Measuring job stress of dental workers in China during the COVID-19 pandemic: reliability and validity of the hospital consultants' job stress questionnaire.

BACKGROUND: The Hospital Consultants' Job Stress Questionnaire (HCJSQ) has been widely used to assess sources and levels of job stress. However, its reliability and validity among Chinese dental workers have not been extensively studied. The objective of this study was to assess the reliability and validity of the HCJSQ specifically in Chinese dental workers. METHODS: The HCJSQ was used to explore the sources and the global ratings of job stress among Chinese dental workers. To assess the reliability and validity of the HCJSQ, various statistical measures were employed, including Cronbach's alpha coefficient, Spearman-Brown coefficient, Spearman correlation coefficient, exploratory factor analysis, confirmatory factor analysis, convergent validity, and discriminant validity. RESULTS: Of the participants, 526 (17.4%) reported high levels of stress, while 1,246 (41.3%) and 1,248 (41.3%) reported moderate and low levels of stress, respectively. The Cronbach's alpha coefficient for the modified HCJSQ was 0.903, and the Spearman-Brown coefficient was 0.904. Spearman correlation coefficient between individuals' items and the total score ranged from 0.438 to 0.785 (p < 0.05). Exploratory factor analysis revealed that three factors accounted for 60.243% of the total variance. Confirmatory factor analysis demonstrated factor loadings between 0.624 and 0.834 on the specified items. The fit indices of the confirmatory factor analysis indicated good model fit, with a Root Mean Square Error of Approximation of 0.064, Normative Fit Index of 0.937, Comparative Fit Index of 0.952, Incremental Fit Index of 0.952, Tucker-Lewis index of 0.941, and Goodness of Fit Index of 0.944. Additionally, the convergent validity and discriminant validity showed a good fit for the three-factor model. CONCLUSION: The results of this study confirm that Chinese dental workers experience high levels of stress, and the three-factor model of the HCJSQ proves to be a suitable instrument for evaluating the sources and levels of job stress among Chinese dental workers. Therefore, it is imperative that relevant entities such as hospitals, medical associations, and government take appropriate measures to address the existing situation.

Treatment response of venlafaxine induced alterations of gut microbiota and metabolites in a mouse model of depression.

Antidepressants remain the first-line treatment for depression. However, the factors influencing medication response are still unclear. Accumulating evidence implicates an association between alterations in gut microbiota and antidepressant response. Therefore, the aim of this study is to investigate the role of the gut microbiota-brain axis in the treatment response of venlafaxine. After chronic social defeat stress and venlafaxine treatment, mice were divided into responders and non-responders groups. We compared the composition of gut microbiota using 16 S ribosomal RNA sequencing. Meanwhile, we quantified metabolomic alterations in serum and hippocampus, as well as hippocampal neurotransmitter levels using liquid chromatography-mass spectrometry. We found that the abundances of 29 amplicon sequence variants (ASVs) were significantly altered between the responders and non-responders groups. These ASVs belonged to 8 different families, particularly Muribaculaceae. Additionally, we identified 38 and 39 differential metabolites in serum and hippocampus between the responders and non-responders groups, respectively. Lipid, amino acid, and purine metabolisms were enriched in both serum and hippocampus. In hippocampus, the concentrations of tryptophan, phenylalanine, gamma-aminobutyric acid, glutamic acid, and glutamine were increased, while the level of succinic acid was decreased in the responders group, compared with the non-responders group. Our findings suggest that the gut microbiota may play a role in the antidepressant effect of venlafaxine by modulating metabolic processes in the central and peripheral tissues. This provides a novel microbial and metabolic framework for understanding the impact of the gut microbiota-brain axis on antidepressant response.

Niraparib with Abiraterone Acetate and Prednisone for Metastatic Castration-Resistant Prostate Cancer: Phase II QUEST Study Results.

Niraparib (NIRA) is a highly selective inhibitor of poly (adenosine diphosphate-ribose) polymerase, PARP1 and PARP2, which play a role in DNA repair. The phase II QUEST study evaluated NIRA combinations in patients with metastatic castration-resistant prostate cancer who were positive for homologous recombination repair gene alterations and had progressed on 1 prior line of novel androgen receptor-targeted therapy. Results from the combination of NIRA with abiraterone acetate plus prednisone, which disrupts androgen axis signaling through inhibition of CYP17, showed promising efficacy and a manageable safety profile in this patient population.

