bluuebunny/crossref_metadata_2025 huggingface dataset:
Network structure and fluctuation data improve inference of metabolic interaction strengths with the inverse Jacobian
Authors: Li Jiahang , Weckwerth Wolfram , Waldherr Steffen
Published: November 2024

Based on high-throughput metabolomics data, the recently introduced inverse differential Jacobian algorithm can infer regulatory factors and molecular causality within metabolic networks close to steady-state. However, these studies assumed perturbations acting independently on each metabolite, corresponding to metabolic system fluctuations. In contrast, emerging evidence puts forward internal network fluctuations, particularly from gene expression fluctuations, leading to correlated perturbations on metabolites. Here, we propose a novel approach that exploits these correlations to quantify relevant metabolic interactions. By integrating enzyme-related fluctuations in the construction of an appropriate fluctuation matrix, we are able to exploit the underlying reaction network structure for the inverse Jacobian algorithm. We applied this approach to a model-based artificial dataset for validation, and to an experimental breast cancer dataset with two different cell lines. By highlighting metabolic interactions with significantly changed interaction strengths, the inverse Jacobian approach identified critical dynamic regulation points which are confirming previous breast cancer studies.
A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor
Authors: Kumar Pankaj , Kabra Saurabh , Cole Jacqueline M.
Published: November 2024

There has been an ongoing need for information-rich databases in the mechanical-engineering domain to aid in data-driven materials science. To address the lack of suitable property databases, this study employs the latest version of the chemistry-aware natural-language-processing (NLP) toolkit, ChemDataExtractor, to automatically curate a comprehensive materials database of key stress-strain properties. The database contains information about materials and their cognate properties: ultimate tensile strength, yield strength, fracture strength, Young’s modulus, and ductility values. 720,308 data records were extracted from the scientific literature and organized into machine-readable databases formats. The extracted data have an overall precision, recall and F-score of 82.03%, 92.13% and 86.79%, respectively. The resulting database has been made publicly available, aiming to facilitate data-driven research and accelerate advancements within the mechanical-engineering domain.
A multi-region single nucleus transcriptomic atlas of Parkinson’s disease
Authors: N. M. Prashant , Fullard John F. , Clarence Tereza , Mathur Deepika , Casey Clara , Hennigan Evelyn , Alvia Marcela , Krause-Massaguer Joana , Barreda Ayled , Davis David A. , Vontell Regina T. , Garamszegi Susanna P. , Vance Jeffery M. , Sang Lorelle , Chatigny Michael , Vismer David , Landin Barry , Burstein David , Lee Donghoon , Voloudakis Georgios , Berretta Sabina , Haroutunian Vahram , Scott William K. , Bendl Jaroslav , Roussos Panos
Published: November 2024

Parkinson’s Disease (PD) is a debilitating neurodegenerative disorder, characterized by motor and cognitive impairments, that affects >1% of the population over the age of 60. The pathogenesis of PD is complex and remains largely unknown. Due to the cellular heterogeneity of the human brain and changes in cell type composition with disease progression, this complexity cannot be fully captured with bulk tissue studies. To address this, we generated single-nucleus RNA sequencing and whole-genome sequencing data from 100 postmortem cases and controls, carefully selected to represent the entire spectrum of PD neuropathological severity and diverse clinical symptoms. The single nucleus data were generated from five brain regions, capturing the subcortical and cortical spread of PD pathology. Rigorous preprocessing and quality control were applied to ensure data reliability. Committed to collaborative research and open science, this dataset is available on the AMP PD Knowledge Platform, offering researchers a valuable tool to explore the molecular bases of PD and accelerate advances in understanding and treating the disease.
Improved facial emotion recognition model based on a novel deep convolutional structure
Authors: Elsheikh Reham A. , Mohamed M. A. , Abou-Taleb Ahmed Mohamed , Ata Mohamed Maher
Published: November 2024

Facial Emotion Recognition (FER) is a very challenging task due to the varying nature of facial expressions, occlusions, illumination, pose variations, cultural and gender differences, and many other aspects that cause a drastic degradation in quality of facial images. In this paper, an anti-aliased deep convolution network (AA-DCN) model has been developed and proposed to explore how anti-aliasing can increase and improve recognition fidelity of facial emotions. The AA-DCN model detects eight distinct emotions from image data. Furthermore, their features have been extracted using the proposed model and numerous classical deep learning algorithms. The proposed AA-DCN model has been applied to three different datasets to evaluate its performance: The Cohn-Kanade Extending (CK+) database has been utilized, achieving an ultimate accuracy of 99.26% in (5 min, 25 s), the Japanese female facial expressions (JAFFE) obtained 98% accuracy in (8 min, 13 s), and on one of the most challenging FER datasets; the Real-world Affective Face (RAF) dataset; reached 82%, in low training time (12 min, 2s). The experimental results demonstrate that the anti-aliased DCN model is significantly increasing emotion recognition while improving the aliasing artifacts caused by the down-sampling layers.
Microresonator photonic wire bond integration for Kerr-microcomb generation
Authors: Takabayashi Alain Yuji , Pavlov Nikolay , Rosborough Victoria , Hoffman Galen , Kanger Lou , Koushyar Farzad Mokhtari , Huffman Taran , Nelson Mike , Turner Charles , Johansson Leif , Musolf Juergen , Garrett Henry , Liu Thomas , Morrison Gordon , Chembo Yanne , Mattis Brian , Nguyen Thien-An , Van Camp Mackenzie , Turner Steven Eugene , Karpov Maxim , Jost John , Burkley Zakary
Published: November 2024

