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Loss of Sirtuin 7 impairs cell motility and proliferation and enhances S-phase cell arrest after 5-fluorouracil treatment in head and neck cancer
Impact of the COVID-19 lockdown in the United Kingdom on adolescent’s time use (CONTRAST study)
Background The COVID-19 pandemic has led to major changes in everyone’s lives, including adolescents. Given that adolescence is a crucial developmental stage, designing strategies to alleviate the impact of the COVID-19 on adolescents is critical. Furthermore, there is a growing literature on the relationship between how adolescents spend their time and impact upon health, nutrition, educational attainment and overall well-being outcomes, and the existence of a socioeconomic gradient with how time is allocated. Therefore, this study explored changes in adolescents’ time use during the first COVID-19 lockdown in the UK and the relationship between these changes and individual-level socioeconomic indicators including family affluence, free school meal eligibility, and food insecurity. Methods The data were collected from 11-15-year-olds using an online survey, which contained questions on demographic characteristics, socioeconomic indicators, and time use across a range of activities before and during the first COVID-19 lockdown. Changes in time use in relation to socioeconomic indicators were explored using descriptive and regression analysis. Results 687 adolescents completed the survey. There was an overall decrease in the amount of time spent on school work, an increase in screen time, and an increase in sleep duration during the week. Descriptive analysis showed evidence of inequalities with changes in time use. In adjusted regression analyses, family affluence was associated with a greater increase in time spent on socialising with household members and a decrease in time spent on exercise. Free school meal eligibility and experience of food insecurity were associated with an increase in sleep duration. Discussion This study contributes to the body of evidence on the impact of the COVID-19 pandemic on young people and suggests that some of the pre-lockdown inequalities in time allocation were attenuated as a result of the lockdown. Furthermore, the results underscore the need for longer term surveillance to monitor changes in time use in adolescents to mitigate the impact on outcomes over the life course.
Custom exome panel revealed new mutations in MAPK14 and novel mutation in RUNX2 gene in patients with PCOS
Export competitiveness network of Chinese provincial agricultural products: E volution, performance, and influencing factors
The development of top-tier agricultural product bases and demonstration zones aims to propel Chinese agriculture into the global market, form international competitiveness, and advance to the high end of the global industrial and value chain. This study contributes to the existing literature by investigating the performance and factors influencing the competitiveness of Chinese agricultural product exports at the provincial level, using a complex network perspective, and offers recommendations for improvement. In this regard, the article uses agricultural product export data from 2015 to 2022 to create export competitiveness networks of Chinese provincial agricultural products. Our analysis revealed four primary observations. Firstly, significant opportunities exist to improve the competitive edge of agricultural product exports across various Chinese provinces. Secondly, with the exception of Guangdong Province, the types of competitively robust agricultural products exported by each province are inconsistent. Thirdly, international sister-city relationships can foster the development of an export competitiveness network of Chinese provincial agricultural products, while geographic distance may hinder this network. These findings are consistent. Lastly, the development of this competition-focused export network is also influenced by province-level and national characteristics, and these influences have unique differences. All provinces should strive to produce distinctive and globally competitive agricultural goods to build their competitive advantage in international trade. They should also implement strategic regional planning to support the global expansion of their agricultural products.
Remote sensing image Super-resolution reconstruction by fusing multi-scale receptive fields and hybrid transformer
Evaluating the impact of COVID-19 protection measures and staff absence on radiotherapy practice: A simulation study
Background Radiotherapy practice for cancer treatment is resource-intensive and demands optimised processes for patient throughput while guaranteeing the quality and safety of the therapy. With the COVID-19 pandemic, ad-hoc changes in the operation of radiotherapy centres became necessary to protect patients and staff. This simulation study aimed to quantify the impact of designated COVID-19 protection measures and pandemic-related staff absence on patient waiting times and throughput. The approach also enables analysis of protective measures and process adjustments for future business disruptions. Methods A discrete event simulation model of a stand-alone radiotherapy centre was developed and used to analyse changes in patient flow when implementing COVID-19 protection measures and experiencing staff absence. The simulation results support business continuity planning and decision-making in radiotherapy. In total, twenty-one scenarios in three categories were analysed. Category 1 scenarios investigated the effect of healthcare staff and equipment shortfalls. Category 2 scenarios simulated the impact of additional COVID-19 protection measures at low COVID-19 incidence rates, while category 3 scenarios evaluated the changes at high incidence rates. Results The simulation results suggested increased patient waiting times when staff is absent. Most scenarios of the three categories behave similarly despite increased patient waiting times due to COVID-19 protection measures in categories 2 and 3. The most significant increase in patient waiting times occurs when only two radiation therapists are available. The absence of a linear accelerator for cancer treatment also leads to increased waiting times. Scenarios where one administrator is absent show the longest average and maximum waiting times for low COVID-19 incidence rates. COVID-19 protection measures reduce patient throughput. In all scenarios, with reduced patient throughput, follow-up radiation appointments were affected. Conclusions The simulated scenario results suggest that appropriate staffing of the radiotherapy centre during a pandemic crisis is essential and that staff absence can lead to prolonged patient waiting times and reduced throughput with severe continuity of care consequences. The simulation model demonstrated that centre administrators are a bottleneck if they must perform COVID-19 protection measures in addition to their administrative duties. The effect could be mitigated by outsourcing COVID-19 protection tasks to external service providers or other centre staff.
