Hepatic artery diameter predicts bleeding risk after gastroesophageal varices treatment: a contrast-enhanced CT study.

OBJECTIVE: Portal hypertension leads to hepatic artery dilatation and a higher risk of bleeding. We tried to identify the bleeding risk after gastroesophageal varices (GOV) treatment using hepatic artery diameter of contrast-enhanced CT. METHODS: Retrospective retrieval of 258 patients with cirrhosis who underwent contrast-enhanced CT from January 2022 to May 2023 and endoscopy within one month thereafter at Hainan Affiliated Hospital of Hainan Medical University. Cirrhotic patients before GOV treatment were used as the test cohort (n = 199), and cirrhotic patients after GOV treatment were used as the validation cohort (n = 59). The grading and bleeding risk was classified according to the endoscopic findings. Arterial-phase images of contrast-enhanced CT were used for coronal reconstruction, and the midpoint diameter of the hepatic artery was measured on coronal images. The optimal cutoff value for identifying bleeding risk was analyzed and calculated in the test cohort, and its diagnostic performance was evaluated in the validation cohort. RESULTS: In the test cohort, hepatic artery diameters were significantly higher in high-risk GOV than in low-risk GOV [4.69 (4.31, 5.56) vs. 3.10 (2.59, 3.77), P < 0.001]. With a hepatic artery diameter cutoff value of 4.06 mm, the optimal area under the operating characteristic curve was 0.940 (95% confidence interval: 0.908-0.972), with a sensitivity of 0.887, a specificity of 0.892, a positive predictive value of 0.904, and a negative predictive value of 0.874 for identifying bleeding risk in the test cohort, while in the validation cohort, the sensitivity was 0.885, specificity was 0.939, positive predictive value was 0.920, and negative predictive value was 0.912. CONCLUSION: Hepatic artery diameter has high diagnostic performance in identifying bleeding risk after GOV treatment.

SARS-CoV-2 Antiviral Prescribing Gaps Among Non-Hospitalized High-Risk Adults.

Within a multi-state clinical cohort, SARS-CoV-2 antiviral prescribing patterns were evaluated from April 2022-June 2023 among non-hospitalized SARS-CoV-2-infected patients with risk factors for severe COVID-19. Among 3,247 adults, only 31.9% were prescribed an antiviral agent (87.6% nirmatrelvir/ritonavir, 11.9% molnupiravir, 0.5% remdesivir), highlighting the need to identify and address treatment barriers.

Drosophila Amus and Bin3 methylases functionally replace mammalian MePCE for capping and the stabilization of U6 and 7SK snRNAs.

U6 and 7SK snRNAs have a 5' cap, believed to be essential for their stability and maintained by mammalian MePCE or Drosophila Bin3 enzymes. Although both proteins are required for 7SK stability, loss of neither destabilizes U6, casting doubts on the function of capping U6. Here, we show that the Drosophila Amus protein, homologous to both proteins, is essential for U6 but not 7SK stability. The loss of U6 is rescued by the expression of an Amus-MePCE hybrid protein harboring the methyltransferase domain from MePCE, highlighting the conserved function of the two proteins as the U6 capping enzyme. Our investigations in human cells establish a dependence of both U6 and 7SK stability on MePCE, resolving a long-standing uncertainty. While uncovering a division of labor of Bin3/MePCE/Amus proteins, we found a "Bin3-Box" domain present only in enzymes associated with 7SK regulation. Targeted mutagenesis confirms its importance for Bin3 function, revealing a possible conserved element in 7SK but not U6 biology.

