Changes in curricula, publication policy and information technology, notably in China have led to concentrations in the role of STEM (science, technology, engineering and mathematics) education in early childhood and applauded to proliferations of imported up-to-date reading materials and mobile apps in English. This paper proposes a longitude study of a Chinese toddler learning STEM by reading picture books and playing with tablet and suggests new horizons in parenting and in STEM education during children's early years. The present study carried out from 2016, when the participant reached one year old, eligible to learn to speak and to concentrate on the picture books read by parents who had filled a language background questionnaire with information on themselves and the participant. Tablet playing brought about for the two-year-old toddler and collections of STEM books in English was added for the second year. Data collection lasted for two years with an iLab video camera, capturing utterances and motions for five minutes per week transcribed by VoiceScript software. Tests were given quarterly at private home by tapping in mobile app "Bilingual Child Learning" which consists of 20 basic STEM themes before scores were collected. Findings indicate that (1) it is accessible for children of very early years to be engaged in English STEM resources, (2) kids' limited English dominance does not impede learning STEM, (3) and to think in English in early STEM contributes to children's English.

This critical review delves into the often-overlooked aspect of early childhood language development: the potential impact of exposure to foreign languages. While multilingualism is widely celebrated for its cognitive and cultural benefits, emerging research suggests that early exposure to foreign languages may pose challenges for young children's linguistic development. The review synthesizes findings from 17 studies to explore the complexities surrounding this issue, including linguistic confusion, language delay, reduced vocabulary growth, impaired language processing, and socio-emotional implications. Additionally, mitigating factors and future directions for research and intervention are discussed. By shedding light on this topic, the review aims to inform educators, parents, and policymakers about the nuances of bilingual language acquisition and the importance of providing tailored support to optimize early childhood language development in multilingual contexts.

Many countries have implemented free early childhood education to solve the affordability and accessibility problems without considering the sustainability of policy; thus, they have to discontinue the policy. The city of Nanjing, China, is no exception. This case study adopted a mixed-methods approach to understanding how and why the policy was formulated, implemented, and failed in the city, using the “policy cycle” framework. Altogether 232 kindergarten principals and teaching/research staff were randomly sampled and surveyed, and 5 kindergarten principals and 5 teaching/researcher staff were interviewed. The results indicated that there were many obstacles to the policy’s sustainability, including the conflict of interest, the inefficient policy implementation, the insufficient funding, and more social inequality issues. And the policymakers made mistakes in the five domains of the policy cycle: the context of influence, the context of policy text production, the context of practice, the context of outcomes, and the context of political strategy. Finally, the lessons for a more sustainable policy decision process are discussed.

This research investigates the perceptions of parents belonging to the Sidama ethnic group re-garding the significance of technology in early childhood education. The study aims to elucidate how parents perceive the role of technology, such as digital devices and educational applications, in the education and development of their young children. Through qualitative interviews con-ducted with 30 parents and thematic analysis, the study uncovers diverse perspectives, shedding light on cultural, socioeconomic, and educational factors influencing parental attitudes towards technology in early childhood education among the Sidama people. Findings indicate a spectrum of views ranging from enthusiastic embracement to cautious reservation, revealing nuanced considerations that inform parental decisions regarding technology integration in their children's learning experiences.

Background/Objectives: While studies suggest that young children can learn and think about sustainability, most research has focused on children aged three to five, leaving a significant gap in understanding how to engage toddlers (under three) in early childhood education for sustainability (ECEfS). This study aims to address this gap, a crucial and often overlooked area, by investigating early childhood teachers' perceptions of ECEfS and their pedagogical practices for nurturing sustainability in a toddler group in a Swedish preschool. Methods: The study employed a case study approach, incorporating observations, interviews, and document analysis for data collection. Qualitative techniques were used for data analysis. The research was conducted with a strong commitment to ethical considerations, including obtaining participants' consent, ensuring confidentiality and privacy, informing them of their right to withdraw, and maintaining anonymity. Results: The findings of this study bring hope. They indicate that teachers understand education for sustainability and can implement sustainability-related pedagogical practices in a toddler group. They can create suitable learning environments and establish connections between sustainability issues and daily life activities in the classroom, enhancing the children's overall learning experience. Conclusions: The study's findings underscore the pivotal role of educators in shaping the mindsets and behaviors of future generations, thereby supporting the long-term goals of sustainable development. By nurturing toddlers' innate curiosity and harnessing their brain's plasticity, educators can effectively engage toddlers in ECEfS and promote sustainable development from an early age. The study's implications highlight the need to prioritize ECEfS during toddlerhood to realize the full potential of this critical investment in the future of our planet.

Antecedents. EFs (EFs) are the basis for establishing a goal and working towards that goal by coordinating thoughts and actions. EFs are fundamental to several aspects of daily life, specifically for academic performance. Aim. To analyze and compare the development of EFs in the transition period between the first and second cycles of Early Childhood Education. Methodology. Non-experimental methodology, ex post facto design, descriptive, cross-sectional evolution study. Participants. Preschoolers of different educational levels (first and second cycle of Infant Education). In this study the participants have been evaluated by different informants: 54.42% by parents and 45.58% by teachers. In relation to gender, 52.65% were male and 47.35% were female. In relation to age, 37.54% had a range of 2-3 years and 62.46% had a range of 4-5 years. Measurement. Instrument development of EFs were evaluated using BRIEF-P by key informants. Results. Preschoolers in the first cycle show significantly higher scores than preschoolers in the second cycle in BRIEP-P. Conclusions. The development of EF is key in these first key moments, having a special impact on later development and academic performance. It is necessary to work on EFs from the first cycle of Early Childhood Education, considering the evolutionary development of EFs.

Severe early childhood caries remains the most common chronic disease affecting children. Its multifactorial etiology has established a controversy about which risk factors were more significant to its development. Therefore our study aimed through meticulous statistical analysis to arrange the “well agreed upon” common risk factors in order of significance, to aid the clinician in tailoring an adequate preventive program for this affected age group. The study reshuffled the risk factors contributing to severe early childhood caries and placed them in the order of their significance as follows: snacking of sugary food several times a day, increased number of siblings to 3 or more, night feeding, child self-employed brushing, mother caries experience, 2 siblings, on demand feeding, once/day sugary food, sharing utensils, 1 Sibling, male gender, father’s education, late first child dental visit, brushing time, mother’s education, no dental visit, decreased brushing frequency & no night brushing.

This research examines sustainable approaches in academic career development by analyzing the interactions between job satisfaction, professional commitment, and research performance among early-career researchers in Romanian institutions. Using a quantitative cross-sectional design, data were collected from 96 individuals classified as R1 and R2 by the European Commission. A detailed questionnaire and Web-Assisted Personal Interviewing (WAPI) identified key relationships. Findings show a significant positive correlation between job satisfaction and research perfor-mance, underscoring the role of professional satisfaction in fostering sustainable academic ex-cellence. Professional commitment is also a crucial predictor of research performance, aligning with existing studies and highlighting the importance of sustainable career practices. Statistical analysis via SPSS version 23.0 validated the initial hypotheses, emphasizing each dimension's significance in a sustainable academic career. Results reflect Romania's research environment, emphasizing the need for sustainable working conditions, effective research evaluation, sup-portive career frameworks, and strong professional commitment to motivate young researchers. This research proposes innovative, sustainable practices for enhancing academic performance and career management, advocating clear objectives, leadership development, continuous competency improvement, and a collaborative, inclusive work environment. Understanding these factors aids individuals and institutions in making informed decisions that support sustainable academic career trajectories and professional growth.

In Kenya, millions of children have limited access to nurturing care. With the COVID-19 pandemic, it is anticipated that vulnerable children will bear the biggest brunt of the direct and indirect impacts of the pandemic. This review aimed to deepen understanding of the effects of COVID-19 on nurturing care from conception to four years of age, a period where the care of children is often delivered through caregivers or other informal platforms. The review has drawn upon the empirical evidence from previous pandemics and epidemics, and anecdotal and emerging evidence from the ongoing COVID-19 crisis. Multifactorial impacts fall into five key domains: direct health; health and nutrition systems, economic, social and child protection, and child development and early learning. The review proposes program and policy strategies to guide the re-orientation of nurturing care, prevent the detrimental effects associated with deteriorating nurturing care environments, and support the optimal development of the youngest and most vulnerable children. These include the provision of cash transfers and essential supplies for vulnerable households, and strengthening of community-based platforms for nurturing care. Further research on COVID-19 and the ability of children’s ecology to provide nurturing care is needed, as is further testing of new ideas.

Many children have suspected delayed language development and need extensive support from parents and the health care team. This study aimed to investigate suspected delayed language development and factors associated with suspected delayed language development among early childhood in Southern Thailand. Children aged 24 to 60 months were recruited as study samples using stratified random sampling conducted in 23 districts and simple randomized seven sections (425 children). Instruments comprised demographic data of the children and families, The preschool temperament questionnaire, and the Language Development Screening questionnaire using developmental surveillance and promotion manual. I was collecting data from July 2020 to January 2021. Data analysis used descriptive statistics and logistic regression. The results showed that 40.9 percent suspected delayed development. Daily screen time exceeding 2 hours per day (A.O.R. = 17.30, 95% CI: 7.35-40.72), and regarding a child's temperament, moderate-to-difficult temperament (A.O.R. = 9.56, 95% CI: 5.12-17.85) were significantly associated with a suspected delay of language development. The study suggested two-way communication and appropriate responses will help develop children's language.

Studies have shown that nearly half of rural toddlers in China have cognitive delays due to an absence of stimulating parenting practices, such as early childhood reading, during the critical first three years of life. However, few studies have examined the reasons behind these low levels of stimulating parenting, and no studies have sought to identify the factors that limit caregivers from providing effective early childhood reading practices (EECRP). This mixed-methods study investigates the perceptions, prevalence and correlates of EECRP in rural China, as well as associations with child cognitive development. We use quantitative survey results from 1,720 caregiver-child dyads across 100 rural villages/townships in northwestern China and field observation and interview data with 60 caregivers from these same sites. The quantitative results show significantly low rates of EECRP despite positive perceptions of early reading and positive associations between EECRP and cognitive development. Qualitative results suggest that low rates of EECRP in rural China are not due to the inability to access books, financial or time constraints, or the absence of aspirations. Rather, the low rate of book ownership and absence of reading to young children is driven by the insufficient and inaccurate knowledge of EECRP among caregivers, which leads to their delayed, misinformed reading decisions with their young children, ultimately contributing to developmental delays.

Malnutrition and dental caries in early childhood remain persistent and intertwined global health challenges, particularly for indigenous and geographically-remote populations. To examine the prevalence and associations between early childhood dental caries, parent-reported mouth pain and malnutrition in the Amazonian region of Ecuador, we conducted a cross-sectional study of the oral health and nutrition status of 1,407 children from birth through age 6 in the “Alli Kiru” program (2011-2013). We used multivariate regression analysis to examine relationships between severe caries, parent-reported mouth pain measures, and nutritional status. The prevalence of dental caries was 65.4%, with 44.7% of children having deep or severe caries, and 33.8% reporting mouth pain. The number of decayed, missing and filled teeth dmft) increased dramatically with age. Malnutrition was prevalent, with 35.9% of children stunted, 1.1% wasted, 7.4% underweight, and 6.8% overweight. As mouth pain increased in frequency, odds for severe caries increased. For each unit increase in mouth pain frequency interfering with sleeping, children had increased odds for underweight (AOR: 1.27; 95% CI: 1.02 – 1.54) and decreased odds for overweight (AOR: 0.76; 95% CI: 0.58 – 0.97). This relationship was most pronounced among 3-6 year-olds. Early childhood caries, mouth pain and malnutrition were prevalent in this sample of young children. Parent-reported mouth pain was associated with severe caries, and mouth pain interfering with sleeping was predictive of poor nutritional status. We demonstrate the utility of a parsimonious parent-reported measure of mouth pain to predict young children’s risk for severe early childhood caries and malnutrition, which has implications for community health interventions.

Digital wellbeing concerns the balance and health we may experience in digital use, and the existing studies have focused on adolescents and adults. However, young children are more vulnerable to digital overuse and addiction than adults; thus, their digital wellbeing deserves empirical exploration. This scoping review synthesized and evaluated 35 collected studies on young children’s digital use and their wellbeing that were published until October of 2022 to understand the definitions, measurements, contributors, and interventions. The synthesis of evidence revealed that: (1) there was no consensus about its definition; (2) there were no effective measurements of young children’s digital wellbeing; (3) both child factors (duration and place of digital use, child demographic characteristics) and parent factors (digital use, parental perception, and mediation) contribute to young children’s wellbeing; and (4) there were some effective applications and interventions. This review contributes to the theoretical development by mapping the existing work on young children's digital wellbeing, proposing a model, and identifying the research gaps for future studies.

