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Background Rifampicin-resistant/multidrug-resistant tuberculosis (RR/MDR-TB) is featured by challenges in the treatment, low cure rate, and high infectivity. Fluoroquinolones (FQs), as the core drugs for the treatment of RR/MDR-TB, have a severe trend of resistance. Analyzing influencing factors for FQs can help to increase the cure rate of RR/MDR-TB and to control the occurrence of the pre-extensive drug resistance (pre-XDR) and extensive drug resistance. Objective To analyze the drug resistance of FQs in hospitalized patients with pulmonary tuberculosis and the influencing factors, and to construct and validate a Nomogram prediction model for the risk factors of drug resistance of FQs. Methods A total of 583 patients with pulmonary tuberculosis who were hospitalized in Guiyang Public Health Clinical Center from January 2021 to February 2022 and tested for drug sensitivity were retrospectively selected as study subjects. They were divided into the initial treatment group (296 patients) and the retreatment group (287 patients) according to the history of previous treatment. Moreover, they were divided into the FQs-resistant group (63 patients) and FQs-sensitive group (520 patients) according to their FQs-resistance status. The distribution of total resistance to 13 antituberculosis drugs in 583 patients was analyzed, and the baseline characteristics of patients in the FQs-resistant group and FQs-sensitive group were compared. After screening the characteristic variables using least absolute shrinkage and selection operator (LASSO) regression model, multivariate Logistic regression was performed to analyze the independent risk factors for the resistance of FQs. A Nomogram prediction model was constructed, and its performance was validated by calculating the area under the curve (AUC) of receiver operating characteristic (ROC), and plotting the calibration curve. Results Among 583 patients, 520 cases were sensitive to FQs and 63 cases were resistant (resistance rate of 10.81%). The resistance rate of FQs was secondary to the total resistance rate of first-line antituberculosis drugs, including the isoniazid (36.36%), rifampicin (32.76%), streptomycin (21.61%), and ethambutol (12.86%). The resistance rates of rifampicin, isoniazid, ethambutol, streptomycin, levofloxacin, moxifloxacin and rifampicin resistance (RR), multidrug resistance (MDR), and pre-XDR were significantly higher in patients of the retreatment group than those of the initial treatment group (P

Deep learning-based image compressive sensing has received extensive attention due to its powerful learning ability and fast processing speed.With the increase in the depth of convolutional neural networks,the existing image reconstruction methods using neural networks do not fully utilize the residual features in the network.In order to solve this problem,this paper proposes a compressed sensing attention neural network framework based on residual feature aggregation(RFA2CSNet)by jointly optimizing the sampling and inverse reconstruction processes.First,the block compressed sensing sampling sub-network and the initial reconstruction sub-network are constructed to adaptively learn the measurement matrix and generate the initial reconstruction image.Then the residual learning and spatial attention mechanisms are introduced to construct the residual feature aggregation attention reconstruction sub-network to make the residual feature more focused on the key spatial content,so as to further improve the reconstructed image quality.Experimental results show that the proposed network is superior to the existing image compressed sensing reconstruction algorithm in the case of comparable reconstruction time,and obtains better image compressive sensing reconstruction quality.Specifically,using 11 images for testing with a sampling rate of 0.10,the average peak signal-to-noise ratio increases by 0.34~6.18 dB compared with other deep learning-based methods.

Stress granules (SGs), formed by untranslated messenger ribonucleoproteins (mRNPs) during cellular stress in eukaryotes, have been linked to flavivirus interference without clear understanding. This study reveals the role of Zika virus (ZIKV) NS2B as a scaffold protein mediating interaction between protein phosphatase 1α (PP1α) and eukaryotic initiation factor 2α (eIF2α). This interaction promotes eIF2α dephosphorylation by PP1α, inhibiting SG formation. The NS2B-PP1α complex exhibits remarkable stability, resisting ubiquitin-induced degradation and amplifying eIF2α dephosphorylation, thus promoting ZIKV replication. In contrast, the NS2BV35A mutant, interacting exclusively with eIF2α, fails to inhibit SG formation, resulting in reduced viral replication and diminished impact on brain organoid growth. These findings reveal PP1α's dual role in ZIKV infection, inducing interferon production as an antiviral factor and suppressing SG formation as a viral promoter. Moreover, we found that NS2B also serves as a versatile mechanism employed by flaviviruses to counter host antiviral defenses, primarily by broadly inhibiting SG formation. This research advances our comprehension of the complex interplay in flavivirus-host interactions, offering potential for innovative therapeutic strategies against flavivirus infections. Author summary: Zika virus (ZIKV) belongs to vector-borne flaviviruses, associated with Guillain-Barré syndrome and neonatal microcephaly. Stress granules (SGs) which forms under stress in eukaryotic cells can interfere with viral replication. Although previous studies have indicated that ZIKV can interfere with SG formation, the precise molecular mechanism and function remain unclear. Exploration of the mechanisms by which ZIKV antagonizes SG formation may help to identify new antiviral approaches. Here, we found that ZIKV NS2B bridge PP1α and eIF2α to promote eIF2α dephosphorylation and SG inhibition. Meanwhile, Reciprocal inhibition of K48-linked ubiquitination stabilized NS2B and PP1α to further facilitate the dephosphorylation of eIF2α and the concurrent inhibition of SG formation. Conversely, we demonstrated that a mutant form of NS2B, NS2BV35A, which interacted solely with eIF2α and not PP1α, attenuated virus replication and mitigated neurotoxicity in brain organoid development. The NS2B-PP1α-eIF2α axis reveals a novel biological function of NS2B as a general mechanism for flavivirus evasion of host antiviral effects, providing new therapeutic strategies for antiviral study. [ABSTRACT FROM AUTHOR]

We disclose herein an electrochemical allylation of unactivated aldehydes and ketones with allylic alcohols. A wide variety of homoallylic alcohols can be obtained by treatment of aldehydes/ketones with allyl alcohols in a simple undivided cell at room temperature. In contrast to previous strategies using allyl organometallic reagents, allylsilicon, allylboron and allyl halides as the allylic precursors, the present method used allyl alcohols as effective surrogates, which makes it more practical and environmentally sustainable. [ABSTRACT FROM AUTHOR]