Critical Gaps Research Articles

The spatio-temporal distribution of small-scale fisheries along the northern Panay Gulf, Philippines: Implications for management

The small-scale fisheries along the northern region of the Panay Gulf face a distinctive challenge as multiple communities compete for access to the same fishing areas and resources. In response, neighboring coastal municipalities implemented conventional management measures, such as Marine Protected Areas (MPAs) and seasonal closures, aiming to enhance the abundance of fisheries resources. However, these measures only imposed economic hardships on artisanal fishermen. To address this issue, a survey involving 135 informants from coastal barangays was conducted between June to November 2021. The study used semi-structured questionnaires and GPS data loggers to collect essential information on the spatial and temporal distribution of fishing activities and specific target catches. The integration of local knowledge played a crucial role in bridging critical data gaps within the study site, facilitating the identification of more effective management reforms. The findings revealed that traditional harvest locations for various gear types exhibited zonation patterns across the gulf. Fishing activities were strategically conducted in areas with available resources, often disregarding municipal fishing boundaries. Coordinated management strategies are deemed imperative due to the varying timing of seasonal closures among municipalities. On the other hand, the temporal analysis of fishing activities revealed peak seasons of fisheries resources, providing a basis for adjusting the selection of target species and the duration of seasonal closures. Interestingly, the existing management measures failed to reduce the annual fishing activities and were ineffective, contrary to popular claims. This outcome was primarily due to constant shifts in the types of fishing gear used and target catches between seasons, highlighting the displacement of exploitation. In conclusion, this study underscores the importance of aligning fisheries policies with the dynamic nature of small-scale fisheries. Unless these policies adapt to the evolving conditions of the sector, they are likely to remain ineffective in addressing issues faced by artisanal fishermen in the region.

Exploratory Research on the Use of Energy Recovery Technology in Sewage Treatment in Indonesia

This research delves into the integration of Energy Recovery Technology (ERT) within sewage treatment processes in Indonesia, addressing the imperative for sustainable wastewater management amid rapid population growth and urbanization. Through a comprehensive investigation encompassing technological, economic, and environmental dimensions, the study identifies challenges, evaluates the feasibility of ERT integration, and bridges critical gaps in the existing literature. The potential synergy between wastewater treatment and energy recovery aligns with Indonesia's commitment to sustainable development. The findings serve as a catalyst for innovative sewage treatment approaches, contributing to a paradigm shift in Indonesia's wastewater management practices. The accompanying bibliometric analysis provides a detailed overview of the academic landscape, key contributors, and impactful studies, enhancing the study's depth and practical implications.

CFD analysis of air flows and temperatures based on radiant heating in industrial environments

Objective. The study aims to investigate the complex interaction between radiant heating and airflow in industrial environments.The aim is to understand the dynamics of temperature, with particular attention to optimizing energy efficiency and comfort in industrial premises heated by a dual-zone dark gas radiant heater. Method. Using Computational Fluid Dynamics (CFD) and Ansis simulation software, the study developed a model that represents typical industrial conditions. This method included the determination and verification of temperature gradients and air velocity parameters, as well as careful mapping of the complexities of the industrial heating process. Result. The analysis provides detailed graphical representations of temperature and air velocity at individual points, revealing the effect of radiant heating on airflow patterns. Particular attention has been paid to how the temperature profiles interact with a dual-zone heating system, revealing important data that helps understand thermal dynamics in industrial environments. Conclusion. The findings demonstrate the potential for significant progress in energy savings and improved worker comfort in industrial environments using radiant heating. The integrated research approach fills a critical gap in existing research, highlighting the need and potential for further exploration of sustainable heating technologies in challenging industrial environments.

Patient-reported outcomes: The unmet needs of the gastrointestinal cancer community.