Extremely high-Q microresonators provide an attractive platform for a plethora of photonic applications including optical frequency combs, high-precision metrology, telecommunication, microwave generation, narrow linewidth lasers, and stable frequency references. Moreover, the desire for compactness and a low power threshold for nonlinear phenomena have spurred investigation into integrated and scalable solutions. Historically, crystalline microresonators with Q $$\sim$$ 109 were one of the first material platforms providing unprecedented optical performance in a small form factor. A key challenge, though, with these devices is in finding alternatives to fragile, bulky, and free-space couplers, such as tapered fibers, prisms, and cleaved fibers. Here, we present for the first time, the evanescent coupling of a photonic wire bond (PWB) to a MgF2-based microresonator to generate solitons and a pure, low-noise microwave signal based on Kerr-microcombs. These results open a path towards scalable integration of crystalline microresonators with integrated photonics. Moreover, because PWBs possess advantages over traditional coupling elements in terms of ease of fabrication, size, and flexibility, they constitute a more advanced optical interface for linear and nonlinear photonics.
EEG features and synek scale indicate severity of neurotoxicity in adult patients treated with CD19 CAR T-cell therapy
Authors: Mao David , Reiner Anne S. , Chen Xi , Park Jae , Pennisi Martina , Perales Miguel-Angel , Avila Edward K. , Santomasso Bianca D.
Published: November 2024

Patients who develop chimeric antigen receptor (CAR) T-cell-related immune effector cell-associated neurotoxicity syndrome (ICANS) frequently undergo evaluation with electroencephalography (EEG). We hypothesize that EEG features and Synek scale score, a measure of degree of EEG abnormality, are associated with ICANS severity. Here, we performed a retrospective review of 125 adult patients at Memorial Sloan Kettering Cancer Center (MSKCC) who received CAR-T cell therapy from 2010 to 2019, including 53 patients with B-acute lymphoblastic leukemia treated with 1928z CAR T cells (NCT01044069) and 72 patients with large B-cell lymphoma (LBCL) treated with the commercial CAR T products axicabtagene ciloleucel or tisagenlecleucel. We collected video EEG monitoring (27 with B-ALL and 20 with LBCL) and recorded daily EEG features, Synek scores, and ICANS grade for 47 eligible patients. Synek scale and ICANS grade were positively correlated (correlation coefficient 0.47, 95% CI: 0.31–0.60). This was further corroborated in the univariable model associating high Synek scale (3 or 4) with high ICANS grade (OR = 15.2; 95%CI:7.8–29.7, p < 0.0001). EEG features such as discontinuity, absence of posterior dominant rhythm, and presence of generalized sharp waves were statistically significantly associated with higher ICANS grade in univariable models. In the multivariable model, discontinuity (OR = 4.2 (95%CI:1.3–13.8, p = 0.02) and absence of posterior dominant rhythm (OR = 10.5 (95%CI:4.6–23.9, p < 0.0001) were statistically associated with higher ICANS grade. Overall, EEG discontinuity and absence of posterior dominant rhythm were independently associated with higher severity of neurotoxicity. Further, our data suggest that Synek Scale, may be a severity marker for neurotoxicity.
Comparison of two negative pressure ureteral access sheaths combined with day-case flexible ureteroscopy for renal stones randomized trial
Authors: Ma Qinghong , Chen Guoqiang , Li Guanghai , Cui Deheng
Published: November 2024

To compare the safety and effectiveness of the combination of intelligent intrarenal pressure control platforms and flexible end ureteral access sheath combined with flexible ureteroscopic lithotripsy (FURL) for the treatment of renal stones less than 2 cm with day case mode. From November 2023 to July 2024, a prospective, randomized, double-blind, parallel-controlled study was conducted to recruit 60 patients with upper urinary tract calculi measuring ≤ 2 cm in longest diameter. A total of 60 eligible patients were consecutively enrolled. Based on a pre-generated random number table and allocation scheme using SPSS 27.0, patients were assigned to either the intelligent pressure control group (IFURL, n = 30) or the head bending group (BFURL, n = 30). Blinding measures were implemented for patients, data collectors, statisticians, and analysts, with the allocation results disclosed to the surgeons prior to the start of the procedure in the operating room. The operation duration for IFURL and BFURL was 52.50 (48.00, 60.00) vs. 46.00 (36.00, 56.25), respectively (p = 0.047). Stone free rate (SFR) on the first postoperative day was 73.33% vs. 93.33% for IFURL and BFURL, respectively (p = 0.038). While, SFR was no significant difference between the two groups after two months(90.00% vs. 96.67%, p = 0.301). One patient in IFURL was readmitted after discharge due to fever 2 days post-discharge, and improved after 2 days of anti-infection treatment. One patient in BFURL was readmitted due to lumbar and abdominal pain from urine extravasation, which improved after 3 days of anti-infection treatment. SFR of one-month post-surgery for renal calculi ≤ 2 cm treated with intelligent pressure control and flexible UAS combined with FURL in day surgery mode was similar, with low infection-related complications and rehospitalization rates, showing no statistical difference. However, the overall hospitalization costs for the BFURL was lower than IFURL.
Identifying future challenges for climate change adaptation through insights from participatory scenario-downscaling in Mumbai
Authors: Petzold Jan , Garschagen Matthias , Deshpande Shankar , Dhiman Ravinder , Doshi Deepal , Katzschner Antje , Santos Alexandre Pereira , Parthasarathy D.
Published: November 2024

