bluuebunny/crossref_metadata_2025_split huggingface dataset:
Is unicompartmental knee arthroplasty a better choice than total knee arthroplasty for unicompartmental osteoarthritis? A systematic review and meta-analysis of randomized controlled trials
Authors: Xia Kuanyu , Min Lang , Xie Wenqing , Yang Guang , Yon Dong Keon , Lee Seung Won , Koyanagi Ai , Jacob Louis , Smith Lee , Shin Jae Il , Rahmati Masoud , Xiao Wenfeng , Li Yusheng 
Published: July 2024

Abstract

Background:
The choice of unicompartmental knee arthroplasty (UKA) vs. total knee arthroplasty (TKA) in the surgical treatment of knee osteoarthritis (KOA) remains controversial. This study aimed to perform a systematic review and meta-analysis of randomized controlled trials (RCTs) to compare the clinical results of UKA and TKA for treating unicompartmental KOA.

Methods:
PubMed, Embase, and the Cochrane Library were systematically searched for articles published up to January 2, 2023. The literature was rigorously screened to include only RCTs comparing UKA and TKA for unicompartmental KOA. A systematic review and meta-analysis were performed to calculate the mean difference (MD), relative risk (RR), and 95% confidence interval (CI) according to the Cochrane standards.

Results:
Thirteen publications involving 683 UKAs and 683 TKAs were analyzed. Except for one study with a follow-up period of 15 years, all outcome measures reported were within 5 years of follow-up. Meta-analysis showed better knee recovery (MD: 1.23; 95% CI: 1.01–1.45; P <0.00001), greater knee function (MD: 1.78; 95% CI: 0.34–3.22; P = 0.02), less pain (MD: 0.75; 95% CI: 0.43–1.06; P <0.00001), and better health status (MD: 3.75; 95% CI: 0.81–6.69; P = 0.01) after UKA than TKA. However, considering the minimal clinically important difference values for these variables, the findings were not clinically relevant. Moreover, UKA patients had fewer complications (RR: 0.59; 95% CI: 0.45–0.78; P = 0.0002) and shorter hospital stays (MD: –0.89; 95% CI: –1.57 to –0.22; P = 0.009) than did TKA patients. There were no statistically significant differences in terms of postoperative range of movement, revision, failure, operation time, and patient satisfaction.

Conclusions:
In terms of clinical efficacy, there was no obvious advantage of UKA over TKA in the surgical treatment of knee OA when considering the minimal clinically important difference. The main advantage of UKA over TKA is that it leads to fewer complications and a shorter length of hospital stay. It is ideal to perform prospective studies with longer follow-up periods to fully evaluate the long-term efficacy and safety of the two procedures in the future.
Association between coronary artery stenosis and myocardial injury in patients with acute pulmonary embolism: A case-control study
Authors: Yang Yinjian , Liu Chao , Ma Jieling , Zhu Xijie , Ma Jingsi , Lu Dan , Yan Xinxin , Gao Xuan , Wang Jia , Wang Liting , Zhang Sijin , Li Xianmei , Wu Bingxiang , Sun Kai , Mao Yimin , Xu Xiqi , Lian Tianyu , Cheng Chunyan , Jing Zhicheng 
Published: July 2024

Abstract

Background:
The potential impact of pre-existing coronary artery stenosis (CAS) on acute pulmonary embolism (PE) episodes remains underexplored. This study aimed to investigate the association between pre-existing CAS and the elevation of high-sensitivity cardiac troponin I (hs-cTnI) levels in patients with PE.

Methods:
In this multicenter, prospective case-control study, 88 cases and 163 controls matched for age, sex, and study center were enrolled. Cases were patients with PE with elevated hs-cTnI. Controls were patients with PE with normal hs-cTnI. Coronary artery assessment utilized coronary computed tomographic angiography or invasive coronary angiography. CAS was defined as ≥50% stenosis of the lumen diameter in any coronary vessel >2.0 mm in diameter. Conditional logistic regression was used to evaluate the association between CAS and hs-cTnI elevation.

