Glaucoma is a disease associated with retina of eye. Presently, millions of human being is suffering from this disease. Early detection of these diseases can save the people from blindness. Therefore, various methods have been developed for its detection. In this paper, we have studied the reported methods and summarized their performance in terms of accuracy of detection.

The first reports of the acute and often fatal illness known as the “English Sweat” are from 1485 and its last known outbreak was in 1551. During this period, the Sweat produced only five epidemic waves. Except for one outbreak which spread to the northern part of the continent of Europe in 1529, the Sweat was confined almost exclusively to England, with only anecdotal reports of isolated infections in other parts of the British Isles. The Sweat was thus only a minor component in the panorama of infectious disease affecting mediaeval and early modern Europe. Nevertheless, it continues to fascinate both medical historians and modern infectious disease biologists – the latter group now often engaged in competing exercises in retrospective diagnosis. This paper seeks to explore the reasons for such enduring interest, using the Early English Books Online (EEBO) text corpus to analyse the various contexts in which the Sweat was discussed up to 1700. EEBO shows that references to the Sweat occur repeatedly in astrological and religious discourses, especially from the mid-17^th century onwards. Four salient examples are examined in detail. It is proposed that the cultural memory of the Sweat, in the 150 years following its disappearance, was kept disproportionately alive not so much by accounts of its alarming symptoms but more due to its metaphorical and illustrative utility in non-medical discourse.

Background: Neonatal sepsis associated with severe morbidity and mortality defines the systemic condition arising from the bacterial, viral, fungal origin associated with hemodynamic and clinical alterations. Symptomatology can be different, from subclinical to severe, focal or systemic disease. The causal agent comes from maternal flora or can be of community/hospital origin. Material and method: Our retrospective study evaluated 121 newborns (both preterm and term), divided into three groups: early onset sepsis (35), late onset sepsis (39), and control group (47), from 0 to 28 days old. Blood samples and cultures were collected at admission, after 24 hours, and 72 hours. Results: The two-sample Wilcoxon signed rank test revealed a statistically significant difference between the initial and final measures of lactate dehydrogenase (LDH) and ferritin within the early onset sepsis (EOS) and late onset sepsis (LOS) groups. No significant differences were observed for those two variables within the control group. There were significant differences for first and last measurements of C-Reactive Protein (CRP) (p = 0.029), leukocyte count (p = 0.002), and platelets (TR) (p = 0.00001). Conclusions: Ferritin is a potential biomarker that can be associated with systemic response and sepsis in both cases of early and late onset sepsis.

Early Life Adversity (ELA) is closely associated with the risk for developing diseases later in life, such as autoimmune diseases, type-2 diabetes and cardiovascular diseases. In humans, early parental separation, physical and sexual abuse or low social-economic status during childhood are known to have great impact on brain development, in the hormonal system and immune responses. Maternal deprivation (MD), the closest animal model available to the human situation, is known to similarly induce long lasting behavioural effects, to cause changes in the HPA axis and to have an impact in the immune system. Even though the immune responses to potential pathogens after early stress have been somehow documented, the mechanisms by which they occur are still not fully understood. Here, we have demonstrated that maternal separation, in both humans and rats, significantly affects the sensitivity of the immune system in adulthood. Particularly, NK cells’ profile and response to target cell lines are significantly changed after childhood adversity. These immune cells in rats are not only less cytotoxic towards YAC-1 cells, but also show a clear increase in the expression of maturation markers after 3h of maternal separation. Similarly, individuals who suffered from ELA display significant changes in the cytotoxic profile of NK cells together with decreased degranulation capacity. Altogether, these results lead us to conclude that one of the key mechanisms by which the immune system becomes impaired after ELA might be due to a shift on the senescent state of the cells, specifically NK cells. Elucidation of such a mechanism highlights the importance of ELA prevention and how NK targeted immunotherapy might help attenuating ELA consequences.

Young women with breast cancer represent 15% of cancer cases in Latin America. Genomic studies have found that early-onset breast-cancer cases exhibit a higher genetic susceptibility and a specific genomic signature as compared to their older counterparts. The aim of this study was to describe clinically relevant germline mutations in a cohort of young women with breast cancer. To achieve this, we analyzed hereditary-cancer genes from whole-exome sequencing data in 108 unrelated women with an extreme phenotype of breast cancer (≤40 years of age), diagnosed and treated at the National Cancer Institute of Mexico; 11% of the patients carried a pathogenic variant. BRCA2 comprised 46% of the mutations, followed by BRCA1 with 23%; PALB2 with 15%; and TP53 and RAD51C with 8 % each. This article describes a novel pathogenic mutation in RAD51C c.519dupT. The median age at diagnosis was 35 years overall; however, it was six years younger in patients with mutations. Age at diagnosis (OR=0.82, CI 95% 0.71-0.94; P= 0.008) and first-degree family history of cancer (OR=8.26, CI95% 1.35-50; P= 0.022) were the only epidemiological variables associated with mutational status. We found no differences in disease-free survival (p=0.403) or overall survival (p=0.735) among mutational status subgroups.

Along most of the European littoral, oysters were appreciated as a wholesome and palatable food since the Stone Age, yet were transported much further from their natural habitats when long-distance trade in marine foodstuffs began in medieval times. The brackish waters of the Baltic Sea are not considered a suitable environment for this mussel, and therefore all archaeological oyster shell finds are the result of import to the eastern Baltic. In this study, over 1000 shells found in different medieval and early modern archaeological contexts in Estonia were analysed and the obtained data recorded in a data repository. Some conclusions are set out, based on shell size and shape, and breakage traces, but more detailed taphonomic studies are left for the future. The study identifies the earliest imports of oysters recorded by archaeological material and written sources. Both show records not much earlier than the 16th century AD. Although no information is preserved about the exact origin of oysters imported to Estonia, the oyster beds most probably exploited are those in the central eastern North Sea, i.e. the Wadden Sea.

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.

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.

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.

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 Süttő 21 site is a fissure fill of the freshwater limestone of the Gazda quarry in Süttő. The material was collected between 2017 and 2019, the results are summarised in this article, with a special focus on the small vertebrate fauna of the site and its stratigraphic and paleoecological significance. The fissure fill can be placed around the early/middle Pleistocene boundary (ca. 1.1 and 0.77 Ma). The paleoecological analysis of the herpeto- and mammal fauna of the sequence indicates the proximity of a permanent water body. The lower part of the sequence is dominated by open habitat indicator taxa indicating a cool, dry climate. Towards the upper part of the sequence, the climate remained cool but became wetter, and the vegetation gradually changed to forest-steppe/open forest. The fauna of the Süttő 21 site can be compared with the material of sites, which are of similar age, thus revealing taxonomic and paleoecological differences between different areas of the country. While a warm, dry climate and open vegetation can be reconstructed in the Villány Hills around the early/middle Pleistocene boundary, the northern Hungarian areas had a cooler, wetter climate, and slightly more closed (grove, forest-steppe) vegetation during this period.

Estimation of the potential consequences from events occurring downstream of a dam are part of the risk assessment needed during the installation phase of a new dam. In case of specific Natural or Man Made ongoing or prospected events, it may be also important to carry out fast computations that can provide information on the areas at risk either because the original design analyses are not available or because the parameters needed are different. This study is aimed to develop a procedure that strongly facilitates the preparation of the input deck and the derivation of the output quantities to allow a fast analysis of a dam break event using a shallow water model, NAMI DANCE, as the analysis tool.

This study aimed to investigate how transplanting date affects the agronomic and grain quality traits of two early maturing rice varieties. The experiment was conducted in the rice research field of Chungnam Agricultural Research and Extension Services, South Korea and rice materials were transplanted at intervals of approximately 15 days from April 16 to July 16 in 2019 and 2020. Results showed that agronomic and grain quality traits varied according to the transplanting date, and earlier transplanting resulted in the longer period of days from transplanting to heading (DTH). The spikelet number m-2 was highly correlated with the milled rice yield (r = 0.963** for Jinbuol, r = 0.909** for Yeoreumi) and it significantly decreased as the transplanting date was delayed, which was leading to lower yield. Environmental factors, the mean temperature during the grain filling stage, had a negative correlation with head rice rate (r2 = 0.825** for Jinbuol, r2 = 0.803** for Yeoreumi), and the number of days from transplanting to heading showed negative correlation with protein content (r2 = 0.777** for Jinbuol, r2 = 0.833** for Yeoreumi). Therefore, increasing the number of days from transplanting to heading date can lead to higher milled rice yield and lower protein content, and avoiding heading dates on July 17 can improve the appearance traits. As a results, it is suggested that early transplanting is advantageous to increase the milled rice yield and grain quality of early maturing rice.

In this paper, we have investigated the impact of an early learning assessment on students' motivation for improving their performance throughout the semester. An observation analysis was conducted on an entry level mechanical engineering course in which students are enrolled in during their first semester of engineering work. This study analyzes the effect that a first exam, with an average below a passing grade, has on student's outcome in the course. It was hypothesized that students were motivated to achieve their desired grade outcomes following inadequate performance on the first exam. This was investigated by diving into the results of the course and referencing initial performance to the remaining exam and assessment outcomes. Students were placed into grade bands ranging from 0 to 100 in 20% increments. Their results were tracked and it was shown that for the second mechanics exam, averages jumped 43.333%, 35.35%, and 30.055% for grade bands of 0 to 20, 20 to 40, and 40 to 60 respectively. Assessment grades increased as well with the remaining assessments being averaged to a score of 91.095%. Variables contributing to student performance came from both with-in and outside the classroom. Learning communities, material differentiation, and student and professor adaptation all contributed to the rise in performance. It was concluded that the internal and external variables acted in combination with one another to increase student dedication to achieve success.

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.

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.

Significant challenges exist globally regarding literacy teaching and learning, particularly in poor socio-economic settings in countries of the Global South. In this paper we argue that to address these challenges, major features of how the brain works that are currently ignored in the educational literature should be taken into account. First, perception is an active process based in detection of errors in hierarchical predictions of sensory data and action outcomes. Reading is a particular case. Second, emotions play a key role in underlying cognitive functioning. Innate affective systems underlie and shape all brain functioning, including oral and written forms of language and sign. Third, there is not the fundamental difference between listening/speaking and reading/writing often alleged on the basis of evolutionary arguments. Both are socio-cultural practices driven and learnt by the communication imperative of the social brain. Fourth, like listening, reading is not a linear, bottom-up process. Both are non-linear contextually shaped psycho-social processes of understanding, shaped by current knowledge and cultural contexts and practices. Reductionist neuroscience studies which focus on decontextualized parts of reading cannot access all the relevant processes. An integrated view of brain function reflecting this non-linear nature implies that an ongoing focus on personal meaning and understanding provides positive conditions for all aspects of literacy learning. Assessment of literacy teaching at all its stages should include indicators that take into account these foundational features relating reading and writing to neuroscience.

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.

