bluuebunny/crossref_metadata_2025_split huggingface dataset:
Degradation of PET Plastics by Wastewater Bacteria Engineered via Conjugation
Authors: Yip Aaron , McArthur Owen D. , Ho Kalista C. , Aucoin Marc G. , Ingalls Brian P. 
Published: February 2024

AbstractMicroplastics are contaminants of global concern that pose risks to ecosystems and human health. Focusing on PET plastics, we present a proof-of-concept for reduction of microplastic pollution:in situengineering of bacteria in wastewater to degrade PET. Using a broad-host-range conjugative plasmid, we enabled various bacterial species from a municipal wastewater sample to express FAST-PETase, which was released into the extracellular environment. We found that FAST-PETase purified from some isolates could degrade about 40% of a 0.25 mm thick PET film within four days at 50 °C. We then demonstrate partial degradation of post-consumer PET over 5-7 days by exposure to conditioned media from isolates. These results have broad implications for addressing the global plastic pollution problem by enabling environmental bacteria to degrade PET plasticsin situ.
A direct readout mechanism regulates the sequence selectivity of humande novoDNA methyltransferases
Authors: Barlas Ayşe Berçin , Karaca Ezgi 
Published: February 2024

ABSTRACTDe novoDNA methylation is crucial for mammalian gene regulation, and it is mediated by DNMT3A and DNMT3B enzymes. Despite their catalytic domains sharing over 90% sequence similarity, they preferentially methylate different flanking nucleotides adjacent to a classical CG motif. To uncover the basis of this selective methylation pattern, we conducted extensive molecular dynamics simulations of DNMT3A/B bound to eight possible CGX[C/G/T/A] motifs. Our comparative analysis of dynamic enzyme-DNA interactions revealed that single nucleotide substitutions in CGX motifs significantly alter DNMT3A-DNA hydrogen bonding profiles, resulting in a more specific readout for DNMT3A compared to DNMT3B. We found that +2 CGX nucleotide selectivity is driven by Arg/Lys-Guanine base-specific hydrogen bonds formed between DNMT3A/B and DNA. More specifically, Arg836 in DNMT3A reads the guanine complementary to C+2 in its cognate CGC motif, while Lys777 in DNMT3B recognizes two consecutive guanines in its cognate CGG. In DNMT3B, the impact of Arg-to-Lys mutation is mitigated through the cooperative nucleotide recognition directed by Asn779. All in all, our study provides fundamental insights into the molecular mechanisms underlying DNA sequence selectivity inde novoDNA methylation at the atomistic scale, which will have direct implications in understanding other DNA sequence recognition mechanisms.
GenomeFace: a deep learning-based metagenome binner trained on 43,000 microbial genomes
Authors: Lettich Richard , Egan Robert , Riley Robert , Wang Zhong , Tritt Andrew , Oliker Leonid , Yelick Katherine , Buluç Aydın 
Published: February 2024

AbstractMetagenomic binning, the process of grouping DNA sequences into taxonomic units, is critical for understanding the functions, interactions, and evolutionary dynamics of microbial communities. We propose a deep learning approach to binning using two neural networks, one based on composition and another on environmental abundance, dynamically weighting the contribution of each based on characteristics of the input data. Trained on over 43,000 prokaryotic genomes, our network for composition-based binning is inspired by metric learning techniques used for facial recognition.Using a task-specific, multi-GPU accelerated algorithm to cluster the embeddings produced by our network, our binner leverages marker genes observed to be universally present in nearly all taxa to grade and select optimal clusters of sequences from a hierarchy of candidates.We evaluate our approach on four simulated datasets with known ground truth. Our linear time integration of marker genes recovers more near complete genomes than state of the art but computationally infeasible solutions using them, while being over an order of magnitude faster. Finally, we demonstrate the scalability and acuity of our approach by testing it on three of the largest metagenome assemblies ever performed. Compared to other binners, we produced 47%-183% more near complete genomes. From these datasets, we find over the genomes of over 3000 new candidate species which have never been previously cataloged, representing a potential 4% expansion of the known bacterial tree of life.
Multi-genome synteny detection using minimizer graph mappings
Authors: Coombe Lauren , Kazemi Parham , Wong Johnathan , Birol Inanc , Warren René L. 
Published: February 2024