Integrated pathway and network analyses of metabolomic alterations in peripheral blood of patients with depression.

Depression is a serious mental illness, but the molecular mechanisms of depression remain unclear. Previous research has reported metabolomic changes in the blood of patients with depression, while integrated analysis based on these altered metabolites was still lacking. The objective of this study was to integrate metabolomic changes to reveal the underlying molecular alternations of depression. We retrieved altered metabolites in the blood of patients with depression from the MENDA database. Pathway analysis was conducted to explore enriched pathways based on candidate metabolites. Pathway crosstalk analysis was performed to explore potential correlations of these enriched pathways, based on their shared candidate metabolites. Moreover, potential interactions of candidate metabolites with other biomolecules such as proteins were assessed by network analysis. A total of 854 differential metabolite entries were retrieved in peripheral blood of patients with depression, including 555 unique candidate metabolites. Pathway analysis identified 215 significantly enriched pathways, then pathway crosstalk analysis revealed that these pathways were clustered into four modules, including amino acid metabolism, nucleotide metabolism, energy metabolism and others. Additionally, eight molecular networks were identified in the molecular network analysis. The main functions of these networks involved amino acid metabolism, molecular transport, inflammatory responses and others. Based on integrated analysis, our study revealed pathway-based modules and molecular networks associated with depression. These results will contribute to the underlying knowledge of the molecular mechanisms in depression.

Liver function test indices-based prediction model for post-stroke depression: a multicenter, retrospective study.

BACKGROUND: Post-stroke depression (PSD) was one of the most prevalent and serious neuropsychiatric effects after stroke. Nevertheless, the association between liver function test indices and PSD remains elusive, and there is a lack of effective prediction tools. The purpose of this study was to explore the relationship between the liver function test indices and PSD, and construct a prediction model for PSD. METHODS: All patients were selected from seven medical institutions of Chongqing Medical University from 2015 to 2021. Variables including demographic characteristics and liver function test indices were collected from the hospital electronic medical record system. Univariate analysis, least absolute shrinkage and selection operator (LASSO) and logistic regression analysis were used to screen the predictors. Subsequently, logistic regression, random forest (RF), extreme gradient boosting (XGBoost), gradient boosting decision tree (GBDT), categorical boosting (CatBoost) and support vector machine (SVM) were adopted to build the prediction model. Furthermore, a series of evaluation indicators such as area under curve (AUC), sensitivity, specificity, F1 were used to assess the performance of the prediction model. RESULTS: A total of 464 PSD and 1621 stroke patients met the inclusion criteria. Six liver function test items, namely AST, ALT, TBA, TBil, TP, ALB/GLB, were closely associated with PSD, and included for the construction of the prediction model. In the test set, logistic regression model owns the AUC of 0.697. Compared with the other four machine learning models, the GBDT model has the best predictive performance (F1 = 0.498, AUC = 0.761) and was chosen to establish the prediction tool. CONCLUSIONS: The prediction model constructed using these six predictors with GBDT algorithm displayed a promising prediction ability, which could be used for the participating hospital units or individuals by mobile phone or computer.

The prevalence of professional burnout among dentists: a systematic review and meta-analysis.

Professional burnout refers to mental weariness caused by occupational stress. However, there is a lack of systematic studies on the prevalence of professional burnout among dentists. The purpose of this study was to investigate the prevalence of professional burnout among dentists. Databases including PubMed, PsycINFO, Embase, Cochrane, and Web of Science were systematically searched from inception to 28 October 2021. The random-effects model and forest plots were used to assess the pooled prevalence of professional burnout among dentists. A total of 15 studies with a total of 6038 study subjects were included in the meta-analysis, and the overall professional burnout among dentists was 13% (95%CI: 6-23). Subgroup analysis suggested a high prevalence of burnout in Europe, and the least in the Americas. The pooled burnout prevalence in cross-sectional surveys was significantly lower than that in longitudinal studies. In addition, the overall burnout prevalence in the last decade was significantly lower than that of a decade ago. This meta-analysis demonstrated that the prevalence of burnout was relatively low among dentists, and there was a downward trend. Therefore, it is important to continue to pay close attention to the mental health of dentists and effectively prevent and treat professional burnout to better maintain the provision of health care services.

