The geographical distribution of the family-genetic risk score for drug use disorder in Sweden and its co-localization with areas of social deprivation.

Background: Drug use Disorder (DUD), the risk for which is substantially influenced by both genetic and social factors, is geographically concentrated in high-risk regions. An important step toward understanding this pattern is to examine geographical distributions of the genetic liability to DUD and a key demographic risk factor - social deprivation.

Methods: We calculated the mean family genetic risk score (FGRS) for DUD ((FGRS) and social deprivation for each of the 5983 areas Demographic Statistical Areas (DeSO) for all of Sweden and used geospatial techniques to analyze and map these factors.

Women's exposure to intimate partner violence and its association with child stunting: findings from a population-based study in rural Rwanda.

Background: Child stunting is a significant challenge for most districts in Rwanda and much of sub-Saharan Africa and persists despite multisectoral efforts. There is a notable lack of population-based studies examining the correlation between violence against women and child stunting in Rwanda.

Objective: We aimed to investigate the association between Rwandan women's exposure to intimate partner violence (IPV) and child stunting in children under 3 years of age.

Deep spectral improvement for unsupervised image instance segmentation.

Recently, there has been growing interest in deep spectral methods for image localization and segmentation, influenced by traditional spectral segmentation approaches. These methods reframe the image decomposition process as a graph partitioning task by extracting features using self-supervised learning and utilizing the Laplacian of the affinity matrix to obtain eigensegments. However, instance segmentation has received less attention than other tasks within the context of deep spectral methods.

Spatial Machine Learning for Exploring the Variability in Low Height-For-Age From Socioeconomic, Agroecological, and Climate Features in the Northern Province of Rwanda.

Childhood stunting is a serious public health concern in Rwanda. Although stunting causes have been documented, we still lack a more in-depth understanding of their local factors at a more detailed geographic level. We cross-sectionally examined 615 height-for-age prevalence observations in the Northern Province of Rwanda, linked with their related covariates, to explore the spatial heterogeneity in the low height-for-age prevalence by fitting linear and non-linear spatial regression models and explainable machine learning.

How do taxi drivers expose to fine particulate matter (PM) in a Chinese megacity: a rapid assessment incorporating with satellite-derived information and urban mobility data.

Background: Taxi drivers in a Chinese megacity are frequently exposed to traffic-related particulate matter (PM) due to their job nature, busy road traffic, and urban density. A robust method to quantify dynamic population exposure to PM among taxi drivers is important for occupational risk prevention, however, it is limited by data availability.

Methods: This study proposed a rapid assessment of dynamic exposure to PM among drivers based on satellite-derived information, air quality data from monitoring stations, and GPS-based taxi trajectory data.

How do household living conditions and gender-related decision-making influence child stunting in Rwanda? A population-based study.

Child stunting (chronic undernutrition) is a major public health concern in low- and middle-income countries. In Rwanda, an estimated 33% of children are affected. This study investigated the household living conditions and the impact of gender-related decision-making on child stunting.

Childhood stunting is highly clustered in Northern Province of Rwanda: A spatial analysis of a population-based study.

Background: In Northern Province, Rwanda, stunting is common among children aged under 5 years. However, previous studies on spatial analysis of childhood stunting in Rwanda did not assess its randomness and clustering, and none were conducted in Northern Province. We conducted a spatial-pattern analysis of childhood undernutrition to identify stunting clusters and hotspots for targeted interventions in Northern Province.

A Review of micro RNAs changes in T2DM in animals and humans.

Type 2 diabetes mellitus (T2DM) and its associated complications have become a crucial public health concern in the world. According to the literature, chronic inflammation and the progression of T2DM have a close relationship. Accumulated evidence suggests that inflammation enhances the insulin secretion lost by islets of Langerhans and the resistance of target tissues to insulin action, which are two critical features in T2DM development.

Understanding the spatial non-stationarity in the relationships between malaria incidence and environmental risk factors using Geographically Weighted Random Forest: A case study in Rwanda.

