A chimeric mRNA vaccine of S-RBD with HA conferring broad protection against influenza and COVID-19 variants.

Influenza and coronavirus disease 2019 (COVID-19) represent two respiratory diseases that have significantly impacted global health, resulting in substantial disease burden and mortality. An optimal solution would be a combined vaccine capable of addressing both diseases, thereby obviating the need for multiple vaccinations. Previously, we conceived a chimeric protein subunit vaccine targeting both influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), utilizing the receptor binding domain of spike protein (S-RBD) and the stalk region of hemagglutinin protein (HA-stalk) components. By integrating the S-RBD from the SARS-CoV-2 Delta variant with the headless hemagglutinin (HA) from H1N1 influenza virus, we constructed stable trimeric structures that remain accessible to neutralizing antibodies. This vaccine has demonstrated its potential by conferring protection against a spectrum of strains in mouse models. In this study, we designed an mRNA vaccine candidate encoding the chimeric antigen. The resultant humoral and cellular immune responses were meticulously evaluated in mouse models. Furthermore, the protective efficacy of the vaccine was rigorously examined through challenges with either homologous or heterologous influenza viruses or SARS-CoV-2 strains. Our findings reveal that the mRNA vaccine exhibited robust immunogenicity, engendering high and sustained levels of neutralizing antibodies accompanied by robust and persistent cellular immunity. Notably, this vaccine effectively afforded complete protection to mice against H1N1 or heterosubtypic H5N8 subtypes, as well as the SARS-CoV-2 Delta and Omicron BA.2 variants. Additionally, our mRNA vaccine design can be easily adapted from Delta RBD to Omicron RBD antigens, providing protection against emerging variants. The development of two-in-one vaccine targeting both influenza and COVID-19, incorporating the mRNA platform, may provide a versatile approach to combating future pandemics.

Associations of genetic variation in E3 SUMO-protein ligase CBX4 with noise-induced hearing loss.

Noise-induced hearing loss (NIHL) is a multifactorial disease caused by environmental, genetic and epigenetic variables. SUMOylation is a post-translational modification that regulates biological processes. The objective of this study was to determine the link between genetic variation in the chromobox 4 (CBX4) and the risk of NIHL. This study applied a case-control design with 588 cases and 582 controls, and the sample was predominantly male (93.76%). The T allele of CBX4 rs1285250 was found to be significantly linked with NIHL (P = 0.002) and showed strong associations in both the codominant and recessive models (TT versus CC, P = 0.005; TT/TC versus CC, P = 0.009). By constructing a mouse model of hearing loss because of noise exposure, changes in hearing thresholds were observed in noise-exposed mice, along with a decrease in the number of cochlear hair cells. Furthermore, noise promotes cochlear hair cell apoptosis by inducing SP1/CBX4 pathway activation. Further functional studies demonstrated that SP1 has an influence on the promoter activity of the CBX4 rs1285250 intron, with the promoter activity of the T allele being higher than that of the C allele. Knockdown of transcription factor SP1 reduced the expression of CBX4 expression and simultaneously reduced apoptosis in HEI-OC1 cells. Together, our findings have shown that CBX4 genetic polymorphism rs1285250 T-allele was associated with increased risk of NIHL and might be used as biomarkers for male workers exposed to noise. Furthermore, we speculate that the CBX4 of rs1285250 T-allele leads to a stronger potential enhancer activity from a predicted gain of stronger SP1 binding.

G6PD and machine learning algorithms as prognostic and diagnostic indicators of liver hepatocellular carcinoma.

BACKGROUND: Liver Hepatocellular carcinoma (LIHC) exhibits a high incidence of liver cancer with escalating mortality rates over time. Despite this, the underlying pathogenic mechanism of LIHC remains poorly understood. MATERIALS & METHODS: To address this gap, we conducted a comprehensive investigation into the role of G6PD in LIHC using a combination of bioinformatics analysis with database data and rigorous cell experiments. LIHC samples were obtained from TCGA, ICGC and GEO databases, and the differences in G6PD expression in different tissues were investigated by differential expression analysis, followed by the establishment of Nomogram to determine the percentage of G6PD in causing LIHC by examining the relationship between G6PD and clinical features, and the subsequent validation of the effect of G6PD on the activity, migration, and invasive ability of hepatocellular carcinoma cells by using the low expression of LI-7 and SNU-449. Additionally, we employed machine learning to validate and compare the predictive capacity of four algorithms for LIHC patient prognosis. RESULTS: Our findings revealed significantly elevated G6PD expression levels in liver cancer tissues as compared to normal tissues. Meanwhile, Nomogram and Adaboost, Catboost, and Gbdt Regression analyses showed that G6PD accounted for 46%, 31%, and 49% of the multiple factors leading to LIHC. Furthermore, we observed that G6PD knockdown in hepatocellular carcinoma cells led to reduced proliferation, migration, and invasion abilities. Remarkably, the Decision Tree C5.0 decision tree algorithm demonstrated superior discriminatory performance among the machine learning methods assessed. CONCLUSION: The potential diagnostic utility of G6PD and Decision Tree C5.0 for LIHC opens up a novel avenue for early detection and improved treatment strategies for hepatocellular carcinoma.

