SARS-CoV-2 vaccination induces immunological T cell memory able to cross-recognize variants from Alpha to Omicron.

We address whether T cell responses induced by different vaccine platforms (mRNA-1273, BNT162b2, Ad26.COV2.S, and NVX-CoV2373) cross-recognize early SARS-CoV-2 variants. T cell responses to early variants were preserved across vaccine platforms. By contrast, significant overall decreases were observed for memory B cells and neutralizing antibodies. In subjects ∼6 months post-vaccination, 90% (CD4+) and 87% (CD8+) of memory T cell responses were preserved against variants on average by AIM assay, and 84% (CD4+) and 85% (CD8+) preserved against Omicron. Omicron RBD memory B cell recognition was substantially reduced to 42% compared with other variants. T cell epitope repertoire analysis revealed a median of 11 and 10 spike epitopes recognized by CD4+ and CD8+ T cells, with average preservation > 80% for Omicron. Functional preservation of the majority of T cell responses may play an important role as a second-level defense against diverse variants.

Reproducibility of [18F]FDG PET/CT liver SUV as reference or normalisation factor.

INTRODUCTION: Although visual and quantitative assessments of [18F]FDG PET/CT studies typically rely on liver uptake value as a reference or normalisation factor, consensus or consistency in measuring [18F]FDG uptake is lacking. Therefore, we evaluate the variation of several liver standardised uptake value (SUV) measurements in lymphoma [18F]FDG PET/CT studies using different uptake metrics. METHODS: PET/CT scans from 34 lymphoma patients were used to calculate SUVmaxliver, SUVpeakliver and SUVmeanliver as a function of (1) volume-of-interest (VOI) size, (2) location, (3) imaging time point and (4) as a function of total metabolic tumour volume (MTV). The impact of reconstruction protocol on liver uptake is studied on 15 baseline lymphoma patient scans. The effect of noise on liver SUV was assessed using full and 25% count images of 15 lymphoma scans. RESULTS: Generally, SUVmaxliver and SUVpeakliver were 38% and 16% higher compared to SUVmeanliver. SUVmaxliver and SUVpeakliver increased up to 31% and 15% with VOI size while SUVmeanliver remained unchanged with the lowest variability for the largest VOI size. Liver uptake metrics were not affected by VOI location. Compared to baseline, liver uptake metrics were 15-18% and 9-18% higher at interim and EoT PET, respectively. SUVliver decreased with larger total MTVs. SUVmaxliver and SUVpeakliver were affected by reconstruction protocol up to 62%. SUVmax and SUVpeak moved 22% and 11% upward between full and 25% count images. CONCLUSION: SUVmeanliver was most robust against VOI size, location, reconstruction protocol and image noise level, and is thus the most reproducible metric for liver uptake. The commonly recommended 3 cm diameter spherical VOI-based SUVmeanliver values were only slightly more variable than those seen with larger VOI sizes and are sufficient for SUVmeanliver measurements in future studies. TRIAL REGISTRATION: EudraCT: 2006-005,174-42, 01-08-2008.

Subregional origins of emerging SARS-CoV-2 variants during the second pandemic wave in Côte d'Ivoire.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with increased transmissibility, virulence and immune escape abilities have heavily altered the COVID-19 pandemic's course. Deciphering local and global transmission patterns of those variants is thus key in building a profound understanding of the virus' spread around the globe. In the present study, we investigate SARS-CoV-2 variant epidemiology in Côte d'Ivoire, Western sub-Saharan Africa. We therefore generated 234 full SARS-CoV-2 genomes stemming from Central and Northern Côte d'Ivoire. Covering the first and second pandemic wave the country had been facing, we identified 20 viral lineages and showed that in Côte d'Ivoire the second pandemic wave in 2021 was driven by the spread of the Alpha (B.1.1.7) and Eta (B.1.525) variant. Our analyses are consistent with a limited number of international introductions of Alpha and Eta into Côte d'Ivoire, and those introduction events mostly stemmed from within the West African subregion. This suggests that subregional travel to Côte d'Ivoire had more impact on local pandemic waves than direct intercontinental travel.

