Render lighting dataset: A collection of rendered images with varied lighting conditions using blender render engines.

The quality of datasets is crucial in computer graphics and machine learning research and development. This paper presents the Render Lighting Dataset, featuring 63,648 rendered images of Blender's primitive shapes with various lighting conditions and engines. The images were created using Blender 4.0's Cycles and Eevee Render Engines, with careful attention to detail in texture mapping and UV unwrapping. The dataset covers six different lighting conditions, including Area Light, Spotlight, Point Light, Tri-Light, HDRI (Sunlight), and HDRI (Overcast), each adjusted using Blender's different options in the Color Management panel. With thirteen unique materials, ranging from Coastal Sand to Glossy Plastic, the dataset provides visual diversity for researchers to explore material properties under different lighting conditions using different render engines. This dataset serves as a valuable resource for researchers looking to enhance 3D rendering engines. Its diverse set of rendered images under varied lighting conditions and material properties allows researchers to benchmark and evaluate the performance of different rendering engines, develop new rendering algorithms and techniques, optimize rendering parameters, and understand rendering challenges. By enabling more realistic and efficient rendering, advancing research in lighting simulation, and facilitating the development of AI-driven rendering techniques, this dataset has the potential to shape the future of computer graphics and rendering technology.

Dataset of computer science course queries from students: Categorized and scored according to Bloom's taxonomy.

"Why don't students learn?" is a common question that educators try to address. To encourage students to become more engaged in the learning process, we believe in fostering their natural curiosity by encouraging them to ask high-level questions. To support this approach, we have compiled a dataset of questions that we hope will aid in the training of artificial intelligence (AI) models and ultimately improve the learning experience for students. To develop our dataset, we collected anonymous student questioning data in the Summer 2023 semester, utilizing our online application named "Palta Question", resulting in a dataset of 8,811 unique questions. The dataset consists of students' inquiries which underwent basic question validation using a sophisticated keyword-based approach, manual categorization by topic and course content, as well as complexity assessment using Bloom's taxonomy keywords which have also been included in the dataset. To ensure question uniqueness, we implemented the Levenshtein distance algorithm to exclude questions with a high similarity rate. This dataset provides targeted insights into student inquiry patterns and knowledge gaps within the domain of 'Introduction to Computers and Research' and 'Data Structure' courses, originating from the students at Independent University, Bangladesh (IUB). While its scope is confined to a specific student group and academic context, limiting broader applicability, it remains valuable for detailed studies in these subjects and serves as a useful foundation for AI-based educational research tools. To demonstrate the effectiveness of the dataset, we also tested it to train the AI to perform basic tasks like sorting questions according to their courses and topics. However, we envision researchers utilizing it to enhance education and aid in students' learning.

RACares: a conceptual design to guide mHealth relational agent development based on a systematic review.

Background: A relational agent (RA) is a digital tool tailored to communicate with users, aiming to establish a sense of social ease and emotional bond, particularly focusing on their health and well-being concerns. A mobile health (mHealth) RA is particularly crafted to communicate with users within their mobile devices. As healthcare becomes increasingly digital, these mHealth RAs can serve as personal health assistants, e.g., guiding users through medical regimens, offering reminders for medication, providing emotional support during health crises, or even aiding in mental well-being exercises. Their accessibility, especially for those in remote areas, can bridge the gap between patients and immediate health assistance, revolutionizing the way healthcare is approached and delivered. Methods: In this paper, our primary focus is introducing a conceptual design for mHealth RAs with the aim of enhanced user engagement, personalized health interventions, consistent support, data collection and monitoring, and enhanced multimodal accessibility. To develop this conceptual design, we employed an inductive approach. This involved conducting a qualitative analysis on data gathered from a systematic literature review of RAs. Consequently, this analysis allowed us to identify a taxonomy of key design features essential for RAs. Results: This paper provides a conceptual design of mHealth RAs which includes five stages: user input receiving stage, input processing stage, data analysis stage, output processing stage, and output generation stage. A stage is a logical assembly of interconnected functionalities (components) that work together to accomplish a certain objective or set of goals. Each stage's outputs are used as inputs in the stages that follow after it. There is also a Data and Personalization Controller for aiding the data analysis stage. The stages are logically arranged one after another as follows: input, process, analysis, and output. Conclusions: The conceptual design aims to create RAs for various mHealth applications, including patient education, mental health counseling, and chronic disease management. This design is crucial in digital health research as it enhances patient-RA interactions, potentially improving health outcomes and experiences in non-life-threatening scenarios where RAs can be an alternative to human healthcare professionals (HCPs).