As found in the health studies literature, the levels of climate association between epidemiological diseases have been found to vary across regions. Therefore, it seems reasonable to allow for the possibility that relationships might vary spatially within regions. We implemented the geographically weighted random forest (GWRF) machine learning method to analyze ecological disease patterns caused by spatially non-stationary processes using a malaria incidence dataset for Rwanda.

Effect of chamomile aromatherapy with and without oxygen on pain of women in post cesarean section with spinal anesthesia: A randomized clinical trial.

Background: Pain is the most common side effect in cesarean section with spinal anesthesia. It seems that oxygen therapy and chamomile aromatherapy may diminish pain. The present study was conducted to examine and compare the effect of chamomile aromatherapy with and without oxygen on the severity of pain of women following cesarean section surgery with spinal anesthesia.

Comparing intensity of pain due to intravenous injection of sodium thiopental, propofol, diazepam, and etomidate during induction of general anesthesia.

Aim: The aim of the present study was to compare the pain intensity due to intravenous injection of sodium thiopental, propofol, diazepam, and etomidate during the induction of general anesthesia.

Methods: This was a non-controlled quasi-experimental double-blinded study performed on eligible patients referred to the operating room of Shahid Beheshti Hospital in Yasouj. A total of 200 patients were randomly selected by convenience sampling and based on a table of random numbers generated on a computer.

The Effect of Low-level Laser Therapy on VEGF, IL-6 Expression and Viability of Oral Squamous Cell Carcinoma Cells.

Low-level laser therapy has shown successful results in the prevention and treatment of oral mucositis. One of the concerns about low-level lasers is their effects on remaining malignant cells in the area. Interleukin-6 is a multifunctional cytokine that plays an important role in a wide range of biological activities in increasing tumor functions, decreasing survival and resistance to chemo-radiotherapy.

How did micro-mobility change in response to COVID-19 pandemic? A case study based on spatial-temporal-semantic analytics.

Cities worldwide adopted lockdown policies in response to the outbreak of coronavirus disease 2019 (COVID-19), significantly influencing people's travel behavior. In particular, micro-mobility, an emerging mode of urban transport, is profoundly shaped by this crisis. However, there is limited research devoted to understanding the rapidly evolving trip patterns of micro-mobility in response to COVID-19.

Kisspeptin levels in relation to sex hormone profile among PCOS patients.

Introduction: Polycystic ovary syndrome (PCOS) is a common endocrine disease among women in the reproductive age that is associated with consequences such as insulin resistance and hyperandrogenemia. This study was aimed to assess the association of sex hormone profile and kisspeptin levels in PCOS women in Gorgan, Iran.

Methods: In this case-control study, 43 women with diagnosed PCOS between the ages of 15 and 37 years and 40 healthy demographically matched controls were recruited.

Spatial Analysis of Ambient Air Pollution and Cardiovascular Disease (CVD) Hospitalization Across Sweden.

The associations of multiple pollutants and cardiovascular disease (CVD) morbidity, and the spatial variations of these associations have not been nationally studied in Sweden. The main aim of this study was, thus, to spatially analyze the associations between ambient air pollution (black carbon, carbon monoxide, particulate matter (both <10 µm and <2.5 µm in diameter) and Sulfur oxides considered) and CVD admissions while controlling for neighborhood deprivation across Sweden from 2005 to 2010.

An ecological study of chronic kidney disease in five Mesoamerican countries: associations with crop and heat.

Background: Mesoamerica is severely affected by an epidemic of Chronic Kidney Disease of non-traditional origin (CKDnt), an epidemic with a marked variation within countries. We sought to describe the spatial distribution of CKDnt in Mesoamerica and examine area-level crop and climate risk factors.

Methods: CKD mortality or hospital admissions data was available for five countries: Mexico, Guatemala, El Salvador, Nicaragua and Costa Rica and linked to demographic, crop and climate data.

Spatio-temporal trends and distribution patterns of typhoid disease in Uganda from 2012 to 2017.

