An 8-month-old patient was found to have an adrenal cortical carcinoma (ACC) characterized by a TP53 c.758C>T (p.T253I) mutation in the TP53 tumor suppressor gene. p53 protein levels were overexpressed in the patient’s ACC, and molecular profiling of the tumor suggested suppression of the remaining wild-type (WT) TP53 allele. As this type of malignancy has been reported to occur in Li-Fraumeni Syndrome (LFS) patients with germline inheritance of loss-of-function TP53 mutations, we evaluated the patient’s TP53 gene in non-tumor tissue and found evidence of a constitutional heterozygous germline TP53 c.758C>T (p.T253I) variant. Since the mutation has not yet been linked to LFS, we sought to characterize the functionality of the T253I mutation. We acquired p53 -/- HEK293 cells and stably transduced them with GFP-tagged wild type (T253) or T253I p53 as well as two established pathogenic p53 mutants (C176Y and R213X). Compared to p53 WT, levels of T253I p53 increased while MDM2 levels decreased, suggesting a loss of MDM2-mediated regulation of T253I p53. Additionally, T253I showed a reduction in DNA damage responsive events, diminished DNA binding capabilities, and blunted transactivation capacity. These experimental data, coupled with clinical observations, lead us to conclude that T253I represents a pathologic variant in TP53 that may predispose to LFS-associated tumors.

Widespread amphibians are frequently impacted by incorrect species assignments and inaccurate taxonomic labelling in open databases and published studies, leading to confusion regarding species boundaries and missing information for population trends at the ecozone level. We examined three genera in the family Dicroglossidae (Fejervarya, Hoplobatrachus and Quasipaa) across the Indomalaya and Palearctic ecozones, where unresolved species boundaries and the introduction of exotic populations are significant issues. Alternative to conventional phylogeny, we employed the Bayes Factor Delimitation method and nested sampling to assess 18 comparative delimitation models for 15 verified species in GenBank, using 4,044 bp unlinked multilocus data from 487 individual Asian Dicroglossids across both ecozones. Our best-supported model delineated 17 clades across three genera, highlighting Fejervarya as the genus with the shallowest clade assemblages, with two clades within each of the F. kawamurai, F. multistriata, and F. limnocharis species complexes, all diverging below 3.70 Mya in the Northern Indomalaya and Southeastern Palearctic. Through adjusted ecological niche modelling with species delimitation data, we verify that precipitation of the driest month, elevation, and mean diurnal temperature range, are key variables influencing the distribution of F. kawamurai and F. multistriata in mainland East Asia. Cross validation using call analysis supported significant differences in call durations and intervals between F. kawamurai [Clade II] and F. multistriata [Clade II] in their overlapping range in the eastern Yangtze River Basin indicated the existence of subspecies boundaries even in the absence of physical barriers and validated the presence of F. multistriata along the central coast of China, i.e. Shanghai. Our findings also showed the clustering of the southern Palearctic Fejervarya clade, including the population in the Jiangsu Plains, within the Yangtze group of F. kawamurai, and delineated the northern limit of F. multistriata in the vicinity of the Huai River.

Animals with different life-history types vary in their stress-coping styles, which can affect their fitness and survival in changing environments. We studied how chronic exposure to manganese sulfate (MnSO4), a common aquatic pollutant, affects life-history traits, physiology, and behavior of zebrafish (Danio rerio) with two life-history types: fast (previously selected for fast juvenile growth, early maturation, and small adult body size) and slow life histories (selected for slow juvenile growth, late maturation, and large adult body size). We found that MnSO4 had negative effects on growth and condition factor, but the magnitude of these effects depended on the life-history type. Individuals with fast life histories were more susceptible to MnSO4 than fish with slow life histories as they had lower growth rate, condition factor and feeding probability in high MnSO4 concentrations. Our results demonstrate that MnSO4 can impair fish performance, and life-history variation can modulate the stress-coping ability of individuals.

