Oestradiol and osteoclast differentiation: Effects on p53 and mitochondrial metabolism.

BACKGROUND: Oestrogen deficiency increases bone resorption, contributing to osteoporosis development. Yet, the mechanisms mediating the effects of oestrogen on osteoclasts remain unclear. This study aimed to elucidate the early metabolic alteration induced by RANKL, the essential cytokine in osteoclastogenesis and 17-beta-oestradiol (E2) on osteoclast progenitor cells, using RAW 264.7 macrophage cell line and primary bone marrow-derived macrophages as biological models. RESULTS: This research demonstrated that, in osteoclast precursors, RANKL stimulates complex I activity, oxidative phosphorylation (OXPHOS) and mitochondria-derived ATP production as early as 3 h of exposure. This effect on mitochondrial bioenergetics is associated with an increased capacity to oxidize TCA cycle substrates, fatty acids and amino acids. E2 inhibited all effects of RANKL on mitochondria metabolism. In the presence of RANKL, E2 also decreased cell number and stimulated the mitochondrial-mediated apoptotic pathway, detected as early as 3 h. Further, the pro-apoptotic effects of E2 during osteoclast differentiation were associated with an accumulation of p392S-p53 in mitochondria. CONCLUSIONS: These findings elucidate the early effects of RANKL on osteoclast progenitor metabolism and suggest novel p53-mediated mechanisms that contribute to postmenopausal osteoporosis.

Working memory and reward increase the accuracy of animal location encoding in the medial prefrontal cortex.

The ability to perceive spatial environments and locate oneself during navigation is crucial for the survival of animals. Mounting evidence suggests a role of the medial prefrontal cortex (mPFC) in spatially related behaviors. However, the properties of mPFC spatial encoding and how it is influenced by animal behavior are poorly defined. Here, we train the mice to perform 3 tasks differing in working memory and reward-seeking: a delayed non-match to place (DNMTP) task, a passive alternation (PA) task, and a free-running task. Single-unit recording in the mPFC shows that although individual mPFC neurons exhibit spatially selective firing, they do not reliably represent the animal location. The population activity of mPFC neurons predicts the animal location. Notably, the population coding of animal locations by the mPFC is modulated by animal behavior in that the coding accuracy is higher in tasks involved in working memory and reward-seeking. This study reveals an approach whereby the mPFC encodes spatial positions and the behavioral variables affecting it.

Brain morphometry and estimation of aging brain in subjects with congenital untreated isolated GH deficiency.

PURPOSE: Individuals with isolated GH deficiency (IGHD) due to a mutation in the GHRH receptor gene have a normal life expectancy and above 50 years of age, similar total cognitive performance, with better attention and executive function than controls. Our objectives were to evaluate their brain morphometry and brain aging using MRI. METHODS: Thirteen IGHD and 14 controls matched by age, sex, and education, were enrolled. Quantitative volumetric data and cortical thickness were obtained by automatic segmentation using Freesurfer software. The volume of each brain region was normalized by the intracranial volume. The difference between the predicted brain age estimated by MRI using a trained neuronal network, and the chronological age, was obtained. p < 0.005 was considered significant and 0.005 < p < 0.05 as a suggestive evidence of difference. RESULTS: In IGHD, most absolute values of cortical thickness and regional brain volumes were similar to controls, but normalized volumes were greater in the white matter in the frontal pole and in the insula bilaterally, and in the gray matter, in the right insula and in left Caudate (p < 0.005 for all comparisons) We also noticed suggestive evidence of a larger volume in IGHD in left thalamus (p = 0.006), right thalamus (p = 0.025), right caudate (p = 0.046) and right putamen (p = 0.013). Predicted brain ages were similar between groups. CONCLUSION: IGHD is primarily associated with similar absolute brain measurements, and a set of larger normalized volumes, and does not appear to alter the process of brain aging.

Physical properties of Scarpa's fascia.

