Browse Articles

Predictors of clozapine concentration and psychiatric symptoms in patients with schizophrenia

Clozapine has superior efficacy to other antipsychotics, especially in patients with treatment-resistant schizophrenia. However, its pharmacokinetics and pharmacodynamics vary largely among patients. We aimed to evaluate the clinical and genetic factors associated with the pharmacokinetics and pharmacodynamics of clozapine in patients with schizophrenia. Blood samples for clozapine pharmacokinetic assessment were collected from patients with schizophrenia at weeks 2 (visit 2), 8 (visit 3), and 18 (visit 4) from the initiation of clozapine treatment. The Positive and Negative Syndrome Scale (PANSS) score was assessed at baseline (visit 1) and visits 3 and 4. Linear mixed models were used to identify the clinical and genetic variables associated with the clozapine concentration and total PANSS score. A total of 45 patients were included in the pharmacogenomic analysis. Owing to the small sample size, we categorized concomitant medications into four groups. However, individual drugs may have different effects on clozapine concentration. Clozapine concentration was significantly associated with smoking status and cumulative clozapine dose. Clozapine concentration was significantly associated with five single nucleotide polymorphisms (SNPs) in three genes (rs28371726 and rs202102799 in CYP2D6, rs4148323 and rs34946978 in UGT1A1, and rs2011404 in UGT1A4). Furthermore, follow-up time, body mass index, and total bilirubin levels were significantly associated with the total PANSS scores. The PANSS score was significantly associated with four SNPs in two genes (rs7787082 and rs10248420 in ABCB1 and rs2133251840 and rs762502 in DRD4). This study suggests potential clinical and genetic predictors of clozapine concentration and psychiatric symptoms in patients with schizophrenia treated with clozapine. With further investigations in diverse populations, our findings may provide important information on variables to be considered in individualized clozapine treatment.

Automatic trailer generation for movies using convolutional neural network

Energy evolution and damage ontology modeling of coal destruction at different water contents

The aim of this study was to investigate the energy evolution characteristics and an ontological model of the deformation of coal under different water contents. Uniaxial compression tests were conducted for coal with different water contents, and the analyses were based on the energy principle and the principle of minimum energy dissipation. The results showed that the physical properties of the coal specimens were different under different water contents, the peak strain was positively correlated with water content, and the compressive strength and elastic modulus were negatively correlated with water content. Additionally, the compressive strength and elastic modulus of the coal specimens showed a steep and subsequent slow-change trend. From an energy perspective, the higher the water content of the coal specimens, the higher their energy dissipation at the peak; the smaller the limiting elastic strain energy, the lower the absorbed energy. The principle of minimum energy dissipation was used to deduce the energy evolution and mechanical properties of coal body damage under different water contents, deriving the initial and critical values of damage. The water content of the coal specimens was positively correlated with their initial and critical values of damage, and the relationship with water content was nonlinear. This result was used to establish a stress–strain ontology model for coal rocks with different water contents under uniaxial compression. The model is an improvement over traditional ontology models, addressing the problem of low accuracy in simulations of materials at the compaction stage.

Modified magnetic chitosan with mono(6-amino-6-deoxy)-β-cyclodextrin as a novel catalyst toward the synthesis of pyrazolopyranopyrimidines and pyrano[2,3-c]pyrazole-3-carboxylates

Healthcare utilization trends in adults with asthma or COPD during the first year of COVID-19 pandemic in comparison to pre-pandemic: A population-based study

