bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nonadherence to Immunosuppressant Therapy of Kidney Transplant Candidate Patients: External Validation of the KATITA-25 Scale
Authors: de Medeiros Oliveira Luana Cristina Lins , Martins Rand Randall , de Oliveira Renata Borges , da Nóbrega Ítala Morgânia Farias , de Medeiros Batista Lorena , Moreira Francisca Sueli Monte , de Andrade Cinthya Cavalcante , Tavares Raquel Padilha Martins , de Vasconcelos Alan Lucena , Oliveira Antonio Gouveia 
Published: March 2024

Background.
The self-administered Kidney AlloTransplant Immunosuppressive Therapy Adherence (KATITA-25) questionnaire is a multidimensional scale for use in the pretransplant setting that evaluates the predisposition to nonadherence of patients who are candidates to kidney transplant. The scale has shown adequate internal consistency and test–retest reliability. This study presents the results of an external validation study of the KATITA-25 scale.

Methods.
Patients >18 y old scheduled for kidney transplant were included in this multicenter study. The KATITA-25 scale was administered before surgery and then at 3-mo posttransplantation for evaluation of scale sensitivity to change. At this time, 2 validated medication adherence scales were applied for assessment of concurrent validity. For evaluation of predictive validity, nonadherence to immunosuppressive medication was assessed at 6 and 12 mo after transplantation by 3 independent methods: patient self-report of nonadherence using the Morisky-Green-Levine Medication Assessment Questionnaire scale, serum trough levels of immunosuppressants, and pharmacy refills.

Results.
Three twenty-two patients were available for evaluation of concurrent validity and 311 patients of predictive validity. After kidney transplant, the median KATITA-25 score decreased from 20 to 8 (P < 0.001), demonstrating scale sensitivity to change, and the KATITA-25 score showed correlation with the Basel Assessment of Adherence to Immunosuppressive Medication Scale score (Spearman’s ρ 0.18, P = 0.002) and the Cuestionario para la Evaluación de la Adhesión al Tratamiento Antiretroviral scores (ρ −0.17, P = 0.002), confirming concurrent validity. The nonadherence rate was 57.6%. The scale predictive validity was demonstrated by the area under the receiver operating characteristics curve (0.68), sensitivity (59.8%), specificity (68.2%), and positive predictive value (71.8%).

Conclusions.
This external validation study of KATITA-25 scale provided evidence of sensitivity to change, and structural, criterion, and predictive validity.
Correlation of the Endoscopic Gastroesophageal Flap Valve with Pathologic Reflux
Authors: Manasa Morgan , Galvin Katie , Fazl Alizadeh Reza , Ruhi-Williams Perisa , Choi Alyssa , Samarasena Jason , Chang Kenneth , Nguyen Ninh T 
Published: March 2024

BACKGROUND:
The Hill classification characterizes the geometry of gastroesophageal junction and Hill grades (HGs) III and IV have a high association with pathologic reflux. This study aimed to understand the use of the Hill classification and correlate the prevalence of pathologic reflux across different HGs.

STUDY DESIGN:
A retrospective review of 477 patients who underwent upper endoscopy and BRAVO pH monitoring between August 2018 and October 2021 was performed. These charts were reviewed for endoscopic findings for hiatal hernia and association of HGs with pathologic reflux, defined as an abnormal esophageal acid exposure time (AET) of ≥4.9%.

RESULTS:
Of 477 patients, 252 (52.8%) had an HG documented on the endoscopy report. Of the 252 patients, 61 had HG I (24.2%), 100 had HG II (39.7%), 61 had HG III (24.2%), and 30 had HG IV (11.9%). The proportion of patients with abnormal AET increases with increasing HGs (p < 0.001) as follows: I (39.3%), II (52.5%), III (67.2%), and IV (79.3%). The mean overall AET is as follows: HG I (5.5 ± 6%), HG II (7.0 ± 5.9%), HG III (10.2 ± 10.3%), and HG IV (9.5 ± 5.5%). The proportion of patients with hiatal hernia was 18% for HG I, 28% for HG II, 39.3% for HG III, and 80% for HG IV.

