Mild traumatic brain injury (mTBI), also referred to as concussion, remains a controversial diagnosis because the brain often appears quite normal on conventional computed tomography (CT) and ...magnetic resonance imaging (MRI) scans. Such conventional tools, however, do not adequately depict brain injury in mTBI because they are not sensitive to detecting diffuse axonal injuries (DAI), also described as traumatic axonal injuries (TAI), the major brain injuries in mTBI. Furthermore, for the 15 to 30 % of those diagnosed with mTBI on the basis of cognitive and clinical symptoms, i.e., the “miserable minority,” the cognitive and physical symptoms do not resolve following the first 3 months post-injury. Instead, they persist, and in some cases lead to long-term disability. The explanation given for these chronic symptoms, i.e., postconcussive syndrome, particularly in cases where there is no discernible radiological evidence for brain injury, has led some to posit a psychogenic origin. Such attributions are made all the easier since both posttraumatic stress disorder (PTSD) and depression are frequently co-morbid with mTBI. The challenge is thus to use neuroimaging tools that are sensitive to DAI/TAI, such as diffusion tensor imaging (DTI), in order to detect brain injuries in mTBI. Of note here, recent advances in neuroimaging techniques, such as DTI, make it possible to characterize better extant brain abnormalities in mTBI. These advances may lead to the development of biomarkers of injury, as well as to staging of reorganization and reversal of white matter changes following injury, and to the ability to track and to characterize changes in brain injury over time. Such tools will likely be used in future research to evaluate treatment efficacy, given their enhanced sensitivity to alterations in the brain. In this article we review the incidence of mTBI and the importance of characterizing this patient population using
objective radiological measures
. Evidence is presented for detecting brain abnormalities in mTBI based on studies that use advanced neuroimaging techniques. Taken together, these findings suggest that more sensitive neuroimaging tools improve the detection of brain abnormalities (i.e., diagnosis) in mTBI. These tools will likely also provide important information relevant to outcome (prognosis), as well as play an important role in longitudinal studies that are needed to understand the dynamic nature of brain injury in mTBI. Additionally, summary tables of MRI and DTI findings are included. We believe that the enhanced sensitivity of newer and more advanced neuroimaging techniques for identifying areas of brain damage in mTBI will be important for documenting the biological basis of postconcussive symptoms, which are likely associated with subtle brain alterations, alterations that have heretofore gone undetected due to the lack of sensitivity of earlier neuroimaging techniques. Nonetheless, it is noteworthy to point out that detecting brain abnormalities in mTBI does not mean that other disorders of a more psychogenic origin are not co-morbid with mTBI and equally important to treat. They arguably are. The controversy of psychogenic versus physiogenic, however, is not productive because the psychogenic view does not carefully consider the limitations of conventional neuroimaging techniques in detecting subtle brain injuries in mTBI, and the physiogenic view does not carefully consider the fact that PTSD and depression, and other co-morbid conditions, may be present in those suffering from mTBI. Finally, we end with a discussion of future directions in research that will lead to the improved care of patients diagnosed with mTBI.
Summary
In recent years, there has been massive progress in artificial intelligence (AI) with the development of deep neural networks, natural language processing, computer vision and robotics. These ...techniques are now actively being applied in healthcare with many of the health service activities currently being delivered by clinicians and administrators predicted to be taken over by AI in the coming years. However, there has also been exceptional hype about the abilities of AI with a mistaken notion that AI will replace human clinicians altogether. These perspectives are inaccurate, and if a balanced perspective of the limitations and promise of AI is taken, one can gauge which parts of the health system AI can be integrated to make a meaningful impact. The four main areas where AI would have the most influence would be: patient administration, clinical decision support, patient monitoring and healthcare interventions. This health system where AI plays a central role could be termed an AI-enabled or AI-augmented health system. In this article, we discuss how this system can be developed based on a realistic assessment of current AI technologies and predicted developments.
