Notes

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The high concentration was due to low ventilation suction flow. We can improve health to reduce exposure by resolving the fundamental cause of risk occurrence.The attribution of changing intensity of rainfall extremes to global warming is a key challenge of climate research. From a thermodynamic perspective, via the Clausius-Clapeyron relationship, rainfall events are expected to become stronger due to the increased water-holding capacity of a warmer atmosphere. Here, we employ global, 1-hourly temperature and 3-hourly rainfall data to investigate the scaling between temperature and extreme rainfall. Although the Clausius-Clapeyron scaling of +7% rainfall intensity increase per degree warming roughly holds on a global average, we find very heterogeneous spatial patterns. Over tropical oceans, we reveal areas with consistently strong negative scaling (below -40%∘C-1). We show that the negative scaling is due to a robust linear correlation between pre-rainfall cooling of near-surface air temperature and extreme rainfall intensity. We explain this correlation by atmospheric and oceanic dynamics associated with cyclonic activity. Our results emphasize that thermodynamic arguments alone are not enough to attribute changing rainfall extremes to global warming. Circulation dynamics must also be thoroughly considered.Monitoring community psychological and behavioural responses to coronavirus disease 2019 (COVID-19) is important for informing policy making and risk communication to sustain public compliance with challenging precautionary behaviours and mitigating the psychological impacts. Monthly telephone-based cross-sectional surveys in January-April 2020 and then weekly surveys from May through December 2020 were conducted to monitor changes in public risk perception of COVID-19, personal efficacy in self-protection, confidence in government's ability to control the pandemic, precautionary behaviours, perceived impact of precautionary behaviours, psychological fatigue and distress in Hong Kong, and examine their inter-relationships. While worry about contracting COVID-19 increased, personal efficacy and confidence in government declined as the community incidence of COVID-19 increased. The public maintained high compliance with most precautionary behaviours throughout but relaxed behaviours that were more challenging when disease incidence declined. Public confidence in government was persistently low throughout, of which, a lower level was associated with more psychological fatigue, lower compliance with precautionary behaviours and greater psychological distress. Perceived greater negative impact of precautionary behaviours was also associated with more psychological fatigue which in turn was associated with relaxation of precautionary behaviours. Female, younger and unemployed individuals reported greater psychological distress throughout different stages of the pandemic. Risk communication should focus on promoting confidence in self-protection and pandemic control to avoid helplessness to act when the pandemic resurges. Policy making should prioritize building public trust, enhancing support for sustaining precautionary behaviours, and helping vulnerable groups to adapt to the stress during the pandemic.The dynamics of epidemics depend on how people's behavior changes during an outbreak. At the beginning of the epidemic, people do not know about the virus, then, after the outbreak of epidemics and alarm, they begin to comply with the restrictions and the spreading of epidemics may decline. Over time, some people get tired/frustrated by the restrictions and stop following them (exhaustion), especially if the number of new cases drops down. After resting for a while, they can follow the restrictions again. But during this pause the second wave can come and become even stronger then the first one. Studies based on SIR models do not predict the observed quick exit from the first wave of epidemics. Social dynamics should be considered. The appearance of the second wave also depends on social factors. Many generalizations of the SIR model have been developed that take into account the weakening of immunity over time, the evolution of the virus, vaccination and other medical and biological details. However, these more sophisticated models do not explain the apparent differences in outbreak profiles between countries with different intrinsic socio-cultural features. In our work, a system of models of the COVID-19 pandemic is proposed, combining the dynamics of social stress with classical epidemic models. Social stress is described by the tools of sociophysics. The combination of a dynamic SIR-type model with the classical triad of stages of the general adaptation syndrome, alarm-resistance-exhaustion, makes it possible to describe with high accuracy the available statistical data for 13 countries. The sets of kinetic constants corresponding to optimal fit of model to data were found. These constants characterize the ability of society to mobilize efforts against epidemics and maintain this concentration over time and can further help in the development of management strategies specific to a particular society.Inherited retinal diseases (IRDs) are a major cause of visual impairment. These clinically heterogeneous disorders are caused by pathogenic variants in more than 270 genes. As 30-40% of cases remain genetically unexplained following conventional genetic testing, we aimed to obtain a genetic diagnosis in an IRD cohort in which the genetic cause was not found using whole-exome sequencing or targeted capture sequencing. We performed whole-genome sequencing (WGS) to identify causative variants in 100 unresolved cases. After initial