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Understanding the specific type of brain malignancy, source of brain metastasis, and underlying transformation mechanisms can help provide better treatment and less harm to patients. The tumor microenvironment plays a fundamental role in cancer progression and affects both primary and metastatic cancers. The use of single-cell RNA sequencing to gain insights into the heterogeneity profiles in the microenvironment of brain malignancies is useful for guiding treatment decisions. To comprehensively investigate the heterogeneity in gliomas and brain metastasis originating from different sources (lung and breast), we integrated data from three groups of single-cell RNA-sequencing datasets obtained from GEO. We gathered and processed single-cell RNA sequencing data from 90,168 cells obtained from 17 patients. We then employed the R package Seurat for dataset integration. Next, we clustered the data within the UMAP space and acquired differentially expressed genes for cell categorization. Our results underscore the significance of macrophages as abundant and pivotal constituents of gliomas. In contrast, lung-to-brain metastases exhibit elevated numbers of AT2, cytotoxic CD4+ T, and exhausted CD8+ T cells. Conversely, breast-to-brain metastases are characterized by an abundance of epithelial and myCAF cells. Our study not only illuminates the variation in the TME between brain metastasis with different origins but also opens the door to utilizing established markers for these cell types to differentiate primary brain metastatic cancers.

BackgroundProstate cancer is affecting males globally, with several complications. Zinc can play roles in cancers. We aimed to clarify the association between zinc levels or intake with prostate cancer development.MethodsWe searched PubMed, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), and Web of Science until May 1, 2023. We included case-controls and cross-sectionals that measured zinc level and/or intake in patients with prostate cancer or cohorts that evaluated the association between zinc and prostate cancer development. Studies that did not have a healthy control group were excluded. Joanna Briggs Institute was used for quality assessment. Publication bias was evaluated using Egger's and Begg's tests and funnel plot.ResultsOverall, 52 studies (n = 44 case controls, n = 4 cohorts, and n = 4 cross sectionals) with a total number of 163909 participants were included. Serum (standardized mean difference (SMD): -1.11; 95% confidence interval (CI): -1.67, -0.56), hair (SMD: -1.31; 95% CI: -2.19, -0.44), and prostatic fluid or tissue zinc levels (SMD: -3.70; 95% CI: -4.90, -2.49) were significantly lower in prostate cancer patients. There were no significant differences in nail zinc level and zinc intake between those with prostate cancer and healthy controls. There was no publication bias except for serum and hair zinc levels based on Begg's and Egger's tests, respectively. The mean risk of bias scores were 4.61 in case-controls, eight in cohorts, and seven in cross-sectionals.ConclusionsOverall, high zinc levels might have a protective role in prostate cancer, which can be used as a therapeutic or preventive intervention. Future large-scale studies are needed to confirm the association.

The emergence of content-centric network has resulted in a substantial increase in data transmission in both uplink and downlink directions. To tackle the ensuing challenges of network congestion and bottlenecks in backhaul links within Beyond Fifth Generation (B5G) networks, data caching has emerged as a popular solution. However, caching for uplink transmission in a distributed B5G scenario poses several challenges, including duplicate content matching and users' obliviousness about cached contents. Furthermore, it is important to maximize available space by caching the most popular contents in a distributed manner. In this paper, we propose two schemes for uplink transmission in distributed B5G SCNs. The first scheme focuses on content matching to eliminate duplicate contents among distributed caches, while the second scheme redistributes un-duplicated cached contents among distributed caches based on their available space and content's size. These approaches aim to enhance energy and spectral efficiency by reducing unnecessary uploads and optimizing distributed content caching, in addition to improve the content delivery. The analysis shows that the proposed schemes outperform the existing schemes by improving the cache hit ratio, cache hit probability, overall distributed cache efficiency, and diversity by 29.17%, 74.89%, 24.17%, and, 80%, respectively. Furthermore, the average throughput, Spectrum Efficiency (SE), and Energy Efficiency (EE) of the access network is improved by 17.78%, 18%, and 78%, respectively. Besides that, the EE and SE of both the sidehaul and backhaul links of the SBSs are also improved.

Degenerative eye diseases cause partial or complete blindness due to photoreceptor degeneration. Optogenetic gene therapy is a revolutionary technique combining genetics and optical methods to control the function of neurons. Due to the inherent risk of photochemical damage, the light intensity necessary to activate Opto-mGluR6 surpasses the safe threshold for retinal illumination. Conversely, red-shifted lights pose a significantly lower risk of inducing such damage compared to blue lights. We designed red-shifted Opto-mGluR6 photopigments with a wide, red-shifted working spectrum compared to Opto-mGluR6 and examined their excitation capability in vitro. ROM19, ROM18 and ROM17, red-shifted variants of Opto-mGluR6, were designed by careful bioinformatics/computational studies. The predicted molecules with the best scores were selected, synthesised and cloned into the pAAV-CMV-IRES-EGFP vector. Expression of constructs was confirmed by functional assessment in engineered HEK-GIRK cells. Spectrophotometry and patch clamp experiments demonstrated that the candidate molecules were sensitive to the desired wavelengths of the light and directly coupled light stimuli to G-protein signalling. Herein, we introduce ROM17, ROM18 and ROM19 as newly generated, red-shifted variants with maximum excitation red-shifted of ~ 40nm, 70 nm and 126 nm compared to Opto-mGluR6. [ABSTRACT FROM AUTHOR]

Background: Gut microbiota play important roles in several diseases like viral infections. In this systematic review, our objective was to assess the efficacy and safety of fecal microbiota transplantation (FMT) in treating various viral diseases. Methods: We conducted searches on databases including PubMed, Web of Science, Scopus, and Google Scholar until November 2023. Clinical trials reported outcomes related to safety of FMT or its efficacy in patients with viral diseases were included. We excluded other types of studies that enrolled healthy individuals or patients with other disorders and did not use FMT. The assessment of bias risk was conducted using the National Institutes of Health (NIH) study quality evaluation tool. Results: Eight studies with total 196 participants were included. Viral diseases were human immunodeficiency virus (HIV), hepatitis B, COVID-19 and Clostridioides difficile coinfection, and cytomegalovirus colitis. In hepatitis B cases, HBeAg clearance was significant in those received FMT (p<0.01), while it was not significant in another one (p = 0.19). A clinical response was noted in 37.5% of patients with cytomegalovirus colitis, with an equal percentage achieving clinical remission post-FMT. There was a significant reduction in Clostridioides difficile relapse rate in FMT group than controls in coinfection of Clostridioides difficile and COVID-19 (2.17% vs. 42.5%, p<0.05). In patients with HIV, partial engraftment of the donor microbiome and increases in alpha diversity were observed after FMT. No severe adverse events were reported. Most studies had fair or good qualities. Conclusions: Our findings revealed FMT as a promising, safe treatment for some viral diseases. It improved viral clearance, clinical outcomes, and inflammation. However, the varying responses and small sample sizes call for more trials on FMT in viral diseases. [ABSTRACT FROM AUTHOR]

