Implications of siRNA Therapy in Bone Health: Silencing Communicates.

The global statistics of bone disorders, skeletal defects, and fractures are frightening. Several therapeutic strategies are being used to fix them; however, RNAi-based siRNA therapy is starting to prove to be a promising approach for the prevention of bone disorders because of its advanced capabilities to deliver siRNA or siRNA drug conjugate to the target tissue. Despite its 'bench-to-bedside' usefulness and approval by food and drug administration for five siRNA-based therapeutic medicines: Patisiran, Vutrisiran, Inclisiran, Lumasiran, and Givosiran, its use for the other diseases still remains to be resolved. By correcting the complications and complexities involved in siRNA delivery for its sustained release, better absorption, and toxicity-free activity, siRNA therapy can be harnessed as an experimental tool for the prevention of complex and undruggable diseases with a personalized medicine approach. The present review summarizes the findings of notable research to address the implications of siRNA in bone health for the restoration of bone mass, recovery of bone loss, and recuperation of bone fractures.

Stevens-johnson Syndrome and Toxic Epidermal Necrolysis: An Overview of Diagnosis, Therapy Options and Prognosis of Patients.

Both Stevens-johnson syndrome (SJS) and Toxic-epidermal necrolysis (TEN) are generally medication-induced pathological conditions that mostly affect the epidermis and mucus membranes. Nearly 1 to 2 patients per 1,000,000 population are affected annually with SJS and TEN, and sometimes these maladies can cause serious life-threatening events. The reported death rates for SJS range from 1 to 5%, and 25 to 35% for TEN. The mortality risk may even be higher among elderly patients, especially in those who are affected by a significant amount of epidermal detachment. More than 50% of TEN patients who survive the illness may experience long-term lower quality of life and lesser life expectancy. The clinical and histopathological conditions of SJS and TEN are characterized by mucocutaneous discomfort, haemorrhagic erosions, erythema, and occasionally severe epidermal separation that can turn into ulcerative patches and dermal necrosis. The relative difference between SJS and TEN is the degree of ulcerative skin detachment, making them two extremes of a spectrum of severe cutaneous adverse drug-induced reactions (cADRs). In the majority of cases, serious drug-related hypercreativities are considered the main cause of SJS & TEN; however, herpes simplex virus and Mycoplasma pneumoniae infections may also produce similar type clinical conditions. The aetiology of a lesser number of cases and their underlying causative factors remain unknown. Among the drugs with a 'greater likelihood' of causing TEN & SJS are carbamazepine (CBZ), trimethoprim-sulfamethoxazole, phenytoin, aminopenicillins, allopurinol, cephalosporins, sulphonamides, antibiotics, quinolones, phenobarbital, and NSAIDs of the oxicam variety. There is also a strong genetic link between the occurrence of SJS and IEN in the Han Chinese population. Such genetic association is based on the human leukocyte antigen (HLA-B*1502) and the co-administration of carbamazepine. The diagnosis of SJS is made mostly on the gross observations of clinical symptoms, and confirmed by the histopathological examination of dermal biopsies of the patients. The differential diagnoses consist of the exclusion of Pemphigus vulgaris, bullous pemphigoid, linear IgA dermatosis, paraneoplastic pemphigus, disseminated fixed bullous drug eruption, acute generalized exanthematous pustulosis (AGEP), and staphylococcal scalded skin syndrome (SSSS). The management of SJS & TEN is rather difficult and complicated, and there is sometimes a high risk of mortality in seriously inflicted patients. Urgent medical attention is needed for early diagnosis, estimation of the SCORTEN prognosis, identification and discontinuation of the causative agent as well as highdose injectable Ig therapeutic interventions along with specialized supportive care. Historical aspects, aetiology, mechanisms, and incidences of SJS and TEN are discussed. An update on the genetic occurrence of these medication-related hypersensitive ailments as well as different therapy options and management of patients is also provided.

