Aid In Planning Research Articles

Development of a Block-Scale Spatial Flood Vulnerability Index—Case Study: Morelia, Mexico

The study of urban floods is increasingly crucial due to their growing frequency and impact on densely populated areas, often characterized by inadequate drainage and located in flood-prone zones. The consequences extend beyond physical damage, significantly affecting economies and livelihoods, necessitating substantial economic resources for recovery and infrastructure rebuilding. Urban planning now must integrate flood risk management, emphasizing not only infrastructural resilience but also comprehensive policies that address environmental and social vulnerabilities to better prepare and protect urban environments against future flood risks. This study addresses the critical issue of urban flood vulnerability through a focused analysis of Morelia, a city known for its susceptibility to flooding due to its geographical and hydrological characteristics and accelerated urban growth. Employing a multifaceted approach that integrates hydrological, socio-economic, and land use data within a Geographic Information Systems (GIS) framework, the research develops a Spatial Flood Vulnerability Index (SFVI). This index is meticulously applied at the urban block level, offering a precise mapping of flood risks across the city. By correlating the SFVI results with historical flood data, the study identifies the most vulnerable areas in Morelia, which are primarily impacted due to their proximity to water bodies, economic density, and infrastructural settings. The methodology not only highlights immediate flood risks but also aids in strategic urban planning to enhance resilience against future flooding events. This paper contributes a novel approach to flood risk assessment, providing a replicable model for similarly affected cities worldwide, aiming to balance structural measures with strategic planning tailored to local needs.

Transmission line sag and magnetic field analysis with sag parabolic equations and Biot-Savart law

This study presents a novel approach to enhance the precision of calculating sag and magnetic fields beneath overhead transmission lines. The Biot-Savart law is integrated with parabolic equations to assign multiple magnetic field sources to each conductor, resulting in improved prediction accuracy. Addressing oversimplifications in traditional models improves the analysis of transmission lines in real-world scenarios. An analysis was performed using MATLAB and Simulink to validate the effectiveness and broad applicability of different configurations. The results demonstrated a significant improvement in precision compared to traditional methods, indicating that this approach has the potential to establish new benchmarks in the field. This methodology makes significant contributions to electromagnetic studies, offering engineers a reliable tool for designing transmission systems that are both safer and more efficient. This advancement in electrical engineering greatly improves transmission network performance by enhancing sag and magnetic field prediction accuracy. This aids in better maintenance planning and reduces outage risks, resulting in more efficient operations and improved overall performance.

Association Between Zinc Levels and the Impact of Its Deficiency on Idiopathic Male Infertility: An Up-to-Date Review

Background: Zinc (Zn) is an essential metal that plays a critical role in normal testicular development, spermatogenesis, prevention of sperm degradation, and overall male fertility. This review aims to offer a comprehensive and current overview of seminal plasma Zn levels in fertile men worldwide. It also aims to compare Zn levels in seminal plasma and blood (serum/plasma) between infertile men (cases) and fertile men (controls), examine the impact of Zn on sperm quality and the reproductive hormone, and highlight the effects of Zn supplementation therapy in male infertility. Methods: To achieve these goals, peer-reviewed studies from 2000 to 2024 were interrogated with regard to strict inclusion/exclusion criteria and were then thoroughly reviewed and analyzed. Results: Our findings indicate that maintaining optimal seminal plasma Zn levels is crucial, as low Zn levels are linked to impaired spermatogenesis and male infertility, while high Zn levels can cause oxidative stress and other changes that contribute to infertility. Seminal plasma Zn levels from 100 to 200 mg/L among fertile men worldwide can be roughly considered safe. Comparative analysis showed that a greater number of studies reported lower levels of seminal Zn in cases than in controls. Research into the impact of Zn levels in seminal plasma has shown that, although the results are not yet conclusive, altered (non-normal) Zn levels could influence semen parameters—particularly motility, morphology, and sperm count—and the level of the reproductive hormone, testosterone. Zinc-deficient infertile men could benefit from supplement therapy. Conclusions: Assessment of seminal plasma Zn levels in infertile men could provide valuable information and aid in diagnosis and treatment planning.