Post-translational modification and mitochondrial function in Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease with currently no cure. Most PD cases are sporadic, and about 5-10% of PD cases present a monogenic inheritance pattern. Mutations in more than 20 genes are associated with genetic forms of PD. Mitochondrial dysfunction is considered a prominent player in PD pathogenesis. Post-translational modifications (PTMs) allow rapid switching of protein functions and therefore impact various cellular functions including those related to mitochondria. Among the PD-associated genes, Parkin, PINK1, and LRRK2 encode enzymes that directly involved in catalyzing PTM modifications of target proteins, while others like α-synuclein, FBXO7, HTRA2, VPS35, CHCHD2, and DJ-1, undergo substantial PTM modification, subsequently altering mitochondrial functions. Here, we summarize recent findings on major PTMs associated with PD-related proteins, as enzymes or substrates, that are shown to regulate important mitochondrial functions and discuss their involvement in PD pathogenesis. We will further highlight the significance of PTM-regulated mitochondrial functions in understanding PD etiology. Furthermore, we emphasize the potential for developing important biomarkers for PD through extensive research into PTMs.

Evidence for SARS-CoV-2 Delta and Omicron co-infections and recombination.

BACKGROUND: Between November 2021 and February 2022, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta and Omicron variants co-circulated in the United States, allowing for co-infections and possible recombination events. METHODS: We sequenced 29,719 positive samples during this period and analyzed the presence and fraction of reads supporting mutations specific to either the Delta or Omicron variant. FINDINGS: We identified 18 co-infections, one of which displayed evidence of a low Delta-Omicron recombinant viral population. We also identified two independent cases of infection by a Delta-Omicron recombinant virus, where 100% of the viral RNA came from one clonal recombinant. In the three cases, the 5' end of the viral genome was from the Delta genome and the 3' end from Omicron, including the majority of the spike protein gene, though the breakpoints were different. CONCLUSIONS: Delta-Omicron recombinant viruses were rare, and there is currently no evidence that Delta-Omicron recombinant viruses are more transmissible between hosts compared with the circulating Omicron lineages. FUNDING: This research was supported by the NIH RADx initiative and by the Centers for Disease Control Contract 75D30121C12730 (Helix).

A machine-learning approach using pubic CT based on radiomics to estimate adult ages.

PURPOSE: Adult skeletal age estimation is an active research field. To evaluate the performance of a pubic CT radiomics-based machine learning model for estimating age, we established a multiple linear regression model based on radiomics and machine learning methods. METHODS: A total of 355 subjects were enrolled in this retrospective study from August 2016 to August 2021, and divided into a training cohort (N = 325) and a testing cohort (N = 30). Computerized texture analysis of the semi-automatically segmentation was performed and 107 texture features were extracted from the regions. Then we used univariate linear regression and multivariate stepwise regression to assess correlations of texture parameters with age. The most vital features were used to make the best predictive model. Eventually, the established radiomics model was tested with an additional 30 patients. RESULTS: Clinical characteristics include age, sex, height, weight and BMI were not statistically significant different between training and testing cohort (p = 0.098-0.888). Through a multivariate regression analysis using stepwise regression, six texture parameters were found to have significant correlations with age. The regression formula estimating the age was constructed. CONCLUSIONS: The radiomics model using machine learning is considered as a new approach forage estimation frompubic symphysis CT features.Digital osteology is obtained in a non-invasive way so that it can be an ideal collection for anthropological studies.

Factors Influencing the Progression of Patellofemoral Articular Cartilage Damage After Anterior Cruciate Ligament Reconstruction.

Background: Although anterior cruciate ligament reconstruction (ACLR) can restore the stability and function of the knee joint, patellofemoral joint cartilage damage still progresses. Currently, the clinically important factors that lead to the progression of patellofemoral articular cartilage damage are not fully understood. Purpose: To investigate the factors that affect the progression of patellofemoral articular cartilage damage after ACLR. Study Design: Cohort study; Level of evidence, 2. Methods: Among 160 patients who underwent ACLR between January 2015 and December 2019, the authors evaluated 129 patients for at least 1 year after surgery. Within 1 week before ACLR and at the last follow-up, patients underwent subjective functional assessment and magnetic resonance imaging evaluations of articular cartilage damage (modified Outerbridge assessment). At the last follow-up, the side-to-side difference on KT-2000 arthrometer and bilateral quadriceps muscle strength were measured. Univariate and multivariate logistic regression analyses were performed. Results: The mean follow-up was 24.69 ± 10.74 months. Progression of patellar cartilage damage from preoperatively to final follow-up was seen in 45 patients (P < .001). Logistic regression analysis revealed that the follow-up period (P = .047; odds radio (OR) = 0.953) (improvement of patellar cartilage damage with longer follow-up), partial lateral meniscal resection (P = .004; OR = 6.929), partial medial meniscal resection (P = .004; OR = 6.032), and quadriceps muscle strength <80% of the contralateral side (P = .001; OR = 4.745) were risk factors for the progression of patellar cartilage damage. Conclusion: Cartilage damage at the patellofemoral joint, especially the patellar cartilage, still progresses after ACLR. At a mean follow-up of 24.69 months after ACLR, partial meniscal resection and quadriceps femoris muscle strength were found to be the main risk factors for the progression of patellofemoral articular cartilage damage after ACLR.

