Leptin Signaling in Obesity and Colorectal Cancer

Obesity and colorectal cancer (CRC) are among the leading diseases causing deaths in the world, showing a complex multifactorial pathology. Obesity is considered a risk factor in CRC development through inflammation, metabolic, and signaling processes. Leptin is one of the most important adipokines related to obesity and an important proinflammatory marker, mainly expressed in adipose tissue, with many genetic variation profiles, many related influencing factors, and various functions that have been ascribed but not yet fully understood and elucidated, the most important ones being related to energy metabolism, as well as endocrine and immune systems. Aberrant signaling and genetic variations of leptin are correlated with obesity and CRC, with the genetic causality showing both inherited and acquired events, in addition to lifestyle and environmental risk factors; these might also be related to specific pathogenic pathways at different time points. Moreover, mutation gain is a crucial factor enabling the genetic process of CRC. Currently, the inconsistent and insufficient data related to leptin’s relationship with obesity and CRC indicate the necessity of further related studies. This review summarizes the current knowledge on leptin genetics and its potential relationship with the main pathogenic pathways of obesity and CRC, in an attempt to understand the molecular mechanisms of these associations, in the context of inconsistent and contradictory data. The understanding of these mechanisms linking obesity and CRC could help to develop novel therapeutic targets and prevention strategies, resulting in a better prognosis and management of these diseases.     

Systematic Review and Meta-Analysis of Mass Spectrometry Proteomics Applied to Human Peripheral Fluids to Assess Potential Biomarkers of Schizophrenia

Mass spectrometry (MS)-based techniques can be a powerful tool to identify neuropsychiatric disorder biomarkers, improving prediction and diagnosis ability. Here, we evaluate the efficacy of MS proteomics applied to human peripheral fluids of schizophrenia (SCZ) patients to identify disease biomarkers and relevant networks of biological pathways. Following PRISMA guidelines, a search was performed for studies that used MS proteomics approaches to identify proteomic differences between SCZ patients and healthy control groups (PROSPERO database: CRD42021274183). Nineteen articles fulfilled the inclusion criteria, allowing the identification of 217 differentially expressed proteins. Gene ontology analysis identified lipid metabolism, complement and coagulation cascades, and immune response as the main enriched biological pathways. Meta-analysis results suggest the upregulation of FCN3 and downregulation of APO1, APOA2, APOC1, and APOC3 in SCZ patients. Despite the proven ability of MS proteomics to characterize SCZ, several confounding factors contribute to the heterogeneity of the findings. In the future, we encourage the scientific community to perform studies with more extensive sampling and validation cohorts, integrating omics with bioinformatics tools to provide additional comprehension of differentially expressed proteins. The produced information could harbor potential proteomic biomarkers of SCZ, contributing to individualized prognosis and stratification strategies, besides aiding in the differential diagnosis.     

Effects of Low-Intensity and Long-Term Aerobic Exercise on the Psoas Muscle of mdx Mice: An Experimental Model of Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is a muscle disease characterized by the absence of the protein dystrophin, which causes a loss of sarcolemma integrity, determining recurrent muscle injuries, decrease in muscle function, and progressive degeneration. Currently, there is a need for therapeutic treatments to improve the quality of life of DMD patients. Here, we investigated the effects of a low-intensity aerobic training (37 sessions) on satellite cells, peroxisome proliferator-activated receptor-gamma coactivator (PGC)-1α protein (PGC-1α), and different types of fibers of the psoas muscle from mdx mice (DMD experimental model). Wildtype and mdx mice were randomly divided into sedentary and trained groups (n = 24). Trained animals were subjected to 37 sessions of low-intensity running on a motorized treadmill. Subsequently, the psoas muscle was excised and analyzed by immunofluorescence for dystrophin, satellite cells, myosin heavy chain (MHC), and PGC-1α content. The minimal Feret’s diameters of the fibers were measured, and light microscopy was applied to observe general morphological features of the muscles. The training (37 sessions) improved morphological features in muscles from mdx mice and caused an increase in the number of quiescent/activated satellite cells. It also increased the content of PGC-1α in the mdx group. We concluded that low-intensity aerobic exercise (37 sessions) was able to reverse deleterious changes determined by DMD.     