Background: Malignant pleural mesothelioma (MPM) is an atypical, belligerent tumor that matures into cancer in the pleura, a stratum of tissue bordering the lungs. Pleural mesothelioma is a common type of mesothelioma that accounts for about 75 percent of all mesothelioma diagnosed yearly in the United States. Diagnosis of mesothelioma takes several months and is expensive. Given the difficulty of diagnosing MPM, early identification is crucial for patient survival. Our study implements artificial intelligence and recommends the best fit model for early diagnosis and prognosis of MPM. Method: We retrospectively retrieved patient’s medical reports generated by Dicle University, Turkey and implemented multi-layered perceptron (MLP), voted perceptron (VP), Clojure classifier (CC), kernel logistic regression (KLR), stochastic gradient decent SGD), adaptive boosting (AdaBoost), Hoeffding tree (VFDT), and primal estimated sub-gradient solver for support vector machine (s-Pegasos). We evaluated the models, compared and tested using paired T-test (corrected) at 0.05 significance based on their respective classification accuracy, f-measure, precision, recall, root mean squared error, receivers characteristic curve (ROC), and precision-recall curve (PRC). Results: In phase-1 SGD, AdaBoost.M1, KLR, MLP, VFDT generates optimal results with the highest possible performance measures. In phase-2, AdaBoost with a classification accuracy of 71.29% outperformed all other algorithms. C-reactive protein, platelet count, duration of symptoms, gender, and pleural protein were found to be the most relevant predictors that can prognosticate mesothelioma. Conclusion: This study confirms that data obtained from biopsy and imagining tests are strong predictors of mesothelioma but are associated with high cost, however, can identify mesothelioma with optimal accuracy. Predictive analytics without using biopsy results can diagnose mesothelioma with acceptable accuracy. Implementation of phase-2 followed by phase-1 can address diagnosis expenses and maximize disease prognosis. Additionally, results indicate improved MPM diagnosis using AI methods dependent upon the specific application.

Background: This study aims to compare the impact of early and late post-discharge cardiopulmonary rehabilitation on the outcomes of intensive care unit (ICU) survivors. Methods: The retrospective, cohort study used a sub-database of the Taiwan National Health Insurance Research Database (NHIRD) that contains information of all patients had ICU admission between 2000 and 2012. Early group was defined if patients had received cardiopulmonary rehabilitation within 30 days after ICU discharge, and late group was define as if patients had received cardiopulmonary rehabilitation between 30 days and one year after ICU discharge. The end points were mortality and re-admission during the 3-year follow-up. Results: Among 2136 patients received cardiopulmonary rehabilitation after ICU discharge, 994 was classified early group and other 1142 patients were classified as late group. Overall, early group had a lower mortality rate (6.64% vs 10.86%, p = 0.0006), and a lower ICU readmission rate (47.8% vs 57.97%, p < 0.0001) than late group after 3-year follow-up. Kaplan-Meier analysis showed that early group had significantly lower mortality (p=0.0009) and readmission rate (p<0.0001) than late group. In multivariate analysis, the risk of ICU readmission was found to be independently associated with late group (HR, 1.28; 95% CI, 1.13-1.47). Conclusions: Early post-discharge cardiopulmonary rehabilitation among ICU survivors has the long-term survival benefit and significantly decreases the readmission rate.

This research paper is mainly aimed to elaborate the initial risk management and measures which government of Pakistan took towards Novel Corona Virus (COVID-2019). This initial response and planning was devised after the early outbreak of COVID-2019 in Wuhan, China in early time of January 2020. Pakistan devised a comprehensive plan that not to evacuate their student from Wuhan, China. The government of Pakistan in compliance with the National Institute of Health (NIH) devised and documented comprehensive plans such as the flight operations postponed related to Umerah pilgrims, which were intended to go to sacred places of KSA (The Kingdom of Saudi Arabia). The process of visa, immigration policy totally changed and the government of Pakistan notified it officially that, no new visas of visit, student, and business would be issued in due course of uncertainty due to COVID-2019. The government of Pakistan also announced medical emergency and notified through the country’s provinces the process of testing and treatment of COVID-2019. The government of Pakistan also allocated funds for medical supplies and named out the particular country’s best laboratories. The government of Pakistan also locked down all the cities with the emergency announcement that people should stay inside the home in quarantine or self-isolation. NIH (The National Institute of Health) played a vital role in executing the planning to cope with COVID – 2019). The National Institute of Health responded as “The Centre for Disease Control”. In aid to the government, the national army of Pakistan responded in a proactive manner towards planed execution. The medical corps of Pakistan army dedicated themselves to treat the suspected patients of COVID – 2019. Due to plans, policies being documented, implemented in such a way productive way that from February 28, 2020 to till date there is not much critical situation and issues are not present. There are much productive results as there is not much boom in a rise of COVID-2019 patients. This lockdown under the authority of the provinces resulted in fruitful outcomes. Background: On January 02, 2020, authorities of the People Republic of China elaborated that they have encountered with a novel type of infectious viral disease 2019. Later on January 12, the authorities from China elaborated the related sequence of Corona Virus diseases 2019 names as COVID – 2019. When COVID-2019 being identified in Wuhan, Hubei China, as an early response the Government of Pakistan in support of the National Institute of Health (Field Epidemiology & Disease Surveillance Division) published a health advisory about novel coronavirus. Methods: According to Global Health Security Index, Pakistan is ranked as 105th country among 195 countries in GHS index. Overall Score of Pakistan is 35.5. The score of Early Detection and Reporting for Epidemics of Potential International Concern is 41.7. A Graphical depiction of the COVID-19 cases placed until April 10, 2020 as well as a graph trend line of recovered as well as death rate is also depicted. According to the graphical facts of Government of Pakistan and World meters, the recovery rate of COVID-19 is about 98 percent and 2.1 percent death rate is reported against the total cases. Trend analysis with line graph was drawn based on available data from official dashboard web portal of the government of Pakistan and worldometers.info. Data figures were incorporated from March to August 18, 2020 in MS Excel and then subsequently deployed to draw trend analysis from managing risk to recovery. Results: The line graph showed a slowdown in the COVID-19 cases and high rate of recoveries from COVID-19 in Pakistan. On March 11, 2020, there were 20 confirmed cases of coronavirus reported in Pakistan. No death was recorded in very first seven days, on March 18, 2020 only two deaths were reported. On August 18, 2020, there were 272128 recoveries, 6201 deaths, total confirmed cases 290445, and total test were 2340072 in Pakistan. As a results, we can report that due to early measures taken by government of Pakistan no mass scale destruction in terms of death and cases been recorded in Pakistan. Conclusions: To till date, the government of Pakistan tried its level best to minimize the coronavirus cases as much as they can. However, the ending of the potential attack of an outbreak would depend upon the well organized and coordinated approach at all levels such as true directed decisions, fully preparedness, as well implementation and evaluation of continuous decisions. As the recovery rate of the cases is 98 percent and merely death rate is 2.1 percent, concluded that in future it would be a good sign to stop the potential outbreak. Also, lock down as well as precautionary measurement taken by the provincial governments resulted a decline number of COVID-19 cases in the country. Another good sign is that merely 4 percent population of Pakistan is of more than 60 years of old it can be concluded that there are less chances of mass death due to outbreak of COVID-19.

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.

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.

It is not plausible to predict disasters; however, still the least that may be done is to get ready for that. In disaster circumstances, nowadays, the existing internet of things (IoT) technology is rather developed and capable of being highly beneficial. For many countries, the early warning system for natural catastrophes is a crucial challenge, especially for high seismic hazard countries. Primary function of an early warning system is to assist individuals and authorities to save lives and reduce secondary damage once a disaster occurs. Even though such systems have been defined for the earthquake on the basis of IoT, the least attention has been focused on the post decisions for substructure monitoring systems which can control the gas and electric lifelines given the critical time. Combination of Fuzzy system with IoT can improve the decision making process after the disasters occur. This program minimizes costs and destruction in cities. Tehran is a high seismic hazard area which contains an expanded network of the gas transmission system. Hence, a major seismic event may cause serious loss directly and indirectly owing to the damage to the gas and electric transmission network. The proposed early warning system contains a grid of strong ground motion stations. Each station contains five sensors to collect accurate data and send the data to the cloud server, then the server executes relevant scenarios.

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.

(1) Background: Neonatal early-onset sepsis (EOS) is associated with important mortality and morbidity. The aims of this study were to evaluate the association between serum biomarkers with early onset neonatal sepsis in a cohort of patients with prolonged rupture of membranes (PROM), and to calculate their diagnostic accuracy. (2) Methods: A retrospective cohort study was conducted on 1355 newborns with PROM admitted between January 2017 and March 2020, who were divided in two groups: group A, with PROM ≥ 18 hours and group B, with PROM < 18 hours. Both groups were further split into subgroups: proven sepsis, probable sepsis and no sepsis. Descriptive statistics, ANOVA analysis, and a Random Effects Generalized Least Squares (GLS) regression were used to evaluate the data. (3) Results: The statistically significant predictors of neonatal sepsis were the high white blood cells count from the first (p = 0.005) and third day (p = 0.028), and high CRP values from the first day (p = 0.004). Procalcitonin (area under the curve - AUC = 0.78) and CRP (AUC = 0.76) measured on the first day had the best predictive performance for early onset neonatal sepsis. (4) Conclusions: Further studies are needed to explore other bi-omarkers of sepsis in both pregnant women and newborns to better predict EOS.

Seemingly normal tissues progressively become populated by mutant clones over time. Most of these clones bear mutations in well-known cancer genes but only rarely do they transform into cancer. This poses questions on what triggers cancer initiation and what implications somatic variation has for cancer early detection. We analysed recent mutational screens of healthy and cancer-free diseased tissues to compare somatic drivers and the causes of somatic variation across tissues. We then reviewed the mechanisms of clonal expansion and their relationships with age and diseases other than cancer. We finally discussed the relevance of somatic variation for cancer initiation and how it can help or hinder cancer detection and prevention. The extent of somatic variation is highly variable across tissues and depends on intrinsic features, such as tissue architecture and turnover, as well as the exposure to endogenous and exogenous insults. Most somatic mutations driving clone expansion are tissue-specific and inactivate tumour suppressor genes involved in chromatin modification and cell growth signalling. Some of these genes are more frequently mutated in normal tissues than cancer, indicating a context-dependent cancer promoting or protective role. Mutant clones can persist over a long time or disappear rapidly, suggesting that their fitness depends on the dynamic equilibrium with the environment. The disruption of this equilibrium is likely responsible for their transformation into malignant clones and knowing what triggers this process is key for cancer prevention and early detection. Somatic variation should be considered in liquid biopsy, where it may contribute cancer-independent mutations, and in the identification of cancer drivers, since not all mutated genes favouring clonal expansion also drive tumourigenesis. Somatic variation and the factors governing homeostasis of normal tissues should be taken into account when devising strategies for cancer prevention and early detection.

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.

Complete pathologic response (pCR) predicts the long-term outcome of neoadjuvant treated (NAC) breast cancer (BC) but is reached in <10% of hormone-receptor-positive patients. Biomarkers able to guide adjustment or interruption of an ineffective therapy are desired. Here, we evaluated whether shifts in the serum concentration of thymidine kinase 1 (sTK1) during NAC could be utilized as a biomarker. In the PROMIX trial, women with localized HER2- BC received neoadjuvant epirubicin/docetaxel in six cycles. sTK1 was measured with an ELISA in 54 patients at cycles 1-4 and in a total of 131 patients before and 48h after cycle 1. The prognostic significance of the results was evaluated by log-rank tests of Kaplan–Meier estimates. Treatment resulted in a 2-fold increase of sTK1 before and 3-fold increase 48h after the cycles, except for the first cycle, where half of patients reacted with a decrease (post/pre sTK1- ratio <1.12) and the other half reacted with an increase (ratio >1.12). OS rates in ER+ patients with ratios of >1.12 and <1.12 were 97.7% and 78% (p=0.005), respectively, and DFS rates were 90.7% and 68% (p=0.006), respectively. Thus, response of sTK1 at the first cycle of chemotherapy could be used both as an early biomarker for guidance of chemotherapy and for the study of inherent tumor chemo-sensitivity, which could predict long-term outcome prior to therapy.