The overall prevalence of professional burnout among dentists was 13%.Subgroup analysis revealed that the prevalence of burnout differed in geographical regions, with the highest in Europe, followed by Asia, and the lowest in America.The pooled burnout prevalence in cross-sectional surveys was significantly lower than that in longitudinal studies. In addition, the overall burnout prevalence in the last decade was significantly lower than that of a decade ago.More attention should be paid to professional burnout among dentists to improve the provision of health care services.

MENDA: a comprehensive curated resource of metabolic characterization in depression.

Depression is a seriously disabling psychiatric disorder with a significant burden of disease. Metabolic abnormalities have been widely reported in depressed patients and animal models. However, there are few systematic efforts that integrate meaningful biological insights from these studies. Herein, available metabolic knowledge in the context of depression was integrated to provide a systematic and panoramic view of metabolic characterization. After screening more than 10 000 citations from five electronic literature databases and five metabolomics databases, we manually curated 5675 metabolite entries from 464 studies, including human, rat, mouse and non-human primate, to develop a new metabolite-disease association database, called MENDA (http://menda.cqmu.edu.cn:8080/index.php). The standardized data extraction process was used for data collection, a multi-faceted annotation scheme was developed, and a user-friendly search engine and web interface were integrated for database access. To facilitate data analysis and interpretation based on MENDA, we also proposed a systematic analytical framework, including data integration and biological function analysis. Case studies were provided that identified the consistently altered metabolites using the vote-counting method, and that captured the underlying molecular mechanism using pathway and network analyses. Collectively, we provided a comprehensive curation of metabolic characterization in depression. Our model of a specific psychiatry disorder may be replicated to study other complex diseases.

Metabolomic changes in animal models of depression: a systematic analysis.

Extensive research has been carried out on the metabolomic changes in animal models of depression; however, there is no general agreement about which metabolites exhibit constant changes. Therefore, the aim of this study was to identify consistently altered metabolites in large-scale metabolomics studies of depression models. We performed vote counting analyses to identify consistently upregulated or downregulated metabolites in the brain, blood, and urine of animal models of depression based on 3743 differential metabolites from 241 animal metabolomics studies. We found that serotonin, dopamine, gamma-aminobutyric acid, norepinephrine, N-acetyl-L-aspartic acid, anandamide, and tryptophan were downregulated in the brain, while kynurenine, myo-inositol, hydroxykynurenine, and the kynurenine to tryptophan ratio were upregulated. Regarding blood metabolites, tryptophan, leucine, tyrosine, valine, trimethylamine N-oxide, proline, oleamide, pyruvic acid, and serotonin were downregulated, while N-acetyl glycoprotein, corticosterone, and glutamine were upregulated. Moreover, citric acid, oxoglutaric acid, proline, tryptophan, creatine, betaine, L-dopa, palmitic acid, and pimelic acid were downregulated, and hippuric acid was upregulated in urine. We also identified consistently altered metabolites in the hippocampus, prefrontal cortex, serum, and plasma. These findings suggested that metabolomic changes in depression models are characterized by decreased neurotransmitter and increased kynurenine metabolite levels in the brain, decreased amino acid and increased corticosterone levels in blood, and imbalanced energy metabolism and microbial metabolites in urine. This study contributes to existing knowledge of metabolomic changes in depression and revealed that the reproducibility of candidate metabolites was inadequate in previous studies.

An integrated meta-analysis of peripheral blood metabolites and biological functions in major depressive disorder.