SARS-CoV-2 variant Delta rapidly displaced variant Alpha in the United States and led to higher viral loads.

We report on the sequencing of 74,348 SARS-CoV-2 positive samples collected across the United States and show that the Delta variant, first detected in the United States in March 2021, made up the majority of SARS-CoV-2 infections by July 1, 2021 and accounted for >99.9% of the infections by September 2021. Not only did Delta displace variant Alpha, which was the dominant variant at the time, it also displaced the Gamma, Iota, and Mu variants. Through an analysis of quantification cycle (Cq) values, we demonstrate that Delta infections tend to have a 1.7× higher viral load compared to Alpha infections (a decrease of 0.8 Cq) on average. Our results are consistent with the hypothesis that the increased transmissibility of the Delta variant could be due to the ability of the Delta variant to establish a higher viral load earlier in the infection as compared to the Alpha variant.

Comprehensive Allele Genotyping in Critical Pharmacogenes Reduces Residual Clinical Risk in Diverse Populations.

Genomic-guided pharmaceutical prescribing is increasingly recognized as an important clinical application of genetics. Accurate genotyping of pharmacogenomic (PGx) genes can be difficult, owing to their complex genetic architecture involving combinations of single-nucleotide polymorphisms and structural variation. Here, we introduce the Helix PGx database, an open-source star allele, genotype, and resulting metabolic phenotype frequency database for CYP2C9, CYP2C19, CYP2D6, and CYP4F2, based on short-read sequencing of >86,000 unrelated individuals enrolled in the Helix DNA Discovery Project. The database is annotated using a pipeline that is clinically validated against a broad range of alleles and designed to call CYP2D6 structural variants with high (98%) accuracy. We find that CYP2D6 has greater allelic diversity than the other genes, manifest in both a long tail of low-frequency star alleles, as well as a disproportionate fraction (36%) of all novel predicted loss-of-function variants identified. Across genes, we observe that many rare alleles (<0.1% frequency) in the overall cohort have 10 times higher frequency in one or more subgroups with non-European genetic ancestry. Extending these PGx genotypes to predicted metabolic phenotypes, we demonstrate that >90% of the cohort harbors a high-risk variant in one of the four pharmacogenes. Based on the recorded prescriptions for >30,000 individuals in the Healthy Nevada Project, combined with predicted PGx metabolic phenotypes, we anticipate that standard-of-care screening of these 4 pharmacogenes could impact nearly half of the general population.

Early Stage Markers of Late Delayed Neurocognitive Decline Using Diffusion Kurtosis Imaging of Temporal Lobe in Nasopharyngeal Carcinoma Patients.