Preservation of Scarpa's fascia has improved clinical outcomes in abdominoplasty procedures and in other body contour surgeries. However, the physical properties of Scarpa's fascia have not yet been described, and grafts are still underexplored. Fresh surgical specimens from five female patients subjected to classical abdominoplasty were dissected and analyzed. A grid was drawn on the fascia surface, dividing it into equal upper and lower halves; four Scarpa's fascia samples (30 × 10 mm) were collected from each half, 40 mm apart. The thickness was measured with a caliper. A strain/stress universal testing machine was used for mechanical tests. Twenty-five samples were obtained (nine from the upper half, 16 from the lower). The average thickness was 0.56 ± 0.11 mm. The average values for stretch, stress, strain, and Young's Modulus were, respectively, 1.436, 4.198 MPa, 43.6%, and 23.14 MPa. The upper half showed significantly greater thickness and strain values (p = 0.020 and p = 0.048; Student's t-test). The physical and biomechanical properties of Scarpa's fascia can make it a donor area for fascial grafts as an alternative to fascia lata, as it is always available and has minimal donor-site morbidity. Further studies are needed to validate this statement. It seems advantageous to use the lower half of the abdomen instead of the upper part as a donor site.

Recounting the FANTOM CAGE-Associated Transcriptome.

Long noncoding RNAs (lncRNAs) have emerged as key coordinators of biological and cellular processes. Characterizing lncRNA expression across cells and tissues is key to understanding their role in determining phenotypes, including human diseases. We present here FC-R2, a comprehensive expression atlas across a broadly defined human transcriptome, inclusive of over 109,000 coding and noncoding genes, as described in the FANTOM CAGE-Associated Transcriptome (FANTOM-CAT) study. This atlas greatly extends the gene annotation used in the original recount2 resource. We demonstrate the utility of the FC-R2 atlas by reproducing key findings from published large studies and by generating new results across normal and diseased human samples. In particular, we (a) identify tissue-specific transcription profiles for distinct classes of coding and noncoding genes, (b) perform differential expression analysis across thirteen cancer types, identifying novel noncoding genes potentially involved in tumor pathogenesis and progression, and (c) confirm the prognostic value for several enhancer lncRNAs expression in cancer. Our resource is instrumental for the systematic molecular characterization of lncRNA by the FANTOM6 Consortium. In conclusion, comprised of over 70,000 samples, the FC-R2 atlas will empower other researchers to investigate functions and biological roles of both known coding genes and novel lncRNAs.

Detection of gases and organic vapors by cellulose-based sensors.

The growing interest in the development of cost-effective, straightforward, and rapid analytical systems has found cellulose-based materials, including cellulose derivatives, cellulose-based gels, nanocellulosic materials, and the corresponding (nano)cellulose-based composites, to be valuable platforms for sensor development. The present work presents recent advances in the development of cellulose-based sensors for the determination of volatile analytes and derivatives of analytical relevance. In particular, strategies described in the literature for the fabrication and modification of cellulose-based substrates with responsive materials are summarized. In addition, selected contributions reported in the field of paper-based volatile sensors are discussed, with a particular emphasis on quick response (QR) code paper-based platforms, intelligent films for food freshness monitoring, and sensor arrays for volatile discrimination purposes. Furthermore, analytical strategies devised for the determination of ionic species by in situ generation of volatile derivatives in both paper-based analytical devices (PADs) and microfluidic PADs will also be described.

Molecular mechanisms of action and chemosensitization of tumor cells in ovarian cancer by phytochemicals: A narrative review on pre-clinical and clinical studies.