One of the critical challenges in managing colorectal cancer (CRC) is the development of oxaliplatin (OXP) resistance. Long non-coding RNAs (lncRNAs) have a crucial role in CRC progression and chemotherapy resistance, with exosomal lncRNAs emerging as potential biomarkers. This study aimed to predict key lncRNAs involved in OXP-resistance using in-silico methods and validate them using RT-qPCR methods in CRC cells and their isolated exosomes. Two public datasets, GSE42387 and GSE119481, were downloaded from the GEO database to identify differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) associated with OXP-resistance in the HCT116 cell line. The analysis of GSE42387 revealed 210 DEGs, and GSE119481 identified 73 DEmiRNAs. A protein-protein interaction (PPI) network analysis of the DEGs identified 133 interconnected genes, from which the top ten genes with the highest degree scores were selected. By intersecting predicted miRNAs targeting these genes with the DEmiRNAs, 38 common miRNAs were found. Subsequently, 224 lncRNAs targeting these common miRNAs were predicted. LncRNA-miRNA-mRNA network were constructed and the top five lncRNAs with the highest degree scores were identified. Analysis using the Kaplan-Meier plotter database revealed that the key lncRNAs NEAT1, OIP5-AS1, and MALAT1 are significantly associated with the overall survival of CRC patients. To validate these lncRNAs, OXP-resistant HCT116 sub-cell line (HCT116/OXR) was developed by exposing parental HCT116 cells to gradually increasing concentrations of OXP. Exosomes derived from both HCT116 and HCT116/OXR cells were isolated and characterized utilizing dynamic light scattering (DLS), transmission electron microscopy (TEM), and Western blotting. RT-qPCR confirmed elevated levels of NEAT1, OIP5-AS1, and MALAT1 in HCT116/OXR cells and their exosomes compared to parental HCT116 cells and their exosomes. This study concludes that NEAT1, OIP5-AS1, and MALAT1 are associated with the OXP-resistance in CRC. The high levels of these lncRNAs in exosomes of resistant cells suggest their involvement in intercellular communication and resistance propagation. This positioning makes them promising biomarkers for OXP-resistance in CRC. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic required higher education institutions to rapidly transition to Emergency Remote Instruction (ERI) with little preparation. Discussions are now underway globally to learn the lessons of COVID-19 and to use this knowledge to shape the future of learning science in higher education. In this study, we examined the experiences of instructors and students to ERI in three universities across three continents-America, Europe, and Australia. We measured the instructional strategies used by instructors including assessment types, and interaction opportunities during and outside class schedules. We also measured the learning challenges experienced by students including planning, distractions, technology, learning resources, their views on educational quality and what characterized quality interactions during ERI. Our findings suggest that most instructional strategies used by instructors changed little during ERI, although the nature of instructor and student interactions during class relied more heavily on technology. Students reported significant learning challenges which included distractions from their physical and social media environments and access to technology. Both instructors and students reported that interactions with each other and their peers were concerningly low, albeit similar to pre COVID-19 pandemic levels. There were differences in the perceptions of instructors and students on whether instructor-student interactions were better or worse online. Common among all universities, there was a large proportion of students reporting mental health and work-related stress. Lessons to be learned from the COVID-19 pandemic include ensuring more support for instructors to implement effective and equitable pedagogies and an increased recognition of the importance of practicals, and the social, interactive and hands-on aspects of learning science in higher education. We predict that the incorporation of active learning pedagogies and strategies which increase student engagement and foster a sense of belonging will be ongoing global challenges for learning science in a post COVID-19 campus.

The study of exercise preconditioning can develop strategies to prevent cardiovascular diseases and outline the efficient exercise model. However, the exercise type with the most protective effect against ischemia-reperfusion injury is unknown. In this study, we examined the effects of three kinds of exercise preconditioning on myocardial ischemia-reperfusion in adult rats and explored the possible underlying mechanisms. Male Wistar rats subjected to ten weeks of endurance, resistance, and concurrent training underwent ischemia (30 min) and reperfusion (120 min) induction. Then, infarction size, serum levels of the CK-MB, the redox status, and angiogenesis proteins (VEGF, ANGP-1, and ANGP-2) were measured in the cardiac tissue. Results showed that different exercise training modes have the same reduction effects on infarction size, but ischemia-reperfusion-induced CK-MB was lower in response to endurance training and concurrent training. Furthermore, cardiac VEGF levels increased in all three kinds of exercise preconditioning but ischemia-reperfusion-induced ANGP-1 elevated more in endurance training. The cardiac GPX activity was improved significantly through the resistance and concurrent exercise compared to the endurance exercise. In addition, all three exercise preconditioning models decreased MPO levels, and ischemia reperfusion-induced MDA was lower in endurance and resistance training. Overall, these results indicated that cardioprotection of exercise training against ischemia-reperfusion injury depends on the exercise modality. Cardioprotective effects of aerobic, resistance, and concurrent exercises are due to different mechanisms. The preconditioning effects of endurance training are mediated mainly by pervasive angiogenic responses and resistance training through oxidative stress amelioration. The preconditioning effects of concurrent training rely on both angiogenesis and oxidative stress amelioration.

IntroductionThe accident of falling from a height is high among construction workers. Construction workers do not use harnesses. Thus, the present study was conducted to identify the factors affecting the non-use of harnesses among construction workers in Tehran, Iran.Materials and methodsIn this study was conducted by interviewing professors and construction workers in order to identify factors affecting the non-use of harness. Factors influencing the non-use of safety harnesses were identified from the workers' point of view. The obtained data were classified and coded using MAXQDA 10 software. After that, the most essential, effective and powerful factors were identified using the degree and intersectionality of social network analysis.ResultsAccording to the interview results, 27 factors were determined as factors affecting the non-use of harnesses by construction workers and divided into four main groups. The four groups were harness design, management factors, harness comfort, and attitudinal factors. Based on the results of the degree centrality, the non-ergonomic design and attitude of the harness inefficiency were identified as the most influential and powerful factors. The betweenness indicator also showed that the non-ergonomic design could mediate other factors in the non-use of the harness.ConclusionThe findings showed that by considering various factors such as considering more comfort in the design of the ergonomic harness, it produced a better product. Also, the use of safety harnesses by workers increases.

