Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive Status and Nutritional Markers in a Sample of Institutionalized Elderly People

Background Since many of the risk factors for cognitive decline can be modified by diet, the study of nutrition and its relationships with cognitive status in aging has increased considerably in recent years. However, there are hardly any studies that have assessed cognitive status using a comprehensive set of neuropsychological tests along with measures of functional capacity and mood and that have related it to nutritional status measured from several nutritional parameters that have shown its relationships with cognitive function. Objective To test the differences in depressive symptomatology and in several measures of nutritional status between three groups classified according to their cognitive status (CS hereafter). Method One hundred thirteen participants from nursing homes in Galicia, Spain, underwent a comprehensive neuropsychological examination, including a general screening test (MMSE) and tests for different cognitive domains along with measures of activities of daily living (ADL) and assessment of depressive symptomatology (GDS-SF). According to established clinical criteria, participants were divided into three CS groups, Cognitively Intact (CI), Mild Cognitive Impairment (MCI), and All-Cause Dementia (ACD). Nutritional status was also examined using blood-derived measures, body mass index (BMI) and a nutritional screening test (MNA-SF). Differences between CS groups in all nutritional variables were studied by one-way ANOVAs with post-hoc Bonferroni correction or Kruskal-Wallis with Games-Howell post-hoc correction when appropriate. Multinomial logistic regression was also applied to test the association between nutritional variables and CS. Results Differences between CS groups were statistically significant for depressive symptomatology, vitamin A and D, albumin, selenium (Se), uric acid (UA), and BMI. The results of multinomial logistic regression found positive associations between groups with better CS and higher concentrations of vitamins A and D, transthyretin (TTR), albumin, Se, and UA, while negative associations were found for BMI. Conclusion Higher serum levels of vitamin A, vitamin D, TTR, albumin, Se, and UA could act as protective factors against cognitive decline, whereas higher BMI could act as a risk factor.
From Therapy Resistance to Targeted Therapies in Prostate Cancer

Prostate cancer (PCa) is the second most common malignancy among men worldwide. Although early-stage disease is curable, advanced stage PCa is mostly incurable and eventually becomes resistant to standard therapeutic options. Different genetic and epigenetic alterations are associated with the development of therapy resistant PCa, with specific players being particularly involved in this process. Therefore, identification and targeting of these molecules with selective inhibitors might result in anti-tumoral effects. Herein, we describe the mechanisms underlying therapy resistance in PCa, focusing on the most relevant molecules, aiming to enlighten the current state of targeted therapies in PCa. We suggest that selective drug targeting, either alone or in combination with standard treatment options, might improve therapeutic sensitivity of resistant PCa. Moreover, an individualized analysis of tumor biology in each PCa patient might improve treatment selection and therapeutic response, enabling better disease management.
Alcohol-Drinking Under Limited-Access Procedures During Mature Adulthood Accelerates the Onset of Cognitive Impairment in Mice