Ovarian cancer is the second-leading cause of death among women with cancer of the genital tract. Currently, drugs derived from platinum and taxanes constitute the majority of ovarian cancer treatments. Patients undergoing this chemotherapy are susceptible to cumulative toxic effects and resistance to chemotherapy. Therefore, it is crucial to identify treatment options that are both more effective and better tolerated by patients. Phytochemicals in this context are plant-derived chemicals with antitumor activity that can be used as therapeutic or adjuvant agents in the treatment of ovarian cancer. Consequently, the purpose of this literature review is to demonstrate through existing pre-clinical and clinical trials the potential of phytochemicals in the treatment of ovarian cancer, the mechanisms of action involved, and to contribute to the development of new therapeutic options for ovarian cancer. For this review, the databases PubMed, Scopus, Science Direct, and ClinicalTrials.gov were queried between 2010 and 2022 using terms such as "ovarian cancer," "phytochemicals," "phenolic compounds," "terpenes," and "alkaloids." The present review summarized the possible molecular mechanisms of action by which phytochemicals, such as phenolic acids, flavonoids, diterpenes, triterpenes, saponins, and alkaloids, inhibit this type of cancer, specifically the ability of phytochemicals to induce cell growth regulation, apoptosis, oxidative stress reduction, anti-angiogenesis, and chemosensitization of tumors in ovarian cancer. As their action and cellular mechanism have already been demonstrated in several pre-clinical trials, the phytochemicals identified in our study have the potential to be investigated for the treatment of ovarian cancer. Through pre-clinical and clinical trials, our study demonstrates the potential of phytochemicals in the treatment of ovarian cancer, contributing to the development of novel therapeutic options for ovarian cancer.

Quantitative analysis of neuronal mitochondrial movement reveals patterns resulting from neurotoxicity of rotenone and 6-hydroxydopamine.

Alterations in mitochondrial dynamics, including their intracellular trafficking, are common early manifestations of neuronal degeneration. However, current methodologies used to study mitochondrial trafficking events rely on parameters that are primarily altered in later stages of neurodegeneration. Our objective was to establish a reliable applied statistical analysis to detect early alterations in neuronal mitochondrial trafficking. We propose a novel quantitative analysis of mitochondria trajectories based on innovative movement descriptors, including straightness, efficiency, anisotropy, and kurtosis. We evaluated time- and dose-dependent alterations in trajectory descriptors using biological data from differentiated SH-SY5Y cells treated with the mitochondrial toxicants 6-hydroxydopamine and rotenone. MitoTracker Red CMXRos-labelled mitochondria movement was analyzed by total internal reflection fluorescence microscopy followed by computational modelling to describe the process. Based on the aforementioned trajectory descriptors, this innovative analysis of mitochondria trajectories provides insights into mitochondrial movement characteristics and can be a consistent and sensitive method to detect alterations in mitochondrial trafficking occurring in the earliest time points of neurodegeneration.

Evaluation of 6-Hydroxydopamine and Rotenone In Vitro Neurotoxicity on Differentiated SH-SY5Y Cells Using Applied Computational Statistics.

With the increase in life expectancy and consequent aging of the world's population, the prevalence of many neurodegenerative diseases is increasing, without concomitant improvement in diagnostics and therapeutics. These diseases share neuropathological hallmarks, including mitochondrial dysfunction. In fact, as mitochondrial alterations appear prior to neuronal cell death at an early phase of a disease's onset, the study and modulation of mitochondrial alterations have emerged as promising strategies to predict and prevent neurotoxicity and neuronal cell death before the onset of cell viability alterations. In this work, differentiated SH-SY5Y cells were treated with the mitochondrial-targeted neurotoxicants 6-hydroxydopamine and rotenone. These compounds were used at different concentrations and for different time points to understand the similarities and differences in their mechanisms of action. To accomplish this, data on mitochondrial parameters were acquired and analyzed using unsupervised (hierarchical clustering) and supervised (decision tree) machine learning methods. Both biochemical and computational analyses resulted in an evident distinction between the neurotoxic effects of 6-hydroxydopamine and rotenone, specifically for the highest concentrations of both compounds.

Entanglement-Assisted Quantum Codes from Cyclic Codes.

