bluuebunny/crossref_metadata_2025_split huggingface dataset:
In-utero HIV exposure and cardiometabolic health among children 5–8 years: findings from a prospective birth cohort in South Africa
Authors: Bengtson Angela M. , Pellowski Jennifer , McGarvey Stephen , McGinty Rae , Botha Maresa , Burd Tiffany , Burgner David , Mansell Toby , Zar Heather J. 
Published: December 2022

Objective:
To evaluate if in-utero HIV exposure is associated with adverse cardiometabolic health outcomes at 5–8 years of age.

Design:
Prospective cohort study.

Methods:
We enrolled a random sample of HIV-exposed but uninfected (HEU) and HIV-unexposed children from the Drakenstein Child Health study, a longitudinal birth cohort study in Cape Town, South Africa, in a cardiometabolic health pilot study. Outcomes were assessed by trained study staff and included: anthropometry, body composition and size, blood pressure, fasting plasma glucose, HbA1c, lipids, and insulin resistance using HOMA-IR. We used multivariable linear and log-binomial regression to estimate associations between HIV-exposure and cardiometabolic outcomes, adjusted for child age, sex, height, body size, and maternal factors as appropriate.

Results:
We included 260 children (HEU n = 100, HIV-unexposed n = 160). HEU children had older mothers (median age 30 vs. 26 years), with minimal differences in gestational age and size at birth by HIV-exposure status. In multivariable analyses, HEU children had lower weight-for-age (mean difference −0.35, 95% confidence interval −0.66, −0.05), and height-for-age (mean difference −0.29, 95% confidence interval −0.56, −0.03; z-scores). There were no differences in adiposity, impaired glucose metabolism, or lipid levels by HIV-exposure status. Overall, 12% of children had blood pressure more than 90th percentile, with no differences by HIV-exposure status.

Conclusion:
Overall, there were few differences in cardiometabolic outcomes between HEU and HIV-unexposed children in this South African cohort. Although these findings are reassuring, monitoring of cardiometabolic health is important as HEU and HIV-unexposed children enter adolescence and cardiometabolic risk trajectories become established.
COVID-19 vaccine immunogenicity in people with HIV
Authors: Costiniuk Cecilia T. , Singer Joel , Lee Terry , Langlois Marc-André , Arnold Corey , Galipeau Yannick , Needham Judy , Kulic Iva , Jenabian Mohammad-Ali , Burchell Ann N. , Shamji Hasina , Chambers Catharine , Walmsley Sharon , Ostrowski Mario , Kovacs Colin , Tan Darrell H.S. , Harris Marianne , Hull Mark , Brumme Zabrina L. , Lapointe Hope R. , Brockman Mark A. , Margolese Shari , Mandarino Enrico , Samarani Suzanne , Vulesevic Branka , Lebouché Bertrand , Angel Jonathan B. , Routy Jean-Pierre , Cooper Curtis L. , Anis Aslam H. 
Published: December 2022

Objectives:
Many vaccines require higher/additional doses or adjuvants to provide adequate protection for people with HIV (PWH). Our objective was to compare COVID-19 vaccine immunogenicity in PWH to HIV-negative individuals.

Design:
In a Canadian multi-center prospective, observational cohort of PWH receiving at least two COVID-19 vaccinations, we measured vaccine-induced immunity at 3 and 6 months post 2nd and 1-month post 3rd doses.

Methods:
The primary outcome was the percentage of PWH mounting vaccine-induced immunity [co-positivity for anti-IgG against SARS-CoV2 Spike(S) and receptor-binding domain proteins] 6 months post 2nd dose. Univariable and multivariable logistic regressions were used to compare COVID-19-specific immune responses between groups and within subgroups.

Results:
Data from 294 PWH and 267 controls were analyzed. Immunogenicity was achieved in over 90% at each time point in both groups. The proportions of participants achieving comparable anti-receptor-binding domain levels were similar between the group at each time point. Anti-S IgG levels were similar by group at month 3 post 2nd dose and 1-month post 3rd dose. A lower proportion of PWH vs. controls maintained vaccine-induced anti-S IgG immunity 6 months post 2nd dose [92% vs. 99%; odds ratio: 0.14 (95% confidence interval: 0.03, 0.80; P = 0.027)]. In multivariable analyses, neither age, immune non-response, multimorbidity, sex, vaccine type, or timing between doses were associated with reduced IgG response.

