Colostrum is a unique channel that contributes to passive immunity transfer and provides nutrients for the growth and newborn lambs development. High yield and quality colostrum are the keys to ensuring the healthy lamb’s survival.However, systematic evidence regarding colostrum characteristics, particularly yield and immunoglobulin concentrations, as well as the underlying genetic-molecular mechanisms, remains insufficient. Therefore, this study aims to measure and analyze the dynamic changes in colostrum yield, immunoglobulin concentrations (IgG, IgA, and IgM), and nutrient composition (including fat, protein, lactose, total solids, non-fat solids, and urea) in sheep, while also identifying genes associated with colostrum characteristics to provide insights for improving the yield and quality of sheep colostrum and for developing efficient lactating sheep breeds. It was found that colostrum production increased significantly with time and total colostrum production could reach 3.489±0.075 Kg in the first 3 days after delivery.At the same time, the highest concentrations of IgG (108.014 mg/mL), IgA (4.139 mg/mL), and IgM (0.447 mg/mL) in colostrum were observed during delivery, and they decreased rapidly at 12 hours and finally stabilized. The contents of fat, protein, lactose, total solids, non-fat solids, and urea decreased after delivery, while the lactose content showed an increasing pattern. In addition, whole genome resequencing analysis revealed six single nucleotide polymorphism (SNP) sites in the LTF gene (rs422619216), PTPRK gene (rs429528738), and LIFR gene rs408968100, rs162154352, rs161149074, and rs411119461). Variations at these loci are significantly associated with colostrum production and immunoglobulin content, serving as important molecular genetic markers for colostrum traits. Notably, these variations also influence the hydrophilicity and three-dimensional structure of the corresponding proteins. LTF, PTPRK, and LIFR genes are important candidate genes for colostrum yield and immunoglobulin concentration, providing robust evidence to support sheep selection and breeding programs.

The World Health Organization (WHO) refers to the 2019 new coronavirus epidemic as COVID-19, and it has caused an unprecedented global crisis for several nations. Nearly every country around the globe is now very concerned about the effects of the COVID-19 outbreaks, which were previously only experienced by Chinese residents. Most of these nations are now under a partial or complete state of lockdown due to the lack of resources needed to combat the COVID-19 epidemic and the concern about overstretched healthcare systems. Every time the pandemic surprises them by providing new values for various parameters, all the connected research groups strive to understand the behavior of the pandemic to determine when it will stop. As a result, the incidence of the COVID-19 outbreak in Malaysia and the United Arab Emirates is predicted in this study using artificial intelligence-based models. These models comprise extended short-term memory networks (LSTM) and bidirectional (biLSTM). Utilizing the determination coefficient and root means square error, the outputs of the models are evaluated. When predicting the cumulative infections for the next week and month, the LSTM model performs best. Furthermore, 90% and 10% of the data reported by the Malaysian and UAE ministries of health and Population between January 03, 2020, and July 05, 2023, respectively, were used to train and test the models, the LSTM model is applied to forecast the spread of this disease for the next month. The result of this study may help policymakers to implement measures to combat any COVID-19 variation.

Bamboo, a species with multiple applications in construction, manufacturing, bioengineering, and disaster recovery, is vital to rural livelihoods in Nepal. This study explores the current and future distribution of seven woody bamboo species (Bambusa balcooa, Bambusa jaintiana, Bambusa nepalensis, Bambusa nutans, Bambusa teres, Dendrocalamus hamiltonii, and Dendrocalamus hookeri) in Nepal in the face of a changing climate, as it is forcing species to relocate and find new regions in search of better habitats. We determined the suitable habitat up to 2090 under two Shared Socioeconomic Pathway (SSP) emission scenarios using an ensemble species distribution modeling approach. Mean diurnal range, minimum temperature of the coldest month, elevation, and temperature annual range were the key environmental variables for limiting bamboo distribution. The Middle Mountains of Eastern and Central Nepal were the most climatically suitable areas for bamboo species. The response to the changing climate was unique to each species, in which B. nepalensis and D. hookeri experienced significant expansion, whereas B. balcooa and B. nutans will experience contraction in climatically suitable areas by 2090. The suitable range of other species was relatively stable. To prevent extirpation, in-situ and ex-situ conservation approaches should be implemented by identifying climate refugia in districts like Parbat, Kaski, and Lamjung, as they are suitable for six of the species. Given the lengthy and varying flowering cycles, we recommend vegetative propagation to establish bamboo in new regions. Furthermore, a strategic bamboo management plan should be developed to tackle the extirpation of bamboo species due to climate change.