CONCLUSIONS:
Use of the Hill classification in clinical practice is low. There is an association of increasing HGs with increasing proportion of patients with abnormal AET. There is a high proportion of patients within HGs I and II with documented pathologic reflux and the presence of a hiatal hernia as observed on endoscopic examination. Our study suggests that endoscopic grading of the gastroesophageal junction may not adequately differentiate between normal vs abnormal reflux status, particularly for HGs I and II.
Development of a First-in-Class RIPK1 Degrader to Enhance Antitumor Immunity
Authors: Yu Xin , Lu Dong , Qi Xiaoli , Lin Hanfeng , Holloman Bryan L. , Jin Feng , Xu Longyong , Ding Lang , Peng Weiyi , Wang Meng C. , Chen Xi , Wang Jin 
Published: March 2024

AbstractThe scaffolding function of receptor interacting protein kinase 1 (RIPK1) confers intrinsic and extrinsic resistance to immune checkpoint blockades (ICBs) and has emerged as a promising target for improving cancer immunotherapies. To address the challenge posed by a poorly defined binding pocket within the intermediate domain, we harnessed proteolysis targeting chimera (PROTAC) technology to develop a first-in-class RIPK1 degrader, LD4172. LD4172 exhibited potent and selective RIPK1 degradation bothin vitroandin vivo. Degradation of RIPK1 by LD4172 triggered immunogenic cell death (ICD) and enriched tumor-infiltrating lymphocytes and substantially sensitized the tumors to anti-PD1 therapy. This work reports the first RIPK1 degrader that serves as a chemical probe for investigating the scaffolding functions of RIPK1 and as a potential therapeutic agent to enhance tumor responses to immune checkpoint blockade therapy.
Spatial and temporal characteristics of laboratory-inducedAnopheles coluzziiswarms: shape, structure and flight kinematics
Authors: Poda Bèwadéyir Serge , Cribellier Antoine , Feugère Lionel , Fatou Mathurin , Nignan Charles , Hien Domonbabele François de Sale , Müller Pie , Gnankiné Olivier , Dabiré Roch Kounbobr , Diabaté Abdoulaye , Muijres Florian T. , Roux Olivier 
Published: March 2024

AbstractAnophelesmosquitoes mate at sunset in aerial swarms. The development of mating-based methods for effective malaria vector control requires a good knowledge of the flight behaviour ofAnophelesspecies in mating swarms. However, the process of how swarms are formed and maintained remains poorly understood. Here, we characterized the three-dimensional spatial and temporal flight kinematics ofAnopheles coluzziimales swarming above a ground marker. We observed that the location, shape and volume of swarms were highly stereotypic, consistent over the swarming duration, regardless of the number of individuals in the swarm. The swarm had an elliptical cone shape, and we observed a differential spatial distribution of flight kinematics parameters within the swarm volume. Among these parameters, only swarm density varied with swarm size. Using a sensory system-informed model, we show that swarm location and shape can accurately be modelled based on visual perception of the marker. To control swarm height, swarming individuals maintain an optical angle of the marker ranging from 24° to 55°. Limiting the viewing angle deviation to 4.5% of the maximum value results in the observed elliptical cone swarm shape. We discuss the implications of these finding in mating success, speciation and for vector control.
py_ped_sim - A flexible forward genetic simulator for complex family pedigree analysis
Authors: Guardado Miguel , Perez Cynthia , Jackson Shalom , Magaña Joaquín , Campana Sthen , Samperio Emily , Rojas Berenice Chavez , Hernandez Selena , Syas Kaela , Hernandez Ryan , Zavala Elena I. , Rohlfs Rori 
Published: March 2024

AbstractBackgroundLarge-scale family pedigrees are commonly used across medical, evolutionary, and forensic genetics. These pedigrees are tools for identifying genetic disorders, tracking evolutionary patterns, and establishing familial relationships via forensic genetic identification. However, there is a lack of software to accurately simulate different pedigree structures along with genomes corresponding to those individuals in a family pedigree. This limits simulation-based evaluations of methods that use pedigrees.ResultsWe have developed a python command-line-based tool called py_ped_sim that facilitates the simulation of pedigree structures and the genomes of individuals in a pedigree. py_ped_sim represents pedigrees as directed acyclic graphs, enabling conversion between standard pedigree formats and integration with the forward population genetic simulator, SLiM. Notably, py_ped_sim allows the simulation of varying numbers of offspring for a set of parents, with the capacity to shift the distribution of sibship sizes over generations. We additionally add simulations for events of misattributed paternity, which offers a way to simulate half-sibling relationships. We validated the accuracy of our software by simulating genomes onto diverse family pedigree structures, showing that the estimated kinship coefficients closely approximated expected values.Conclusionspy_ped_sim is a user-friendly and open-source solution for simulating pedigree structures and conducting pedigree genome simulations. It empowers medical, forensic, and evolutionary genetics researchers to gain deeper insights into the dynamics of genetic inheritance and relatedness within families.
Systematic Evaluation of Cell Type Deconvolution Methods for Plasma Cell-free DNA
Authors: Sun Tongyue , Yuan Jinqi , Zhu Yacheng , Yang Shen , Zhou Junpeng , Ge Xinzhou , Qu Susu , Li Wei , Li Jingyi Jessica , Li Yumei 
Published: March 2024