Typhoid disease continues to be a global public health burden. Uganda is one of the African countries characterized by high incidences of typhoid disease. Over 80% of the Ugandan districts are endemic for typhoid, largely attributable to lack of reliable knowledge to support disease surveillance.

Management of the essential data element in the differential diagnosis of oral medicine: An effective step in promoting oral health.

Background: Oral soft tissue diseases include a broad spectrum, and the wide array of patient data elements need to be processed in their diagnosis. One of the biggest and most basic challenges is the analysis of this huge amount of complex patient data in an increasing number of complicated clinical decisions. This study seeks to identify the necessary steps for collecting and management of these data elements through establishing a consensus-based framework.

Role of vitamin D in oxidative stress modulation in end-stage renal disease patients: A double-blind randomized clinical trial.

Introduction: Oxidative stress is considered as important actor in uremia-associated morbidity and mortality in hemodialysis (HD) patients. We aimed to evaluate the role of vitamin D supplementation on oxidative stress parameters in this group.

Methods: This double-blind randomized clinical trial was conducted on HD patients who were randomly allocated into intervention (n = 40) or control groups (n = 38) for 10 weeks.

A Comparative Study of Low-Level Laser Therapy and Transcutaneous Electrical Nerve Stimulation as an Adjunct to Pharmaceutical Therapy for Myofascial Pain Dysfunction Syndrome: A Randomized Clinical Trial.

Objectives: Myofascial pain dysfunction syndrome (MPDS) is the most common form of temporomandibular disorders. Because of the multifactorial nature of the problem, its management usually involves several treatment modalities to maximize their synergistic effects. This randomized clinical trial aimed to assess the efficacy of low-level laser therapy (LLLT) and transcutaneous electrical nerve stimulation (TENS) as an adjunct to pharmaceutical therapy for treatment of MPDS.

Association of Perforin and Granzyme-B Levels with Hyperandrogenism in Polycystic Ovary Syndrome: A Case-Control Study.

Background And Objective: Polycystic ovary syndrome (PCOS) is shown to be associated with hyperandrogenemia and has some features such as cytotoxic T-cells activation and release of perforin and granzyme-B. Present work was aimed to investigate the relation of perforin and granzyme-B to androgenic state in PCOS.

Materials And Methods: Forty three PCOS and 40 control women were recruited.

Establishing spatially-enabled health registry systems using implicit spatial data pools: case study - Uganda.

Background: Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal numbers, which are geocoded. However, for most resource-constrained African countries, the absence of a means to capture patient resident location as well as inexistence of spatial data infrastructures makes capturing of patient-level spatial data unattainable.

Spatial analysis of HIV-TB co-clustering in Uganda.

Background: Tuberculosis (TB) is the leading cause of death for individuals infected with Human immunodeficiency virus (HIV). Conversely, HIV is the most important risk factor in the progression of TB from the latent to the active status. In order to manage this double epidemic situation, an integrated approach that includes HIV management in TB patients was proposed by the World Health Organization and was implemented in Uganda (one of the countries endemic with both diseases).

Predictive risk mapping of human leptospirosis using support vector machine classification and multilayer perceptron neural network.

Leptospirosis is a zoonotic disease found wherever human is in direct or indirect contact with contaminated water and environment. Considering the increasing number of cases of this disease in the northern part of Iran, identifying areas characterized by high disease incidence risk can help policy-makers develop strategies to prevent its further spread. This study presents an approach for generating predictive risk maps of leptospirosis using spatial statistics, environmental variables and machine learning.

Developing a new intelligent system for the diagnosis of oral medicine with case-based reasoning approach.

Objective: Since the clinical manifestations of many oral diseases can be quite similar despite the wide variety in etiology and pathology, the differential diagnosis of oral diseases is a complex and challenging process. Intelligent system for differential diagnosis of oral medicine using the artificial intelligence (AI) capabilities helps specialists in achieving differential diagnosis in a wide range of oral diseases.

Materials And Methods: First, the essential data elements to design and develop an intelligent system were identified in a cross-sectional descriptive study.