Cortical changes associated with an anterior cruciate ligament injury may retrograde skilled kicking in football: preliminary EEG findings
Abstract Anterior cruciate ligament injuries (ACLi) impact football players substantially leading to performance declines and premature career endings. Emerging evidence suggests that ACLi should be viewed not merely as peripheral injuries but as complex conditions with neurophysiological aspects. The objective of the present study was to compare kicking performance and associated cortical activity between injured and healthy players. Ten reconstructed and 15 healthy players performed a kicking task. Kicking biomechanics were recorded using wearable inertial measurement unit sensors. Cortical activity was captured with a 64-electrode mobile electroencephalography. Multiscale entropy (MSE) analysis of biomechanics revealed increased variability in foot external rotation among injured players. Source-derived event-related spectral perturbations indicated significant differences in posterior alpha and frontal theta oscillations between the two groups. Furthermore, kick-related complexity of these regions as indexed by MSE was reduced in injured players at medium and coarse scales. Our findings suggest sensorimotor changes during kicking in injured players, which may necessitate compensatory strategies involving augmented attention at the cost of processing visuospatial information. This conflict may hinder the integration of task-relevant information across distributed networks. Our study provides preliminary insights into the neurophysiological implications of ACLi within football context and underscores the potential for prospective research.
Exploring the impact of Brownian motion on novel closed-form solutions of the extended Kairat-II equation
This work considers a stochastic form of an extended version of the Kairat-II equation by adding Browning motion into the deterministic equation. Two analytical approaches are utilized to derive analytical solutions of the modified equation. The first method is the modified Tanh technique linked with the Riccati equation, which is implemented to extract some closed-form solutions in the form of tangent and cotangent functions. The second technique is the Sardar sub-equation method (SSEM) which is used to attain several analytical solutions in the form of trigonometric and hyperbolic functions. Solutions selected randomly from the large families of solutions with suggested techniques are visualized in 3D and 2D scenarios. From the simulations an intriguing observation is made: the solutions generated through the modified tanh method exhibit a singular nature, with some of hybrid waves among them. On contrary to this, solutions derived through the SSEM, tend to be mostly non-singular in nature. The varying influence of the noise intensity revealed that the high amplitude and high energy regions of the waves are more vulnerable to the induced noise as compared to lower energy regions, which are relatively robust. This study introduces novel approaches by incorporating Brownian motion into the extended Kairat-II equation, providing new insights into the behavior of stochastic integrable systems that have not been previously explored.
Evaluating energy consumption patterns in novel foamed ternary alkali-activated masonry blocks
Abstract This study endeavors to tackle the energy requirements of the building sector by employing passive design strategies. However, there exists a dearth of comprehension regarding the energy efficiency performance of foamed alkali-activated materials. To bridge this research gap, the study proposes a solution in the form of a thermally proficient wall material crafted from ceramic tile dust (CTD), class C fly ash (FA), and Ground Granulated Blast-Furnace Slag (GGBS), all of which are industrial by-products. The foamed ternary alkali-activated (FTAA) blocks, developed as a result of this research, exhibited commendable performance in terms of mechanical strength of 18.6 MPa, lower density of 1200 kg/m3, porosity of 15.95%, lower specific heat capacity (SHC) of 831 J/(Kg·K), and thermal conductivity (TC) of 0.38 W/(m·K). The thermal efficiency of FTAA blocks curtails the transfer of heat from the external environment to the interior, thereby engendering a more agreeable indoor milieu for occupants. A simulation study utilizing the eQuest tool was executed to evaluate the thermal attributes of the developed blocks and their consequential impact on energy requirements. The findings revealed that in comparison to clay bricks, employing FTAA blocks could yield potential annual energy savings of approximately 4%. Furthermore, notable cost savings of about 4.94% during peak summer months and 5.51% annually were observed. The significance of utilizing these ternary blocks, derived from industrial waste, resides in their affirmative contribution to environmental preservation, augmented indoor thermal comfort, and diminished energy consumption for end users. Consequently, this research makes a meaningful stride towards diminishing operational energy in buildings, harmonizing with sustainability objectives.
