One carbon metabolism and its implication in health and immune functions.

One carbon (1C) metabolism is critical for cellular viability and physiological homeostasis. Starting from its crucial involvement in purine biosynthesis to posttranslational modification of proteins, 1C metabolism contributes significantly to the development and cellular differentiation through methionine and folate cycles that are pivotal for cellular function. Genetic polymorphisms of several genes of these pathways are implicated in disease pathogenesis and drug metabolism. Metabolic products of 1C metabolism have significant roles in epigenetic modifications through DNA and histone protein methylation. Homocysteine is a product that has clinical significance in the diagnosis and prognosis of several critical illnesses, including chronic immune diseases and cancers. Regulation of the function and differentiation of immune cells, including T-cells, B-cells, macrophages, and so forth, are directly influenced by 1C metabolism and thus have direct implications in several immune disease biology. Recent research on therapeutic approaches is targeting nuclear, cytoplasmic, and mitochondrial 1C metabolism to manage and treat metabolic (i.e., type 2 diabetes), neurodegenerative (i.e., Alzheimer's disease), or immune (i.e., rheumatoid arthritis) diseases. 1C metabolism is being explored for therapeutic intervention as a common determinant for a spectrum of immune and metabolic diseases. Identifying the association or correlation between essential metabolic products of this pathway and disease onset or prognosis would further facilitate the clinical monitoring of diseases.

Targeting mitochondria in the regulation of neurodegenerative diseases: A comprehensive review.

Mitochondria are one of the essential cellular organelles. Apart from being considered as the powerhouse of the cell, mitochondria have been widely known to regulate redox reaction, inflammation, cell survival, cell death, metabolism, etc., and are implicated in the progression of numerous disease conditions including neurodegenerative diseases. Since brain is an energy-demanding organ, mitochondria and their functions are important for maintaining normal brain homeostasis. Alterations in mitochondrial gene expression, mutations, and epigenetic modification contribute to inflammation and neurodegeneration. Dysregulation of reactive oxygen species production by mitochondria and aggregation of proteins in neurons leads to alteration in mitochondria functions which further causes neuronal death and progression of neurodegeneration. Pharmacological studies have prioritized mitochondria as a possible drug target in the regulation of neurodegenerative diseases. Therefore, the present review article has been intended to provide a comprehensive understanding of mitochondrial role in the development and progression of neurodegenerative diseases mainly Alzheimer's, Parkinson's, multiple sclerosis, and amyotrophic lateral sclerosis followed by possible intervention and future treatment strategies to combat mitochondrial-mediated neurodegeneration.

Epidemiology and genetics of granulomatosis with polyangiitis.

Granulomatosis with polyangiitis (GPA) previously known as Wegener's granulomatosis (WG) is a rare rheumatic disease affecting subjects of all ages. Prevalence and incidence of this systemic disease greatly varies across different ethnic groups. GPA is the commonest form of ANCA-associated vasculitis (AAV) with PR3 positivity among 85-95% of the cases. Scientific investigations of GPA is warranted because its severity, clinical heterogeneity, fast disease manifestation and end-organ damage. The etiology of GPA is still unknown. Major role of HLA and non-HLA genes with immune functions were identified, however, very limited replication was observed in different ethnic populations. In the present review, we have discussed the updates on the global epidemiology and contribution of HLA and major non-HLA genes/loci in GPA. We have also highlighted the cross disease association of GPA associated genes that may help in better disease management and predictive medicine. We proposed that high-resolution HLA typing and development of genetic risk model would help in early disease diagnosis and understanding the prognosis.

Polarimetric imaging in backscattering for the structural characterization of strongly scattering birefringent fibrous media.

Interpreting the polarimetric data from fiber-like macromolecules constitutive of tissue can be difficult due to strong scattering. In this study, we probed the superficial layers of fibrous tissue models (membranes consisting of nanofibers) displaying varying degrees of alignment. To better understand the manifestation of membranes' degree of alignment in polarimetry, we analyzed the spatial variations of the backscattered light's Stokes vectors as a function of the orientation of the probing beam's linear polarization. The degree of linear polarization reflects the uniaxially birefringent behavior of the membranes. The rotational (a-)symmetry of the backscattered light's degree of linear polarization provides a measure of the membranes' degree of alignment.

