Forensic Analysis of WhatsApp: A Review of Techniques, Challenges, and Future Directions
Published on: 18th June, 2024
WhatsApp, a widely used instant messaging application, has become a valuable source of digital evidence in forensic investigations. This review article explores the forensic analysis techniques, challenges, and future directions associated with WhatsApp. It covers the extraction and analysis of data from various sources, including mobile devices, cloud backups, and network traffic. The article discusses the challenges faced by forensic examiners, such as encryption, data volatility, and the need for proper validation of tools. It also highlights the importance of keeping up with the latest updates and changes in WhatsApp’s features and security measures. The future directions for WhatsApp forensics are explored, focusing on the development of more advanced and efficient analysis techniques, the need for standardization, and the importance of international cooperation in addressing cross-border investigations. This review provides insights for forensic examiners, researchers, and legal professionals involved in cases requiring WhatsApp evidence.
Evaluation of Performance Research Nuclear Reactors' Steady-state and Kinetic Model Analyses
Published on: 18th June, 2024
The mainstays of nuclear substance radiation and isotopic synthesis are nuclear-powered power plants, however effective safety evaluation is made tougher by the complicated construction topologies and physical connection effects. This work proposes a multiphysics-linked technique for evaluating both the kinetic and steady-state behaviors of the MPRR and LVR-15 laboratory reactors. To represent complicated member geometries, homogenized assembling sections are generated using two-dimensional whole-core computational simulations. It is discovered that the steady-state findings and the so-called Monte Carl solution comparisons correspond quite nicely. The greatest assemble power mistakes for LVR-15 and MPRR are 6.49%/10%, and the highest command rod value mistakes are 31 pcm/136 pcm, and the mistakes are 377 pcm/383 pcm, accordingly. Meanwhile, the study is done on transitory procedures, such as reactivity-initiated disasters and exposed loss-of-flow mishaps. Both units' modeling findings show plausible adverse feedback events. Furthermore, it is shown that the two reactors' accident-related behaviors are comparable though having different core architectures since they employ the exact same kinds of water as a fluid. The technique for studying nuclear power plant kinetics known as Multi-Physics Simulation (MPM) is explained. Drawing on many research and verification efforts conducted at Politecnico di Milan, Italy, MPM is shown to be a valuable instrument for managing reactors' security and oversight. It may be viewed as a holistic analytical tool that is implemented during the reactor architecture design phase. The capacity to concurrently answer the interrelated equations that control the many physical processes taking place in a nuclear plant inside the same simulated setting is a core characteristic of MPM.
Remote Effect of Fascial Manipulation on Knee Pain: A Case Report
Published on: 13th June, 2024
The study on the remote effect of fascial manipulation on knee pain presents a case report of a patient with knee pain who underwent a single session of fascial manipulation to reduce pain and improve daily activities. The report explains the anatomy of the knee joint and the potential causes of knee pain, including bony and soft tissue involvement. Fascial manipulation is a technique that involves applying mechanical force to areas of fascial dysfunction to stimulate the body’s natural inflammatory response. The therapy is based on applying physical friction to the densified connective tissue with an elbow or knuckle to raise the temperature and change the consistency of loose connective tissue rich in hyaluronic acid. The locations picked were proximal and distal to the problematic area, and no point was treated over the painful region, which is consistent with the notion of pain being caused by aberrant fascial tensions. Manipulation of the connective tissue is thought to cause mechanical stress and heat, resulting in less macromolecular crowding and defragmentation of the Hyaluronic Acid (HA) polymers and normalised fascial gliding across the connective tissue. Reduced discomfort and enhanced range of motion are two more regularly reported effects of Fascial Manipulation. The patient was urged to resume his everyday activities after each treatment session to favour typical physiological motions that would align collagen fibres along normal lines of force. The report concludes that fascial manipulation can be a beneficial technique for managing knee pain, and it can be complemented with exercises and stretches to improve outcomes.
