Identification of Risk Factors Associated with Tuberculosis in Southwest Iran: A Machine Learning Method.

Background: Tuberculosis is a principal public health issue. Reducing and controlling tuberculosis did not result in the expected success despite implementing effective preventive and therapeutic programs, one of the reasons for which is the delay in definitive diagnosis. Therefore, creating a diagnostic aid system for tuberculosis screening can help in the early diagnosis of this disease. This research aims to use machine learning techniques to identify economic, social, and environmental factors affecting tuberculosis. Methods: This case-control study included 80 individuals with TB and 172 participants as controls. During January-October 2021, information was collected from thirty-six health centers in Ahvaz, southwest Iran. Five different machine learning approaches were used to identify factors associated with TB, including BMI, sex, age , marital status, education, employment status, size of the family, monthly income, cigarette smoking, hookah smoking, history of chronic illness, history of imprisonment, history of hospital admission, first-class family, second-class family, third-class family, friend, co-worker, neighbor, market, store, hospital, health center, workplace, restaurant, park, mosque, Basij base, Hairdressers and school. The data was analyzed using the statistical programming R software version 4.1.1. Results: According to the calculated evaluation criteria, the accuracy level of 5 SVM, RF, LSSVM, KNN, and NB models is 0.99, 0.72, 0.97,0.99, and 0.95, respectively, and except for RF, the other models had the highest accuracy. Among the 39 investigated variables, 16 factors including First-class family (20.83%), friend (17.01%), health center (41.67%), hospital (24.74%), store (18.49%), market (14.32%), workplace (9.46%), history of hospital admission (51.82%), BMI (43.75%), sex (40.36%), age (22.83%), educational status (60.59%), employment status (43.58%), monthly income (63.80%), addiction (44.10%), history of imprisonment (38.19%) were of the highest importance on tuberculosis. Conclusion: The obtained results demonstrated that machine-learning techniques are effective in identifying economic, social, and environmental factors associated with tuberculosis. Identifying these different factors plays a significant role in preventing and performing appropriate and timely interventions to control this disease.

Sleep characteristics of middle-aged adults with non-alcoholic fatty liver disease: findings from the Shahrekord PERSIAN cohort study.

BACKGROUND: Several studies have reported short sleep duration in people with non-alcoholic fatty liver disease (NAFLD) but other sleep characteristics have been less studied. We aimed to assess the cross-sectional association of NAFLD with sleep duration and quality in an Iranian population sample. METHODS: We used data from 9,151 participants in the Shahrekord Prospective Epidemiological Research Studies in Iran (PERSIAN) Cohort Study, including 1,320 that were diagnosed with NAFLD. Log-binomial regression models sequentially adjusted for sociodemographic, lifestyle, clinical and biological variables were used to estimate relative risks (RR) and 95% confidence intervals (95% CI) for the association between NAFLD and sleep characteristics. RESULTS: Participants with NAFLD had shorter sleep duration, later wake-up time and bedtime, worse sleep efficiency, and more frequent daytime napping and use of sleeping pills, in age- and sex-adjusted models. After controlling for sociodemographic, lifestyle, clinical, and biological variables the associations remained strong for sleep efficiency (per 10%, RR = 0.92, 95%CI: 0.88-0.96) and use of sleeping pills (RR = 1.48, 95%CI: 1.17-1.88). The association between NAFLD and sleep efficiency was stronger in participants aged > 60 years (RR = 0.81, 0.70-0.93) and 40-60 years (RR = 0.87, 0.82-0.94), compared with those aged < 40 years (P-heterogeneity < 0.001). More frequent daytime napping in participants with NAFLD, compared with non-NAFLD, was observed in males but not females (P-heterogeneity = 0.007), and in those with body mass index (BMI) < 30 but not in obese participants (P-heterogeneity < 0.001). CONCLUSIONS: Diagnosis of NAFLD is associated with several poor sleep characteristics in middle-aged Iranians. Although longitudinal studies would help to clarify the direction of causality, our study shows that poor sleep is an important aspect of NAFLD.

Investigating the intensity of social contacts associated with tuberculosis: a weighted networks model.

