Fear of acquiring HIV infection among healthcare workers can impede the quality of prevention of mother-to-child transmission (PMTCT) services. Objectives This paper focuses on understanding healthcare workers’ fear of acquiring HIV infection and aims to identify the key contributing factors associated with that fear while providing PMTCT related services to pregnant women in Fiji. Additionally, this paper highlights the implications of this fear on providing quality PMTCT related service to pregnant women. Design Qualitative methodology was employed in this study. Setting Three tertiary hospitals and associated health centers in Fiji. Study Sample A total of 58 healthcare providers were interviewed, including doctors (n=12), midwives (n=19), nurses (n=14), laboratory technicians (n=5) and counsellors (n=8) were interviewed, using in-depth interviews. Methods We collected the data through in-depth interviews conducted in Fiji between April-May 2013 and February-March 2014. Thematic analysis was used to analyse the data. Results We found that fear of occupationally acquired HIV infection was prevalent among healthcare workers, especially among nurses and midwives. Needlestick injuries, lack of awareness of infection control process, shortage of personal protective equipment, and delayed presentation of pregnant women with unknown HIV status in labour ward were identified as the main contributory factors associated with the fear. Conclusion Our findings would be valuable in developing strategies to overcome the fear among healthcare workers. Simple intervention such as standardised infection prevention and control training would be valuable for mitigating the fear of HIV infection among healthcare workers.

Objective: To examine the impact of viral infection and carcinogens on the head and neck squamous cell carcinoma (HNSCC) tumor immune microenvironment (TIME) and assess whether the immune signature offers valuable clinical insights for immunotherapy. Methods: By integrating the scRNA-seq data of tumor-infiltrating leukocytes (TILs) from both HPV-negative (HPV -) and HPV-positive (HPV +) HNSCC patients from TCGA cohort, a comprehensive map of TIME in HNSCC was created. Results and Conclusions: TILs exhibited distinct cellular composition and gene expression between HPV - and HPV + HNSCC. The remodeling of myeloid cells indicated that activated dendritic cells possess migratory potential in HNSCC. C1QC + tumor-associated macrophages (TAMs) displayed an M2 signature in HPV - HNSCC, which may result from the regulation of NR1H3. Further analysis of T cells demonstrated that increased T follicular helper (Tfh) infiltration predicted improved survival in HPV + HNSCC. These data point to an activation-dependent exhaustion expression program, particularly for TIGIT in GZMK + exhausted T cells in HPV - HNSCC. And more robust CCL signaling in HPV + HNSCC provides insights into the molecular basis for precision medicine.

This paper presents the design and optimization of a power and communication architecture for a car dashcam system with integrated WiFi data transmission. The system architecture utilizes a 5V DC power supply regulated through DC-DC buck converters and Low Dropout Regulators (LDOs) to provide stable power to the image sensor and other subsystems. To improve image quality, especially in low-light conditions, power stability was enhanced using additional capacitors and beads to mitigate noise and ripple effects. The primary communication link between the dashcam’s sensor and the WiFi module is established via a UART interface, enabling efficient real-time data transmission to mobile devices. The image sensor’s digital data is processed by an ISP (Image Signal Processor) and transmitted through the MIPI interface to the SoC, while the WiFi module provides seamless data connectivity for remote access and live monitoring. This paper discusses the power design challenges, particularly in the analog and digital domains, and evaluates the impact of power noise on image quality and transmission reliability over WiFi. Test results demonstrate that improving power integrity significantly reduces noise artifacts, such as horizontal bands in low-light video, and enhances the overall performance of the WiFi transmission. This solution is particularly relevant for automotive and IoT applications where stable image capture and efficient wireless communication are critical.

OBJECTIVE: To examine the effects of social media use on eating disorders and to explore the pathways of eating disorders in people with normal/abnormal perceptions of their weight. METHODS: The Eating Disorder Examination Self-Assessment Questionnaire, the Rosenberg Self-Esteem Scale, the Chinese Frost Perfectionism Questionnaire, and the Self-Objectification Questionnaire were used to investigate 240 Chinese social media users. RESULTS: Social media use and self-esteem were direct predictors of eating disorders, and body mass index partially mediated the relationship between social media use and eating disorders; perfectionism and self-objectification fully chain-mediated the relationship between social media use and eating disorders. For the non-normally perceived group, low self-esteem and perfectionism were the most significant factors in the formation of eating disorders, whereas the level of eating disorders in the normally perceived group was mainly influenced by body mass index, perfectionism and media use. CONCLUSION: The formation of eating disorder tendencies is a dynamic process,

A document by Sheetal Temara. Click on the document to view its contents.

