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Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the (where we applied realignment, smoothing, and tCompCor as a final step) and the (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency . Furthermore, we found that the strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency.

Objectives The distribution of pathology in neurodegenerative disease can be predicted by the organizational characteristics of white matter in healthy brains. However, we have very little evidence for the impact these pathological changes have on brain function. Understanding any such link between structure and function is critical for understanding how underlying brain pathology influences the progressive behavioral changes associated with neurodegeneration. Here, we demonstrate such a link between structure and function in individuals with premanifest Huntington's. Methods Using diffusion tractography and resting state functional magnetic resonance imaging to characterize white matter organization and functional connectivity, we investigate whether characteristic patterns of white matter organization in the healthy human brain shape the changes in functional coupling between brain regions in premanifest Huntington's disease. Results We find changes in functional connectivity in premanifest Huntington's disease that link directly to underlying patterns of white matter organization in healthy brains. Specifically, brain areas with strong structural connectivity show decreases in functional connectivity in premanifest Huntington's disease relative to controls, while regions with weak structural connectivity show increases in functional connectivity. Furthermore, we identify a pattern of dissociation in the strongest functional connections between anterior and posterior brain regions such that anterior functional connectivity increases in strength in premanifest Huntington's disease, while posterior functional connectivity decreases. Interpretation Our findings demonstrate that organizational principles of white matter underlie changes in functional connectivity in premanifest Huntington's disease. Furthermore, we demonstrate functional antero–posterior dissociation that is in keeping with the caudo–rostral gradient of striatal pathology in HD.

BackgroundIn Huntington’s disease (HD), there is neuronal loss in distributed brain regions predominating in the basal ganglia but also present in the cortex. Functional imaging studies at rest have reported reduced long-range functional connectivity within motor areas as well as associative areas of the frontal and parietal lobes, the basal ganglia and the default mode network. Changes in functional connectivity over time in longitudinal studies in HD and preHD is less known although two studies did not find significant changes in connectivity over one- to three-year periods.AimsWe evaluated the changes in functional organisation within the sensorimotor, associative and limbic cortico-basal ganglia networks in preHD and HD patients compared with controls using resting-state fMRI (rs-fMRI) and graph theory over a two-year period.MethodsWe acquired structural MRI and rs-fMRI in three visits one year apart, in 18 adult HD patients, 24 preHD and 18 gender- and age-matched healthy volunteers from the TRACK-HD study. We inferred topological changes in functional connectivity between 182 regions within cortico-basal ganglia networks using graph theory measures.ResultsWe found significant differences for global graph theory measures in HD but not in preHD. The average shortest path length (L) decreased, which indicated a change toward the random network topology. HD patients also demonstrated increases in degree k, reduced betweeness centrality bc and reduced clustering C. Changes predominated in the sensorimotor network for bc and C and were observed in all circuits for k. Hubs were reduced in preHD and no longer detectable in HD in the sensorimotor and associative networks.ConclusionPreHD is characterised by progressive decrease in hub organisation, and these changes aggravate in HD patients with changes in local metrics.

The global evolution of pre-hospital care systems faces dynamic challenges, particularly in multinational settings. Machine learning (ML) techniques enable the exploration of deeply embedded data patterns for improved patient care and resource optimisation. This study's objective was to accurately predict cases that necessitated transportation versus those that did not, using ML techniques, thereby facilitating efficient resource allocation. ML algorithms were utilised to predict patient transport decisions in a Middle Eastern national pre-hospital emergency medical care provider. A comprehensive dataset comprising 93,712 emergency calls from the 999-call centre was analysed using R programming language. Demographic and clinical variables were incorporated to enhance predictive accuracy. Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost) algorithms were trained and validated. All the trained algorithm models, particularly XGBoost (Accuracy = 83.1%), correctly predicted patients' transportation decisions. Further, they indicated statistically significant patterns that could be leveraged for targeted resource deployment. Moreover, the specificity rates were high; 97.96% in RF and 95.39% in XGBoost, minimising the incidence of incorrectly identified \"Transported\" cases (False Positive). The study identified the transformative potential of ML algorithms in enhancing the quality of pre-hospital care in Qatar. The high predictive accuracy of the employed models suggested actionable avenues for day and time-specific resource planning and patient triaging, thereby having potential to contribute to pre-hospital quality, safety, and value improvement. These findings pave the way for more nuanced, data-driven quality improvement interventions with significant implications for future operational strategies.