BACKGROUND: Tuberculosis is known as one of the principal health problems, especially in developing countries. This study aimed to visualize, statistically model, and describe the weighted networks to investigate the intensity of social contacts associated with tuberculosis. METHODS: In this case-control study, we applied weighted network analysis to assess the network of person-time spent in stores, workplaces, restaurants, mosques, Police bases, homes, hospitals, colleges, hairdressers, schools, contact homes, health centers, cinemas, parks, and markets. Modules will be determined based on the similarities between the variables in a topology overlap matrix. The most important variables will be found considering the association between each variable and module eigenvalues. RESULTS: The result shows the extracted modules of locations based on the connectivity followed by the person-time at each place. The correlation (p-value) between TB and the turquoise, blue, and brown modules was 0.058 (0.351), 0.004 (0.943), and 0.117 (0.039), respectively. The brown module is the most important one, demonstrating a significant connection between homes, contact homes, health centers, and hospitals. Therefore, an association was found between person-time in four places and the occurrence of TB. CONCLUSION: The finding of this study showed that most transmission of tuberculosis infection occurs in homes, contact homes, health centers, and hospitals. These place evaluations allow the identification of people with more contact and in need of screening, so critically leading to the identification of more patients with active TB.

Multiple sclerosis projection in Tehran, Iran using Bayesian structural time series.

BACKGROUND: The prevalence of Multiple Sclerosis (MS) has been increasing worldwide and the highest prevalence ratio among Asian countries was reported in Iran. This study aims to estimate the increase in MS occurrence during more than three decades in Tehran and forecast the future condition of the disease using time series approaches for the next ten years. METHODS: The cross-sectional study was conducted from 1999 to 2019 based on records of MS cases from Iranian MS Society (IMSS) registry system. The prevalence was estimated using population data presented by the Statistical Centre of Iran. Through Bayesian Structural Time Series (BSTS) model, we want to predict the prevalence of familial and sporadic MS in the next ten years. . RESULTS: Among 22,421 cases with MS, 16,831 (75.1 %) were female and 5589 (24.9 %) were male. Female to male ratio was 3.0:1 and the number of familial MS cases were 2982 (13.3 %) of subjects. Female gender was less responsible for higher rate of MS in familial definition (beta = 0.020) in comparison to sporadic cases (beta = 0.034). Forecasting by BSTS revealed an increase in MS prevalence for the next ten years so that the prevalence rate for total, familial and sporadic MS respectively begins with 189.50 (183.94-195.14), 25.69 (24.97-26.45) and 163.74(159.06-168.57) in 2020 and ends with 220.84 (171.48-266.92), 30.79 (24.16-37.15), and 189.33(146.97-230.19) in 2029. CONCLUSIONS: According to the findings, MS prevalence increased during three decades and it will increase over the next ten years. Tehran province is one of the regions with highest MS prevalence in Asia. The results of present study indicated that females are at higher risk for MS than males in both sporadic and familial MS.

Assisted reproductive technology and the risk of preeclampsia: an updated systematic review and meta-analysis.

BACKGROUND: The objective of this systematic review and meta-analyses was to assess the risk of preeclampsia among women who conceived with assisted reproductive technology (ART). METHODS: We searched the ISI Web of Knowledge, Medline/PubMed, Scopus, and Embase (from inception to May 2017) for English language articles using a list of key words. In addition, reference lists from identified studies and relevant review articles were also searched. Data extraction was performed by two authors, and the study quality was assessed using the Newcastle-Ottawa Scale. Random-effects model meta-analysis was applied to pool the relative risks (RR) across studies. RESULTS: A total of 48 studies (5 case-control studies and 43 cohort studies) were included in this meta-analysis. The Cochran Q test and I2 statistics revealed substantial heterogeneity (Q = 26,313.92, d.f. = 47, p < 0.001 and I2 = 99.8%). Meta-analysis showed a significant increase in preeclampsia in women who conceived by ART compared with those who conceived spontaneously (RR = 1.71, 95% CI = 1.11-2.62, p = 0.015). CONCLUSIONS: The findings of this systematic review indicate that the use of ART treatment is associated with a 1.71-fold increase in preeclampsia.

The reliability and validity of the Patient Health Questionnaire-9 (PHQ-9) and PHQ-2 in patients with infertility.