Car manufacturers face challenges in optimizing platforms and portfolio management to meet evolving customer demands, regulatory requirements, and technological advancements. By leveraging the power of data science and deep learning, automakers can gain valuable insights into consumer preferences, market trends, and product performance, enabling informed decision-making for platform and portfolio strategies. In the automotive industry, product features play a significant role in shaping consumer perceptions, preferences, and purchasing decisions. This article explores how data science and optimization techniques can be used to develop and implement effective product feature strategies. By integrating Python programming with advanced analysis and optimization algorithms, automakers can Deploy IDSS to enhance competition, customer satisfaction, and innovation in the automotive sector.

Objective: To construct a training needs scale for general practitioners, conduct empirical research, provide an effective tool for clarifying the training needs of general practitioners, and lay a foundation for further scientifically constructing a training system for general practitioners. It also aims to provide a reference for developing countries and underdeveloped regions in cultivating general practitioners. Methods: Through literature review and interviews with key informants, the ”Grassroots General Practitioner Training Needs Scale” was designed based on the post competency of general practitioners. A questionnaire survey was conducted in China’s primary healthcare institutions using convenience sampling from May to August 2022. The reliability and validity of the scale were verified through reliability and validity tests, and further quantitative analysis was conducted to verify the practical significance of the scale. Results: A total of 2616 valid questionnaires were collected, with a recovery efficiency of 99.47%. The scale consists of 4 dimensions and 33 items. The overall Cronbach’s α coefficient of the scale is 0.989, and the split-half reliability is 0.978. The content validity analysis results showed that there were significant internal correlations between the various dimensions of the scale (P<0.05); the AVE values of the convergent validity test were all greater than 0.36, and the CR values were all greater than 0.7. In the analysis of structural validity, the results of exploratory factor analysis showed that the factor loadings of each factor were all above 0.40, and the cumulative factor contribution rate reached 84.306%. The results of confirmatory factor analysis showed that all fitting indicators of the scale met the standards. The empirical study showed that general practitioners’ needs for training in various dimensions reached the required level, and the training needs of general practitioners in different positions were different. Conclusion: The scale has good reliability and validity, as well as practical significance. It can be applied to clarifying the training needs of grassroots general practitioners and providing a basis for conducting scientific training. Grassroots general practitioners have differentiated and personalized characteristics in their training needs, so the implementation of training should be based on demand to enhance the pertinence of training. Ultimately, the goal is to comprehensively enhance the post competency of grassroots general practitioners.

Guerbet alcohol (GA) is β-branched primary alcohol having excellent physiochemical properties like lower pour point (PP) and higher kinematic viscosity (KV) in comparison to linear alcohol. Although different aspects of the synthesis of GA, such as methods of synthesis, catalytic systems, and reaction conditions, have been studied, but statistical modeling and optimization of the synthesis of GA have not been carried out. In the present work, the optimization of the synthesis of GA using a mixture of lauryl and myristyl alcohol was carried out with the aid of response surface methodology (RSM) considering the conversion of the reaction, PP and KV at 40˚C & 100˚C as dependent variables. The optimal reaction conditions were temperature, pressure, and time of 220˚C, 300 mbar, and 10 hours respectively. The optimum conversion was 99.141%, including dimer yield of 81.755%, PP of -3˚C, KV at 40˚C & 100˚C of 34.12 cSt & 7.22 cSt, respectively. The results obtained by the RSM were then authenticated, applying artificial neural networks (ANN) generated with the help of MATLAB. The ability of the generated model to predict the response variables was validated by less than 5% error for almost all the models, confirming the statistical significance. Also, the tribological potential for linear Ginol-12,14 (FA) and synthesized branched GA as lubricant additive was evaluated by determining its physiochemical, thermal and tribological properties.

