bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical Study of Diesel Engine with Different Injection Strategies
Authors: Zhao Yiting , Dong Pingping , Wu Shi , Feng Shiquan
Published: February 2023

In this paper, a reduced mechanism for diesel engines is developed, including 148 species and 647 reactions. The reduced mechanism includes NOX and soot sub-mechanism. Based on the reduced mechanism, a three-dimensional simulation of a diesel engine is carried out. Diesel is injected directly into the cylinder. By changing the strategy of diesel injection, the combustion in the engine cylinder under fixed conditions is simulated, and the pollution of combustion is analyzed. According to the simulation results, it is found that the injection strategy can change the temperature and pressure in the cylinder. Hence a better strategy will improve the combustion efficiency, reduce the generation of no and no2, and maybe reduce the mass fraction of soot et.al. The simulation results showed that different injection strategies have a great influence on the in-cylinder pressure, temperature, and pollution. The conclusion will be helpful in improving the fuel injection strategy and improving the performance of diesel engines.
Regional Comprehensive Energy System Planning Considering Construction Cost under Dual Carbon Goals
Authors: Wei Dongni , Che Bin , Zhang Zelong , Qi Caijuan , Dong Xiaojing
Published: February 2023

Under the dual-carbon goal of carbon peaking and carbon neutrality, from the perspectives of energy supply, coupling, consumption, etc., analyzing the carbon reduction path of the regionally integrated energy system and making an overall plan for it is the key to carbon emission reduction in the power industry, boosting an important starting point for the realization of the “double carbon” goal. To this end, under the constraints of carbon targets, a regional comprehensive energy system planning model considering construction cost is proposed that considers optimal construction timing and demand response. First, regional carbon emission quotas were allocated through the baseline method, and a regional comprehensive energy system planning model was established. Finally, the future challenges faced by the regional low-carbon integrated energy system have been prospected.
Experimental Study on Geometrical Characteristics of a Square Turbulent Buoyant Jet Flame
Authors: Sun Y , Liu N , Gao W
Published: February 2023

This paper gives the experimental results for the buoyant jet diffusion flame in square burners. The flame height and lift-off were measured and discussed. The results show that the normalized flame height and lift-off height of square flames are lower than that of round flames with the same experimental conditions, which indicates enhanced air entrainment in square flames. The model of flame height based on the flame Froude-number, which integrates a correction factor to account for the enhancement of air entrainment, reasonably collapses the square flame data under different experimental cases. The critical Froude number for the transition from buoyancy to momentum controlled regime of a square jet flame is highly dependent on the fuel type and burner size. The lift-off height of the square jet flames increases linearly when the initial velocity increases, but also depends on the fuel type and burner size. A unified correlation using a dimensionless flow number derived from the mixedness-reactedness flamelet model is established, which reasonably predicts the lift-off distances of square jet flames.
Experimental Research on Photovoltaic-Temperature Difference Hybrid Power Generation System
Authors: Lin Yujie , Ma Xinxia , Qi Yumin , Wu Tianyu
Published: February 2023

With the increasingly prominent environmental problems, more and more attention has been paid to new energy power generation. A photovoltaic power generation is currently a well-developed form of new energy power generation. However, in the process of photovoltaic power generation, only part of the wavelength of light can be used to generate power. The rest will be converted to heat, which increases the temperature of the photovoltaic panels, resulting in lower power generation efficiency. In order to improve the efficiency of photovoltaic panels, a photovoltaic-temperature difference (PV-TE) hybrid power generation system can be formed by combining photovoltaic power generation with the thermoelectric generation, which is based on the Seebeck effect. Based on this, we set up the photovoltaic-temperature hybrid power system test bench for testing. The results show that when the working circuit of the TE device is closed, the residual heat of the photovoltaic panel can be used to generate power. It can also cool down the photovoltaic panel at the same time. Thus, the output power increase by about 0.68%.
Application of LSTM Method Combined with Feature Optimization in Chiller Failure Detection
Authors: He Yan , Zhou Chuanhui , Hu Yunpeng
Published: February 2023