BACKGROUND: Depression in patients with infertility often goes undiagnosed and untreated. The Patient Health Questionnaire-9 (PHQ-9) and its ultra-brief version (i.e. PHQ-2) are widely used measures of depressive symptoms. These scales have not been validated in patients with infertility. The aim of the present study was to examine the reliability and validity of the PHQ-9 and PHQ-2 in patients with infertility. METHODS: In this cross-sectional study, a total of 539 patients with infertility from a referral infertility clinic in Tehran, Iran completed the PHQ-9, along with other relevant scales: the WHO-five Well-being Index (WHO-5), the Hospital Anxiety and Depression Scale (HADS), and the Generalized Anxiety Disorder-7 (GAD-7). Factor structure and internal consistency of PHQ-9 were examined via confirmatory factor analysis (CFA) and Cronbach's alpha, respectively. Convergent validity was evaluated by relationship with WHO-5, HADS and GAD-7. RESULTS: The mean total PHQ-9 and PHQ-2 scores were 8.47 ± 6.17 and 2.42 ± 1.86, respectively, and using a cut-off value of 10 (for PHQ-9) and 3 (for PHQ-2), the prevalence of depressive symptoms was 38.6 and 43.6%, respectively. The Cronbach's alphas for PHQ-9 and PHQ-2 were, respectively, 0.851 and 0.767, indicating good internal consistency. The CFA results confirmed the one-factor model of the PHQ-9 (χ2/df = 4.29; CFI = 0.98; RMSEA = 0.078 and SRMR = 0.044). Both PHQ-9 and PHQ-2 showed moderate to strong correlation with the measures of WHO-5, HADS-depression, HADS-anxiety, and the GAD-7, confirming convergent validity. In univariate analysis, female sex, long infertility duration, and unsuccessful treatment were significantly associated with depression symptoms. CONCLUSION: Both PHQ-9 and PHQ-2 are brief and easy to use measures of depressive symptoms with good psychometric properties that appear suitable for routine use in patients with infertility.

Evaluation of the effect of teriparatide therapy on mandibular fracture healing in rats with medication-related osteonecrosis of the jaw.

OBJECTIVE: The aim of this study was to evaluate the effect of teriparatide therapy on mandibular fracture healing in rats with medication-related osteonecrosis of the jaw (MRONJ). MATERIALS AND METHODS: To induce MRONJ, a total of 120 rats received intravenous zoledronate 0.06 mg/kg once a week for 6 weeks and their right mandibular first molar was extracted. Eighty of 94 rats with MRONJ were randomly selected and underwent unilateral mandibular osteotomy to replicate a fracture. After surgery, the rats were randomly assigned to T (teriparatide-treated) and C (control) groups. Group T (n = 40) received subcutaneous injection of 2 µg/kg/day teriparatide and group C (n = 40) received the same volume of normal saline until sacrifice. Four and 8 weeks after surgery, 20 rats in each group were sacrificed. Fracture healing was scored using a histological grading system (1 to 10). RESULTS: In group C, at 4 weeks and 8 weeks post-fracture, fibrous and cartilaginous tissues and scant bone formation at the fracture site and lacunae without osteocyte in adjacent mandibular bone were seen. In group T, substantial amounts of new trabecular bone rimmed by osteoblasts and some areas of remodeled mature bone were seen. After 8 weeks, extensive replacement of trabecular bone with mature bone occurred. Except between C4 and C8 groups, the healing score was significantly different between all subgroups. CONCLUSION: Teriparatide therapy successfully improved mandibular fracture healing in rats with MRONJ. However, this study was limited by the use of an animal model whose anatomy, physiology, and drug metabolism might be different from humans. CLINICAL RELEVANCE: The present study showed that teriparatide therapy may be used adjunctive to surgery in the treatment of mandibular fractures in MRONJ patients.

Application of the dyadic data analysis in behavioral medicine research: marital satisfaction and anxiety in infertile couples.