AbstractIn recent years, the landscape of reference-grade genome assemblies has seen substantial diversification. With such rich data, there is pressing demand for robust tools for scalable, multi-species comparative genomics analyses, including detecting genome synteny, which informs on the sequence conservation between genomes and contributes crucial insights into species evolution. Here, we introduce ntSynt, a scalable utility for computing large-scale multi-genome synteny blocks using a minimizer graph-based approach. Through extensive testing utilizing multiple ∼3 Gbp genomes, we demonstrate how ntSynt produces synteny blocks with coverages between 79–100% in at most 2h using 34 GB of memory, even for genomes with appreciable (>15%) sequence divergence. Compared to existing state-of-the-art methodologies, ntSynt offers enhanced flexibility to diverse input genome sequences and synteny block granularity. We expect the macrosyntenic genome analyses facilitated by ntSynt will have broad utility in generating critical evolutionary insights within and between species across the tree of life.
Global diversity, recurrent evolution, and recent selection on amylase structural haplotypes in humans
Authors: Bolognini Davide , Halgren Alma , Lou Runyang Nicolas , Raveane Alessandro , Rocha Joana L. , Guarracino Andrea , Soranzo Nicole , Chin Jason , Garrison Erik , Sudmant Peter H. 
Published: February 2024

AbstractThe adoption of agriculture, first documented ∼12,000 years ago in the Fertile Crescent, triggered a rapid shift toward starch-rich diets in human populations. Amylase genes facilitate starch digestion and increased salivary amylase copy number has been observed in some modern human populations with high starch intake, though evidence of recent selection is lacking. Here, using 52 long-read diploid assemblies and short read data from ∼5,600 contemporary and ancient humans, we resolve the diversity, evolutionary history, and selective impact of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in populations with agricultural subsistence compared to fishing, hunting, and pastoral groups. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history.AMY1andAMY2Agenes each exhibit multiple duplications/deletions with mutation rates >10,000-fold the SNP mutation rate, whereasAMY2Bgene duplications share a single origin. Using a pangenome graph-based approach to infer structural haplotypes across thousands of humans, we identify extensively duplicated haplotypes present at higher frequencies in modern day populations with traditionally agricultural diets. Leveraging 533 ancient human genomes we find that duplication-containing haplotypes (i.e. haplotypes with moreamylase genecopies than the ancestral haplotype) have increased in frequency more than seven-fold over the last 12,000 years providing evidence for recent selection in West Eurasians. Together, our study highlights the potential impacts of the agricultural revolution on human genomes and the importance of long-read sequencing in identifying signatures of selection at structurally complex loci.
Unified machine learning framework uncovers overlooked bias control in immunogenic neoantigen identification
Authors: Zhang Ziting , Wu Wenxu , Wei Lei , Qi Hai , Wang Xiaowo 
Published: February 2024

AbstractNeoantigens play a crucial role in tumor immune process and precisely identifying them can greatly contribute to tumor immunotherapy design. There are three main steps in the neoantigen immune process, i.e., binding with MHCs, extracellular presentation, and immunogenicity induction. Various computational methods have been developed, but the overall accuracy of neoantigen identification remains relatively low. Here, we established a unified transformer-based framework ImmuBPI that comprised three tasks. Cross-task model interpretation discovered a counterfactual pattern learned by the immunogenicity prediction model overlooked in previous studies. We demonstrated that this model bias arose from training data imbalance and the neglect of bias control would not only mislead the models but also hinder existing benchmarks from fair evaluation. We further designed a mutual information-based debiasing strategy that showed preliminary potential in alleviating the bias. We believe these observations will provide insightful perspectives for future neoantigen prediction by high-lighting the necessity of bias control.
Study protocol for a pilot clinical trial to understand neural mechanisms of response to a psychological treatment for pain and anxiety in pediatric functional abdominal pain disorders (FAPD)
Authors: Cunningham Natoshia R. , Adler Michelle A. , Barber Garcia Brittany N. , Abounader Taylor , Miller Alaina K. , Monzalvo Mariela , Hashemi Ismaeel , Cox Ryan , Ely Samantha L. , Zhou Yong , DeLano Mark , Mulderink Todd , Reeves Mathew J. , Peugh James L. , Kashikar-Zuck Susmita , Coghill Robert C. , Arnetz Judith E. , Zhu David C. 
Published: February 2024

