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PURPOSE: To investigate whether the diffusion tensor imaging (DTI) parameters alterations in the in hypoxia-related neuroanatomical localizations in patients after COVID-19. Additionally, the relationship between DTI findings and the clinical severity of the disease is evaluated. METHODS: The patients with COVID-19 were classified into group 1 (total patients, n = 74), group 2 (outpatient, n = 46), and group 3 (inpatient, n = 28) and control (n = 52). Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were calculated from the bulbus, pons, thalamus, caudate nucleus, globus pallidum, putamen, and hippocampus. DTI parameters were compared between groups. Oxygen saturation, D dimer and lactate dehydrogenase (LDH) values associated with hypoxia were analyzed in inpatient group. Laboratory findings were correlated with ADC and FA values. RESULTS: Increased ADC values in the thalamus, bulbus and pons were found in group 1 compared to control. Increased FA values in the thalamus, bulbus, globus pallidum and putamen were detected in group 1 compared to control. The FA and ADC values obtained from putamen were higher in group 3 compared to group 2. There was a negative correlation between basal ganglia and hippocampus FA values and plasma LDH values. The ADC values obtained from caudate nucleus were positively correlated with plasma D Dimer values. CONCLUSION: ADC and FA changes may reveal hypoxia-related microstructural damage after COVID-19 infection. We speculated that the brainstem and basal ganglia can affected during the subacute period.
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In the present work, at first, DFT calculations were carried out to study the molecular structure of the tenofovir at B3LYP/MidiX level of theory and in the water as solvent. The HOMO/LUMO molecular orbitals, excitation energies and oscillator strengths of investigated drug were also calculated and presented. NBO analysis was performed to illustrate the intramolecular rehybridization and electron density delocalization. In the following, a molecular docking study was performed for screening of effective available tenofovir drug which may act as an efficient inhibitor for the SARS-CoV-2 M-pro. The binding energy value showed a good binding affinity between the tenofovir and SARS-CoV-2 Mpro with binding energy of-47.206 kcal/mol. Therefore, tenofovir can be used for possible application against the SARS-CoV-2 M-pro.
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Background: Nervous system post-acute sequelae of COVID-19 (NS-PASC) include cognitive and mental health symptoms. To further define these, we applied a Research Domain Criteria (RDoC) approach to examine motor, positive valence (PV) and negative valence (NV) systems, and social processing data in The COVID Mind Study of NS-PASC. Method(s): NS-PASC participants (>3 months after COVID-19) referred from a NeuroCOVID Clinic and non-COVID controls from New Haven, CT and Baltimore, MD completed an RDoC test battery for cognition (language, declarative and working memory, cognitive control, perception), motor, PV, NV, and social processes. To date, 3T MRI with diffusion tensor imaging was performed in 11 NS-PASC to assess white matter integrity (global white matter fractional anisotropy [FA]) as a contributor to alterations identified on the RDoC tests. Analysis of Covariance examined group differences after adjusting for sex, race, ethnicity, age, and years of education. Result(s): 25 NS-PASC participants (age 43.4+/-11.3 yrs, 76% female, 402 days after COVID-19 symptom onset) and 29 controls (age 46.2.6+/-13.1 yrs, 66% female) completed the battery. Controls were more racially diverse and less educated than NS-PASC (43% vs. 12% Black, p=0.005;14.5 vs. 16.1 yrs of education, p< 0.05). Means and statistics for RDoC between NS-PASC and controls are shown in Table. NS-PASC performed worse in language, verbal working and declarative memory, and perception and reported greater cognitive control difficulties (e.g., behavioral inhibition, set shifting) without issues on performance-based metrics (Stroop, Trail Making Test-Part B), and had slower motor function. NS-PASC reported more NV issues including greater symptoms of depression, rumination in response to depressive mood, apathy, childhood trauma, anxiety, and perceived stress. There were no differences in PV and social processing. In a subset of NS-PASC participants who underwent MRI, there was a dynamic range of FA values with a mean of 0.509 (IQR 0.481 - 0.536). Conclusion(s): Our findings extend previous PASC studies characterizing cognitive and mental health alterations, indicating that additional RDoC assessments warrant focus, including alterations in motor and the negative valence system. In future analyses, we will examine white matter integrity as a pathophysiologic contributor to these RDoC systems.