Near Lossless Compression for 3D Radiological Images Using Optimal Multilinear Singular Value Decomposition (3D-VOI-OMLSVD).

Storage and transmission of high-compression 3D radiological images that create high-quality reconstruction upon decompression are critical necessities for effective and efficient teleradiology. To cater to this need, we propose a near lossless 3D image volume compression method based on optimal multilinear singular value decomposition called "3D-VOI-OMLSVD." The proposed strategy first eliminates any blank 2D image slices from the 3D image volume and uses the selective bounding volume (SBV) to identify and extract the volume of Interest (VOI). Following this, the VOI is decomposed with an optimal multilinear singular value decomposition (OMLSVD) to obtain the corresponding core tensor, factor matrices, and singular values that are compressed with adaptive binary range coder (ABRC), integrated as an entropy encoder. The compressed file can be transferred or transmitted and then decompressed in order to reconstruct the original image. The resultant decompressed VOI is acquired by reversing the above process and then fusing it with the background, using the bound volume coordinates associated with the compressed 3D image. The proposed method performance was tested on a variety of 3D radiological images with different imaging modalities and dimensions using quantitative evaluation metrics such as the compression rate (CR), bit rate (BR), peak signal to noise ratio (PSNR), and structural similarity index (SSIM). Furthermore, we also investigate the impact of VOI extraction on the model performance, before comparing it with two popular compression methods, namely JPEG and JPEG2000. Our proposed method, 3D-VOI-OMLSVD, displayed a high CR value, with a maximum of 37.31, and a low BR, with the lowest reported to be 0.21. The SSIM score was consistently high, with an average performance of 0.9868, while using < 1 second for decoding the image. We observe that with VOI extraction, the compression rate increases manifold, and bit rate drops significantly, and thus reduces the encoding and decoding time to a great extent. Compared to JPEG and JPEG2000, our method consistently performs better in terms of higher CR and lower BR. The results indicate that the proposed compression methodology performs consistently to create high-quality image compressions, and overall gives a better outcome when compared against two state-of-the-art and widely used methods, JPEG and JPEG2000.

Omicron variant evolution on vaccines and monoclonal antibodies.

The severe acute respiratory syndrome coronavirus (SARS-CoV)-2 responsible for the global COVID-19 pandemic has caused almost 760 million confirmed cases and 7 million deaths worldwide, as of end-February 2023. Since the beginning of the first COVID-19 case, several virus variants have emerged: Alpha (B1.1.7), Beta (B135.1), Gamma (P.1), Delta (B.1.617.2) and then Omicron (B.1.1.529) and its sublineages. All variants have diversified in transmissibility, virulence, and pathogenicity. All the newly emerging SARS-CoV-2 variants appear to contain some similar mutations associated with greater "evasiveness" of the virus to immune defences. From early 2022 onward, several Omicron subvariants named BA.1, BA.2, BA.3, BA.4, and BA.5, with comparable mutation forms, have followed. After the wave of contagions caused by Omicron BA.5, a new Indian variant named Centaurus BA.2.75 and its new subvariant BA.2.75.2, a second-generation evolution of the Omicron variant BA.2, have recently been identified. From early evidence, it appears that this new variant has higher affinity for the cell entry receptor ACE-2, making it potentially able to spread very fast. According to the latest studies, the BA.2.75.2 variant may be able to evade more antibodies in the bloodstream generated by vaccination or previous infection, and it may be more resistant to antiviral and monoclonal antibody drug treatments. In this manuscript, the authors highlight and describe the latest evidences and critical issues have emerged on the new SARS-CoV-2 variants.

Virtual Screening of Repurposed Drugs as Potential Spike Protein Inhibitors of Different SARS-CoV-2 Variants: Molecular Docking Study.

