bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Fc glycosylation on the activity of WNT mimetic agonistic antibodies
Authors: Chen Hui , Lee Sung-Jin , Ouyang Brian , Suen Nicholas , Ye Jay , Lu Chenggang , Li Yang 
Published: January 2024

Abstract
Monoclonal antibodies have been explored in a broad range of applications including receptor agonism. Given the importance of receptor conformation in signaling, the agonistic activity of antibodies that engage these receptors are influenced by many parameters. Tetravalent bispecific antibodies that target the frizzled and lipoprotein receptor-related protein receptors and subsequently activate WNT (“Wingless-related integration site” or “Wingless and Int-1” or “Wingless-Int”) signaling have been constructed. Because WNT activation stimulates stem cell proliferation and tissue regeneration, immune effector functions should be eliminated from therapeutic antibodies targeting this pathway. Here, we report an unexpected effect of Fc glycosylation on the agonistic activity of WNT mimetic antibodies. Our findings underscore the importance of antibody format, geometry and epitope in agonistic antibody design, and highlight the need to establish appropriate early discovery screening strategies to identify hits for further optimization.
Effects of study design parameters on estimates of bee abundance and richness in agroecosystems: a meta-analysis
Authors: Levenson Hannah K , Metz Bradley N , Tarpy David R 
Published: January 2024

AbstractPollinators are critical for agricultural production and food security, leading to many ongoing surveys of pollinators (especially bees) in crop and adjacent landscapes. These surveys have become increasingly important to better understand the community of potential pollinators, quantify relative insect abundance, and secure crop ecosystem services. However, as some bee populations are declining, there is a need to align and improve bee survey efforts, so that they can best meet research and conservation goals, particularly in light of the logistical and financial constraints of conducting such studies. Here, we mined the existing literature on bee surveys in or around agricultural lands to better understand how sampling methods can be optimized to maximize estimates of 2 key measures of bee communities (abundance and richness). After reviewing 72 papers spanning 20 yr of publication, we found that study duration, number of sites, sampling time, and sampling method most significantly influenced abundance, while the number of trips per year and collection method significantly influenced richness. Our analysis helps to derive thresholds, priorities, and recommendations that can be applied to future studies describing bee communities in agroecosystems.
What are the priorities for research of older people living in their own home, including those living with frailty? A systematic review and content analysis of studies reporting older people’s priorities and unmet needs
Authors: Graham Liz , Brundle Caroline , Harrison Nicola , Andre Deirdre , Clegg Andrew , Forster Anne , Spilsbury Karen 
Published: January 2024

Abstract

Background
There is limited evidence regarding the needs of older people, including those living with frailty, to inform research priority setting.

Objectives
This systematic review aimed to identify the range of research priorities of community-dwelling older people living in their own home, including those living with frailty.

Methods
Included studies were from economically developed countries and designed to identify the priorities for research or unmet needs of community-dwelling older people. Studies were excluded if they described priorities relating to specific health conditions. Medline, Embase, PsycInfo and CINAHL were searched (January 2010–June 2022), alongside grey literature. Study quality was assessed, but studies were not excluded on the basis of quality. A bespoke data extraction form was used and content analysis undertaken to synthesise findings.

Results
Seventy-five reports were included. Seven explicitly aimed to identify the priorities or unmet needs of frail older people; 68 did not specify frailty as a characteristic. Study designs varied, including priority setting exercises, surveys, interviews, focus groups and literature reviews. Identified priorities and unmet needs were organised into themes: prevention and management, improving health and care service provision, improving daily life, meeting carers’ needs and planning ahead.

Discussion
Many priority areas were raised by older people, carers and health/care professionals, but few were identified explicitly by/for frail older people. An overarching need was identified for tailored, collaborative provision of care and support.

