Management Of Disease Research Articles

CARDIAC REHABILITATION AND PSYCHOLOGICAL TREATMENT: CONTRASTS IN ANXIETY, DEPRESSION AND ILLNESS PERCEPTION LEVELS

Abstract Background Investigating the relationship between psychological factors and cardiovascular diseases (CVD) has long been a focal point of previous research. Researchers have primarily focused on identifying possible predictive factors for CVD’s development and examining patients’ responses during acute or chronic phases, but less is known about the role of cardiac rehabilitation and the types of psychological treatments on patients’ psychological status. Aims The aim of this study is to compare anxiety, depression, and illness perception levels of patients affected by different cardiovascular diseases at the beginning (t0), at the end (t1), and three months after a cardiac rehabilitation program (t2) in which patients were involved in three different types of psychological treatments: psychoeducational intervention group, progressive muscle relaxation training integrated with Jacobson‘s technique and imaginative stabilization techniques, individual counseling. Methods In this study were involved patients with recent episodes of Acute Coronary Syndrome (ACS), heart failure (HF) or cardiac surgery undergoing cardiac rehabilitation between January 2023 and August 2023 at ASST Bergamo Est. To assess anxiety, depression and illness perception levels of participants we used self–report questionnaires that included the Hospital Anxiety and Depression Scale (HADS) and the Brief Illness Perception Questionnaire (Brief–IPQ). Patients could be assigned to different psychological treatments based on their clinical condition. Results The study involved 181 participants, namely N=36 ACS cases (19.9%), N=25 CHF (13.8%), and N=120 cardiac surgery (66.3%). As shown in Table 1, males were 71.3% (N=129) and the average age was 65.96 years old (SD=11.904). One hundred–sixty einght patients participated in psychoeducational intervention group, 120 in relaxation training, and 35 in individual counseling. Statistically significant differences in anxiety, depression, and illness perception levels were observed at the program‘s initiation (t0) and upon completion (t1 and t2) in relation to the psychological treatments: individual counseling had a better impact on levels of anxiety and depression and on the development of a more adequate perception of illness. Conclusions The type of psychological treatment during cardiac rehabilitation appears to give different results in terms of psychological status, self–care and disease management of patients.

Sex Differences in Primary Care–Based Chronic Kidney Disease Management

This retrospective study uses electronic health record data to investigate the sex differences in guideline-based management outcomes between male and female patients with chronic kidney disease.

Efficient Faba Bean Leaf Disease Identification through Smart Detection using Deep Convolutional Neural Networks

Background: Legumes, such as lentils, field peas, Faba beans and chickpeas, are high in vitamins, fiber, important minerals and protein and can help avoid obesity and cardiovascular illnesses. They also contribute to ecosystem services, such as nitrogen fixation and resilience to environmental stresses. Despite a 60% increase in global pulse production from 2000 to 2021, a demand-supply gap, especially in South Asia, raises concerns about nutritional access. Since illnesses are currently an issue to the food security of faba beans, machine learning is required for efficient disease identification. Methods: This research employs Convolutional Neural Networks (CNNs) for robust Faba bean leaf disease identification. The CNN model is trained with diverse images representing specific diseases. The study focuses on diseases like Chocolate Spot, Faba Bean Gall, Rust and Healthy leaves. Image processing involves resizing, grayscale conversion and labeling. The CNN architecture includes eight convolutional layers, four max-pooling layers and three dropout layers. The model is trained using 80% of the dataset, validated using 20% and tested for accuracy. Result: The CNN model achieves an accuracy of 99.37% during training and 89.69% during validation after 75 epochs. Confusion matrix and classification report illustrate the model’s performance. It shows high precision, recall and F1 scores for each class, indicating balanced performance. Chocolate Spot and Rust exhibit the highest precision and F1 scores. The overall accuracy is 91%, comparable to other studies on Faba bean disease detection. The study presents a CNN-based disease identification system for Faba beans, demonstrating high accuracy and balanced performance across different diseases. The model’s effectiveness is comparable to other advanced techniques. The research highlights the potential of machine learning in optimizing disease management for Faba beans. Future work could explore a broader range of diseases and incorporate hybrid machine learning algorithms for further improvement.