Artificial Intelligence in Dentistry - A Review Article

The ability of machines to carry out tasks that often call for human intelligence is known as artificial intelligence (AI). Big data (which comes from digital devices), processing power, and AI algorithms are the three pillars of modern AI technology that have developed quickly over the past 20 years. As a result, AI applications have begun to make people's lives more convenient. AI has enormous potential to influence dentistry in the future. AI has the potential to revolutionize dentistry practice and greatly improve patient outcomes through its capacity to analyze enormous volumes of data, provide precise diagnoses, aid in treatment planning, enhance image analysis, expedite patient management and provide individualized care. Keywords: Artificial intelligence (AI), Dentistry, Diagnosis, Treatment planning

68Ga-DOTATATE PET/CT in the Initial Staging of Well-Differentiated Gastroenteropancreatic and Non-Gastroenteropancreatic Neuroendocrine Tumors: Results of a Prospective Registry

Background and Objectives: At diagnosis, the initial staging of well-differentiated neuroendocrine tumors (WD NETs) aids in treatment planning. The somatostatin receptor (SSTR)-PET has been recommended for staging of WD NETs although limited data are available on its impact on non-gastroeneteropancreatic (GEP) NETs. The main purpose of this study was to compare the stage migration after the addition of SSTR-PET to the workup of patients at the initial staging of GEP NETs to those with non-GEP NETs, and its potential impact on patient management. Methods: This prospective study included patients with WD NETs at initial staging. Demographic data, results of conventional and SSTR-PET staging, and SUVmax were recorded. Three panels of experts assessed the potential impact of SSTR-PET to management. Results: There were 482 patients, including 376 with gastroenteropancreatic (GEP) NETs and 106 non-GEP NETs with a median SUVmax of 34.7 [Q1, Q3: 22.8, 59.1]) and 19.0 [Q1, Q3: 7.9, 39.8]), respectively; p < 0.001. The discordant M-stage was recorded in 111/473 patients (23.5%). PET suggested a higher stage in 78/369 GEP NETs (21.1%), including the detection of extrahepatic metastatic disease in 42/114 (36.8%) patients with liver metastases only on CI. For non-GEP NETs, PET suggested a higher stage in 10/104 (9.6%) and CI suggested a higher stage in 15/104 (14.4%), with CI detecting liver metastases more frequently. The potential impact to management for patients with discordant M-stage was scored as moderate to high between 57/101 (56.4%) and 79/101 (78.2%) of patients. Conclusions: One in five patients are upstaged following SSTR-PET, more frequently with GEP NETs than others. SSTR-PET identifies extrahepatic metastatic disease in >1/3 of patients with presumed liver-only metastases on CI. Stage migration following SSTR-PET may result in frequent moderate or significant management change.

D-MGDCN-CLSTM: A Traffic Prediction Model Based on Multi-Graph Gated Convolution and Convolutional Long-Short-Term Memory.

Real-time and accurate traffic forecasting aids in traffic planning and design and helps to alleviate congestion. Addressing the negative impacts of partial data loss in traffic forecasting, and the challenge of simultaneously capturing short-term fluctuations and long-term trends, this paper presents a traffic forecasting model, D-MGDCN-CLSTM, based on Multi-Graph Gated Dilated Convolution and Conv-LSTM. The model uses the DTWN algorithm to fill in missing data. To better capture the dual characteristics of short-term fluctuations and long-term trends in traffic, the model employs the DWT for multi-scale decomposition to obtain approximation and detail coefficients. The Conv-LSTM processes the approximation coefficients to capture the long-term characteristics of the time series, while the multiple layers of the MGDCN process the detail coefficients to capture short-term fluctuations. The outputs of the two branches are then merged to produce the forecast results. The model is tested against 10 algorithms using the PeMSD7(M) and PeMSD7(L) datasets, improving MAE, RMSE, and ACC by an average of 1.38% and 13.89%, 1% and 1.24%, and 5.92% and 1%, respectively. Ablation experiments, parameter impact analysis, and visual analysis all demonstrate the superiority of our decompositional approach in handling the dual characteristics of traffic data.