Entanglement-assisted quantum-error-correcting (EAQEC) codes are quantum codes which use entanglement as a resource. These codes can provide better error correction than the (entanglement unassisted) codes derived from the traditional stabilizer formalism. In this paper, we provide a general method to construct EAQEC codes from cyclic codes. Afterwards, the method is applied to Reed-Solomon codes, BCH codes, and general cyclic codes. We use the Euclidean and Hermitian construction of EAQEC codes. Three families have been created: two families of EAQEC codes are maximal distance separable (MDS), and one is almost MDS or almost near MDS. The comparison of the codes in this paper is mostly based on the quantum Singleton bound.

Disseminated Cutaneous Leishmaniasis and Alcohol Misuse, Northeast Brazil, 2015-2018.

Disseminated cutaneous leishmaniasis (DCL) is an uncommon form of Leishmania braziliensis infection. It remains unknown why some people develop this clinical condition. We describe 14 DCL patients in Northeast Brazil during 2015-2018. These patients regularly drank large amounts of alcohol, possibly increasing their risk for DCL.

Synthesis, antibiotic modifying activity, ADMET study and molecular docking of chalcone (E)-3-(2,4-dichlorophenyl)-1-(2-hydroxyphenyl)prop-2-en-1-one in strains of Staphylococcus aureus carrying MepA efflux pumps.

The Staphylococcus aureus bacteria is a Gram-positive, immobile, non-spore bacterium, with catalase and positive coagulase, among other characteristics. It is responsible for important infections caused in the population and for hospital infections. Because of that many strategies are being developed to combat the resistance of microorganisms to drugs, in recent times, chalcones have been studied for this purpose. Chalcones are found in parts of plants and can be found, for example, in the roots, leaves, bark, among others, but are mainly found as petal pigments, they are a class of compounds considered an exceptional model due to chemical simplicity and a wide variety of biological activities. This study aimed to evaluate the ability of chalcone (E)-3-(2,4-dichlorophenyl)-1-(2-hydroxyphenyl)prop-2-en-1-one to reverse the efflux pump resistance, present in the bacteria S. aureus 1199B and S. aureus K2068. The synthetic chalcone (E)-3-(2,4-dichlorophenyl)-1-(2-hydroxyphenyl)prop-2-en-1-one was able to synergistically modulate the antibiotic Ciprofloxacino and Ethidium Bromide against the bacterial strain S. aureus K2068, and with the antibiotic Norfloxacino against the strain 1199B. Thus, it is suggested that this chalcone may be acting by inhibiting the efflux pump mechanism of these bactéria. The theoretical physicochemical and pharmacokinetic properties of chalcone showed that the chalocne did not present a severe risk of toxicity, such as genetic mutation or cardiotoxicity. Molecular docking showed that the chalcone could act as a competitive inhibitor of the MepA efflux pump, as at hinders the binding of other substrates, such as EtBr.

Nanomaterial-Integrated Cellulose Platforms for Optical Sensing of Trace Metals and Anionic Species in the Environment.

The development of disposable sensors that can be easily adapted to every analytical problem is currently a hot topic that is revolutionizing many areas of science and technology. The need for decentralized analytical measurements at real time is increasing for solving problems in areas such as environment pollution, medical diagnostic, food quality assurance, etc., requiring fast action. Despite some current limitations of these devices, such as insufficient detection capability at (ultra)trace level and risk of interferent effects due to matrix, they allow low-cost analysis, portability, low sample consumption, and fast response. In the last years, development of paper-based analytical devices has undergone a dramatic increase for on-site detection of toxic metal ions and other pollutants. Along with the great availability of cellulose substrates, the immobilization of receptors providing enhanced recognition ability, such as a variety of nanomaterials, has driven the design of novel sensing approaches. This review is aimed at describing and discussing the different possibilities arisen with the use of different nanoreceptors (e.g., plasmonic nanoparticles, quantum dots, carbon-based fluorescent nanoparticles, etc.) immobilized onto cellulose-based substrates for trace element detection, their advantages and shortcomings.