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Background: Post-acute sequelae of SARS-COV-2 infection (PASC) is associated with cognitive impairment (CI) with unclear pathogenesis though blood brain barrier (BBB) impairment and excitotoxic injury appear significant. Post-acute sequelae of SARS-COV-2 infection (PASC) is associated with cognitive impairment (CI) with unclear pathogenesis though blood brain barrier (BBB) impairment and excitotoxic injury appear significant. We hypothesized that PASC CI patients would have brain inflammation and BBB disruption using advanced MR imaging. Method(s): In this prospective longitudinal study, 14 patients with PASC CI (mild and non-hospitalised) were enrolled (mean age of 45;10 F and 4 M) and 10 sex and age matched healthy controls. 13 had a follow up MR at 9-12 months (mean 10 months). All participants underwent DCE perfusion (an index of BBB integrity with Ktrans as the measurement), Diffusion Tensor Imaging (DTI) and single voxel MR spectroscopy (MRS) of the frontal cortex/white matter and the brainstem in addition to brain anatomical MRI. Between group analyses were used to determine which MRI outcomes were significantly different from controls in patients with PASC CI. Result(s): The PASCI CI group showed significantly increased (ie BBB impairment) Ktrans, and increased region (Frontal white matter and Brain Stem)-specific areas in the brain (p=< 0.005), reduction in NAA (ie neuronal injury) and mild reduction of Glx (ie excitotoxicity) in the frontal white matter and brain stem (p=0.004), and reduction in white matter integrity (increased diffusivity -greater radial and mean diffusivity). Increased Ktrans was correlated with increased both radial and mean diffusivity (r=0.9) in all tested brain regions. Ktrans significantly improved in the follow up MR (p= 002596 Z=-2.794872) with no difference between subjects and controls indicating BBB normalisation (p= 0.442418, z= -0.144841). White matter integrity also improved especially in the fractional anisotropy values in the executive networks (p=< 0.00045). MRS showed significant improvement in the NAA in the frontal white matter but Glx remain high as compared to the controls (p=0.0006). Conclusion(s): PASC CI was characterised by reversible diffuse BBB impairment, neuronal/axonal and excitotoxic injury. BBB impairment was associated with white matter disruption. These are suggestive biomarkers for the presence, severity and prognosis of PASC CI. Such biomarkers could underpin appropriate trial design and timing of intervention.
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With the expansion of novel coronavirus pneumonia's influence on the world, people's dependence on infrared thermometer guns is increasing. In order to improve the measurement accuracy of the infrared temperature measuring gun and meet the requirements of rapid and accurate measurement of human body temperature, the core components for the infrared temperature measuring gun are developed and prepared in this paper. The film fogging phenomenon caused by the anisotropy of metal germanium and semiconductor properties is analysed and solved by measuring the atomic force microscope image and infrared spectrum of the film, the 5.5-micron infrared filter with high transmittance and good film quality was prepared by electron beam evaporation, resistance evaporation and ion source assisted deposition. © 2022 IEEE.
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In December 2019, the SARS-CoV-2 virus, often referred to as COVID-19, was discovered in Wuhan, China. It is very virulent and has spread very quickly throughout the world. With COVID-19, people have described a wide variety of symptoms, from little discomfort to life-threatening respiratory illness. In this study, chest X-ray scan images are preprocessed using an anisotropic diffusion filter and three classifiers, and the Covid-19 cases are classified from the chest X-ray images using the GLRLM feature extraction approach. Common metrics like sensitivity, selectivity, and accuracy are utilized to compare the performance of the classifiers. When compared to other classifiers in this study, the Gaussian Mixture Model had the best accuracy of 91.07%. © 2022 IEEE.
