bluuebunny/crossref_metadata_2025_split huggingface dataset:
Omega-3 PUFAs prevent bone impairment and bone marrow adiposity in mouse model of obesity
Authors: Benova Andrea , Ferencakova Michaela , Bardova Kristina , Funda Jiri , Prochazka Jan , Spoutil Frantisek , Cajka Tomas , Dzubanova Martina , Balcaen Tim , Kerckhofs Greet , Willekens Wouter , van Lenthe G. Harry , Charyyeva Arzuv , Alquicer Glenda , Pecinova Alena , Mracek Tomas , Horakova Olga , Coupeau Roman , Hansen Morten Svarer , Rossmeisl Martin , Kopecky Jan , Tencerova Michaela 
Published: October 2023

AbstractObesity adversely affects bone and fat metabolism in mice and humans. Omega-3 polyunsaturated fatty acids (omega-3 PUFAs) have been shown to improve glucose metabolism and bone homeostasis in obesity. However, the impact of omega-3 PUFAs on bone marrow adipose tissue (BMAT) and bone marrow stromal cell (BMSC) metabolism has not been intensively studied yet. In the present study we demonstrated that omega-3 PUFA supplementation in high fat diet (HFD + F) improved bone parameters, mechanical properties along with decreased BMAT in obese mice when compared to the HFD group. Primary BMSCs isolated from HFD + F mice showed decreased adipocyte and higher osteoblast differentiation with lower senescent phenotype along with decreased osteoclast formation suggesting improved bone marrow microenvironment promoting bone formation in mice. Thus, our study highlights the beneficial effects of omega-3 PUFA-enriched diet on bone and cellular metabolism and its potential use in the treatment of metabolic bone diseases.
The maximal and current accuracy of rigorous protein-ligand binding free energy calculations
Authors: Ross Gregory A. , Lu Chao , Scarabelli Guido , Albanese Steven K. , Houang Evelyne , Abel Robert , Harder Edward D. , Wang Lingle 
Published: October 2023

AbstractComputational techniques can speed up the identification of hits and accelerate the development of candidate molecules for drug discovery. Among techniques for predicting relative binding affinities, the most consistently accurate is free energy perturbation (FEP), a class of rigorous physics-based methods. However, uncertainty remains about how accurate FEP is and can ever be. Here, we present what we believe to be the largest publicly available dataset of proteins and congeneric series of small molecules, and assess the accuracy of the leading FEP workflow. To ascertain the limit of achievable accuracy, we also survey the reproducibility of experimental relative affinity measurements. We find a wide variability in experimental accuracy and a correspondence between binding and functional assays. When careful preparation of protein and ligand structures is undertaken, FEP can achieve accuracy comparable to experimental reproducibility. Throughout, we highlight reliable protocols that can help maximize the accuracy of FEP in prospective studies.
Ab-initio simulations of coherent phonon-induced pumping of carriers in zirconium pentatelluride
Authors: Jiang Tao , Orth Peter P. , Luo Liang , Wang Lin-Lin , Zhang Feng , Wang Cai-Zhuang , Zhao Jin , Ho Kai-Ming , Wang Jigang , Yao Yong-Xin 
Published: October 2023

AbstractLaser-driven coherent phonons can act as modulated strain fields and modify the adiabatic ground state topology of quantum materials. Here we use time-dependent first-principles and effective model calculations to simulate the effect of the coherent phonon induced by strong terahertz electric field on electronic carriers in the topological insulator ZrTe5. We show that a coherentA1gRaman mode modulation can effectively pump carriers across the band gap, even though the phonon energy is about an order of magnitude smaller than the equilibrium band gap. We reveal the microscopic mechanism of this effect which occurs via Landau–Zener-Stückelberg tunneling of Bloch electrons in a narrow region in the Brillouin zone center where the transient energy gap closes when the system switches from strong to weak topological insulator. The quantum dynamics simulation results are in excellent agreement with recent pump-probe experiments in ZrTe5at low temperature.
The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems
Authors: Biazzo Indaco 
Published: October 2023