Purpose/Objective: Frequent consumption of fermented carbohydrates and bottle feeding contribute to the development of early childhood caries (ECC). There are no substantial findings on the effects of breastfeeding patterns on oral health conditions in children in the United States. We aimed to assess the nexus between exclusive breastfeeding during the first 6 months and oral health disorders, namely toothache, decayed teeth, or unfilled cavities in early childhood. Materials and Methods: Design: Cross-sectional epidemiologic design of nationally representative data collected via telephone surveys in the United States was utilized. Setting: National Survey of Children’s Health, 2012 Participants: Population-based random sample of parents/guardians of 24,655 children aged 6 months to 5 years. Main Outcome and Measure: Parent-reported oral health condition including toothache, decayed teeth or unfilled cavity in the past 12 months. Results: A total of 2,392 (9.7%) children aged 6 months to 5 years experienced an oral health disorder, mainly toothache, decayed teeth, or unfilled cavity in the previous 12 months. Relative to non-Hispanic White children (7.7%), a greater proportion of non-Hispanic Black (12.9%) and multi-racial children (12.6%) experienced oral health disorders (OHD). In the univariable model, relative to children who never breastfed, those who were breastfed exclusively for 6 months were 28% less likely to present with OHD, Odds Ratio (OR) = 0.72, 95% CI, 0.52-0.98. After adjustment, the protective nature of exclusive breastfeeding against OHD did not remain, adjusted OR (aOR) =1.11, 99% CI 0.79-1.57. Children of mothers with fair/poor health were almost twice as likely to have poor OHD compared with children of mothers with excellent/very good health (aOR = 1.79, 99% CI 1.08-2.69). Conclusions and Relevance: Exclusive breastfeeding for the first six months of life improved pediatric OHD and remains mutually beneficial for mothers and children. These findings suggest the importance of exclusive breastfeeding and maternal health in relation to dental hygiene in children.

Rangelands are a key resource present all over the world as it covers half of emerged lands. They are even more important in drylands, where they cover 48% of the total area. Intensification and the additional pressure added by climate change push these systems towards desertification. Over the last two decades, we have developed and applied System Dynamics (SD) models for the study of Mediterranean grasslands. In addition, we have developed procedures and analysis tools, such as global sensitivity analysis, stability analysis condition, or risk analysis, in order to detect the main drivers of these socio-ecological systems and provide indicators about their long-term sustainability. This paper reviews these works, their scientific background, and the most relevant conclusions, including purely technical and rangeland-related ones as well as our experience as systemic modelers in a world driven by field specialists.

Diabetes mellitus and dental caries (tooth decay) are not only common Non Communicable Diseases (NCDs) contributing to high burden of diseases but costly diseases to manage. Diabetes mellitus is a leading cause of mortality and reduced life expectancy across the globe. Early child hood dental caries (ECC) denotes a common chronic childhood disease and cariogenic dietary patterns dominated by refined sugar is one of the main causative factors. Thus, high burden of ECC could be a proxy indicator of excessive refined sugar consumption of a child. If such unhealthy dietary patterns are continued through to adolescent to adulthood, there is a high probability of an individual becoming a diabetic. Therefore, it is rational to argue high ECC burden in a country could be an indicator of future burden of diabetes. Moreover, ECC provides a critical period and a window of opportunity across life-course perspective, to intervene with cariogenic dietary patterns underpinned by common risk factor approach. This could be achieved by tailored dietary counseling for parental care givers of children with ECC. A healthy dietary pattern fostered in the childhood, most probably would continue to adulthood which may become beneficial in reducing the incidence of diabetes. Against this backdrop, we provide a perspective from Sri Lanka: a lower-middle-income country (LMIC) which records the highest prevalence of diabetes and pre-diabetes in south Asia. Our perspective will provide novel insights and innovative ideas into prevention and control of diabetes burden in LMICs, harnessing the potential of preventive dentistry.

Education and heritage are fundamental to achieving sustainable development goals. Integrating heritage into education is crucial for cultivating children's connection to heritage and promoting sustainable development. However, the lack of a scientific framework to guide educational goals across age groups results in unclear integration. This study aims to develop a framework for cultural identity enlightenment within heritage education by conducting literature research and validating it through field observations in kindergartens. It identifies cognitive, emotional and behavioral dimensions, outlining the developmental trajectory of these goals. This framework illustrates how children's understanding progresses from direct experiences to deeper appreciation and creative involvement. It provides teachers with a tool to set goals that empower children as agents, fostering the emergence of cultural awareness and identity. This approach not only enhances cultural identity but also supports sustainable development by advancing the transmission and innovation of cultural heritage.

Physical literacy (PL) is increasingly recognised as essential to fostering lifelong physical activity (PA) engagement, particularly when nurtured in early childhood. However, there remains limited understanding of how key stakeholders in early years (EY) education perceive, value, and implement a PL informed approach. This exploratory study aimed to investigate a variety of EY stakeholders' knowledge and beliefs regarding PL and PA in relation to 3-5-year-olds. A concurrent mixed-methods approach was used, incorporating semi-structured expert interviews (n=11), focus groups (n=22), and a survey (n=210) to gather both qualitative and quantitative data. Thematic analysis was applied to identify key themes, and survey data was analysed to complement and triangulate qualitative findings. Findings revealed variation in stakeholders' awareness of PA recommendations, confusion over terminology, and the influence of environmental and policy constraints on practice. Stakeholders acknowledged the importance of PL but expressed uncertainty about the connection between academic theory and practical application. Resource limitations, conflicting priorities, and lack of training and policy support emerged as key barriers. Feedback on an educational PL-EY model was generally positive, emphasising its potential educational value while underscoring the need for clearer guidance and support. Given the pivotal role of EY education in shaping children’s behaviours, health, and well-being, this study highlights the necessity of a holistic approach to interventions, strong stakeholder involvement, and evidence-based practices to foster PL in EY children and raises critical questions about what effective interventions to develop PL in this age group should consider and look like.

It is essential to consider the factors that affect early childhood development because doing so can help identify potential risks and window of opportunity for intervention to improve outcomes for children. However, identifying risk and protective factors in early childhood requires careful consideration of several challenges and an integrated approach that recognises the complex and dynamic nature of development. The purpose of this study was to identify and describe the prevalent psychosocial risk and protective factors in the early childhood development phase, using an ecological perspective. The study employed a quantitative cross-sectional study using a random sampling technique. The final sample consisted of 505 caregivers of children aged 5 years old and younger. This study revealed that the most prevalent protective factors include child self-regulation, parent-child warmth, family management and collective efficacy but more importantly social support. While risk factors may exist this is mitigated by social support as it moderates and buffers against the effects of risk factors, as indicated by the various research studies cited.

Keywords: early childhood; education; quality; measurement; monitoring; majority world; Item Response Theory; psychometrics

This study examined the status of Education for Sustainable Development (ESD) practices and the understanding of Sustainable Development (SD) among Saudi kindergarten teachers in a specific governorate. Two hundred twenty-seven kindergarten teachers participated, and data was collected through a questionnaire. The results indicated that most kindergarten teachers (89.9%) were unaware of SD. The overall status of ESD practices among the participating teachers was weak, with an average score of 2.60 out of 4. Among the different dimensions, values (2.74), competencies (2.69), and practice (2.65) obtained relatively higher scores, while the content dimension (2.49) received the lowest score. Significant differences were found in the mean scores of ESD practices based on teachers’ qualifications and the type of school. However, no differences were observed based on experience. The lack of awareness regarding SD emerged as the primary barrier to implementing ESD in kindergarten institutions. Expanding teacher training was identified as the most crucial step in promoting ESD in kindergartens. The findings highlight the importance of raising awareness among Saudi kindergarten teachers about SD, providing professional development opportunities to enhance ESD implementation in classrooms, and creating teaching materials aligned with ESD principles.

Early childhood may be a stressful period for families with a significant impact on parents’ mental health and the child’s healthy development. The goal of the SKKIPPI cohort study was to assess the occurrence and determinants of psychosocial stress and mental health disorders in parents as well as in their offspring in early childhood in three German regions. Based on random samples from three residents' registration offices, parents with infants up to 12 months of age at the time of sampling, were invited to participate in the study. A screening online questionnaire was newly developed, available in four languages, to assess common psy-chosocial stressors and mental health problems of parents with small children. The study enrolled 4,984 mothers and 962 fathers. The most common potential psychosocial stressors at baseline were professional problems (mothers 22%, fathers 33%), lack of social sup-port (20%, 14%), and severe, negative experiences in childhood (22%, 16%). Obses-sive-compulsive thoughts (21%, 16%), depressive (9%, 9%) and anxiety symptoms (11%, 7%) were the most frequently reported mental health problems by both parents. Regulatory prob-lems of the child were reported by between 1.5% and 5.1% of parents. The SKKIPPI study showed that a substantial proportion of parents are burdened by psychoso-cial problems and suffer from mental health problems in the first years after birth. Early pre-ventive and low-threshold support measures should be available in the health and social care system. The newly developed questionnaire can be used to screen in the relevant populations in order to avoid disturbances in the mother-child attachment.

Abstract: NFinFET transistors with fin channel length 90nm and a planar MOSFET transistor with channel length 180nm and 90nm are presented with characteristic curves at various gate biases. A finalized algorithm with kink effects is effectively responsible for addressing the field effect transistors. The algorithm includes the modified conventional current-voltage formula and a nonlinear heat-associated kink solution which is simplified as a Gaussian form. Three parameters in modified model includes kN (related with channel width, channel length, and gate oxide capacitor, and proportional to the mobility of carriers)Vth(Threshold Voltage), and (the inverse of Early Voltage). Those parameters are determined to minimize the discrepancies between the measured data and the fitting values, but leave kinks located at around (VGS－Vth), which are deliberately eliminated by the Gaussian form because of the agitation of thermal kink effects. The whole fitting is made to be as close as the as-measured IDS-VDS. In the mean time, those determined parameters are physically meaningful after the analysis has been done.

The AUC-ROC is a widespread measure to assess the performance of a binary classification model across various discrimination thresholds. Yet, it is not apt for unbalanced class problems and is misleading for early retrieval. For instance, link prediction in complex networks is an unbalanced early retrieval problem, whose goal is to offer a ranking of the nonobserved network links, prioritizing a small cohort of positive links (for which we are sure the labels are reliable) on top of a list largely populated by unlabeled links (for which the labels are uncertain). Differently from binary classification, here the evaluation focuses on how the predictor prioritizes the positive class, because the negative class does not exist and is replaced by an unlabeled class. For decades, scholars have been investigating the necessity to correct and to generalize the AUC-ROC to work for both unbalanced classification and early retrieval evaluation, this is requested in many applied domains of computational science. Here we propose the area under the magnified ROC (AUC-mROC), a new measure that adjusts the standard AUC-ROC to work for unbalanced early retrieval problems such as link prediction. Finally, we introduce the area under the generalized ROC (AUC-gROC), which unifies both AUC-mROC and AUC-ROC to provide a universal and reliable evaluation measure that can work for both classification and early retrieval problems, regardless of class proportion.This discovery represents a critical achievement, culminating in success after decades of contentious research. Its solution promises to significantly impact various domains within applied computational science.

The impact of early maternal age on several outcomes (e.g. mental health issues, delinquency, aggression, impulsivity, victimization and interpersonal difficulties) has been studied since the late 1980s. Research has demonstrated links between exposure to adverse childhood experiences (ACEs) and trauma related outcomes such as substance abuse, interpersonal and self-directed violence, and sexual risk-taking, to name a few. The current study analyzed the incidence of ACE exposure and mental health outcomes (e.g. suicidal behaviors or self-harm, psychiatric hospitalizations, and substance use) as related to early maternal age in youth known to have experienced trafficking or sexual abuse. General demographics and incidence of various experiences and clinical presentations (e.g. ACE exposure, age of mother at birth of youth and age at first birth), and history of self-harm, substance use and psychiatric hospitalization were examined in a sample of 225 youth referred for services subsequent to experiences of sex trafficking or exploitation. Relationships between ACE exposure and maternal age related to mental health outcomes was also examined. Trafficked and exploited youth reported rates of ACE exposure and poor mental health outcomes at far greater rates than the general population. Significant findings were related to early maternal age and engaging in self-harm or suicidal behaviors. Previously anticipated mediational analyses were not conducted due to the sample size and lack of correlations. Findings highlight the significant ACE exposure and high needs of exploited, trafficked and abused youth and related mental health outcomes, emphasizing the need for early and comprehensive preventive and therapeutic interventions.

Pancreatic cancer is the most lethal cancer, it has lowest 5-year survival rate among other types of cancers. More than half of pancreatic cancer are diagnosed at distant stage due to its insidious and non-specific symptoms. Surgery is the most effective treatment to date, but only 10-20% are resectable upon diagnosis. Currently, the only biomarker approved by the United States Food and Drug Administration (US-FDA) for pancreatic cancer is carbohydrate antigen 19-9 (CA19-9); however, it has limited use for early diagnosis. An increasing number of studies have a combination of biomarkers. Recently, the application for liquid biopsy has drawn a lot of attention, such as the use of microRNA (miRNA), circulating tumor DNA (ctDNA), and circulating tumor cells (CTC). Screening for pancreatic cancer is indicated for high-risk patients; studies of new diagnostic models combined with biomarkers for early detection also showed promising results to aid clinicians in deciding on whether to start screening. This review aims to summarize the progress on current biomarkers and new potential strategies for early detection of pancreatic cancer.