Inhibition of Sn2+ Oxidation in FASnI3 Perovskite Precursor Solution and Enhanced Stability of Perovskite Solar Cells by Reductive Additive.

Tin-based halide perovskite solar cells (Sn-PSCs) have attracted a progressive amount of attention as a potential alternative to lead-based PSCs (Pb-PSCs). Sn-perovskite films are fabricated by a solution process spin-coating technique. However, the efficiency of these devices varies significantly with the different batches of precursor solution due to the poor chemical stability of SnI2-DMSO and the oxidation of Sn2+ to Sn4+. This study investigated the origin of Sn2+ oxidation before film formation, and it was identified that the ionization of SnI2 in dimethyl sulfoxide (DMSO) causes the oxidation of free Sn2+ and I- ions. To address these issues, this study introduces the reductive additive 4-fluorophenylhydrazine hydrochloride (4F-PHCl) in the FASnI3 perovskite precursor solution. The hydrazine functional (-NH-NH2) group converted detrimental Sn4+ and I2 defects back to Sn2+ and I- in precursor solution while retaining the properties of the perovskite solution. Furthermore, the addition of 4F-PHCl in the precursor solution effectively slows the crystallization process, enhancing the crystallinity of FASnI3 perovskite films and guaranteeing the Sn2+/I- stoichiometric ratio, ultimately leading to a power conversion efficiency (PCE) of 10.86%. The hydrophobic fluorinated benzene ring in 4F-PHCl ensures moisture stability in perovskite films, allowing unencapsulated PSCs to retain over 92% of their initial PCE in an N2-filled glovebox for 130 days. Moreover, the 4F-PHCl-modified encapsulated PSCs showed superior operational stability for 420 h and maintained 95% of their initial PCE for 300 h under maximum power point tracking at 1 sun continuous illumination. This study's findings provide a promising pathway to create a controlled Sn-based perovskite precursor solution for highly reproducible and stable Pb-free Sn-PSCs.

A qualitative investigation of stressful life events and mental health disorders: The views of patients and caregivers in Bangladesh.

BACKGROUND: Mounting mental health disorders among students has become a significant challenge in producing quality graduates with bright minds. Therefore, it is crucial to investigate the underlying causes of students' mental health-related problems and their experiences while living with mental health disorders. This study investigates the causes and exposures of mental health problems among university students in Bangladesh. For this purpose, a qualitative method was used, and an unstructured in-depth interview schedule was used to collect data from students and caregivers. The students were selected from Khulna University, and data were collected in two consecutive months, i.e., November and December 2021. Using a convenient sampling technique, eight (8) students with mental health issues and five (5) caregivers were interviewed to obtain the necessary data. RESULTS: The findings showed that the intertwined social circumstances led to mental health problems among university students. The students experienced deep depression following a breakup of their romantic affairs/relationships. The prolonged isolation or social distancing due to the government-imposed strict lockdown during the COVID-19 also produced frustration regarding the possible loss of both academic and professional careers. Furthermore, the growing academic pressure in a form of an unfamiliar approach to teaching and learning-online education-also compelled students to complain about depression and suicidal tendencies as parts of their experiences. CONCLUSIONS: This study recommends that the government and policymakers prioritize mental health issues in educational institutions, and they should enforce specific strategies, such as introducing age-specific mental health services and student counseling at educational institutions to reduce growing mental health issues. Furthermore, a positive approach from the family and community is also required to battle against mental health disorders. Besides, nationally representative empirical research is recommended to comprehend the growing mental health issues among students in the 21st century to figure out solutions for the present and the future.

Design Validation of a Relational Agent by COVID-19 Patients: Mixed Methods Study.