Conclusion:
Vaccine-induced IgG was elicited in the vast majority of PWH and was overall similar between groups. A slightly lower proportion of PWH vs. controls maintained vaccine-induced anti-S IgG immunity 6 months post 2nd dose demonstrating the importance of timely boosting in this population.
Update on treatments for anxiety-related disorders
Authors: Lee Hyun Jeong , Stein Murray B. 
Published: December 2022

Purpose of review
This review examines recent evidence that informs the treatment of anxiety-related disorders.

Recent findings
In addition to selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), and benzodiazepines, agomelatine has demonstrated efficacy in treating generalized anxiety disorder (GAD). Other novel products, such as ketamine, psilocybin and cannabidiol, are in the process of gathering evidence in support of the treatment of anxiety disorders. In psychological therapy, various psychological treatments for anxiety disorders, such as mindfulness-based intervention, acceptance and commitment therapy, psychodynamic therapy, emotion-focused therapy and dialectical behavioural therapy, have been tried. Still, most therapies have not proven superior to cognitive behavioural therapy (CBT). In very preliminary findings: Repetitive transcranial magnetic stimulation (rTMS) was effective in GAD; transcranial direct current stimulation (tDCS) was effective for social anxiety disorder (SAD) and GAD and augmented exposure therapy for specific fears. Internet and mobile-based interventions have comparable efficacy to face-to-face therapy.

Summary
Pharmacotherapy of anxiety disorders is expanding to novel products. Despite trying other psychological therapies for anxiety disorders, most therapies were comparable to but not superior to CBT. rTMS and tDCS were also used and show early promise for GAD, but further studies are needed. Most internet or mobile app based psychological therapies were based on CBT, and some can be considered as alternatives to in-person face-to-face therapy.
Multi-omics analysis identifies drivers of protein phosphorylation
Authors: Zhang Tian , Keele Gregory R. , Gyuricza Isabela Gerdes , Vincent Matthew , Brunton Catherine , Bell Timothy A. , Hock Pablo , Shaw Ginger D. , Munger Steven C. , de Villena Fernando Pardo-Manuel , Ferris Martin T. , Paulo Joao A. , Gygi Steven P. , Churchill Gary A. 
Published: December 2022

AbstractPhosphorylation of proteins is a key step in the regulation of many cellular processes including activation of enzymes and signaling cascades. The abundance of a phosphorylated peptide (phosphopeptide) is determined by the abundance of its parent protein and the proportion of target sites that are phosphorylated. We quantified phosphopeptides, proteins, and transcripts in heart, liver, and kidney tissue samples of mice from 58 strains of the Collaborative Cross strain panel. We mapped ∼700 phosphorylation quantitative trait loci (phQTL) across the three tissues and applied genetic mediation analysis to identify causal drivers of phosphorylation. We identified kinases, phosphatases, cytokines, and other factors, including both known and potentially novel interactions between target proteins and genes that regulate site-specific phosphorylation. Our analysis highlights multiple targets of pyruvate dehydrogenase kinase 1 (PDK1), a regulator of mitochondrial function that shows reduced activity in the NZO/HILtJ mouse, a polygenic model of obesity and type 2 diabetes.
Modeling electron interference at the neuronal membrane yields a holographic projection of representative information content
Authors: Stoll Elizabeth A 
Published: December 2022

