bluuebunny/crossref_metadata_2025_split huggingface dataset:
Barriers to Alzheimer Disease Clinical Trial Participation in a Minority Population
Authors: Lee Anson Y. , Jahansooz Julia R. , Guittu Darrell , Suzuki Rexton , Pak Lauren , Ishikawa Kyle M. , Goo Connor , Chen John J. , Carrazana Enrique , Viereck Jason , Liow Kore K. 
Published: October 2023

Background:
Alzheimer disease (AD), the most common neurodegenerative disorder in the United States, disproportionately burdens minority populations.

Objective:
To explore barriers to AD clinical trial participation by Asian and Native Hawaiian patients diagnosed with AD or mild cognitive impairment.

Method:
We surveyed 187 patients with a Mini-Mental State Examination score ≥14 between January 2022 and June 2022. The score cutoff for clinical trial eligibility was set by the institution. Individuals also completed a 15-question telephone survey that assessed demographics, barriers to clinical trial participation, and clinical trial improvement methods.

Results:
Forty-nine patients responded, with a response rate of 26%. Asian and Native Hawaiian patients were less likely than White patients to participate in AD trials. The main barrier to participation was a lack of information about AD trials. Providing additional information regarding AD trials to patients and family members were listed as the top two reasons patients would consider participating in a clinical trial.

Conclusion:
Insufficient information about AD clinical trials is the primary barrier to participation among Asian and Native Hawaiian patients, followed by difficulty coordinating transportation and, in the case of Asians, the time required for clinical trials. Increased outreach, education, and assistance with logistics in these populations should be pursued to improve rates of participation in clinical trials.
Substrate profiling of human Transglutaminase 1 using cDNA display and next-generation sequencing
Authors: Munaweera T.I.K. , Damnjanović Jasmina , Camagna Maurizio , Nezu Moeri , Jia Beixi , Hitomi Kiyotaka , Nemoto Naoto , Nakano Hideo 
Published: October 2023

AbstractHuman transglutaminase 1 regulates skin development and is linked with several disease conditions with yet fully unknown mechanisms. To uncover all of its roles in health and disease, the understanding of protein substrates and their reactivity with transglutaminase 1 is necessary. To gain insight into the substrate profile of human transglutaminase 1, this study uses anin vitroselection system based on the cDNA display technology to screen two displayed peptide libraries differing in the number and position of mutated sites relative to the reactive glutamine, in terms of their reactivity to transglutaminase 1. Analysis of the selected DNA pools of by next-generation sequencing and in-house bioinformatics methods revealed a detailed transglutaminase 1 substrate profile indicating preferred and non-preferred amino acid sequences. We have identified a peptide with sequence AEQHKLPSKWPF showing high reactivity to human transglutaminase 1 and low reactivity to transglutaminase 2 and transglutaminase 3. The position weight matrix consisting of per residue amino acid enrichment factors of all selected peptides was used to search human proteins by our in-house search algorithm and identify highly scoring sequence motifs in their primary structure. The search identified six already known transglutaminase 1 substrate proteins as highly scored hits as well as a list of candidate substrates that are under investigation.
Visual and pharmacotherapy outcomes after transverse sinus stenting for idiopathic intracranial hypertension
Authors: Handzic Armin , Xie Jim Shenchu , Hendriks Eef , Mosimann Pascal , Nicholson Patrick , Micieli Jonathan , Margolin Edward 
Published: October 2023