Due to climate change, heat stress is an increasing health risk in cities that requires adaptation measures from both citizens and city planning. This study proposes a routing service for the reduction of solar exposure and investigates its potential to reduce heat stress from the individual as well as from the planning perspective. The solar exposure of the pedestrian paths in the city of Heidelberg, Germany, was modeled throughout the day and subsequently integrated into a specialized routing service. The aggregated average of solar exposure of simulated pedestrian trips across the city could be reduced by 12 to 26%. In some cases, the solar exposure of a route could be reduced up to 90% with only a length increase of 12% at noon, the most critical time of day in regard to heat intake. This makes it a promising option for citizens to effectively reduce but not completely eliminate their heat stress. Therefore, action from city planners is still necessary. A network analysis identified critical roads in the city where built measures would have the greatest impact on reducing the heat stress of pedestrians. This provides the base for follow-up investigations in cooperation with citizens and planners. Our approach also supports the shift toward sustainable urban mobility as prioritized by both the EU Green Deal and the UN SDGs. To adapt car-focused cities and make them walkable it is essential to provide pleasant routes, resting points, and, regarding the increasing temperatures, shade. Our project shows that a shade-preferring routing service for pedestrians can both help in analyzing the road network to find focus areas for adaptation measures as well as providing a solution for inner city areas where many detours are possible to reduce the solar exposure of individuals. In addition to the analysis presented here, a functional and publicly accessible routing app is available specifically for Heidelberg at https://heal.openrouteservice.org.

M13 bacteriophages are used as very important tools in molecular biology, biotechnology and, nanotechnology. Many methods have been developed so far for the purification of these phages. However, it is important that phages retain their infecting properties, especially in biotechnological applications such as phage display technology. The most widely used is the PEG precipitation method, but it has some limitations such as impurities and reduced infectivity. To overcome them, we developed a new method for purification of M13 bacteriophages using syringe filters made of cellulose acetate membranes with a pore diameter of 0.22 µm. Phages were aggregated so that they could remain on the filters and for this purpose, the pH of the phage cultures was reduced to 3. The phage cultures were filtered and then the phages were recovered in TBS buffer (pH 10.5) by reversing the filter. The recovery rate was 250% higher than the standard PEG method. This new Faj-elek method offers an alternative to existing methods, allowing cheaper, easier and faster purification of M13 phages using syringe filters available in every research laboratory.

Objective: We examined the possible impact of selective serotonin reuptake inhibitor (SSRI)-trajectories describing the timing of different SSRI dosages on adverse neonatal outcomes. Design: Longitudinal register study Setting: Population based study from Kuopio University Hospital Birth Register. Population or Sample: Altogether 508 mothers who reported using SSRIs in pregnancy, where matched to a five-fold comparison group (n=2540), based on maternal depression, psychiatric diagnoses and age. Methods: We applied unsupervised k-Means longitudinal clustering method to identify four distinct patterns of SSRI use, and propensity score adjusted generalized estimating equations to examine the associations between the exposure groups and the neonatal outcomes, using the unexposed group as reference. Main Outcome Measures: Birth weight, placenta weight, placenta-to-birth-weight ratio (PBWR), umbilical cord length, gestational length, premature birth, low 5-min Apgar score, neonatal intensive care unit (NICU) admission. Results: Compared to the no SSRI group, we found no associations between the use of SSRI up to standard doses and the neonatal outcomes. However, the sustained high dose group (~twice the standard dose) displayed significantly higher mean PBWR (B=1.65, 95% CI=0.83, 2.47). In addition, the odds of low Apgar score for the high dose group were about 3.2-fold (OR=3.2; 95%CI=1.04, 9.79), and the odds of NICU admission 2.6-fold (OR=2.6; 95%CI=1.10,6.03), compared with no SSRI group. Conclusions: Sustained, increasing, or decreasing use of SSRI up to standard doses were not associated with adverse neonatal outcomes. However, caution is advised as sustained higher doses may be linked to reduced placental efficacy and higher risk of adverse neonatal health.