Pancreatic cancer (PC) is the most lethal type of cancer, it has the lowest 5-year survival rate among all other types of cancers. More than half of PC cases are diagnosed at an advanced stage due to PC’s insidious and non-specific symptoms. Surgery remains the most efficacious treatment option currently available, but only 10-20% of PC cases are resectable upon diagnosis. As of now, the sole biomarker approved by the United States Food and Drug Administration (US-FDA) for PC is carbohydrate antigen 19-9 (CA19-9); however, its use is limited use for early diagnosis. An in-creasing number of studies have investigated a combination of biomarkers. Lately, there has been considerable interest in the application of a liquid biopsy, including the utilization of microRNAs (miRNAs), circulating tumor DNA (ctDNA), and circulating tumor cells (CTCs). Screening for PC is indicated for high-risk patients; studies on new diagnostic models combined with biomarkers for early detection have also shown promising results for the ability of these models and biomarkers to aid clinicians in deciding on whether to start screening. This review seeks to provide a concise overview of the advancements in existing biomarkers and explore novel strategies for the early detection of PC.

Volunteering has many social, emotional and health benefits and could be an option for people with younger/early onset dementia to engage in stage and age-appropriate, personally meaningful activities within their local communities. This study explored how people with young onset dementia volunteer in the UK, the benefits and barriers, and how we can improve access to volunteering opportunities. Audio data of people with young onset dementia discussing their experiences of volunteering were taken from the Dementia Diaries audio and video diary project (https://dementiadiaries.org/). The data were co-analysed by a co-production team, (X), made up of six researchers living with young onset dementia and two facilitators. The findings suggest that stigma is the overarching concept (or net) which influences people’s experiences of volunteering with dementia. Within the stigma net, three themes were developed that employed a lifespan approach to challenging said stigma: 1) Valuing the past, 2) Valuing the present and 3) Valuing the future, each with additional subthemes. This research contributes to the limited pool of literature that highlights the clear benefits of volunteering for people with young onset dementia, while also considering how dementia stigma can create practical and institutional barriers to accessing volunteering. Guidance is provided for how to deliver meaningful and accessible volunteering opportunities.

Adverse childhood experiences are known to program children for disrupted biological cycles, premature aging, microbiome dysbiosis, immune-inflammatory misregulation, and chronic disease multimorbidity. To date, the microbiome has not been a major focus of deprogramming efforts despite its emerging role in every aspect of ACE-related dysbiosis and dysfunction. This article examines: 1) the utility of incorporating microorganism-based, anti-aging approaches to combat ACE-programmed chronic diseases (also known as noncommunicable diseases and conditions, NCDs) and 2) microbiome regulation of core systems biology cycles that affect NCD comorbid risk. In this review microbiota influence over three key cyclic rhythms (circadian cycles, the sleep cycle, and the lifespan/longevity cycle) as well as tissue inflammation and oxidative stress are discussed as an opportunity to deprogram ACE-driven chronic disorders. Microbiota, particularly those in the gut, have been shown to affect host-microbe interactions regulating the circadian clock, sleep quality, as well as immune function/senescence and regulation of tissue inflammation. The microimmunosome is one of several systems biology targets of gut microbiota regulation. Furthermore, correcting misregulated inflammation and increased oxidative stress is key to protecting telomere length and lifespan/longevity and extending what has become known as the healthspan. This review article concludes that to reverse the tragedy of ACE-programmed NCDs and premature aging, managing the human holobiont microbiome should become a routine part of healthcare and preventative medicine across the life course.

Children’s health, development and education cannot be handled separated; they form one process and are profoundly interrelated. This article considers how to ensure children’s physical and mental fitness for school and maintain it once they are there. Rwanda Is a case study of health and development issues which render children unreceptive to education. This is not news to Rwanda’s government, but until recently the donor community was not interested in supporting implementation. The story of Rwanda illustrates the need to think about changes of policy and practice in their context of structures and culture – how they interact and how they are facilitated or constrained by structures and by cultural understandings. To grasp what is going on and for successful implementation of policy, it is necessary to look at situations as a whole and consider human and governmental agency as real influences rather than just consequences of causal mechanisms.

Agriculture is an industry that heavily relies on the environment. The increasing frequency of ex-treme disasters attributable to climate change has adversely affected agricultural land and dis-rupted the stability of the supply of agricultural products. Therefore, we implemented a research program focused on current strategies for adapting to agricultural meteorological disasters. The primary goal was to actively promote disaster prevention information and techniques through information platforms and applications and to provide refined forecasting and an early warning system to enhance preparedness for and recovery from agricultural disasters. This initiative can transform passive mitigation into dynamic action by disseminating crucial information to farmers. We integrated meteorological data and crop characteristics to develop disaster prevention strate-gies for the predisaster, during-disaster, and postdisaster stages to empower farmers to implement autonomous disaster prevention, ensuring their profitability and minimizing the impact of disas-ters. This paper presents an agricultural disaster prevention system involving cross-disciplinary collaboration to establish an early warning system for crop disasters. However, the effectiveness of the early warning system relies on the availability of complete meteorological and crop infor-mation, necessitating high-density agricultural meteorological stations, refined weather forecast services, historical crop damage data, and ongoing research and development on disaster preven-tion technology. In the system, a diversified social media interface is used to provide local farmers with weather forecast information. When impending disasters are identified, the platform acti-vates disaster prevention measures to reduce agricultural losses. This article paper introduces Taiwan’s agricultural disaster prevention system as a complete disaster prevention strategy.

Based on the detailed exploration of AI techniques for the early identification of learning difficulties in education, this study underscores the pivotal role of educational data analysis in enhancing student outcomes. Educators can proactively identify and address learning challenges through systematic data collection and analysis, thereby minimizing long-term academic obstacles and emotional stress. The integration of AI, particularly through natural language processing and computer vision technologies, facilitates personalized learning paths and real-time interventions, offering tailored support that maximizes each student's learning potential. These advancements optimize educational resource allocation and foster a more inclusive and effective learning environment, paving the way for future advancements in personalized education and intelligent teaching practices.

Approximately 20% of patients with colorectal cancer (CRC) are diagnosed with a mucinous subtype of this tumor, have a worse prognosis, and often show resistance to available therapies. Molecules from the mucin family are involved in the regulation of epithelial-mesenchymal transition (EMT), which significantly determines the cancer aggressiveness. This study aimed to examine the diagnostic and prognostic significance of mucinous histology and EMT markers in patients with early-onset CRC and their association with disease severity and tumor characteristics. The study included tumor tissue samples from 106 patients diagnosed with CRC before the age of 45, 53 with mucinous and 53 with non-mucinous tumors. The EMT status was determined by immunohistochemical analysis of E-cadherin and Vimentin in tissue sections. Mucinous tumors had a significantly higher cytoplasmic E-cadherin score (P=0.043), they were significantly less differentiated (P=0.007), more advanced (P=0.005), and predominately affected right colon (P=0.030) in comparison to non-mucinous tumors. Epithelial tumors were significantly better differentiated (P=0.034) and with less prominent tumor budding (P < 0.001) than mesenchymal tumors. The process of EMT appears to be more prominent in tumors of younger patients regardless of mucinous histology. EMT status may represent a useful prognostic tool in early-onset CRC.

Early and accurate mapping of winter canola planting areas provides critical support for sustainable cropland management. Although some methods have been proposed to map the winter canola at the flowering or later stage, mapping winter canola planting areas at the early stage is still challenging, due to the insufficient understanding of the multi-source remote sensing features sensitive for winter canola mapping. This study proposed an early-stage winter canola area mapping method by using the combination of optical and synthetic aperture radar (SAR) data. We analyzed the spectral features, backscatter coefficients, and textural features of winter canola based on Sentinel-2 and Sentinel-1 images. Random forest (RF) and Support Vector Machine (SVM) classification models were built to map winter canola based on early-stage images and field samples in 2017 and then apply the best model to corresponding satellite data in 2018-2022. Results showed that: (1) The red edge and near-infrared-related spectral features were most important for the mapping of early-stage winter canola, followed by VV, DVI and GOSAVI, which also showed greater differences than the other features; (2) Based on Sentinel-1 and Sentinel-2 data, winter canola could be earliest mapped around 130 days prior to ripening (i.e., early overwinter stage) with the F-score over 0.85 and the OA over 81%; (3) Adding Sentinel-1 could improve the OA by about 2%-4% and the F-score by about 1% -2% in winter canola mapping. (4) The F-score of winter canola mapping based on the classifier transfer approach in 2018-2022 varied between 0.75 and 0.97, and the OA ranged from 79% to 86%. This study demonstrates the potential of early-stage winter canola mapping using the combination of Sentinel-2 and Sentinel-1 images, which could provide valuable and timely information for stakeholders and decision makers.

Lung cancer is one of the leading causes of cancer-related mortality globally. Pulmonary nodules are one of the risk factors and their discovery rate has been increasing. Based on the nodule size and growth rate, their malignancy propensity is determined; however, it is very challenging to distinguish between benign and cancerous nodules. Many tumour-associated antigens (TAA) have been studied as blood biomarkers for lung cancer, most commonly the Cytokeratin 19 fragment (CYFRA 21-1), squamous cell carcinoma antigen (SCC Ag), carbohydrate antigen (CA19-9) and carcinoembryonic antigen (CEA). Due to their low sensitivity, TAAs are not recommended as tools for the early detection of lung cancer. However, cancer testis antigens (CTAs) are highly specific for carcinomas but their expression is more commonly associated with advanced stages of cancer and poor prognosis. Despite the fact that TAAs may provide useful insights for the diagnosis and prognosis of early lung cancer, their potential to do so has yet to be demonstrated.

This study examines the historiography of early Islam by assessing the reliability of Qurʾānic exegeses as sources documenting the early history of Islam and the biography of the Prophet Muḥammad in Mecca. Focusing on Qurʾānic exegetical practices from late antiquity to the medieval period, this article argues that there is a significant discontinuity in how Qurʾānic exegeses align with the historical context of the Qur'an, especially in relation to Meccan sūras such as Q 107. Significantly, this challenges the continuity of tradition, the fundamental concept upon which the “Islamic sciences” are based. This discontinuity is herein revealed through a historical-critical analysis of the exegesis of Q 107:4 that demonstrates how Qurʾānic exegetical practices have reinterpreted and reshaped early Islamic history in response to the pressures of new identity formation and made Qurʾānic exegeses more reflective of the social and political contexts of the exegetes than of the historical milieu of the Qurʾān itself. This analysis contributes to the ongoing discussion of the role exegesis played in reshaping the history of Islam. Indeed, it emphasises the importance of critically evaluating these sources in order to uncover a more nuanced historical narrative of early Islam.

Existing studies provide evidence that buildings and the construction sector are the largest consumers of natural resources and carry the greatest responsibility for greenhouse gas emissions. In order to reverse this situation, future challenges involve utilising the least resources possible. To this end, building refurbishment becomes a crucial strategy given its potential to improve operational energy efficiency and to extend the life span of existing building stock, thereby reducing the environmental impact while also providing social and economic benefits to our cities. Life Cycle Sustainability Assessment (LCSA) has become one of the scientific community’s most widely recognised methodologies for the evaluation of the social, economic, and environmental dimensions (Triple Bottom Line), since it assesses sustainability using quantitative metrics. However, the implementation of this methodology to support the refurbishment process at the project stage in building design tools, such as BIM, remains scarce. One of the main obstacles lies in the difficulties of accessing the building information, given that the system boundaries only cover new materials and products. Hence, this study proposes a BIM plug-in development to support the multi-dimensional building material selection in the early design steps based on the LCSA of a building during the refurbishment stage and validates its application in a case study. The results show the viability of using this tool during the early design stages and demonstrate the consistency of the results to evaluate various material and product alternatives for the refurbishment of the envelope system of a multi-family residential building. This study contributes towards the integration of decision-making by providing real-time assessment of the building envelope.

Early weaning management followed by energy supplementation can lead to metabolic alterations in the calf that exert long-term effects on the animal’s health and performance. It is believed that the main molecular basis underlying these metabolic adaptations are epigenetic mechanisms that regulate, activate, or silence genes at different stages of development and/or in response to different environmental stimuli. However, little is known about postnatal metabolic programming in Bos indicus. Therefore, this study aimed to compare the DNA methylation profile of Nellore animals submitted to conventional and early weaning and to correlate the findings with genes differentially expressed in Longissimus thoracis skeletal muscle of Bos indicus cattle. A total of 481 differentially methylated regions were identified, with 52% (250) being hypermethylated and 48% (231) hypomethylated. Functional enrichment analysis of 53 differentially methylated and differentially expressed genes was performed. The main enriched terms and pathways were associated with 3’-5’-cyclic adenosine monophosphate (cAMP) signaling which present the upregulated adenylate cyclase 3 (ADCY3) gene and significatively hypomethylated in promoter region. Alterations in cAMP signaling are involved in numerous processes, many of them related to lipid metabolism. The relative differential expression of key genes of this pathway demonstrates the relationship between cAMP signaling and de novo lipogenesis. These findings suggest an important role of postnatal metabolic programming through DNA methylation mechanisms in determining fat deposition in beef.

