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Developments in deep learning techniques have led to significant advances in automated abnormality detection in radiological images and paved the way for their potential use in computer-aided diagnosis (CAD) systems. However, the development of CAD systems for pulmonary tuberculosis (TB) diagnosis is hampered by the lack of training data that is of good visual and diagnostic quality, of sufficient size, variety, and, where relevant, containing fine region annotations. This study presents a collection of annotations/segmentations of pulmonary radiological manifestations that are consistent with TB in the publicly available and widely used Shenzhen chest X-ray (CXR) dataset made available by the U.S. National Library of Medicine and obtained via a research collaboration with No. 3. People's Hospital Shenzhen, China. The goal of releasing these annotations is to advance the state-of-the-art for image segmentation methods toward improving the performance of fine-grained segmentation of TB-consistent findings in digital Chest X-ray images. The annotation collection comprises the following: 1) annotation files in JSON (JavaScript Object Notation) format that indicate locations and shapes of 19 lung pattern abnormalities for 336 TB patients; 2) mask files saved in PNG format for each abnormality per TB patient; 3) a CSV (comma-separated values) file that summarizes lung abnormality types and numbers per TB patient. To the best of our knowledge, this is the first collection of pixel-level annotations of TB-consistent findings in CXRs. Dataset: https://data.lhncbc.nlm.nih.gov/public/Tuberculosis-Chest-X-ray-Datasets/Shenzhen-Hospital-CXR-Set/Annotations/index.html.

Paclitaxel-induced peripheral neuropathy is a condition of nerve degeneration induced by chemotherapy, which afflicts up to 70% of treated patients. Therapeutic interventions are unavailable due to an incomplete understanding of the underlying mechanisms. We previously discovered that major physiological changes in the skin underlie paclitaxel-induced peripheral neuropathy in zebrafish and rodents. The precise molecular mechanisms are only incompletely understood. For instance, paclitaxel induces the upregulation of MMP-13, which, when inhibited, prevents axon degeneration. To better understand other gene regulatory changes induced by paclitaxel, we induced peripheral neuropathy in mice following intraperitoneal injection either with vehicle or paclitaxel every other day four times total. Skin and dorsal root ganglion neurons were collected based on distinct behavioural responses categorised as "pain onset" (d4), "maximal pain" (d7), "beginning of pain resolution" (d11), and "recovery phase" (d23) for comparative longitudinal RNA sequencing. The generated datasets validate previous discoveries and reveal additional gene expression changes that warrant further validation with the goal to aid in the development of drugs that prevent or reverse paclitaxel-induced peripheral neuropathy.

Malaria is a serious infectious disease that leads to massive casualties globally. Myanmar is a key battleground for the global fight against malaria because it is where the emergence of drug-resistant malaria parasites has been documented. Controlling the spread of malaria in Myanmar thus carries global significance, because the failure to do so would lead to devastating consequences in vast areas where malaria is prevalent in tropical/subtropical regions around the world. Thanks to its wide and consistent spatial coverage, remote sensing has become increasingly used in the public health domain. Specifically, remote sensing-based land cover/land use (LCLU) maps present a powerful tool that provides critical information on population distribution and on the potential human-vector interactions interfaces on a large spatial scale. Here, we present a 30-meter LCLU map that was created specifically for the malaria control and eradication efforts in Myanmar. This bottom-up approach can be modified and customized to other vector-borne infectious diseases in Myanmar or other Southeastern Asian countries.