Highly stable mesoporous Co/Ni mixed metal-organic framework [Co/Ni(µ3-tp)2(µ2-pyz)2] for Co (II) heavy metal ions (HMIs) remediation.

A bimetallic cobalt/nickel-based metal-organic framework (MOF), [Co/Ni(µ3-tp)2(µ2-pyz)2], denoted as Co/Ni-MOF, has been successfully prepared by a hydrothermal method. The MOF was prepared by incorporating mixed O- and N- donor ligands, specifically terephthalic acid (tp) and pyrazine (pyz). The Mesoporous Co/Ni-MOF was comprehensively characterized using various analytical methods such as XRD, BET, FT-IR, TGA (23 % char yields), SEM, and EDS analyses. The synthesized mesoporous Co/Ni-MOF was then used to absorb Co (II) from aquatic areas efficiently. Several critical parameters, such as the beginning Co (II) concentration (25-150 mg/L), the effect of pH (2-10), the duration of time (5-30 min), and the amount of adsorbent (0.003-0.02 g), were systematically investigated. Remarkably, the Mesoporous Co/Ni MOF displayed a significant adsorption capacity of 372.66 mg g-1 in the optimum conditions, including pH = 6, amount of adsorbent = 0.003 g, duration of time = 25 min, and beginning Co (II) concentration = 150 mg/L. Adsorption data from the experimental studies of the mesoporous Co/Ni MOF are matched based on the non-linear pseudo-first-order (PSO) kinetic model (R2 = 0.9999), and a chemical process is suggested for chemisorption. Furthermore, the adsorption isotherms of Co (II) heavy metal ions (HMIs) are an excellent fit with the non-linear Temkin, indicating that they explain the sorbent/sorbate interactions concerning the heat of adsorption. It is evident from the thermodynamic parameters that adsorption is a spontaneous and favorable exothermic process. These results highlight the promising adsorption performance and potential applications of the mesoporous Co/Ni-MOF as an effective adsorbent for Co (II) elimination from aquatic areas. Four-cycle regeneration studies were the most effective for the Co (II) under study.

Surgical Treatment of Anterior Plagiocephaly With Limited Calvarial Osteotomy.

OBJECTIVE: Anterior plagiocephaly is a condition in which the unicoronal suture is prematurely fused and the skull shape will change due to asymmetric growth. METHODS: This is a retrospective study describing the unilateral limited frontal osteotomy for remodeling deformed areas in the frontal and orbital bone and its pros and cons. RESULTS: Twenty-eight patients were included in the study, with a mean age of 16.8 (±11.7) months. Mean intraoperative bleeding was 78.1 (±23.6) mL. One (3.57%) patient developed postoperative bleeding, around 200 mL. After 12 months, all patients (100%) had grade I Whitaker. CONCLUSION: The described technique is safe and may have promising short-term outcomes for the correction of anterior plagiocephaly.

Assessing wildfire impact on Trigonella elliptica habitat using random forest modeling.

Wildfires have a significant impact on ecosystems worldwide, especially on the degradation of arid and semi-arid rangelands. This research focuses on assessing the effects of wildfires on the habitat of Trigonella elliptica, a valuable herb species found in the central rangelands of Iran. To achieve this, the Random Forest (RF) algorithm has been deployed to predict T. elliptica habitat and fire hazard using socio-environmental variables in Yazd province, Iran. 225 fire points and 103 habitat locations were used for model training and testing. The IncNodePurity index and Probability Curves (PC) have been utilized to determine the influence of socio-environmental variables. The combination of the prediction maps of the habitat and wildfires pointed out the possible damage due to fire. The high performance of the RF model is confirmed by the area under the curve (AUC) and the true skill statistic (TSS) values (0.90 and 0.81 for the habitat; 0.92 and 0.82 for the wildfire). The importance assessment of variables revealed that elevation, slope, and precipitation are the most influential variables in the distribution of T. elliptica, while distance to roads, population density, and wind speed are the key factors affecting wildfire occurrence. In the final map, a comparison of different regions of T. elliptica habitat under fire hazard with fire-free habitats using Kruskal-Wallis and Dunn tests indicated that the fire hazard in the T. elliptica habitat is a serious concern. Since the areas with the highest fire hazard and the highest presence of T. elliptica cover approximately 2311.38 km2, neglecting these regions could lead to the gradual reduction of T. elliptica, and create conditions for secondary succession dominated by less valuable annual species. The findings of this study underscore the importance of implementing fire management strategies, protection projects, and continuous monitoring to ensure the safety and conservation of the T. elliptica habitat.