BACKGROUND: Dyadic data analysis (DDA) is increasingly being used to better understand, analyze and model intra- and inter-personal mechanisms of health in various types of dyads such as husband-wife, caregiver-patient, doctor-patient, and parent-child. A key strength of the DDA is its flexibility to take the nonindependence available in the dyads into account. In this article, we illustrate the value of using DDA to examine how anxiety is associated with marital satisfaction in infertile couples. METHODS: This cross-sectional study included 141 infertile couples from a referral infertility clinic in Tehran, Iran between February and May 2017. Anxiety and marital satisfaction were measured by the anxiety subscale of the Hospital Anxiety and Depression Scale and 10-Item ENRICH Marital Satisfaction Scale, respectively. We apply and compare tree different dyadic models to explore the effect of anxiety on marital satisfaction, including the Actor-Partner Interdependence Model (APIM), Mutual Influence Model (MIM), and Common Fate Model (CFM). RESULTS: This study demonstrated a practical application of the dyadic models. These dyadic models provide results that appear to give different interpretations of the data. The APIM analysis revealed that both men's and women's anxiety excreted an actor effect on their own marital satisfaction. In addition, women's anxiety exerted a significant partner effect on their husbands' marital satisfaction. In MIM analysis, in addition to significant actor effects of anxiety on marital satisfaction, women's reports of marital satisfaction significantly predicted men's marital satisfaction. The CFM analysis revealed that higher couple anxiety scores predicted lower couple marital satisfaction scores. CONCLUSION: In sum, the study highlights the usefulness of DDA to explore and test the phenomena with inherently dyadic nature. With regard to our empirical data, the findings confirmed that marital satisfaction was influenced by anxiety in infertile couples at both individual and dyadic level; thus, interventions to improve marital satisfaction should include both men and women. In addition, future studies should consider using DDA when dyadic data are available.

The effect of depression on quality of life in infertile couples: an actor-partner interdependence model approach.

BACKGROUND: Infertility can cause psychological distress and has a negative impact on quality of life (QoL). There have been no studies investigating the effect of depression on QoL in infertile couples at the dyadic level. This study aimed to investigate the effects of actors' and partners' depression on QoL in male-female dyads experiencing infertility using an innovative dyadic analysis approach, the Actor-Partner Interdependence Model (APIM). METHODS: We conducted this cross-sectional study on 180 infertile couples in Tehran, Iran, during August-September 2017. Quality of life and depression were assessed using Fertility Quality of Life and Patient Health Questionnaire-9, respectively. Dyadic data were analyzed by the APIM approach. In this method, actor effect is the impact of a person's depression on his/her own QoL. Partner effect is the impact of a person's depression on his/her partner's QoL. RESULTS: Results from APIM revealed that both males and females' depression exuded an actor effect on their own QoL (ß = - 0.589, p < 0.001; ß = - 0.588, p < 0.001, respectively). Furthermore, males' depression exuded a significant partner effect on their wives' QoL (ß = - 0.128, p = 0.030). Although the partner effect of females' depression on males' QoL was not statistically significant (ß = - 0.108, P = 0.070), males whose wives had higher depression were more to indicate their own QoL was poorer. Based on equality constraint test, both actor and partner effects of depression on QoL were similar between males and females. CONCLUSIONS: The findings suggest that QoL in infertile patients was influenced by not only their own depression but also their spouses' depression; therefore, interventions to improve QoL should include both males and females.

The relationship between marital satisfaction and depression in infertile couples: an actor-partner interdependence model approach.

BACKGROUND: Much evidence consistent with the Marital Discord Model of Depression (MDMD) suggests that marital discord is associated with depression, but no studies examine the relationship between marital satisfaction and depression at the dyadic level in infertile couples. This study examined the effect of actors' and partners' marital satisfaction on depressive symptoms in husband-wife dyads with infertility using an innovative dyadic analysis approach, the Actor-Partner Interdependence Model (APIM). METHODS: In this cross-sectional study, the sample comprised of 141 infertile couples in the evaluation phase of treatment. We collected data in a referral infertility center in Tehran, Iran between February and May 2017. Marital satisfaction and depression were measured using ENRICH marital satisfaction scale and Hospital Anxiety and Depression Scale, respectively, before starting the treatment. Dyadic analysis applying the APIM was used. In this study, actor effect is the impact of a person's marital satisfaction on his/her own depression. Partner effect is the impact of a person's marital satisfaction on his/her partner's depression. RESULTS: The APIM analysis revealed that both men and women's marital satisfaction excreted an actor effect on their own depression (ß = - 0.412, P < 0.001; ß = - 0.263, P = 0.002, respectively). Furthermore, men's marital satisfaction exerted a significant partner effect on their wives' depression symptoms (ß = - 0.170, p = 0.047). However, the wives' marital satisfaction was not related to their husbands' depressive symptoms (ß = - 0.028, P = 0.735). CONCLUSIONS: The findings support that the MDMD is a valid theoretical model for the conceptualization of marital satisfaction and depressive symptoms among infertile couples and suggest that interventions to reduce depressive symptoms should include both men and women.

Locus of control, anxiety, and depression in infertile patients.