A history of heavy drinking increases vulnerability to, and the severity of, Alzheimer’s disease (AD) and related dementias, with alcohol use disorder identified as the strongest modifiable risk factor for early-onset dementia. Heavy drinking has increased markedly in women over the past 10 years, particularly in mature adult women during the coronavirus (COVID-19) pandemic. This is concerning as women are more sensitive to many alcohol-related disease states, including AD and related dementias. Herein, we conducted two studies to determine if a 1-month period of binge drinking during mature adulthood (i.e., 5–9 months of age) impairs spatial and working memory to a greater extent in female vs. male C57BL/6J (B6J) mice. The anxiogenic and cognitive-impairing effects of binge drinking were also compared between mature adult and old B6J mice (18 months of age) in a third study. Throughout, females consumed more alcohol than males, indicating that a sex difference in binge drinking persists into old age. Despite the sex difference in intake, we detected no consistent sex difference in our measures of alcohol withdrawal-induced anxiety during a behavioral test battery. Although mature adult females exhibited more cognitive deficits than males, the precise outcome exhibiting a female-selective effect varied across studies. Old mice drank lower amounts of alcohol than mature adult mice, yet their blood ethanol concentrations (BECs) were within error of the 80 mg/dl criterion for binge drinking, indicative of an age-related slowing of alcohol metabolism. As expected, 18-month-old controls exhibited more signs of cognitive impairment than their 6-month-old counterparts, and binge drinking history impaired the Morris water maze performance of mice of both ages. In contrast, binge drinking history impaired the radial arm maze performance of 6-month-old mice only, and the extent of the impairment was comparable to the behavior exhibited by the older mice. We conclude from our studies that: (1) both biological sex and the age of drinking onset are subject factors that impact voluntary alcohol consumption by mice into old age; (2) binge drinking during later life elicits a negative affective state that is relatively sex-independent; (3) binge drinking during both mature adulthood and old age impairs spatial learning and memory; (4) binge drinking during mature adulthood accelerates deficits in working memory; and (5) mature adult females tend to exhibit more alcohol-induced cognitive impairments than males. If relevant to humans, these findings suggest that binge-like drinking by older adult men and women induces a negative affective state and cognitive decline, but that mature adult women, in particular, may be more sensitive to both the immediate and persistent cognitive-impairing effects of heavy drinking.
Nitrogen Removal Capacity of Microbial Communities Developing in Compost- and Woodchip-Based Multipurpose Reactive Barriers for Aquifer Recharge With Wastewater

Global water supplies are threatened by climate changes and the expansion of urban areas, which have led to an increasing interest in nature-based solutions for water reuse and reclamation. Reclaimed water is a possible resource for recharging aquifers, and the addition of an organic reactive barrier has been proposed to improve the removal of pollutants. There has been a large focus on organic pollutants, but less is known about multifunctional barriers, that is, how barriers also remove nutrients that threaten groundwater ecosystems. Herein, we investigated how compost- and woodchip-based barriers affect nitrogen (N) removal in a pilot soil aquifer treatment facility designed for removing nutrients and recalcitrant compounds by investigating the composition of microbial communities and their capacity for N transformations. Secondary-treated, ammonium-rich wastewater was infiltrated through the barriers, and the changes in the concentration of ammonium, nitrate, and dissolved organic carbon (DOC) were measured after passage through the barrier during 1 year of operation. The development and composition of the microbial community in the barriers were examined, and potential N-transforming processes in the barriers were quantified by determining the abundance of key functional genes using quantitative PCR. Only one barrier, based on compost, significantly decreased the ammonium concentration in the infiltrated water. However, the reduction of reactive N in the barriers was moderate (between 21 and 37%), and there were no differences between the barrier types. All the barriers were after 1 year dominated by members of Alphaproteobacteria, Gammaproteobacteria, and Actinobacteria, although the community composition differed between the barriers. Bacterial classes belonging to the phylum Chloroflexi showed an increased relative abundance in the compost-based barriers. In contrast to the increased genetic potential for nitrification in the compost-based barriers, the woodchip-based barrier demonstrated higher genetic potentials for denitrification, nitrous oxide reduction, and dissimilatory reduction of nitrate to ammonium. The barriers have previously been shown to display a high capacity to degrade recalcitrant pollutants, but in this study, we show that most barriers performed poorly in terms of N removal and those based on compost also leaked DOC, highlighting the difficulties in designing barriers that satisfactorily meet several purposes.
1-Mesityl-3-(3-Sulfonatopropyl) Imidazolium Protects Against Oxidative Stress and Delays Proteotoxicity in C. elegans