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Aim/Introduction: A recent report prepared by the Centers for Disease Control and Prevention indicates that 71% of patients experience persistent fatigue even after recovery from the acute phase of COVID-19 infection. We investigated if post-COVID-19 fatigue is associated with alterations in brain metabolism and microstructure to better understand the underlying neurobiological mechanism. Material(s) and Method(s): Brain F-18 FDG PET and diffusion tensor magnetic resonance imaging (DTIMR) were performed in 12 patients experiencing persistent post- COVID-19 fatigue that lasted more than six weeks post-discharge from hospitalization or discontinued home isolation after acute SARS-CoV-2 infection (fatigue group, Male:Female = 6:6, mean > SD age 35.7 > 13.8 years, Chalder fatigue scale score 8.3 > 2.2, time since COVID-19 diagnosis 7.9 > 5.5 months) and 9 recovered patients without such fatigue (non-fatigue group, M:F = 3:6, age 25.6 > 9.2, fatigue score 1.6 > 1.5, time since COVID-19 diagnosis 8.0 > 6.0 months). A commercially available normative brain FDG PET database (MIMneuro, v7.0.5, MIM Software, Inc.) was used to derive z scores for regional cerebral glucose metabolism. Fractional anisotropy (FA) values were extracted from DTI-MR datasets. Twotailed t-tests were performed for group comparison and P < 0.05 was considered statistically significant. Result(s): The fatigue group demonstrated significantly higher regional cerebral glucose metabolism in the left inferior and middle cerebellar peduncle (P = 0.001 and 0.043, respectively), left middle temporal gyrus (P = 0.002), left parahippocampal gyrus (P = 0.029), primary visual cortex (P = 0.031), supplementary motor area (P = 0.036), supramarginal gyrus (P = 0.044), and lower metabolism in the left precentral gyrus (P = 0.001) when compared to the non-fatigue group. The fatigue group also demonstrated significantly higher FA values in the left and right middle frontal gyrus (P = 0.014 and 0.038, respectively), left precentral gyrus (P = 0.024), right superior frontal gyrus (P =0.032), right postcentral gyrus (P = 0.047), left superior parietal gyrus (P = 0.048), and corpus callosum (P = 0.016) when compared to the nonfatigue group. Conclusion(s): Patients experiencing persistent fatigue after recovering from acute SARS-CoV-2 infection demonstrated significant changes in regional cerebral glucose metabolism and microstructure, when compared to those individuals without on-going fatigue symptoms. The altered cerebral metabolic and microstructural profile may help to better understand the neurobiological mechanism for management of patients suffering from lingering post-COVID-19 fatigue.
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Aim/Introduction: A recent report prepared by the Centers for Disease Control and Prevention indicates that 71% of patients experience persistent fatigue even after recovery from the acute phase of COVID-19 infection. We investigated if post-COVID-19 fatigue is associated with alterations in brain metabolism and microstructure to better understand the underlying neurobiological mechanism. Material(s) and Method(s): Brain F-18 FDG PET and diffusion tensor magnetic resonance imaging (DTIMR) were performed in 12 patients experiencing persistent post- COVID-19 fatigue that lasted more than six weeks post-discharge from hospitalization or discontinued home isolation after acute SARS-CoV-2 infection (fatigue group, Male:Female = 6:6, mean > SD age 35.7 > 13.8 years, Chalder fatigue scale score 8.3 > 2.2, time since COVID-19 diagnosis 7.9 > 5.5 months) and 9 recovered patients without such fatigue (non-fatigue group, M:F = 3:6, age 25.6 > 9.2, fatigue score 1.6 > 1.5, time since COVID-19 diagnosis 8.0 > 6.0 months). A commercially available normative brain FDG PET database (MIMneuro, v7.0.5, MIM Software, Inc.) was used to derive z scores for regional cerebral glucose metabolism. Fractional anisotropy (FA) values were extracted from DTI-MR datasets. Twotailed t-tests were performed for group comparison and P < 0.05 was considered statistically significant. Result(s): The fatigue group demonstrated significantly higher regional cerebral glucose metabolism in the left inferior and middle cerebellar peduncle (P = 0.001 and 0.043, respectively), left middle temporal gyrus (P = 0.002), left parahippocampal gyrus (P = 0.029), primary visual cortex (P = 0.031), supplementary motor area (P = 0.036), supramarginal gyrus (P = 0.044), and lower metabolism in the left precentral gyrus (P = 0.001) when compared to the non-fatigue group. The fatigue group also demonstrated significantly higher FA values in the left and right middle frontal gyrus (P = 0.014 and 0.038, respectively), left precentral gyrus (P = 0.024), right superior frontal gyrus (P =0.032), right postcentral gyrus (P = 0.047), left superior parietal gyrus (P = 0.048), and corpus callosum (P = 0.016) when compared to the nonfatigue group. Conclusion(s): Patients experiencing persistent fatigue after recovering from acute SARS-CoV-2 infection demonstrated significant changes in regional cerebral glucose metabolism and microstructure, when compared to those individuals without on-going fatigue symptoms. The altered cerebral metabolic and microstructural profile may help to better understand the neurobiological mechanism for management of patients suffering from lingering post-COVID-19 fatigue.