UBE2L3 promotes benzene-induced hematotoxicity via autophagy-dependent ferroptosis.

Benzene is a common environmental pollutant and significant health hazard. Low-dose benzene exposure is common in most industrial settings, and some workers exhibit hematotoxicity characterized by impaired hematopoietic function. Consequently, understanding the early hematopoietic damage and biomarkers associated with low-dose benzene exposure is of critical importance for health risk assessment. Using data from a 5-year prospective cohort study on benzene exposure and the National Center for Biotechnology Information's Gene Expression Omnibus database, we detected significant downregulation of the ubiquitin-conjugating enzyme UBE2L3 (E2) in benzene-exposed subjects compared to control subjects. Liquid chromatography tandem mass spectrometry and co-immunoprecipitation experiments illustrated the binding interaction between UBE2L3 and the ubiquitin-protein ligase ZNF598 (E3). We applied deep learning algorithms to predict candidate interacting proteins and then conducted validation via co-immunoprecipitation experiments, which showed that ZNF598 engages in binding with the autophagy protein LAMP-2. Subsequent overexpression and knockdown of UBE2L3 coupled with immunofluorescence experiments and transmission electron microscopy revealed that UBE2L3 disrupts the ubiquitination-degradation of LAMP-2 by ZNF598, reduces GPX4 expression levels, and activates an autophagy-dependent ferroptosis pathway. It also leads to increased lipid peroxidation, thereby promoting ferroptosis and contributing to the hematotoxicity induced by benzene. In summary, our results suggest that UBE2L3 may be involved in early hematopoietic damage by modulating the autophagy-dependent ferroptosis signaling pathway in benzene-induced hematotoxicity.

Yield and Efficiency of a Population-Based Mass Tuberculosis Screening Intervention Among Persons With Diabetes in Jiangsu Province, China.

BACKGROUND: The evidence-base for mass tuberculosis screening among persons with diabetes (PWD) is poor. We evaluated the yield and costs of mass screening among PWD in eastern China. METHODS: We included individuals with type 2 diabetes from 38 townships in Jiangsu Province. Screening comprised of physical examinations, symptom screening, and chest X-rays; smear and culture testing were performed through clinical triage. We assessed the yield and number needed to screen (NNS) to detect 1 tuberculosis case among all PWD, those with symptoms, and with suggestive chest X-rays. Unit costing was collected to estimate screening costs and to calculate cost per case detected. We performed a systematic review of other mass tuberculosis screening programs concentrated on PWD. RESULTS: Of 89 549 screened PWD, 160 were diagnosed with tuberculosis (179 cases per 100 000 persons; 95% confidence interval [CI]: 153-205). The NNS was 560 (95% CI: 513-606), 248 (95% CI: 217-279), and 36 (95% CI: 24-48) among all participants, with abnormal chest X-rays, and symptoms. The cost per case was high overall (US$13 930) but lower with symptoms (US$1037) and high fasting blood glucose levels (US$6807). From systematic review, the pooled NNS to detect one case among all PWD (regardless of symptoms or chest X-ray results) in high- versus low-burden settings was 93 (95% CI: 70-141) versus 395 (95% CI: 283-649). CONCLUSIONS: A mass tuberculosis screening program focused on PWD was feasible however, the overall yield was low and not cost-efficient. Risk-stratified approaches may be practical among PWD in low- and medium tuberculosis burden settings.

Postmortem biochemical analysis of soluble ST2 in the pericardial fluid of patients with sudden cardiac death caused by ischemic heart disease: a pilot study.