A Robotic Flutist Framework for Exploring Acoustics, Human—Instrument Interaction, and Musical Creation

Abstract This article introduces an experimental robotic setup designed to investigate the performance and sound production of flutes. The flute, renowned for its intricate mechanism enabling musicians to dynamically adjust various parameters, yields a diverse range of rich sounds. A key feature of the flute involves the embouchure—the shaping of the air channel by the musician's lips—providing control over airflow, velocity, distance to the labium, inclination, and position. The robotic testbed manipulates critical parameters of the sound-producing system, incorporating an artificial mouth and a motorized mechanism for adjusting jet length, incident angle, and offset. Specialized software aids in route planning, visualization, and description of the controllable parameter trajectories, also generating automatic positions based on a predefined dictionary. Experimental findings showcase the robot's proficiency in playing simple melodies and producing harmonically rich sounds within the specified range. Spectrogram analysis reveals successful reproduction of intended pitches and timbres. This robotic testbed emerges as a valuable tool for delving into the acoustics of the flute and the interaction between performers and flutes. It provides a robust platform for composers to create music that surpasses normal human capabilities and contributes to the comprehension and design of these intricate instruments.

Performance and Analysis of FCN, U-Net, and SegNet in Remote Sensing Image Segmentation Based on the LoveDA Dataset

Remote sensing image segmentation is a vital method in image analysis that significantly contributes to the extraction of surface information and aids in land use planning. This study utilizes the LoveDA dataset to investigate the segmentation performance of three classic deep learning models: Fully Convolutional Networks(FCN), U-Net, and SegNet, in both urban and rural scenarios. By partitioning the Urban-Rural dataset of LoveDA for training and testing, it was determined that SegNet excels in detail restoration and boundary handling, while U-Net demonstrates robust adaptability across various scenarios. In contrast, FCN, with its simpler architecture, shows lower segmentation accuracy in certain contexts. This paper offers a comprehensive comparison of the strengths and weaknesses of different models in remote sensing image segmentation and proposes enhancements in model structure and data preprocessing optimization. The findings provide valuable insights for improving the performance of semantic segmentation models and are of significant importance for the precise analysis and practical applications of remote sensing images.

Preoperative surgical planning MRI for fibroids: What the surgeon needs to know and what to report.

Uterine leiomyomata, commonly known as fibroids, are prevalent benign tumours affecting a significant percentage of women of reproductive age. Although many patients remain asymptomatic, a substantial proportion experience severe symptoms, including abnormal uterine bleeding and adverse reproductive outcomes. Surgical intervention often becomes necessary for patients with symptomatic fibroids, despite advancements in medical therapies. This article explores the critical role of Magnetic Resonance Imaging (MRI) in the preoperative planning and management of fibroid surgeries. MRI has been proven superior to traditional imaging methods, such as transvaginal ultrasound (TVS), offering a more accurate evaluation of fibroid size, location, number, and characteristics. This enhanced imaging aids in surgical planning by providing detailed anatomical insights, helping gynaecologists choose the appropriate surgical techniques and predict potential complications. Moreover, MRI is instrumental in assessing the risk of malignancy, guiding decisions onwhether to proceed with myomectomy or hysterectomy. Technological advancements, such as 3D MRI modelling and augmented reality, promise further improvements in surgical outcomes by enhancing anatomical understanding and precision. These innovations, along with artificial intelligence integration, show potential in reducing operation times and improving patient outcomes. This review underscores the essential role of MRI in contemporary fibroid management and highlights future directions in the field.

Endosonography in head and neck imaging and surgery.

This CME article explores the evolving role of endosonography in otorhinolaryngology and head and neck surgery. Endosonography offers significant potential to improve imaging inside the upper respiratory tract, particularly with advancements in probe technology and imaging resolution. Thearticle will describe the sonoanatomy of the oral cavity, pharynx, and larynx and the selection of probes and scanning techniques used for the various anatomical sites. Transoral ultrasound can be used to improve the diagnosis of salivary gland diseases, oropharyngeal abscesses, and ultrasound-guided puncture and biopsy. Endoscopic endolaryngeal ultrasound is used especially for diagnosing small laryngeal cancer and determining infiltration status. The article highlights the role of endosonography in managing oncologic diseases, especially in oral tongue carcinoma, where it aids in surgical planning by assessing the depth of invasion. In cases of HPV-positive carcinoma of unknown primary, high-frequency endosonography is crucial for detecting small tumors in the oropharyngeal region. In summary, the article advocates the broader integration of endosonography in clinical practice, highlighting its potential to enhance diagnostic accuracy and improve patient outcomes in head and neck oncology.

