A Robust Malaria Cell Detection Framework Using Adaptive and Atrous Convolution-Based Recurrent Mobilenetv2 with Trans-MobileUNet + + -Based Abnormality Segmentation.

The highly contagious malaria disease is spread by the female Anopheles mosquito. This disease results in a patient's death or incapacity to move their muscles, if it is not appropriately identified in the early stages. A Rapid Diagnostic Test (RDT) is a frequently used approach to find malaria cells in red blood cells.

Silver-Gold Alloy Nanoparticles (AgAu NPs): Photochemical Synthesis of Novel Biocompatible, Bimetallic Alloy Nanoparticles and Study of Their In Vitro Peroxidase Nanozyme Activity.

Facile synthesis of metal nanoparticles with controlled physicochemical properties using environment-friendly reagents can open new avenues in biomedical applications. Nanomaterials with controlled physicochemical properties have opened new prospects for a variety of applications. In the present study, we report a single-step photochemical synthesis of ~5 nm-sized silver (Ag) and gold (Au) nanoparticles (NPs), and Ag-Au alloy nanoparticles using L-tyrosine.

Chimeric antibody targeting unique epitope on onco-mucin16 reduces tumor burden in pancreatic and lung malignancies.

Aberrantly expressed onco-mucin 16 (MUC16) and its post-cleavage generated surface tethered carboxy-terminal (MUC16-Cter) domain are strongly associated with poor prognosis and lethality of pancreatic (PC) and non-small cell lung cancer (NSCLC). To date, most anti-MUC16 antibodies are directed towards the extracellular domain of MUC16 (CA125), which is usually cleaved and shed in the circulation hence obscuring antibody accessibility to the cancer cells. Herein, we establish the utility of targeting a post-cleavage generated, surface-tethered oncogenic MUC16 carboxy-terminal (MUC16-Cter) domain by using a novel chimeric antibody in human IgG1 format, ch5E6, whose epitope expression directly correlates with disease severity in both cancers.

Acceptance, hesitancy and refusal towards COVID-19 vaccination.

Problem: The determinants of COVID-19 vaccine acceptance, hesitancy, and refusal remain poorly understood. We assessed the general population of Pune after visiting tertiary care hospital for their willingness to accept the vaccine and the reason for their hesitancy and refusal.

Methodology: A six-month descriptive cross-sectional study with 386 community members over the age of 18 who visited the Tertiary Hospital OPD was conducted.

A rare case of double ectopic thyroid in the superior mediastinum: a case report.

Primary ectopic mediastinal thyroid is rare, seen in <1% of patients with ectopic thyroid. A patient with two ectopic foci in mediastinum is even rare. Our patient presented with chronic cough and discomfort.

Solitary Penile Metastasis from Prostate Cancer on F-Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography.

We report a case of a 66-year-old man with prostate cancer who underwent F-prostate-specific membrane antigen positron emission tomography/computed tomography for baseline staging that revealed primary lesion in prostate gland along with a solitary metastatic deposit in the penile shaft. Penile metastasis is rare and usually associated with widespread metastatic disease. Solitary penile metastasis is even rarer and can present as a unifocal, multifocal, or diffuse lesion.

MicroRNA-1 attenuates the growth and metastasis of small cell lung cancer through CXCR4/FOXM1/RRM2 axis.

Background: Small cell lung cancer (SCLC) is an aggressive lung cancer subtype that is associated with high recurrence and poor prognosis. Due to lack of potential drug targets, SCLC patients have few therapeutic options. MicroRNAs (miRNAs) provide an interesting repertoire of therapeutic molecules; however, the identification of miRNAs regulating SCLC growth and metastasis and their precise regulatory mechanisms are not well understood.

Exploration of Despair Eccentricities Based on Scale Metrics with Feature Sampling Using a Deep Learning Algorithm.

The majority of people in the modern biosphere struggle with depression as a result of the coronavirus pandemic's impact, which has adversely impacted mental health without warning. Even though the majority of individuals are still protected, it is crucial to check for post-corona virus symptoms if someone is feeling a little lethargic. In order to identify the post-coronavirus symptoms and attacks that are present in the human body, the recommended approach is included.

Recognition of Diabetic Retinopathy with Ground Truth Segmentation Using Fundus Images and Neural Network Algorithm.

Diabetes problems can lead to a condition called diabetic retinopathy (DR), which permanently damages the blood vessels in the retina. If not treated, DR is a significant cause of blindness. The only DR treatments currently accessible are those that block or delay vision loss, which emphasizes the value of routine scanning with high-efficiency computer-based technologies to identify patients early.

Aerial Separation and Receiver Arrangements on Identifying Lung Syndromes Using the Artificial Neural Network.

Lung disease is one of the most harmful diseases in traditional days and is the same nowadays. Early detection is one of the most crucial ways to prevent a human from developing these types of diseases. Many researchers are involved in finding various techniques for predicting the accuracy of the diseases.

Prevention of Cyber Security with the Internet of Things Using Particle Swarm Optimization.

High security for physical items such as intelligent machinery and residential appliances is provided via the Internet of Things (IoT). The physical objects are given a distinct online address known as the Internet Protocol to communicate with the network's external foreign entities through the Internet (IP). IoT devices are in danger of security issues due to the surge in hacker attacks during Internet data exchange.

Accrual and Dismemberment of Brain Tumours Using Fuzzy Interface and Grey Textures for Image Disproportion.

