Improved hypertensive stroke classification based on multi-scale feature fusion of head axial CT angiogram and multimodal learning

PURPOSE

Strokes are severe cardiovascular and circulatory diseases with two main types: ischemic and hemorrhagic. Clinically, brain images such as computed tomography (CT) and computed tomography angiography (CTA) are widely used to recognize stroke types. However, few studies have combined imaging and clinical data to classify stroke or consider a factor as an Independent etiology.

METHODS

In this work, we propose a classification model that automatically distinguishes stroke types with hypertension as an independent etiology based on brain imaging and clinical data. We first present a preprocessing workflow for head axial CT angiograms, including noise reduction and feature enhancement of the images, followed by an extraction of regions of interest. Next, we develop a multi-scale feature fusion model that combines the location information of position features and the semantic information of deep features. Furthermore, we integrate brain imaging with clinical information through a multimodal learning model to achieve more reliable results.

RESULTS

Experimental results show our proposed models outperform state-of-the-art models on real imaging and clinical data, which reveals the potential of multimodal learning in brain disease diagnosis.

CONCLUSION

The proposed methodologies can be extended to create AI-driven diagnostic assistance technology for categorizing strokes.

Evaluation of immunogenicity and protective efficacy of the outer membrane porin F (OprF) against Pseudomonas plecoglossicida in large yellow croaker (Larimichthys crocea)

Large yellow croaker (Larimichthys crocea) farming dominates the marine aquaculture industry in China. However, the epidemic outbreaks of visceral white nodules disease (VWND), caused by bacterial pathogen Pseudomonas plecoglossicida, have emerged as a significant concern within the large yellow croaker industry. Although vaccination is considered to be an effective method for preventing and controlling P. plecoglossicida infection, there is currently no commercially available vaccine targeting this bacterium. In the present study, the outer membrane porin F (OprF) of P. plecoglossicida was characterized and revealed a high sequence similarity with that of other Pseudomonas species. The recombinant OprF protein (rOprF) produced in Escherichia coli was then evaluated for its immunogenicity and protective role against P. plecoglossicida in large yellow croaker. The rOprF was identified to have immunogenicity by Western blot using large yellow croaker anti-P. plecoglossicida sera. Additionally, the indirect immunofluorescence assay (IIFA) provided evidence indicating the surface exposure of OprF in P. plecoglossicida. Fish vaccinated twice via intraperitoneal (IP) injection with the purified rOprF combined with commercial adjuvant ISA 763A VG exhibited a relative percent survival (RPS) of 70.60% after challenge with virulent P. plecoglossicida strain through immersion. The administration of rOprF resulted in a notable increase in specific serum antibody levels and serum lysozyme activity compared to the control groups. The immune-related genes in the spleen and head kidney of rOprF-vaccinated fish were remarkably upregulated compared with the PBS-vaccinated sham group after the P. plecoglossicida challenge. In summary, the findings of this study suggest that rOprF exhibits considerable potential in inducing a robust immune response, making it a viable candidate for vaccination against P. plecoglossicida infection in large yellow croaker.

[Research on quantitative evaluation of revise requirements of Specifications of Air Sampling for Hazardous Substances Monitoring in the Workplace (GBZ 159-2004)]

Objective: To conduct quantitative evaluation on the revise requirements of Specifications of Air Sampling for Hazardous Substances Monitoring in the Workplace (GBZ 159-2004) , clarify the problems and suggestions during its implementation for improvement, and provide a basis for the revision of the standard. Methods: From April to September 2021, stratified convenient sampling method was adopted and semi-open questionnaire was used to investigate the occupational health personnel in CDC, occupational prevention and control institutes, employers, third-party technical service institutions and universitie. The entropy weight of each index and the score based on entropy weight of GBZ 159 were calculated. Spearman rank correlation analysis was used to describe the correlation between the two indexes and radar chart was drawn for comprehensive evaluation. Results: A total of 151 questionnaires were received from the respondents, of which 147 were valid, with an effective recovery rate of 97.35%, involving 29 provinces, autonomous regions and municipalities. The median G scores of the necessity and urgency of GBZ 159 revision based on entropy weight were 2.84 and 3.17, respectively, and the difference was statistically significant (M=-25.50, P<0.001) . The trend of the score G of necessity and urgency based on entropy weight was basically the same for all secondary items (r(s)=0.9998, P<0.001) , and the score G of urgency based on entropy weight was higher than that of necessity. The highest score G of necessity and urgency based on entropy weight was "3.13 long time sampling", which were 7.56 and 8.23 respectively. This was followed by "3.12 short time sampling", which were 7.19 and 7.13 respectively. Conclusion: GBZ 159 has encountered some new problems and challenges in the implementation process, and some of its technical indicators have been out of line with the actual practice of occupational health at present. These are the two items that urgently needs to be revised and improved, such as "3.13 long time sampling" and "3.12 short time sampling" and other items need to be revised and improved.

[Study on the implementation effect evaluation of Specifications of Air Sampling for Hazardous Substances Monitoring in the Workplace (GBZ 159-2004)]

Systematically evaluate the implementation of Specifications of Air Sampling for Hazardous Substances Monitoring (GBZ 159-2004) , so as to provide technical basis for the future standard revision. The semi-structured interview method was used to interview the industry experts from centers for disease control and prevention, occupational disease prevention and control hospitals/institutes, employers, third-party technical service institutions and universities, and the induction method was used to refine the topics and relevant suggestions. Some technical indicators of GBZ 159 are not suitable for the current actual work of occupational health, and need to be revised and improved urgently. The revised GBZ 159 should comply with the current situation of China's industrial development and the development of occupational health testing equipment in the new era, and improve the relevant technical requirements of sampling quality control.

Comparative secretome analysis reveals cross-talk between type III secretion system and flagella assembly in Pseudomonas plecoglossicida

The Gram-negative bacterium Pseudomonas plecoglossicida has caused visceral granulomas disease in several farmed fish species, including large yellow croaker (Larimichthys crocea), which results in severe economic losses. Type III secretion systems (T3SS) are protein secretion and translocation nanomachines widely employed by many Gram-negative bacterial pathogens for infection and pathogenicity. However, the exact role of T3SS in the pathogenesis of P. plecoglossicida infection is still unclear. In this study, a T3SS translocators deletion strain (△popBD) of P. plecoglossicida was constructed to investigate the function of T3SS. Then comparative secretome analysis of the P. plecoglossicida wild-type (WT) and △popBD mutant strains was conducted by label-free quantitation (LFQ) mass spectrometry. The results show that knockout of T3SS translocators popB and popD has an adverse effect on the effector protein ExoU secretion, flagella assembly, and biofilm formation. Further experimental validations also confirmed that popB-popD deletion could affect the P. plecoglossicida flagella morphology/formation, adherence, mobility, and biofilm formation. These data indicate that a cross-talk exists between the P. plecoglossicida T3SS and the flagella system. Our results, therefore, will facilitate the further under-standing of the pathogenic mechanisms leading to visceral granulomas disease caused by P. plecoglossicida.

Study of efficacy and antibody duration to fourth-dose booster of Ad5-nCoV or inactivated SARS-CoV-2 vaccine in Chinese adults: a prospective cohort study

Introduction

China experienced a record surge of coronavirus disease 2019 cases in December 2022, during the pandemic.

Methods

We conducted a randomized, parallel-controlled prospective cohort study to evaluate efficacy and antibody duration after a fourth-dose booster with Ad5-nCoV or inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine.

Results

A total of 191 participants aged ≥18 years who had completed a three-dose regimen of the inactivated SARS-CoV-2 vaccine 6 months earlier were recruited to receive the intramuscular Ad5-nCoV booster or the inactivated SARS-CoV-2 vaccine. The Ad5-nCoV group had significantly higher antibody levels compared with the inactivated vaccine group at 6 months after the fourth vaccination dose. After the pandemic, the breakthrough infection rate for the Ad5-nCoV and the inactivated vaccine groups was 77.89% and 78.13%, respectively. Survival curve analysis (p = 0.872) and multivariable logistic regression analysis (p = 0.956) showed no statistically significant differences in breakthrough infection between the two groups.

Discussion

Compared with a homologous fourth dose, a heterologous fourth dose of Ad5-nCoV elicited a higher immunogenic response in healthy adults who had been immunized with three doses of inactivated vaccine. Nevertheless, the efficacy of the two vaccine types was equivalent after the pandemic.

