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Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (claims) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms physical distancing and social distancing. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

Abstract Sustainable transportation is vital to climate justice and social equity. Despite the efforts to achieve sustainability, there is still a lack of adequate measurement that integrates land use and transportation systems, which can be barriers to planning implementation. With methodological improvements in fuzzy theory application, this study develops an integrated index to measure the sustainability of multimodal accessibility. We do so by defining a fuzziness degree based on the different trip purposes and modes of transportation with a case study in Isfahan, Iran. Sustainable accessibility indicators were developed for walking, biking, and public transportation to represent the performance of each transportation system, considering the integration with land-use patterns. We analyze transportation modes and the accessibility to five main urban activities, including employment opportunities, education, healthcare, shopping, and recreation services, based on the travel distances, followed by a statistical integration method with Principal Components Analysis (PCA) for each travel mode. The outcome provides insights for urban planners and transportation planners to effectively evaluate the degree of integration between transportation and land-use systems and contribute to enhancing sustainable accessibility.

Abstract Proteolysis-targeting chimeras (PROTACs) have been explored for the degradation of drug targets for more than two decades. However, only a handful of E3 ligase substrate receptors have been efficiently used. Downregulation and mutation of these receptors would reduce the effectiveness of such PROTACs. We recently developed potent ligands for DCAF1, a substrate receptor of EDVP and CUL4 E3 ligases. Here, we focus on DCAF1 toward the development of PROTACs for WDR5, a drug target in various cancers. We report four DCAF1-based PROTACs with endogenous and exogenous WDR5 degradation effects and high-resolution crystal structures of the ternary complexes of DCAF1-PROTAC-WDR5. The structures reveal detailed insights into the interaction of DCAF1 with various WDR5-PROTACs, indicating a significant role of DCAF1 loops in providing needed surface plasticity, and reflecting the mechanism by which DCAF1 functions as a substrate receptor for E3 ligases with diverse sets of substrates.

Abstract Background Research on the relationship between dietary phytochemical intake and the anthropometric indices as well as the diabetic foot ulcers (DFUs) remains inconsistent. We aimed to investigate the associations of dietary phytochemical index (DPI) with the novel anthropometric indices and the severity of DFUs. Methods This cross-sectional study was conducted on 339 adults with type 2 diabetes. Dietary intake was assessed using three 24-hour dietary recalls. To quantify the phytochemical content of the diet, the DPI estimation was done through an equation proposed by McCarty. The International Working Group on the Diabetic Foot (IWGDF) criteria and Wagner classification system were applied to assess DFUs. New anthropometric indices including a body shape index (ABSI), body roundness index (BRI) and abdominal volume index (AVI) were calculated based on formulas. We employed analysis of variance (ANOVA), analysis of covariance (ANCOVA) and logistic regression to explore associations between DPI and the anthropometric indices and DFU variables. Results Our results revealed no significant association between DPI and the foot ulcer indices, following adjusting for the possible covariates. Furthermore, we also examined the relationship between diabetic neuropathy, as measured by monofilament score, and the DPI. Similarly, we did not find any substantial relationship between the DPI and monofilament score (OR: 1.18; 95% CI: 0.66–2.09; Ptrend = 0.56), as well as biochemical indices. Our analysis did not reveal any significant associations between the DPI and ABSI (OR: 0.70; 95% CI: 0.35–1.38; Ptrend = 0.30), BRI (OR: 0.80; 95% CI: 0.33–1.95; Ptrend = 0.59), and AVI (OR: 1.99; 95% CI: 0.92–4.33; Ptrend = 0.08). Conclusions Our study revealed no significant links between the DPI and foot ulcer indices, neuropathy measures, and anthropometric indices. These findings imply that factors beyond dietary phytochemical intake may exert greater influence on the development of foot ulcers in diabetes.

