RESUMO
Ganoderma lucidum polysaccharides are valuable natural compounds possessing significant biological activity, with glycosyltransferases playing a crucial role in their biosynthesis. Although the function of ß-1,3-glucosyltransferase in polysaccharides production is well understood, the role of α-1,3-glucosyltransferase in edible fungi remains unclear. In this study, over-expression of the α-1,3-glucosyltransferase gene in G. lucidum (glagt) was found to suppress the growth, with the maximum biomass and mycelial growth rate decreasing by 21.78 % and 79.61 %, respectively, a behavior distinct from ß-1,3-glucosyltransferase. The fungal pellet diameter decreased by 38 % and the cell-wall thickness by 32.44 %, whereas intracellular and extracellular polysaccharides production increased by 27.58 % and 66.08 %, respectively. In the transcription level, overexpressing the glagt gene i) downregulated the citrate synthase and isocitrate dehydrogenase gene in the TCA cycle, disrupting energy metabolism and fungal growth; ii) upregulated key enzymes involved in UDP-glucose synthesis and glycosyltransferases (gl24465, gl24971, and gl22535); and iii) universally increased the transcriptional level of glucosidases gl21451, gl30087, and gl24581 by 22 %-397 %, contributing to cell-wall thinning to facilitate polysaccharides export. Conversely, the glagt gene downregulation promoted G. lucidum growth and decreased polysaccharides production. The results elucidate the roles of GLAGT and are expected to inspire in-depth exploration of polysaccharides biosynthesis pathways.
Assuntos
Regulação Fúngica da Expressão Gênica , Glucosiltransferases , Reishi , Reishi/genética , Reishi/enzimologia , Reishi/crescimento & desenvolvimento , Reishi/metabolismo , Glucosiltransferases/metabolismo , Glucosiltransferases/genética , Polissacarídeos/biossíntese , Biomassa , Polissacarídeos Fúngicos/biossíntese , Parede Celular/metabolismo , Proteínas Fúngicas/genética , Proteínas Fúngicas/metabolismoRESUMO
BACKGROUND: It is unclear whether alternating placements during clinical clerkship, without an explicit emphasis on clinical competencies, would bring about optimal educational outcomes. METHODS: This is an explanatory sequential mixed-methods research. We enrolled a convenience sample of 41 eight-year programme medical students in Sun Yat-sen University who received alternating placements during clerkship. The effects of competence-based approach (n = 21) versus traditional approach (n = 20) to clerkship teaching were compared. In the quantitative phase, course satisfaction was measured via an online survey and academic performance was determined through final scores on summative assessment. Then, in the qualitative phase, students were invited for semi-structured interviews about their learning experiences, and the transcripts were used for thematic analysis. RESULTS: Quantitative findings showed that students in the study group rated high course satisfaction and performed significantly better in their final scores compared with those in the control group. Qualitative findings from thematic analysis showed that students were relatively neutral about their preference on placement models, but clearly perceived, capitalised, and appreciated that their competencies were being cultivated by an instructor who was regarded as a positive role model. CONCLUSION: A competence-based approach to clerkship teaching resulted in better course satisfaction and academic performance, and was perceived, capitalised, and appreciated by students.
RESUMO
BACKGROUND: Non-anemic thalassemia trait (TT) accounted for a high proportion of TT cases in South China. OBJECTIVE: To use artificial intelligence (AI) analysis of erythrocyte morphology and machine learning (ML) to identify TT gene carriers in a non-anemic population. METHODS: Digital morphological data from 76 TT gene carriers and 97 controls were collected. The AI technology-based Mindray MC-100i was used to quantitatively analyze the percentage of abnormal erythrocytes. Further, ML was used to construct a prediction model. RESULTS: Non-anemic TT carriers accounted for over 60% of the TT cases. Random Forest was selected as the prediction model and named TT@Normal. The TT@Normal algorithm showed outstanding performance in the training, validation, and external validation sets and could efficiently identify TT carriers in the non-anemic population. The top three weights in the TT@Normal model were the target cells, microcytes, and teardrop cells. Elevated percentages of abnormal erythrocytes should raise a strong suspicion of being a TT gene carrier. TT@Normal could be promoted and used as a visualization and sharing tool. It is accessible through a URL link and can be used by medical staff online to predict the possibility of TT gene carriage in a non-anemic population. CONCLUSIONS: The ML-based model TT@Normal could efficiently identify TT carriers in non-anemic people. Elevated percentages of target cells, microcytes, and teardrop cells should raise a strong suspicion of being a TT gene carrier.
Assuntos
Talassemia , Talassemia beta , Humanos , Inteligência Artificial , Talassemia/diagnóstico , Talassemia/genética , Talassemia beta/diagnóstico , Talassemia beta/genética , Aprendizado de Máquina , Eritrócitos AnormaisRESUMO
Rhabdomyolysis refers to the destruction or disintegration of striated muscles. This syndrome is characterized by muscle breakdown and necrosis, resulting in the leakage of intracellular muscle constituents into the circulation and extracellular fluid. We report a rare case of rhabdomyolysis complicating multi-organ failure caused by T-cell lymphoma in a 32-year-old woman. The final diagnosis was rhabdomyolysis caused by peripheral T-cell lymphoma based on bone marrow aspirate and biopsy.