731 Background: According to the World Health Organization International Agency for Research on Cancer, gastrointestinal (GI) cancers account for 1 in 4 cancer cases and 1 in 3 cancer-related deaths worldwide. An estimated 4.8 million new cases of GI cancers and 3.4 million related deaths occur annually. Understanding the need for increased GI cancer awareness, patient education and support, the GI Cancers Alliance developed a series of engagement activities for the GI cancer community as a needs assessment to identify critical gaps in support services, fragmented education, and disease awareness. Methods: Our 12-month patient-reported outcomes (PRO) research included an online anonymous survey, individual and small group interviews, focus groups, advisory boards, and an interactive workshop at the 2023 American Society of Clinical Oncology annual meeting. 1,122 patients participated during this 12-month PRO research period. Participants reported being diagnosed with one of the following GI cancer primary tumor types: Anus (3%), Appendix (2%), Bile Duct (6%), Colon (19%), Esophagus (7%), Gallbladder (5%), Gastric (14%), GI NET / GI Carcinoid Tumor (3%), Liver (7%), Pancreas (6%), Small Intestine (4%), Rectum (23%), Unknown primary location (1%). Results: Overarching areas of unmet need include: health disparities throughout the care continuum for underserved populations (21%); lack of adequate precision oncology patient education, including biomarker education and testing (19%); the rise of early-age onset (EAO) in GI cancers and the unique needs of the young adult (YA) population (18%); nutritional wellness education (17%); insufficient support for family caregivers and caregiver respite services (16%) scarcity of patient-centered care and adequate patient-clinician communication (11%). Conclusions: Our PRO research underscores the unmet needs and gaps in support services of the GI cancer community. Our global call to action includes partnering with our 100+ member organizations to amplify the patient voice and patient-lived experience, and cross-collaboration with our community of advocates, patients, caregivers, and clinicians. Our shared call to action and continued collaboration provides a greater impact for our GI cancer community to help meet patient needs and eliminate critical gaps in services.

Utility of gene expression–based cancer classification in diagnosis of malignant peritoneal mesothelioma (MPeM): Filling in the gaps in standard pathologic work-up for a rare cancer.

728 Background: Malignant peritoneal mesothelioma (MPeM) is a rare cancer (incidence of 0.12 per 100,000) and an arduous diagnostic challenge, requiring skillful evaluation by expert pathologists. Subjective and experiential immunophenotyping coupled with inattention to this rare entity causes delayed or misdiagnosis and leads to suboptimal treatment and outcomes. Gene-expression-based cancer classification offers an objective molecular assessment of the tissue of origin for cancers with uncertain diagnosis and improves diagnostic accuracy for MPeM compared to standard pathology. Methods: We retrospectively evaluated 23 patients (pts) with cancer of unknown primary (CUP) or uncertain diagnoses, with peritoneal/retroperitoneal carcinomatosis and reported as malignant mesothelioma using a 92-gene assay (CancerTYPE ID), a validated classifier for predicting tumor types, between January 2013 to December 2016. Pathology was verified by central review. Clinicopathologic data including immunohistochemistry (IHC) was collected using archived pathology specimens and reports. Results: Pts had a median age of 64 years (range: 39 – 93) at diagnosis, 57% were females and 74% had biopsy from omentum/peritoneum. Original histopathology was reported as poorly differentiated in 81% and as adenocarcinoma, carcinoma and malignant neoplasm in 10 (43%), 7 (30%) and 6 (27%) of cases, respectively. The number of IHC stains performed ranged between 0 and 28 (median: 10). Key IHC stains are shown in the table. Conclusions: In this cohort of CUP or uncertain diagnoses with a molecular cancer classification of malignant mesothelioma, we found huge variability and critical gaps in pathological work-up. Integration of molecular cancer classification using the 92-gene assay helped resolve this diagnostic uncertainty, further supporting its clinical utility to complement standard pathology. The impact of these findings goes beyond just MPeM and may benefit numerous pts with orphan cancers, who account for nearly 20% of all cancers diagnosed globally. [Table: see text]

Revitalizing Emergency Care Ecosystem in India through Comprehensive Transformation and Innovative Solutions

Emergency care is a critical pillar of healthcare systems, serving as the initial point of contact for individuals facing acute conditions. However, consistent access to prompt emergency care remains a challenge in many regions, particularly low and middle-income countries (LMICs), where a substantial burden of disease is attributed to emergencies. This paper explores the emergency care ecosystem in India, emphasizing the role of first responders, effective communication, ambulance services, and trained healthcare staff. It also highlights challenges, solutions, technological advancements, and the benefits of implementing an emergency surveillance system to improve emergency care services. The multifaceted approach includes strengthening pre-hospital care systems, equipping communities with basic first aid skills, optimizing ambulance services, strengthening formal education and training in emergency care, harnessing technological solutions, data-driven insights, innovative approaches, and telemedicine. These efforts collectively aim to establish a seamless continuum of care, minimize patient treatment delays, and ensure that healthcare professionals are both incentivized and adequately prepared for high-stress emergency environments. Additionally, addressing violence against healthcare professionals and ensuring equitable access to emergency care are crucial components of the transformation agenda. This transformation is not only essential for saving lives, reducing disabilities, and advancing universal health coverage but also addresses a critical gap in India's healthcare landscape by enhancing the efficiency and accessibility of emergency care services.

