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Tuberculous meningitis remains highly lethal. In this trial, an intensified regimen of levofloxacin and higher-dose rifampin added to standard therapy was compared with standard antituberculosis therapy alone. The intensified regimen did not result in a higher survival rate. Early treatment with antituberculosis chemotherapy and adjunctive treatment with glucocorticoids reduce the rate of death and disability from tuberculous meningitis, but the disease still kills or disables almost half the patients with the condition. 1 , 2 The current guidelines recommend treatment with four antituberculosis drugs for at least the first 2 months of therapy, followed by treatment with two drugs (rifampin and isoniazid) for an additional 7 to 10 months. 3 , 4 However, these recommendations are based on data from pulmonary tuberculosis and do not take into account the differential ability of antituberculosis drugs to penetrate the brain. Rifampin is considered to . . .

Tuberculosis transmission continues to be a major public health challenge. In this cluster-randomized, controlled trial conducted in Vietnam, active community-wide screening for tuberculosis over 4 years is shown to decrease the prevalence of tuberculosis.

Most of the existing chest X-ray datasets include labels from a list of findings without specifying their locations on the radiographs. This limits the development of machine learning algorithms for the detection and localization of chest abnormalities. In this work, we describe a dataset of more than 100,000 chest X-ray scans that were retrospectively collected from two major hospitals in Vietnam. Out of this raw data, we release 18,000 images that were manually annotated by a total of 17 experienced radiologists with 22 local labels of rectangles surrounding abnormalities and 6 global labels of suspected diseases. The released dataset is divided into a training set of 15,000 and a test set of 3,000. Each scan in the training set was independently labeled by 3 radiologists, while each scan in the test set was labeled by the consensus of 5 radiologists. We designed and built a labeling platform for DICOM images to facilitate these annotation procedures. All images are made publicly available in DICOM format along with the labels of both the training set and the test set. Measurement(s) diseases and abnormal findings from chest X-ray scans Technology Type(s) AI is used to detect diseases and abnormal findings Sample Characteristic - Location Vietnam

Purpose Circulating microRNAs (miRNAs) are potential diagnostic biomarkers for breast cancer (BC). The application of miRNA panels could improve the performance of screening tests. Here, we integrated bioinformatic tools and meta-analyses to select circulating miRNAs with high diagnostic accuracy and combined these markers to develop diagnostic panels for BC. Methods Analyses across databases were performed to identify potential BC-related circulating miRNAs. Next, a comprehensive meta-analysis was conducted for each miRNA following the PRISMA guidelines. An electronic and manual search for relevant literature was carried out by two reviewers through PubMed, ScienceDirect, Biomed Central, and Google Scholar. The quality of the included studies was assessed using the QUADAS-2, and the statistical analyses were performed using R software 4.1.1. Finally, the accurate biomarkers confirmed through meta-analyses were combined into diagnostic models for BC. Results Twenty-seven circulating miRNAs were identified as BC-related by bioinformatic tools. After screening, only 10 miRNAs presented in 45 studies were eligible for meta-analyses. By assessing pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio, 8 miRNAs (miR-21, miR-30b, miR-125b, miR-145, miR221 miR-222, and miR-335) were revealed as promising BC diagnostic biomarkers. Two panels constructed from these miRNAs showed excellent diagnostic accuracy for BC, with areas under the SROC curve of 0.917 and 0.944. Conclusion We identified 8 potential circulating miRNAs and 2 diagnostic models that are useful for diagnosing BC. However, the established miRNA panels have not been tested in any experimental studies and thus should be validated in large case–control studies for clinical use.

Nine isolates of Canine parvovirus (CPV) were obtained from Vietnamese dogs and cats. One canine isolate showed a unique antigenic property which indicates a novel antigenic variant of CPV-2b when examined with hemagglutination inhibition tests using our monoclonal antibodies, 21C3 and 19D7, which were recently developed. This isolate had an amino acid substitution of residue 426, Asp to Glu, and the same substitution has recently been found in CPV from Italian dogs. This study first showed that such substitution caused an antigenic difference demonstrable by monoclonal antibodies and that a similar evolution may have occurred in CPV in Vietnam.

Dioxin levels in the breast milk of mothers residing near a contaminated former airbase in Vietnam remain much higher than in unsprayed areas, suggesting high perinatal dioxin exposure for their infants. The present study investigated the association of perinatal dioxin exposure with autistic traits in 153 3-year-old children living in a contaminated area in Vietnam. The children were followed up from birth using the neurodevelopmental battery Bayley-III. The high-2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) exposed groups (⩾3.5 pg per g fat) showed significantly higher Autism Spectrum Rating Scale (ASRS) scores for both boys and girls than the mild-TCDD exposed groups, without differences in neurodevelopmental scores. In contrast, the high total dioxin-exposed group, indicated by polychlorinated dibenzo-p-dioxins/furans (PCDDs/Fs)—the toxic equivalents (TEQ) levels⩾17.9 pg-TEQ per g fat, had significantly lower neurodevelopmental scores than the mild-exposed group in boys, but there was no difference in the ASRS scores. The present study demonstrates a specific impact of perinatal TCDD on autistic traits in childhood, which is different from the neurotoxicity of total dioxins (PCDDs/Fs).