Soluble growth stimulation expressed gene 2 protein (sST2) is a myocardial protein induced by biomechanical stress. sST2 is widely present in the serum of patients with heart failure and is recommended as an important indicator to predict adverse outcomes in these patients. However, no postmortem biochemical analysis of sST2 in forensic practice has been reported. The present pilot study aimed to investigate the expression of sST2 in the pericardial fluid of patients with sudden cardiac death (SCD) caused by ischemic heart disease (IHD). In addition, to explore the relationship of sST2 with CK-MB, cTnT, and NT-proBNP, which have been proven to be auxiliary biomarkers for the diagnosis of SCD, we analyzed CK-MB, cTnT, NT-proBNP, and sST2 levels in twenty-one pericardial fluid samples from the Center of Forensic Investigation, China Medical University, with a Roche cobas e 411 electrochemiluminescence automatic immunoassay system and ST2/IL-33R Valukine™ enzyme-linked immunosorbent assay kit. The levels of sST2 in the pericardial fluid of patients with SCD caused by IHD were significantly increased (P < 0.01) and positively correlated with CK-MB and NT-proBNP (P < 0.0001). Receiver operating characteristic curve analysis indicated that the combined measurement of sST2 and NT-proBNP has a higher diagnostic value for SCD caused by IHD than the measurement of either indicator alone. This study preliminarily demonstrated that sST2 in the pericardial fluid was significantly increased in patients with SCD caused by IHD and might be used as a novel auxiliary biomarker for postmortem diagnosis of SCD in forensic practice.

The impact of intestinal microbiota in antithymocyte globulin-based myeloablative allogeneic hematopoietic cell transplantation.

BACKGROUND: The correlation between intestinal microbiota and clinical outcomes after allogeneic hematopoietic stem cell transplantation (allo-HCT) has been reported in platforms with T-cell depletion or postcyclophosphamide-based graft-vs-host disease (GVHD) prophylaxis regimens. It is still unclear whether it is the same in platforms of antithymocyte globulin (ATG)-based myeloablative allo-HCT. METHODS: A total of 603 fecal specimens from 100 consecutive patients receiving allo-HCT were collected between December 2018 and July 2020. Fetal samples were profiled with next-generation sequencing of bacterial 16S ribosomal RNA (rRNA) genes. RESULTS: The diversity decreased to the lowest level at approximately day 12 after allo-HCT and then increased over time. According to the diversity of 314 samples that were collected from 86 patients during the engraftment period, patients were grouped into the low- and high-diversity groups. Two-year overall survival in the high-diversity group was significantly longer than that in the low-diversity group (83.7% vs 60.6%, P = .026). Further analysis revealed that worse outcomes for patients with low diversity were associated with increased risk of worse outcomes for patients with low diversity (adjusted hazard ratio, 4.95; P = .046). Its association with relapse and GVHD was not found. Compositional analysis of fecal microbiota revealed that the abundance of bacteroides decreased greatly during allo-HCT, whereas that of Enterococcus, Klebsiella, and Escherichia was found to be increased. CONCLUSIONS: This study indicates that gut dysbiosis in platforms of ATG-based myeloablative allo-HCT featured loss of bacterial diversity. The diversity of the intestinal flora at the engraftment period was an independent predictor of longer survival. LAY SUMMARY: The correlation between intestinal microbiota and clinical outcomes after allogeneic hematopoietic stem cell transplantation (allo-HCT) is reported in platforms with T-cell depletion or postcyclophosphamide-based graft-vs-host disease (GVHD) prophylaxis regimens. It is still unclear whether it is the same pattern in platforms of antithymocyte globulin (ATG)-based T-cell repletion myeloablative allo-HCT. Our study indicated that gut dysbiosis in platforms of ATG-based myeloablative allo-HCT also features loss of bacterial diversity. The diversity of the intestinal flora at the engraftment period is an independent predictor of longer survival.

Effects of Postmortem Hemolysis and Ultrafiltration on Creatinine Detection Results.