Major depressive disorder (MDD) is a serious mental illness, characterized by high morbidity, which has increased in recent decades. However, the molecular mechanisms underlying MDD remain unclear. Previous studies have identified altered metabolic profiles in peripheral tissues associated with MDD. Using curated metabolic characterization data from a large sample of MDD patients, we meta-analyzed the results of metabolites in peripheral blood. Pathway and network analyses were then performed to elucidate the biological themes within these altered metabolites. We identified 23 differentially expressed metabolites between MDD patients and controls from 46 studies. MDD patients were characterized by higher levels of asymmetric dimethylarginine, tyramine, 2-hydroxybutyric acid, phosphatidylcholine (32:1), and taurochenodesoxycholic acid and lower levels of L-acetylcarnitine, creatinine, L-asparagine, L-glutamine, linoleic acid, pyruvic acid, palmitoleic acid, L-serine, oleic acid, myo-inositol, dodecanoic acid, L-methionine, hypoxanthine, palmitic acid, L-tryptophan, kynurenic acid, taurine, and 25-hydroxyvitamin D compared with controls. L-tryptophan and kynurenic acid were consistently downregulated in MDD patients, regardless of antidepressant exposure. Depression rating scores were negatively associated with decreased levels of L-tryptophan. Pathway and network analyses revealed altered amino acid metabolism and lipid metabolism, especially for the tryptophan-kynurenine pathway and fatty acid metabolism, in the peripheral system of MDD patients. Taken together, our integrated results revealed that metabolic changes in the peripheral blood were associated with MDD, particularly decreased L-tryptophan and kynurenic acid levels, and alterations in the tryptophan-kynurenine and fatty acid metabolism pathways. Our findings may facilitate biomarker development and the elucidation of the molecular mechanisms that underly MDD.

Alteration of lipids and amino acids in plasma distinguish schizophrenia patients from controls: A targeted metabolomics study.

BACKGROUND: Schizophrenia (SCZ) is a serious psychiatric disorder. Metabolite disturbance is an important pathogenic factor in schizophrenic patients. In this study, we aim to identify plasma lipid and amino acid biomarkers for SCZ using targeted metabolomics. METHODS: Plasma from 76 SCZ patients and 50 matched controls were analyzed using the LC/MS-based multiple reaction monitoring (MRM) metabolomics approach. A total of 182 targeted metabolites, including 22 amino acids and 160 lipids or lipid-related metabolites were observed. We used binary logistic regression analysis to determine whether the lipid and amino acid biomarkers could discriminate SCZ patients from controls. The area under the curve (AUC) from receiver operation characteristic (ROC) curve analysis was conducted to evaluate the diagnostic performance of the biomarkers panel. RESULTS: We identified 19 significantly differentially expressed metabolites between the SCZ patients and the controls (false discovery rate < 0.05), including one amino acid and 18 lipids or lipid-related metabolites. The binary logistic regression-selected panel showed good diagnostic performance in the drug-naïve group (AUC = 0.936) and all SCZ patients (AUC = 0.948), especially in the drug-treated group (AUC = 0.963). CONCLUSIONS: Plasma lipids and amino acids showed significant dysregulation in SCZ, which could effectively discriminate SCZ patients from controls. The LC/MS/MS-based approach provides reliable data for the objective diagnosis of SCZ.

Overlap of burnout-depression symptoms among Chinese neurology graduate students in a national cross-sectional study.

BACKGROUND: The overlap of burnout and depression is a phenomenon that can effectively reflect the psychological state of a group. However, whether burnout is a type of depression is still debated in current research. The high incidence of burnout and depressive symptoms among medical students indicates that it is urgent to provide appropriate health services for them. However, the proportion of burnout and depression in the overlapping symptoms experienced by medical students, and the characteristics of the relative influencing factors, remain unclear. Therefore, we addressed these issues for neurology graduate students in China. METHODS: Using data from a cross-sectional survey of Chinese neurology graduate students, a diagnostic model was established according to their burnout and/or depression symptoms. Burnout was assessed by using the Maslach Burnout Inventory. Depression symptoms were assessed with a two-item depression screening tool for primary care evaluation of mental disorders. Univariate analyses with chi-squared tests were conducted to assess associations between variables. Multinomial logistic regression models were used to analyze the effects of multiple factors on dependent variables. The factors included demographic information and three medical-study related problems. RESULTS: In total, 32.2% of surveyed students evidenced overlapping burnout and depression symptoms. Students with depressive symptoms tended to be included in the burnout students' category. In the regression model, being unmarried, having children, and career choice regret were related to students who had only burnout, while the students with overlapping symptoms were affected by more factors such as family income, the consideration of dropping out once. CONCLUSIONS: The symptoms and related factors of burnout and depression among Chinese neurology postgraduates have obvious overlap and show a significant trend. The occurrence of depressive symptoms among medical students is closely related to whether they are burned out. Students with only burnout were common, but students with only depressive symptoms were uncommon. Finally, burnout may be a pre-depression state.