Engaging Community-Academic Partnerships: A Case Study of the Influence of Social Drivers of Health on Equitable Transitions of Cancer Care in the United States.

Enduring community-academic partnerships are essential for expediting the successful dissemination and implementation of promising interventions and programs, particularly for complex public health issues such as cancer prevention and control. The purpose of this case study was to understand the combined voices of a diverse group of stakeholders to outline the essential factors needed to translate research into sustainable cancer care within communities. System dynamics group model building was used to develop system maps of the factors impacting equitable access to cancer care services among three stakeholder groups (Group A: survivors and family members, n = 20; Group B: providers and administrators in community agencies/organizations, n = 40; Group C: administrators from a cancer institute, academic universities, foundations, and healthcare facilities that coordinate care, n = 25) in central Texas, USA. The lead researcher identified factors involved in transitions of care and their linkages with each other. The analysis of this work displays these connections visually. These models represent the ripple effect of factors influencing the transition of care for stakeholders who are invested in cancer care outcomes. All three groups identified medical mistrust, a culturally sensitive and diverse provider workforce, and care coordination as three essential factors (i.e., themes). Group A also identified caregiver navigation. The groups varied in their emphasis on upstream vs. downstream social drivers of health, with Group B emphasizing the former and Group C emphasizing the latter. To achieve cancer care equity, all stakeholder groups agreed on the importance of addressing the impact of social drivers as critical gaps. Eliminating or reducing these impacts allows each stakeholder group to work more efficiently and effectively to improve cancer care for patients.

Durian Species Classification Using Deep Learning Method

Durian is a popular fruit in Southeast Asia, and the market offers various species of durians. Accurate species classification is crucial for quality control, grading, and marketing. However, the complexity of this task has led to the utilization of machine learning and deep learning methods. Traditional machine learning algorithms, such as K-Nearest Neighbors, Linear Discriminant Analysis, Support Vector Machines, and Random Forests, have demonstrated good accuracy, but they require extensive feature engineering. Deep learning algorithms, particularly Convolutional Neural Networks, can automatically extract features, making them less dependent on manual feature selection. This research aims to review deep learning classification algorithms, including Convolutional Neural Networks and Recurrent Neural Networks, to determine the most suitable algorithm for an efficient and accurate durian classification system. The objective is to enhance the precision and speed of durian species classification, presenting potential advantages for both durian producers and consumers. The literature review revealed that Convolutional Neural Networks outperformed other deep learning and traditional machine learning algorithms on datasets of varying sizes, achieving the highest accuracy of 98.96% through techniques like image resizing, color conversion, and additional parameters such as days harvested and dry weight. Deep learning emerges as a promising approach for robust and accurate durian species recognition, with future directions including developing models to classify durian species from different plant parts and even real-time video analysis. However, while Convolutional Neural Networks lead the way, a critical research gap exists in identifying optimal features, necessitating further investigation to refine durian species recognition accuracy.

Effects of Kinesio Taping and Modified Constraint-Induced Movement Therapy on Upper Extremity Function, Quality of Life, and Spasticity in Individuals Recovering from Stroke