Conclusion
Review findings provide a valuable resource for researchers and health/care staff wishing to focus their research or service provision on areas of importance for older people.
Implementation of clopidogrel pharmacogenetic clinical decision support for a preemptive return of results program
Authors: Aquilante Christina L , Trinkley Katy E , Lee Yee Ming , Crooks Kristy R , Hearst Emily C , Heckman Simeon M , Hess Kaitlyn W , Kudron Elizabeth L , Martin James L , Swartz Carolyn T , Kao David P 
Published: January 2024

Abstract

Purpose
To describe our experiences implementing and iterating CYP2C19 genotype–guided clopidogrel pharmacogenetic clinical decision support (CDS) tools over time in the setting of a large health system–wide, preemptive pharmacogenomics program.

Summary
Clopidogrel-treated patients who are genetically predicted cytochrome P450 isozyme 2C19 (CYP2C19) intermediate or poor metabolizers have an increased risk of atherothrombotic events, some of which can be life-threatening. The Clinical Pharmacogenetics Implementation Consortium provides guidance for the use of clopidogrel based on CYP2C19 genotype in patients with cardiovascular and cerebrovascular diseases. Our multidisciplinary team implemented an automated, interruptive alert that fires when clopidogrel is ordered or refilled for biobank participants with structured CYP2C19 intermediate or poor metabolizer genomic indicators in the electronic health record. The implementation began with a narrow cardiovascular indication and setting and was then scaled in 4 primary dimensions: (1) clinical indication; (2) availability across health-system locations; (3) care venue (e.g., inpatient vs outpatient); and (4) provider groups (eg, cardiology and neurology). We iterated our approach over time based on evolving clinical evidence and proactive strategies to optimize CDS maintenance and sustainability. A key facilitator of expansion was socialization of the broader pharmacogenomics initiative among our academic medical center community, accompanied by clinician acceptance of pharmacogenetic alerts in practice.

Conclusion
A multidisciplinary collaboration is recommended to facilitate the use of CYP2C19 genotype–guided antiplatelet therapy in patients with cardiovascular and cerebrovascular diseases. Evolving clopidogrel pharmacogenetic evidence necessitates thoughtful iteration of implementation efforts and strategies to optimize long-term maintenance and sustainability.
Patterns ofGrewia(Malvaceae) diversity across geographical scales in Africa and Madagascar
Authors: Karimi Nisa , Hanes Margaret M 
Published: January 2024

AbstractBackground and AimsQuantifying spatial species richness is useful to describe biodiversity patterns across broad geographical areas, especially in large, poorly known plant groups. We explore patterns and predictors of species richness across Africa in one such group, the palaeotropical genus Grewia L. (Malvaceae).MethodsGrewia species richness was quantified by extracting herbarium records from GBIF and Tropicos and creating geographical grids at varying spatial scales. We assessed predictors of species richness using spatial regression models with 30 environmental variables. We explored species co-occurrence in Madagascar at finer resolutions using Schoener’s index and compared species range sizes and International Union for Conservation of Nature status among ecoregions. Lastly, we derived a trait matrix for a subset of species found in Madagascar to characterize morphological diversity across space.Key ResultsGrewia species occur in 50 countries in Africa, with the highest number of species in Madagascar (93, with 80 species endemic). Species richness is highest in Madagascar, with ≤23 Grewia species in a grid cell, followed by coastal Tanzania/Kenya (≤13 species) and northern South Africa and central Angola (11 species each). Across Africa, higher species richness was predicted by variables related to aridity. In Madagascar, a greater range in environmental variables best predicted species richness, consistent with geographical grid cells of highest species richness occurring near biome/ecoregion transitions. In Madagascar, we also observe increasing dissimilarity in species composition with increasing geographical distance.ConclusionsThe spatial patterns and underlying environmental predictors that we uncover in Grewia represent an important step in our understanding of plant distribution and diversity patterns across Africa. Madagascar boasts nearly twice the Grewia species richness of the second most species-rich country in Africa, which might be explained by complex topography and environmental conditions across small spatial scales.
Correction of Rectus Abdominis Diastasis: A Prospective Comparative Study Between a New Suturable Polypropylene Mesh vs Polypropylene Standard Suture Plication
Authors: Marangi Giovanni Francesco , Gratteri Marco , Savani Luca , Porso Daniela , Cimmino Andrea , Arcari Lucrezia , Romano Fara Desiree , Segreto Francesco , Mirra Carlo , Persichetti Paolo 
Published: January 2024

Abstract

Background
Duramesh (Mesh Suture Inc., Chicago, IL) is a new suturing concept, combining the principles of mesh with the precision, flexibility, and versatility of a suture, suitable also for abdominal rectus diastasis (ARD) correction.

