bluuebunny/crossref_metadata_2025_split huggingface dataset:
Liver transplantation provides survival benefit at all levels of frailty: From the Multicenter Functional Assessment in Liver Transplantation Study
Authors: Wang Melinda , Chiou Sy Han , Ganger Daniel , Ruck Jessica , Huang Chiung-Yu , Kappus Matthew R. , King Elizabeth A. , Ladner Daniela P. , Rahimi Robert S. , Duarte-Rojo Andres , Volk Michael L. , Tevar Amit D. , Verna Elizabeth C. , Lai Jennifer C. 
Published: July 2024

Background and Aims:
Offering LT to frail patients may reduce waitlist mortality but may increase post-LT mortality. LT survival benefit is the concept of balancing these risks. We sought to quantify the net survival benefit with LT by liver frailty index (LFI).

Approach and Results:
We analyzed data in the multicenter Functional Assessment in LT (FrAILT) study from 2012 to 2021. Pre-LT cohort included ambulatory patients with cirrhosis awaiting LT, without HCC; the post-LT cohort included those who underwent LT. Primary outcomes were pre-LT and post-LT mortality. We computed 1-, 3-, and 5-year restricted mean survival times (RMSTs) from adjusted Cox models. The survival benefit was calculated as a net gain in life-years with LT. Pre-LT cohort included 2628 patients: median Model for End-Stage Liver Disease-Sodium was 18 (IQR: 14–22); 731 (28%) were frail; 440 (17%) died before LT. Post-LT cohort included 1335 patients: median Model for End-Stage Liver Disease-Sodium was 20 (IQR: 14–24); 325 (24%) were frail; 103 (8%) died after LT. Pre-LT RMST decreased substantially as LFI increased. Post-LT RMST also decreased as LFI increased but only modestly. There was no LFI threshold at which pre-LT and post-LT RMST intersected—patients had net survival benefits at all LFI values.

Conclusions:
Pre-LT and, to a lesser degree, post-LT mortality increased as LFI increased. Transplant offered a survival benefit at all LFI values, driven by a reduction in pre-LT mortality. No threshold of LFI was identified at which the risk of post-LT mortality exceeded pre-LT mortality. LT offers net survival benefits even in the presence of advanced frailty among those selected for LT.
The Effect of Postoperative Sleeping Position on Knee Extension and Range of Motion Following Primary Total Knee Arthroplasty
Authors: Goodwin Tyler M. , Brazier Brett G. , Cien Adam J. , Riggle Patrick K. , Popovich John M. , Penny Phillip C. , Cochran Jason M. 
Published: July 2024

Total knee arthroplasty (TKA) is an orthopaedic operation that improves quality of life and reduces pain in patients with disabling arthritis of the knee. One commonly recognized complication is flexion contracture of the knee. Early physical therapy helps prevent flexion contracture and improve range of motion (ROM) postoperatively. This study evaluated postoperative sleeping position and its effect on terminal knee extension and ROM following primary TKA. We hypothesized that patients who slept in the supine position would achieve earlier knee extension and greater ROM when compared to those in the lateral recumbent position. A total of 150 consecutive primary TKAs were performed by a single surgeon (J.M.C.) from April 2014 to December 2014. The data were collected prospectively to determine preoperative ROM, postoperative ROM, and sleeping position. Mean postoperative terminal extension ROM at 1 month was 2.9 degrees in the supine group versus 6.0 degrees (p< .001) in the lateral group. No significant demographic differences between the two groups at baseline were found. Our results demonstrate that sleeping position affects initial postoperative terminal extension, however, not overall ROM. We found a statistically significant difference in extension when comparing patients in the supine versus lateral group. Patients who slept in the lateral position lacked 6 degrees of extension which is greater than the 5 degrees needed for normal gait mechanics. Those in the supine group lacked 2.9 degrees of extension, allowing for normal gait mechanics. This study identifies an easy, effective means of increasing patients initial ability to achieve knee extension and satisfaction following TKA.
Quantitative Liver Imaging in Children
Authors: Yoon Haesung , Kim Jisoo , Lim Hyun Ji , Lee Mi-Jung 
Published: July 2024