Results:
The percentage of CAS was higher in the case group compared to the control group (44.3% [39/88] vs. 30.1% [49/163]; P = 0.024). In multivariable conditional logistic regression model 1, CAS (adjusted odds ratio [OR], 2.680; 95% confidence interval [CI], 1.243–5.779), heart rate >75 beats/min (OR, 2.306; 95% CI, 1.056–5.036) and N-terminal pro-B type natriuretic peptide (NT-proBNP) >420 pg/mL (OR, 12.169; 95% CI, 4.792–30.900) were independently associated with elevated hs-cTnI. In model 2, right CAS (OR, 3.615; 95% CI, 1.467–8.909) and NT-proBNP >420 pg/mL (OR, 13.890; 95% CI, 5.288–36.484) were independently associated with elevated hs-cTnI.

Conclusions:
CAS was independently associated with myocardial injury in patients with PE. Vigilance towards CAS is warranted in patients with PE with elevated cardiac troponin levels.
Perceptions of general surgery residents at military treatment facilities: Excellent training with crisis of confidence
Authors: West Erin , Green Kristina , Horton John , Gillern Suzanne M. , Faler Byron , Krell Robert W. , Nelson Daniel , Krzyzaniak Michael J. , Vicente Diego , Choi Pamela M. 
Published: July 2024

BACKGROUND
The declining operative volume at Military Treatment Facilities (MTFs) has resulted in Program Directors finding alternate civilian sites for resident rotations. The continued shift away from MTFs for surgical training is likely to have unintended negative consequences.

METHODS
An anonymous survey was generated and sent to the program directors of military general surgery training programs for distribution to their residents.

RESULTS
A total of 42 residents responded (response rate 21%) with adequate representation from all PGY years. Ninety-five percent of residents believed that their programs provided the training needed to be a competent general surgeon. However, when asked about career choices, only 30.9% reported being likely/extremely likely to remain in the military beyond their initial service obligation, while 54.7% reported that it was unlikely/extremely unlikely and 19% reported uncertainty. Eighty-eight percent reported that decreasing MTF surgical volume directly influenced their decision to stay in the military, and half of respondents regretted joining the military. When asked to assess their confidence in the military to provide opportunities for skill sustainment as a staff surgeon, 90.4% were not confident or were neutral.

CONCLUSION
Although military surgical residents have a generally positive perception of their surgical training, they also lack confidence in their future military surgical careers. Our findings suggest that declining MTF surgical volume will likely negatively impact long-term retention of military surgeons and may negatively impact force generation for Operational Commander.

LEVEL OF EVIDENCE
Prognostic and Epidemiological, Level IV.
Identification of whole-body reaching movement phenotypes in young and older active adults: an unsupervised machine learning approach
Authors: Pfaff Michel , Casteran Matthieu 
Published: July 2024

AbstractStudies reported age-related motor control modifications in whole-body movement in several aspects of spatiotemporal movement organization by comparing young and older adults. However, studies on motor control involve high complexity and high-dimensional data of different natures, in which machine learning has proved to be effective. Furthermore, conventional studies focus on comparisons of movement parameters based on a priori grouping, whereas unsupervised machine learning allows the identification of inherent groupings within the dataset. The current investigation was carried out by using the unsupervised machine learning on motor control features across age-groups. An important question was whether we could identify different movement patterns based on motor control features and whether they were age-dependent or independent. We investigated motor control parameters variations in a whole-body reaching movement across young and active older adults including woman and man (n=19). We applied the K-means clustering algorithm to segment the kinematic data (21 features) of all individuals. We propose a methodology applying the latest recommendations for clustering methods in the field of whole-body movement motor control. Analysis revealed two distinct motor control patterns which were age independent. The first pattern exhibited higher shoulder, ankle and knee angular excursions, along with a higher vertical velocity of center of mass (CoM), compared to the second pattern, which had higher hip and back angular excursions, along with a lower vertical velocity CoM. The clustering methodology demonstrated its effectiveness to identify distinct motor patterns based solely on motor control features independently of age-grouping.Significance StatementK-means clustering algorithm enabled us to identify two distinct age-independent motor patterns: a first pattern with high shoulder, ankle and knee angular excursions, and vertical velocity of CoM; a second pattern with high hip and back angular excursions and low vertical velocity of CoM.Demonstrates how unsupervised machine learning can identify motor patterns and proposes a methodology to apply it in the field of whole-body movement motor control.Proves the complementary contribution of unsupervised machine learning to conventional approach for motor control studies, which enables to process the high complexity and dimensionality of movements.Advances understanding of motor behaviours through unsupervised machine learning analysis of whole-body reaching movements.
3D Brain Vascular Niche Model Captures Invasive Behavior and Gene Signatures of Glioblastoma
Authors: Lee Vivian K. , Tejero Rut , Silvia Nathaniel , Sattiraju Anirudh , Ramakrishnan Aarthi , Shen Li , Wojcinski Alexandre , Kesari Santosh , Friedel Roland H. , Zou Hongyan , Dai Guohao 
Published: July 2024