BACKGROUND: Relational agents (RAs) have shown effectiveness in various health interventions with and without doctors and hospital facilities. In situations such as a pandemic like the COVID-19 pandemic when health care professionals (HCPs) and facilities are unable to cope with increased demands, RAs may play a major role in ameliorating the situation. However, they have not been well explored in this domain. OBJECTIVE: This study aimed to design a prototypical RA in collaboration with COVID-19 patients and HCPs and test it with the potential users, for its ability to deliver services during a pandemic. METHODS: The RA was designed and developed in collaboration with people with COVID-19 (n=21) and 2 groups of HCPs (n=19 and n=16, respectively) to aid COVID-19 patients at various stages by performing 4 main tasks: testing guidance, support during self-isolation, handling emergency situations, and promoting postrecovery mental well-being. A design validation survey was conducted with 98 individuals to evaluate the usability of the prototype using the System Usability Scale (SUS), and the participants provided feedback on the design. In addition, the RA's usefulness and acceptability were rated by the participants using Likert scales. RESULTS: In the design validation survey, the prototypical RA received an average SUS score of 58.82. Moreover, 90% (88/98) of participants perceived it to be helpful, and 69% (68/98) of participants accepted it as a viable alternative to HCPs. The prototypical RA received favorable feedback from the participants, and they were inclined to accept it as an alternative to HCPs in non-life-threatening scenarios despite the usability rating falling below the acceptable threshold. CONCLUSIONS: Based on participants' feedback, we recommend further development of the RA with improved automation and emotional support, ability to provide information, tracking, and specific recommendations.

A Community-Based Cross-Sectional Study about the Knowledge, Attitude, and Practices of Food Safety Measures among Rural Households in Bangladesh.

Background: Food handlers have been found to play essential roles in transmitting foodborne diseases and can pose a significant public health problem. Our study aimed to assess the knowledge, attitude, and practices (KAP) of food safety measures among the rural households of Bangladesh. Materials and Methods: We conducted this community-based cross-sectional study among women above 18 years involved with food preparation in rural households of four villages in Bangladesh. A total of 400 respondents were selected using the multistage cluster sampling technique. Data were collected using pretested and predesigned questionnaires based on the World Health Organization's (WHO) five keys for food safety. We used Stata (Version 16) for all statistical analyses. Results: The mean age of the participants was 42.09 ± 12.96 years. The median KAP scores [interquartile range (IQR)] were 7 (21-10), 16 (5-18), and 26 (9-30), respectively. We found the median KAP scores were significantly lower in the age group >55 years than in age groups of 18-25, 26-35, 36-45, and 46-55 years (P < 0.05 for all). In addition, the median KAP scores were significantly higher in respondents who were married, literate, employed/active, living in pakka/semipakka house, and with a monthly family income of >5,000 BDT (P < 0.05 for all). Among all, 33.75%, 80.25%, and 69.00% had good (≥80% of total) KAP scores, respectively. Multivariable regression analysis revealed that monthly family income >5,000 BDT was a significant predictor of good knowledge [Adjusted Odds Ratio (aOR): 3.51, 95%CI: 1.55-7.98], good attitude (aOR: 5.82, 95%CI: 2.80-11.70), and good practice (aOR: 3.18, 95%CI: 1.67-6.07). Age >55 years was a significant predictor of good attitude (aOR: 0.38, 95%CI: 0.17-0.81) and good practice (aOR: 0.48, 95%CI: 0.21-0.89). Having ≤4 members in the family was a significant predictor of good practice (aOR: 1.85, 95%CI: 1.13-3.03) regarding food safety measures. Conclusion: The study found that KAP among rural Bangladeshi women regarding food safety were relatively satisfactory. However, having a poor monthly income and living in a large family were impediments to good food-safety practices where work can be done. The findings of this study may help develop health intervention programs for food handlers to further improve KAP toward food safety, thereby reducing foodborne illness in households.

Promising Nitrogen-Doped Graphene Derivatives; A Case Study for Preparations, Fabrication Mechanisms, and Applications in Perovskite Solar Cells.

Graphene (G) has been a game-changer for conductive optical devices and has shown promising aspects for its implementation in the power industry due to its diverse structures. Graphene has played an essential role as electrodes, hole transport layers (HTLs), electron transport layers (ETLs), and a chemical modulator for perovskite layers in perovskite solar cells (PSCs) over the past decade. Nitrogen-doped graphene (N-DG) derivatives are frequently evaluated among the existing derivatives of graphene because of their versatility of design, easy synthesis process, and high throughput. This review presents a state-of-the-art overview of N-DG preparation methods, including wet chemical process, bombardment, and high thermal treatment methods. Furthermore, it focuses on different structures of N-DG derivatives and their various applications in PSC applications. Finally, the challenges and opportunities for N-DG derivatives for the continuous performance improvement of PSCs have been highlighted.

'He was a brilliant student but became mad like his grandfather': an exploratory investigation on the social perception and stigma against individuals living with mental health problems in Bangladesh.