Populations in many coastal urban areas are increasingly exposed to climate-related hazards. At the same time, the number of people residing in coastal cities is growing, and, especially in the Global South, these cities are characterised by rapid urbanisation and social inequality. However, the progress of adaptation is lagging, and there is a limited understanding of how future socioeconomic urban developments will affect cities’ social vulnerability and challenges to adaptation. We use the case study of Mumbai to apply a participatory scenario approach, in which we downscale the global Shared Socioeconomic Pathway (SSP) narratives to the local level. Our results stress the relevance of addressing social inequality in urban change processes across different sectors, including labour, housing, transport, and health and streamlining urban planning across different governance scales. Our study lays the ground for integrated modelling of future vulnerability and exposure scenarios and the development of local adaptation pathways.
Using network analysis to understand the association between menopause and depressive symptoms
Authors: Martin-Key Nayra A. , Funnell Erin L. , Benacek Jiri , Spadaro Benedetta , Bahn Sabine
Published: November 2024

It has been proposed that depressive symptoms occurring throughout the menopause may be linked to specific menopause symptoms. The objectives of this study were (i) to use network analysis to explore the symptom structure of menopause and depressive symptoms, and (ii) to compare the symptom structure of menopause and depressive symptoms between the perimenopause and the post-menopause. The Menopause-specific Quality of Life (MENQOL) and the eight-item Patient Health Questionnaire (PHQ-8) were used to measure menopause and depressive symptoms, with online survey data from 858 respondents included for analysis. The most central symptoms were decreased stamina, decreased physical strength, feeling depressed, and change in sexual desire. The network demonstrated good stability (CS-strength = 0.75 and CS-influence = 0.75), with no significant differences in structure between the perimenopause and post-menopause groups. Addressing decreased stamina and psychosocial symptoms could prove instrumental in managing menopause symptoms. Early intervention is crucial for overcoming barriers and providing essential support.
Unidirectional bubble transportation on slippery micro-cone array electrodes enables spontaneous 99.99% gas separation in membrane-less water electrolysis
Authors: Yu Linfeng , Yang Yingze , Xie Pengpeng , Xu Qingzhen , Kumar Anuj , Luo Liang , Li Hui , Xu Haijun , Duan Haohong , Sun Xiaoming
Published: November 2024

Slippery micro-cone array electrodes for membrane-free water electrolysis with spontaneous 99.99% directional gas separation.
Integrated thermal management-sensing-actuation functional artificial muscles
Authors: Wang Lufeng , Yang Shiju , Yang Lixue , Guo Yang , Zhang Yiyao , Li Xiong , Wang Hongzhi , Zhu Liping , Zhu Meifang , Mu Jiuke
Published: November 2024

A fluid pump and sensing layer for artificial muscle thermal management and real-time monitoring is introduced to reduce cooling time by 90%, triple power density, enhance actuation frequency, and broaden applications by integrating smart composites.
Influence of counterions on the thermal and solution properties of strong polyelectrolytes
Authors: Pelras Théophile , Es Sayed Julien , Pierik Jin , Giuntoli Andrea , Hofman Anton H. , Loos Katja , Kamperman Marleen
Published: November 2024

Straightforward polymerisation and nucleophilic deprotection enable the production of a plurality of strong polyelectrolytes with various counterions, the nature of which strongly influences the thermal and solution properties of the macromolecules.
H2O2 accumulation promoting internalization of ox-LDL in early atherosclerosis revealed via a synergistic dual-functional NIR fluorescence probe
Authors: Wang Hui , Guo Jingjing , Xiu Tiancong , Tang Yue , Li Ping , Zhang Wei , Zhang Wen , Tang Bo
Published: November 2024

H2O2 accumulation leads to an increased intake of ox-LDL in the early stages of plaque formation.
Manipulating defects simultaneously boosts the crystal stability and the electrochemical reversibility toward long-life aqueous zinc ion batteries
Authors: Hou Shuyue , Chen Xinyue , He Gangguo , Peng Xin , Wang Jingjing , Huang Can , Liu Huan , Liu Tiezhong , Wang Xin , Zhao Lingzhi , Hou Shuang
Published: November 2024

Combining sulfur-doping and heterojunction in vanadium oxide cathodes is first proposed herein toward long-life aqueous zinc ion batteries. The obtained S-VO2/V6O13-2 manifests a high capacity retention rate of 85.8% after 500 cycles at 0.5 A g−1.
Blockchain controlled trustworthy federated learning platform for smart homes
Authors: Biswas Sujit , Sharif Kashif , Latif Zohaib , Alenazi Mohammed J. F. , Pradhan Ashok Kumar , Bairagi Anupam Kumar
Published: November 2024