AbstractBackgroundFunctional abdominal pain disorders (FAPD) are the most common chronic pain conditions of childhood and are made worse by co-occurring anxiety. Our research team found that the Aim to Decrease Pain and Anxiety Treatment (ADAPT), a six-session coping skills program using cognitive behavioral therapy strategies, was effective in improving pain-related symptoms and anxiety symptoms compared to standard care. In follow-up, this current randomized clinical trial (RCT) aims to test potential neural mechanisms underlying the effect of ADAPT. Specifically, this two-arm RCT will explore changes in amygdalar functional connectivity (primary outcome) following the ADAPT protocol during the water loading symptom provocation task (WL-SPT). Secondary (e.g., changes in regional cerebral blood flow via pulsed arterial spin labeling MRI) and exploratory (e.g., the association between the changes in functional connectivity and clinical symptoms) outcomes will also be investigated.MethodsWe will include patients ages 11 to 16 years presenting to outpatient pediatric gastroenterology care at a midwestern children’s hospital with a diagnosis of FAPD plus evidence of clinical anxiety based on a validated screening tool (the Generalized Anxiety Disorder-7 [GAD-7] measure). Eligible participants will undergo baseline neuroimaging involving the WL-SPT, and assessment of self-reported pain, anxiety, and additional symptoms, prior to being randomized to a six-week remotely delivered ADAPT program plus standard medical care or standard medical care alone (waitlist). Thereafter, subjects will complete a post assessment neuroimaging visit similar in nature to their first visit.ConclusionsThis small scale RCT aims to increase understanding of potential neural mechanisms of response to ADAPT. ClinicalTrials.gov registration:NCT03518216
Effectiveness of Psychosocial care interventions in improving the Quality of Life for Adult Patients with Cancer in low-and middle-income countries (LMICs): A Systematic Review and Meta-Analysis Protocol
Authors: Kavuma David , Namisango Eve , Downing Julia , Niyonzima Nixon , Kinengyere Alison Annet , Kasasa Simon , Makumbi Fredrick Edward , Obuku Ekwaro Anthony , Nuwaha Fred 
Published: February 2024

AbstractBackgroundPsychosocial care interventions are part and parcel of cancer care and are known for their significant contribution to the improvement of the quality of life (QoL) for cancer patients and their families. Assessment of the QoL of patients with cancer and their families has become critical in cancer care nowadays since it guides health care providers in making informed decisions during the care process. The aim of this meta-analysis is to synthesise the online literature of primary studies from LMICs in order to understand the effectiveness of psychosocial care interventions towards the improvement of the QoL of adult patients with cancer.MethodsThis study will be done in tandem with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. Primary studies that would have investigated the effectiveness of psychosocial care interventions on quality of life of adult cancer patients will be identified through searches in the various electronic databases that are known to produce optimal and efficient searches for systematic reviews and meta-analyses include: Ovid MEDLINE(R), PubMed, EMBASE, APA PsychINFO, Web of Science, PubMed, and Google Scholar. Studies published between 1stJanuary 2002 and 31stDecember 2023 in any LMIC, will be searched. After developing the meta-analysis question, we have developed a search string from the PICOST (population, intervention, comparison, outcome, study design, setting and Time-frame) model with a limitation on study design.DiscussionThis systematic review and meta-analysis will gather evidence from primary studies on the effectiveness of psychosocial care interventions in improving the QoL for adult patients with cancer in LMICs.Protocol registrationThis protocol was registered on 5thJune 2023 and its registration number is CRD42023421561.
HEALTH PROMOTION AND PREVENTIVE INTERVENTIONS FOR SENIOR CITIZENS IN COUNTRIES WITH ACCESSIBLE AND FUNDED HEALTH CARE: STUDY PROTOCOL FOR A SCOPING REVIEW
Authors: Lostelius Petra Vikman , Aromaa Henri , Karlsson Malin Lohela , Revenäs Åsa , Nordgren Lena 
Published: February 2024