BACKGROUND: Worldwide, mental health issues constitute a substantial threat to people's social, economic, and mental well-being and contribute significantly to many fatalities each year. In Bangladesh, people with mental health issues typically delay contacting health professionals because they prefer traditional or religious healers. Moreover, the situation is exacerbated by a lack of awareness, social stigma, and negative perception of sufferers of mental health issues on the part of families and the community. Therefore, this paper investigates the social perception and stigmatization of individuals living with mental health problems and their caregivers in Khulna, Bangladesh. METHODS: Data were collected from university students with concurring mental health issues as well as their closest caregivers, who had in-depth knowledge of the problem and a willingness to take care of the individuals with mental health issues. Following the criteria for data collection, eight individuals living with mental health problems and five caregivers were purposively selected for this research. A semi-structured in-depth interview guide was used for the confidential data collection process, which took place in November and December 2021, and each interview lasted 40-50 min on average. RESULTS: This study used thematic analysis to present the results; the findings showed that: individuals afflicted with mental health problems sought both medical and spiritual support to recover. Those with mental health issues who received positive family support recovered relatively faster than those who did not. However, negative social perception and stigmatization were the key impediments for individuals suffering from mental health problems and their families, as they found it difficult to discuss their issues with relatives and communities when attempting to access support or seek remedies. Moreover, the commonality of social stigmas, such as labeling mental health problems as equal to 'madness,' hindered disclosure to family members, peers, and the community. CONCLUSION AND RECOMMENDATIONS: In Bangladesh, the majority of individuals living with mental health problems are stigmatized and do not receive emotional support. Hence, we suggest nationwide community-based awareness-building programs to promote more positive perceptions of the fight against mental health disorders. Furthermore, counseling and awareness-building programs for effective discouragement of non-scientific remedies such as spiritual healing, as well as diagnosis and medication at the primary stage of sickness, are recommended for early detection and better medical assistance.

A Mobile Application-Based Relational Agent as a Health Professional for COVID-19 Patients: Design, Approach, and Implications.

Relational Agents' (RAs) ability to maintain socio-emotional relationships with users can be an asset to COVID-19 patients. The goal of this research was to identify principles for designing an RA that can act as a health professional for a COVID-19 patient. We first identified tasks that such an RA can provide by interviewing 33 individuals, who had recovered from COVID-19. The transcribed interviews were analyzed using qualitative thematic analysis. Based on the findings, four sets of hypothetical conversations were handcrafted to illustrate how the proposed RA will execute the identified tasks. These conversations were then evaluated by 43 healthcare professionals in a qualitative study. Thematic analysis was again used to identify characteristics that would be suitable for the proposed RA. The results suggest that the RA must: model clinical protocols; incorporate evidence-based interventions; inform, educate, and remind patients; build trusting relationships, and support their socio-emotional needs. The findings have implications for designing RAs for other healthcare contexts beyond the pandemic.

Targeted delivery of an anti-inflammatory corticosteroid to Ly6C/G-positive cells abates severity of influenza A symptoms.

The distribution of Ly6C/G-positive cells in response to an infection of the mouse respiratory tract with influenza A virus was followed noninvasively over time by immuno-positron emission tomography. We converted nanobodies that recognize Ly6C and Ly6G, markers of neutrophils and other myeloid cells, as well as an influenza hemagglutinin-specific nanobody, into 89Zr-labeled PEGylated positron emission tomography (PET) imaging agents. The PET images showed strong accumulation of these imaging agents in the lungs of infected mice. Immunohistochemistry of influenza virus-infected mice and control mice, injected with a biotinylated and PEGylated version of the Ly6C/G-specific nanobody, showed the presence of abundant Ly6C/G-positive myeloid cells and positivity for Ly6C/G on bronchial epithelium in influenza virus-infected mice. This is consistent with focal inflammation in the lungs, a finding that correlated well with the immuno-PET results. No such signals were detected in control mice. Having shown by PET the accumulation of the Ly6C/G-specific nanobody in infected lungs, we synthesized conjugates of Ly6C/G-specific nanobodies with dexamethasone to enable targeted delivery of this immunosuppressive corticosteroid to sites of inflammation. Such conjugates reduced the weight loss that accompanies infection, while the equivalent amount of free dexamethasone was without effect. Nanobody-drug conjugates thus enable delivery of drugs to particular cell types at the appropriate anatomic site(s). By avoiding systemic exposure to free dexamethasone, this strategy minimizes its undesirable side effects because of the much lower effective dose of the nanobody-dexamethasone conjugate. The ability to selectively target inflammatory cells may find application in the treatment of other infections or other immune-mediated diseases.