Exophthalmos Revealing a Spheno Temporo Orbital Meningioma
Published on: 18th June, 2024
Intracranial meningiomas are usually non-cancerous tumors that develop from arachnoid cells in the meningeal envelope. However, there are rare forms called intraosseous meningiomas, which present unique challenges for diagnosis and treatment. In this report, we describe a rare case of a giant sphenotemporal meningioma in a 72-year-old male with diabetes. The patient experienced progressive exophthalmos and visual impairment over a period of five months. Radiological imaging confirmed the diagnosis, showing extensive infiltration into the infra-temporal region. Histopathological examination confirmed a plaque-type meningothelial meningioma. The patient underwent surgical management, which involved maxillofacial surgery. Intraosseous meningiomas are rare but are increasingly being recognized, accounting for about two percent of all meningiomas. The spheno-orbital region is a common site for these tumors. Histologically, there are various subtypes, with meningothelial meningioma being the most common. The differential diagnosis includes Paget’s disease and osteomas. The optimal treatment approach involves extensive surgical resection, followed by adjuvant radiotherapy for any remaining or symptomatic tumors. The prognosis depends on the extent of resection and tumor progression, underscoring the importance of regular monitoring. Early intervention is crucial to preserve visual function and achieve favorable outcomes.
Wealth in Water: A Blueprint for Sustainable Global Ocean Research
Published on: 19th June, 2024
Pushing forward with leveraging water resources, promoting international cooperation, and ensuring transparency in deep-sea mining operations. There is also a concern about where to discharge the toxins of unpurified water. Artificial Intelligence has created a dominance in the applications field with a totally automated system.Out of a thorough analysis completed with indicators, satellite radar, and A Journals, there are 30 years of research and 8 years of monitored testing to achieve accuracy and relevance. The patents in place are, Oceanic Mining System (4446636), Flexible Solar Skin in Combination with an Airplane (4768738), Cargo Torpedo (4421050), Oceanic seaplow system (4398362), and previous articles like “Is Extracting Lithium and deep-sea mining more sustainable?”, “AI as a Means of Water Purification Protection”, “Global Water Distribution”, and “Can Deep Sea Water be Processed into Potable Water and Distributed into the Middle East’?To report some ballpark numbers on the proposal and how we would navigate these projects, there will be an exact location of where the plant will be built as well as a water/salinity report of the water being treated. There are still issues with analyzing the cost of desalination compared to other alternatives. Deep Sea Water proves to be a higher quality water and the investment is well worth it. The surveys lean toward clients preferring the International Standards Operating Procedure. All recipients agree there should be a sense of urgency on water shortages. Currently, AI has proven to be a vital asset in eliminating biases and expenses.
MRI-based Tumor Habitat Analysis for Treatment Evaluation of Radiotherapy on Esophageal Cancer
Published on: 24th June, 2024
Introduction: We aim to evaluate the performance of pre-treatment MRI-based habitat imaging to segment tumor micro-environment and its potential to identify patients with esophageal cancer who can achieve pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT).Material and methods: A total of 18 patients with locally advanced esophageal cancer (LAEC) were recruited into this retrospective study. All patients underwent MRI before nCRT and surgery using a 3.0 T scanner (Ingenia 3.0 CX, Philips Healthcare). A series of MR sequences including T2-weighted (T2), diffusion-weighted imaging (DWI), and Contrast Enhance-T1 weighted (CE-T1) were performed. A clustering algorithm using a two-stage hierarchical approach groups MRI voxels into separate clusters based on their similarity. The t-test and receiver operating characteristic (ROC) analysis were used to evaluate the predictive effect of pCR on habitat imaging results. Cross-validation of 18 folds is used to test the accuracy of predictions.Results: A total of 9 habitats were identified based on structural and physiologic features. The predictive performance of habitat imaging based on these habitat volume fractions (VFs) was evaluated. Students’ t-tests identified 2 habitats as good classifiers for pCR and non-pCR patients. ROC analysis shows that the best classifier had the highest AUC (0.82) with an average prediction accuracy of 77.78%.Conclusion: We demonstrate that MRI-based tumor habitat imaging has great potential for predicting treatment response in LAEC. Spatialized habitat imaging results can also be used to identify tumor non-responsive sub-regions for the design of focused boost treatment to potentially improve nCRT efficacy.
Utilizing Smartphone ECG for Early Detection and Management of Ischemic Heart Disease: A Case Report
Published on: 24th June, 2024
Ischemic Heart Disease (IHD) remains a significant cause of morbidity and mortality worldwide. We present a case report of a 54-year-old individual presenting with symptoms suggestive of IHD, including palpitations and chest heaviness. Utilizing a Spandan device at home, the patient detected anteroseptal and lateral wall ischemia, prompting consultation with a cardiologist. Subsequent diagnostic evaluations revealed Left Ventricular Hypertrophy (LVH), concentric LVH, regional wall motion abnormality, and Grade I diastolic dysfunction. Hypertension and dyslipidemia were identified as prominent risk factors, with additional findings of carotid artery disease. Management strategies included antihypertensive medications, lipid-lowering therapy, and lifestyle modifications. This case underscores the complexity of diagnosing and managing IHD, highlighting the importance of comprehensive assessment and multidisciplinary care in optimizing patient outcomes.