AbstractIt has historically proven difficult to explain the relationship between neural activity and representative information content. A new approach focuses on the unique properties of cortical neurons, which allow both upstream signals and random electrical noise to affect the likelihood of reaching action potential threshold. Here, each electron is modeled as an electromagnetic point source, inter-acting in a probabilistic manner with each neuronal membrane. The electron is described as some set of probability amplitudes, distributed across five orthogonal axes:x, y, z, energy state, andtime. The membrane potential of each neuron is defined by the probabilistic spatial position and atomic orbital of each local electron, after some time evolution. The mixed sum of all probabilistic component pure states is the physical quantity of information held by the neural network, given by a complex-valued wavefunction. If the probabilistic trajectory of each electron over timetaffects the voltage state of multiple computational units, then the system state must be computed as a whole, with the state of each neuron being resolved as every component pure state is resolved. This computational process yields a defined system state at a defined location in time, which immediately becomes the past as a new probability density forms. If the membrane surface of each computational unit is also a charge-detecting polymer substrate that meets the criteria of a holographic recording surface, then this encoding process will generate a holographic projection of representative information content. The constructive and destructive interference of high-dimensional probability amplitudes yields a non-deterministic computational outcome for each neuron. That now-defined system state is paired with a multi-sensory percept, which is exclusively accessed by the encoding structure, with content limited by the range and sensitivity of the sensory apparatus. This model usefully offers a plausible explanation for both perceptual content and non-deterministic computational outcomes emerging from cortical neural network activity.
Assessment of Storm Impact on Coral Reef Structural Complexity
Authors: Yuval Matan , Pearl Naama , Tchernov Dan , Martinez Stephane , Loya Yossi , Bar-Massada Avi , Treibitz Tali 
Published: December 2022

AbstractExtreme weather events are increasing in frequency and magnitude. Consequently, it is important to understand their effects and remediation. Resilience reflects the ability of an ecosystem to absorb change, which is important for understanding ecological dynamics and trajectories. To describe the impact of a powerful storm on coral reef structural complexity, we used novel computational tools and detailed 3D reconstructions captured at three time points over three years. Our data-setReefs4Dof 21 co-registered image-based models enabled us to calculate the differences at seven sites over time and is released with the paper. We employed six geometrical metrics, two of which are new algorithms for calculating fractal dimension of reefs in full 3D. We conducted a multivariate analysis to reveal which sites were affected the most and their relative recovery. We also explored the changes in fractal dimension per size category using our cube-counting algorithm. Three metrics showed a signicant difference between time points, i.e., decline and subsequent recovery in structural complexity. The multivariate analysis and the results per size category showed a similar trend. Coral reef resilience has been the subject of seminal studies in ecology. We add important information to the discussion by focusing on 3D structure through image-based modeling. The full picture shows resilience in structural complexity, suggesting that the reef has not gone through a catastrophic phase shift. Our novel analysis framework is widely transferable and useful for research, monitoring, and management.Graphical AbstractHighlightsThe effect of storms on coral reef 3D structure is poorly understood.We studied the impact of a storm on coral reefs using a novel 3D imaging framework.We used geometrical metrics including new methods for calculating fractal dimension.The reefs recovered in two years with regards to structural complexity.Based on 3D analysis the reefs exhibit structural resilience.
Moderate High Temperature is Beneficial or Detrimental Depending on Carbon Availability in the Green AlgaChlamydomonas reinhardtii
Authors: Zhang Ningning , Venn Benedikt , Bailey Catherine E. , Xia Ming , Mattoon Erin M. , Mühlhaus Timo , Zhang Ru 
Published: December 2022

AbstractHigh temperatures impair plant and algal growth and reduce food and biofuel production, but the underlying mechanisms remain elusive. The unicellular green algaChlamydomonas reinhardtiiis a superior model to study heat responses in photosynthetic cells due to its fast growth rate, many similarities in cellular processes to land plants, simple and sequenced genome, and ample genetic and genomics resources. Chlamydomonas grows in light by photosynthesis and/or with the externally supplied organic carbon source, acetate. Most of the published research about Chlamydomonas heat responses used acetate-containing medium. Understanding how organic carbon sources affect heat responses is important for the algal industry but understudied. We cultivated Chlamydomonas wild-type cultures under highly controlled conditions in photobioreactors at control of 25°C, moderate high temperature of 35°C, or acute high temperature of 40°C with and without constant acetate supply for 1- or 4-days. Our results showed that 35°C increased algal growth with constant acetate supply but reduced algal growth without sufficient acetate. The overlooked and dynamic effects of 35°C could be explained by induced carbon metabolism, including acetate uptake and assimilation, glyoxylate cycle, gluconeogenesis pathways, and glycolysis. Acute high temperature at 40°C for more than 2 days was lethal to algal cultures with and without constant acetate supply. Our research provides insights to understand algal heat responses and help improve thermotolerance in photosynthetic cells.HighlightWe revealed the overlooked, dynamic effects of moderate high temperature in algae depending on carbon availability and demonstrated the importance of carbon metabolism in thermotolerance of photosynthetic cells.
Guidelines for extracting biologically relevant context-specific metabolic models using gene expression data
Authors: Gopalakrishnan Saratram , Joshi Chintan J. , Valderrama Gomez Miguel , Icten Elcin , Rolandi Pablo , Johnson William , Kontoravdi Cleo , Lewis Nathan E. 
Published: December 2022