Like most of the RNA viruses, SARS-CoV-2 continuously mutates. Although many mutations have an insignificant impact on the virus properties, mutations in the surface protein, especially those in the receptor-binding domain, may lead to immune or vaccine escape variants, or altered binding activities to both the cell receptor and the drugs targeting such a protein. The current study intended to assess the ability of different variants of interest (VOIs) and variants of concern (VOCs) of SARS-CoV-2 for their affinities of binding to different repurposed drugs. Seven FDA approved drugs, namely, camostat, nafamostat mesylate, fenofibrate, umifenovir, nelfinavir, cefoperazone and ceftazidime, were selected based on their reported in vitro and clinical activities against SARA-CoV-2. The S1 protein subunit from eleven different variants, including the latest highly contiguous omicron variant, were used as targets for the docking study. The docking results revealed that all tested drugs possess moderate to high binding energies to the receptor-binding domain (RBD) of the S1 protein for all different variants. Cefoperazone was found to possess the highest binding energy to the RBD of the S1 protein of all the eleven variants. Ceftazidime was the second-best drug in terms of binding affinity towards the S1 RBD of the investigated variants. On the other hand, fenofibrate showed the least binding affinity towards the RBD of the S1 protein of all eleven variants. The binding affinities of anti-spike drugs varied among different variants. Most of the interacting amino acid residues of the receptor fall within the RBD (438-506).

Modeling Anthropogenic and Environmental Influences on Freshwater Harmful Algal Bloom Development Detected by MERIS Over the Central United States.

Human and ecological health have been threatened by the increase of cyanobacteria harmful algal blooms (cyanoHABs) in freshwater systems. Successful mitigation of this risk requires understanding the factors driving cyanoHABs at a broad scale. To inform management priorities and decisions, we employed random forest modeling to identify major cyanoHAB drivers in 369 freshwater lakes distributed across 15 upper Midwest states during the 2011 bloom season (July-October). We used Cyanobacteria Index (CI_cyano)-A remotely sensed product derived from the MEdium Resolution Imaging Spectrometer (MERIS) aboard the European Space Agency's Envisat satellite-as the response variable to obtain variable importance metrics for 75 landscape and lake physiographic predictor variables. Lakes were stratified into high and low elevation categories to further focus CI_cyano variable importance identification by anthropogenic and natural influences. "High elevation" watershed land cover (LC) was primarily forest or natural vegetation, compared with "low elevation" watersheds LC dominated by anthropogenic landscapes (e.g., agriculture and municipalities). We used the top ranked 25 Random Forest variables to create a classification and regression tree (CART) for both low and high elevation lake designations to identify variable thresholds for possible management mitigation. Mean CI_cyano was 3 times larger for "low elevation" lakes than for "high elevation" lakes, with both mean values exceeding the "High" World Health Organization recreational guidance/action level threshold for cyanobacteria (100,000 cells/mL). Agrarian-related variables were prominent across all 369 lakes and low elevation lakes. High elevation lakes showed more influence of lakeside LC than for the low elevation lakes.

Design of a high-coverage ground-based CO2 monitoring layout using a novel information theory-based optimization model.

Over the past decade, monitoring of the carbon cycle has become a major concern accented by the severe impacts of global warming. Here, we develop an information theory-based optimization model using the NSGA-II algorithm that determines an optimum ground-based CO2 monitoring layout with the highest spatial coverage using a finite number of stations. The value of information (VOI) concept is used to assess the efficacy of the monitoring stations given their construction cost. In conjunction with VOI, the entropy theory-in terms of transinformation-is adopted to determine the redundant (overlapping) information rendered by the selected monitoring stations. The developed model is used to determine a ground-based CO2 monitoring layout for Iran, the eighth-ranked country emitting CO2 worldwide. An NSGA-II optimization model provides a tradeoff curve given the objectives of (1) minimizing the size of monitoring network; (2) maximizing VOI, i.e., spatial coverage; and (3) minimizing transinformation, i.e., overlapping information. Borda count method is then employed to select the most appropriate compromise monitoring layout from the Pareto-front solutions given regional priorities and concerns.

Essential information: Uncertainty and optimal control of Ebola outbreaks.

Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.

Optimization of a secondary VOI protocol for lung imaging in a clinical CT scanner.