Impacts of a Commercially Available Horticultural Oil Biopesticide (EF-400) on the Tomato-Phytophthora infestans Pathosystem.

Biopesticide fungicides are naturally derived compounds that offer protection from plant diseases through various modes of action, including antimicrobial activity and upregulation of defense responses in host plants. These plant protectants provide a sustainable and safe alternative to conventional pesticides in integrated disease management programs and are especially salient in the management of high-risk and economically important diseases such as late blight of tomato and potato, for which host resistance options are limited. In this study, a commercially available biopesticide, EF400 comprised of clove (8.2%), rosemary (8.1%), and peppermint oils (6.7%) (Anjon AG, Corcoran, CA), was investigated for its effects on the Phytophthora infestans-tomato pathosystem. Specifically, we evaluated the impact of EF400 on P. infestans growth in culture, disease symptoms in planta, and activation of host defenses through monitoring transcript accumulation of defense-related genes. The application timing and use rate of EF400 were further investigated for managing tomato late blight. EF400 delayed the onset of tomato late blight symptoms, although not as effectively as the copper hydroxide fungicide Champ WG (Nufarm Americas Inc., Alsip, IL). Pathogen mycelial growth and sporangial quantity on late blight-susceptible tomato leaves were significantly reduced with EF400. The biopesticide also had an enhancing or suppressing effect on the transcript accumulation of three defense-related genes: Pin2, PR1a, and PR1b. Our work in exploring a commercially available horticultural oil biopesticide meaningfully contributed to the essential knowledge base for optimizing recommendations for the management of tomato late blight.

A Case Study of Non-specialist Disease Management Using Teladoc Health Support: A Case Report

A Case Study of Non-specialist Disease Management Using Teladoc Health Support: A Case Report

Comments on the guidelines (2023) of the ESC on the management of cardiovascular diseases in patients with diabetes

Comments on the guidelines (2023) of the ESC on the management of cardiovascular diseases in patients with diabetes

Design and Rationale of the Cardiometabolic Health Program Linked with Community Health Workers and Mobile Health Telemonitoring to Reduce Health DisparitieS (LINKED-HEARTS) Program.

Hypertension and diabetes are major risk factors for cardiovascular diseases, stroke, and chronic kidney disease (CKD). Disparities in hypertension control persist among Black and Hispanic adults and persons living in poverty in the United States. The "LINKED-HEARTS Program" (a Cardiometabolic Health Program LINKED with Community Health WorkErs and Mobile HeAlth TelemonitoRing To reduce Health DisparitieS"), is a multi-level intervention that includes home blood pressure (BP) monitoring (HBPM), blood glucose telemonitoring, and team-based care. This study aims to examine the effect of the LINKED-HEARTS Program intervention in improving BP control compared to enhanced usual care (EUC) and to evaluate the reach, adoption, sustainability, and cost-effectiveness of the program. Using a hybrid type I effectiveness-implementation design, 428 adults with uncontrolled hypertension (systolic BP ≥ 140 mm Hg) and diabetes or CKD will be recruited from 18 primary care practices, including community health centers, in Maryland. Using a cluster-randomized trial design, practices are randomly assigned to the LINKED-HEARTS intervention arm or EUC arm. Participants in the LINKED-HEARTS intervention arm receive training on HBPM, BP and glucose telemonitoring, and community health worker and pharmacist telehealth visits on lifestyle modification and medication management over 12 months. The primary outcome is the proportion of participants with controlled BP (<140/90 mm Hg) at 12 months. The study tests a multi-level intervention to control multiple chronic diseases. Findings from the study may be leveraged to reduce disparities in the management and control of chronic diseases and make primary care more responsive to the needs of underserved populations.

Janus Membrane-Based Wearable pH Sensor with Sweat Absorption, Gas Permeability, and Self-Adhesiveness.

