Miracle-dz/UniFAR-FTUs huggingface dataset:
A Case of Kaposi’s Sarcoma Associated with Disseminated AIDS: The Management Challenges

Background As a malignant tumor derived from vascular endothelial cells, Kaposi’s sarcoma (KS) is quite common in AIDS patients. Nonspecific clinical symptoms often lead to timely diagnosis or wrong treatment, leading to recurrent disease and poor prognosis. Anti-retroviral therapy (ART) could significantly reduce its morbidity and aggressiveness. As one of the ARTs, liposome anthracyclines are the preferred chemotherapy regimen for disseminated KS with multiple organs or tissue invasion. The curative effect is highly related to the degree of immunosuppression. This is the first case of AIDS with Kaposi’s sarcoma, who was cured after ART and two consecutive chemotherapy with doxorubicin liposome without recurrence. This case may provide new ideas and methods for the clinical management of AIDS with Kaposi’s sarcoma. Case Description The patient, a male aged 60 years, was hospitalized on 21/11/2018 following having a cough, expectoration, and difficulty breathing. He was infected with HIV eight years ago and presented symptoms of blood-stained sputum. The patient complained that he had not received ART before. After admission, he was diagnosed as KS with disseminated AIDS after multiple biopsies and histopathological examinations. The patient was treated with ten months of ART (lamivudine+tenofovir+dolutegravir) and 14 times of chemotherapy with doxorubicin liposome (20 mg/m2, three times per week, seven times per course of treatment). The patient’s disease was finally alleviated, and there was no recurrence during the follow-up. Conclusion The reconstitution of immune function and consecutive chemotherapy with doxorubicin liposome play a vital role in treating KS. In addition, for the early general symptoms of AIDS patients, such as thrombocytopenia and hemorrhagic purple papules, it is necessary to increase vigilance and obtain the results of histopathological verification as soon as possible to diagnose KS patients at an earlier stage and realize clinical intervention in time.
Epidemiological application of the cycle threshold value of RT-PCR for estimating infection period in cases of SARS-CoV-2

Epidemiological control of coronavirus disease 2019 (COVID-19) is needed to estimate the infection period of confirmed cases and identify potential cases. The present study, targeting confirmed cases for which the time of COVID-19 symptom onset was disclosed, aimed to investigate the relationship between intervals (day) from symptom onset to testing the cycle threshold (CT) values of real-time reverse transcription-polymerase chain reaction. Of the COVID-19 confirmed cases, those for which the date of suspected symptom onset in the epidemiological investigation was specifically disclosed were included in this study. Interval was defined as the number of days from symptom onset (as disclosed by the patient) to specimen collection for testing. A locally weighted regression smoothing (LOWESS) curve was applied, with intervals as explanatory variables and CT values (CTR for RdRp gene and CTE for E gene) as outcome variables. After finding its non-linear relationship, a polynomial regression model was applied to estimate the 95% confidence interval values of CTR and CTE by interval. The application of LOWESS in 331 patients identified a U-shaped curve relationship between the CTR and CTE values according to the number of interval days, and both CTR and CTE satisfied the quadratic model for interval days. Active application of these results to epidemiological investigations would minimize the chance of failing to identify individuals who are in contact with COVID-19 confirmed cases, thereby reducing the potential transmission of the virus to local communities.
Two-Step Engulfment of Apoptotic Cells

ABSTRACT Apoptotic cells expose phosphatidylserine on their surface as an “eat me” signal, and macrophages respond by engulfing them. Although several molecules that specifically bind phosphatidylserine have been identified, the molecular mechanism that triggers engulfment remains elusive. Here, using a mouse pro-B cell line, Ba/F3, that grows in suspension, we reconstituted the engulfment of apoptotic cells. The parental Ba/F3 cells did not engulf apoptotic cells. Ba/F3 transformants expressing T cell immunoglobulin- and mucin-domain-containing molecule 4 (Tim4), a type I membrane protein that specifically binds phosphatidylserine, efficiently bound apoptotic cells in a phosphatidylserine-dependent manner but did not engulf them. However, Ba/F3 transformants expressing both Tim4 and the integrin αvβ3 complex bound to and engulfed apoptotic cells in the presence of milk fat globule epidermal growth factor factor VIII (MFG-E8), a secreted protein that can bind phosphatidylserine and integrin αvβ3. These results indicate that the engulfment of apoptotic cells proceeds in two steps: Tim4 tethers apoptotic cells, and the integrin αvβ3 complex mediates engulfment in coordination with MFG-E8. A similar two-step engulfment of apoptotic cells was observed with mouse resident peritoneal macrophages. Furthermore, the Tim4/integrin-mediated engulfment by the Ba/F3 cells was enhanced in cells expressing Rac1 and Rab5, suggesting that this system well reproduces the engulfment of apoptotic cells by macrophages.
Prevention of Chronic Obstructive Pulmonary Disease (COPD) Exacerbations with Statin Therapy: A Systematic Review

