bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differences in epigenetic age by HIV status among patients with a non-AIDS defining cancer
Authors: Dickey Brittney L. , Putney Ryan M. , Suneja Gita , Kresovich Jacob K. , Spivak Adam M. , Patel Ami B. , Teng Mingxiang , Extermann Martine , Giuliano Anna R. , Gillis Nancy , Berglund Anders , Coghill Anna E. 
Published: July 2023

Objective:
People with HIV (PHIV) are living longer and experiencing non-AIDS defining cancers (NADC). Epigenetic aging biomarkers have been linked to cancer risk, and cancer is now a leading cause of death in PHIV, but these biomarkers have not been investigated in PHIV and cancer.

Design:
In order to compare epigenetic age by HIV status, HIV-uninfected participants were matched to PHIV by reported age, tumor site, tumor sequence number, and treatment status.

Methods:
DNA from blood was assayed using Illumina MethylationEPIC BeadChip and estimated immune cell composition and three epigenetic clocks: Horvath, GrimAge, and epiTOC2. Age acceleration by clock was computed as the residual from the expected value, calculated using linear regression, for each study participant. Comparisons across HIV status used the Wilcoxon rank sum test. Hazard ratios and 95% confidence intervals for the association between age acceleration and survival in PHIV were estimated with Cox regression.

Results:
Among 65 NADC participants with HIV and 64 without, biological age from epiTOC2 (p < 0.0001) and GrimAge (p = 0.017) was significantly higher in PHIV. Biological age acceleration was significantly higher in PHIV using epiTOC2 (p < 0.01) and GrimAge (p < 0.0001), with the difference in the GrimAge remaining statistically significant after adjustment for immune cell composition. Among PHIV, GrimAge acceleration was significantly associated with increased risk of death (HR: 1.11; 95% CI:1.04–1.18).

Conclusions:
We observed a higher epigenetic age in PHIV with a NADC diagnosis compared to their HIV-uninfected counterparts, as well as a significant association between this accelerated biological aging and survival for patients diagnosed with a NADC.
The incidence and dynamic risk factors of chronic kidney disease among people living with HIV – A population-based Cohort Study
Authors: Gao Haoyuan , Zhang Jiajia , Yang Xueying , Chen Shujie , Mathew Roy , Weissman Sharon , Olatosi Bankole , Li Xiaoming 
Published: July 2023

Objectives:
We investigate the incidence of chronic kidney disease (CKD) among people living with HIV (PLWH) and the dynamic risk factors associated with CKD incidence.

Design:
A population-based cohort study of PLWH in South Carolina.

Methods:
Adults (age ≥18yrs) PLWH diagnosed between 2006 and 2019 who were CKD-free at baseline were included. The associations of HIV-related risk factors and conventional risk factors with the incidence of CKD were investigated during the overall study period and by different follow-up periods (i.e., 5-, 10-, and 15-years) by multivariate logistic regression.

Results:
Among 9,514 PLWH, the incidence of CKD was 12.39 per 1000 person-years. The overall model indicated that conventional risk factors, such as hypertension, dyslipidemia, cardiovascular disease, and diabetes were significantly associated with higher risk of developing CKD. HIV-related characteristics, such as high percent of days with viral suppression, recent CD4 count, and percent of retention in care, were associated with a lower risk of CKD compared to their counterparts. In the subgroup analysis, the results were similar for the 5-year and 6–10 years follow-up groups. Among patients who did not develop CKD by the 10th year, the risk factors for developing CKD within 11–15 years were dyslipidemia, diabetes, low recent CD4 count, and short duration of retention in care while other predictors vanished.

Conclusions:
Diabetes, CD4 count, and retention in care were persistently associated with CKD despite of follow-up duration. Closely monitoring diabetes and improving CD4 count and retention in care are important to lower the risk of CKD in PLWH.
‘No cyst, no echinococcosis’: a scoping review update on the diagnosis of cystic echinococcosis after the issue of the WHO-IWGE Expert Consensus and current perspectives
Authors: Siles-Lucas Mar , Uchiumi Leonardo , Tamarozzi Francesca 
Published: July 2023

Purpose of review
In 2010, the WHO-Informal Working Group on Echinococcosis (IWGE) published an Expert Consensus on the diagnosis and treatment of echinococcal infections. We provide an update on the diagnosis of cystic echinococcosis through a scoping review of the literature published after the release of the WHO-IWGE document.