Wearable biomedical sensors have enabled noninvasive and continuous physiological monitoring for daily health management and early detection of chronic diseases. Among biomedical sensors, wearable pH sensors attracted significant interest, as pH influences most biological reactions. However, conformable pH sensors that have sweat absorption ability, are self-adhesive to the skin, and are gas permeable remain largely unexplored. In this study, we present a pioneering approach to this problem by developing a Janus membrane-based pH sensor with self-adhesiveness on the skin. The sensor is composed of a hydrophobic polyurethane-polydimethylsiloxane porous hundreds nanometer-thick substrate and a hydrophilic poly(vinyl alcohol)-poly(acrylic acid) porous nanofiber layer. This Janus membrane exhibits a thickness of around 10 μm, providing a conformable adhesion to the skin. The simultaneous realization of solution absorption, gas permeability, and self-adhesiveness makes it suitable for long-term continuous monitoring without compromising the comfort of the wearer. The pH sensor was tested successfully for continuous monitoring for 7.5 h, demonstrating its potential for stable analysis of skin health conditions. The Janus membrane-based pH sensor holds significant promise for comprehensive skin health monitoring and wearable biomedical applications.

Enhancing chickpea (Cicer arietinum L.) production through front-line demonstration in sub mountainous region of Punjab, India

In the present study, 38 frontline demonstrations (FLDs) on chickpea variety (PBG-7) were conducted in an area of 15 ha during Rabi 2021-22 and 2022-23 for demonstrating improved cultivation technologies to the farmers. Results of front-line demonstrations showed that the cultivation practices comprised under FLDs viz., use of improved varieties, optimum seed rate, balanced application of fertilizers, line sowing, timely management of weeds, insects and disease, produced grain yield of 13.2 q ha-1 and 13.1q ha-1 during Rabi 2021-22 and 2022-23 respectively which was 53.8% higher as compared to the prevailing farmers practice. The findings of the study showed that the technology gap for chickpea was 6.8 q ha-1 and 6.9 q ha-1 during Rabi 2021-22 and 2022-23 with an average of 6.85 q ha-1 over the two years. The technology index was 34.0 and 34.5 percent during Rabi 2021-22 and 2022-23, respectively with a mean value of 34.2%. The extension gap was 4.5 q ha-1 and 4.7 q ha-1 for the years 2021 and 2022 with the average value of 4.6 q ha-1 over the two years. The data reported that the technology demonstrated fetched more average gross returns (Rs. 92,050 ha-1), net return (Rs. 70,050 ha-1) and B:C ratio (4.1) over two years compared to farmers practice. On the other hand, under farmers’ practice, the average gross returns was Rs. 59,850 ha-1, average net profit to the tune was Rs. 37,250 ha-1 and the average B: C ratio was 2.6 over two years.

A Holistic Approach to Parkinson's Disease: Integrating Advances in Pathophysiology, Diagnosis, and Therapy

Background: Parkinson's disease (PD) is a prevalent neurodegenerative disorder affecting millions worldwide, with an increasing burden projected in the coming years. It involves complex neurological decline primarily affecting the Substantia nigra and Locus coeruleus, leading to motor and non-motor symptoms. Objective: This study aims to provide a comprehensive overview of Parkinson's disease, including its epidemiology, pathophysiology, diagnosis, and available therapies, encompassing both traditional pharmaceutical treatments and emerging technological advancements. Methods: A thorough review of literature was conducted, synthesizing information from various studies and clinical trials to elucidate the current understanding of Parkinson's disease and its management strategies. Results: Parkinson's disease is characterized by the gradual loss of dopamine-producing cells and the presence of Lewy bodies in the brain. Diagnosis relies on clinical evaluation, and treatment typically involves pharmaceutical interventions such as levodopa, COMT inhibitors, dopamine agonists, and deep brain stimulation. Additionally, advancements in technology offer promising avenues for objective symptom assessment and personalized treatment approaches. Conclusion: The management of Parkinson's disease requires a multidisciplinary approach, integrating traditional pharmacological treatments with emerging technologies and complementary therapies like dance therapy, tai chi, and speech therapy. By combining these diverse modalities, healthcare professionals can provide more effective and personalized care, ultimately enhancing the quality of life for individuals living with Parkinson's disease. Keywords: Parkinson's disease, medical therapy, device-aided therapy, alternative interventions, personalized treatment, neurodegenerative disorder

Antisense oligonucleotide as a new technology application for CsLOB1 gene silencing aiming citrus canker resistance.