UNDERSTANDING SATTVA PAREEKSHA– A COMPREHENSIVE CLINICAL GUIDE TO MENTAL STATUS EVALUATION

Ayurveda, an ancient system of medicine, considers human existence as dependent on the harmonious interac-tion of Shareera (body), Indriya (senses), Sattva (psychic strength) and Atma (spirit). Which Sattva component influences health and illness. Sattva, representing psychic strength (Sattva Bala), bridges the connection between body and soul, facilitating normal sensory function. The assessment of Sattva Bala, crucial in clinical practice, aids in diagnosis, treatment planning and prognostic evaluation by determining an individual's resilience and coping abilities. Therefore, integrating Sattva assessment, including Manasika Bhava evaluation, into clinical protocols is essential to optimise treatment efficacy. Individuals with higher Sattva Gunas demonstrate superior coping abilities, influencing their overall mental well-being and treatment response. According to the National Mental Health Survey of India (2015-16), the prevalence of mental disorders in India is estimated to be around 10-12% of the population. Sattva Bala is important for all individuals who are carrying out any activity, and it can also be assessed in pathological conditions. Whether the pathological condition is related to bodily or psy-chological factors, there will be a disturbance in the sattva that needs to be examined. A non-randomized, cross-sectional survey was conducted across 220 subjects to elicit the significance of Sattva Pareeksha among clini-cians. Discussion was done based on the importance of Sattva Pareeksha and uses of Sattva Pareeksha in clinical practice. This paper aims to critically analyse the concept of Sattva Pareeksha as depicted in Ayurvedic litera-ture, advocating for its systematic integration into clinical protocols to enhance patient care and treatment out-comes. So, in this study, analysis of the role of Sattva Pareeksha in clinical practice will be done.

Tampa difficulty score: a scoring system for difficulty of robotic pancreaticoduodenectomy.

Robotic platforms are increasingly utilized in surgery, offering unique technical advantages, though there is a scarcity of difficulty scoring systems (DSS) for these procedures. DSS aids in understanding operative complexities and enhancing preoperative planning. With IRB approval, data were collected on 200 consecutive adult patients who underwent robotic pancreaticoduodenectomy at a high-volume institution from 2019 to 2022. Linear regression was employed on clinical variables to analyze operative time and estimated blood loss as markers of surgical complexity. Weighted scoring system was developed using significant linear coefficient values, and an ANOVA analysis created the difficulty-level grouping system. Significant variables affecting operative time and/or EBL included: history of alcoholism, preoperative endoscopic intervention, tumor size, nodal disease on preoperative imaging, pancreatic duct dilation. These factors created the DSS ranging from 0 to 33. Group 1 (0-8, n = 9), Group 2 (9-20, n = 145), Group 3 (21-26, n = 37), and Group 4 (27-33, n = 9) showed significant differences in age, history of alcoholism, preoperative jaundice, tumor size, nodal disease, and operative metrics. Our novel DSS for robotic pancreaticoduodenectomy effectively predicts intraoperative challenges and aids in preoperative planning. Future steps include validating the system internally and externally.