Paper-Based Analytical Devices for Colorimetric and Luminescent Detection of Mercury in Waters: An Overview.

Lab-on-paper technologies, also known as paper-based analytical devices (PADs), have received increasing attention in the last years, and nowadays, their use has spread to virtually every application area, i.e., medical diagnostic, food safety, environmental monitoring, etc. Advantages inherent to on-field detection, which include avoiding sampling, sample preparation and conventional instrumentation in central labs, are undoubtedly driving many developments in this area. Heavy metals represent an important group of environmental pollutants that require strict controls due to the threat they pose to ecosystems and human health. In this overview, the development of PADs for Hg monitoring, which is considered the most toxic metal in the environment, is addressed. The main emphasis is placed on recognition elements (i.e., organic chromophores/fluorophores, plasmonic nanoparticles, inorganic quantum dots, carbon quantum dots, metal nanoclusters, etc.) employed to provide suitable selectivity and sensitivity. The performance of both microfluidic paper-based analytical devices and paper-based sensors using signal readout by colorimetry and luminescence will be discussed.

Error Probability Mitigation in Quantum Reading Using Classical Codes.

A general framework describing the statistical discrimination of an ensemble of quantum channels is given by the name quantum reading. Several tools can be applied in quantum reading to reduce the error probability in distinguishing the ensemble of channels. Classical and quantum codes can be envisioned for this goal. The aim of this paper is to present a simple but fruitful protocol for this task using classical error-correcting codes. Three families of codes are considered: Reed-Solomon codes, BCH codes, and Reed-Muller codes. In conjunction with the use of codes, we also analyze the role of the receiver. In particular, heterodyne and Dolinar receivers are taken into consideration. The encoding and measurement schemes are connected by the probing step. As probes, we consider coherent states. In such a simple manner, interesting results are obtained. As we show, there is a threshold below which using codes surpass optimal and sophisticated schemes for any fixed rate and code. BCH codes in conjunction with Dolinar receiver turn out to be the optimal strategy for error mitigation in quantum reading.

AGREE-Analytical GREEnness Metric Approach and Software.

Green analytical chemistry focuses on making analytical procedures more environmentally benign and safer to humans. The amounts and toxicity of reagents, generated waste, energy requirements, the number of procedural steps, miniaturization, and automation are just a few of the multitude of criteria considered when assessing an analytical methodology's greenness. The use of greenness assessment criteria requires dedicated tools. We propose the Analytical GREEnness calculator, a comprehensive, flexible, and straightforward assessment approach that provides an easily interpretable and informative result. The assessment criteria are taken from the 12 principles of green analytical chemistry (SIGNIFICANCE) and are transformed into a unified 0-1 scale. The final score is calculated based on the SIGNIFICANCE principles. The result is a pictogram indicating the final score, performance of the analytical procedure in each criterion, and weights assigned by the user. Freely available software makes the assessment procedure straightforward. It is open-source and downloadable from https://mostwiedzy.pl/AGREE.

Data-driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders.