This systematic review focuses on examining the treatment of chronic obstructive pulmonary disease (COPD) and preventing exacerbations. Despite the pharmacological interventions available, chronic obstructive pulmonary disease (COPD) is not curable. The goal of treatment in chronic obstructive pulmonary disease (COPD) patients is more focused on providing relief of symptoms such as dyspnea and shortness of breath. The purpose is to review the efficacy of daily Statin use in patients with newly diagnosed chronic obstructive pulmonary disease (COPD)
A Rotating Machinery Fault Diagnosis Method Based on Multi-Sensor Fusion and ECA-CNN

Fault diagnosis is critical to maintaining the performance of rotating machinery and ensuring the safe operation of the equipment. Convolutional neural networks (CNNs) have recently shown great potential with excellent automatic feature learning and nonlinear mapping abilities in the field of rotating machinery fault diagnosis. However, the CNN-based methods still suffer from some defects, such as inadequate data utilization and uneconomical computational efficiency, which limit the further improvement of diagnosis performance. Therefore, this paper proposes a fault diagnosis method based on multi-sensor fusion and Convolutional Neural Network with Efficient Channel Attention (ECA-CNN). First, multi-sensor vibration signals are sampled, converted, and channel fused into multi-channel images with rich and comprehensive features. Then, the efficient channel attention mechanism is introduced into CNN to increase the feature learning ability by adaptively scoring and assigning weights to the channel features. The ECA-CNN is proposed to learn representative fault features from multi-sensor fusion data to achieve fault identification. Finally, two experimental cases on the bearing and gearbox datasets prove that the proposed method has excellent performance, strong generalization capability, and high computational efficiency.
Reverse Genetics Systems for Emerging and Re-Emerging Swine Coronaviruses and Applications

Emerging and re-emerging swine coronaviruses (CoVs), including porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and swine acute diarrhea syndrome-CoV (SADS-CoV), cause severe diarrhea in neonatal piglets, and CoV infection is associated with significant economic losses for the swine industry worldwide. Reverse genetics systems realize the manipulation of RNA virus genome and facilitate the development of new vaccines. Thus far, five reverse genetics approaches have been successfully applied to engineer the swine CoV genome: targeted RNA recombination, in vitro ligation, bacterial artificial chromosome-based ligation, vaccinia virus -based recombination, and yeast-based method. This review summarizes the advantages and limitations of these approaches; it also discusses the latest research progress in terms of their use for virus-related pathogenesis elucidation, vaccine candidate development, antiviral drug screening, and virus replication mechanism determination.
Origins and Levels of Seasonal Forecast Skill for Sea Ice in Hudson Bay Using Canonical Correlation Analysis

Abstract Canonical correlation analysis (CCA) is used to estimate the levels and sources of seasonal forecast skill for July ice concentration in Hudson Bay over the 1971–2005 period. July is an important transition month in the seasonal cycle of sea ice in Hudson Bay because it is the month when the sea ice clears enough to allow the first passage of ships to the Port of Churchill. Sea surface temperature (quasi global, North Atlantic, and North Pacific), Northern Hemisphere 500-mb geopotential height (z500), sea level pressure (SLP), and regional surface air temperature (SAT) are tested as predictors at 3-, 6-, and 9-month lead times. The model with the highest skill has three predictors—fall North Atlantic SST, fall z500, and fall SAT—and significant tercile forecast skill covering 61% of the Hudson Bay region. The highest skill for a single-predictor model is from fall North Atlantic SST (6-month lead). Fall SST explains 69% of the variance in July ice concentration in Hudson Bay and a possible atmosp.
Moroccan students’ acceptance and use of Learning Management Systems (LMS) platforms to enhance writing skills: Moulay Ismail University as a case study

Within this increasingly globalized world, technology integration in education has become a critical component of teaching and learning to prepare learners to face 21st-century challenges. Learning Management System (LMS) is a software application for administering, documenting, tracking, reporting, and delivering e-learning courses or training. LMS platforms offer a diverse learning environment that is highly interactive, dynamic, and nonlinear, making them appropriate for teaching writing, which is a crucial twenty-first-century skill. Using LMS in teaching writing skills can provide students with more opportunities to practice and develop their writing skills outside the classroom, thereby promoting learners' autonomy. Additionally, using LMS to teach writing skills can help address the challenges teachers face in the classroom, such as limited time and resources. LMS allows students to engage in writing activities at their own pace and in their own time, and teachers can monitor and assess their progress online. To this end, the study aims to explore the factors influencing the integration of Learning Management Systems (LMS) in teaching writing skills from the perspective of student acceptance and usage at the University of Moulay Ismail, Meknes. The study uses the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework to guide the research questions and hypotheses. The UTAUT model is widely used in technology acceptance research, and it identifies several factors that influence individuals' intention to use and actual usage of technology, including performance expectancy, effort expectancy, social influence, and facilitating conditions. The result revealed that EE, PE, SI, and FC significantly impact student behavioral intention to accept and use LMS for writing improvement.
Fluid-solid substitution in rocks with disconnected and partially connected porosity