Purpose: To determine whether the early assessment of temporal lobe microstructural changes using diffusion kurtosis imaging (DKI) can predict late delayed neurocognitive decline after radiotherapy in nasopharyngeal carcinoma (NPC) patients. Methods and Materials: Fifty-four NPC patients undergoing intensity-modulated radiotherapy (IMRT) participated in a prospective DKI magnetic resonance (MR) imaging study. MR imaging was acquired prior to IMRT (-0), 1 month (-1), and 3 (-3) months after IMRT. Kurtosis (Kmean, Kax, Krad) and Diffusivity (Dmean, Dax, Drad) variables in the temporal lobe gray and white matter were computed. Neurocognitive function tests (MoCA) were administered pre-radiotherapy and at 2 years post-IMRT follow-up. All the patients were divided into neurocognitive function decline (NFD group) and neurocognitive function non-decline groups (NFND group) according to whether the MoCA score declined ≥3 2 years after IMRT. All the DKI metrics were compared between the two groups, and the best imaging marker was chosen for predicting a late delayed neurocognitive decline. Results: Kurtosis (Kmean-1, Kmean-3, Kax-1, Kax-3, Krad-1, and Krad-3) and Diffusivity (Dmean-1 and Dmean-3) of white matter were significantly different between the two groups (p<0.05). Axial Kurtosis (Kax-1, Kax-3) of gray matter was significantly different between the two groups (p<0.05). By receiver operating characteristic (ROC) curves, Kmean-1 of white matter performed best in predicting of MoCA scores delayed decline (p<0.05). The radiation dose was also significantly different between NFD and NFND group (p=0.031). Conclusions: Temporal lobe white matter is more vulnerable to microstructural changes and injury following IMRT in NPC. Metrics derived from DKI should be considered as imaging markers for predicting a late delayed neurocognitive decline. Both temporal lobe white and gray matter show microstructural changes detectable by DKI. The Kmean early after radiotherapy has the best prediction performance.

The developmental and experience-dependent expression of IGF-2 in mice visual cortex.

The circuitry associated with the visual cortex is particularly sensitive to experiences during the early stages of life, which are collectively known as critical periods. Critical period of ocular dominance plasticity is regulated by both environmental and genetic factors. Previous studies demonstrated that IGF-1 significantly influenced the regulation of visual cortex synaptic plasticity. IGF-2 can reportedly regulate synapse formation, dendritic spine maturation, and memory consolidation in rodents. Association between IGF-2 and the regulation of visual cortex synaptic plasticity remains unclear. Here, we first aimed to elucidate the normal expression patterns of IGF-2 and its laminar expression pattern during the process of visual cortex development in mice. This confirmed that IGF-2 may influence the regulation of ocular dominance plasticity in mice. We further elucidated the role of IGF-2 in the regulation of visual cortex synaptic plasticity by examining the effect of monocular deprivation (MD) on IGF-2 expression in the visual cortex. Interestingly, we observed that MD remarkably reduced IGF-2 expression in the visual cortex. Rodents reared in an enriched environment, with enhanced sensory, motor, and social experiences, were capable of effectively accelerating the development of the visual system and could restore normal visual acuity. Although the enriched environment facilitated the restoration of normal visual acuity in the MD mice, IGF-2 expression levels in the visual cortex remained unchanged. Therefore, we considered the possibility that IGF-2 may have a different role with regard to the modulation of plasticity in the visual cortex of the mice, which we aim to study in the future.

The impact of the interval between the induction of chemotherapy and radiotherapy on the survival of patients with nasopharyngeal carcinoma.

BACKGROUND: There have been no reliable scientific studies examining whether the interval between induction chemotherapy (IC) and initiating radiotherapy is associated with poor outcomes of nasopharyngeal carcinoma (NPC). PATIENTS AND METHODS: In this retrospective study, we included a total of 239 local advanced NPC patients who underwent concurrent chemoradiotherapy and IC. Based on the interval between IC and intensity-modulated radiation therapy (IMRT), the patients were classified into three groups as follows: Group A (≤7 vs >7 days), Group B (≤14 vs >14 days), and Group C (≤ 21 vs >21 days). Univariate and multivariate regression analyses were performed to determine the prognostic factors of survival outcomes. The differences between the two groups were compared by the log-rank test. RESULTS: The median IC-IMRT interval was 9 days (range, 1-76 days). The median follow-up time was 40 months (range, 4-58 months). The IC-IMRT interval including Group A, Group B, and Group C was not significantly associated with overall survival (OS), distant metastasis-free survival (DMFS), locoregional relapse-free survival (LRFS), or disease-free survival (DFS). Multivariate analysis showed that the tumor stage was the independent significant predictor for OS, DMFS, LRFS, and DFS. But it appears that there was a trend toward improvement in the outcome of ≤7 days group in OS from the Kaplan-Meier curves. CONCLUSION: It is also feasible to postpone radiotherapy for 1-3 weeks if patients were unable to receive treatment immediately due to chemotherapy complications such as bone marrow suppression. However, we suggest that patients should start IMRT as soon as possible after IC.

