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Ultrasound-Guided Regional Anesthesia (UGRA) becomes a standard procedure in surgical operations and contributes to pain management. It offers the advantages of the targeted nerve detection and provides the visualization of regions of interest such as anatomical structures. However, nerve detection is one of the most challenging tasks that anesthetists can encounter in the UGRA procedure. A computer-aided system that can detect automatically the nerve region would facilitate the anesthetist's daily routine and allow them to concentrate more on the anesthetic delivery. In this paper, we propose a new method based on merging deep learning models from different data to detect the median nerve. The merged architecture consists of two branches, one being one-dimensional (1D) convolutional neural networks (CNN) branch and another 2D CNN branch. The merged architecture aims to learn the high-level features from 1D handcrafted noise-robust features and 2D ultrasound images. The obtained results show the validity and high accuracy of the proposed approach and its robustness.

Objectives To define key genetic elements, single or in clusters, underlying SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) evolutionary diversification across continents, and their impact on drug-binding affinity and viral antigenicity. Methods A total of 12 150 SARS-CoV-2 sequences (publicly available) from 69 countries were analysed. Mutational clusters were assessed by hierarchical clustering. Structure-based virtual screening (SBVS) was used to select the best inhibitors of 3-chymotrypsin-like protease (3CL-Pr) and RNA-dependent RNA polymerase (RdRp) among the FDA-approved drugs and to evaluate the impact of mutations on binding affinity of these drugs. The impact of mutations on epitope recognition was predicted following Grifoni et al. (Cell Host Microbe 2020; 27 671–80.) Results Thirty-five key mutations were identified (prevalence: ≥0.5%), residing in different viral proteins. Sixteen out of 35 formed tight clusters involving multiple SARS-CoV-2 proteins, highlighting intergenic co-evolution. Some clusters (including D614GSpike + P323LRdRp + R203KN + G204RN) occurred in all continents, while others showed a geographically restricted circulation (T1198KPL-Pr + P13LN + A97VRdRp in Asia, L84SORF-8 + S197LN in Europe, Y541CHel + H504CHel + L84SORF-8 in America and Oceania). SBVS identified 20 best RdRp inhibitors and 21 best 3CL-Pr inhibitors belonging to different drug classes. Notably, mutations in RdRp or 3CL-Pr modulate, positively or negatively, the binding affinity of these drugs. Among them, P323LRdRp (prevalence: 61.9%) reduced the binding affinity of specific compounds including remdesivir while it increased the binding affinity of the purine analogues penciclovir and tenofovir, suggesting potential hypersusceptibility. Finally, specific mutations (including Y541CHel + H504CHel) strongly hampered recognition of Class I/II epitopes, while D614GSpike profoundly altered the structural stability of a recently identified B cell epitope target of neutralizing antibodies (amino acids 592–620). Conclusions Key genetic elements reflect geographically dependent SARS-CoV-2 genetic adaptation, and may play a potential role in modulating drug susceptibility and hampering viral antigenicity. Thus, a close monitoring of SARS-CoV-2 mutational patterns is crucial to ensure the effectiveness of treatments and vaccines worldwide.

The anti-HBc-positive/HBsAg-negative status is frequent in HIV-infection and correlates with poor survival. Here, by highly-sensitive assays, we evaluate cryptic HBV replication and factors correlated with its detection in 81 anti-HBc-positive/HBsAg-negative HIV-infected patients. Patients were treated for &gt, 12 months with HBV-active modern combined antiretroviral-therapy (cART) and had serum HBV-DNA &lt, 20 IU/mL by commercial Real-Time PCR. Serum HBV-DNA was quantified by droplet digital PCR, serum HBV-RNA by an Abbott research assay, and anti-HBc titer (proposed to infer intrahepatic cccDNA) by Lumipulse/Fujirebio. Cryptic serum HBV-DNA was detected in 29.6% of patients (median (IQR): 4(1&ndash, 15) IU/mL) and serum HBV-RNA in 3.7% of patients despite HBsAg-negativity and HBV-active cART. Notably, cryptic serum HBV-DNA correlated with an advanced CDC-stage (p = 0.01) and a lower anti-HBs titer (p = 0.05), while serum HBV-RNA correlated with lower nadir CD4+ cell-count (p = 0.01). By analyzing serological HBV-markers, the combination of anti-HBs &lt, 50 mIU/mL (indicating lower immune response) plus anti-HBc &gt, 15COI (reflecting higher HBV replicative activity) was predictive of cryptic serum HBV-DNA (OR: 4.7(1.1&ndash, 21.7), p = 0.046, PPV = 62.5%, and NPV = 72%). In conclusion, cryptic HBV-replication (not detected by classical assays) characterizes a conspicuous set of anti-HBc-positive HIV-infected patients despite HBsAg-negativity and HBV-active combined antiretroviral therapy (cART). The integration of classical and novel markers may help identify patients with cryptic HBV-replication, thus optimizing the monitoring of anti-HBc-positive/HBsAg-negative HIV-infected patients.