OBJECTIVES: To investigate the interference of postmortem hemolysis on the detection of creatinine and whether ultrafiltration can reduce the interference. METHODS: A total of 33 non-hemolyzed whole blood samples from the left heart were collected. Hemolyzed samples with 4 hemoglobin mass concentration gradients H1-H4 were artificially prepared. Ultrafiltration was performed on each hemolyzed sample. Creatinine concentrations in non-hemolyzed serum (baseline serum), hemolyzed samples and ultrafiltrate were detected. Bias (B), Pearson correlation and receiver operator characteristic (ROC) of baseline creatinine concentration between before and after ultrafiltration were analyzed. RESULTS: As the hemoglobin mass concentration increased, B of the hemolyzed samples in the H1-H4 groups gradually increased, the |B| was 2.41(0.82, 8.25)-51.31(41.79, 188.25), reaching a maximum of 589.06%, and there was no statistically significant between the creatinine concentration and the baseline creatinine concentration (P=0.472 7, r=0.129 5). After ultrafiltration of hemolyzed samples, the interference of creatinine concentration in ultrafiltrate was significantly reduced, the |B| was 5.32(2.26, 9.22)-21.74(20.06, 25.58), reaching a maximum of 32.14%, and there was a positive correlation with baseline creatinine concentration (P<0.05, r=0.918 2). In the hemolyzed samples of H3 and H4 groups, there were 7 false-positive samples and 1 false-negative sample; in the ultrafiltrate samples, there were no false-positive sample and 1 false-negative sample. ROC analysis results showed the hemolyzed samples were lack of diagnostic value (P=0.117 5). CONCLUSIONS: The postmortem hemolysis significantly interferes creatinine detection results of blood samples, ultrafiltration can reduce hemolysis-induced interference in postmortem creatinine detection.

Warming Shapes nirS- and nosZ-Type Denitrifier Communities and Stimulates N2O Emission in Acidic Paddy Soil.

Warming strongly stimulates soil nitrous oxide (N2O) emission, contributing to the global warming trend. Submerged paddy soils exhibit huge N2O emission potential; however, the N2O emission pathway and underlying mechanisms for warming are not clearly understood. We conducted an incubation experiment using 15N to investigate the dynamics of N2O emission at controlled temperatures (5, 15, 25, and 35°C) in 125% water-filled pore space. The community structures of nitrifiers and denitrifiers were determined via high-throughput sequencing of functional genes. Our results showed that elevated temperature sharply enhanced soil N2O emission from submerged paddy soil. Denitrification was the main contributor, accounting for more than 90% of total N2O emission at all treatment temperatures. N2O flux was coordinatively regulated by nirK-, nirS-, and nosZ-containing denitrifiers but not ammonia-oxidizing archaea or ammonia-oxidizing bacteria. The nirS-containing denitrifiers were more sensitive to temperature shifts, especially at a lower temperature range (5 to 25°C), and showed a stronger correlation with N2O flux than that of nirK-containing denitrifiers. In contrast, nosZ-containing denitrifiers exhibited substantial variation at higher temperatures (15 to 35°C), thereby playing an important role in N2O consumption. Certain taxa of nirS- and nosZ-containing denitrifiers regulated N2O flux, including nirS-containing denitrifiers affiliated with Rhodanobacter and Cupriavidus as well as nosZ-containing denitrifiers affiliated with Azoarcus and Azospirillum. Together, these findings suggest that elevated temperature can significantly increase N2O emission from denitrification in submerged paddy soils by shifting the overall community structures and enriching some indigenous taxa of nirS- and nosZ-containing denitrifiers. IMPORTANCE The interdependence between global warming and greenhouse gas N2O has always been the hot spot. However, information on factors contributing to N2O and temperature-dependent community structure changes is scarce. This study demonstrated high-temperature-induced N2O emission from submerged paddy soils, mainly via stimulating denitrification. Further, we speculate that key functional denitrifiers drive N2O emission. This study showed that denitrifiers were more sensitive to temperature rise than nitrifiers, and the temperature sensitivity differed among denitrifier communities. N2O-consuming denitrifiers (nosZ-containing denitrifiers) were more sensitive at a higher temperature range than N2O-producing denitrifiers (nirS-containing denitrifiers). This study's findings help predict N2O fluxes under different degrees of warming and develop strategies to mitigate N2O emissions from paddy fields based on microbial community regulation.

Interference of hemolysis on the postmortem biochemical analysis of IgE by ECLIA.

Forensic diagnosis of anaphylactic shock is a challenging task in forensic practice due to the lack of characteristic morphological changes. Postmortem analysis of serum IgE can provide helpful information for determining anaphylaxis. However, postmortem serum always suffers from hemolysis. To investigate the interference of hemolysis on postmortem analysis of total IgE by electrochemiluminescent immunoassay (ECLIA) and verify the suitability of the commercially available ECLIA kit for postmortem hemolyzed blood with the dilution-correction method, different levels of hemolyzed serum were prepared to evaluate the interference of hemolysis. A linear regression analysis was then performed on the concentration of total IgE in the completely hemolyzed blood and the corresponding serum. Our results indicated that hemolysis negatively interfered with the total IgE analysis by ECLIA and the interference (|Bias%|) increased with increasing levels of hemolysis. After controlling for |Bias%| by dilution, the test concentration of total IgE in the completely hemolyzed blood was still significantly lower than that in the serum (P < 0.05) and resulted in eight false-negative cases. A strong correlation was observed between the test concentration of total IgE in the completely hemolyzed blood and that in the serum (r = 0.983). After correction by the regression formula, the corrected concentration revealed no significant differences and exhibited the same diagnostic ability, compared with the serum total IgE concentration. These results indicate that the completely hemolyzed blood is not recommended for postmortem analysis of total IgE directly. The dilution-correction method might have potential utility in forensic practice for evaluating serum total IgE concentrations.