Growth-preserving instrumentation techniques are utilized in early-onset scoliosis (EOS) cases requiring surgical intervention. Shilla technique corrects the deformity and may reduce the need for surgical treatment with its growth-directing effect. As with other techniques, various prob-lems can be encountered following the administration of the Shilla technique. The aim of this study was to examine the effect of complications encountered with Shilla treatment on correction and growth. Sixteen patients with a follow-up period of at least 1 year who received Shilla growth guidance for EOS were included in the study. No complications occurred in 50% cases and no unplanned surgery was required. Of the remaining 8 patients with postoperative im-plant-related complications (50%), 6 (37.5%) required unplanned surgery; this consequently caused implant failure in the proximal region in 5 cases (31.25%) and deep tissue infection around the implant in 1 case (6.25%). Deformity correction, spine length, and quality-of-life scores significantly improved in EOS through Shilla growth guidance. Although implant-related com-plications were observed and related unplanned surgeries were required with Shilla growth guidance in our patients, these complications did not have a significant negative effect on correc-tion and spine growth.

The survival rates of women with stage 0 or 1 breast cancer stands at almost 100% and around 93% for stage 2. As the disease advances with decreasing survival, the rate detoriates to 72% for stage 3 and about 22% for stage 4 (ACS, 2018). Undoubtedly, earlier presentation is synonymous with better prognosis and survival. In fact data indicates that early stage breast cancer diagnoses has 90% survival rate as compared to 27% for the advanced states (ACS, 2018). In this regard, governmental and non-governmental agencies are working tirelessly towards the realization of improved breast cancer care and survival through early presentation and detection. For instance, the Sustainable Development Goal (SDG) Target 3.4 seeks to reduce by one third, premature mortality from cancers and other non-communicable diseases through prevention and treatment. Clearly, early presentation, diagnoses and treatment will assist in the realization of the SDG target 3.4 goal. To achieve this, research must be focused on early presentation among women with breast cancer.. However, current studies have focused mainly on advanced breast cancer regarding treatment, symptoms experience (emotional and psychological), coping and support systems, and the reasons for delayed diagnoses and treatment. Objective In this review, it is argued that, rather than focusing on advanced breast cancer which has been adequately explored, the attention has to be on what measures or approaches promote early presentations among Ghanaian women. Methods The review included all primary studies that provided answers to the phenomenon of interest. It included both quantitative and qualitative studies. Search scope encompassed studies within the last ten years; thus from 2010 to 2020 irrespective of the country of study.Studies were included if: The paper is of a primary study; the study population included women with early BC or BC symptoms; the study outcome is the association between early stage breast cancer and earlier presentation; the study has a comprehensive data analysis protocol; the results of the studies are unique.A thorough literature search was conducted using the following electronic database: Google scholar and Pubmed. Google scholar alert on new studies was subscribed. This gave update on newly published papers for appraisal and possible inclusion.Manual identified of other potentially eligible publications by searching the reference lists of retrieved studies was also done. After a thorough search, this review included studies from several countries around the Globe such as Ireland, London, Turkey, Iran, Ghana, Kenya, Ethiopia etc Data Collection The title and or abstract of all retrieved papers were independently scanned through to establish which studies should be further evaluated. The full texts of these potential articles were then assessed. Extraction The Cochrane extraction form for data extraction was resorted to. From each eligible article, the following study identifiers/information were extracted: author(s), first author, year, title, objective, article type, location, setting, study design and method, sample size, instruments used, and results. Results Prompt help seekers mainly self-discovered their BC, and this occurred through accidental touch, after menstruation, through breastfeeding, during grooming, and while taking their bath.Notably, women who were termed prompt help seekers had higher seriousness perception of their symptoms. This was likened to their level of understanding and awareness, as well as periodic examination and comparison. Similarly, women who knew they were at risk for breast on account of family history, and increased incidence of BC in their localities, labeled their initial symptoms as requiring prompt attention.Following interpretation and labeling of symptoms, the participants generally resorted to symptom monitoring until the onset of additional and or intense symptoms. Though most women thought of benign growths, a few feared it could be malignant. These emotional reactions led the women to purposively seek clarification by selectively consulting others. Further, participants opened up to social acquaintances such as family relationships, people with prior experience of breast disease, and in some few instances health professionals. Some women also resorted to media items to better their understanding. Remarkably, prompt help seekers sort for help within one month. Last but not least, some women first communed with their creator after discovery and labeling based on their spiritual affiliations.Also, researchers should consider conducting surveys to assess the BC risks for specific smaller groups. This would help tailor specific educational interventions to promote earlier presentation and treatment among the vulnerable.

Background: Ankle fractures, comprising about 10% of musculoskeletal injuries, pose a significant healthcare burden with an increasing incidence, particularly among an aging population. This study focuses on isolated Danis-Weber type B fractures. Recent trends lean towards surgical intervention for anatomical restoration, quicker recovery, albeit with associated complications. This report aims to assess the safety and efficacy of NewClip narrow locking plate system with early weight bearing in treating isolated fibular fractures. Methods: The study includes patients with Danis-Weber type B fractures surgically treated with NewClip narrow locking plate system. Exclusions involved nondisplaced fractures, open fractures, or those requiring additional fixation.Results: Fifteen patients were enrolled in this study. Minor complications, including wound swelling, were observed in two cases. The Visual Analogue Scale (VAS) for pain exhibited a steady decline postoperatively, with almost complete resolution by the third month. At three months, the FAOS demonstrated excellent results, and final follow-up at twelve months revealed complete osseous healing without complications.Conclusions: The use of this type of plates in treating isolated fibular fractures with early weight bearing shows promising results in terms of fracture healing, pain resolution, and functional outcomes warranting further investigation with larger cohorts.

It has been suggested that primordial planets could have formed in the early Universe and the missing baryons in the Universe could be explained by primordial free-floating planets of solid hydrogen. Many such planets were recently discovered around the old and metal poor stars and such planets could have formed at early epochs. Another possibility for missing baryons in the Universe could be that these baryons are admixed with DM particles inside the primordial planets. Here we discuss the possibility of admixture of baryons to the DM primordial planets discussed earlier. We consider gravitationally bound DM objects with the DM particles constituting them varying in mass from 20 to100GeV. Different fractions of DM particles mixed with baryonic matter in forming the primordial planets are discussed. For the different mass range of DM particles forming DM planets, we have estimated the radius and density of these planets with different fractions of DM and baryonic particles. It is found that for heavier mass DM particles with the admixture of certain fractions of baryonic particles, the mass of the planet increases and can reach or even substantially exceed Jupiter-mass. The energy released during the process of merger of such primordial planets is discussed. Also the energy required for the tidal breakup of such an object in the vicinity of a black hole is also discussed.

The application of movement-detection sensors is crucial for understanding surface movement and tectonic activities. The development of modern sensors has been instrumental in earthquake monitoring, prediction, early warning, emergency commanding and communication, search and rescue, and life detection. There are numerous sensors currently being utilized in earthquake engineering and science. It is essential to review their mechanisms and working principles thoroughly. Hence, we have attempted to review the development and application of these sensors by classifying them based on the timeline of earthquakes, physical or chemical mechanisms of sensors, and location of sensor platforms. In this study, we analyzed all available sensor platforms that have been widely used in recent years, with satellites and UAVs being among the most used. The findings of our study will be useful for future earthquake response and relief efforts, as well as research aimed at reducing earthquake disaster risks.

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.

Background: Early-stage interventions in a potential pandemic are important tounderstand as they can make the difference between runaway exponential growththat is hard to turn back and stopping the spread before it gets that far. COVID-19 is an interesting case study because there have been very different outcomesin different localities. These variations are best studied after the fact if precisionis the goal; while a pandemic is still unfolding less precise analysis is of value inattempting to guide localities in the early stages to learn lessons of those that pre-ceded them. Methods: I examine three factors that could differentiate strategy: asymptomaticspread, differences in use of the Bacillus Calmette-Guerin (BCG) tuberculosis vac-cine and cloth face masks.Results:Differences in disease progression as well as the possibility of alternativestrategies to prevent COVID-19 from entering the runaway phase or damping itdown later can be elucidated by a study of asymptomatic infection. A study todemonstrate not only what fraction are asymptomatic but how contagious they arewill also inform policy on universal mask wearing. Conclusions: While a COVID-19 outbreak is at a level that makes accurate trace-and test possible, investigation of asymptomatic transmission is viable and shouldbe attempted to enhance understanding of spread and variability in the disease aswell as policy options for slowing the spread.

.Bacground: Sepsis remains a major health challenge worldwide, characterized by a dysre-gulated host response to infection, leading to high mortality and morbidity in intensive care units (ICUs). The Fibrosis 4 (FIB-4) index, originally developed to assess liver fibrosis in hepatitis C patients, has recently been explored for its potential prognostic value in sepsis patients. Method: This study retrospectively analyzed 309 sepsis patients admitted to the Internal Me-dicine and Anaesthesia ICUs between December 12, 2021, and December 15, 2023, to inves-tigate the relationship between FIB-4 levels, Acute Physiology and Chronic Health Evaluation (APACHE), and Sequential Organ Failure Assessment (SOFA) and clinical outcomes. Results: The study found that higher FIB-4 measurements were statistically significantly asso-ciated with increased 28-day mortality, with a cut-off value of 4.9 providing a sensitivity of 54.92% and specificity of 74.25%. Logistic regression analysis indicated that elevated Conclusion:FIB-4 levels were a significant predictor of early mortality, suggesting that the FIB-4 index could serve as a valuable prognostic tool in assessing the severity and prognosis of sepsis patients.

Background: Colorectal adenoma undergoes neoplastic progression via the normal epithelium-adenoma-adenocarcinoma sequence as reported in the Vogelgram. The risk of developing cancer is strongly associated with the number and size of adenoma and with the subtype. Currently, adenomatous polyps can be distinguished on the basis of histology: the prevalence are tubular, 5-15% are villous and tubular/villous. Considering the increased risk for malignant transformation described for tubular/villous adenomas, patients diagnosed with adenomatous polyposis are at increased risk of developing CRC. The Wnt/β-catenin pathway plays a key role in the onset of colorectal adenoma, in particular intestinal cells first acquire loss-of-function mutations in APC gene that induce the formation of adenomas. Methods: Wnt/β-catenin pathway APC, Wnt3a, Wnt5a, LEF1, BCL9 genes and protein expression analyses were conducted by qRT-PCR and western blot in 68 colonic samples (polyps and adjacent mucosa) from 41 patients, of which 17 affected by FAP. Ten normal colonic mucosal samples were collected from 10 healthy donors. Results: In this study both APC gene and protein resulted less expressed in colon tumor compared to the adjacent colonic mucosa. Conversely, activated β-catenin was more expressed in polyps than in the adjacent mucosa. All results confirmed literature data on carcinomas. A statistically significant correlation between Wnt3a and BCL9 both in polyps and in the adjacent mucosa underlies that the canonical Wnt pathway is activated in early colon carcinogenesis and that the adjacent mucosa is already altered. Conclusion: This is the first study analyzing the difference in expression of Wnt/β-catenin pathway in human colorectal adenomas. Understanding the progression from adenomas to colorectal carcinomas is essential for the development of new therapeutic strategies and improving clinical outcomes.