Climate change poses significant challenges to global livestock systems, necessitating a deeper understanding of how sheep adapt to diverse environmental conditions. This study aimed to identify genomic regions associated with hot and cold climate adaptation in 3066 sheep from 90 breeds worldwide using medium-density SNP data. The breeds were categorized into hot and cold-adapted groups based on their environmental origins. Through PCAdapt, we identified 132 genomic regions under selection across all breeds, with distinct signatures observed in hot (53 regions) and cold (49 regions) adapted groups. These regions encompassed genes crucial for thermoregulation (DNAJB5, SYCP2, TCF7, TSHR, NPR1, and MSRB3), coat colour (MITF, DCTN2) and immune response (CCL26, CDH1, TCF7, and TNFSF12). Functional enrichment analysis revealed biological processes and pathways associated with climate adaptation, including keratin filament organization and cytokine receptor binding in hot climate breeds, and calcium ion binding in cold climate breeds. Protein-protein interaction networks highlighted key hub genes like TP53 and S100A16, implicating their roles in adaptation mechanisms. Overlapping selection signals were observed across datasets, with several regions corroborated by previous studies. Our findings contribute to the understanding of sheep resilience to climate change and provide genetic markers for future breeding strategies aimed at enhancing livestock sustainability and productivity under changing climatic conditions.

In the present study, we investigate the focal surfaces of the translation surface in the Euclidean space E 3 . We define the focal surfaces of the translation surface and derive conditions under which these surfaces are flat and minimal. Additionally, we provide examples of these surfaces and present visualizations for each type of focal surface of the translation surface in E 3 .

Studies in evolution, ecology and conservation are increasingly based on genetic and genomic inferences. With increased focus on molecular approaches, ethical concerns about destructive or more invasive techniques need to be considered, with a push for minimally invasive sampling to be optimised. Buccal swabs have been increasingly used to collect DNA in a number of taxa, including amphibians. However, DNA yield and purity from swabs is often low, limiting its use. In this study we compare different types of swabs, preservation method and storage, and DNA extraction technique in three case studies to assess the optimal approach for recovering DNA in anurans. Out of the five different types of swab that we tested, Isohelix MS-02 and Rapidry swabs generated higher DNA yields than other swabs. When comparing storage buffers, ethanol is a better preservative than a non-alcoholic alternative. Dried samples resulted in similar or better final DNA yields than ethanol-fixed samples if kept cool. DNA extraction via a Qiagen™ DNeasy Blood and Tissue Kit and McHale’s salting out extraction method resulted in similar DNA yields but the Qiagen™ kit extracts contained less contamination. We also found that samples produce better DNA recovery if frozen as soon as possible after collection. We provide recommendations for sample collection and extraction under different conditions, including budgetary considerations, size of individual sampled, access to cold storage facilities, and DNA extraction methodology. Maximising efficacy of all of these factors for better DNA recovery will allow buccal swabs to be used for genetic and genomic studies in a range of vertebrates.

This study focuses on predicting climatic parameters, including average temperature, relative humidity, and total precipitation, across various ecological zones in Türkiye using machine learning techniques. The study area encompasses Türkiye’s diverse climatic regions, including the Black Sea, Mediterranean, and continental climates as well as transitional zones. Utilizing meteorological and topographic data from the Turkish State Meteorological Service and digital elevation models, predictive models were developed using Random Forest (RF), Gradient Boosting Regressor (GBR), and Gated Recurrent Unit (GRU) deep learning methods. The performance of these models was evaluated based on R² and RMSE values, highlighting GRU as the most reliable method for predicting the average temperature and relative humidity, particularly when utilizing ten years of training data. Geostatistical methods were then employed to map the spatial variability of the predicted climatic parameters, illustrating temperature gradients across different regions of Türkiye and revealing trends in relative humidity and total precipitation. Overall, this study provides valuable insights into the application of machine learning techniques for climate prediction and offers a comprehensive understanding of climatic patterns across Türkiye’s ecological zones.

