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The rapid advancements in machine learning, graphics processing technologies and the availability of medical imaging data have led to a rapid increase in the use of deep learning models in the medical domain. This was exacerbated by the rapid advancements in convolutional neural network (CNN) based architectures, which were adopted by the medical imaging community to assist clinicians in disease diagnosis. Since the grand success of AlexNet in 2012, CNNs have been increasingly used in medical image analysis to improve the efficiency of human clinicians. In recent years, three-dimensional (3D) CNNs have been employed for the analysis of medical images. In this paper, we trace the history of how the 3D CNN was developed from its machine learning roots, we provide a brief mathematical description of 3D CNN and provide the preprocessing steps required for medical images before feeding them to 3D CNNs. We review the significant research in the field of 3D medical imaging analysis using 3D CNNs (and its variants) in different medical areas such as classification, segmentation, detection and localization. We conclude by discussing the challenges associated with the use of 3D CNNs in the medical imaging domain (and the use of deep learning models in general) and possible future trends in the field.

Intracranial hemorrhage is a medical emergency that requires urgent diagnosis and immediate treatment to improve patient outcome. Machine learning algorithms can be used to perform medical image classification and assist clinicians in diagnosing radiological scans. In this paper, we apply 3-dimensional convolutional neural networks (3D CNN) to classify computed tomography (CT) brain scans into normal scans (N) and abnormal scans containing subarachnoid hemorrhage (SAH), intraparenchymal hemorrhage (IPH), acute subdural hemorrhage (ASDH) and brain polytrauma hemorrhage (BPH). The dataset used consists of 399 volumetric CT brain images representing approximately 12,000 images from the National Neuroscience Institute, Singapore. We used a 3D CNN to perform both 2-class (normal versus a specific abnormal class) and 4-class classification (between normal, SAH, IPH, ASDH). We apply image thresholding at the image pre-processing step, that improves 3D CNN classification accuracy and performance by accentuating the pixel intensities that contribute most to feature discrimination. For 2-class classification, the F1 scores for various pairs of medical diagnoses ranged from 0.706 to 0.902 without thresholding. With thresholding implemented, the F1 scores improved and ranged from 0.919 to 0.952. Our results are comparable to, and in some cases, exceed the results published in other work applying 3D CNN to CT or magnetic resonance imaging (MRI) brain scan classification. This work represents a direct application of a 3D CNN to a real hospital scenario involving a medically emergent CT brain diagnosis.

Defective lysosomal acidification contributes to virtually all lysosomal storage disorders (LSDs) and to common neurodegenerative diseases like Alzheimer’s and Parkinson’s. Despite its fundamental importance, the mechanism(s) underlying this defect remains unclear. The v-ATPase, a multisubunit protein complex composed of cytosolic V1-sector and lysosomal membrane-anchored V0-sector, regulates lysosomal acidification. Mutations in the CLN1 gene, encoding PPT1, cause a devastating neurodegenerative LSD, INCL. Here we report that in Cln1 −/− mice, which mimic INCL, reduced v-ATPase activity correlates with elevated lysosomal pH. Moreover, v-ATPase subunit a1 of the V0 sector (V0a1) requires palmitoylation for interacting with adaptor protein-2 (AP-2) and AP-3, respectively, for trafficking to the lysosomal membrane. Notably, treatment of Cln1 −/− mice with a thioesterase (Ppt1)-mimetic, NtBuHA, ameliorated this defect. Our findings reveal an unanticipated role of Cln1 in regulating lysosomal targeting of V0a1 and suggest that varying factors adversely affecting v-ATPase function dysregulate lysosomal acidification in other LSDs and common neurodegenerative diseases. Lysosomal acidification defects have been implicated in various neurodegenerative disorders. Bagh et al . show that the V0a1 subunit of v-ATPase requires palmitoylation for correct sorting and trafficking to the lysosome membrane, and that such a process is impaired in a mouse model of a devastating neurodegenerative lysosomal storage disease, INCL.