Multi-Stage Classification of Retinal OCT Using Multi-Scale Ensemble Deep Architecture.

Accurate noninvasive diagnosis of retinal disorders is required for appropriate treatment or precision medicine. This work proposes a multi-stage classification network built on a multi-scale (pyramidal) feature ensemble architecture for retinal image classification using optical coherence tomography (OCT) images. First, a scale-adaptive neural network is developed to produce multi-scale inputs for feature extraction and ensemble learning. The larger input sizes yield more global information, while the smaller input sizes focus on local details. Then, a feature-rich pyramidal architecture is designed to extract multi-scale features as inputs using DenseNet as the backbone. The advantage of the hierarchical structure is that it allows the system to extract multi-scale, information-rich features for the accurate classification of retinal disorders. Evaluation on two public OCT datasets containing normal and abnormal retinas (e.g., diabetic macular edema (DME), choroidal neovascularization (CNV), age-related macular degeneration (AMD), and Drusen) and comparison against recent networks demonstrates the advantages of the proposed architecture's ability to produce feature-rich classification with average accuracy of 97.78%, 96.83%, and 94.26% for the first (binary) stage, second (three-class) stage, and all-at-once (four-class) classification, respectively, using cross-validation experiments using the first dataset. In the second dataset, our system showed an overall accuracy, sensitivity, and specificity of 99.69%, 99.71%, and 99.87%, respectively. Overall, the tangible advantages of the proposed network for enhanced feature learning might be used in various medical image classification tasks where scale-invariant features are crucial for precise diagnosis.

Therapeutic potential of flavonoids in the management of obesity-induced Alzheimer's disease: an overview of preclinical and clinical studies.

Obesity is a global epidemic that affects people of all ages, genders, and backgrounds. It can lead to a plethora of disorders, including diabetes mellitus, renal dysfunction, musculoskeletal problems, metabolic syndrome, cardiovascular, and neurodegenerative abnormalities. Obesity has also been linked to neurological diseases such as cognitive decline, dementia, and Alzheimer's disease (AD), caused by oxidative stress, pro-inflammatory cytokines, and the production of reactive oxygen free radicals (ROS). Secretion of insulin hormone is impaired in obese people, leading to hyperglycaemia and increased accumulation of amyloid-ß in the brain. Acetylcholine, a key neurotransmitter necessary for forming new neuronal connections in the brain, decreases in AD patients. To alleviate acetylcholine deficiency, researchers have proposed dietary interventions and adjuvant therapies that enhance the production of acetylcholine and assist in the management of AD patients. Such measures include dietary intervention with antioxidant and anti-inflammatory flavonoid-rich diets, which have been found to bind to tau receptors, reduce gliosis, and reduce neuroinflammatory markers in animal models. Furthermore, flavonoids like curcumin, resveratrol, epigallocatechin-3-gallate, morin, delphinidins, quercetin, luteolin, and oleocanthal have shown to cause significant reductions in interleukin-1ß, increase BDNF levels, stimulate hippocampal neurogenesis and synapse formation, and ultimately prevent the loss of neurons in the brain. Thus, flavonoid-rich nutraceuticals can be a potential cost-effective therapeutic option for treating obesity-induced AD, but further well-designed, randomized, and placebo-controlled clinical studies are needed to assess their optimal dosages, efficacy, and long-term safety of flavonoids in humans. The main objectives of this review are to underscore the therapeutic potential of different nutraceuticals containing flavonoids that can be added in the daily diet of AD patients to enhance acetylcholine and reduce neuronal inflammation in the brain.

Outpatient medications associated with protection from COVID-19 hospitalization.