Abstract
In children and adults, quantitative imaging examinations determine the effectiveness of treatment for liver disease. However, pediatric liver disease differs in presentation from liver disease in adults. Children also needed to be followed for a longer period from onset and have less control of their bodies, showing more movement than adults during imaging examinations, which leads to a greater need for sedation. Thus, it is essential to appropriately tailor and accurately perform noninvasive imaging tests in these younger patients. This article is an overview of updated imaging techniques used to assess liver disease quantitatively in children. The common initial imaging study for diffuse liver disease in pediatric patients is ultrasound. In addition to preexisting echo analysis, newly developed attenuation imaging techniques have been introduced to evaluate fatty liver. Ultrasound elastography is also now actively used to evaluate liver conditions, and the broad age spectrum of the pediatric population requires caution to be taken even in the selection of probes. Magnetic resonance imaging (MRI) is another important imaging tool used to evaluate liver disease despite requiring sedation or anesthesia in young children because it allows quantitative analysis with sequences such as fat analysis and MR elastography. In addition to ultrasound and MRI, we review quantitative imaging methods specifically for fatty liver, Wilson disease, biliary atresia, hepatic fibrosis, Fontan-associated liver disease, autoimmune hepatitis, sinusoidal obstruction syndrome, and the transplanted liver. Lastly, concerns such as growth and motion that need to be addressed specifically for children are summarized.
Inflammatory Neuropathy in Mouse and Primate Models of Colorectal Cancer
Authors: Gaffney Caitlyn M. , Casaril Angela M. , Mahmud Iqbal , Wei Bo , Valadez Karen M. , Kolb Elizabeth A. , Cherry Fisher R. , Guise Theresa A. , Lorenzi Philip L. , Shi Lei , Hodo Carolyn L. , Shepherd Andrew J. 
Published: July 2024

AbstractColorectal cancer survivors are at increased risk of developing neurological issues, particularly peripheral neuropathy and chronic pain. Although pre-existing neuropathy is a risk factor for chronic pain, tumor-induced neuropathy has not been firmly established in pre-clinical models. Consistent with clinical observations, we show that mice with colorectal cancer develop peripheral neuropathy, which was associated with subtle locomotor deficits, without overt hypersensitivity. We detected widespread differences in pro-inflammatory cytokines and lipid metabolites in peripheral nerves from tumor-bearing mice. Macrophage accumulation, myelin decompaction and ryanodine receptor oxidation were associated with dysfunctional calcium homeostasis and reduced spike amplitude in sensory neurons. Inflammatory neuropathy and macrophage accumulation were also observed in peripheral nerves of rhesus macaques with colorectal cancer. These findings suggest colorectal cancer is causally linked to a subacute form of chronic inflammatory demyelinating polyneuropathy across species, which may represent an under-reported, yet important risk factor for neurological dysfunction in colorectal cancer survivors.
The structure of full-length AFPK supports the ACP linker in a role that regulates iterative polyketide and fatty acid assembly
Authors: Schubert Heidi L , Li Feng , Hill Christopher P. , Schmidt Eric W. 
Published: July 2024

ABSTRACTWe present the full structures of two animal fatty acid synthase (FAS)-like polyketide synthases (AFPKs), PKS1 and PKS2 fromElysia chlorotica.Unlike the related FAS enzymes that use malonate to produce reduced lipids, EcPKS1 and EcPKS2 accept methylmalonyl-CoA to produce oxidized polypropionate products. When incubated with inhibitory malonyl-CoA (MC), the resulting EcPKS2(MC) structure revealed MC bound to the acyltransferase active site and the phosphopantetheinylated acyl carrier protein (ACP-pPant) bound to the ketosynthase (KS) active site. Remarkably, the entire linker from one modifying region to the ACP was visible in full-length EcPKS2(MC), revealing an asymmetric mega-enzyme structure. Mutations disrupting the affinity between the ACP linker and modifying domains altered substrate selectivity and active site selection, despite an expectation that the interactions are transient and that the wild-type linker alternates between the observed ordered and disordered conformations during the competing catalytic cycles of the homodimeric protein. A second structure, EcPKS2(AC), was acylated both on the KS catalytic cysteine and on the ACP-pPant. The ACP was docked at the dehydratase site, revealing further interactions between ACP and these FAS-like enzymes. The results suggest an unexpected role for the ACP linker in the control of substrate and product selectivity across the AFPK/FAS clade in animals and highlight ACP interfaces and mega-enzyme dynamics over the course of the catalytic cycle.
Gene expression changes in long-term memory unlikely to replicate in the long term
Authors: Mukamel Eran A. , Yu Zhaoxia 
Published: July 2024