Pattern of LRR in Endometrial Cancer and Identification of Predictive Factors
Published on: 8th July, 2024
Background: Tailored adjuvant treatment is key to managing endometrial cancer effectively. Understanding prognostic factors of loco-regional failure and the impact of adjuvant treatment can help in treatment de-escalation without compromising survival outcomes.The aim of this study was to assess the pattern of failure in endometrial cancer patients and to determine predicting Loco-Regional Recurrence (LRR) factors.Patients and methods: Data were collected from 214 patients treated for endometrial cancer between 2005 and 2012 in Salah Azaiez Institute in Tunisia. All patients underwent upfront surgery followed by adjuvant brachytherapy with or without external beam radiation. The median follow-up period was 44 months. Univariate and multivariate analyses were performed to identify prognostic factors for LRR.Results: The 5-year overall survival rate was 78.1%, and the 5-year progression-free survival rate was 80.1%. LRR occurred in 25 patients (11.6%), with a median recurrence time of 29 months (range 4 months - 46 months). Pelvic relapse was the most common site, occurring in 10 patients. Vaginal relapses were observed in 9 patients, and retro-peritoneal relapses were observed in 6 cases. FIGO stage, tumor grade, histologic type, Lympho-Vascular Space Invasion (LVSI), and delays in adjuvant treatment were significant predictors of LRR.Conclusion: Identifying prognostic factors for LRR in endometrial cancer is crucial for optimizing adjuvant treatment strategies. Higher FIGO stages and the presence of LVSI were independent predictive factors for LRR. Tailored adjuvant treatment, taking these prognostic factors into account, is essential to improve patient outcomes and minimize unnecessary treatment-related toxicity.
Review of AI in Civil Engineering
Published on: 8th July, 2024
This paper reviews the transformative impact of Artificial Intelligence (AI) on civil engineering. It explores AI's fundamental concepts and its applications across structural analysis, construction management, transportation, geotechnical engineering, and sustainability. The review highlights AI's role in automating tasks, predicting outcomes, and optimizing designs throughout project lifecycles. Recent advancements in AI-driven technologies for structural health monitoring, predictive maintenance, and risk assessment are discussed, along with challenges like data quality and model interpretability. Future trends such as autonomous construction and digital twins are examined, emphasizing the need for continued research and interdisciplinary collaboration. In conclusion, this paper offers insights for leveraging AI to address evolving challenges and opportunities in civil engineering, fostering innovation, sustainability, and resilience in infrastructure development.
Detecting Pneumothorax on Chest Radiograph Using Segmentation with Deep Learning
Published on: 9th July, 2024
Introduction: Pneumothorax is a life-threatening condition that requires prompt recognition and therapy to prevent deterioration. Radiologist workload often precludes rapid assessment of the usual diagnostic modality, the chest radiograph, particularly after hours. The aim was to develop a deep learning model using a segmentation-based Deep Convolutional Neural Network (DCNN) to detect pneumothorax on chest radiographs to provide rapid and accurate pneumothorax diagnosis.Methods: This is a retrospective study of spontaneous pneumothorax at a single center, containing 130 positive and 70 negative radiographs. Subsequent manual contour mapping was performed to draw a mask of the pneumothorax. These image pairs were used to train a DCNN model (a modified AlexNet) after pretraining on the ImageNet dataset.Results: The DCNN achieved an accuracy of 0.83, with sensitivity of 98.1%, and specificity of 68.5%.Conclusion: This segmentation-based DCNN accuracy is comparable to previous categorization-based CDNN models, despite using a smaller sample size for training, while including the benefits of visual representation for clinician feedback. Segmentation-based DCNNs show promise in the development of accurate and clinically useful models for medical imaging.