We present a solution to meet an unmet clinical need of an in-situ "close look" at a pulmonary nodule or at the margins of a pulmonary cyst revealed by a primary (screening) chest CT while the patient is still in the scanner. We first evaluated options available on current whole-body CT scanners for high resolution screening scans, including ROI reconstruction of the primary scan data and HRCT, but found them to have insufficient SNR in lung tissue or discontinuous slice coverage. Within the capabilities of current clinical CT systems, we opted for the solution of a secondary, volume-of-interest (VOI) protocol where the radiation dose is focused into a short-beam axial scan at the z position of interest, combined with a small-FOV reconstruction at the xy position of interest. The objective of this work was to design a VOI protocol that is optimized for targeted lung imaging in a clinical whole-body CT system. Using a chest phantom containing a lung-mimicking foam insert with a simulated cyst, we identified the appropriate scan mode and optimized both the scan and recon parameters. The VOI protocol yielded 3.2 times the texture amplitude-to-noise ratio in the lung-mimicking foam when compared to the standard chest CT, and 8.4 times the texture difference between the lung mimicking and reference foams. It improved details of the wall of the simulated cyst and better resolution in a line-pair insert. The Effective Dose of the secondary VOI protocol was 42% on average and up to 100% in the worst-case scenario of VOI positioning relative to the standard chest CT. The optimized protocol will be used to obtain detailed CT textures of pulmonary lesions, which are biomarkers for the type and stage of lung diseases.

Value of Information Based Data Retrieval in UWSNs.

Sensor nodes in underwater sensor networks may acquire data at a higher rate than their ability to communicate over underwater acoustic channels. Autonomous underwater vehicles may mitigate this mismatch by offloading high volumes of data from the sensor nodes and ferrying them to the sink. Such a mode of data transfer results in high latency. Occasionally, these networks need to report high priority events such as catastrophes or intrusions. In such a scenario the expectation is to have a minimal end-to-end delay for event reporting. Considering this, underwater vehicles should schedule their visits to the sensor nodes in a manner that aids efficient reporting of high-priority events. We propose the use of the Value of Information metric in order to improve the reporting of events in an underwater sensor network. The proposed approach classifies the recorded data in terms of its value and priority. The classified data is transmitted using a combination of acoustic and optical channels. We perform experiments with a binary event model, i.e., we classify the events into high-priority and low-priority events. We explore a couple of different path planning strategies for the autonomous underwater vehicle. Our results show that scheduling visits to sensor nodes, based on algorithms that address the value of information, improves the timely reporting of high priority data and enables the accumulation of larger value of information.

In vivo assessment of tumor heterogeneity in WHO 2016 glioma grades using diffusion kurtosis imaging: Diagnostic performance and improvement of feasibility in routine clinical practice.

PURPOSE: To assess the diagnostic performance of normalized and non-normalized diffusion kurtosis imaging (DKI) metrics extracted from different tumor volume data for grading glioma according to the integrated approach of the revised 2016 WHO classification. MATERIALS AND METHODS: Sixty patients with histopathologically confirmed glioma, who provided written informed consent, were retrospectively assessed between 01/2013 and 08/2016 from a prospective trial approved by the local institutional review board. Mean kurtosis (MK) and mean diffusivity (MD) metrics from DKI were assessed by two blinded physicians from four different volumes of interest (VOI): whole solid tumor including (VOItu-ed) and excluding perifocal edema (VOItu), infiltrative zone (VOIed), and single slice of solid tumor core (VOIslice). Intra-class correlation coefficient (ICC) was calculated to assess inter-rater agreement. One-way ANOVA was used to compare MK between 2016 CNS WHO tumor grades. Friedman's test compared MK and MD of each VOI. Spearman's correlation coefficient was used to correlate MK with 2016 CNS WHO tumor grades. ROC analysis was performed on MK for significant results. RESULTS: The MK assessment showed excellent inter-rater agreement for each VOI (ICC, 0.906-0.955). MK was significantly lower in IDHmutant astrocytoma (0.40±0.07), than in 1p/19q-confirmed oligodendroglioma (0.54±0.10, P=0.001) or IDHwild-type glioblastoma (0.68±0.13, P<0.001). MK and 2016 WHO tumor grades were strongly and positively correlated (VOItu-ed, r=0.684; VOItu, r=0.734; VOIed, r=0.625; VOIslice, r=0.698; P<0.001). CONCLUSIONS: Non-normalized MK values obtained from VOItu and VOIslice showed the best reproducibility and highest diagnostic performance for stratifying glioma according to the integrated approach of the recent 2016 WHO classification.