Transdermal delivery provides numerous benefits over conventional routes of administration. However, this strategy is generally limited to a few molecules with specific physicochemical properties (low molecular weight, high potency, and moderate lipophilicity) due to the barrier function of the stratum corneum layer. Researchers have developed several physical enhancement techniques to expand the applications of the transdermal field; among these, microneedle technology has recently emerged as a promising platform to deliver therapeutic agents of any size into and across the skin. Typically, hydrophilic biomolecules cannot penetrate the skin by passive diffusion. Microneedle insertion disrupts skin integrity and compromises its protective function, thus creating pathways (microchannels) for enhanced permeation of macromolecules. Microneedles not only improve stability but also enhance skin delivery of various biomolecules. Academic institutions and industrial companies have invested substantial resources in the development of microneedle systems for biopharmaceutical delivery. This review article summarizes the most recent research to provide a comprehensive discussion about microneedle-mediated delivery of macromolecules, covering various topics from the introduction of the skin, transdermal delivery, microneedles, and biopharmaceuticals (current status, conventional administration, and stability issues), to different microneedle types, clinical trials, safety and acceptability of microneedles, manufacturing and regulatory issues, and the future of microneedle technology.

We compared seven node vaccination strategies in twelve real-world complex networks. The node vaccination strategies are modeled as node removal on networks. We performed node vaccination strategies both removing nodes according to the initial network structure, i.e., non-adaptive approach, and performing partial node rank recalculation after node removal, i.e., semi-adaptive approach. To quantify the efficacy of each vaccination strategy, we used three epidemic spread indicators: the size of the largest connected component, the total number of infected at the end of the epidemic, and the maximum number of simultaneously infected individuals. We show that the best vaccination strategies in the non-adaptive and semi-adaptive approaches are different and that the best strategy also depends on the number of available vaccines. Furthermore, a partial recalculation of the node centrality increases the efficacy of the vaccination strategies by up to 80%.

Localization is a key-enabling technology for many applications in underwater wireless sensor networks. Traditional approaches for received signal strength (RSS)-based localization often require uniform distribution for anchor nodes and suffer from poor estimates according to unpredictable and uncontrollable noise conditions. In this paper, we establish an RSS-based localization scheme to determine the location of an unknown normal sensor from a certain measurement set of potential anchor nodes. First, we present a practical path loss model for wireless communication in underwater acoustic environments, where anchor nodes are deployed in a random circumstance. For a given area of interest, the RSS data collection is performed dynamically, where the measurement noises and the correlation among them are taken into account. For a pair of transmitter and receiver, we approximate the geometry distance between them according to a linear regression model. Thus, we can obtain a quick access for the range information, while keeping the error, the communication head and the response time low. We also present a method to correct noises in the distance estimate. Simulation results demonstrate that our localization scheme achieves a better performance for certain scenario settings. The successful localization probability can be up to 90%, where the anchor rate is fixed at 10%.

Background Klebsiella pneumoniae is a leading cause of bloodstream infection (BSI). Strains producing extended-spectrum beta-lactamases (ESBLs) or carbapenemases are considered global priority pathogens for which new treatment and prevention strategies are urgently required, due to severely limited therapeutic options. South and Southeast Asia are major hubs for antimicrobial-resistant (AMR) K. pneumoniae and also for the characteristically antimicrobial-sensitive, community-acquired “hypervirulent” strains. The emergence of hypervirulent AMR strains and lack of data on exopolysaccharide diversity pose a challenge for K. pneumoniae BSI control strategies worldwide. Methods We conducted a retrospective genomic epidemiology study of 365 BSI K. pneumoniae from seven major healthcare facilities across South and Southeast Asia, extracting clinically relevant information (AMR, virulence, K and O antigen loci) using Kleborate , a K. pneumoniae -specific genomic typing tool. Results K. pneumoniae BSI isolates were highly diverse, comprising 120 multi-locus sequence types (STs) and 63 K-loci. ESBL and carbapenemase gene frequencies were 47% and 17%, respectively. The aerobactin synthesis locus ( iuc ), associated with hypervirulence, was detected in 28% of isolates. Importantly, 7% of isolates harboured iuc plus ESBL and/or carbapenemase genes. The latter represent genotypic AMR-virulence convergence, which is generally considered a rare phenomenon but was particularly common among South Asian BSI (17%). Of greatest concern, we identified seven novel plasmids carrying both iuc and AMR genes, raising the prospect of co-transfer of these phenotypes among K. pneumoniae . Conclusions K. pneumoniae BSI in South and Southeast Asia are caused by different STs from those predominating in other regions, and with higher frequency of acquired virulence determinants. K. pneumoniae carrying both iuc and AMR genes were also detected at higher rates than have been reported elsewhere. The study demonstrates how genomics-based surveillance—reporting full molecular profiles including STs, AMR, virulence and serotype locus information—can help standardise comparisons between sites and identify regional differences in pathogen populations.