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Mechanical characterisation of the layer-specific, viscoelastic properties of the human oesophagus is crucial in furthering the development of devices emerging in the field, such as robotic endoscopic biopsy devices, as well as in enhancing the realism, and therefore effectiveness, of surgical simulations. In this study, the viscoelastic and stress-softening behaviour of the passive human oesophagus was investigated through ex vivo cyclic mechanical tests. Due to restrictions placed on the laboratory as a result of COVID-19, only oesophagi from cadavers fixed in formalin were allowed for testing. Three oesophagi in total were separated into their two main layers and the mucosa-submucosa layer was investigated. A series of uniaxial tensile tests were conducted in the form of increasing stretch level cyclic tests at two different strain rates: 1% s[Formula: see text] and 10% s[Formula: see text]. Rectangular samples in both the longitudinal and circumferential directions were tested to observe any anisotropy. Histological analysis was also performed through a variety of staining methods. Overall, the longitudinal direction was found to be much stiffer than the circumferential direction. Stress-softening was observed in both directions, as well as permanent set and hysteresis. Strain rate-dependent behaviour was also apparent in the two directions, with an increase in strain rate resulting in an increase in stiffness. This strain rate dependency was more pronounced in the longitudinal direction than the circumferential direction. Finally, the results were discussed in regard to the histological content of the layer, and the behaviour was modelled and validated using a visco-hyperelastic matrix-fibre model.
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COVID-19 , Humans , Anisotropy , Stress, Mechanical , Esophagus , Mucous Membrane , Biomechanical PhenomenaABSTRACT
Objective: This study investigates the effects of COVID-19 on brain microstructure among those recently recovering from COVID-19 through self isolation. Background: Microstructural differences have previously been detected in comparisons of COVID-19 patients with controls, particularly in regions related to the olfactory system. The olfactory system is connected with the caudate, putamen, thalamus, precuneus, and cingulate regions. Design/Methods: Here we report diffusion magnetic resonance imaging (3 T Siemens MRI) findings from 40 patients (mean age: 43.7, 68% female) who self-isolated after testing positive for COVID (COV+), and 14 COVID negative (COV-) subjects (mean age: 43, 64% female) who had flu-like symptoms. This is part of the Canadian-based NeuroCOVID-19 study. Fractional anisotropy (FA), mean diffusivity (MD), mode of anisotropy (MO), free water fraction (F), tissue-specific FA (FAt) and tissue-specific MD (MDt) were obtained using data with b=700 and 1400 (DIPY free-water model). Regions of interest in the grey matter and white matter were delineated using FreeSurfer. Differences between groups were assessed using an analysis of variance (ANOVA), the Kruskal-Wallis Test and the Mann-Whitney Test, corrected for false-discovery rate of 0.05. Effect size (Cohen's d) was also computed (d>0.45 deemed large effect). Results: In the COV+ group, all three tests revealed decreased FA and FAt in the insula, and increased MD in the parstriangularis cortex. Increased FA and FAt in the cuneus (along with decreased MD) was also found. MD was reduced in COV+ in the temporal and supramarginal areas. MO was lower in COV+ in the insula and amygdala regions. Conclusions: In patients, higher MD with lower FA and MO suggest increased extracellular fluids, while lower MD with decreased FA and MO may suggest necrotic debris built up following inflammation. The cuneus and insula are involved in visual and taste processing, respectively. This study highlights the need to study neurological effects of COVID-19.