Robots have a profound impact on human production and life, which have been developed by leaps and bounds in recent decades. The original robot is large and requires a wired power supply to drive, whose working space and functions are limited. As the higher and higher requirements for operations in complex environments, researchers continue to develop wireless driven miniature robots. In this paper, the ratio and deformation properties of PNIPAM and PEGDA hydrogels were researched, and the microcrawls and microgrippers with 3D structure were prepared. They have light stimulus response and magnetic response characteristics, and can be reversibly transformed from 3D to two-dimensional structure to complete crawling and transportation functions. Highlights: 1. PNIPAM-PEGDA bilayer structure with photo-magnetic response was prepared based on secondary curing technology. 2. The optimal ratio and thickness of PNIPAM hydrogel were studied. 3. Crawler and gripper were made based on the bilayer structure for transport.

Social integration of the migrant population is the goal of new urbanization in China, which is also inextricably linked to access to higher education. Based on data from a sample of 105,219 rural--urban migrants from the 2017 China Migrant Population Dynamic Monitoring Survey, whether acquisition of higher education among the surveyed sample affected their level of social integration was analyzed using mediation effect and multilevel linear models. The results showed that access to higher education effectively promoted the social integration of rural--urban migrants. Higher education can promote migrants' social integration through employment quality factors such as increased work income, employment formality, higher social security level, and reduced work intensity. A greater share of tertiary education enrollment should thus be allocated to rural households. Improving the quality of employment for rural--urban migrants would also help to ameliorate their social integration difficulties.

The devastating global toll precipitated by the SARS CoV-2 outbreak and the profound impact of vaccines in stemming that outbreak has established the need for molecular platforms capable of rapidly delivering effective, safe and accessible medical interventions in pandemic preparedness. We describe a simple, efficient and adaptable process to purify SARS CoV-2 virus-like particles (VLPs) that can be readily scaled for manufacturing. A rapid but gentle method of tangential flow filtration using a 100 kDa semi-permeable membrane concentrates and buffer exchanges 0.5 L of SARS CoV-2 VLP containing supernatant into low salt and optimal pH for anion exchange chromatography. VLPs are washed, eluted under high salt, dialysed into physiological buffer, sterile filtered and aliquoted for storage at – 80 0C. Purification is completed in less than two days. A simple quality control process includes Western blot for coincident detection of Spike, Membrane and Envelope protein as a proxy for intact VLP, ELISA to detect conformationally sensitive Spike using readily available anti-Spike and/or anti-RBD antibodies, and negative stain and immunogold electron microscopy to validate particulate, Spike crowned VLPs. This process to purify SARS CoV-2 VLPs for preclinical studies serves as a roadmap for preparation of more distantly related VLPs for pandemic preparedness.

Movement of atoms in material takes place by a process known as diffusion, which can take place in all the three phases of material. It (diffusion) plays very significant part in number of microstructure changes that occur during processing of metals, alloys, ceramics, semiconductor polymers etc. Diffusion, a mass movement phenomenon of atomic movement between two different points due to thermal and gradient effect. Due to limited experimental facilities, it is very difficult to understand the diffusion phenomenon, so here we use Atomistic computer simulation methods which are gaining momentum due to their realistic prediction powers and visualization capabilities. MD method is useful to narrate the behaviour and structure of the molecules at the microscopic level. We use Newton’s equation of motion to calculate the dynamics of the particle. Using MD (molecular dynamics simulations technique) a computer-based technique, Diffusion coefficient of alloys can be calculated. Molecular dynamics simulations of proposed work will be done using LAMMPS which is Large-scale Atomic/Molecular Massively Parallel Simulator. MD method is useful to narrate the behaviour and structure of the molecules at the microscopic level. Output data that is obtained with the help of molecular dynamic technique can be analyzed using of tools like OVITO and VMD.

A document by Lianghui Zheng. Click on the document to view its contents.

Single-cell proteomics (SCP) has advanced significantly in recent years, with new tools that have been specifically designed for preparation and analysis of single cells now commercially available to researchers. The field is sufficiently mature to be broadly accessible to any lab capable of isolating single cells and performing bulk-scale proteomic analyses. In this review, we highlight recent work in the SCP field that has significantly lowered the barrier to entry, thus providing a practical guide for those who are newly entering the SCP field. We outline the fundamental principles and report multiple paths to accomplish the key steps of a successful SCP experiment including sample preparation, separation and mass spectrometry data acquisition and analysis. We recommend that researchers start with a label-free SCP workflow, as achieving high-quality and quantitatively accurate results is more straightforward than label-based multiplexed strategies. By leveraging these accessible means, researchers can confidently perform SCP experiments and make meaningful discoveries at the single-cell level.