Aiming at the characteristics of a long short-term memory network (LSTM) which is suitable for processing high-dimensional, strongly coupled, and highly time-dependent data, it combines the advantages of feature selection to reduce the difficulty of learning tasks and improve the performance of model fault diagnosis. This paper proposes an LSTM method combining sequential floating forward search with integrated feature selection for chiller sensor deviation fault detection. The detection results of the proposed method are compared with those of the single feature selection method, and it is concluded that the detection efficiency of the proposed method in chiller sensor deviation fault detection is significantly better than that of the single feature selection method.
Numerical Simulation of Icing Characteristics on the Surface of an Aero-engine Guide Blade
Authors: Zhu Qiankun , Guan Ning
Published: February 2023

This paper takes the guiding blade of a type of aero-engine needle as the research object for the icing problem of the guiding blade and uses the numerical simulation method to simulate the airflow field, supercooled water droplet impact and icing situation on the surface of the guiding blade under different flight conditions, to analyze the influence of flight speed on the icing situation of the guiding blade. It is found that the incoming flow velocity has a significant effect on the icing of the guide vanes, with the flight velocity increasing from 34m/s to 102m/s, the icing of the leading edge of the vanes increases by 98.1%; meanwhile, the icing range of the guide vanes is significantly related to the incoming flow velocity, with the flight velocity increasing, the icing range expands significantly; in addition, the icing range gradually expands from the root to the outermost end of the vanes, with the flow velocity The maximum icing range at 102m/s was extended from 17% to 20% of the chord length.
Based on Phase Change Materials of Research on Compressor Tip Clearance Control
Authors: Peng RenLiang , Li JiangHong , Cai FeiChao
Published: February 2023

The reduction of tip clearance height of the compressor has an important influence on the improvement of compressor efficiency. The goal of tip clearance control technology is to reduce clearance height. Firstly, the phase change principle of phase change materials is analyzed. Under temperature excitation, when the phase change material is in the solid-liquid two-phase region, the volume of the phase change material will change with temperature. A phase change mechanism for tip clearance control was developed, and the clearance control scheme was designed. Finally, the feasibility of the gap control scheme is verified by the gap control function experiment.
Model Development and Numerical Investigation of the Slag Formation in an Entrained-Flow Gasifier
Authors: Jiang Shuai , Zhou Quan , Ge Zhi-Hong , Chen Wei , Xing Jing-Wen , Zhang Wen-Bin , Jiang Cong-Bin , Ding Jian-Ping
Published: February 2023

Understanding the formation and the flow of molten slag in the water-cooled membrane wall pulverized coal entrained flow gasifier was very important to determine the wall heat transfer and the reactor operation. In the standard model’s CFD simulation, the wall boundary condition was only able to be set as a fixed heat flow, which was not accurate in describing the influence of the temperature distribution and slag distribution on heat transfer under the actual situation. In this work, an extensive and detailed slag model was established and validated. The complete slag model included a particle capture model, wall heat transfer model, and slag thickness model through real-time coupling with CFD. Particle capture criteria were discussed and used to decide the particle behavior if particles collide on the reactor wall. The slag flow model was established from this criterion to calculate the mass flow rate and the thickness of the liquid slag. The slag thickness model calculated the heat transfer at each wall location, and the coupled temperature, slag thickness, and heat transfer curves were finally obtained through iteration. The models were proved reliable by comparing the simulation with industrial results. The model predicted the slag thickness of liquid and solid slags, the wall temperature, and the heat flux through the wall. The model’s establishment further understood the slag formation, slag thickness distribution, and wall temperature distribution. It also played a guiding function in industrial operations.
The XeBRA platform for liquid xenon time projection chamber development
Authors: Baur Daniel , Bismark Alexander , Brown Adam , Dierle Julia , Fischer Horst , Glade-Beucke Robin , Grigat Jaron , Kaminsky Basho , Kuger Fabian , Lindemann Sebastian , Masson Darryl , Meinhardt Patrick , Rajado Silva Mariana , Schumann Marc , Tönnies Florian , Toschi Francesco
Published: February 2023