It is usually believed that Gassmann fluid substitution can be performed only for a fully interconnected portion of the pore space. While this is certainly true, the presence of disconnected porosity does not necessarily invalidate Gassmann’s predictions. This unconventional view is supported withananalyticproofoftheequivalenceofGassmanntheory and the noninteraction approximation for the effective elasticity of solids with isolated self-similar pores. Numerical tests for more realistic microgeometries, where pores have diverse shapes and the pore space is partially disconnected, demonstrate that errors in Gassmann-type infill substitution are typically small and unlikely to exceed a few percent as long as the aspect ratios of pores are greater than approximately0.2. Ifthefracture-likeporesarealignedorelasticities of the substituted infills are close, Gassmann theory remains accurateforisolatedporeswithsmalleraspectratios.
A fine balance: epigenetic control of cellular quiescence by the tumor suppressor PRDM2/RIZ at a bivalent domain in the cyclin a gene

Adult stem cell quiescence is critical to ensure regeneration while minimizing tumorigenesis. Epigenetic regulation contributes to cell cycle control and differentiation, but few regulators of the chromatin state in quiescent cells are known. Here we report that the tumor suppressor PRDM2/RIZ, an H3K9 methyltransferase, is enriched in quiescent muscle stem cells in vivo and controls reversible quiescence in cultured myoblasts. We find that PRDM2 associates with >4400 promoters in G0 myoblasts, 55% of which are also marked with H3K9me2 and enriched for myogenic, cell cycle and developmental regulators. Knockdown of PRDM2 alters histone methylation at key promoters such as Myogenin and CyclinA2 (CCNA2), and subverts the quiescence program via global de-repression of myogenesis, and hyper-repression of the cell cycle. Further, PRDM2 acts upstream of the repressive PRC2 complex in G0. We identify a novel G0-specific bivalent chromatin domain in the CCNA2 locus. PRDM2 protein interacts with the PRC2 protein EZH2 and regulates its association with the bivalent domain in the CCNA2 gene. Our results suggest that induction of PRDM2 in G0 ensures that two antagonistic programs—myogenesis and the cell cycle—while stalled, are poised for reactivation. Together, these results indicate that epigenetic regulation by PRDM2 preserves key functions of the quiescent state, with implications for stem cell self-renewal.
Catalytic depolymerization of lignin by metal and metal oxide: a review

ABSTRACT Lignin, with its rich reserves of phenolic compounds, holds great promise as a candidate for renewable energy and valuable chemical production. However, the complex molecular structure and low reactivity of lignin have impeded progress in this research direction. Consequently, the depolymerization of lignin into high-value small-molecule chemicals has become a new area of focus. Metal and metal oxides have emerged as a promising catalyst to overcome this obstacle due to their high selectivity in depolymerizing lignin and the mild reaction conditions required. This paper reviews the properties, and products of various metal and metal oxides used for lignin depolymerization under microwave, pyrolysis, hydrogenolysis, and oxidation conditions. The research prospects and challenges of metal oxide degradation of lignin are summarized to pave the way for future applications and development of lignin depolymerization.
Spatial Variability of Soil Properties using Nested Variograms at Multiple Scales

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.
Recent and deep pasts in paleoclimate model intercomparison project

Second Workshop of the Palaeoclimate Modelling Intercomparison Project Phase 3;Crewe, United Kingdom, 6–11 May 2012 The Palaeoclimate Modelling Intercomparison Project (PMIP) is an international initiative endorsed by the World Climate Research Programme, the International Geosphere-Biosphere Programme, and the Past Global Changes Project. Its objective is to provide a coherent framework to assess climate models and investigate climate dynamics on the basis of paleoclimate evidence. To this end, PMIP provides protocols for simulations of a set of past epochs with climate models, centralizes model output and facilitates access to it, and organizes syntheses of paleoclimate observations for model evaluation.
Towards Autonomous Robotic Ultrasound Scanning Using the Reinforcement Learning-Based Volumetric Data Navigation Method

