Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of microbiological influences on the transport properties of intact mudstone and sandstone and its relevance to the geological disposal of radioactive waste

Abstract The role of the microbial activity on the transport properties of host rocks for geological repositories, particularly in the far-field, is an area of active research. This paper compares results from experiments investigating changes in transport properties caused by microbial activity in sedimentary rocks in Japan (mudstones) and sandstone (UK). These experiments show that both Pseudomonas denitrificans and Pseudomonas aeruginosa appear to survive and thrive in pressurized flow-through column experiments which utilized host rock materials of relevance to radioactive waste disposal. Indeed, despite there being a difference in the numbers of organisms introduced into both biotic experiments, numbers appear to stabilize at ~105 ml-1 at their completion. Post experimental imaging has highlighted the distinct differences in biofilm morphology, for the chosen rock types and bacteria, with Pseudomonas aeruginosa derived biofilms completely covering the surface of the sandstone host and Pseudomonas denitrificans forming biofilament structures. Regardless of substrate host or choice of microbe, microbial activity results in measurable changes in permeability. Such activity appears to influence changes in fluid flow and suggests that the transport of radionuclides through the far-field will be complicated by the presence of microbes.
Imaging and Genetic Tools for the Investigation of the Endocannabinoid System in the CNS

As central nervous system (CNS)-related disorders present an increasing cause of global morbidity, mortality, and high pressure on our healthcare system, there is an urgent need for new insights and treatment options. The endocannabinoid system (ECS) is a critical network of endogenous compounds, receptors, and enzymes that contribute to CNS development and regulation. Given its multifaceted involvement in neurobiology and its significance in various CNS disorders, the ECS as a whole is considered a promising therapeutic target. Despite significant advances in our understanding of the ECS’s role in the CNS, its complex architecture and extensive crosstalk with other biological systems present challenges for research and clinical advancements. To bridge these knowledge gaps and unlock the full therapeutic potential of ECS interventions in CNS-related disorders, a plethora of molecular–genetic tools have been developed in recent years. Here, we review some of the most impactful tools for investigating the neurological aspects of the ECS. We first provide a brief introduction to the ECS components, including cannabinoid receptors, endocannabinoids, and metabolic enzymes, emphasizing their complexity. This is followed by an exploration of cutting-edge imaging tools and genetic models aimed at elucidating the roles of these principal ECS components. Special emphasis is placed on their relevance in the context of CNS and its associated disorders.
Constitutive Interleukin-7 Cytokine Signaling Enhances the Persistence of Epstein–Barr Virus-Specific T-Cells

The efficacy of therapeutic T-cells is limited by a lack of positive signals and excess inhibitory signaling in tumor microenvironments. We previously showed that a constitutively active IL7 receptor (C7R) enhanced the persistence, expansion, and anti-tumor activity of T-cells expressing chimeric antigen receptors (CARs), and C7R-modified GD2.CAR T-cells are currently undergoing clinical trials. To determine if the C7R could also enhance the activity of T-cells recognizing tumors via their native T-cell receptors (TCRs), we evaluated its effects in Epstein–Barr virus (EBV)-specific T-cells (EBVSTs) that have produced clinical benefits in patients with EBV-associated malignancies. EBVSTs were generated by stimulation of peripheral blood T-cells with overlapping peptide libraries spanning the EBV lymphoma antigens, LMP1, LMP2, and EBNA 1, followed by retroviral vector transduction to express the C7R. The C7R increased STAT5 signaling in EBVSTs and enhanced their expansion over 30 days of culture in the presence or absence of exogenous cytokines. C7R-EBVSTs maintained EBV antigen specificity but were dependent on TCR stimulation for continued expansion. C7R-EBVSTs produced more rapid lymphoma control in a murine xenograft model than unmodified EBVSTs and persisted for longer. The findings have led to a clinical trial, evaluating C7R-EBVSTs for the treatment of refractory or relapsed EBV-positive lymphoma (NCT04664179).
WEttING AND DRyING: REDuCING GREENhOuSE GAS EmISSIONS AND SAvING WAtER FROm RICE PRODuCtION