Recent findings
Ultrasound accurately and reliably depicts the pathognomonic signs of cystic echinococcosis (CE) stages compared with other imaging techniques. Among these, T2-wighted MRI is to be preferred to computed tomography, which has poor performance for the etiological diagnosis of CE. A negative serology cannot exclude the diagnosis of CE, while a positive serology, applied after the visualization of a CE-compatible lesion, may confirm a CE diagnosis. Serology alone must not be used to define ‘CE’ nor as ‘screening’ tool for infection. Other imaging and laboratory techniques did not show clinically applicable performances.

Summary
In the absence of a focal lesion compatible with a CE cyst, no diagnosis of CE should be attempted. There is urgent need to achieve univocal CE case definitions and consensus diagnostic algorithm, as well as standardization of diagnostic methods and issue of a Target Product Profile of CE diagnostics, as advocated by the WHO in the 2021–2030 roadmap for neglected tropical diseases (NTDs).
Evaluating Capabilities of Large Language Models: Performance of GPT4 on Surgical Knowledge Assessments
Authors: Beaulieu-Jones Brendin R , Shah Sahaj , Berrigan Margaret T , Marwaha Jayson S , Lai Shuo-Lun , Brat Gabriel A 
Published: July 2023

AbstractBackgroundArtificial intelligence (AI) has the potential to dramatically alter healthcare by enhancing how we diagnosis and treat disease. One promising AI model is ChatGPT, a large general-purpose language model trained by OpenAI. The chat interface has shown robust, human-level performance on several professional and academic benchmarks. We sought to probe its performance and stability over time on surgical case questions.MethodsWe evaluated the performance of ChatGPT-4 on two surgical knowledge assessments: the Surgical Council on Resident Education (SCORE) and a second commonly used knowledge assessment, referred to as Data-B. Questions were entered in two formats: open-ended and multiple choice. ChatGPT output were assessed for accuracy and insights by surgeon evaluators. We categorized reasons for model errors and the stability of performance on repeat encounters.ResultsA total of 167 SCORE and 112 Data-B questions were presented to the ChatGPT interface. ChatGPT correctly answered 71% and 68% of multiple-choice SCORE and Data-B questions, respectively. For both open-ended and multiple-choice questions, approximately two-thirds of ChatGPT responses contained non-obvious insights. Common reasons for inaccurate responses included: inaccurate information in a complex question (n=16, 36.4%); inaccurate information in fact-based question (n=11, 25.0%); and accurate information with circumstantial discrepancy (n=6, 13.6%). Upon repeat query, the answer selected by ChatGPT varied for 36.4% of inaccurate questions; the response accuracy changed for 6/16 questions.ConclusionConsistent with prior findings, we demonstrate robust near or above human-level performance of ChatGPT within the surgical domain. Unique to this study, we demonstrate a substantial inconsistency in ChatGPT responses with repeat query. This finding warrants future consideration and presents an opportunity to further train these models to provide safe and consistent responses. Without mental and/or conceptual models, it is unclear whether language models such as ChatGPT would be able to safely assist clinicians in providing care.
Marker and readout genes for priming in the Arabidopsis –Pseudomonas cannabinapv. alisalensis interaction
Authors: Sistenich Andrea J. , Fürtauer Lisa , Scheele Franziska , Conrath Uwe 
Published: July 2023