SUMMARYIdentifying the cellular effects of memory-forming experiences on neurons which enable subsequent memory recall is a fundamental aim of neuroscience. The search for the engram could benefit from single cell RNA sequencing, which can estimate the mRNA expression of all genes in large samples of individual brain cells from animals exposed to specific experiences. A recent study used spatial transcriptomics and single cell RNA-sequencing to identify “transcriptional signatures in subpopulations of neurons and astrocytes that were memory-specific and persisted for weeks”1. However, because the authors did not account for multiple statistical comparisons2and instead used an “unadjusted” threshold for statistical significance, the reported findings are likely dominated by false positives3. Moreover, the statistical analysis treated individual cells as independent samples without accounting for correlations across cells derived from the same biological tissue sample. Reanalysis of the study’s data using appropriate, widely accepted statistical procedures, identifies no significant differentially expressed genes. This suggests the data do not support the author’s claim to have identified cell type-specific transcriptional signatures of memory in the mouse basolateral amygdala.
Sensitive Detection of Structural Differences using a Statistical Framework for Comparative Crystallography
Authors: Hekstra Doeke R. , Wang Harrison K. , Klureza Margaret A. , Greisman Jack B. , Dalton Kevin M. 
Published: July 2024

AbstractChemical and conformational changes underlie the functional cycles of proteins. Comparative crystallography can reveal these changes over time, over ligands, and over chemical and physical perturbations in atomic detail. A key difficulty, however, is that the resulting observations must be placed on the same scale by correcting for experimental factors. We recently introduced a Bayesian framework for correcting (scaling) X-ray diffraction data by combining deep learning with statistical priors informed by crystallographic theory. To scale comparative crystallography data, we here combine this framework with a multivariate statistical theory of comparative crystallography. By doing so, we find strong improvements in the detection of protein dynamics, element-specific anomalous signal, and the binding of drug fragments.
SOLeNNoID: A Deep Learning Pipeline For Solenoid Residue Detection in Protein Structures
Authors: Nikov Georgi , Pretorius Daniella , Murray James W. 
Published: July 2024

Solenoid proteins are a subset of tandem repeat proteins, which are structurally distinct from globular proteins. Solenoid proteins are defined by their modular, elongated structures, dependent on interactions between adjacent repeats. These proteins are found across all domains of life and have many important functions such as protein binding, enzymatic catalysis, ice binding and nucleic acid binding. Furthermore, engineered variants of solenoid proteins such as DARPins and designed PPR proteins have therapeutic commercial applications. In order to advance the study of natural solenoid proteins and the design of novel solenoid proteins, accurate tools for solenoid detection and annotation are required. As solenoid structures are more conserved than solenoid sequences and owing to recent developments in protein structure prediction, structure-based solenoid detection is preferred. Here we propose SOLeNNoID - a deep learning pipeline for solenoid residue prediction in protein structures. We cover all three solenoid sub-classes: alpha-, alpha/beta- and beta-solenoids. We use a CNN architecture to reason over protein distance matrices and compare our method to existing structure-based methods. Finally, we produce predictions on the entire PDB and demonstrate a 71 percent increase in solenoid-containing entries over the gold-standard RepeatsDB database using our method.GitHubhttps://github.com/gnik2018/SOLeNNoIDZenodoTBC
Confidence-Enhanced Semi-supervised Learning for Mediastinal Neoplasm Segmentation1
Authors: Fu Xiaotong , Zhang Shuying , Zhou Jing , Ji Ying 
Published: July 2024