AbstractPlasma cell-free DNA (cfDNA) is derived from cellular death in various tissues. Investigating the origin of cfDNA through tissue/cell type deconvolution allows us to detect changes in tissue homeostasis that occur during disease progression or in response to treatment. Consequently, cfDNA has emerged as a valuable noninvasive biomarker for disease detection and treatment monitoring. Although there are numerous methylation-based methods of cfDNA cell type deconvolution available, a comprehensive and systematic evaluation of these methods has yet to be conducted. In this study, we thoroughly benchmarked five previously published methods: MethAtlas, cfNOMe, CelFiE, CelFEER, and UXM. Utilizing deep whole-genome bisulfite sequencing data from 35 human cell types, we generated cfDNA mixtures with known ground truth to assess the deconvolution performance under various scenarios. Our findings indicate that different factors, including sequencing depth, reference marker selection, and reference completeness, influence cell type deconvolution performance. Notably, omitting cell types present in a mixture from the reference leads to suboptimal results. Despite each method exhibited distinct performances under various scenarios, CelFEER and UXM exhibit overall superior performance compared to the others. In summary, we comprehensively evaluated factors influencing methylation-based cfDNA cell type deconvolution and proposed general guidelines to maximize the performance.
Aging-associated long non-coding RNA boosts longevity and reduces the ribosome content of non-dividing fission yeast cells
Authors: Anver Shajahan , Sumit Ahmed Faisal , Sun Xi-Ming , Hatimy Abubakar , Thalassinos Konstantinos , Marguerat Samuel , Alic Nazif , Bähler Jürg 
Published: March 2024

AbstractGenomes produce widespread long non-coding RNAs (lncRNAs) of largely unknown functions. We characterizeaal1(aging-associated lncRNA) which is induced in quiescent cells of fission yeast. Deletion ofaal1shortens the chronological lifespan of non-dividing cells, while ectopic overexpression ofaal1prolongs their lifespan, indicating that this lncRNA actsin trans. The overexpression ofaal1leads to the repression of ribosomal protein genes and inhibition of cell growth, andaal1genetically interacts with coding genes functioning in protein translation. Theaal1RNA localizes to the cytoplasm and associates with ribosomes. Notably,aal1deletion or overexpression is sufficient to increase or decrease the cellular ribosome content. Therpl1901mRNA, encoding a ribosomal protein, is a binding target ofaal1.The levels ofrpl1901are reduced ∼2-fold byaal1,which is critical and sufficient to extend the lifespan. Remarkably, the expression ofaal1lncRNA inDrosophilatriggers an extension of fly lifespan. We propose thataal1reduces the ribosome content by decreasing the levels of Rpl1901, thus attenuating protein translation and promoting longevity. Although theaal1lncRNA itself is not conserved, its effect in flies raises the possibility that animals feature related mechanisms that modulate aging, based on the conserved translational machinery.
Mechanical cues of extracellular matrix determine tumor innervation
Authors: Jiang Shu-Heng , Zhang Shan , Cai Zhiwei , Yu Min-Hao , Li Hui , Jiang Luju , Cai Shuqi , Zhu Yuheng , Wang Hao , Huo Rui-Xue , Xia Xiang , Yao Hong-Fei , Zhu Lei , Zhang Xue-Li , Hu Li-Peng , Li Qing , Li Jun , Huo Yan-Miao , Hua Rong , Xue Junli , Jiang Chongyi , Sun Yong-Wei , Zhang Jun-Feng , Zhang Zi-Zhen , Liu De-Jun , Xiao Gary Gui-Shan , Zhang Zhi-Gang 
Published: March 2024

