SAIBR: a simple, platform-independent method for spectral autofluorescence correction.

Biological systems are increasingly viewed through a quantitative lens that demands accurate measures of gene expression and local protein concentrations. CRISPR/Cas9 gene tagging has enabled increased use of fluorescence to monitor proteins at or near endogenous levels under native regulatory control. However, owing to typically lower expression levels, experiments using endogenously tagged genes run into limits imposed by autofluorescence (AF). AF is often a particular challenge in wavelengths occupied by commonly used fluorescent proteins (GFP, mNeonGreen). Stimulated by our work in C. elegans, we describe and validate Spectral Autofluorescence Image Correction By Regression (SAIBR), a simple platform-independent protocol and FIJI plug-in to correct for autofluorescence using standard filter sets and illumination conditions. Validated for use in C. elegans embryos, starfish oocytes and fission yeast, SAIBR is ideal for samples with a single dominant AF source; it achieves accurate quantitation of fluorophore signal, and enables reliable detection and quantification of even weakly expressed proteins. Thus, SAIBR provides a highly accessible low-barrier way to incorporate AF correction as standard for researchers working on a broad variety of cell and developmental systems.

The Role of Oxytocin in Polycystic Ovary Syndrome: A Systematic Review.

Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorder that affects women of reproductive age, representing the primary cause of anovulatory infertility. The nonapeptide oxytocin (OT) plays an important role in cognitive, emotional, and reproductive functions in human beings. Oxytocin receptors are expressed in several body parts, including the ovaries. Despite this, the possible role played by oxytocin in symptoms of PCOS is not clear. The present systematic review aimed at understanding the presence of possible oxytocin level alterations in PCOS, the connection between alterations of OT levels and the symptoms of PCOS, and the effect of oxytocin administration in PCOS. After a systematic search in the principal databases, eight studies, five human and three animal, were included. Four human studies and one animal study highlighted the role played by oxytocin in fertility issues related to PCOS. Three human and two animal studies investigated the role of body weight and OT levels. Studies that analyzed oxytocin basal levels in women agreed that PCOS is associated with a reduction in the serum level of oxytocin. Two human studies and one animal study agreed about lower levels of oxytocin, confirming a possible implication of the dysfunction of OT in the pathogenesis of PCOS.

Reproducibility of arterial spin labeling cerebral blood flow image processing: A report of the ISMRM open science initiative for perfusion imaging (OSIPI) and the ASL MRI challenge.

PURPOSE: Arterial spin labeling (ASL) is a widely used contrast-free MRI method for assessing cerebral blood flow (CBF). Despite the generally adopted ASL acquisition guidelines, there is still wide variability in ASL analysis. We explored this variability through the ISMRM-OSIPI ASL-MRI Challenge, aiming to establish best practices for more reproducible ASL analysis. METHODS: Eight teams analyzed the challenge data, which included a high-resolution T1-weighted anatomical image and 10 pseudo-continuous ASL datasets simulated using a digital reference object to generate ground-truth CBF values in normal and pathological states. We compared the accuracy of CBF quantification from each team's analysis to the ground truth across all voxels and within predefined brain regions. Reproducibility of CBF across analysis pipelines was assessed using the intra-class correlation coefficient (ICC), limits of agreement (LOA), and replicability of generating similar CBF estimates from different processing approaches. RESULTS: Absolute errors in CBF estimates compared to ground-truth synthetic data ranged from 18.36 to 48.12 mL/100 g/min. Realistic motion incorporated into three datasets produced the largest absolute error and variability between teams, with the least agreement (ICC and LOA) with ground-truth results. Fifty percent of the submissions were replicated, and one produced three times larger CBF errors (46.59 mL/100 g/min) compared to submitted results. CONCLUSIONS: Variability in CBF measurements, influenced by differences in image processing, especially to compensate for motion, highlights the significance of standardizing ASL analysis workflows. We provide a recommendation for ASL processing based on top-performing approaches as a step toward ASL standardization.

Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications.

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.

Dietary metabarcoding reveals the simplification of bird-pest interaction networks across a gradient of agricultural cover.