Berberine alleviates visceral hypersensitivity in rats by altering gut microbiome and suppressing spinal microglial activation.

Accumulating evidence shows that agents targeting gut dysbiosis are effective for improving symptoms of irritable bowel syndrome (IBS). However, the potential mechanisms remain unclear. In this study we investigated the effects of berberine on the microbiota-gut-brain axis in two rat models of visceral hypersensitivity, i.e., specific pathogen-free SD rats subjected to chronic water avoidance stress (WAS) and treated with berberine (200 mg· kg-1 ·d-1, ig, for 10 days) as well as germ-free (GF) rats subjected to fecal microbiota transplantation (FMT) from a patient with IBS (designated IBS-FMT) and treated with berberine (200 mg· kg-1 ·d-1, ig, for 2 weeks). Before the rats were sacrificed, visceral sensation and depressive behaviors were evaluated. Then colonic tryptase was measured and microglial activation in the dorsal lumbar spinal cord was assessed. The fecal microbiota was profiled using 16S rRNA sequencing, and short chain fatty acids (SCFAs) were measured. We showed that berberine treatment significantly alleviated chronic WAS-induced visceral hypersensitivity and activation of colonic mast cells and microglia in the dorsal lumbar spinal cord. Transfer of fecal samples from berberine-treated stressed donors to GF rats protected against acute WAS. FMT from a patient with IBS induced visceral hypersensitivity and pro-inflammatory phenotype in microglia, while berberine treatment reversed the microglial activation and altered microbial composition and function and SCFA profiles in stools of IBS-FMT rats. We demonstrated that berberine did not directly influence LPS-induced microglial activation in vitro. In both models, several SCFA-producing genera were enriched by berberine treatment, and positively correlated to the morphological parameters of microglia. In conclusion, activation of microglia in the dorsal lumbar spinal cord was involved in the pathogenesis of IBS caused by dysregulation of the microbiota-gut-brain axis, and the berberine-altered gut microbiome mediated the modulatory effects of the agent on microglial activation and visceral hypersensitivity, providing a potential option for the treatment of IBS.

Breath-, air- and surface-borne SARS-CoV-2 in hospitals.

The COVID-19 pandemic has brought an unprecedented crisis to the global health sector. When discharging COVID-19 patients in accordance with throat or nasal swab protocols using RT-PCR, the potential risk of reintroducing the infection source to humans and the environment must be resolved. Here, 14 patients including 10 COVID-19 subjects were recruited; exhaled breath condensate (EBC), air samples and surface swabs were collected and analyzed for SARS-CoV-2 using reverse transcription-polymerase chain reaction (RT-PCR) in four hospitals with applied natural ventilation and disinfection practices in Wuhan. Here we discovered that 22.2% of COVID-19 patients (n = 9), who were ready for hospital discharge based on current guidelines, had SARS-CoV-2 in their exhaled breath (~105 RNA copies/m3). Although fewer surface swabs (3.1%, n = 318) tested positive, medical equipment such as face shield frequently contacted/used by healthcare workers and the work shift floor were contaminated by SARS-CoV-2 (3-8 viruses/cm2). Three of the air samples (n = 44) including those collected using a robot-assisted sampler were detected positive by a digital PCR with a concentration level of 9-219 viruses/m3. RT-PCR diagnosis using throat swab specimens had a failure rate of more than 22% in safely discharging COVID-19 patients who were otherwise still exhaling the SARS-CoV-2 by a rate of estimated ~1400 RNA copies per minute into the air. Direct surface contact might not represent a major transmission route, and lower positive rate of air sample (6.8%) was likely due to natural ventilation (1.6-3.3 m/s) and regular disinfection practices. While there is a critical need for strengthening hospital discharge standards in preventing re-emergence of COVID-19 spread, use of breath sample as a supplement specimen could further guard the hospital discharge to ensure the safety of the public and minimize the pandemic re-emergence risk.

gcMeta: a Global Catalogue of Metagenomics platform to support the archiving, standardization and analysis of microbiome data.