Background: Early rehabilitation is an important strategy for the treatment of severe diseases. The study aimed to assess the efficacy of early rehabilitation of patients with mild-to-moderate COVID-19. Methods: The retrospective single-center study with propensity score matching. Results: 180 patients (54 (44 - 62.3) yo) divided into three equal groups: 1 - physical exercises; 2 - physical exercises and chest massage in an electrostatic field; 3 - no rehabilitation. The length of stay (LOS) in the hospital in group 1 was 14 (11-15) days, group 2 - 13 (11-15) days, group 3 - 15 (13-18) days, p=0.0026. Physical exercises for patients with CT-1 improved the quality of life, assessed by the EQ-5D questionnaire, by reducing the level of anxiety and depression. The Hazard Ratio (HR) for desaturation (<93%) was 2.34 (95% Confidence Interval (CI) 1.18-4.63) for group 2, p=0.001. The HR for C-reactive protein level above 50 mg/l in patients with CT-2 was 2.33 (95% CI 1.56-3.47), p=0.0001. Conclusions: Rehabilitation programs are safe for СOVID-19-patients; reduce hospital LOS; improve the quality of life. Continuous monitoring of a patient's condition during rehabilitation is essential. ClinicalTrials.gov ID: NCT0580836

Chronological frameworks based on artefact typologies are essential for interpreting the archaeological record, but they inadvertently treat transitions between phases as abrupt events and disregard the temporality of transformation processes within and between individual phases. This study presents an absolute chronological investigation of a dynamic material culture from Early Iron Age urnfields in Denmark. The chronological framework of Early Iron Age in Southern Scandinavia is largely unconstrained by absolute dating, primarily due to it coinciding with the so-called ‘Hallstatt calibration plateau’ (c.750 to 400 cal BC), and it is difficult to correlate it with Central European chronologies due to a lack of imported artefacts. This study applies recent methodological advances in radiocarbon dating and Bayesian chronological modelling, specifically a statistical model for wood-age offsets in cremated bone and presents the first large-scale radiocarbon investigation of regional material culture from Early Iron Age in Southern Jutland, Denmark. Dated material is primarily cremated bone from 111 cremation burials from three urnfields. The study presents absolute date ranges for 16 types of pottery and 15 types of metalwork, which include most of the recognised metalwork types from the period. This provides new insights into gradual change in material culture, when certain artefact types were in production and primary use, how quickly types were taken up and later abandoned, and distinguishing periods of faster and slower change. The study also provides the first absolute chronology for the period, enabling correlation with chronologies from other regions. Urnfields were introduced at the Bronze-Iron Age transformation, which is often assumed to have occurred c.530-500 BC. We demonstrate that this transformation took place in the 7^th century BC, however, which revives the discussion of whether the final Bronze Age period VI should be interpreted as a transitional phase to the Iron Age.

Rationale. A biomaterial is proposed for closing extensive bone defects in the maxillofacial region. The composition of the biomaterial includes high molecular weight chitosan, chondroitin sulfate, hyaluronate, heparin, alginate and inorganic nanostructured hydroxyapatite. The purpose of the study is to demonstrate morphological and histological early signs of reconstruction of a bone cavity of a critical size. Materials and methods. The studies were carried out on 84 white female rats weighing 200 g. The control group of animals consisted of 44 individuals, the study group - 40. In all animals, three-walled bone defects 0.5 cm in size were applied subperiosteally in the region of the angle of the lower jaw and filled in the experimental group with a gel mass of chitosan -alginate-hydroxyapatite (CH-SA-HA). In control animals, the bone cavities were filled with an auto-blood clot. The follow-up periods were 3.5.7 days, 2.3.4.6.8 and 10 weeks. Results. The chitosan construct after implantation actively replaced defects early with the formation of a full-fledged new bone tissue compared to control animals. Morphological analysis of the walls of the bone defect on the 7th day showed signs of the formation of spongy bone tissue, after two weeks - a pronounced increase in bone volume (P<0.01), after 6 weeks after surgery, the closure of the defect was 70-80%, after 8 weeks - 100% without disturbing bone morphology with a high degree of mineralization. Conclusion The use of modified chitosan after filling eliminates bone defects of critical size in the maxillofacial region, reveals early signs of bone neoformation, and serves as a promising material in reconstructive dentistry.

The review aims to examine how well numerical indicators of business bankruptcy can predict outcomes. The paper examines ten critical studies that concentrate on statistical models for bankruptcy predictions utilizing PRISMA criteria. The findings highlight the usefulness of numerical indicators in indicating financial hardship, particularly cash flow ratios. In order to connect theoretical knowledge with real-world corporate strategy applications, the study ends by reaffirming the importance of these indicators in strategic decision-making.

Fragility scales are intended to help in therapeutic decisions. Here we asked if the fragility as-sessment in MM patients ≥75 years old qualified for treatment by the local physician correlates with the choice of treatment: a 2- or 3-drug regimen. Between 7/2018 to 12/2019 we prospectively enrolled 197 MM patients at the start of treatment from the 13 Polish Myeloma Group centers. The data to assess fragility were prospectively collected, but centrally assessed fragility was not disclosed to the local center. The activity of daily living (ADL) could be assessed in 192 (97.5%) and was independent in 158 (80.2%), moderately impaired in 23 (11.7%), and 11 (5.6%) in com-pletely dependent. Patients with more than 3 comorbidities were 26.9% (53 patients). Thus, ac-cording to the Palumbo calculator, 43 patients were in the intermediate-fitness group (21.8%), and the rest belonged to the frailty group (153, 77.7%). Overall, 79.7% of patients (157) received 3-drug regimens and 20.3% (40) received 2-drug regimens. In each ECOG group, more than 3/4 of patients received 3-drug regimens. According to the ADL scale, 82.3% of the independent 65.2% of moderately impaired, and 81.8% of the dependent received 3-drug regimens. Out of 53 pa-tients with at least 4 comorbidities, 71.7% received 3-drug regimens, and the rest 2-drug regi-mens. Three-drugs regimens received 34 patients from the intermediate-fit group (79.0%), and 123 (79.9%) from the frail group. Early mortality occurred in 25 patients (12.7%). No one discon-tinued treatment due to toxicity. To conclude, MM patients over 75 are mainly treated with tri-ple-drug regimens, not only in reduced doses, regardless of their frailty scores. However, the absence of prospective fragility assessment did not negatively affect early mortality and the number of treatment discontinuations which questions the clinical utility of current fragility scales in everyday practice.

The coronavirus disease 2019 (COVID-19) has spread over the world for more than one year. COVID-19 often develops life-threatening hypoxemia. Endothelial injury caused by the viral infection leads to intravascular coagulation and ventilation-perfusion mismatch. However, besides above pathogenic mechanisms, the role of alveolar edema in the disease progression has not been discussed comprehensively. Since the exudation of pulmonary edema fluid was extremely serious in COVID-19 patients, we bring out a hypothesis that severity of alveolar edema may determine the size of poorly-ventilated area and the blood oxygen content. Treatments to pulmonary edema (alcohol-oxygen vapor therapy and fluid management) may be great helpful for reducing occurrence of severe cases. Given that late mechanical ventilation may cause mucus (edema fluid) to be blown to the deep of the small airways, oxygen therapy should be given at the early stages. The optimal time and SpO₂ threshold for oxygen therapy are also discussed.

Gastric cancer (GC) is a major cause of cancer-related mortality worldwide, often associated with a bad prognosis because of its asymptomatic phenotype until advanced stages, highlighting the need for its prevention and early detection. GC development is preceded by gastric preneoplasia lesions (GPNL), namely atrophic gastritis (AG), intestinal metaplasia (IM), and dysplasia (DYS). GC is currently diagnosed by endoscopy, which is invasive and costly and has limited effectiveness for the detection of GPNL. Therefore, the discovery of non-invasive biomarkers in liquid biopsies, such as blood samples, to identify the presence of gastric preneoplasia and/or cancer lesions at an asymptomatic stage, is of paramount interest. This comprehensive review provides an overview of plasma/serum proteins recently identified and their diagnostic performance for the prediction of GPNL and early cancer lesions. Autoantibodies appear as promising biomarkers for AG, IM and early gastric cancer detection, along with inflammation and immunity-related proteins and antibodies against H. pylori virulence factors. There is a lack of specific protein biomarkers to detect DYS. Despite the need for further investigation and validation, some emerging candidates could pave the way to develop reliable, non-invasive diagnostic tests for the detection and prevention of GC.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a single stranded RNA virus which has resulted in the Coronavirus Disease 2019 (COVID-19) pandemic and has infected millions of people all over the world. SARS-CoV-2 has been mutating rapidly resulting in the emergence of multiple variants to escape the host immune system mainly by mutations in its receptor binding domain (RBD) of the spike protein. This rapid evolution of the SARS-CoV-2 posed a great challenge regarding the efficacy and effectiveness of the current SARS-CoV-2 vaccines. The RBD and full-length spike of SARS-CoV-2 is the main target of the neutralizing antibodies. Many SARS-CoV-2 variants are considered to have the potential to escape from the host immune system. In this study, the RBD of Alpha, Beta, Gamma, Kappa and Omicron and the full-length spike of BA.1, BA.2, BA.3, BA.4/5, BQ.1.1 and XBB.1.5 Omicron variants were used as coating antigens in Enzyme Linked Immuno-Sorbent Assay (ELISA) to check the neutralization capability of COVID-19 convalescent sera from patients of first wave of infection occurring in Wuhan. Our results show that the currently circulating Omicron BQ.1.1, XBB.1.5 and previous Omicron BA.1, BA.2 and BA.4/5 do not show significant reduction in neutralization, while Omicron BA.3 and previous variants Alpha, Beta, Gamma, Kappa, and Omicron showed a significantly reduced neutralization when compared to the wild-type Wuhan strain. These results indicate patients recovering from natural infection of early original Wuhan strain may have the potential to resist infection of current circulating variants and the vaccines using the prototype antigen may still working for newly emerged variants.

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.

Food allergy (FA) affects approximately 6–8% of children worldwide causing a significant impact on the quality of life of children and their families. In the years, the possible role of weaning in the development of FA has been studied. According to recent studies, the role of weaning in its development is still controversial and influenced by several factors, such as the type of food, the age at food introduction and family history. In this narrative review, we aimed to collected the most recent evidence about weaning and its role in FA development, organizing the gathered data based on both the type of study and the food.

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 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.