BackgroundThe precise impact of sex difference on in-hospital mortality in ST-elevation myocardial infarction (STEMI) patients are unclear, and the studies are no longer consistent. Therefore, we sought to evaluate the impact of sex differences in a cohort of STEMI patients.MethodsWe analyzed the data of 2647 STEMI patients enrolled in the Kermanshah STEMI Cohort from July 2017 to May 2020. To accurately clarify the relationship between sex and hospital mortality, propensity score matching (PSM) and causal mediation analysis was applied to the selected confounder and identified intermediate variables, respectively.ResultsBefore matching, the two groups differed on almost every baseline variable and in-hospital death. After matching with 30 selected variables, 574 male and female matched pairs were significantly different only for five baseline variables and women were no longer at greater risk of in-hospital mortality (10.63% vs. 9.76%, p = 0.626). Among the suspected mediating variables, creatinine clearance (CLCR) alone accounts for 74% (0.665/0.895) of the total effect equal to 0.895(95% CI: 0.464-1.332). In this milieu, the relationship between sex and in-hospital death was no longer significant and reversed -0.233(95% CI: -0.623-0.068), which shows the full mediating role of CLCR.ConclusionOur research could help address sex disparities in STEMI mortality and provide a consequence. Moreover, CLCR alone can fully explain this relationship, which can highlight the importance of CLCR in predicting the short-term outcomes of STEMI patients and provide a useful indicator for clinicians.

Auricularia cornea Ehrenb (syn. A. polytricha) is a wood-decaying fungi known as black ear mushroom. Earlike gelatinous fruiting body distinguishes them from other fungi. Industrial wastes have the potential to be used as the basic substrate to produce mushrooms. Therefore, 16 substrate formulations were prepared from different ratios of beech (BS) and hornbeam sawdust (HS) supplemented with wheat (WB) and rice brans (RB). The pH and initial moisture content of substrate mixtures were adjusted to 6.5 and 70%, respectively. The comparison of in vitro growth characteristics of the fungal mycelia under the different temperatures (25, 28, and 30°C), and culture media [yeast extract agar (YEA), potato extract agar (PEA), malt extract agar (MEA), and also HS and BS extract agar media supplemented with maltose, dextrose, and fructose revealed that the highest mycelial growth rate (MGR; 7.5 mm/day) belonged to HS and BS extract agar media supplemented with three mentioned sugar at 28°C. In A. cornea spawn study, the substrate combination of BS (70%) + WB (30%) at 28°C and moisture contents of 75% displayed the highest mean MGR (9.3 mm/day) and lowest spawn run period (9.0 days). In the bag test, "BS (70%) + WB (30%)" was the best substrate displaying the shortest spawn run period (19.7 days), and the highest fresh sporophore yield (131.7 g/bag), biological efficiency (53.1%) and number of basidiocarp (9.0/bag) of A. cornea. Also, A. cornea cultivation was processed to model yield, biological efficiency (BE), spawn run period (SRP), days for pinhead formation (DPHF), days for the first harvest (DFFH), and total cultivation period (TCP) by multilayer perceptron-genetic algorithm (MLP-GA). MLP-GA (0.81-0.99) exhibited a higher predictive ability than stepwise regression (0.06-0.58). The forecasted values of the output variables were in good accordance with their observed ones corroborating the good competency of established MLP-GA models. MLP-GA modeling exhibited a powerful tool for forecasting and thus selecting the optimal substrate for maximum A. cornea production.

Background and aims: Application of developmental assets, one of existing Positive Youth Development (PYD) frameworks, has gained momentum in research, policy formulations, and interventions, necessitating the introduction of the most efficient scales for this framework. The present study protocol aims to conduct a systematic review and meta-analysis of developmental assets scales to document the underlying logic, objectives, and methodologies earmarked for the identification, selection, and critical evaluation of these scales. Methods and materials: In accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P), the intended search will encompass databases of PubMed, Scopus, Web of Knowledge, and PsycINFO, spanning from the inception of 1988 to 1st of April 2024. The review will include articles published published in English language focusing on individuals aged 10 to 29 years and reporting at least one type of reliability or validity of developmental assets scales. The review process will be in compliance with the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN), and the overall quality of evidence will be determined using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) guidelines. Discussion: This comprehensive assessment aims to identify potential biases in prior research and offer guidance to scholars regarding the optimal scales for developmental assets in terms of validity, reliability, responsiveness, and interpretability The evidence-based appraisal of the scales strengths and limitations is imperative in shaping future research, enhancing their methodological rigor, and proposing refinements to existing instruments for developmental assets. [ABSTRACT FROM AUTHOR]

Understanding the specific type of brain malignancy, source of brain metastasis, and underlying transformation mechanisms can help provide better treatment and less harm to patients. The tumor microenvironment plays a fundamental role in cancer progression and affects both primary and metastatic cancers. The use of single-cell RNA sequencing to gain insights into the heterogeneity profiles in the microenvironment of brain malignancies is useful for guiding treatment decisions. To comprehensively investigate the heterogeneity in gliomas and brain metastasis originating from different sources (lung and breast), we integrated data from three groups of single-cell RNA-sequencing datasets obtained from GEO. We gathered and processed single-cell RNA sequencing data from 90,168 cells obtained from 17 patients. We then employed the R package Seurat for dataset integration. Next, we clustered the data within the UMAP space and acquired differentially expressed genes for cell categorization. Our results underscore the significance of macrophages as abundant and pivotal constituents of gliomas. In contrast, lung-to-brain metastases exhibit elevated numbers of AT2, cytotoxic CD4+ T, and exhausted CD8+ T cells. Conversely, breast-to-brain metastases are characterized by an abundance of epithelial and myCAF cells. Our study not only illuminates the variation in the TME between brain metastasis with different origins but also opens the door to utilizing established markers for these cell types to differentiate primary brain metastatic cancers. [ABSTRACT FROM AUTHOR]

To effectively remove Diazinon (DZ), Amoxicillin (AMX), and Crystal Violet (CV) from aquatic environments, a novel granular activated carbon (GAC) modified with Polyethylene glycol 600 (PEG) was created and manufactured. The chemical properties were investigated using a variety of characteristic analyses, including FT-IR, XRD, FESEM, and N2 adsorption/desorption. The effectiveness of GAC-PEG's adsorption for the removal of DZ, AMX, and CV was assessed under a variety of conditions, including a pH of 4–9 for the solution, 0.003–0.05 g doses of adsorbent, 50–400 ppm starting concentration, and a reaction time of 5–25 min. For DZ, AMX, and CV adsorption, the maximum adsorption capacity (Qmax) was 1163.933, 1163.100, and 1150.300 mg g-1, respectively. The Langmuir isotherm described all of the data from these adsorption experiments, and the pseudo-second-order well explains all-adsorption kinetics. Most contacts between molecules, electrostatic interactions, π–π interactions, hydrogen bonding, and entrapment in the modified CAG network were used to carry out the DZ, AMX, and CV adsorption on the GAC-PEG. The retrievability of the prepared adsorbent was successfully investigated in studies up to two cycles without loss of adsorption efficiency, and it was shown that it can be efficiently separated. [ABSTRACT FROM AUTHOR]