The COVID-19 pandemic remains the pre-eminent global health problem, and yet after more than three years there is still no prophylactic agent against the disease aside from vaccines. The objective of this study was to evaluate whether pre-existing, outpatient medications approved by the US Food and Drug Administration (FDA) reduce the risk of hospitalization due to COVID-19. This was a retrospective cohort study of patients from across the United States infected with COVID-19 in the year 2020. The main outcome was adjusted odds of hospitalization for COVID-19 amongst those positive for the infection. Outcomes were adjusted for known risk factors for severe disease. 3,974,272 patients aged 18 or older with a diagnosis of COVID-19 in 2020 met our inclusion criteria and were included in the analysis. Mean age was 50.7 (SD 18). Of this group, 290,348 patients (7.3%) were hospitalized due to COVID-19, similar to the CDC's reported estimate (7.5%). Four drugs showed protective effects against COVID-19 hospitalization: rosuvastatin (aOR 0.91, p = 0.00000024), empagliflozin-metformin (aOR 0.69, p = 0.003), metformin (aOR 0.97, p = 0.017), and enoxaparin (aOR 0.88, p = 0.0048). Several pre-existing medications for outpatient use may reduce severity of disease and protect against COVID-19 hospitalization. Well-designed clinical trials are needed to assess the efficacy of these agents in a therapeutic or prophylactic setting.

Impact assessment of Intensified Malaria Control Project in transitioning a high malaria-endemic district to a low-endemic district: an epidemiological aspect.

Intensified Malaria Control Project (IMCP) was implemented in 2005 to control malaria in all North-Eastern and Odisha states of India. The present study aimed to investigate the impact of IMCP in reducing the malaria burden in Udalguri district, Assam state of North-East India. Malaria epidemiological data were obtained for IMCP intervention (Udalguri) and nonintervention district (West Singhbhumi, Jharkhand state). IMCP activities include introducing bi-valent rapid diagnostic kits (RDTs), Artemether-Lumefantrine drug in North-East India, long-lasting insecticidal nets (LLINs) distribution, and creating awareness programs about malaria in an intensified mode. The data revealed a significant decline in annual parasite incidence (API) from 14.94 (2005) to 2.61 (2018), -37% (95%CI: -57%, -19%, p = 001) after using LLINs in 2009 and -64% (95%CI: -116%, -14%, p = 013) after the introduction of RDTs in district Udalguri. Whereas control district showed a -28% (95%CI: -63%, 6.3%, p = 0.051) decrease in API using LLINs and a 10% (95%CI: -7.6%, 28%, p = 0.122) increase after the introduction of RDTs. Plasmodium falciparum (Pf) and P. vivax (Pv) were the major malarial parasites in Udalguri. Pv-malaria was much higher (71%) than Pf-malaria (29%) during the study period. An increasing trend of Pf cases was observed in Udalguri. Udalguri and Khoirabari BPHCs showed an overall reduction of 94% (95%CI: -143%, -45%, p = 0.001) and 84% (95%CI: -126%, -39%, p = 0.003), respectively; however, only a 10% (95%CI: -65%, -41%, p = 0.360) reduction in API was observed in Orang BPHC. An overall decrease in malaria indicates the effective implementation of vector and disease control strategies in the Udalguri district.

Predicting the Level of Respiratory Support in COVID-19 Patients Using Machine Learning.

In this paper, a machine learning-based system for the prediction of the required level of respiratory support in COVID-19 patients is proposed. The level of respiratory support is divided into three classes: class 0 which refers to minimal support, class 1 which refers to non-invasive support, and class 2 which refers to invasive support. A two-stage classification system is built. First, the classification between class 0 and others is performed. Then, the classification between class 1 and class 2 is performed. The system is built using a dataset collected retrospectively from 3491 patients admitted to tertiary care hospitals at the University of Louisville Medical Center. The use of the feature selection method based on analysis of variance is demonstrated in the paper. Furthermore, a dimensionality reduction method called principal component analysis is used. XGBoost classifier achieves the best classification accuracy (84%) in the first stage. It also achieved optimal performance in the second stage, with a classification accuracy of 83%.