Interpretation of backscattering polarimetric images recorded from multiply scattering systems: a study on colloidal suspensions.

Extracting a system's physical features from polarimetric experiments constitutes a challenging task, especially in the presence of multiple scattering. This can be attributed to the difficulty in interpreting the polarimetric measurements. In this study, we demonstrate that polarimetric images recorded in the backscattering geometry can be interpreted by analyzing the spatial variations of the backscattered light's Stokes vectors and using symmetry/geometry arguments. To illustrate the applicability of our method, we examine experimental and simulation data collected by probing colloidal suspensions. We present an analytical model based on the coherency matrix and the geometric phase to describe the polarimetric behavior of the probed samples.

Multi-type skin diseases classification using OP-DNN based feature extraction approach.

In the current world, the disorders occurring in dermatological images are among the foremost widespread diseases. Despite being common, its identification is tremendously hard because of the complexities like skin tone and color variation due to the presence of hair regions. Therefore the type of skin disease prediction is not accurately achieved in many pieces of research. To deal with mentioned concerns, a novel optimal probability-based deep neural network is proposed to assist medical professionals in appropriately diagnosing the type of skin disease. Initially, the input dataset is fed into the pre-processing stage, which helps to remove unwanted contents in the image. Afterward, features extracted for all the pre-processed images are subjected to the proposed Optimal Probability-Based Deep Neural Network (OP-DNN) for the training process. This classification algorithm classifies incoming clinical images as different skin diseases with the help of probability values. While learning OP-DNN, it is essential to determine the optimal weight values for reducing the training error. For optimizing weight in OP-DNN structure, an optimization approach is implemented in this research. For that, whale optimization is utilized because it works faster than other methods. The proposed multi-type skin disease prediction model is implemented in MatLab software and achieved 95% of accuracy, 0.97 of specificity, and 0.91 of sensitivity. This exposes the superiority of the proposed multi-type skin disease prediction model using an effective OP-DNN based feature extraction approach to attain a high accuracy rate and also it predict several kinds of skin disease than the previous models, which can protect the patients survives as well as can assist the physicians in making a decision certainly.

Mucous patch of secondary syphilis masquerading as leukokeratosis: An atypical presentation.

Syphilis is known to inflict human being since long. It has varied clinical presentations. Atypical presentations are not uncommon and may jeopardize the clinical acumen of experienced clinician. Here, we are reporting a case of syphilis presenting as a sole manifestation in oral cavity.

Backscattering polarimetric imaging of the human brain to determine the orientation and degree of alignment of nerve fiber bundles.

The nerve fiber bundles constitutive of the white matter in the brain are organized in such a way that they exhibit a certain degree of structural anisotropy and birefringence. The birefringence exhibited by such aligned fibrous tissue is known to be extremely sensitive to small pathological alterations. Indeed, highly aligned anisotropic fibers exhibit higher birefringence than structures with weaker alignment and anisotropy, such as cancerous tissue. In this study, we performed experiments on thick coronal slices of a healthy human brain to explore the possibility of (i) measuring, with a polarimetric microscope the birefringence exhibited by the white matter and (ii) relating the measured birefringence to the fiber orientation and the degree of alignment. This is done by analyzing the spatial distribution of the degree of polarization of the backscattered light and its variation with the polarization state of the probing beam. We demonstrate that polarimetry can be used to reliably distinguish between white and gray matter, which might help to intraoperatively delineate unstructured tumorous tissue and well organized healthy brain tissue. In addition, we show that our technique is able to sensitively reconstruct the local mean nerve fiber orientation in the brain, which can help to guide tumor resections by identifying vital nerve fiber trajectories thereby improving the outcome of the brain surgery.

Association of Social Distancing, Population Density, and Temperature With the Instantaneous Reproduction Number of SARS-CoV-2 in Counties Across the United States.