We have reviewed over 60 years of studies on healthcare education outreach programs that are aimed to support first-generation, low-income, as well as underrepresented racial and ethnic minority groups (historically marginalized students) to pursue pre-health professions. As a systematic literature review, we present the challenges studies on healthcare education outreach programs had as three main categories: 1) Design, 2) Evaluation, and 3) Analysis. 1) Designs of studies on healthcare education outreach programs often lacked theoretical foundations whereby a) the interventions did not present theories underlying a causal mechanism of inequity in health professions; and/or 1b) the defined outcome measures were not clearly aligned with the problem the intervention tried to address. 2) Evaluations of studies on healthcare education outreach programs were not always conducted effectively whereby: 2a) controlled groups were commonly absent for comparison with the intervention group; and/or 2b) post measures were solely used without pre-measures. 3) Analyses of studies on healthcare education outreach programs were not adequate whereby: 3a) the response rates and effect size were commonly low; and/or 3b) qualitative results commonly did not supplement quantitative results. Overall, our findings reveal studies on healthcare education outreach programs have common challenges that hinder the reliability of their effects supporting historically marginalized students in pursuing pre-health professions. To address such challenges with studies on healthcare education outreach programs aimed at supporting historically marginalized students, we created a decision flow chart for researchers to ask themselves: 1) how is the design guided by theoretical goals; 2) how are measurements used to evaluate success; and 3) how does the analysis lead to reliable results?

Anxiety disorders, including panic disorder (PD), generalized anxiety disorder (GAD), social anxiety disorder (SAD), agoraphobia, and specific phobia, are among the most common psychiatric disorders. Although the traditional pharmacologic treatments for anxiety included barbiturates and then benzodiazepines, the introduction of tricyclic antidepressants, followed by the selective serotonin reuptake inhibitors (SSRIs), marked a tidal shift in the treatment of anxiety. Although not approved for treatment of anxiety disorders (with the exception of trifluoperazine) there is ongoing off-label, unapproved use of both first-generation "typical" antipsychotics (FGAs) and second-generation or "atypical" antipsychotics (SGAs) for anxiety. Although there have been systematic reviews and meta-analyses on the use of antipsychotics in anxiety disorders, most of these reviews focused on SGAs, primarily the use of quetiapine in GAD. Given that there is little known about the potential benefits and short-and long-term risks of using antipsychotics in anxiety, there is a need for an umbrella review of systematic reviews and meta-analyses of the use of both FGAs and SGAs in anxiety disorders. The specific aims of this study are as follows: (1) Evaluate the evidence of efficacy of FGAs and SGAs in anxiety disorders as an adjunctive treatment to SSRIs, serotonin norepinephrine reuptake inhibitors (SNRIs) and other non-antipsychotic medications; (2) Compare monotherapy with antipsychotics to first-line treatments for anxiety disorders in terms of effectiveness, risks, and side effects; and (3) Evaluate the short- and long-term risks and side effects of prescribing antipsychotics in anxiety disorders. The review is registered on PROSPERO (CRD42021237436). Since data extraction has not begun, there is not preliminary data to share.

BackgroundExtracellular vesicles (EVs), including exosomes and microvesicles, are involved in intercellular communication by transferring biomolecules such as mRNA, which has been shown to be as essential biomarkers for many physiological and pathological conditions such as diabetic nephropathy (DN). This study aimed to investigate the expression of CDH1, CDH2, MCP-1, and PAI-1 mRNAs in blood EVs of DN patients and to determine their accuracy in predicting early-stage DN.MethodsWe recruited 196 participants, including 35 overt DN patients, 53 incipient DN patients, 62 diabetic patients (DM), and 46 healthy individuals. Quantification of the mRNA profile of blood EVs was performed using the qRT-PCR method. The diagnostic performance of mRNA was evaluated using receiver operating characteristic analysis.ResultsThe mRNA expression of CDH2 and MCP-1 was downregulated in overt DN group (0.22-fold change and 0.15-fold change, respectively) and incipient DN group (0.60-fold change and 0.43-fold change, respectively) compared to DM group (1.72-fold change and 2.77-fold change, respectively), while PAI-1 mRNA expression decreased in incipient DN group (0.70-fold change) and DM group (0.58-fold change) compared to control. However, the expression level of CDH1 mRNA was not significantly different among the four groups (p = 0.408). Moreover, CDH2 and MCP-1 mRNAs inversely correlated with creatinine (r = -0.370 and r = -0.361, pConclusionCDH2 and MCP-1 mRNAs expression in blood EVs was decreased with the development of DN, suggesting the renoprotective effect of these mRNAs in diabetic individuals. Moreover, their quantifications could serve as diagnostic biomarkers for early-stage DN.

The advent of content-centric networks and Small Cell Networks (SCN) has resulted in the exponential growth of data for both uplink and downlink transmission. Data caching is considered one of the popular solutions to cater to the resultant challenges of network congestion and bottleneck of backhaul links in B5G networks. Caching for uplink transmission in distributed B5G scenarios has several challenges such as duplicate matching of contents, mobile station's unawareness about the cached contents, and the storage of large content size. This paper proposes a cache framework for uplink transmission in distributed B5G SCNs. Our proposed framework generates comprehensive lists of cache contents from all the Small Base Stations (SBSs) in the network to remove similar contents and assist uplink transmission. In addition, our framework also proposes content matching at a Mobile Station (MS) in contrast to an SBS, which effectively improves the energy and spectrum efficiency. Furthermore, large size contents are segmented and their fractions are stored in the distributed cache to improve the cache hit ratio. Our analysis shows that the proposed framework outperforms the existing schemes by improving the energy and spectrum efficiency of both access and core networks. Compared to the existing state of the art, our proposed framework improves the energy and spectrum efficiency of the access network by 41.28% and 15.58%, respectively. Furthermore, the cache hit ratio and throughput are improved by 9% and 40.00%, respectively.

There is a substantial body of work in physics education looking at gender disparities in physics. Recent work has linked gender disparities in college physics course performance to disparities in high school physics preparation, but to our knowledge, the origin of the disparity in high school physics preparation is still underexplored. In a select sample, we found that women on average had lower force and motion conceptual evaluation (FMCE) pre-scores (the FMCE is a short conceptual assessment of Newton's laws), and FMCE pre-score entirely mediated the effects of high school preparation and social-psychological factors on exam performance. The gender gap in FMCE pre-scores could not be explained by differences in the number of physics courses taken in high school. Instead, we find that the gender gap in the FMCE is partially explained by female students' higher levels of general test anxiety. We hypothesize that the format of the FMCE, a timed assessment, triggers stereotype threat in female students despite being a low-stakes assessment. Therefore, instructors and researchers should take care in interpreting the results of such concept inventory scores and should re-think the way they assess understanding of physics concepts. Results of this work aligned with previous findings on gender disparity in timed exams call upon investigating gender equitable assessment formats for evaluating physics knowledge to replace timed assessments, either high or low stakes.

Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from medical experts. Therefore, artificial intelligence has become a popular tool for the automatic processing of medical data, acting as a supportive tool for doctors. However, the machine learning models used to build these tools are highly dependent on the data used to train them. Large amounts of data can be difficult to obtain in medicine due to privacy reasons, expensive and time-consuming annotations, and a general lack of data samples for infrequent lesions. In this study, we present a novel synthetic data generation pipeline, called SinGAN-Seg, to produce synthetic medical images with corresponding masks using a single training image. Our method is different from the traditional generative adversarial networks (GANs) because our model needs only a single image and the corresponding ground truth to train. We also show that the synthetic data generation pipeline can be used to produce alternative artificial segmentation datasets with corresponding ground truth masks when real datasets are not allowed to share. The pipeline is evaluated using qualitative and quantitative comparisons between real data and synthetic data to show that the style transfer technique used in our pipeline significantly improves the quality of the generated data and our method is better than other state-of-the-art GANs to prepare synthetic images when the size of training datasets are limited. By training UNet++ using both real data and the synthetic data generated from the SinGAN-Seg pipeline, we show that the models trained on synthetic data have very close performances to those trained on real data when both datasets have a considerable amount of training data. In contrast, we show that synthetic data generated from the SinGAN-Seg pipeline improves the performance of segmentation models when training datasets do not have a considerable amount of data. All experiments were performed using an open dataset and the code is publicly available on GitHub.

BackgroundPrevious studies proposed possible applications of spectral-domain optical coherence tomography (SD-OCT) measurements in prognosticating pathologies observed in overweight/obesity, including ocular, vascular, and neurologic consequences. Therefore, we conducted a systematic review and meta-analysis to investigate the changes in the in SD-OCT measurements of the patients with higher body mass index (BMI) compared to normal weight individuals.Materials and methodsWe conducted a systematic search on PubMed, Scopus, and Embase. The search results underwent two-phase title/abstract and full-text screenings. We then analyzed SD-OCT measurements differences in patients with high BMI and controls, and performed meta-regression, sub-group analysis, quality assessment, and publication bias assessment. The measurements included macular thickness, cup to disc ratio, ganglion cell-inner plexiform layer (GC-IPL) and its sub-sectors, RNFL and peripapillary RNFL (pRNFL) and their sub-layers, and choroidal thickness and its sub-sectors.Results19 studies were included in this meta-analysis accounting for 1813 individuals, 989 cases and 824 controls. There was an overall trend towards decreased thickness in high BMI patients, but only two measurements reached statistical significance: temporal retinal nerve fiber layer (RNFL) (Standardized mean difference (SMD): -0.33, 95% confidence interval (CI): -0.53 to -0.14, pConclusionSome ocular layers are thinner in patients with higher BMI than the controls. These SD-OCT measurements might correlate with adverse events related to increased body weight and have prognostic abilities. As SD-OCT is a robust, rapid and non-invasive tool, future guidelines and studies are needed to evaluate the possibility of their integration into care of the patients with obesity.

This study aimed to evaluate the effects of two types of provisional resin cements on the color and retentive strength of two different all-ceramic restorations cemented onto customized zirconia abutments. Forty-two crowns were made of monolithic zirconia and lithium disilicate ceramics (n = 21 per group) and cemented on customized zirconia abutments by using two provisional resin cements of TempBond Clear and Implantlink Semi, and TempBond serving as the control (n = 7 per cement subgroup). The specimens' color was measured before and after cementation and after thermocycling. The color difference was calculated by using CIEDE2000 formula (ΔE00). The tensile force was applied to assess the retentive strength. Kruskal-Wallis, Dunn's post-hoc, and Mann-Whitney non-parametric tests were used to compare ΔE00(1) and ΔE00(2) and two-way ANOVA followed by one-way ANOVA and Tukey's HSD post hoc test and T-test were used to compare retentive strength between subgroups. In the lithium disilicate group, ΔE00 of the control subgroup (TempBond) was significantly higher than that of Implantlink Semi cements subgroup (P = 0.001). But, in the monolithic zirconia group, ΔE00 of the control subgroup (TempBond) was significantly higher than that of Implantlink Semi (P = 0.020) and TempBond Clear cements (P = 0.007). In the monolithic zirconia group, the control subgroup (TempBond) was significantly more retentive than TempBond Clear (P = 0.003) and Implantlink Semi cement (P = 0.001). However, in the lithium disilicate group, Implantlink Semi cement was significantly more retentive than TempBond Clear (P = 0.019) and TempBond (control) (P = 0.001). The final color of both restorations was significantly affected by the provisional resin cement type. The retentive strength was influenced by both the type of cement and ceramic.

Next-generation sequencing (NGS) has revolutionized genetics and enabled the accurate identification of many genetic variants across many genomes. However, detection of biologically important low-frequency variants within genetically heterogeneous populations remains challenging, because they are difficult to distinguish from intrinsic NGS sequencing error rates. Approaches to overcome these limitations are essential to detect rare mutations in large cohorts, virus or microbial populations, mitochondria heteroplasmy, and other heterogeneous mixtures such as tumors. Modifications in library preparation can overcome some of these limitations, but are experimentally challenging and restricted to skilled biologists. This paper describes a novel quality filtering and base pruning pipeline, called Complex Heterogeneous Overlapped Paired-End Reads (CHOPER), designed to detect sequence variants in a complex population with high sequence similarity derived from All-Codon-Scanning (ACS) mutagenesis. A novel fast alignment algorithm, designed for the specified application, has O(n) time complexity. CHOPER was applied to a p53 cancer mutant reactivation study derived from ACS mutagenesis. Relative to error filtering based on Phred quality scores, CHOPER improved accuracy by about 13% while discarding only half as many bases. These results are a step toward extending the power of NGS to the analysis of genetically heterogeneous populations.

The emergence of content-centric network has resulted in a substantial increase in data transmission in both uplink and downlink directions. To tackle the ensuing challenges of network congestion and bottlenecks in backhaul links within Beyond Fifth Generation (B5G) networks, data caching has emerged as a popular solution. However, caching for uplink transmission in a distributed B5G scenario poses several challenges, including duplicate content matching and users' obliviousness about cached contents. Furthermore, it is important to maximize available space by caching the most popular contents in a distributed manner. In this paper, we propose two schemes for uplink transmission in distributed B5G SCNs. The first scheme focuses on content matching to eliminate duplicate contents among distributed caches, while the second scheme redistributes un-duplicated cached contents among distributed caches based on their available space and content's size. These approaches aim to enhance energy and spectral efficiency by reducing unnecessary uploads and optimizing distributed content caching, in addition to improve the content delivery. The analysis shows that the proposed schemes outperform the existing schemes by improving the cache hit ratio, cache hit probability, overall distributed cache efficiency, and diversity by 29.17%, 74.89%, 24.17%, and, 80%, respectively. Furthermore, the average throughput, Spectrum Efficiency (SE), and Energy Efficiency (EE) of the access network is improved by 17.78%, 18%, and 78%, respectively. Besides that, the EE and SE of both the sidehaul and backhaul links of the SBSs are also improved. [ABSTRACT FROM AUTHOR]

Providing less prepared students with supplemental instruction (SI) in introductory STEM courses has long been used as a model in math, chemistry, and biology education to improve student performance, but this model has received little attention in physics education research. We analyzed the course performance of students enrolled in SI courses for introductory mechanics and electricity and magnetism (E&M) at Stanford University compared with those not enrolled in the SI courses over a two-year period. We calculated the benefit of the SI course using multiple linear regression to control for students' level of high school physics and math preparation. We found that the SI course had a significant positive effect on student performance in E&M, but that an SI course with a nearly identical format had no effect on student performance in mechanics. We explored several different potential explanations for why this might be the case and were unable to find any that could explain this difference. This suggests that there are complexities in the design of SI courses that are not fully understood or captured by existing theories as to how they work.