Surgical-related risk factors associated with anastomotic leakage after resection for rectal cancer: a meta-analysis.

OBJECTIVES: Anastomotic leakage (AL) after anterior resection always leads to longer hospital stays, decreased quality of life and even increased mortality. Despite extensive research, no consensus on the world well-concerned surgical-related risk factors exists. We therefore conducted a meta-analysis of the available published literature to identify the effects of surgical-related risk factors for AL after anterior resection for rectal cancer, hoping to provide more information and improved guidance for clinical workers managing patients with rectal cancer who are at a high risk for AL. METHODS: In this study, the relevant articles were systematically searched from EMBASE, MEDLINE, PubMed, WangFang (Database of Chinese Ministry of Science & Technology), Chinese National Knowledge Infrastructure Database and China Biological Medicine Database. The pooled odds ratio (OR) with 95% confidence interval (95% CI) were calculated. Meta-analysis was performed using of RevMan 5.3 software. RESULTS: A total of 26 studies met the inclusion criteria and comprised 34238 cases. Analysis of these 26 studies showed that no defunctioning stoma was highly correlated with AL (pooled OR = 1.28, 95%CI: 1.05-1.57, P = 0.01, random effect), and intraoperative blood transfusion was significantly associated with AL (pooled OR = 1.64, 95%CI: 1.34-2.02, P = 0.02, random effect). However, the AL was not associated with type of anastomosis, type of surgery, technique of anastomosis, level of inferior mesenteric artery ligation, operation time and splenic flexure mobilization. CONCLUSIONS: Depend on this meta-analysis, no defunctioning stoma and intraoperative blood transfusion are the major surgical-related risk factors for AL after resection for rectal cancer. Because of the inherent limitations of the research, future prospective randomized controlled trials will need to confirm this conclusion.

Metabolomic analysis of animal models of depression.

BACKGROUND: Our understanding of the molecular mechanisms of depression remains largely unclear. Previous studies have shown that the prefrontal cortex (PFC) is among most important brain regions that exhibits metabolic changes in depression. A comprehensive analysis based on candidate metabolites in the PFC of animal models of depression will provide valuable information for understanding the pathogenic mechanism underlying depression. METHODS: Candidate metabolites that are potentially involved in the metabolic changes of the PFC in animal models of depression were retrieved from the Metabolite Network of Depression Database. The significantly altered metabolic pathways were revealed by canonical pathway analysis, and the relationships among altered pathways were explored by pathway crosstalk analysis. Additionally, drug-associated pathways were investigated using drug-associated metabolite set enrichment analysis. The interrelationships among metabolites, proteins, and other molecules were analyzed by molecular network analysis. RESULTS: Among 88 candidate metabolites, 87 altered canonical pathways were identified, and the top five ranked pathways were tRNA charging, the endocannabinoid neuronal synapse pathway, (S)-reticuline biosynthesis II, catecholamine biosynthesis, and GABA receptor signaling. Pathway crosstalk analysis revealed that these altered pathways were grouped into three interlinked modules involved in amino acid metabolism, nervous system signaling/neurotransmitters, and nucleotide metabolism. In the drug-associated metabolite set enrichment analysis, the main enriched drug pathways were opioid-related and antibiotic-related action pathways. Furthermore, the most significantly altered molecular network was involved in amino acid metabolism, molecular transport, and small molecule biochemistry. CONCLUSIONS: This study provides important clues for the metabolic characteristics of the PFC in depression.

Discovery of Metabolic Biomarkers Predicting Radiation Therapy Late Effects in Prostate Cancer Patients.

