Search

Nowadays, Fiber-reinforced Polymer Composites (FRPCs) are extensively utilized due to their remarkable properties such as high stiffness, excellent strength to weight ratio, resistance to wear, corrosion etc. Earlier, the FRPCs are prepared through synthetic fibers in order to attain high strength in conjunction with high elastic modulus. However, with the increasing economic and environmental factors regarding the accumulation of plastic waste, the development of natural and hybrid (combination of any two) fibers were started. The mechanical properties of FRPCs are largely determined by the way loads are transferred between the matrix and fibers, or by the strength of the bond between the fiber-matrix interfaces. Additionally, these factors play a significant role in determining the overall performance of FRPCs. Therefore, this review discusses the recent advancements in enhancing the interaction between fiber and matrix by means of chemical treatment and the inclusion of nanoparticles. The resulting mechanical performance of the end composites and their intended applications are also presented. Few targeted application areas of FRPCs such as aerospace, automobile, mechanical and biomedical implants were discussed in detail.

Mucocutaneous diseases are the most common manifestation of human immunodeficiency virus and because of abnormal presentation, diagnosis and management is a challenge for clinicians. Here, we present three cases of unusual and severe presentation of common sexually transmitted diseases, out of which two patients had ulcerative lesions in genitals and one patient had cauliflower-like growth involving the pubic and anal region.

The recent trends of vitrimer studies enhance the thermoset material with superior properties, therefore, it is particularly important to address the critical scientific inquiries in this area using their research metrics. The reported vitrimer systems have been highly required for future real-time applications; however, the inquisitiveness of material exchange mechanisms extends the research studies further. Significantly, more scientific information's are required to achieve the evident prospective outcomes via these materials. This article highlights the trends and developments of the most relevant publications, authors, articles, countries, and keywords in the vitrimer research field over the past 10 years. The represented bibliometric survey would elevate the basic understanding of the current vitrimer research stats and also help follow the particular research community to learn and develop insight. To generate bibliometric networks, bibliometric data has obtained from Scopus and visualised in VOS-viewer; as an overview of that, the highest number of publications were from China, United States, France, United Kingdom, and Spain.

A 68-year-old man with a 3-month history of low back pain presented to urgent care, where X-rays revealed rib abnormalities. Further workup was significant for an elevated prostate-specific antigen (PSA) to 285. Technetium-99m-MDP bone scan and computed tomography showed extensive sclerotic osseous metastatic disease within the axial and appendicular skeleton and adenopathy in the retroperitoneum, pelvis, and superior mediastinum. Biopsy of a pelvic lymph node confirmed the diagnosis of prostate adenocarcinoma. The patient was treated with androgen deprivation therapy with luteinizing hormone-releasing hormone agonist along with targeted endocrine therapies. Despite initial PSA and radiographic response, 2 years after diagnosis, PSA started to rise. He developed a raised, erythematous plaque on his right upper chest. Biopsy revealed a poorly differentiated basaloid tumor consistent with metastatic prostate adenocarcinoma. He was started on docetaxel chemotherapy with a marked improvement of his skin lesion and decline in PSA. Unfortunately, the patient experienced disease progression with worsening bone and lymph node metastasis and died eight months after initial skin findings. It is crucial to suspect cutaneous metastasis in individuals with persistently elevated PSA despite treatment, especially if they develop nodular lesions.