Agriculture is vital for supporting human populations, but its intensification often leads to landscape homogenization and a decline in non-provisioning ecosystem services. Ecological intensification and multifunctional landscapes are suggested as nature-based alternatives to intensive agriculture, using ecological processes like natural pest regulation to maximize food production. Birds are recognized for their role in increasing crop yields by consuming invertebrate pests in several agroecosystems. However, the understanding of how bird species, their traits and agricultural land cover influence the structure of bird-pest interactions remains limited. We sampled bird-pest interactions monthly for 1 year, at four sites within a multifunctional landscape, following a gradient of increasing agricultural land cover. We analysed 2583 droppings of 55 bird species with DNA metabarcoding and detected 225 pest species in 1139 samples of 42 bird species. As expected, bird-pest interactions were highly variable across bird species. Dietary pest richness was lower in the fully agricultural site, while predation frequency remained consistent across the agricultural land cover gradient. Network analysis revealed a reduction in the complexity of bird-pest interactions as agricultural coverage increased. Bird species abundance affected the bird's contribution to the network structure more than any of the bird traits analysed (weight, phenology, invertebrate frequency in diet and foraging strata), with more common birds being more important to network structure. Overall, our results show that increasing agricultural land cover increases the homogenization of bird-pest interactions. This shows the importance of maintaining natural patches within agricultural landscapes for biodiversity conservation and enhanced biocontrol.

A agricultura é essencial para suportar a população humana, mas a sua intensificação geralmente leva à homogeneização da paisagem e à redução dos serviços do ecossistema que não sejam de provisão. A intensificação ecológica e paisagens multifuncionais são sugeridas como alternativas naturais à agricultura intensiva, utilizando processos ecológicos como a regulação natural de pragas para maximizar a produção de alimentos. As aves são conhecidas pelo seu papel no aumento da produtividade das culturas por consumirem pragas em diversos agroecossistemas. Contudo, o conhecimento de como as espécies de aves, as suas características e a cobertura agrícola influenciam as interações entre aves e pragas são limitados. Nós amostrámos estas interações mensalmente durante um ano, em quatro locais, numa paisagem multifuncional, ao longo um gradiente de aumento da cobertura agrícola. Analisamos 2583 dejetos de 55 espécies de aves com DNA metabarcoding e detetamos 225 espécies praga em 1139 amostras de 42 espécies de aves. Como esperado, as interações entre aves e pragas foram muito distintas entre as várias espécies de aves. A riqueza de pragas na dieta foi menor no local completamente dominado por área agrícola, enquanto a frequência de predação de pragas foi constante ao longo do gradiente de cobertura agrícola. A análise de redes demonstrou uma redução na complexidade das interações entre aves e pragas à medida que a cobertura agrícola aumenta. A abundância das espécies de aves influenciou mais a contribuição das aves para a estrutura da rede do que qualquer uma das características analisadas (peso, fenologia, frequência de invertebrados na dieta e estrato de alimentação), sendo as aves mais comuns as mais importantes na estrutura da rede. De forma geral, os nossos resultados indicam que o aumento da cobertura agrícola aumenta a homogeneização das interações entre aves e pragas. Isto demonstra a importância de preservar áreas naturais em paisagem agrícolas para a conservação de biodiversidade e melhor controlo biológico.

Metabolomics perspectives of the ecotoxicological risks of polycyclic aromatic hydrocarbons: A scoping review.

Polycyclic Aromatic Hydrocarbons (PAHs) represent persistent environmental pollutants ubiquitously distributed in the environment. Their presence alongside various other contaminants gives rise to intricate interactions, culminating in profound deleterious consequences. The combination effects of different PAH mixtures on biota remains a relatively unexplored domain. Recent studies have harnessed the exceptional sensitivity of metabolomic techniques to unveil the significant ecotoxicological perils of PAH pollution confronting both human populations and ecosystems. This article furnishes a comprehensive overview of current literature focused on the metabolic repercussions stemming from exposure to complex mixtures of PAHs or PAH-pollution sources using metabolomics approaches. These insights are obtained through a wide range of models, including in vitro assessments, animal studies, investigations on human subjects, botanical specimens, and soil environments. The findings underscore that PAH mixtures induce cellular stress responses and systemic effects, leading to metabolic dysregulations in amino acids, carbohydrates, lipids, and other key metabolites (e.g., organic acids, purines), with specific variations observed based on the organism and PAH compounds involved. Additionally, the ecological consequences of PAH pollutants on plant and soil microbial responses are emphasized, revealing significant changes in stress-related metabolites and nutrient cycling in soil ecosystems. The complex interplay of various PAHs and their metabolic effects on several models, as elucidated through metabolomics, highlight the urgency of further research and the need for comprehensive strategies to mitigate the risks posed by these widespread environmental pollutants.

Working memory during spontaneous migraine attacks: an fMRI study.

