Macrophages orchestrate elimination of Shigella from the intestinal#journal

Bacteria of the genus Shigella replicate in intestinal epithelial cells and cause shigellosis, a severe diarrheal disease that resolves spontaneously in most healthy individuals. During shigellosis, neutrophils are abundantly recruited to the gut and have long been thought to be central to Shigella control and pathogenesis. However, how shigellosis resolves remains poorly understood due to the longstanding lack of a tractable and physiological animal model. Here, using our newly developed Nlrc4–/–Casp11–/– mouse model of shigellosis, we unexpectedly find no major role for neutrophils in limiting Shigella or in disease pathogenesis. Instead, we uncover an essential role for macrophages in the host control of Shigella. Macrophages respond to Shigella via Toll-like receptors (TLRs) to produce IL-12, which then induces IFN-γ, a cytokine that is essential to control Shigella replication in intestinal epithelial cells. Collectively, our findings reshape our understanding of the innate immune response to Shigella.

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A case of chronic hyperplastic candidiasis #journal

Oral candidiasis is the most common opportunistic oral infection, typically presenting as easily scrapable, white mucosal plaques or papules known as pseudomembranous candidiasis. In contrast, chronic hyperplastic candidiasis (CHC), a rare variant occurring in approximately 0.04% to 1.61% of cases, presents as nonscrapable, adherent white plaques, at times referred to as candidal leukoplakia

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Fluorescence discrimination of pathogenic Bacteria #journal

The lack of rapid and precise microbial identification technologies, coupled with the insufficient sensitivity or time-consuming procedures of current microbiological detection methods, may hinder effective pathogen management in both clinical settings and food safety surveillance. This poses significant risks to public health. We fabricated a broad-spectrum fluorescent nanomaterial, fragmented crystalline mannose-conjugated lectin-modified amidoxime-functionalized covalent organic framework (FcMBL@afCOF), for the rapid and efficient discrimination of both clinical and foodborne pathogens. A strategy inspired by the classic black box theory was utilized to amplify the spectral differences; the undifferentiated bacteria were regarded as a black box, external environmental stress was applied as the input, and the fluorescent spectra of FcMBL@afCOF/bacteria exposed to the same stress were output. To systematically validate this methodology, ultrasound was investigated as a typical environmental stress.

the resultant fluorescent spectra were processed simply to discriminate bacteria. The bacterial identification platform based on FcMBL@afCOF and environmental stress-assisted black box strategy circumvents the cumbersome synthesis of multiple biosensor receptors and the requirement of complex manipulation/precision equipment, reduces costs, and features a fast response and simple processing without washing procedures. This work provides a facile tactic for establishing an adaptable COF-based bacterial biosensing platform, making a positive contribution to precise medicine and food security.

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Intelligent microfluidic device for multiplex detection and prompt warni...

Abstract

Introduction

The increasing incidence and co-infection rates of multiple respiratory diseases have emphasized the necessity for efficient and reliable multiplex diagnostic methods for respiratory pathogens.

Objective

This study aims to develop a multiplex diagnostic tool for monitoring and early warning of respiratory infections.

Methods

A portable, centrifugal and highly integrated microfluidic device based on real-time recombinase-aided amplification (RAA) assays capable of specifically identifying 15 common respiratory pathogens was developed. Its point-of-care application was validated using simulated swabs and sputum spiked with 15 pathogens. A total of 427 collected samples were employed to assess its clinical performance, in parallel with traditional extraction kits and RT-qPCR/qPCR assays. Additionally, the feasibility of its connected monitoring and early warning platform was validated across 22 scenarios in 8 cities of mainland China.