AbstractAutomated segmentation of mediastinal neoplasms in preoperative computed tomography (CT) scans is critical for accurate diagnosis. Though convolutional neural networks (CNNs) have proven effective in medical imaging analysis, the segmentation of mediastinal neoplasms, which vary greatly in shape, size, and texture, presents a unique challenge due to the inherent local focus of convolution operations. To address this limitation, we propose a confidence-enhanced semi-supervised learning framework for mediastinal neoplasm segmentation. Specifically, we introduce a confidence-enhanced module that improves segmentation accuracy over indistinct tumor boundaries by assessing and excluding unreliable predictions simultaneously, which can greatly enhance the efficiency of exploiting unlabeled data. Additionally, we implement an iterative learning strategy designed to continuously refine the estimates of prediction reliability throughout the training process, ensuring more precise confidence assessments. Quantitative analysis on a real-world dataset demonstrates that our model significantly improves the performance by leveraging unlabeled data, surpassing existing semi-supervised segmentation benchmarks. Finally, to promote more efficient academic communication, the analysis code is publicly available athttps://github.com/fxiaotong432/CEDS.Author summaryIn clinical practice, computed tomography (CT) scans can aid in the detection and evaluation of mediastinal tumors. The early detection of mediastinal tumors plays a crucial role in formulating appropriate treatment plans and improving patient survival rates. To reduce the high cost of manual annotation, researchers have attempted to employ convolutional neural networks (CNNs) for efficient automatic segmentation. However, the significant challenges arise due to the considerable variation in shape, size, and texture of mediastinal tumors, posing difficulties for the segmentation task. In this study, we introduce a confidence-enhanced module with a semi-supervised learning framework. By evaluating the model’s prediction confidence and selecting high-confidence predictions, we improve the efficiency and quality of data utilization. This approach demonstrates the achievement of accurate mediastinal tumor segmentation with only a minimal amount of labeled data. Our research not only provides an effective technical approach for automatic segmentation of mediastinal tumors but also opens up new possibilities for optimizing strategies in semi-supervised learning methods.
Non-floral scent sources of orchid bees: observations and significance
Authors: Henske Jonas , De Dijn Bart P. E. , Eltz Thomas 
Published: July 2024

ABSTRACTMales of the neotropical orchid bees collect environmental volatiles to concoct complex species-specific perfumes that are later used in sexual communication. While perfumes are typically seen as being derived from floral sources, these bees also collect scents from non-floral resources such as decaying wood or tree wounds, even though reports of these sources remain scarce. Here we report observations of male orchid bees collecting scent at 21 different non-floral sources in Central and South America. MaleEufriesea coruscathat were marked at one of them, a woundedProtium raveniisecreting odoriferous sap/resin, returned repeatedly over periods of up to 19 days. Chemical analyses of hind-leg contents suggest that this single non-floral source accounted for a substantial fraction (>50%) of the species-specific perfume. This and other findings strengthen the view that non-floral scent sources play a central role in orchid bee perfume biology. Moreover, at the sameProtiumwe also observed femaleEuglossaspp. harvesting resin for nest construction. The collection of substances by both euglossine male and female bees at the same source strengthens the notion that the evolution of male perfume signaling was promoted by a sensory bias for resinous nest construction materials in females.
Evaluating the Anti-Tumor Efficacy and Safety of AEV01 in Glioblastoma and Hepatocellular Carcinoma: AnIn VitroandIn VivoApproach
Authors: Biswas Indrani , Precilla S Daisy , Kumar Aravinda , Sekhar MM , Medasani Renu , TS Anitha 
Published: July 2024