Objectives To assess how changes in outpatient services during the first year of the COVID-19 pandemic were related to acute healthcare use (emergency department or hospitalizations) for individuals with asthma or chronic obstructive pulmonary disease (COPD). Methods We conducted an observational study using health administrative data in Ontario (Canada) from January 2016 to March 2021 on all adults with diagnosed asthma or COPD. We used monthly time series auto-regressive integrated moving-average (ARIMA) and pre-pandemic monthly rates (January 2016 to February 2020) to calculate projected rates (i.e., a pandemic had not occurred) during the pandemic (March 2020 to March 2021), and Quasi-Poisson models with two-way interaction to estimate crude and adjusted rate ratios. Results In the first pandemic year, in individuals with asthma or COPD, outpatient visit rates started lower than projected (Mar-May 2020), returned to projected in the middle of the year (Jun-Aug 2020) and then rose to higher than projected between Sep 2020 and Mar 2021: observed rates of 80,293 per 100,000 persons vs. projected 74,192 (95% CI: 68,926-79,868) in individuals with asthma, and 92,651 vs. projected 85,871 (95% CI: 79,975-92,207) in individuals with COPD. Acute care rates remained below projected during the first pandemic year. While pulmonary function test (PFT) rates remained below projected during the first pandemic year, in both populations, a decrease in acute care visits during the pandemic, compared to pre-pandemic, was noted during months with the highest PFT rates (interaction p-values < 0.0001). Conclusions Despite asthma and COPD being ambulatory-care sensitive conditions, lower rates of outpatient visits during the beginning of the pandemic were not associated with increased rates of acute care use. Lower PFT rates were associated with higher acute care visit rates, suggesting that access to PFT during pandemic is likely important for individuals with asthma or COPD.

The effect of preoperative total antioxidant capacity on short-term outcomes after kerato-lenticule extraction surgery

Medical students’ and educators’ opinions of teleconsultation in practice and undergraduate education: A UK-based mixed-methods study

Introduction As information and communication technology continues to shape the healthcare landscape, future medical practitioners need to be equipped with skills and competencies that ensure safe, high-quality, and person-centred healthcare in a digitised healthcare system. This study investigated undergraduate medical students’ and medical educators’ opinions of teleconsultation practice in general and their opinions of teleconsultation education. Methods This study used a cross-sectional, mixed-methods approach, utilising the additional coverage design to sequence and integrate qualitative and quantitative data. An online questionnaire was sent out to all medical schools in the UK, inviting undergraduate medical students and medical educators to participate. Questionnaire participants were given the opportunity to take part in a qualitative semi-structured interview. Descriptive and correlation analyses and a thematic analysis were conducted. Results A total of 248 participants completed the questionnaire and 23 interviews were conducted. Saving time and the reduced risks of transmitting infectious diseases were identified as common advantages of using teleconsultation. However, concerns about confidentiality and accessibility to services were expressed by students and educators. Eight themes were identified from the thematic analysis. The themes relevant to teleconsultation practice were (1) The benefit of teleconsultations, (2) A second-best option, (3) Patient choice, (4) Teleconsultations differ from in-person interactions, and (5) Impact on the healthcare system. The themes relevant to teleconsultation education were (6) Considerations and reflections on required skills, (7) Learning and teaching content, and (8) The future of teleconsultation education. Discussion The results of this study have implications for both medical practice and education. Patient confidentiality, safety, respecting patients’ preferences, and accessibility are important considerations for implementing teleconsultations in practice. Education should focus on assessing the appropriateness of teleconsultations, offering accessible and equal care, and developing skills for effective communication and clinical reasoning. High-quality teleconsultation education can influence teleconsultation practice.

Oral mucosal lesions in Polish patients with acute myeloid leukemia after allogeneic hematopoietic cell transplantation

Unveiling the digital revolution: Catalyzing total factor productivity in agriculture

Drawing upon panel data spanning the years 2011 to 2022 and encompassing 30 provinces across China, this research employs empirical methodologies, specifically the difference GMM and system GMM methods, to scrutinize the impact of the digital economy on the total factor productivity (TFP) within the agricultural sector. The study reveals a significant augmentation of China’s agricultural TFP attributable to the digital economy, a finding robust to various methodological examinations. Notably, the influential role of the digital economy on agricultural TFP is more conspicuous in the central and western regions, as well as in locales characterized by lower productivity levels. Mechanistic analysis underscores that the digital economy exerts a positive influence on agricultural TFP through the stimulation of innovation and marketization effects. Furthermore, strategic recommendations emerge from this study, advocating for the reinforcement of institutional and mechanistic reforms to cultivate an enabling external milieu for the digital economy to propel agricultural TFP. It is posited that regional development strategies should be tailored based on individual resource endowments and the extent of digital economic development. Additionally, there is a call to refine mechanisms promoting high-quality development in agriculture, with an overarching goal of comprehensively elevating agricultural TFP. The implications of this research extend to the imperative need for a nuanced and context-specific approach to advancing agricultural productivity across diverse regions in China.

