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A total of 10,696 randomly selected sheep have been collected in two slaughterhouses in the north of Algeria (El Harrach and Boufarik) to determine the prevalence of muscular cysticercosis and macroscopic cysts of sarcosporidiosis, to find out the association between prevalence and potential risk factors, as well as to assess the distribution of these parasites in the surface’s muscles of slaughtered sheep. All of the slaughtered sheep carcasses were visually and carefully inspected. Cysticercosis and sarcosporidiosis were found in 220 (2.06 %) and 76 (0.7 %) sheep, respectively. For both diseases, the prevalence was significantly higher in females than males. The prevalence of Cysticercus ovis increased with age, and the difference was statistically significant (P < 0.0001), while all infected animals were old (over 5 years old) for sarcosporidiosis. For C. ovis, it didn’t have significant difference between the seasons, however, all sheep were infected in the spring for sarcosporidiosis. All the detected cysts of C. ovis were non-viable, and were more frequently detected in the heart (51.82 %), followed by the diaphragm (30.77 %) and the oesophagus (17.41 %). This anatomical distribution of C. ovis cysts showed a significant variation (P < 0.001) in different predilection sites. Whereas, for sarcosporidiosis, the species involved was identified as S. gigantea by histology and were distributed in the organs as follows: the skeletal muscles (38.15 %), the oesophagus (31.57 %) and the diaphragm (30.26 %); no significant difference were noted between the 3 sites. The present study has revealed that these parasites are present in Algeria. Appropriate control measures need to be introduced to eradicate these parasites in sheep.

Muscular samples of the oesophagus and diaphragm of 335 sheep collected from the slaughterhouse of El Harrach were analyzed by the histopathological method to describe the morphology of two species of Sarcocystis: S. arieticanis and S. tenella. The cysts were counted and measured with a micrometer for their dimensions. A total of 895 cysts were measured. The width, length, shape index (length/width), the thickness of the wall and the length of the projections were recorded. The thick-walled cysts of S. tenella were 10—450 μm long (the mean ± SD value was 50.35 μm ± 1.380) and 1—110 μm (the mean ± SD value was 27.51 μm ± 0.533) wide. The cyst walls were 0.5—4 μm thick (the mean ± SD value was 1.547 μm ± 0.020) and provided with radial striations. The shape index was 1—14 μm (the mean ± SD value was 1.93 ± 0.045). While in the S. arieticanis, the cyst wall was thin and had long hair-like protrusions, the cysts measured 8—780 μm (the mean ± SD value was 123.13 μm ± 12.799) in length and 5—100 μm (the mean ± SD value was 37.00 μm ± 1.68) in width. The hair-like protrusions reached a length of 3—14 μm (the mean ± SD value was 5.428 ± 0.353) and the shape index was 1—17 μm (the mean ± SD value was 3.10 ± 0.281). For the length, the width and the shape index, the differences were statistically significant between thin-walled cysts and thick-walled cysts. The general structural features of the cysts, previously described by other authors, were confirmed.

The decision to explore a novel option or exploit a known one — referred to as the explore-exploit trade-off — has received much attention from diverse fields of research, ranging from computer science to developmental psychology. However, much of the work on this topic has focused exclusively on an individual agent acting alone, a scenario that does not fully capture the rich social dynamics of human decision-making. In particular, the presence and participation of others can theoretically influence the decision to explore or exploit. One factor which may affect how individuals navigate the explore-exploit tradeoff is the presence of caregivers, who can help buffer the downside costs of more exploratory decision making. Across two pre-registered studies, we investigated whether children and adults predicted more or less exploratory behavior in the presence of a caregiver. In Study 1, we presented U.S. American children (N=87, ages 4 to 8) with vignettes of other children faced with the choice of exploring a novel option or exploiting a known one across a range of domains. In the vignettes, the characters either faced these decisions alone or in the presence of a parent. In Study 2, we presented the same vignettes to U.S. American adults (N=79). Across both studies, and as predicted, we found that both children and adults believed others would be more exploratory in the presence of caregivers. These results add important nuance to our understanding of how individuals navigate the explore-exploit tradeoff, and highlight the role of the social context in shaping these decisions. We aim to build on these results on future work centralizing the role and function of care in decision-making and exploration.