ABSTRACTGenome-scale metabolic models comprehensively describe an organism’s metabolism and can be tailored using omics data to model condition-specific physiology. The quality of context-specific models is impacted by (i) choice of algorithm and parameters and (ii) alternate context-specific models that equally explain the -omics data. Here we quantify the influence of alternate optima on microbial and mammalian model extraction using GIMME, iMAT, MBA, and mCADRE. We find that metabolic tasks defining an organism’s phenotype must be explicitly and quantitatively protected. The scope of alternate models is strongly influenced by algorithm choice and the topological properties of the parent genome-scale model with fatty acid metabolism and intracellular metabolite transport contributing much to alternate solutions in all models. mCADRE extracted the most reproducible context-specific models and models generated using MBA had the most alternate solutions. There were fewer qualitatively different solutions generated by GIMME inE. coli, but these increased substantially in the mammalian models. Screening ensembles using a receiver operating characteristic plot identified the best-performing models. A comprehensive evaluation of models extracted using combinations of extraction methods and expression thresholds revealed that GIMME generated the best-performing models inE. coli, whereas mCADRE is better suited for complex mammalian models. These findings suggest guidelines for benchmarking -omics integration algorithms and motivate the development of a systematic workflow to enumerate alternate models and extract biologically relevant context-specific models.
Megan Server: facilitating interactive access to metagenomic data on a server
Authors: Gautam Anupam , Zeng Wenhuan , Huson Daniel H. 
Published: December 2022

MotivationMetagenomic projects of large sequencing datasets (totaling hundreds of gigabytes of data). Thus, computational preprocessing and analysis are usually performed on a server rather than on a personal computer. The results of such analyses are then usually explored interactively. One approach is to use MEGAN, an interactive program that allows analysis and comparison of metagenomic datasets. Previous releases of MEGAN have required that the user first download the computed data from the server, an increasingly time-consuming process. Here we present Megan Server, a stand-alone program that serves MEGAN files to the web, using a RESTful API, facilitating interactive analysis without downloading the complete data. We describe a number of different application scenarios.AvailabilityMegan Server is provided as a standalone program tools/megan-server in the Megan6 software suite, available athttps://software-ab.cs.uni-tuebingen.de/download/megan6.
Spatial frequency-based correction of the spherical aberration in living brain imaging
Authors: Gohma Aoi , Adachi Naoya , Horiba Daiki , Yonemaru Yasuo , Nishiwaki Daisuke , Yokoi Eiji , Higuchi Kaori , Ue Yoshihiro , Miyawaki Atsushi , Monai Hiromu 
Published: December 2022

AbstractWe previously developed a fully automated spherical aberration compensation microscope system, Deep-C, to obtain spherical aberration-free images, but the contrast-based algorithm (Peak-C) may limit applications for low signal-to-noise ratio images. Herein we propose a new spatial frequency-based algorithm called Peak-F and compared its performance to Peak-C. Unlike Peak-C, Peak-F is robust to any noise level since it is independent of the dynamic range of the images, and it does not suffer from image saturation. Finally, Peak-F was implemented in a two-photon microscope to observe living aged and young mouse brains. Consequently, the average refractive index of brain tissue was higher in old mice than in young mice. The Peak-F algorithm determines high-resolution microscopic images stably and robustly.
Shear Stress Initiates Endothelial to Mesenchymal Transition in Endocardial Endothelial Cells
Authors: Brown Kathleen N. , Phan Hong Kim T. , Mustafa Tasneem , Jui Elysa , Ahmad Fariha N. , Birla Ravi P. , Sucosky Philippe , Connell Jennifer P. , Keswani Sundeep G. , Grande-Allen K. Jane 
Published: December 2022