Protective effects of Lactobacillus plantarum strain against protein malnutrition-induced muscle atrophy and bone loss in juvenile mice
Early-life malnutrition adversely affects nearly all organ systems, resulting in multiple physiological adaptations, including growth restriction and muscle and bone loss. Although there is growing evidence that probiotics effectively improve systemic growth under malnourished conditions in different animal models, our knowledge of the beneficial effects of probiotics on various organs is limited. Here, we show that Lactobacillus plantarum strain WJL (LpWJL) can mitigate skeletal muscle and bone loss in protein-malnourished juvenile mice. Mice on prenatal day 21 were fed a protein-malnourished (P-MAL) diet with or without LpWJL supplementation for six weeks. Compared to mice on the P-MAL diet alone, LpWJL supplementation significantly increased muscle mass and size, resulting in enhanced muscle strength and endurance capacity. Furthermore, LpWJL supplementation induced the expression of the key growth factor IGF-1 while decreasing muscle atrophy markers such as Atrogin-1 and MuRF-1, indicating potential mechanisms by which protein malnutrition-induced muscle wasting is counteracted. Additionally, LpWJL supplementation alleviated the reduction in cortical bone thickness and the deterioration of trabecular bone microstructure in the femur. Taken together, these results indicate that LpWJL can protect against skeletal muscle atrophy and compromised bone microarchitecture caused by protein malnutrition, providing novel insights into the potential therapeutic applications of probiotics for treating malnutrition-related disorders.
A systematic epidemiological trends analysis study in global burden of multiple myeloma and 29 years forecast
Assessment of antenatal care quality in Ethiopia: Facility-based study using service provision assessment data
Background Antenatal care (ANC) coverage in low- and middle-income countries has increased in the past few decades. However, merely increasing care coverage may not enhance maternal and newborn health unless the recommended service components are also provided. Our aim was to assess the quality of ANC and its associated factors in Ethiopia. Methods We used data from 2,042 pregnant women whose first ANC consultation was observed. Data were obtained from the 2021–2022 Ethiopian Service Provision Assessment survey conducted among a nationally representative sample of 1,158 healthcare facilities. Twenty-four components of ANC were assessed, and their values were summed to generate a total ANC quality score (range: 0–24). A higher score indicated a superior ANC quality. A multiple generalized Poisson regression model was fitted to identify factors influencing the quality of ANC. All statistical analyses were performed using STATA version 16. Results The mean ANC quality score was 11 (standard deviation [SD]: 3.8). Blood pressure measurement was the most commonly performed ANC component, at 79.5%, and breast examination for cancer screening was the most neglected component of ANC, at 3.3%. ANC quality was higher in the Amhara region (incidence rate ratio [IRR]: 1.088; 95% confidence interval [CI]: 1.0–1.171) and Southern Nations, Nationalities, and Peoples’ Region (IRR: 1.081; 95% CI: 1.002–1.166), and when the care was provided by a female healthcare worker (IRR: 1.054; 95% CI: 1.021–1.088). On the other hand, ANC quality decreased in rural healthcare facilities (IRR: 0.964; 95% CI: 0.932–0.998), clinics (IRR: 0.666; 95% CI: 0.581–0.764), and health posts (IRR: 0.817; 95% CI: 0.732–0.91). Similarly, ANC quality decreased when gestational age at the first antenatal visit increased (IRR: 0.994; 95% CI: 0.992–0.996) and when care was received from a non-nearby healthcare facility (IRR: 0.956; 95% CI: 0.923–0.990). Conclusion Overall, the quality of ANC in Ethiopia is suboptimal. Encouraging women to initiate ANC early and utilize nearby facilities, assisting providers in delivering standardized services through preservice training, supervision, and continuous education, and ensuring the availability and proper use of necessary resources at all facilities are important to improve ANC quality.
Regulation of reactive oxygen species and the role of mitochondrial apoptotic-related genes in rheumatoid arthritis
Empirically validating a computational model of automatic behavior shaping
Background Mobile sensing technology allows automated behavior shaping routines to be incorporated into health behavior interventions and other settings. In previous work, a computational model was built to investigate how to best arrange automatic behavior shaping procedures, but the degree to which this model reflects actual human behavior is not known. Purpose To translate a previously developed computational model of automatic behavior shaping into an experimental setting. Methods Participants (n = 54) operated a computer mouse and attempted to locate a hidden, randomly-placed target circle on a blank computer screen and clicks within some threshold distance of the target circle were reinforced by a pleasant auditory tone. As the trial progressed, the threshold distance narrowed according to a shaping function until eventually only clicks within the target circle were reinforced. Accumulated Area Under Trajectory Curves and Time Until 10 Consecutive Target Clicks were used to quantify the probability of the target behavior. Linear mixed effects models were used to assess differential outcomes for concave up, concave down, and linear shaping functions. Results In congruence with the computational model, concave-up functions most effectively shaped participants’ behavior, with linear and then concave-down shaping functions producing the next best outcomes. Conclusion Concave-up shaping routines most effectively generated target behavior, which should be confirmed in health behavior trials. The automatic shaping routines that this study helps develop can be applied in a number of domains, including exercise intensity and duration, tobacco/cannabis smoking, caloric intake, and screen time.