Worldwide genetic variation of the IGHV and TRBV immune receptor gene families in humans.

The immunoglobulin heavy variable (IGHV) and T cell beta variable (TRBV) loci are among the most complex and variable regions in the human genome. Generated through a process of gene duplication/deletion and diversification, these loci can vary extensively between individuals in copy number and contain genes that are highly similar, making their analysis technically challenging. Here, we present a comprehensive study of the functional gene segments in the IGHV and TRBV loci, quantifying their copy number and single-nucleotide variation in a globally diverse sample of 109 (IGHV) and 286 (TRBV) humans from over a 100 populations. We find that the IGHV and TRBV gene families exhibit starkly different patterns of variation. In addition to providing insight into the different evolutionary paths of the IGHV and TRBV loci, our results are also important to the adaptive immune repertoire sequencing community, where the lack of frequencies of common alleles and copy number variants is hampering existing analytical pipelines.

SCALING LIMITS OF A MODEL FOR SELECTION AT TWO SCALES.

The dynamics of a population undergoing selection is a central topic in evolutionary biology. This question is particularly intriguing in the case where selective forces act in opposing directions at two population scales. For example, a fast-replicating virus strain outcompetes slower-replicating strains at the within-host scale. However, if the fast-replicating strain causes host morbidity and is less frequently transmitted, it can be outcompeted by slower-replicating strains at the between-host scale. Here we consider a stochastic ball-and-urn process which models this type of phenomenon. We prove the weak convergence of this process under two natural scalings. The first scaling leads to a deterministic nonlinear integro-partial differential equation on the interval [0, 1] with dependence on a single parameter, λ. We show that the fixed points of this differential equation are Beta distributions and that their stability depends on λ and the behavior of the initial data around 1. The second scaling leads to a measure-valued Fleming-Viot process, an infinite dimensional stochastic process that is frequently associated with a population genetics.

Estimating Copy Number and Allelic Variation at the Immunoglobulin Heavy Chain Locus Using Short Reads.

The study of genomic regions that contain gene copies and structural variation is a major challenge in modern genomics. Unlike variation involving single nucleotide changes, data on the variation of copy number is difficult to collect and few tools exist for analyzing the variation between individuals. The immunoglobulin heavy variable (IGHV) locus, which plays an integral role in the adaptive immune response, is an example of a complex genomic region that varies in gene copy number. Lack of standard methods to genotype this region prevents it from being included in association studies and is holding back the growing field of antibody repertoire analysis. Here we develop a method that takes short reads from high-throughput sequencing and outputs a genetic profile of the IGHV locus with the read coverage depth and a putative nucleotide sequence for each operationally defined gene cluster. Our operationally defined gene clusters aim to address a major challenge in studying the IGHV locus: the high sequence similarity between gene segments in different genomic locations. Tests on simulated data demonstrate that our approach can accurately determine the presence or absence of a gene cluster from reads as short as 70 bp. More detailed resolution on the copy number of gene clusters can be obtained from read coverage depth using longer reads (e.g., ≥ 100 bp). Detail at the nucleotide resolution of single copy genes (genes present in one copy per haplotype) can be determined with 250 bp reads. For IGHV genes with more than one copy, accurate nucleotide-resolution reconstruction is currently beyond the means of our approach. When applied to a family of European ancestry, our pipeline outputs genotypes that are consistent with the family pedigree, confirms existing multigene variants and suggests new copy number variants. This study paves the way for analyzing population-level patterns of variation in IGHV gene clusters in larger diverse datasets and for quantitatively handling regions of copy number variation in other structurally varying and complex loci.