Safety and immunogenicity of Ad5-nCoV immunization after three-dose priming with inactivated SARS-CoV-2 vaccine in Chinese adults

Data on the safety and immunity of a heterologous booster (fourth dose) after three-doses of inactivated SARS-CoV-2 vaccine in Chinese adults are limited. We evaluate the safety and immunogenicity of Ad5-nCoV in a randomized, double-blind, parallel-controlled phase 4 clinical trial in Zhejiang, China (NCT05373030). Participants aged 18-80 years (100 per group), administered three doses of inactivated SARS-CoV-2 vaccine ≥6 months earlier, are enrolled and randomized 1:1 into two groups, which are administered intramuscular Ad5-nCoV or inactivated SARS-CoV-2 vaccine (CoronaVac or Covilo). All observed adverse reactions are predictable and manageable. Ad5-nCoV elicits significantly higher RBD-specific IgG levels, with a geometric mean concentration of 2924.0 on day 14 post-booster, 7.8-fold that of the inactivated vaccine. Pseudovirus-neutralizing antibodies to Omicron BA.4/5 show a similar pattern, with geometric mean titers of 228.9 in Ad5-nCoV group and 65.5 in inactivated vaccine group. Ad5-nCoV booster maintains high antibody levels on day 90, with seroconversion of 71.4%, while that of inactivated vaccine is 5.2%, almost pre-booster levels. A fourth Ad5-nCoV vaccination following three-doses of inactivated SARS-CoV-2 vaccine is immunogenic, tolerable, and more efficient than inactivated SARS-CoV-2 vaccine. Ad5-nCoV elicits a stronger humoral response against Omicron BA.4/5 and maintains antibody levels for longer than homologous boosting.

Megalocytivirus and Other Members of the Family Iridoviridae in Finfish: A Review of the Etiology, Epidemiology, Diagnosis, Prevention and Control

Aquaculture has expanded to become the fastest growing food-producing sector in the world. However, its expansion has come under threat due to an increase in diseases caused by pathogens such as iridoviruses commonly found in aquatic environments used for fish farming. Of the seven members belonging to the family Iridoviridae, the three genera causing diseases in fish comprise ranaviruses, lymphocystiviruses and megalocytiviruses. These three genera are serious impediments to the expansion of global aquaculture because of their tropism for a wide range of farmed-fish species in which they cause high mortality. As economic losses caused by these iridoviruses in aquaculture continue to rise, the urgent need for effective control strategies increases. As a consequence, these viruses have attracted a lot of research interest in recent years. The functional role of some of the genes that form the structure of iridoviruses has not been elucidated. There is a lack of information on the predisposing factors leading to iridovirus infections in fish, an absence of information on the risk factors leading to disease outbreaks, and a lack of data on the chemical and physical properties of iridoviruses needed for the implementation of biosecurity control measures. Thus, the synopsis put forth herein provides an update of knowledge gathered from studies carried out so far aimed at addressing the aforesaid informational gaps. In summary, this review provides an update on the etiology of different iridoviruses infecting finfish and epidemiological factors leading to the occurrence of disease outbreaks. In addition, the review provides an update on the cell lines developed for virus isolation and culture, the diagnostic tools used for virus detection and characterization, the current advances in vaccine development and the use of biosecurity in the control of iridoviruses in aquaculture. Overall, we envision that the information put forth in this review will contribute to developing effective control strategies against iridovirus infections in aquaculture.

Effect of organophosphate esters on microbial community and proteomics in constructed wetlands and its removal mechanism

Organophosphorus esters (OPEs) may cause potential risks to human health and ecological environment safety when they enter water. In this study, A lab-scale vertical flow constructed wetlands (VFCWs) exposed to dichlorvos (DDVP) was carried out to reveal removal effect and mechanism of DDVP in VFCWs. The findings indicated CWs can remove DDVP with 94%-95% average removal efficiency in long-term operation. Besides, soluble phosphate (SRP) and total phosphorus (TP) were removed by VFCWs with 48.60%-64.10% average removal efficiency, and the addition of DDVP enhanced the effect of CWs on nitrogen removal. High-throughput sequencing demonstrated that Massiilia (2.67%-18.06%), Denitratisoma (2.07%-3.80%) and SM1A02 (2.85%-4.67%) played an important role in the removal process of DDVP in VFCWs. Proteomics of plant root showed that A0A3B6ARQ4 (increased 29.53 times) and LOC_Os11g38050.1 protein (decreased 0.001 times) responsed more sensitive to OPEs which suggested DDVP enhancesenhancing plants energy production and hydrolyase synthesis, thereby promoting it hydrolysis. Therefore, the use of VFCWs to treat organic phosphate wastewater has future prospects.

Gamma distribution based predicting model for breast cancer drug response based on multi-layer feature selection

In the pursuit of precision medicine for cancer, a promising step is to predict drug response based on data mining, which can provide clinical decision support for cancer patients. Although some machine learning methods for predicting drug response from genomic data already exist, most of them focus on point prediction, which cannot reveal the distribution of predicted results. In this paper, we propose a three-layer feature selection combined with a gamma distribution based GLM and a two-layer feature selection combined with an ANN. The two regression methods are applied to the Encyclopedia of Cancer Cell Lines (CCLE) and the Cancer Drug Sensitivity Genomics (GDSC) datasets. Using ten-fold cross-validation, our methods achieve higher accuracy on anticancer drug response prediction compared to existing methods, with an R ² and RMSE of 0.87 and 0.53, respectively. Through data validation, the significance of assessing the reliability of predictions by predicting confidence intervals and its role in personalized medicine are illustrated. The correlation analysis of the genes selected from the three layers of features also shows the effectiveness of our proposed methods.

Complete genome sequence and characterization of four Decapod iridescent virus 1 isolates from crab and shrimp

Decapod iridescent virus 1 (DIV1) is an emerging viral pathogen that infects diverse freshwater and marine crustacean species and causes considerable economic losses that seriously threaten crustacean farming and has caused enormous financial losses in recent years. In this study, we detected DIV1 from diseased crabs, with clinical symptoms such as loss of vitality and white gill filaments with edema, in a Marsupenaeus japonicus and Portunus trituberculatus polyculture pond. Four DIV1 isolates from crab samples (two isolates) and shrimp samples (two isolates) were sequenced and assembled successfully. Molecular characterization and phylogenetic analysis of the four DIV1 isolates were conducted. The DIV1 isolates from crab samples have a close genetic relationship with shrimp DIV1s, indicating the viruses share the same ancestor with those from shrimps. Our study provides valuable insights into disease prevention and control of the shrimp-crab polyculture system.

A self-training subspace clustering algorithm based on adaptive confidence for gene expression data

Gene clustering is one of the important techniques to identify co-expressed gene groups from gene expression data, which provides a powerful tool for investigating functional relationships of genes in biological process. Self-training is a kind of important semi-supervised learning method and has exhibited good performance on gene clustering problem. However, the self-training process inevitably suffers from mislabeling, the accumulation of which will lead to the degradation of semi-supervised learning performance of gene expression data. To solve the problem, this paper proposes a self-training subspace clustering algorithm based on adaptive confidence for gene expression data (SSCAC), which combines the low-rank representation of gene expression data and adaptive adjustment of label confidence to better guide the partition of unlabeled data. The superiority of the proposed SSCAC algorithm is mainly reflected in the following aspects. 1) In order to improve the discriminative property of gene expression data, the low-rank representation with distance penalty is used to mine the potential subspace structure of data. 2) Considering the problem of mislabeling in self-training, a semi-supervised clustering objective function with label confidence is proposed, and a self-training subspace clustering framework is constructed on this basis. 3) In order to mitigate the negative impact of mislabeled data, an adaptive adjustment strategy based on gravitational search algorithm is proposed for label confidence. Compared with a variety of state-of-the-art unsupervised and semi-supervised learning algorithms, the SSCAC algorithm has demonstrated its superiority through extensive experiments on two benchmark gene expression datasets.

Association between insulin-like growth factor-1 and cardiovascular events: a systematic review and dose-response meta-analysis of cohort studies

BACKGROUND

Insulin-like growth factor-1 (IGF-1) has increasingly been reported as linked to cardiovascular (CV) events; however, reported results have been inconsistent, and no meta-analysis has been undertaken to quantitatively assess this association.

METHODS

We searched PubMed, Embase, and Web of Science databases for cohort articles published up to December 1, 2020. Fixed or random-effects models were used to estimate the summary relative risks (RRs) and 95% confidence intervals (CIs) of CV events in relation to IGF-1. Restricted cubic splines were used to model the dose-response association.

RESULTS

We identified 11 articles (thirteen cohort studies) covering a total of 22,995 participants and 3040 CV events in this meta-analysis. The risk of overall CV events reduced by 16% from the highest to the lowest IGF-1 levels (RR 0.83, 95% CI 0.72-0.95), while the occurrence of CV events reduced by 28% (RR 0.72, 95% CI 0.56-0.92), but not for CV deaths, however (RR 1.00, 95% CI 0.65-1.55). We also found linear associations between IGF-1 levels and CV events. With each per 45 μg/mL IGF-1 increase, the pooled RRs were 0.91 (95% CI 0.86-0.96), 0.91 (95% CI 0.85-0.97) and 0.91 (95% CI 0.84-0.98) for overall CV events, for the occurrence of CV events, and for CV deaths, respectively.