Sampling rare and clustered populations is challenging because of the effort required to find rare units. Heuristically, a practitioner would prefer to discontinue sampling in areas where rare units of interest are apparently extremely sparse or absent. We take advantage of the characteristics of inverse sampling to adaptively inform practitioners when it is efficient to move on to sample new areas. We introduce Adaptive Two-stage Inverse Sampling (ATIS), which is designed to leave a selected area after observation of an a priori number of only non-rare units and to continue sampling in the area when rare units are observed. ATIS is efficient in many cases and yields more rare units than conventional sampling for a rare and clustered population. We derive unbiased estimators of population total and variance. We also introduce an easy-to-compute estimator, which is nearly as efficient as the unbiased estimator. A simulation study on a rare plant population of buttercups (Ranunculus) shows that ATIS even with the easy-to-compute estimator is more efficient than its conventional sampling counterparts and is more efficient than Two-stage Adaptive Cluster Sampling (TACS) for small and moderate final sample sizes. Additional simulations reveal that ATIS is efficient for binary data (e.g., presence or absence) whereas TACS is inefficient for binary data. The overall results indicate that ATIS is consistently efficient compared to conventional sampling and to adaptive cluster sampling in some important cases.

ObjectiveThis study aimed to review the reasons why postpartum women present to the emergency department (ED) over a short term (≤10 days post-delivery) and to identify the risk factors associated with early visits to the ED.MethodsThis retrospective chart review included all women who delivered at a regional health system (William Osler Health System, WOHS) in 2018 and presented to the WOHS ED within 10 days after delivery. Baseline descriptive statistics were used to examine the patient demographics and identify the timing of the postpartum visit. Univariate tests were used to identify significant predictors for admission. A multivariate model was developed based on backward selection from these significant factors to identify admission predictors.ResultsThere were 381 visits identified, and the average age of the patients was 31.22 years (SD: 4.83), with median gravidity of 2 (IQR: 1-3). Most patients delivered via spontaneous vaginal delivery (53.0%). The median time of presentation to the ED was 5.0 days, with the following most common reasons: abdominal pain (21.5%), wound-related issues (12.6%), and urinary issues (9.7%). Delivery during the weekend (OR 1.91, 95% CI 1.00-3.65, P = 0.05) was predictive of admission while Group B Streptococcus positive patients were less likely to be admitted (OR 0.22, CI 0.05-0.97, PConclusionsThis was the first study in a busy community setting that examined ED visits over a short postpartum period. Patient education on pain management and wound care can reduce the rate of early postpartum ED visits.

BackgroundModifications of adjuvants that induce cell-mediated over antibody-mediated immunity is desired for development of vaccines. Nanocapsules have been found to be viable adjuvants and are amenable to engineering for desired immune responses. We previously showed that natural nanocapsules called vaults can be genetically engineered to elicit Th1 immunity and protection from a mucosal bacterial infection. The purpose of our study was to characterize immunity produced in response to OVA within vault nanoparticles and compare it to another nanocarrier.Methodology and principal findingsWe characterized immunity resulting from immunization with the model antigen, ovalbumin (OVA) encased in vault nanocapsules and liposomes. We measured OVA responsive CD8(+) and CD4(+) memory T cell responses, cytokine production and antibody titers in vitro and in vivo. We found that immunization with OVA contain in vaults induced a greater number of anti-OVA CD8(+) memory T cells and production of IFNγ plus CD4(+) memory T cells. Also, modification of the vault body could change the immune response compared to OVA encased in liposomes.Conclusions/significanceThese experiments show that vault nanocapsules induced strong anti-OVA CD8(+) and CD4(+) T cell memory responses and modest antibody production, which markedly differed from the immune response induced by liposomes. We also found that the vault nanocapsule could be modified to change antibody isotypes in vivo. Thus it is possible to create a vault nanocapsule vaccine that can result in the unique combination of immunogen-responsive CD8(+) and CD4(+) T cell immunity coupled with an IgG1 response for future development of vault nanocapsule-based vaccines against antigens for human pathogens and cancer.

Paclitaxel is an effective natural-source chemotherapeutic agent commonly applied to treat a vast range of cancers. In vitro Corylus avellana culture has been reported as a promising and inexpensive system for paclitaxel production. Fungal elicitors have been made known as the most efficient strategy for the biosynthesis induction of secondary metabolites in plant in vitro culture. In this research, C. avellana cell suspension culture (CSC) was exposed to cell extract (CE) and culture filtrate (CF) derived from Camarosporomyces flavigenus, either individually or combined treatment, in mid and late log phase. There is no report on the use of whole fungal elicitors (the combined treatment of CE and CF) for the elicitation of secondary metabolite biosynthesis in plant in vitro culture. The combined treatment of CE and CF significantly led to more paclitaxel biosynthesis and secretion than the individual use of them. Also, multivariate statistical approaches including stepwise regression (SR), ordinary least squares regression (OLSR), principal component regression (PCR) and partial least squares regression (PLSR) were used to model and predict paclitaxel biosynthesis and secretion. Based on value account for (VAF), root mean square error (RMSE), coefficient of determination (R2), mean absolute percentage error (MAPE) and relative percent difference (RPD) can be concluded that mentioned regression models effectively worked only for modeling and predicting extracellular paclitaxel portion in C. avellana cell culture.