The first 1000 days of life is a critical period that contributes significantly to the programming of an individual's future health. Among the many changes that occur during this period, there is growing evidence that the establishment of a healthy gut microbiota early in life plays an important role in the prevention of both short- and long-term health problems. Numerous publications suggest that the quality of gut microbiota colonization depends on several dietary factors, including breastfeeding. In this respect, a relationship between breastfeeding and the risk of inflammatory bowel disease (IBD) has been suggested. IBD are chronic intestinal diseases in which perinatal factors may be partly responsible for its onset. We propose to review the existence of links between breastfeeding and IBD, based on experimental and clinical studies. Overall, despite encouraging experimental data in rodents, the association between breastfeeding and the development of IBD remains controversial in humans, partly due to considerable heterogeneity between clinical studies. The duration of exclusive breastfeeding is probably decisive for its lasting effect on IBD. Thus, specific improvements in our knowledge could support dietary interventions targeting the gut microbiome, such as the early use of prebiotics, probiotics or postbiotics in order to prevent the disease.

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

Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions could change across the health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 heat wave definitions associated with HRI emergency department visits over five summer seasons (2011-2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the heat wave definitions to identify an optimal heat wave definition. In the Coastal region, heat wave definition based on daily maximum temperature with a threshold >90^th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, heat wave definition based on the daily minimum temperature with a threshold value >90^th percentile for two or more consecutive days was optimal. Additionally, we observed that the optimal heat wave definitions from this study captured moderate and frequent heat episodes than the national weather service (NWS) heat products that worked best for extreme heat episodes. This study compared the HRI morbidity risk associated with epidemiologic-based heat wave definitions and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products.

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.

Increasing evidence suggests that prenatal exposure to opioids can adversely influence brain development, yet, limited data exists on the effects of opioid-exposure on preschool language development. Our study aimed to characterize the nature and prevalence of language problems in children prenatally exposed to opioids, and the factors that support or hinder language acquisition. A sample of 100 children born to pregnant women in methadone maintenance treatment and 110 randomly identified non-exposed children were studied from birth to age 4.5 years. At 4.5 years, 89 opioid-exposed and 103 non-exposed children completed the preschool version of the Clinical Evaluation of Language Fundamentals (CELF-P) as part of a comprehensive neurodevelopmental assessment. Children prenatally exposed to opioid had poorer receptive and expressive language outcomes at age 4.5 years compared to non-exposed children. After adjustment for child sex, maternal education, other pregnancy substance use, maternal pregnancy nutrition and prenatal depression, opioid exposure remained a significant independent predictor of children’s total CELF-P language score. Examination of a range of potential intervening factors showed that a composite measure of the quality of parenting and home environment at 18 months and early childhood education participation at 4.5 years were important positive mediators.

The aim of this article is to analyze the evidence against the effectiveness of intervention programs based on the participation of parents of children with autism. To obtain the data, a systematic search was carried out in four databases (ProQuest-PsychArticles, ProQuest-ERIC, ProQuest-PubMed, and Scopus). These documents were refined under the inclusion/exclusion criteria and a total of 51 empirical studies were selected. They were classified, first, according to the function of the intervention objective and, later, by the methodology applied (19 studies based on comprehensive interventions, 11 focused on the nuclear symptoms of ASD, 12 focused on the promotion of positive parenting and 9 interactions focused on children play). Once all the documents have been analyzed, the evidence indicates scientific efficacy in most studies, mainly in those based on child development and the application of behavioral analysis principles. Also, the positive influence of parent participation in such programs was demonstrated.

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.

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.

The assessment of welfare and disease progression in animal models is critical. Most tools rely on evaluating individual subjects, whereas social behaviors, also sensitive to acute illness, chronic diseases, or mental health, are scarcely monitored because of their complexity, are invasive, and time-consuming. We propose the evaluation of social nesting, a species-typical behavior naturally occurring in standard housing conditions, for such behavioral monitoring. We provide an example of its use to evaluate social deficits and the long-term effects of neonatal sensorial stimulation in male and female adult 3xTg-AD mice for Alzheimer's disease compared to sex- and age-matched NTg counterparts with normal aging. Social nesting was sensitive to genotype (worse in 3xTg-AD mice), sex (worse in males), profile, and treatment (distinct temporal patterns, time to observe the maximum score and incidence of the perfect nest). Since social nesting can be easily included in housing routines, this neuroethological approach can be useful for animal's welfare, monitoring the disease's progress, and evaluating potential risk factors and effects of preventive/therapeutical strategies. Finally, the non-invasive, painless, simple, short time and low-cost features of this home-cage monitoring are advantages that make social nesting feasible to be successfully implemented in most animal department settings.

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.

(1) Background: Motor neuron diseases (MNDs) are fatal neurodegenerative diseases. Biomarkers could help in defining patients’ prognosis and stratification. Beyond neurofilaments, chitinases are a promising family of possible biomarker, which correlate with neuroinflammatory status. We evaluated plasmatic levels of CHI3L1 in MNDs, MND mimics and healthy controls (HCs); (2) Methods: We used Sandwich ELISA to quantify CHI3L1 in plasma samples from 44 MNDs, 7 HSP, 9 MND mimics and 19 HCs. We collect also ALSFRSr scale, MRC scale, spirometry, mutational status, progression rate (PR), blood sampling, neuropsychological evaluation; (3) Results: Plasma levels of CHI3L1 resulted to be different among groups (p= 0.005). Particularly, MND mimics showed higher CHI3L1 levels compared to MNDs and HCs. CHI3LI levels did not differ among PMA, PLS and ALS and we do not find correlation among CHI3L1 levels and clinical scores, spirometry parameters, PR, and neuropsychological features. Of note, red blood cells count and haemoglobin correlated with CHI3L1 levels (respectively, p&lt;0.001, r=0.63; p= 0.022, r=0.52); (4) Conclusions: CHI3L1 plasma levels resulted to be increased in the MND mimics cohort when compared to MNDs. The increase of CHI3L1 in neuroinflammatory processes could explain our findings. We confirmed that CHI3L1 plasma levels did not differentiate between ALS and HCs and nor correlate with neuropsychological impairment.

Stroke is a global leading cause of death and disability. Knowledge of related guidelines is crucial for Emergency Department (ED) staff, influencing early diagnosis and timely treatment. We investigated Greek-Cypriot ED healthcare professionals' (nurses and physicians) knowledge in recognizing and managing stroke. A descriptive cross-sectional study spanned November 2019 to April 2020, encompassing four private and seven public EDs in the Republic of Cyprus. The data were collected through a self-reported questionnaire developed by the research team, consisting of 37 questions. Eight questions focused on sociodemographic and employment characteristics, 28 assessed knowledge in stroke recognition and management (each item was equally weighted without deliberate prioritization), and one question addressed self-assessment of knowledge in stroke care. 255 nurses [Response Rate (RR): 74.1%] and 26 physicians (RR: 47.3%) completed the questionnaire. The average correct response rate was 12.9 out of 28 statements (SD: 4.2), with nurses and physicians scoring 12.6 (SD: 4.1) and 15.7 (SD: 4), respectively. Work experience significantly influenced stroke knowledge, with all groups demonstrating superiority over those with less than one year of experience. Participants with previous training scored an average of 1.45 additional correct answers while educational attainment did not significantly influence stroke knowledge. Investigating stroke knowledge among Emergency Department nurses and physicians in the Republic of Cyprus revealed significant deficits. The study stresses targeted interventions, including, education, yearly examinations, workshops with hands-on training, and repeated training, to address these gaps and enhance the overall stroke care capabilities of the healthcare professionals.

Intrinsic disorder accounts for the flexibility of protein loops, molecular building blocks that are largely responsible for the processes and molecular functions of the living world. While loops likely represent early structural forms that served as intermediates in the emergence of protein structural domains, their origin and evolution remains poorly understood. Here, we conduct a phylogenomic survey of disorder in loop prototypes sourced from the ArchDB classification. Tracing prototypes associated with protein fold families along an evolutionary chronology revealed ancient prototypes tended to be more disordered than their derived counterparts, with ordered prototypes developing later in evolution. This highlights the central evolutionary role of disorder and flexibility. While mean disorder increased with time, a minority of ordered prototypes exist that emerged early in evolutionary history, possibly driven by the need to preserve specific molecular functions. We also revealed percolation of evolutionary constraints from higher to lower levels of organization. Percolation resulted in trade-offs between flexibility and rigidity that impacted prototype structure and geometry. Our findings provide a deep evolutionary view of the link between structure, disorder, flexibility and function, as well as insights into the evolutionary role of intrinsic disorder in loops and their contribution to protein structure and function.

Oiola archeological site, located in the mining complex of La Arboleda (Biscay, North Spain) was an important iron smelting center from the Roman Period to the Early Middle Ages and even in more current times (19th-20th centuries). Tap-slags and some plano-convex slags were identified as smelting slags. Samples were analyzed by optical microscopy, X-ray powder diffraction, scanning electron microscopy coupled with electron-dispersive spectroscopy and Raman microspectroscopy to perform a mineralogical and textural characterization. Additionally, thermogravimetric and thermodiffraction analyses were carried out to determine furnace operating temperatures. The mineral assemblage reflects furnace cooling rates and temperatures and the addition of quartz as the main flux to decrease the melting temperature of the iron ore. The comparison of slags from the Roman Period and the Early Middle Age allows to observe changes in the pyrometallurgical process through time.

The work is devoted to the search for effective solutions to the applied problem of early diagnostics of plant stress in the conditions of smart farming and based on modern explicable artificial intelligence (XAI). The study mostly oriented on the theory and practice of XAI, focused on the use of hyperspectral imagery (HSI) and Thermal Infra-Red (TIR) sensor data at the input of a neural network. The first our goal is to build an XAI neural network, explainable due to its structure, the input of which is a datascientist oriented HSI 'explanator', and the output is a biologist oriented TIR 'explanator'. In the middle is SLP-regressor which solves the universal problem of training HSI pixels to temperatures of plants, needed for early plant stress diagnostic. The result can be considered as prototype of a special XAI explanator which is assigned to transform explanator specialized on area 1 onto explanator specialized on area 2. Using this HSI-TIR explanator we ensured the follows: extend HSI data by TIR attribute; providing TIR data for early diagnostic of plant stress; reducing dimensionality HSI needed for TIR training 25 times (from 204 to 8) preserving the same accuracy of temperature prediction (RMSE=0.2-0.3C). This reducing was achieved without using PCA methods. The constructed model is computationally efficient in training: the average training time is significantly less then 1 min (Intel Core i3-8130U, 2.2 GHz, 4 cores, 4 GB). One of the 8 channels, 820 nm, is the leader in correlation with TIR, what allows building local linear temperature prediction functions.

The cultivation of Hevea brasiliensis, the primary commercial source of natural rubber, is strongly impacted by South American Leaf Blight (SALB) disease, caused by the fungus Pseudocercospora ulei. Various management strategies have been implemented, including the selection of resistant genotypes and the identification of escape zones. This study evaluated the growth, early yield, and resistance to SALB of nine Colombian elite genotypes from the ECC-100 series and IAN 873 clone (control) in a large-scale clone trial in a low SALB pressure zone in the Colombian Amazon, 2017 - 2020. Favorable early performance was evident, although there was a significant increase in the severity and sporulation of P. ulei over time, especially in the ECC 35, ECC 60, and IAN 873 genotypes. However, these scores represented a low susceptibility. Genotypes with higher resistance to SALB demonstrated greater growth and early yield compared to higher susceptible genotypes. The ECC 64, ECC 73, ECC 90, ECC 25, and ECC 29 genotypes were more desirable in low SALB pressure zones due to their higher resistance and early performance. It is important to highlight that this research contributes to the selection of new SALB-resistant Colombian genotypes of H. brasiliensis in the growth stage. Therefore, it is necessary to evaluate their productivity in the mature stage and long-term resistance to SALB, before recommending and promoting their commercial adoption in the Colombian Amazon.