Smart device manufacturers rely on insights from smart home (SH) data to update their devices, and similarly, service providers use it for predictive maintenance. In terms of data security and privacy, combining distributed federated learning (FL) with blockchain technology is being considered to prevent single point failure and model poising attacks. However, adding blockchain to a FL environment can worsen blockchain's scaling issues and create regular service interruptions at SH. This article presents a scalable Blockchain‐based Privacy‐preserving Federated Learning (BPFL) architecture for an SH ecosystem that integrates blockchain and FL. BPFL can automate SHs' services and distribute machine learning (ML) operations to update IoT manufacturer models and scale service provider services. The architecture uses a local peer as a gateway to connect SHs to the blockchain network and safeguard user data, transactions, and ML operations. Blockchain facilitates ecosystem access management and learning. The Stanford Cars and an IoT dataset have been used as test bed experiments, taking into account the nature of data (i.e. images and numeric). The experiments show that ledger optimisation can boost scalability by 40–60% in BCN by reducing transaction overhead by 60%. Simultaneously, it increases learning capacity by 10% compared to baseline FL techniques.
Digital twin framework and platform for zero‐emission heavy haul locomotive design and development
Authors: Spiryagin Maksym , Bernal Esteban , Ahmad Sanjar , Wu Qing , Cole Colin , Mcsweeney Tim
Published: November 2024

In recent years, significant development activity has been seen in battery electric and hydrogen locomotives. To fully understand the potential benefits of these zero‐emission technologies and their application in locomotive design, a design study utilising a digital twin framework can be employed. While current research on the use of digital twins for battery and hydrogen‐powered rail vehicles is limited, recent studies conducted at the Centre for Railway Engineering at CQUniversity indicate potential challenges with implementing standard 6‐axle locomotives for zero‐emission designs considering heavy haul operational needs and scenarios. These challenges are related to limitations in energy storage capacity and optimisation of train operation scenarios. By considering an 8‐axle locomotive design concept and employing a digital twin framework in the design process, a more comprehensive assessment of conceptual development, design and requirements can be achieved. This will ensure the locomotive design meets standards, guidelines, and codes of practice, ultimately contributing to achieving net‐zero emission goals in locomotive traction.
Machine tool operating vibration prediction based on multi‐sensor fusion and LSTM neural network
Authors: Shi Zhonglou , Duan Jinjie , Li Faquan
Published: November 2024

This study proposes a machine tool vibration prediction method based on multi‐sensor fusion and a long short‐term memory (LSTM) network. Machine tool vibration significantly impacts machining quality, surface roughness, dimensional accuracy, and tool wear. By combining deep learning with industrial applications, this method achieves high‐precision vibration prediction through multi‐sensor data fusion. Data is input into the LSTM model to predict the next moment's vibration. Experimental results demonstrate strong prediction capability for periodic vibrations and machining‐specific vibration errors, effectively enhancing machining accuracy.
Human essential gene identification based on feature fusion and feature screening
Authors: Zhang Zhao‐Yue , Fan Yue‐Er , Huang Cheng‐Bing , Du Meng‐Ze
Published: November 2024

Essential genes are necessary to sustain the life of a species under adequate nutritional conditions. These genes have attracted significant attention for their potential as drug targets, especially in developing broad‐spectrum antibacterial drugs. However, studying essential genes remains challenging due to their variability in specific environmental conditions. In this study, the authors aim to develop a powerful prediction model for identifying essential genes in humans. The authors first obtained the essential gene data from human cancer cell lines and characterised gene sequences using 7 feature encoding methods such as Kmer, the Composition of K‐spaced Nucleic Acid Pairs, and Z‐curve. Subsequently, feature fusion and feature optimisation strategies were employed to select the impactful features. Finally, machine learning algorithms were applied to construct the prediction models and evaluate their performance. The single‐feature‐based model achieved the highest area under the Receiver Operating Characteristic curve (AUC) of 0.830. After fusing and filtering these features, the classical machine learning models achieved the highest AUC at 0.823 while the deep learning model reached 0.860. Results obtained by the authors show that compared to using individual features, feature fusion and feature optimisation strategies significantly improved model performance. Moreover, the study provided an advantageous method for essential gene identification compared to other methods.
Diversity of disc viscosities can explain the period ratios of resonant and non-resonant systems of hot super-Earths and mini-Neptunes
Authors: Bitsch Bertram , Izidoro Andre
Published: November 2024

Migration is a key ingredient in the formation of close-in super-Earth and mini-Neptune systems. The migration rate sets the resonances in which planets can be trapped, where slower migration rates result in wider resonance configurations compared to higher migration rates. We investigate the influence of different migration rates – set by disc viscosity – on the structure of multi-planet systems via N-body simulations, where planets grow via pebble accretion. Planets in low-viscosity environments migrate slower due to partial gap opening compared to planets forming in high-viscosity environments. Consequently, systems formed in low-viscosity environments tend to have planets trapped in wider resonant configurations (typically 4:3, 3:2, and 2:1 configurations). Simulations of high-viscosity discs mostly produce planetary systems in 7:6, 5:4, and 4:3 resonances. After the gas disc dissipates, the damping forces of eccentricity and inclination cease to exist and the systems can undergo instities on timescales of a few tens of millions of years, rearranging their configurations and breaking the resonance chains. We show that low-viscosity discs naturally account for the configurations of resonant chains, such as Trappist-1, TOI-178, and Kepler-223, unlike high-viscosity simulations, which produce chains that are more compact. Following dispersal of the gas disc, about 95% of our low-viscosity resonant chains became unstable, experiencing a phase of giant impacts. Dynamical instabilities in our low-viscosity simulations are more violent than those of high-viscosity simulations due to the effects of leftover external perturbers (P>200 days). About 50% of our final systems end with no planets within 200 days, while all our systems harbour remaining outer planets. We speculate that this process could be qualitatively consistent with the lack of inner planets in a large fraction of the Sun-like stars. Systems produced in low-viscosity simulations alone do not match the overall period ratio distribution of observations, but give a better match to the period distributions of chains, which may suggest that systems of super-Earths and mini-Neptunes form in natal discs with a diversity of viscosities.
Circular Chemistry: An Enabler of Circular Economy To Achieve the Zero-Waste Goal
Authors: Singh Santosh Bahadur
Published: November 2024

