Emotions, COVID-19 related thoughts and satisfaction with life during the critical period from control to relaxation

IntroductionIn the context of declining mortality rates and increasing infectivity, it has become unavoidable for the majority of individuals to experience a COVID-19 infection at some point. This study aimed to investigate the psychological well-being of the general population during China’s transition period from strict control measures to relaxed policies in COVID-19 prevention and control, as well as the impact of COVID-19 related thoughts on emotion and life satisfaction during widespread infections.MethodsA cross-sectional study was conducted involving a sample size of 1578 participants. Participants completed self-report questionnaires assessing positive and negative emotions, thoughts about COVID-19, and satisfaction with life. Demographic characteristics such as sex, age, and education level were controlled for in the analysis.ResultsThe findings revealed that individuals who had been infected with COVID-19 (specifically the Omicron variant BA.5.2 or BF.7) reported lower levels of positive emotions compared to those who were uninfected or had recovered from the infection. There was a significant relationship between COVID-19-related thoughts, emotions, and life satisfaction. Positive COVID-19 related thoughts were found to mediate the relationship between negative emotions and satisfaction with life.DiscussionThis study represents a comprehensive examination conducted in China, focusing on assessing the impact of the COVID-19 pandemic on the general population during the critical transition period from control to relaxation. Throughout this period, the number of infections experienced fluctuations, initially rising but eventually declining over a one-month span. In such a momentous historical period, maintaining a positive perspective on COVID-19 and its management becomes paramount in enhancing the emotional well-being, life satisfaction and overall well-being of individuals

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

The progress and development of antidepressants

Major depressive disorder is a common emotional mood disorder disease, which mainly manifests as depression, cognitive impairment, weakened volition activities, loss of appetite, and sleep disorders. Depression is a common mental disorder affecting more than 264 million people worldwide. There are many antidepressant drugs in clinic, e.g., tricyclic antidepressants, monoamine oxidase inhibitors, selective serotonin (5-HT) reuptake inhibitors and selective norepinephrine (NA) reuptake inhibitors. Although great progress has been made in the research of new antidepressant drugs, the current clinical use of drugs still has many shortcomings, e.g., the unmet efficiency, slow onset of action, and multiple adverse reactions, which are difficult to meet the requirements of the increasing number of the depressed patients. This article mainly focuses on the development process of antidepressant drugs and compares their effects. Specifically, the N-methyl-D-aspartate receptor as a new antidepressant has a good effect, which is worthy of further study. These results shed light for providing a research idea for the study of new antidepressants

Depletion of CUL4B in macrophages ameliorates diabetic kidney disease via miR-194-5p/ITGA9 axis

Summary: Diabetic kidney disease (DKD) is the most prevalent chronic kidney disease. Macrophage infiltration in the kidney is critical for the progression of DKD. However, the underlying mechanism is far from clear. Cullin 4B (CUL4B) is the scaffold protein in CUL4B-RING E3 ligase complexes. Previous studies have shown that depletion of CUL4B in macrophages aggravates lipopolysaccharide-induced peritonitis and septic shock. In this study, using two mouse models for DKD, we demonstrate that myeloid deficiency of CUL4B alleviates diabetes-induced renal injury and fibrosis. In vivo and in vitro analyses reveal that loss of CUL4B suppresses migration, adhesion, and renal infiltration of macrophages. Mechanistically, we show that high glucose upregulates CUL4B in macrophages. CUL4B represses expression of miR-194-5p, which leads to elevated integrin α9 (ITGA9), promoting migration and adhesion. Our study suggests the CUL4B/miR-194-5p/ITGA9 axis as an important regulator for macrophage infiltration in diabetic kidneys

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press