AbstractAfter a local infection, the entire plant foliage becomes primed for the superinduction of defense responses after rechallenge. The identity of genes expressed during priming (priming-marker genes) or with hyperexpression in primed plants after rechallenge (priming-readout genes) remained largely unknown. We show inArabidopsis thalianathat genesAT1G76960(with unknown function),AT3G51860(encoding vacuolar Ca2+/H+antiporter CAX3), andAT3G45860(cysteine-rich receptor-like protein kinase CRK4) are strongly expressed duringPseudomonas cannabinapv. alisalensis-induced priming but not, or much less, in uninfected or challenged plants, or in primed plants after rechallenge. Expression of these genes thus solely marks the primed state for enhanced defense. In contrast to these genes, expression ofAT2G14610(pathogenesis-related protein PR1),AT2G32680(receptor-like protein RLP23),AT3G25010(RLP41) and some less expressed loci are activated, about equally, in primed plants before and after rechallenge. They may also serve as marker genes for priming. In further contrast, genesAT2G39530(encoding Casparian strip domain-like protein 4D1),AT2G19190(flg22-induced receptor-like kinase FRK1),AT3G28510(P loop-containing nucleoside triphosphate hydrolases superfamily protein) and some less strongly expressed genes are not, or only faintly activated in uninfected plants, during priming and upon challenge. However, their expression is very strong in primed plants after rechallenge. They are, therefore, specific readout genes for the primed state. Remarkably, mutation in solely priming-readout geneAT5G36970(encoding NDR1/HIN1-like protein 25) impaired both infection-induced defense priming and systemic acquired resistance suggesting a previously unknown critical role of this gene in the systemic plant immune response.
A Template for Translational Bioinformatics: Facilitating Multimodal Data Analyses in Preclinical Models of Neurological Injury
Authors: Gaudio Hunter A. , Padmanabhan Viveknarayanan , Landis William P. , Silva Luiz E. V. , Slovis Julia , Starr Jonathan , Weeks M. Katie , Widmann Nicholas J. , Forti Rodrigo M. , Laurent Gerard H. , Ranieri Nicolina R. , Mi Frank , Degani Rinat E. , Hallowell Thomas , Delso Nile , Calkins Hannah , Dobrzynski Christiana , Haddad Sophie , Kao Shih-Han , Hwang Misun , Shi Lingyun , Baker Wesley B. , Tsui Fuchiang , Morgan Ryan W. , Kilbaugh Todd J. , Ko Tiffany S. 
Published: July 2023

AbstractBackgroundPediatric neurological injury and disease is a critical public health issue due to increasing rates of survival from primary injuries (e.g., cardiac arrest, traumatic brain injury) and a lack of monitoring technologies and therapeutics for the treatment of secondary neurological injury. Translational, preclinical research facilitates the development of solutions to address this growing issue but is hindered by a lack of available data frameworks and standards for the management, processing, and analysis of multimodal data sets.MethodsHere, we present a generalizable data framework that was implemented for large animal research at the Children’s Hospital of Philadelphia to address this technological gap. The presented framework culminates in an interactive dashboard for exploratory analysis and filtered data set download.ResultsCompared with existing clinical and preclinical data management solutions, the presented framework accommodates heterogeneous data types (single measure, repeated measures, time series, and imaging), integrates data sets across various experimental models, and facilitates dynamic visualization of integrated data sets. We present a use case of this framework for predictive model development for intra-arrest prediction of cardiopulmonary resuscitation outcome.ConclusionsThe described preclinical data framework may serve as a template to aid in data management efforts in other translational research labs that generate heterogeneous data sets and require a dynamic platform that can easily evolve alongside their research.
Solving the Pervasive Problem of Protocol Non-Compliance in MRI using an Open-Source toolmrQA
Authors: Sinha Harsh , Raamana Pradeep Reddy 
Published: July 2023

AbstractPooling data across diverse sources acquired by multisite consortia requires compliance with a predefined reference protocoli.e., ensuring different sites and scanners for a given project have used identical or compatible MR physics parameter values. Traditionally, this has been an arduous and manual process due to difficulties in working with the complicated DICOM standard and lack of resources allocated towards protocol compliance. Moreover, issues of protocol compliance is often overlooked for lack of realization that parameter values are routinely improvised/modified locally at various sites. The inconsistencies in acquisition protocols can reduce SNR, statistical power, and in the worst case, may invalidate the results altogether. An open-source tool, mrQA was developed to automatically assess protocol compliance on standard dataset formats such as DICOM and BIDS, and to study the patterns of non-compliance in over 20 open neuroimaging datasets, including the large ABCD study. The results demonstrate that the lack of compliance is rather pervasive. The frequent sources of non-compliance include but are not limited to deviations in Repetition Time, Echo Time, Flip Angle, and Phase Encoding Direction. It was also observed that GE and Philips scanners exhibited higher rates of non-compliance relative to the Siemens scanners in the ABCD dataset. Continuous monitoring for protocol compliance is strongly recommended before any pre/post-processing, ideally right after the acquisition, to avoid the silent propagation of severe/subtle issues. Although, this study focuses on neuroimaging datasets, the proposed tool mrQA can work with any DICOM-based datasets.
An individual’s skin stiffness predicts their tactile acuity
Authors: Li Bingxu , Gerling Gregory J. 
Published: July 2023