Citrus canker disease, caused by Xanthomonas citri subsp. citri, poses a significant threat to global citrus production. The control of the disease in the field relies mainly on the use of conventional tools such as copper compounds, which are harmful to the environment and could lead to bacterial resistance. This scenario stresses the need for new and sustainable technologies to control phytopathogens, representing a key challenge in developing studies that translate basic into applied knowledge. During infection, X. citri subsp. citri secretes a transcriptional activator-like effector that enters the nucleus of plant cells, activating the expression of the canker susceptibility gene LATERAL ORGAN BOUNDARIES 1 (LOB1). In this study, we explored the use of antisense oligonucleotides (ASOs) with phosphorothioate modifications to transiently inhibit the gene expression of CsLOB1 in Citrus sinensis. We designed and validated three potential ASO sequences, which led to a significant reduction in disease symptoms compared to the control. The selected ASO3-CsLOB1 significantly decreased the expression level of CsLOB1 when delivered through two distinct delivery methods and the reduction of the symptoms ranged from approximately 15% to 83%. Notably, plants treated with ASO3 did not exhibit an increase in symptoms development over the evaluation period. This study highlights the efficacy of ASO technology, based on short oligonucleotide chemically modified sequences, as a promising tool for controlling phytopathogens without the need for genetic transformation or plant regeneration. Our results demonstrate the potential of ASOs as a biotechnological tool for the management of citrus canker disease.

Lipid-lowering, antihypertensive, and antithrombotic effects of nattokinase combined with red yeast rice in patients with stable coronary artery disease: a randomized, double-blinded, placebo-controlled trial

Nattokinase (NK) and red yeast rice (RYR) are both indicated for their potential in cardiovascular disease prevention and management, but their combined effects especially in coronary artery disease (CAD) are scarcely examined. This 90-day randomized, double-blind trial aims to investigate the effect of NK and RYR supplementations on cardiometabolic parameters in patients with stable CAD. 178 CAD patients were randomized to four groups: NK + RYR, NK, RYR, and placebo. No adverse effects due to the interventions were reported. In comparisons across groups, NK + RYR showed the maximum effect in reducing triglyceride (−0.39 mmol), total cholesterol (−0.66 mmol/L), diastolic blood pressure (−7.39 mmHg), and increase in high-density lipoprotein cholesterol (0.195 mmol/L) than other groups (all p for multiple groups comparison&amp;lt;0.01). Both NK + RYR and NK groups had significantly better-improved lactate dehydrogenase than the others (−29.1 U/L and − 26.4 U/L). NK + RYR group also showed more potent reductions in thromboxane B2 and increases in antithrombin III compared to placebo (both p &amp;lt; 0.01). These improved markers suggest that combined NK and RYR may preferably alter antithrombin and COX-1 pathways, potentially reducing thrombosis risks in CAD patients. Overall, the combined NK and RYR supplementation is safe and more effective than separately in improving cardiometabolic markers among CAD patients with multiple heart medications use.

A systematic review of the factors associated with malaria infection among forest rangers.

Malaria is a vector-borne disease that initially manifests as fever, headache, and chills. The illness could progress to more severe conditions, including lethargy, impaired consciousness, convulsions, shortness of breath, blood in urine, jaundice, and haemorrhage if left untreated. The risk of contracting malaria is considerably heightened in specific occupational settings, particularly among forest rangers, following frequent exposure to natural habitats. Consequently, advancing the understanding of malaria and emphasising how specific occupational environments (including those of forest rangers) contribute to disease risk and management is imperative. The present study aims to determine the factors associated with malaria infection among forest rangers by systematically reviewing electronic articles from three databases (EBSCOhost, ScienceDirect, and ResearchGate). The current review was prepared based on the updated preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. First, three independent reviewers screened the titles and abstracts of the data collected. The information was then stored in Endnote20 based on the inclusion and exclusion criteria. The articles were critically appraised with the mixed methods appraisal tool (MMAT) to assess their quality. A total of 103, 31, and 51 articles from EBSCOhost, ScienceDirect, and ResearchGate, respectively, were selected, resulting in 185 unique hits. Nevertheless, only 63 full-text publications were assessed following a rigorous selection screening, from which only five were included in the final review. The studies revealed that several factors contribute to malaria infection among forest rangers. The parameters were classified into sociodemographic, individual, and living condition-related. A better understanding of malaria progresses and identifying its potential risk factors is essential to impact worker well-being. The findings might be utilised to improve malaria infection prevention programme implementations, hence maximising their success. Pre-employment and regular health screenings could also aid in evaluating and identifying potential risks for malaria infection among forest rangers.