Radiomics by Quantitative Diffusion-weighted MRI for Predicting Response in Patients with Extremity Soft-tissue Undifferentiated Pleomorphic Sarcoma
Published on: 9th July, 2024
Purpose: This study aimed to determine the relevance of first- and high-order radiomic features derived from Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) maps for predicting treatment response in patients with Undifferentiated Pleomorphic Sarcoma (UPS).Methods: This retrospective study included 33 extremity UPS patients with pre-surgical DWI/ADC and surgical resection. Manual volumetric tumor segmentation was performed on DWI/ADC maps acquired at Baseline (BL), Post-Chemotherapy (PC), and Post-Radiation Therapy (PRT). The percentage of pathology-assessed treatment effect (PATE) in surgical specimens categorized patients into responders (R; PATE ≥ 90%; 16 patients), partial-responders (PR; 89% - 31% PATE; 10 patients), and non-responders (NR; PATE ≤ 30%; 7 patients). 107 radiomic features were extracted from BL, PC, and PRT ADC maps. Statistical analyses compared R vs. PR/NR.Results: Pseudo-progression at PC and universal stability at PRT were observed in R and PR/NR based on RECIST, WHO, and volumetric assessments. At PRT, responders displayed a 35% increase in ADC mean (p = 0.0034), a 136% decrease in skewness (p = 0.0001), and a 363% increase in the 90th percentile proportion (p = 0.0009). Comparing R vs. PR/NR at BL, statistically significant differences were observed in glrlm_highgraylevelrunemphasis (p = 0.0081), glrlm_shortrunhighgraylevelemphasis (p = 0.0138), gldm_highgraylevelemphasis (p = 0.0138), glcm_sumaverage (p = 0.0164), glcm_jointaverage (p = 0.0164), and glcm_autocorrelation (p = 0.0193). At PC, firstorder_meanabsolutedeviation (p = 0.0078), firstorder_interquartilerange (p = 0.0109), firstorder_variance (p = 0.0109), and firstorder_robustmeanabsolutedeviation (p = 0.0151) provided statistically significant differences.Conclusion: Observing a high post-therapeutic ADC mean, low skewness, and high 90th percentile proportion with respect to baseline is predictive of successfully treated UPS patients presenting > 90% PATE. Highly significant higher-order radiomic results include glrlm-highgraylevelrunemphasis (BL) and first-order-mean absolute deviation (PC).
Sinonasal Myxoma Extending into the Orbit in a 4-Year Old: A Case Presentation
Published on: 30th July, 2024
Background: Sinonasal myxomas are exceptionally rare benign tumors in pediatric patients. This report presents the case of a 4-year-old boy diagnosed with a sinonasal myxoma extending into the right orbit.Case presentation: The patient’s clinical presentation included moderate-angle esotropia and ocular torticollis. Advanced imaging revealed an expansile lesion in the right posterior ethmoid cavity with orbital involvement. The differential diagnosis considered included malignancies such as rhabdomyosarcoma and lymphoma, as well as benign neoplasms and inflammatory changes. A biopsy confirmed the diagnosis of sinonasal myxoma. The patient underwent a wide local resection performed by a multidisciplinary team, leading to a confirmed histopathological diagnosis of sinonasal myxoma.Conclusion: This case highlights the diagnostic challenges and the importance of thorough clinical and radiologic evaluation in pediatric patients with unusual ocular symptoms. The report underscores the need for a multidisciplinary approach in managing rare neoplasms such as sinonasal myxomas.
Evaluating the Pros and Cons of Evening and Weekend Outpatient Medical Imaging: Implications for Patients and Radiology Professionals
Published on: 8th August, 2024
Evening and weekend imaging services at outpatient radiology centers offer extended access to diagnostic imaging, potentially increasing patient satisfaction and accessibility, especially for underserved populations. This review explores the benefits and challenges associated with these after-hours operations, focusing on health equity, patient satisfaction, economic considerations, energy and cost savings, and the impact on healthcare professionals. Findings indicate that while after-hours operations can enhance patient satisfaction and access, they also pose challenges such as increased operational costs and staff fatigue. Strategies for improvement include optimizing shift schedules, leveraging technology for better scheduling and communication, and enhancing patient-centered care. Collaborative efforts among imaging centers can further improve service delivery and efficiency.