AbstractPeripheral tumors can establish local autonomic and sensory nerve networks, termed as tumor innervation (TIN), to support tumorigenesis and metastasis. While nerve dependence in cancers is well-established, the mechanisms governing TIN remain unclear. Here, we report that extracellular matrix (ECM) stiffness, a major mechanical abnormality in the tumor microenvironment (TME), is an essential contributor of TIN. In preclinical models, reducing lysyl oxidase-mediated ECM crosslinking lowers tissue stiffness and TIN in pancreatic cancer, while inflammation-induced matrix stiffening boosts the hyperinnervation of the pancreatic precursor lesions. Mechanistically, β1-containing integrins sense the mechanical cues exerted by ECM stiffness, and the translational co-activator YAP1 acts as an essential nuclear relay to induce the expression of neurotropic genes, particularly brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF). 3D imaging of the whole cleared pancreas reveals that blockade of mechanosensor integrin β1 or pharmacological inhibition of the mechanotransducer YAP1 effectively reduces TIN. In clinical settings, tumor samples with a dense, crosslinked, and stiffened ECM exhibit significant TIN. In summary, these findings identify ECM stiffness as an important driver of TIN and suggest that targeting integrin β1/YAP1-dependent mechanotransduction may counteract TIN.
IFNγ-dependent remodelling of the myeloid landscape underlies control of IFNγ-insensitive tumours
Authors: Lau Vivian W.C. , Mead Gracie , Mazet Julie M. , Krishnan Anagha , Roberts Edward W. , Prota Gennaro , Gileadi Uzi , Cerundolo Vincenzo , Gérard Audrey 
Published: March 2024

AbstractLoss of IFNγ-sensitivity by tumours is thought to be a mechanism enabling evasion, as some cancers lacking IFNγ-signalling demonstrate resistance to checkpoint immunotherapy. However, recent studies demonstrated that IFNγ-resistant tumours are well-controlled and sensitized for immunotherapy. The underlying mechanism leading to enhanced immune responses in those patients is unknown. Using IFNγ-insensitive melanoma tumours which were well-controlled by the endogenous anti-tumour response, we found that despite low basal MHC class I expression by tumours, CD8+T cell infiltration was not hindered and, unexpectedly, their production of IFNγ was still important for tumour control. Mechanistically, IFNγ triggers pro-inflammatory remodelling of IFNγ-insensitive tumours, affecting the differentiation of myeloid cells. Predominantly, immunosuppressive macrophages are inhibited, while inflammatory phenotypes of monocytes and ‘mono-macs’ are preserved in IFNγ-insensitive tumours. This is supported by a co-dependency between CD8+T cells and monocyte/macrophages, as depletion of one resulted in loss of the other. Our work demonstrates an important mechanistic understanding of how IFNγ resistance does not preclude failure of anti-tumour responses. Importantly, immune remodelling appears to be dominant in IFNγ-sensitive and IFNγ-insensitive mixed tumours, and is enriched in humans with tumours mutated in the IFNγ pathway, suggesting this may be leveraged for therapy in the future.
Notch3is a genetic modifier of NODAL signalling for patterning asymmetry during mouse heart looping
Authors: Bønnelykke Tobias Holm , Chabry Marie-Amandine , Perthame Emeline , Desgrange Audrey , Meilhac Sigolène M. 
Published: March 2024

AbstractThe TGFβ secreted factor NODAL is a major left determinant required for the asymmetric morphogenesis of visceral organs, including the heart. Yet, when this signalling is absent, shape asymmetry, for example of the embryonic heart loop, is not fully abrogated, indicating that there are other factors regulating left-right patterning. Here, we used a tailored transcriptomic approach to screen for genes asymmetrically expressed in the field of heart progenitors. We thus identifyNotch3as a novel left-enriched gene and validate, by quantitative in situ hybridization, its transient asymmetry in the lateral plate mesoderm and node crown, overlapping withNodal. In mutant embryos, we analysed the regulatory hierarchy and demonstrate thatNodalin the lateral plate mesoderm amplifiesNotch3asymmetric expression. The function ofNotch3was uncovered in an allelic series of mutants. In single neonate mutants, we observe thatNotch3is required with partial penetrance for the development of ventricles, in addition to its known role in coronary arteries. In compound mutants, we reveal thatNotch3acts as a genetic modifier ofNodal, able to modulate heart looping direction and the curvature of the outflow tract. WhereasNotch3was previously associated with the CADASIL syndrome, its contribution to asymmetric organogenesis is now relevant to severe laterality defects such as the heterotaxy syndrome.
Teaching deep networks to see shape: Lessons from a simplified visual world
Authors: Jarvers Christian , Neumann Heiko 
Published: March 2024