Impact of partial volume effect correction on cerebral ß-amyloid imaging in APP-Swe mice using [(18)F]-florbetaben PET.

We previously investigated the progression of ß-amyloid deposition in brain of mice over-expressing amyloid-precursor protein (APP-Swe), a model of Alzheimer's disease (AD), in a longitudinal PET study with the novel ß-amyloid tracer [(18)F]-florbetaben. There were certain discrepancies between PET and autoradiographic findings, which seemed to arise from partial volume effects (PVE). Since this phenomenon can lead to bias, most especially in the quantitation of brain microPET studies of mice, we aimed in the present study to investigate the magnitude of PVE on [(18)F]-florbetaben quantitation in murine brain, and to establish and validate a useful correction method (PVEC). Phantom studies with solutions of known radioactivity concentration were performed to measure the full-width-at-half-maximum (FWHM) resolution of the Siemens Inveon DPET and to validate a volume-of-interest (VOI)-based PVEC algorithm. Several VOI-brain-masks were applied to perform in vivo PVEC on [(18)F]-florbetaben data from C57BL/6(N=6) mice, while uncorrected and PVE-corrected data were cross-validated with gamma counting and autoradiography. Next, PVEC was performed on longitudinal PET data set consisting of 43 PET scans in APP-Swe (13-20months) and age-matched wild-type (WT) mice using the previously defined masks. VOI-based cortex-to-cerebellum ratios (SUVR) were compared for uncorrected and PVE-corrected results. Brains from a subset of transgenic mice were ultimately examined by autoradiography ex vivo and histochemistry in vitro as gold standard assessments, and compared to VOI-based PET results. The phantom study indicated a FWHM of 1.72mm. Applying a VOI-brain-mask including extracerebral regions gave robust PVEC, with increased precision of the SUVR results. Cortical SUVR increased with age in APP-Swe mice compared to baseline measurements (16months: +5.5%, p<0.005; 20months: +15.5%, p<0.05) with uncorrected data, and to a substantially greater extent with PVEC (16months: +12.2% p<0.005; 20months: +36.4% p<0.05). WT animals showed no binding changes, irrespective of PVEC. Relative to autoradiographic results, the error [%] for uncorrected cortical SUVR was 18.9% for native PET data, and declined to 4.8% upon PVEC, in high correlation with histochemistry results. We calculate that PVEC increases by 10% statistical power for detecting altered [(18)F]-florbetaben uptake in aging APP-Swe mice in planned studies of disease modifying treatments on amyloidogenesis.

Multimodal imaging of subventricular zone neural stem/progenitor cells in the cuprizone mouse model reveals increased neurogenic potential for the olfactory bulb pathway, but no contribution to remyelination of the corpus callosum.

Multiple sclerosis is a devastating demyelinating disease of the central nervous system (CNS) in which endogenous remyelination, and thus recovery, often fails. Although the cuprizone mouse model allowed elucidation of many molecular factors governing remyelination, currently very little is known about the spatial origin of the oligodendrocyte progenitor cells that initiate remyelination in this model. Therefore, we here investigated in this model whether subventricular zone (SVZ) neural stem/progenitor cells (NSPCs) contribute to remyelination of the splenium following cuprizone-induced demyelination. Experimentally, from the day of in situ NSPC labeling, C57BL/6J mice were fed a 0.2% cuprizone diet during a 4-week period and then left to recover on a normal diet for 8weeks. Two in situ labeling strategies were employed: (i) NSPCs were labeled by intraventricular injection of micron-sized iron oxide particles and then followed up longitudinally by means of magnetic resonance imaging (MRI), and (ii) SVZ NSPCs were transduced with a lentiviral vector encoding the eGFP and Luciferase reporter proteins for longitudinal monitoring by means of in vivo bioluminescence imaging (BLI). In contrast to preceding suggestions, no migration of SVZ NSPC towards the demyelinated splenium was observed using both MRI and BLI, and further validated by histological analysis, thereby demonstrating that SVZ NSPCs are unable to contribute directly to remyelination of the splenium in the cuprizone model. Interestingly, using longitudinal BLI analysis and confirmed by histological analysis, an increased migration of SVZ NSPC-derived neuroblasts towards the olfactory bulb was observed following cuprizone treatment, indicative for a potential link between CNS inflammation and increased neurogenesis.