Authors : Joseph A. Tobias1*, James M. Bullock2, Lynn V. Dicks3, Brenna Forester4, Orly Razgour5Affiliations :1 Department of Life Sciences, Imperial College London, Silwood Park, Buckhurst Road, Ascot, SL5 7PY, UK2 UK Centre for Ecology & Hydrology (UKCEH), Maclean Building, Benson Lane, Wallingford, OX10 8BB, UK3 Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK4 U.S. Fish and Wildlife Service, Fort Collins, CO, USA5 Biosciences, University of Exeter, Exeter, EX4 4PS, UK*To whom correspondence should be addressed:

The analysis of the composition of alkali-excited concrete in the civil engineering industry is of great significance for material development. However, there is no machine learning method suitable for alkali excited concrete composition analysis. Therefore, in this study, we use the test results of alkali slag concrete specimens as research samples. The composition of broken specimen blocks was analyzed by developing an ensemble learning algorithm called MLP-RF. Finally, by comparing the prediction results of this experiment with the prediction results of other scholars and optimizing the results, it is found that the ensemble learning algorithm has high accuracy and certain universality. This provides a feasible method to analyze the composition of alkali-excited concrete using machine learning.

One of the main challenges in wireless sensor networks is the limited energy of nodes and their lifetime. In this paper, we utilize compressed sensing theory to reduce the number of transmissions and ultimately increase the lifetime of the wireless sensor network. The data in some wireless sensor networks, in addition to spatial correlation, also have temporal correlation. The proposed method in this paper benefits from both types of correlation to minimize the mean square error of the reconstructed data signal. We also use a sleep/wake algorithm to reduce energy consumption of nodes. The awake nodes in the proposed method are determined using a genetic algorithm, as finding optimal nodes is an NP-Hard problem. After determining the awake nodes, the ant colony algorithm is used to construct the optimal aggregation tree of the awake nodes. Simulation results show that our proposed approach in selecting awake nodes and routing them leads to an improvement of more than 48% in reconstruction error and an increase of more than 18% in network lifetime compared to the evaluated methods.

This study presents an innovative federated learning framework that addresses the challenge of identifying the breeds of Iranian sheep using an SNP-based genotype dataset which contains the SNP values of four breeds of Iranian sheep. In the first phase of the research, an SNP selection phase is performed using the Particle Swarm Optimization algorithm to find the best subset of SNPs which will result in the best possible classification accuracy. In this phase, PSO detected 5565 SNPs among 46000 which has resulted in 98% classification accuracy. The second phase then uses a federated learning framework with the aggregation algorithm kfedAvg to train different local learning models with different private local datasets. The result achieved from this phase indicates, on average, the accuracy of 85% by the clients on the local test data.

In the context of regional integration and collaborative development, investigating the spatial correlation network characteristics and driving factors of construction land use efficiency within urban clusters is crucial for mitigating the tension between economic growth and the scarcity of construction land resources. It assesses efficiency using the DEA-BCC method for 13 cities and analyzes the network’s structure and evolution with a modified gravitational model and social network analysis. QAP regression dynamically explores influencing factors. Key findings include: 1) A complex, multi-tiered spatial correlation network with increasing interconnectivity yet fragile core-periphery links, indicating a need for enhanced correlation in land use. 2) Beijing and Tianjin are central, while Hebei cities are peripheral, with Shijiazhuang, Baoding, and Cangzhou’s roles growing. 3) Beijing-Tianjin-Langfang are major beneficiaries, and Hengshui-Qinhuangdao are significant spillover contributors. 4) The network shows limited integration with peripheral cities, influenced by geospatial, economic, innovation, industrial, and urbanization disparities. This study provides insights into land use efficiency and regional development dynamics within the cluster.