Abstract Dedifferentiated liposarcoma (DDLPS) is the most frequent high-grade soft tissue sarcoma subtype. It is characterized by a component of undifferentiated tumor cells coexisting with a component of well-differentiated adipocytic tumor cells. Both dedifferentiated (DD) and well-differentiated (WD) components exhibit MDM2 amplification, however their cellular origin remains elusive. Using single-cell RNA sequencing, DNA sequencing, in situ multiplex immunofluorescence and functional assays in paired WD and DD components from primary DDLPS tumors, we characterize the cellular heterogeneity of DDLPS tumor and micro-environment. We identify a population of tumor adipocyte stem cells (ASC) showing striking similarities with adipocyte stromal progenitors found in white adipose tissue. We show that tumor ASC harbor the ancestral genomic alterations of WD and DD components, suggesting that both derive from these progenitors following clonal evolution. Last, we show that DD tumor cells keep important biological properties of ASC including pluripotency and that their adipogenic properties are inhibited by a TGF-β-high immunosuppressive tumor micro-environment.

Abstract Background There is a growing demand for colonoscopy, worldwide, resulting in increased rate of inappropriate referrals. This “overuse” of colonoscopies has become a major burden for health care. Objectives to assess the appropriateness of colonoscopies performed at the endoscopy unit of the university hospital of Sousse and to compare these results of appropriateness according to the European Panel of Appropriateness of Gastrointestinal Endoscopy (EPAGE) I and EPAGE II criteria. Patients and methods this cross-sectional study included all consecutive patients referred for a diagnostic colonoscopy, between January 2017 and December 2018. Patients referred for exclusively therapeutic indications, those with incomplete colonoscopies were not included. Patients with poor bowel preparation or missing data were also excluded. Indications were assessed using the EPAGE I and EPAGE II criteria. Results From 1972 consecutive patients, 1307 were included. Overall, 986 (75.4%) of all referrals were for out-patients. The majority of patients were referred by gastroenterologists (n = 1026 patients; 78.5%), followed by general surgeons (n = 85; 6.5%). The commonest indications were lower abdominal symptoms (275; 21%) followed by uncomplicated diarrhea (152; 11.6%). Relevant findings were present in 363 patients (27.7%). Neoplastic lesions were the dominant finding in 221 patients (16.9%). EPAGE I and EPAGE II criteria were applicable for 1237 (88.8%) and 1276 (97.7%) patients respectively. Hematochezia and abdominal pain recorded the highest inappropriate rates with both sets of criteria. Appropriate colonoscopies increased to 76.4% when EPAGE II criteria were applied; whereas uncertain and inappropriate procedures decreased to 10.3% and 10.9% respectively Appropriateness of indication was significantly higher in hospitalized patients. For the EPAGE II criteria, the specialty of the referring physician was also significantly associated to the appropriate use. The agreement between EPAGE I and EPAGE II criteria was slight using the weighted version of k (k = 0.153). Conclusions The updated and improved EPAGE II guidelines are a simple and valid tool for assessing the appropriateness of colonoscopies. They decreased the inappropriate rate and the possibility of missing potentially severe diagnoses.

Abstract Extended teleparallel gravity, characterized by function F(Q), where Q is the non-metricity scalar, is one of the most promising approaches to general relativity. In this paper, we reexamine a specific dynamical dark energy model, which is indistinguishable from the $$\Lambda $$ Λ CDM model at the present time and exhibits a special event in the future, within F(Q) gravity. To constrain the free parameters of the model, we perform Markov chain Monte Carlo (MCMC) analysis, using the last data from $$\hbox {Pantheon}^{+}$$ Pantheon + and the latest measurements of the H(z) parameter, combined. On the basis of this analysis, we find that our dynamical dark energy model, in the context of F(Q) gravity, lies in the quintessence regime rather than in the phantom regime, as in the case of general relativity. Furthermore, this behavior affects the future expansion of the Universe, as it becomes decelerating at a $$1\sigma $$ 1 σ confidence level for $$z

Soil erosion, triggered by rainfall and runoff, poses a significant challenge for Mediterranean countries, leading to sedimentation in dam reservoirs, decreased storage capacities, and reduced agricultural fertility. Among various erosion estimation models, the RUSLE equation stands out for its consistency and minimal data requirements. The present study aims to utilize geographic information systems (GIS) software to quantify and map soil loss in the Isser watershed in northern Algeria employing the RUSLE model to strategically plan development measures and prioritize actions to safeguard high-risk erosion areas. Implementing the RUSLE-GIS approach involves integrating multiple datasets, including precipitation, soil erodibility, topography, vegetation cover, and anti-erosion practices. By combining these factors, a comprehensive map depicting erosion rates is generated. The findings categorize potential soil erosion into six groups, ranging from very low to extremely high. They indicate that 61.5% of the Isser Basin faces erosion, varying from moderate to very high (>20 t ha−1 year−1). In addition, 25% of the total surface experiences erosion levels classified as high to very high (>50 t ha−1 year−1). This underscores the urgent need for anti-erosive measures. These measures aim to safeguard the basin's soils, extend the lifespan of existing dam reservoirs (Koudiet Acerdoune and Beni Amran), and preserve their water potential. HIGHLIGHTS Use the RUSLE-GIS approach by considering all pivotal factors in water erosion processes.; Generate comprehensive factor maps for the entire watershed.; Create a geospatial potential soil erosion map.; Identify areas prone to erosion risks.; Provide a robust foundation for strategic planning to protect high-risk erosion areas, mitigate crop issues, and prolong the longevity of the existing critical dams.;