Background: Cerebral palsy is a neurological condition affecting children and adolescents, often resulting in hemiparesis and impaired upper limb functionality. Constraint-Induced Movement Therapy (CIMT) has shown promise in rehabilitation, and Kinesio Taping (KT) is increasingly considered for its potential benefits. This study explores the synergistic impact of CIMT and KT on upper limb function and muscle tone in this population, filling a critical gap in research. Objective: To investigate the combined effects of CIMT and KT on upper limb functionality and spasticity in children and adolescents with hemiparesis. Methods: A comprehensive randomized clinical trial adhering to CONSORT guidelines was conducted. Forty-six participants aged 6 to 17 years, diagnosed with hemiparesis due to cerebral palsy, were divided into two groups: CIMT-only and CIMT + KT. Baseline assessments included age, gender, stroke type, time since stroke, and initial upper limb function (FMA-UE, BBT, SF-36, MAS). CIMT sessions were conducted intensively over four weeks, with the CIMT + KT group additionally receiving KT application. Post-intervention assessments were conducted using the same measures. Results: Both the CIMT and CIMT + KT groups demonstrated significant improvements in the use of the affected limb for daily tasks, as indicated by the Motor Activity Log (MAL) scores. The CIMT-only Group showed a mean change in MAL score of 15.4 ± 8.1, while the CIMT + KT Group exhibited a mean change of 10.2 ± 6.5. Strong performance in upper limb functionality, assessed through the Wolf Motor Function Test (WMFT) Functional Ability Scale (FAS), was observed in both groups. The CIMT-only Group demonstrated a mean change in WMFT FAS score of 12.3 ± 6.2, and the CIMT + KT Group had a mean change of 8.4 ± 5.1. Additionally, both groups experienced a notable reduction in muscle tone, assessed using the Modified Ashworth Scale (MAS). The CIMT-only Group had a mean change in MAS score of -0.6 ± 0.4, while the CIMT + KT Group had a mean change of -0.4 ± 0.5. No statistically significant differences were observed between the two groups regarding the quality and quantity of movement. Conclusion: Integrating Kinesio Taping with Constraint-Induced Movement Therapy effectively reduces muscular tone in the wrist and fingers, enhancing upper limb functionality in children and adolescents with hemiparesis. While Kinesio Taping alone and in combination with CIMT demonstrates efficacy, further research is warranted to optimize therapeutic applications.

Addressing disparities in the global epidemiology of stroke.

Stroke is the second leading cause of death and the third leading cause of disability worldwide. Though the burden of stroke worldwide seems to have declined in the past three decades, much of this effect reflects decreases in high-income countries (HICs). By contrast, the burden of stroke has grown rapidly in low-income and middle-income countries (LMICs), where epidemiological, socioeconomic and demographic shifts have increased the incidence of stroke and other non-communicable diseases. Furthermore, even in HICs, disparities in stroke epidemiology exist along racial, ethnic, socioeconomic and geographical lines. In this Review, we highlight the under-acknowledged disparities in the burden of stroke. We emphasize the shifting global landscape of stroke risk factors, critical gaps in stroke service delivery, and the need for a more granular analysis of the burden of stroke within and between LMICs and HICs to guide context-appropriate capacity-building. Finally, we review strategies for addressing key inequalities in stroke epidemiology, including improvements in epidemiological surveillance and context-specific research efforts in under-resourced regions, development of the global workforce of stroke care providers, expansion of access to preventive and treatment services through mobile and telehealth platforms, and scaling up of evidence-based strategies and policies that target local, national, regional and global stroke disparities.

Relationship Between Upper Respiratory Tract Symptoms And Treatment-Seeking Behaviour In Healthy Attendants Of Patients Presenting To Opd Clinics Of Bbs Teaching Hospital Abbottabad.

Indiscriminate use of antibiotics is a well-known reason for increasing antimicrobial resistance. Upper respiratory tract infection presents with similar symptoms and signs irrespective of its bacterial or viral causes and is either ignored or managed aggressively by the primary care physicians. The objective was to determine the relationship between upper respiratory tract infections and treatment-seeking behaviour in healthy individuals attending the OPD clinics of BBS Teaching Hospital with their sick family members. Six hundred and eighty-five healthy individuals who accompanied patients to the OPD clinics of BBS Teaching Hospital, Abbottabad were enrolled in this cross-sectional survey. They were given a modified questionnaire to respond to and their replies were analyzed for assessment. In a survey of 685 individuals, 98.2% were aware of antibiotics, but only 28.6% correctly understood their use against infections. Misconceptions about antibiotic resistance were common, with 54.5% believing it arises from human immunity. Only 31.53% consulted a doctor for upper respiratory symptoms and 72.6% of those expected antibiotics. Women showed higher antibiotic knowledge than men, but education level was a stronger predictor of both knowledge and attitudes. This study highlights a critical gap in public understanding and responsible usage of antibiotics, particularly in the context of upper respiratory tract infections. This study reveals that increased awareness and more informed attitudes about antibiotic resistance correlate with a decreased likelihood of inappropriate antibiotic prescription.