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Objective: This study investigates the chronic effects of COVID-19 on brain microstructure. Background: Microstructural differences have previously been detected in comparisons of COVID-19 patients with controls, particularly in the insula, cuneus, inferior temporal and anterior cingulate regions. Design/Methods: Here we report diffusion magnetic resonance imaging (3 T Siemens MRI) findings from 20 participants (mean age: 45.3, 55% female), both immediately after recovery and at a 3-month follow-up. Fractional anisotropy (FA), mean diffusivity (MD), mode of diffusivity (MO), free water fraction (F), tissue-specific FA (FAt) and tissue-specific MD (MDt) were obtained using DTI data with b=700 and 1400 (DIPY free-water model). Regions of interest in the grey matter and white matter were delineated using FreeSurfer. To assess differences between baseline and follow-up, a paired t-test, the Wilcoxon Test and Friedman Test were performed, corrected for false-discovery rate of 0.05. Effect size (Cohen's d) was also computed (d>0.45 deemed large effect). Results: All three tests revealed decreased F in the hippocampus and decreased MD in the parahippocampal region of the WM at follow-up. In the GM, F was increased in the medial orbitofrontal region. In the WM, MD was increased in the paracentral region and MDt was increased in the parahippocampal and lateral orbitofrontal regions. Conclusions: These results suggest that microstructural abnormalities persist following recovery. Increased extracellular fluid (i.e. F and MD) in the frontal lobe suggest spreading of COVID-19 impact, while decreased F and MD in the hippocampal region suggest debris accumulation as part of the inflammatory process. None of the regions affected in sub-acute COVID-19 appear to fully recover within three months.
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This paper proposes an automated classification method of chest CT volumes based on likelihood of COVID-19 cases. Novel coronavirus disease 2019 (COVID-19) spreads over the world, causing a large number of infected patients and deaths. Sudden increase in the number of COVID-19 patients causes a manpower shortage in medical institutions. Computer-aided diagnosis (CAD) system provides quick and quantitative diagnosis results. CAD system for COVID-19 enables efficient diagnosis workflow and contributes to reduce such manpower shortage. This paper proposes an automated classification method of chest CT volumes for COVID-19 diagnosis assistance. We propose a COVID-19 classification convolutional neural network (CNN) that has a 2D/3D hybrid feature extraction flows. The 2D/3D hybrid feature extraction flows are designed to effectively extract image features from anisotropic volumes such as chest CT volumes for diagnosis. The flows extract image features on three mutually perpendicular planes in CT volumes and then combine the features to perform classification. Classification accuracy of the proposed method was evaluated using a dataset that contains 1288 CT volumes. An averaged classification accuracy was 83.3%. The accuracy was higher than that of a classification CNN which does not have 2D and 3D hybrid feature extraction flows. © 2022 SPIE.
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The oesophagus is a primarily mechanical organ whose material characterisation would aid in the investigation of its pathophysiology, help in the field of tissue engineering, and improve surgical simulations and the design of medical devices. However, the layer-dependent, anisotropic properties of the organ have not been investigated using human tissue, particularly in regard to its viscoelastic and stress-softening behaviour. Restrictions caused by the COVID-19 pandemic meant that fresh human tissue was not available for dissection. Therefore, in this study, the layer-specific material properties of the human oesophagus were investigated through ex vivo experimentation of the embalmed muscularis propria layer. For this, a series of uniaxial tension cyclic tests with increasing stretch levels were conducted at two different strain rates. The muscular layers from three different cadaveric specimens were tested in both the longitudinal and circumferential directions. The results displayed highly nonlinear and anisotropic behaviour, with both time- and history-dependent stress-softening. The longitudinal direction was found to be stiffer than the circumferential direction at both strain rates. Strain rate-dependent behaviour was apparent, with an increase in strain rate resulting in an increase in stiffness in both directions. Histological analysis was carried out via various staining methods; the results of which were discussed with regard to the experimentally observed stress-stretch response. Finally, the behaviour of the muscularis propria was simulated using a matrix-fibre model able to capture the various mechanical phenomena exhibited, the fibre orientation of which was driven by the histological findings of the study.
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COVID-19 , Pandemics , Anisotropy , Biomechanical Phenomena , Esophagus , Humans , Stress, MechanicalABSTRACT
This article presents an overview of the dynamics of the human heart and the main goal is the discussion of its fluid mechanic features. We will see, however, that the flow in the heart can not be fully described without considering its electrophysiology and elastomechanics as well as the interaction with the systemic and pulmonary circulations with which it is strongly connected. Biologically, the human heart is similar to that of all warm-blooded mammals and it satisfies the same allometric laws. Since the Paleolithic Age, however, humans have improved their living conditions, have modified the environment to satisfy their needs and, more recently, have developed advanced medical knowledge which has allowed triple the number of heartbeats with respect to other mammals. In the last century, effective diagnostic tools, reliable surgical procedures and prosthetic devices have been developed and refined leading to substantial progress in cardiology and heart surgery with routine clinical practice which nowadays cures many disorders, once lethal. Pulse duplicators have been built to reproduce the pulsatile flow and ‘blood analogues’, have been realized. Heart phantoms, can attain deformations similar to the real heart although the active contraction and the tissue anisotropy still can not be replicated. Numerical models have also become a viable alternative for cardiovascular research: they do not suffer from limitations of material properties and device technologies, thus making possible the realization of truly digital twins. Unfortunately, a high-fidelity model for the whole heart consists of a system of coupled, nonlinear partial differential equations with a number of degrees of freedom of the order of a billion and computational costs become the bottleneck. An additional challenge comes from the inherent human variability and the uncertainty of the heart parameters whose statistical assessment requires a campaign of simulations rather than a single deterministic calculation;reduced and surrogate models can be employed to alleviate the huge computational burden and all possibilities are currently being pursued. In the era of big data and artificial intelligence, cardiovascular research is also advancing by exploiting the latest technologies: equation-based augmented reality, virtual surgery and computational prediction of disease progression are just a few examples among many that will become standard practice in the forthcoming years.