Moderate Rainfall and High Humidity During the Monsoon Season, Negligence in Using Malaria Protection Methods and High Proportion of Mild Symptomatic Patients Were the Driving Forces for Upsurge of Malaria Cases in 2018 Among Tea Tribe Populations in Endemic Dolonibasti Health Sub-center, Udalguri District, Assam State, North-East India.

Malaria elimination is a global priority, which India has also adopted as a target. Despite the malaria control efforts like long-lasting insecticidal nets distribution, rounds of indoor residual spray, the introduction of bi-valent rapid diagnostic tests and artemisinin combination therapy, malaria remained consistent in Dolonibasti sub-center of Orang block primary health center (BPHC) under the district Udalguri, Assam state followed by abrupt rise in cases in 2018. Therefore, we aimed to investigate the factors driving the malaria transmission in the outbreak area of Dolonibasti sub-center. Malaria epidemiological data (2008-2018) of Udalguri district and Orang BPHC was collected. The annual (2011-2018) and monthly (2013-2018) malaria and meteorological data of Dolonibasti sub-center was collected. An entomological survey, Knowledge, Attitude and Practices study among malaria cases (n = 120) from Dolonibasti was conducted. In 2018, 26.1 % (2136/ 8188) of the population of Dolonibasti were found to be malaria positive, of which 55% were adults (n = 1176). Majority of cases were from tea tribe populations (90%), either asymptomatic or with fever only, 67.5 % (81/120) had experienced malaria infection during past years. The outbreak was characterized by a strong increase in cases in June 2018, high proportion of slide falciparum rate of 26.1% (other years average, 15.8%) and high proportion of P. falciparum of 81.2 % (other years average, 84.3%). Anopheles minimus s.l. was the major vector with 28.6% positivity and high larval density in paddy fields/ drainage area. Annual relative humidity was associated with rise in malaria cases, annual parasite incidence (rs = 0.69, 90%CI; p = 0.06) and slide positivity rate (rs = 0.83, 95%CI; p = 0.01). Older people were less educated (rs = -0.66; p < 0.001), had lesser knowledge about malaria cause (rs = -0.42; χ2=21.80; p < 0.001) and prevention (rs = -0.18; p = 0.04). Malaria control practices were followed by those having knowledge about cause of malaria (rs = 0.36; χ2 = 13.50; p < 0.001) and prevention (rs = 0.40; χ2 = 17.71; p < 0.001). Altogether, 84.6% (44/52) of the respondents did not use protective measures. We described a sudden increase in malaria incidence in a rural, predominantly tea tribe population group with high illiteracy rate and ignorance on protective measures against malaria. More efforts that are concerted needed to educate the community about malaria control practices.

Virus Dynamics and Decay in Evaporating Human Saliva Droplets on Fomites.

The transmission of most respiratory pathogens, including SARS-CoV-2, occurs via virus-containing respiratory droplets, and thus, factors that affect virus viability in droplet residues on surfaces are of critical medical and public health importance. Relative humidity (RH) is known to play a role in virus survival, with a U-shaped relationship between RH and virus viability. The mechanisms affecting virus viability in droplet residues, however, are unclear. This study examines the structure and evaporation dynamics of virus-containing saliva droplets on fomites and their impact on virus viability using four model viruses: vesicular stomatitis virus, herpes simplex virus 1, Newcastle disease virus, and coronavirus HCoV-OC43. The results support the hypothesis that the direct contact of antiviral proteins and virions within the "coffee ring" region of the droplet residue gives rise to the observed U-shaped relationship between virus viability and RH. Viruses survive much better at low and high RH, and their viability is substantially reduced at intermediate RH. A phenomenological theory explaining this phenomenon and a quantitative model analyzing and correlating the experimentally measured virus survivability are developed on the basis of the observations. The mechanisms by which RH affects virus viability are explored. At intermediate RH, antiviral proteins have optimal influence on virions because of their largest contact time and overlap area, which leads to the lowest level of virus activity.