AbstractTo improve health in a growing population with increasing life expectancy, a stepwise health care program for citizens aged 65 years and older will be implemented in Region Västmanland in Central Sweden. This scoping review builds on a previous review and aims to map interventions in a larger number of countries and from 2019 to present. The objective of this scoping review is to map the literature on the components of health promotion and preventive interventions in countries that provide accessible and funded health care. The JBI methodology will be employed for good structure. Searches will be conducted in databases and websites, for grey literature. The searches will include health promotion studies, preventive health measures, intervention methods, intervention delivery, outcome measures, or health-economic evaluations for people aged 65 years and older. Two reviewers will individually assess each study and extract data. Data analysis will consist of basic frequencies and percentages. The results will be presented in tables and/or diagrams and a narrative summary.
Perceptual constancy of pareidolias across paper and digital testing formats in neurodegenerative diseases
Authors: Revankar Gajanan S. , Ozono Tatsuhiko , Suzuki Maki , Kanemoto Hideki , Furuya Kota , Kamae Kazue , Yoshiyama Kenji , Yamamoto Yuki , Ogasawara Issei , Yoshida Natsuki , Iwasaki Susumu , Saeki Chizu , Nishio Yoshiyuki , Nakatani Daisaku , Asai Kanako , Kajiyama Yuta , Shimizu Mikito , Hayashi Tatsuya , Taniguchi Seira , Suzuki Yu , Inada Rino , Taminato Tomoya , Nagai Yoshitaka , Hashimoto Mamoru , Ikeda Manabu , Mori Etsuro , Mochizuki Hideki , Nakata Ken 
Published: February 2024

AbstractPareidolias refer to visual perceptual deficits where ambiguous shapes take on meaningful appearances. In neurodegenerative diseases, pareidolias are examined via a paper-based neuropsychological tool called the noise pareidolia test. In this study, we present initial findings regarding the utilization of pareidolia test on a digital format to analyze variations between paper-based and digital testing approaches. We performed our experiments on healthy controls, patients diagnosed with Alzheimer’s disease (AD), Dementia with Lewy body disease (DLB) and Parkinson’s disease (PD). Baseline MMSE assessments were conducted, followed by pareidolia testing using both paper-based tools and smartphones. Bland-Altman analysis was performed to evaluate the agreement between the two methods. We found that the illusionary phenomenon of pareidolia is consistent across paper and digital modalities of testing; that perceptual constancy is maintained across patient groups despite variations in image sizes; and pareidolic misperceptions, to some extent, are stabilized on a digital format. Our findings demonstrate a practical way of testing pareidolias on smartphones without compromising on the functionality of the test.
Outcomes of prognostication in people living with advanced cancer: a qualitative study to inform a Core Outcome Set
Authors: Spooner Caitlin , Vivat Bella , White Nicola , Stone Patrick 
Published: February 2024