AbstractAutoregressive Neural Networks (ARNNs) have shown exceptional results in generation tasks across image, language, and scientific domains. Despite their success, ARNN architectures often operate as black boxes without a clear connection to underlying physics or statistical models. This research derives an exact mapping of the Boltzmann distribution of binary pairwise interacting systems in autoregressive form. The parameters of the ARNN are directly related to the Hamiltonian’s couplings and external fields, and commonly used structures like residual connections and recurrent architecture emerge from the derivation. This explicit formulation leverages statistical physics techniques to derive ARNNs for specific systems. Using the Curie–Weiss and Sherrington–Kirkpatrick models as examples, the proposed architectures show superior performance in replicating the associated Boltzmann distributions compared to commonly used designs. The findings foster a deeper connection between physical systems and neural network design, paving the way for tailored architectures and providing a physical lens to interpret existing ones.
Establishment of a transparent soil system to study Bacillus subtilis chemical ecology
Authors: Lozano-Andrade Carlos N , Nogueira Carla G , Henriksen Nathalie N S E , Wibowo Mario , Jarmusch Scott A , Kovács Ákos T 
Published: October 2023

Abstract
Bacterial secondary metabolites are structurally diverse molecules that drive microbial interaction by altering growth, cell differentiation, and signaling. Bacillus subtilis, a Gram-positive soil-dwelling bacterium, produces a wealth of secondary metabolites, among them, lipopeptides have been vastly studied by their antimicrobial, antitumor, and surfactant activities. However, the natural functions of secondary metabolites in the lifestyles of the producing organism remain less explored under natural conditions, i.e. in soil. Here, we describe a hydrogel-based transparent soil system to investigate B. subtilis chemical ecology under controllable soil-like conditions. The transparent soil matrix allows the growth of B. subtilis and other isolates gnotobiotically and under nutrient-controlled conditions. Additionally, we show that transparent soil allows the detection of lipopeptides production and dynamics by HPLC-MS, and MALDI-MS imaging, along with fluorescence imaging of 3-dimensional bacterial assemblages. We anticipate that this affordable and highly controllable system will promote bacterial chemical ecology research and help to elucidate microbial interactions driven by secondary metabolites.
Node authentication and encrypted data transmission in mobile ad hoc network using the swarm intelligence‐based secure ad‐hoc on‐demand distance vector algorithm
Authors: Patil Anita R. , Borkar Gautam M. 
Published: October 2023

AbstractIn a mobile ad hoc network (MANET), all nodes are communicated with one another across wireless networks to create a temporary network without the support of centralised management. Due to dynamic topology in MANET, secure routing is a crucial issue. The existing secure routing protocol and their security concerns are analysed in this work. The suggested Swarm Intelligence‐based Secure Ad‐hoc On‐demand Distance Vector (SIS‐AODV) algorithm offers security by applying a secret key and hash mechanism to prevent the involvement of malicious nodes in routing operations. A secure routing system of MANET guards against internal and external network attacks. The proposed SIS‐AODV algorithm consists of two sections: the secret key value generated by applying Elliptical Curve Cryptography (ECC)‐based algorithm and the PRESENT algorithm to encrypt the data packets. Besides, authentication and non‐repudiation are applied using the H‐PRESENT 128 algorithm. The PRESENT algorithm and H‐PRESENT 128 hash function require less computational power. Centralised management is optional in this scheme, so overhead decreases. The second section of SIS‐AODV consists of Ant Colony Grey Wolf Optimization over the AODV algorithm to improve network performance while implementing a security algorithm over MANET. Analysis results show maximum performance with a packet delivery ratio of 98% and throughput of 85%. In addition, end‐to‐end delay is reduced by up to 25%, and routing overhead decreases by up to 20%. Keywords: AODV, Elliptical Curve, PRESENT, H‐PRESENT, Euclidean Algorithm, ACO, GWO, Blackhole attack.
Characterization of diterpene synthase genes in Brachypodium distachyon, a monocotyledonous model plant, provides evolutionary insight into their multiple homologs in cereals
Authors: Shimada Takeru , Minato Shiho , Hasegawa Yuto , Miyamoto Koji , Minato Yasumasa , Shenton Matthew R , Okada Kazunori , Kawaide Hiroshi , Toyomasu Tomonobu 
Published: October 2023