Automatic detecting multiple bone metastases in breast cancer using deep learning based on low-resolution bone scan images

Increased galanin-galanin receptor 1 signaling, inflammation, and insulin resistance are associated with affective symptoms and chronic fatigue syndrome due to long COVID

Background Patients with Long COVID (LC) often experience neuropsychiatric symptoms such as depression, anxiety, and chronic fatigue syndrome (CFS), collectively referred to as the physio-affective phenome of LC. Activated immune-inflammatory pathways and insulin resistance significantly contribute to the physio-affective phenome associated with LC. Methods In a cohort of 90 individuals, categorized into those with and without LC, we evaluated, 3-6 months following acute SARS-CoV-2 infection, the correlations between the Hamilton Depression (HAMD), Hamilton Anxiety (HAMA), and Fibro-Fatigue (FF) Rating Scale scores, and serum C-reactive protein (CRP), prostaglandin E2 (PGE2), galanin-galanin receptor 1 (GAL-GALR1) signaling, insulin resistance, insulin-like growth factor (IGF-1), plasminogen activator inhibitor-1 (PAI1), S100B and neuron-specific enolase (NSE). Results HAMD, HAMA, FF scores, CRP, PGE2, GAL-GALR1 signaling, insulin resistance, PAI1, NSE, and S100B are all higher in people with LC compared to those without LC. The HAMD/HAMA/FF scores were significantly correlated with PGE, CRP, GAL, GALR1, insulin resistance, and PAI1 levels, and a composite score based on peak body temperature (PBT) – oxygen saturation (SpO2) (PBT/SpO2 index) during the acute infectious phase. A combination of biomarkers explained a large part of the variance in CFS and affective scores (33.6%-42.0%), with GAL-GALR1 signaling, PGE2, and CRP being the top 3 most important biomarkers. The inclusion of the PBT/SpO2 index increased the prediction (55.3%-67.1%). The PBT/SpO2 index predicted the increases in GAL-GALR1 signaling. Conclusion These results indicate that the CFS and affective symptoms that are linked to LC are the consequence of metabolic aberrations, activated immune-inflammatory pathways, and the severity of inflammation during the acute phase of SARS-CoV-2 infection.

Hyperspectral discrimination of vegetable crops grown under organic and conventional cultivation practices: a machine learning approach

Location estimation of UWB-based wireless capsule endoscopy using TDoA in various gastrointestinal simulation models

Wireless capsule endoscopy (WCE) is a revolutionary field that aids in treating gastrointestinal disorders. For the development of a futuristic endoscopic capsule, identifying the location of abnormality is challenging yet a crucial step in determining the treatment procedure. Though the present-day wireless capsule endoscopes certified for endoscopic procedures predominantly work on the Medical Implant Communication System (MICS) band, the applications based on the Ultra-Wide Band (UWB) are gaining popularity for their immense possibilities. While received signal strength, time of arrival, phase of arrival, and angle of arrival are the basic parameters applied in research for location estimation of WCE, this paper uses a time difference of arrival (TDoA) approach using the Chan algorithm. To test the effectiveness of the algorithm, a series of UWB propagation experiments are performed utilizing human voxel models to find out the variance in distance error using an advanced electromagnetic simulation environment, which is then applied as the error to the distance estimate of the Chan algorithm, and the performance is analysed using different cases. Positioning receivers in three rows reduces the estimation error by 44%, and positioning the reference receiver in the middle row reduces it by 33%. The algorithm performance is observed for different variances in the distance estimation using different numbers of receivers, and the results are compared to the Cramér-Rao lower bound (CRLB). The calculated error in thickness from the different sections of abdominal tissues of the individual voxel models is applied to the distance estimates from the corresponding receiver sections prior to the WCE location estimation. The RMSE in WCE location estimation is found for individual voxel models, and the error is observed to reduce approximately from 4 mm to 1 mm, with variations in individual models, when the number of receivers are increased from 9 to 33.