OBJECTIVE: To investigate the neural correlates of working memory during a spontaneous migraine attack compared to the interictal phase, using functional magnetic resonance imaging (fMRI). BACKGROUND: Cognitive disturbances are commonly observed during migraine attacks, particularly in the headache phase. However, the neural basis of these changes remains unknown. METHODS: In a fMRI within-subject test-retest design study, eleven women (32 years of age, average) with episodic migraine were evaluated twice, first during a spontaneous migraine attack, and again in a pain-free period. Each session consisted in a cognitive assessment and fMRI while performing a working memory task (N-back). RESULTS: Cognitive test scores were lower during the ictal session than in the pain-free session. Regions typically associated with working memory were activated during the N-back task in both sessions. A voxel wise between session comparison showed significantly greater activation in the left frontal pole and orbitofrontal cortex during the attack relative to the interictal phase. CONCLUSION: Migraine patients exhibited greater activation of the left frontal pole and orbitofrontal cortex while executing a verbal working memory task during a spontaneous migraine attack when compared to the interictal state. Given the association of these regions with pain processing and inhibitory control, these findings suggest that patients recruit inhibitory areas to accomplish the cognitive task during migraine attacks, a neural signature of their cognitive difficulties.

Metabolomics Reveals Tyrosine Kinase Inhibitor Resistance-Associated Metabolic Events in Human Metastatic Renal Cancer Cells.

The development of resistance to tyrosine kinase inhibitors (TKIs) is a major cause of treatment failure in metastatic renal cell carcinoma (mRCC). A deeper understanding of the metabolic mechanisms associated with TKI resistance is critical for refining therapeutic strategies. In this study, we established resistance to sunitinib and pazopanib by exposing a parental Caki-1 cell line to increasing concentrations of sunitinib and pazopanib. The intracellular and extracellular metabolome of sunitinib- and pazopanib-resistant mRCC cells were investigated using a nuclear magnetic resonance (NMR)-based metabolomics approach. Data analysis included multivariate and univariate methods, as well as pathway and network analyses. Distinct metabolic signatures in sunitinib- and pazopanib-resistant RCC cells were found for the first time in this study. A common metabolic reprogramming pattern was observed in amino acid, glycerophospholipid, and nicotinate and nicotinamide metabolism. Sunitinib-resistant cells exhibited marked alterations in metabolites involved in antioxidant defence mechanisms, while pazopanib-resistant cells showed alterations in metabolites associated with energy pathways. Sunitinib-resistant RCC cells demonstrated an increased ability to proliferate, whereas pazopanib-resistant cells appeared to restructure their energy metabolism and undergo alterations in pathways associated with cell death. These findings provide potential targets for novel therapeutic strategies to overcome TKI resistance in mRCC through metabolic regulation.

Brain perfusion imaging by multi-delay arterial spin labeling: Impact of modeling dispersion and interaction with denoising strategies and pathology.

PURPOSE: Arterial spin labeling (ASL) acquisitions at multiple post-labeling delays may provide more accurate quantification of cerebral blood flow (CBF), by fitting appropriate kinetic models and simultaneously estimating relevant parameters such as the arterial transit time (ATT) and arterial cerebral blood volume (aCBV). We evaluate the effects of denoising strategies on model fitting and parameter estimation when accounting for the dispersion of the label bolus through the vasculature in cerebrovascular disease. METHODS: We analyzed multi-delay ASL data from 17 cerebral small vessel disease patients (50 ± 9 y) and 13 healthy controls (52 ± 8 y), by fitting an extended kinetic model with or without bolus dispersion. We considered two denoising strategies: removal of structured noise sources by independent component analysis (ICA) of the control-label image timeseries; and averaging the repetitions of the control-label images prior to model fitting. RESULTS: Modeling bolus dispersion improved estimation precision and impacted parameter values, but these effects strongly depended on whether repetitions were averaged before model fitting. In general, repetition averaging improved model fitting but adversely affected parameter values, particularly CBF and aCBV near arterial locations in patients. This suggests that using all repetitions allows better noise estimation at the earlier delays. In contrast, ICA denoising improved model fitting and estimation precision while leaving parameter values unaffected. CONCLUSION: Our results support the use of ICA denoising to improve model fitting to multi-delay ASL and suggest that using all control-label repetitions improves the estimation of macrovascular signal contributions and hence perfusion quantification near arterial locations. This is important when modeling flow dispersion in cerebrovascular pathology.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 2.

Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1.