SWOT analysis of e-library initiatives in Punjab, Pakistan: perspectives from library and information science professionals

Purpose This study aims to meticulously examine the current state and operational dynamics of e-libraries in Punjab, Pakistan. Using a qualitative research methodology and strength, weakness, opportunities and threats (SWOT) analysis as a principal analytical framework, the study seeks to capture a detailed portrait of these digital repositories. The goal is to uncover the strengths, weaknesses, opportunities and threats associated with the e-libraries. Design/methodology/approach A qualitative research approach was chosen to gain deeper insights into the e-libraries in Punjab. The study involved conducting detailed interviews with 14 librarians from these e-libraries, an interview guide that was developed specifically for this study. The guide was refined by experts and validated in a pilot study. Findings The study reveals that e-libraries in Punjab, Pakistan, excel in providing access to diverse digital resources and enhancing digital literacy but face significant challenges related to infrastructure, hardware and digital skills. Opportunities exist in leveraging mobile technology and enhancing staff training to improve service delivery. However, financial constraints, inadequate skilled personnel and regulatory issues pose threats to their efficacy and sustainability. Practical implications This study offers key recommendations for improving Punjab’s e-libraries, such as upgrading infrastructure, enhancing staff training and bolstering cybersecurity. It stresses the need for sustained government funding and support. The findings can help librarians boost digital literacy, refine resources and increase community involvement, while guiding policymakers in shaping effective legal frameworks and practitioners in enhancing resource quality and access. Social implications This research highlights the transformative potential of e-libraries in fostering education and culture in Punjab. It emphasizes integrating technology with community and government support to maximize benefits, bridge digital divides and promote social equity. The study calls for ongoing collaboration among librarians, educators and policymakers to harness e-libraries as catalysts for social change and development. Originality/value The originality of this study stems from its innovative application of SWOT analysis to e-libraries in Punjab, a first in this context. This approach not only offers new insights into the operational strengths, weaknesses, opportunities and threats of e-libraries but also significantly aids in strategic planning. The findings are pivotal in shaping decisions that foster the effective use of e-libraries, ultimately enhancing digital literacy and educational growth across the region.

Prediction and Management of Small-for-Size Syndrome in Living Donor Liver Transplantation.

Small-for-Size Syndrome (SFSS) remains a critical challenge in living donor liver transplantation (LDLT), characterized by graft insufficiency due to inadequate liver volume, leading to significant postoperative morbidity and mortality. As the global adoption of LDLT increases, the ability to predict and manage SFSS has become paramount in optimizing recipient outcomes. This review provides a comprehensive examination of the pathophysiology, risk factors, and strategies for managing SFSS across the pre-, intra-, and postoperative phases. The pathophysiology of SFSS has evolved from being solely volume-based to incorporating portal hemodynamics, now recognized as Small-for-Flow Syndrome. Key risk factors include donor-related parameters like age and graft volume, recipient-related factors such as MELD score and portal hypertension, and intraoperative factors related to venous outflow and portal inflow modulation. Current strategies to mitigate SFSS include careful graft selection based on graft-to-recipient weight ratio and liver volumetry, surgical techniques to optimize portal hemodynamics, and novel interventions such as splenic artery ligation and hemiportocaval shunts. Pharmacological agents like somatostatin and terlipressin have also shown promise in modulating portal pressure. Advances in 3D imaging and artificial intelligence-based volumetry further aid in preoperative planning. This review emphasizes the importance of a multifaceted approach to prevent and manage SFSS, advocating for standardized definitions and grading systems. Through an integrated approach to surgical techniques, hemodynamic monitoring, and perioperative management, significant strides can be made in improving the outcomes of LDLT recipients. Further research is necessary to refine these strategies and expand the application of LDLT, especially in challenging cases involving small-for-size grafts.

Geospatial analysis of sports tourism resources in China's urban clusters: a case study of the Sichuan-Chongqing region utilizing GIS and the geographic detector

IntroductionThis study aims to elucidate the temporal and spatial distribution patterns of sports tourism resources within the Sichuan-Chongqing Urban Agglomeration, examining how these distributions reflect the developmental pathways of urban regions. The theoretical framework posits that the availability and allocation of sports tourism resources are influenced by various geographical and socio-economic factors, with topography, economic conditions, and population density playing pivotal roles in determining their distribution and development.MethodsUtilizing GeoDetector technology alongside indices such as the Geographic Concentration Index and the Disparities Index, we conducted a comprehensive analysis of the spatiotemporal dynamics of sports tourism resources, revealing that the distribution of these resources serves as a key indicator of urban development speed.ResultsOur findings indicate that topographical features significantly influence sports tourism resource development differently in Chengdu compared to Chongqing. Furthermore, we identified a strong positive correlation between population density and the distribution of sports tourism resources, highlighting the motivational role of populated areas and emphasizing potential inequalities if attention is focused solely on densely populated regions.DiscussionThis research provides novel insights into the complex relationships governing sports tourism resource distribution by employing advanced geo-analytical tools. It offers a strategic roadmap for equitable and sustainable urban development by addressing disparities in resource allocation, ultimately contributing to informed policy-making and enhanced regional resilience. This research aids in the strategic planning and sustainable development of sports tourism, providing a blueprint for urban development in the region that balances the needs of diverse populations and landscapes.