When can scientific studies promote consensus among conflicting stakeholders?

While scientific studies may help conflicting stakeholders come to agreement on a best management option or policy, often they do not. We review the factors affecting trust in the efficacy and objectivity of scientific studies in an analytical-deliberative process where conflict is present, and show how they may be incorporated in an extension to the traditional Bayesian decision model. The extended framework considers stakeholders who differ in their prior beliefs regarding the probability of possible outcomes (in particular, whether a proposed technology is hazardous), differ in their valuations of these outcomes, and differ in their assessment of the ability of a proposed study to resolve the uncertainty in the outcomes and their hazards--as measured by their perceived false positive and false negative rates for the study. The Bayesian model predicts stakeholder-specific preposterior probabilities of consensus, as well as pathways for increasing these probabilities, providing important insights into the value of scientific information in an analytic-deliberative decision process where agreement is sought. It also helps to identify the interactions among perceived risk and benefit allocations, scientific beliefs, and trust in proposed scientific studies when determining whether a consensus can be achieved. The article provides examples to illustrate the method, including an adaptation of a recent decision analysis for managing the health risks of electromagnetic fields from high voltage transmission lines.

PET quantification performance of the oversize-volume-of-interest approach in the context of tumour dosimetry in radionuclide therapy planning.

Objective.The partial-volume effect (PVE) is an important factor impairing tumour quantification in molecular imaging. The commonly used contour-volume-of-interest (contour-VOI) approach to correct for this effect employs phantom-based recovery coefficients. Applying oversize-VOIs could offer superior quantification accuracy in small lesions. The oversize-VOI approach uses a large oversize volume to determine the total tumour activity after applying a background correction. Aims of this study were to provide a procedure for the application of the oversize-VOI approach and to compare its performance to the contour-VOI approach in PET imaging.Approach.A sphere tumour model was simulated to determine the oversize diameter that contained 90%, 95%, and 98% of the total activity as a function of the tumour size. Experimental investigations involving phantom and clinical data were conducted on a digital PET/CT scanner. In the phantom investigation, 12 spherical tumour inserts (diameters ranging from 3.7 to 37.4 mm) containing18F-solution were used. The accuracy of the contour- and oversize-VOI approach was evaluated for different signal-to-background ratios (20-3). Clinically, both approaches were applied on PET/CT images acquired with18F-labelled prostate-specific membrane antigen in prostate cancer patients.Main results.From the tumour model, we deduced that an oversize-VOI of two PET spatial resolutions larger than the physical lesion diameter contains at least 98% of the total activity for lesions with diameters down to one PET spatial resolution, while minimizing the background contribution. Both approaches were robust against varying phantom and clinical imaging conditions. Performance of the oversize-VOI approach was favorable for lesions below 10 mm in diameter, whereas the contour-VOI approach was slightly more accurate for sizes above 10 mm.Significance.The oversize-VOI approach facilitates image quantification of small tumours. It is simple and effective to correct for the PVE and may be used in pre-therapeutic (small) tumour dosimetry.

Corrigendum: Genomic characterization of SARS-CoV-2 from an indigenous reserve in Mato Grosso do Sul, Brazil.

[This corrects the article DOI: 10.3389/fpubh.2023.1195779.].

A Methodology to Measure Glucose Metabolism by Quantitative Analysis of PET Images.

Positron emission tomography (PET) with F-18 fluorodeoxyglucose (FDG) tracer is the standard clinical technique to measure myocardial and vessel metabolism and viability and to investigate the metabolic syndrome associated with cardiovascular diseases. The quantitative analysis of PET images allows one to study the cardiovascular physiological processes, by extracting quantitative parameters from the analysis of the tracer kinetic. Here, we propose a new methodology to quantify and evaluate the evolution of glucose metabolism inside the myocardium and the large vascular structures over time. We merge and analyze PET and CT cardiac images, extracting different volumes of interest (VOI) and performing quantitative measurements. To validate it, we apply the methodology to merge images of the aorta vessel for patients affected by metabolic syndrome. The application of the proposed approach to the use case reveals a correlation between administered drugs and metabolic syndrome, measuring the glucose metabolic rate (MRGlu) in both the myocardium and aorta. The proposed methodology can be used to evaluate some cardiovascular risk indexes of diabetic patients, too. The proposed methodology can also be deployed to analyze other application domains.