prioritization, we performed an in-depth interrogation of all noncoding and structural variants in genes when one candidate variant was detected. In addition, functional analysis of putative splice-altering variants was performed using in vitro splice assays. We identified the genetic cause of the disease in 24 patients. Causative coding variants were observed in genes such as ATXN7, CEP78, EYS, FAM161A, and HGSNAT. Gene disrupting structural variants were also detected in ATXN7, PRPF31, and RPGRIP1. In 14 monoallelic cases, we prioritized candidate noncanonical splice sites or deep-intronic variants that were predicted to disrupt the splicing process based on in silico analyses. Of these, seven cases were resolved as they carried pathogenic splice defects. selleck chemical WGS is a powerful tool to identify causative variants residing outside coding regions or heterozygous structural variants. This approach was most efficient in cases with a distinct clinical diagnosis. In addition, in vitro splice assays provide important evidence of the pathogenicity of rare variants.Tumor metabolism patterns have been reported to be associated with the prognosis of many cancers. However, the metabolic mechanisms underlying prostate cancer (PCa) remain unknown. This study aimed to explore the metabolic characteristics of PCa. First, we downloaded mRNA expression data and clinical information of PCa samples from multiple databases and quantified the metabolic pathway activity level using single-sample gene set enrichment analysis (ssGSEA). Through unsupervised clustering and principal component analyses, we explored metabolic characteristics and constructed a metabolic score for PCa. Then, we independently validated the prognostic value of our metabolic score and the nomogram based on the metabolic score in multiple databases. Next, we found the metabolic score to be closely related to the tumor microenvironment and DNA mutation using multi-omics data and ssGSEA. Finally, we found different features of drug sensitivity in PCa patients in the high/low metabolic score groups. In total, 1232 samples were analyzed in the present study. Overall, an improved understanding of tumor metabolism through the characterization of metabolic clusters and metabolic score may help clinicians predict prognosis and aid the development of more personalized anti-tumor therapeutic strategies for PCa.The COVID-19 pandemic caused by SARS-CoV-2 has infected millions worldwide, therefore there is an urgent need to increase our diagnostic capacity to identify infected cases. Although RT-qPCR remains the gold standard for SARS-CoV-2 detection, this method requires specialised equipment in a diagnostic laboratory and has a long turn-around time to process the samples. To address this, several groups have recently reported the development of loop-mediated isothermal amplification (LAMP) as a simple, low cost and rapid method for SARS-CoV-2 detection. Herein we present a comparative analysis of three LAMP-based assays that target different regions of the SARS-CoV-2 ORF1ab RdRP, ORF1ab nsp3 and Gene N. We perform a detailed assessment of their sensitivity, kinetics and false positive rates for SARS-CoV-2 diagnostics in LAMP or RT-LAMP reactions, using colorimetric or fluorescent detection. Our results independently validate that all three assays can detect SARS-CoV-2 in 30 min, with robust accuracy at detecting as little as 1000 RNA copies and the results can be visualised simply by color changes. Incorporation of RT-LAMP with fluorescent detection further increases the detection sensitivity to as little as 100 RNA copies. We also note the shortcomings of some LAMP-based assays, including variable results with shorter reaction time or lower load of SARS-CoV-2, and false positive results in some experimental conditions and clinical saliva samples. Overall for RT-LAMP detection, the ORF1ab RdRP and ORF1ab nsp3 assays have faster kinetics for detection but varying degrees of false positives detection, whereas the Gene N assay exhibits no false positives in 30 min reaction time, which highlights the importance of optimal primer design to minimise false-positives in RT-LAMP. This study provides validation of the performance of LAMP-based assays as a rapid, highly sensitive detection method for SARS-CoV-2, which have important implications in development of point-of-care diagnostics for SARS-CoV-2.Herein it was evaluated the impact of PD-L1 immunohistochemical expression and stromal tumor-infiltrating lymphocyte (sTIL) counts in pretreatment needle core biopsy on response to neoadjuvant chemotherapy (NACT) for patients with breast carcinomas (BC). In 127 paired pre- and post-NACT BC specimens, immunohistochemical expression of PD-L1 was evaluated in stroma and in neoplastic cells. In the same samples sTILs were semi-quantified in tumor stroma. Post-NACT specimens were histologically rated as having residual cancer burden (RCB of any degree), or with complete pathological response (pCR). PD-L1 expression and higher sTIL counts were associated with histological grade 3 BC. PD-L1 expression was also associated with the non-luminal-HER2+ and triple negative immunohistochemical profiles of BC. Pathological complete response was associated with histological grade 3 tumors, and with the non-luminal-HER2+ and triple negative profiles. Additionally, our results support an association between PD-L1 expression and pCR to NACT. It was also observed that there is a trend to reduction of sTIL counts in the post-NACT specimens of patients with pCR. Of note, PD-L1 was expressed in half of the hormone receptor positive cases, a finding that might expand the potential use of immune checkpoint inhibitors for BC patients.
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