Single nucleotide and copy number variants of cancer driver genes inform drug response in multiple cancers.

Due to the heterogeneity of cancer, precision medicine has been a major challenge for cancer treatment. Determining medication regimens based on patient genotypes has become a research hotspot in cancer genomics. In this study, we aim to identify key biomarkers for targeted therapies based on single nucleotide variants (SNVs) and copy number variants (CNVs) of genes. The experiment is carried out on 7 cancers on the Encyclopedia of Cancer Cell Lines (CCLE) dataset. Considering the high mutability of driver genes which result in abundant mutated samples, the effect of data sparsity can be eliminated to a large extent. Therefore, we focus on discovering the relationship between driver mutation patterns and three measures of drug response, namely area under the curve (AUC), half maximal effective concentration (EC50), and log2-fold change (LFC). First, multiple statistical methods are applied to assess the significance of difference in drug response between sample groups. Next, for each driver gene, we analyze the extent to which its mutations can affect drug response. Based on the results of multiple hypothesis tests and correlation analyses, our main findings include the validation of several known drug response biomarkers such as BRAF, NRAS, MAP2K1, MAP2K2, and CDKN2A, as well as genes with huge potential to infer drug responses. It is worth emphasizing that we identify a list of genes including SALL4, B2M, BAP1, CCDC6, ERBB4, FOXA1, GRIN2A, and PTPRT, whose impact on drug response spans multiple cancers and should be prioritized as key biomarkers for targeted therapies. Furthermore, based on the statistical p-values and correlation coefficients, we construct gene-drug sensitivity maps for cancer drug recommendation. In this work, we show that driver mutation patterns could be used to tailor therapeutics for precision medicine.

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.

Effect of remimazolam combined with remifentanil on hemodynamics in elderly patients undergoing painless bronchoscopy / 中国内镜杂志

Objective To explore the effect of remimazolam combined with remifentanil on painless bronchoscopy in elderly patients and observe its impact on hemodynamics.Methods Collect 80 elderly patients underwent bronchoscopy examination from October 2021 to October 2022 as research subjects,and divide them into remifentanil group and combination group according to anesthesia methods.Remifentanil group was given remifentanil assisted painless bronchoscopy,and the combined group was given remimazolam assisted painless bronchoscopy based on remifentanil group.The hemodynamics and operation conditions of the two groups at different time points[before anesthesia induction(T1),at the time of transglottis(T2),1 min after transglottis(T3),5 min after transglottis(T4),at the end of the inspection(T5)]were compared,and the changes of intraoperative and postoperative adverse reactions of patients with different anesthesia methods were observed,and satisfaction analysis was conducted.Results Compared with remifentanil group,the heart rate(HR)in the combined group at T2,T3,and T4 was slower,percutaneous arterial oxygen saturation(SpO2)was lower at T3,T4,diastolic blood pressure(DBP)and systolic blood pressure(SBP)were higher in T2,T3,T4,and the differences were statistically significant(P<0.05).The onset time of drugs was shorter,the recovery time of patients was long,the incidence of hypoxemia,hypotension and HR slowdown was lower,the incidence of HR increased was higher,and the postoperative satisfaction was higher,with statistical significance(P<0.05).There was no statistically significant difference in the incidence of postoperative nausea,vomiting,dizziness,headache,and drowsiness between the two groups of patients(P>0.05).Conclusion Remimazolam combined with remifentanil for painless bronchoscopy in elderly patients may have a good application effect,which can maintain hemodynamic stability,rapid onset,long duration of efficacy,reduce the rate of intraoperative adverse reactions,have a good safety,and can improve patient satisfaction.

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.

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.

A diagnostic scoring model of ENKTCL in the nose-Waldeyer's ring based on logistic regression: Differential diagnosis from DLBCL.