Objectives
This prospective research aimed to compare mesh with the standard polypropylene suture plication for rectus diastasis repair with regard to safety (infection, seroma, hematoma, surgical wound dehiscence, and fistula rates and hospital stay); effectiveness (ARD recurrence by ultrasound sonography, palpability of the muscular suture, surgical time, and postoperative pain evaluation); and satisfaction of the patients based on the BODY-Q, a patient-reported outcome measure.

Methods
Sixty-five of the initial 70 patients who underwent rectus diastasis repair with a 6-month follow-up were randomly divided into 2 groups, comprising 33 patients treated with Duramesh and 32 patients treated with standard 0 polypropylene suture plication. Data regarding infection, seroma, hematoma, surgical wound dehiscence, and fistula rates; hospital stay; ARD recurrence; palpability of the muscular suture; surgical time; postoperative pain evaluation (measured by visual analog scale, or VAS); and the BODY-Q were analyzed by Prism 9 (GraphPad Software Inc., San Diego, CA).

Results
No significant differences were reported between the 2 groups with regard to infection, seroma, hematoma, surgical wound dehiscence, and fistula rates and hospital stay. The mesh decreased the time required to perform plication compared with standard polypropylene detached sutures. No statistically significant differences were found with respect to the VAS and BODY-Q data.

Conclusions
Duramesh 0 application for rectus diastasis repair is safe and effective without compromising aesthetic improvement when compared with standard 0 polypropylene plication.

Level of Evidence: 2
Assembling spatial clustering framework for heterogeneous spatial transcriptomics data with GRAPHDeep
Authors: Liu Teng , Fang Zhaoyu , Li Xin , Zhang Lining , Cao Dong-Sheng , Li Min , Yin Mingzhu 
Published: January 2024

Abstract

Motivation
Spatial clustering is essential and challenging for spatial transcriptomics’ data analysis to unravel tissue microenvironment and biological function. Graph neural networks are promising to address gene expression profiles and spatial location information in spatial transcriptomics to generate latent representations. However, choosing an appropriate graph deep learning module and graph neural network necessitates further exploration and investigation.

Results
In this article, we present GRAPHDeep to assemble a spatial clustering framework for heterogeneous spatial transcriptomics data. Through integrating 2 graph deep learning modules and 20 graph neural networks, the most appropriate combination is decided for each dataset. The constructed spatial clustering method is compared with state-of-the-art algorithms to demonstrate its effectiveness and superiority. The significant new findings include: (i) the number of genes or proteins of spatial omics data is quite crucial in spatial clustering algorithms; (ii) the variational graph autoencoder is more suitable for spatial clustering tasks than deep graph infomax module; (iii) UniMP, SAGE, SuperGAT, GATv2, GCN, and TAG are the recommended graph neural networks for spatial clustering tasks; and (iv) the used graph neural network in the existent spatial clustering frameworks is not the best candidate. This study could be regarded as desirable guidance for choosing an appropriate graph neural network for spatial clustering.

Availability and implementation
The source code of GRAPHDeep is available at https://github.com/narutoten520/GRAPHDeep. The studied spatial omics data are available at https://zenodo.org/record/8141084.
DESpace: spatially variable gene detection via differential expression testing of spatial clusters
Authors: Cai Peiying , Robinson Mark D , Tiberi Simone 
Published: January 2024

Abstract

Motivation
Spatially resolved transcriptomics (SRT) enables scientists to investigate spatial context of mRNA abundance, including identifying spatially variable genes (SVGs), i.e. genes whose expression varies across the tissue. Although several methods have been proposed for this task, native SVG tools cannot jointly model biological replicates, or identify the key areas of the tissue affected by spatial variability.