A new species of Jungia L. fil. (Asteraceae Bercht. & J. Presl), Jungia alba is described and illustrated from the high Andean scrublands of the western slope of the Southern Peru. The species resembles J. axilaris and J. polita but differs from it in the shrubby habit, glutinous consistence, stipules absent and paniculate synflorescences of white flowers. Furthermore, we reported J. woodii for the first time to the Flora of Peru. A detailed morphological description, illustration, ecological information, distribution and conservation status for each taxon are provided.

Title PageManuscript type: Case Report

IntroductionDistal abdominal aortic thrombus is one of the rare entities in cardiovascular pathologies (1), and being spontaneous makes it unique. Only a few cases are encountered in clinical practice; thus, it is rare to diagnose before the patient suffers embolic complications. This makes the true incidence of this particular disease unknown (2) and therefore a high index of suspicion in patients without risk of coagulability states or any previous risk factors predisposing them to thrombus formation should be thought of; especially in patients presenting with signs of lower extremity ischemia which may mimic signs of venous insufficiency due to deep vein thrombosis (3). The management guidelines for this condition are still lacking as there is no clear consensus on whether, conservative pharmacological versus endovascular surgery, is the best option (3). These guidelines are referenced from developed countries, which possess the full availability of resources and equipment, as opposed to our medical setting. In this case, we present a 69-year-old female of Asian descent who was diagnosed with distal aortic occlusion of approximately more than ninety percent (90%) and was managed with intra-arterial papaverine and streptokinase infusion before being referred for endovascular therapy to salvage the limb.

The rapid growth of aquaculture is driven by the increasing demand for fish which provide essential nutrients for balanced health. Empurau is a highly-sought freshwater fish with high market value due to its unique flesh taste, making it one of the most famous species among the aquaculture industry. However, the main challenge of the industry remains as the infectious disease outbreak with Pseudomonas species as one of the most threatening fish pathogens while residing a wide range of environments. Given antibiotics administration as the common solution to disease outbreaks, contributing to the worsening of antimicrobial resistance, the development of disease-resistant broodstock through the identification of SNP markers appeared as one of a promising strategy. In this study, a total of 1,048,576 SNP markers were identified via whole genome pooled sequencing on samples treated with LD 50, forming resistant and susceptible group. Multiple tests (pairwise F ST test, CMH test and FE test) and visualization had been conducted to screen and select candidate SNP markers for further validation using T-plex ARMS real-time PCR assay. The genotyping results on the selected candidate markers were confirmed using Sanger sequencing. Statistical analysis had been performed to validate the significance of the candidate marker. The successful validation of 19,564 G/C SNP markers is expected to advance research on disease-resistant association SNPs and support their integration into breeding programs, enabling the use of genomic information to optimize artificial selection in empurau breeding.

The pathophysiology of vitiligo is very complex because the interaction of the genetic components and oxidative stress or melanocytes epithelium, immunity innate or adaptive. The highly sensitive C-reactive Protein is more susceptible for the inflammation in the body. When the Nutrient deficiencies in our body then high the level of the homocysteine because they inhibit the tyrosine enzymes by the binding with the copper or it reversible hypo pigmentation. There are two elements are present in body zinc and copper they have a various role in the homeostatic processes in the body including Oxidative stress. Autoimmune disease is rise when the immunity get confusion about the self and unself cells. There are various types of auto-immune diseases, like rheumatoid arthritis, diabetes type 1, multiple sclerosis, thyroid disease, inflammatory bowel disease, Graves's disease, vascular scleritis. These are some autoimmune diseases caused by the decrease in the immunity. The S100B Protein is increase in the patient of vitiligo this protein is react with less than 6 months in all vitiligo patient when the rapidity increases the concentration of S100B protein in the patients they cause the neuronal dysfunction and cell death it produces pro-inflammatory cytokines that are harmful for the tissue. The Neutrophil growth factor is also a factor of causing the depigmentation of skin because when the person is surfer from the schizophrenia and other mental disorder. When the range of vit D level decrease in our body then they cause the disease such as DM, RA, Vitiligo or other disease.

