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A patient's comprehension and memory of conversations with their providers plays an important role in their healthcare. Adult breast cancer patients whose legal sex was female and who underwent treatment at the Center for Reconstructive Surgery at The University of Texas MD Anderson Cancer Center were asked to indicate which breast reconstruction procedures they discussed with their surgeon. We focused on the three most frequent responses: (a) participants who remembered discussing implant-based, tissue-based, and combination procedures; (b) participants who remembered only an implant-based option being discussed; and (c) participants who remember only a tissue-based option being discussed. We used multinomial logistic regression models to explore the psychosocial factors associated with patients' recollections of their breast reconstruction options after discussions with their reconstructive surgeons, controlling for medical factors that impact surgical decision-making. Our analyses identified body mass index, body image investment, and body image as statistically significantly associated with the reconstructive options that a participant recalls discussing with their surgeon. Our findings highlight body image investment and body image as important psychological factors that may influence what patients remember from consultations about breast reconstruction options. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is one of the leading causes of cancer-related deaths in women. The purpose of this study is to identify key molecular markers related to the diagnosis and prognosis of early breast cancer (EBC). The data of mRNA, lncRNA and DNA methylation were downloaded from The Cancer Genome Atlas (TCGA) dataset for identification of differentially expressed mRNAs (DEmRNAs), differentially expressed lncRNAs (DElncRNAs) and DNA methylation analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyzes were used to identify the biological functions of DEmRNAs. The correlation analysis between DNA methylation and DEmRNAs was carried out. Then, diagnostic analysis and prognostic analysis of identified DEmRNAs and DElncRNAs were also performed in the TCGA database. Subsequently, methylation state verification for identified DEmRNAs was performed in the GSE32393 dataset. In addition, real-time polymerase chain reaction (RT-PCR) in vitro verification of genes was performed. Finally, AC093110.1 was overexpressed in human BC cell line MCF-7 to verify cell proliferation and migration. In this study, a total of 1633 DEmRNAs, 750 DElncRNAs and 8042 differentially methylated sites were obtained, respectively. In the Venn analysis, 11 keys DEmRNAs (ALDH1L1, SPTBN1, MRGPRF, CAV2, HSPB6, PITX1, WDR86, PENK, CACNA1H, ALDH1A2 and MME) were we found. ALDH1A2, ALDH1L1, HSPB6, MME, MRGPRF, PENK, PITX1, SPTBN1, WDR86 and CAV2 may be considered as potential diagnostic gene biomarkers in EBC. Strikingly, CAV2, MME, AC093110.1 and AC120498.6 were significantly actively correlated with survival. Methylation state of identified DEmRNAs in GSE32393 dataset was consistent with the result in TCGA. AC093110.1 can affect the proliferation and migration of MCF-7. ALDH1A2, ALDH1L1, HSPB6, MME, MRGPRF, PENK, PITX1, SPTBN1, WDR86 and CAV2 may be potential diagnostic gene biomarkers of EBC. Strikingly, CAV2, MME, AC093110.1 and AC120498.6 were significantly actively correlated with survival. The identification of these genes can help in the early diagnosis and treatment of EBC. In addition, AC093110.1 can regulate SPTBN1 expression and play an important role in cell proliferation and migration, which provides clues to clarify the regulatory mechanism of EBC. [ABSTRACT FROM AUTHOR]

A novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified as the cause of the COVID-19 pandemic that originated in China in December 2019. Although extensive research has been performed on SARS-CoV-2, the binding behavior of spike (S) protein and receptor binding domain (RBD) of SARS-CoV-2 at different environmental conditions have yet to be studied. The objective of this study is to investigate the effect of temperature, fatty acids, ions, and protein concentration on the binding behavior and rates of association and dissociation between the S protein and RBD of SARS-CoV-2 and the hydrophobic aminopropylsilane (APS) biosensors using biolayer interferometry (BLI) validated with molecular dynamics simulation. Our results suggest three conditions—high ionic concentration, presence of hydrophobic fatty acids, and low temperature—favor the attachment of S protein and RBD to hydrophobic surfaces. Increasing the temperature within an hour from 0 to 25 °C results in S protein detachment, suggesting that freezing can cause structural changes in the S protein, affecting its binding kinetics at higher temperature. At all the conditions, RBD exhibits lower dissociation capabilities than the full-length S trimer protein, indicating that the separated RBD formed stronger attachment to hydrophobic surfaces compared to when it was included in the S protein. [ABSTRACT FROM AUTHOR]