Meta-omics approaches have been increasingly used to study the structure and function of the microbial communities. A variety of large-scale collaborative projects are being conducted to encompass samples from diverse environments and habitats. This change has resulted in enormous demands for long-term data maintenance and capacity for data analysis. The Global Catalogue of Metagenomics (gcMeta) is a part of the 'Chinese Academy of Sciences Initiative of Microbiome (CAS-CMI)', which focuses on studying the human and environmental microbiome, establishing depositories of samples, strains and data, as well as promoting international collaboration. To accommodate and rationally organize massive datasets derived from several thousands of human and environmental microbiome samples, gcMeta features a database management system for archiving and publishing data in a standardized way. Another main feature is the integration of more than ninety web-based data analysis tools and workflows through a Docker platform which enables data analysis by using various operating systems. This platform has been rapidly expanding, and now hosts data from the CAS-CMI and a number of other ongoing research projects. In conclusion, this platform presents a powerful and user-friendly service to support worldwide collaborative efforts in the field of meta-omics research. This platform is freely accessible at https://gcmeta.wdcm.org/.

Single nucleotide polymorphisms in JNK1 are associated with susceptibility to noise-induced hearing loss in a Chinese population.

PURPOSE: This study intended to explore the effect of C-Jun N-terminal kinases 1 (JNK1) polymorphisms on the sensitivity of individual hearing loss. METHODS: A total of 1333 subjects, including 683 NIHL workers and 650 normal-hearing workers from east China, were included in this cross-sectional study. Genotyping of three JNK1 single nucleotide polymorphisms (rs9284, rs8428, and rs11598320) was performed. The relationship between different genotypes and noise-induced hearing loss was analyzed. RESULTS: Results show that rs11598320 TT genotype was associated with a higher risk of NIHL (OR 1.57, 95% CI 0.91-2.70). Stratified analysis indicated that the rs11598320 AT + AA genotype was associated with a decreased risk of hearing loss in subjects exposed to noise ≤ 16 years or a noise level > 92 dB (OR 0.68, 95% CI 0.50-0.93 and OR 0.64, 95% CI 0.42-0.96, respectively). The rs8428 TT genotype was associated with an increased risk of noise-induced hearing loss when the noise level was > 92 dB (OR 1.73, 95% CI 1.11-2.70). Haplotype TCT (rs9284-rs8424-rs11598320) was associated with an increased risk of noise-induced hearing loss (OR 1.30, 95% CI 1.00-1.68). CONCLUSION: Single nucleotide polymorphisms (rs11598320 and rs8424) in JNK1 can be used as new biomarkers of susceptibility for noise-induced hearing loss in Chinese workers.

Verifying earplug attenuation and evaluating the effectiveness of one-on-one training along with earplug fit testing at nine facilities in China.

BACKGROUND: The purpose of this study was twofold: (1) to measure the personal attenuation ratings (PARs) in Chinese workers wearing hearing protection devices (HPDs), to evaluate the effectiveness of the single number rating (SNR), the noise reduction rating (NRR), and the associated derated values of earplugs; and (2) to evaluate the effectiveness of one-on-one training along with earplug fit testing on PAR improvement. METHODS: Noise exposure measurements, one-on-one training, and fit tests to measure earplug attenuation were conducted at nine manufacturing facilities located in eastern China from 2016 to 2017. 503 workers participated in the study. Ninety-three percent were male. 199 workers were provided one-on-one training. RESULTS: Before training, 14% and 15% of the workers achieved the attenuation predicted by the manufacturer's SNR and NRR, 56% and 65% exceeded the derated SNR and NRR, respectively. Following one-on-one training, mean PAR improved significantly by 15 dB (p < 0.01); 26% of the workers achieved SNR and NRR, 79% and 91% met the associated derated values, respectively. CONCLUSIONS: Labeled noise attenuation ratings and their derated values overestimated the actual level of attenuation among workers wearing HPDs. One-on-one training along with earplug fit testing contributed to improved PARs.

Serum Copper Level and Polycystic Ovarian Syndrome: A Meta-Analysis.