Due to the increase in life expectancy worldwide, age-related disorders such as neurodegenerative diseases (NDs) have become more prevalent. Conventional treatments comprise drugs that only attenuate some of the symptoms, but fail to arrest or delay neuronal proteotoxicity that characterizes these diseases. Due to their diverse biological activities, imidazole rings are intensively explored as powerful scaffolds for the development of new bioactive molecules. By using C. elegans, our work aims to explore novel biological roles for these compounds. To this end, we have tested the in vivo anti-proteotoxic effects of imidazolium salts. Since NDs have been largely linked to impaired antioxidant defense mechanisms, we focused on 1-Mesityl-3-(3-sulfonatopropyl) imidazolium (MSI), one of the imidazolium salts that we identified as capable of improving iron-induced oxidative stress resistance in wild-type animals. By combining mutant and gene expression analysis we have determined that this protective effect depends on the activation of the Heat Shock Transcription Factor (HSF-1), whereas it is independent of other canonical cytoprotective molecules such as abnormal Dauer Formation-16 (DAF-16/FOXO) and Skinhead-1 (SKN-1/Nrf2). To delve deeper into the biological roles of MSI, we analyzed the impact of this compound on previously established C. elegans models of protein aggregation. We found that MSI ameliorates β-amyloid-induced paralysis in worms expressing the pathological protein involved in Alzheimer’s Disease. Moreover, this compound also delays age-related locomotion decline in other proteotoxic C. elegans models, suggesting a broad protective effect. Taken together, our results point to MSI as a promising anti-proteotoxic compound and provide proof of concept of the potential of imidazole derivatives in the development of novel therapies to retard age-related proteotoxic diseases.
Body Composition in Preschool Children and the Association With Prepregnancy Weight and Gestational Weight Gain: An Ambispective Cohort Study

Objective To describe the body composition in preschool children and to evaluate the association with prepregnancy BMI and gestational weight gain (GWG). Methods Children were recruited in their first year in kindergarten (3 years old) and followed up for the next 2 years. Information during pregnancy and birth was retrieved from medical records. Height, weight, fat mass, fat-free mass, and percentage of body fat (FM%) were measured through a bioelectrical impedance analysis for each child visit, and BMI, fat mass index (FMI), and fat-free mass index (FFMI) were calculated. Generalized linear mixed models (GLMMs) were used to evaluate the associations between prepregnancy weight, GWG, and adiposity indicators. Results A total of 3,329 single-birth 3-year-old children were recruited as the baseline population and were followed at 4 and 5 years old. During the 3 years of follow-up, the mean (±SD) values of BMI, FMI, FFMI, and FM% of the children were 15.6 (±1.6) kg/m2, 2.8 (±1.3) kg/m2, 12.8 (±0.7) kg/m2, and 17.2% (±5.8%), respectively. The prevalence rates of overweight and obesity in mothers before pregnancy were 16.6 and 3.2%, respectively. Mothers were divided into three groups based on GWG: appropriate (1,233, 37.0%), excessive (767, 23.0%), and insufficient (1,329, 39.9%). GLMMs analyses showed that the preschool children’s BMI, FMI, FFMI, and FM% were all significantly positively related to maternal prepregnancy BMI and GWG (all P < 0.001); the children of mothers who were overweight/obese before pregnancy were more likely to be overweight/obese, high FMI, high FFMI, and high FM% at preschool age (all P < 0.001); although maternal excessive GWG was not correlated with offspring’s overweight/obese (P = 0.156), the children of mothers with excessive GWG are more likely to have higher FMI, but not to be with a higher FFMI status than the children of mothers with appropriate GWG. For prepregnancy overweight/obese women, compared with the GWG-appropriate group, maternal excessive GWG was related to the risk of high FMI (coefficient = 0.388, 95% CI: 0.129–0.647) and high FM% (coefficient = 0.352, 95% CI: 0.097–0.607), but was not related to the risk of overweight/obese or high FFMI of the offspring at preschool age. Conclusion Fat mass index decreased with age, while FFMI increased with age among 3- to 5-year-old children. It is necessary to optimize maternal weight prior to conception and GWG management to improve the health outcomes of the offspring.
Current Researches on Nanodrug Delivery Systems in Bladder Cancer Intravesical Chemotherapy