Early prediction of medical students' performance in high-stakes examinations using machine learning approaches.

Introduction: Since the advent of medical education systems, managing high-stakes exams has been a top priority and challenge for all policymakers. However, considering machine learning (ML) techniques as a replacement for medical licensing examinations, particularly during crises such as the COVID-19 outbreak, could be an effective solution. This study uses ML models to develop a framework for predicting medical students' performance on high-stakes exams, such as the Comprehensive Medical Basic Sciences Examination (CMBSE). Material and methods: Prediction of students' status and score on high-stakes examinations faces several challenges, including an imbalanced number of failing and passing students, a large number of heterogeneous and complex features, and the need to identify at-risk and top-performing students. In this study, two major categories of ML approaches are compared: first, classic models (logistic regression (LR), support vector machine (SVM), and k-nearest neighbors (KNN)), and second, ensemble models (voting, bagging (BG), random forests (RF), adaptive boosting (ADA), extreme gradient boosting (XGB), and stacking). Results: To evaluate the models' discrimination ability, they are assessed using a real dataset containing information on medical students over a five-year period (n = 1005). The findings indicate that ensemble ML models demonstrate optimal performance in predicting CMBSE status (RF and stacking). Similarly, among the classic regressors, LR exhibited the highest root-mean-square deviation (RMSD) (0.134) and coefficient of determination (R2) (0.62), whereas the RF model had the highest RMSD (0.077) and R2 (0.80) overall. Furthermore, Anatomical Sciences, Biochemistry, Parasitology, and Entomology grade point average (GPA) and grades demonstrated the strongest positive correlation with the outcomes. Conclusion: Comparing classic and ensemble ML models revealed that ensemble models are superior to classic models. Therefore, the presented framework could be considered a suitable alternative for the CMBSE and other comparable medical licensing examinations.

Investigating the Effect of Leap Motion on Upper Extremity Rehabilitation in Children with Cerebral Palsy: A Randomized Controlled Trial.

In this randomized clinical trial, we look for the following questions' answer: How does the integration of LMC affect (1) upper extremity (UE) function, (2) grip strength, and (3) lateral and palmar pinch strength in children with cerebral palsy (CP), in comparison with conventional rehabilitation methods? Twenty patients were randomly assigned to LMC (case) or conventional (control) groups. The grip, lateral and palmar pinch forces increased in case group patients more than control group both at the end of intervention (P < .001 for all three), and at 20 weeks' follow-up (P values 0.035, 0.002, and 0.002). The Quality of Upper Extremity Skills Test (QUEST) score changes were similar between two groups, except for grasp score at the end of step 2 and 3 (P = .04 and 0.01, respectively). The addition of LMC to the rehabilitation program of patients with CP may improve the UE motor function outcomes.

Prediction of medical sciences students' performance on high-stakes examinations using machine learning models: a protocol for a systematic review.