ABSTRACT
Gibberellins are diterpenoid phytohormones that regulate plant growth, and are biosynthesized from a diterpene intermediate, ent-kaurene, which is produced from geranylgeranyl diphosphate via ent-copalyl diphosphate (ent-CDP). The successive 2 cyclization reactions are catalyzed by 2 distinct diterpene synthases, ent-CDP synthase (ent-CPS) and ent-kaurene synthase (KS). Various diterpene synthase genes involved in specialized metabolism were likely created through duplication and neofunctionalization of gibberellin-biosynthetic ent-CPS and KS genes in crops. Brachypodium distachyon is a monocotyledonous species that is a model plant in grasses. We herein found 1 ent-CPS gene homolog BdCPS and 4 tandemly arrayed KS-like genes BdKS1, KSL2, KSL3, and KSL4 in the B. distachyon genome, a simpler collection of paralogs than in crops. Phylogenetic and biochemical analyses showed that BdCPS and BdKS1 are responsible for gibberellin biosynthesis. BdKSL2 and BdKSL3 are suggested to be involved in specialized diterpenoid metabolism. Moreover, we restored KS activity of BdKSL2 through amino acid substitution.
PreHom-PCLM: protein remote homology detection by combing motifs and protein cubic language model
Authors: Shao Jiangyi , Zhang Qi , Yan Ke , Liu Bin 
Published: October 2023

Abstract
Protein remote homology detection is essential for structure prediction, function prediction, disease mechanism understanding, etc. The remote homology relationship depends on multiple protein properties, such as structural information and local sequence patterns. Previous studies have shown the challenges for predicting remote homology relationship by protein features at sequence level (e.g. position-specific score matrix). Protein motifs have been used in structure and function analysis due to their unique sequence patterns and implied structural information. Therefore, designing a usable architecture to fuse multiple protein properties based on motifs is urgently needed to improve protein remote homology detection performance. To make full use of the characteristics of motifs, we employed the language model called the protein cubic language model (PCLM). It combines multiple properties by constructing a motif-based neural network. Based on the PCLM, we proposed a predictor called PreHom-PCLM by extracting and fusing multiple motif features for protein remote homology detection. PreHom-PCLM outperforms the other state-of-the-art methods on the test set and independent test set. Experimental results further prove the effectiveness of multiple features fused by PreHom-PCLM for remote homology detection. Furthermore, the protein features derived from the PreHom-PCLM show strong discriminative power for proteins from different structural classes in the high-dimensional space. Availability and Implementation: http://bliulab.net/PreHom-PCLM.
JCcirc: circRNA full-length sequence assembly through integrated junction contigs
Authors: Zhang Jingjing , Zhang Huiling , Ju Zhen , Peng Yin , Pan Yi , Xi Wenhui , Wei Yanjie 
Published: October 2023