ABSTRACTIndividual differences in tactile acuity have been correlated with age, gender, and finger size, while the role of the skin’s stiffness has been underexplored. Using an approach to image the 3- D deformation of the skin surface while in contact with transparent elastic objects, we evaluate a cohort of 40 young participants, who present a diverse range of finger size, skin stiffness, and fingerprint ridge breadth. The results indicate that skin stiffness generally correlates with finger size, although individuals with relatively softer skin can better discriminate compliant objects. Analysis of contact at the skin surface reveals that softer skin generates more prominent patterns of deformation, in particular greater rates of change in contact area, which correlate with higher rates of perceptual discrimination, regardless of finger size. Moreover, upon applying hyaluronic acid to soften individuals’ skin, we observe immediate, marked and systematic changes in skin deformation and consequent improvements in perceptual acuity. Together, the combination of 3- D imaging of the skin surface, biomechanics measurements, multivariate regression and clustering, and psychophysical experiments show that subtle distinctions in skin stiffness modulate the mechanical signaling of touch and shape individual differences in perceptual acuity.Key points described in the manuscriptWhile declines in tactile acuity with aging are a function of multiple factors, for younger people the current working hypothesis has been that smaller fingers are better at informing perceptual discrimination due to a higher density of neural afferents.To decouple relative impacts on tactile acuity of skin properties of finger size, skin stiffness, and fingerprint ridge breadth, we combined 3D imaging of skin surface deformation, biomechanical measurements, multivariate regression and clustering, and psychophysics.The results indicate skin stiffness generally correlates with finger size, although more robustly correlates with and predicts an individual’s perceptual acuity.In particular, more elastic skin generates higher rates of deformation, which correlate with perceptual discrimination, shown most dramatically by softening each participant’s skin with hyaluronic acid.In refining the current working hypothesis, we show the skin’s stiffness strongly shapes the signaling of touch and modulates individual differences in perceptual acuity.
DNA methylation sites in early adulthood characterised by pubertal timing and development: A twin study
Authors: Sehovic Emir , Zellers Stephanie M. , Youssef Markus K. , Heikkinen Aino , Kaprio Jaakko , Ollikainen Miina 
Published: July 2023

ABSTRACTBackgroundPuberty is a highly heritable and variable trait, with environmental factors having a role in its eventual timing and development. Early and late pubertal onset are both associated with various diseases developing later in life, and epigenetic characterisation of pubertal timing and development could lead to important insights. Blood DNA methylation, reacting to both genotype and environment, has been associated with puberty; however, such studies are relatively scarce. We investigated peripheral blood DNA methylation profiles (using Illumina 450K and EPIC platforms) of 1539 young adult Finnish twins associated with pubertal development scale (PDS) and pubertal age (PA).ResultsFixed effect meta-analysis of the two platforms on 347521 CpGs in common identified 58 CpG sites associated (p < 1 x 10-5) with either PDS or PA. All four CpGs associated with PA and 45 CpGs associated with PDS were sex specific. Thirteen CpGs had a high heritability (h2: 0.51-0.98), while one CpG site (mapped toGET4) had a high shared environmental component accounting for 68% of the overall variance in methylation at the site. Utilising twin discordance analysis, we found 6 CpG sites (5 associated with PDS and 1 with PA) that had an environmentally driven association with puberty. Furthermore, genes with PDS- or PA-associated CpGs were linked to various developmental processes and diseases, such as breast, prostate and ovarian cancer, while methylation quantitative trait loci (meQTLs) of associated CpG sites were enriched in immune pathways developing during puberty.ConclusionsBy identifying puberty-associated DNA methylation sites and examining the effects of sex, environment and genetics, we shed light on the intricate interplay between environment and genetics in the context of puberty. Through our comprehensive analysis, we not only deepen the understanding of the significance of both genetic and environmental factors in the complex processes of puberty and its timing but also gain insights into potential links with disease risks.
Predicting cell morphological responses to perturbations using generative modeling
Authors: Palma Alessandro , Theis Fabian J. , Lotfollahi Mohammad 
Published: July 2023