This study aimed to examine the relationship of locus of control (LoC) with anxiety and depression disorders, applying multivariate statistical techniques to control for the effects of demographic/fertility variables. This cross-sectional study included 312 infertile patients in a referral fertility center in Tehran, Iran via convenience sampling. The Hospital Anxiety and Depression Scale and the Levenson's Locus of Control Scale were administered to all participants. Hierarchical multiple linear regressions were used to identify factors associated with anxiety and depression. After controlling for demographic/fertility variables, hierarchical regression analyses showed that internal LoC was negatively associated with anxiety (ß = -.213, p < .001) and depression (ß = -.269, p < .001). Powerful others subscale was positively associated with anxiety (ß = .176, p < .001), but there was no significant relationship between this subscale and depression (ß = .047, p = .467). The findings of this study merit the understanding of the role of demographic/fertility characteristics and LoC orientations in anxiety and depression of infertile patients to identify beforehand those patients who might be at risk of experiencing high anxiety and depression and in need of support.

Impact on intraocular pressure after 20-mg decanted triamcinolone acetonide (kenalog) injection when using prophylactic antiglaucoma therapy.

PURPOSE: To analyze intraocular pressure (IOP) response after 20-mg decanted intravitreal triamcinolone acetonide followed by early prophylactic IOP-lowering therapy. METHODS: Overall, IOP results of 120 high-dose decanted intravitreal triamcinolone acetonide injections from 58 nonglaucomatous patients with macular edema, with antiglaucoma therapy prescribed from Week 1 regardless of baseline IOP were retrospectively reviewed. RESULTS: In cases of consistent compliance with IOP-lowering drugs (79.2%), IOP increased by 2 mmHg at 4 months (P = 0.300) and returned to baseline at 6 months. In cases of noncompliance (20.8%), IOP increased by 7 mmHg at 1 month (P < 0.001) and returned to baseline after starting treatment. Multivariate regression analysis showed that nonvitrectomized eyes and noncompliance with IOP-lowering drugs were independent predictors of increase in IOP greater than 21 mmHg (P = 0.0098 and P = 0.0019, respectively). Nonvitrectomized eyes had a 46% greater chance to experience increase in IOP compared with vitrectomized ones. Poor compliance with IOP-lowering drugs lead to a 45% greater likelihood of experiencing increase in IOP compared with compliant patients. Multiple injections were not associated with the increased risk for increase in IOP greater than 21 mmHg (P = 0.273). Of 120 cases, 2 eyes (1.7%) developed uncontrolled IOP and required glaucoma surgery by 4 months, with good final IOP outcome. CONCLUSION: Twenty milligram decanted intravitreal triamcinolone acetonide can be safely used to treat macular edema in nonglaucomatous patients; IOP elevation can be adequately controlled with prophylactic antiglaucoma drugs. Noncompliance with prophylactic therapy creates an early spike in IOP, and vitreous status can significantly impact increase in IOP. Compliance with IOP-lowering drugs should be stressed to patients receiving high-dose intravitreal triamcinolone acetonide especially in cases of nonvitrectomized eyes.

Predicting the pulse of urban water demand: a machine learning approach to deciphering meteorological influences.

OBJECTIVE: This study delves into the impact of urban meteorological elements-specifically, air temperature, relative humidity, and atmospheric pressure-on water consumption in Kamyaran city. Data on urban water consumption, temperature (in Celsius), air pressure (in hectopascals), and relative humidity (in percent) were used for the statistical period 2017-2023. Various models, including the correlation coefficient, generalized additive models (GAM), generalized linear models (GLM), and support vector machines (SVM), were employed to scrutinize the data. RESULTS: Water consumption increases due to the influence of relative humidity and air pressure when the temperature variable is controlled. Under specific air temperature conditions, elevated air pressure coupled with high relative humidity intensifies the response of water consumption to variations in these elements. Water consumption exhibits heightened sensitivity to high relative humidity and air pressure compared to low levels of these factors. During winter, when a western low-pressure air mass arrives and disrupts normal conditions, causing a decrease in pressure and temperature, urban water consumption also diminishes. The output from the models employed in this study holds significance for enhancing the prediction and management of water resource consumption.

Evaluating the mortality and health rate caused by the PM2.5 pollutant in the air of several important Iranian cities and evaluating the effect of variables with a linear time series model.