Abstract
Recent studies have shed light on the potential of circular RNA (circRNA) as a biomarker for disease diagnosis and as a nucleic acid vaccine. The exploration of these functionalities requires correct circRNA full-length sequences; however, existing assembly tools can only correctly assemble some circRNAs, and their performance can be further improved. Here, we introduce a novel feature known as the junction contig (JC), which is an extension of the back-splice junction (BSJ). Leveraging the strengths of both BSJ and JC, we present a novel method called JCcirc (https://github.com/cbbzhang/JCcirc). It enables efficient reconstruction of all types of circRNA full-length sequences and their alternative isoforms using splice graphs and fragment coverage. Our findings demonstrate the superiority of JCcirc over existing methods on human simulation datasets, and its average F1 score surpasses CircAST by 0.40 and outperforms both CIRI-full and circRNAfull by 0.13. For circRNAs below 400 bp, 400–800 bp, 800 bp–1200 bp and above 1200 bp, the correct assembly rates are 0.13, 0.09, 0.04 and 0.03 higher, respectively, than those achieved by existing methods. Moreover, JCcirc also outperforms existing assembly tools on other five model species datasets and real sequencing datasets. These results show that JCcirc is a robust tool for accurately assembling circRNA full-length sequences, laying the foundation for the functional analysis of circRNAs.
One-year outcomes following operative or non-operative management of adhesional small bowel obstruction
Authors: Mortensen Marie R , Alouda Mohammad , Bond Zara , Burcharth Jakob , Finne Katrine F , Jensen Thomas K , Lolle Ida , Malik Talha , Ngo-Stuyt Loan , Nielsen Liv B J , Olausson Maria , Skovsen Anders P , Tolver Mette A , Smith Henry G 
Published: October 2023

Abstract

Background
A trial of initial non-operative management is recommended in stable patients with adhesional small bowel obstruction. However, recent retrospective studies have suggested that early operative management may be of benefit in reducing subsequent recurrences. This study aimed to compare recurrence rates and survival in patients with adhesional small bowel obstruction treated operatively or non-operatively.

Methods
This was a prospective cohort study conducted at six acute hospitals in Denmark, including consecutive patients admitted with adhesional small bowel obstruction over a 4-month interval. Patients were stratified into two groups according to their treatment (operative versus non-operative) and followed up for 1 year after their index admission. Primary outcomes were recurrence of small bowel obstruction and overall survival within 1 year of index admission.

Results
A total of 201 patients were included, 118 (58.7 per cent) of whom were treated operatively during their index admission. Patients undergoing operative treatment had significantly better 1-year recurrence-free survival compared with patients managed non-operatively (operative 92.5 per cent versus non-operative 66.6 per cent, P &lt;0.001). However, when the length of index admission was taken into account, patients treated non-operatively spent significantly less time admitted to hospital in the first year (median 3 days non-operative versus 6 days operative, P &lt;0.001). On multivariable analysis, operative treatment was associated with decreased risks of recurrence (HR 0.22 (95 per cent c.i. 0.10–0.48), P &lt;0.001) but an increased all-cause mortality rate (HR 2.48 (95 per cent c.i. 1.13–5.46), P = 0.024).

Conclusion
Operative treatment of adhesional small bowel obstruction is associated with reduced risks of recurrence but increased risk of death in the first year after admission.

Registration number
NCT04750811 (http://www.clinicaltrials.gov).prior (registration date: 11 February 2021).
Graded functional organization in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity
Authors: Diveica Veronica , Riedel Michael C , Salo Taylor , Laird Angela R , Jackson Rebecca L , Binney Richard J 
Published: October 2023

Abstract
The left inferior frontal gyrus has been ascribed key roles in numerous cognitive domains, such as language and executive function. However, its functional organization is unclear. Possibilities include a singular domain-general function, or multiple functions that can be mapped onto distinct subregions. Furthermore, spatial transition in function may be either abrupt or graded. The present study explored the topographical organization of the left inferior frontal gyrus using a bimodal data-driven approach. We extracted functional connectivity gradients from (i) resting-state fMRI time-series and (ii) coactivation patterns derived meta-analytically from heterogenous sets of task data. We then sought to characterize the functional connectivity differences underpinning these gradients with seed-based resting-state functional connectivity, meta-analytic coactivation modeling and functional decoding analyses. Both analytic approaches converged on graded functional connectivity changes along 2 main organizational axes. An anterior–posterior gradient shifted from being preferentially associated with high-level control networks (anterior functional connectivity) to being more tightly coupled with perceptually driven networks (posterior). A second dorsal–ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal functional connectivity), and with the semantic network, on the other (ventral). These results provide novel insights into an overarching graded functional organization of the functional connectivity that explains its role in multiple cognitive domains.
Prediction of misfolded proteins spreading in Alzheimer’s disease using machine learning and spreading models
Authors: Gherardini Luca , Zajdel Aleksandra , Pini Lorenzo , Crimi Alessandro 
Published: October 2023