Abstract After cryopreservation, reactive oxygen species (ROS) can damage sperm. Antioxidants are the primary defense against oxidative damage. Berberine is a bioactive alkaloid found in Berberis vulgaris, Curcuma longa, and Ergon grape, and is a potent antioxidant. Due to the negative effects of free radicals in oxidative stress processes, antioxidant chemicals are required to protect sperm. However, berberine has low bioavailability, making it less effective. Loading techniques on nanoparticles and nanotechnology can help overcome this limitation. Selenium nanoparticles were synthesized with barberry extract, and berberine was loaded on them. Berberine nanoparticles were then synthesized using anti-solvent precipitation with a syringe pump technique. The synthesis of nanoparticles was confirmed by EDX, UV-visible, FE-SEM, Zeta-Potential, and FTIR tests. In this experiment, we aim to investigate the impact of nano-berberine and berberine loaded on Se-NPs on goat sperm parameters after freeze-thawing. We assessed the generation of reactive oxygen species (ROS), in vitro fertility, and the subsequent embryo development of zygote with treated sperm after determining the optimal concentration of various chemicals on sperm parameters. The study found that all treatments had significant differences from the control group in terms of motility, viability, DNA and membrane integrity, ROS level, lipid peroxidation, in vitro fertility ability, and the capacity to develop inseminated oocytes (p

Abstract Introduction The accurate prediction of COVID-19 mortality risk, considering influencing factors, is crucial in guiding effective public policies to alleviate the strain on the healthcare system. As such, this study aimed to assess the efficacy of decision tree algorithms (CART, C5.0, and CHAID) in predicting COVID-19 mortality risk and compare their performance with that of the logistic model. Methods This retrospective cohort study examined 5080 cases of COVID-19 in Babol, a city in northern Iran, who tested positive for the virus via PCR from March 2020 to March 2022. In order to check the validity of the findings, the data was randomly divided into an 80% training set and a 20% testing set. The prediction models, such as Logistic regression models and decision tree algorithms, were trained on the 80% training data and tested on the 20% testing data. The accuracy of these methods for the test samples was assessed using measures like ROC curve, sensitivity, specificity, and AUC. Results The findings revealed that the mortality rate for COVID-19 patients who were admitted to hospitals was 7.7%. Through cross validation, it was determined that the CHAID algorithm outperformed other decision tree and logistic regression algorithms in specificity, and precision but not sensitivity in predicting the risk of COVID-19 mortality. The CHAID algorithm demonstrated a specificity, precision, accuracy, and F-score of 0.98, 0.70, 0.95, and 0.52 respectively. All models indicated that factors such as ICU hospitalization, intubation, age, kidney disease, BUN, CRP, WBC, NLR, O2 sat, and hemoglobin were among the factors that influenced the mortality rate of COVID-19 patients. Conclusions The CART and C5.0 models had outperformed in sensitivity but CHAID demonstrates a better performance compared to other decision tree algorithms in specificity, precision, accuracy and shows a slight improvement over the logistic regression method in predicting the risk of COVID-19 mortality in the population under study.

Dowry is considered one of the social traditions rooted in religious principles in Iranian society. The diverse functions of dowry have led this tradition to persist over the years. In recent decades, the prevalence of exorbitant and unreasonable dowries and its social harmful consequences have prompted a reexamination of the legal and jurisprudential nature of such dowries. One of the undesirable consequences is the inheritance of the right to claim them, leading to the prolonged existence of the cases related to it for many years. In this article, the mentioned problem has been examined with a descriptive- analytic method. It appears that solutions based on invalidating unreasonable dowries or relying on evidence indicating the non-inheritance of such rights are not adequate. Hence, as an alternative way, proposing agreements contract like dowry including its positive function but devoid of undesirable consequences is suggested. Such contracts will not addressed to this subject and solve the interpretation of the parties’ intentions, clarify the conditions of mutual consent, and other complex issues around the topic of unreasonable dowries.