Title PageManuscript type Case Report

Background and Purpose: Preclinical studies suggest that highly selective dopamine D3 receptor (D3R) antagonists or partial agonists hold promise for treating substance use disorders (SUD). However, their limited effectiveness in reducing cocaine self-administration is a major drawback. This study investigated whether cariprazine (a D3R-preferring partial agonist) and its analogs ESG-1-60 and ESG-1-61 have enhanced efficacy in reducing cocaine-taking and -seeking behavior. Experimental Approach: In vitro BRET experiments were used to characterize the functional efficacies of cariprazine and its analogs. Intravenous cocaine self-administration and reinstatement models were used to evaluate efficacy in reducing cocaine-taking and -seeking behavior. Optical intracranial self-stimulation (oICSS) procedures assessed effects on DA-dependent behavior. Open-field locomotion, oral sucrose self-administration, and conditioned place-preference were used to evaluate potential unwanted side effects. Key Results: BRET functional assays indicated that cariprazine and ESG-1-60 are D3R-preferring partial agonists, while ESG-1-61 is a D3R-preferring antagonist/inverse agonist. All three compounds inhibited cocaine self-administration under both fixed-ratio and progressive-ratio reinforcement schedules and reduced cocaine-induced reinstatement of drug-seeking behavior in both male and female rats. The compounds did not alter locomotor behavior but suppressed sucrose intake and DA-dependent oICSS. Cariprazine and ESG-1-61 produced significant place aversion, while ESG-1-60 did not. Chronic administration of ESG-1-60 inhibited cocaine self-administration. Conclusions and Implications: Novel D3R-preferring compounds ESG-1-60 and ESG-1-61 are highly effective in reducing cocaine taking and seeking under various reinforcement conditions. ESG-1-60 warrants further investigation as a new pharmacotherapy for treating cocaine use disorder due to its effectiveness in these models and lack of unwanted behavioral effects.

Cancer therapies have attempted to target the transcription factor p53, a gene also described as the “guardian of the genome,” for decades. However, the approach has faced numerous barriers to clinical efficacy due to several factors: mutations in p53 occur in almost half of all human cancers, mutations are cancer-specific, and the associated genomic changes grant mutant p53 with oncogenic potential unique from that of wild-type p53. A host of new therapeutic agents have emerged that work to target mutant p53. These agents can broadly be classified into six categories: the viral approach, direct modifiers of the p53 pathway, epigenetic modifiers of the p53 pathway, synthetic lethal agents, structural reactivators, and immune activating vaccines. Even these strategies have been met with limited success. Bypassing p53 entirely may be the next avenue in cancer therapeutics to kill tumor cells regardless of p53’s mutation pattern.

Atypical Hemolytic Uremic Syndrome Triggered by COVID-19 Infection in a Pediatric Patient with CD46 MutationParisa Maleki Dana1, Parsa Lorestani2, Mohamad Reza Tohidi3

Cold Ceramic for Repairing Perforations: A Case Series

Transgenerational plasticity in plants is an increasingly recognized phenomenon, yet it is mostly unclear whether transgenerational plasticity is relevant to both the fitness of the plant and its interacting species. Using monoclonal strains of the giant duckweed (Spirodela polyrhiza) and its native herbivore, the waterlily aphid (Rhopalosiphum nymphaeae), we assessed whether pre-treating plants with copper excess, both indoors and outdoors, induces transgenerational plasticity in plant defences that alter plant and herbivore fitness. Outdoors, copper pre-treatment tended to increase plant growth rates under recurring copper excess. Indoors, copper pre-treatment either increased or decreased plant growth rates under recurring conditions, depending on the plant genotype. Copper pre-treatment induced anthocyanins that protected plants against copper toxicity, and these elevated levels were transgenerationally retained. Copper pre-treatment also transgenerationally increased the levels of 12-oxo-phytodienoic acid (OPDA), a jasmonate precursor. Nevertheless, aphids grew up to 50% better when the plants were pre-treated with copper. The increased aphid growth was likely caused by transgenerationally elevated OPDA levels, as aphids grew better when jasmonates were externally applied to plants. Taken together, this study shows that transgenerational plasticity is relevant to both plant and herbivore fitness, which highlights the role of transgenerational plasticity in plant evolution and species interactions.