Objectives: To develop a multivariate model for risk factors specific to early onset preeclampsia (EOP) and late onset preeclampsia (LOP) in our entire population (singleton and twin pregnancies). Material and methods: 20 year-observational population-based historical cohort study (2001-2020). All consecutive births delivered at the Centre Hospitalier Universitaire Hospitalier Sud Reunion’s maternity. A standardized validated epidemiological perinatal data base. Results: During the 20-year period, there were 81,834 pregnancies and 83,555 infants born, 1232 dichorionic and 350 monochorionic twin pregnancies. There were 2120 cases of preeclampsia, of which 2001preeclamptic singleton pregnancies and 119 twin pregnancies (incidence 7.5% in twin pregnancies vs 2.5% singletons, OR 3.0, p<0.001). Independent risk factors for EOP and LOP in a multivariate model (controlling for the two major confounders: namely maternal ages -both risks for EOP and LOP- and maternal pre-pregnancy BMI – specific risk factor for LOP) were: history of preeclampsia (aOR 11.7 for EOP, 7.8 for LOP, p < 0.0001), chronic hypertension (aOR 7.3 for EOP, 3.9 for LOP, p < 0.0001), history of perinatal death (aOR 2.2 for EOP, p < 0.0001 and 1.48 for LOP, p= 0.007), primipaternity (aOR 3.0 for EOP and 3.6 for LOP, p = 0.001), dizygotic twin pregnancies (aOR 3.7 for EOP, p < 0.0001 and 2.1 for LOP, p = 0.003), monozygotic twin pregnancies (aOR 3.98 for EOP, p = 0.003 and NS for LOP), ovulation induction (aOR 5.6 for EOP, p = 0.004 and NS for LOP), and in vitro fertilization (aOR 2.8 for EOP, p = 0.05 and NS for LOP). Specific to LOP and NS for EOP: renal diseases (aOR for LOP 2.9, p= 0.007) and gestational diabetes mellitus (aOR 1.2, p= 0.04). Conclusions: Maternal ages over 35 years, chronic hypertension , history of preeclampsia, ovulation induction, in vitro fertilizations, history of perinatal deaths and twin pregnancy (in our experience, especially mono zygotic twin pregnancies) are significant risk factors for EOP. New paternity is an independent factor for both EOP and LOP.

Background/Objectives: The latest WHO classification underscores the importance of the complete blood count (CBC) and cell morphology assessment in diagnosing lymphoid neoplasms. This study evaluated the diagnostic role of Research Use Only (RUO) parameters from the BC-6800 Plus Mindray analyzer in differentiating cell chronic lymphocytic leukemia (CLL), acute lymphoblastic leukemia (ALL), and other lymphoproliferative disorders. Methods: CBCs were performed on 90 patients (66% male, median age 67 years) with pathological blood counts (ALL, n=14; CLL, n=47; other lymphoproliferative disorders, n=29) at Novara’s University Hospital. Univariable and multivariable logistic regression assessed the association of basic (WBC, Hb, RDW, NE#, LY#, MO#, PLT) and research cell parameters (NLR, NMR, LMR, NeuX, NeuY, NeuZ, LymX, LymY, LymZ, MonX, MonY, MonZ). Results: In multivariable analysis, Hb (p=0.02), NeuY (p=0.04), and MonY (p=0.01) independently predicted CLL versus ALL, correctly classifying 93.4% of cases (AUC 0.91, 95% CI 0.81-1.0). MO# (p=0.003), LymY (p&lt;0.0001), and MonY (p=0.004) were independent predictors of CLL versus other lymphoproliferative disorders, classifying 77.6% of cases (AUC 0.86, 95% CI 0.78-0.95). NeuZ (p=0.01) and NeuY (p=0.04) independently predicted ALL versus other lymphoproliferative disorders, classifying 93% of cases (AUC 0.98, 95% CI 0.95-1.0). Conclusions: The use of RUO parameters offers valuable, cost-effective support in the early diagnosis of ALL, CLL, and other lymphoproliferative disorders.

Background and Aims: Late diagnosis of sepsis is associated with adverse consequences and high mortality rate. The aim of this study was to evaluate the diagnostic value of hematologic research parameters, that reflect the cell morphology of blood cells, available on the BC 6800 plus automated analyzer (Mindray) for the early detection of sepsis. Materials and Methods: A complete blood count (CBC) was performed by Mindray BC 6800 Plus Analyzer in 327 patients (223 with a confirmed diagnosis of sepsis following sepsis-3 criteria, 104 without sepsis), admitted at the Intensive Care Unit of the Novara’s Hospital (Italy) and in 56 patients with localized infection. Results: In univariate logistic regression, age, Hb, RDW, MO#, NMR, NeuX, NeuY, NeuZ, LymX, MonX, MonY, MonZ were associated with sepsis (p<0.005). In multivariate analysis, only RDW, NeuX, NeuY, NeuZ, MonX and MonZ were found to be independent predictors of sepsis (p<0.005). Morphological research parameters are confirmed to be predictors of sepsis even when analyzing the group with localized infection. Conclusions: In addition to already established biomarkers and basic CBC parameters, new morphological cell parameters can be a valuable aid in the early diagnosis of sepsis at no additional cost.

Multiple myeloma (MM) is a hematological malignancy characterized by the clonal proliferation of plasma cells in the bone marrow (BM) microenvironment. Despite the progress made in treatment, some MM patients still die within the first year of diagnosis. Numerous studies investigating microRNA (miRNA) expression patterns suggest they may be good prognostic markers. The primary aim of this study was to analyze the expression of selected miRNAs in the serum of MM patients subsequently treated with bortezomib-based regimens and determine their potential to predict early mortality. The study was conducted in 69 prospectively-recruited patients with newly-diagnosed MM admitted to the Department of Hematology of the Copernicus Memorial Hospital, Lodz (Poland) between 2017 and 2021. Among them, 17 patients experienced death within 12 months of diagnosis. The expression of 31 selected miRNAs was determined using miRCURY LNA miRNA Custom PCR Panel. The obtained clinical data included patient characteristics on diagnosis, treatment regimen, response to treatment, and follow-up. Differential expression analysis found two miRNAs to be significantly downregulated in the early mortality group: hsa-miR-328-3p (fold change- FC: 0.72, p=0.0342) and hsa-miR-409-3p (FC: 0.49, p=0.0357). Univariate and multivariate logistic regression analyses were performed to assess the early mortality rate. The final model consisted of hsa-miR-409-3p, hsa-miR-328-3p, age and R-ISS 3. It yielded an area under the curve (AUC) of 0.863 (95%CI: 0.761-0.965) with 88.2% sensitivity and 77.5% specificity. Further external validation of our model is necessary to confirm its clinical value.

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.

From June 18 to 19, 2013, the Ésera river in the Pyrenees, Northern Spain, caused widespread damage due to flooding as a result of torrential rains and sustained snowmelt. We estimate the contribution of snow melt to total discharge applying a snow energy balance to the catchment. Precipitation is derived from sparse local measurements and the WRF-ARW model over three nested domains, down to a grid cell size of 2 km. Temperature profiles, precipitation and precipitation gradient are well simulated, although with a possible displacement regarding the observations. Snowpack melting was correctly reproduced and verified in three instrumented sites, and according to satellite images. We found that the hydrological simulations agree well with measured discharge. Snowmelt represented 33% of total runoff during the main flood event and 23% at peak flow. The snow energy balance model indicates that most of the energy for snow melt during the day of maximum precipitation came from turbulent fluxes. This approach forecast correctly peak flow and discharge during normal conditions at least 24h in advance and could give an early warning of the extreme event 2.5 days before.

Parkinson’s disease (PD) is a common multisystem neurodegenerative disorder affecting 1% of the population above 60 years. The main neuropathological features of PD are the loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and the presence of alpha synuclein (Syn)-rich Lewy bodies both manifesting with classical motor signs. Syn has emerged as a key protein in PD pathology as it can spread through synaptic networks to reach several anatomical regions of the body contributing to the appearance of non-motor symptoms (NMS) considerate prevalent among individuals before PD diagnosis and persisting throughout the patient’s life. NMS mainly include loss of taste and smell, constipation, psychiatric disorders, dementia, rapid eye movement (REM) sleep behavior impairment, urogenital dysfunction, and cardiovascular impairment. This review summarizes the more recent findings showing the impact of Syn deposits on several prodromal NMS and emphasizes the importance of early detection of Syn toxic species in biofluids and peripheral biopsies as prospective biomarkers in PD.

We present the use of interconnected optical mesh networks for early earthquake detection and localization, exploiting existing terrestrial fiber infrastructure. Employing a Waveplate model, we integrate real ground displacement data from seven earthquakes, magnitudes ranging from four to six, to simulate the strains within fiber cables and collect large set of light’s polarization evolution data. These simulations help to enhance a Machine-Learning model that is trained and validated to detect Primary waves arrivals that precede earthquakes’ destructive Surface waves. The validation results show that the model achieves over 95% accuracy. The Machine-Learning model is then tested against an M4.3 earthquake, exploiting three interconnected mesh networks as a smart sensing grid. Each network is equipped with a sensing fiber placed to correspond with three distinct seismic stations. The objective is to confirm earthquake detection across the interconnected networks, localize the epicenter coordinates by a triangulation method and calculate fibers to epicenter distance. This setup allows early warning generation to municipalities close to epicenter location, and progressing to those further away. The model testing shows 98% of accuracy in detecting primary wave and one-second of detection time, affording nearby areas 21-seconds to take countermeasures, and an extended 57-seconds in more distant areas.

IIt is important that Master’s Degree students in psychology, regardless of their future specialisa-tion, know about Attention Deficit Hyperactivity Disorder (ADHD). The aim is evaluate and an-alyse the ADHD-related knowledge held by students of Early Childhood Education and Primary Education. The findings that were obtained in this study (on the chronicity of the disorder, changes in manifestations throughout the life cycle, and the importance of early and multidisci-plinary intervention) have clear implications in relation to the specific training in ADHD for fu-ture teachers. It is essential to broaden the specific training in relation to ADHD in studies for the Master’s Degrees in Early Childhood Education and Primary Education and through contin-uous training.

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.

Blood-based circulating cell free DNA(cfDNA) detection offers a non-invasive and easily accessible way for early cancer detection. Despite the extensive utility of cfDNA, there are still many challenges to develop the clinical biomarkers. For example, cfDNA with genetic alterations often compose a small portion of the DNA circulating in plasma, which can be confounded by cfDNA contributed by normal cells. Therefore, filtering out the potential false-positive cfDNA mutations from health population will be important for the cancer-based biomarkers. Additionally, many low-frequency genetic alterations are easily overlooked in small amount of cfDNA-based cancer test. We hypothesize that, the combination of diverse types of cancer studies on cfDNA can provide us a new insight to identify low-frequency genetic variant across cancer types for early clinical detection of cancers. By building a standardized computational pipeline for 1358 cfDNA samples across seven cancer types, we prioritize 129 shard genetic variants in the major cancer types. Further functional analysis of the 129 variants found that they are mainly enriched in ribosome pathways such as cotranslational protein targeting to membrane, some of which are tumor suppressor, oncogene and related to cancer initiation. In summary, our integrative analysis revealed the important roles of ribosome proteins as the common biomarkers in early cancer diagnosis.

