Antimicrobial Activity of Lactobacillus Species Against Carbapenem-Resistant Enterobacteriaceae

ObjectiveThis study aims to identify suitable lactobacilli that have anti-carbapenem-resistant Enterobacteriaceae (CRE) activity with in vitro tolerance to pepsin and bile salts.MethodsFifty-seven Lactobacillus spp. strains encompassing nine species were collected for investigation. Their viabilities in the presence of pepsin and bile salts were tested using tolerance tests. Their anti-CRE effects were assessed by agar well diffusion and broth microdilution assay, as well as time-kill test.ResultsOf the 57 Lactobacillus isolates collected, 31 had a less than 2-log reduction in their viability in both pepsin and bile salt tolerance tests. Of these 31 isolates, 5 (LUC0180, LUC0219, LYC0289, LYC0413, and LYC1031) displayed the greatest anti-CRE activity with a CRE zone of inhibition greater than 15 mm in agar well diffusion assays. The minimal inhibitory percentages of supernatants from these five strains against CREs ranged from 10 to 30%. With the exception of LUC0180, which had a minimal bactericidal percentage ≥ 40%, the bactericidal percentage of all the strains ranged from 20 to 40%. The inhibitory effect of the cell-free culture supernatants from these Lactobacillus strains did not change after heating but was abolished as the pH changed to 7.0. After a 24-h incubation, five of the Lactobacillus strains at a concentration of 108 CFU/ml totally inhibited the growth of carbapenem-resistant Escherichia coli (CRE316) and Klebsiella pneumoniae (CRE632). After a 48-h incubation, the growth of CRE316 was completely inhibited under each concentration of lactobacilli based on time-kill test. Furthermore, when the concentration of lactobacilli was at 108 CFU/ml, the decline in pH was faster than at other concentrations.ConclusionSome Lactobacillus strains exhibit anti-CRE activity, which suggests potential applications for controlling or preventing CRE colonization or infection

CSR and Organizational Attractiveness: The Impacts of Crisis and Crisis Response

This study explores whether different sources of CSR information (i.e., the organization itself vs. the third party) and CSR reputation (i.e., leading vs. backward) affect job applicants’ attraction to organizations. This study demonstrates the interaction effects of sources of CSR information and CSR reputation on organizational attractiveness and contributes to the literature by identifying the impact of crisis and crisis management strategies of the organization on its organizational attractiveness. From a Situational Crisis Communication Theory (SCCT), we examined the impacts of the crisis on organizations and what the crisis response strategies (i.e., excusing, apology, and scapegoating) organizations applied influence their organizational attractiveness. A fictitious food company was created for the experimental study. In total, 345 undergraduate business students at a university in central Taiwan were randomly assigned to 13 groups in different experimental settings. ANOVA and paired-sample t-tests were used to test the hypothesis. We found that (1) significant impacts made by the interaction effects of CSR reputations and the sources of CSR information of organizational attractiveness; (2) crisis events decreased organizational attraction dramatically regardless of the interaction of the sources of CSR information and CSR reputations; and (3) crisis management strategies effectively reduced the damages of crises on organizational attractiveness

Artificial Intelligence in Kidney Disease: A Comprehensive Study and Directions for Future Research

Artificial intelligence (AI) has emerged as a promising tool in the field of healthcare, with an increasing number of research articles evaluating its applications in the domain of kidney disease. To comprehend the evolving landscape of AI research in kidney disease, a bibliometric analysis is essential. The purposes of this study are to systematically analyze and quantify the scientific output, research trends, and collaborative networks in the application of AI to kidney disease. This study collected AI-related articles published between 2012 and 20 November 2023 from the Web of Science. Descriptive analyses of research trends in the application of AI in kidney disease were used to determine the growth rate of publications by authors, journals, institutions, and countries. Visualization network maps of country collaborations and author-provided keyword co-occurrences were generated to show the hotspots and research trends in AI research on kidney disease. The initial search yielded 673 articles, of which 631 were included in the analyses. Our findings reveal a noteworthy exponential growth trend in the annual publications of AI applications in kidney disease. Nephrology Dialysis Transplantation emerged as the leading publisher, accounting for 4.12% (26 out of 631 papers), followed by the American Journal of Transplantation at 3.01% (19/631) and Scientific Reports at 2.69% (17/631). The primary contributors were predominantly from the United States (n = 164, 25.99%), followed by China (n = 156, 24.72%) and India (n = 62, 9.83%). In terms of institutions, Mayo Clinic led with 27 contributions (4.27%), while Harvard University (n = 19, 3.01%) and Sun Yat-Sen University (n = 16, 2.53%) secured the second and third positions, respectively. This study summarized AI research trends in the field of kidney disease through statistical analysis and network visualization. The findings show that the field of AI in kidney disease is dynamic and rapidly progressing and provides valuable information for recognizing emerging patterns, technological shifts, and interdisciplinary collaborations that contribute to the advancement of knowledge in this critical domain