Abstract Global dysregulation of RNA splicing and imbalanced sphingolipid metabolism has emerged as promoters of cancer cell transformation. Here, we present specific signature of alternative splicing (AS) events of sphingolipid genes for each breast cancer subtype from the TCGA-BRCA dataset. We show that ceramide synthase 2 (CERS2) undergoes a unique cassette exon event specifically in Luminal B subtype tumors. We validated this exon 8 skipping event in Luminal B cancer cells compared to normal epithelial cells, and in patient-derived tumor tissues compared to matched normal tissues. Differential AS-based survival analysis shows that this AS event of CERS2 is a poor prognostic factor for Luminal B patients. As Exon 8 corresponds to catalytic Lag1p domain, overexpression of AS transcript of CERS2 in Luminal B cancer cells leads to a reduction in the level of very-long-chain ceramides compared to overexpression of protein-coding (PC) transcript of CERS2. We further demonstrate that this AS event-mediated decrease of very-long-chain ceramides leads to enhanced cancer cell proliferation and migration. Therefore, our results show subtype-specific AS of sphingolipid genes as a regulatory mechanism that deregulates sphingolipids like ceramides in breast tumors, and can be explored further as a suitable therapeutic target.

This study aims to provide comparative data on clinical features and in-hospital outcomes among U.S. adults admitted to the hospital with COVID-19 and influenza infection using a nationwide inpatient sample (N.I.S.) data 2020. Data were collected on patient characteristics and in-hospital outcomes, including patient’s age, race, sex, insurance status, median income, length of stay, mortality, hospitalization cost, comorbidities, mechanical ventilation, and vasopressor support. Additional analysis was performed using propensity matching. In propensity-matched cohort analysis, influenza-positive (and COVID-positive) patients had higher mean hospitalization cost (USD 129,742 vs. USD 68,878, p = 0.04) and total length of stay (9.9 days vs. 8.2 days, p = 0.01), higher odds of needing mechanical ventilation (OR 2.01, 95% CI 1.19–3.39), and higher in-hospital mortality (OR 2.09, 95% CI 1.03–4.24) relative to the COVID-positive and influenza-negative cohort. In conclusion, COVID-positive and influenza-negative patients had lower hospital charges, shorter hospital stays, and overall lower mortality, thereby supporting the use of the influenza vaccine in COVID-positive patients.

Academics and the health community are paying much attention to developing smart remote patient monitoring, sensors, and healthcare technology. For the analysis of medical scans, various studies integrate sophisticated deep learning strategies. A smart monitoring system is needed as a proactive diagnostic solution that may be employed in an epidemiological scenario such as COVID-19. Consequently, this work offers an intelligent medicare system that is an IoT-empowered, deep learning-based decision support system (DSS) for the automated detection and categorization of infectious diseases (COVID-19 and pneumothorax). The proposed DSS system was evaluated using three independent standard-based chest X-ray scans. The suggested DSS predictor has been used to identify and classify areas on whole X-ray scans with abnormalities thought to be attributable to COVID-19, reaching an identification and classification accuracy rate of 89.58% for normal images and 89.13% for COVID-19 and pneumothorax. With the suggested DSS system, a judgment depending on individual chest X-ray scans may be made in approximately 0.01 s. As a result, the DSS system described in this study can forecast at a pace of 95 frames per second (FPS) for both models, which is near to real-time.

The task of recognising an object and estimating its 6d pose in a scene has received considerable attention in recent years. The accessibility and low-cost of consumer RGB-D cameras, make object recognition and pose estimation feasible even for small industrial businesses. An example is the industrial assembly line, where a robotic arm should pick a small, textureless and mostly homogeneous object and place it in a designated location. Despite all the recent advancements of object recognition and pose estimation techniques in natural scenes, the problem remains challenging for industrial parts. In this paper, we present a framework to simultaneously recognise the object’s class and estimate its 6d pose from RGB-D data. The proposed model adapts a global approach, where an object and the Region of Interest (ROI) are first recognised from RGB images. The object’s pose is then estimated from the corresponding depth information. We train various classifiers based on extracted Histogram of Oriented Gradient (HOG) features to detect and recognize the objects. We then perform template matching on the point cloud based on surface normal and Fast Point Feature Histograms (FPFH) to estimate the pose of the object. Experimental results show that our system is quite efficient, accurate and robust to illumination and background changes, even for the challenging objects of Tless dataset.

A rare case of non-ossifying fibroma of the maxilla is being reported alogwith the review of literature.