化学纤维的发展特点及趋势

从化学纤维的发展历程来说,过去一段时期内其经历了快速发展,并将在未来很长时期内持续这一态势,在这一过程中这类纤维的发展使命已经发生了飞跃,其最新进展不仅保持了化学纤维的可持续性,还带来了性能上的提升。     

Improved diagnosis using enhanced fault dominance

Defect diagnosis can benefit from fault dominance relations to reduce the set of defect candidate sites. This paper presents new fault dominance collapsing operators that further reduce the set of candidates considered during the initial phase of diagnosis. In contrast to existing dominance-based methods which operate on pairs of faults, the proposed method operates on sets of faults. Fault-related entities are generated to guide the diagnosis process. The proposed collapsing operators can be used to accelerate effect-cause diagnosis. Experimental results demonstrate that the proposed method achieves a higher collapsing ratio than existing methods.     

玛丽蒂姆会议酒店,柏林,德国

立面、周边环境以及对所在街区的一系列回应,是玛丽蒂姆酒店的设计要点。这个占地约1.2万m2的酒店基地紧邻文化中心（Kulturforum）和著名的文物保护建筑贝壳屋（Shellhaus,建筑师：Emil Fahrenkamp）,且距国家美术馆和波茨坦广场不远。     

Exploring the universality of personality judgments: Evidence from the great transformation (1000 BCE–200 BCE).

We examined whether personality judgments were present in texts of the diverse religious and philosophical traditions that emerged during the Great Transformation, an era spanning roughly 1000 BCE to 200 BCE. Some psychologists have suggested that the tendency of humans to judge personality has evolved; if some ancient societies failed to record personality judgments, it would be evidence against such an evolutionary position. In addition, learning about the prevalence and specifics of ancient personality judgments can help psychologists better understand the prehistory of personality psychology. Eight cultural traditions were studied: two each from China (Confucianism, Taoism), Greece (Classical and Hellenistic philosophy), India (Buddhism, Hinduism), and the Middle East (Judaism, Zoroastrianism). We found evidence that personality judgments were an important aspect of all of these traditions. Not only did people judge one another, but they also offered instructions on how to judge others. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

On the formalization and reuse of scientific research

The reuse of scientific knowledge obtained from one investigation in another investigation is basic to the advance of science. Scientific investigations should therefore be recorded in ways that promote the reuse of the knowledge they generate. The use of logical formalisms to describe scientific knowledge has potential advantages in facilitating such reuse. Here, we propose a formal framework for using logical formalisms to promote reuse. We demonstrate the utility of this framework by using it in a worked example from biology: demonstrating cycles of investigation formalization [F] and reuse [R] to generate new knowledge. We first used logic to formally describe a Robot scientist investigation into yeast (Saccharomyces cerevisiae) functional genomics [f₁]. With Robot scientists, unlike human scientists, the production of comprehensive metadata about their investigations is a natural by-product of the way they work. We then demonstrated how this formalism enabled the reuse of the research in investigating yeast phenotypes [r₁ = R(f₁)]. This investigation found that the removal of non-essential enzymes generally resulted in enhanced growth. The phenotype investigation was then formally described using the same logical formalism as the functional genomics investigation [f₂ = F(r₁)]. We then demonstrated how this formalism enabled the reuse of the phenotype investigation to investigate yeast systems-biology modelling [r₂ = R(f₂)]. This investigation found that yeast flux-balance analysis models fail to predict the observed changes in growth. Finally, the systems biology investigation was formalized for reuse in future investigations [f₃ = F(r₂)]. These cycles of reuse are a model for the general reuse of scientific knowledge.