Importance: Local variation in the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across the United States has not been well studied. Objective: To examine the association of county-level factors with variation in the SARS-CoV-2 reproduction number over time. Design, Setting, and Participants: This cohort study included 211 counties, representing state capitals and cities with at least 100 000 residents and including 178 892 208 US residents, in 46 states and the District of Columbia between February 25, 2020, and April 23, 2020. Exposures: Social distancing, measured by percentage change in visits to nonessential businesses; population density; and daily wet-bulb temperatures. Main Outcomes and Measures: Instantaneous reproduction number (Rt), or cases generated by each incident case at a given time, estimated from daily case incidence data. Results: The 211 counties contained 178 892 208 of 326 289 971 US residents (54.8%). Median (interquartile range) population density was 1022.7 (471.2-1846.0) people per square mile. The mean (SD) peak reduction in visits to nonessential business between April 6 and April 19, as the country was sheltering in place, was 68.7% (7.9%). Median (interquartile range) daily wet-bulb temperatures were 7.5 (3.8-12.8) °C. Median (interquartile range) case incidence and fatality rates per 100 000 people were approximately 10 times higher for the top decile of densely populated counties (1185.2 [313.2-1891.2] cases; 43.7 [10.4-106.7] deaths) than for counties in the lowest density quartile (121.4 [87.8-175.4] cases; 4.2 [1.9-8.0] deaths). Mean (SD) Rt in the first 2 weeks was 5.7 (2.5) in the top decile compared with 3.1 (1.2) in the lowest quartile. In multivariable analysis, a 50% decrease in visits to nonessential businesses was associated with a 45% decrease in Rt (95% CI, 43%-49%). From a relative Rt at 0 °C of 2.13 (95% CI, 1.89-2.40), relative Rt decreased to a minimum as temperatures warmed to 11 °C, increased between 11 and 20 °C (1.61; 95% CI, 1.42-1.84) and then declined again at temperatures greater than 20 °C. With a 70% reduction in visits to nonessential business, 202 counties (95.7%) were estimated to fall below a threshold Rt of 1.0, including 17 of 21 counties (81.0%) in the top density decile and 52 of 53 counties (98.1%) in the lowest density quartile.2. Conclusions and Relevance: In this cohort study, social distancing, lower population density, and temperate weather were associated with a decreased Rt for SARS-CoV-2 in counties across the United States. These associations could inform selective public policy planning in communities during the coronavirus disease 2019 pandemic.

FAST MRI breast screening revisited.

INTRODUCTION: Screening for breast cancer in high-risk women takes about 40 minutes to acquire an MRI scan and is time-intensive to report. There is recent interest in the performance of an abbreviated MRI protocol (FAST) in the screening setting. FAST scans have a reported negative predictive value of 99.8%. This study evaluates the false positive rates (FPR) and recall rates for FAST scans as compared to full diagnostic studies (FD). METHODS: A database of all screening breast MRI scans performed at our institution between 30 June 2013 and 1 July 2014 (n = 591) was created by one of the researchers, who did not subsequently analyse the MRI scans. The T1W and first post-contrast and subtracted images from each of these scans (FAST protocol) were assessed by experienced breast MRI radiologists, blinded to the final diagnosis. The findings were then compared with the FD result. RESULTS: The recall rates were 6.6% for FAST scans and 5.8% for FD scans. FPR rates were 4.7% and 3.9% respectively. There is no statistically significant difference in the recall rates or FPR of FAST scans in comparison with full diagnostic studies. CONCLUSIONS: Given the absence of statistically significant difference in the FPR and recall rates in comparison with FD, FAST scans can replace FD for screening of breast cancer.

Oral delivery of therapeutic proteins and peptides: a review on recent developments.

Advent of recombinant technology in protein synthesis has given birth to a new range of biopharmaceuticals. These therapeutic peptides and proteins are now emerging as an imperative part of various treatment protocols especially in the cancer therapeutics. Despite extensive research efforts, oral delivery of therapeutic peptide or protein is still a challenge for pharmaceutical industries and researchers. Number of factors including high proteolytic activity and low pH conditions of gastrointestinal tract act as major barriers in the successful delivery of intact protein/peptide to the targeted site. Low permeability of protein/peptide across the intestinal barrier is also a factor adding to the low bioavailability. Therefore, because of the short circulatory half-life exhibited by peptides in vivo, they need to be administered frequently resulting in increased cost of treatment and low patient compliance. Nano-carrier-based delivery presents an appropriate choice of drug carriers owing to their property to protect proteins from degradation by the low pH conditions in stomach or by the proteolytic enzymes in the gastrointestinal tract. This review focuses on recent aspects and patents on oral delivery of therapeutic proteins and peptides with special emphasis on nano-carrier-based approach.