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•Metabolomics reveals potential diagnostic markers for diabetic nephropathy (DN).•Lipid metabolism in podocytes emerges as pivotal in DN.•Cinaciguat activation of NO/sGC/PKG pathway ...shows promise in DN.•Tryptophan levels serve as prognostic indicators for DN progression.•Integration of metabolomics enhances understanding and management of DN.
Diabetic nephropathy (DN), a severe complication of diabetes, involves a range of renal abnormalities driven by metabolic derangements. Metabolomics, revealing dynamic metabolic shifts in diseases like DN and offering insights into personalized treatment strategies, emerges as a promising tool for improved diagnostics and therapies.
We conducted an extensive literature review to examine how metabolomics contributes to the study of DN and the challenges associated with its implementation in clinical practice. We identified and assessed relevant studies that utilized metabolomics methods, including nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) to assess their efficacy in diagnosing DN.
Metabolomics unveils key pathways in DN progression, highlighting glucose metabolism, dyslipidemia, and mitochondrial dysfunction. Biomarkers like glycated albumin and free fatty acids offer insights into DN nuances, guiding potential treatments. Metabolomics detects small-molecule metabolites, revealing disease-specific patterns for personalized care.
Metabolomics offers valuable insights into the molecular mechanisms underlying DN progression and holds promise for personalized medicine approaches. Further research in this field is warranted to elucidate additional metabolic pathways and identify novel biomarkers for early detection and targeted therapeutic interventions in DN.
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has been associated with neurological and neuropsychiatric illness in many ...individuals. We sought to further our understanding of the relationship between brain tropism, neuro-inflammation, and host immune response in acute COVID-19 cases.
Three brain regions (dorsolateral prefrontal cortex, medulla oblongata, and choroid plexus) from 5 patients with severe COVID-19 and 4 controls were examined. The presence of the virus was assessed by western blot against viral spike protein, as well as viral transcriptome analysis covering > 99% of SARS-CoV-2 genome and all potential serotypes. Droplet-based single-nucleus RNA sequencing (snRNA-seq) was performed in the same samples to examine the impact of COVID-19 on transcription in individual cells of the brain.
Quantification of viral spike S1 protein and viral transcripts did not detect SARS-CoV-2 in the postmortem brain tissue. However, analysis of 68,557 single-nucleus transcriptomes from three distinct regions of the brain identified an increased proportion of stromal cells, monocytes, and macrophages in the choroid plexus of COVID-19 patients. Furthermore, differential gene expression, pseudo-temporal trajectory, and gene regulatory network analyses revealed transcriptional changes in the cortical microglia associated with a range of biological processes, including cellular activation, mobility, and phagocytosis.
Despite the absence of detectable SARS-CoV-2 in the brain at the time of death, the findings suggest significant and persistent neuroinflammation in patients with acute COVID-19.
To test the hypothesis that use of antihypertensive medication is associated with lower Alzheimer disease (AD) neuropathology.
This was a postmortem study of 291 brains limited to those with normal ...neuropathology or with uncomplicated AD neuropathology (i.e., without other dementia-associated neuropathology) in persons with or without hypertension (HTN) who were and were not treated with antihypertensive medications. Neuritic plaque (NP) and neurofibrillary tangle (NFT) densities, quantified in selected brain regions according to the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropathologic criteria, with additional cortical NP counts, yielded 24 neuropathologic regional measures or summaries. Medicated hypertension (HTN-med; n = 77), nonmedicated HTN (HTN-nomed; n = 42), and non-HTN (no-HTN; n = 172) groups were compared by analyses of variance.
The HTN-med group had significantly less neuropathology than the no-HTN group. The no-HTN group averaged over 50% higher mean NP and NFT ratings, and double the mean NP count, of the HTN-med group. The HTN-nomed group had significantly more neuropathology than the HTN-med group, but not significantly less than the no-HTN group.
There was substantially less Alzheimer disease (AD) neuropathology in the medicated hypertension group than the nonhypertensive group, which may reflect a salutary effect of antihypertensive medication against AD-associated neuropathology.