Comprehensive investigation of matrix metalloproteinases in skin cutaneous melanoma: diagnostic, prognostic, and therapeutic insights
Development and validation of an interpretable machine learning model for predicting left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients
Purpose Left atrial thrombus or spontaneous echo contrast (LAT/SEC) are widely recognized as significant contributors to cardiogenic embolism in non-valvular atrial fibrillation (NVAF). This study aimed to construct and validate an interpretable predictive model of LAT/SEC risk in NVAF patients using machine learning (ML) methods. Methods Electronic medical records (EMR) data of consecutive NVAF patients scheduled for catheter ablation at the First Hospital of Jilin University from October 1, 2022, to February 1, 2024, were analyzed. A retrospective study of 1,222 NVAF patients was conducted. Nine ML algorithms combined with demographic, clinical, and laboratory data were applied to develop prediction models for LAT/SEC in NVAF patients. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. Multiple ML classification models were integrated to identify the optimal model, and Shapley Additive exPlanations (SHAP) interpretation was utilized for personalized risk assessment. Diagnostic performances of the optimal model and the CHA2DS2-VASc scoring system for predicting LAT/SEC risk in NVAF were compared. Results Among 1,078 patients included, the incidence of LAT/SEC was 10.02%. Six independent predictors, including age, non-paroxysmal AF, diabetes, ischemic stroke or thromboembolism (IS/TE), hyperuricemia, and left atrial diameter (LAD), were identified as the most valuable features. The logistic classification model exhibited the best performance with an area under the receiver operating characteristic curve (AUC) of 0.850, accuracy of 0.812, sensitivity of 0.818, and specificity of 0.780 in the test set. SHAP analysis revealed the contribution of explanatory variables to the model and their relationship with LAT/SEC occurrence. The logistic regression model significantly outperformed the CHA2DS2-VASc scoring system, with AUCs of 0.831 and 0.650, respectively (Z = 7.175, P < 0.001). Conclusions ML proves to be a reliable tool for predicting LAT/SEC risk in NVAF patients. The constructed logistic regression model, along with SHAP interpretation, may serve as a clinically useful tool for identifying high-risk NVAF patients. This enables targeted diagnostic evaluations and the development of personalized treatment strategies based on the findings.
Implication of tumor morphology and MRI characteristics on the accuracy of automated versus human segmentation of GBM areas
Cosmic carnage: planetary rubble spotted at a dying star
Attributes and factors associated with long covid in patients hospitalized for acute COVID-19: A retrospective cohort study
Background It is now recognized that many patients have persistent symptoms after recovery from acute COVID-19 infection, an infection caused by the coronavirus SARS-CoV-2. This constellation of symptoms known as ‘Long COVID’ may manifest with a wide range of physical and cognitive/psychological symptoms. Few data are available on the prevalence, attributes, and factors associated with Long COVID in Africa. Method This was a retrospective review of patients’ electronic medical records from Hallelujah General Hospital (one of the first private hospitals to treat COVID-19 patients). The hospital’s database was searched for patients hospitalized for acute COVID-19 infection from March 2020 to December 2022. Two hundred and forty-seven participants who underwent follow-up beginning four weeks after symptom onset were assessed for Long COVID. Admission and follow-up data were collected using Kobo Toolbox and exported into SPSS 27 for analysis. The relationship between the independent and dependent variables was explored through binary logistic regression. Results One hundred seventy-eight (72.1%) participants had at least one persisting symptom 4 weeks post-symptom onset, at a median follow-up time of 35 (IQR 32–40) days. The most frequently reported symptoms were fatigue (41.7%), shortness of breath (31.2%), cough (27.1%), and sleep disturbances (15%). Duration of symptoms more than 7 days before admission [aOR = 1.97; CI95% = 1.04 to 3.75; P = 0.038] and length of stay more than 10 days in the hospital [aOR = 2.62; CI95% = 1.20 to 5.72; P = 0.016] were found to be significantly associated with Long COVID. Conclusion There is a high prevalence of Long COVID among patients hospitalized for acute COVID-19. Those who had a longer duration of symptoms before admission and a longer stay in the hospital appear to have a higher risk.