Paclitaxel as a microtubule-stabilizing agent is widely used for the treatment of a vast range of cancers. Corylus avellana cell suspension culture (CSC) is a promising strategy for paclitaxel production. Elicitation of paclitaxel biosynthesis pathway is a key approach for improving its production in cell culture. However, optimization of this process is time-consuming and costly. Modeling of paclitaxel elicitation process can be helpful to predict the optimal condition for its high production in cell culture. The objective of this study was modeling and forecasting paclitaxel biosynthesis in C. avellana cell culture responding cell extract (CE), culture filtrate (CF) and cell wall (CW) derived from endophytic fungus, either individually or combined treatment with methyl-β-cyclodextrin (MBCD), based on four input variables including concentration levels of fungal elicitors and MBCD, elicitor adding day and CSC harvesting time, using adaptive neuro-fuzzy inference system (ANFIS) and multiple regression methods. The results displayed a higher accuracy of ANFIS models (0.94-0.97) as compared to regression models (0.16-0.54). The great accordance between the predicted and observed values of paclitaxel biosynthesis for both training and testing subsets support excellent performance of developed ANFIS models. Optimization process of developed ANFIS models with genetic algorithm (GA) showed that optimal MBCD (47.65 mM) and CW (2.77% (v/v)) concentration levels, elicitor adding day (16) and CSC harvesting time (139 h and 41 min after elicitation) can lead to highest paclitaxel biosynthesis (427.92 μg l-1). The validation experiment showed that ANFIS-GA method can be a promising tool for selecting the optimal conditions for maximum paclitaxel biosynthesis, as a case study.

The susceptibility to cardiovascular disease in offspring could be reduced prior to birth through maternal intervention, before and during pregnancy. We evaluated whether the initiation periods of maternal exercise in preconception and pregnancy periods induce beneficial effects in the adult male offspring. Thirty-two female rats were divided into control and exercise groups. The exercise groups involve exercise before pregnancy or the preconception periods, exercise during pregnancy, and exercise before and during pregnancy. The mothers in the exercise groups were run on the treadmill in different periods. Then the birth weight and weekly weight gain of male offspring were measured, and the blood and left ventricle tissue of samples were collected for analysis of the Sirtuin 6 (Sirt6) and insulin growth factor-2 (IGF-2) gene expression, serum levels of low-density lipoprotein (LDL), high-density lipoprotein (HDL), cholesterol (Cho), and triglycerides (TG). There was no significant difference in the birth weight of offspring groups (P = 0.246) while maternal HIIT only during pregnancy leads to reduce weekly weight gain of offspring. Our data showed that Sirt6 and IGF-2 gene expression was increased (P = 0.017) and decreased (P = 0.047) by maternal exercise prior to and during pregnancy, respectively. Also, the serum level of LDL (p = 0.002) and Cho (P = 0.007) were significantly decreased and maternal exercise leads to improves the running speed of the adult male offspring (p = 0.0176). This study suggests that maternal HIIT prior to and during pregnancy have positive intergenerational consequence in the health and physical readiness of offspring.

3D printing is a rapidly evolving field for biological (bioprinting) and non-biological applications. Due to a high degree of freedom for geometrical parameters in 3D printing, prototype printing of bioreactors is a promising approach in the field of Tissue Engineering. The variety of printers, materials, printing parameters and device settings is difficult to overview both for beginners as well as for most professionals. In order to address this problem, we designed a guidance including test bodies to elucidate the real printing performance for a given printer system. Therefore, performance parameters such as accuracy or mechanical stability of the test bodies are systematically analysed. Moreover, post processing steps such as sterilisation or cleaning are considered in the test procedure. The guidance presented here is also applicable to optimise the printer settings for a given printer device. As proof of concept, we compared fused filament fabrication, stereolithography and selective laser sintering as the three most used printing methods. We determined fused filament fabrication printing as the most economical solution, while stereolithography is most accurate and features the highest surface quality. Finally, we tested the applicability of our guidance by identifying a printer solution to manufacture a complex bioreactor for a perfused tissue construct. Due to its design, the manufacture via subtractive mechanical methods would be 21-fold more expensive than additive manufacturing and therefore, would result in three times the number of parts to be assembled subsequently. Using this bioreactor we showed a successful 14-day-culture of a biofabricated collagen-based tissue construct containing human dermal fibroblasts as the stromal part and a perfusable central channel with human microvascular endothelial cells. Our study indicates how the full potential of biofabrication can be exploited, as most printed tissues exhibit individual shapes and require storage under physiological conditions, after the bioprinting process.

Commercially pure titanium was processed by equal channel angular pressing (ECAP) and surface mechanical attrition treatment (SMAT) for the purpose of developing functionally graded titanium used for implants and a gradient structure including nanostructured, deformed and undeformed zones were produced on the samples. In particular, it was aimed to design the gradient-structure in the titanium with enhanced properties by applying 4 ECAP passes to form bulk structure of ultrafine-grains and subsequently subjecting SMAT to the surface of ECAPed samples to produce nanostructured surface region. Microstructural examination was made by electron back scatter diffraction (EBSD). Also, microhardness, nanoindentation, topography, roughness and wettability were evaluated. To examine the biological response, human osteosarcoma cells were cultured in contact with the samples in various time periods and morphology change, cell viability and alkaline phosphate activity were conducted also cell morphology was monitored. EBSD showed development of ultrafine-grained structure after 4 passes of ECAP with an average grain size of 500 nm. Applying SMAT resulted in additional refinement in the ECAP samples, particularly in the subsurface regions to a depth of 112 μm. Furthermore, the SMATed samples showed an enhancement in roughness, wettability and hardness magnitudes. Viability enhanced up to 7% in SMATed + ECAPed sample, although the acceptable cell adhesion, improved cell differentiation and mineralization were seen. The combined use of ECAP and SMAT has shown a good potential for optimizing the design of modern functionally graded medical devices and implants.

Regulating ecosystem services provided by urban forests are of great importance for the quality of life among city dwellers. To reach a maximum contribution to well-being in cities, the urban regulating ecosystem services (URES) must match with the demands in terms of space and time. If we understand the matches or mismatches between the current urban dwellers' desired quality conditions (demand) and the supply of URES by urban forests (UF) in the cities, this will facilitate integrating the concepts of ecosystem services in urban planning and management, but such an assessment has suffered from major knowledge limitations. Since it is complex and problematic to identify the direct demands for URES and the spatiotemporal patterns therein, improving the demand indicators can help to determine the actual requirements. In this paper, a methodological approach based on indicators is presented and demonstrated for two important URES: air quality improvement and global climate change mitigation provided by urban trees and shrubs. Four air quality standards and greenhouse gas reduction targets were used and compared to supplies of the URES in Tabriz, Iran. Our results show that the mean contribution of the URES supply to air quality standards and greenhouse gas reduction targets is modest. Hence, in Tabriz, there is a strong mismatch between demand and supply. Mismatches at the city scale will have to be reduced by both a reduction in pollutant emissions and an increased provisioning of URES supply through urban greenery. The presented assessment approach and the results for Tabriz make it explicit how different the demands and supplies of the two studied URES are, and we expect similar mismatches in many other cities. Therefore, our approach, relatively simple but still realistic and easy-to-apply, can raise awareness about, and the utility of, the ecosystem services concepts for urban planning and policymaking.