Cardiovascular Biomarkers: Lessons of the Past and Prospects for the Future.

Cardiovascular diseases (CVDs) are a major healthcare burden on the population worldwide. Early detection of this disease is important in prevention and treatment to minimise morbidity and mortality. Biomarkers are a critical tool to either diagnose, screen, or provide prognostic information for pathological conditions. This review discusses the historical cardiac biomarkers used to detect these conditions, discussing their application and their limitations. Identification of new biomarkers have since replaced these and are now in use in routine clinical practice, but still do not detect all disease. Future cardiac biomarkers are showing promise in early studies, but further studies are required to show their value in improving detection of CVD above the current biomarkers. Additionally, the analytical platforms that would allow them to be adopted in healthcare are yet to be established. There is also the need to identify whether these biomarkers can be used for diagnostic, prognostic, or screening purposes, which will impact their implementation in routine clinical practice.

The Role of Different Retinal Imaging Modalities in Predicting Progression of Diabetic Retinopathy: A Survey.

Diabetic retinopathy (DR) is a devastating condition caused by progressive changes in the retinal microvasculature. It is a leading cause of retinal blindness in people with diabetes. Long periods of uncontrolled blood sugar levels result in endothelial damage, leading to macular edema, altered retinal permeability, retinal ischemia, and neovascularization. In order to facilitate rapid screening and diagnosing, as well as grading of DR, different retinal modalities are utilized. Typically, a computer-aided diagnostic system (CAD) uses retinal images to aid the ophthalmologists in the diagnosis process. These CAD systems use a combination of machine learning (ML) models (e.g., deep learning (DL) approaches) to speed up the diagnosis and grading of DR. In this way, this survey provides a comprehensive overview of different imaging modalities used with ML/DL approaches in the DR diagnosis process. The four imaging modalities that we focused on are fluorescein angiography, fundus photographs, optical coherence tomography (OCT), and OCT angiography (OCTA). In addition, we discuss limitations of the literature that utilizes such modalities for DR diagnosis. In addition, we introduce research gaps and provide suggested solutions for the researchers to resolve. Lastly, we provide a thorough discussion about the challenges and future directions of the current state-of-the-art DL/ML approaches. We also elaborate on how integrating different imaging modalities with the clinical information and demographic data will lead to promising results for the scientists when diagnosing and grading DR. As a result of this article's comparative analysis and discussion, it remains necessary to use DL methods over existing ML models to detect DR in multiple modalities.

A Systematic Review of the Bioactive Components, Nutritional Qualities and Potential Therapeutic Applications of Donkey Milk.

In addition to providing individualized, specific, and ample nutritional compounds, donkey milk (DM) offers immunological modulation during health and disease. Recently, DM has attracted major interest in preparing infant formulas due to its similarity to human milk in terms of high protein and lactose content and low-fat concentration. The antimicrobial, anti-inflammation, antioxidant, and hypo-allergenicity properties of DM in human infants are well-documented. The purpose of this review is to summarize the knowledge of studies done in characterizing the composition of DM, including bioactive macronutrient levels influenced by the lactation status. The manufacture of DM-based food products and promising therapeutic applications in humans will also be discussed. The beneficial health effects of DM have been extensively studied as a valuable alternative source to breast milk. DM has proven to be a suitable nutrient to relieve milk-related allergies in human infants as opposed to cow's milk. Factors that influence the levels of macronutrients in DM include lactation status, processing, and manufacturing techniques. A wide variety of dairy products have been prepared using DM, such as cheese, ice cream, milk powder, novel functional fermented beverages, and milk powder for infant formulas. The bioactive macromolecules of DM exhibit antibacterial, antiviral, and antifungal effects as well as hypo-allergenicity, anti-inflammation, and antioxidant properties.

Pharmacokinetics and toxicity profiling of 4-(methylthio)butyl isothiocyanate with special reference to pre-clinical safety assessment studies.