The main aims of zero-waste goals are the promotion of sustainable production and consumption through the societal move toward circular approaches. The chemical industry includes a variety of processes to produce various useful consumables, but many of these processes have serious negative environmental, health, and safety impacts at every level of their design, production, processing, and uses. Circularity is at the core of eco-design and the production technology in which waste is repurposed and their environmental impacts are reduced via the 3Rs concepts: reduce, reuse, and recycle. The integration of circular approaches with chemistry makes it a circular chemistry (CC). This article provides a brief literature review on CC and why it is important to tackle the various sustainability-related issues. Here we conduct a structured opinion as well as evidence-based review to explore the role of CC to make it more sustainable. Fundamental aspects of CC and its role
in the circular economy have been discussed, and it is concluded that the design of clean chemical processes, recovery, and reuse of wastes, and reintroducing recovered materials back to the industrial production chain is possible and scalable. This article aligns with 7 UN’s Sustainable Development Goals, that is, 3, 6, 9, 12, 13, 14, and 15.
Chirurgische Versorgung typischer osteoporotischer
Frakturen
Authors: Pankratz Carlos , Gebhard Florian , Schütze Konrad
Published: November 2024

Die steigende Inzidenz Osteoporose-assoziierter Frakturen stellt eine zunehmende
Herausforderung für die operative Versorgung dar. Diese Arbeit bietet einen
Überblick über die aktuellen Strategien zur Versorgung der häufigsten
osteoporotischen Frakturen. Ziel ist es Wissen über aktuelle Techniken zu
vermitteln und für spezifische Herausforderungen zu sensibilisieren. Hierzu
wurde eine Übersicht über operative Verfahren für Frakturen des proximalen
Femurs, des Beckens, der Wirbelsäule, des distalen Radius und des proximalen
Humerus erstellt. Die operative Versorgung Osteoporose-assoziierter Frakturen
erfordert aufgrund der verminderten Knochenqualität und -quantität sowie der
häufigen Multimorbidität der Patienten einige Besonderheiten. Zunehmend
angewendet werden verschiedene Augmentationstechniken, die die Stabilität von
Osteosynthesen steigern und eine frühzeitige Mobilisation ermöglichen. Bei
Frakturen der Wirbelsäule und des Beckenringes hat die schmerzbedingte
Immobilität oftmals fatale Folgen für die Betroffenen. Die operative Versorgung
beinhaltet hier einen teilweise präventiven Aspekt. Minimalinvasive Verfahren,
wie die perkutane Schraubenosteosynthese bei Beckenringfrakturen, haben sich als
risikoarme Methode etabliert. Die Kyphoplastie bei osteoporotischen
Wirbelkörperfrakturen kann durch eine Hybrid-Versorgung mit zusätzlicher
dorsaler Instrumentierung ergänzt werden. Vor allem bei Frakturen der oberen
Extremität hat die konservative Therapie weiterhin ihren Stellenwert.
Hüftgelenksnahe Femurfrakturen werden unmittelbar operativ versorgt. Weitere
Forschung ist notwendig, um evidenzbasierte Standardverfahren für die Anwendung
von Augmentationstechniken bei verschiedenen Frakturtypen zu etablieren.
Radiographic Assessment of Total Knee Arthroplasty Alignment With and Without Accelerometer-Based Navigation at a Resident Training Institution
Authors: Brazier Brett G. , Allen Christian B. , Hilyard Daryl G. , Shah Darshan S. , Vizurraga David E. , Hope Donald N.
Published: November 2024