A Relational Agent for the COVID-19 Patients: Design, Approach, and Implications.

BACKGROUND: Relational agents (RAs) have shown effectiveness in various health interventions with and without doctors and hospital facilities. We suggest that in situations such as a pandemic like the COVID-19 when healthcare professionals (HCPs) and facilities are unable to cope with increased demands, RAs can play a major role in ameliorating the situation. OBJECTIVE: The goal of this research was to seek design validation on a prototypical RA to address healthcare needs of the COVID-19 patients. METHODS: Therefore, RAs can deliver health interventions during COVID-19 pandemic, but they have not been well-explored in this domain. To address this gap, a prototypical RA is iteratively designed and developed in collaboration with infected patients (n=21) and two groups of HCPs (n=19 and n=16 respectively) to aid COVID-19 patients at various stages by performing four main tasks: testing guidance, support during self-isolation, handling emergency situations, and promoting post-recovery mental well-being. RESULTS: A survey with 98 individuals was used to evaluate the usability of the prototype by system usability scale (SUS) and it received an average score of 58.82. Moreover, participants indicated perceived usefulness and acceptability of the system on Likert Scales where 89.65% perceived it to be helpful, 68.97% accepted it as a viable alternative to HCPs. CONCLUSIONS: The prototypical RA received favorable feedback from the participants and they were inclined to accept it as an alternative to HCPs in non-life-threatening scenarios despite the usability rating falling below the acceptable threshold. Based on participants' feedback, we recommend further development of the RA with improved automation and emotional support, ability to provide information, tracking, and specific recommendations.

Sero-prevalence and risk factors for Severe Acute Respiratory Syndrome Coronavirus 2 infection in women and children in a rural district of Bangladesh: A cohort study.

Background: Bangladesh reported its first COVID-19 case on March 8, 2020. Despite lockdowns and promoting behavioural interventions, as of December 31, 2021, Bangladesh reported 1.5 million confirmed cases and 27 904 COVID-19-related deaths. To understand the course of the pandemic and identify risk factors for SARs-Cov-2 infection, we conducted a cohort study from November 2020 to December 2021 in rural Bangladesh. Methods: After obtaining informed consent and collecting baseline data on COVID-19 knowledge, comorbidities, socioeconomic status, and lifestyle, we collected data on COVID-like illness and care-seeking weekly for 54 weeks for women (n = 2683) and their children (n = 2433). Between March and July 2021, we tested all participants for SARS-CoV-2 antibodies using ROCHE's Elecsys® test kit. We calculated seropositivity rates and 95% confidence intervals (95% CI) separately for women and children. In addition, we calculated unadjusted and adjusted relative risk (RR) and 95% CI of seropositivity for different age and risk groups using log-binomial regression models. Results: Overall, about one-third of women (35.8%, 95% CI = 33.7-37.9) and one-fifth of children (21.3%, 95% CI = 19.2-23.6) were seropositive for SARS-CoV-2 antibodies. The seroprevalence rate doubled for women and tripled for children between March 2021 and July 2021. Compared to women and children with the highest household wealth (HHW) tertile, both women and children from poorer households had a lower risk of infection (RR, 95% CI for lowest HHW tertile women (0.83 (0.71-0.97)) and children (0.75 (0.57-0.98)). Most infections were asymptomatic or mild. In addition, the risk of infection among women was higher if she reported chewing tobacco (RR = 1.19,95% CI = 1.03-1.38) and if her husband had an occupation requiring him to work indoors (RR = 1.16, 95% CI = 1.02-1.32). The risk of infection was higher among children if paternal education was >5 years (RR = 1.37, 95% CI = 1.10-1.71) than in children with a paternal education of ≤5 years. Conclusions: We provided prospectively collected population-based data, which could contribute to designing feasible strategies against COVID-19 tailored to high-risk groups. The most feasible strategy may be promoting preventive care practices; however, collecting data on reported practices is inadequate. More in-depth understanding of the factors related to adoption and adherence to the practices is essential.

Identification of visible colored dissolved organic matter in biological and tertiary municipal effluents using multiple approaches including PARAFAC analysis.