The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring SARS-CoV-2 prevalence in a city in Northern Italy from October 2021 to May 2023. Starting from a widely applied deterministic model, this study proposed a variation to take into account population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated with healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred in the considered period, demonstrating the model’s capacity to predict relevant fluctuations in the number of cases. Population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied for comparing virus load values across cities with varying population demographics and sewer network structures, enhancing the comparability of WBE data for effective surveillance and intervention strategies.

Systemic AL amyloidosis is a challenging disease for which many patients are considered frail in daily clinical practice. However, no study has so far addressed frailty and its impact on the outcome of these patients. We built a simple score to predict mortality based on three frailty-associated variables: age, ECOG performance status (&lt;2 vs. 2) and NT-proBNP (&lt;8500 vs. 8500 ng/L). Four-hundred and sixteen consecutive newly diagnosed patients diagnosed at ten sites from the Spanish Myeloma Group were eligible for the study. The score was developed in a derivation cohort from a referral center, and it was externally validated in a multicenter cohort. On multivariate analysis the three variables were independent predictors of survival. The score was able to discriminate four groups of patients in terms of overall survival and early mortality in both cohorts. Comorbidity was also analyzed with the Charlson comorbidity index, but it did not reach statistical significance in the model. A nomogram was created to easily estimate the mortality risk of each patient at each time point. This score is a simple, robust, and efficient approach to dynamically assess frailty-dependent mortality both at diagnosis and throughout the follow-up. The optimal treatment for frail AL amyloidosis patients remains to be determined but we suggest that the estimation of frailty-associated risk could complement current staging systems, adding value in clinical decision-making in this complex scenario.

Traditional applications of Interferometric Synthetic Aperture Radar (InSAR) data involved inverting an interferogram stack to determine the average displacement velocity. While this approach has useful applications in continuously deforming regions, much information is lost by simply fitting a line through the time series. Thanks to regular acquisitions across most of the the world by the ESA Sentinel-1 satellite constellation, we are now in a position to explore opportunities for near-real time deformation monitoring. In this paper we present a simple statistical approach for detecting offsets and gradient changes in InSAR time series. Our key assumption is that 5 years of Sentinel-1 data is sufficient to calculate the population standard deviation of the detection variables. Our offset detector identifies statistically significant peaks in the first, second and third difference series. The gradient change detector identifies statistically significant movements in the second derivative series. We exploit the high spatial resolution of Sentinel-1 data and the spatial continuity of geophysical deformation signals to filter out false positive detections that arise due to signal noise. When combined with near-real time processing of InSAR data these detectors, particularly the gradient change, could be used to detect incipient ground deformation associated with geophysical phenomena, for example from landslides or volcanic eruptions.

Breast cancer remains a major public health concern, and early detection can result in more treatment options, which are crucial for improving survival rates. Metabolomics offers the potential to develop blood-based screening and diagnostics tools that are less invasive and more cost-effective. However, the inherent complexity of metabolomic datasets makes identifying the most diagnostically relevant biomarkers a difficult task, with multiple studies demonstrating lim-ited agreement on the specific metabolites and pathways involved. This study aims to identify a set of biomarkers for early diagnosis of breast cancer using metabolomics data. Plasma samples from 185 breast cancer patients and 53 controls (CHTN) were analyzed. We utilized univariate Naïve Bayes, L2-regularized Support Vector Machines, and Principal Component Analysis (PCA), along with feature engineering techniques, to select the most informative features. Multiple ma-chine learning models, including Support Vector Machines, Multidimensional Scaling, Logistic Regression, and Ensemble Learning were utilized for classification. The best-performing feature set comprised 4 biomarkers and 2 demographic variables, achieving an accuracy of 98%, demon-strating the potential for a robust, cost-effective, non-invasive breast cancer screening and diagnostic tool.

Early detection improves prognosis in pancreatic ductal adenocarcinoma (PDAC) but is challenging as lesions are often small and poorly defined on contrast-enhanced computed tomography scans (CE-CT). Deep learning can facilitate PDAC diagnosis, however current models still fail to identify small (&lt;2cm) lesions. In this study, state-of-the-art deep learning models were used to develop an automatic framework for PDAC detection, focusing on small lesions. Additionally, the impact of integrating surrounding anatomy was investigated. CE-CT scans from a cohort of 119 pathology-proven PDAC patients and a cohort of 123 patients without PDAC were used to train a nnUnet for automatic lesion detection and segmentation (nnUnet_T). Two additional nnUnets were trained to investigate the impact of anatomy integration: (1) segmenting the pancreas and tumor (nnUnet_TP), (2) segmenting the pancreas, tumor, and multiple surrounding anatomical structures (nnUnet_MS). An external, publicly available test set was used to compare the performance of the three networks. The nnUnet_MS achieved the best performance, with an area under the receiver operating characteristic curve of 0.91 for the whole test set and 0.88 for tumors &lt;2cm, showing that state-of-the-art deep learning can detect small PDAC and benefits from anatomy information.

Phytophthora cinnamomi is a devastating soil-borne plant pathogen. The primary source of P. cinnamomi infection is the soil, where the pathogen can persist for long periods. Effective prevention and management of this pathogen in tree crops require an early and reliable detection method. In this study, we develop a simple, fast, reliable, and sensitive method based on real-time quantitative PCR (qPCR) for P. cinnamomi detection and quantification directly in plant or soil samples. Primers were developed targeting the nuclear single-copy ras-related protein gene Ypt1, suitable for Phytophthora-specific PCR. The specificity of the assay was confirmed by testing it against genomic DNA from 50 isolates across 8 different Phytophthora clades, including very similar P. parvispora. The efficiency and reliability of the qPCR protocol were evaluated on challenging environmental samples, such as plant tissue of different host trees (walnut, chestnut, oak) and naturally infected soils in walnut orchards. The main outcome was the development of a qPCR method for the specific identification and quantification of P. cinnamomi in natural soil samples. Additionally, this study established a systematic and repeatable soil sampling method and developed an efficient soil DNA extraction technique to apply the developed qPCR in naturally infested soils of walnut orchards.

Although the presence of dark energy is well established from various observations, its true nature is still not well understood. The cosmological constant term seems to be the preferred candidate. In earlier work we had a constant cosmological constant term to limit the sizes of large-scale structures at lower redshifts. In this work, we extend this to large scale structures at higher redshifts. Here we invoke a time varying cosmological constant to set constraints on sizes of galaxies at high redshifts and see that they are consistent with their observed sizes. The time-varying cosmological constant also provides a possible solution to the puzzle of structure formation of large disk galaxies (like the Wolfe disk) observed at very early stages of the Universe. Future observations of galaxies at even higher redshifts could support our approach.

Adenomyosis, a benign gynecological condition characterized by the infiltration of endometrial tissue into the myometrium, poses significant challenges to women's reproductive health. Recently, the landscape of adenomyosis diagnosis transformed significantly, thanks to advancements in imaging technologies such as transvaginal ultrasound and magnetic resonance imaging. This lead to a noticeable shift in the demographic profile of patients diagnosed with adenomyosis, including younger women of reproductive age who frequently present with a diverse array of symptoms. Approximately 20% of women are affected by adenomyosis. Adenomyosis manifests with various subtypes, distinct epidemiological profiles, symptomatology, and treatment responses, necessitating tailored approaches for optimal management. Despite its clinical significance, adenomyosis remains understudied, resulting in a significant disparity in research and literature compared to other gynecological conditions. The severity of adenomyosis is compounded when coexisting with endometriosis, particularly deep infiltrating endometriosis (DIE), leading to exacerbated fertility issues and severe symptomatology. The wide range of symptoms, including adverse pregnancy outcomes such as pre-eclampsia, highlights its wider impact and emphasizes the need for increased awareness of the condition. Furthermore, Adenomyosis is frequently associated with treatment failure in endometriosis, contributing to dienogest resistance, elevated discontinuation rates, and persistent pain post endometriosis surgery. Additionally, the lack of specific treatments tailored to adenomyosis poses a considerable challenge in clinical management.

Osteosarcoma is the most common subtype of primary bone cancers, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its molecular etiology has still not been determined with precision. Therefore, we applied a consensus strategy with the use of several bioinformatics tools to prioritize genes involved in its pathogenesis. Subsequently, we assessed the physical interactions of the previously selected genes and applied a communality analysis to this protein-protein interaction network. The consensus strategy prioritized a total list of 553 genes. Our enrichment analysis validates several studies that describe the signaling pathways PI3K/AKT and MAPK/ERK as pathogenic. The gene ontology described TP53 as a principal signal transducer that chiefly mediates processes associated with cell cycle and DNA damage response It is interesting to note that the communality analysis clusters several members involved in metastasis events such as MMP2 and MMP9 and genes associated with DNA repair complexes, like ATM, ATR, CHEK1, and RAD51. In this study, we could identify well-known pathogenic genes for osteosarcoma and prioritized genes that need to be further explored.

The endometrium, the inner mucosal lining of the uterus, undergoes complex molecular and cellular changes across the menstrual cycle in preparation for embryo implantation. Transcrip-tome-wide analyses have mainly been utilized to study the endometrial receptivity, the prerequisite for successful implantation, with most of the studies, so far, comparing the endometrial transcriptomes between (i) secretory versus proliferative endometrium or (ii) mid-secretory versus early-secretory endometrium. In the current study, we provide the complete transcriptome description of the endometrium across the entire menstrual cycle and, for the first time, comprehensively characterize the proliferative phase of the endometrium. Our temporal transcriptome analysis includes five time points: mid-proliferative, late-proliferative (peri-ovulatory phase), early-secretory, mid-secretory, and late-secretory phases. Thus, we exhaustively unveil the transitions between the consecutive proliferative and secretory phases, highlighting their unique gene expression profiles and possible distinct biological functions. Transcriptome analysis reveals many differentially expressed genes (DEGs) across the menstrual cycle, most of which are phase-specific. As an example of the coordinated gene activity, the expression profile of his-tone-encoding genes within the HIST cluster on chromosome 6 showed an increase in cluster activity during the late-proliferative and a decline during the mid-secretory phase. Moreover, numerous DEGs are shared among all phases. In conclusion, in the current study, we delineate the endometrial proliferative phase-centered view of transcriptome dynamics across the menstrual cycle. Data analysis highlights significant transcriptomic and functional changes occurring during the late-proliferative phase – an essential transition point from the proliferative to the secretory phase. Future studies should explore how the biology of the late-proliferative phase endometrium impacts the achievement of mid-secretory endometrial receptivity or contributes to molecular aberrations leading to embryo implantation failure.

Different severe energy crises episodes occurred in the world in the last five decades. Energy crises lead to deterioration of international relations, economic crises, changes in monetary systems and social problems in countries. This paper aims to show the essential determinants of energy crises by developing a binary logit model which estimates the predictive ability of thirteen indicators in a sample that covers the period from January 1973 to December 2022. The empirical results show that the energy crises are mainly due to energy supply-demand imbalances (petroleum stocks, fossil energy production-consumption imbalance and changes in energy imports by country groups), energy investments (oil and natural gas drilling activities), economic and financial disruptions (inflation, dollar index, index of global real economic activity) and geopolitical risks. Additionally, the model is capable of accurately predicting the world energy crisis event months with 99% probability.

The incidence and prevalence of food allergy (FA) are increasing. While several studies have established the safety and efficacy of early introduction of single allergens in infants for the prevention of FA, the exact dose, frequency, and number of allergens that can be safely introduced to infants particularly in those at high or low risk of atopy are still unclear. This 1-year study evaluated the safety of early introduction of single foods (milk, egg, or peanut), vs. two foods (milk/egg, egg/peanut, milk/peanut), vs. multiple foods (milk/egg/peanut/cashew/almond/shrimp/walnut/wheat/fish/soy at low, medium, or high doses) vs no early introduction in infants between 4-6 months of age. At the end of the study, they were evaluated for plasma biomarkers associated with food reactivity with standardized blood tests. Two to four years after the start of the study, participants were evaluated by standardized food challenges. The serving sizes for the single, double, and low dose mixtures were 300 mg total protein per day. The serving sizes for the medium and high dose mixture was 900 mg and 3000 mg total protein, respectively. Equal parts of each protein were used for double or mixture foods. All infants were breastfed until at least 6 months of age. Results demonstrate that infants at either high or low risk for atopy were able to tolerate early introduction of multiple allergenic foods with no increases in any safety issues, including eczema, FA, or food protein induced enterocolitis. The mixtures of foods at either low, medium, or high doses demonstrated trends for improvement in food challenge reactivity and plasma biomarkers compared to single and double food introductions. The results of this study suggest that early introduction of foods, particularly simultaneous mixtures of many allergenic foods is efficacious for preventing FA and can occur safely.