Dendritic cells (DCs) have been implicated in the pathogenesis of psoriasis but the roles for specific DC subsets are not well defined. Here we show that DCs are required for psoriasis-like changes in mouse skin induced by the local injection of IL-23. However, Flt3L-dependent DCs and resident Langerhans cells are dispensable for the inflammation. In epidermis and dermis, the critical DCs are TNF-producing and IL-1β-producing monocyte-derived DCs, including a population of inflammatory Langerhans cells. Depleting Ly6C hi blood monocytes reduces DC accumulation and the skin changes induced either by injecting IL-23 or by application of the TLR7 agonist imiquimod. Moreover, we find that IL-23-induced inflammation requires expression of CCR6 by DCs or their precursors, and that CCR6 mediates monocyte trafficking into inflamed skin. Collectively, our results imply that monocyte-derived cells are critical contributors to psoriasis through production of inflammatory cytokines that augment the activation of skin T cells. Imiquimod exacerbates IL-23-induced skin inflammation and models psoriasis in mice. Here the authors show that this pathology is not dependent on resident dendritic cells, but on CCR6-induced immigration of monocyte-derived cells.

Enzymes from haloalkaliphilic microorganisms have recently focused attention on their potential and suitability in various applications. In this study, the growth and production of extracellular amylases in the marine actinomycetes, using kitchen waste as the raw starch source, have been investigated. Actinobacteria were isolated from the seawater of the Kachhighadi Coast near Dwarika, Gujarat. Seven Actinobacterial isolates of pre-monsoon, monsoon, and post-monsoon seasons belonging to different strains of Nocardiopsis genera were screened and selected for amylase production. The amylase production was initially assessed on the solid media supplemented with the extracts of different fruits and vegetable peels as a substrate by agar plate assay. The strains Kh-2(13), Kh-2(1), and Kh-3(12) produced maximum amylase with potato peel as a substrate, while no significant differences were found with the media containing other peels. Nevertheless, all strains produced amylases at a significant level with other raw substrates as well. For the optimization of the growth and enzyme production, the selected two isolates Kh-2(13) and Kh-3(12) of the monsoon and winter seasons were cultivated in a liquid medium under the submerged fermentation conditions, with potato peel as a substrate. In both organisms, the optimum amylase production was observed in the stationary phase of growth. For amylase production, the effect of different physical and chemical parameters was evaluated. The optimum growth and amylase production was achieved in 2% inoculum size, at pH 8.0, 28℃, and 5% salt concentration. On the basis of the amylase production index (API) (a ratio of the amylase units and cell growth), both isolates produced significant amylase with the only extract of potato peels, without any other supplements. The trends further indicated that while additional complex sources, such as yeast extract and peptone can enhance the cell growth of the actinobacteria, the amylase production remained unaltered. The study projects the significance of waste raw materials for the production of enzymes in extremophilic microorganisms.

Marine sediments are complex ecosystems where structures and functions constantly change due to natural and anthropogenic influences. In this investigation, a comprehensive and comparative analysis of the bacterial communities and their functional potential of the pristine and polluted marine sediments were carried out using MiSeq. The phylum Proteobacteria was dominant in all study sites. Other phyla were Actinobacteria , Bacteroidetes , Planctomycetes , Acidobacteria , Chloroflexi , Nitrospirae , Cyanobacteria , Verrucomicrobia , Tenericutes , and Chlorobi . Interestingly, about 50% of genera belong to the unclassified categories. The key genera were identified as Acinetobacter , Bacillus , Pseudomona , Idiomarina , Thalassospira , and Marinobacter , Halomonas , Planctomyces , Psychrobacter , and Vogesella. PICRUSt analysis revealed that major functions are associated with the metabolism category. Additionally, metabolism related to amino acids, carbohydrates, energy generation, xenobiotics degradation, nitrogen, sulfate, and methane were prominent. Similarly, the predicted metabolisms by COG and KEGG were observed in the microbial communities of the marine sediments. To date, a comprehensive description of the microbial life with metabolic potential in these study sites has not been investigated. This study therefore significantly adds to our understanding of the microbiome and its functional attributes of marine sediments.

Nanotechnology utilizes engineered materials and devices which function with biological systems at the molecular level and could transform the management of neurodegenerative diseases (NDs) by provoking, reacting to, and intermingling with target sites to stimulate physiological responses while minimizing side effects. Blood-brain barrier (BBB) protects the brain from harmful agents, and transporting drugs across the BBB is a major challenge for diagnosis, targeting, and treatment of NDs. The BBB provides severe limitations for diagnosis and treatment of Alzheimer's disease (AD), Parkinson's disease (PD), and various other neurological diseases. Conventional drug delivery systems generally fail to cross the BBB, thus are inefficient in treatment. Although gradual development through research is ensuring the progress of nanotheranostic approaches from animal to human modeling, aspects of translational applicability and safety are a key concern. This demands a deep understanding of the interaction of body systems with nanomaterials. There are various plant-based nanobioactive compounds which are reported to have applicability in the diagnosis and treatment of these NDs. This review article provides an overview of applications of nanotheranostics in AD and PD. The review also discusses nano-enabled drug delivery systems and their current and potential applications for the treatment of various NDs.