Objective: To establish a logistic regression model based on CT and MRI imaging features and Epstein-Barr (EB) virus nucleic acid to develop a diagnostic score model to differentiate extranodal NK/T nasal type (ENKTCL) from diffuse large B cell lymphoma (DLBCL). Methods: This study population was obtained from two independent hospitals. A total of 89 patients with ENKTCL (n = 36) or DLBCL (n = 53) from January 2013 to May 2021 were analyzed retrospectively as the training cohort, and 61 patients (ENKTCL=27; DLBCL=34) from Jun 2021 to Dec 2022 were enrolled as the validation cohort. All patients underwent CT/MR enhanced examination and EB virus nucleic acid test within 2 weeks before surgery. Clinical features, imaging features and EB virus nucleic acid results were analyzed. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predictors of ENKTCL and establish a predictive model. Independent predictors were weighted with scores based on regression coefficients. A receiver operating characteristic (ROC) curve was created to determine the diagnostic ability of the predictive model and score model. Results: We searched for significant clinical characteristics, imaging characteristics and EB virus nucleic acid and constructed the scoring system via multivariate logistic regression and converted regression coefficients to weighted scores. The independent predictors for ENKTCL diagnosis in multivariate logistic regression analysis, including site of disease (nose), edge of lesion (blurred), T2WI (high signal), gyrus like changes, EB virus nucleic acid (positive), and the weighted score of regression coefficient was 2, 3, 4, 3, 4 points. The ROC curves, AUCs and calibration tests were carried out to evaluate the scoring models in both the training cohort and the validation cohort. The AUC of the scoring model in the training cohort were 0.925 (95% CI, 0.906-0.990) and the cutoff point was 5 points. In the validation cohort, the AUC was 0.959 (95% CI, 0.915-1.000) and the cutoff value was 6 points. Four score ranges were as follows: 0-6 points for very low probability of ENKTCL, 7-9 points for low probability; 10-11 points for middle probability; 12-16 points for very high probability. Conclusion: The diagnostic score model of ENKTCL based on Logistic regression model which combined with imaging features and EB virus nucleic acid. The scoring system was convenient, practical and could significantly improve the diagnostic accuracy of ENKTCL and the differential diagnosis of ENKTCL from DLBCL.

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.

Chicken or Porcine Aminopeptidase N Mediates Cellular Entry of Pseudoviruses Carrying Spike Glycoprotein from the Avian Deltacoronaviruses HKU11, HKU13, and HKU17.

Members of deltacoronavirus (DCoV) have mostly been identified in diverse avian species as natural reservoirs, though the porcine DCoV (PDCoV) is a major swine enteropathogenic virus with global spread. The important role of aminopeptidase N (APN) orthologues from various mammalian and avian species in PDCoV cellular entry and interspecies transmission has been revealed recently. In this study, comparative analysis indicated that three avian DCoVs, bulbul DCoV HKU11, munia DCoV HKU13, and sparrow DCoV HKU17 (Chinese strain), and PDCoV in the subgenera Buldecovirus are grouped together at whole-genome levels; however, the spike (S) glycoprotein and its S1 subunit of HKU17 are more closely related to night heron DCoV HKU19 in Herdecovirus. Nevertheless, the S1 protein of HKU11, HKU13, or HKU17 bound to or interacted with chicken APN (chAPN) or porcine APN (pAPN) by flow cytometry analysis of cell surface expression of APN and by coimmunoprecipitation in APN-overexpressing cells. Expression of chAPN or pAPN allowed entry of pseudotyped lentiviruses with the S proteins from HKU11, HKU13 and HKU17 into nonsusceptible cells and natural avian and porcine cells, which could be inhibited by the antibody against APN or anti-PDCoV-S1. APN knockdown by siRNA or knockout by CRISPR/Cas9 in chicken or swine cell lines significantly or almost completely blocked infection of these pseudoviruses. Hence, we demonstrate that HKU11, HKU13, and HKU17 with divergent S genes likely engage chAPN or pAPN to enter the cells, suggesting a potential interspecies transmission from wild birds to poultry and from birds to mammals by certain avian DCoVs. IMPORTANCE The receptor usage of avian deltacoronaviruses (DCoVs) has not been investigated thus far, though porcine deltacoronavirus (PDCoV) has been shown to utilize aminopeptidase N (APN) as a cell receptor. We report here that chicken or porcine APN also mediates cellular entry by three avian DCoV (HKU11, HKU13, and HKU17) spike pseudoviruses, and the S1 subunit of three avian DCoVs binds to APN in vitro and in the surface of avian and porcine cells. The results fill the gaps in knowledge about the avian DCoV receptor and elucidate important insights for the monitoring and prevention of potential interspecies transmission of certain avian DCoVs. In view of the diversity of DCoVs, whether this coronavirus genus will cause novel virus to emerge in other mammals from birds, are worthy of further surveillance and investigation.