Introduction: Lung cancer remains a global health concern, with non-small cell lung cancer (NSCLC) comprising the majority of cases. Early detection of lung cancer has led to an increased number of cases identified in the earlier stages of NSCLC. This required the revaluation of the NSCLC treatment approaches for early-stage NSCLC. Methods: We conducted a comprehensive search using multiple databases to identify relevant studies on treatment modalities for early-stage NSCLC. Inclusion criteria prioritized but were not limited to, clinical trials and meta-analyses on surgical approaches to early-stage NSCLC conducted from 2021 onwards. Discussion: Minimally invasive approaches, such as VATS and RATS, along with lung resection techniques, including sublobar resection have emerged as treatments for early-stage NSCLC. Ground-glass opacities (GGOs) hve shown prognostic significance, especially when analyzing the consolidation-tumor ratio (CTR). There have also been updates on managing GGOs, including the non-surgical approaches, the extent of lung resection indicated, and the level of lymphadenectomy required. Conclusion: The management of early-stage NSCLC requires further assessment of treatment strategies. This includes understanding the required extent of surgical resection, interpreting the significance of GGOs (specifically GGOs with a high CTR), and evaluating the efficacy of alternative therapies. Customized treatment involving surgical and non-surgical interventions is essential for advancing patient care.

Multi-cancer early detection (MCED) tests are being developed, but little is known about patient receptivity to their use for cancer screening. The current study assessed patient interest in such testing. Our team conducted a prospective, observational study among primary care patients in a large, urban health system. They were asked to complete a telephone survey that briefly described a new blood test in development to identify multiple types of cancer, but was not currently recommended or covered by insurance. The survey included items to assess respondent background characteristics, perceptions about MCED testing, and interest in having such an MCED test. We also used multivariable analyses to identify factors associated with patient interest in test use. In 2023, we surveyed 159 (32%) of 500 identified patients. Among respondents, 125 (79%) reported a high level of interest in having an MCED test. Interest was not associated with personal background characteristics, but was positively associated with the following expectations: testing would be recommended for cancer screening, be convenient, and be effective in finding early-stage disease (OR=11.70, 95% CI: 4.02, 34.04, p < 0.001). Research is needed to assess patient interest and actual uptake when detailed information on testing is presented in routine care.

This is growing recognition of early onset gastrointestinal (GI) malignancies in young adults

The article discusses early diagnosis and intervention for developmental delays in children, emphasizing the role of specialized services and personnel in supporting recovery and development. It presents findings from a pilot project initiated in Bucharest, aiming to assess the incidence of developmental delays in children aged 1-3 years in selected kindergartens, including ASD. The study involved children, parents, and specialists, utilizing systematic behavior observation (SBO) and semi-structured interviews. Results indicate that out of 613 evaluated children, 81 received specialized control recommendations, with 4 cases showing potential risk of ASD. Additionally, 8 children were diagnosed with autism. The incidence of autism in children aged 1-3 years was 1 in 51. Although exploratory, these findings suggest a model of good practice for future early diagnosis campaigns nationally. Conclusively, the study underscores the importance of early diagnosis and intervention for developmental delays, advocating for a responsive community and emphasizing the significance of national-level efforts to address these issues effectively.

Prevalence estimates of Parkinson’s disease (PD) – the fastest growing neurodegenerative disease – are underestimated due to issues surrounding diagnostic accuracy, symptomatic undiagnosed cases, suboptimal prodromal monitoring, and limited screening access. Remotely monitored wearable devices and sensors provide precise, objective, and frequent measures of motor and non-motor symptoms. Here, we used consumer-grade wearable device and sensor data from the WATCH-PD study to develop a PD screening tool aimed at eliminating gaps between patient symptoms and diagnosis. Early-stage PD (n=82) and age-matched comparison (n=50) participants completed a multidomain assessment battery during a one-year longitudinal multicenter study. Using disease- and behavior-relevant feature engineering and multivariate machine learning modeling of early-stage PD status, we developed a highly accurate (92.3%), sensitive (90.0%), and specific (100%) Random Forest classification model (AUC=0.92) that performed well across environmental contexts. These findings provide robust support for further exploring consumer-grade wearable devices and sensors for global population-wide PD screening and surveillance.

Definitive surgical resection is the preferred treatment for early-stage non-small-cell lung cancer (NSCLC). Research into genetic alterations, including epidermal growth factor receptor (EGFR) mutation, in early stage NSCLC remains insufficient. Here, we investigated the prevalence of genetic alterations in early-stage NSCLC and the association between EGFR mutation and recurrence after complete resection. Between January 2019 and December 2021, 659 patients with NSCLC who underwent curative surgical resection at a single regional cancer center were recruited. We compared the clinical and pathological data between the recurrence and non-recurrence groups. Multivariate logistic regression was used to predict the risk factors for recurrence. Among the 659 enrolled cases, the most common histology was adenocarcinoma (74.5%), followed by squamous cell carcinoma (21.7%). The prevalence of EGFR mutation was 43% (194/451). Among them, L858R point mutation and exon 19 deletion was 52.3% and 42%, respectively. ALK rearrangement was found at 5.7% (26/453), and ROS1 fusion was found at 1.6% (7/441). The recurrence rate of the entire population was 19.7%. In multivariate analysis, the presence of EGFR mutation, stage II or III (vs. stage I), and pathologic subtype (presence of solid type) were associated with recurrence. Among the recurred group, 86.5% of the patients with EGFR mutation experienced distant recurrence compared to only 66.7% of wild-type (p = 0.016), with no significant difference in median disease-free survival (p = 0.983). In conclusion, the prevalence of EGFR mutation, ALK rearrangement, and ROS1 fusion was 43.0%, 5.7%, and 1.6%, respectively in patients with early-stage NSCLC who underwent curative resection. Along with stage II/III and solid pathologic subtype, EGFR mutation was an independent risk factor for recurrence. In the recurrence group, the rate of distant metastasis was higher in patients with EGFR mutation than in those with wild-type.

Breast cancer prevention is very important for a woman's health worldwide. We have demonstrated a correlation between mammography and ultrasound with diagnoses using passive microwave radiometry (MWR) and a miRNA oncopanel. While mammography screening dynamics could be completed in 3-6 months, MWR will provide us with a prediction in a matter of weeks or even days with the potential for complementary miRNA diagnostics. An early breast cancer diagnosis may be accomplished using either one of these novel techniques alone or in conjunction with more established techniques

In the case that ship operators may not be aware of the potential risks of environmental factors in situation of high causation probability during the initial stage of the geometric probability analysis process, it is likely that higher-grade collision accident measures will not be taken. However, if any risks is told to the ship operators, more effective and intentional measures can be taken in time. Moreover, if the causation probability corresponding to environmental factors is no less than the risk early warning critical value calculated based on historical collision accident data, there would be a high-risk level that a collision may occur. A new method is put forward based on quantitative analysis of environmental factors and previous collision statistics to provide early warning of any accident risk, and a risk early-warning critical value (REWCV) can be obtained based on this simple but highly operational and practical method. A case study of Three Gorges Reservoir in China indicates that the range of environmental factors where the probability of collision accident grows rapidly is consistent with environmental limits defined by Chinese maritime standards. In addition, the relationship between the risk early-warning critical value and the number of previous collision accident is also clarified.

A prospective longitudinal study of 54 patients who underwent intestinal anastomosis and were started on early enteral nutrition at the University Hospital of the Central University of Venezuela (November 2022 to September 2023), all of them fulfilled the inclusion criteria. Taking as early enteral nutrition two study groups: GROUP 1 tolerance at 24 hours and GROUP 2. Tolerance at 48 hours. Hospital stay and complications were evaluated. Of the 54 patients 40(74.1%) were operated on in emergency surgery 46(85.2%) patients were male. There was no difference in the mean ages of the two diet groups (P=0.254), the mean age was 33.9/14.8 years. There was no statistically significant difference (P=0.086) in the mean number of days of hospitalization (4.7/2.4 days) between patients according to the type of diet. Vomiting occurred in 20.37%, with no statistically significant differences between the groups of patients with diet 1 and 2. There were 2 (3.7%) cases of leakage that required reintervention, and this complication was not associated with the initiation of a particular type of diet, type of surgery, surgical time or site of injury. Early enteral nutrition is a viable option in patients undergoing intestinal anastomosis, is not associated with the incidence of dehiscence, is well tolerated by the patients, has acceptable complications, most frequently associated with vomiting, and reduces hospital stay.

Allergic diseases are becoming a major healthcare issue in many developed nations, where living environment and lifestyle are most predominantly distinct. Such differences include urbanized, industrialized living environments, overused hygiene products, antibiotics, stationary lifestyle, and fast-food based diets tend to reduce microbial diversity and lead to impared immune protection, which further increase the development of allergic diseases. In the same time, studies also showed that modulating microbiomes can ameliorate allergic symptoms. Therefore, in this paper, we aimed to review recent findings on the potential role of the human microbiome in the gastrointestinal tract, surface of skin and respiratory tract for the development of allergic diseases. Furthermore, we addressed a potential therapeutic or even preventive strategy for such allergic diseases by modulating the human microbial composition.

Landslides are natural disasters that normally cause misery over the Mount Elgon region, especially in Bududa district. A landslide early warning system was developed in collaboration with the community and this study investigated it’s effectiveness in disseminating warnings to the community. The data were collected from 82 respondents (mean age 43) and 4 focus group discussions (one per village). Majority of the respondents lost crops (35.9%); land (29.8%); lives and livestock (6.9%). The frequent occurrence of landslides is due to the changes in landuse patterns; settlement on steep slopes; and prolonged rainfall of low intensities. The study found that, 93.2% of respondents have ever received the warnings and alerts. 78.8% of those who received the warnings evacuated. The use of radios to disseminate warnings is the most efficient communication channel (44.4%) followed by using the clan members (19.5%). Only 40% of the women received the early warning through radios, an indicator that this channel puts women at a disadvantage. The main challenges regarding utilization of early warning system were: poor timing (29.9%); poor coordination (20.7%); and poor sensitization (18.4%). There is need to strengthen the community networks, and with continuous sensitization, the effectiveness of the landslides early warning will improve and this is expected to enhance the resilience of the community to landslides.

Purpose: This study evaluates the performance of the Early Intervention Physiotherapist Framework (EIPF) for injured workers. This study provides a proper follow-up period (3 years) to examine the impacts of the EIPF program on injury outcomes such as return to work (RTW) and time to RTW. This study also identifies the factors influencing the outcomes. Methods: The study was conducted on data collected from compensation claims of people who were injured at work in Victoria, Australia. Injured workers who commenced their compensation claims after the first of January 2010 and had their initial physiotherapy consultation after the first of August 2014 are included. To conduct the comparison, we divided the injured workers into two groups: physiotherapy services provided by EIPF-trained physiotherapists (EP) and regular physiotherapists (RP) over the three-year intervention period. We used three different statistical analysis methods to evaluate the performance of the EIPF program. We used descriptive statistics to compare two groups based on physiotherapy services and injury outcomes. We also completed survival analysis using Kaplan-Meier curves in terms of time to RTW. We developed univariate and multivariate regression models to investigate whether the difference in outcomes achieved after adjusting for significantly associated variables. Results: The results showed that physiotherapists in the EP group on average dealt with more claims (over twice as many) than those in the RP group. Time to RTW for the injured workers treated by the EP group was significantly lower than for those who were treated by the RP group, indicated by descriptive, survival and regression analyses. Earlier intervention by physiotherapists led to earlier RTW. Conclusion: This evaluation showed that the EIPF program achieved successful injury outcomes three years after implementation. Motivating physiotherapists to intervene earlier in the recovery process of injured workers by initial consultation helps to improve injury outcomes.

At the beginning of 2023 the Italian former prime minister, the former health minister and 17 others including the current president of Lombardy region, were placed under investigation on suspicion of aggravated culpable epidemic in connection with the government’s response at the start of the COVID-19 pandemic. The charges revolve around the failure by authorities to take adequate measures to prevent the spread of the virus in the Bergamo area, which experienced a significant excess of deaths during the initial outbreak. The aim of this paper is to analyse pandemic data of Italy and Lombardy region in the first 10 days of the pandemic, spanning from the 24th of February 2020 to the 4th of March 2020. The objective is to determine whether the use early warning indicators could have facilitated the identification of a critical increase in infections. This identification, in turn, would have enabled the timely formulation of strategies for pandemic containment, thereby reducing the number of deaths. In conclusion, to translate our findings into practical guidelines, we propose a low-cost early warning method for infectious respiratory diseases with asymptomatic carriers.

The estimation of the Hubble constant in the past few decades has increasingly become more accurate with the advance of new techniques. But its value seems to depend on the epoch at which the measurements are made. The Planck estimate of the Hubble constant from the observations of the CMBR in the early Universe is about 67.