Human Th17/type 17 cells express the chemokine receptor CCR6, but the functions of CCR6 and other chemokine receptors in human type 17 Th cell extravasation have not been fully delineated. Here we show that human peripheral blood CD4 + CCR6 + T cells co-expressing CCR2 have a pathogenic Th17 signature, can produce inflammatory cytokines without T cell receptor activation, and show enhanced expression of pathogenicity-associated and activation-associated genes in the cerebrospinal fluid of patients with multiple sclerosis as compared to controls. In flow chambers with activated endothelial cell (EC) monolayers, CD4 + CCR6 + CCR2 + T cells are efficient at transendothelial migration (TEM). Ligands for CCR5, CCR6 and CXCR3 localize to EC surfaces and mediate only arrest, whereas CCR2 ligands fail to bind well to ECs and mediate only TEM. Conversely, expressing a chimeric CCR2 ligand engineered to bind glycosaminoglycans on ECs results in CCR2-mediated arrest but blocks TEM induction. Our results from human pathogenic-like type 17 cells thus suggest that T cell migration arrest requires chemokine bound to EC surfaces, whereas TEM requires a transendothelial chemokine gradient. Human pathogenic-like Th17 cells express the chemokine receptor CCR6, but how CCR6, together with other chemokine receptors, modulate Th17 functions is still unclear. Here the authors show that CCR2 is coexpressed with CCR6 on these cells, and specifically mediates transendothelial migration, while CCR6 and other chemokine receptors induce T cell arrest on activated endothelial cells.

Lenacapavir (LEN) is a highly potent and long-acting antiretroviral that works by a unique mechanism of targeting the viral capsid protein. The inhibitor is used in combination with other antiretrovirals to treat multi-drug-resistant HIV-1 infection in heavily treatment-experienced adults. Furthermore, LEN is in clinical trials for preexposure prophylaxis (PrEP) with interim results indicating 100% efficacy to prevent HIV-1 infections. However, one notable shortcoming is a relatively low barrier of viral resistance to LEN. Clinical trials and cell culture experiments identified emergent resistance mutations near the inhibitor binding site on capsid. The M66I variant was the most prevalent capsid substitution identified in patients receiving LEN to treat multi-drug-resistant HIV-1 infections. The studies described here elucidate the underlying mechanism by which the M66I substitution confers a marked resistance to the inhibitor. Furthermore, our structural findings will aid future efforts to develop the next generation of capsid inhibitors with enhanced barriers to resistance.

Clinical observations and mouse models have suggested that inflammation can be pro-tumorigenic. Since chemokines are critical in leukocyte trafficking, we hypothesized that chemokines play essential roles in inflammation-associated cancers. Screening for 37 chemokines in prostate cancer cell lines and xenografts revealed CXCL16, the ligand for the receptor CXCR6, as the most consistently expressed chemokine. Immunohistochemistry and/or immunofluorescence and confocal imaging of 121 human prostate specimens showed that CXCL16 and CXCR6 were co-expressed, both on prostate cancer cells and adjacent T cells. Expression levels of CXCL16 and CXCR6 on cancer cells correlated with poor prognostic features including high-stage and high-grade, and expression also correlated with post-inflammatory changes in the cancer stroma as revealed by loss of alpha-smooth muscle actin. Moreover, CXCL16 enhanced the growth of CXCR6-expressing cancer and primary CD4 T cells. We studied expression of CXCL16 in an additional 461 specimens covering 12 tumor types, and found that CXCL16 was expressed in multiple human cancers associated with inflammation. Our study is the first to describe the expression of CXCL16/CXCR6 on both cancer cells and adjacent T cells in humans, and to demonstrate correlations between CXCL16 and CXCR6 vs. poor both prognostic features and reactive changes in cancer stoma. Taken together, our data suggest that CXCL16 and CXCR6 may mark cancers arising in an inflammatory milieu and mediate pro-tumorigenic effects of inflammation through direct effects on cancer cell growth and by inducing the migration and proliferation of tumor-associated leukocytes.