Summary A sustainable food future will require reductions in greenhouse gas emissions from agriculture even as the world produces substantially more food. The production of rice, the staple crop for the majority of the world’s population, emits large quantities of methane, a potent greenhouse gas. According to various governments, global rice production emits 500 million tons of greenhouse gases (carbon dioxide equivalent) per year—or at least 10 percent of total agricultural emissions. The figure may be closer to 800 million tons when adjusted for new estimates by the Intergovernmental Panel on Climate Change of the sustained warming effect of methane. Although uncertain, there is evidence that increasing levels of carbon dioxide in the atmosphere could also increase future rice-related emissions substantially through its effect on soil microbes. Most of the world’s rice grows in inundated conditions, and one of the most promising techniques for reducing rice-related emissions is to reduce or interrupt the periods of flooding. The production of rice in flooded paddies produces methane because the water blocks oxygen from penetrating the soil, creating conditions conducive for methane-producing bacteria. Shorter flooding intervals and more frequent interruptions of flooding lower bacte rial methane production and thus methane emissions.
Correlation of metal ions with specific brain region volumes in neurodegenerative diseases

Background/aim There are reports stating that deteriorations in metal homeostasis in neurodegenerative diseases promote abnormal protein accumulation. In this study, the serum metal levels in Alzheimer’s disease (AD) and Parkinson’s disease (PD) and its relationship with the cortical regions of the brain were investigated. Materials and methods The patients were divided into 3 groups consisting of the AD group, PD group, and healthy control group (n = 15 for each). The volumes of specific brain regions were measured over the participants’ 3-dimensional magnetic resonance images, and they were compared across the groups. Copper, zinc, iron, and ferritin levels in the serums were determined, and their correlations with the brain region volumes were examined. Results The volumes of left hippocampus and right substantia nigra were lower in the AD and PD groups, while the volume of the left nucleus caudatus (CdN) and bilateral insula were lower in the AD group compared to the control group. Serum zinc levels were lower in the AD and PD groups, while the iron level was lower in the PD group in comparison to the control group. In addition, the serum ferritin level was higher in the AD group than in the control group. Serum zinc and copper levels in the AD group were positively correlated with the volumes of the right entorhinal cortex, thalamus, CdN, and insula. Serum zinc and copper levels in the PD group showed a negative correlation with the left nucleus accumbens (NAc), right putamen, and right insula volumes. While the serum ferritin level in the PD group displayed a positive correlation with the bilateral CdN, putamen, and NAc, as well as the right hippocampus and insula volumes, no area was detected that showed a correlation with the serum ferritin level in the AD group. Conclusion A relationship was determined between the serum metal levels in the AD and PD groups and certain brain cortical regions that showed volumetric changes, which can be important for the early diagnosis of neurodegenerative diseases.
Receptor-based approaches and therapeutic targets in Alzheimer’s disease along with role of AI in drug designing: Unraveling pathologies and advancing treatment strategies

Alzheimer’s disease (AD) is a prevalent cause of dementia in the elderly, characterized by progressive cognitive decline and neurodegeneration. This review focuses on the etiology of AD, the role of various receptors [TNF (Tumor necrosis factor) receptor, nAChR (Neuronal nicotinic acetylcholine receptors), NMDARs (N-Methyl-D-aspartate receptors), APOE (Apolipoprotein E) receptor, and amyloid-beta receptor], and risk factors contributing to its development. AD progresses through mild, moderate, and severe stages, each exhibiting distinct symptoms. The hallmark pathologies are neurofibrillary tangles and amyloid plaques, comprised of hyperphosphorylated tau protein and amyloid-beta peptides, respectively. Current pharmacotherapeutic options alleviate symptoms but lack a complete cure. To address the challenges in developing effective AD treatments, researchers have turned to artificial intelligence (AI) and computational approaches in drug design. AI techniques, including machine learning and molecular docking, enable the analysis of large datasets and prediction of molecular interactions between potential drug candidates and target receptors. Virtual screening and molecular modeling aid in identifying novel therapeutic compounds. Predictive modeling and optimization algorithms optimize drug properties and predict efficacy. AI also facilitates the repurposing of existing drugs by analyzing their interactions with AD-related receptors and pathways. Clinical trial optimization using AI algorithms enhances patient selection, treatment monitoring, and outcome prediction. Integrating AI into AD drug design holds tremendous promise for accelerating the discovery of effective interventions. By leveraging AI’s capabilities, researchers can efficiently analyze extensive data, predict drug-target interactions, and optimize drug properties, leading to the identification of novel AD treatments. However, further research and validation are needed to translate AI-driven drug design approaches into clinically viable solutions for AD patients. Through continued advancements in AI and collaborative efforts, the development of targeted and advanced therapies for AD is within reach.
Stormwater and Aquatic Life: Making the Connection Between Impervious Cover and Aquatic Life Impairments for TMDL Development in Connecticut Streams