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.

Impact of Different Saccharides on the In-Process Stability of a Protein Drug During Evaporative Drying: From Sessile Droplet Drying to Lab-Scale Spray Drying.

OBJECTIVES: Solid biopharmaceutical products can circumvent lower temperature storage and transport and increase remote access with lower carbon emissions and energy consumption. Saccharides are known stabilizers in a solid protein produced via lyophilization and spray drying (SD). Thus, it is essential to understand the interactions between saccharides and proteins and the stabilization mechanism. METHODS: A miniaturized single droplet drying (MD) method was developed to understand how different saccharides stabilize proteins during drying. We applied our MD to different aqueous saccharide-protein systems and transferred our findings to SD. RESULTS: The poly- and oligosaccharides tend to destabilize the protein during drying. The oligosaccharide, Hydroxypropyl ß-cyclodextrin (HPßCD) shows high aggregation at a high saccharide-to-protein molar ratio (S/P ratio) during MD, and the finding is supported by nanoDSF results. The polysaccharide, Dextran (DEX) leads to larger particles, whereas HPBCD leads to smaller particles. Furthermore, DEX is not able to stabilize the protein at higher S/P ratios either. In contrast, the disaccharide Trehalose Dihydrate (TD) does not increase or induce protein aggregation during the drying of the formulation. It can preserve the protein's secondary structure during drying, already at low concentrations. CONCLUSION: During the drying of S/P formulations containing the saccharides TD and DEX, the MD approach could anticipate the in-process (in) stability of protein X at laboratory-scale SD. In contrast, for the systems with HPßCD, the results obtained by SD were contradictory to MD. This underlines that depending on the drying operation, careful consideration needs to be applied to the selection of saccharides and their ratios.

Development of a Workflow to Engineer Tailored Microparticles Via Inkjet Printing.

PURPOSE: New drug development and delivery approaches result in an ever-increasing demand for tailored microparticles with defined sizes and structures. Inkjet printing technologies could be promising new processes to engineer particles with defined characteristics, as they are created to precisely deliver liquid droplets with high uniformity. METHODS: D-mannitol was used as a model compound alone or co-processed with the pore former agent ammonium bicarbonate, and the polymer polyethylene glycol 200. Firstly, a drop shape analyzer was used to characterize and understand ink/substrate interactions, evaporation, and solidification kinetics. Consequently, the process was transferred to a laboratory-scale inkjet printer and the resulting particles collected, characterized and compared to others obtained via an industrial standard technique. RESULTS: The droplet shape analysis allowed to understand how 3D structures are formed and helped define the formulation and process parameters for inkjet printing. By adjusting the drop number and process waveform, spherical particles with a mean size of approximately 100 µm were obtained. The addition of pore former and polymer allowed to tailor the crystallization kinetics, resulting in particles with a different surface (i.e., spike-like surface) and bulk (e.g. porous and non-porous) structure. CONCLUSION: The workflow described enabled the production of 3D structures via inkjet printing, demonstrating that this technique can be a promising approach to engineer microparticles.

Learning from the covid-19 outbreaks in long-term care facilities: a systematic review.

BACKGROUND: The COVID-19 pandemic has devastatingly affected Long-Term Care Facilities (LTCF), exposing aging people, staff members, and visitors. The world has learned through the pandemic and lessons can be taken to adopt effective measures to deal with COVID-19 outbreaks in LTCF. We aimed to systematically review the available evidence on the effect of measures to minimize the risk of transmission of COVID-19 in LTCs during outbreaks since 2021. METHODS: The search method was guided by the preferred reporting items for systematic reviews (PRISMA) and the reporting guideline synthesis without meta-analysis (SWiM) in systematic reviews. The search was performed in April 2023. Observational and interventional studies from the databases of PubMed, Web of Science, Scopus, Cochrane Systematic Reviews, CINAHL, and Academic Search were systematically reviewed. We included studies conducted in the LTCF with outbreaks that quantitatively assess the effect of non-pharmacological measures on cases of COVID-19. Two review authors independently reviewed titles for inclusion, extracted data, and undertook the risk of bias according to pre-specified criteria. The quality of studies was analyzed using the Joanna Briggs Institute Critical Appraisal. RESULTS: Thirteen studies were included, with 8442 LTCF experiencing COVID-19 outbreaks and 598 thousand participants (residents and staff members). Prevention and control of COVID-19 infection interventions were grouped into three themes: strategic, tactical, and operational measures. The strategic measures reveal the importance of COVID-19 prevention and control as LTCF structural characteristics, namely the LTCF size, new admissions, infection control surveillance, and architectural structure. At the tactical level, the lack of personal and long staff shifts is related to COVID-19's spread. Operational measures with a favorable effect on preventing COVID-19 transmission are sufficient. Personal protective equipment stock, correct mask use, signaling, social distancing, and resident cohorting. CONCLUSIONS: Operational, tactical, and strategic approaches may have a favorable effect on preventing the spread of COVID-19 in LTCFs experiencing outbreaks. Given the heterogeneous nature of the measures, performing a meta-analysis was not possible. Future research should use more robust study designs to explore similar infection control measures in LTCFs during endemic situations with comparable outbreaks. TRIAL REGISTRATION: The protocol of this systematic review was registered in PROSPERO (CRD42020214566).