AbstractDeep neural networks have been remarkably successful as models of the primate visual system. One crucial problem is that they fail to account for the strong shape-dependence of primate vision. Whereas humans base their judgements of category membership to a large extent on shape, deep networks rely much more strongly on other features such as color and texture. While this problem has been widely documented, the underlying reasons remain unclear. We design simple, artificial image datasets in which shape, color, and texture features can be used to predict the image class. By training networks to classify images with single features and feature combinations, we show that some network architectures are unable to learn to use shape features, whereas others are able to use shape in principle but are biased towards the other features. We show that the bias can be explained by the interactions between the weight updates for many images in mini-batch gradient descent. This suggests that different learning algorithms with sparser, more local weight changes are required to make networks more sensitive to shape and improve their capability to describe human vision.Author summaryWhen humans recognize objects, the cue they rely on most is shape. In contrast, deep neural networks mostly use local features like color and texture to classify images. We investigated how this difference arises, using images of simple shapes like rectangles and the letters L and T, combined with color and texture features. By testing different feature combinations, we show that some networks are generally unable to learn about shape, whereas others could learn to recognize shapes in isolation, but ignored shape if another feature was present. We show that this bias for color and texture arises from the way in which networks are trained: by averaging the learning signal over many images, the training algorithm favors simple features that are relatively similar in many images and removes sparser, more varied shape features. These insights can help build networks that are more sensitive to shape and work better as models of human vision.
Astrocytes mediate two forms of spike timing-dependent depression at entorhinal cortex-hippocampal synapses
Authors: Martínez-Gallego Irene , Coatl-Cuaya Heriberto , Rodríguez-Moreno Antonio 
Published: March 2024

AbstractThe entorhinal cortex (EC) connects to the hippocampus sending different information from cortical areas that is first processed at the dentate gyrus (DG) including spatial, limbic, and sensory information. Excitatory afferents from lateral (LPP) and medial (MPP) perforant pathways of the EC connecting to granule cells of the DG play a role in memory encoding and information processing and are deeply affected in humans suffering Alzheimeŕs disease and temporal lobe epilepsy, contributing to the dysfunctions found in these pathologies. The plasticity of these synapses is not well known yet, as are not known the forms of long-term depression (LTD) existing at those connections. We investigated whether spike timing-dependent long-term depression (t-LTD) exists at these two different EC-DG synaptic connections in mice, and whether they have different action mechanisms. We have found two different forms of t-LTD, at LPP- and MPP-GC synapses and characterised their cellular and intracellular mechanistic requirements. We found that both forms of t-LTD are expressed presynaptically and that whereas t-LTD at LPP-GC synapses does not require NMDAR, t-LTD at MPP-GC synapses requires ionotropic NMDAR containing GluN2A subunits. The two forms of t-LTD require different group I mGluR, mGluR5 LPP-GC synapses and mGluR1 MPP-GC synapses. In addition, both forms of t-LTD require postsynaptic calcium, eCB synthesis, CB1R, astrocyte activity, and glutamate released by astrocytes. Thus, we discovered two novel forms of t-LTD that require astrocytes at EC-GC synapses.
Water position prediction with SE(3)-Graph Neural Network
Authors: Park Sangwoo 
Published: March 2024

AbstractMost protein molecules exist in a water medium and interact with numerous water molecules. Consideration of interactions between protein molecules and water molecules is essential to understanding the functions of the protein. In computational studies on protein functions, either implicit solvation or explicit solvation methods are used to consider the effect of water on the protein. Implicit solvation methods consider water as a continuous solvent and have lower computational costs than explicit methods that consider water as a collection of individual water molecules. However, some water molecules have specific interactions with protein molecules, which are critical to protein function and require explicit treatment to consider these specific interactions. Thus, as a compromise between computational cost and consideration of specific interactions, hybrid methods use explicit consideration of water molecules with specific interaction with protein molecules while considering other water molecules implicitly. Prediction of the water positions having specific interaction is required to perform such hybrid methods, where various water position prediction methods have been developed. However, currently developed water position prediction methods still require considerable computational cost. Here, we present a water position prediction method with low computational cost and state-of-the-art prediction performance by utilizing SE(3)-an equivariant graph neural network. The introduction of a graph neural network enabled the consideration of the atom as a single data point, which makes computational costs less than our previous water prediction method using a convolutional neural network, which considers an atom as multiple data points. Our new water position prediction method, WatGNN, showed an average computation time of 1.86 seconds while maintaining state-of-the-art prediction performance. The source code of this water prediction method is freely available athttps://github.com/shadow1229/WatGNN.