CONCLUSIONS

Our findings based on cohort studies support the contention that any increase in IGF-1 is helpful in reducing the overall risk of CV events. As an important biomarker for assessing the likelihood of CV events, IGF-1 appears to offer a promising prognostic approach for aiding prevention.

[Survival and prognosis analysis of patients with Hodgkin lymphoma treated with standard treatment paradigm]

Objective: To analyze the survival and prognosis of Hodgkin lymphoma (HL) patients receiving standard first-line therapy. Methods: Data of clinical characteristics and treatment outcomes of patients with HL diagnosed in Cancer Hospital Chinese Academy of Medical Sciences (CHCAMS) from January 1st, 2000 to December 31st, 2018 who received standard first-line treatment were retrospectively analyzed and compared with that of HL patients who received treatment in the Surveillance, Epidemiology and End Results (SEER) database in the United States during the same period. Factors associated with freedom from progression (FFP) of patients in CHCAMS were analyzed. Treatment and survival data of patients with relapsed/refractory HL (r/rHL) who had failed the standard first-line treatment during the corresponding period in CHCAMS were collected to analyze the outcomes of salvage therapy. Results: A total of 764 HL patients in CHCAMS were included in this study. The median age was 30 years (range, 14-83 years), with 424 males and 340 females. By February 26th, 2022, the patients were followed-up for a median time of 111 months(range, 0.3-262.0 months). Lymphoma-specific survival (LSS) rate and overall survival (OS) rate at 10 years for HL patients in CHCAMS was 91.7% (95%CI: 89.5%-93.9%) and 87.1% (95%CI: 84.5%-89.8%), respectively. LSS and OS rate at 10 years for HL patients from SEER database was 86.8% (95%CI: 86.3%-87.2%) and 79.0% (95%CI: 78.5%-79.5%), respectively. The unadjusted LSS and OS rate for patients in CHCAMS were higher than those for patients from SEER database (both P<0.001). No significant difference was observed in LSS and OS rate (both P>0.05) between the two groups after adjustment. European Organization for Research and Treatment of Cancer staging system (early-stage unfavorable: HR=2.35, 95%CI: 1.13-4.89, P=0.023; advanced stage: HR=5.44, 95%CI: 2.62-11.30, P<0.001) and serum β2 microglobulin (HR=1.67, 95%CI: 1.08-2.58, P=0.021) were influencing factors of FFP for patients in CHCAMS. The complete remission rate, median progression-free survival (PFS), 5-year PFS rate and 5-year OS rate for the 116 patients with r/rHL was 37.9% (95%CI: 29.6%-47.0%), 15.0 months (95%CI: 9.9-20.1 months), 29.9% (95%CI: 20.9%-38.9%) and 62.9% (95%CI: 54.1%-71.7%), respectively. Conclusions: The outcomes of HL patients receiving standard first-line treatment are excellent. However, the therapeutic effect of HL patients who incurrs disease progression or relapse after standard first-line treatment is not satisfying.

Prediction of axillary lymph node pathological complete response to neoadjuvant therapy using nomogram and machine learning methods

Purpose

To determine the feasibility of predicting the rate of an axillary lymph node pathological complete response (apCR) using nomogram and machine learning methods.

Methods

A total of 247 patients with early breast cancer (eBC), who underwent neoadjuvant therapy (NAT) were included retrospectively. We compared pre- and post-NAT ultrasound information and calculated the maximum diameter change of the primary lesion (MDCPL): [(pre-NAT maximum diameter of primary lesion – post-NAT maximum diameter of preoperative primary lesion)/pre-NAT maximum diameter of primary lesion] and described the lymph node score (LNS) (1): unclear border (2), irregular morphology (3), absence of hilum (4), visible vascularity (5), cortical thickness, and (6) aspect ratio <2. Each description counted as 1 point. Logistic regression analyses were used to assess apCR independent predictors to create nomogram. The area under the curve (AUC) of the receiver operating characteristic curve as well as calibration curves were employed to assess the nomogram’s performance. In machine learning, data were trained and validated by random forest (RF) following Pycharm software and five-fold cross-validation analysis.

Results

The mean age of enrolled patients was 50.4 ± 10.2 years. MDCPL (odds ratio [OR], 1.013; 95% confidence interval [CI], 1.002–1.024; p=0.018), LNS changes (pre-NAT LNS – post-NAT LNS; OR, 2.790; 95% CI, 1.190–6.544; p=0.018), N stage (OR, 0.496; 95% CI, 0.269–0.915; p=0.025), and HER2 status (OR, 2.244; 95% CI, 1.147–4.392; p=0.018) were independent predictors of apCR. The AUCs of the nomogram were 0.74 (95% CI, 0.68–0.81) and 0.76 (95% CI, 0.63–0.90) for training and validation sets, respectively. In RF model, the maximum diameter of the primary lesion, axillary lymph node, and LNS in each cycle, estrogen receptor status, progesterone receptor status, HER2, Ki67, and T and N stages were included in the training set. The final validation set had an AUC value of 0.85 (95% CI, 0.74–0.87).

Conclusion

Both nomogram and machine learning methods can predict apCR well. Nomogram is simple and practical, and shows high operability. Machine learning makes better use of a patient’s clinicopathological information. These prediction models can assist surgeons in deciding on a reasonable strategy for axillary surgery.

Zn2+ Cross-Linked Alginate Carrying Hollow Silica Nanoparticles Loaded with RL-QN15 Peptides Provides Promising Treatment for Chronic Skin Wounds

Chronic and non-healing wounds pose a great challenge to clinical management and patients. Many studies have explored novel interventions against skin wounds, with bioactive peptides, nanoparticles, and hydrogels arousing considerable attention regarding their therapeutic potential. In this study, the prohealing peptide RL-QN15 was loaded into hollow silica nanoparticles (HSNs), with these HSN@RL-QN15 nanocomposites then combined with zinc alginate (ZA) gels to obtain HSN@RL-QN15/ZA hydrogel. The characteristics, biological properties, and safety profiles of the hydrogel composites were then evaluated. Results showed that the hydrogel had good porosity, hemocompatibility, biocompatibility, and broad-spectrum antimicrobial activity, with the slow release of loaded RL-QN15. Further analysis indicated that the hydrogel promoted skin cell proliferation and keratinocyte scratch repair, regulated angiogenesis, reduced inflammation, and accelerated re-epithelialization and granulation tissue formation, resulting in the rapid healing of both full-thickness skin wounds and methicillin-resistant Staphylococcus aureus biofilm-infected chronic wounds in mice. This peptide-based hydrogel provides a novel intervention for the treatment of chronic skin wounds and shows promise as a wound dressing in the field of tissue regeneration.

Bile acids promote the caveolae-associated entry of swine acute diarrhea syndrome coronavirus in porcine intestinal enteroids

Intestinal microbial metabolites have been increasingly recognized as important regulators of enteric viral infection. However, very little information is available about which specific microbiota-derived metabolites are crucial for swine enteric coronavirus (SECoV) infection in vivo. Using swine acute diarrhea syndrome (SADS)-CoV as a model, we were able to identify a greatly altered bile acid (BA) profile in the small intestine of infected piglets by untargeted metabolomic analysis. Using a newly established ex vivo model–the stem cell-derived porcine intestinal enteroid (PIE) culture–we demonstrated that certain BAs, cholic acid (CA) in particular, enhance SADS-CoV replication by acting on PIEs at the early phase of infection. We ruled out the possibility that CA exerts an augmenting effect on viral replication through classic farnesoid X receptor or Takeda G protein-coupled receptor 5 signaling, innate immune suppression or viral attachment. BA induced multiple cellular responses including rapid changes in caveolae-mediated endocytosis, endosomal acidification and dynamics of the endosomal/lysosomal system that are critical for SADS-CoV replication. Thus, our findings shed light on how SECoVs exploit microbiome-derived metabolite BAs to swiftly establish viral infection and accelerate replication within the intestinal microenvironment.

Bile acids (BAs), a commonly studied category of microbial metabolites, have long been acknowledged to have proviral or antiviral activities. Recent studies using different swine enteric coronaviruses (SECoVs) showed that BA play an important role in regulating viral replication in vitro. A mechanistic understanding of how BA regulates SECoV replication in small intestinal enterocytes is lacking. Herein, we utilized an emerging highly pathogenic SECoV, swine acute diarrhea syndrome (SADS)-CoV, which possesses the potential for zoonotic transmission, to investigate the crucial role of BA in modulating viral replication in porcine intestinal enteroids (PIEs). Our observations explain how BAs acts on epithelial cells to enhance SADS-CoV replication by inducing caveolae-mediated endocytosis and endosomal acidification, altering the dynamics of viral trafficking through the cellular endosomal/lysosomal system. Our results shed light on the role of BAs in the rapid establishment of SECoV infection within the intestinal microenvironment.