Patients presenting with prostate cancers undergo clinical staging evaluations to determine the extent of disease to guide therapeutic recommendations. Management options may include watchful waiting, surgery, or radiation therapy. Thus, initial risk stratification of prostate cancer patients is important for achieving optimal therapeutic results or cancer cure and preservation of quality of life. Predictive biomarkers for risks of complications or late effects of treatment are needed to inform clinical decisions for treatment selection. Here, we analyzed pre-treatment plasma metabolites in a cohort of prostate cancer patients (N = 99) treated with Stereotactic Body Radiation Therapy (SBRT) at Medstar-Georgetown University Hospital in a longitudinal, quality-of-life study to determine if individuals experiencing radiation toxicities can be identified by a molecular profile in plasma prior to treatment. We used a multiple reaction mass spectrometry-based molecular phenotyping of clinically annotated plasma samples in a retrospective outcome analysis to identify candidate biomarker panels correlating with adverse clinical outcomes following radiation therapy. We describe the discovery of candidate biomarkers, based on small molecule metabolite panels, showing high correlations (AUCs ≥ 95%) with radiation toxicities, suitable for validation studies in an expanded cohort of patients.

Relationship between burnout and career choice regret among Chinese neurology postgraduates.

BACKGROUND: In China, the shortage of doctors leads to stressful clinical work and increasing turnover. Medical students undergoing postgraduate specialty training will be the country's medical workforce in the coming decades, but are also subject to high workloads and academic pressure. This may have significant implications for burnout and career choice regret. Despite the importance of burnout and career choice regret, the status and relationship of these aspects in Chinese neurology postgraduates are largely unexplored, and associated factors remain unknown. METHODS: This study investigated the prevalence of and factors influencing burnout and career choice regret among neurology postgraduates in China. We conducted a national cross-sectional study of Chinese neurology postgraduates. Data were collected using a self-administered questionnaire that covered demographic information, the Maslach Burnout Inventory, and additional item to assess career choice regret. RESULTS: Of 4902 neurology postgraduates, 2008 returned completed questionnaires (response rate 41%). After excluding incomplete questionnaires, data for 1814 participants were analyzed. In total, 83.6% of participants had experienced symptoms of burnout, and 46.6% reported career choice regret. Binary logistic regression analysis showed postgraduate entrance examination scores, marital status, and having children were associated with burnout (all P <  0.05). Career choice regret was the strongest risk factor for burnout (odds ratio [OR] = 3.17, 95% confidence interval [CI] 2.33-4.32). Multiple logistic regression showed postgraduates with shorter work or study hours per week (OR = 0.64, 95% CI 0.47-0.88) had a low risk for career choice regret, whereas married participants (OR = 1.54, 95% CI 1.07-2.20) had a high risk for career choice regret. No symptoms of burnout (OR = 0.33, 95% CI 0.24-0.45) was also associated with a low risk for career choice regret. CONCLUSIONS: Burnout symptoms and career choice regret are prevalent among neurology postgraduates in China. Career choice regret is an important predictor of burnout. Further research on reducing burnout and career choice regret among neurology postgraduates is needed.

Depressive symptoms and quality of life among Chinese medical postgraduates: a national cross-sectional study.

High workloads and heavy academic pressure can have significant implications for the risk for depression and poor quality of life (QoL). This study aimed to investigate QoL and depressive symptoms in medical students undergoing postgraduate neurology specialty training in China. The survey covered demographic characteristics, the 8-itemMedical Outcomes Study Short-Formquestionnaire (SF-8), and the 2-itemPrimary Care Evaluation of Mental Disorders depression screening tool. Logistic regression analysis was used to investigate the determinants of QoL and depressive symptoms. Participants were 1,814 postgraduates from 249 hospitals in 27 Chinese provinces. The mean SF-8 physical and mental component summary scores were 78.17 (standard deviation [SD] 15.20) and 68.33 (SD 17.15), respectively. One-third of respondents had depressive symptoms, and those without depressive symptoms had significantly higher QoL scores. The multivariate regression analysis showed that factors independently associated with depressive symptoms were being in the second year of study, a lower household income, and less sleep  time. Although QoL among our sample of Chinese medical students undergoing postgraduate neurology specialty training was favorable relative to other comparable populations, one-third of respondents had depressive symptoms. Accurate measures should be taken to change this situation.