INTRODUCTION: Predicting medical science students' performance on high-stakes examinations has received considerable attention. Machine learning (ML) models are well-known approaches to enhance the accuracy of determining the students' performance. Accordingly, we aim to provide a comprehensive framework and systematic review protocol for applying ML in predicting medical science students' performance on high-stakes examinations. Improving the current understanding of the input and output features, preprocessing methods, setting of ML models and required evaluation metrics seems essential. METHODS AND ANALYSIS: A systematic review will be conducted by searching the electronic bibliographic databases of MEDLINE/PubMed, EMBASE, SCOPUS and Web of Science. The search will be limited to studies published from January 2013 to June 2023. Studies explicitly predicting student performance in high-stakes examinations and referencing their learning outcomes and use of ML models will be included. Two team members will first screen literature meeting the inclusion criteria at the title, abstract and full-text levels. Second, the Best Evidence Medical Education quality framework rates the included literature. Later, two team members will extract data, including the studies' general data and the ML approach's details. Finally, the information consensus will be reached and submitted for analysis. The synthesised evidence from this review provides helpful information for medical education policy-makers, stakeholders and other researchers in adopting the ML models to evaluate medical science students' performance in high-stakes exams. ETHICS AND DISSEMINATION: This systematic review protocol summarises findings of existing publications rather than primary data and does not require an ethics review. The results will be disseminated in publications of peer-reviewed journals.

Correlation of Ultrasonography and MRI with Electrodiagnostic Studies in Carpal Tunnel Syndrome.

Background: One controversial question in Carpal Tunnel Syndrome (CTS) diagnosis is whether magnetic resonance imaging (MRI) and Ultrasound (US) imaging tools have any relationship with electrodiagnostic (EDX) study. The objective of this study is to determine the possible correlation between MRI and US measurements with EDX parameters. Methods: Both US and MRI of the median nerve were simultaneously performed in 12 confirmed CTS wrists, at two levels of forearm distal fold (proximal) and the hook of the hamate (distal), to measure various anatomic parameters of the nerve. EDX parameters of median motor distal latency (DL) and median sensory proximal latency (PL) were evaluated in milliseconds. Results: Nerve cross-sectional area (CSA), measured by MRI, correlated with sensory PL at distal level (p = 0.015). At proximal level MRI, nerve width and width to height ratio also correlated with motor DL (p = 0.033 and 0.021, respectively). Median nerve CSA proximal to distal ratio correlated with sensory PL (p = 0.028) at MRI. No correlation was found between US and EDX measurements. Conclusions: Median nerve MRI measurement of nerve CSA at hook of the hamate (distal) level or CSA proximal to distal ratio correlated with EDX parameter of sensory PL. On the other hand, nerve MRI width and width to height ratio at distal level correlated with motor DL in EDX. Level of Evidence: Level III (Diagnostic).

Magnetic Resonance Imaging and Sonographic Features before and after Surgery in Carpal Tunnel Syndrome: Association with Clinical Findings.

Background: The interest in ultrasonography (US) and magnetic resonance imaging (MRI) assessment of the patients with carpal tunnel syndrome (CTS) is growing. This paper aimed to find the correlation of postoperative changes in these modalities' parameters with clinical outcomes. Methods: Boston CTS questionnaire-symptom severity (BQ-SS), Boston CTS questionnaire-functional status (BQ-FS), and visual analog scale (VAS) questionnaires (for pain, paresthesia, and grip weakness assessment) were used to evaluate clinical outcomes. Various imaging parameters of the median nerve and carpal tunnel were evaluated using US and MRI at two levels of the hook of the hamate (distal) and the pisiform (proximal) once preoperatively and then 3 months postoperatively. Corresponding US and MRI parameter measures were compared, and correlational analysis was performed between alteration of imaging findings and changes in clinical parameters postoperatively. Results: Patients' functional status (BQ-FS score) was positively correlated with the nerve width both in US and MRI at the proximal level (r = 0.457 and r = 0.453, respectively) and also with the MRI nerve circumference at the distal level (r = -0.482). Correlation between paresthesia and the nerve width was notable in MRI at the distal hook of the hamate level (r = -0.403). Grip weakness VAS score was correlated with the nerve width-to-height ratio (WHR) in US at the distal level (r = 0.432). Conclusions: Changes in US and MRI parameters of the median nerve width, circumference, and WHR were associated with clinical changes in patients with CTS after surgery.

Predictive Value of Blood Markers in Pediatric Brain Tumors Using Machine Learning.