Background: Circulating rare cells participate in breast cancer evolution as systemic components of the disease and thus, are a source of theranostic information. Exploration of cancer-associated rare cells is in its infancy. We determined the validity of a rare-cell detection platform and demonstrated the usefulness of a certain rare cell subset as a novel approach to characterize the breast cancer system. Methods: Linearity of the Rarmax® platform was established using a spike-in approach. The platform includes red blood cell lysis, leukocyte depletion and high-resolution fluorescence image recording. Rare cell analysis was conducted on 28 samples (before and after surgery) from 14 patients with breast cancer, 20 healthy volunteers and 9 non-cancer control volunteers. In-depth identification of rare cells, including circulating tumor cells, endothelial-like cells, erythroblasts and inflammation-associated cells, was performed using a phenotype and morphology-based classification system. Results: The platform performed linearly over a range of 5-950 spiked cells, with an average recovery of 84.6%. Circulating epithelial and endothelial-like cell subsets have been demonstrated to be associated with or independent of cancer with tumor presence. Furthermore, certain cell patterns may be associated with treatment-related adverse effects. The sensitivity in detecting tumor-presence and cancer-associated abnormality before surgery was 50% and 85.7%, respectively and the specificity was 100% and 96.6%, respectively. Conclusion: The present study supports the idea of a cancer-associated rare cell abnormality to represent tumor entities as well as systemic cancer. The latter is independent of the apparent clinical cancer.

Castanopsis hystrix, a precious tree species in Southeast Asia, has the advantages of rapid growth and high-quality wood materials. However, there are problems such as long breeding cycle, time-consuming and low efficiency, which greatly restricts the industrial development of C. hystrix. To perform the genome selection (GS) for growth and wood traits and the early selection of superior progeny have great significance for the rapid breeding of new superior varieties of C. hystrix. The 226 clones in the main distribution and 479 progenies within 23 half-sib families were used as experimental materials in this study. Genotyping datasets were obtained by high-throughput re-sequencing technology, and GS studies were conducted on the growth (tree height (H), diameter at breast height (DBH)) and wood (wood density (WD), fiber length (FL), and fiber length-width ratio (LWR)) traits. The coefficient of variation (CV) of five phenotypic traits ranged from 10.1% to 22.73%, the average CV of growth traits was 19.93%, and the average CV of wood traits was 9.72%. The Pearson correlation coefficients between the five traits were almost significantly positive. Based on the Genomic Best Linear Unbiased Prediction (GBLUP) model, the broad-sense heritabilities of growth traits were higher than those of wood quality traits, and the different number of SNPs had little effect on the heritability estimation. GS prediction accuracy first increased and then reached a plateau around 3K SNPs for all five traits. The broad-sense heritability of these five traits was significantly positively correlated with their GS predictive ability (r=0.564, P

Aim: This analytical cross-sectional study aimed to examine whether there is a correlation between tumor differentiation and certain biomarkers in patients with hepatocellular carcinoma (HCC). Methods: Poorly differentiated (n=443), moderately differentiated (n=379), and well-differentiated (n=272) tumors were separated from the research population, along with a control group (n=364). Biopsies were used to establish the presence of HCC, and biomarker levels were analyzed using chemiluminescence immunoassays in both infected and uninfected individuals. Results: The correlation between age and tumor size was shown to be statistically significant (p0.05) across all subgroups using both descriptive and inferential statistics. Patients with hepatitis C virus and non-A, non-B hepatitis had more advanced tumors than those with other types of poorly differentiated liver cancer. Similarly, individuals with HBsAg and moderate differentiation had bigger tumors, although there was no correlation between hepatitis C and non-A, non-B. Patients with HBsAg or hepatitis C had bigger tumors in the well-differentiated group, albeit the hepatitis C connection was not statistically significant. In addition, the study stressed that tumor size increases with age and that farmers were the most commonly diagnosed profession category. Conclusions: It is clear that early detection in infected populations is crucial for improving HCC outcomes and that chemiluminescence immunoassay has the potential to be a helpful platform for biomarker research. However, the study is limited by its small sample size and its emphasis on only three tumor markers, indicating that more biomarker research is required to improve the accuracy of HCC diagnosis and prognosis.

The concept and policies of multiple early cancer detection (MCED) have gained significant attention from governments worldwide in recent years. In the era of burgeoning artificial intelligence (AI) technology, the integration of MCED with AI has become a prevailing trend, giving rise to a plethora of MCED AI products. However, due to the heterogeneity of both the detection targets and the AI technologies, the overall diversity of MCED AI products remains considerable. The types of detection targets encompass protein biomarkers, cell-free DNA, or combinations of these biomarkers. In the development of AI models, different model training approaches are employed, including datasets of case-control researches or real-world cancer screening datasets. Various validation techniques, such as cross-validation, location-wise validation, and time-wise validation are used. All of the factors show significant impacts on the predictive efficacy of MCED AIs. After the completion of AI model development, deploying the MCED AIs in clinical practice presents numerous challenges, including presenting the predictive reports, identifying the potential locations and types of tumor, and addressing cancer-related information such as clinical follow-up and treatment. This study reviews several mature MCED AI products currently available in the market, detecting their composing factors from serum biomarkers detection, MCED AIs training/validation, and the clinical application. The review illuminates the challenges encountered by existing MCED AI products across these stages, offering insights into the continued development and obstacles within the field of MCED AI.

During the last few years, several approaches have been proposed to improve early warning systems for reducing rock-fall risk. In this regard, this paper introduces a Deep learning-and (IoT) based Framework for Rock-fall Early Warning, devoted to reducing the rock-fall risk with high accuracy. In this framework, the prediction accuracy was augmented by eliminating the uncertainties and confusion plaguing the prediction model. In order to achieve augmented prediction accuracy, this framework fused the prediction model-based deep learning with a detection model-based Internet of Things. In order to determine the framework’s performance, this study adopted parameters, namely overall prediction performance measures, based on a confusion matrix and the ability to reduce the risk. The result indicates an increase in prediction model accuracy from 86% to 98.8%. In addition, a framework reduced the risk probability from (1.51 ×10-3) to (8.57 ×10-9). Our results indicate the framework’s high prediction accuracy; it also provides a robust decision-making process for delivering early warning and lowering the rock-fall risk probability.

There is a major clinical need for accurate biomarkers for prostate cancer prognosis, to better inform treatment strategies and disease monitoring. Current clinically recognised prognostic factors, including prostate-specific antigen (PSA) levels, lack sensitivity and specificity in distinguishing aggressive from indolent disease, particularly in patients with localised intermediate grade prostate cancer. There has therefore been a major focus on identifying molecular biomarkers that can add prognostic value to existing markers, including investigation of DNA methylation, which has a known role in tumorigenesis. In this review, we will provide a comprehensive overview of the current state of DNA methylation biomarker studies in prostate cancer prognosis, and highlight the advances that have been made in this field. We cover the numerous studies into well-established candidate genes, and explore the technological transition that has enabled hypothesis-free genome-wide studies and the subsequent discovery of novel prognostic genes.

To help reduce the impact of geohazards, an innovative landslide early-warning technology based on an energy demodulation-based fiber optic sensing (FOS-LW for short) technology, is introduced in this paper. FOS-LW measures the energy change in a sensing fiber at the segment of micro-bending, which can be caused by landslide movements, and automatically raises an alarm as soon as the measured signal intensity in the fiber reaches a pre-set threshold. Based on the sensing of micro-bending losses in the fiber optics, a two-event sensing algorithm has been developed for the landslide early-warning. The feasibility of the FOS-LW technology is verified through laboratory simulation and field tests. The result shows that FOS-LW has some unique features such as the graded alarm, real-time responses, remote monitoring, low cost and passive optical network, and can be applied in the early-warning of landslides.

Purpose: Early glottic cancer is a highly curable malignancy. Disease control is achieved by resec-tion or external beam radiation with similar long-term results according survival. Surgery is predominantly performed by transoral endoscopic approach, due to reduced complication rates when compared to open cordectomy. Open cordectomy might still be warranted in cases of inad-equate surgical accessibility. Aim of the present study was to compare endoscopic versus open approach in relation to complications and outcome in an up-to-date patient group. Methods: 219 patients underwent primary tumor resection in early glottic cancer (UICC stages I-II). 168 opera-tions were performed endoscopically, 51 operations were open transcervical cordectomies. We compared survival data with non-parametric methods and functional outcome according to need of tracheostomy, feeding tube and voice functional outcome following ELS protocol. Results: There were no significant differences in overall survival (OS). 2 years OS after endoscopic surgery was 90.5% vs 95.3% after transcervical resection. As expected, OS in T1b and T2 tumors was worse than in T1a tumors. We found a statistically significant difference in disease free survival (DFS) within the T1a and T1b/T2 group (Log rank test: p=0.006) but no relevant difference be-tween the two surgical modalities, even when the data was stratified by T-categories performing a Cox regression (hazard ratio 1.21, p=0.712). Patients who underwent open surgery had a sig-nificantly worse peri- and postoperative course with longer hospital stay, higher frequency of tracheotomies and longer need for nasogastric tubes. Functional results were comparable within the two patient groups while higher tumor size / stage was an unfavorable predictor for voice re-habilitation. Conclusion: Open cordectomy leads to more complications but offers comparable oncological and functional outcome when compared to transoral endoscopic approach in early glottic cancer. Open surgery therefore continues to be a valid treatment option when endoscopic resection is not possible.

Background: Oral hypoglycemic agents are typically the first-line treatment for type 2 diabetes mellitus (T2DM). This study examines the benefits of initiating insulin as the first-line therapy for newly diagnosed T2DM patients. Methods: A PubMed search using keywords ‘Type 2 Diabetes Mellitus’ and ‘Early STIIT’ included RCTs assessing beta cell function, insulin resistance, glycemic control, and lipid profiles. Revman 5.4.1 software was used for meta-analysis, with outcomes represented as mean difference (MD) and 95% confidence intervals (CI). Results: Significant reductions in fasting blood glucose (FBG: MD -4.75, 95% CI -7.07, -2.43), HbA1c (MD -1.84, 95% CI -3.01, -0.68), and postprandial glucose (PPG: MD -9.02, 95% CI -10.48, -7.56) were observed with early STIIT therapy compared to baseline. Beta cell function improved (HOMA-B: MD 53.70, 95% CI 27.78, 79.63) and insulin resistance decreased (HOMA-IR: MD -1.84, 95% CI -3.65, -0.04). Lipid profile improvements included reductions in total cholesterol (TC), triglycerides (TG), and LDL, with no change in HDL. BMI remained stable (MD -0.15, 95% CI -0.82, 0.51). Most patients achieved long-term remission and glycemic control without oral hypoglycemic agents. Conclusion: Early STIIT in newly diagnosed T2DM patients significantly reduces glycemic markers and maintains long-term glycemic control, preserving beta cell function. The therapy also improves lipid profiles, reducing TC, TG, and LDL. Initiating insulin as a first-line treatment shows promising results for glycemic control and overall metabolic health.

Early marriage is a phenomenon that has an impact on various aspects of life which then affects human development. This study aims to conduct a literature review on the implications of early marriage on human development. The method used in this study is the SLR (Systematic Literature Review) method. Data collection was carried out by documenting all literature that met the research inclusion requirements. The literature obtained as many as 25 articles from the Google Scholer database with the help of Harzing's Publish or Perish application. From this literature study, it was found that the phenomenon of early marriage has implications for the human development index based on health indicators and life expectancy, education, and welfare. Another finding is that women are the most disadvantaged from the impact of early marriage. Things that can be done to deal with the phenomenon and impact of early marriage include formal and non-formal education, strengthening access to health and education services, creating empowerment programs, and strengthening regulations and legal protection.

Samarinda City is one of the most attractive cities in Borneo Island (Indonesia) and also as a capital city of EastBorneo Province. The expansion of urban areas becomes essential due to rapid population and housing demand. Base on the statistical report, the annual population growth rate is 0.018% from the year 2016-2017 with a total population of 843446 inhabitants. Many natural disasters occur in some areas in this city, especially flooding. This natural disaster occurs almost every year, many people suffered and forced to evacuate. In 2018 there is 3 flood event with 28311 people was suffered and evacuated, and 5170 houses were flooded [1]. During the flood event, it was very possible to gain damages to their property and make traffic stuck. One common way to reducing the damages is using Early Warning Systems (EWS). Early warning is a major element for disaster risk reduction, including damages. To prevent and mitigate the impact of a disaster, many countries had taken action to build various methods of a public warning system. An effective early warning system focused on people-centered and comprises the following element, such as risk knowledge, technical monitoring and service, communication and dissemination of warnings, and community response capability [2]. Related to the existing condition which Samarinda is a Muslim-dominated city and obviously has a lot of a number of mosques. This is a good potency to develop an early warning system because every mosque has a loudspeaker for echoing Adzan (Muslim prayer-calling). With this existing condition, the loudspeaker can be utilized as a flood outdoor-voice warning announcer. The aim of this study is to briefly introduce the strategy of dissemination early warning by utilizing mosques. The hope of early warning dissemination is giving enough time to the people to evacuate their property to reduce damages and possibly to giving information to avoiding traffic stuck (in a certain location)due to flooding. The results of this study can be used as input for decision-makers to develop effective flood management strategies and policies, especially in the case of an early warning system where not well-developed in Samarinda.