This study provided insights into the persistent yellowish color in biological and tertiary effluents of municipal wastewater through a multi-characterization approach and fluorescence excitation-emission matrix-parallel factor (EEM-PARAFAC) analysis. The characterization was performed on three to five full-scale municipal wastewater treatment plants (WWTPs), including differential log-transformed absorbance (DLnA) spectroscopy, resin fractionation, size-exclusion chromatography for apparent molecular weight analysis (SEC-AMW), and X-ray photoelectron spectroscopy (XPS) analysis. Hydrophobic acids (HPOA) were abundant in visible colored dissolved organic matter (DOM). The SEC-AMW result showed that the molecular weight of the colored substances in the secondary effluents is mainly distributed in the range of 2-3 kDa. Through XPS analysis, C-O/C-N and pyrrolic/pyridonic (N-5) were found to be positively correlated with chroma. PARAFAC component models were built on biological (two components) and tertiary effluent (three components) and the correlation analysis revealed that PARAFAC component 2 in biological effluent (BE-C2) and component 1 in tertiary effluent (TE-C1), which were ascribed to Hydrophobic acids and Humic acid-like, were the responsible visible colored DOM components cause yellowish color. In addition, component similarity testing found that the identified visible colored DOM PARAFAC BE-C2, and PARAFAC TE-C1 were identical (0.96) in physicochemical properties, with 4% removal efficacy on average, compared with 11% for invisible colored DOM. This implied that tertiary effluents containing colorants (TE-C1) were resistant to degradation/removal using different disinfection and filtration processes in advanced treatments. This sheds light on many physicochemical aspects of PARAFAC-identified visible colored DOM components and provides spectral data to build an online monitoring system.

The use of viral vectors to promote repair after spinal cord injury.

Spinal cord injury (SCI) is a devastating event that can permanently disrupt multiple modalities. Unfortunately, the combination of the inhibitory environment at a central nervous system (CNS) injury site and the diminished intrinsic capacity of adult axons for growth results in the failure for robust axonal regeneration, limiting the ability for repair. Delivering genetic material that can either positively or negatively modulate gene expression has the potential to counter the obstacles that hinder axon growth within the spinal cord after injury. A popular gene therapy method is to deliver the genetic material using viral vectors. There are considerations when deciding on a viral vector approach for a particular application, including the type of vector, as well as serotypes, and promoters. In this review, we will discuss some of the aspects to consider when utilizing a viral vector approach to as a therapy for SCI. Additionally, we will discuss some recent applications of gene therapy to target extrinsic and/or intrinsic barriers to promote axon regeneration after SCI in preclinical models. While still in early stages, this approach has potential to treat those living with SCI.

Correction: Toward Designs of Workplace Stress Management Mobile Apps for Frontline Health Workers During the COVID-19 Pandemic and Beyond: Mixed Methods Qualitative Study.

[This corrects the article DOI: 10.2196/30640.].

Hippocampal acetylcholine modulates stress-related behaviors independent of specific cholinergic inputs.

Acetylcholine (ACh) levels are elevated in actively depressed subjects. Conversely, antagonism of either nicotinic or muscarinic ACh receptors can have antidepressant effects in humans and decrease stress-relevant behaviors in rodents. Consistent with a role for ACh in mediating maladaptive responses to stress, brain ACh levels increase in response to stressful challenges, whereas systemically blocking acetylcholinesterase (AChE, the primary ACh degradative enzyme) elicits depression-like symptoms in human subjects, and selectively blocking AChE in the hippocampus increases relevant behaviors in rodents. We used an ACh sensor to characterize stress-evoked ACh release, then used chemogenetic, optogenetic and pharmacological approaches to determine whether cholinergic inputs from the medial septum/diagonal bands of Broca (MSDBB) or ChAT-positive neurons intrinsic to the hippocampus mediate stress-relevant behaviors in mice. Chemogenetic inhibition or activation of MSDBB cholinergic neurons did not result in significant behavioral effects, while inhibition attenuated the behavioral effects of physostigmine. In contrast, optogenetic stimulation of septohippocampal terminals or selective chemogenetic activation of ChAT-positive inputs to hippocampus increased stress-related behaviors. Finally, stimulation of sparse ChAT-positive hippocampal neurons increased stress-related behaviors in one ChAT-Cre line, which were attenuated by local infusion of cholinergic antagonists. These studies suggest that ACh signaling results in maladaptive behavioral responses to stress if the balance of signaling is shifted toward increased hippocampal engagement.