In this paper, our study is divided into two parts. The first part involves analyzing a coupled system of beam deflection type that involves nonlinear equations with sequential Caputo derivatives. The also system incorporates the Caputo derivatives in the initial conditions, which adds a layer of complexity and realism to the problem. We focus on proving the existence of a unique solution for this system, and highlighting the robustness and applicability of fractional derivatives in modeling complex physical phenomena. In the second part of the paper, we employ conformable fractional derivatives, as defined by Khalil, to examine another system consisting of two coupled evolution equations. By the Tanh method, we derive new progressive waves. The connection between these two parts lies in the use of fractional calculus to extend and enhance classical problems.

In this paper, we observationally test the f(Q) gravity model at both background and perturbation levels using Pantheon+, Hubble measurements, and Redshift Space Distortion Data. We obtain the best-fit parameters by solving numerically the modified Friedmann equations for two distinct cosmological models of f(Q) gravity namely the Power law and Exponential models. This involves performing a Markov Chain Monte Carlo analysis for these specific forms of f(Q). To evaluate the statistical significance of the f(Q) gravity models, we use the Bayesian and corrected Akaike Information Criteria. Our results indicate that the Exponential model in f(Q) gravity is statistically favored over both the Power-law model and the ΛCDM model.

Toxic pollutants released from various human activities persistently pose significant threats to living organisms, affecting soil fertility, and impacting human health. Among the various remediation approaches, phytoremediation has gained popularity due to its cost-effectiveness and environmentally friendly characteristics. This method involves utilizing plant species to restore polluted soils, emphasizing the intrinsic abilities of plants to remediate contaminated environments. There are various phytoremediation approaches and combinations that have been developed, ranging from phytoextraction to rhizofiltration, each tailored to specific contaminants and environmental conditions. While acknowledging the slow and time-consuming nature of the phytoremediation process and its potential impact on plant growth and development, this review emphasizes the increasing significance of this eco-friendly approach. Moreover, the exploration suggests that leveraging plant-microbe interactions could enhance the efficiency of remediating contaminated areas. Furthermore, understanding the microbial mechanisms involved in phytoremediation is crucial for optimizing remediation outcomes. Microbes play a pivotal role in enhancing plant tolerance to pollutants, facilitating pollutant degradation, and promoting plant growth in contaminated environments. Harnessing the power of microbial communities through bioaugmentation or stimulating indigenous microbial populations can significantly improve phytoremediation efficiency. Emerging omics technologies and the application of CRISPR/Cas9 technology in phytoremediation offer promising avenues for advancing soil remediation efforts. Omics approaches, including genomics, transcriptomics, proteomics, and metabolomics, provide insights into the genetic and molecular mechanisms underlying plant responses to pollutants and can aid in identifying key genes or pathways for enhancing phytoremediation efficiency. Meanwhile, CRISPR/Cas9 technology presents an innovative solution for targeted genome editing in plants, enabling precise modification of genes involved in pollutant uptake, tolerance, and detoxification. By engineering plants with enhanced capabilities for metal sequestration or pollutant degradation, CRISPR/Cas9 holds tremendous potential for accelerating the remediation of contaminated soils. This comprehensive review serves as a valuable resource for environmental practitioners and scientists, providing insights into both traditional and innovative technologies that have the potential to transform soil remediation practices, ultimately contributing to a cleaner and healthier environment.

This paper aimed to determine the impact of faculty communication style, student proactiveness, and academic discipline on student academic performance and student-faculty relationship quality in the United Arab Emirates (UAE) higher education context. This study also aimed to contribute to the literature by verifying the mediating impact of communication effectiveness between the selected factors. Using a cross-sectional survey design, the study sample comprised 193 university students, and it was analyzed using partial least squares structural equation modeling (PLS-SEM). The results revealed that academic discipline and the professor’s communication style enhanced communication effectiveness, whereas student proactiveness had a minimal effect. The results also show that effective communication significantly influences students’ academic success and the quality of faculty-student interactions. The mediating role of communication effectiveness has also been proven. These findings underscore the importance of robust communication in the faculty-student dynamics and its impact on academic performance in higher education. This research provides valuable strategies for higher education institutes to develop a high-interaction learning environment to ensure a high level of performance for both professors and students.