Background: Diabetes, a currently threatening disease, has severe consequences for individuals’ health conditions. The present study aimed to investigate the factors affecting the changes in the longitudinal outcome of blood sugar using a three-level analysis with the presence of missing data in diabetic patients. Methods: A total of 526 diabetic patients were followed longitudinally selected from the annual data collected from the rural population monitored by Tonekabon health centers in the North of Iran during 2018-2019 from the Iranian Integrated Health System (SIB) database. In analyzing this longitudinal data, the three-level model (level 1: observation (time), level 2: subject, level 3: health center) was carried out with multiple imputations of possible missing values in longitudinal data. Results: Results of fitting the three-level model indicated that every unit of change in the body mass index (BMI) significantly increased the fasting blood sugar by an average of 0.5 mg/dl (p=0.024). The impact of level 1 (observations) was insignificant in the three-level model. Still, the random effect of level 3 (healthcare centers) showed a highly significant measure for health centers (14.62, p

Objective: to investigate the effects of sodium valproate on plasma concentrations of homocysteine, folate and vitamin B12 levels in epileptic patients with long-standing tonic-clonic seizures compared to newly diagnosed epileptic patients and healthy controls.Material and methods. The study included 90 participants (mean age 36.30±12.83 years, the majority (58.89%) were males) divided into three groups: 30 non-epileptic people (control Group 1), 30 newly diagnosed epileptic patients (Group 2), and 30 patients with long-term tonic-clonic seizures epilepsy (Group 3). In Group 3, patients received sodium valproate therapy. All subjects underwent clinical and neurological examinations. Differences in plasma levels of homocysteine, folic acid and vitamin B12 in three groups were investigated after 6 months of follow-up.Results. Homocysteine level in Groups 2 and 3 was increased; for Group 2 it was significantly higher than for Groups 3 and 1 (p=0.001). Plasma folate level in Groups 2 and 3 was decreased; for Group 3 it was significantly higher than for Group 2 and lower than for Group 1 (p=0.001). Vitamin B12 level in Groups 2 and 3 was decreased, but the difference was not significant (p=0.090). In Groups 1 and 2, a significant correlation was observed between the indicators.Conclusion. Sodium valproate аdministration might disrupt the homeostatic level of homocysteine, folate and vitamin B12 and cause irregularity of their plasma contents in epileptic patients with long-standing tonic-clonic seizures.

Background: This study aimed to investigate the integration of the health belief model (HBM) and the theory of intention to plan preventive behavior for COVID-19 during the pandemic. Methods: In a cross-sectional study, a sample of 480 adult participants from different outpatient clinics were recruited in the study. The participant responded by self-report; the health belief model (HBM) scale, preventive behavior scale, subjective norms scale, the intention of planned behavior scale, and perceived control behavior scale were measured. The hypothesized causal path models were examined using SEM analysis. Results: The HBM had significant effects on perceived behavior control (β=0.60, P=0.001), the intended preventive behavior (β=0.32, P=0.001), and subjective norm (β=0.53, P=0.001). Subsequently, the intention of preventive behavior (β==0.39, P=0.001) and subjective norms (β=0.27, P=0.001) significantly affected the performance of preventive behaviors. The estimated fitting criteria showed that the hypothesized model fits relatively well. Conclusion: The health belief model with the integration of subjective norms, perceived control behavior and mediation by the intention of planned behavior in a pathway relationship explains well the preventive behavior of COVID-19. The findings present a deeper understanding of how integrating HBM and intended planned behavior enhances people’s preventive behavior against COVID-19.

This study aimed to investigate COVID-19's effect on the investments of companies listed on the Tehran Stock Exchange. Descriptive research has two aspects: its purpose and its data collection method. This study's population included all companies on the Tehran Stock Exchange from 2017 to 2022. This period includes 11 seasons of COVID-19 and 11 seasons of normal period. This study used interim financial reporting data. We analyzed it using regression with Stata and E-Views. The test results showed a strong link between COVID-19 and corporate investment. Researchers have studied variables like cash flexibility, life cycle, company size, and ownership structure. The results also showed that the company's ownership and size did not significantly affect its COVID-19 investment. However, the company's life cycle and cash flexibility did have a significant impact on that relationship.