Imaging Challenge in Recurrent Spontaneous Coronary Artery Dissection (SCAD): A Case Report
Published on: 8th August, 2024
Spontaneous Coronary Artery Dissection (SCAD) represents a significant cause of acute coronary syndrome (ACS) in patient populations with low-risk cardiovascular profiles and, therefore can be sometimes underdiagnosed. On the other hand, it often preserves the typical clinical presentation of ACS which makes coronary artery angiography (CAG) execution mandatory. A 62-year-old woman with a history of recurrent SCAD presented to the emergency department for a new episode of acute chest pain with troponin elevation. CAG revealed an ambiguous angiography image suggesting a sub-occlusive type 2 SCAD involving the distal segment of the left circumflex artery. The patient was managed conservatively due to the absence of ongoing ischemia or hemodynamic instability. At the seven-day follow-up, a computed tomography coronary angiography (CTCA) was performed to better assess SCAD and detect concomitant associated arteriopathies. Optimized medical therapy was prescribed at the discharge and at one-month follow-up, no recurrence of symptoms was referred.
Clinical Case of Successful Therapy for the Patient with Autism by use of Fetal Stem Cells
Published on: 19th August, 2024
More than 60 million persons all over the world are living with the diagnosis of “Autism”, in accordance with the UNO. According to the WHO, almost every hundredth child is a sufferer of ASD. Such figures emphasize globalization of the problem, and its impact not only on the child’s family but also on the economies of entire countries.Autism diagnosis is difficult and based on the general symptoms in kids. Today, the neuroimaging techniques (methods of functional Magnetic Resonance Imaging (MRI) and MRI tractography), Electroencephalography (EEG), evoked cognitive potentials and dynamic monitoring of the results help with an objective evaluation of stem cell therapy.Treatment options in modern pharmacology and rehabilitation psychotherapy for ASD kids are limited. Therapy methods do not ensure a full integration into social life and personality awareness. To alleviate likely problems in society, different therapeutic approaches exist that might reduce the manifestation of the various autism symptoms. FSC therapy is one such innovative method that has recently become enough popular.We inform about the clinical case of successful treatment using fetal stem cells for a child with autism followed by the period of 1-year follow-up showing significant clinical results. Over one year, the positive changes that had been proved by the ATEC questionnaire, the EEG results, and MRI-tractography were noted by the patient’s family. As emphasized in the clinical case report, fetal stem cell therapy is a promising and efficient treatment for children with autism. All that was sufficiently confirmed by the results acquired because we saw an overall improvement in this patient.
Contrast Echocardiography for the Detection of a Giant Right Coronary Artery Aneurysm: A Useful Diagnostic Tool
Published on: 22nd August, 2024
Coronary artery aneurysm is an uncommon condition defined as abnormal dilatation of the coronary artery.We report the case of a man admitted to the Emergency Department for suspected intestinal obstruction. At abdominal/thoracic Computed Tomography (CT) it was reported a suspected pericardial cyst. Contrast echocardiography showed a clear pattern of blood flow inside the mass with a probable origin at a very limited region where it was also possible to sample an ECG-synchronized system-diastolic Pulse-Wave (PW)-Doppler pattern, typical for a coronary artery flow. Our suspicion of a giant coronary artery aneurysm was then confirmed by coronary CT and coronary angiography. The patient was transferred to a Cardiac Surgery center where he underwent surgical treatment for the aneurysm.Most coronary aneurysms are clinically silent and are often incidentally detected. Coronary angiography is the ‘‘gold standard’’ for diagnosis and evaluation of coronary artery aneurysms. Among non-invasive diagnostic techniques, Computed Tomography Coronary Angiography is the best method for coronary artery anatomy and coronary abnormalities. However, echocardiography with the use of a contrast agent, a cost-effective non-radiation nature, and a widespread use method, maybe a reliable method to detect and characterize the masses, allowing a differential diagnosis.Learning objective1. Recognition and evaluation of cardiac masses require first-line imaging methods such as echocardiography.2. The use of additional non-invasive (cardiac CT or MRI) and/or invasive imaging methods are often required. 3. Contrast echocardiography may be helpful, as second-line imaging methods, to better characterize the mass and approach the correct diagnosis.