JN.1 variant in enduring COVID-19 pandemic: is it a variety of interest (VoI) or variety of concern (VoC)?

The emergence of the SARS-CoV-2 Omicron variant, classified as a Variant of Concern (VoC) in November 2021, marked a significant shift in the COVID-19 landscape. This study investigates the subsequent development of a novel Omicron sublineage, JN.1, which displays distinctive mutations in the spike protein. The study delves into the phylogenetic differences between these variants and their potential implications. A comprehensive analysis of the genomic profiles and mutation patterns of JN.1 and BA.2.86 was conducted, utilizing SARS-CoV-2 database. The study explores the unique mutations, such as S:L455S in JN.1, associated with increased transmissibility and immune escape. Furthermore, a comparison with prevalent strains like XBB.1.5 and HV.1 highlights the substantial genetic divergence of JN.1. JN.1, first detected in August 2023, exhibits a notable spike protein mutation profile, including the reappearance of earlier variants' mutations (E484K and P681R). The variant's increased transmissibility and immune evasion potential are attributed to specific spike protein mutations like R21T, S50L, V127F, R158G, and others. The study also explores the distribution and prevalence of JN.1 globally, with a focus on the rising cases in India. JN.1 poses a unique challenge as one of the most immune-evading variants, with potential implications for COVID-19 transmission. The study emphasizes the importance of monitoring and understanding emerging variants, especially those with distinct spike protein mutations. The observed cases in India highlight the need for vigilance and prompt public health responses. As JN.1 continues to evolve, ongoing surveillance, vaccination strategies, and adherence to preventive measures are crucial to mitigating its potential impact on global public health.

Differential impact of hyponatremia and hepatic encephalopathy on health-related quality of life and brain metabolite abnormalities in cirrhosis.

BACKGROUND & AIMS: Hyponatremia (HN) and hepatic encephalopathy (HE) together can impair health-related quality of life (HRQOL) and cognition in cirrhosis. We aimed at studying the effect of hyponatremia on cognition, HRQOL, and brain MR spectroscopy (MRS) independent of HE. METHODS: Four cirrhotic groups (no HE/HN, HE alone, HN alone (sodium <130 mEq/L), HE+HN) underwent cognitive testing, HRQOL using Sickness Impact Profile (SIP: higher score is worse; has psychosocial and physical sub-scores) and brain MRS (myoinositol (mI) and glutamate+glutamine (Glx)), which were compared across groups. A subset underwent HRQOL testing before/after diuretic withdrawal. RESULTS: 82 cirrhotics (30 no HE/HN, 25 HE, 17 HE+HN, and 10 HN, MELD 12, 63% hepatitis C) were included. Cirrhotics with HN alone and without HE/HN had better cognition compared to HE groups (median abnormal tests no-HE/HN: 3, HN: 3.5, HE: 6.5, HE+HN: 7, p=0.008). Despite better cognition, HN only patients had worse HRQOL in total and psychosocial SIP while both HN groups (with/without HE) had a significantly worse physical SIP (p<0.0001, all comparisons). Brain MRS showed the lowest Glx in HN and the highest in HE groups (p<0.02). mI levels were comparably decreased in the three affected (HE, HE+HN, and HN) groups compared to no HE/HN and were associated with poor HRQOL. Six HE+HN cirrhotics underwent diuretic withdrawal which improved serum sodium and total/psychosocial SIP scores. CONCLUSIONS: Hyponatremic cirrhotics without HE have poor HRQOL despite better cognition than those with concomitant HE. Glx levels were lowest in HN without HE but mI was similar across affected groups. HRQOL improved after diuretic withdrawal. Hyponatremia has a complex, non-linear relationship with brain Glx and mI, cognition and HRQOL.