Malalignment and lack of surgeon experience are cited as risk factors for prosthetic failure and the need for subsequent revision surgery in total knee arthroplasty (TKA). Various conventional (CON) and computer-assisted surgical (CAS) methods have been developed to try and prevent malalignment and limit outliers. One of these methods is through an accelerometer-based CAS (aCAS), which intraoperatively helps determine the angulation and amount of resection necessary to restore alignment in TKA. The purpose of this study was to determine the number of TKA alignment outliers in TKAs performed both with CON and aCAS methods at a single training institution in cases that trainees were involved in. In this retrospective single-center study, radiographic analysis of 150 primary TKAs performed at our training institution was performed. The medial distal femoral angle (DFA), medial proximal tibial angle (PTA), and posterior slope angle (PSA) were evaluated on immediate postoperative radiographs of 75 aCAS and 75 CON knees. Outlier measurements were defined as DFA outside of 5 ± 3 degrees valgus, PTA > ± 3 degrees from neutral axis, and PSA outside 0 to 7 degrees for cruciate retaining and 0 to 5 degrees for posterior stabilized implants. Data was analyzed using chi-squared, analysis of variance, and Student's t-tests. There was no significant difference found between these two groups in the total number of outliers (8% aCAS vs. 9.8% CON, p = 0.508). Additionally, there was also no significant difference found for any of the radiographic measurements independently; DFA (8% vs. 8%, p = 1.00), PTA (4% vs. 9%, p = 0.184), and PSA (12% vs. 12%, p = 1.00), when comparing aCAS and CON TKAs. Primary TKAs performed at a single training institution demonstrated no significant difference between aCAS and CON methods in the total number of outliers or in the number of outliers for each postoperative radiographic measurement. This study would suggest that there is no advantage in limiting outliers when utilizing aCAS for TKAs at training institutions in cases that trainees are involved in.

Level of Evidence Level III Retrospective Cohort Study
Isolated Lateral Extra-Articular Tenodesis for Ongoing Instability Following Anterior Cruciate Ligament (ACL) Reconstruction with an Intact Graft is Effective and Has Low Surgical Morbidity
Authors: Davies Peter S.E. , Muirhead Cameron , Mayne Alistair I.W. , Ebert Jay R. , Edwards Peter K. , Simpson Ashley , Williams Andy , D'Alessandro Peter
Published: November 2024

The management of persisting instability following anterior cruciate ligament reconstruction (ACLR) includes isolated lateral extra-articular tenodesis (LEAT). The present study investigates the outcomes following isolated LEAT to address ongoing instability following ACLR without LEAT. Patients with ongoing symptomatic instability following ACLR with a radiologically intact and well-positioned graft who underwent an isolated LEAT between January 2017 and March 2022 were retrospectively recruited. Patients completed patient-reported outcome measures at baseline and mean 26 months postoperatively. Twelve knees in 11 patients underwent an isolated LEAT. All Knee Injury and Osteoarthritis Outcome Score domains improved significantly between pre- and postoperative measurements (pain 60.9–91.7, p = 0.002; symptoms 62.5–93.8, p = 0.003; activities of daily living 64.3–95.2, p = 0.002; sport 61.9–82.5, p = 0.012; quality of life 17.2–80.2, p = 0.002). One patient required revision ACL surgery 19 months following their subsequent LEAT procedure. An isolated LEAT demonstrated clinically significant improvements in patient function and activity with acceptable surgical morbidity and should be considered as an option for appropriate cases with instability despite an intact ACL graft.

Level of evidence Level IV prospective case series
Microwave-Assisted Catalyst-Free Hydride Transfer: Synthesis and Evaluation of Antioxidant Properties of N-Benzylindolines
Authors: Deb Mohit L. , Baruah Pranjal K. , Boruah Aditi
Published: November 2024

We report a catalyst-free intermolecular hydride-transfer reaction to synthesize N-benzylindolines under microwave heating in the absence of a solvent. The reactions are performed by taking indoline (two equivalents) with aryl aldehydes, which give good yields of products. Tetrahydroisoquinoline can also be used in place of indoline to give excellent yields of the expected products. A mechanism has also been proposed. The antioxidant properties of all the N-benzylindolines were tested and compared with that of ascorbic acid, showing that some of them are powerful antioxidants.
Laser powder bed fusion of biodegradable magnesium alloys: process, microstructure and properties
Authors: Wu Xuehua , Liu Junying , Yang Youwen , Bai Jing , Shuai Cijun , Buhagiar Joseph , Ning Xinghai
Published: November 2024

Magnesium (Mg) alloys have gained recognition as revolutionary biomaterials, owing to their inherent degradability, favorable biocompatibility and mechanical properties. Additive manufacturing (AM) provides high design flexibility and enables the creation of implants with personalized complex shapes and internal porous structures tailored to individual anatomical and functional needs. Particularly, laser powder bed fusion (LPBF), one prevalent AM technique, utilizes a fine laser beam as heat source and results in tiny molten pool with extremely fast cooling rate, which effectively restricts grain growth, inter-metallic precipitation and macroscopic segregation, thus facilitating the fabrication of high-performance metal parts. This review critically assesses the significance of biodegradable Mg alloys and investigates the feasibility of utilizing LPBF for Mg alloys applications in biomedical field. Detailed discussions on LPBF-processed biomedical Mg alloys parts cover process parameters, microstructure, metallurgical defects, and properties like mechanical performance, corrosion behavior, and biological response in both as-built and post-processed states. Additionally, suggestions for advancing knowledge in LPBF of biodegradable Mg alloys for biomedical applications are highlighted to propel further research and development in this field.
All-Cause Mortality and 1990-1991 Gulf War Service within the Millennium Cohort Study (2001-2021)
Authors: Carey Felicia R , Sharifian Neika , Boparai Satbir , Dursa Erin K , Boyko Edward J , Rull Rudolph P , Cohort Study for the Millennium
Published: November 2024