XeBRA is a flexible cryogenic platform designed to perform
research and development for liquid xenon detectors searching for
rare events. Its extra-large outer cryostat makes it possible to
install a wide variety of detector designs. We present the system,
including its cryogenic, gas handling, data acquisition and slow
control subsystems. Two dual phase time projection chambers with
sensitive masses at the 1 kg scale have so far been operated in
XeBRA. Using data from these, we determine the field-dependence of
the electron drift velocity in liquid xenon. We also measure the
relative charge and light yields for 41.5 keV energy deposits from 
83mKr with electric drift fields between 50 V/cm and
677 V/cm.
Carbodiimide crosslinked decellularized lenticules as a drug carrier for sustained antibacterial eye treatments
Authors: Rao Jing , Zhou Qizhi , Chen Jiansu , Gu Jianing , Wang Yini , Liu Yonghuan
Published: February 2023

In this study, the drug-loading and antibacterial activity of carbodiimide/N-hydroxysuccinimide (EDC/NHS) crosslinked decellularized lenticules (CDLs) were evaluated. Small incision lenticule extraction derived lenticules were decellularized and modified with crosslinking concentrations of 0.00 (E/L00, non-crosslinked), 0.01 (E/L01), 0.05 (E/L05) and 0.25 mmol (E/L25) EDC per mg lenticules at 5:1 EDC/NHS ratios with non-decellularized non-crosslinked lenticules (NDLs) as controls. NDLs and EDC/NHS CDLs had similar water contents. The light transmittance percentages (400–800 nm) were 91.55 ± 1.16%, 88.68 ± 1.19%, 80.86 ± 1.94%, 85.12 ± 2.42% and 85.62 ± 2.84% for NDLs, E/L00, E/L01, E/L05 and E/L25, respectively (P < 0.01). The EDC/NHS CDLs (diameter: 6.36 ± 0.18 mm; central thickness: 117.31 ± 3.46 μm) were soaked in 3% (wt./vol.) levofloxacin (LEV) solution for 3 h. The drug release concentrations of LEV-impregnated EDC/NHS CDLs were determined by high-performance liquid chromatography. Zone inhibition (ZOI) against Staphylococcus aureus of E/L01, E/L05 and E/L25 were superior to E/L00 CDLs (P < 0.01) and among the different crosslinked groups, E/L05 lenticules produced the largest ZOIs and their drug concentration release over 21 d was the highest. EDC/NHS crosslinking can improve the drug-loading effect and antibacterial activity of decellularized lenticules. LEV-impregnated EDC/NHS CDLs are promising drug delivery carriers.
Diffusion with stochastic resetting screened by a semipermeable interface
Authors: Bressloff Paul C
Published: February 2023

In this paper we consider the diffusive search for a bounded target

Ω
∈

R

d

with its boundary

∂
Ω

totally absorbing. We assume that the target is surrounded by a semipermeable interface given by the closed surface

with

. That is, the interface totally surrounds the target and thus partially screens the diffusive search process. We also assume that the position of the diffusing particle (searcher) randomly resets to its initial position x
0 according to a Poisson process with a resetting rate r. The location x
0 is taken to be outside the interface,

, which means that resetting does not occur when the particle is within the interior of

. (Otherwise, the particle would have to cross the interface in order to reset to x
0.) Hence, the semipermeable interface also screens out the effects of resetting. We illustrate the theory by explicitly solving the boundary value problem for a three-dimensional (3D) spherically symmetric interface and a concentric spherical target. We calculate the mean first passage time (MFPT) to find (be absorbed by) the target and explore its behavior as a function of the permeability κ
0 of the interface and the radius of the interface R. In particular, we find that increasing R for a fixed target size reduces the MFPT and increases the optimal resetting rate at which the MFPT is minimized. We also find that the sensitivity of the MFPT to changes in κ
0 is a decreasing function of R. Finally, we introduce a stochastic single-particle realization of the search process based on a generalization of so-called snapping out Brownian motion (BM). The latter sews together successive rounds of reflecting BM on either side of the interface. The main challenge is establishing that the probability density generated by the snapping out BM satisfies the permeable boundary conditions at the interface. We show how this can be achieved using renewal theory.
Partially coherent sources whose coherent modes are spatiotemporal optical vortex beams
Authors: Hyde IV Milo W , Korotkova Olga , Spencer Mark F
Published: February 2023