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Mutations in the spike protein generated a highly infectious and transmissible D614G variant, which is present in newly evolved fast-spreading variants. The D614G, Alpha, Beta, and Delta spike variants of SARS-CoV-2 appear to expedite membrane fusion process for entry, but the mechanism of spike-mediated fusion is unknown. Here, we reconstituted an in vitro pseudovirus-liposome fusion reaction and report that SARS-CoV-2 wild-type spike is a dynamic Ca2+ sensor, and D614G mutation enhances dynamic calcium sensitivity of spike protein for facilitating membrane fusion. This dynamic calcium sensitivity for fusion is found to be higher in Alpha and Beta variants and highest in Delta spike variant. We find that efficient fusion is dependent on Ca2+ concentration at low pH, and the fusion activity of spike dropped as the Ca2+ level rose beyond physiological levels. Thus, evolved spike variants may control the high fusion probability for entry by increasing Ca2+ sensing ability.
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COVID-19 , SARS-CoV-2 , Calcium , Humans , Membrane Fusion , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/metabolismABSTRACT
Direct solar vapor generation (SVG) provides a sustainable and eco‐friendly solution to the current global water scarcity challenges. However, existing SVG systems operating under natural sunlight suffer from low water yield and high energy requirement of vaporization. New materials with reduced latent heat of water vaporization are in urgent demand to boost SVG process. Herein, we propose a novel strategy to additively fabricate anisotropic hybrid 3D structure from photocurable thermoresponsive p(NIPAm‐co‐PEGDA) hydrogel on the top of PEGDA foam for SVG. The in‐situ post‐printing synthesis of iron oxide nanoparticles within the p(NIPAm‐co‐PEGDA) hydrogel on the top surface, thus introducing anisotropy, is achieved by adding metallic salt precursor into the printing solution. The as‐fabricated hydrogel composite structure exhibits superior light absorption properties and rapid capillary‐driven water transport through a 3D‐printed microchannel network within the hydrogel. As a result, our SVG device achieves an extraordinary water evaporation rate of 5.12 kg m−2 h−1 under one sun (1 kW/m2). The intrinsic water activation states, in addition to wettability modulation with temperature increase within p(NIPAm‐co‐PEGDA) hydrogel, plays a critical role in reducing the equivalent vaporization enthalpy and shifting the vaporization to relatively lower temperatures. The proposed hybrid SVG device is feasible, portable, and highly efficient, promising great potential for grand water‐energy nexus challenges.
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Pulmonary diseases, driven by pollution, industrial farming, vaping, and the infamous COVID-19 pandemic, lead morbidity and mortality rates worldwide. Computational biomechanical models can enhance predictive capabilities to understand fundamental lung physiology; however, such investigations are hindered by the lung's complex and hierarchical structure, and the lack of mechanical experiments linking the load-bearing organ-level response to local behaviors. In this study we address these impedances by introducing a novel reduced-order surface model of the lung, combining the response of the intricate bronchial network, parenchymal tissue, and visceral pleura. The inverse finite element analysis (IFEA) framework is developed using 3-D digital image correlation (DIC) from experimentally measured non-contact strains and displacements from an ex-vivo porcine lung specimen for the first time. A custom-designed inflation device is employed to uniquely correlate the multiscale classical pressure-volume bulk breathing measures to local-level deformation topologies and principal expansion directions. Optimal material parameters are found by minimizing the error between experimental and simulation-based lung surface displacement values, using both classes of gradient-based and gradient-free optimization algorithms and by developing an adjoint formulation for efficiency. The heterogeneous and anisotropic characteristics of pulmonary breathing are represented using various hyperelastic continuum formulations to divulge compound material parameters and evaluate the best performing model. While accounting for tissue anisotropy with fibers assumed along medial-lateral direction did not benefit model calibration, allowing for regional material heterogeneity enabled accurate reconstruction of lung deformations when compared to the homogeneous model. The proof-of-concept framework established here can be readily applied to investigate the impact of assorted organ-level ventilation strategies on local pulmonary force and strain distributions, and to further explore how diseased states may alter the load-bearing material behavior of the lung. In the age of a respiratory pandemic, advancing our understanding of lung biomechanics is more pressing than ever before.