A Comparison of the Sensing Behavior for Pt-Mo/C-, Pt-Zr/C-, Pt-Fe-Ir/C-, and Pt/C-Modified Glassy Carbon Electrodes for the Oxidation of Ascorbic Acid and Dopamine

This study compares the sensing performance for platinum-molybdenum-, platinum-zirconium-, platinum-iron-iridium-, and platinum-modified electrodes in terms of the amperometric detection of ascorbic acid (AA) and dopamine (DA). The Pt, Pt-Mo, Pt-Zr, and Pt-Fe-Ir electrocatalysts are fabricated by chemical reduction on a carbon black support (XC-72) and are further modified on a glassy carbon electrode (GCE) as sensing electrodes. The Pt-Mo/C/GCE exhibits better electrocatalytic activity toward AA and DA than the Pt/C/GCE, Pt-Zr/C/GCE, and Pt-Fe-Ir/C/GCE. The Pt-Mo/C/GCE exhibits a sensitivity of 31.29 µA mM−1 to AA at 0.3 V vs. Ag/AgCl and a sensitivity of 72.24 µA mM−1 to DA at 0.6 V vs. Ag/AgCl and is reproducible and stable. This electrode has a respective limit of detection of 7.69 and 6.14 µM for AA and DA. Sucrose, citric acid, tartaric acid, and uric acid do not interfere with AA and DA detection. The diffusion coefficient and kinetic parameters, such as the catalytic rate constant and the heterogeneous rate constant for AA and DA, are determined using electrochemical approaches

In Silico Prediction of Skin Permeability Using a Two-QSAR Approach

Topical and transdermal drug delivery is an effective, safe, and preferred route of drug administration. As such, skin permeability is one of the critical parameters that should be taken into consideration in the process of drug discovery and development. The ex vivo human skin model is considered as the best surrogate to evaluate in vivo skin permeability. This investigation adopted a novel two-QSAR scheme by collectively incorporating machine learning-based hierarchical support vector regression (HSVR) and classical partial least square (PLS) to predict the skin permeability coefficient and to uncover the intrinsic permeation mechanism, respectively, based on ex vivo excised human skin permeability data compiled from the literature. The derived HSVR model functioned better than PLS as represented by the predictive performance in the training set, test set, and outlier set in addition to various statistical estimations. HSVR also delivered consistent performance upon the application of a mock test, which purposely mimicked the real challenges. PLS, contrarily, uncovered the interpretable relevance between selected descriptors and skin permeability. Thus, the synergy between interpretable PLS and predictive HSVR models can be of great use for facilitating drug discovery and development by predicting skin permeability

Cisplatin-Induced Giant Cells Formation Is Involved in Chemoresistance of Melanoma Cells

Melanoma is notoriously resistant to current cancer therapy. However, the chemoresistance mechanism of melanoma remains unclear. The present study unveiled that chemotherapy drug cisplatin induced the formation of giant cells, which exhibited enlargement in cell diameter and nucleus in mice and human melanoma cells. Giant cells were positive with melanoma maker S100 and cancer stem cell markers including ABCB5 and CD133 in vitro and in vivo. Moreover, giant cells retained the mitotic ability with expression of proliferation marker Ki-67 and exhibited multiple drug resistance to doxorubicin and actinomycin D. The mitochondria genesis/activities and cellular ATP level were significantly elevated in giant cells, implicating the demand for energy supply. Application of metabolic blockers such as sodium azide or 2-deoxy glucose abolished the cisplatin-induced giant cells formation and expression of cancer stemness markers. The present study unveils a novel chemoresistance mechanism of melanoma cells via size alteration and the anti-neoplastic strategy by targeting giant cells