In the context of an abrupt shift to online learning, particularly during the COVID-19 pandemic, this study examines the efficacy of Emergency Remote Teaching (ERT) and derives important insights from this transformation. The research investigated ERT's application at Arabian Gulf University (AGU), especially within its College of Graduate Studies (CGS). Employing a mixed-methods approach, blending quantitative and qualitative techniques through two specifically designed questionnaires, the study gathered input from 98% of CGS students and 96% of faculty members. The analysis centered on using platforms such as Zoom and Moodle, integrating diverse teaching strategies, and overall satisfaction with ERT. The findings indicate a gradual increase in satisfaction levels with ERT among students and faculty, reaching its zenith towards the study period’s conclusion. Importantly, these satisfaction levels did not vary significantly based on gender or academic qualification. The outcomes suggest that given AGU's heterogeneous student body, ERT can effectively replace traditional teaching methods in both crisis situations and regular conditions. Nonetheless, the paper underscores AGU's need to develop precise guidelines and policies for an effective blended learning approach. The implications of this study extend broadly, offering valuable insights for global universities that primarily employ traditional teaching techniques. It contributes to the conversation regarding higher education institutions’ capacity to adapt to ERT, highlighting both the challenges and opportunities in contexts where, traditionally, only in-person taught degrees are prevalent.

Accurate forecasting of solar power output and load demand is critical for the efficient operation and management of isolated microgrids, where reliability and sustainability are paramount. Traditional methods often struggle with data scarcity, limitations in capturing intricate temporal dynamics, and lack of scalability. This research introduces a novel multi-task learning (MTL) model, the Self-Aware Quantized Multi-Task ConvLSTM (SAQ-MTCLSTM), which addresses these challenges by jointly forecasting solar power and load demand while leveraging shared representations across these interdependent time series. The SAQ-MTCLSTM incorporates a sophisticated architecture that combines convolutional and LSTM layers with self-aware quantization to enhance computational efficiency and model adaptability. This allows for effective knowledge transfer, improved data utilization, and the capture of intricate temporal patterns. Evaluated on a real-world isolated microgrid dataset from the Micro Reseau Mafate research project, the model demonstrates significant improvements in forecasting accuracy, with MSE values of 0.0021 for solar power output and 0.0037 for load demand forecasting, compared to single-task and other advanced models. Extensive experiments highlight the impact of data scarcity, seasonality patterns, and microgrid topology on forecasting performance. Such forecasting is essential to optimize the integration and utilization of renewable resources, enhancing operational stability and reducing dependency on external energy supplies.

BackgroundThe rapid evolution of SARS-CoV-2 imposed a huge challenge on disease control. Immune evasion caused by genetic variations of the SARS-CoV-2 spike protein’s immunogenic epitopes affects the efficiency of monoclonal antibody–based therapy of COVID-19. Therefore, a rapid method is needed to evaluate the efficacy of the available monoclonal antibodies against the new emerging variants or potential novel variants. ObjectiveThe aim of this study is to develop a rapid computational method to evaluate the neutralization power of anti–SARS-CoV-2 monoclonal antibodies against new SARS-CoV-2 variants and other potential new mutations. MethodsThe amino acid sequence of the extracellular domain of the spike proteins of the severe acute respiratory syndrome coronavirus (GenBank accession number YP_009825051.1) and SARS-CoV-2 (GenBank accession number YP_009724390.1) were used to create computational 3D models for the native spike proteins. Specific mutations were introduced to the curated sequence to generate the different variant spike models. The neutralization potential of sotrovimab (S309) against these variants was evaluated based on its molecular interactions and Gibbs free energy in comparison to a reference model after molecular replacement of the reference receptor-binding domain with the variant’s receptor-binding domain. ResultsOur results show a loss in the binding affinity of the neutralizing antibody S309 with both SARS-CoV and SARS-CoV-2. The binding affinity of S309 was greater to the Alpha, Beta, Gamma, and Kappa variants than to the original Wuhan strain of SARS-CoV-2. However, S309 showed a substantially decreased binding affinity to the Delta and Omicron variants. Based on the mutational profile of Omicron subvariants, our data describe the effect of the G339H and G339D mutations and their role in escaping antibody neutralization, which is in line with published clinical reports. ConclusionsThis method is rapid, applicable, and of interest to adapt the use of therapeutic antibodies to the treatment of emerging variants. It could be applied to antibody-based treatment of other viral infections.