ERF transcription factors were identified in A. argyi genome, encoding proteins consisting of 88-483 amino acids with a relative molecular mass of 10-52.94 kDa and a theoretical isoelectric point of 4.62-9.88. Subcellular prediction showed that the majority of AP2/ERFs were located in the nucleus, cytoplasm, and the minority of them is located in the membrane and chloroplasts. According to the Arabidopsis AP2/ERF family classification, A. argyi AP2/ERF proteins were divided into four subfamilies: Soloist, AP2, ERF (B3, B4, B5, B6), and DREB (A1, A2, A4, A5, A6), among which DREB family accounted for the largest proportion, and the same subfamily had similar conserved motifs. cis-Acting element analysis showed that AP2/ERF promoters have a large number of elements responding to light and abiotic stress. Expression pattern analysis showed that most of the genes of the AP2/ERF family were dominantly expressed mainly in roots and stems, of which 19 were dominantly expressed in leaves, 77 would be induced to be expressed by methyl jasmonate, of which 16 genes were both dominantly expressed in leaves and induced to be expressed by methyl jasmonate, and these AP2/ERF genes may be the key regulatory genes for the synthesis of active ingredients in A. argyi leaves.This study lays the foundation for the functional study of AP2/ERF family genes and their regulating roles in the active components biosynthesis in A. argyi leaves.

Abrin,the most lethal plant-derived toxin known today,has attracted widespread attention from both the International Chemical Weapon Convention and the Biological and Toxin Weapons Convention.There is an urgent demand for the development of efficient detection and detoxification countermeasures against Abrin to adress its potential threats to human health and public safety.This review,based on clustering analysis of literature and on knowledge of the structures of various subtypes of Abrin,provides an overview of the analysis and detection techniques,the mechanism of toxicity,and detoxification countermeasures against Abrin.It concludes with an examination of the challenges and emerging trends in this field.The main analysis and detection techniques of Abrin include affinity-based analysis,physico-chemical-based analysis,and activity-based detection techniques.The challenges and developments in this field are also outlined.There is a pressing need to establish sensitive,specific,and accurate methods of measurement that are tailored to the structure and activity of Abrin in order to precisely assess and mitigate the toxin threat.Unfortunately,no effective antidotes have been deployed so far,with medical treatments confined to symptomatic care.Research and development of neutralizing antibodies remain stands as the most promising strategy for counteracting Abrin intoxication.

Objective:To evaluate the detection performance of left ventricular ejection fraction (LVEF) in patients with chronic renal failure (CRF) by an artificial intelligence (AI) model based on yolox framework integrating left ventricular segmentation and critical point detection.Methods:From January 2019 to June 2023, a total of 4 284 echocardiographic images of 2 000 adults aged 18-80 years without segmental wall motion abnormalities, structural heart disease, cardiac surgery or cardiomyopathy were collected in Henan Provincial People′s Hospital to delineate the endocardial membrane, as a training set, an AI model based on yolox framework integrating left ventricular segmentation and critical point detection was established. The images were divided into the training set( n=1 675) and the test set( n=325) in a ratio of about 5∶1. All 228 echocardiographic images of 100 normal adult volunteers who were treated in Henan Provincial Chest Hospital from May 2020 to May 2021 were collected as external test set validation. All 792 echocardiographic images of 204 patients treated in Henan Provincial People′s Hospital from April 2019 to June 2023 were continuously enrolled to evaluate the measurement efficiency of AI model. Spearman correlation statistical method was used to analyze the consistency of AI model measurement with manual measurement and TomTec software measurement methods of 3 senior echocardiographic professionals. Subjects were divided into clear image group, unclear image group, normal LVEF group and reduced LVEF group, the differences of general data between the two groups were compared. The correlation coefficient(ICC) within the group was calculated to analyze the consistency, so as to evaluate the model performance. Results:LVEF measured by AI model was significantly correlated with both manual measurement and TomTec model measurement ( rs=0.834, 0.826; all P<0.01). ICC values of the clear image group and the unclear image group were 0.96 and 0.97, respectively. ICC values for all subjects, normal LVEF group and reduced LVEF group were 0.96, 0.90 and 0.96, respectively. Conclusions:The AI model based on yolox framework integrating left ventricular segmentation and critical point detection has good diagnostic performance in the automatic measurement of LVEF in patients with CRF.

In the face of the severe challenges posed by chronic illnesses, patients not only experience negative emotions due to their condition but also undergo positive transformations, such as a sense of benefit finding. This article summarizes the theoretical foundations, assessment tools, influencing factors, and intervention measures related to benefit finding among chronic disease patients. The aim is to provide references for healthcare professionals to develop and implement personalized psychological nursing care for chronic disease patients.