Vanadium has been shown to catalyze the generation of reactive oxygen species. Since free radical production and lipid peroxidation are potentially important mediators in testicular physiology and pathophysiology, the present study was conducted to elucidate vanadium-induced oxidative damage in rat testis and the ameliorative role of Salvia officinalis essential oil (SEO) against the adverse effects of this heavy metal. Adult male Wistar rats were treated daily during 10 days either with ammonium metavanadate (5 mg/kg bw, intraperitoneally), SEO (15 mg/kg bw, orally) or their combination. A group of rats receiving daily a saline solution served as a negative control. Vanadium treatment induced a significant decrease in body and reproductive organ weights, serum testosterone level and sperm number and motility. An increase in lipid peroxidation and protein oxidation as well as a marked inhibition in the activities of antioxidant enzymes in the testes and seminal vesicles indicated the occurrence of oxidative stress after vanadium toxicity. Histopathological changes in testis and seminal vesicles were also observed following vanadium administration. However, co-administration of SEO to vanadium-treated rats resulted in an appreciable improvement of these parameters, emphasizing the therapeutic effects of SEO. It can be suggested that SEO mitigates vanadium-induced reproductive damage due to its antioxidant capacity. Thus, we can hypothesize that SEO supplementation could protect against vanadium poisoning.

This trial aimed to assess the efficacy of Atorvastatin reloading on the prevention of Contrast-induced nephropathy (CIN) in patients pre-treated with this statin and undergoing coronary catheterization. This was a prospective randomized controlled study including patients on chronic atorvastatin therapy. We randomly assigned the population to the Atorvastatin Reloading group (AR group), by reloading patients with 80 mg of atorvastatin one day before and three days after the coronary procedure, and the Non-Reloading group (NR group), including patients who received their usual dose without a reloading dose. The primary endpoints were the incidence of cystatin (Cys)-based CIN and Creatinine (Scr)-based CIN. The secondary endpoints consisted of the changes in renal biomarkers (Δ biomarkers) defined as the difference between the follow-up level and the baseline level. Our population was assigned to the AR group (n = 56 patients) and NR group (n = 54 patients). The baseline characteristics of the 2 groups were similar. Serum creatinine (SCr)-based CIN occurred in 11.1% in the NR group, and in 8.9% in the AR group without any significant difference. Cys-based CIN occurred in 37% in the NR group and 26.8% in the AR group without any significant difference. The subgroup analysis showed that high dose reloading had significantly reduced the CYC-based CIN risk in patients with type 2 diabetes (43.5% vs 18.8%, RR = 0.43. CI 95% [0.18-0.99])). The comparison of \"Δ Cystatin\" and Δ eGFR between the AR and NR groups didn't show any significant difference. However, cystatin C had significantly increased between baseline and at 24 hours in the NR group (0.96 vs 1.05, p = 0.001), but not in the AR group (0.94 vs 1.03, p = 0.206). Our study did not find a benefit of systematic atorvastatin reloading in patients on chronic atorvastatin therapy in preventing CIN. However, it suggested that this strategy could reduce the risk of CyC-based CIN in diabetic type 2 patients.