Investigating resource selection patterns of declining species is critical to developing effective conservation strategies and mitigating negative population trends. We trapped and radio-collared northern bobwhite (Colinus virginianus) and recorded the location of each individual three times per week during the northern bobwhite breeding season (April – September) to infer resource selection by non-brooding adults. We defined 13 vegetation communities with varying fire histories and assessed their relative use via a distance-based logistic regression model within a Bayesian framework. We found reliable evidence that non-brooding northern bobwhite preferred supplemental feed lines, recently burned natural pine stands, one-year rough in shrub/scrub, and one-year rough in hardwood-pine stands. Conversely, we found they avoided one-year rough in natural pine stands, recently burned shrub/scrub, and recently burned hardwood-pine stands. Our data suggest that non-brooding bobwhite’s successional stage preference may vary between vegetation communities within the same study area and adds further evidence to the importance of fire and vegetation interspersion in bobwhite management. Results from our study may be applied to enhance habitat for non-brooding northern bobwhite and potentially increase adult survival, an important metric correlated with bobwhite population growth.

Boost converters are used in photovoltaic systems for maximum power point tracking. Their performance depends on the environmental conditions under which the converter operates. This article aims to optimize the losses, volume, and weight of the converter in a multi-objective optimization applied using the NSGA-II metaheuristic, considering the operating points of the photovoltaic panel for specific temperature and real irradiance values from a given location. As a second objective, this article verifies whether the converter obtained in one location will be capable of operating in another location within the working operation ranges of the components present in the converter.

The lifespan of a converter depends on component reliability. In non-redundant designs like buck converters, a single component failure can shut down the circuit. Capacitors are more prone to failure than inductors or semiconductors. Monitoring parameters such as equivalent series resistance, rather than manual data, better assesses a converter’s useful life. This article compares two parameter estimation methods: recursive state space and non-linear least squares, with R² values and residuals analysis ensuring reliable results that closely correlate with real converter values.

Understanding how metacommunities respond to natural and anthropogenic disturbances is a key objective in ecology. In this study, we introduce a robust analytical framework to identify communities whose extirpation triggers stronger (hereafter keystone communities) or weaker (hereafter idle communities) cascading effects on extinction and colonization events that ultimately drive temporal changes in compositional patterns of the remaining communities. These cascading dynamics reflect the impact of extirpated communities on connectivity and subsequent dispersal dynamics. Since the framework uses spatial information on compositional similarities to infer changes that would unfold over time due to the extirpation of one or more communities, we describe it as a space-for-time approach. Through mechanistic simulation models that replicate removal experiments, we demonstrate that our framework accurately estimates ”keystoneness”, ranking local communities by their role in maintaining the metacommunity’s compositional patterns. As such, our models demonstrate that the relationship between patch characteristics and our keystoneness metric is closely linked to the structure and dynamics of their metacommunities. A key feature of our framework is its ability to generate community keystoneness estimates that are statistically independent of local diversity, providing a valuable tool for assessing the relevance and conservation value of local communities. This is particularly important in cases where high local diversity reflects an influx of individuals into demographic sinks, a common consequence of human activities near natural areas. To showcase the unique insights of this framework, we examined and contrasted the effects of artificial light at night on the diversity and keystoneness of a moth metacommunity sampled over two decades. We conclude with a discussion of the framework’s potential applications and underlying assumptions, emphasizing its relevance for addressing both conceptual and applied ecological questions, particularly its potential to assess the conservation value of local communities under ecological stress.

We propose a system analysis approach to address the challenges associated with the rapid changes in pulsed light technology within unpredictable and time-varying systems. Additionally, we introduce a new virtual system fish scale controller. This approach considers the unpredictable nature of pulsed light and ionization events and involves developing a comprehensive full-order node model that accounts for both forward and reverse effects. The fish scale virtual controller ensures a global balance between the primary and auxiliary inputs, while maintaining stability in the input of the sub-node system. By employing linear approximation, we aim to minimize errors caused by nonlinear flow variations. The virtual system’s various reverse balance parameters effectively counteract the fluctuations in light and enable stable tracking control of the time-varying system represented by the full-order node model. Finally, we present a practical example of intense pulsed light to demonstrate the efficacy of our system analysis approach and the fish scale virtual controller.