Atorvastatin is commonly used among type 2 diabetic (DM2) patients at the University of Jordan Hospital to prevent cardiovascular complication. However, we noticed that there is a wide inter-individual variation in the efficacy and toxicity of atorvastatin. This study aimed to find out the effects of major genetic variants in 3-Hydroxy-3-Methylglutaryl-CoA Reductase (HMGCR), Apolipoprotein E (APOE), and Solute Carrier Organic Anion (SLCO1B1) genes on atorvastatin response among DM2 patients. A sample of 139 DM2 patients on 20 mg of atorvastatin was included in this study. The lipid and glycemic profile and the levels of hepatic enzymes alanine aminotransferase (ALT) and aspartate transaminase were recorded before and after 3 months of atorvastatin treatment. Additionally, the genetic variants HMGCR rs17244841,APOE rs7412 and rs429357, and SLCO1B1 rs2306283 and rs11045818 were genotyped using an Applied Biosystems DNA sequencing method (ABI3730&times, 1). We found that atorvastatin reduced total cholesterol and low-density lipoprotein (LDL) more significantly (p-value &lt, 0.05) in patients with wild genotype than variant alleles APOE rs7412C &gt, T and SLCO1B1 rs2306283A &gt, G. Furthermore, the ALT level was elevated significantly (p-value &lt, 0.05) by 27% in patients with heterozygous SLCO1B1 rs11045818 G/A genotype, while it was not elevated among wild genotype carriers. Additionally, atorvastatin reduced total cholesterol more significantly (p-value &lt, 0.05) in patients with SLCO1B1 rs2306283A and rs11045818G haplotypes and increased ALT levels by 27% (p-value &lt, 0.05) in patients with SLCO1B1 rs2306283G and rs11045818A haplotypes. In conclusion, it was found in this study that APOE rs7412, SLCO1B1 rs2306283, and rs11045818 genotypes can be considered as potential genetic biomarkers of atorvastatin response among DM2 patients of Jordanian Arabic origin. Further clinical studies with larger sample numbers are needed to confirm these findings.

Coronaviridae is a peculiar viral family, with a very large RNA genome and characteristic appearance, endowed with remarkable tendency to transfer from animals to humans. Since the beginning of the 21st century, three highly transmissible and pathogenic coronaviruses have crossed the species barrier and caused deadly pneumonia, inflicting severe outbreaks and causing human health emergencies of inconceivable magnitude. Indeed, in the past two decades, two human coronaviruses emerged causing serious respiratory illness: severe acute respiratory syndrome coronavirus (SARS-CoV-1) and Middle Eastern respiratory syndrome coronavirus (MERS-CoV), causing more than 10,000 cumulative cases, with mortality rates of 10 % for SARS-CoV-1 and 34.4 % for MERS-CoV. More recently, the severe acute respiratory syndrome coronavirus virus 2 (SARS-CoV-2) has emerged in China and has been identified as the etiological agent of the recent COVID-19 pandemic outbreak. It has rapidly spread throughout the world, causing nearly 22 million cases and ∼ 770,000 deaths worldwide, with an estimated mortality rate of ∼3.6 %, hence posing serious challenges for adequate and effective prevention and treatment. Currently, with the exception of the nucleotide analogue prodrug remdesivir, and despite several efforts, there is no known specific, proven, pharmacological treatment capable of efficiently and rapidly inducing viral containment and clearance of SARS-CoV-2 infection as well as no broad-spectrum drug for other human pathogenic coronaviruses. Another confounding factor is the paucity of molecular information regarding the tendency of coronaviruses to acquire drug resistance, a gap that should be filled in order to optimize the efficacy of antiviral drugs. In this light, the present review provides a systematic update on the current knowledge of the marked global efforts towards the development of antiviral strategies aimed at coping with the infection sustained by SARS-CoV-2 and other human pathogenic coronaviruses, displaying drug resistance profiles. The attention has been focused on antiviral drugs mainly targeting viral protease, RNA polymerase and spike glycoprotein, that have been tested in vitro and/or in clinical trials as well as on promising compounds proven to be active against coronaviruses by an in silico drug repurposing approach. In this respect, novel insights on compounds, identified by structure-based virtual screening on the DrugBank database endowed by multi-targeting profile, are also reported. We specifically identified 14 promising compounds characterized by a good in silico binding affinity towards, at least, two of the four studied targets (viral and host proteins). Among which, ceftolozane and NADH showed the best multi-targeting profile, thus potentially reducing the emergence of resistant virus strains. We also focused on potentially novel pharmacological targets for the development of compounds with anti-pan coronavirus activity. Through the analysis of a large set of viral genomic sequences, the current review provides a comprehensive and specific map of conserved regions across human coronavirus proteins which are essential for virus replication and thus with no or very limited tendency to mutate. Hence, these represent key druggable targets for novel compounds against this virus family. In this respect, the identification of highly effective and innovative pharmacological strategies is of paramount importance for the treatment and/or prophylaxis of the current pandemic but potentially also for future and unavoidable outbreaks of human pathogenic coronaviruses.