Gwadar: China’s Future Gateway to the Middle East

The China-Pakistan Economic Corridor, the flagship project of China’s Belt and Road Initiative, completed a decade in July 2023. During this time, it has enabled Pakistan to overcome critical gaps in energy, transportation and communication. The CPEC’s long-term plan is to develop Pakistan’s industrial capacity and contribute to its emergence as a trading hub between China and the Middle East. The deep-sea seaport of Gwadar in the Arabian Sea would play an instrumental role in this respect due to its proximity with the strategic sea-lanes for global energy trade in the Persian Gulf. This article offers a critical analysis of CPEC’s strategic value for Pakistan’s economic development and regional connectivity, especially Gwadar’s valuable role in this regard. The discussion ahead covers the key challenges and opportunities concerning CPEC, China’s economic profile in Central Asia and the Gulf, and the emerging interest among oil-rich Gulf for investment in Gwadar. The article concludes with a narration of CPEC’s significance for China, Pakistan and regional stakeholders, and Gwadar’s future potential as a regional trading hub and a strategic outpost for China.

Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models

In the last decade, despite rapid advancements in artificial intelligence (AI) transforming many industry practices, construction largely lags in adoption. Recently, the emergence and rapid adoption of advanced large language models (LLMs) like OpenAI’s GPT, Google’s PaLM, and Meta’s Llama have shown great potential and sparked considerable global interest. However, the current surge lacks a study investigating the opportunities and challenges of implementing Generative AI (GenAI) in the construction sector, creating a critical knowledge gap for researchers and practitioners. This underlines the necessity to explore the prospects and complexities of GenAI integration. Bridging this gap is fundamental to optimizing GenAI’s early stage adoption within the construction sector. Given GenAI’s unprecedented capabilities to generate human-like content based on learning from existing content, we reflect on two guiding questions: What will the future bring for GenAI in the construction industry? What are the potential opportunities and challenges in implementing GenAI in the construction industry? This study delves into reflected perception in literature, analyzes the industry perception using programming-based word cloud and frequency analysis, and integrates authors’ opinions to answer these questions. This paper recommends a conceptual GenAI implementation framework, provides practical recommendations, summarizes future research questions, and builds foundational literature to foster subsequent research expansion in GenAI within the construction and its allied architecture and engineering domains.

The effects of lockdown during the COVID-19 pandemic on fetal movement profiles

PurposeThe current study investigated the direct impact of the COVID-19 lockdown on fetal movements, addressing a critical research gap. While previous research has predominantly examined the effects of lockdown on maternal health and postnatal outcomes, little attention has been paid to the direct consequences on fetal well-being as indicated by their movement profile.MethodsWe conducted analysis of movement profiles in 20 healthy fetuses during the COVID-19 pandemic lockdown (third national UK lockdown period between January and March 2021) and compared them with 20 healthy fetuses from pre-covid pregnancies, all at 32 weeks gestation. We controlled for maternal stress, depression, and anxiety.ResultsPregnant mothers during pre-covid compared with those during the COVID-19 lockdown reported similar levels of stress (p = 0.47), depression (p = 0.15), and anxiety (p = 0.07). Their fetuses, however, differed in their movement profiles with mouth movement frequencies significantly higher during COVID-19 lockdown (COVID-19 lockdown: mean of 5.909) compared to pre-Covid pregnancies (mean of 3.308; p = 0.029). Furthermore, controlling for maternal anxiety a regression analysis indicated that frequency of fetal mouth movements (p = 0.017), upper face movements (p = 0.008), and touch movements (p = 0.031) were all significantly higher in fetuses observed during lockdown compared to fetuses before the Covid period.ConclusionFetuses show an effect of lockdown independent of maternal anxiety, stress, or depression. These findings contribute to our understanding of fetal development during extraordinary circumstances, raising questions about the potential effects of having to stay indoors during lockdowns.

Modulators of Candida albicans Membrane Drug Transporters: A LucrativePortfolio for the Development of Effective Antifungals.