ABSTRACTGlioblastoma (GBM) is a lethal brain cancer with no effective treatment; understanding how GBM cells respond to tumor microenvironment remains challenging as conventional cell cultures lack proper cytoarchitecture whilein vivoanimal models present complexity all at once. Developing a culture system to bridge the gap is thus crucial. Here, we employed a multicellular approach using human glia and vascular cells to optimize a 3-dimensional (3D) brain vascular niche model that enabled not only long-term culture of patient derived GBM cells but also recapitulation of key features of GBM heterogeneity, in particular invasion behavior and vascular association. Comparative transcriptomics of identical patient derived GBM cells in 3D andin vivoxenotransplants models revealed that glia-vascular contact induced genes concerning neural/glia development, synaptic regulation, as well as immune suppression. This gene signature displayed region specific enrichment in the leading edge and microvascular proliferation zones in human GBM and predicted poor prognosis. Gene variance analysis also uncovered histone demethylation and xylosyltransferase activity as main themes for gene adaption of GBM cellsin vivo. Furthermore, our 3D model also demonstrated the capacity to provide a quiescence and a protective niche against chemotherapy. In summary, an advanced 3D brain vascular model can bridge the gap between 2D cultures andin vivomodels in capturing key features of GBM heterogeneity and unveil previously unrecognized influence of glia-vascular contact for transcriptional adaption in GBM cells featuring neural/synaptic interaction and immunosuppression.
HERMES: Holographic Equivariant neuRal network model for Mutational Effect and Stability prediction
Authors: Visani Gian Marco , Pun Michael N. , Galvin William , Daniel Eric , Borisiak Kevin , Wagura Utheri , Nourmohammad Armita 
Published: July 2024

AbstractPredicting the stability and fitness effects of amino-acid mutations in proteins is a cornerstone of biological discovery and engineering. Various experimental techniques have been developed to measure mutational effects, providing us with extensive datasets across a diverse range of proteins. By training on these data, machine learning approaches have advanced significantly in predicting mutational effects. Here, we introduce HERMES, a 3D rotationally equivariant structure-based neural network model for mutation effect prediction. Pre-trained to predict amino-acid propensities from their surrounding 3D structure atomic environments, HERMES can be efficiently fine-tuned to predict mutational effects, thanks to its symmetry-aware parameterization of the output space. Benchmarking against other models demonstrates that HERMES often outperforms or matches their performance in predicting mutation effects on stability, binding, and fitness, using either computationally or experimentally resolved protein structures. HERMES offers a versatile suit of tools for evaluating mutation effects and can be easily fine-tuned for specific predictive objectives using our open-source code.
Immunisation of chickens with inactivated and/or infectious H9N2 avian influenza virus leads to differential immune B cell repertoire development
Authors: Dascalu Stefan , Sealy Joshua E. , Sadeyen Jean-Remy , Flammer Patrik G. , Fiddaman Steven , Preston Stephen G. , Dixon Robert J. , Bonsall Michael B. , Smith Adrian L. , Iqbal Munir 
Published: July 2024