ABSTRACTGliomas and hepatocellular carcinoma (HCC) are aggressive cancers with poor prognoses, often leading to less than a year of survival. Therapeutic resistance underscores the need for novel therapeutic strategies. AEV01, derived fromPicrorhiza kurroa, has shown promise as a potential anticancer agent. In this context, the current study aimed to evaluate the anti-tumor efficacy and safety profile of AEV01 bothin vitroandin vivoin glioblastoma and HCC models. Briefly, cytotoxicity and apoptosis were assessed using MTT assays and AO/EtBr staining, while ELISA and immunofluorescence measured inflammatory markers, TP53 and CD36 expression.In vivo, ELISA was performed against the inflammatory and tumor suppressor markers while, histopathological analysis assessed tumor morphology and organ toxicity. AEV01 exhibited dose-dependent cytotoxicity against U-87 MG glioblastoma and HepG2 liver cancer cells, with optimal concentrations at 400 µg and 300 µg respectively. Treatment downregulated inflammatory markers, CD36 expression and concomitantly increased TP53 expression. Xenograft models depicted similar results, with reduced tumor markers expression, reduced tissue architecture, and no significant organ toxicity. Thus, AEV01 demonstrated potent anti-tumor activity with a favorable safety profile, suggesting its potential as a novel therapeutic agent for gliomas and HCC, warranting further clinical investigation.
Multi trait assessment of wheat variety mixtures performance and stability: mixtures for the win!
Authors: Stefan Laura , Strebel Silvan , Camp Karl-Heinz , Christinat Sarah , Fossati Dario , Städeli Christian , Levy Häner Lilia 
Published: July 2024

AbstractIn the current quest for a more sustainable, environment-friendly agriculture, variety mixtures are often suggested as a practical option to increase the stability of food production systems. Their effects on yield have been extensively researched, yet clear conclusions remain elusive, notably in terms of mechanistic processes and optimal variety combinations. Furthermore, in the case of wheat, yield is not the only component in the equation: grain quality is crucial for the bread value chain, yet the effects of variety mixtures on wheat quality and its stability have rarely been investigated. To that end, we conducted a multi-year, multi-site wheat variety mixture experiment investigating the role of variety mixtures on the performance and stability of five traits linked to grain yield and quality, and the mechanisms underlying these effects. Eight varieties were grown in pure stands and 2-variety mixtures, following a full diallel design. We considered the responses of grain yield, protein content, thousand kernel weight, hectoliter weight, and Zeleny sedimentation value. Results showed that mixtures generally outperformed pure stands in terms of global performance and stability for the 5 parameters. We particularly noticed an increase in quality stability and in Zeleny sedimentation value in mixtures, showing the potential of mixtures to improve crop quality. Moreover, we highlighted the important role of light interception for increased mixtures benefits. A more detailed investigation into individual mixture performances led us to some practical rules for optimal variety combinations: we advise combining varieties with similar heights and phenologies but different tillering abilities and yield potential. This study thus shows that variety mixtures represent a promising solution to sustainably increase the stability of wheat yield and quality. With practical recommendations, our results could benefit farmers but also processors and bakers, and promote the adoption of wheat variety mixtures.
Nuclease-Resistant L-DNA Tension Probes Enable Long-Term Force Mapping of Single Cells and Cell Consortia
Authors: Sethi Soumya , Xu Tao , Sarkar Aritra , Drees Christoph , Jacob Claire , Walther Andreas 
Published: July 2024

AbstractDNA-based tension probes with precisely programmable force response provide important insights into cellular mechanosensing. However, their degradability in cell culture limits their use for long-term imaging, for instance, when cells migrate, divide, and differentiate. This is a critical limitation for providing insights into mechanobiology for these longer-term processes. Here, we present DNA-based tension probes that are entirely designed based on the stereoisomer of biological D-DNA, i.e., L-DNA. We demonstrate that L-DNA tension probes are essentially indestructible by nucleases and provide days-long imaging without significant loss in image quality. We also show their superiority already for short imaging times commonly used for classical D-DNA tension probes. We showcase the potential of these resilient probes to image minute movements, and for generating long term force maps of single cells and for the first time, of collectively migrating cell populations.