Fecal pancreatic elastase-1 in the evaluation of pancreatic function after pediatric intestinal transplantation.

Fat malabsorption is common after SBT. To identify whether anatomic variant transplants differ in occurrence of exocrine pancreatic insufficiency that could contribute to fat malabsorption, we measured FPE repeatedly in 54 recipients of a SBT, ages 6.2 to 320 months. FPE determination most distant from SBT was 6.1 years. Of the 54, 39% received an isolated intestinal graft (native pancreas only), 48% received an en bloc liver-intestinal-pancreas graft (native and graft pancreas), and 13% received a multivisceral graft (graft pancreas only). Initial FPE was normal (>200 µg/g) in 15 of the 54 at a median of 22 (11-61) days after SBT. Recipients of a liver-intestine-pancreas transplant were more likely to have normal FPE within 30 days after SBT than were isolated intestinal or multivisceral transplant recipients (47%, 19%, and 0%, respectively, P = .049). Of the remaining 39 patients, 34 eventually demonstrated a normal FPE at a median of 168 (31-943) days after SBT. Type of SBT did not influence the likelihood of achieving a normal FPE level or time when it occurred. Five (9%) patients failed to achieve normal FPE, including 3 who died within 2 years after SBT. In conclusion, possessing both graft and native pancreas as in transplantation of an en bloc liver-intestinal-pancreas graft facilitates early normalization of FPE that eventually occurs in most patients irrespective of transplant type. Failure to recover normal pancreatic function may be associated with severe post-transplant complications.

Trichosanthin-induced autophagy in gastric cancer cell MKN-45 is dependent on reactive oxygen species (ROS) and NF-κB/p53 pathway.

Trichosanthin (TCS), isolated from the root tuber of Trichosanthes kirilowii tubers in the Cucurbitaceae family, owns a great deal of biological and pharmacological activities including anti-virus and anti-tumor. TCS has been reported to induce cell apoptosis of a diversity of cancers, including cervical cancer, choriocarcinoma, and gastric cancer, etc. However, whether TCS would induce autophagy in gastric cancer cells was seldom investigated. In current study, human gastric cancer MKN-45 cell growth was significantly inhibited by TCS. The anti-proliferation effect of TCS was due to an increased autophagy, which was confirmed by monodansylcadervarine (MDC) staining, up-regulation of Autophagy protein 5 (Atg5), and conversion of LC3 I to LC3 II (autophagosome marker). In addition, TCS induced reactive oxygen species (ROS) in MKN-45 cells and ROS scavenger N-acetylcysteine (NAC) significantly reversed TCS-induced autophagy. Furthermore, NF-κB/p53 pathway was activated during the process of autophagy induced by TCS and the ROS generation was mediated by it in MKN-45 cells. In vivo results showed that TCS exerted significantly anti-tumor effect on MKN-45 bearing mice. Considering the clinical usage of TCS on other human diseases, these research progresses provided a new insight into cancer research and new therapeutic avenues for patients with gastric cancer.

Liver metabolomics reveals increased oxidative stress and fibrogenic potential in gfrp transgenic mice in response to ionizing radiation.

Although radiation-induced tissue-specific injury is well documented, the underlying molecular changes resulting in organ dysfunction and the consequences thereof on overall metabolism and physiology have not been elucidated. We previously reported the generation and characterization of a transgenic mouse strain that ubiquitously overexpresses Gfrp (GTPH-1 feedback regulatory protein) and exhibits higher oxidative stress, which is a possible result of decreased tetrahydrobiopterin (BH4) bioavailability. In this study, we report genotype-dependent changes in the metabolic profiles of liver tissue after exposure to nonlethal doses of ionizing radiation. Using a combination of untargeted and targeted quantitative mass spectrometry, we report significant accumulation of metabolites associated with oxidative stress, as well as the dysregulation of lipid metabolism in transgenic mice after radiation exposure. The radiation stress seems to exacerbate lipid peroxidation and also results in higher expression of genes that facilitate liver fibrosis, in a manner that is dependent on the genetic background and post-irradiation time interval. These findings suggest the significance of Gfrp in regulating redox homeostasis in response to stress induced by ionizing radiation affecting overall physiology.