In [2] M. Jaoua et al. studied the linear approximation of Robin problem on Ω an open bounded domain of R d , and they given some important results. In this paper, we study a nonlinear approximation of an elliptic problem with a nonlinear Robin boundary condition in a domain of R 2 . We prove the existence and uniqueness of solution by an iterative construction method with admissible condition on ∂Ω.

Studying neurological disorders in vitro is still challenging due to the human brain’s complexity and the difficulty of obtaining primary neural cells. However, tissue engineering and tridimensional (3D) cell culture have become increasingly important tools for disease modeling. By providing an extracellular matrix (ECM) substrate that closely resembles physiological conditions, 3D cell culture offers several advantages over standard monolayer cell culture, including enhanced cell-cell and cell-matrix interactions. This results in a microenvironment that more accurately reflects in vivo biology. In this study, we performed an in-depth analysis of the proteome and matrisome of 3D tissue-engineered dermis, made from human primary dermal fibroblasts cultivated in 3D and embedded in a self-produced ECM. Interestingly, in silico analysis revealed that neurogenesis and associated functions were predicted to be strongly activated in this tissue-engineered 3D model. Indeed, we showed that ECM proteins involved in neuronal development and maintenance, typically produced by cerebral cells, were also expressed by dermal fibroblasts. Of particular interest, the 3D co-cultivation of dermal fibroblasts with iPSC-derived motor neurons readily enabled long-lasting culture periods without costly media supplementation with exogenous additives. Patient-derived dermal fibroblasts, cultivated in 3D, could therefore become valuable models for the study of neurological diseases. This approach offers a cost-effective and a less invasive alternative to brain biopsies for modeling complex neurological disorders in vitro.

Introduction: This study investigated the potential association between morbid obesity and SNHL in a homogenous cohort of patients eligible for bariatric surgery. Methods: In this prospective study, one hundred adult patients with morbid obesity who met the criteria for bariatric surgery were enrolled. Patients with known causes of hearing loss and otologic abnormalities were excluded. To assess their hearing status, all participants underwent detailed audiometric evaluations, including pure-tone and speech audiometry. Medical history and anthropometric measurements were also collected. Results: In this cohort of morbidly obese patients, 16% were found to have SNHL, primarily in high frequencies. There was no statistically significant association between morbid obesity, as measured by body mass index (BMI), weight, or obesity duration, and the risk of hearing loss. Older age and male gender were identified as significant risk factors for SNHL in this population. Notably, a significant discrepancy was found between patients’ subjective complaints of hearing loss and objective audiometry results. Conclusion: Contrary to previous conceptions, this study did not find a significant association between morbid obesity and hearing loss in a homogenous morbidly obese cohort. Further research is needed to explore the multifactorial nature of hearing loss in individuals with obesity and to understand its underlying mechanisms better.

Chromosomes, which contain genetic information crucial for the human body, exhibit a thread-like structure within the cell nucleus. Analyzing chromosomes, a process known as karyotyping, is essential for identifying abnormalities within them. Despite the development of various methods for detecting abnormalities, existing approaches often suffer from inefficiencies such as being time-consuming and ineffective in feature extraction. To address these challenges, a novel Visual Geometric Transformer-based Mantis search (VGT-MS) algorithm is proposed that detect abnormal conditions of chromosomes. However, these images often contain extraneous elements that need to be removed. Subsequently, the VGG-16 model is employed to extract features and Vision Transformer is utilized to identify chromosome abnormalities. The parameters are tuned and optimized by Mantis Search Algorithm that validated the performance of the model. The effectiveness of the developed model is evaluated using metrics such as F1-score, accuracy, recall, ROC, and precision. The results reviewed that the proposed achieved superior performance boosting an accuracy, precision, recall and F1-score is 98.0%, 97.2%, 96.2%, 97.6%, all while maintaining lower execution time. Overall, the VGT-MS algorithm presents a robust solution for chromosome abnormality detection, effectively overcoming the limitations of previous approaches and providing enhanced performance metrics.