Slow-roll inflation may simultaneously solve the horizon problem and generate a near scale-free fluctuation spectrum $P(k)$. These two processes are intimately connected via the initiation and duration of the inflationary phase. But a recent study based on the latest {\it Planck} release suggests that $P(k)$ has a hard cutoff, $k_{\rm min}\not=0$, inconsistent with this conventional picture. Here we demonstrate quantitatively that most---perhaps all---slow-roll inflationary models fail to accommodate this minimum cutoff. We show that the small parameter $\epsilon$ must be $\gtrsim 0.9$ throughout the inflationary period to comply with the data, seriously violating the slow-roll approximation. Models with such an $\epsilon$ predict extremely red spectral indices, at odds with the measured value. We also consider extensions to the basic picture (suggested by several earlier workers) by adding a kinetic-dominated or radiation-dominated phase preceding the slow-roll expansion. Our approach differs from previously published treatments principally because we require these modifications to---not only fit the measured fluctuation spectrum, but to simultaneously also---fix the horizon problem. We show, however, that even such measures preclude a joint resolution of the horizon problem and the missing correlations at large angles.

The recent measurement of a cutoff k_min in the fluctuation power spectrum P(k) of the cosmic microwave background may vitiate the possibility that slow-roll inflation can simultaneously solve the horizon problem and account for the formation of structure via the growth of quantum fluctuations in the inflaton field. Instead, we show that k_min may be interpreted more successfully in the R_h=ct cosmology, as the first mode exiting from the Planck scale into the semi-classical Universe shortly after the Big Bang. In so doing, we demonstrate that such a scenario completely avoids the well-known trans-Planckian problem plaguing standard inflationary cosmology, with some additional clues that may motivate further development of Kaluza-Klein cosmologies, string theories and supergravity.

Understanding the nature of the Dark Matter (DM) is one of the current challenges in modern astrophysics and cosmology. Knowing the properties of the DM particle would shed light on physics beyond the Standard Model and even provide us with details of the early Universe. In fact, the detection of such a relic would bring us information from the pre-Big Bang Nucleosynthesis (BBN) period, an epoch from which we have no data, and could even hint at inflationary physics. In this work, we assume that the expansion rate of the Universe after inflationary is governed by the kinetic energy of a scalar field ϕ, in the so-called “kination” model. We assume that the ϕ field decays into both radiation and DM particles, which we take to be Weakly Interacting Massive Particles (WIMPs). The present abundance of WIMPs is then fixed during the kination period through either a thermal “freeze-out” or “freeze-in” mechanism, or through a non-thermal process governed by the decay of ϕ. We explore the parameter space of this theory with the requirement that the present WIMP abundance provides the correct DM relic budget. Requiring that BBN occurs during the standard cosmological scenario sets a limit on the temperature at which the kination period ends. Using this limit and assuming the WIMP has a mass m_χ = 100 GeV, we obtain that the thermally-averaged WIMP annihilation cross section has to satisfy the constraints 3.5 × 10⁻¹⁶ GeV⁻² ≲ (σv) ≲ 1.4 × 10⁻⁵ GeV⁻² in order for having at least one of the production mechanism to yield the observed amount of DM. This result shows how the properties of the WIMP particle, if ever measured, can yield information on the pre-BBN content of the Universe.

From the various perspectives of Machine Learning (ML) and the multiple models used in this discipline, there is an approach aimed at training models for the Early Detection (ED) of anoma-lies. The early detection of anomalies is crucial in multiple areas of knowledge since identifying and classifying them allows for early decision-making and provides a better response to mitigate the negative effects caused by late detection in any system. This article presents a literature review to examine which machine learning models (MLM) operate with a focus on ED in a multidisci-plinary manner and specifically how these models work in the field of fraud detection. A variety of models were found, including Logistic Regression (LR), Support Vector Machines (SVM), De-cision Trees (DT), Random Forests (RF), Naive Bayesian Classifier (NB), K-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), Extreme Gradient Boosting (XGB), among others. It was identified that MLMs operate as isolated models, categorized in this article as Single Base Models (SBM) and Stacking Ensemble Models (SEM). It was identified that MLMs for ED in multiple areas under SBM and SEM implementation achieved accuracies greater than 80% and 90%, respectively. n fraud detection, accuracies greater than 90% were reported by the authors. The article concludes that MLMs for ED in multiple applications, including fraud, offer a viable way to identify and classify anomalies robustly, with a high degree of accuracy and precision. MLMs for ED in fraud are useful as they can quickly process large amounts of data to detect and classify suspicious transactions or activities, helping to prevent financial losses.

(1) Background: Endoscopic submucosal dissection (ESD) has been widely accepted as the standard method for treating early-stage cancer or precancerous lesions in the upper gastrointestinal tract, however it may be difficult in patients with liver cirrhosis due to coagulation dysfunction or presence of gastroesophageal varices. We aimed to demonstrate the safety and efficacy of ESD in these population. (2) Methods: We retrospectively collected the clinical data and analyzed. Patients inclusion criteria: 1) patients with liver cirrhosis; 2) patients who underwent ESD; 3) patients diagnosed of early-stage cancer or precancerous lesions in the upper gastrointestinal tract. (3) Results: Eight patients were enrolled from April 2019 to April 2023, of whom 3 were male and 5 female, with age ranging from 43 to 70 years old. Seven lesions were located in the stomach, and the other one lesion in the esophagus. ESD was performed successfully in all patients, and the resected lesion size ranged from 2 to 6 cm. Only one patient encountered postoperative complication, chest pain and fever. No recurrence of noticed during a follow-up of 6 to 36 months. (4) Conclusions: ESD is safe and effective for treating upper gastrointestinal early-stage cancer or precancerous lesions in patients with liver cirrhosis.

Timely diagnosis of Alzheimer's diseases(AD) is crucial to obtain more practical treatments. In this paper, a novel approach Based on Multi-Level Fuzzy Neural Networks (MLFNN) for early detection of AD is proposed. The focus of study was on the problem of diagnosing AD and MCI patients from healthy people using MLFNN and selecting the best feature(s) and most compatible classification algorithm. In this way, we achieve an excellent performance using only a single feature i.e. MMSE score, by fitting the optimum algorithm to the best area using optimum possible feature(s) namely one feature for a real life problem. It can be said, the proposed method is a discovery that help patients and healthy people get rid of painful and time consuming experiments. Experiments shows the effectiveness of proposed method in current research for diagnosis of AD with one of the highest performance (accuracy rates of 96.6%), ever reported in the literature.

This article reviews the introduction of Alzheimer's Disease (AD), neural networks, training and learning of neural networks, applications of neural networks in early diagnosis of AD, applications of neural networks in AD drug discovery, other brain diseases, and challenges faced by AD. First, the paper introduces the background and characteristics of AD. AD is a degenerative neurological disorder characterized by impaired memory, decreased cognitive function, and loss of neurons. These characteristics place a huge burden on the lives and families of patients. Next, the basic principle and structure of neural network are discussed. A neural network is a computational model made up of multiple neurons that can perform tasks by learning and adapting to input data. In particular, the key concepts of neural network hierarchy, activation function and weight adjustment are discussed. Then, the training and learning methods of neural networks are discussed. Common techniques such as backpropagation algorithm and gradient descent optimizer are introduced in detail, as well as the importance of data preprocessing and model evaluation. Next, the paper focuses on the application of neural network in early diagnosis of AD. By extracting features from brain image data, neural networks can automatically identify differences between AD patients and healthy subjects, enabling early diagnosis and intervention. In addition, the application of neural networks in AD drug discovery is also discussed. By analyzing and predicting a database of known drugs, neural networks can help discover potential treatments for AD and speed up the drug discovery process. The paper further explores the application of neural networks in other brain diseases and highlights the challenges faced by AD, such as the lack of reliable biomarkers, complex pathological mechanisms, etc. In summary, this paper presents a systematic overview of AD, neural networks, training and learning of neural networks, applications of neural networks in early diagnosis of AD and drug discovery, and other brain diseases and challenges associated with AD.

In the recent concrete industry, high fluidity concrete is being widely used for the pouring of dense reinforced concrete. Normally, in the case of high fluidity concrete, it includes high binder contents, so it is necessary to replace part of the cement through admixtures such as fly ash to procure economic feasibility and durability. This study shows the mechanical properties and field applicability of high fluidity concrete that using mass of fly ash as alternative materials of cement. The high fluidity concrete mixed with 50% fly ash was measured to manufacture concrete that applies low water/binder ratio to measure the mechanical characteristics as compressive strength and elastic modulus. Also, in order to evaluate the field applicability, high fluidity concrete containing high volume fly ash was evaluated that fluidity, compressive strength, heat of hydration and drying shrinkage of concrete.

The article is devoted to solving the problem of searching for universal explainable features that can remain explainable for a wide class of objects and phenomena and become an integral part of Explainable AI (XAI). The study is implemented on the example of an applied problem of early diagnostics of plant stress, using Thermal IR (TIR) and HSI, presented by 8 vegetation indices/channels. Each such index was presented by 5 statistical values. A Single-Layer-Perceptron classifier was used as the main instrument. TIR turned out to be the best of the indices in terms of efficiency in the field and sufficient to detect all 7 key days with 100% accuracy. Our study shows also that there are a number of indices, inluding NDVI, and usual color channels Red, Green, Blue, which are close to TIR possibilities in early plant stress detection with 100% accurasy or near, and can be used for wide class of plants and in different conditions their treatment. The stability of the stress classification in our study was maintained when the training set was reduced up to 10% of the dataset volume. The entropy-like feature of (max-min) for any indices/channels have determined as a leadersheep universal high-level explainable feature for the plant stress detection, which used in interaction with some of other statistical features.

Background. This study aimed to establish a prognostic nomogram for predicting overall survival (OS) and cancer-specific survival (CSS) of patients with early-onset endometrial cancer (EOEC). Methods. Patients diagnosed with EOEC during 2004-2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analyses were performed to ascertain the independent factors impacting the prognosis of EOEC patients, while a prognostic nomogram was established. Its performance was verified by the receiver operating characteristic (ROC) curves, and calibration plots. The prediction accuracy and clinical net benefit between the model, TNM stage and SEER stage were further compared by the concordance index (C-index) and decision curve analysis (DCA). Results. A total of 4415 eligible patients with EOEC were identified and enrolled in this study. Independent prognostic factors for OS and CSS were confirmed by multivariate Cox regression, which were further incorporated to constructed a nomogram. ROC curves and calibration curves indicated an optimal accuracy of the nomogram. Meanwhile, the C-index and DCA showed the predictive capability and the clinical applicability of the nomogram was superior over the TNM stage and SEER stage. Conclusions. Nomogram based on risk factors was developed as an individualized tool to predict OS and CSS for EOEC patients. The novel tool will assist in patient counseling and selection of appropriate therapeutic regimens.

This study develops a 7-layer Long Short-Term Memory (LSTM) model to enhance early diabetes detection in Oman, aligning with the theme of 'Artificial Intelligence in Healthcare'. The model focuses on addressing the increasing prevalence of Type 2 diabetes, projected to impact 23.8% of Oman's population by 2050. It employs LSTM neural networks to manage factors contributing to this rise, including obesity and genetic predispositions, and aims to bridge the gap in public health awareness and prevention. The model's performance is evaluated through various metrics. It achieves an accuracy of 99.40%, specificity and sensitivity of 100% for positive cases, a recall of 99.34% for negative cases, an F1 score of 96.24%, and an AUC score of 94.51%. These metrics indicate the model's capability in diabetes detection. The implementation of this LSTM model in Oman's healthcare system is proposed to enhance early detection and prevention of diabetes. This approach reflects an application of AI in addressing a significant health concern, with potential implications for similar healthcare challenges globally.st diagnostic capabilities, representing a significant leap forward in healthcare technology in Oman.

Advances in gastric cancer screening and endoscopic technology have made it possible to detect and treat gastric cancer at an early stage. As a result, about 40% of all gastric cancers have now been resected by endoscopic treatment in Japan. In endoscopic diagnosis, magnifying endoscopic observation using band-limited light such as narrow band imaging (NBI) has significantly improved the accuracy of gastric cancer diagnosis. At the same time, in endoscopic treatment, endoscopic submucosal dissection (ESD) has contributed to increase explosively the number of gastric cancers which could be resected endoscopically. In recent years, the construction of algorism for endoscopic diagnosis and treatment with a view to personalized medicine has been explored, and endoscopic use for gastric cancer managements is expected to develop further in the future. Keywords (5 words):

It is generally believed that the universe emerged from the Big Bang, before which space and time did not exist. However, Penrose proposed his theory of conformal cyclic cosmology, in which an aeon existed preceding this universe. Based on the cosmological principle, the universe is homogeneous and isotropic, expanding without center, but recently more and more deviations have been observed. By studying the fundamental particles and reactions of nature, we initiated a model that the Big Bang is the result of the collapse of a neutrino star within a black hole. We therefore re-analyze the cosmic microwave background (CMB) and find that the Center of the universe where the Big Bang occurred was at 0.66 ^+0.03 _-0.01 times the radius of the surface of last scattering away from the Local Supercluster (LS) and at Galactic coordinates (l, b) = (286^o +/- 10^o, -43^{o +7} _-6). If we look from the LS to the Center, the universe is spinning clockwise. Our findings are supported by Penrose’s conformal cyclic cosmology, low-variance circle sets in the CMB, and many other independent observational evidence of cosmic inhomogeneities, spatial anisotropies, and time variations.