•Pure and antimony doped SnO2 thin films were fabricated by sol- gel spin coating technique.•The crystallite size was decreased with increasing the Sb doping concentration in SnO2.•The optical ...bandgap energy was varied from 3.65 to 4.03 eV.•Sample C0 shows the highest gas response at the inflection point of 30 °C (ambient temperature).•Sample C0 was found suitable for humidity sensing.
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Antimony-doped SnO2 (SnO2:Sb) thin films were deposited on glass substrates via sol-gel spin coating and tested for CO2 gas and humidity sensors. The dominant peak (110) of XRD pattern of SnO2:Sb thin films confirmed the cassiterite tetragonal structure regardless of Sb dopant concentration. The spherical particles like morphology were found for all sample and confirmed by scanning electron microscopy (SEM). The transmittance spectra were recorded in the wavelength range 300–800 nm and the optical bandgap was varied from 3.65 to 4.03 eV on increasing Sb concertation in SnO2. From I-V characteristics, sample C3 has the minimum resistivity (1.08 × 108 Ω.cm) and maximum conductivity 9.23 × 10−9 (Ω.cm)−1 at bias voltage 5 V. The gas sensing characteristics of Sb-SnO2 thin films were examined at different operating temperatures (30 °C to 80 °C) for sample C0 to C4. The optimized sample C0 have gas sensor response 78.5% at ambient temperature (30 °C). The higher doping of Sb in SnO2 as sample C3 and C4 were suitable for higher operating temperatures (80 °C) and responses were 18.74% and 71%, respectively. The characteristics of humidity sensors were analysed in relative humidity (%RH) range from 10% to 90%RH for Sb-SnO2 thin films and found suitable for sample C0 at ambient temperature in mid humidity range (35–60%RH). The present study is an attempt to design a cost-effective and low-temperature-based resistive CO2 gas sensor and humidity sensor for the enhancement in sensing properties.
► Synthesis of Boron doped ZnO (ZnO:B) films. ► Minimum of resistivity is observed to be 7.9×10−4Ωcm. ► Maximum transmittance ∼91% for 450°C annealed films. ► Applicable for window materials in Dye ...Sensitized Solar Cell.
Highly transparent and conducting boron doped zinc oxide (ZnO:B) films grown by sol–gel method are reported. The annealing temperature is varied from 350 to 550°C and doping concentration of boron is kept fixed for 0.6at.% for all the films. At low temperature the stress in the films is compressive, which becomes tensile for the films annealed at higher temperature. A minimum resistivity of 7.9×10−4Ωcm and maximum transmittance of ∼91% are observed for the film annealed at 450°C. This could be attributed to minimum stress of films, which is further evident by the evolution of A1 and defect related Raman modes without any shifting in its position. Such kind of highly transparent and conducting ZnO:B thin film could be used as window material in Dye Sensitized Solar Cell (DSSC).
In the present paper, confined dry Cu nanoaerosols of controlled particle size are inspected under a time-resolved LIBS scheme to explore the effect of laser-particulate matter interaction upon the ...detection capability of airborne nanoparticulate material. Optically catapulted streams probed showed linear intensity vs mass correlation and similar signal stability which is linked to the seeding effect caused by smaller particles yielding hotter, albeit shorter plasmas. Seeding effect is demonstrated by hyperspectral time-resolved aerosol inspection, which exposes both, the interaction between multiple plasma nuclei and the discrete nature of the laser-particle interaction. Observed population/exhaustion cycles at the focal volume of the inspection laser explained the uncertainty values characteristic of LIBS inspection of aerosols. A thorough inspection of the emission in time evidenced a significantly different evolution of the intensity profile for commonly monitored Cu lines owed not only to the nature of the monitored transit and pulse energy, but also to particle size. These results suggest that the experimental settings for quantitative ultrafine aerosol inspection need to be tuned according to the target particle size and the particle density of the aerosol as seeding effects facilitates signal saturation, therefore this effect simultaneously contributes to and detracts from the analytical performance of LIBS on nanometric aerosols.