BACKGROUND: The brain tumor is the most common solid tumor in children. Blood markers in most malignancies are altered due to the effect of inflammatory mediators on the bone marrow. OBJECTIVE: This study aimed to predict the malignancy of pediatric brain tumors using blood markers. METHODS: The pediatric brain tumors were divided into benign and malignant groups. Blood markers, including RBC, WBC, neutrophil, lymphocyte, monocyte, platelet, neutrophil to lymphocyte ratio, lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio, and derived neutrophil to lymphocyte ratio were extracted. Differences in blood markers between two groups were assessed using statistical analysis. The accuracy of machine learning to determine pediatric brain tumors' malignancy was evaluated using blood markers and demographic information. RESULTS: Among 113 patients, 55 patients were in the benign tumor group, and 58 patients were in the malignant tumor group. In the statistical study of blood markers in two groups, LMR was significantly different and positively correlated with malignancy. Other blood markers were not significantly different between two groups. This study showed that support-vector machines using blood markers, age, and sex can differentiate benign and malignant pediatric brain tumors with 71.6% accuracy. CONCLUSIONS: Despite the statistically significant differences in blood markers in different grades of brain tumors in adults, their differences in pediatric brain tumors, except LMR, were not significant. Machine learning using blood markers can differentiate between benign and malignant pediatric brain tumors with 71.6% accuracy.

The Effect of Using In Vitro Fertilization (IVF) on Increasing the Prevalence of Craniosynostosis.

BACKGROUND: Craniosynostosis, a malformation caused by premature closure of one or more cranial sutures, is a rare congenital disability usually of unknown cause; however, it is often associated with assisted reproductive technology. Given the increasing prevalence of craniosynostosis and the use of the in vitro fertilization (IVF) method, the authors evaluated the association between IVF and the prevalence of craniosynostosis. METHODS: This retrospective study reviewed records of patients with nonsyndromic craniosynostosis who underwent surgery in Mofid Hospital, a tertiary children's hospital affiliated to Shahid Beheshti University of Medical Sciences, between 2010 and 2019. RESULTS: A total of 200 patients aged one month to 7 years old, were evaluated. Out of 200 patients, 43% were plagiocephalic, 39% trigonocephalic, 8.5% scaphocephalic, 8% brachiocephalic, and 1.5% were mixed. Nine (4.5%) patients had received clomiphene citrate. Eight (4%) mothers had become pregnant under IVF, and they all had used clomiphene citrate for ovulation stimulation. No use of artificial insemination was reported. Of the eight patients whose mother had become pregnant through IVF, three were trigonocephalic, and five were plagiocephalic. CONCLUSIONS: Without a control group, we are not able report the statistical results confirming or denying a link between craniosynostosis and infertility treatment. However, 4% prevalence of IVF use among craniosynostosis patients is significant. Further studies with a broader statistical community are suggested in this regard.

A case of diffuse leptomeningeal glioneuronal tumor in a 10-year-old boy: First report from Iran.

A 10-year-old boy who was referred due to acute hydrocephalus symptoms was diagnosed as the first case of pediatric DLGNT in Iran. The results suggested that using shunting for hydrocephaly and anti-seizure medicines, as well as chemotherapeutic agents, can be an effective treatment strategy for DLGNT. Although the patient was stable without a tumor recurrence for a limited follow-up period of 22 months, further studies are expected.

Analyzing WSTP trend: a new method for global warming assessment.

This paper tries to introduce a time-series of temperature parameters as a potential method for studying the global warming. So, we investigated the spatial-temporal variations of warm-season temperature parameters (WSTP), including start time, end time, length of season, base value, peak time, peak value, amplitude, large integrated value, right drive, and left drive, using a database of 30 years' period in different climates of Iran. We used daily temperature data from 1989 to 2018 over Iran to extract the parameters by TIMESAT software. We studied the trend analysis of WSTP through the Mann-Kendall method. Then, we considered the Pearson correlation coefficient to calculate the correlation between WSTP and time. We assessed the trends of the slope using a simple linear regression method. Then, we compared the results of the WSTP trend analysis in climatic zones. Our results accused the hyper-arid climatic zone has the longest warm season (194.89 days a year). The warm season in this region starts earlier than other regions and increases with moderate speed (left drive, 0.19 °C day-1). Then, it reaches a peak value (31.3 °C) earlier than the different climatic zones. On the other hand, the humid regions' warm season starts with the shortest length and ends later than the other climatic zones (112.1 and 297.5 days a year for start and end times, respectively). We detected that the trend of the start time parameter has decreased by 98.02% of the study area during the last 30 years. The base value, length, and large integrated value parameters have an increasing trend of 66.47%, 80.11%, and 92.95% in Iran. The highest correlation coefficient with time was for start time and large integrated value parameters. Hence, the start time and large integrated value parameters have almost the most negative (< - 0.5) and positive (> 5) trend slope, among other parameters, respectively. In general, these results demonstrate that the studied region has faced global warming impacts over time by increasing the warm season and thermal energy, especially in arid and hyper-arid. We highlight the necessity of planning the land use under the high natural vulnerability of the studied local, especially in this new age of global warming.