Results
Here, we introduce DESpace, a framework, based on an original application of existing methods, to discover SVGs. In particular, our approach inputs all types of SRT data, summarizes spatial information via spatial clusters, and identifies spatially variable genes by performing differential gene expression testing between clusters. Furthermore, our framework can identify (and test) the main cluster of the tissue affected by spatial variability; this allows scientists to investigate spatial expression changes in specific areas of interest. Additionally, DESpace enables joint modeling of multiple samples (i.e. biological replicates); compared to inference based on individual samples, this approach increases statistical power, and targets SVGs with consistent spatial patterns across replicates. Overall, in our benchmarks, DESpace displays good true positive rates, controls for false positive and false discovery rates, and is computationally efficient.

Availability and implementation
DESpace is freely distributed as a Bioconductor R package at https://bioconductor.org/packages/DESpace.
scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution
Authors: Chen Zeyu , Miao Yuxin , Tan Zhiyuan , Hu Qifan , Wu Yanhong , Li Xinqi , Guo Wenbo , Gu Jin 
Published: January 2024

Abstract

Summary
Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular compositions in the tumor microenvironment (TME). As previous studies have defined many meaningful cell subtypes in several tumor types, there is a great need to computationally transfer these labels to new datasets. Also, different studies used different approaches or criteria to define the cell subtypes for the same major cell lineages. The relationships between the cell subtypes defined in different studies should be carefully evaluated. In this updated package scCancer2, designed for integrative tumor scRNA-seq data analysis, we developed a supervised machine learning framework to annotate TME cells with annotated cell subtypes from 15 scRNA-seq datasets with 594 samples in total. Based on the trained classifiers, we quantitatively constructed the similarity maps between the cell subtypes defined in different references by testing on all the 15 datasets. Secondly, to improve the identification of malignant cells, we designed a classifier by integrating large-scale pan-cancer TCGA bulk gene expression datasets and scRNA-seq datasets (10 cancer types, 175 samples, 663 857 cells). This classifier shows robust performances when no internal confidential reference cells are available. Thirdly, scCancer2 integrated a module to process the spatial transcriptomic data and analyze the spatial features of TME.

Availability and implementation
The package and user documentation are available at http://lifeome.net/software/sccancer2/ and https://doi.org/10.5281/zenodo.10477296.
Many-core algorithms for high-dimensional gradients on phylogenetic trees
Authors: Gangavarapu Karthik , Ji Xiang , Baele Guy , Fourment Mathieu , Lemey Philippe , Matsen Frederick A , Suchard Marc A 
Published: January 2024

Abstract

Motivation
Advancements in high-throughput genomic sequencing are delivering genomic pathogen data at an unprecedented rate, positioning statistical phylogenetics as a critical tool to monitor infectious diseases globally. This rapid growth spurs the need for efficient inference techniques, such as Hamiltonian Monte Carlo (HMC) in a Bayesian framework, to estimate parameters of these phylogenetic models where the dimensions of the parameters increase with the number of sequences N. HMC requires repeated calculation of the gradient of the data log-likelihood with respect to (wrt) all branch-length-specific (BLS) parameters that traditionally takes O(N2) operations using the standard pruning algorithm. A recent study proposes an approach to calculate this gradient in O(N), enabling researchers to take advantage of gradient-based samplers such as HMC. The CPU implementation of this approach makes the calculation of the gradient computationally tractable for nucleotide-based models but falls short in performance for larger state-space size models, such as Markov-modulated and codon models. Here, we describe novel massively parallel algorithms to calculate the gradient of the log-likelihood wrt all BLS parameters that take advantage of graphics processing units (GPUs) and result in many fold higher speedups over previous CPU implementations.