Competitive exclusion by autologous antibodies can prevent broad HIV-1 antibodies from arising.

The past decade has seen the discovery of numerous broad and potent monoclonal antibodies against HIV type 1 (HIV-1). Eliciting these antibodies via vaccination appears to be remarkably difficult, not least because they arise late in infection and are highly mutated relative to germline antibody sequences. Here, using a computational model, we show that broad antibodies could in fact emerge earlier and be less mutated, but that they may be prevented from doing so as a result of competitive exclusion by the autologous antibody response. We further find that this competitive exclusion is weaker in infections founded by multiple distinct strains, with broadly neutralizing antibodies emerging earlier than in infections founded by a single strain. Our computational model simulates coevolving multitype virus and antibody populations. Broadly neutralizing antibodies may therefore be easier for the adaptive immune system to generate than previously thought. If less mutated broad antibodies exist, it may be possible to elicit them with a vaccine containing a mixture of diverse virus strains.

The challenges of modelling antibody repertoire dynamics in HIV infection.

Antibody affinity maturation by somatic hypermutation of B-cell immunoglobulin variable region genes has been studied for decades in various model systems using well-defined antigens. While much is known about the molecular details of the process, our understanding of the selective forces that generate affinity maturation are less well developed, particularly in the case of a co-evolving pathogen such as HIV. Despite this gap in understanding, high-throughput antibody sequence data are increasingly being collected to investigate the evolutionary trajectories of antibody lineages in HIV-infected individuals. Here, we review what is known in controlled experimental systems about the mechanisms underlying antibody selection and compare this to the observed temporal patterns of antibody evolution in HIV infection. We describe how our current understanding of antibody selection mechanisms leaves questions about antibody dynamics in HIV infection unanswered. Without a mechanistic understanding of antibody selection in the context of a co-evolving viral population, modelling and analysis of antibody sequences in HIV-infected individuals will be limited in their interpretation and predictive ability.

A simple model of group selection that cannot be analyzed with inclusive fitness.

A widespread claim in evolutionary theory is that every group selection model can be recast in terms of inclusive fitness. Although there are interesting classes of group selection models for which this is possible, we show that it is not true in general. With a simple set of group selection models, we show two distinct limitations that prevent recasting in terms of inclusive fitness. The first is a limitation across models. We show that if inclusive fitness is to always give the correct prediction, the definition of relatedness needs to change, continuously, along with changes in the parameters of the model. This results in infinitely many different definitions of relatedness - one for every parameter value - which strips relatedness of its meaning. The second limitation is across time. We show that one can find the trajectory for the group selection model by solving a partial differential equation, and that it is mathematically impossible to do this using inclusive fitness.

A unifying framework reveals key properties of multilevel selection.

Natural selection can act at multiple biological levels, often in opposing directions. Viral evolution is an important example, with selection occurring both within infected hosts and between hosts via transmission. A fast-replicating virus may outcompete a slower strain within the same host, however, if rapid viral replication incapacitates the host, this fast-replicating virus may not be transmitted as frequently as its slower counterpart. Such examples of antagonistic multilevel selection arise across biological taxa and scales, from microbial public goods production to male mating strategies. A general formalism for describing and analyzing these diverse systems can identify their common underlying properties. Here I introduce such a unifying framework, which can be intuitively visualized as a stochastic ball-and-urn process. This ball-and-urn process illustrates the dynamics of antagonistic selective forces and allows the systematic derivation of properties with little or no dependence on model parameterization. These properties are consistent with previous studies, both theoretical and empirical, of multilevel selection. In particular I show that selection at the group level is favored when group-level events occur frequently relative to individual-level events, when there is little or no mutation, and when there are many groups relative to the number of individuals in each group. This approach demonstrates how multilevel selection can be understood as a general biological phenomenon, and identifies recurring characteristics that may be independent of specific biological contexts.