4-(methylthio)butyl isothiocyanate (4-MTBITC) also called erucin is abundantly present in the seeds of Eruca sativa plant closely related to cruciferous vegetables rich in isothiocyanates. We have previously reported the molecular targets of 4-MTBITC, but no acute, subacute and subchronic toxicity studies have been carried out to evaluate its safety. The non-everted gut sac method was used to study intestinal absorption and it revealed the highest absorption of 4-MTBITC in the jejunum. Dose-dependent pharmacokinetic parameters were observed in rats given 10, 20, and 40 mg/kg oral doses of 4-MTBITC. At the highest dose of 40 mg/kg, Cmax was 437.33 µg/ml and Tmax was 30 min, suggesting quick absorption and delayed elimination with elimination constant, 0.0036 ± 0.0002min-1. In a 14 days toxicity study, the mean LD50 of 4-MTBITC was 500 mg/kg body weight. After 28 and 90 days of treatment with 4-MTBITC (2.5, 10, 40 mg/kg/day), significant increases were observed in SGOT, cholesterol, and antioxidant enzymes. The levels of glycine, alanine and lysine were markedly increased in the liver tissue, thereby indicating that the liver was the target organ of 4-MTBITC induced toxicity in female animals. The histopathological examination of liver, kidney, and lung tissues revealed little focal necrosis, apoptosis, and reduction in the levels of amino acids involved in cellular metabolic pathways, indicating the anti-proliferative potential of 4-MTBITC against rapidly growing cells.

NUCB2/Nesfatin-1 Reduces Obesogenic Diet Induced Inflammation in Mice Subcutaneous White Adipose Tissue.

BACKGROUND: Excess adipose tissue accumulation and obesity are characterised by chronic, low-grade, systemic inflammation. Nestfatin-1 is a neuropeptide derived from the precursor protein nucleobindin-2 (NUCB2), which was initially reported to exert anorexigenic effects. The present study aimed to investigate the effects of an obesogenic diet (OD; high-fat, high-sugar) in NUCB2 knockout (KO) mice and of nesfatin-1 treatment in LPS-stimulated 3T3-L1 preadipocytes. METHODS: Subcutaneous white adipose tissue (Sc-WAT) samples from wild type (WT) and NUCB2 KO mice that were fed a normal diet (ND), or the OD for 12 weeks were used for RNA and protein extraction, as well as immunohistochemistry. 3T3-L1 cells were treated with 100 nM nesfatin-1 during differentiation and stimulated with 1 µg/mL LPS for measuring the expression and secretion of pro-inflammatory mediators by qPCR, western blotting, immunofluorescence, Bioplex, and ELISA. RESULTS: Following the OD, the mRNA, protein and cellular expression of pro-inflammatory mediators (Tnfα, Il-6, Il-1ß, Adgre1, Mcp1, TLR4, Hmbgb1 and NF-kB) significantly increased in the ScWAT of NUCB2 KO mice compared to ND controls. Adiponectin and Nrf2 expression significantly decreased in the ScWAT of OD-fed NUCB2 KO, without changes in the OD-fed WT mice. Furthermore, nesfatin-1 treatment in LPS-stimulated 3T3-L1 cells significantly reduced the expression and secretion of pro-inflammatory cytokines (Tnfα, Il-6, Il-1ß, Mcp1) and hmgb1. CONCLUSION: An obesogenic diet can induce significant inflammation in the ScWAT of NUCB2 KO mice, involving the HMGB1, NRF2 and NF-kB pathways, while nesfatin-1 reduces the pro-inflammatory response in LPS-stimulated 3T3-L1 cells. These findings provide a novel insight into the metabolic regulation of inflammation in WAT.

Insights into the Research Trends on Bovine Colostrum: Beneficial Health Perspectives with Special Reference to Manufacturing of Functional Foods and Feed Supplements.