Chest L-Transformer: Local Features With Position Attention for Weakly Supervised Chest Radiograph Segmentation and Classification

We consider the problem of weakly supervised segmentation on chest radiographs. The chest radiograph is the most common means of screening and diagnosing thoracic diseases. Weakly supervised deep learning models have gained increasing popularity in medical image segmentation. However, these models are not suitable for the critical characteristics presented in chest radiographs: the global symmetry of chest radiographs and dependencies between lesions and their positions. These models extract global features from the whole image to make the image-level decision. The global symmetry can lead these models to misclassification of symmetrical positions of the lesions. Thoracic diseases often have special disease prone areas in chest radiographs. There is a relationship between the lesions and their positions. In this study, we propose a weakly supervised model, called Chest L-Transformer, to take these characteristics into account. Chest L-Transformer classifies an image based on local features to avoid the misclassification caused by the global symmetry. Moreover, associated with Transformer attention mechanism, Chest L-Transformer models the dependencies between the lesions and their positions and pays more attention to the disease prone areas. Chest L-Transformer is only trained with image-level annotations for lesion segmentation. Thus, Log-Sum-Exp voting and its variant are proposed to unify the pixel-level prediction with the image-level prediction. We demonstrate a significant segmentation performance improvement over the current state-of-the-art while achieving competitive classification performance.

Psychiatric care following deliberate self-harm and prospective mortality: evidence from a national cohort of patients in routine care

Introduction

Psychiatric care following self-harm treatment is pivotal in patients´ life both in short- and long-terms.

Objectives

To examine follow-up psychiatric care received by patients treated for deliberate self-harm (DSH), and to assess the influence of psychiatric referral and treatment attendance on risk for subsequent mortality.

Methods

Nationwide registries were interlinked to follow all DSH patients for data on personal socioeconomic status, clinical features of DSH, psychiatric treatment and cause of death. Data were analyzed with Logistic regression and cause-specific survival analysis.

Results

The study identified 43153 patients involving 69569 DSH episodes. Of these patients 15.7% were referred or transferred to psychiatric services and 51.0% attended psychiatric treatment within subsequent 3 months. Evidently, prior psychiatric history and psychiatric comorbidities had strong influence on both referral and attendance to psychiatric healthcare, personal socioeconomic status also deviated the likelihoods. During the follow-up, 7041 patients died from suicide (n=911) or other causes (n=6130). While suicide risk was highly associated with male gender, middle age, and particularly, prior and coexisting psychopathologies, other cause mortality was strongly associated with old age and socioeconomic disadvantages. Meanwhile, a referral to psychiatric services was associated with suicide risk, and the risk was particularly high for patients who received the referral but did not attend psychiatric treatment. The observed effect was more pronounced during the early years, and in patients of young or middle age and those with a clear intent of self-harm.

Conclusions

The insightful findings highlight the importance of patients´ attendance and engagement in follow-up psychiatric care on risk for subsequent mortality.

Disclosure

No significant relationships.

Does country of resettlement influence the risk of suicide in refugees? A case-control study in Sweden and Norway

Introduction

Little is known regarding how the risk of suicide in refugees relates to their host country. Specifically, to what extent, inter-country differences in structural factors between the host countries may explain the association between refugee status and subsequent suicide is lacking in previous literature.

Objectives

We aimed to investigate the risk of suicide among refugees in Sweden and Norway according to their sex, age, region/country of birth and duration of residence.

Methods

Each suicide case between the age of 18-64 years during 1998 and 2018 (17,572 and 9,443 cases in Sweden and Norway, respectively) was matched with up to 20 population-based controls, by sex and age. Multivariate-adjusted conditional logistic regression models yielding adjusted odds ratios (aORs) with 95% confidence intervals (95% CI) were used to test the association between refugee status and suicide.

Results

The aORs for suicide in refugees in Sweden and Norway were 0.5 (95% CI: 0.5-0.6) and 0.3 (95% CI: 0.3-0.4), compared with the Swedish-born and Norwegian-born individuals, respectively. Stratification by region/country of birth showed similar statistically significant lower odds for most refugee groups in both host countries except for refugees from Eritrea (aOR 1.0, 95% CI: 0.7-1.6) in Sweden. The risk of suicide did not vary much across refugee groups by their duration of residence, sex and age.

Conclusions

The findings of almost similar suicide mortality advantages among refugees in two host countries may suggest that resiliency and culture/religion-bound attitudes could be more influential for suicide risk among refugees than other post-migration environmental and structural factors in the host country.

Disclosure

No significant relationships.

Suicide trends in Norway during the first year of the Covid-19 pandemic. A register-based cohort study

Background

There is a concern that the COVID-19 pandemic will lead to an increase in suicides. Several reports from the first months of the pandemic showed no increase in suicide rates while studies with longer observation times report contrasting results. In this study, we explore the suicide rates in Norway during the first year of the pandemic for the total population as well as for relevant subgroups such as sex, age, geographical areas, and pandemic phases.

Methods

This is a cohort study covering the entire Norwegian population between 2010 and 2020. The main outcome was age-standardized suicide rates (per 100,000 inhabitants) in 2020 according to the Norwegian Cause of Death Registry. This was compared with 95% prediction intervals (95% PI) based on the suicide rates between 2010 and 2019.

Results

In 2020, there were 639 suicides in Norway corresponding to a rate of 12.1 per 100,000 (95% PI 10.2–14.4). There were no significant deviations from the predicted values for suicides in 2020 when analyzing age, sex, pandemic phase, or geographical area separately. We observed a trend toward a lower than predicted suicide rate among females (6.5, 95% PI 6.0–9.2), and during the two COVID-19 outbreak phases in 2020 (2.8, 95% PI 2.3–4.3 and 2.8, 95% CI 2.3–4.3).

Conclusion

There is no indication that the COVID-19 pandemic led to an increase in suicide rates in Norway in 2020.

BUSnet: A Deep Learning Model of Breast Tumor Lesion Detection for Ultrasound Images

Ultrasound (US) imaging is a main modality for breast disease screening. Automatically detecting the lesions in US images is essential for developing the artificial-intelligence-based diagnostic support technologies. However, the intrinsic characteristics of ultrasound imaging, like speckle noise and acoustic shadow, always degenerate the detection accuracy. In this study, we developed a deep learning model called BUSnet to detect the breast tumor lesions in US images with high accuracy. We first developed a two-stage method including the unsupervised region proposal and bounding-box regression algorithms. Then, we proposed a post-processing method to enhance the detecting accuracy further. The proposed method was used to a benchmark dataset, which includes 487 benign samples and 210 malignant samples. The results proved the effectiveness and accuracy of the proposed method.

First evidence that an emerging mammalian alphacoronavirus is able to infect an avian species

A novel swine enteric alphacoronavirus, swine acute diarrhea syndrome coronavirus (SADS-CoV), related to Rhinolophus bat CoV HKU2 in the subgenus Rhinacovirus has emerged in southern China in 2017, causing diarrhea in newborn piglets, and critical questions remain about the pathogenicity, cross-species transmission and potential animal reservoirs. Our laboratory's previous research has shown that SADS-CoV can replicate in various cell types from different species, including chickens. Here, we systematically explore the susceptibility of chicken to a cell-adapted SADS-CoV strain both in vitro and in vivo. Firstly, evidences of SADS-CoV replication in primary chicken cells including cytopathic effects, immunofluorescence staining, growth curve and structural protein expression were proven. Furthermore, we observed that SADS-CoV could replicate in chicken embryos without causing gross lesion, and that experimental infection of chicks resulted in mild respiratory symptoms. More importantly, SADS-CoV shedding and viral distribution in lungs, spleens, small intestines and large intestines of infected chickens were confirmed by quantitative RT-PCR and immunohistochemistry. The genomic sequence of the original SADS-CoV from the pig source sample in 2017 was determined to have nine nucleotide differences compared to the used cell-adapted strain; among these were three non-synonymous mutations in the spike gene. These results collectively demonstrate that chickens are susceptible to SADS-CoV infection, suggesting that they are a potential animal reservoir. To our knowledge, this study provides the first experimental evidence of cross-species infection that a mammalian alphacoronavirus is able to infect an avian species. This article is protected by copyright. All rights reserved.

Factors Influencing Total Delay of Breast Cancer in Northeast of China

Objectives

Delay in diagnosis and treatment, called total delay, could probably result in lower survival rates in breast cancer patients. This study aimed to investigate the factors associated with the comprehensive delay behaviors and to evaluate its effect on outcomes in patients with breast cancer in Dalian, a northeast city of China.

