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Abstract Missions into Deep Space are planned this decade. Yet the health consequences of exposure to microgravity and galactic cosmic radiation (GCR) over years-long missions on indispensable visceral organs such as the kidney are largely unexplored. We performed biomolecular (epigenomic, transcriptomic, proteomic, epiproteomic, metabolomic, metagenomic), clinical chemistry (electrolytes, endocrinology, biochemistry) and morphometry (histology, 3D imaging, miRNA-ISH, tissue weights) analyses using samples and datasets available from 11 spaceflight-exposed mouse and 5 human, 1 simulated microgravity rat and 4 simulated GCR-exposed mouse missions. We found that spaceflight induces: 1) renal transporter dephosphorylation which may indicate astronauts’ increased risk of nephrolithiasis is in part a primary renal phenomenon rather than solely a secondary consequence of bone loss; 2) remodelling of the nephron that results in expansion of distal convoluted tubule size but loss of overall tubule density; 3) renal damage and dysfunction when exposed to a Mars roundtrip dose-equivalent of simulated GCR.

Abstract Age-related Macular Degeneration (AMD), a retinal disease that affects the macula, can be caused by aging abnormalities in number of different cells and tissues in the retina, retinal pigment epithelium, and choroid, leading to vision loss. An advanced form of AMD, called exudative or wet AMD, is characterized by the ingrowth of abnormal blood vessels beneath or into the macula itself. The diagnosis is confirmed by either fundus auto-fluorescence imaging or optical coherence tomography (OCT) supplemented by fluorescein angiography or OCT angiography without dye. Fluorescein angiography, the gold standard diagnostic procedure for AMD, involves invasive injections of fluorescent dye to highlight retinal vasculature. Meanwhile, patients can be exposed to life-threatening allergic reactions and other risks. This study proposes a scale-adaptive auto-encoder-based model integrated with a deep learning model that can detect AMD early by automatically analyzing the texture patterns in color fundus imaging and correlating them to the vasculature activity in the retina. Moreover, the proposed model can automatically distinguish between AMD grades assisting in early diagnosis and thus allowing for earlier treatment of the patient’s condition, slowing the disease and minimizing its severity. Our model features two main blocks, the first is an auto-encoder-based network for scale adaption, and the second is a convolutional neural network (CNN) classification network. Based on a conducted set of experiments, the proposed model achieves higher diagnostic accuracy compared to other models with accuracy, sensitivity, and specificity that reach 96.2%, 96.2%, and 99%, respectively.

Abstract Pre-clinical studies have shown that spinal cord epidural stimulation (scES) at the level of pelvic and pudendal nerve inputs/outputs (L5-S1) alters storage and/or emptying functions of both the bladder and bowel. The current mapping experiments were conducted to investigate scES efficacy at the level of hypogastric nerve inputs/outputs (T13-L2) in male and female rats under urethane anesthesia. As found with L5-S1 scES, T13-L2 scES at select frequencies and intensities of stimulation produced an increase in inter-contraction interval (ICI) in non-injured female rats but a short-latency void in chronic T9 transected rats, as well as reduced rectal activity in all groups. However, the detrusor pressure during the lengthened ICI (i.e., urinary hold) remained at a low pressure and was not elevated as seen with L5-S1 scES, an effect that’s critical for translation to the clinic as high fill pressures can damage the kidneys. Furthermore, T13-L2 scES was shown to stimulate voiding post-transection by increasing bladder activity while also directly inhibiting the external urethral sphincter, a pattern necessary to overcome detrusor-sphincter dyssynergia. Additionally, select scES parameters at T13-L2 also increased distal colon activity in all groups. Together, the current findings suggest that optimization of scES for bladder and bowel will likely require multiple electrode cohorts at different locations that target circuitries coordinating sympathetic, parasympathetic and somatic outputs.

Abstract Spinal cord epidural stimulation (scES) mapping at L5-S1 was performed to identify parameters for bladder and bowel inhibition and/or contraction. Using spinally intact and chronic transected rats of both sexes in acute urethane-anesthetized terminal preparations, scES was systematically applied using a modified Specify 5–6–5 (Medtronic) electrode during bladder filling/emptying cycles while recording bladder and colorectal pressures and external urethral and anal sphincter electromyography activity. The results indicate frequency-dependent effects on void volume, micturition, bowel peristalsis, and sphincter activity just above visualized movement threshold intensities that differed depending upon neurological intactness, with some sex-dependent differences. Thereafter, a custom-designed miniature 15-electrode array designed for greater selectivity was tested and exhibited the same frequency-dependent urinary effects over a much smaller surface area without any concurrent movements. Thus, select activation of autonomic nervous system circuitries with scES is a promising neuromodulation approach for expedient translation to individuals with SCI and potentially other neurologic disorders.

Early detection of thyroid nodules can greatly contribute to the prediction of cancer burdening and the steering of personalized management. We propose a novel multimodal MRI-based computer-aided diagnosis (CAD) system that differentiates malignant from benign thyroid nodules. The proposed CAD is based on a novel convolutional neural network (CNN)-based texture learning architecture. The main contribution of our system is three-fold. Firstly, our system is the first of its kind to combine T2-weighted MRI and apparent diffusion coefficient (ADC) maps using a CNN to model thyroid cancer. Secondly, it learns independent texture features for each input, giving it more advanced capabilities to simultaneously extract complex texture patterns from both modalities. Finally, the proposed system uses multiple channels for each input to combine multiple scans collected into the deep learning process using different values of the configurable diffusion gradient coefficient. Accordingly, the proposed system would enable the learning of more advanced radiomics with an additional advantage of visualizing the texture patterns after learning. We evaluated the proposed system using data collected from a cohort of 49 patients with pathologically proven thyroid nodules. The accuracy of the proposed system has also been compared against recent CNN models as well as multiple machine learning (ML) frameworks that use hand-crafted features. Our system achieved the highest performance among all compared methods with a diagnostic accuracy of 0.87, specificity of 0.97, and sensitivity of 0.69. The results suggest that texture features extracted using deep learning can contribute to the protocols of cancer diagnosis and treatment and can lead to the advancement of precision medicine.

A series of linear dipeptide derivatives (4–10) were prepared and evaluated as antimicrobial agents via the synthesis of N-(2-(2-hydrazinyl-2-oxoethylamino)-2-oxoethyl) nicotinamide (4). Compound 4 was reacted with 4-chlorobenzaldehyde or 4-hydroxybenzaldehyde, to give the hydrazones 5 and 6, respectively. On the other hand, Compound 4 was coupled with phenylisocyanate or methylisothiocyanate to give Compounds 7 and 8, respectively. The latter compounds (7 and 8) were coupled with chloroacetic acid to give oxazolidine (9) and thiazolidine (10), respectively. The newly synthesized dipeptide compounds were confirmed by means of their spectral data. The antimicrobial activity of the newly synthesized compounds 4–10 was evaluated by agar well diffusion, and they showed good activity. Compounds 4, 5, and 9 gave the most promising activity in this study. Most of the tested compounds possessed MIC values ranging from 50 to 500 µg/mL. Furthermore, docking studies were carried out on enoyl reductase from E. coli and cytochrome P450 14 α-sterol demethylase (Cyp51) from Candida albicans active sites. The MolDock scores of the seven tested compounds ranged between −117 and −171 and between −107 and −179, respectively.