Background and Objective In the last decade, Ultrasound-Guided Regional Anesthesia (UGRA) gained importance in surgical procedures and pain management, due to its ability to perform target delivery of local anesthetics under direct sonographic visualization. However, practicing UGRA can be challenging, since it requires high skilled and experienced operator. Among the difficult task that the operator can face, is the tracking of the nerve structure in ultrasound images. Tracking task in US images is very challenging due to the noise and other artifacts. Methods In this paper, we introduce a new and robust tracking technique by using Adaptive Median Binary Pattern(AMBP) as texture feature for tracking algorithms (particle filter, mean-shift and Kanade-Lucas-Tomasi(KLT)). Moreover, we propose to incorporate Kalman filter as prediction and correction steps for the tracking algorithms, in order to enhance the accuracy, computational cost and handle target disappearance. Results The proposed method have been applied on real data and evaluated in different situations. The obtained results show that tracking with AMBP features outperforms other descriptors and achieved best performance with 95% accuracy. Conclusions This paper presents the first fully automatic nerve tracking method in Ultrasound images. AMBP features outperforms other descriptors in all situations such as noisy and filtered images.

Background: Obstructive sleep apnea (OSA) is a known risk factor for atrial fibrillation (AF) that is principally driven by left atrial enlargement. The impact of hypoventilation caused by obesity-induced hypoventilation syndrome (OHS) on left atrial diameter has not been examined. We investigated the association between OHS and left atrial diameter in obese patients. Methods: We performed a retrospective review of 210 consecutive medical records of patients diagnosed as obese (body mass index [BMI] >30 kg/m2) and as having OHS and OSA for the period January 2010 through December 2016 at St. Vincent Charity Medical Center in Cleveland, OH. Logistic regression analysis was performed for left atrial diameter ≥4 cm in 2 groups of patients: those with OHS+OSA and those with OSA alone. Results: A total of 104 obese patients with OHS+OSA and 106 obese patients with OSA alone were identified. Statistically significant differences were found in 6 demographic and baseline characteristics: median BMI, median left atrial diameter, history of type 2 diabetes mellitus, history of stroke, history of coronary artery disease, and history of congestive heart failure. The median left atrial diameter for the OHS+OSA and OSA alone groups was 4.45 cm and 4.20 cm, respectively (P = 0.014). Left ventricular ejection fraction Conclusion: The results of this study indicate that OHS may be an independent risk factor for left atrial enlargement and may possibly contribute to AF development irrespective of left ventricular function.