AbstractDiscrete subaortic stenosis (DSS) is a congenital heart disease characterized by the formation of a fibrotic membrane below the aortic valve. The underlying cellular mechanisms of this disease are currently unknown. As one of the distinguishing features of DSS is the elevated pressure gradient in the left ventricular outflow tract, it is hypothesized that membrane formation is caused by elevated wall shear stress applied to the endocardial endothelial cells (EECs), triggering fibrosis. To correlate shear stress to an EEC fibrotic phenotype, we applied fluid shear stress to EECs at physiological and pathological shear rates using a cone-and-plate device, designed to recapitulate physiological wall shear stress in a controlled in vitro environment. Controlled shear stress regimes were applied to EECs to replicate the conditions observed in DSS patients. We found that elevated shear stress triggered EEC alignment as well as endothelial-to-mesenchymal transformation (EndMT) signaling pathways driven by upregulation ofSNAI1gene expression. The EECs were then treated with a small molecule inhibitor of Snail1 protein, CYD19, to attempt to attenuate EndMT signaling, and subsequently subjected to pathological shear stress. The Snail1 inhibitor did downregulate selected markers of EndMT signaling, although only transiently. Interestingly, the application of shear stress had a greater effect on the EEC gene and protein expression than did the Snail1 inhibition. This investigation of EEC response to shear stress reveals the pronounced and complex effect of this mechanical stimulation on the EEC phenotype. Further study should reveal the mechanisms that drive fibrosis and the formation of the DSS membrane.
Predicting the Influence of Fat Food Intake on the Absorption and Systemic Exposure of Small Drugs using ANDROMEDA by Prosilico Software
Authors: Fagerholm Urban , Hellberg Sven , Alvarsson Jonathan , Spjuth Ola 
Published: December 2022

AbstractIntroductionThe ANDROMEDA software by Prosilico has previously been successfully applied and validated for predictions of absorption characteristics of small drugs in man. The influence of fat food on the gastrointestinal uptake and systemic exposure of drugs have, however, not yet been evaluated with the software.Objective and MethodologyThe main objective was to use ANDROMEDA to predict area under the plasma concentration-time curve ratios in the fed (fat food) and fasted states (AUCfed/AUCfast) for small drugs (including those marketed in 2021) and compare results with corresponding measured clinical estimates. Actual dose sizes were considered. Another objective was to compare the performance of ANDROMEDAvsphysiologically based pharmacokinetic (PBPK) modelling and simulations by The Food Effect PBPK IQ Working Group. PBPK results generated using Simcyp and GastroPlus software were based on various physicochemical,in vitroandin vivodata and a decision tree for model verification and optimization.Results and Discussion63 drugs, including 17 new drugs, with observed AUCfed/AUCfastbetween 0.2 and 5.5 were found and used for this evaluation. Predicted AUCfed/AUCfasthad mean and maximum errors of 1.5- and 4.1-fold, respectively, and the predictive accuracy (correlation between predicted and observed AUCfed/AUCfast; Q2) was 0.3. 14 % of predictions had >2-fold error. For 72 % of drugs, food interaction class was correctly predicted. The level of predictive accuracy was overall similar to results obtained with PBPK modelling and simulations, however, with lower maximum error and higher compound coverage. With PBPK models, maximum simulation error was 7.7-fold and 3 highly lipophilic compounds were not possible to simulate.ConclusionThe results validate ANDROMEDA for prediction of fat food-drug interaction size for small drugs in man. Major advantages with the methodology include that prediction results are produced directly from molecular structure and oral dose and are similar to PBPK-simulation results obtained usingin vitroand clinical data. Furthermore, ANDROMEDA showed lower maximum errors and wider compound range.