Feasibility of 3D Body Tracking from Monocular 2D Video Feeds in Musculoskeletal Telerehabilitation.

Musculoskeletal conditions affect millions of people globally; however, conventional treatments pose challenges concerning price, accessibility, and convenience. Many telerehabilitation solutions offer an engaging alternative but rely on complex hardware for body tracking. This work explores the feasibility of a model for 3D Human Pose Estimation (HPE) from monocular 2D videos (MediaPipe Pose) in a physiotherapy context, by comparing its performance to ground truth measurements. MediaPipe Pose was investigated in eight exercises typically performed in musculoskeletal physiotherapy sessions, where the Range of Motion (ROM) of the human joints was the evaluated parameter. This model showed the best performance for shoulder abduction, shoulder press, elbow flexion, and squat exercises. Results have shown a MAPE ranging between 14.9% and 25.0%, Pearson's coefficient ranging between 0.963 and 0.996, and cosine similarity ranging between 0.987 and 0.999. Some exercises (e.g., seated knee extension and shoulder flexion) posed challenges due to unusual poses, occlusions, and depth ambiguities, possibly related to a lack of training data. This study demonstrates the potential of HPE from monocular 2D videos, as a markerless, affordable, and accessible solution for musculoskeletal telerehabilitation approaches. Future work should focus on exploring variations of the 3D HPE models trained on physiotherapy-related datasets, such as the Fit3D dataset, and post-preprocessing techniques to enhance the model's performance.

Metabolomic Signatures of Treatment Response in Bladder Cancer.

Bladder cancer (BC) stands as one of the most prevalent urological malignancies, with over 500 thousand newly diagnosed cases annually. Treatment decisions in BC depend on factors like the risk of recurrence, the type of tumor, and the stage of the disease. While standard therapeutic approaches encompass transurethral resection of the bladder tumor, radical cystectomy, and chemo- or immunotherapy, these methods exhibit limited efficacy in mitigating the aggressive and recurrent nature of bladder tumors. To overcome this challenge, it is crucial to develop innovative methods for monitoring and predicting treatment responses among patients with BC. Metabolomics is gaining recognition as a promising approach for discovering biomarkers. It has the potential to reveal metabolic disruptions that precisely reflect how BC patients respond to particular treatments, providing a revolutionary method to improve accuracy in monitoring and predicting outcomes. In this article, we present a comprehensive review of studies employing metabolomics approaches to investigate the metabolic responses associated with different treatment modalities for BC. The review encompasses an exploration of various models, samples, and analytical techniques applied in this context. Special emphasis is placed on the reported changes in metabolite levels derived from these studies, highlighting their potential as biomarkers for personalized medicine in BC.

Comprehensive Metabolomics and Lipidomics Profiling of Prostate Cancer Tissue Reveals Metabolic Dysregulations Associated with Disease Development.

Prostate cancer (PCa) is a global health problem that affects millions of men every year. In the past decade, metabolomics and related subareas, such as lipidomics, have demonstrated an enormous potential to identify novel mechanisms underlying PCa development and progression, providing a good basis for the development of new and more effective therapies and diagnostics. In this study, a multiplatform metabolomics and lipidomics approach, combining untargeted mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based techniques, was applied to PCa tissues to investigate dysregulations associated with PCa development, in a cohort of 40 patients submitted to radical prostatectomy for PCa. Results revealed significant alterations in the levels of 26 metabolites and 21 phospholipid species in PCa tissue compared with adjacent nonmalignant tissue, suggesting dysregulation in 13 metabolic pathways associated with PCa development. The most affected metabolic pathways were amino acid metabolism, nicotinate and nicotinamide metabolism, purine metabolism, and glycerophospholipid metabolism. A clear interconnection between metabolites and phospholipid species participating in these pathways was observed through correlation analysis. Overall, these dysregulations may reflect the reprogramming of metabolic responses to produce high levels of cellular building blocks required for rapid PCa cell proliferation.