A Mobile-Based System for Detecting Plant Leaf Diseases Using Deep Convolutional Neural Network

Plant diseases pose a significant challenge to agriculture in India, causing substantial losses in crop production each year. Limited-resource farmers often struggle with diagnosing these diseases accurately, especially when relying on visual observation of leaf symptoms. Hence, there is an urgent need to enhance the detection, monitoring, and prediction of crop diseases to mitigate agricultural losses effectively. To address this challenge, we propose a mobile-based system empowered by Machine Learning (ML) and computer vision tailored for the Indian context. Our system utilizes Convolutional Neural Networks (CNNs) as the core deep learning engine to classify 37 disease categories commonly found in Indian crops. We have curated a comprehensive dataset comprising 96,206 images of plant leaves, encompassing both healthy and infected, for training, validation, and testing purposes. The user interface of our system is designed as an Android mobile application, enabling farmers to capture images of diseased plant leaves effortlessly. Upon image capture, the system swiftly identifies the disease category and presents it to the user along with a confidence percentage. This functionality empowers farmers to take timely action to protect their crops, thereby reducing reliance on incorrect fertilizers that may exacerbate plant stress. Furthermore, we evaluated the performance of our system using various metrics, including classification accuracy and processing time. Our results indicate an impressive overall classification accuracy of 94% across the 37 disease classes prevalent in 14 different crop species commonly cultivated in India. In essence, our ML-powered mobile-based solution offers Indian farmers a robust tool for efficient crop disease diagnosis and management, ultimately contributing to the enhancement of agricultural productivity and sustainability in the country.

Facilitators and barriers to self-management in Iranian men with chronic obstructive pulmonary disease: a qualitative study

IntroductionSelf-management, as the most common method of chronic obstructive pulmonary disease (COPD) management, is not an isolated behaviour, but a set of physical, social, cultural, psychological and existential factors affecting...

Nanotechnology - An advanced dental innovation

Researchers are interested in exploring the possible uses and advantages of nanotechnology compared to traditional materials, particularly in the domains of dentistry and medicine. The study and creation of materials, tools, systems with distinct biological, chemical, physical characteristics from those found in larger system is known as nanotechnology. Numerous advancements and improvement in oral disease prevention, diagnosis, and treatment are possible because of nanotechnology. Recent Nano - technology breakthrough developments in dentistry are progressively providing a viable therapeutic option for a wide range of dental problems. The purpose of this review was to provide an overview role of nanotechnology in dentistry, as well as to evaluate its application in the prevention and treatment of oral disorders, along with providing crucial new updates on the various nanotechnology – based techniques for dental disease management. The current review will also assist the reader in comprehending Nano science, as well as its benefits and drawbacks, by discussing its ethical, social, and health consequences. In addition, Nano -applications in dental diagnostics and their function in dentistry will be discussed.

Synergistic integration of deep learning with protein docking in cardiovascular disease treatment strategies.

This research delves into the exploration of the potential of tocopherol-based nanoemulsion as a therapeutic agent for cardiovascular diseases (CVD) through an in-depth molecular docking analysis. The study focuses on elucidating the molecular interactions between tocopherol and seven key proteins (1O8a, 4YAY, 4DLI, 1HW9, 2YCW, 1BO9 and 1CX2) that play pivotal roles in CVD development. Through rigorous in silico docking investigations, assessment was conducted on the binding affinities, inhibitory potentials and interaction patterns of tocopherol with these target proteins. The findings revealed significant interactions, particularly with 4YAY, displaying a robust binding energy of -6.39 kcal/mol and a promising Ki value of 20.84 μM. Notable interactions were also observed with 1HW9, 4DLI, 2YCW and 1CX2, further indicating tocopherol's potential therapeutic relevance. In contrast, no interaction was observed with 1BO9. Furthermore, an examination of the common residues of 4YAY bound to tocopherol was carried out, highlighting key intermolecular hydrophobic bonds that contribute to the interaction's stability. Tocopherol complies with pharmacokinetics (Lipinski's and Veber's) rules for oral bioavailability and proves safety non-toxic and non-carcinogenic. Thus, deep learning-based protein language models ESM1-b and ProtT5 were leveraged for input encodings to predict interaction sites between the 4YAY protein and tocopherol. Hence, highly accurate predictions of these critical protein-ligand interactions were achieved. This study not only advances theunderstanding of these interactions but also highlights deep learning's immense potential in molecular biology and drug discovery. It underscores tocopherol's promise as a cardiovascular disease management candidate, shedding light on its molecular interactions and compatibility with biomolecule-like characteristics.