All over the world, the level of special air pollutants that have the potential to cause diseases is increasing. Although the relationship between exposure to air pollutants and mortality has been proven, the health risk assessment and prediction of these pollutants have a therapeutic role in protecting public health, and need more research. The purpose of this research is to evaluate the ill-health caused by PM2.5 pollution using AirQ + software and to evaluate the different effects on PM2.5 with time series linear modeling by R software version 4.1.3 in the cities of Arak, Esfahan, Ahvaz, Tabriz, Shiraz, Karaj and Mashhad during 2019-2020. The pollutant hours, meteorology, population and mortality information were calculated by the Environmental Protection Organization, Meteorological Organization, Statistics Organization and Statistics and Information Technology Center of the Ministry of Health, Treatment and Medical Education for 24 h of PM2.5 pollution with Excel software. In addition, having 24 h of PM2.5 pollutants and meteorology is used to the effect of variables on PM2.5 concentration. The results showed that the highest and lowest number of deaths due to natural deaths, ischemic heart disease (IHD), lung cancer (LC), chronic obstructive pulmonary disease (COPD), acute lower respiratory infection (ALRI) and stroke in The effect of disease with PM2.5 pollutant in Ahvaz and Arak cities was 7.39-12.32%, 14.6-17.29%, 16.48-8.39%, 10.43-18.91%, 12.21-22.79% and 14.6-18.54 % respectively. Another result of this research was the high mortality of the disease compared to the mortality of the nose. The analysis of the results showed that by reducing the pollutants in the cities of Karaj and Shiraz, there is a significant reduction in mortality and linear modeling provides a suitable method for air management planning.

Social determinants of spatial inequalities in COVID-19 outcomes across England: A multiscale geographically weighted regression analysis.

A variety of factors are associated with greater COVID-19 morbidity or mortality, due to how these factors influence exposure to (in the case of morbidity) or severity of (in the case of mortality) COVID-19 infections. We use multiscale geographically weighted regression to study spatial variation in the factors associated with COVID-19 morbidity and mortality rates at the local authority level across England (UK). We investigate the period between March 2020 and March 2021, prior to the rollout of the COVID-19 vaccination program. We consider a variety of factors including demographic (e.g. age, gender, and ethnicity), health (e.g. rates of smoking, obesity, and diabetes), social (e.g. Index of Multiple Deprivation), and economic (e.g. the Gini coefficient and economic complexity index) factors that have previously been found to impact COVID-19 morbidity and mortality. The Index of Multiple Deprivation has a significant impact on COVID-19 cases and deaths in all local authorities, although the effect is the strongest in the south of England. Higher proportions of ethnic minorities are associated with higher levels of COVID-19 mortality, with the strongest effect being found in the west of England. There is again a similar pattern in terms of cases, but strongest in the north of the country. Other factors including age and gender are also found to have significant effects on COVID-19 morbidity and mortality, with differential spatial effects across the country. The results provide insights into how national and local policymakers can take account of localized factors to address spatial health inequalities and address future infectious disease pandemics.

Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens.

Radiotheranostics refers to the pairing of radioactive imaging biomarkers with radioactive therapeutic compounds that deliver ionizing radiation. Given the introduction of very promising radiopharmaceuticals, the radiotheranostics approach is creating a novel paradigm in personalized, targeted radionuclide therapies (TRTs), also known as radiopharmaceuticals (RPTs). Radiotherapeutic pairs targeting somatostatin receptors (SSTR) and prostate-specific membrane antigens (PSMA) are increasingly being used to diagnose and treat patients with metastatic neuroendocrine tumors (NETs) and prostate cancer. In parallel, radiomics and artificial intelligence (AI), as important areas in quantitative image analysis, are paving the way for significantly enhanced workflows in diagnostic and theranostic fields, from data and image processing to clinical decision support, improving patient selection, personalized treatment strategies, response prediction, and prognostication. Furthermore, AI has the potential for tremendous effectiveness in patient dosimetry which copes with complex and time-consuming tasks in the RPT workflow. The present work provides a comprehensive overview of radiomics and AI application in radiotheranostics, focusing on pairs of SSTR- or PSMA-targeting radioligands, describing the fundamental concepts and specific imaging/treatment features. Our review includes ligands radiolabeled by 68Ga, 18F, 177Lu, 64Cu, 90Y, and 225Ac. Specifically, contributions via radiomics and AI towards improved image acquisition, reconstruction, treatment response, segmentation, restaging, lesion classification, dose prediction, and estimation as well as ongoing developments and future directions are discussed.