Gender disparity in science, technology, engineering, and math (STEM) fields is an on-going challenge. Gender bias is one of the possible mechanisms leading to such disparities and has been extensively studied. Previous work showed that there was a gender bias in how students perceived the competence of their peers in undergraduate biology courses. We examined whether there was a similar gender bias in a mechanical engineering course. We conducted the study in two offerings of the course, which used different instructional practices. We found no gender bias in peer perceptions of competence in either of the offerings. However, we did see that the offerings' different instructional practices affected aspects of classroom climate, including: the number of peers who were perceived to be particularly knowledgeable, the richness of the associated network of connections between students, students' familiarity with each other, and their perceptions about the course environment. These results suggest that negative bias against female students in peer perception is not universal, either across institutions or across STEM fields, and that instructional methods may have an impact on classroom climate.

Background and objectiveHigh quality evidence-based clinical practice guidelines (CPGs) have a major impact on the appropriate diagnosis and management and positive outcomes. The evidence-based healthcare for patients with attention deficit hyperactive disorder (ADHD) is challenging. The objective of this study was to appraise the quality of published CPGs for ADHD.MethodsA systematic review was conducted for ADHD CPGs using CPG databases, DynaMed, PubMed, and Google Scholar. The quality of each included CPG was appraised by three independent appraisers using the Appraisal of Guidelines for Research & Evaluation II (AGREE II) instrument.ResultsSix CPGs were critically reviewed. The AGREE II standardized domain scores revealed variation between the quality of these CPGs with the National Institute of Health and Care Excellence (NICE), University of Michigan Health System, and American Academy of Pediatrics CPGs as the top three. Overall, the recommendations for management of ADHD were similar in these CPGs.ConclusionsReporting of CPG development is often poorly documented. Guideline development groups should aim to follow the AGREE II criteria to improve the standards and quality of CPGs. The NICE CPG showed the best quality. Embedding the AGREE II appraisal of CPGs in the training and education of healthcare providers is recommended. The protocol for this study was published in PROSPERO (International prospective register of systematic reviews). Link: http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42017078712 and is additionally available from protocols.io. Link: https://dx.doi.org/10.17504/protocols.io.q27dyhn.

Road Traffic Accidents (RTA) are a major worldwide public health problem. The aim of this study was to use the growth mixture model for clustering countries on the basis of the mortality rate patterns of RTAs from 2007 to 2013. We obtained the data on RTA death rates from World Health Organization reports and Human Development Index (HDI) of United Nations Development Programme reports for the years 2007, 2010 and 2013. Simple Latent Growth Models (LGM) in 181 countries were applied to estimate overall RTA mortality rate growth trajectories and the latent growth mixture modeling utilized to cluster them. According to non-linear LGM, the overall mortality rate of RTAs showed a decrease from 2007 to 2010 followed by an increase from 2010 to 2013. The HDI covariate had a significant negative and positive effect on intercept and slope of the LGM, respectively. The extracted mixture model appeared to have seven classes with different trends in RTA mortality rates. The worldwide countries were clustered into seven classes. Further studies on each of the seven classes are suggested to provide recommendations for reducing the mortality rate of the RTAs. Additionally, increasing HDI in some countries could have a significant effect on reducing the RTA death rates.

Ambient air quality is one of the most critical threats to human health. In this study, the health and economic benefits of reducing PM2.5 were estimated in the city of Arak during the period of 2017–2019. The concentration data were obtained from the Environmental Protection Organization of Central Province, while the demographic data were obtained from the website of the Iran Statistics Center. The number of premature deaths from all causes, ischemic heart disease, chronic obstructive pulmonary disease, and lung cancer, attributable to PM2.5 pollution was estimated using the Environmental Benefits Mapping and Analysis Program-Comprehensive Version (BenMAP_CE) to limit the guidelines of the World Health Organization. The results showed that improving air quality in 2017, 2018, and 2019 in Arak could prevent the deaths of 729, 654, and 460 people, respectively. The number of years of life lost (YLL) in 2017, 2018, and 2019 was 11383, 10362, and 7260 years, respectively. The total annual economic benefits of reducing the PM2.5 concentration in Arak under the proposed scenarios in 2017, 2018, and 2019 were estimated to be 309,225,507, 262,868,727, and 182,224,053 USD, respectively, using the statistical life method (VSL). Based on the results of this study, there are significant health and economic benefits to reducing PM2.5 concentrations in Arak City. Therefore, planning and adopting control policies to reduce air pollution in this city are necessary. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic required higher education institutions to rapidly transition to Emergency Remote Instruction (ERI) with little preparation. Discussions are now underway globally to learn the lessons of COVID-19 and to use this knowledge to shape the future of learning science in higher education. In this study, we examined the experiences of instructors and students to ERI in three universities across three continents–America, Europe, and Australia. We measured the instructional strategies used by instructors including assessment types, and interaction opportunities during and outside class schedules. We also measured the learning challenges experienced by students including planning, distractions, technology, learning resources, their views on educational quality and what characterized quality interactions during ERI. Our findings suggest that most instructional strategies used by instructors changed little during ERI, although the nature of instructor and student interactions during class relied more heavily on technology. Students reported significant learning challenges which included distractions from their physical and social media environments and access to technology. Both instructors and students reported that interactions with each other and their peers were concerningly low, albeit similar to pre COVID-19 pandemic levels. There were differences in the perceptions of instructors and students on whether instructor-student interactions were better or worse online. Common among all universities, there was a large proportion of students reporting mental health and work-related stress. Lessons to be learned from the COVID-19 pandemic include ensuring more support for instructors to implement effective and equitable pedagogies and an increased recognition of the importance of practicals, and the social, interactive and hands-on aspects of learning science in higher education. We predict that the incorporation of active learning pedagogies and strategies which increase student engagement and foster a sense of belonging will be ongoing global challenges for learning science in a post COVID-19 campus. [ABSTRACT FROM AUTHOR]

Introduction: The accident of falling from a height is high among construction workers. Construction workers do not use harnesses. Thus, the present study was conducted to identify the factors affecting the non-use of harnesses among construction workers in Tehran, Iran. Materials and methods: In this study was conducted by interviewing professors and construction workers in order to identify factors affecting the non-use of harness. Factors influencing the non-use of safety harnesses were identified from the workers' point of view. The obtained data were classified and coded using MAXQDA 10 software. After that, the most essential, effective and powerful factors were identified using the degree and intersectionality of social network analysis. Results: According to the interview results, 27 factors were determined as factors affecting the non-use of harnesses by construction workers and divided into four main groups. The four groups were harness design, management factors, harness comfort, and attitudinal factors. Based on the results of the degree centrality, the non-ergonomic design and attitude of the harness inefficiency were identified as the most influential and powerful factors. The betweenness indicator also showed that the non-ergonomic design could mediate other factors in the non-use of the harness. Conclusion: The findings showed that by considering various factors such as considering more comfort in the design of the ergonomic harness, it produced a better product. Also, the use of safety harnesses by workers increases. [ABSTRACT FROM AUTHOR]