INTRODUCTION: The association of serum copper with polycystic ovarian syndrome (PCOS) has been studied for years, but no definite conclusion is drawn. Therefore, we conducted a meta-analysis to investigate serum copper concentrations in PCOS subjects compared with healthy controls. METHODS: Electronic search was performed in PubMed, Google Scholar, and Scopus up to June 30, 2020, without any restriction. Standardized mean differences (SMDs) with corresponding 95% CIs in serum copper levels were employed with random-effects model. I2 was applied to evaluate heterogeneity among studies. RESULTS: Nine studies, measuring plasma copper levels in 1,168 PCOS patients and 1,106 controls, were included. Pooled effect size suggested serum copper level was significantly higher in women with PCOS (SMD = 0.51 µg/mL, 95% CI = [0.30, 0.72], p < 0.0001). The overall heterogeneity was not connected with subgroups of the country, but derived from the opposite result of 1 study. CONCLUSION: Our research generally indicated circulating copper level in PCOS sufferers was significantly higher than normal controls. Large-scale studies are still needed to elucidate the clear relation between copper status and etiology of PCOS.

A Multimodality Machine Learning Approach to Differentiate Severe and Nonsevere COVID-19: Model Development and Validation.

BACKGROUND: Effectively and efficiently diagnosing patients who have COVID-19 with the accurate clinical type of the disease is essential to achieve optimal outcomes for the patients as well as to reduce the risk of overloading the health care system. Currently, severe and nonsevere COVID-19 types are differentiated by only a few features, which do not comprehensively characterize the complicated pathological, physiological, and immunological responses to SARS-CoV-2 infection in the different disease types. In addition, these type-defining features may not be readily testable at the time of diagnosis. OBJECTIVE: In this study, we aimed to use a machine learning approach to understand COVID-19 more comprehensively, accurately differentiate severe and nonsevere COVID-19 clinical types based on multiple medical features, and provide reliable predictions of the clinical type of the disease. METHODS: For this study, we recruited 214 confirmed patients with nonsevere COVID-19 and 148 patients with severe COVID-19. The clinical characteristics (26 features) and laboratory test results (26 features) upon admission were acquired as two input modalities. Exploratory analyses demonstrated that these features differed substantially between two clinical types. Machine learning random forest models based on all the features in each modality as well as on the top 5 features in each modality combined were developed and validated to differentiate COVID-19 clinical types. RESULTS: Using clinical and laboratory results independently as input, the random forest models achieved >90% and >95% predictive accuracy, respectively. The importance scores of the input features were further evaluated, and the top 5 features from each modality were identified (age, hypertension, cardiovascular disease, gender, and diabetes for the clinical features modality, and dimerized plasmin fragment D, high sensitivity troponin I, absolute neutrophil count, interleukin 6, and lactate dehydrogenase for the laboratory testing modality, in descending order). Using these top 10 multimodal features as the only input instead of all 52 features combined, the random forest model was able to achieve 97% predictive accuracy. CONCLUSIONS: Our findings shed light on how the human body reacts to SARS-CoV-2 infection as a unit and provide insights on effectively evaluating the disease severity of patients with COVID-19 based on more common medical features when gold standard features are not available. We suggest that clinical information can be used as an initial screening tool for self-evaluation and triage, while laboratory test results should be applied when accuracy is the priority.

Accurately Differentiating Between Patients With COVID-19, Patients With Other Viral Infections, and Healthy Individuals: Multimodal Late Fusion Learning Approach.

BACKGROUND: Effectively identifying patients with COVID-19 using nonpolymerase chain reaction biomedical data is critical for achieving optimal clinical outcomes. Currently, there is a lack of comprehensive understanding in various biomedical features and appropriate analytical approaches for enabling the early detection and effective diagnosis of patients with COVID-19. OBJECTIVE: We aimed to combine low-dimensional clinical and lab testing data, as well as high-dimensional computed tomography (CT) imaging data, to accurately differentiate between healthy individuals, patients with COVID-19, and patients with non-COVID viral pneumonia, especially at the early stage of infection. METHODS: In this study, we recruited 214 patients with nonsevere COVID-19, 148 patients with severe COVID-19, 198 noninfected healthy participants, and 129 patients with non-COVID viral pneumonia. The participants' clinical information (ie, 23 features), lab testing results (ie, 10 features), and CT scans upon admission were acquired and used as 3 input feature modalities. To enable the late fusion of multimodal features, we constructed a deep learning model to extract a 10-feature high-level representation of CT scans. We then developed 3 machine learning models (ie, k-nearest neighbor, random forest, and support vector machine models) based on the combined 43 features from all 3 modalities to differentiate between the following 4 classes: nonsevere, severe, healthy, and viral pneumonia. RESULTS: Multimodal features provided substantial performance gain from the use of any single feature modality. All 3 machine learning models had high overall prediction accuracy (95.4%-97.7%) and high class-specific prediction accuracy (90.6%-99.9%). CONCLUSIONS: Compared to the existing binary classification benchmarks that are often focused on single-feature modality, this study's hybrid deep learning-machine learning framework provided a novel and effective breakthrough for clinical applications. Our findings, which come from a relatively large sample size, and analytical workflow will supplement and assist with clinical decision support for current COVID-19 diagnostic methods and other clinical applications with high-dimensional multimodal biomedical features.