2024 ACC/AHA/AACVPR/APMA/ABC/SCAI/SVM/SVN/SVS/SIR/VESS Guideline for the Management of Lower Extremity Peripheral Artery Disease: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines.

The "2024 ACC/AHA/AACVPR/APMA/ABC/SCAI/SVM/SVN/SVS/SIR/VESS Guideline for the Management of Lower Extremity Peripheral Artery Disease" provides recommendations to guide clinicians in the treatment of patients with lower extremity peripheral artery disease across its multiple clinical presentation subsets (ie, asymptomatic, chronic symptomatic, chronic limb-threatening ischemia, and acute limb ischemia). A comprehensive literature search was conducted from October 2020 to June 2022, encompassing studies, reviews, and other evidence conducted on human subjects that was published in English from PubMed, EMBASE, the Cochrane Library, CINHL Complete, and other selected databases relevant to this guideline. Additional relevant studies, published through May 2023 during the peer review process, were also considered by the writing committee and added to the evidence tables where appropriate. Recommendations from the "2016 AHA/ACC Guideline on the Management of Patients With Lower Extremity Peripheral Artery Disease" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing comprehensive care for patients with peripheral artery disease have been developed.

Exploring X: barriers to care for eosinophilic esophagitis.

Patients with chronic diseases have increasingly turned to social media to discuss symptoms and share the challenges they face with disease management. The primary aim of this study is to use naturally occurring data from X (formerly known as Twitter) to identify barriers to care faced by individuals affected by eosinophilic esophagitis (EoE). For this qualitative study, the X application programming interface with academic research access was used to search for posts that referenced EoE between 1 January 2019 and 10 August 2022. The posts were identified as being either related to barriers to care for EoE or not. Those related to barriers to care were further categorized by the type of barrier that was expressed. A total of 8636 EoE-related posts were annotated of which 12.1% were related to barriers to care in EoE. The themes that emerged about barriers to care included: dietary challenges, limited treatment options, lack of community support, lack of physician awareness of disease, misinformation, cost of care, lack of patient belief in disease or trust in physician, and limited access to care. Saturation of themes was achieved. This study highlights barriers to care in EoE using readily accessible social media data that is not derived from a curated research setting. Identifying these obstacles is key to improving care for this chronic disease.

Arachis pintoi Krapov. &amp; W.C. Greg.–A multifunctional legume

AbstractArachis pintoi, commonly known as pinto or forage peanut, is used mainly in consortia with grass pastures and as cover plant. In addition to increasing the productivity of livestock and plantations, it contributes to the mitigation of environmental impacts (reduction of greenhouse gas emissions) and soil improvement (nitrogen fixation, reduction of fertilizers use), as well as to pests and disease management. Several cultivars that are tolerant to specific climates and soil conditions are suitable to be used as ground covers in agroforestry and silvopastoral systems, orchards, and plantations. Biotechnological and phytochemical investigations revealed the potential of pinto peanut as a sustainable source of resveratrol and other stilbenoids. Extracts from plants grown under natural conditions and from materials obtained in vitro displayed allelopathic, anthelmintic, or antioxidant activities. Other studies revealed the potential of pinto peanut for erosion control, phytoremediation, seed and essential oils production, materials for animal tissue engineering, synthesis of nanoparticles for drug delivery, and as green biorefineries to produce proteins, biochemicals, and biomaterials.