Abstract Cryopreservation of sperm can cause oxidative stress and damage, leading to decreased different functional parameters and fertilization potential. In this study, we evaluated two types of H2S donors: NaHS, a fast-releasing donor, and GYY4137, a slow-releasing donor during cryopreservation of goat sperm. Initially, we determined that 1.5 and 3 μM NaHS, and 15 and 30 μM GYY4137 are optimal concentrations that improved different sperm functional parameters including motility, viability, membrane integrity, lipid peroxidation, and ROS production during incubation at 38.5 °C for 90 min. We subsequently evaluated the impact of the optimal concentration of NaHS and GYY4137 supplementation on various functional parameters following thawing during cryopreservation. Our data revealed that supplementation of extender improved different parameters including post-thaw sperm motility, viability, membrane integrity, and reduced DNA damage compared to the frozen-thawed control group. The supplementation also restored the redox state, decreased lipid peroxidation, and improved mitochondrial membrane potential in the thawed sperm. Finally, we found that supplementation of the extender with NaHS and GYY4137 enhanced IVF outcomes in terms of blastocyst rate and quality of blastocysts. Our results suggest that both donors can be applied for cryopreservation as antioxidants to improve sperm quality and IVF outcomes of frozen-thawed goat sperm.

Abstract Introduction An important application of ROC analysis is the determination of the optimal cut-point for biomarkers in diagnostic studies. This comprehensive review provides a framework of cut-point election for biomarkers in diagnostic medicine. Methods Several methods were proposed for the selection of optional cut-points. The validity and precision of the proposed methods were discussed and the clinical application of the methods was illustrated with a practical example of clinical diagnostic data of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and malondialdehyde (MDA) for prediction of inflammatory bowel disease (IBD) patients using the NCSS software. Results Our results in the clinical data suggested that for CRP and MDA, the calculated cut-points of the Youden index, Euclidean index, Product and Union index methods were consistent in predicting IBD patients, while for ESR, only the Euclidean and Product methods yielded similar estimates. However, the diagnostic odds ratio (DOR) method provided more extreme values for the optimal cut-point for all biomarkers analyzed. Conclusion Overall, the four methods including the Youden index, Euclidean index, Product, and IU can produce quite similar optimal cut-points for binormal pairs with the same variance. The cut-point determined with the Youden index may not agree with the other three methods in the case of skewed distributions while DOR does not produce valid informative cut-points. Therefore, more extensive Monte Carlo simulation studies are needed to investigate the conditions of test result distributions that may lead to inconsistent findings in clinical diagnostics.

Abstract Background Given the limited specificity of D-dimer, there is a perceived need to discover a more precise marker for diagnosing individuals who are suspected of having pulmonary embolism (PE). In this study, by evaluating the increase in the serum level of Apelin-13 and D-dimer, we found valuable findings about Apelin-13, which can be suggested as an auxiliary and non-invasive diagnostic biomarker in individuals with suspected PE, based on the obtained results. Methods In this case-control study, 52 Iranian individuals were included, all of whom were suspected to have PE. These individuals were then divided into two groups based on the results of CT angiography, which is considered the gold standard imaging method for diagnosing PE. The two groups were patients with PE and patients without PE. Finally, the levels of certain markers in the serum were compared between the two groups. Results The mean serum D-dimer levels in patients with PE were significantly elevated (p

Understanding scientific phenomena requires learners to construct mental models of causal systems. Simulation-based discovery learning offers learners the opportunity to construct mental models and test them against the behavior of a simulation. The purpose of this study was to investigate sequential patterns of learner actions and utterances associated with outcomes of simulation-based guided discovery learning. We conducted a "sequence analysis" of data gathered from 11 undergraduate students engaged in discovery learning. Three related methods were used for the sequence analysis: Levenshtein edit distance, k-means clustering of the Levenshtein distance, and the Kohonen generalized median sequence. The median sequences of high-gaining and low-gaining participants showed qualitative differences in how they gathered evidence, stated claims, and drew explanatory inferences. Differences between the sequences of actions and utterances of high-gaining and low-gaining participants suggested ways that students might be guided to enhance discovery learning. By tracking the learning patterns of learners, researchers can determine the conditions under which prompts should be provided and offer recommendations for transforming less effective learning strategies to more effective ones.