The escalating prevalence of membrane drug transporters and drug efflux pumps in pathogenic yeast like Candida albicans necessitates a comprehensive understanding of their roles in MDR. The overexpression of drug transporter families, ABC and MFS, implicated in MDR through drug efflux and poses a significant challenge in the diagnosis and treatment of fungal infection. Various mechanisms have been proposed for MDR; however, the upregulation of ABC and MFS superfamily transporters is most noticeable in MDR. The direct inhibition of these transporters seems an efficient strategy to overcome this problem. The goal of the article is to present an overview of the prospect of utilizing these modulators of C. albicans drug transports as effective antifungal molecules against MDR addressing a critical gap in the field. The review tries to address to prevent drug extrusion by modulating the expression of drug transporters of C. albicans. The review discussed the progress in identifying potent, selective, and non-toxic modulators of these transporters to develop some effective antifungals and overcome MDR. We reviewed major studies in this area and found that recent work has shifted toward the exploration of natural compounds as potential modulators to restore drug sensitivity in MDR fungal cells. The focus of this review is to survey and interpret current research information on modulators of C. albicans drug transporters from natural sources emphasizing those compounds that are potent antifungal agents.

Starting early: Case study of mentoring for undergraduate training through the Veterans Health Administration and implications for promoting equity.

Undergraduate mentoring and research internships promote entry into graduate training, academic success, research productivity, and greater career satisfaction. Most pathway programs to enhance representation within academia and health care intervene at the graduate level, leaving a critical gap in undergraduate training. The Veterans Health Administration's (VHA's) national network of clinicians and researchers is uniquely suited to provide equitable access to quality mentorship and education for undergraduates interested in health care careers. We present a program evaluation case study of a VHA undergraduate training program incorporating empirically supported components that promote success and transition to graduate school, including tiered mentorship, a didactic-preceptor model, hands-on experience, and interdisciplinary work. We describe participant characteristics and consider the program elements that may contribute to trainees' success, highlighting the importance of undergraduate training within a health care system like VHA. We found that all program completers attained their bachelor's degree and nearly 70% advanced to graduate studies. Despite some differences based on participant characteristics, all program components were deemed useful preparation for professional success, with hands-on research experience and mentoring cited as the most helpful. The promising results of our case study demonstrate the feasibility of successfully implementing an undergraduate training program to provide a pathway to advanced careers in health care within the VHA. We posit that programs like ours can serve as a framework for creating pathway training programs that target undergraduates traditionally underrepresented, subsequently empowering them to pursue health care careers, and ultimately increasing diversity by training professionals who are better prepared to assist with diverse patient needs. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Comprehensive Review on Mechanistic Insights, Optimal Dosages, and Safety Prospective of Natural Products in Anticancer Therapeutics

Cancer remains a formidable global health challenge, necessitating sustained research efforts to develop innovative and efficacious therapeutic modalities. The exploration of alternative cancer therapies has gained prominence, given the adverse side effects associated with conventional treatments like chemotherapy. Natural medicines, particularly those derived from botanical sources, emerge as a potentially more viable option for cancer treatment within the confines of therapeutic and safe dosage parameters. This comprehensive review elucidates the effective mechanisms and safety profiles related to the dosage of these natural compounds. The literature under consideration spans and has been meticulously curated from reputable databases, including PubMed, Scopus, and Google Scholar. Noteworthy natural substances encompassed in this scrutiny include gossypol, curcumin, resveratrol, genistein, anthocyanin, and hispidulin. The review outlines their respective mechanisms, therapeutic dosages, and safety perspectives within the context of cancer treatment. These compounds manifest diverse anticancer effects, ranging from the induction of apoptosis and inhibition of cell proliferation to the modulation of crucial signaling pathways. These natural compounds exhibit promising anticancer potential by targeting key facets of cancer progression, notably by i) instigating apoptosis and ii) intervening in cell cycle checkpoints. However, a more strategic and nuanced investigation is imperative to fully elucidate their optimal dosages, modes of action, and potential synergies with existing cancer treatment modalities. This critical gap in our understanding underscores the necessity for further in-depth research to optimize the therapeutic potential of these plant-derived chemicals.