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•Plasma lifetime increases proportionally to the nanoparticle size whereas plasma temperature decreases inversely with size.•Decreasement in Te is caused by seeding effects, indicating larger nanoparticle-laser interaction for smaller diameters.•RSD values were attributed to the cyclic population/exhaustion of the focal volume using hyperspectral imaging.•The novelty of this application opens a new horizon to the quantitative inspection of nanoaerosols by LIBS.
The widespread existence of different organic contaminants mostly phenolic compounds, organic dyes and antibiotics in water bodies initiated by the various industrial wastes that raised great ...scientific concern and public awareness as well recently owing to their prospective capability to spread these contaminants resistant gene and pose hazard to human. In the present study, a series of nanostructured ZnO-CdO incorporated with reduced graphene oxide (ZCG nanocomposites) were successfully synthesized by a simple refluxing method and characterized by using the X-ray diffraction (XRD), Raman spectroscopy, FT-IR spectroscopy, photoluminescence spectroscopy, field emission-scanning microscope (FE-SEM) and UV–visible diffused reflectance spectroscopy (DRS) for the photocatalytic degradation of bisphenol A (BPA), thymol blue (ThB) and ciprofloxacin (CFn) with illumination of UV light. The maximum degradation and mineralization of BPA, ThB and CFn was achieved around 98.5%, 98.38% and 99.28% over the ZCG-5 nanocomposite photocatalyst after UV light irradiation for 180 min, 120 min and 75 min, respectively. The superior photocatalytic activity of ZCG-5 ascribed to enhance adsorption capacity, effective separation of charge carriers consequential for the production of more ROS after incorporation of RGO nanosheets with ZnO-CdO in photocatalyst. The conceivable photocatalytic degradation mechanism of BPA, ThB and CFn was elucidated through ROS identification and the assessment of photocatalyst stability by reusability, EEO (kwh/m3order) and UV light dose (mJ/cm2) were evaluated. The plausible photocatalytic degradation pathways were proposed for the degradation of BPA, ThB and CFn via GC-MS analysis. The present work investigates the efficient removal of BPA, ThB and CFn using ZCG nanocomposites as photocatalyst.
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•Synthesis of ZnO-CdO-RGO nanocomposites by refluxing method.•Reusability and sustainability of ZCG-5 nanocomposite as photocatalyst.•Photodegradation kinetics of Bisphenol A, Thymol blue and ciprofloxacin using ZCG nanocomposites.•Significance of ZnO-CdO and RGO nanosheets in ZCG nanocomposites and Plausible photocatalytic degradation mechanism.•Plausible photocatalytic degradation pathway of bisphenol A, thymol blue and ciprofloxacin.
•Deformation and resulting residual stresses were studied in a Ti-7Al alloy.•Crystal-scale modeling was combined with high energy X-ray diffraction (HEXD).•HEXD data was used to initialize the model ...microstructure and rate sensitivity.•Stress values and slip activities are determined at the grain and subgrain level.•Prismatic slip was dominant and accurate rate sensitivity was critical to modeling.
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Finite element simulations are carried out to follow the evolution of residual stresses in Ti-7Al (α-hcp) alloy, as developed under an applied stress gradient. A model built upon phenomenological mesoscopic field dislocation mechanics is employed to simulate the deformation behavior. Model predictions are validated with results generated from high energy X-ray diffraction experiments using synchrotron radiation. These experiments provide for important simulation input, viz. grain positions and orientations, and strain rate sensitivities of the prismatic and basal slip systems of Ti-7Al. X-ray diffraction data obtained from individual grains enabled calculation of strain rate sensitivities of the prismatic and basal slip systems and the values are estimated as ∼ 0.04 and ∼ 0.02 respectively. Residual stresses at the length scale of individual grains and subgrains are successfully predicted and validated against experimental data. A key achievement of the present work is the measurement and simulation of residual stress gradients within individual grains. Conclusions from this work are that grains deform mainly via prismatic slip, and accurate characterization of rate-sensitivity is needed to model the development of grain-level residual stresses.
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