The overuse of antibiotics has caused an increased prevalence of drug-resistant bacteria. Bacterial resistance in E. coli is regulated via production of β-lactam-hydrolyzing β-lactamases enzymes. Escherichia coli O104: H4 is a multi-drug resistant strain known to resist β-lactam as well as several other antibiotics. Here, we report a molecular dynamic simulation–combined docking approach to identify, screen, and verify active pharmacophores against enterohemorrhagic Escherichia coli (EHEC). Experimental studies revealed a boronic acid cyclic monomer (BACM), a non-β-lactam compound, to inhibit the growth of E. coli O104: H4. In vitro Kirby Bauer disk diffusion susceptibility testing coupled interaction analysis suggests BACM inhibits E. coli O104:H4 growth by not only inhibiting the β-lactamase pathway but also via direct inhibition of the penicillin-binding protein. These results suggest that BACM could be used as a lead compound to develop potent drugs targeting beta-lactam resistant Gram-negative bacterial strains. Key messages: • An in silico approach was reported to identify pharmacophores against E. coli O104: H4. • In vitro studies revealed a non-β-lactam compound to inhibit the growth of E. coli O104: H4. • This non-β-lactam compound could be used as a lead compound for targeting beta-lactam strains. [ABSTRACT FROM AUTHOR]

This paper presents a modified half-sine-squared load model of the jumping impulses for a single person. The model is based on a database of 22,921 experimentally measured single jumping load cycles from 100 test subjects. Threedimensional motion capture technology in conjunction with force plates was employed in the experiment to record jumping loads. The variation range and probability distribution of the controlling parameters for the load model such as the impact factor, jumping frequency and contact ratio, are discussed using the experimental data. Correlation relationships between the three parameters are investigated. The contact ratio and jumping frequency are identified as independent model parameters, and an empirical frequency-dependent function is derived for the impact factor. The feasibility of the proposed load model is established by comparing the simulated load curves with measured ones, and by comparing the acceleration responses of a single-degree-of-freedom system to the simulated and measured jumping loads. The results show that a realistic individual jumping load can be generated by the proposed method. This can then be used to assess the dynamic response of assembly structures. [ABSTRACT FROM AUTHOR]

The correct affiliations are listed below: Affiliation 1: Department of Breast Center, The Fourth Hospital of Hebei Medical University, 169 Tianshan Street, Shijiazhuang, Hebei 050011, People's Republic of China Affiliation 2: Gland Surgery, Shijiazhuang People's Hospital, Shijiazhuang, People's Republic of China Furthermore, Affiliation 1 was omitted for Wenshan Zhang. Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-022-05486-3, published online 07 February 2022 In the original version of this Article, Affiliation 1 and 2 were not listed in the correct order. [Extracted from the article]

To address the problems of poor welding completeness and inefficient configuration for defective automotive body-in-white panels, we propose a method for detecting and configuring the welding completeness of automotive body-in-white panels based on digital twin (DT) and mixed reality (MR). The method uses DT to build an MR-oriented DT framework for the detections and configuration of body-in-white panel welding completeness. We propose a method to build a DT knowledge base for panels, a Yolov4-based welding completeness detection method, and a MR-based configuration method for the welding completeness in panels. Our team develop a panel welding completeness detection and configuration system to fully validate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Mounting evidence suggests that microbiota dysbiosis caused by antibiotic administration is a risk factor for cancer, but few research reports focus on the relationships between antibiotics and chemotherapy efficiency. We evaluated the influence of antibiotic administration on neoadjuvant therapy efficacy in patients with breast cancer (BC) in the present study. BC patients were stratified into two groups: antibiotic-treated and control based on antibiotic administration within 30 days after neoadjuvant therapy initiation. Disease-free survival (DFS) and overall survival (OS) were assessed using the Kaplan–Meier method, and the Cox proportional hazards model was used for multivariate analyses. The pathologic complete response rate of the control group was significantly higher than that of the antibiotic-treated group (29.09% vs. 10.20%, p = 0.017). Further univariate analysis with Kaplan–Meier calculations demonstrated that antibiotic administration was strongly linked with both reduced DFS (p = 0.04) at significant statistical levels and OS (p = 0.088) at borderline statistical levels. Antibiotic administration was identified as a significant independent prognostic factor for DFS [hazard ratio (HR) 3.026, 95%, confidence interval (CI) 1.314–6.969, p = 0.009] and OS (HR 2.836, 95% CI 1.016–7.858, p = 0.047) by Cox proportional hazards model analysis. Antibiotics that initiated reduced efficiency of chemotherapy were more noticeable in the HER2-positive subgroup for both DFS (HR 5.51, 95% CI 1.77–17.2, p = 0.003) and OS (HR 7.0395% CI 1.94–25.53, p = 0.003), as well as in the T3-4 subgroup for both DFS (HR 20.36, 95% CI 2.41–172.07, p = 0.006) and OS (HR 13.45, 95% CI 1.39–130.08, p = 0.025) by stratified analysis. Antibiotic administration might be associated with reduced efficacy of neoadjuvant therapy and poor prognosis in BC patients. As a preliminary study, our research made preparations for further understanding and large-scale analyses of the impact of antibiotics on the efficacy of neoadjuvant therapy. [ABSTRACT FROM AUTHOR]