Sudden Death Due to Severe Ovarian Hyperstimulation Syndrome: An Autopsy-Centric Case Report.

ABSTRACT: Ovarian hyperstimulation syndrome (OHSS) is a rare iatrogenic disorder associated with controlled ovarian stimulation during assisted reproductive technology. Severe OHSS may impose serious complications, including pleural effusion, acute renal insufficiency, venous thrombosis, and even death, although lethal outcomes are rare in forensic practice. The reported incidence of severe OHSS ranges from 0.008% to 10%. Herein, we present the case of a 29-year-old woman who diagnosed with polycystic ovary syndrome and infertility chose to undergo assisted reproduction. She received leuprorelin acetate and follicle stimulating hormone prior to egg retrieval. Three days after the retrieval procedure, she developed abdominal pain and distension. Later that same day, she died unexpectedly. The subsequent autopsy revealed turbid effusions of pleural and peritoneal cavities, abnormal ovarian enlargement, and duskiness of multiple organ surfaces. Microscopic examination disclosed edema and hemorrhage in follicles of both ovaries, thrombosis within the myocardial matrix, and massive pulmonary edema. Routine toxicology screening was negative. The death was attributed to severe OHSS. This case provides a morphologic reference for clinical and forensic work. Autopsy findings in instances of severe OHSS provide valuable insight into the mechanisms and pathogenesis of this disease.

Analysis of m6A RNA Methylation-Related Genes in Liver Hepatocellular Carcinoma and Their Correlation with Survival.

N6-methyladenosine (m6A) modification on RNA plays an important role in tumorigenesis and metastasis, which could change gene expression and even function at multiple levels such as RNA splicing, stability, translocation, and translation. In this study, we aim to conduct a comprehensive analysis on m6A RNA methylation-related genes, including m6A RNA methylation regulators and m6A RNA methylation-modified genes, in liver hepatocellular carcinoma, and their relationship with survival and clinical features. Data, which consist of the expression of widely reported m6A RNA methylation-related genes in liver hepatocellular carcinoma from The Cancer Genome Atlas (TCGA), were analyzed by one-way ANOVA, Univariate Cox regression, a protein-protein interaction network, gene enrichment analysis, feature screening, a risk prognostic model, correlation analysis, and consensus clustering analysis. In total, 405 of the m6A RNA methylation-related genes were found based on one-way ANOVA. Among them, DNA topoisomerase 2-alpha (TOP2A), exodeoxyribonuclease 1 (EXO1), ser-ine/threonine-protein kinase Nek2 (NEK2), baculoviral IAP repeat-containing protein 5 (BIRC5), hyaluronan mediated motility receptor (HMMR), structural maintenance of chromosomes protein 4 (SMC4), bloom syndrome protein (BLM), ca-sein kinase I isoform epsilon (CSNK1E), cytoskeleton-associated protein 5 (CKAP5), and inner centromere protein (INCENP), which were m6A RNA methylation-modified genes, were recognized as the hub genes based on the protein-protein interaction analysis. The risk prognostic model showed that gender, AJCC stage, grade, T, and N were significantly different between the subgroup with the high and low risk groups. The AUC, the evaluation parameter of the prediction model which was built by RandomForest, was 0.7. Furthermore, two subgroups were divided by consensus clustering analysis, in which stage, grade, and T differed. We identified the important genes expressed significantly among two clusters, including uridine-cytidine kinase 2 (UCK2), filensin (BFSP1), tubulin-specific chaperone D (TBCD), histone-lysine N-methyltransferase PRDM16 (PRDM16), phosphorylase b ki-nase regulatory subunit alpha (PHKA2), serine/threonine-protein kinase BRSK2 (BRSK2), Arf-GAP with coiled-coil (ACAP3), general transcription factor 3C polypep-tide 2 (GTF3C2), and guanine nucleotide exchange factor MSS4 (RABIF). In our study, the m6A RNA methylation-related genes in liver hepatocellular carcinoma were analyzed systematically, including the expression, interaction, function, and prognostic values, which provided an important theoretical basis for m6A RNA methylation in liver cancer. The nine important m6A-related genes could be prognostic markers in the survival time of patients.