Establishment of a Best Practice Recommendation (BPR) for Abdominal Aortic Aneurysms in a Large Multi-State Radiology Practice: Adoption and Impact
Published on: 26th August, 2024
Purpose of the study: To evaluate the performance of Best Practice Recommendation (BPR) compliance in reporting abdominal aortic aneurysm findings on imaging, comparing the results before and after its deployment.Methods: Best Practice Recommendations for AAA were deployed in 2020 at a large radiology practice site. Reports between January 2018 through October 2022 were reviewed, representing studies read prior to and subsequent to the implementation of the reporting standards. Cases of abdominal aortic aneurysms ≥ 2.6 cm were counted by year. Adherence to the BPR for each year was calculated as [total number of confirmed cases of ≥ 2.6 cm AAAs with compliant reports] * 100 / [the total number of confirmed ≥ 2.6 cm AAAs]. A secondary analysis was performed to determine whether there was a statistically significant difference in the proportion of BPR-compliant reports for AAA cases before (from 2018 to 2019) and after (from 2020 to 2022) BPR deployment using a chi-square test. Results: From January 2018 to December 2022, there were 8,693 reports referencing AAA. After excluding cases of suspected AAA (N = 2,131), confirmed AAAs with indeterminate sizes (N = 103), and confirmed AAAs with sizes < 2.6 cm (N = 85), the number of AAA cases ≥ 2.6 cm in size was 6,374. Concordance with the BPR standards for the remaining cases with sizes ≥ 2.6 cm were 1.6% and 4.1% in 2018 and 2019, respectively. Post-implementation of BPRs, there was a substantial improvement in guideline adherence to 32.1%, 84.3%, and 83.6% in 2020, 2021, and 2022, respectively. In general, the proportion of BPR-compliant reports of AAA cases in the pre-deployment (3.6%) period statistically differs (p - value < 0.0001) from those in the post-deployment period (73.9%)Conclusion: Adherence to reporting standards increased after the BPR deployment in 2020. The inclusion of management recommendations in the radiology report when AAA is identified is a simple and cost-effective way of improving outcomes for patients with AAAs through appropriate follow-up treatment.
Characteristics of Stones Ageing for Climate Resilience Due to Carbon Lifeform Environment
Published on: 24th August, 2024
The aging of stones in response to climate change and the carbon lifeform environment is a fascinating topic that highlights the resilience and adaptability of geological structures to the ever-changing conditions of our planet. Stones, as foundational components of the Earth's crust, undergo a complex process of weathering, erosion, and transformation in the face of environmental challenges such as climate change and the presence of carbon-based lifeforms. In this essay, we will explore the key characteristics of how stones age in response to these factors and the implications for climate resilience.
Development of a Web-based Tomato Plant Disease Detection and Diagnosis System using Transfer Learning Techniques
Published on: 13th September, 2024
A significant obstacle to agricultural productivity that jeopardizes the availability of food is crop diseases and farmer livelihoods by reducing crop yields. Traditional visual assessment methods for disease diagnosis are effective but complex, often requiring expert observers. Recent advancements in deep learning indicate the potential for increasing accuracy and automating disease identification. Developing accessible diagnostic tools, such as web applications leveraging CNNs, can provide farmers with efficient and accurate disease identification, especially in regions with limited access to advanced diagnostic technologies. The main goal is to develop a productive system that can recognize tomato plant diseases. The model was trained on a collection of images of healthy and damaged tomato leaves from PlantVillage using transfer learning techniques. The images from the dataset were cleansed by resizing them from 256 × 256 to 224 × 224 to match the dimensions used in pre-trained models using min-max normalization. An evaluation of VGG16, VGG19, and DenseNet121 models based on performance accuracy and loss value for 7 categories of tomatoes guided the selection of the most effective model for practical application. VGG16 achieved 84.54% accuracy, VGG19 achieved 84.62%, and DenseNet121 achieved 98.28%, making DenseNet121 the chosen model due to its highest performance accuracy. The web application development based on the DenseNet121 architecture was integrated using the Django web framework, which is built on Python. This enables real-time disease diagnosis for uploaded images of tomato leaves. The proposed system allows early detection and diagnosis of tomato plant diseases, helping to mitigate crop losses. This supports sustainable farming practices and increases agricultural productivity.
Obesity in Patients with Chronic Obstructive Pulmonary Disease as a Separate Clinical Phenotype
Published on: 19th September, 2024
Chronic obstructive pulmonary disease (COPD) is a heterogeneous, progressive disease characterized not only by pathological changes in the lungs but also by significant extrapulmonary manifestations and serious concomitant diseases. The current problem for the study is the features of the relationship between COPD and adipose tissue since there are contradictory data in the literature. This review presents studies that claim that obesity aggravates the course of COPD, as well as the results of studies that describe the “obesity paradox” in patients with COPD. Due to the lack of unambiguous data, it is necessary to continue studying this problem to optimize the tactics of managing this group of patients and draw up clear recommendations for patients with COPD.
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