AbstractBackgroundStudies of prognostication in advanced cancer use a wide range of outcomes and outcome measures, making it difficult to compare these studies and their findings. Core Outcome Sets facilitate comparability and standardisation between studies and would benefit future prognostic research. This qualitative study is the second step in developing such a Core Outcome Set, with the aim to explore the perceptions and experiences of patients with advanced cancer, informal caregivers, and clinicians regarding the potential outcomes of prognostication.MethodsWe conducted semi-structured interviews with patients living with advanced cancer (n=8), informal caregivers (n=10), and clinicians (n=10) recruited from palliative care services across three sites in London, United Kingdom. Interviews were conducted in-person, via telephone, or video conferencing, and were audio-recorded. Data were analysed using a thematic framework analysis approach. Findings were compared with outcomes derived from a previously published systematic review.ResultsWe identified 33 outcomes, 16 of which were not previously reported in the literature. We grouped outcomes into 10 domains, using a modified COMET taxonomy: 1) mortality/survival; 2) general physiological/clinical outcomes; 3) psychiatric outcomes; 4) spiritual/religious/existential functioning/wellbeing; 5) emotional functioning/wellbeing; 6) social functioning; 7) delivery of care; 8) perceived health status; 9) personal circumstances; 10) societal/carer burden. These findings highlighted discrepancies between the priorities of existing research and those of stakeholders.ConclusionsThis study offers valuable insights into outcomes significant to key stakeholders, underscoring the need for a patient-centred approach in research and clinical practice in prognostication in advanced cancer. These outcomes will play a key role in the development of a Core Outcome Set to assess the impact of prognostication in advanced cancer.
Influenza vaccination allocation in tropical settings under constrained resources
Authors: Servadio Joseph L , Choisy Marc , Thai Pham Quang , Boni Maciej F 
Published: February 2024

AbstractInfluenza virus seasonality, synchronicity, and vaccine supply differ substantially between temperate and tropical settings, and optimal vaccination strategy may differ on this basis. Most national vaccine recommendations focus on high-risk groups, elderly populations, and healthcare workers despite previous analyses demonstrating broad benefits to vaccinating younger high-contact age groups. Here, we parameterized an age-structured non-seasonal asynchronous epidemiological model of influenza virus transmission for a tropical low-income setting. We evaluated timing and age allocation of vaccines across vaccine supplies ranging from 10% to 90% using decade-based age groups. Year-round vaccination was beneficial when comparing to vaccination strategies focused on a particular time of year. When targeting a single age-group for vaccine prioritization, maximum vaccine allocation to the 10-19 high-contact age group minimized annual influenza mortality for all but one vaccine supply. When evaluating across all possible age allocations, optimal strategies always allocated a plurality of vaccines to school-age children (10-19). The converse however was not true as not all strategies allocating a plurality to children aged 10-19 minimized mortality. Allocating a high proportion of vaccine supply to the 10-19 age group is necessary but not sufficient to minimize annual mortality as distribution of remaining vaccine doses to other age groups also needs to be optimized. Strategies focusing on indirect benefits (vaccinating children) showed higher variance in mortality outcomes than strategies focusing on direct benefits (vaccinating the elderly). However, the indirect benefit approaches showed lower mean mortality and lower minimum mortality than vaccination focused on the elderly.Significance statementInfluenza exhibits strong annual seasonality in temperate countries, but less consistent and predictable patterns in tropical countries. Many tropical countries are low-income countries with low influenza vaccine coverage. Globally, influenza vaccines are recommended for elderly adults and vulnerable groups, though evidence has shown that vaccinating school-age children is beneficial due to their high rates of social contact. Our modeling study evaluated whether age-based vaccine allocations can effectively minimize population influenza mortality in a tropical country with constrained resources and little seasonality. Prioritizing school-aged children for vaccination minimized mortality, with secondary emphasis on elderly adults. These benefits are most apparent under low vaccine supplies and can inform most effective ways to develop or expand influenza vaccination campaigns in low-income tropical settings.
PLAPT: Protein-Ligand Binding Affinity Prediction Using Pretrained Transformers
Authors: Rose Tyler , Monti Nicolò , Anand Navvye , Shen Tianyu 
Published: February 2024

AbstractPredicting protein-ligand binding affinity is crucial for drug discovery, as it enables efficient identification of drug candidates. We introduce PLAPT, a novel model utilizing transfer learning from pre-trained transformers like ProtBERT and ChemBERTa to predict binding affinities with high accuracy. Our method processes one-dimensional protein and ligand sequences, leveraging a branching neural network architecture for feature integration and affinity estimation. We demonstrate PLAPT’s superior performance through validation on multiple datasets, achieving state-of-the-art results while requiring significantly less computational resources for training compared to existing models. Our findings indicate that PLAPT offers a highly effective and accessible approach for accelerating drug discovery efforts.