We analyze three non-stationary partially coherent sources whose coherent modes are spatiotemporal optical vortex (STOV) beams. Using spatiotemporal (ST) Bessel–Gauss and Laguerre–Gauss beams (STOV-carrying solutions to the space-time paraxial wave equation) as eigenfunctions in the coherent-modes representation of the mutual coherence function, we derive the ST versions of J
0-Bessel-correlated, I

n
-Bessel-correlated, and twisted Gaussian Schell-model beams. We model, in simulation, these ST random beams via their coherent-modes expansions, compare and contrast the simulated results to theory, and analyze/discuss their free-space propagation characteristics. The work presented in this paper will be useful for simulating or physically generating these ST beams for use in applications or future studies.
Powerful but short-lived: pop bands as influencers of climate discussions on twitter
Authors: Deb Briti , Murali Ranjini , Nagendra Harini
Published: February 2023

Influencers are considered important in raising environmental awareness on social media. In February 2021, BlackPink, a popular popband, were announced as official advocates for COP26, which was followed by tweets on Twitter. We aimed to study the effectiveness of influencers for climate communication on social media. We analyzed the spread of tweets and the duration of effects over a period of four weeks following the announcement. We found that on the day of the event there were 1518 primary tweets which were liked and retweeted 2600 times which reduced to 62 primary tweets and 209 retweets and likes four weeks after the event. We also found that the influencer engaged a community that might not have been otherwise engaged, specifically fans of BlackPink, but this was short lived. Our findings suggest that influencers are potentially important to raise awareness, but efforts are needed to sustain engagement.
Key bottlenecks and distinct contradictions in fast commercialization of perovskite solar cells
Authors: Liu Wenguang , Raza Hasan , Hu Xiaodong , Liu Sanwan , Liu Zonghao , Chen Wei
Published: February 2023

Despite significant improvements in photo-electricity conversion efficiency of perovskite solar cells (PSCs) over the past several years, this emerging photovoltaic technology is still years away from large-scale commercial application. In this review, important research progresses on PSCs’ ‘golden triangle’ parameters of efficiency, stability, and cost in literatures were objectively analyzed. We focused on their key bottlenecks and distinct contradictions hindering their fast commercialization. We also proposed the most urgent directions requiring intensive research and development input in the coming years to speed up the commercialization process of PSCs.
Initial ciliary assembly in Chlamydomonas requires Arp2/3 complex–dependent endocytosis
Authors: Bigge Brae M. , Rosenthal Nicholas E. , Avasthi Prachee
Published: February 2023

Using the ciliary model system Chlamydomonas reinhardtii, we find that the Arp2/3 complex is required for ciliary maintenance and for initial ciliary assembly. We also show that endocytosis occurs in these cells. Finally, we show that ciliary membrane proteins can and do come from the cell body plasma membrane and that this requires the Arp2/3 complex. Therefore, we propose a model where Arp2/3 complex-mediated endocyosis is needed to reclaim cell body plasma membrane for early ciliary assembly.
An improved hierarchical variational autoencoder for cell–cell communication estimation using single-cell RNA-seq data
Authors: Liu Shuhui , Zhang Yupei , Peng Jiajie , Shang Xuequn
Published: February 2023

Analysis of cell–cell communication (CCC) in the tumor micro-environment helps decipher the underlying mechanism of cancer progression and drug tolerance. Currently, single-cell RNA-Seq data are available on a large scale, providing an unprecedented opportunity to predict cellular communications. There have been many achievements and applications in inferring cell–cell communication based on the known interactions between molecules, such as ligands, receptors and extracellular matrix. However, the prior information is not quite adequate and only involves a fraction of cellular communications, producing many false-positive or false-negative results. To this end, we propose an improved hierarchical variational autoencoder (HiVAE) based model to fully use single-cell RNA-seq data for automatically estimating CCC. Specifically, the HiVAE model is used to learn the potential representation of cells on known ligand–receptor genes and all genes in single-cell RNA-seq data, respectively, which are then utilized for cascade integration. Subsequently, transfer entropy is employed to measure the transmission of information flow between two cells based on the learned representations, which are regarded as directed communication relationships. Experiments are conducted on single-cell RNA-seq data of the human skin disease dataset and the melanoma dataset, respectively. Results show that the HiVAE model is effective in learning cell representations, and transfer entropy could be used to estimate the communication scores between cell types.
MiRNA–gene network embedding for predicting cancer driver genes
Authors: Peng Wei , Wu Rong , Dai Wei , Ning Yu , Fu Xiaodong , Liu Li , Liu Lijun
Published: February 2023