ABSTRACTBackgroundTransverse sinus stenting (TSS) is an increasingly commonly used treatment for patients with idiopathic intracranial hypertension (IIH). However, detailed neuro-ophthalmic evidence on visual and pharmacotherapy outcomes after TSS is scarce and heterogeneous. This study aimed to describe the visual outcomes of patients undergoing TSS for IIH and to ascertain the proportion of patients who could be weaned off intracranial pressure (ICP)-lowering medication after this procedure.MethodsA retrospective chart review of all patients with IIH from two tertiary academic neuro-ophthalmology practices who underwent TSS between 2016 and 2022 was performed. Indications for stenting included failure of pharmacotherapy, intolerance of pharmacotherapy, and acute vision loss from severe papilledema. Data on demographics, symptoms, visual function, and TSS were collected. The paired Wilcoxon rank sum test was used to compare changes in visual acuity (VA) and visual field mean deviation (VFMD) between the baseline and most recent visits.ResultsOf 435 patients with IIH, 15 (13 women) met inclusion criteria. After TSS, ICP-lowering pharmacotherapy was discontinued in 10 patients and decreased in 4; one patient was not on ICP-lowering medication before TSS. All patients experienced resolution or improvement of symptoms (10 resolution, 4 improved, 1 asymptomatic before TSS) and papilledema (11 resolution, 4 improved) after stenting. Papilledema resolution was confirmed with optical coherence tomography-measured peripapillary nerve fibre layer thickness (median decrease 147 μm, interquartile range 41.8 – 242.8, p<0.001). Change in VA between the baseline and most recent visit was not significant, but VFMD improved significantly after stenting (median increase 3.0, IQR 2.0 – 4.2, p<0.001). No patient developed transverse sinus restenosis nor in-stent thrombosis postoperatively across a median venogram follow-up of 20.8 weeks (11.3 – 49.8) and no patient required subsequent surgical intervention for IIH.ConclusionIn this cohort of patients with IIH and fulminant presentation, medication resistance, or medication intolerance, TSS was an effective and safe treatment modality. Most patients were able to stop ICP-lowering medications while demonstrating striking improvement in symptomatology and visual function.
A possible mechanistic insight on how Compromised Hydrolysis of Triacylglycerol 7 (CHT7) restrains the involvement of it’s DNA binding CXC domain from quiescence repression
Authors: Chauhan Manisha , Arshi Syeda Amna , Narayanan Naveen , Arfin Haseeb Ul , Sharma Amit 
Published: October 2023

AbstractCHT7 is a regulator of quiescence repression and TAG degradation between the nitrogen deprived and the nitrogen replenished states inChlamydomonas reinhardtii. Initially it was thought that the CHT7’s repression activity is managed by its DNA binding CXC domain which is a tandem repeat of two cysteine rich subdomains. Later, it was found that the CXC (CHT7_CXC) domain is effectively dispensable for CHT7’s activities. Rather, CHT7’s predicted protein binding domains are proposed to be involved in gene regulation activities by binding through other repressors in the cell. Yet, it remains unclear why and how CHT7 manages to refrain its own CXC domain from participating in any transcriptional activities. The question becomes more intriguing, because CXC binding regions are available in promoter regions of some of the misregulated genes in the CHT7 mutant (cht7). Through the combination of biophysical experiments and molecular dynamics approaches, we have studied the DNA recognition behavior of CHT7_CXC. The results show that CHT7_CXC domain is highly selective towards DNA sequences and this selectivity is imparted due to the differential binding abilities of the CXC subdomains. Further, to understand if the case is - that CXC looses it’s DNA binding capabilities in the vicinity of other repressor molecules, we carried out CHT7_CXC’s DNA binding stability test by simulating the spatial constraint conditions using the AsLOV2- CXC fusion. Our test results show limited ability of CHT7_CXC to withstand steric forces and provide insights to why and how algal cells may hold back CHT7_CXC’s indulgence in quiescence repression.SignificanceMicroalgae, under nutrient rich conditions, provide biomass. Whereas, nutrient deprivation leads to accumulation of biofuel feedstock, but cells enter quiescence. Net enhancement in feedstock, therefore relies on the precision of the quiescence regulator. InChlamydomonas reinhardtii, CHT7 is a central regulator of quiescence. Surprisingly, rather than using its own DNA binding domain (DBD) for the regulatory activities, CHT7 recruits external transcriptional regulators using its non DBDs. To ensure smooth functioning, CHT7’s DBD must rapidly switch to inactive form. Modifications in DNA binding profiles of DBDs due to non DBDs are seen in transcription factors of many organisms. The switching mechanism discussed could therefore be a generic approach of timely regulation of individual components of the complex transcriptional machineries.
Bioinformatics analysis of Uncyclotides: a potential antimicrobial peptide to protect against heart failure diseases
Authors: Maya-Ramírez Carlos Eliel , Sufyan Muhammad , Alanzi Abdullah R 
Published: October 2023