Background Sfax is a very industrialized city located in the southern region of Tunisia where heavy metals (HMs) pollution is now an established matter of fact. The health of its residents mainly those engaged in industrial metals-based activities is under threat. Indeed, such workers are being exposed to a variety of HMs mixtures, and this exposure has cumulative properties. Whereas current HMs exposure assessment is mainly carried out using direct air monitoring approaches, the present study aims to assess health risks associated with chronic occupational exposure to HMs in industry, using a modeling approach that will be validated later on. Methods To this end, two questionnaires were used. The first was an identification/descriptive questionnaire aimed at identifying, for each company: the specific activities, materials used, manufactured products and number of employees exposed. The second related to the job-task of the exposed persons, workplace characteristics (dimensions, ventilation, etc.), type of metals and emission configuration in space and time. Indoor air HMs concentrations were predicted, based on the mathematical models generally used to estimate occupational exposure to volatile substances (such as solvents). Later on, and in order to validate the adopted model, air monitoring will be carried out, as well as some biological monitoring aimed at assessing HMs excretion in the urine of workers volunteering to participate. Lastly, an interaction-based hazard index HI int and a decision support tool will be used to predict the cumulative risk assessment for HMs mixtures. Discussion One hundred sixty-one persons working in the 5 participating companies have been identified. Of these, 110 are directly engaged with HMs in the course of the manufacturing process. This model-based prediction of occupational exposure represents an alternative tool that is both time-saving and cost-effective in comparison with direct air monitoring approaches. Following validation of the different models according to job processes, via comparison with direct measurements and exploration of correlations with biological monitoring, these estimates will allow a cumulative risk characterization.

Given the lack of information about the lipid profile of local durum wheat landraces, and their presumed high nutritional value, gas chromatography coupled to a time-of-flight mass analyzer was used to investigate the lipid profiles of three of the most important local durum wheat landraces. The obtained results indicated the nutritional adequacy and quality of Mahmoudi’s and Jnah khottifa’s whole grain wheat flour. Analysis of the biosynthetic pathway highlighted that the linoleic acid metabolism and the fatty acid biosynthesis pathway are impactful metabolic pathways in discriminating between landraces. β-Sitosterol and 2-linoleoylglycerol were identified as hub metabolites. Based on this, GC–TOF-MS™-based lipid profiling could be used as an authenticity tool to differentiate local whole grain flours or guide the selection of specific marker compounds to set proper quality standards for better restoration and in situ and ex situ conservation of the subsequent use of these valuable germ.

In this study, the effects of cultivar, harvest year and the geographical regions were investigated by determining the sensory and chemical characteristics (Fatty acids, Triacyglycerid and Tocopherols compositions) of the cultivars from different geographical origins (Tunisia, Portugal, France and Turkey) over a 2-year harvest period. Parameters such as palmitic acid, oleic acid, linoleic acid and oxidative stability were found to be significantly affected according to the region and cultivar. The highest linoleic and lowest oleic acid content were detected in Tunisia. The amount of palmitic acid was found to be higher in some cultivar (Tunisia and Turkey) than in others (Portugal and France). Nevertheless, principal component analysis allowed us to highlight the Tunisian olive oils for its interesting oxidative stability.

Two yeast strains are enriched and isolated from industrial refinery wastewater. These strains were observed for their ability to utilize several classes of petroleum hydrocarbons substrates, such as n-alkanes and aromatic hydrocarbons as a sole carbon source. Phylogenetic analysis based on the D1/D2 variable domain and the ITS-region sequences indicated that strains HC1 and HC4 were members of the genera Candida and Trichosporon, respectively. The mechanism of hydrocarbon uptaking by yeast, Candida, and Trichosporon has been studied by means of the kinetic analysis of hydrocarbons-degrading yeasts growth and substrate assimilation. Biodegradation capacity and biomass quantity were daily measured during twelve days by gravimetric analysis and gas chromatography coupled with mass spectrometry techniques. Removal of n-alkanes indicated a strong ability of hydrocarbon biodegradation by the isolated yeast strains. These two strains grew on long-chain n-alkane, diesel oil, and crude oil but failed to grow on short-chain n-alkane and aromatic hydrocarbons. Growth measurement attributes of the isolates, using n-hexadecane, diesel oil, and crude oil as substrates, showed that strain HC1 had better degradation for hydrocarbon substrates than strain HC4. In conclusion, these yeast strains can be useful for the bioremediation process and decreasing petroleum pollution in wastewater contaminated with petroleum hydrocarbons.