Estimating the health impacts of exposure to Air pollutants and the evaluation of changes in their concentration using a linear model in Iran.

In big and industrial cities of developing countries, illness and mortality from long-term exposure to air pollutants have become a serious issue. This research was carried out in 2019-2020 to estimate the health impacts of PM10, NO2 and O3 pollutants by using AirQ+ and R statistical programming software in Arak, Isfahan, Tabriz, Shiraz, Karaj, and Mashhad. Mortality statistics, number of people in required age groups, and amount of pollutants were gathered respectively from different agencies like Statistics and Information Technology of the Ministry of Health, Statistical Center, and Department of Environment and by using Excel, the average 24-hour and 1-hour concentration and maximum 8-hour concentration for PM10, NO2 and O3 pollutants were gathered. We used linear mixed impacts model to account for the longitudinal observations and heterogeneity of the cities. The results of the study showed high number of deaths due to chronic bronchitis in adults, premature death of infants, and respiratory diseases in Mashhad. This research highlights the importance of estimation of health impacts from exposure to air pollutants on residents of the studied cities.

Investigating the diagnostic and prognostic value of anti-SARS-CoV-2 Spike IgG/IgM ELISA tests in patients infected with coronavirus Delta variant.

Aim: This study aimed to investigate the diagnostic and prognostic value of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike IgG/IgM antibodies in patients infected with coronavirus Delta variant. Methods: This analytical observational study included 270 unvaccinated patients (aged ≥18 years) diagnosed with coronavirus disease 2019 (COVID-19) Delta variant who referred to Emergency Department of our hospital. The serum levels of anti-SARS-CoV-2 Spike IgG and IgM were measured by indirect ELISA. Main measured outcomes included anti-SARS-CoV-2 Spike IgG and IgM, chest computed tomography (CT) severity score, clinical and laboratory findings which were prospectively evaluated throughout the study period. Results: The IgM levels in critical patients were significantly higher than non-critical patients (p<0.05). But the mean level of IgG in critical patients was not significantly different from its level in non-critical patients (p>0.05). However, a significant positive correlation was observed between the levels of both antibodies and chest CT severity score (p<0.0001); this implies that their levels may reflect the degree of lung involvement. The IgM level on 15th-16th days after symptoms onset was significantly associated with the hazard of death even after adjusting for all other factors (adjusted HR (95%CI):1.28(1.014_1.63), p=0.03), whereas IgG was not (p>0.05). The survival probability among patients with IgM level ≥8.67 RU/ml (34.2%) was significantly lower than those with IgM level <8.67 RU/ml (99.5%, p=0.0001). Conclusions: Anti-SARS-CoV-2 Spike IgM antibody was significantly associated with the disease severity and risk of death in unvaccinated patients infected with coronavirus Delta variant. However, further large-scale investigations on diverse infected populations are required to precisely determine the diagnostic/prognostic value of these antibodies.

Infants' gut microbiome data: A Bayesian Marginal Zero-inflated Negative Binomial regression model for multivariate analyses of count data.

The infants' gut microbiome is dynamic in nature. Literature has shown high inter-individual variability of gut microbial composition in the early years of infancy compared to adulthood. Although next-generation sequencing technologies are rapidly evolving, several statistical analysis aspects need to be addressed to capture the variability and dynamic nature of the infants' gut microbiome. In this study, we proposed a Bayesian Marginal Zero-inflated Negative Binomial (BAMZINB) model, addressing complexities associated with zero-inflation and multivariate structure of the infants' gut microbiome data. Here, we simulated 32 scenarios to compare the performance of BAMZINB with glmFit and BhGLM as the two other widely similar methods in the literature in handling zero-inflation, over-dispersion, and multivariate structure of the infants' gut microbiome. Then, we showed the performance of the BAMZINB approach on a real dataset using SKOT cohort (I and II) studies. Our simulation results showed that the BAMZINB model performed as well as those two methods in estimating the average abundance difference and had a better fit for almost all scenarios when the signal and sample size were large. Applying BAMZINB on SKOT cohorts showed remarkable changes in the average absolute abundance of specific bacteria from 9 to 18 months for infants of healthy and obese mothers. In conclusion, we recommend using the BAMZINB approach for infants' gut microbiome data taking zero-inflation and over-dispersion properties into account in multivariate analysis when comparing the average abundance difference.