Methods

A retrospective chart review was conducted using a cancer registry dataset including 298 patients. The Kaplan–Meier survival analysis was used to identify the threshold of total delay, dividing the patients into a group with significant uncertainty and a group without substantial delay. The factors associated with the significant total delay were investigated from the potential candidates, like income level and marital status, by using the chi-squared test. The difference of the clinicopathologic characteristics between the patients grouped by the significant total delay, like tumor size and lymph node metastasis, was also investigated to find out the effect of the total delay.

Results

A total of 238 charts were used for analysis. The mean age was 57.3. The median of total delays was 3.75 months. Thirty days was identified as a threshold, more than which the total delay can lead to worse survival. Patients’ marital status (p = 0.010), income levels (p = 0.003), smoking status (p = 0.031), initial visiting hospital level (p = 0.005), self-health care (p = 0.001), and self-concern about initial symptom (p ≈ 0.000) were identified as the independent predictors of the total delay. Metastasis (p ≈ 0.000) was identified as the significant result relating to the significant total delay.

Conclusions

A total delay of more than 30 days predicts worse survival in breast cancer patients in Dalian. Several factors, like patients’ marital status and income levels, can be considered to be relevant to the significant total delay. We recommend that these factors be used to predict the potential patients with the significant total delay in the clinical practice.

U-shaped GAN for Semi-Supervised Learning and Unsupervised Domain Adaptation in High Resolution Chest Radiograph Segmentation

Deep learning has achieved considerable success in medical image segmentation. However, applying deep learning in clinical environments often involves two problems: (1) scarcity of annotated data as data annotation is time-consuming and (2) varying attributes of different datasets due to domain shift. To address these problems, we propose an improved generative adversarial network (GAN) segmentation model, called U-shaped GAN, for limited-annotated chest radiograph datasets. The semi-supervised learning approach and unsupervised domain adaptation (UDA) approach are modeled into a unified framework for effective segmentation. We improve GAN by replacing the traditional discriminator with a U-shaped net, which predicts each pixel a label. The proposed U-shaped net is designed with high resolution radiographs (1,024 × 1,024) for effective segmentation while taking computational burden into account. The pointwise convolution is applied to U-shaped GAN for dimensionality reduction, which decreases the number of feature maps while retaining their salient features. Moreover, we design the U-shaped net with a pretrained ResNet-50 as an encoder to reduce the computational burden of training the encoder from scratch. A semi-supervised learning approach is proposed learning from limited annotated data while exploiting additional unannotated data with a pixel-level loss. U-shaped GAN is extended to UDA by taking the source and target domain data as the annotated data and the unannotated data in the semi-supervised learning approach, respectively. Compared to the previous models dealing with the aforementioned problems separately, U-shaped GAN is compatible with varying data distributions of multiple medical centers, with efficient training and optimizing performance. U-shaped GAN can be generalized to chest radiograph segmentation for clinical deployment. We evaluate U-shaped GAN with two chest radiograph datasets. U-shaped GAN is shown to significantly outperform the state-of-the-art models.

Genetic and Pathogenic Characterization of a New Iridovirus Isolated from Cage-Cultured Large Yellow Croaker (Larimichthys crocea) in China

Iridoviruses are an important pathogen of ectothermic vertebrates and are considered a significant threat to aquacultural fish production. Recently, one of the most economically important marine species in China, the large yellow croaker (Larimichthys crocea), has been increasingly reported to be the victim of iridovirus disease. In this study, we isolated and identified a novel iridovirus, LYCIV-ZS-2020, from cage-cultured large yellow croaker farms in Zhoushan island, China. Genome sequencing and subsequent phylogenetic analyses showed that LYCIV-ZS-2020 belongs to the genus Megalocytivirus and is closely related to the Pompano iridoviruses isolated in the Dominican Republic. LYCIV-ZS-2020 enriched from selected tissues of naturally infected large yellow croaker was used in an artificial infection trial and the results proved its pathogenicity in large yellow croaker. This is the first systematic research on the genetic and pathogenic characterization of iridovirus in large yellow croakers, which expanded our knowledge of the iridovirus.

Age and Sex Differences in the Association of Sleep Duration and Overweight/Obesity among Chinese Participants Age above 45 Years: A Cohort Study

OBJECTIVES

We aimed to evaluate the association between sleep duration and obesity and estimate the attributable risk of sleep in the China Health and Retirement Longitudinal Study surveys (CHARLS).

METHODS

A total of 9061 adults aged 45 years above from CHARLS (2011-2015) were included. The main outcome of this study was incident overweight/obesity specific to general and abdominal obesity. Overweight/obesity was defined as BMI ≥ 23.0 (kg/m2) and BMI≥27.5 (kg/m2), respectively. Abdominal obesity was defined as waist circumference ≥90 cm for men and ≥80 cm for women. Self-reported sleep durations were obtained using a structured questionnaire. We assessed hazard ratios (HRs) and 95% confidence intervals (CIs) as well as the population attributable fraction (PAF) for associations between sleep duration and obesity.

RESULTS

986 and 606 participants were identified as overweight and general obesity respectively, 1253 experienced abdominal obesity events. In multivariable-adjusted models, participants with daytime sleep of 0-30 minutes and more than 30 minutes associated with 30% (HR: 0.70, 95% CI: 0.56-0.87) and 35% (HR: 0.65, 95% CI: 0.55-0.78) decreased incident overweight risk respectively compared to those having no daytime sleep, this association also found among females and middle-aged, not males or elderly. Similarly, 0-30 minutes (HR: 0.68, 95% CI: 0.48-0.96) and more than 30 minutes of daytime sleep (HR: 0.73, 95% CI: 0.59-0.91) were associated with a reduced risk of abdominal obesity, similar results also found among females and middle-aged. Compared with 7-9 hours of nocturnal sleep, people who slept 5-7 hours had a reduced risk of overweight (HR: 0.59, 95% CI=0.47-0.74),but not found in subgroups. The hazard role of long nocturnal sleep for abdominal obesity was only found among elderly (HR: 2.33, 95% CI=1.35-4.04) and males (HR: 2.24, 95% CI=1.17-4.29). Compared with moderate total sleepers (7-9hours/day), participants with short total sleep duration exhibited an elevated risk of overweight (HR: 1.13, 95% CI=1.00-1.28), this also found among middle-aged. The PAF for inadequate total sleep duration (<7 hours/day) was 10.77% for overweight individuals.

CONCLUSIONS

Insufficient sleep duration was associated with an elevated risk of overweight only detected among middle-aged not elderly and other subgroups specific by age. The risks for abdominal obesity were increased for males and middle-aged with long nocturnal sleep. Daytime sleep may significantly reduce the risk of overweight and abdominal obesity in female and middle-aged individuals. The link between sleep duration and obesity requires further study.

Mesoporous polydopamine nanoparticles carrying peptide RL-QN15 show potential for skin wound therapy

BACKGROUND

Skin wound healing remains a considerable clinical challenge, thus stressing the urgent need for the development of new interventions to promote repair. Recent researches indicate that both peptides and nanoparticles may be potential therapies for the treatment of skin wounds.

METHODS

In the current study, the mesoporous polydopamine (MPDA) nanoparticles were prepared and the peptide RL-QN15 that was previously identified from amphibian skin secretions and exhibited significant potential as a novel prohealing agent was successfully loaded onto the MPDA nanoparticles, which was confirmed by results of analysis of scanning electron microscopy and fourier transform infrared spectroscopy. The encapsulation efficiency and sustained release rate of RL-QN15 from the nanocomposites were determined. The prohealing potency of nanocomposites were evaluated by full-thickness injured wounds in both mice and swine and burn wounds in mice.

RESULTS

Our results indicated that, compared with RL-QN15 alone, the prohealing potency of nanocomposites of MPDA and RL-QN15 in the full-thickness injured wounds and burn wounds in mice was increased by up to 50 times through the slow release of RL-QN15. Moreover, the load on the MPDA obviously increased the prohealing activities of RL-QN15 in full-thickness injured wounds in swine. In addition, the obvious increase in the prohealing potency of nanocomposites of MPDA and RL-QN15 was also proved by the results from histological analysis.

CONCLUSIONS

Based on our knowledge, this is the first research to report that the load of MPDA nanoparticles could significantly increase the prohealing potency of peptide and hence highlighted the promising potential of MPDA nanoparticles-carrying peptide RL-QN15 for skin wound therapy.