Honeybees are an important economic source for humans. Still, interaction and overlap of trophic resources between honeybees and non-managed pollinators such as wild bees have been recently studied, and concerns about possible competition have been raised in environments where the number of hives is high. Apis mellifera L. is a social species, with large perennial colonies and can communicate to choose foraging sites that are very remunerative. Moreover, they may show territorial behaviour that can depress wild pollinator species. For those reasons, actions that focus on solutions to pollinator decline shall also consider the competition that can occur between honeybees and wild species. Our study aimed at seeding and managing entomophilous plant mixtures in marginal areas of river belt basins for the support of pollinators. During a three-year experimental period, we found that plots with higher percentages of flower coverage and fewer dominant plant species attracted a high abundance of honeybees. Wild bee abundances and species were negatively influenced by the simultaneous presence of high honeybee density and mass flowerings of a few flowering species. Our results can be useful when designing mixtures of entomophilous plants for conservation purposes. Creating oligotrophic flowering areas can support wild pollinators and decrease interspecific competition.

Climate warming is affecting the composition and distribution of Andean tropical montane forests (TMFs), leading to varied growth responses among tree species. However, the underlying mechanisms driving growth responses to climate warming remain largely unexplored. To investigate this, we established a common garden experiment along a 2000m natural thermosequence in the Andes. We planted individuals of 15 dominant Andean species from both montane and lowland origins under common soil and water conditions at different temperatures. We measured 19 leaf traits, including photosynthetic, thermotolerance, structural, and water use to explore their influence on tree growth responses to warming and cooling. Relationships between individual traits and growth showed the significant influence of thermal tolerance and the temperature response of photosynthesis in all but one treatment. When combining all traits, leaf nitrogen content emerged as the primary trait linked to growth in the trees home environments while leaf mass per area was the key trait influencing growth responses to temperature change. Overall, these traits explained over 50% of growth in three of four treatments and 25% in the remaining case. Climate change can alter trait growth relationships, however our understanding of trait influences on growth responses to warming remains incomplete.

This article addresses the derivation and analysis of an optimal quadrature formula for numerical integration of fractional integrals in the Hilbert space W 2 ( 2 , 1 ) ( t , 1 ) , where functions φ with prescribed properties reside. The quadrature formula is expressed as a linear combination of function values and their first-order derivative at equidistant nodes in the interval [ t,1]. The coefficients are determined by minimizing the norm of the error functional in the dual space W 2 ( 2 , 1 ) ∗ ( t , 1 ) . The error functional is defined as the difference between the integral of a function over the interval and the quadrature approximation. Key results include explicit expressions for the coefficients and the norm of the error functional. The optimization problem is formulated and solved, leading to a system of linear equations for the coefficients. Analytical solutions of the system are obtained, providing an explicit expression for the optimal coefficients. Fractional integrals of several functions are numerically calculated with the constructed optimal quadrature formula, and the convergence with the exact value of the integral is analyzed in numerical experiments.

Ecologists have long argued about the strength of density dependence and population regulation, respectively defined as the short-term and long-term rate of return to equilibrium. Here, I argue that we cannot reliably quantify population regulation with time series data. An analysis of the Global Population Dynamics Database reveals that conclusions about population regulation are heavily dependent on model choice, with no clear way to select a particular model. A parallel debate in macroeconomics — regarding whether GDP shocks have permanent effects — remains unresolved despite extensive research, implying that the population regulation question is similarly intractable. However, we can measure the short-term property of density dependence, which is moderate on-average and shows considerable variation across populations: half-lives of perturbations typically last 0.7 to 4.2 years (interquartile range). Rather than a universal balance of nature, stability varies widely across populations in ways that correlate with life history and taxonomy.