Abstract
The pervasive impact of Alzheimer’s disease on aging society represents one of the main challenges at this time. Current investigations highlight 2 specific misfolded proteins in its development: Amyloid-$\beta$ and tau. Previous studies focused on spreading for misfolded proteins exploited simulations, which required several parameters to be empirically estimated. Here, we provide an alternative view based on 2 machine learning approaches which we compare with known simulation models. The first approach applies an autoregressive model constrained by structural connectivity, while the second is based on graph convolutional networks. The aim is to predict concentrations of Amyloid-$\beta$ 2 yr after a provided baseline. We also evaluate its real-world effectiveness and suitability by providing a web service for physicians and researchers. In experiments, the autoregressive model generally outperformed state-of-the-art models resulting in lower prediction errors. While it is important to note that a comprehensive prognostic plan cannot solely rely on amyloid beta concentrations, their prediction, achieved by the discussed approaches, can be valuable for planning therapies and other cures, especially when dealing with asymptomatic patients for whom novel therapies could prove effective.
Personalizing electrolytes in the dialysis prescription: what, why and how?
Authors: Dilaver R Gulsah , Ikizler T Alp 
Published: October 2023

ABSTRACT
Maintenance hemodialysis patients suffer from multiple comorbidities and treatment-related complications. A personalized approach to hemodialysis prescription could reduce some of these burdens by preventing complications such as excessive changes in blood pressure, arrhythmias, post-dialysis fatigue and decreased quality of life. A patient-centered approach to dialysate electrolyte concentrations represents one such opportunity. In addition to modifications in dialysate electrolyte concentrations, consideration of individual factors such as patients’ serum concentrations, medication profiles, nutritional status and comorbidities is critical to tailoring hemodialysis prescriptions to optimize patient outcomes. The development of personalized dialysis treatment depends on the collection of comprehensive patient data, advances in technology, resource allocation and patient involvement in decision-making. This review discusses how the treatment of maintenance hemodialysis patients could benefit from individualized changes in certain dialysis fluid components.
Intraventricular haemodynamic changes caused by increased left ventricular afterload in re-coarctation of aorta: a case report
Authors: Shibagaki Yuki , Oka Hideharu , Nakau Kouichi , Takahashi Satoru 
Published: October 2023

Abstract

Background
Long-term re-coarctation of the aorta can cause aortic dilatation, hypertension, and cardiac dysfunction due to increased left ventricular (LV) afterload. It is difficult to detect changes in LV function due to increased afterload if the contractile force of the left ventricle is maintained. Herein, we have reported a case of re-coarctation of the aorta, for which four-dimensional (4D) flow magnetic resonance imaging (MRI) scan was obtained both before and after balloon dilatation for aortic re-coarctation. Ultimately, improvement in aortic helical flow and LV haemodynamics was observed.

Case summary
A 29-year-old female was diagnosed with coarctation of the aorta and a bicuspid aortic valve after birth and underwent surgery at 1 month. At 8 years of age, she underwent balloon dilatation for re-coarctation. At the age of 28 years, she was diagnosed with re-coarctation triggered by hypertension. She underwent balloon dilatation as her cardiac catheterization revealed a systolic pressure gradient of 40 mmHg. Pretreatment 4D flow MRI demonstrated helical flow in the ascending aorta and descending thoracic aorta and LV blood flow analysis revealed a decrease in LV kinetic energy during systole; these improved after treatment.

Discussion
The use of helical flow evaluation by 4D flow MRI for aortic re-coarctation is well known in clinical practice. However, our report is the first to evaluate intraventricular blood flow before and after the re-coarctation treatment. The MRI evaluation demonstrated that the helical flow and LV blood flow distribution improved after re-coarctation treatment due to the reduction of afterload.