Long-term non-sustainable soil erosion rates and soil compaction in drip-irrigated citrus plantation in Eastern Iberian Peninsula.

Agriculture is known to commonly cause soil degradation. In the Mediterranean, soil erosion is widespread due to the millennia-old farming, and new drip-irrigated plantations on slopes, such as the citrus ones, accelerate the process of soil degradation. Until now, the published data about soil erosion in citrus orchards is based on short-term measurements. Long-term soil erosion measurements are needed to assess the sustainability of drip-irrigated citrus production and to design new strategies to control high soil erosion rates. The objective of this study is to assess long-term soil erosion rates in citrus plantations and report the changes in soil bulk density as indicators of land degradation. We applied ISUM (Improved Stock-Unearthing Method) to 67 paired trees in an inter-row of 134 m (802 m2 plot) with 4080 measurements to determine the changes in soil topography from the plantation (2007) till 2020. Soil core samples (469) were collected (0-6 cm depth) to determine the soil bulk density at the time of plantation (2007) and in 2020. The results demonstrate an increase in soil bulk density from 1.05 g cm-3 to 1.33 g cm-3. Changes in soil bulk density were higher in the center of the row as a result of compaction due to passing machinery. Soil erosion was calculated to be 180 Mg ha-1 y-1 due to a mean soil lowering of 1.5 cm yearly. The highest soil losses were found in the center of the inter-row and the lowest underneath the trees. The extreme soil erosion rates measured in new drip-irrigated citrus plantations are due to soil lowering in the center of the inter-row and in the lower inter-row position where the incision reached 80 cm in 13 years. The whole field showed a lowering of the soil topography due to extreme soil erosion and no net sedimentation within the plantation. The results show the urgent need for soil erosion control strategies to avoid soil degradation, loss of crop production, and damages to off-site infrastructures.

Long-term monitoring of soil bulk density and erosion rates in two Prunus Persica (L) plantations under flood irrigation and glyphosate herbicide treatment in La Ribera district, Spain.

Early season fruit production for the northern European market is highly intensive in fertilization, machinery, irrigation and the use of herbicides. Those conditions increase the soil losses and soil compaction and threaten the Sustainable Goals for Development of the United Nations by 2030. Long-term soil erosion measurements are necessary to determine the sustainability of agriculture managements. Moreover, soil erosion on flood irrigation land is a topic that request more surveys and research as rainfed sloping terrains attracted all the attention of scientists and research investment. Improved Stock Unearthing Method (ISUM) was applied to two 15 years-old herbicide treated fields of Saturn peaches (Prunus persica var. platycarpa) to determine long-term soil erosion rates (2004-2019). Using ISUM, a 1 mm thick nylon rope (700 mm length) was used to connect trees perpendicular to the direction of rows at the height of the graft. To detection soil lowering, the vertical distance of the rope to the soil surface was measured at 10 cm intervals along the rope. The ring method (264 samples at 0-6 cm) was used to determine the soil bulk density, which was in average 1.15 gr cm-3 for both plots. There was found a compaction in the centre of both plots due to the pass of machinery with mean bulk density values of 1.23 gr cm-3, meanwhile underneath of the trees, the soil bulk density was 1.05 gr cm-3. The topography survey carried out with ISUM (2508 sampling points) informed that flood irrigation redistributed the soil from the upper to the lower field position, where a sedimentation layer was measured. We found that the two studied fields showed a contrasted response, with low soil erosion values in Benimodo and high in L'Alcúdia study sites. Soil erosion rates were in average 1.46 Mg ha-1 yr-1 and 8.02 Mg ha-1 yr-1 for Benimodo and L'Alcúdia, respectively. However, the maps development using ISUM allow to inform that the pattern of soil redistribution is similar for both fields as the highest soil lowering was found in the upper field part, where the flood discharge detach soil particles. In the lower field position sedimentation takes place. The dataset allows us to conclude that soil erosion in Saturn peaches fields is non-sustainable and more soil conservation management should be applied to reduce the soil erosion rates due to the bare soils as a consequence of the use of herbicides. This research informs that soil erosion in flood irrigated fields is a relevant process that needs more investigations around the world, where 94% of the irrigated land is under flood or furrow irrigation, and where irrigation is growing year after year.