Ultrasound-guided regional anesthesia (UGRA) becomes a standard procedure in surgical operations and pain management, offers the advantages of nerve localization, and provides region of interest anatomical structure visualization. Nerve tracking presents a crucial step for practicing UGRA and it is useful and important to develop a tool to facilitate this step. However, nerve tracking is a very challenging task that anesthetists can encounter due to the noise, artifacts, and nerve structure variability. Deep-learning has shown outstanding performances in computer vision task including tracking. Many deep-learning trackers have been proposed, where their performance depends on the application. While no deep-learning study exists for tracking the nerves in ultrasound images, this paper explores thirteen most recent deep-learning trackers for nerve tracking and presents a comparative study for the best deep-learning trackers on different types of nerves in ultrasound images. We evaluate the performance of the trackers in terms of accuracy, consistency, time complexity, and handling different nerve situations, such as disappearance and losing shape information. Through the experimentation, certain conclusions were noted on deep learning trackers performance. Overall, deep-learning trackers provide good performance and show a comparative performance for tracking different kinds of nerves in ultrasound images.

Hepatitis B virus (HBV) persistence is at the basis of HBV reactivation as a consequence of chemotherapy and immunosuppressive treatments. The identification of early viral replication indicators and markers of effective HBV immunological control would be useful in monitoring patients who are at risk of potential viral reactivation during the course of immunosuppressive treatment. Currently, international guidelines have shared some criteria to identify patients with a low, medium or high risk of HBV reactivation; however, permanently placing a patient in a definitive category is not always easy. More often, patients move from one category to another during the course of their immunosuppressive treatment; therefore, in many cases, there are no precise indicators or tools for monitoring possible reactivation and establishing the duration and suspension of antiviral prophylaxis. Historically, the sequence of HBV antigens and antibodies and HBV DNA levels has been used to evaluate the different stages of the acute and chronic phases of an HBV infection. In the last few years, new biomarkers, such as anti-HBs and anti-HBc titres, HBV core-related antigen (HBcrAg), ultra-sensitive HBsAg evaluation and HBV RNA, have been used in patients with an HBV infection to evaluate their diagnostic and prognostic potential. The aim of this review is to evaluate the published results on the use of new infection markers in the diagnosis and monitoring of HBV reactivation over the course of immunosuppressive treatments. Moreover, the importance of viral genotypic studies was emphasized, given the diagnostic and therapeutic implications of the mutational profiles of HBsAg during the HBV reactivation phase.

We aimed to investigate HBx genetic elements correlated with hepatitis B virus (HBV) -related hepatocellular carcinoma (HCC) and their impact on (a) HBV replicative efficiency, (b) HBx binding to circular covalently closed DNA (cccDNA), (c) apoptosis and cell-cycle progression, and (d) HBx structural stability.This study included 123 individuals chronically infected with HBV: 27 with HCC (77.9% (21/27) genotype D; 22.1% (6/27) genotype A) and 96 without HCC (75% (72/96) genotype D; 25.0% (24/96) genotype A). HepG2 cells were transfected by wild-type or mutated linear HBV genome to assess pre-genomic RNA (pgRNA) and core-associated HBV-DNA levels, HBx-binding onto cccDNA by chromatin immunoprecipitation-based quantitative assay, and rate of apoptosis and cell-cycle progression by cytofluorimetry.F30V was the only HBx mutation correlated with HCC (18.5% (5/27) in HCC patients versus 1.0% (1/96) in non-HCC patients, p 0.002); a result confirmed by multivariate analysis. In vitro, F30V determined a 40% and 60% reduction in pgRNA and core-associated HBV-DNA compared with wild-type (p0.05), in parallel with a significant decrease of HBx binding to cccDNA and decreased HBx stability. F30V also decreased the percentage of apoptotic cells compared with wild-type (14.8 ± 6.8% versus 19.1 ± 10.1%, p0.01, without affecting cell-cycle progression) and increased the probability of HBx-Ser-31 being phosphorylated by PI3K-Akt kinase (known to promote anti-apoptotic activity).F30V was closely correlated with HBV-induced HCC in vivo, reduced HBV replicative efficiency by affecting HBx-binding to cccDNA and increased anti-apoptotic HBx activity in vitro. This suggests that F30V (although hampering HBV's replicative capacity) may promote hepatocyte survival, so potentially allowing persistent production of viral progeny and initiating HBV-driven hepatocarcinogenesis. Investigation of viral genetic markers associated with HCC is crucial to identify those patients at higher risk of HCC, who hence deserve intensive liver monitoring and/or early anti-HBV therapy.