Occurrence, spatial distribution, source, and ecological risk assessment of organochlorine pesticides in Dongting Lake, China

The occurrence, distribution, sources, and ecological risks of organochlorine pesticides in Dongting Lake of China were investigated. The average concentrations of organochlorine pesticides (OCPs) in 22 surface water samples and 14 sediment samples were 90.07 ng/L and 80.65 ng/g dw, respectively. Sixteen types of OCPs, dominated by HCHs, DDTs and heptachlor, were detected in the Dongting Lake. The relationships of OCP residues between Dongting Lake and its tributary rivers have been discussed and the hydraulic connections with the Yangtze River and the Three Gorges Dam (TGD) were also considered. Results showed that the shortage of runoff, earlier dry season, and reduction of sediment deposition extremely deteriorated the hydraulic conditions, magnified the water cycle, and restrained the self-purification of OCPs. The ∑OCPs in surface water were concentrated in the inlets of Yangtze River, Lishui River, Zishui River, Yuanshui River, and Xiangjiang River. Moreover, the ∑OCPs in the outlet of the Yangtze River also maintained a high level, indicating that OCPs posed adverse effects on the Yangtze River. Risk assessments of OCPs in the surface water of Dongting Lake were estimated according to available water quality guidelines and health risk assessment models. The results indicated that OCPs in the surface water of Dongting Lake were safe for aquatic organisms and human health. In addition, sediment quality guidelines (SQGs) were also applied to evaluate the potential ecotoxicological risks of OCPs in sediments. The results presented that contaminants of γ-HCH; o,p'-DDD; and dieldrin in sediment had adverse effects on benthic organisms, indicating that fundamental solutions should be proposed to control OCP contamination in Dongting Lake.

Ventilation and air cleaning to limit aerosol particle concentrations in a gym during the COVID-19 pandemic

SARS-CoV-2 can spread by close contact through large droplet spray and indirect contact via contaminated objects. There is mounting evidence that it can also be transmitted by inhalation of infected saliva aerosol particles. These particles are generated when breathing, talking, laughing, coughing or sneezing. It can be assumed that aerosol particle concentrations should be kept low in order to minimize the potential risk of airborne virus transmission. This paper presents measurements of aerosol particle concentrations in a gym, where saliva aerosol production is pronounced. 35 test persons performed physical exercise and aerosol particle concentrations, CO₂ concentrations, air temperature and relative humidity were obtained in the room of 886 m³. A separate test was used to discriminate between human endogenous and exogenous aerosol particles. Aerosol particle removal by mechanical ventilation and mobile air cleaning units was measured. The gym test showed that ventilation with air-change rate ACH = 2.2 h^-1, i.e. 4.5 times the minimum of the Dutch Building Code, was insufficient to stop the significant aerosol concentration rise over 30 min. Air cleaning alone with ACH = 1.39 h^-1 had a similar effect as ventilation alone. Simplified mathematical models were engaged to provide further insight into ventilation, air cleaning and deposition. It was shown that combining the above-mentioned ventilation and air cleaning can reduce aerosol particle concentrations with 80 to 90% , depending on aerosol size. This combination of existing ventilation supplemented with air cleaning is energy efficient and can also be applied for other indoor environments.

High-throughput sequencing of the porcine antibody repertoire with or without PEDV infection: A proof-of-concept study

A host's adaptive immune system can protect against a wide variety of pathogens by producing diverse antibodies. The antibody repertoire is so vast that traditional low-throughput methods cannot fully sequence it. In this study, we developed a high-throughput sequencing (HTS) method for antibody repertoire assessment in swine, and tested it with or without porcine epidemic diarrhea virus (PEDV) infection. We isolated peripheral blood mononuclear cells from normal or PEDV-seropositive pigs and applied multiplex PCR to amplify the porcine B cell receptor heavy chain library, followed by HTS using the Illumina Miseq system to obtain full sequence information. The results from sequence analysis demonstrated that in normal conditions, several V gene segments were preferentially used, with IGHV1-4 and IGHV1S2 being the two most frequent. The IGHV usage in PEDV-seropositive pigs was not exactly the same as that of PEDV-seronegative pigs, with an increased usage of IGHV1-6. Our study provides an effective approach to comprehensively understand the overall porcine antibody repertoire, as well as to monitor broad antibody responses to viral challenge in pigs.

Identification of Potential Early Diagnostic Biomarkers of Sepsis

Objective

The goal of this article was to identify potential biomarkers for early diagnosis of sepsis in order to improve their survival.

Methods

We analyzed differential gene expression between adult sepsis patients and controls in the GSE54514 dataset. Coexpression analysis was used to cluster coexpression modules, and enrichment analysis was performed on module genes. We also analyzed differential gene expression between neonatal sepsis patients and controls in the GSE25504 dataset, and we identified the subset of differentially expressed genes (DEGs) common to neonates and adults. All samples in the GSE54514 dataset were randomly divided into training and validation sets, and diagnostic signatures were constructed using least absolute shrink and selection operator (LASSO) regression. The key gene signature was screened for diagnostic value based on area under the receiver operating characteristic curve (AUC). STEM software identified dysregulated genes associated with sepsis-associated mortality. The ssGSEA method was used to quantify differences in immune cell infiltration between sepsis and control samples.

Results

A total of 6316 DEGs in GSE54514 were obtained spanning 10 modules. Module genes were mainly enriched in immune and metabolic responses. Screening 51 genes from among common genes based on AUC > 0.7 led to a LASSO model for the training set. We obtained a 25-gene signature, which we validated in the validation set and in the GSE25504 dataset. Among the signature genes, SLC2A6, C1ORF55, DUSP5 and RHOB were recognized as key genes (AUC > 0.75) in both the GSE54514 and GSE25504 datasets. SLC2A6 was identified by STEM as associated with sepsis-associated mortality and showed the strongest positive correlation with infiltration levels of Th1 cells.

Conclusion

In summary, our four key genes may have important implications for the early diagnosis of sepsis patients. In particular, SLC2A6 may be a critical biomarker for predicting survival in sepsis.

Lysosomal ion channels involved in cellular entry and uncoating of enveloped viruses: Implications for therapeutic strategies against SARS-CoV-2

Ion channels are necessary for correct lysosomal function including degradation of cargoes originating from endocytosis. Almost all enveloped viruses, including coronaviruses (CoVs), enter host cells via endocytosis, and do not escape endosomal compartments into the cytoplasm (via fusion with the endolysosomal membrane) unless the virus-encoded envelope proteins are cleaved by lysosomal proteases. With the ongoing outbreak of severe acute respiratory syndrome (SARS)-CoV-2, endolysosomal two-pore channels represent an exciting and emerging target for antiviral therapies. This review focuses on the latest knowledge of the effects of lysosomal ion channels on the cellular entry and uncoating of enveloped viruses, which may aid in development of novel therapies against emerging infectious diseases such as SARS-CoV-2.

Simultaneous, Rapid and Nondestructive Determination of Moisture, Fat Content and Storage Time in Leisure Dried Tofu Using LF-NMR

Leisure dried tofu is a kind of small packaged food which is popular with consumers in China. However, during the storage of leisure dried tofu, moisture and fat may be lost and deteriorate. For their own benefit, bad business operators might forge or mark the production date and shelf life. Therefore, it is necessary to explore a method to determine simultaneously the moisture, fat content, and storage time of leisure dried tofu. Samples were measured for obtaining transverse relaxation data by using low-field nuclear magnetic resonance (LF-NMR) spectrometer. The experimental data were analyzed and modeled by methods including partial least squares (PLS) or back-propagation artificial neural network (BP-ANN). The results show that the models can be used to predict the moisture, fat content, and storage time rapidly, nondestructively, accurately, and simultaneously. Furthermore, in order to explore the changes of nutrients in leisure dried tofu with the storage time, the storage dynamics of moisture and fat was considered by a using corresponding calibration model.

A novel spike subunit 1-based enzyme-linked immunosorbent assay reveals widespread porcine torovirus infection in eastern China

Toroviruses (ToVs), closely related but genetically distinct from coronaviruses, are known to infect horses, cows, pigs, goats and humans, mainly causing enteritic disorders. However, due to the lack of an adaptive culture system, porcine ToV (PToV) has received less attention. In this study, we developed a novel serological detection method based on the PToV envelope spike subunit 1 (S1) protein for the first time, and compared it to an existing indirect enzyme-linked immunosorbent assay (ELISA) based on the nucleocapsid protein. By using the S1-based ELISA, we carried out the first seroepidemiological survey of PToV in China, assaying both specific IgG and IgA responses in 1,037 serum samples collected from diarrheic pigs in eastern China. There was a relatively high incidence of seropositivity in pigs of different ages, especially one-week-old piglets and sows (78% and 43%), the former probably reflecting maternal antibodies. Furthermore, 3/20 (15%) of faecal samples collected from one PToV-seropositive swine herd in Zhejiang province tested positive by RT-PCR. The complete PToV genome was sequenced from one of these samples, and its phylogenetic relationship with other full-length PToV sequences available in GenBank was determined. Our data provide the first serological evidence for PToV infection in pigs from China, which will help elucidate the potential pathogenicity of PToV in pigs.