Insights into the Impact of Nanostructural Properties on Powder Tribocharging: The Case of Milled Salbutamol Sulfate.

The impact of the crystallinity of organic solid materials on their tribocharging propensity is well reported. However, no unequivocal explanation about the potential underlying mechanism(s) could be found so far in the literature. This study reports the effect that different degrees of crystalline disorder has on the tribocharging propensity of a small molecular organic material, salbutamol sulfate (SS). Ball-milling was used to induce structural transformations in the crystalline structure of SS. Particles with different nanostructures were produced and analyzed for their solid-state, particle properties, and tribocharging. It was found that differences in the amorphous content among the processed particles and related moisture levels had an impact on powder tribocharging. A correlation between the latter and the nanostructural properties of the particles was also established. The presence of interfaces between nanodomains of different densities and shorter average lengths within the phases seems to lead to a mitigation of charge. This suggests that undetected, subtle nanostructural differences of materials can affect powder handling and processability by altering their tribocharging. The present findings demonstrate the nanostructural implications of powder triboelectrification, which can help toward the rational design of a wide variety of organic solids.

Impact of white-matter mask selection on DTI histogram-based metrics as potential biomarkers in cerebral small vessel disease.

OBJECTIVE: Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small vessel disease (SVD), but methods and results have varied across studies. This work aims to assess the impact of mask selection for extracting histogram-based metrics of fractional anisotropy (FA) and mean diffusivity (MD) on their sensitivity as SVD biomarkers. METHODS: DTI data were collected from 17 SVD patients and 12 healthy controls. FA and MD maps were estimated; from these, histograms were computed on two whole-brain white-matter masks: normal-appearing white-matter (NAWM) and mean FA tract skeleton (TBSS). Histogram-based metrics (median, peak height, peak width, peak value) were extracted from the FA and MD maps. These were compared between groups and correlated with the patients' cognitive scores (executive function and processing speed). RESULTS: White-matter mask selection significantly impacted FA and MD histogram metrics. In particular, significant interactions were found between Mask and Group for FA peak height (p = 0.027), MD Median (p = 0.035) and MD peak width (p = 0.047); indicating that the mask used affected their ability to discriminate between groups. In fact, MD peak width showed a significant 8.8% increase in patients when using TBSS (p = 0.037), but not when using NAWM (p = 0.69). Moreover, the mask may have an effect on the correlations with cognitive measures. Nevertheless, MD peak width (TBSS: r = - 0.75, NAWM: r = - 0.71) and MD peak height (TBSS: r = 0.65, NAWM: r = 0.62) remained significantly correlated with executive function, regardless of the mask. CONCLUSION: The impact of the processing methodology, in particular the choice of white-matter mask, highlights the need for standardized MRI data-processing pipelines.

Paper-based laser-induced graphene for sustainable and flexible microsupercapacitor applications.

Laser-induced graphene (LIG) is as a promising material for flexible microsupercapacitors (MSCs) due to its simple and cost-effective processing. However, LIG-MSC research and production has been centered on non-sustainable polymeric substrates, such as polyimide. In this work, it is presented a cost-effective, reproducible, and robust approach for the preparation of LIG structures via a one-step laser direct writing on chromatography paper. The developed strategy relies on soaking the paper in a 0.1 M sodium tetraborate solution (borax) prior to the laser processing. Borax acts as a fire-retardant agent, thus allowing the laser processing of sensitive substrates that other way would be easily destroyed under the high-energy beam. LIG on paper exhibiting low sheet resistance (30 Ω sq-1) and improved electrode/electrolyte interface was obtained by the proposed method. When used as microsupercapacitor electrodes, this laser-induced graphene resulted in specific capacitances of 4.6 mF cm-2 (0.015 mA cm-2). Furthermore, the devices exhibit excellent cycling stability (> 10,000 cycles at 0.5 mA cm-2) and good mechanical properties. By connecting the devices in series and parallel, it was also possible to control the voltage and energy delivered by the system. Thus, paper-based LIG-MSC can be used as energy storage devices for flexible, low-cost, and portable electronics. Additionally, due to their flexible design and architecture, they can be easily adapted to other circuits and applications with different power requirements.