Although 1990-1991 Gulf War deployment has been linked to worse health outcomes such as chronic multisymptom illness (CMI), often referred to as Gulf War Illness, among deployed Gulf War Veterans, less is known regarding Gulf War service and mortality. Using 20 years of longitudinal data from Gulf War Veteran and Era personnel from the Millennium Cohort Study (2001-2021; n=45381), Cox proportional hazard models estimated the relative effects of Gulf War service status, CMI, and their corresponding interaction on all-cause mortality. Although age- and sex-adjusted mortality ratios suggested that Gulf War Veterans had higher mortality rates than Era personnel, no association was observed between Gulf War service status and mortality risk. Screening positive for CMI was associated with greater risk of all-cause mortality compared with those who did not screen positive across both GWV and Era personnel; interactions between CMI and Gulf War status were not statistically significant. This finding suggests that CMI increases mortality risk regardless of whether the symptomology is associated with Gulf War deployment. Future research is necessary to examine specific occupational and environmental exposures experienced during deployments and service in support of the 1990-1991 Gulf War and their association with mortality in this population.
Transient Receptor Potential Channels in Vascular Mechanotransduction
Authors: Solano Alfredo Sanchez , Lavanderos Boris , Metwally Elsayed , Earley Scott
Published: November 2024

Transmural pressure and shear stress are mechanical forces that profoundly affect the smooth muscle cells (SMCs) comprising the vascular wall and the endothelial cells (ECs) lining the lumen. Pressure and flow are detected by mechanosensors in these cells and translated into appropriate responses to regulate blood pressure and flow. This review focuses on the role of the transient receptor potential (TRP) superfamily of cation channels in this process. We discuss how specific members of the TRP superfamily (TRPC6, TRPM4, TRPV1, TRPV4, and TRPP1) regulate the resting membrane and intracellular Ca2+ levels in SMCs and ECs to promote changes in vascular tone in response to intraluminal pressure and shear stress. Although TRP channels participate in vascular mechanotransduction, little evidence supports their intrinsic mechanosensitivity. Therefore, we also examine the evidence exploring the force-sensitive signal transduction pathways acting upstream of vascular TRP channels. Understanding the interplay between mechanosensors, force-induced signaling cascades, and TRP channels holds promise for the development of targeted therapies for diseases caused by vascular dysfunction.
Association between burnout and workplace climate in transplant clinical pharmacists
Authors: Lichvar Alicia , Park Jeong M , Alvey Nicole , Feist Ashley , Pierce Dana R , Fredrick Stacy , Melaragno Jennifer I , Chandran Mary Moss , Sweiss Helen I , Harris Matt
Published: November 2024

Purpose

An assessment of workplace culture is needed to further elucidate the factors that contribute to solid organ transplant (SOT) pharmacist burnout and attrition. Therefore, the primary objective of this study was to describe the association between workplace climate and burnout of SOT pharmacists within the United States.

Methods

A 79-question survey was distributed to transplant pharmacy organization listservers from May 30 through July 25, 2023. Burnout was assessed with the Maslach Burnout Inventory Human Services Survey for Medical Personnel (MBI-HSS-MP) in 3 subscales: depersonalization, emotional exhaustion, and personal accomplishment. Scores on the Organizational Constraints Scale (OCS), Quantitative Workload Inventory Scale (QWIS), Interpersonal Conflict at Work Scale (ICAWS; repeated 3 times—once each for interactions with clinical pharmacists, pharmacy management/administration, and nonpharmacist members of the transplant team), and Utrecht Work Engagement Scale (UWES-9) were compared between those with and without burnout to assess the impact of workplace climate. The likelihood of respondents’ leaving their current job was also measured. Univariate and multivariate logistic regression modeling was conducted to identify risk factors for burnout.

Results

A total of 135 responses were received from 664 survey recipients (response rate, 20.3%). The mean age of survey participants was 36.2 years (SD, 7.2 years), and participants were predominantly Caucasian (86.7%), female (84.4%), and/or married/partnered (68.9%), with a median (IQR) of 7 (3-12) years posttraining practice experience. A total of 65.9% of responders met MBI-HSS-MP criteria for burnout. In univariate analysis, burnout was strongly associated with the intent to leave their current position (odds ratio [OR], 8.05, P = 0.001). The univariate analysis revealed that higher ICAWS scores were associated with higher risk of burnout in all 3 domain categories: pharmacy team (OR, 1.39; P = 0.001), pharmacy management (OR, 1.45; P = 0.002), and nonpharmacy SOT team members (OR, 1.24; P = 0.017). In multivariate analysis, higher OCS scores (OR, 1.21; P < 0.001) and higher QWIS scores (OR, 1.22; P = 0.003) were associated with a higher incidence of burnout, whereas higher UWES-9 scores (OR, 0.85; P < 0.001) were associated with a lower likelihood of burnout.

Conclusion

Burnout was observed in a majority of survey respondents, with different workplace climate factors serving as significant risk factors for its development. Burnout mitigation and prevention strategies within the workplace should be researched, trialed, and implemented to reduce the impact on individuals, to improve quality of life, and to prevent attrition of the SOT pharmacist workforce.
Securing affiliation and managing disagreement: Epistemic primacy claims in group-based L2 oral assessments
Authors: Stephenson Michael , Hazel Spencer
Published: November 2024

This study explores the use by examinees of claims of epistemic primacy, in the form of noun-copula clause constructions, as devices through which to perform the social action of disagreeing during group-based, task-oriented second language oral assessment tasks. Using a conversation analytic approach to examine sequences in which these disagreeing turns occur, we report on this turn format’s ability to secure an affiliative response from fellow examinees and thereby maintain a collaborative flow. In doing so, we uncover one way of disagreeing which is particularly germane to the collaborative demands of these assessment tasks. The relevance of these findings for the development of learner and assessor training and assessment materials are considered.
Pyriform Aperture Enlargement Through a Rhinoplasty Approach
Authors: Shah Anil R , Grande David P , Buckner Hallie , Nordgren Rachel
Published: November 2024

Background

The pyriform aperture can limit airflow in some patients. In this study, the authors describe a new surgical technique to access and modify the pyriform aperture.