Toward Designs of Workplace Stress Management Mobile Apps for Frontline Health Workers During the COVID-19 Pandemic and Beyond: Mixed Methods Qualitative Study.

BACKGROUND: In recent years, mobile apps have been developed to prevent burnout, promote anxiety management, and provide health education to workers in various workplace settings. However, there remains a paucity of such apps for frontline health workers (FHWs), even though FHWs are the most susceptible to stress due to the nature of their jobs. OBJECTIVE: The goal of this study was to provide suggestions for designing stress management apps to address workplace stressors of FHWs based on the understanding of their needs from FHWs' own perspectives and theories of stress. METHODS: A mixed methods qualitative study was conducted. Using a variety of search strings, we first collected 41 relevant web-based news articles published between December 2019 and May 2020 through the Google search engine. We then conducted a cross-sectional survey with 20 FHWs. Two researchers independently conducted qualitative analysis of all the collected data using a deductive followed by an inductive approach. RESULTS: Prevailing uncertainty and fear of contracting the infection was causing stress among FHWs. Moral injury associated with seeing patients die from lack of care and lack of experience in handling various circumstances were other sources of stress. FHWs mentioned 4 coping strategies. Quick coping strategies such as walking away from stressful situations, entertainment, and exercise were the most common ways to mitigate the impact of stress at work. Peer support and counseling services were other popular methods. Building resilience and driving oneself forward using internal motivation were also meaningful ways of overcoming stressful situations. Time constraints and limited management support prevented FHWs from engaging in stress management activities. CONCLUSIONS: Our study identified stressors, coping strategies, and challenges with applying coping strategies that can guide the design of stress management apps for FHWs. Given that the pandemic is ongoing and health care crises continue, FHWs remain a vulnerable population in need of attention.

Immunobiology of cancer-associated fibroblasts in the context of radiotherapy.

Radiotherapy (RT) still represents a mainstay of treatment in clinical oncology. Traditionally, the effectiveness of radiotherapy has been attributed to the killing potential of ionizing radiation (IR) over malignant cells, however, it has become clear that therapeutic efficacy of RT also involves activation of innate and adaptive anti-tumor immune responses. Therapeutic irradiation of the tumor microenvironment (TME) provokes profound cellular and biological reconfigurations which ultimately may influence immune recognition. As one of the major constituents of the TME, cancer-associated fibroblasts (CAFs) play central roles in cancer development at all stages and are recognized contributors of tumor immune evasion. While some studies argue that RT affects CAFs negatively through growth arrest and impaired motility, others claim that exposure of fibroblasts to RT promotes their conversion into a more activated phenotype. Nevertheless, despite the well-described immunoregulatory functions assigned to CAFs, little is known about the interplay between CAFs and immune cells in the context of RT. In this review, we go over current literature on the effects of radiation on CAFs and the influence that CAFs have on radiotherapy outcomes, and we summarize present knowledge on the transformed cellular crosstalk between CAFs and immune cells after radiation.

Self-Assembled Hierarchical Cu x O@C18H36O2 Nanoflakes for Superior Fenton-like Catalysis over a Wide Range of pH.

A novel copper-based catalyst supported by a long-chain hydrocarbon stearic acid (Cu x O@C18H36O2) was synthesized by a hydrothermal method and double replacement reactions. The as-prepared catalyst is shown as self-assembled hierarchical nanoflakes with an average size of ∼22 nm and a specific surface area of 51.4 m2 g-1. The catalyst has a good performance on adsorption as well as Fenton-like catalytic degradation of Rhodamine B (RhB). The catalyst (10 mg/L) showed an excellent adsorption efficiency toward RhB (20 mg/L) for pH ranging from 5 to 13, with the highest adsorption rate (99%) exhibited at pH 13. The Fenton-like catalytic degradation reaction of RhB (20 mg/L) by Cu x O@C18H36O2 nanoflakes was effective over a wide range of pH of 3-11, and •OH radicals were generated via Cu2O/H2O2 interactions in acidic conditions and CuO/H2O2 reactions in a neutral solution. The highest efficiency catalytic degradation of RhB (20 mg/L) was 99.2% under acidic conditions (pH = 3, H2O2 = 0.05 M), with an excellent reusability of 96% at the 6th cycle. The results demonstrated that the as-prepared Cu x O@C18H36O2 nanoflakes are an efficient candidate for wastewater treatment, with excellent adsorption capacity and superior Fenton-like catalytic efficiency and stability for RhB.