Biological nitrogen fixation by nitrogenase is often assumed to rely exclusively on molybdenum as an enzymatic cofactor, despite molybdenum scarcity in terrestrial ecosystems and recent demonstrations of vanadium nitrogenase (V-Nase) activity in cryptogamic organisms, collectively responsible for over 40% of terrestrial biological nitrogen input. Here we highlight a global role for vanadium in nitrogen biogeochemistry in extratropical forests’ cryptogams. Measurements in bryophytes and cyanolichens from three continents indicate V-Nase activity in each forest surveyed. We use V-Nase regulation by molybdenum content and nitrogen fixation rates to estimate the global contribution of vanadium to nitrogen fixation by extratropical cryptogams as 30%, with human activities likely responsible for a 30% relative decrease since pre-industrial times. This newly discovered global role of vanadium forces a reevaluation of the nitrogen cycle, where including nitrogenase enzymatic heterogeneity will help better predict the response of the terrestrial carbon sink to global change and understand species biogeography.

The IUCN Convention on Biological Diversity Post-2020 Global Biodiversity Framework established a goal to protect at least 30% of earth’s ecosystems by 2030. A key component of this target is the need to conserve representative examples of all ecosystem types. Identification of ecosystem type and locality is an essential first step. We stratified World Terrestrial Ecosystems by zoogeographic regions to identify a total of 2,394 distinct terrestrial ecosystems. We classified these ecosystems by level of protection and conversion. Those identified as vulnerable, endangered, and critically endangered were deemed “crisis ecosystems;” they comprise a quarter of the 2,394 ecosystems. These crisis ecosystems may contain some relatively intact, functioning areas that could serve as the basis to maintain function and perhaps restore more extensive areas. The portion of crisis ecosystems that show low Human Modification are in what we deem “Last Chance Ecosystem” status. Globally, 2.6% of the terrestrial world (2.888 million km2) is in this stage and protection may help meet global representation targets and prevent ecosystem collapse.

One of the most prevalent diseases in the world is malaria. The aim of this work is to investigate Caputo fractional order models with temperature variability in order to analyze the age-related aspects of malaria in a human host. The model is well-posed, both from an epidemiological and mathematical perspective. The model indicates that the rate of mosquito contact and the probability of disease transmission are significant factors in the disease’s spread. The steady states and stability of the model are examined. Using the next-generation approach, the basic reproduction number is obtained. It is demonstrated that, whenever the basic reproduction number is greater than unity, there is a distinct endemic equilibrium that is both locally and globally asymptotically stable under the requirements for the stability of the equilibrium points. The study investigated how temperature variability and fractional order together influence malaria dynamics. We nevertheless revealed the uniqueness of the endemic equilibrium point. The Adams-Bashforth-Moulton numerical technique and simulations of Caputo fractional order with and without temperature variability were performed using MATLAB. According to the model, efforts should be undertaken to reduce mosquito populations and contact rates through the use of chemical or biological treatments, along with any other tactic that lowers the incidence of malaria infection.