Role of eXtended Reality use in medical imaging interpretation for pre-surgical planning and intraoperative augmentation.

eXtended Reality (XR) technology, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), is a growing field in healthcare. Each modality offers unique benefits and drawbacks for medical education, simulation, and clinical care. We review current studies to understand how XR technology uses medical imaging to enhance surgical diagnostics, planning, and performance. We also highlight current limitations and future directions. We reviewed the literature on immersive XR technologies for surgical planning and intraoperative augmentation, excluding studies on telemedicine and 2D video-based training. We cited publications highlighting XR's advantages and limitations in these categories. A review of 556 papers on XR for medical imaging in surgery yielded 155 relevant papers reviewed utilizing the aid of chatGPT. XR technology may improve procedural times, reduce errors, and enhance surgical workflows. It aids in preoperative planning, surgical navigation, and real-time data integration, improving surgeon ergonomics and enabling remote collaboration. However, adoption faces challenges such as high costs, infrastructure needs, and regulatory hurdles. Despite these, XR shows significant potential in advancing surgical care. Immersive technologies in healthcare enhance visualization and understanding of medical conditions, promising better patient outcomes and innovative treatments but face adoption challenges such as cost, technological constraints, and regulatory hurdles. Addressing these requires strategic collaborations and improvements in image quality, hardware, integration, and training.

Characteristics of High-Risk Bipolar Bone Loss Lesions Using 3-Dimensional Imaging.

The concept of on-track versus off-track bone lesions in glenohumeral instability continues to evolve. Although much has been ascertained from an original biomechanical model, bony pathological changes, especially on 3-dimensional (3D) imaging, have not been fully evaluated. To compare the differences in on-track versus off-track lesions to characterize glenoid and humeral head bone defects using 3D modeling software. Cross-sectional study; Level of evidence, 3. A consecutive cohort of 75 patients with recurrent anterior instability, with evidence of Hill-Sachs lesions (HSLs) and glenoid bone loss (GBL) and a mean age of 27.1 years (range, 18-48 years), were reviewed. 3D models of unilateral proximal humeri and glenoids were reconstructed. The volume, surface area, width, and depth of identified HSLs were quantified, along with their location (medial, superior) and orientation (Hill-Sachs angle). The percentage, width, and length of GBL as well as the glenoid track status were calculated. The on-track and off-track groups were compared using the Mann-Whitney U test. The off-track group had greater HSL surface area (374.23 vs 272.64 mm2, respectively; P = .001), more HSL medialization (14.96 vs 17.62 mm, respectively; P = .028), greater HSL volume (603.08 vs 433.61 mm3, respectively; P = .007), and a greater mean HSL width (16.06 vs 11.53 mm, respectively; P = .001) than the on-track group. The off-track group also had greater GBL (22.55% vs 17.73%, respectively; P = .037), a greater GBL width (6.92 vs 3.58 mm, respectively; P < .001), and a greater GBL length (21.61 vs 16.1mm, respectively; P = .015) than the on-track group. Further analysis of large off-track lesions revealed a greater Hill-Sachs angle (33.16° vs 26.20°, respectively; P = .035) and a more superior extent of HSLs compared with borderline off-track and on-track lesions. Off-track lesions were found to have larger GBL, a larger HSL width, a more medialized HSL, and greater HSL surface area. This study outlines the specific characteristics of high-risk bipolar bone loss lesions to simplify the identification of patients in a clinical setting and aid in appropriate treatment planning.