Objectives

Describe the technique to measure the width of the pyriform aperture and surgically enlarge the pyriform aperture using ultrasonic instrumentation. Quantify improvement in nasal airway function with pyriform aperture size and Nasal Obstruction Symptom Evaluation (NOSE) scores.

Methods

The pyriform aperture was measured intraoperatively using calipers. Preoperative and postoperative NOSE scores were compared in a retrospective analysis to examine the effects of pyriform aperture enlargement on nasal breathing.

Results

On average, pyriform aperture width was enlarged by 2.9 mm (P < .0001) and NOSE scores decreased from 69.4 to 8.3 at 6 months (P < .0001).

Conclusions

The pyriform aperture can be modified through an open rhinoplasty approach, and enlargement of the pyriform aperture can improve nasal obstruction symptoms.

Level of Evidence: 5

(Therapeutic)
Predicting the genetic component of gene expression using gene regulatory networks
Authors: Mohammad Gutama Ibrahim , Michoel Tom
Published: November 2024

Motivation

Gene expression prediction plays a vital role in transcriptome-wide association studies. Traditional models rely on genetic variants in close genomic proximity to the gene of interest to predict the genetic component of gene expression. Here, we propose a novel approach incorporating distal genetic variants acting through gene regulatory networks, in line with the omnigenic model of complex traits.

Results

Using causal and coexpression Bayesian networks reconstructed from genomic and transcriptomic data, inference of gene expression from genotypic data is achieved through a two-step process. Initially, the expression level of each gene is predicted using its local genetic variants. The residual differences between the observed and predicted expression levels are then modeled using the genotype information of parent and/or grandparent nodes in the network. The final predicted expression level is obtained by summing the predictions from both models, effectively incorporating both local and distal genetic influences. Using regularized regression techniques for parameter estimation, we found that gene regulatory network-based gene expression prediction outperformed the traditional approach on simulated data and real data from yeast and humans. This study provides important insights into the challenge of gene expression prediction for transcriptome-wide association studies.

Availability and implementation

The code is available on Github at github.com/guutama/GRN-TI.
ViraLM: empowering virus discovery through the genome foundation model
Authors: Peng Cheng , Shang Jiayu , Guan Jiaojiao , Wang Donglin , Sun Yanni
Published: November 2024

Motivation

Viruses, with their ubiquitous presence and high diversity, play pivotal roles in ecological systems and public health. Accurate identification of viruses in various ecosystems is essential for comprehending their variety and assessing their ecological influence. Metagenomic sequencing has become a major strategy to survey the viruses in various ecosystems. However, accurate and comprehensive virus detection in metagenomic data remains difficult. Limited reference sequences prevent alignment-based methods from identifying novel viruses. Machine learning-based tools are more promising in novel virus detection but often miss short viral contigs, which are abundant in typical metagenomic data. The inconsistency in virus search results produced by available tools further highlights the urgent need for a more robust tool for virus identification.

Results

In this work, we develop ViraLM for identifying novel viral contigs in metagenomic data. By using the latest genome foundation model as the backbone and training on a rigorously constructed dataset, the model is able to distinguish viruses from other organisms based on the learned genomic characteristics. We thoroughly tested ViraLM on multiple datasets and the experimental results show that ViraLM outperforms available tools in different scenarios. In particular, ViraLM improves the F1-score on short contigs by 22%.

Availability and implementation

The source code of ViraLM is available via: https://github.com/ChengPENG-wolf/ViraLM.
An exploratory penalized regression to identify combined effects of temporal variables—application to agri-environmental issues
Authors: Fontez Bénedicte , Loisel Patrice , Simonneau Thierry , Hilgert Nadine
Published: November 2024

The development of sensors is opening new avenues in several fields of activity. Concerning agricultural crops, complex combinations of agri-environmental dynamics, such as soil and climate variables, are now commonly recorded. These new kinds of measurements are an opportunity to improve knowledge of the drivers of crop yield and crop quality at harvest. This involves renewing statistical approaches to account for the combined variations of these dynamic variables, here considered as temporal variables. The objective of the paper is to estimate an interpretable model to study the influence of the two combined inputs on a scalar output. A Sparse and Structured Procedure is proposed to Identify Combined Effects of Formatted temporal Predictors, hereafter denoted S piceFP. The method is based on the transformation of both temporal variables into categorical variables by defining joint modalities, from which a collection of multiple regression models is then derived. The regressors are the frequencies associated with joint class intervals. The class intervals and related regression coefficients are determined using a generalized fused lasso. S piceFP is a generic and exploratory approach. The simulations we performed show that it is flexible enough to select the non-null or influential modalities of values. A motivating example for grape quality is presented.