Results

This device successfully facilitated sample-to-answer diagnostics by automating nucleic acid extraction, real-time RAA, fluorescence detection and wireless data transmission. Compared with conventional methods, this device has obvious advantages in the turnaround time (30 min for swabs and 60 min for sputum) and the detectable targets/types in a single test. The lowest detection limits of this device were 0.1 TCID50/mL for viral targets and 10 CFU/mL for bacterial or fungal targets. This newly developed device has good versatility in detecting various types of pathogens (viruses, bacteria, and fungi) in clinical samples, achieving an AUC above 0.98 for all targets and an accuracy of 99.30% in the analysis of 345 swab and 82 sputum samples. Moreover, this device achieved seamless data interaction with the intelligent monitoring and early warning system across 22 scenarios, enabling the successful visualization of data statistics and early warning analyses for uploaded information.

Conclusion

This device provides an intelligent, portable, rapid, and sensitive platform for early diagnosis of multiple pathogens, particularly in resource-limited settings.

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Genetic evolution, phylodynamic and phylogeographic #journal

The growing incidence of H5Ny virus infection in humans and mammals causes an increasing public health concern. To date, H5Ny virus infection in humans and mammals has been reported in 46 countries around the world, and the infection scope is gradually expanding from Southeast Asia to Europe and from Europe to the Americas. Virus subtypes include H5N1, H5N2, H5N5, H5N6 and H5N8, among which H5N1 subtype accounts for more than 95.63% cases. Forty clades have been identified, of which clade 2.3.4.4b accounts for majority of H5Ny mammalian infection cases. From 1997–2021, the number of H5Ny mammalian infection cases was low, with a small peak in 2006, and a sharp rise after 2022. The main clades of H5Ny viruses were clade 0 and 1 in 1997–2004, and gradually shifted to clade 2.1.3.2, 2.1.3.2b, 2.2.1, 2.2.1.2, and 2.3.4 from 2005 to 2014, and gradually shifted to 2.3.4.4b, 2.3.4.4e and 2.3.4.4 h after 2015, among which clade 2.3.4.4b became the dominant clade. The H5Ny AIVs from 14 mammal species could be classified into 31 genotypes, including G1–G3, G6–G7, G13, G25–G27 and G31 in cats, G18–G23, G28–G29 and G31 in foxes, G2, G9–G10, G14–G16 and G24 in minks, G1–G2, G4–G5, G8 and G11 in tigers, G21–G22, G29 and G31 in skunks, and G31 in dairy cows. From 2021 to early 2024, there are two main migration patterns: intra-European spread and European spread to North America. The infection of H5Ny AIVs in mammals is hampered by host body temperature, receptor distribution, pH value, and other factors, including ANP32, TUFM, DDX17 and BDN3A3. Comprehensive measures should be taken to prevent and control of H5Ny AIVs infection in mammals, including surveillance, vaccination and biosafety control measures.

AIVs are naturally transmitted in birds, with waterfowl serving as their natural hosts.4 The inter-species infectivity of AIVs has been an important public health concern since their initial were discovered. They not only cause substantial economic losses to the global poultry industry but also have the potential to infect humans and other mammals.5, 6 The high variability and rapid evolution of AIVs enable viruses to continuously adapt to new host environments, leading to inter-species infections in humans and other mammals, posing a serious threat to public health.7 Currently, the World Health Organization (WHO) and other organizations have taken global surveillance measures to monitor human infection with H5Ny AIVs. The widespread prevalence of H5Ny virus in poultry poses a serious threat to public health.

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Computational intelligence of Bayesian regularization backpropagation #j...

Computational intelligence of Bayesian regularization backpropagation neural networks to study the thermo-bioconvection flow of hybrid-nanofluid with thermal Radiation: Biotechnological perspectives

This study aims to develop a deep neural network that utilizes Bayesian regularization to investigate the performance of gyrotactic and oxytactic microbes in hybrid nanofluid flow over a sheet, taking into account local thermal non-equilibrium effects and thermal radiation. Two different activation functions, namely radial basis and log-sigmoid utilized in the designed network. The model improves the efficiency of pollutant removal by optimizing the dynamics of gyrotactic and oxytactic microbes under local thermal non-equilibrium conditions. The enhanced microbial activity for the degradation of organic waste and the breakdown of pollutants are made easier by the hybrid nanofluid's improved thermal and physicochemical characteristics. 80 % of the data fixed for the training of the deep neural network and 20 % data employed for the testing purpose. The base fluid water is coupled with titanium dioxide  and iron oxide  nanoparticles to produce a hybrid nanofluid. The input dataset of the network generated using the bvp4c command. To examine how the various parameters on the suggested model varied, three distinct examples were created. Various statistical metrics are taken into consideration to assess the network's accuracy and precision.