BACKGROUND: Impairment of executive function (EF), the goal-directed regulation of thoughts, actions, and emotions, drives negative outcomes and is common across neurodevelopmental disorders including attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). A primary challenge to its amelioration is heterogeneity in symptom expression within and across disorders. Parsing this heterogeneity is necessary to attain diagnostic precision, a goal of the NIMH Research Domain Criteria Initiative. We aimed to identify transdiagnostic subtypes of EF that span the normal to impaired spectrum and establish their predictive and neurobiological validity. METHODS: Community detection was applied to clinical parent-report measures in 8-14-year-old children with and without ADHD and ASD from two independent cohorts (discovery N = 320; replication N = 692) to identify subgroups with distinct behavioral profiles. Support vector machine (SVM) classification was used to predict subgroup membership of unseen cases. Preliminary neurobiological validation was obtained with existing functional magnetic resonance imaging (fMRI) data on a subsample (N = 84) by testing hypotheses about sensitivity of EF subgroups versus DSM categories. RESULTS: We observed three transdiagnostic EF subtypes characterized by behavioral profiles that were defined by relative weakness in: (a) flexibility and emotion regulation; (b) inhibition; and (c) working memory, organization, and planning. The same tripartite structure was also present in the typically developing children. SVM trained on the discovery sample and tested on the replication sample classified subgroup membership with 77.0% accuracy. Split-half SVM classification on the combined sample (N = 1,012) yielded 88.9% accuracy (this SVM is available for public use). As hypothesized, frontal-parietal engagement was better distinguished by EF subtype than DSM diagnosis and the subgroup characterized with inflexibility failed to modulate right IPL activation in response to increased executive demands. CONCLUSIONS: The observed transdiagnostic subtypes refine current diagnostic nosology and augment clinical decision-making for personalizing treatment of executive dysfunction in children.

A paper-based gas sensor for simultaneous noninstrumental colorimetric detection of nitrite and sulfide in waters.

The use of paper-based devices in combination with noninstrumental detection systems is becoming increasingly important in the analytical field due to its simplicity, rapidity, and low cost. However, their use for determination of volatile analyte derivatives is still relatively scarce. The present work reports on the assessment of a paper-based gas-sensing approach for the simultaneous noninstrumental colorimetric detection of nitrite and sulfide. Colorimetric systems based on the Griess and methylene blue assays, formation of colored metallic sulfides, and interaction/reaction with in situ generated metallic nanoparticles were preliminary evaluated. Then, the effect of experimental variables affecting the analytical performance of the paper-based gas sensor was studied with two digitization systems, namely a scanner and a smartphone. Under optimal conditions, the developed system yielded limits of detection of 0.055 and 0.005 mg/L for nitrite and sulfide, respectively. The repeatability, expressed as relative standard deviation, was found to be 5.9 and 6.7% for nitrite and sulfide, respectively. The proposed method was finally applied to the analysis of water samples, showing recoveries in the range of 95-105%.

Toroidal plasmoid generation via extreme hydrodynamic shear.

Saint Elmo's fire and lightning are two known forms of naturally occurring atmospheric pressure plasmas. As a technology, nonthermal plasmas are induced from artificially created electromagnetic or electrostatic fields. Here we report the observation of arguably a unique case of a naturally formed such plasma, created in air at room temperature without external electromagnetic action, by impinging a high-speed microjet of deionized water on a dielectric solid surface. We demonstrate that tribo-electrification from extreme and focused hydrodynamic shear is the driving mechanism for the generation of energetic free electrons. Air ionization results in a plasma that, unlike the general family, is topologically well defined in the form of a coherent toroidal structure. Possibly confined through its self-induced electromagnetic field, this plasmoid is shown to emit strong luminescence and discrete-frequency radio waves. Our experimental study suggests the discovery of a unique platform to support experimentation in low-temperature plasma science.

Searching for Solvents with an Increased Carbon Dioxide Solubility Using Multivariate Statistics.

Ionic liquids (ILs) are used in various fields of chemistry. One of them is CO2 capture, a process that is quite well described. The solubility of CO2 in ILs can be used as a model to investigate gas absorption processes. The aim is to find the relationships between the solubility of CO2 and other variables-physicochemical properties and parameters related to greenness. In this study, 12 variables are used to describe a dataset consisting of 26 ILs and 16 molecular solvents. We used a cluster analysis, a principal component analysis, and a K-means hierarchical clustering to find the patterns in the dataset and the discriminators between the clusters of compounds. The results showed that ILs and molecular solvents form two well-separated groups, and the variables were well separated into greenness-related and physicochemical properties. Such patterns suggest that the modeling of greenness properties and of the solubility of CO2 on physicochemical properties can be difficult.