Integration of cone beam computed tomography for interdisciplinary diagnosis and treatment planning

Cone-beam computed tomography (CBCT) has revolutionized dental imaging by providing precise three-dimensional visualization of hard tissue structures with minimal radiation exposure compared to conventional CT. This review explores the integration of CBCT in interdisciplinary diagnosis and treatment planning across various fields of dentistry. CBCT offers versatile applications including assessment of impacted teeth, airway analysis, temporomandibular joint evaluation, detection of jaw pathologies, and precise diagnosis of dento-maxillofacial fractures. Its ability to generate static and rotational 3D images aids in surgical planning and treatment outcome prediction. Furthermore, CBCT plays a crucial role in orthodontics for localization of impacted teeth and evaluation of craniofacial anomalies such as cleft lip and palate. In periodontics and implantology, CBCT facilitates detailed assessment of periodontal structures, bone defects, and precise implant placement. Additionally, CBCT assists in maxillofacial prosthetics by enabling virtual surgical planning and custom prosthetic fabrication. This paper underscores CBCT as an indispensable tool in modern dental practice, enhancing diagnostic accuracy, treatment precision, and patient outcomes across diverse clinical scenarios.

Vegetation Recovery Patterns at Jeongseon Alpine Stadium, Mount Gariwang, in the Republic of Korea, After the PyeongChang 2018 Winter Olympics

This study assessed vegetation recovery at Jeongseon Alpine Stadium, Mt. Gariwang, 5 years after the 2018 PyeongChang Winter Olympics to aid in restoration planning. A total of 50 quadrats were surveyed across undisturbed areas, forest edges, and damaged areas at different altitudes. Species occurrences were recorded using a tabulation method to identify characteristic and differential species based on disturbance type. Importance value analysis showed that tree layers were present only in undisturbed areas at all altitudes, while shade-intolerant species, such as Amur choke cherry (P. glandulifolia), had high importance in the subtree layer in low-altitude damaged areas and mid-altitude forest edges. Species diversity was higher in forest edges at medium and high altitudes, whereas control areas exhibited higher diversity at low altitudes. DCA ordination revealed distinct community groupings based on altitude and disturbance type, indicating community heterogeneity. The study found rapid vegetation recovery in damaged areas and forest edges, driven by shade-intolerant species. Restoration efforts should prioritize these species to support successful recovery.

Clinical, Laboratory, and Molecular Characteristics of Inherited Vitamin K-Dependent Coagulation Factors Deficiency.

Vitamin K-dependent coagulation factors deficiency (VKCFD) is a rare autosomal recessive genetic disease characterized by impaired levels of multiple coagulation factors (II, VII, IX, and X) and natural anticoagulants (proteins C and S). VKCFD is part of familial multiple coagulation factor deficiencies, reporting overall 50 affected families thus far. Disease manifestations are quite heterogeneous, bleeding symptoms may vary, and even, although generally mild, some patients may succumb to fatal outcomes. VKCFD diagnosis may be delayed because the disease phenotype simulates the most frequently acquired deficiencies of vitamin K. First-line coagulation assays, prothrombin time/international normalized ratio (PT/INR) and activated partial thromboplastin time (aPTT), are both prolonged; mixing test typically normalizes the clotting times; and vitamin K-dependent coagulation factors will be variably decreased. Molecularly, VKCFD is associated with mutations in γ-glutamyl-carboxylase (GGCX) or vitamin K epoxide reductase complex subunit 1 (VKORC1) genes. Vitamin K is involved not only in the biosynthesis of coagulation proteins but also in bone metabolism and cell proliferation. Therapeutic options are based on vitamin K supplementation, coagulation factors (prothrombin complex), and fresh frozen plasma, in case of severe bleeding episodes. Two case studies here illustrate the diagnostic challenges of VKCFD: case 1 depicts a woman with a history of bleeding episodes, diagnosed, only in her third decade of life with inherited homozygous GGCX gene mutation. Case 2 shows a man with an acquired vitamin K deficiency caused by Crohn's disease. Better understanding of GGCX and VKORC1 mutations aids in prognosis and treatment planning, with emerging insights suggesting potential limitations in the effectiveness of vitamin K supplementation in certain mutations.