The porcine deltacoronavirus accessory protein NS6 is expressed in vivo and incorporated into virions

Porcine deltacoronavirus (PDCoV) is one of the emerged coronaviruses posing a significant threat to the swine industry. Previous work showed the presence of a viral accessory protein NS6 in PDCoV-infected cells. In this study, we detected the expression of the NS6 protein in small intestinal tissues of PDCoV-infected piglets. In addition, SDS-PAGE and Western blot analysis of sucrose gradient-purified virions showed the presence of a 13-kDa NS6 protein. Further evidences of the presence of NS6 in the PDCoV virions were obtained by immunogold staining of purified virions with anti-NS6 antiserum, and by immunoprecipitation of NS6 from purified virions. Finally, the anti-NS6 antibody was not able to neutralize PDCoV in cultured cells. These data establish for the first time that the accessory protein NS6 is expressed during infection in vivo and incorporated into PDCoV virions.

Occurrence and risk evaluation of organophosphorus pesticides in typical water bodies of Beijing, China

AbstractHuman activities, particularly in large cities, can lead to pollution caused by micropollutants such as pesticides in water bodies, which have been recognized as serious threats to the environment and human health. The pollution level of six organophosphorus pesticides, three herbicides, and one bactericide in groundwater and the Wenyu River, and their fates in three sewage treatment plants (STPs) and a hospital were investigated in this study. The concentrations of the ten detected pesticides ranged from not detected (ND) to 323.44 ng L^-1 in different water samples from Beijing; metalaxyl was detected to have the highest concentration (89.58 ng L^-1), and the detection frequencies of atrazine and metalaxyl were 100%. The maximum concentrations of pesticides in the Wenyu River, STPs, and the hospital were 1-2 orders of magnitude higher than those in the groundwater. Good removal efficiencies by the treatment processes were observed for ametryn (100%), while the removal efficiencies for atrazine and omethoate were the lowest in the three STPs (- 9.6% and 12.67%, respectively). Finally, risk quotient (RQ) values of each contaminant were estimated from the maximum values determined for typical urban to assess the ecology and health effects. In the case of environmental toxicity, the highest RQ values (> 1) were obtained for dichlorvos and omethoate. In the case of health toxicity, the RQ values show that the pesticides found in groundwater pose no potential health risks to humans at current concentrations.

Removal of tri-(2-chloroisopropyl) phosphate (TCPP) by three types of constructed wetlands

In this study, three types of constructed wetlands (CWs) (biofilm-attachment-surface-CWs, packed bed-CWs and traditional-CWs) were assembled to comparatively evaluate their ability and mechanism to remove tri-(2-chloroisopropyl) phosphate (TCPP) under continuous flow operation. The removal rate (26%-28%) of TCPP in two types of CWs containing plants was twice as much as that in plant-free CWs in 6-month experiments, and TCPP showed a terminal accumulation phenomenon in Cyperus alternifolius with the order of accumulation of leaf>stem>root. The mass balance indicated that the contributions of filler and hydrophyte absorption to TCPP removal were less than 1%, but the transpiration of hydrophytes may make an important contribution (approximately 10%) to TCPP removal. Species in the genera Massilia, Denitratisoma and SM1A02 may be responsible for TCPP biodegradation. In addition, the effect of TCPP on the metabolic pathways and energy generation in the roots of C. alternifolius suggested that TCPP may be transported and utilized through cellular metabolism.

Discovery of a novel short peptide with efficacy in accelerating the healing of skin wounds

Despite extensive efforts to develop efficacious therapeutic approaches, the treatment of skin wounds remains a considerable clinical challenge. Existing remedies cannot sufficiently meet current needs, so the discovery of novel pro-healing agents is of growing importance. In the current research, we identified a novel short peptide (named RL-QN15, primary sequence 'QNSYADLWCQFHYMC') from Rana limnocharis skin secretions, which accelerated wound healing in mice. Exploration of the underlying mechanisms showed that RL-QN15 activated the MAPK and Smad signaling pathways, and selectively modulated the secretion of cytokines from macrophages. This resulted in the proliferation and migration of skin cells and dynamic regulation of TGF-β1 and TGF-β3 in wounds, which accelerated re-epithelialization and granulation tissue formation and thus skin regeneration. Moreover, RL-QN15 showed significant therapeutic potency against chronic wounds, skin fibrosis, and oral ulcers. Our results highlight frog skin secretions as a potential treasure trove of bioactive peptides with healing activity. The novel peptide (RL-QN15) identified in this research shows considerable capacity as a candidate for the development of novel pro-healing agents.

FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network

Identification of driver genes, whose mutations cause the development of tumors, is crucial for the improvement of cancer research and precision medicine. To overcome the problem that the traditional frequency-based methods cannot detect lowly recurrently mutated driver genes, researchers have focused on the functional impact of gene mutations and proposed the function-based methods. However, most of the function-based methods estimate the distribution of the null model through the non-parametric method, which is sensitive to sample size. Besides, such methods could probably lead to underselection or overselection results. In this study, we proposed a method to identify driver genes by using functional impact prediction neural network (FI-net). An artificial neural network as a parametric model was constructed to estimate the functional impact scores for genes, in which multi-omics features were used as the multivariate inputs. Then the estimation of the background distribution and the identification of driver genes were conducted in each cluster obtained by the hierarchical clustering algorithm. We applied FI-net and other 22 state-of-the-art methods to 31 datasets from The Cancer Genome Atlas project. According to the comprehensive evaluation criterion, FI-net was powerful among various datasets and outperformed the other methods in terms of the overlap fraction with Cancer Gene Census and Network of Cancer Genes database, and the consensus in predictions among methods. Furthermore, the results illustrated that FI-net can identify known and potential novel driver genes.

CheXLocNet: Automatic localization of pneumothorax in chest radiographs using deep convolutional neural networks

BACKGROUND

Pneumothorax can lead to a life-threatening emergency. The experienced radiologists can offer precise diagnosis according to the chest radiographs. The localization of the pneumothorax lesions will help to quickly diagnose, which will be benefit for the patients in the underdevelopment areas lack of the experienced radiologists. In recent years, with the development of large neural network architectures and medical imaging datasets, deep learning methods have become a methodology of choice for analyzing medical images. The objective of this study was to the construct convolutional neural networks to localize the pneumothorax lesions in chest radiographs.

METHODS AND FINDINGS

We developed a convolutional neural network, called CheXLocNet, for the segmentation of pneumothorax lesions. The SIIM-ACR Pneumothorax Segmentation dataset was used to train and validate CheXLocNets. The training dataset contained 2079 radiographs with the annotated lesion areas. We trained six CheXLocNets with various hyperparameters. Another 300 annotated radiographs were used to select parameters of these CheXLocNets as the validation set. We determined the optimal parameters by the AP50 (average precision at the intersection over union (IoU) equal to 0.50), a segmentation evaluation metric used by several well-known competitions. Then CheXLocNets were evaluated by a test set (1082 normal radiographs and 290 disease radiographs), based on the classification metrics: area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and positive predictive value (PPV); segmentation metrics: IoU and Dice score. For the classification, CheXLocNet with best sensitivity produced an AUC of 0.87, sensitivity of 0.78 (95% CI 0.73-0.83), and specificity of 0.78 (95% CI 0.76-0.81). CheXLocNet with best specificity produced an AUC of 0.79, sensitivity of 0.46 (95% CI 0.40-0.52), and specificity of 0.92 (95% CI 0.90-0.94). For the segmentation, CheXLocNet with best sensitivity produced an IoU of 0.69 and Dice score of 0.72. CheXLocNet with best specificity produced an IoU of 0.77 and Dice score of 0.79. We combined them to form an ensemble CheXLocNet. The ensemble CheXLocNet produced an IoU of 0.81 and Dice score of 0.82. Our CheXLocNet succeeded in automatically detecting pneumothorax lesions, without any human guidance.

CONCLUSIONS

In this study, we proposed a deep learning network, called, CheXLocNet, for the automatic segmentation of chest radiographs to detect pneumothorax. Our CheXLocNets generated accurate classification results and high-quality segmentation masks for the pneumothorax at the same time. This technology has the potential to improve healthcare delivery and increase access to chest radiograph expertise for the detection of diseases. Furthermore, the segmentation results can offer comprehensive geometric information of lesions, which can benefit monitoring the sequential development of lesions with high accuracy. Thus, CheXLocNets can be further extended to be a reliable clinical decision support tool. Although we used transfer learning in training CheXLocNet, the parameters of CheXLocNet was still large for the radiograph dataset. Further work is necessary to prune CheXLocNet suitable for the radiograph dataset.