Comparing mechanical, barrier and antimicrobial properties of nanocellulose/CMC and nanochitosan/CMC composite films.

Nano-chitosan (NCH), nano-cellulose (NCL) and cellulose derivative are biodegradable biopolymer. Nano-chitosan or nano-cellulose at different concentrations (0.1, 0.5 and 1%) incorporated in carboxymethyl cellulose (CMC) film solution using casting methods. Both CMC/NCH and NCL decreased physical properties (water solubility, moisture content and moisture absorption) especially in concentration of 1%. However, these properties in CMC/NCH were significantly (p < 0.05) lower than CMC/NCL. Water vapor permeability of polymer and nanofiller decreased when nanocomposite concentration increased. Tensile strength and Elongation at break improved in nanocomposite film by increasing concentration. Thermal properties of CMC/NCH were significantly (p < 0.05) lower than CMC/NCL. Emersion of crystalline peaks in X-ray analyses certified the presence of nanofiller in polymer. However, in high content (1%) cause to create aggregation of nanofiller in CMC film. Finally antibacterial activity against five pathogens was studied and good effective inhibition on CMC/NCH was observed while CMC/NCL had no inhibitory effect. These results show that use of CMC/NCH as a biocompatible film has more advantages than CMC/NCL biopolymer.

Prolonging shelf life of chicken breast fillets by using plasma-improved chitosan/low density polyethylene bilayer film containing summer savory essential oil.

Cold plasma assay was potentially useful persuade surface modification. In this study, antimicrobial properties of chitosan and low density polyethylene bilayer film with method cold plasma incorporated with summer savory essential oil (SEO) (1, 2 and 3%) for extending shelf life of chicken breast fillets was investigated. Moreover, mechanical and physical properties of film were assessed. Result showed that plasma treatment could improvement properties film and increase shelf life processing. After plasma treatment chitosan/polyethylene film containing 3% summer savory essential oil decreased water vapor permeability and oxygen transmission rate chitosan film. Addition of summer savory essential oil to the two-layer film, also improved tensile strength and elongation at break of film. The bilayer film with 3% of essential oil treatment cold plasma was chosen for microbial analysis during storage. All samples plasma-treated, films for this study included polyethylene (PE), bilayer of polyethylene and chitosan (PE/Ch) and Chitosan containing essential oil in direct contact (D) and gas phase (G). Result showed that shelf life of fillets were extended in direct contact and gas phase treatments to 13 days at refrigerator. It was 6 days for polyethylene and 8 days for Chitosan treatments. Essential oil incorporated film also decreased thiobarbitoric acid value of sample during storage. Cold plasma has a high potential in active packaging and food preservation.

Retinal Nerve Fiber Layer Thickness and Total Macular Volume in Multiple Sclerosis Subtypes and Their Relationship with Severity of Disease, a Cross-Sectional Study.