Bladder cancer is one of the most common malignant tumors in urinary system. Intravesical chemotherapy is a common adjuvant therapy after transurethral resection of bladder tumors. However, it has several disadvantages such as low drug penetration rate, short residence time, unsustainable action and inability to release slowly, thus new drug delivery and new modalities in delivery carriers need to be continuously explored. Nano-drug delivery system is a novel way in treatment for bladder cancer that can increase the absorption rate and prolong the duration of drug, as well as sustain the action by controlling drug release. Currently, nano-drug delivery carriers mainly included liposomes, polymers, and inorganic materials. In this paper, we reveal current researches in nano-drug delivery system in bladder cancer intravesical chemotherapy by describing the applications and defects of liposomes, polymers and inorganic material nanocarriers, and provide a basis for the improvement of intravesical chemotherapy drugs in bladder cancer.
A Deep Learning System to Predict the Histopathological Results From Urine Cytopathological Images

Background Although deep learning systems (DLSs) have been developed to diagnose urine cytology, more evidence is required to prove if such systems can predict histopathology results as well. Methods We retrospectively retrieved urine cytology slides and matched histological results. High-power field panel images were annotated by a certified urological pathologist. A deep learning system was designed with a ResNet101 Faster R-CNN (faster region-based convolutional neural network). It was firstly built to spot cancer cells. Then, it was directly used to predict the likelihood of the presence of tissue malignancy. Results We retrieved 441 positive cases and 395 negative cases. The development involved 387 positive cases, accounting for 2,668 labeled cells, to train the DLS to spot cancer cells. The DLS was then used to predict corresponding histopathology results. In an internal test set of 85 cases, the area under the curve (AUC) was 0.90 (95%CI 0.84–0.96), and the kappa score was 0.68 (95%CI 0.52–0.84), indicating substantial agreement. The F1 score was 0.56, sensitivity was 71% (95%CI 52%–85%), and specificity was 94% (95%CI 84%–98%). In an extra test set of 333 cases, the DLS achieved 0.25 false-positive cells per image. The AUC was 0.93 (95%CI 0.90–0.95), and the kappa score was 0.58 (95%CI 0.46–0.70) indicating moderate agreement. The F1 score was 0.66, sensitivity was 67% (95%CI 54%–78%), and specificity was 92% (95%CI 88%–95%). Conclusions The deep learning system could predict if there was malignancy using cytocentrifuged urine cytology images. The process was explainable since the prediction of malignancy was directly based on the abnormal cells selected by the model and can be verified by examining those candidate abnormal cells in each image. Thus, this DLS was not just a tool for pathologists in cytology diagnosis. It simultaneously provided novel histopathologic insights for urologists.
High-Order Multilinear Discriminant Analysis via Order-n Tensor Eigendecomposition

Higher-order data with high dimensionality is of immense importance in many areas of machine learning, computer vision, and video analytics. Multidimensional arrays (commonly referred to as tensors) are used for arranging higher-order data structures while keeping the natural representation of the data samples. In the past decade, great efforts have been made to extend the classic linear discriminant analysis for higher-order data classification generally referred to as multilinear discriminant analysis (MDA). Most of the existing approaches are based on the Tucker decomposition and $\textit{n}$-mode tensor-matrix products. The current paper presents a new approach to tensor-based multilinear discriminant analysis referred to as High-Order Multilinear Discriminant Analysis (HOMLDA). This approach is based upon the tensor decomposition where an order-$\textit{n}$ tensor can be written as a product of order-$\textit{n}$ tensors and has a natural extension to traditional linear discriminant analysis (LDA). Furthermore, the resulting framework, HOMLDA, might produce a within-class scatter tensor that is close to singular. Thus, computing the inverse inaccurately may distort the discriminant analysis. To address this problem, an improved method referred to as Robust High-Order Multilinear Discriminant Analysis (RHOMLDA) is introduced. Experimental results on multiple data sets illustrate that our proposed approach provides improved classification performance with respect to the current Tucker decomposition-based supervised learning methods.
Optimization investigation on the liquid cooling heat dissipation structure for the lithium-ion battery package in electric vehicles