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.

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.

Mechanism of Bushen Gutai Mixture on Improving Uterine Decidual Tissue and Spiral Artery Blood Supply of Abortion Model Rats by Regulating PKA/CREB/AQP5 Pathway / 世界科学技术-中医药现代化

Objective To observe the effect of Bushen Gutai mixture on uterine blood supply of rat model of abortion induced by hydroxyurea tablets combined with mifepristone through PKA-CREB signal pathway and its mechanism of calming fetus.Methods 60 pregnant rats of SPF grade SD rats were prepared by closing cages at 2∶1.According to the order of pregnancy,60 pregnant rats were randomly divided into 6 groups with 10 rats in each group:Bushen Gutai mixture group(low,middle and high dose),normal pregnancy group,model group and Di qu progesterone group.On the 1st to 9th day of pregnancy,except the normal group,the pregnant rats in each group were gavaged with hydroxyurea tablets at 5∶00 pm every day(450 mg·kg-1),and at 10∶00 am on the 10th day of pregnancy.Mifepristone tablets were given by intragastric administration(4.0 mg·kg-1).At 9∶00 am every day from the 1st to 9th day of pregnancy,Bushen Gutai mixture was given to the low,middle and high dose groups(0.5,1.0,2.0 g·kg-1),didrone group(3.02 mg·kg-1),model group and normal pregnancy group with 0.9%normal saline.24 hours after the last administration of pentobarbital sodium(50 mg kg-1),all pregnant rats were killed by intraperitoneal injection of pentobarbital sodium,and the uterine decidual tissue of pregnant rats was bluntly isolated in sterile environment.Hematoxylin-eosin(HE)staining was used to observe the lumen diameter and wall thickness of spiral artery in uterine decidual tissue.Immunohistochemical staining(IHC)was used to detect the expression of vascular endothelial growth factor(VEGF)in decidual tissues.Western blot was used to detect the protein expression of phosphorylated protein kinase A,protein kinase A,phosphorylated cyclic adenosine monophosphate response element binding protein,Cyclic Adenosine monophosphate response element binding protein and aquaporin 5 in the decidua of pregnant rats.The apoptosis of decidual cells was detected by in situ end labeling(TUNEL)of DNA fragmentation.Results Compared with the model group,the wall thickness of spiral artery was higher than that in other groups(P<0.05),the lumen diameter was lower than that in other groups(P<0.05)and the expression of VEGF protein was lower than that of other groups(P<0.01).Compared with the model group,the apoptosis level of decidual cells in uterine decidua of abortive rats in high,middle and low dose groups of Bushen Gutai mixture and diqu progesterone group decreased in varying degrees.Bushen Gutai mixture can up-regulate the levels of p-PKA/PKA and p-CREB/CREB in uterine decidua(P<0.01)and promote the expression of AQP5 protein in uterine decidua of abortion rats(P<0.01).Conclusion Bushen Gutai mixture can improve uterine blood supply of aborted rats by activating PKA and CREB phosphorylation,up-regulating AQP5 expression,promoting physiological recasting of spiral artery and high expression of Vascular endothelial growth factor.

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.

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.

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.

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.