A neurological disorder is a problem with the neural system of the body, as a brain tumor is one of the deadliest neurological conditions and it requires an early and effective detection procedure. The existing detection and diagnosis methods for image evaluation are based on the judgment of the radiologist and neurospecialist, where a risk of human mistakes can be found. Therefore, a new flanged method and methodology for detecting brain tumors using magnetic resonance imaging and the artificial neural network (ANN) technique are applied.

Perception Exploration on Robustness Syndromes With Pre-processing Entities Using Machine Learning Algorithm.

The majority of the current-generation individuals all around the world are dealing with a variety of health-related issues. The most common cause of health problems has been found as depression, which is caused by intellectual difficulties. However, most people are unable to recognize such occurrences in them, and no procedures for discriminating them from normal people have been created so far.

Human Intelligence Analysis through Perception of AI in Teaching and Learning.

Instructional practices have undergone a drastic change as a result of the development of new educational technology. Artificial intelligence (AI) as a teaching and learning technology will be examined in this theoretical review study. To enhance the quality of teaching and learning, the use of artificial intelligence approaches is being studied.

The Pleiotropic role, functions and targeted therapies of LIF/LIFR axis in cancer: Old spectacles with new insights.

The dysregulation of leukemia inhibitory factor (LIF) and its cognate receptor (LIFR) has been associated with multiple cancer initiation, progression, and metastasis. LIF plays a significant tumor-promoting role in cancer, while LIFR functions as a tumor promoter and suppressor. Epithelial and stromal cells secrete LIF via autocrine and paracrine signaling mechanism(s) that bind with LIFR and subsequently with co-receptor glycoprotein 130 (gp130) to activate JAK/STAT1/3, PI3K/AKT, mTORC1/p70s6K, Hippo/YAP, and MAPK signaling pathways.

Expedite Quantification of Landslides Using Wireless Sensors and Artificial Intelligence for Data Controlling Practices.

The power of wireless network sensor technologies has enabled the development of large-scale in-house monitoring systems. The sensor may play a big part in landslide forecasting where the sensor linked to the WLAN protocol can usefully map, detect, analyze, and predict landslide distant areas, etc. A wireless sensor network comprises autonomous sensors geographically dispersed for monitoring physical or environmental variables, comprising temperature, sound, pressure, etc.

Computational Approach for Detection of Diabetes from Ocular Scans.

The estimated 30 million children and adults are suffering with diabetes across the world. A person with diabetes can recognize several symptoms, and it can also be tested using retina image as diabetes also affects the human eye. The doctor is usually able to detect retinal changes quickly and can help prevent vision loss.

Artificial Intelligence-Based Robotic Technique for Reusable Waste Materials.

Waste management is a critical problem for every country, whether it is developed or developing. Selecting and managing waste are a critical part of preserving the environment and maximizing resource efficiency. In addition to reducing trash and disposal, reusable items are predicted to be of great benefit since they lessen our dependence on raw materials.

DNA-gold nanoprobe-based integrated biosensing technology for non-invasive liquid biopsy of serum miRNA: A new frontier in prostate cancer diagnosis.

The low specificity of prostate-specific antigen contributes to overdiagnosis and ov ertreatment of prostate cancer (PCa) patients. Hence, there is an urgent need for inclusive diagnostic platforms that could improve the diagnostic accuracy of PCa. Dysregulated miRNAs are closely associated with the progression and recurrence and have emerged as promising diagnostic and prognostic biomarkers for PCa.

An Attribute Extraction for Automated Malware Attack Classification and Detection Using Soft Computing Techniques.

Malware has grown in popularity as a method of conducting cyber assaults in former decades as a result of numerous new deception methods employed by malware. To preserve networks, information, and intelligence, malware must be detected as soon as feasible. This article compares various attribute extraction techniques with distinct machine learning algorithms for static malware classification and detection.

Deep Learning Approaches for Prognosis of Automated Skin Disease.

Skin problems are among the most common ailments on Earth. Despite its popularity, assessing it is not easy because of the complexities in skin tones, hair colors, and hairstyles. Skin disorders provide a significant public health risk across the globe.

Development of Advanced Artificial Intelligence and IoT Automation in the Crisis of COVID-19 Detection.

Internet of Things (IoT) is a successful area for many industries and academia domains, particularly healthcare is one of the application areas that uses IoT sensors and devices for monitoring. IoT transition replaces contemporary health services with scientific and socioeconomic viewpoints. Since the epidemic began, diverse scientific organizations have been making accelerated efforts to use a wide range of tools to tackle this global challenge and the founders of IoT analytics.

Implementation of Whale Optimization for Budding Healthiness of Fishes with Preprocessing Approach.

This article examines distinctive techniques for monitoring the condition of fishes in underwater and also provides tranquil procedures after catching the fishes. Once the fishes are hooked, two different techniques that are explicitly designed for smoking and drying are implemented for saving the time of fish suppliers. Existing methods do not focus on the optimization algorithms for solving this issue.

Nanocarriers for pancreatic cancer imaging, treatments, and immunotherapies.

Pancreatic tumors are highly desmoplastic and immunosuppressive. Delivery and distribution of drugs within pancreatic tumors are compromised due to intrinsic physical and biochemical stresses that lead to increased interstitial fluid pressure, vascular compression, and hypoxia. Immunotherapy-based approaches, including therapeutic vaccines, immune checkpoint inhibition, CAR-T cell therapy, and adoptive T cell therapies, are challenged by an immunosuppressive tumor microenvironment.