The development and progression of cancer arise due to the accumulation of mutations in driver genes. Correctly identifying the driver genes that lead to cancer development can significantly assist the drug design, cancer diagnosis and treatment. Most computer methods detect cancer drivers based on gene–gene networks by assuming that driver genes tend to work together, form protein complexes and enrich pathways. However, they ignore that microribonucleic acid (RNAs; miRNAs) regulate the expressions of their targeted genes and are related to human diseases. In this work, we propose a graph convolution network (GCN) approach called GM-GCN to identify the cancer driver genes based on a gene–miRNA network. First, we constructed a gene–miRNA network, where the nodes are miRNAs and their targeted genes. The edges connecting miRNA and genes indicate the regulatory relationship between miRNAs and genes. We prepared initial attributes for miRNA and genes according to their biological properties and used a GCN model to learn the gene feature representations in the network by aggregating the features of their neighboring miRNA nodes. And then, the learned features were passed through a 1D convolution module for feature dimensionality change. We employed the learned and original gene features to optimize model parameters. Finally, the gene features learned from the network and the initial input gene features were fed into a logistic regression model to predict whether a gene is a driver gene. We applied our model and state-of-the-art methods to predict cancer drivers for pan-cancer and individual cancer types. Experimental results show that our model performs well in terms of the area under the receiver operating characteristic curve and the area under the precision-recall curve compared to state-of-the-art methods that work on gene networks. The GM-GCN is freely available via https://github.com/weiba/GM-GCN.
High-accuracy protein model quality assessment using attention graph neural networks
Authors: Zhang Peidong , Xia Chunqiu , Shen Hong-Bin
Published: February 2023

Great improvement has been brought to protein tertiary structure prediction through deep learning. It is important but very challenging to accurately rank and score decoy structures predicted by different models. CASP14 results show that existing quality assessment (QA) approaches lag behind the development of protein structure prediction methods, where almost all existing QA models degrade in accuracy when the target is a decoy of high quality. How to give an accurate assessment to high-accuracy decoys is particularly useful with the available of accurate structure prediction methods. Here we propose a fast and effective single-model QA method, QATEN, which can evaluate decoys only by their topological characteristics and atomic types. Our model uses graph neural networks and attention mechanisms to evaluate global and amino acid level scores, and uses specific loss functions to constrain the network to focus more on high-precision decoys and protein domains. On the CASP14 evaluation decoys, QATEN performs better than other QA models under all correlation coefficients when targeting average LDDT. QATEN shows promising performance when considering only high-accuracy decoys. Compared to the embedded evaluation modules of predicted ${C}_{\alpha^{-}} RMSD$ (pRMSD) in RosettaFold and predicted LDDT (pLDDT) in AlphaFold2, QATEN is complementary and capable of achieving better evaluation on some decoy structures generated by AlphaFold2 and RosettaFold. These results suggest that the new QATEN approach can be used as a reliable independent assessment algorithm for high-accuracy protein structure decoys.
Improved drug response prediction by drug target data integration via network-based profiling
Authors: Pak Minwoo , Lee Sangseon , Sung Inyoung , Koo Bonil , Kim Sun
Published: February 2023

Drug response prediction (DRP) is important for precision medicine to predict how a patient would react to a drug before administration. Existing studies take the cell line transcriptome data, and the chemical structure of drugs as input and predict drug response as IC50 or AUC values. Intuitively, use of drug target interaction (DTI) information can be useful for DRP. However, use of DTI is difficult because existing drug response database such as CCLE and GDSC do not have information about transcriptome after drug treatment. Although transcriptome after drug treatment is not available, if we can compute the perturbation effects by the pharmacologic modulation of target gene, we can utilize the DTI information in CCLE and GDSC. In this study, we proposed a framework that can improve existing deep learning-based DRP models by effectively utilizing drug target information. Our framework includes NetGP, a module to compute gene perturbation scores by the network propagation technique on a network. NetGP produces genes in a ranked list in terms of gene perturbation scores and the ranked genes are input to a multi-layer perceptron to generate a fixed dimension vector for the integration with existing DRP models. This integration is done in a model-agnostic way so that any existing DRP tool can be incorporated. As a result, our framework boosts the performance of existing DRP models, in 64 of 72 comparisons. The performance gains are larger especially for test scenarios with samples with unseen drugs by large margins up to 34% in Pearson’s correlation coefficient.
HGTphyloDetect: facilitating the identification and phylogenetic analysis of horizontal gene transfer
Authors: Yuan Le , Lu Hongzhong , Li Feiran , Nielsen Jens , Kerkhoven Eduard J
Published: February 2023

