Occupational skin diseases and prevention among sanitation workers in China

Background: Little research has been focused on the health status or the occupational protection awareness of sanitation workers. The policy recommendations on the occupational safety and health of sanitation workers based on the scientific research are also insufficient in developing countries like China. Objective: To study the incidence of dermatoses and the relevance with occupational exposure, protection awareness and protective measures among sanitation workers for better management and protection of the sanitation workers. Methods: 273 sanitation workers and 113 administrative staff from 11 streets of Wuhan were recruited. Dermatological problems were evaluated and recorded by physical examination. Occupational exposure, protection awareness, the use of protective equipments and personal history of skin disease were assessed by questionnaires. Results: Compared with administrative staff, sanitation workers had much more occupational dermatological problems and had a much higher rate of harmful ultraviolet ray exposure. Young sanitation workers were more aware of occupational self-protection and a relatively higher rate of them using protective equipments compared with old ones. Conclusion: Exposure to multiple health hazards and the poor use of protective equipments are related to skin diseases in sanitation workers. Prejob training of self-protection and the use of protective equipments are recommended

Anti-PD-1 immunotherapy combined with stereotactic body radiation therapy and GM-CSF for the treatment of advanced malignant PEComa: A case report

BackgroundPerivascular epithelioid cell neoplasm (PEComa) is a rare mesenchymal tumour. Due to its low incidence, a standard treatment regimen for PEComa has not yet been established. Radiotherapy has a synergistic effect with PD-1 inhibitors and GM-CSF. We treated advanced malignant PEComa with a triple regimen of PD-1 inhibitor, SBRT and GM-CSF to provide better therapeutic effect.Case presentationA 63-year-old woman was diagnosed with malignant PEComa after presenting with postmenopausal vaginal bleeding. Despite two surgeries, the neoplasm eventually metastasized throughout the body. We formulated triple therapy with SBRT, a PD-1 inhibitor, and GM-CSF for the patient. The patient’s local symptoms were controlled at the radiotherapy site, and the lesions at the unirradiated sites were also relieved.ConclusionsFor the first time, a triple regimen of PD-1 inhibitor, SBRT and GM-CSF was used in the treatment of malignant PEComa and achieved good efficacy. Considering the lack of prospective clinical studies in PEComa, we believe that this triple therapy is a good-quality regimen for advanced malignant PEComa

HSPA12A Unstabilizes CD147 to Inhibit Lactate Export and Migration in Human Renal Cell Carcinoma

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions. Background: Metastasis accounts for 90% of cancer-associated mortality in patients with renal cell carcinoma (RCC). However, the clinical management of RCC metastasis is challenging. Lactate export is known to play an important role in cancer cell migration. This study investigated the role of heat shock protein A12A (HSPA12A) in RCC migration. Methods: HSPA12A expression was examined in 82 pairs of matched RCC tumors and corresponding normal kidney tissues from patients by immunoblotting and immunofluorescence analyses. The proliferation of RCC cells was analyzed using MTT and EdU incorporation assays. The migration of RCC cells was evaluated by wound healing and Transwell migration assays. Extracellular acidification was examined using Seahorse technology. Protein stability was determined following treatment with protein synthesis inhibitor cycloheximide and proteasome inhibitor MG132. Mass spectrometry, immunoprecipitation, and immunoblotting were employed to examine protein-protein interactions. Results: RCC tumors from patients showed downregulation of HSPA12A, which was associated with advanced tumor node metastasis stage. Intriguingly, overexpression of HSPA12A in RCC cells inhibited migration, whereas HSPA12A knockdown had the opposite effect. Lactate export, glycolysis rate, and CD147 protein abundance were also inhibited by HSPA12A overexpression but promoted by HSPA12A knockdown. An interaction of HSPA12A with HRD1 ubiquitin E3 ligase was detected in RCC cells. Further studies demonstrated that CD147 ubiquitination and proteasomal degradation were promoted by HSPA12A overexpression whereas inhibited by HSPA12A knockdown. Notably, the HSPA12A overexpression-induced inhibition of lactate export and migration were abolished by CD147 overexpression. Conclusion: Human RCC shows downregulation of HSPA12A. Overexpression of HSPA12A in RCC cells unstabilizes CD147 through increasing its ubiquitin-proteasome degradation, thereby inhibits lactate export and glycolysis, and ultimately suppresses RCC cell migration. Our results demonstrate that overexpression of HSPA12A might represent a viable strategy for managing RCC metastasis

An Engineered Arginase FC Protein Inhibits Tumor Growth In Vitro

Arginine is a semiessential amino acid required for the growth of melanoma and hepatocellular carcinoma, and the enzymatic removal of arginine by pegylated arginine deiminase (ADI) or arginase is being tested clinically. Here, we report a genetically engineered arginase FC fusion protein exhibiting a prolonged half-life and enhanced efficacy. The use of this enzyme to treat different tumor lines both inhibited cell proliferation and impaired cellular migration in vitro and in vivo. Our data reinforce the hypothesis that nutritional depletion is a key strategy for cancer treatment

Momordicoside G Regulates Macrophage Phenotypes to Stimulate Efficient Repair of Lung Injury and Prevent Urethane-Induced Lung Carcinoma Lesions