BACKGROUND: Optic neuritis (ON) is an inflammatory demyelinating lesion in the optic nerve, which is strongly associated with multiple sclerosis (MS). Optical coherence tomography (OCT) is a noninvasive technique for the evaluation of the retinal layers. Our aim was to examine OCT metrics including retinal nerve fiber layer thickness (RNFLT), and total macular volume (TMV), in MS subtypes and their relationship with duration, first manifestation, and severity of disease. MATERIAL AND METHODS: In this cross-sectional study, patients with a definite diagnosis of MS underwent complete ophthalmic and neurologic examination. OCT parameters including TMV and RNFLT were compared between MS subtypes and different first manifestations of MS. Their relationships were also studied with the duration and severity of disease based on the Expanded Disability Status Scale (EDSS) score. RESULTS: A total of 240 eyes were examined in 120 enrolled MS patients. The differences in RNFLT were not analytically meaningful between the subtypes of MS, but the differences in TMV values were statistically significant between the subtypes of MS (P: 0.39 and P: 0.04, respectively). The differences between RNFLT and TMV of eyes with and without ON were statistically significant between these two groups (P<0.001 and P<0.001). There was also an inverse correlation between EDSS disability score and RNFLT and TMV values (P: 0.00, r: -0.33 and P: 0.034, r: -0.11, respectively) and a significant inverse correlation between the duration of MS and RNFLT (P: 0.00, r: -0.47). The differences in RNFLT and TMV values were analytically meaningful between the categories of first manifestations of MS (P: 0.000 and P: 0.027, respectively). CONCLUSION: RNFLT and TMV represent noninvasive parameters for assessment of neuroaxonal degeneration in the anterior visual pathway that correlate with the severity and duration of multiple sclerosis. The lowest RNFLT and TMV values were also seen in the perceptual category between the first manifestations of MS. Therefore, they may be useful in the evaluation of MS patients.

Spatial hazard assessment of the PM10 using machine learning models in Barcelona, Spain.

Air pollution, and especially atmospheric particulate matter (PM), has a profound impact on human mortality and morbidity, environment, and ecological system. Accordingly, it is very relevant predicting air quality. Although the application of the machine learning (ML) models for predicting air quality parameters, such as PM concentrations, has been evaluated in previous studies, those on the spatial hazard modeling of them are very limited. Due to the high potential of the ML models, the spatial modeling of PM can help managers to identify the pollution hotspots. Accordingly, this study aims at developing new ML models, such as Random Forest (RF), Bagged Classification and Regression Trees (Bagged CART), and Mixture Discriminate Analysis (MDA) for the hazard prediction of PM10 (particles with a diameter less than 10 µm) in the Barcelona Province, Spain. According to the annual PM10 concentration in 75 stations, the healthy and unhealthy locations are determined, and a ratio 70/30 (53/22 stations) is applied for calibrating and validating the ML models to predict the most hazardous areas for PM10. In order to identify the influential variables of PM modeling, the simulated annealing (SA) feature selection method is used. Seven features, among the thirteen features, are selected as critical features. According to the results, all the three-machine learning (ML) models achieve an excellent performance (Accuracy > 87% and precision > 86%). However, the Bagged CART and RF models have the same performance and higher than the MDA model. Spatial hazard maps predicted by the three models indicate that the high hazardous areas are located in the middle of the Barcelona Province more than in the Barcelona's Metropolitan Area.

Iran in transition.

Being the second-largest country in the Middle East, Iran has a long history of civilisation during which several dynasties have been overthrown and established and health-related structures have been reorganised. Iran has had the replacement of traditional practices with modern medical treatments, emergence of multiple pioneer scientists and physicians with great contributions to the advancement of science, environmental and ecological changes in addition to large-scale natural disasters, epidemics of multiple communicable diseases, and the shift towards non-communicable diseases in recent decades. Given the lessons learnt from political instabilities in the past centuries and the approaches undertaken to overcome health challenges at the time, Iran has emerged as it is today. Iran is now a country with a population exceeding 80 million, mainly inhabiting urban regions, and has an increasing burden of non-communicable diseases, including cardiovascular diseases, hypertension, diabetes, malignancies, mental disorders, substance abuse, and road injuries.