Bovine colostrum (BC) is the initial mammary secretion after parturition, which is nature's bountiful source consisting of nutritional and bioactive components present in a highly concentrated low-volume format. All mammalian newborns require colostrum to enhance physiological processes such as lifelong immunity, gastrointestinal development, and resistance to microbial infections. The genetic, environmental, and processing methods can all have an impact on the biochemical contents of BC and its supplements. BC and its derivatives have been intensively researched for their potential use in functional foods, medicines, and animal feed. Evidence from clinical studies suggests that BC products are well-tolerated, nontoxic, and safe for human ingestion. Functional foods, feed, and pharmaceutical formulations based on bovine colostrum are playing noteworthy roles in the development of innovative products for promoting health and the prevention of chronic illnesses. This systematic review sheds light on recent research on (a) the effects of processing techniques on BC components, (b) emerging techniques used in the isolation and identification of novel components, (c) BC-based functional foods for human consumption and animal feed supplements, and (d) the role of BC in current drug delivery, as well as future recommendations.

Automated Diagnosis of Optical Coherence Tomography Angiography (OCTA) Based on Machine Learning Techniques.

Diabetic retinopathy (DR) refers to the ophthalmological complications of diabetes mellitus. It is primarily a disease of the retinal vasculature that can lead to vision loss. Optical coherence tomography angiography (OCTA) demonstrates the ability to detect the changes in the retinal vascular system, which can help in the early detection of DR. In this paper, we describe a novel framework that can detect DR from OCTA based on capturing the appearance and morphological markers of the retinal vascular system. This new framework consists of the following main steps: (1) extracting retinal vascular system from OCTA images based on using joint Markov-Gibbs Random Field (MGRF) model to model the appearance of OCTA images and (2) estimating the distance map inside the extracted vascular system to be used as imaging markers that describe the morphology of the retinal vascular (RV) system. The OCTA images, extracted vascular system, and the RV-estimated distance map is then composed into a three-dimensional matrix to be used as an input to a convolutional neural network (CNN). The main motivation for using this data representation is that it combines the low-level data as well as high-level processed data to allow the CNN to capture significant features to increase its ability to distinguish DR from the normal retina. This has been applied on multi-scale levels to include the original full dimension images as well as sub-images extracted from the original OCTA images. The proposed approach was tested on in-vivo data using about 91 patients, which were qualitatively graded by retinal experts. In addition, it was quantitatively validated using datasets based on three metrics: sensitivity, specificity, and overall accuracy. Results showed the capability of the proposed approach, outperforming the current deep learning as well as features-based detecting DR approaches.

A Novel Computer-Aided Diagnostic System for Early Detection of Diabetic Retinopathy Using 3D-OCT Higher-Order Spatial Appearance Model.

Early diagnosis of diabetic retinopathy (DR) is of critical importance to suppress severe damage to the retina and/or vision loss. In this study, an optical coherence tomography (OCT)-based computer-aided diagnosis (CAD) method is proposed to detect DR early using structural 3D retinal scans. This system uses prior shape knowledge to automatically segment all retinal layers of the 3D-OCT scans using an adaptive, appearance-based method. After the segmentation step, novel texture features are extracted from the segmented layers of the OCT B-scans volume for DR diagnosis. For every layer, Markov-Gibbs random field (MGRF) model is used to extract the 2nd-order reflectivity. In order to represent the extracted image-derived features, we employ cumulative distribution function (CDF) descriptors. For layer-wise classification in 3D volume, using the extracted Gibbs energy feature, an artificial neural network (ANN) is fed the extracted feature for every layer. Finally, the classification outputs for all twelve layers are fused using a majority voting schema for global subject diagnosis. A cohort of 188 3D-OCT subjects are used for system evaluation using different k-fold validation techniques and different validation metrics. Accuracy of 90.56%, 93.11%, and 96.88% are achieved using 4-, 5-, and 10-fold cross-validation, respectively. Additional comparison with deep learning networks, which represent the state-of-the-art, documented the promise of our system's ability to diagnose the DR early.