AbstractAdvancements in high-throughput screening have enabled the exploration of rich phenotypic readouts like high-content microscopy, expediting drug target identification and mode of action studies. However, scaling these experiments to the vast space of drug or genetic manipulations poses challenges, as only a small subset of compounds show activity in screenings. Despite being widely used in various applications, machine learning methods have not shown a reliable ability to extrapolate predictions to scenarios involving unseen phenomena, specifically transforming an unseen control cell image into a desired perturbation. We present a generative model, the IMage Perturbation Autoencoder (IMPA), which predicts cellular morphological effects of chemical and genetic perturbations using untreated cells as input. IMPA learns perturbation-specific styles from generalized embeddings and generates counterfactual treatment response predictions in control cells. We demonstrate IMPA can predict morphological changes caused by small molecule perturbations on breast cancer cells. Additionally, we test IMPA on the unseen drug effect prediction task, showing improved performance over state-of-the-art generative models when compounds are structurally related to the training set. Finally, generalizability and capability to predict more subtle effects are showcased through its application to large microscopy datasets with hundreds of genetic perturbations on U2OS cells. We envision IMPA to become a valuable tool in computational microscopy for aiding phenotypic drug discovery, facilitating navigation of the perturbation space, and rational experimental design.
Attractor neural networks with double well synapses
Authors: Feng Yu , Brunel Nicolas 
Published: July 2023

AbstractIt is widely believed that memory storage depends on activity-dependent synaptic modifications. Classical studies of learning and memory in neural networks describe synaptic efficacy either as continuous [1, 2] or discrete [2–4]. However, recent results suggest an intermediate scenario in which synaptic efficacy can be described by a continuous variable, but whose distribution is peaked around a small set of discrete values [5, 6]. Motivated by these results, we explored a model in which each synapse is described by a continuous variable that evolves in a potential with multiple minima. External inputs to the network can switch synapses from one potential well to another. Our analytical and numerical results show that this model can interpolate between models with discrete synapses which correspond to the deep potential limit [7], and models in which synapses evolve in a single quadratic potential [8]. We find that the storage capacity of the network with double-well synapses exhibits a power law dependence on the network size, rather than the logarithmic dependence observed in models with single well synapses [9]. In addition, synapses with deeper potential wells lead to more robust information storage in the presence of noise. When memories are sparsely encoded, the scaling of the capacity with network size is similar to previously studied network models in the sparse coding limit [2, 10–13].
Click-train evoked steady state harmonic response as a novel pharmacodynamic biomarker of cortical oscillatory synchrony
Authors: Gautam Deepshila , Raza Muhammad Ummear , Miyakoshi M , Molina JL , Joshi YB , Clayson PE , Light GA , Swerdlow NR , Sivarao Digavalli V. 
Published: July 2023

AbstractSensory networks naturally entrain to rhythmic stimuli like a click train delivered at a particular frequency. Such synchronization is integral to information processing, can be measured by electroencephalography (EEG) and is an accessible index of neural network function. Click trains evoke neural entrainment not only at the driving frequency (F), referred to as the auditory steady state response (ASSR), but also at its higher multiples called the steady state harmonic response (SSHR). Since harmonics play an important and non-redundant role in acoustic information processing, we hypothesized that SSHR may differ from ASSR in presentation and pharmacological sensitivity. In female SD rats, a 2 s-long train stimulus was used to evoke ASSR at 20 Hz and its SSHR at 40, 60 and 80 Hz. Narrow band evoked responses were evident at all frequencies; signal power was strongest at 20 Hz while phase synchrony was strongest at 80 Hz. SSHR at 40 Hz took the longest time (∼180 ms from stimulus onset) to establish synchrony. The NMDA antagonist MK801 (0.025-0.1 mg/kg) did not consistently affect 20 Hz ASSR phase synchrony but robustly and dose-dependently attenuated synchrony of all SSHR. Evoked power was attenuated by MK801 at 20 Hz ASSR and 40 Hz SSHR only. Thus, presentation as well as pharmacological sensitivity distinguished SSHR from ASSR, making them non-redundant markers of cortical network function. SSHR is a novel and promising translational biomarker of cortical oscillatory dynamics that may have important applications in CNS drug development and personalized medicine.