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BACKGROUND: Increasing evidence supported the possible neuro-invasion potential of SARS-CoV-2. However, no studies were conducted to explore the existence of the micro-structural changes in the central nervous system after infection. We aimed to identify the existence of potential brain micro-structural changes related to SARS-CoV-2. METHODS: In this prospective study, diffusion tensor imaging (DTI) and 3D high-resolution T1WI sequences were acquired in 60 recovered COVID-19 patients (56.67% male; age: 44.10 ± 16.00) and 39 age- and sex-matched non-COVID-19 controls (56.41% male; age: 45.88 ± 13.90). Registered fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were quantified for DTI, and an index score system was introduced. Regional volumes derived from Voxel-based Morphometry (VBM) and DTI metrics were compared using analysis of covariance (ANCOVA). Two sample t-test and Spearman correlation were conducted to assess the relationships among imaging indices, index scores and clinical information. FINDINGS: In this follow-up stage, neurological symptoms were presented in 55% COVID-19 patients. COVID-19 patients had statistically significantly higher bilateral gray matter volumes (GMV) in olfactory cortices, hippocampi, insulas, left Rolandic operculum, left Heschl's gyrus and right cingulate gyrus and a general decline of MD, AD, RD accompanied with an increase of FA in white matter, especially AD in the right CR, EC and SFF, and MD in SFF compared with non-COVID-19 volunteers (corrected p value <0.05). Global GMV, GMVs in left Rolandic operculum, right cingulate, bilateral hippocampi, left Heschl's gyrus, and Global MD of WM were found to correlate with memory loss (p value <0.05). GMVs in the right cingulate gyrus and left hippocampus were related to smell loss (p value <0.05). MD-GM score, global GMV, and GMV in right cingulate gyrus were correlated with LDH level (p value <0.05). INTERPRETATION: Study findings revealed possible disruption to micro-structural and functional brain integrity in the recovery stages of COVID-19, suggesting the long-term consequences of SARS-CoV-2. FUNDING: Shanghai Natural Science Foundation, Youth Program of National Natural Science Foundation of China, Shanghai Sailing Program, Shanghai Science and Technology Development, Shanghai Municipal Science and Technology Major Project and ZJ Lab.
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Respiratory illnesses, such as bronchitis, emphysema, asthma, and COVID-19, substantially remodel lung tissue, deteriorate function, and culminate in a compromised breathing ability. Yet, the structural mechanics of the lung is significantly understudied. Classical pressure-volume air or saline inflation studies of the lung have attempted to characterize the organ's elasticity and compliance, measuring deviatory responses in diseased states; however, these investigations are exclusively limited to the bulk composite or global response of the entire lung and disregard local expansion and stretch phenomena within the lung lobes, overlooking potentially valuable physiological insights, as particularly related to mechanical ventilation. Here, we present a method to collect the first non-contact, full-field deformation measures of ex vivo porcine and murine lungs and interface with a pressure-volume ventilation system to investigate lung behavior in real time. We share preliminary observations of heterogeneous and anisotropic strain distributions of the parenchymal surface, associative pressure-volume-strain loading dependencies during continuous loading, and consider the influence of inflation rate and maximum volume. This study serves as a crucial basis for future works to comprehensively characterize the regional response of the lung across various species, link local strains to global lung mechanics, examine the effect of breathing frequencies and volumes, investigate deformation gradients and evolutionary behaviors during breathing, and contrast healthy and pathological states. Measurements collected in this framework ultimately aim to inform predictive computational models and enable the effective development of ventilators and early diagnostic strategies.