Long-Term Follow-Up of Outer Retinal Layers in Patients with Epiretinal Membranes.

PURPOSE: This study aimed to investigate the long-term effect of observed epiretinal membranes on the outer retinal layers and visual acuity. METHODS: It is a retrospective observational study. Subjects with an epiretinal membrane and consecutive optical coherence tomography scans were followed for changes in visual acuity, central macular thickness, ellipsoid zone loss, and outer foveal thickness (OFT). RESULTS: The study consisted of 24 eyes of 22 patients, with a mean follow-up of 5 ± 1.6 years. The mean visual acuity was slightly worse at the last follow-up (0.22 ± 0.36 LogMAR [20/33] vs. 0.27 ± 0.36 LogMAR [20/36], p = 0.05). Ellipsoid zone loss was found in 37.5% of eyes. Vision loss was associated with initial size of ellipsoid disruption (p = 0.048) and age (p = 0.027). A decrease in OFT was associated with an initially larger zone of ellipsoid disruption (p = 0.006) and an initially thicker OFT (p = 0.011). An epiretinal membrane associated with vitreomacular adhesion within 1,000 µm of the foveal center at baseline was associated with ellipsoid zone loss (p = 0.012) but not with a change in visual acuity. CONCLUSIONS: Ellipsoid zone changes were common in this study and tended to enlarge over time. Epiretinal membranes associated with vitreomacular adhesion within 1,000 µm of the foveal center may be a risk factor for ellipsoid zone loss.

Recent Advances in the Local Drug Delivery Systems for Improvement of Anticancer Therapy

The conventional anticancer chemotherapies not only cause serious toxic effects but also produce resistance in tumor cells exposed to long-term therapy. Usually, the selective killing of metastasized cancer cells requires long-term therapy with higher drug doses because the cancer cells develop resistance due to the induction of poly-glycoproteins (P-gps) that act as a transmembrane efflux pump to transport drugs out of the cells. During the last few decades, scientists have been exploring new anticancer drug delivery systems such as microencapsulation, hydrogels, and nanotubes to improve bioavailability, reduce drug-dose requirement, decrease multiple drug resistance, and save normal cells as non-specific targets. Hopefully, the development of novel drug delivery vehicles (nanotubes, liposomes, supramolecules, hydrogels, and micelles) will assist in delivering drug molecules at the specific target site and reduce undesirable side effects of anticancer therapies in humans. Nanoparticles and lipid formulations are also designed to deliver a small drug payload at the desired tumor cell sites for their anticancer actions. This review will focus on the recent advances in drug delivery systems and their application in treating different cancer types in humans.

Demystifying therapeutic potential of medicinal plants against chikungunya virus.

Viral infections are posing a great threat to humanity for the last few years. Among these, Chikungunya which is a mosquito-borne viral infection has produced enormous epidemics around the world after been rebounded. Although this infection shows a low mortality rate, patients suffer from fever, arthralgia, and maculopapular rashes, which reduce the quality of life for several weeks to years. The currently available treatments only provide symptomatic relief based on analgesics, antipyretics, and anti-inflammatory drugs which are nonspecific without satisfactory results. Medicinal plants are a widely accepted source of new molecules for the treatment of infectious diseases including viral infections. The scientific reports, primarily focusing on the anti-chikungunya activity of plant extracts, natural origin pure compounds, and their synthetic analog published from 2011 to 2021, were selected from PubMed, Google Scholar, and Scopus by using related keywords like anti-chikungunya plants, natural antivirals for Chikungunya. The present review decodes scientific reports on medicinal plants against chikungunya virus (CHIKV) infection and demystifies the potential phytoconstituents which reveals that the screening of flavonoids containing plants and phytochemicals showing efficacy against other arbovirus infections, may prove as a potential lead for drug development against CHIKV. The present article also outlines pathogenesis, clinical aspects, molecular virology, and diagnostic approaches of CHIKV infection.