Ultrasound scanning is an indispensable diagnostic tool in modern medicine, but obtaining an accurate standard plane relies heavily on the sonographer’s skill and expertise. This paper presents a novel approach toward autonomous robotic ultrasound scanning using a reinforcement learning-based navigation method with volumetric ultrasound data. The proposed method enables an ultrasound robot to autonomously acquire high-quality 2D standard planes from patients, thereby reducing the need for human intervention. The core of the approach is a deep reinforcement learning algorithm that detects 2D standard planes within the 3D ultrasound volume and guides the ultrasound probe to extract high-quality standard planes. To assess the effectiveness of the 2D standard plane detection method, an evaluation was conducted using a realworld ultrasound dataset, and a comparison was made between its performance and that of other state-of-the-art autonomous approaches. The simulation experiment was also conducted to validate the autonomous robotic ultrasound acquisition workflow. Results demonstrate that the reinforcement learning-based volumetric data navigation method outperforms existing techniques in terms of standard plane accuracy and is very effective for volumetric data-based robotic navigation.
The Correlation Between Widal Diagnostic Test, Total Leukocyte Count, and Platelet Count in Suspected Typhoid Fever Patients at RS Aura Syifa Kediri

Typhoid fever is an acute systemic infectious disease that is related to poor personal hygiene and environmental sanitation. The diagnosis of typhoid fever is established through laboratory examinations, including serological, hematological, and bacteriological tests. This research aims to determine the correlation between the Widal diagnostic test and the total leukocyte count and platelet count in suspected typhoid fever patients at RS Aura Syifa Kediri. The study design used in this research is quantitative descriptive analysis with a cross-sectional approach. The data was collected retrospectively from secondary sources, specifically medical records of patients from August 1, 2021, to March 31, 2022, at RS Aura Syifa Kediri. The total population comprised 157 patients, and a purposive sampling method was used to select 41 patients who met the inclusion and exclusion criteria. The statistical analysis using the Spearman correlation test resulted in p-values ≥ α = 0.05 for the following correlations: Widal test O with leukocytes (0.538 ≥ 0.05), Widal test H with leukocytes (0.915 ≥ 0.05), Widal test O with platelets (0.476 ≥ 0.05), and Widal test H with platelets (0.965 ≥ 0.05). These findings indicate that there is no significant correlation between the Widal test O and H with the platelet count in patients with typhoid fever. Therefore, it can be concluded that there is no significant relationship between the Widal test O and H results and the platelet count in typhoid fever patients.
Characterization of a Thermophilic and Inhibitor-Tolerant GH1 β-Glucosidase Present in a Hot Spring

β-glucosidase is a key enzyme in the degradation of lignocellulosic biomass, which is responsible for the conversion of oligosaccharides from cellulose hydrolysates to glucose. However, its required high temperatures and the presence of inhibitors have limited its use in industry. In this study, a new β-glucosidase gene, named thbg2, was obtained from the metagenome Ruidian Hot Spring, Tengchong City, Yunnan Province, southwestern China. The gene was synthesized, cloned, heterologously expressed, and enzymatically characterized. Its optimum temperature and pH were 60 °C and pH 5.6, respectively. ThBg2 exhibited more than 60% relative activity in temperatures ranging from 40 °C to 70 °C and across a pH of 4.0–6.6. It maintained 100% relative activity after incubation at either 50 °C for 24 h or 60 °C for 12 h and more than 80% residual activity after incubation at pH 4.0–6.0 for 24 h. Moreover, it maintained more than 80% relative activity in the presence of heavy metal ions, ethanol, SDS etc. Furthermore, glucose yields from corn stalks increased by 20% after ThBg2 (0.05 mg/mL) was added to the commercial cellulase reaction system. Overall, this work identified a thermophilic and inhibitor-tolerant β-glucosidase with potential applications in commercial lignocellulose utilization and the bioenergy industry.
Feedbacks in Emission-Driven and Concentration-Driven Global Carbon Budgets

AbstractEmissions of CO2 into the atmosphere affect the carbon budgets of the land and ocean as biogeochemical processes react to increased CO2 concentrations. Biogeochemical processes also react to changes in temperature and other climate parameters. This behavior is characterized in terms of carbon–concentration and carbon–climate feedback parameters. The results of this study include 1) the extension of the direct carbon feedback formalism of Boer and Arora to include results from radiatively coupled simulations, as well as those from the biogeochemically coupled and fully coupled simulations used in earlier analyses; 2) a brief analysis of the relationship between this formalism and the integrated feedback formalism of Friedlingstein et al.; 3) the feedback analysis of simulations based on each of the representative concentration pathways (RCPs) RCP2.6, RCP4.5, and RCP8.5; 4) a comparison of the effects of specifying atmospheric CO2 concentrations or CO2 emissions; and 5) the quantification of the rel.