Exosomes are cell derived and membrane-surrounded particles that deliver bioactive molecules to various cells. Their small size, low immunogenicity, extended blood circulation, and involvement in cellular communication make them a potentially effective drug carrier. Exosomes found in different biological fluids including mare’s milk, a traditional drink in central Asia. Therefore, the aim of this study is to compare exosomes isolation methodology and determine the stability of mare’s milk-derived exosomes as potential therapeutic carrier. Three extraction methods namely, immunoprecipitation, size exclusion chromatography, and total exosome isolation were compared in terms of exosome characteristics, purity, and content. The isolated exosomes then loaded with quercetin and their ability of increasing its bioavailability were tested in vitro and in vivo. Out of the three tested methods, total exosome isolation appeared to be the most efficient method that produced good quality exosomes, which were then loaded with quercetin and compared to free quercetin and exosomes only. Interestingly, exosomes loaded with 80µM quercetin significantly restored β-galactosidase activity and cellular viability in doxorubicin treated cells more than negative control and exosomes only, with a potency similar to that of 160µM free quercetin. Interestingly, aged model animals treated with exosomes loaded with quercetin showed significantly less frequent patterns of acute and subacute damage in the myocardium, kidneys, and liver compared to the untreated control group of aged models. The current study is a proof-of-concept that shows mare’s milk-derived exosomes are able to be absorbed by cells and animal tissues, which support their potential use as drug carrier.

A document by Maryam Sahibqran. Click on the document to view its contents.

Object: To investigate the association between Kaposi’s sarcoma-associated herpesvirus (KSHV)/human herpesvirus 8 (HHV8) infection and both all-cause and cardiovascular mortality in a representative cohort of US adults. Methods: Data from the National Health and Nutrition Examination Survey III (NHANES III; 1988-1994) were analyzed, including 13,993 participants aged 18-90 years who underwent KSHV serology evaluations. Mortality outcomes were ascertained through December 2019 using the National Death Index. Cox proportional hazards models were employed to examine the association between KSHV seropositivity and mortality, adjusting for potential confounders such as age, sex, ethnicity, body mass index, and smoking status. Results: Over a median follow-up period of 26.5 years, 5,503 deaths were recorded. KSHV seropositivity was associated with an increased hazard of all-cause mortality (Hazard Ratio [HR]: 1.32, 95% Confidence Interval [CI]: 1.03-1.69) and cardiovascular mortality (HR: 1.58, 95% CI: 1.00-2.50) after adjusting for age, sex, ethnicity, and body mass index. However, further adjustment for smoking status attenuated these associations. Notably, the association between KSHV infection and all-cause mortality persisted among women (HR: 1.32, 95% CI: 1.02-1.72) after adjusting for all confounders, whereas the association with cardiovascular mortality was only statistically significant for men (HR: 1.90, 95% CI: 1.02, 3.53). Conclusions: KSHV infection may represent an independent risk factor for all-cause and cardiovascular mortality among US adults. These findings highlight the need for further research to validate these associations in independent populations and to elucidate the biological mechanisms underlying the observed increased mortality associated with KSHV infection.

A document by Francisco-J Renero-C. Click on the document to view its contents.

Detection and Recognition of on-shelf and off-shelf retail products is challenging in computer vision because of an extremely high number of different products. Some of the existing approaches extracted text information to recognize the retail products. However, these approaches work effectively only if the text information, such as product name, price, and expiration date, is explicitly visible in the image. In this paper, a novel image processing framework is implemented to detect and recognize retail products using shape and colour features. This framework comprises of three modules: illumination-invariant representation, colour-based object identification, and shape-based object identification. The images acquired from retail stores may contain reflective effects such as shadows and illuminations because they are captured in an uncontrolled environment that can be eliminated using a three-step process defined in the first module. In the second module, the salient region detection and mean shift segmentation algorithms are utilized to capture the location of the product region based on colour features from a rectified image. After removing backgrounds, the segmented region of interest containing retail products is given as input to the final module. In the final module, a Contour Line Inflection Arc Extraction (CLIAE) algorithm is proposed to detect and recognize retail products using shape features. Finally, the Speeded Up Robust Features (SURF) algorithm is employed to perform the object matching between the known object and the target object. The performance and robustness of the proposed framework are evaluated using two benchmark datasets, GroZi-3.2k and Grocery Products (GP). However, the proposed framework outperforms both combined features-based object recognition algorithms and state-of-the-art retail product recognition algorithms by achieving a recognition accuracy of 95.5% and 95.8% on GroZi-3.2k and GP datasets, respectively. The usefulness of each module in the framework is also demonstrated by conducting a variety of experiments on benchmark datasets.