AbstractHeart failure (also known as HF) is a clinical disorder triggered by functional and structural defects in cardiac muscles causing blood ejection or damage of ventricular filling. Even though the progression in the field of medicine, HF control, which generally presents as a syndrome, has been a task to healthcare sources. This is reproduced by the comparatively higher ration of readmissions with enhanced disease and death linked with HF. Congestive heart failure is also linked with expressional changes of human uncoupling protein proteins. So, we need to tackle the heart failure problem with the help of bioinformatics analysis. In this study, we retrieved three antimicrobial peptides (Cathelicidins, CRAMP and Uncyclotides) and four human uncoupling proteins (UCP 1, UCP 2, UCP 3 & UCP 4) from DRAMP and NCBI web server. Physiochemical properties and domains analysis of UCPs and antimicrobial peptides was performed by using Protparam, DRAMP and InterPro databases correspondingly. To predict the UCPs structure, homology modelling was performed by SWISS-MODEL server and structural assessment was done by Ramachandran plots. We detected the best antimicrobial peptide (Uncyclotides) against heart failure diseases after HPEPDOCK analysis. We also confirmed stability of UCP 1-Uncyclotides complex, and shown the slight distortion of the deformability plot supported by highest eigenvalues after Molecular Dynamics analysis. Therefore, this in silico approach identifies potential antimicrobial peptides “Uncyclotides” (acts as inhibitors) of heart failure diseases, which have to be confirmed further after experimental and clinical trials.
Mechanism for controlled assembly of transcriptional condensates by Aire
Authors: Huoh Yu-San , Zhang Qianxia , Torner Ricarda , Baca Sylvan C. , Arthanari Haribabu , Hur Sun 
Published: October 2023

AbstractTranscriptional condensates play a crucial role in gene expression and regulation1–4, yet the mechanisms governing their assembly at the correct location and time remain poorly understood2,5–7. We here report a multi-layered mechanism for condensate assembly by the Autoimmune regulator (Aire), an essential transcriptional regulator (TR) that orchestrates gene expression reprogramming for central T-cell tolerance8,9. Previous studies demonstrated that Aire utilizes its polymerizing domain CARD to form nuclear condensates critical for its transcriptional activity10,11. Our current data show that Aire condensates assemble on enhancers, stimulating local transcriptional activities, while also connecting disparate inter-chromosomal genomic loci. This process of functional condensate formation hinges upon the coordination between three Aire domains: the CARD, the histone binding domain PHD1 and the activation domain C-terminal tail (CTT). Specifically, CTT directly binds CBP/p300 coactivators, recruiting Aire to CBP/p300-rich enhancers and promoting CARD-mediated condensate assembly. Conversely, PHD1 restrains spontaneous Aire polymerization by binding to the ubiquitous unmethylated H3K4, ensuring Aire remains dispersed throughout the genome until it nucleates on enhancers. Accordingly, deletion of CTT or PHD1 leads to a complete loss of Aire’s functions through distinct mechanisms––deletion of CTT abrogates Aire condensate formation, whereas deletion of PHD1 leads to dysfunctional Aire condensates detached from chromatin. Thus, our findings highlight the balance between PHD1-mediated suppression and CTT-mediated stimulation of Aire polymerization to form transcriptionally active condensates at appropriate target sites, providing new insights into controlled polymerization of TRs.
Protein Language Models Uncover Carbohydrate-Active Enzyme Function in Metagenomics
Authors: Thurimella Kumar , Mohamed Ahmed M. T. , Graham Daniel B. , Owens Róisín M. , La Rosa Sabina Leanti , Plichta Damian R. , Bacallado Sergio , Xavier Ramnik J. 
Published: October 2023