Factors Affecting Treatment Selection Among Patients With Hidradenitis Suppurativa

Despite the US Food and Drug Administration's approval of adalimumab for the treatment of hidradenitis suppurativa (HS), prescription rates remain low, indicating a critical gap between evidence-based guidelines and clinical practice. Understanding the medical decision-making process that these patients use when considering biologic agents and other HS therapies may uncover opportunities for improved patient-physician communication and HS disease control. To elucidate factors that affect the medical decision-making process for patients with HS, with an emphasis on biologic therapies. Open-ended semistructured interviews were conducted with English-speaking adults with HS (aged ≥18 years) recruited from 2 dermatology clinics that are part of Emory University School of Medicine in Atlanta, Georgia. All participants had an average 7-day pain score of 1 or higher on a 0- to 10-point numeric rating scale. Surveys were conducted between November 2019 and March 2020, and data were analyzed from December 2021 to August 2022. Data collection continued until thematic saturation was reached at 21 interviews. A total of 21 participants (median [IQR] age, 38.5 [27.9-43.4] years; 16 females [76%]) were included in the analysis. Almost all participants (96%) had Hurley stage II or III disease, and 15 (71%) had a history of adalimumab use. Suffering threshold, perceptions of treatment risk, treatment fatigue, disease understanding, and sources of information (included dermatologists, the internet, advertisements, and friends and loved ones) were identified as factors affecting participants' decisions to initiate new treatments for HS. Results of this qualitative study suggest that mitigating misconceptions about treatment risk, identifying gaps in disease knowledge, and emphasizing early treatment to prevent scarring and disease progression may empower patients with HS to engage in treatment planning and to try new therapies.

Molecular Basis and Engineering Strategies for Transcription Factor-Mediated Reproductive-Stage Heat Tolerance in Crop Plants

Heat stress (HS) is a major threat to crop productivity and is expected to be more frequent and severe due to climate change challenges. The predicted increase in global temperature requires us to understand the dimensions of HS experienced by plants, particularly during reproductive stages, as crop productivity is majorly dependent on the success of plant reproduction. The impact of HS on crop productivity is relatively less-studied than the other abiotic stresses, such as drought and salinity. Plants have evolved diverse mechanisms to perceive, transduce, respond, and adapt to HS at the molecular, biochemical, and physiological levels. Unraveling these complex mechanisms underlying plant HS response and tolerance would facilitate designing well-informed and effective strategies to engineer HS tolerance in crop plants. In this review, we concisely discuss the molecular impact of HS on plant reproductive processes and yield, with major emphasis on transcription factors. Moreover, we offer vital strategies (encompassing omics studies, genetic engineering and more prominently gene editing techniques) that can be used to engineer transcription factors for enhancing heat tolerance. Further, we highlight critical shortcomings and knowledge gaps in HS tolerance research that should guide future research investigations. Judicious studies and a combination of these strategies could speed up the much-needed development of HS-resilient crop cultivars.

Evaluating ChatGPT performance in Arabic dialects: A comparative study showing defects in responding to Jordanian and Tunisian general health prompts

Background: The role of artificial intelligence (AI) is increasingly recognized to enhance digital health literacy. There is of particular importance with widespread availability and popularity of AI chatbots such as ChatGPT and its possible impact on health literacy. The involves the need to understand AI models’ performance across different languages, dialects, and cultural contexts. This study aimed to evaluate ChatGPT performance in response to prompting in two different Arabic dialects, namely Tunisian and Jordanian.
 Methods: This descriptive study followed the METRICS checklist for the design and reporting of AI based studies in healthcare. Ten general health queries were translated into Tunisian and Jordanian dialects of Arabic by bilingual native speakers. The performance of two AI models, ChatGPT-3.5 and ChatGPT-4 in response to Tunisian, Jordanian, and English were evaluated using the CLEAR tool tailored for assessment of health information generated by AI models.
 Results: ChatGPT-3.5 performance was categorized as average in Tunisian Arabic, with an overall CLEAR score of 2.83, compared to above average score of 3.40 in Jordanian Arabic. ChatGPT-4 showed a similar pattern with marginally better outcomes with a CLEAR score of 3.20 in Tunisian rated as average and above average performance in Jordanian with a CLEAR score of 3.53. The CLEAR components consistently showed superior performance in the Jordanian dialect for both models despite the lack of statistical significance. Using English content as a reference, the responses to both Tunisian and Jordanian dialects were significantly inferior (P<.001).
 Conclusion: The findings highlight a critical dialectical performance gap in ChatGPT, underlining the need to enhance linguistic and cultural diversity in AI models’ development, particularly for health-related content. Collaborative efforts among AI developers, linguists, and healthcare professionals are needed to improve the performance of AI models across different languages, dialects, and cultural contexts. Future studies are recommended to broaden the scope across an extensive range of languages and dialects, which would help in achieving equitable access to health information across various communities.