Passenger physiology in self-driving vehicles during unexpected events

Abstract While using fully autonomous vehicles is expected to radically change the way we live our daily lives, it is not yet available in most parts of the world, so we only have sporadic results on passenger reactions. Furthermore, we have very limited insights into how passengers react to an unexpected event during the ride. Previous physiological research has shown that passengers have lower levels of anxiety in the event of a human-driven condition compared to a self-driving condition. The aim of our current study was to investigate these differences in unexpected road events in real-life passenger experiences. All subjects were driven through a closed test track in human-driven and then self-driving mode. During the journey, unforeseen obstacles were encountered on the path (deer and human-shaped dummies appeared). Using physiological measurements (EEG, eye movements, head movements and blinking frequencies) our results suggest that passengers had moderate affective preferences for human-driven conditions. Furthermore, multifractal spectra of eye movements and head movements were wider and blinking frequencies were decreased during unexpected events. Our findings further establish real-world physiological measurements as a source of information in researching the acceptance and usage of self-driving technologies.

Antifreeze proteins produced by Antarctic yeast from the genus Glaciozyma as cryoprotectants in food storage

Synthesis of antifreeze proteins (AFPs) is one of the adaptations of psychrophilic yeast to live in cold environments. AFPs demonstrate thermal hysteresis (TH) activity and inhibit the recrystallization of ice (IRI) during periodic temperature fluctuations. In this study, the Antarctic yeast strain 186, identified as Glaciozyma martinii, was found to synthesize an extracellular, glycosylated ~27 kDa ice-binding protein (GmAFP) exhibiting IRI activity. It is the first evidence of AFP secretion by the psychrophilic yeast Glaciozyma martinii. To scale up protein production, a synthetic gene from a closely related cold-adapted species, Glaciozyma antarctica, was expressed in Pichia pastoris GS115 strain. The recombinant 26.57 kD protein (GaAFP) displayed IRI activity and a cryoprotective effect in food storage. The addition of GaAFP to the stored frozen vegetables and fruits (carrot, kohlrabi, and blueberry) markedly reduced the drip loss during the thawing process and positively affected their structure, with an effect similar to glycerol. Moreover, GaAFP increased the cell survival of Saccharomyces cerevisiae after freezing. The insights from this study provided proof that AFPs from natural sources may serve as competent biodegradable, eco-friendly, non-cytotoxic and biocompatible substitutes for traditional cryoprotectants in enhancing the quality of frozen foods.

GWO and WOA variable step MPPT algorithms-based PV system output power optimization

Abstract The nonlinear characteristics and low efficiency of photovoltaic (PV) systems remain critical challenges that necessitate advanced solutions. This study proposes two innovative Maximum Power Point Tracking (MPPT) algorithms based on the Whale Optimization Algorithm (WOA) and Grey Wolf Optimization (GWO). The primary advantage of these methods lies in their adaptive step-size optimization, leveraging multiple criteria to determine the optimal step size. A novel fitness function was developed to improve tracking accuracy, minimize ripple, and reduce overshoot. Simulation results demonstrated remarkable improvements, including up to 98% reduction in ripple, 67% reduction in overshoot, and significant improvements in tracking accuracy compared to fixed-step methods. Field validation was conducted using real-world data from the Ain El Melh PV station in Algeria on June 21, 2023. Experimental results confirmed the effectiveness of the proposed methods, with the WOA-based MPPT achieving up to 99% ripple reduction and 40% overshoot reduction under dynamic environmental conditions. A comparative analysis of MPPT algorithms revealed superior performance metrics for the bio-inspired methods. The PO-WOA algorithm achieved the highest efficiency of 98.87% in simulation and 98.94% in real data, surpassing both PO and PO-GWO. It also minimized power loss to 0.56 W in simulation and 0.39 W in real data, demonstrating its optimization capabilities under fluctuating conditions. Although its response time was slightly longer than other methods, at 0.65 s in simulation and 0.48 s in real data, it prioritized stability and precision. These findings underscore the potential of WOA and GWO algorithms to enhance PV system performance, offering robust and efficient solutions for optimizing energy output in both simulation and real-world scenarios.