AbstractAvian influenza viruses (AIVs) are a major economic burden to the poultry industry, and pose serious zoonotic risk, with human infections being reported every year. To date, the vaccination of birds remains the most important method for the prevention and control of AIV outbreaks. Most national vaccination strategies against AIV infection use whole-virus inactivated vaccines, which predominantly trigger a systemic antibody-mediated immune response. There are currently no studies that have examined the antibody repertoire of birds that were infected with and/or vaccinated against AIV. To this end, we evaluate the changes in the H9N2-specific IgM and IgY repertoires in chickens subjected to vaccination(s) and/or infectious challenge. We show that a large proportion of the IgM and IgY clones were shared across multiple individuals, and these public clonal responses are dependent on both the immunisation status of the birds and the specific tissue that was examined. Furthermore, analysis reveals specific clonal expansions which are restricted to particular H9N2 immunisation regimes. These results indicate that both the nature and number of immunisations are important drivers of the antibody responses and repertoire profiles in chickens following H9N2 antigenic stimulation. We discuss how the repertoire biology of avian B cell responses may affect the success of AIV vaccination in chickens, in particular the implications of public versus private clonal selection.
Unraveling the immunological roles of serum amyloid A3 in aortic immune cell subsets during atherosclerosis progression
Authors: Chou Tzu-Yin , Ye Yu-Zhen , Lin I-Jung , Lien Chia-Jung , Yang Chen-Hsuan , Chen Yen-Ting , Chao Pei-An , Lin Jian-Da 
Published: July 2024

AbstractAtherosclerosis is a growing concern in developed nations, necessitating the identification of therapeutic targets for advancing personalized medicine. Serum amyloid A3 (Saa3) has been linked to accelerated plaque progression by affecting cholesterol metabolism and modulation of inflammation. We hypothesize that knocking outSaa3(Saa3-/-) could mitigate plaque development by regulating aortic immune cell subsets during atherosclerosis progression. Using a murine model, we induced atherosclerosis via a gain-of-function mutant PCSK9-encoding adeno-associated viral vector (AAVmPCSK9) in wild-type (WT) andSaa3-/-mice. Single-cell RNA sequencing revealed thatSaa3-/-mice developed smaller plaques than WT mice, with significant differences in aortic immune cell populations, particularly aortic macrophages.Saa3-/-macrophages, characterized by highGpnmb,Lpl, andSpp1expressions, predominated over the typical resident foamy macrophages in WT mice.Saa3-/-mice also showed enhanced intercellular immune communication and increased signaling interactions, suggesting a shift towards an anti-inflammatory and tissue-repairing phenotype. Our study highlights the potential ofSaa3as a therapeutic target for atherosclerosis.
Reproductive fluids enabling cryptic female choice of paternity do not induce concomitant gamete-mediated paternal effects in embryos of hybridizing salmonid fishes
Authors: Lantiegne Tyler H. , Wagle Ranjan , Purchase Craig F. 
Published: July 2024

AbstractPost-mating sexual selection in the form of cryptic female choice provides opportunities for females to bias paternity to favor preferred males. However, little is known regarding how cryptic female choice might affect offspring outside of paternity, via female modified changes to sperm environmental experience. Gamete-mediated paternal effects are widespread, and female alteration of sperm experience may play an unrecognized role in shaping cryptic female choice. Using hybridizing salmonid fishes that have documented female mediated conspecific sperm preference via differential upregulation of sperm swimming performance, we created artificial split-brood and split-ejaculate fertilizations to determine if sperm experience in different conditions influences offspring development. Prior to contact with eggs, sperm experienced 20s of swimming in either water, or water with the addition of conspecific ovarian fluid or heterospecific ovarian fluid. Over 186 days, we quantified hatch timing, hatchling size, and developmental stage and found that differential sperm experience created biologically irrelevant (average effect size of 1.06%) changes on offspring development, which were much smaller than the effects of hybridization itself (average effect size of 10.45% for the species of the father). Since ovarian fluid drastically changes sperm experience when compared to water, we conclude that females can use ovarian fluid to bias paternity without concomitant consequences to offspring development.
Optimization of gene knockout approaches and practical solutions to sgRNA selection challenges in hPSCs with inducible Cas9 system
Authors: Ni Jie , Gong Junhao , Ran Yuqing , Bai Rui , Huang Pufeng , Zheng Zihe , Zhou Meng , You Yi , Lan Feng , Liu Xujie 
Published: July 2024