Background

Horizontal gene transfer (HGT) is an important driver in genome evolution, gain-of-function, and metabolic adaptation to environmental niches. Genome-wide identification of putative HGT events has become increasingly practical, given the rapid growth of genomic data. However, existing HGT analysis toolboxes are not widely used, limited by their inability to perform phylogenetic reconstruction to explore potential donors, and the detection of HGT from both evolutionarily distant and closely related species.

Results

In this study, we have developed HGTphyloDetect, which is a versatile computational toolbox that combines high-throughput analysis with phylogenetic inference, to facilitate comprehensive investigation of HGT events. Two case studies with Saccharomyces cerevisiae and Candida versatilis demonstrate the ability of HGTphyloDetect to identify horizontally acquired genes with high accuracy. In addition, HGTphyloDetect enables phylogenetic analysis to illustrate a likely path of gene transmission among the evolutionarily distant or closely related species.

Conclusions

The HGTphyloDetect computational toolbox is designed for ease of use and can accurately find HGT events with a very low false discovery rate in a high-throughput manner. The HGTphyloDetect toolbox and its related user tutorial are freely available at https://github.com/SysBioChalmers/HGTphyloDetect.
Improving drug–drug interactions prediction with interpretability via meta-path-based information fusion
Authors: Zhao Weizhong , Yuan Xueling , Shen Xianjun , Jiang Xingpeng , Shi Chuan , He Tingting , Hu Xiaohua
Published: February 2023

Drug–drug interactions (DDIs) are compound effects when patients take two or more drugs at the same time, which may weaken the efficacy of drugs or cause unexpected side effects. Thus, accurately predicting DDIs is of great significance for the drug development and the drug safety surveillance. Although many methods have been proposed for the task, the biological knowledge related to DDIs is not fully utilized and the complex semantics among drug-related biological entities are not effectively captured in existing methods, leading to suboptimal performance. Moreover, the lack of interpretability for the predicted results also limits the wide application of existing methods for DDIs prediction. In this study, we propose a novel framework for predicting DDIs with interpretability. Specifically, we construct a heterogeneous information network (HIN) by explicitly utilizing the biological knowledge related to the procedure of inducing DDIs. To capture the complex semantics in HIN, a meta-path-based information fusion mechanism is proposed to learn high-quality representations of drugs. In addition, an attention mechanism is designed to combine semantic information obtained from meta-paths with different lengths to obtain final representations of drugs for DDIs prediction. Comprehensive experiments are conducted on 2410 approved drugs, and the results of predictive performance comparison show that our proposed framework outperforms selected representative baselines on the task of DDIs prediction. The results of ablation study and cold-start scenario indicate that the meta-path-based information fusion mechanism red is beneficial for capturing the complex semantics among drug-related biological entities. Moreover, the results of case study demonstrate that the designed attention mechanism is able to provide partial interpretability for the predicted DDIs. Therefore, the proposed method will be a feasible solution to the task of predicting DDIs.
MAK: a machine learning framework improved genomic prediction via multi-target ensemble regressor chains and automatic selection of assistant traits
Authors: Liang Mang , Cao Sheng , Deng Tianyu , Du Lili , Li Keanning , An Bingxing , Du Yueying , Xu Lingyang , Zhang Lupei , Gao Xue , Li Junya , Guo Peng , Gao Huijiang
Published: February 2023

