aging

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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

Verrucous hyperplasia is a wart-like lesion that can develop on amputation stumps, often due to poor-fitting prostheses, venous stasis, friction, and bacterial infections. While surgical excision is sometimes necessary for intractable cases, many instances can be managed non-surgically. We present the case of a 35-year-old male with a slowly growing verrucous plaque on his amputated stump that had caused repeated infections. His prosthesis was loose, allowing the stump to hang loosely inside the socket. After histological confirmation of verrucous hyperplasia, he was advised to change his prosthesis and use compression bandaging. Over 5 months, the lesion resolved without surgery. Early recognition and non-surgical management, including proper prosthetic fit, compression, and hygiene, can often successfully treat verrucous hyperplasia of amputation stumps. This avoids the need for excision in many cases. Patients and clinicians should be aware of this condition and the importance of prosthetic fit and limb care to prevent and treat it.

Background: Non-Communicable Diseases (NCDs) in India have increased from 37.9% in 1990 to 61.8% in 2016. They are slowly progressive are of long duration and are responsible for more than 50% of the global burden of disease Very few studies have been conducted that studied the prevalence of risk factors in non-communicable diseases among medical students. The authors observed that most of the students are at risk of developing NCDs, and the cumulative effect of risk factors bundles up and eventually leads to disease as students advance through their lives.Aim and objectives: (i) To estimate the prevalence of risk factors of NCD amongst medical students, (ii) To study the association between various risk factors and NCDs in study subjects.Settings and design: A cross-sectional analytical study involving 362 undergraduate students of Rama Medical College using simple random sampling.Material and methods: The study used a pretested structured questionnaire which was conducted by using the WHO NCD steps approach.Statistical analysis used: Data analysis was done by using M S Excel and software SPSS version 26.Results: Our study results showed that physical activity is Prevalent in female students at 51% and in male students at 48.9%, almost equal. Junk food consumption had an overall prevalence of 69.34% of females outnumbering males in junk food consumption. The association of BMI with NCD as a risk factor was statistically significant in the current 75 smokers only.Conclusion: There is a huge opportunity to reduce modifiable risk factors and NCD among our future doctors by encouraging them to change their behavior-related lifestyles such as smoking habits, alcohol use, junk food, etc.

This article examines the relationship between Premenstrual Dysphoric Disorder (PMDD), neurovascular dynamics, and sensory sensitivities in autistic women during menstruation. The redirection of blood flow to the uterus during the menstrual cycle has been found to exacerbate cerebral perfusion deficits in neurodivergent individuals, particularly in the Prefrontal Cortex (PFC), which contributes to the mood dysregulation and emotional instability characteristic of PMDD. Autistic women, who often exhibit heightened sensory sensitivities, experience intensified discomfort during menstruation, as sensory overload and altered pain perception compound the emotional challenges of PMDD. These findings emphasize the need for neurodivergent-friendly menstrual products that mitigate both physical and emotional discomfort. Additionally, innovations using biodegradable materials, smart fabrics, and custom-fit menstrual solutions are discussed as potential breakthroughs to improve the quality of life for autistic women managing PMDD. This research highlights the importance of addressing both neurobiological and sensory aspects when designing interventions for PMDD in neurodivergent populations.

Venous Thromboembolism (VTE) is a major public health concern, affecting approximately 900,000 people annually in the United States. In rare cases, a Patent Foramen Ovale (PFO) may allow a venous thrombus to cross into the arterial circulation, causing a paradoxical embolism. This case report presents a 46-year-old male who developed left renal artery stenosis after a paradoxical embolism, likely triggered by a prolonged flight and binge alcohol consumption. The patient was found to have a moderate-sized PFO and renal infarction, confirmed by imaging studies. Despite initial anticoagulation therapy and a planned stenting procedure, intraoperative findings revealed only mild stenosis, leading to cancellation of the stent placement. The patient ultimately underwent PFO closure with an Amplatzer Talisman device. This case underscores the diagnostic challenges in managing paradoxical embolism and the need for individualized treatment, particularly concerning anticoagulation duration, the decision for PFO closure, and post-procedural antithrombotic therapy. Further research is required to establish optimal management strategies for cryptogenic embolic events.

Pneumomediastinum (mediastinal emphysema) is an uncommon condition characterized by the accumulation of air or gas in the mediastinum. Here is a case of a 16-year-old female known to have depression who presented to the emergency department with complaints of shortness of breath, restlessness, chest discomfort, and hoarseness of voice for 2 days. She was initially diagnosed with panic attack, and later on clinical examination, surgical emphysema over the right supraclavicular area was noticed. Chest X-ray was found to be normal, and further imaging with high-resolution computed tomography (HRCT) of the thorax showed pneumomediastinum. In this report, the clinical presentations, radiological features, and management of pneumomediastinum will be discussed.

To expand the spectrum of used radiopharmaceuticals, it is proposed to obtain a positron-emitting isotope of technetium 94mTc. The intention of this work is to research the possibility of producing various technetium isotopes on a medical cyclotron. For this purpose, we carried out a series of irradiations of an aqueous solution of molybdenum of natural isotopic composition with protons of 11 MeV energy. After technetium isolation, results were analyzed on a γ-spectrometer. 511 keV gamma-ray line was obtained.

Calorie restriction has been shown to slow the aging process in numerous organisms including primates. Caloric excess states, such as type 2 diabetes, are associated with accelerated aging and the incidence and severity of chronic diseases. The nutrient-sensing pathways and intestinal microbiome are important systems that affect aging and chronic disease development. This manuscript reviews the various pathways involved with aging and chronic disease development and examines the pharmacological manipulation of these systems which appear to slow aging and the chronic diseases of aging in experimental model organisms and collaborating human data when available. Finally, the abundance of experimental and human data suggesting the newer diabetic medications, the sodium-glucose transport inhibitors, are potent anti-aging agents is provided.