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.

Ulcerative colitis (UC) is a chronic inflammation of the gastrointestinal tract and is characterized by alternating periods of inflammation and remission. Although UC incidence is lower in Taiwan than in Western countries, its impact remains considerable, demanding updated guidelines for addressing local healthcare challenges and patient needs. The revised guidelines employ international standards and recent research, emphasizing practical implementation within the Taiwanese healthcare system. Since the inception of the guidelines in 2017, the Taiwan Society of Inflammatory Bowel Disease has acknowledged the need for ongoing revisions to incorporate emerging therapeutic options and evolving disease management practices. This updated guideline aims to align UC management with local contexts, ensuring comprehensive and context-specific recommendations, thereby raising the standard of care for UC patients in Taiwan. By adapting and optimizing international protocols for local relevance, these efforts seek to enhance health outcomes for patients with UC.

Crohn’s disease (CD) is a chronic, fluctuating inflammatory condition that primarily affects the gastrointestinal tract. Although the incidence of CD in Taiwan is lower than that in Western countries, the severity of CD presentation appears to be similar between Asia and the West. This observation indicates the urgency for devising revised guidelines tailored to the unique reimbursement system, and patient requirements in Taiwan. The core objectives of these updated guidelines include the updated treatment choices and the integration of the treat-to-target strategy into CD management, promoting the achievement of deep remission to mitigate complications and enhance the overall quality of life. Given the diversity in disease prevalence, severity, insurance policies, and access to medical treatments in Taiwan, a customized approach is imperative for formulating these guidelines. Such tailored strategies ensure that international standards are not only adapted but also optimized to local contexts. Since the inception of its initial guidelines in 2017, the Taiwan Society of Inflammatory Bowel Disease (TSIBD) has acknowledged the importance of continuous revisions for incorporating new therapeutic options and evolving disease management practices. The latest update leverages international standards and recent research findings focused on practical implementation within the Taiwanese healthcare system.

Child ; Humans ; Malacoplakia/pathology* ; Intestines/pathology*

Objective:To investigate the diagnostic accuracy of serological indicators and evaluate the diagnostic value of a new established combined serological model on identifying the minimal hepatic encephalopathy (MHE) in patients with compensated cirrhosis.Methods:This prospective multicenter study enrolled 263 compensated cirrhotic patients from 23 hospitals in 15 provinces, autonomous regions and municipalities of China between October 2021 and August 2022. Clinical data and laboratory test results were collected, and the model for end-stage liver disease (MELD) score was calculated. Ammonia level was corrected to the upper limit of normal (AMM-ULN) by the baseline blood ammonia measurements/upper limit of the normal reference value. MHE was diagnosed by combined abnormal number connection test-A and abnormal digit symbol test as suggested by Guidelines on the management of hepatic encephalopathy in cirrhosis. The patients were randomly divided (7∶3) into training set ( n=185) and validation set ( n=78) based on caret package of R language. Logistic regression was used to establish a combined model of MHE diagnosis. The diagnostic performance was evaluated by the area under the curve (AUC) of receiver operating characteristic curve, Hosmer-Lemeshow test and calibration curve. The internal verification was carried out by the Bootstrap method ( n=200). AUC comparisons were achieved using the Delong test. Results:In the training set, prevalence of MHE was 37.8% (70/185). There were statistically significant differences in AMM-ULN, albumin, platelet, alkaline phosphatase, international normalized ratio, MELD score and education between non-MHE group and MHE group (all P<0.05). Multivariate Logistic regression analysis showed that AMM-ULN [odds ratio ( OR)=1.78, 95% confidence interval ( CI) 1.05-3.14, P=0.038] and MELD score ( OR=1.11, 95% CI 1.04-1.20, P=0.002) were independent risk factors for MHE, and the AUC for predicting MHE were 0.663, 0.625, respectively. Compared with the use of blood AMM-ULN and MELD score alone, the AUC of the combined model of AMM-ULN, MELD score and education exhibited better predictive performance in determining the presence of MHE was 0.755, the specificity and sensitivity was 85.2% and 55.7%, respectively. Hosmer-Lemeshow test and calibration curve showed that the model had good calibration ( P=0.733). The AUC for internal validation of the combined model for diagnosing MHE was 0.752. In the validation set, the AUC of the combined model for diagnosing MHE was 0.794, and Hosmer-Lemeshow test showed good calibration ( P=0.841). Conclusion:Use of the combined model including AMM-ULN, MELD score and education could improve the predictive efficiency of MHE among patients with compensated cirrhosis.