We present a Quantum Space Model (QSM) of the evolution of the universe based on the theory that space consists of energy quanta from which it began. We used the Friedmann equations to trace its history and show that Dark Energy is the energy of space which caused its accelerating expansion.The universe started from a quanta of space which was triggered by quantum fluctuations that caused the Big Bang. It then expanded and cooled undergoing phase transitions to radiation, fundamental particles, and matter. Matter grew into galaxies, and was consolidated by gravity into Black Holes, ending in a Big Crunch and Deep Freeze inside a Black hole at 1.380 trillion years. Fluctuations caused a new Bang to start another cycle in its life. If the Law of Conservation of Energy is universal, then the cosmos is eternal. Our results support the theoretical predictions of a cyclic universe by Steinhardt and associates, as well as Penrose. Space and energy are equivalent as embodied in the Planck energy equation. They are the two most fundamental quantities that govern cosmic evolution. The two principal long range forces are the gravitational force and the space force,which maybe the fifth force in the universe. They provide the clockwork mechanism operating our cyclic universe.

Experimental and epidemiological evidence has shown that modifications of the intrauterine environment can have deleterious consequences for individuals, expressed as an increased risk of suffering non-communicable pathologies in adult life, which is known as the hypothesis of the early origin of diseases or programming fetal. On the other hand, changes in gene expression patterns through epigenetic modifications can be the basis for long-term maintenance of the effects of fetal programming. In this sense, epigenetics comprises the study of intrauterine disturbances, which develop diseases in the adult, including Celiac Disease (CD). In addition, early feeding practices could influence the risk of CD development, such as breastfeeding timing and duration and age at gluten introduction in the diet. Gluten acts as a trigger for CD in genetically predisposed subjects, although approximately 30% of the world population has HLA DQ2 or DQ8, the prevalence of the disease is only 1-3%. It is not known what factors act to modify the risk of disease in genetically at risk subjects. Taking into account all these considerations, the aim of the current review is to elucidate the role of early programming and the effect of early nutrition on the development and progression of CD.

In a recent paper we had discussed possibility of DM at high redshifts forming primordial planets composed entirely of DM to be one of the reasons for not detecting DM (as the flux of ambient DM particles would be consequently reduced). In this paper we discuss the evolution of these DM objects as the universe expands. As universe expands there will be accretion of DM, Helium and Hydrogen layers (discussed in detail) on these objects. As they accumulate more and more mass, the layers get heated up leading to nuclear reactions which burn H and He when a critical thickness is reached. In the case of heavier masses of these DM objects, matter can be ejected explosively. It is found that the time scale of ejection is smaller than those from other compact objects like neutron stars (that lead to x-ray bursts). These flashes of energy could be a possible observational signature for these dense DM objects.

Introduction: The choice of Cardiac Preservation Solution (CPS) for myocardial protection at the time of heart procurement remains controversial and uncertainties persist regarding its effect on the early and midterm Heart Transplantation (HTx) outcomes. Thus, we retrospectively analyzed our adult HTx performed with two different CPS, during a period of 12 years, in terms of hospital mortality, mid-term survival, inotropic score, primary graft dysfunction and rejection score. Methods: From January 2009 to December 2020, 154 adult HT were performed in our hospital. Patients were divided in two groups according to the CPS used: St. Thomas (n=75, group P 1) and HTK-Custodiol (n=79, group P 2). The choice of CPS was related to an institutional policy; from 2009 to 2015, St. Thomas solution was exclusively used, and after that, HTK-Custodiol alone. Results: There was no significant difference between the two groups in terms of preoperative and intraoperative features. Postoperatively, the Custodiol group showed significantly lower inotropic score (p&lt;0.0001), mean rejection score (p= 0.036) and 30 days mortality (p=0.0068). The use of HTK-Custodiol was the only variable that improved midterm survival (HTK-Custodiol vs St Thomas, HR= 0.20 (95% CI: 0.069 -0.6) p=0.0039). Conclusion: In our single center experience, using HTK-Custodiol as myocardial protection during heart procurement leads to improved outcomes after HTx, including postoperative inotropic score, rejection score, 30-days mortality and midterm survival.

Molecular autism research is evolving towards a biopsychosocial framework that is more informed by autistic experiences. In this context, research aims are moving away from correcting external autistic behaviors and towards alleviating internal distress. Autism Spectrum Conditions (ASCs) are associated with high rates of depression, suicidality and other comorbid psychopathologies, but this relationship is poorly understood. Here, we integrate emerging characterizations of internal autistic experiences within a molecular framework to yield insight into the prevalence of psychopathology in ASC. We demonstrate that descriptions of social camouflaging and autistic burnout resonate closely with the accepted definitions for early life stress (ELS) and chronic adolescent stress (CAS). We propose that social camouflaging could be considered a distinct form of CAS that contributes to allostatic overload, culminating in a pathophysiological state that is experienced as autistic burnout. Autistic burnout is thought to contribute to psychopathology via psychological and physiological mechanisms, but these remain largely unexplored by molecular researchers. Building on converging fields in molecular neuroscience, we discuss the substantial evidence implicating mitochondrial dysfunction in ASC to propose a novel role for mitochondrial allostatic load in the relationship between autism and psychopathology. An interplay between mitochondrial, neuroimmune and neuroendocrine signaling is increasingly implicated in stress-related psychopathologies, and these molecular players are also associated with neurodevelopmental, neurophysiological and neurochemical aspects of ASC etiology. Together, this suggests an increased exposure and underlying molecular susceptibility to ELS that increases the risk of psychopathology in ASC. This article describes an integrative framework shaped by autistic experiences that highlights novel avenues for molecular research into mechanisms that directly affect the quality of life and well-being of autistic individuals. Moreover, this framework emphasizes the need for increased access to diagnoses, accommodations, and resources to improve mental health outcomes in autism.

Eating Disorders (ED) constitute a serious public health issue affecting predominantly women and appearing typically in adolescence or early adulthood. EDs are extremely difficult to treat as these disorders are ego-syntonic and many patients do not seek treatment. It is vital to focus on the development of successful early-intervention programs for individuals presenting at-risk and are on a trajectory towards developing EDs. This study is a randomized controlled trial evalu-ating an innovative digital gamified Acceptance and Commitment early-intervention program (AcceptME) for young females showing signs and symptoms of an ED and at high-risk for an ED. Participants (N=92; Mage=15.30 years, SD=2.15) received either AcceptME (N=62) or a waitlist control (N=30). Analyses indicated that the AcceptME program effectively reduced weight and shape concerns, with large effects when compared to waitlist controls. Most participants scored below the at-risk cut-off (WCS score<52) in the AcceptME at end-of-intervention (57.1%) com-pared to controls (7.1%) with odds of falling into the at-risk group being 14.5 times higher for participants in the control group. At follow-up, 72% of completers reported scores below the at-risk cut-off in the AcceptME group. The intervention also resulted in a decrease in ED symp-tomatology and increased body image flexibility. Overall, results suggest that the AcceptME program holds promise for early-intervention of young women at-risk for developing an ED.

Rapid spread of African swine fever virus (ASFV), causing severe disease with often high fatality rates in Eurasian suids, prevails as a threat for pig populations and dependent industries world-wide. Although advancing scientific progress continually enhances our understanding of ASFV pathogenesis, alternative transmission routes for ASFV have yet to be assessed. Here, we demonstrate that ASFV can efficiently be transferred from infected boars to naïve recipient gilts through artificial insemination (AI). In modern pig production, semen from boar studs often supplies many sow herds. Thus, the infection of a boar stud presents the risk of rapidly and widely distributing ASFV within or between countries. Daily blood and semen collection from four boars after intramuscular inoculation with ASFV strain ‘Estonia 2014’ resulted in detection of ASFV genomes in the semen as early as 2 dpi, in blood at 1 dpi while semen quality remained largely unaffected. Ultimately, after insemination with extended semen, 7 of 14 gilts were ASFV positive by 7 days post insemination, and all gilts were ASFV positive by 35 days post insemi-nation. Twelve out of 13 gilts aborted at the onset of fever. A proportion of fetuses originating from the remaining gilt showed both abnormalities and replication of ASFV in fetal tissues. Thus, we present evidence for the efficient transmission of ASFV to gilts via AI and also to im-planted embryos. These results underline the critical role that boar semen could play in ASFV transmission.

Epidemiological studies point cholesterol as a possible key factor for both prostate cancer incidence and progression. So, it could represent a targetable metabolite as the most aggressive tumors also appear to be sensitive to therapies designed to decrease hypercholesterolemia, such as statins. However, whether and how cholesterol, through its dietary uptake and its metabolism, could be important for early tumorigenesis, remains unknown. Oncogene clonal induction in Drosophila melanogaster accessory gland allows to reproduce tumorigenesis from initiation to early progression, where tumour cells undergo basal extrusion to form extra-epithelial tumors. Here we show that these tumors accumulate lipids, and especially esterified cholesterol, as in human late carcinogenesis. Interestingly, high cholesterol diet displays limited effect on accessory gland tumorigenesis. On the contrary, cell-specific downregulation of cholesterol uptake, intracellular transport or metabolic response, impairs the formation of such tumors. Furthermore, in this context, high cholesterol diet suppresses this impairment. Taken together, these results reveal that during early tumorigenesis, tumour cells strongly increase their uptake and use of dietary cholesterol to specifically promote the step of basal extrusion. Interestingly, expression data from primary prostate cancer tissues indicate an early signature of redirection from cholesterol de novo synthesis to uptake. Altogether, these results suggest by which mechanism reduction of dietary cholesterol could lower the risk and slow down the progression of prostate cancer.

The question of whether the early visual cortex (EVC) is involved in visual mental imagery remains a topic of debate. In this paper, I propose that the inconsistency in findings can be explained by the unique challenges associated with investigating EVC activity during imagery. During perception, the EVC processes low-level features which means that activity is highly sensitive to variation in visual details. If the EVC has the same role during visual mental imagery, any change in the visual details of the mental image would lead to corresponding changes in EVC activity. Within this context, the question should not be whether EVC is ‘active’ during imagery but how its activity relates to specific imagery properties. Studies using methods that are sensitive to variation in low-level features reveal that imagery can recruit the EVC in similar ways as perception. However, not all mental images contain a high level of visual details. Therefore, I end by considering a more nuanced view which states that imagery can recruit the EVC, but that does not mean that it always does so.

The BKL singularity inside a rotating black hole would be a neutrino star. Once its mass exceeds the limit that neutrino degeneracy pressure could support (larger than 3×10²² M_⊙), the neutrino star singularity would collapse, raising the temperature to the maximum and dropping the entropy to the minimum to initiate a Big Bang. From the cosmic microwave background, we find where the Big Bang occurred at about 0.66 times the radius of the surface of last scattering away from us and at Galactic coordinates (l, b) ≃ (286°,-43°). As it expands, the clockwise spinning universe has been veering towards the ellipsoidal. These findings are consistent with independent observations of cosmic inhomogeneities, spatial anisotropies, and time variations.

Breeding early-maturing cultivars is one of the most important objectives for pear breeding. Very early-maturing pear provides an excellent parental material for crossing, while the immature embryo and low seed germination of its hybrid progenies often limit the selection and breeding of new early-maturing pear cultivars. In this study, we choose a very early maturing pear cultivar ‘Pearl Pear’ as study object, and investigate the effects of cold stratification, culture medium and seed coat on the germination and growth of early maturing pear seeds. Our results show that cold stratification (4℃) treatment could significantly improve the germination rates of early maturing pear seeds. A 100 days of low temperature pre-treatment and germination on White medium could increase the germination rate up to 84.54%. We also observe that seed coat removal could improve the germination activity of early maturing pear seeds, and middle seed coat removal (MSR) represents an optimal method with its high germination rate and low contamination. The results of our study established an improved protocol for seed germination of early-maturing pear seeds, which will greatly facilitate the breeding of new very early-maturing pear cultivars.

Lung cancer remains the leading cause of cancer-related death worldwide. The involvement of lymph nodes by the tumor has a strong impact on survival of patients. For this reason, lymphadenectomy plays a crucial role in the staging and prognosis of NSCLC, to define the most appropriate therapeutic strategies concerning the stage of the disease. To date, the benefit, in terms of survival, of the different extents of lymphadenectomy remains controversial in the scientific community. It is recognized that metastatic involvement of mediastinal lymph nodes in lung cancer is one of the most significant prognostic factors, in terms of survival, and it is therefore mandatory to identify patients with lymph node metastases who may benefit from adjuvant therapies, to prevent distant disease and local recurrences. The purpose of this review is to evaluate, the role of lymphadenectomy in early-stage NSCLC in terms of efficacy and accuracy, comparing systematic, sampling and lobe-specific lymph node dissection and analyzing the existing critical issue, through a search of the most relevant articles published in the last decades.