AbstractIn metagenomics, the pool of uncharacterized microbial enzymes presents a challenge for functional annotation. Among these, carbohydrate-active enzymes (CAZymes) stand out due to their pivotal roles in various biological processes related to host health and nutrition. Here, we present CAZyLingua, the first tool that harnesses protein language model embeddings to build a deep learning framework that facilitates the annotation of CAZymes in metagenomic datasets. Our benchmarking results showed on average a higher F1 score (reflecting an average of precision and recall) on the annotated genomes ofBacteroides thetaiotaomicron,Eggerthella lentaandRuminococcus gnavuscompared to the traditional sequence homology-based method in dbCAN2. We applied our tool to a paired mother/infant longitudinal dataset and revealed unannotated CAZymes linked to microbial development during infancy. When applied to metagenomic datasets derived from patients affected by fibrosis-prone diseases such as Crohn’s disease and IgG4-related disease, CAZyLingua uncovered CAZymes associated with disease and healthy states. In each of these metagenomic catalogs, CAZyLingua discovered new annotations that were previously overlooked by traditional sequence homology tools. Overall, the deep learning model CAZyLingua can be applied in combination with existing tools to unravel intricate CAZyme evolutionary profiles and patterns, contributing to a more comprehensive understanding of microbial metabolic dynamics.
Application of Transfer Learning for Rapid Calibration of Spatially-resolved Diffuse Reflectance Probes for Extraction of Tissue Optical Properties
Authors: Hannan Md Nafiz , Baran Timothy M. 
Published: October 2023

AbstractSignificanceTreatment planning for light-based therapies including photodynamic therapy requires tissue optical property knowledge. These are recoverable with spatially-resolved diffuse reflectance spectroscopy (DRS), but requires precise source-detector separation (SDS) determination and time-consuming simulations.AimAn artificial neural network (ANN) to map from DRS at short SDS to optical properties was created. This trained ANN was adapted to fiber-optic probes with varying SDS using transfer learning.ApproachAn ANN mapping from measurements to Monte Carlo simulation to optical properties was created with one fiber-optic probe. A second probe with different SDS was used for transfer learning algorithm creation. Data from a third were used to test this algorithm.ResultsThe initial ANN recovered absorber concentration with RMSE=0.29 µM (7.5% mean error) and µs’at 665 nm (µs,665’) with RMSE=0.77 cm-1(2.5% mean error). For probe-2, transfer learning significantly improved absorber concentration (0.38 vs. 1.67 µM, p=0.0005) and µs,665’(0.71 vs. 1.8 cm-1, p=0.0005) recovery. A third probe also showed improved absorber (0.7 vs. 4.1 µM, p<0.0001) and µs,665’(1.68 vs. 2.08 cm-1, p=0.2) recovery.ConclusionsA data-driven approach to optical property extraction can be used to rapidly calibrate new fiber-optic probes with varying SDS, with as few as three calibration spectra.
Rewiring of cortical glucose metabolism fuels human brain cancer growth
Authors: Scott Andrew J. , Mittal Anjali , Meghdadi Baharan , Palavalasa Sravya , Achreja Abhinav , O’Brien Alexandra , Kothari Ayesha U. , Zhou Weihua , Xu Jie , Lin Angelica , Wilder-Romans Kari , Edwards Donna M. , Wu Zhe , Feng Jiane , Andren Anthony C. , Zhang Li , Tarnal Vijay , Redic Kimberly A. , Qi Nathan , Fischer Joshua , Yang Ethan , Regan Michael S. , Stopka Sylwia A , Baquer Gerard , Lawrence Theodore S. , Venneti Sriram , Agar Nathalie Y. R. , Lyssiotis Costas A. , Al-Holou Wajd N. , Nagrath Deepak , Wahl Daniel R. 
Published: October 2023

AbstractThe brain avidly consumes glucose to fuel neurophysiology. Cancers of the brain, such as glioblastoma (GBM), lose aspects of normal biology and gain the ability to proliferate and invade healthy tissue. How brain cancers rewire glucose utilization to fuel these processes is poorly understood. Here we perform infusions of13C-labeled glucose into patients and mice with brain cancer to define the metabolic fates of glucose-derived carbon in tumor and cortex. By combining these measurements with quantitative metabolic flux analysis, we find that human cortex funnels glucose-derived carbons towards physiologic processes including TCA cycle oxidation and neurotransmitter synthesis. In contrast, brain cancers downregulate these physiologic processes, scavenge alternative carbon sources from the environment, and instead use glucose-derived carbons to produce molecules needed for proliferation and invasion. Targeting this metabolic rewiring in mice through dietary modulation selectively alters GBM metabolism and slows tumor growth.SignificanceThis study is the first to directly measure biosynthetic flux in both glioma and cortical tissue in human brain cancer patients. Brain tumors rewire glucose carbon utilization away from oxidation and neurotransmitter production towards biosynthesis to fuel growth. Blocking these metabolic adaptations with dietary interventions slows brain cancer growth with minimal effects on cortical metabolism.
Identification of proteotoxic and proteoprotective bacteria that non-specifically affect proteins associated with neurodegenerative diseases
Authors: Walker Alyssa C , Bhargava Rohan , Bucher Michael , Brust Amanda S , Czyż Daniel M 
Published: October 2023