Early detection of wildfires has been limited using the sun-synchronous orbit satellites due to their low temporal resolution and wildfires’ fast spread in the early stage. NOAA’s geostationary weather satellites GOES-R can acquire images every 15 minutes at 2km spatial resolution, and have been used for early fire detection. However, advanced processing algorithms are needed to provide timely and reliable detection of wildfires. In this research, a deep learning framework, based on Gated Recurrent Units (GRU), is proposed to detect wildfires at early stage using GOES-R dense time series data. GRU model maintains good performance on temporal modelling while keep a simple architecture, makes it suitable to efficiently process time-series data. 36 different wildfires in North and South America under the coverage of GOES-R satellites are selected to assess the effectiveness of the GRU method. The detection times based on GOES-R are compared with VIIRS active fire products at 375m resolution in NASA’s Fire Information for Resource Management System (FIRMS). The results show that GRU-based GOES-R detections of the wildfires are earlier than that of the VIIRS active fire products in most of the study areas. Also, results from proposed method offer more precise location on the active fire at early stage than GOES-R Active Fire Product in mid-latitude and low-latitude regions.

Crop-type mapping is an important intermediate step for cost-effective crop management at the field level, as an overview of all fields with a particular crop type can be used for monitoring or yield forecasting, for instance. Our study used a data set with 2400 fields and corresponding satellite observations from the federal state of Bavaria, Germany. The study classified corn, winter wheat, winter barley, sugar beet, potato, and winter rapeseed as the main crops grown in Upper Bavaria. We additionally experimented with a rejection class "Other", which summarised further crop types. Corresponding Sentinel-2 data included the normalised difference vegetation index (NDVI) and raw bands from 2016 to 2018 for each selected field. The influence of raw bands compared to NDVI was analysed and the classification algorithms, i.e. support vector machine (SVM) and random forest (RF), were compared. The study showed that the use of an index should be critically questioned and that raw bands provided a wider spectral bandwidth, which significantly improved the mapping of crop types. The results underline the use of RF with raw bands and achieved overall accuracies (OA) of up to 92%. We also predicted crop types in an unknown year with significantly different weather conditions and several months before the end of the growing season. Thus, the influence of climate anomalies and the accuracy depending on the time of prediction were assessed. The crop types of a test site and year without labels could be determined with an OA of up to 86%. The results demonstrate the usefulness of the proof-of-concept and its readiness for use in real applications.

The movement direction of propagating convective systems originating from both inland and offshore over the north coast of West Java in Indonesia is determined primarily by the prevailing wind. However, the role of a land-sea contrast and a rugged topography over southern West Java is also expected to affect propagating convective systems by increasing land-sea breezes and enhancing upward motion. These hypotheses are tested using a weather prediction model incorporating convection (up to 3 km height) to simulate the heavy rainfall event during 26–29 January associated with the 2002 Jakarta flood. First, we addressed the influence of land-sea contrast and topography on the local circulation, particularly in the area surrounding Jakarta, by replacing the inland topography over western Indonesia (96°–119°E, 17°S–0°) with a water body with an altitude of 0 m. We then compared the results of model simulations with and without topography. The results show that the main role of the topography here is enhancing the upward motion and generating a deep convective cloud in response to the land-based convective system during 26–27 January 2002, which then continuously and rapidly propagates offshore due to the cold pool mechanism. Furthermore, the land-sea contrast has a significant role in increasing sea breeze under the rapidness of the landward propagation system during 28–29 January 2002, which was strengthened by the gravity waves and resulted in early morning convection over coastal regions.

The evolutionary origin of the genome remains elusive. Here, I hypothesize that its first iteration, the protogenome, was a multi-ribozyme RNA. It evolved, likely within liposomes (the protocells) forming in dry-wet cycling environments, through the random fusion of ribozymes by a ligase and was amplified by a polymerase. The protogenome thereby linked, in one molecule, the information required to seed the protometabolism (a combination of RNA-based autocatalytic sets) in newly forming protocells. If this combination of autocatalytic sets was evolutionarily advantageous, the protogenome would have amplified in a population of multiplying protocells. It likely was a quasispecies with redundant information, e.g., multiple copies of one ribozyme. As such, new functionalities could evolve, including a genetic code. Once one or more components of the protometabolism were templated by the protogenome (e.g., when a ribozyme was replaced by a protein enzyme), and/or addiction modules evolved, the protometabolism became dependent on the protogenome. Along with increasing fidelity of the RNA polymerase, the protogenome could grow, e.g., by incorporating additional ribozyme domains. Finally, the protogenome could have evolved into a DNA genome with increased stability and storage capacity. I will provide suggestions for experiments to test some aspects of this hypothesis.

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.

Recent analyses of cosmic microwave background (CMB) maps have been interpreted as demonstrating that the Universe was born without an initial rotation. However, these analyses are based on unrealistic models and do not contain essential ingredients such as quantum effects, the strong, weak and gravitational interactions between the components, their intrinsic spins and magnetic moments, as well as primordial black holes. If the Universe was born spinning these effects would distribute the initial spin angular momentum among its components long before the CMB forms at recombination. A primordial spin would now appear as a nonzero total angular momentum of its components along the direction of the original spin, and a primordial large-scale rotation would no longer be apparent. The existence of a special axis or direction would break a fundamental symmetry assumed in general relativity, cosmic isotropy, and a net angular momentum implies a cosmic parity violation.

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.

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.

Introduction: Some of the practices in medicine are carried out of habit without proven benefits. This is the case of premature babies from 30 to 34 weeks of gestation who are always given parenteral fluids, even though this practice has been associated with an increase incidence of infection. At the end of 2017, we started a protocol of rationalization in the use of parenteral fluid. To administer nutrition/fluids, we used oral fluids by suction if this was possible or otherwise by oral/nasogastric tube at volumes of 70-80 mL/Kg/day divided every 3 hours, with 5 mL increments every 12-24 hours until 200 mL/K/day was achieved, always using breast milk when possible. Material and methods: The present study sought to compare results before and after this new policy. For this work, we review all premature babies between 30-34 weeks of gestation in two time periods, the first from 01/01/2010 to 12/31/2017 and the second from 01/01/2018 to 08/15/2022. The number of cases with and without parenteral fluids (PF), the incidence of infection, the weight at admission and discharge, and the change in the weight Z score between birth and discharge were compared. Both the anthropometric and outcome variables were compared using the different statistical methods according to each variable. Results: were found 920 cases with the described characteristics. The groups before and after the intervention did not show significant differences in their general demographic characteristics. We observed a decrease use of PF in the second period, from 425 cases (82.0%) before to 297 (26.2%) after implementation, p <0.0001 and fewer days of use (4.1 days/average before vs 1.3 after, p <0.0001) of PF. The weight at discharge and the change in weight Z-score were the same in both groups. Infections went from nine cases before to two cases after but it was not statistically significant. There were no complications due to less use of PF. Discussion: This study showed that the use of PF is not associated with significant changes in outcomes of interest, which reinforces that its use does not generate any benefit for the patient. Larger number of cases is required to detect differences in low incidence events such as infections.

A distinction is made between data rescue (i.e., copying, digitizing and archiving) and data recovery that implies deciphering, interpreting and transforming early instrumental readings and their metadata to obtain high-quality datasets in modern units. This requires a multidisciplinary approach that includes: palaeography and knowledge of Latin and other languages to read the handwritten logs and additional documents; history of science to interpret the original text, data e metadata within the cultural frame of the 17th, 18th and early 19th century; physics and technology to recognize bias of early instruments or calibrations, or to correct for observational bias; astronomy to calculate and transform the original time in canonical hours that started from twilight. The liquid-in-glass thermometer was invented in 1641 and the earliest temperature records started in 1654. Since then, different types of thermometers were invented, based on the thermal expansion of air or selected thermometric liquids with deviation from linearity. Reference points, thermometric scales, calibration methodologies were not comparable, and not always adequately described. Thermometers had various locations and exposures, e.g., indoor, outdoor, on windows, gardens or roofs, facing different directions. Readings were made only one or a few times a day, not necessarily respecting a precise time schedule: this bias is analysed for the most popular combinations of reading times. The time was based on sundials and local Sun, but the hours were counted starting from twilight. In 1789-90 Italy changed system and all cities counted hours from their lower culmination (i.e., local midnight), so that every city had its local time; in 1866, all the Italian cities followed the local time of Rome; in 1893, the whole Italy adopted the present-day system, based on the Coordinated Universal Time and the time zones. In 1873, when the International Meteorological Committee (IMO) was founded, later transformed in World Meteorological Organization (WMO), a standardization of instruments and observational protocols was established, and all data became fully comparable. In the early instrumental period, from 1654 to 1873, the comparison, correction and homogenization of records is quite difficult, mainly because of the scarcity or even absence of metadata. This paper deals about this confused situation, discussing the main problems, but also the methodologies to recognize missing metadata, distinguish indoor from outdoor readings; correct and transform early datasets in unknown or arbitrary units into modern units; finally, in which cases it is possible to reach the quality level required by WMO. The focus is to explain the methodology needed to recover early instrumental records, i.e., the operations that should be performed to interpret, correct, and transform the original raw data into a high-quality dataset of temperature, usable for climate studies.

The early Paleozoic is a crucial period in the formation and evolution of the Eastern Kunlun Orogenic Belt (EKOB), and is of great significance for understanding the evolutionary history of the Proto-Tethyan Ocean. This paper presents new petrography, geochemistry, zircon U–Pb dating, and Lu–Hf isotopic research on the Yuejingshan gabbro from the eastern segment of the EKOB. Zircon U–Pb data suggests that the gabbro formed in the Early Silurian (435 ± 2 Ma). All samples have relatively low TiO₂ contents (0.45–2.97%), widely varying MgO (6.58–8.41%) and Mg^# (58–65) contents, and are rich in large ion lithophile elements (LILE such as Rb, Ba, Th, and U) and light rare earth elements (LREE). This indicates that it has a similar geochemical composition to island arc basalt. The major element features indicate that the formation of this gabbro underwent fractional crystallization of clinopyroxene, olivine, and plagioclase. The depletion of high field strength elements (HFSE, such as Nb, Ta, and Ti), and a slightly positive Hf isotope (with εHf_(t) ranging from 1.13 to 2.45) may be related to the partial melting of spinel-bearing peridotite, led by slab fluid metasomatism. The gabbro likely represents magmatic records of the latest period of the early Paleozoic oceanic crust subduction in the Eastern Kunlun. Therefore, the final closure of the Proto-Tethyan Ocean and the beginning of collisional orogeny occurred before the Early Silurian.

The most important prognostic factors in curatively treated prostate cancer at the initial diagnosis are T and N stage, histological subtype, Gleason score, initial PSA, PSA density and percentage of core biopsy positivity. Newer, but non-standard prognostic factors are urine PCA3 and genetic markers of prostate cancer. A simple, but seemingly underestimated standard test is serum Calcium (Ca) level, which has been shown by a previous study group to be a good predictor of lethal prostate cancer, but there is scarce evidence regarding the prognostic value of calcium levels at diagnosis. We aimed to determine whether a Ca level in the upper part of normal values has a prognostic value in curatively treated prostate cancer. We have retrospectively included 84 consecutive patients with prostate cancer, who underwent curative radiotherapy (primary or adjuvant; external beam RT with or without brachytherapy). We have performed statistical analysis of available prognostic factors. Ca level at diagnosis was found to be a statistically significant predictor of disease-free survival.