This article goal is to design a deep neural network approach optimized with Bayesian regularization algorithm to scrutinize the performance of gyrotactic and Oxytactic microbes in hybrid nanofluid flow along a sheet with thermophoresis and heat radiation characteristics. The present study scrutinizes the properties of heat transport in the absenteeism of LTECs using a simple mathematical model. The consequences of the important factors are investigated and numerical solutions are produced by employing the shooting method. This is the analysis's goal.

• ❖
  The designed deep neural network contains of dual hidden layers with 20 and 30 hidden neurons in radial-basis and log-sigmoid hidden layers respectively.
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  To analyze the precision and accuracy of the deep network the statistical measures like regression, mean square error and error histogram.
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  To regulate how Oxytactic and gyrotactic microbes influence the HNF using LTNE condition.
• ❖
  To assess how the thermal radiation affects the thermal transport of the hybrid nanofluid using HCM.
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  To examine the influences of the thermophoretic parameter on SBLflow HNF.
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  To investigate the impact of MHD on the bioconvection flow deep neural network approach trained with Bayesian regularization algorithm.
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  To inspect the properties of inter face heat transmission parameter on solid and liquid phase TBL flow HNF using.

The contagion effects of the COVID-19 pandemic: Evidence from gold and c...

At the beginning of the 2020 global COVID-2019 pandemic, Chinese financial markets acted as the epicentre of both physical and financial contagion. Our results indicate that a number of characteristics expected during a “flight to safety” were present during the period analysed. The volatility relationship between the main Chinese stock markets and Bitcoin evolved significantly during this period of enormous financial stress. We provide a number of observations as to why this situation occurred. Such dynamic correlations during periods of stress present further evidence to cautiously support the validity of the development of this new financial product within mainstream portfolio design through the diversification benefits provided.We specifically investigate the contagion effects associated with the onset of the COVID-2019 pandemic between Chinese stock markets, identified as the epicentre of the first registered cases as outlined in the timetable presented in Table 1. We utilise these events to generate dummy variables through which we analyse the contagion effects centred in the price volatility of both the Shanghai and Shenzhen Stock Exchanges

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Transcriptomics of Marburg virus-infected primary proximal tubular cells...

Marburg virus, a member of the Filoviridae, is the causative agent of Marburg virus disease (MVD), a hemorrhagic fever with a case fatality rate of up to 90 %. Acute kidney injury is common in MVD and is associated with increased mortality, but its pathogenesis in MVD remains poorly understood. Interestingly, autopsies show the presence of viral proteins in different parts of the nephron, particularly in proximal tubular cells (PTC). These findings suggest a potential role for the virus in the development of MVD-related kidney injury. To shed light on this effect, we infected primary human PTC with Lake Victoria Marburg virus and conducted transcriptomic analysis at multiple time points. Unexpectedly, infection did not induce marked cytopathic effects in primary tubular cells at 20 and 40 h post infection. However, gene expression analysis revealed robust renal viral replication and dysregulation of genes essential for different cellular functions. The gene sets mainly downregulated in PTC were associated with the targets of the transcription factors MYC and E2F, DNA repair, the G2M checkpoint, as well as oxidative phosphorylation. Importantly, the downregulated factors comprise PGC-1α, a well-known factor in acute and chronic kidney injury. By contrast, the most highly upregulated gene sets were those related to the inflammatory response and cholesterol homeostasis. In conclusion, Marburg virus infects and replicates in human primary PTC and induces downregulation of processes known to be relevant for acute kidney injury as well as a strong inflammatory response.

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