SummaryNeurodegenerative protein conformational diseases (PCDs), such as Alzheimer’s, Parkinson’s, and Huntington’s, are a leading cause of death and disability worldwide and have no known cures or effective treatments. Emerging evidence suggests a role for the gut microbiota in the pathogenesis of neurodegenerative PCDs; however, the influence of specific bacteria on the culprit proteins associated with each of these diseases remains elusive, primarily due to the complexity of the microbiota. In the present study, we employed a single-strain screening approach to identify human bacterial isolates that enhance or suppress the aggregation of culprit proteins and the associated toxicity inCaenorhabditis elegansexpressing Aβ1-42, α-synuclein, and polyglutamine tracts. Here, we reveal the first comprehensive analysis of the human microbiome for its effect on proteins associated with neurodegenerative diseases. Our results suggest that bacteria affect the aggregation of metastable proteins by modulating host proteostasis rather than selectively targeting specific disease-associated proteins. These results reveal bacteria that potentially influence the pathogenesis of PCDs and open new promising prevention and treatment opportunities by altering the abundance of beneficial and detrimental microbes.
A quantitative genetics framework for understanding the selection response of microbial communities
Authors: Xie Li , Yuan Alex E , Shou Wenying 
Published: October 2023

AbstractHeritability, a quantity that reflects the degree of resemblance between parent and offspring traits, is measured during plant and animal breeding because it predicts selection success during artificial selection of individuals. However, when whole microbial communities are under artificial selection to improve their traits, high heritability of the community trait does not necessarily predict selection success. To better understand the relationship between heritability and success during community selection, we establish a quantitative genetics framework, and in doing so, we obtain practical recommendations. Specifically, we decompose a community trait into “trait determinants”: genotype compositions and species compositions that impact the community trait and that vary among communities. This allows us to interpret heritability of a community trait in terms of the heritability of its determinants. We then use the Price equation to partition the selection response of a community trait into three phenomena: inter-community selection (heritability multiplied by selection intensity), transmission infidelity (the change in community trait from parent to offspring), and nonlinearity (due to a nonlinear relationship between parent and offspring traits). We illustrate that evolution within a community can cause the three terms to covary: in addition to the known effect of worsening transmission infidelity, intra-community evolution can lead to inflated heritability values greater than one (through an effect whereby “the poor get poorer”), and simultaneously magnify nonlinearity. As a consequence of these effects, heritability no longer predicts the selection response of a community trait. We propose effective selection strategies that improve heritability without accelerating intra-community evolution.
Unfolding the potential of the ARIMA model in forecasting maize production in Tanzania
Authors: Lwaho Joseph , Ilembo Bahati 
Published: October 2023

PurposeThis paper was set to develop a model for forecasting maize production in Tanzania using the autoregressive integrated moving average (ARIMA) approach. The aim is to forecast future production of maize for the next 10 years to help identify the population at risk of food insecurity and quantify the anticipated maize shortage.Design/methodology/approachAnnual historical data on maize production (hg/ha) from 1961 to 2021 obtained from the FAOSTAT database were used. The ARIMA method is a robust framework for forecasting time-series data with non-seasonal components. The model was selected based on the Akaike Information Criteria corrected (AICc) minimum values and maximum log-likelihood. Model adequacy was checked using plots of residuals and the Ljung-Box test.FindingsThe results suggest that ARIMA (1,1,1) is the most suitable model to forecast maize production in Tanzania. The selected model proved efficient in forecasting maize production in the coming years and is recommended for application.Originality/valueThe study used partially processed secondary data to fit for Time series analysis using ARIMA (1,1,1) and hence reliable and conclusive results.