Stormwater can be a significant source of stressors to aquatic stream biota in many urban areas. The 2006 List of Connecticut Waterbodies Not Meeting Water Quality Standards has a total of 105 stream segments that do not meet aquatic life goals established in Connecticut’s Water Quality Standards. At least 58% of these waterbodies have stressors related to urbanization as the suspected cause of the impairment (e.g. stormwater, habitat modifications, erosion, sedimentation etc.). Modeling stormwater impacts can be challenging due to their episodic nature. In many instances, surrogate measures of stormwater impacts may provide useful benchmarks when data are unavailable to support more complex stormwater models. The State of Connecticut, Department of Environmental Protection (DEP), has developed an Impervious Cover (IC) model applicable in situations where the most probable cause of the aquatic life support impairment is stormwater. An IC target of 12% was established for developing Total Maximum Daily Loads (TMDLs) based on correlating the percent IC upstream of macroinvertebrate monitoring locations with a final assessment of passing or failing Connecticut's aquatic life standards. Connecticut DEP has used the IC Model to develop a TMDL for a small stream in Eastern Connecticut and has engaged stakeholders to focus stormwater management efforts to restore aquatic life in the brook.
Examining ESL Preservice Teachers’ Personal Factors That Best Predict Their Confidence to Integrate Technology in Future Classrooms

This study was designed to examine preservice teachers' personal characteristics that can predict their confidence to integrate technology in their teaching practices. The investigators used a questionnaire designed based on Bandura’s Social Cognitive Theory to ask 168 ESL preservice teachers enrolled in the English Department in a public university located in central Anatolia. The results of this study found that the use of technology during ESL preservice teachers' training was the most significant predictor of their self-efficacy to integrate technology in their teaching practices, then followed by the number of years they are attending the education training and finally their learning preferences such as the use of multimedia and digital materials. The results of this study also found that ESL preservice teachers’ gender and age were insignificant causes for building their confidence to integrate technology. The study also has found that there is a significant relationship between ESL preservice teachers' use of technology and their levels of self-efficacy and this relationship was strong and positive. These findings indicate that prior experience with technology among preservice teachers is a key component in determining their confidence in integrating technology into teaching and learning. The study offers vital insights into how teacher education programs might effectively prepare ESL preservice teachers for technology integration. Teacher education programs should prioritize chances for preservice teachers to obtain practical experience using technology in classroom settings. Finally, the investigators provide interpretation and recommendations based on these findings.Keywords: ESL, Personal Factors, Preservice Teachers, Self-Efficacy, Technology Integration
Endurance Exercise Attenuates Established Progressive Experimental Autoimmune Encephalomyelitis and Is Associated with an Amelioration of Innate Immune Responses in NOD Mice

Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease causing axonal degeneration and demyelination. Exercise in mice with active monophasic experimental autoimmune encephalomyelitis (EAE) attenuates disease severity associated with diverse impacts on T cell-mediated immunity. However, studies have so far focused on preventive approaches. In this study, we investigated the impact of endurance exercise on established EAE disease in a model of secondary progressive MS. When the exercise program on motorized running wheels was started at disease manifestation, the disease course was significantly ameliorated. This was associated with a significant decrease in B cell, dendritic cell, and neutrophil cell counts in the central nervous system (CNS). Furthermore, we observed an increased expression of major histocompatibility complex class II (MHC-II) as well as alterations in costimulatory molecule expression in CNS B cells and dendritic cells. In contrast, T cell responses were not altered in the CNS or periphery. Thus, exercise training is capable of attenuating the disease course even in established secondary progressive EAE, potentially via modulation of the innate immune compartment. Further studies are warranted to corroborate our findings and assess the potential of this lifestyle intervention as a complementary therapeutic strategy in secondary progressive MS patients.
A Retrospective Review of Chronic Non-Communicable Dermatoses Among Older Adults at a Tertiary Healthcare Facility in Southwestern Nigeria

Introduction Aging is a ubiquitous human trait that predisposes older persons to chronic diseases. Compared with systemic non-communicable diseases, a significant gap exists in literature on the burden of non-communicable dermatoses (NCDs) amongst older adults particularly in low and middle-income countries. Objectives The aim of this study was to document the epidemiology and clinical pattern of non-communicable skin diseases among older adults at a tertiary healthcare facility in Southwestern Nigeria. Methods We conducted a retrospective review of medical records of ambulant adults aged ≥60 years referred for dermatological care at a teaching hospital in ile-ife, South-Western Nigeria between February 2017 and February 2022. The frequency and pattern of NCDs were recorded for descriptive statistical analysis using SPSS 20 statistics software. The level of statistical significance was set at 0.05. Results A total 553 medical records were reviewed with a female: male ratio of 1.3:1 The mean age of the study population was 68.85 ±7.87. Six out of every 10 patients (60.6%) had at least one chronic NCD. The incidence of chronic NCDs declined with increasing age. Chronic eczemas (22.4%), pigmentary dermatoses (9.4%) and skin tumors (8.7%) were the most frequent chronic non-communicable dermatoses recorded. Older males had a significantly higher incidence of chronic eczemas while chronic urticarias and skin tumors demonstrated significant female preponderance. Conclusions There is a high burden of chronic NCDs with significant gender disparities among older adults with skin problems in Nigeria. Pre-emptive planning and resource allocation towards specialist geriatric-dermatology services are needed to address skin-health needs of the growing geriatric population.
Optimization of tilapia (Oreochromis niloticus) viscera oil extraction using
response surface methodology

Tilapia is one of the export commodities with superior fish fillet products. Fillet processing produces much waste, one of which is viscera, which has the potential as raw material for fish oil. Several factors, including the method, temperature, and extraction time, influenced the quality of fish oil. This study aimed to determine the effect of wet rendering, extraction time and temperature on tilapia viscera oil and determine the best temperature and time based on the characteristics of fish oil using response surface methodology (RSM). The data analysis comprised the peroxide value, free fatty acid, anisidine value, total oxidation, and yield value. The result was then optimized using the response surface method with Design Expert 11. The recommended model is linear. The results for extraction at 60℃ for 25.95 mins had a yield, peroxide, free fatty acid, p-anisidine, and total oxidation value of 21.6%, 6.69 meq/kg, 4.16%, 3.87 meq/kg, 17.79, respectively, with, a desirability value of 0.62.
Empowering behavior of the nurse-leader from the perspective of nursing technicians and assistants

Objective Associate demographic and work data and the empowering behavior of the nurse-leader from the perspective of nursing technicians and assistants. Methods Cross-sectional and correlational research carried out in a tertiary university hospital in the state of São Paulo. A total of 260 mid-level nursing professionals (nursing technicians and assistants) participated, using self-administered instruments from May to August 2021. To verify the association between the scale classes and the explanatory variables, a chi-square or Fisher’s exact test was performed in the SAS program. Relationships were statistically significant if p<0.05. Results The profile of the participants was predominantly female, mean age 41.9 years, daytime workers, workload of 36.7 hours and satisfied with their work. The application of the Leader’s Empowering Behavior instrument showed that the domain with the highest average of empowering behavior was “meaningful work” and the one with the lowest average was “autonomy in relation to bureaucracy”. Nursing assistants and technicians who worked during the day did not have other work relationships and were satisfied with it, in addition to observing the leader’s empowering behavior more. Conclusion Nurses’ behavior to empower their team, from the perspective of technicians and nursing assistants in the studied hospital, was good in most domains, except in the domain “autonomy from bureaucracy”, where it was reasonable. Working the day shift, not having other jobs and being satisfied with the job were aspects of greater empowerment.
RCM Polarimetric SAR for Enhanced Ship Detection and Classification