AbstractRationaleCRISPR/Cas9 has been extensively used to knock out genes, allowing the study of genetic loss-of-function in human pluripotent stem cells (hPSCs). However, the current use of the Cas9-sgRNA plasmid or iCas9 system for gene editing in hPSCs has resulted in limited and inconsistent editing efficiency, as well as labor-intensive work. Additionally, identifying single-guide RNAs (sgRNAs) with high cleavage efficiency and distinguishing them from ineffective ones, which efficiently induce frameshift INDELs (Indels and Deletions) but fail to eliminate target proteins expression, are major challenges in gene knockout experiments.MethodsThis study addresses above issues using an optimized doxycycline-induced spCas9-expressing hPSCs (hPSCs-iCas9) system. We initially developed this system by optimizing a number of parameters to maximize INDELs introducing efficiency in hPSCs-iCas9 cells. The INDELs determined by this system were then compared to predicted scores from three cleavage efficiency scoring algorithms to validate the algorithms’ accuracy and consistency. Furthermore, we conducted gene knockout using a set of sgRNAs targeting different exons of the ACE2 gene to achieve approximately 80% INDELs for each targeting locus. Western blotting was then performed to detect ACE2 protein expression levels, enabling the identification of potentially ineffective sgRNAs.ResultsSeveral critical factors, including cell tolerance to nucleofection stress, sgRNA stability, nucleofection frequency, and the cell-to-sgRNA ratio, were found to have significant impact on editing efficiency in hPSCs-iCas9. Fine-tuning these parameters markedly improved this efficiency, resulting in up to 93% INDELs for single gene knockout. The three scoring algorithms exhibited significant differences or even conflicts in scoring cleavage efficiency. Through comparing experimental observations to predicted scores, we discovered that the Benchling algorithm outperformed the other two in terms of accuracy and consistency. Furthermore, a sgRNA targeting exon 2 of ACE2 gene was quickly identified as ineffective, as evidenced by the edited cells pool containing 80% INDELs while ACE2 protein expression retained unchanged detected by Western blot.ConclusionThe findings of this study offer valuable insights into the optimal design of gene knockout experiments in hPSCs and provide practical solutions to sgRNA selection challenges for gene editing.
Multi-Model Machine Learning for Automated Identification of Rice Diseases Using Leaf Image Data
Authors: Tiwari Rovin , Patel Jaideep , Khan Nikhat Raza , Dadhich Ajay , Jain Jay Kumar 
Published: July 2024

AbstractPurposeRice is grown almost everywhere in the world but is notably prevalent in Asian nations where it serves as the main food source for nearly half of the world’s population. Yet, enduring agricultural problems like various rice diseases have been a problem for farmers and planting specialists for ages. A fast, efficient, less expensive, and reliable approach to detecting rice diseases is urgently required in agricultural information since severe rice infections could result in no harvest of grains. Automated disease monitoring of rice plants using leaf images is critical for transitioning from labor-intensive, experience-based decision-making to an automated, data-driven strategy in agricultural production. In the modern era, Artificial Intelligence (AI) is being widely investigated in various areas of the medical and plant sciences to assess and diagnose the types of diseases.MethodsThis work proposes a hybrid deep-machine learning system for the automated detection of rice plant diseases using a leaf image dataset. Benchmarked MobileNetV2 architecture is employed to extract the deep features from the input images. Obtained features are fed as input to various machine learning classifiers with different kernel functions using a 10-fold validation strategy.ResultsThe developed hybrid system attained the highest classification accuracy of 98.6%, specificity of 98.85%, and sensitivity of 97.25% using a medium neural network. The results demonstrate that the established system is computationally faster and more efficient. The proposed system is ready for testing with more databases.ConclusionsThe suggested technology accurately diagnoses various rice plant illnesses, reducing manual labor and allowing farmers to receive prompt treatment. Future research topics include incorporating cloud-based monitoring for leaf image capture in non-connected farms, as well as building mobile IoT platforms for continuous screening.