Wang Jinmin1, Li Jiaxin1, Wei Yuan1*Author’s Affilications : 1 Peking University Third Hospital, Haidian 100096, Beijing,∗Corresponding author , E-mail: weiyuanbysy@163.com[Keywords] Monochorionic twin pregnancy; Single intrauterine fetal death; Renal dysplasia

Current research regarding Baby Sign and its effect on early language and communication development is inconclusive. This study investigated the effects of Baby Sign class attendance on early language and communication development, when the possible effects of birth order, nursery attendance, and multilingual family background were also taken into account. Participants (130 parents of children aged 12-48 months) completed online questionnaires on nursery attendance, language exposure, and experiences with Baby Sign. Language and communication development were assessed using the Bayley Scales of Infant and Toddler Development (Bayley-III) Parent reported Communication subsection. Results found a significant interaction between Baby Sign attendance and birth order, with firstborns scoring significantly higher on the Bayley-III than laterborns in the Baby Sign group. Additionally, in the Baby Sign group, children from multilingual homes scored significantly higher than children from monolingual families. These findings suggest that Baby Sign may interact with birth order and multilingual development.

The axially-symmetric solutions to the Navier-Stokes equations coupled with the heat conduction are considered. in a bounded cylinder Ω ⊂ R 3 . We assume that v r , v φ , ω φ vanish on the lateral part S 1 of the boundary ∂Ω and v z , ω φ , ∂ z v φ vanish on the top and bottom of the cylinder, where we used standard cylindrical coordinates and ω = rot v is the vorticity of the fluid. Moreover, vanishing of the heat flux through the boundary is imposed. Assuming existence of a sufficiently regular solution we derive a global a priori estimate in terms of data. The estimate is such that a global regular solutions can be proved. We prove the estimate because some reduction of nonlinearity are found. Moreover, we need that f ( p ) ≡ ∥ v φ ∥ L t ∞ L x p / ∥ v φ ∥ L t ∞ L x ∞ is bounded from below by a positive constant. The quantity f( p) is close to 1 for large p because f(∞)=1. Moreover, deriving the global estimate for a local solution implies a possibility of its extension in time as long as the estimate holds.

Background and Purpose: Phlorizin is the active ingredient in the Cynomorium songaricum ethyl acetate extract, and it has been shown that Phlorizin can regulate lipid metabolism disorders as well as anti-ageing.But there are no studies on the relevance of PHZ in attenuating Aβ-induced toxicity in Alzheimer’s disease(AD) by regulating lipid metabolism.Our purpose is to investigate the effects of phlorizin on the regulation of lipid metabolism disorders and resistance to Aβ-associated toxicity in the AD Caenorhabditis elegans and their mechanisms of action. Experimental Approach: Wild-type N2 and AD model CL4176 C.elegans was used, the lifespan, heat stress, chronic paraquat stress, behavioral testing and lipofuscin assay was exaimed to detected anti-ageing efficacy,non-esterified fatty acid,triglyceride and lipidomic contents were quantified after PHZ treatment. The detection of genes related to lipid metabolism pathways was performed using qpcr. nhr-49 knockout mutant RB1716,GFP-binding mutants PMD150 WBM170 were uesd to observed the effect of PHZ on NHR-49 pathways and molecular docking studies were performed combining phlorizin and NHR-49 proteins. Key Results: PHZ improved worms survival and delayed senescence in lifespan, heat stress and chronic paraquat assays, PHZ also reduced lipid accumulation in worms, affected the unsaturated fatty acid pathway and significantly increased the expression of fatty acid metabolism-related genes nhr-49, acs-2 and cpt-5, and can be tightly coupled to NHR-49 targets. Conclusion: PHZ may play an anti-Aβ toxicity role by regulating lipid metabolism disorders through nhr-49 related pathway and anti-ageing in AD worms. Keywords：Phlorizin；C.elegans；AD；lipid metabilosm