Behavior of selected organophosphate flame retardants (OPFRs) and their influence on rhizospheric microorganisms after short-term exposure in integrated vertical-flow constructed wetlands (IVCWs)

Considering its ubiquitous occurrence and potential adverse effects of organophosphorus flame retardant (OPFR), it is urgent to explore the efficient treatment for OPFRs wastewater. Thus, integrated vertical-flow constructed wetlands (IVCWs) were set up to comparatively evaluate their nitrogen removal capacity under tidal flow operations and to investigate environmental behavior and rhizosphere microbial responses after short-term exposure to three OPFRs. The results show that IVCWs have an excellent TN removal rate (628.13 ± 110.63 mg m^-2 d^-1) and moderate mitigation efficiencies (48.37 ± 9.52 to 82.28 ± 7.48%) for target OPFRs when treating low-C/N ratio wastewater. Moreover, the sorption of selected OPFRs to soil (28.85-308.41 ng g^-1, dry weight (dw)), igneous rock (659.85-970.80 ng g^-1 dw) and zeolite (1045.60-1351.70 ng g^-1 dw) and accumulation in tissues of C. alternifolius (0-289.68 ng g^-1 dw) and P. australis (0.56-108.22 ng g^-1 dw) showed a hydrophobicity-specific feature. Namely, the highly hydrophobic compound tricresyl phosphate (TCrP) partitioned preferentially to sediment, and the chlorinated analytes were more easily taken up and then translocated into the plant body. Simultaneously, further mass balance analysis revealed the fate of OPFRs in IVCW components. A total of 53.25% of the highly hydrophobic TCrP inflow mass settled in sediment, while tris (2-chloroethyl) phosphate (TCEP) and tris (1-chloro-2-propyl) phosphate (TCPP) were more liable to discharge (35.33-50.89%) and other pathways (38.77-39.87%). Furthermore, the abundance of aerobic denitrifying bacteria (AD) in rhizosphere soil (2.25-5.12%), jointly with the prevalence of nitrobacteria (NOBs, 1.84-13.60%) and denitrifying bacteria (DNBs, 5.84-7.89%) in sublayer matrices, was responsible for superior TN removal. Additionally, the rhizosphere microbial richness, diversity and nitrogen-related microorganisms were clearly influenced by the presence of OPFRs. Notably, the genera Pseudomonas and Sphingobium might be the functional microorganisms for mixture OPFRs biodegradation.

Trypsin promotes porcine deltacoronavirus mediating cell-to-cell fusion in a cell type-dependent manner

Porcine deltacoronavirus (PDCoV) is a newly emerging threat to the global porcine industry. PDCoV has been successfully isolated using various medium additives including trypsin, and although we know it is important for viral replication, the mechanism has not been fully elucidated. Here, we systematically investigated the role of trypsin in PDCoV replication including cell entry, cell-to-cell membrane fusion and virus release. Using pseudovirus entry assays, we demonstrated that PDCoV entry is not trypsin dependent. Furthermore, unlike porcine epidemic diarrhea virus (PEDV), in which trypsin is important for the release of virus from infected cells, PDCoV release was not affected by trypsin. We also demonstrated that trypsin promotes PDCoV replication by enhancing cell-to-cell membrane fusion. Most importantly, our study illustrates two distinct spreading patterns from infected cells to uninfected cells during PDCoV transmission, and the role of trypsin in PDCoV replication in cells with different virus spreading types. Overall, these results clarify that trypsin promotes PDCoV replication by mediating cell-to-cell fusion transmission but is not crucial for viral entry. This knowledge can potentially contribute to improvement of virus production efficiency in culture, not only for vaccine preparation but also to develop antiviral treatments.

Characterization of a novel bat-HKU2-like swine enteric alphacoronavirus (SeACoV) infection in cultured cells and development of a SeACoV infectious clone

Swine enteric alphacoronavirus (SeACoV), also known as swine acute diarrhea syndrome coronavirus (SADS-CoV), belongs to the species Rhinolophus bat coronavirus HKU2. Herein, we report on the primary characterization of SeACoV in vitro. Four antibodies against the SeACoV spike, membrane, nucleocapsid and nonstructural protein 3 capable of reacting with viral antigens in SeACoV-infected Vero cells were generated. We established a DNA-launched SeACoV infectious clone based on the cell adapted passage-10 virus and rescued the recombinant virus with a unique genetic marker in cultured cells. Six subgenomic mRNAs containing the leader-body junction sites, including a bicistronic mRNA encoding the accessory NS7a and NS7b genes, were experimentally identified in SeACoV-infected cells. Cellular ultrastructural changes induced by SeACoV infection were visualized by electron microscopy. The availability of the SeACoV infectious clone and a panel of antibodies against different viral proteins will facilitate further studies on understanding the molecular mechanisms of SeACoV replication and pathogenesis.

Specific recombinant proteins of porcine epidemic diarrhea virus are immunogenic, revealing their potential use as diagnostic markers

Given the highly contagious and acute nature of porcine epidemic diarrhea (PED), especially in piglets, there is an urgent need for the development of rapid and sensitive diagnostic assays. The diagnostic potentials of specific porcine epidemic diarrhea virus (PEDV) accessory and nonstructural proteins, if any, have not yet been investigated. In order to determine and compare which of the viral proteins may be useful as diagnostic antigens, whole virus (WV) particles and a panel of structural and nonstructural PEDV proteins [spike subunit 1 (S1), the C-terminal part of ORF3 (ORF3C), envelope (E), nonstructural protein 1 (Nsp1), Nsp2, Ac (acidic domain of Nsp3), and ADRP (ADP-ribose-1-monophosphatase domain of Nsp3), expressed individually in bacterial and/or mammalian cells] were tested for reactivity with sera from PEDV-infected pigs by ELISA and/or western blot analysis. According to western blots, serum antibody interactions with the S1 protein were relatively more sensitive and specific than ORF3C, E and Ac. Furthermore, a total of 851 serum samples from diarrheal pigs of different ages were analyzed by ELISA, with most showing immune-reactivity towards the WV, S1, ORF3C, and E proteins. The earliest IgG antibody response was observed in the one-week-old piglets, with similar antibody ontogeny and patterns of seroconversion for S1, ORF3C, E, and WV antigens. In addition, the pattern of neutralizing antibody was more similar to that of IgA in weaning piglets after PEDV infection. Collectively, these data provide more reliable information on the host immune response to different viral proteins, which will be useful for development of novel serological assays and for design of vaccines that better stimulate protective immunity.

Inhibition of SGK1 confers vulnerability to redox dysregulation in cervical cancer

Cervical cancer has poor prognosis and patients are often diagnosed at advanced stages of the disease with limited treatment options. There is thus an urgent need for the discovery of new therapeutic strategies in cervical cancer. The activation of SGK1 has been linked to the development of various cancer types but little is known about the role of SGK1 in cervical cancer and its potential as a therapeutic target. Here we report that SGK1 is an antioxidative factor that promotes survival of cervical cancer cells. Gene set enrichment analysis of RNA-Seq data reveals a strong inverse association between SGK1 and oxidative phosphorylation. Consistently, inhibition of SGK1 via siRNA or pharmacological inhibitor GSK650394 induces ROS and cytotoxicity upon H₂O₂ stress. Further analysis of clinical data associates SGK1 with gene expression signatures regulated by the antioxidant transcription factor NRF2 in cervical cancer. Mechanistically, SGK1 activation exerts antioxidant effect through induction of c-JUN-dependent NRF2 expression and activity. Importantly, we find that inhibition of SGK1 confers vulnerability to melatonin as a pro-oxidant, resulting in ROS over-accumulation and consequently enhanced cell cytotoxicity. We further demonstrate that combined use of GSK650394 and melatonin yields substantial regression of cervical tumors in vivo. This work opens new perspectives on the potential of SGK1 inhibitors as sensitizing agents to enable the design of therapeutically redox-modulating strategies against cervical cancer.

Characteristics of the Life Cycle of Porcine Deltacoronavirus (PDCoV) In Vitro: Replication Kinetics, Cellular Ultrastructure and Virion Morphology, and Evidence of Inducing Autophagy

Porcine deltacoronavirus (PDCoV) causes severe diarrhea and vomiting in affected piglets. The aim of this study was to establish the basic, in vitro characteristics of the life cycle such as replication kinetics, cellular ultrastructure, virion morphology, and induction of autophagy of PDCoV. Time-course analysis of viral subgenomic and genomic RNA loads and infectious titers indicated that one replication cycle of PDCoV takes 5 to 6 h. Electron microscopy showed that PDCoV infection induced the membrane rearrangements with double-membrane vesicles and large virion-containing vacuoles. The convoluted membranes structures described in alpha- and beta-coronavirus were not observed. PDCoV infection also increased the number of autophagosome-like vesicles in the cytoplasm of cells, and the autophagy response was detected by LC3 I/II and p62 Western blot analysis. For the first time, this study presents the picture of the PDCoV infection cycle, which is crucial to help elucidate the molecular mechanism of deltacoronavirus replication.