The impact of urban parks on the thermal environment of built-up areas and an optimization method

Rapid urbanization, while transforming people’s living environments, also brings a series of urban issues such as the urban heat island effect. The urban park is an effective means to alleviate the urban heat island effect in summer. How to make better use of the cold island effect formed by urban parks to improve the urban outdoor thermal environment is an important topic. This manuscript takes Xi’an as the research area, using remote sensing data as the data source and combining field surveys, to explore the cooling characteristics of the cold island effect in the urban built-up area. It is demonstrated that, the influencing factors of the cooling effect of urban park cold islands are summarized: the area and perimeter of the park, the area and perimeter of water bodies, and the area of trees are all positively correlated with the cooling effect. The surrounding building density and building plot ratio are also positively correlated with the cooling effect of the green space. A comprehensive scoring model for each influencing factor is established, and the principal component analysis method is used to determine the weight of each indicator on the cooling effect of park design elements, among which the area of green space parks has the greatest influence weight. The demand space for cold islands in Xi’an’s parks is analyzed, and optimization strategies and suggestions for improving the urban thermal environment are put forward from both inside and outside the park.

Predictive role of exteroceptive and interoceptive bodily dimensions to schizotypal personality traits

Multilevel analysis of undergoing clinical breast examination and its associated factors among mothers of reproductive age in Kenya: Kenyan Demographic and Health Survey 2022

Introduction Breast cancer is one of the most common public health concerns among women around the world. The incidence of breast cancer is increasing in all areas of the world. It is the first cause of death from malignant tumors. Breast cancer in Sub-Saharan African countries is the number one cancer and the leading cause of cancer mortality among women. In low-income countries like Kenya, early screening programs, including clinical breast examination by health professionals, can identify women’s health status and risk of breast cancer. Therefore, this study was conducted to assess the uptake of clinical breast examination for cancer and to determine the associated factors among mothers of reproductive age. Methods A total weighted sample of 10,267 mothers of reproductive age was included in this study. The data were taken from the recent Kenyan Demographic and Health Survey 2022. A multilevel multivariable logistic regression model was used to identify the associated factors associated with the uptake of clinical breast examination. In the multivariable multilevel analysis, the adjusted odds ratio (AOR) with a 95% CI was used to declare statistically significant associations with uptake among mothers of reproductive age in Kenya. Results In Kenya, the overall prevalence of clinical breast examination uptake among mothers of reproductive age was 11.39%. In multilevel analysis, the significant factors associated with the uptake of clinical breast examination were the age of the mothers; age was significantly associated with the uptake of clinical breast examination; when compared with mothers aged 15–24 years, examination increased in those aged 25–34 years (AOR =  1.45; 95% CI (1.15–1.83)) and 34–49 years (AOR =  2.4; 95% CI (1.88–3.29)), when compared to no education, odds of examination increased in those with primary education (AOR =  2.0; 95% CI (1.19–3.37)) and secondary and higher (AOR =  2.67; 95% CI (1.56–4.57)), when compared to mothers who are unemployed, the odds of examination were higher among those who are employed (AOR =  1.42; 95% CI (1.16–1.74)), place of delivery; when compared to mothers who delivered at home, the odds of examination were higher among those who delivered at a health institution (AOR =  1.5; 95% CI (1.0–2.19)), when compared to those who are not exposed to television, odds of examination increased in those who were exposed to this form of media (AOR =  1.34; 95% CI (1.0–1.72)), when compared to those who travel on foot, odds of examination increased in those who used vehicles for transportation (AOR =  1.34; 95% CI (1.12–1.62)), and when compared to communities with a high level of literacy, the odds of examination increased in communities with a low level of literacy (AOR =  1.7; 95% CI (1.14–2.54)). Conclusion In Kenya, the uptake of clinical breast examinations among mothers of reproductive age remains low. To address this, policymakers and stakeholders need to prioritize breast cancer screening programs to reduce mortality rates. The factors identified in this study are crucial for developing strategies to enhance clinical breast examination services, facilitating early detection and treatment of breast cancer.

Optimization of waste plastic fiber concrete with recycled coarse aggregate using RSM and ANN