Based on a reflection on the tensions between play, education, and learning in early childhood, this article aims to identify and analyze the factors that limit or negatively condition the possibilities for play at school during the transition between Early Childhood Education and Primary Education in Chile. The study was conducted in four Chilean schools, with the Transition Levels of Chilean Early Childhood Education (children aged 4 and 5) and the first two levels of Primary Education (children aged 6 and 7). Based on an ethnographic approach, we combined 22 ethnographic observation days spread over two consecutive years and 59 interviews of various types with children, educators, and parents. The results show structural-material limitations on school play that mainly affect children in Primary Education. Beyond, factors associated with routines, indications, and statements governing functioning and participation in this level tend to limit or prevent play, often considered a "non-legitimate" activity. Conclusions highlight the potentialities that children's restricted or resisted play can present in terms of learning.

The clinical requirement for a good esthetic result for immediate implant placement is the absence of dehiscence in the anterior facial alveolar bone. In the presence of a dehiscence, it is recommend-ed to use a connective tissue graft in addition to immediate implant placement or to change to ear-ly implant placement. However, the literature focusing on dehiscence is scarce, and the influence of different placement times and combined use of connective tissue graft on postoperative esthetics in cases with dehiscence is unclear. Therefore, we quantitatively evaluated the pre-extraction de-hiscence morphology and postoperative changes in the facial tissue of implants in three groups: immediate implant placement (Group I), immediate implant placement with connective tissue graft (Group IC), and early implant placement (Group E). Fifty-two implants were obtained (20 in Group I, 16 in Group IC, and 16 in Group E). A wider dehiscence increases the risk of soft tissue regression, which was one reason for choosing early implant placement. A combination of imme-diate implant placement and connective tissue graft, or early implant placement, tended to result in less soft tissue regression due to the thicker postoperative facial soft tissue volume.

B and T lymphocytes demonstrate important alterations in patients with Systemic Lupus Erythematous (SLE), with significant up-regulation of Double Negative (DN) B cells. Aim of this study was to evaluate correlation of T cell immunity changes with the distinct B cell-pattern SLE. In the present study, Flow cytometry was performed in 30 patients with SLE, on remission, and 31 healthy controls, to detect DN B cells (CD19+IgD-CD27-) and a wide range of T lymphocyte subpopulations, based on the presence of CD45RA, CCR7, CD31, CD28, CD57, defined as naive, memory and advanced differentiated/senescent T cells. Both B and T lymphocytes were significantly reduced in SLE patients. However, the percentage of DN B cells were increased, compared to HC, 12.9(2.3-74.2) vs. 8(1.7-35), p=0.04. Distribution of CD4 and CD8 lymphocytes demonstrated a shift to advanced differentiated subsets. The population of DN B cells had significant positive correlation with most of early differentiated T lymphocytes, CD4CD31+, CD4CD45RA+CD28+, CD4CD45RA+CD57-, CD4CD45RA-CD57-, CD4CD28+CD57-, CD4CD28+CD57+, CD4 CM, CD8 CD31+, CD8 NAÏVE, CD8CD45RA-CD57-, CD8CD28+CD57-, CD8CD28+CD57+. Multiple Regression analysis revealed CD4CD31+, CD8CD45RA-CD57- and CD8CD28+CD57- cells as independent parameters contributing to DN B cells, adjusted R2=0.534, p<0.0001. The predominance of DN B cells in patients with SLE is closely associated with early differentiated T lymphocyte subsets, indicating a potential causality role of DN B cells in T lymphocyte activation.

The objective is to describe infant feeding practices and the nutritional status of infants under six months among Syrian refugees in Greater Beirut, Lebanon. A cross-sectional study was conducted among Syrian refugee mothers with children under five years (July-October 2018), mothers with infants under six months were included in the analysis (n=114). Additionally, eleven focus groups discussions were conducted to explore supportive factors and barriers associated with early breastfeeding practices. The prevalence of pre-lacteal feeding was high (62.5%), whereas early initiation of breastfeeding (EIBF) was low (31%), and exclusive breastfeeding (EBF) very low (24.6%). About one-fifth of the infants were suffering from anemia (20.5%) and 9.6% were wasted. Supporting factors of adequate infant feeding practices comprised knowledge on maternal nutrition and EBF, in addition to receiving support from healthcare professionals and family members. Identified barriers included preterm delivery, pre-lacteal feeding, an at-risk waist circumference and moderate to severe depression among mothers, bottle feeding, early introduction of food, maternal health reasons, breastmilk substitutes’ distribution, and misinformation offered by mothers-in-law. To address sub-optimal feeding practices documented among Syrian refugees in our study, existing infant and young child feeding policies and programs need to be strengthened and revised to tackle the identified gaps.

This study introduces an advanced method for climate downscaling using a Super-Resolution Generative Adversarial Network (SRGAN), referred to as Elevation-integrated TEmperature and Precipitation SRGAN downscaling (E-TEPS), to enhance the spatial resolution of climate data, specifically 2m-temperature above the surface and total precipitation, from the high-resolution Euro-Mediterranean Center on Climate Change (CMCC) dataset over Italy. Traditional Numerical weather prediction (NWP) as well as global climate models (GCMs) generally lack the resolution required for local applications, and this research addresses that gap by refining GCM outputs to provide detailed local climate insights. E-TEPS incorporates elevation maps as auxiliary inputs, significantly improving the accuracy of downscaled temperature and precipitation data. Utilizing Google Cloud's computational resources, the model processes large climate datasets and runs complex training operations efficiently. The system is exceptionally fast, delivering all results in under 10 seconds. The model demonstrates superior performance over two interpolation methods (bicubic and linear), used as traditional downscaling methods, achieving lower Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), higher Pearson Correlation for temperature, and higher agreement values for the precipitation. Visual comparisons confirm that E-TEPS generated high-resolution outputs exhibit fewer artifacts and better detail preservation, particularly in regions with complex terrain and variable climatic conditions. These findings underscore the potential of our model in delivering precise, high-resolution climate predictions, thereby enhancing the performance of early-warning systems and supporting more effective climate-related decision-making. This paper is the first part of a two-part series; the second part will demonstrate the integration of this downscaling method with the FourCastNet global forecasting model to enhance climate predictions at a regional level, particularly focusing on high-resolution forecasts for Italy.

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.

Early-life adversity can profoundly impact individual development, yet some demonstrate resilience. Longitudinal studies tracking individuals over extended periods have aided our understanding of resilience and growth following adverse childhood experiences. This paper reviews insights from influential studies like the Kauai Longitudinal Study, the Adverse Childhood Experiences (ACE) Study, and the Dunedin Study. It explores key findings on risk and protective factors, adaptation trajectories, and long-term outcomes associated with resilience. Theoretical frameworks and methodological considerations are discussed. The paper examines how this research informs interventions, policies, and support systems for fostering resilience. It highlights the need for diverse samples, integrating biological and environmental factors, and investigating intergenerational impacts. By synthesizing longitudinal research, this paper elucidates complex pathways to resilience and positive development despite early adversity, offering insights for research and supporting vulnerable populations.

High seismic activity in the Himalayas and the increasing urbanization of its surrounding areas in the northern Indian region pose significant threats to both lives and properties. To mitigate the risk of seismic events, an earthquake early warning system can be used in the region. This system would be particularly beneficial to cities and towns in the mountainous and foothill regions that are located near earthquake sources. The government and the science and engineering community have re-sponded to this call by establishing the Uttarakhand State Earthquake Early Warning System (UEEWS). The system became fully operational on August 4, 2021, after being launched by the government of Uttarakhand. The UEEWS includes 170 accelerometers in the seismogenic part of the Uttarakhand region of the Himalayas. Ground motion data is transmitted to a central server through a dedicated private telecommunication network 24 hours a day, seven days a week.The system is designed to issue warnings for moderate to high-magnitude earthquakes via a mobile application installed on users' devices and sirens installed in government-owned public buildings. The UEEWS has successfully issued alerts for light earthquakes that occurred in the instrumented region and warnings for moderate earthquakes that occurred in the vicinity of the instrumented area. This paper provides an overview of the design of the UEEWS, details of the instrumentation, adaptation of attributes and their relation to earthquake parameters, the operational flow of the system, and information about the dissemination of warnings

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

The Standard Model (SM) of particle physics successfully describes electromagnetic, weak, and strong forces but omits gravity. We introduce the Kinematrix Field Theory (KFT), integrating gravity into this fundamental force framework through a novel particle, the kinematon. This gauge boson, existing in both massless and massive forms, advances the SM's scope to address enigmas like dark matter and neutrino masses. We detail the mathematical structure of the KFT and establish Feynman rules for kinematon interactions with fermions and gauge bosons. The KFT, synergizing with the Higgs mechanism and general relativity, aspires to a unified quantum theory of gravity. We explore the kinematon's phenomenological implications and potential experimental signatures, forecasting significant advancements in fundamental physics and setting a course for future explorations in the SM.

Over recent years, the swine industry has witnessed the withdrawal of antibiotics and continuous regulation of zinc and copper oxides in the early-life nutrition of piglets. Due to this development, alternative ingredients or additives from plant sources have been tremendously explored. Therefore, this study's objective was to evaluate the effect of dietary supplementation with tannins on weaned piglets’ growth performance, serum antioxidant capacity, and immune status using a meta-analysis approach. With only the inclusion of non-challenged weaned piglets, a total of 16 studies with parameters of interest were deemed eligible after a two-step screening process following a comprehensive literature search in the scientific databases of Web of Science, Scopus, ScienceDirect, PubMed, and Google Scholar. Two main categories of data, including the study’s characteristics and response variables (growth performance, serum antioxidant, and immune indices), were extracted. Applying the random-effects models, Hedges’ g effect size of supplementation with tannins was calculated using the R software to determine the standardized mean difference (SMD) at a 95% confidence interval. Sub-group analysis and meta-regression further explored heterogeneity (PSMD 0.05, I2 50%, n ≥10). Supplementation with tannin reduced average daily gain (p = 0.20) and feed conversion ratio (p 0.01); however, it increased average daily feed intake (p = 0.07) and final body weight (p 0.01). Meta-regression models indicated that tannin dosage and supplementation duration were directly associated with tannins' effectiveness on productive performance. In the serum, the concentration of glutathione peroxidase, superoxide dismutase, and total antioxidant capacity were elevated (p 0.01) in response to tannins supplementation, while malondialdehydes was reduced (p 0.01). Likewise, decreased immunoglobin A (p = 0.47) and increased immunoglobin M and G levels (p 0.01) were detected. In conclusion, dietary supplementation with tannins, particularly with chestnut and grape seed proanthocyanidins, increases the productivity of weaned piglets. At the same time, it is a possible nutritional strategy to mitigate oxidative stress and stimulate gut health. Thus, supplementing chestnut and grape seed proanthocyanidin tannins in the early phase of swine production could be used to alleviate the incidence of diarrhea.