The requirements of cooling and weight reduction for lithium-ion battery packages in electric vehicles are increasingly important. In this paper, a liquid cooling heat dissipation structure is designed and optimized. First of all, the effects of tube diameter, spacing, thickness and layout of the cooling plate on the heat dissipation of the battery package are investigated by using computational fluid dynamics. Afterwards, based on the optimal results of the single factor analysis, an orthogonal table with four factors and three levels are constructed to perform a single-objective optimization, where the minimization of the maximum temperature is the optimization object. Meanwhile, an experiment is carried out to verify the accuracy of the simulation model. In order to further reduce the mass of the cooling plate, a multi-objective optimization is performed, where the minimization of the maximum temperature and the mass are the optimization objects. The maximum temperature is increased by 10.9% in the multi-objective optimization when compared with that in the single objective optimization. However, the mass of the cooling plate in the multi-objective optimization can drop by 82.4%.
The material production of virtuality: trials of explication in the design and development of computer games

This article seeks to contribute to the development of a relationship between digital game studies and science and technology studies by studying the design and development of computer games at three leading UK studios in the light of what MacKenzie refers to “the material production of virtuality” (MacKenzie 2007). The article examines the common ground in treatment of ‘the virtual’ and ‘virtuality’ in science and technology studies and studies of material culture and the importance placed in the relationship between ‘virtuality’ and ‘materiality’ as “a dialectical process of imagination followed by its realisation” (Miller 2005) for the “expressions of immaterial ideals through material forms” (Miller 2005). The article explores the concept of ‘explication’ as a crucial part of this dialectical process through which previously unmapped and unformatted aspects of the world are articulated to the formalisms on which social life depends and through which certain of its features become gradually more explicit and ultimately knowable socially. Work in progress: The paper may be further developed before presentation. Please contact the author for permission before citation or circulation.
Molecular regulation of carotenoid biosynthesis in tomato fruits new biotechnological strategies

Los carotenoides son metabolitos isoprenoides de gran relevancia economica como pigmentos naturales y fitonutrientes. Durante la maduracion del fruto de tomate (Solanum lycopersicum) se acumulan niveles elevados de carotenoides como β-caroteno (naranja) y licopeno (rojo) en un tipo de plasto especializado denominado cromoplasto. En la maduracion se pueden distinguir tres estadios segun el color del fruto: Verde Maduro (VM), Naranja (N) y Rojo (R). La transicion de VM a N y por ultimo a R, se caracteriza por una fuerte induccion en la acumulacion de los niveles de carotenoides y, por ende, la diferenciacion de cloroplastos en cromoplastos. La acumulacion global de carotenoides depende de la actividad de enzimas biosinteticas como PSY. En el fruto de tomate, la actividad PSY procede fundamentalmente de la isoforma PSY1. Durante esta tesis se ha demostrado que el gen PSY1 es una diana directa de un factor de transcripcion regulado por luz denominado PIF1a, que se une al promotor del gen para reprimir su expresion. En concordancia, frutos de tomate con niveles reducidos de PIF1a mostraron una mayor expresion de PSY1 y por tanto una mayor acumulacion de carotenoides. Ademas, hemos establecido un mecanismo molecular basado en la regulacion de la estabilidad por luz de PIF1a que permite ajustar la sintesis de carotenoides al estado real de maduracion del fruto. En la segunda parte de la tesis se ha explorado la relevancia del complejo de la Clp proteasa plastidica en la regulacion de los niveles de proteinas implicadas en el metabolismo de carotenoides y en el almacenamiento de estos pigmentos en el fruto de tomate. La disminucion de dicha actividad proteolitica mediante silenciamiento genico, genero frutos transgenicos enriquecidos en β-caroteno (pro-vitamina A). Mas aun, la caracterizacion de dichos frutos mediante TEM y microscopia Raman sirvio como plataforma para establecer la importancia de dicho complejo proteolitico durante la diferenciacion de cloroplastos en cromoplastos. Finalmente, estudios en el campo de la proteomica cuantitativa ayudaron a la elucidacion de posibles nuevas proteinas diana de dicha proteasa, incluyendo PSY1.