Results
We benchmark these GPU algorithms on three computing systems using three evolutionary inference examples exploring complete genomes from 997 dengue viruses, 62 carnivore mitochondria and 49 yeasts, and observe a &gt;128-fold speedup over the CPU implementation for codon-based models and &gt;8-fold speedup for nucleotide-based models. As a practical demonstration, we also estimate the timing of the first introduction of West Nile virus into the continental Unites States under a codon model with a relaxed molecular clock from 104 full viral genomes, an inference task previously intractable.

Availability and implementation
We provide an implementation of our GPU algorithms in BEAGLE v4.0.0 (https://github.com/beagle-dev/beagle-lib), an open-source library for statistical phylogenetics that enables parallel calculations on multi-core CPUs and GPUs. We employ a BEAGLE-implementation using the Bayesian phylogenetics framework BEAST (https://github.com/beast-dev/beast-mcmc).
A note on minimax robustness of designs against correlated or heteroscedastic responses
Authors: Wiens D P 
Published: January 2024

Abstract
We present a result according to which certain functions of covariance matrices are maximized at scalar multiples of the identity matrix. This is used to show that experimental designs that are optimal under an assumption of independent, homoscedastic responses can be minimax robust, in broad classes of alternate covariance structures. In particular, it can justify the common practice of disregarding possible dependence, or heteroscedasticity, at the design stage of an experiment.
LT and SOX9 expression are associated with gene sets that distinguish Merkel cell polyomavirus (MCPyV)-positive and MCPyV-negative Merkel cell carcinoma
Authors: Torre-Castro Juan , Rodríguez Marta , Alonso-Alonso Ruth , Mendoza Cembranos María Dolores , Díaz-Alejo Jesús Frutos , Rebollo-González Marcos , Borregón Jennifer , Nájera Botello Laura , Mahillo-Fernández Ignacio , Samimi Mathab , Kervarrec Thibault , Requena Luis , Piris Miguel Ángel 
Published: January 2024

Abstract

Background
Merkel cell carcinoma (MCC) is an aggressive malignant neuroendocrine tumour. There are two subsets of MCC, one related to Merkel cell polyomavirus (MCPyV) and the other to ultraviolet radiation (UVR). MCPyV-positive and MCPyV-negative MCCs have been considered to be different tumours, as the former harbour few DNA mutations and are not related to UVR, and the latter usually arise in sun-exposed areas and may be found in conjunction with other keratinocytic tumours, mostly squamous cell carcinomas. Two viral oncoproteins, large T antigen (LT; coded by MCPyV_gp3) and small T antigen (sT; coded by MCPyV_gp4), promote different carcinogenic pathways.

Objectives
To determine which genes are differentially expressed in MCPyV-positive and MCPyV-negative MCC; to describe the mutational burden and the most frequently mutated genes in both MCC subtypes; and to identify the clinical and molecular factors that may be related to patient survival.

Methods
Ninety-two patients with a diagnosis of MCC were identified from the medical databases of participating centres. To study gene expression, a customized panel of 172 genes was developed. Gene expression profiling was performed with nCounter technology. For mutational studies, a customized panel of 26 genes was designed. Somatic single nucleotide variants (SNVs) were identified following the GATK Best Practices workflow for somatic mutations.

Results
The expression of LT enabled the series to be divided into two groups (LT positive, n = 55; LT negative, n = 37). Genes differentially expressed in LT-negative patients were related to epithelial differentiation, especially SOX9, or proliferation and the cell cycle (MYC, CDK6), among others. Congruently, LT displayed lower expression in SOX9-positive patients, and differentially expressed genes in SOX9-positive patients were related to epithelial/squamous differentiation. In LT-positive patients, the mean SNV frequency was 4.3; in LT-negative patients it was 10 (P = 0.03). On multivariate survival analysis, the expression of SNAI1 [hazard ratio (HR) 1.046, 95% confidence interval (CI) 1.007–1.086; P = 0.02] and CDK6 (HR 1.049, 95% CI 1.020–1.080; P = 0.001) were identified as risk factors.

Conclusions
Tumours with weak LT expression tend to co-express genes related to squamous differentiation and the cell cycle, and to have a higher mutational burden. These findings are congruent with those of earlier studies.