Abstract. The RADARSAT Constellation Mission (RCM), which involves three small synthetic aperture radar (SAR) satellites flying in a constellation configuration, will be equipped with fully polarimetric (FP) capabilities in addition to single-polarization (HH, HV, VV), conventional (HH-HV, VV-VH, and HH-VV), and hybrid (i.e., compact) dual polarization. In this article, the added value of polarimetric SAR information for enhanced ship detection is demonstrated using polarimetric RADARSAT-2 (RS2) data collected over vessels (validated with Automatic Identification System (AIS) data) in the Strait of Georgia, near Vancouver, Canada. It is shown that the excursion (Δp) of the degree of polarization (DoP) provides a significant increase in ship–sea contrast in comparison with conventional (i.e., scalar) single-channel polarizations (HH, HV, VV) and compact. Δp, which is a measure of the variation of the DoP with transmit antenna polarization, performs better than compact intensities and degree of depolarization (DoD) promoted recently for ship detection. The unique potential of FP for ship classification is also demonstrated using polarimetric Convair-580 SAR data collected off Cape Race, Newfoundland, Canada. An efficient combination of successive wide-swath ScanSAR and FP, which exploits the RCM rapid-revisit capability at high latitudes, is considered for operational ship detection and classification. Résumé. La mission de la Constellation RADARSAT (MCR), qui est constituée de trois petits satellites SAR évoluant en configuration de constellation, sera équipée avec des capacités de polarisation en quadrature (FP) en plus de la polarisation simple (HH, HV, VV), de la polarisation classique (HH-HV, VV-VH, et HH-VV) et de la bipolarisation hybride (c.-à-d., compacte). Dans cet article, la valeur ajoutée des informations polarimétriques SAR pour améliorer la détection de navires est démontrée en utilisant des données polarimétriques RADARSAT-2 (RS2) recueillies sur des navires (validées avec le système d'identification automatique (AIS) de données) dans le détroit de Georgia, près de Vancouver (Canada). Il apparait que la différence (delta p) du degré de polarisation (DOP) fournit une augmentation significative du contraste entre le navire et l'eau par rapport à des polarisations simples classiques (p.ex., scalaire) (HH, HV, VV) et compactes. Le delta p, qui est une mesure de la variation de la polarisation DoP avec l'antenne d'émission, est plus performant que les intensités compactes et le degré de dépolarisation (DoD) promus récemment pour la détection de navires. Le potentiel unique de la FP pour la classification de navires est également démontré en utilisant les données polarimétriques Convair-580 SAR recueillies au large du cap Race à Terre-Neuve (Canada). Une combinaison efficace de la large fauchée ScanSAR consécutive à la FP, qui exploite la capacité de revisite rapide de la MCR dans les hautes latitudes, est considérée pour la détection et la classification opérationnelles de navires.
The Characteristics of Four-Tier Diagnostic Test: Classical Test Theory Perspective

This study is part of developing a four-tier online diagnostic test for geometry in junior high schools in Indonesia. After wrote the items and validated by experts, items were tested on 249 students in Yogyakarta, one of the Special Regions in Indonesia. This study aims to identify the characteristics of a four-tier online diagnostic test, from a classical test theory (CTT) perspective. This test contains 20 items of four-tier multiple choice with four options. The students ’ response s were analyzed using Item and Test Analysis (ITEMAN) package. Item difficulty index, discriminant index, and reliability coefficient were three attributes analyzed. The average of item difficulty index is 0.384 (moderate category). The average item discriminant index is 0.513 (good category). The estimation of the reliability coefficient using the Cronbach-Alpha formula is 0.706 (good category)