Comprehensive characterization of long QT syndrome-associated genes in cancer and development of a robust prognosis model.

Cancer is the leading public health problem worldwide. However, the side effects accompanying anti-cancer therapies, particularly those pertaining to cardiotoxicity and adverse cardiac events, have been the hindrances to treatment progress. Long QT syndrome (LQTS) is one of the major clinic manifestations of the anti-cancer drug associated cardiac dysfunction. Therefore, elucidating the relationship between the LQTS and cancer is urgently needed. Transcriptomic sequencing data and clinic information of 10,531 patients diagnosed with 33 types of cancer was acquired from TCGA database. A pan-cancer applicative gene prognostic model was constructed based on the LQTS gene signatures. Meanwhile, transcriptome data and clinical information from various cancer types were collected from the GEO database to validate the robustness of the prognostic model. Furthermore, the expression level of transcriptomes and multiple clinical features were integrated to construct a Nomo chart to optimize the prognosis model. The ssGSEA analysis was employed to analysis the correlation between the LQTS gene signatures, clinic features and cancer associated signalling pathways. Our findings revealed that patients with lower LQTS gene signatures enrichment levels exhibit a poorer prognosis. The correlation of enrichment levels with the typical pathways was observed in multiple cancers. Then, based on the 17 LQTS gene signatures, we construct a prognostic model through the machine-learning approaches. The results obtained from the validation datasets and training datasets indicated that our prognostic model can effectively predict patient outcomes across diverse cancer types. Finally, we integrated this model with clinical features into a nomogram, demonstrating its potential as a valuable prognostic tool for cancer patients. Our study sheds light on the intricate relationship between LQTS and cancer pathways. A LQTS feature based clinic decision tool was developed aiming to enhance precision treatment of cancer.

Optimizing drug combination and mechanism analysis based on risk pathway crosstalk in pan cancer.

Combination therapy can greatly improve the efficacy of cancer treatment, so identifying the most effective drug combination and interaction can accelerate the development of combination therapy. Here we developed a computational network biological approach to identify the effective drug which inhibition risk pathway crosstalk of cancer, and then filtrated and optimized the drug combination for cancer treatment. We integrated high-throughput data concerning pan-cancer and drugs to construct miRNA-mediated crosstalk networks among cancer pathways and further construct networks for therapeutic drug. Screening by drug combination method, we obtained 687 optimized drug combinations of 83 first-line anticancer drugs in pan-cancer. Next, we analyzed drug combination mechanism, and confirmed that the targets of cancer-specific crosstalk network in drug combination were closely related to cancer prognosis by survival analysis. Finally, we save all the results to a webpage for query ( http://bio-bigdata.hrbmu.edu.cn/oDrugCP/ ). In conclusion, our study provided an effective method for screening precise drug combinations for various cancer treatments, which may have important scientific significance and clinical application value for tumor treatment.

Altruistic preferences of pre-service teachers: The mediating role of empathic concern and the moderating role of self-control.

Empathy and altruistic behavior are more crucial abilities for pre-service teachers to possess when compared with other study fields. The relationship between empathy and altruistic behavior in Chinese pre-service teachers and their underlying mechanisms, however, has received relatively little attention in the literature. Therefore, the goal of the current study was to examine the links between study fields (i.e., pre-service teachers whose study field is pedagogy and non-pre-service teachers whose study field is non-pedagogy), self-control, emotional empathy (i.e., empathic concern), and altruistic preferences among undergraduates and graduates in five Chinese universities (the age range of participants is 18-20 years; 58.4% women) with the Interpersonal Reactivity Index-C Questionnaire, the Self-Control Scale, and the Chinese Self-Report Altruism Scale tests. The results showed a significant difference between pre-service and non-pre-service teachers in empathic concern and self-control. Furthermore, empathic concern and altruistic behavior tendency of pre-service teachers were significantly higher than those of non-pre-service teachers. Moreover, mediation analyses indicated that empathic concern partially mediated the relationship between study fields and altruistic tendency. Moderated mediation analysis further revealed that self-control buffered the relation between empathic concern and altruistic behavior tendency. These results demonstrate that altruistic tendency of pre-service teachers is influenced by empathic concern and self-control.

Prevalence of sulfonamide-resistant bacteria, resistance genes and integron-associated horizontal gene transfer in natural water bodies and soils adjacent to a swine feedlot in northern Taiwan.

Antibiotics are commonly used in swine feed to treat and prevent disease, as well as to promote growth. Antibiotics released into the environment via wastewater could accelerate the emergence of antibiotic-resistant bacteria and resistance genes in the surrounding environment. In this study, we quantified the occurrence of sulfonamides, sulfonamide-resistant microorganisms and resistance genes in the wastewater from a swine farm in northern Taiwan and its surrounding natural water bodies and soils. Sulfonamide levels were similar in the receiving downstream and upstream river water. However, the prevalence of sulfonamide-resistant bacteria and resistance genes, as analyzed by cultivation-dependent and -independent molecular approaches, was significantly greater in the downstream compared to the upstream river water samples. Barcoded-pyrosequencing revealed a highly diverse bacterial community structure in each sample. However, the sequence identity of the sulfonamide resistance gene sul1 in the wastewater and downstream environment samples was nearly identical (99-100%). The sul1 gene, which is genetically linked to class 1 integrons, was dominant in the downstream water bodies and soils. In conclusion, the increased prevalence of sulfonamide resistance genes in the wastewater from a swine farm, independent of the persistent presence of sulfonamides, could be a potential source of resistant gene pools in the surrounding environment.