Studies have indicated that prolonged exposure to unwanted acoustic stimuli can trigger noise annoyance. Large engines are prevalent in industrial and traffic settings, but their high performance often comes with significant radiated noise emissions, leading to relevant staff members’ annoyance. Traditional evaluations, for example psychoacoustic parameters, of noise annoyance fail to adequately account for the physiological processes involved in sound perception. Electroencephalogram (EEG) signals can provide insights into the physiological responses to external acoustic stimuli. Here, we design an experimental paradigm to capture EEG signals and extract spectral and brain’s functional connectivity features when the participants evaluate the annoyance of diesel engine radiated noise samples. The correlation between spectral features and subjective annoyance shows that the delta and alpha bands’ relative power could reflect noise annoyance. Delta-band brain network analysis inferred those differences in exogenous temporal attention networks’ threshold, about 30%, result in variations in noise annoyance perception.

Aims CYP2D6 is a key enzyme for metabolizing tamoxifen into active metabolites, but polymorphisms in this enzyme lead to varying metabolic capacities. Increasing the tamoxifen dose in patients with deficient CYP2D6 metabolism can elevate endoxifen levels to those of patients with normal phenotypes. This study examines the impact of increasing the dose of tamoxifen on toxicity in poor metabolizers of the CYP2D6 enzyme. Methods Eighty-six breast cancer patients treated with tamoxifen were classified by CYP2D6 metabolizer phenotype according to Clinical Pharmacogenetics Implementation Consortium guidelines. All patients started with a 20 mg/day dose of tamoxifen, with poor metabolizers having their doses increased to 60 mg/day. Side effects, including osteoarticular pain, hot flashes, asthenia, and uterine changes, were analyzed using Kaplan-Meier analysis and the Cox proportional hazards regression model to assess the relationship between CYP2D6 metabolizer type and these side effects. Results Significant differences were found only in uterine changes among CYP2D6 metabolizer types in both the overall cohort and a subgroup selected via Propensity Score Matching (PSM). Rapid metabolizers exhibited a lower incidence of uterine changes (p < 0.001 in Kaplan-Meier analysis; HR 0.195, 95% CI: 0.07 - 0.52, p = 0.001) in the complete cohort. In the PSM cohort, Kaplan-Meier analysis showed a p-value of 0.001 with an HR of 0.07 (95% CI: 0.01 - 0.54, p = 0.011). Conclusion Tamoxifen dose scalation in patients with poor CYP2D6 metabolism may increase the occurrence of uterine changes but does not significantly affect the incidence of osteoarticular pain, hot flashes, or asthenia.

Augmented reality (AR) technology can provide immersive and natural interactive interfaces for brain-computer interface (BCI) systems. The control architecture of existing AR-BCIs is at joint-level (JL) or action-level (AL), which brings a huge user burden and poor interactive experiences. A task-level (TL) BCI control method was proposed in this study to enhance interactive experiences. The TL AR-BCI system based on steady-state visual evoked potentials (SSVEPs) was implemented controlling a robotic arm to grab and drop blocks. The online experiment of 10 subjects shows TL AR-BCI can effectively reduce the number of control steps and stimulation time while maintaining the same performance as JL and AL AR-BCIs. The performance of three AR-BCIs (JL, AL, TL) was calculated(Mean accuracy: 90.66\%, 92.52\%, and 92.2\%. Mean information transfer rates: 77.56bits/min, 80.06bis/min, and 82.71bits/min. Mean numbers of control steps: 35.48, 17.32 and 13.05. Mean stimulation time: 0.97s, 0.97s and 0.89s). The results show that TL AR-BCI can effectively reduce the number of control steps and stimulation time while maintaining the same performance as JL and AL AR-BCIs.

Dispersal is a fundamental process driving many ecological patterns. During transfer, species often make large-scale displacements resulting in significant energetic losses with implications for fitness and survival, however generalising these losses across different taxonomic groups is challenging. We developed a bioenergetic dispersal model based on fundamental processes derived from species traits. By balancing energy storage and energy loss during active dispersal, our mechanistic model can quantify energetic expenditures depending on landscape configuration and the species in focus. Moreover, it can be used to predict the maximum dispersal capacity of animals, which we compare with recorded maximum dispersal distances (n = 1571). Due to its foundation in bioenergetics it can easily be integrated into various ecological models, such as food-web and meta-community models. Furthermore, as dispersal is integral to ecological research, the quantification of dispersal capacities provides valuable insight into landscape connectivity, species persistence, and distribution patterns with implications for conservation research.