Momordicoside G is a bioactive component from Momordica charantia, this study explores the contributions of macrophages to the effects of momordicoside G on lung injury and carcinoma lesion. In vitro, when administered at the dose that has no effect on cell viability in M2-like macrophages, momordicoside G decreased ROS and promoted autophagy and thus induced apoptosis in M1-like macrophages with the morphological changes. In the urethane-induced lung carcinogenic model, prior to lung carcinoma lesions, urethane induced obvious lung injury accompanied by the increased macrophage infiltration. The lung carcinoma lesions were positively correlated with lung tissue injury and macrophage infiltration in alveolar cavities in the control group, these macrophages showed mainly a M1-like (iNOS+/CD68+) phenotype. ELISA showed that the levels of IL-6 and IL-12 were increased and the levels of IL-10 and TGF-β1 were reduced in the control group. After momordicoside G treatment, lung tissue injury and carcinoma lesions were ameliorated with the decreased M1-like macrophages and the increased M2-like (arginase+/CD68+) macrophages, whereas macrophage depletion by liposome-encapsulated clodronate (LEC) decreased significantly lung tissue injury and carcinoma lesions and also attenuated the protective efficacy of momordicoside G. The M2 macrophage dependent efficacy of momordicoside G was confirmed in a LPS-induced lung injury model in which epithelial closure was promoted by the transfer of M2-like macrophages and delayed by the transfer of M1-like macrophages. To acquire further insight into the underlying molecular mechanisms by which momordicoside G regulates M1 macrophages, we conduct a comprehensive bioinformatics analysis of momordicoside G relevant targets and pathways involved in M1 macrophage phenotype. This study suggests a function of momordicoside G, whereby it selectively suppresses M1 macrophages to stimulate M2-associated lung injury repair and prevent inflammation-associated lung carcinoma lesions

Functional Mapping of Dynamic Traits with Robust t-Distribution

Functional mapping has been a powerful tool in mapping quantitative trait loci (QTL) underlying dynamic traits of agricultural or biomedical interest. In functional mapping, multivariate normality is often assumed for the underlying data distribution, partially due to the ease of parameter estimation. The normality assumption however could be easily violated in real applications due to various reasons such as heavy tails or extreme observations. Departure from normality has negative effect on testing power and inference for QTL identification. In this work, we relax the normality assumption and propose a robust multivariate -distribution mapping framework for QTL identification in functional mapping. Simulation studies show increased mapping power and precision with the distribution than that of a normal distribution. The utility of the method is demonstrated through a real data analysis

SVSI: Fast and Powerful Set-Valued System Identification Approach to Identifying Rare Variants in Sequencing Studies for Ordered Categorical Traits: SVSIfor Genetic Association Studies

For genetic association studies that involve an ordered categorical phenotype, we usually either regroup multiple categories of the phenotype into two categories (“cases” and “controls”) and then apply the standard logistic regression (LG), or apply ordered logistic (oLG) or ordered probit (oPRB) regression which accounts for the ordinal nature of the phenotype. However, these approaches may lose statistical power or may not control type I error rate due to their model assumption and/or instable parameter estimation algorithm when the genetic variant is rare or sample size is limited. Here to solve this problem, we propose a set-valued (SV) system model, which assumes that an underlying continuous phenotype follows a normal distribution, to identify genetic variants associated with an ordinal categorical phenotype. We couple this model with a set-valued system identification algorithm to identify all the key system parameters. Simulations and two real data analyses show that SV and LG accurately controlled the Type I error rate even at a significance level of 10−6 but not oLG and oPRB in some cases. LG had significantly smaller power than the other three methods due to disregarding of the ordinal nature of the phenotype, and SV had similar or greater power than oLG and oPRB. For instance, in a simulation with data generated from an additive SV model with odds ratio of 7.4 for a phenotype with three categories, a single nucleotide polymorphism with minor allele frequency of 0.75% and sample size of 999 (333 per category), the power of SV, oLG and LG models were 70%, 40% and <1%, respectively, at a significance level of 10−6. Thus, SV should be employed in genetic association studies for ordered categorical phenotype

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Will Digital Financial Inclusion Increase Chinese Farmers’ Willingness to Adopt Agricultural Technology?

Studies consider the impact of financial support on agricultural technology adoption, but do not consider the role of the rapidly evolving Digital Financial Inclusion (DFI). This study analyzes the impact of DFI on farmers’ willingness to adopt agricultural technology (WTAAT) using data from the China Labor-force Dynamics Survey and the Digital Financial Inclusion Index of Peking University, China. The results show that DFI significantly increases farmers’ WTAAT, consistent with the results of robustness tests. Moreover, the analysis of moderating effects shows that the contribution of DFI to WTAAT increases with the level of financial market development. Finally, WTAAT is affected by DFI development among farmers who receive government subsidies, participate in production technology training, and have no local non-agricultural economy. Therefore, we propose policy recommendations for developing DFI in rural areas, improving the financial market environment, and increasing subsidies and technical training. Our study provides some empirical evidence for exploring the field of agricultural technology adoption from the perspective of DFI and also provides new ideas for combining the digital transformation of finance with sustainable agricultural development, enriching the development of research in this field, which may also provide policy insights for the development of agricultural modernization in China and other countries