Incorporating the genotypic and phenotypic of the correlated traits into the multi-trait model can significantly improve the prediction accuracy of the target trait in animal and plant breeding, as well as human genetics. However, in most cases, the phenotypic information of the correlated and target trait of the individual to be evaluated was null simultaneously, particularly for the newborn. Therefore, we propose a machine learning framework, MAK, to improve the prediction accuracy of the target trait by constructing the multi-target ensemble regression chains and selecting the assistant trait automatically, which predicted the genomic estimated breeding values of the target trait using genotypic information only. The prediction ability of MAK was significantly more robust than the genomic best linear unbiased prediction, BayesB, BayesRR and the multi trait Bayesian method in the four real animal and plant datasets, and the computational efficiency of MAK was roughly 100 times faster than BayesB and BayesRR.
Cognitive biases in surgery: systematic review
Authors: Armstrong Bonnie A , Dutescu Ilinca A , Tung Arthur , Carter Diana N , Trbovich Patricia L , Wong Sherman , Saposnik Gustavo , Grantcharov Teodor
Published: February 2023

Background

Although numerous studies have established cognitive biases as contributors to surgical adverse events, their prevalence and impact in surgery are unknown. This review aimed to describe types of cognitive bias in surgery, their impact on surgical performance and patient outcomes, their source, and the mitigation strategies used to reduce their effect.

Methods

A literature search was conducted on 9 April and 6 December 2021 using MEDLINE, Embase, PsycINFO, Scopus, Web of Science, Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews. Included studies investigated how cognitive biases affect surgery and the mitigation strategies used to combat their impact. The National Institutes of Health tools were used to assess study quality. Inductive thematic analysis was used to identify themes of cognitive bias impact on surgical performance.

Results

Thirty-nine studies were included, comprising 6514 surgeons and over 200 000 patients. Thirty-one types of cognitive bias were identified, with overconfidence, anchoring, and confirmation bias the most common. Cognitive biases differentially influenced six themes of surgical performance. For example, overconfidence bias associated with inaccurate perceptions of ability, whereas anchoring bias associated with inaccurate risk–benefit estimations and not considering alternative options. Anchoring and confirmation biases associated with actual patient harm, such as never events. No studies investigated cognitive bias source or mitigation strategies.

Conclusion

Cognitive biases have a negative impact on surgical performance and patient outcomes across all points of surgical care. This review highlights the scarcity of research investigating the sources that give rise to cognitive biases in surgery and the mitigation strategies that target these factors.
A TMC8 splice variant causes epidermodysplasia verruciformis in a Pakistani family
Authors: Xiong Xing , Uddin Syed Ashraf , Munir Sobia , Cesarato Nicole , Thiele Holger , Hassan Noor , Kumar Surjeet , Rehman Fazal Ur , Naeem Muhammad , Wali Abdul , Basit Sulman , Basmanav F Buket , Ayub Muhammad , Betz Regina C
Published: February 2023

We identified a novel homozygous disease-causing variant in TMC8 in a Pakistani family with epidermodysplasia verruciformis (EV). The phenotype of EV in the affected individuals was most probably caused by an aberrant splicing process. The molecular genetic findings in our patients expand the mutational spectrum of the disease.
Relative Effectiveness of Coronavirus Disease 2019 Vaccination and Booster Dose Combinations Among 18.9 Million Vaccinated Adults During the Early Severe Acute Respiratory Syndrome Coronavirus 2 Omicron Period—United States, 1 January 2022 to 31 March 2022
Authors: Kompaniyets Lyudmyla , Wiegand Ryan E , Oyalowo Adewole C , Bull-Otterson Lara , Egwuogu Heartley , Thompson Trevor , Kahihikolo Ka‘imi , Moore Lori , Jones-Jack Nkenge , El Kalach Roua , Srinivasan Arunkumar , Messer Ashley , Pilishvili Tamara , Harris Aaron M , Gundlapalli Adi V , Link-Gelles Ruth , Boehmer Tegan K
Published: February 2023

Background

Small sample sizes have limited prior studies' ability to capture severe COVID-19 outcomes, especially among Ad26.COV2.S vaccine recipients. This study of 18.9 million adults aged ≥18 years assessed relative vaccine effectiveness (rVE) in three recipient cohorts: (1) primary Ad26.COV2.S vaccine and Ad26.COV2.S booster (2 Ad26.COV2.S), (2) primary Ad26.COV2.S vaccine and mRNA booster (Ad26.COV2.S+mRNA), (3) two doses of primary mRNA vaccine and mRNA booster (3 mRNA).

Methods

We analyzed two de-identified datasets linked using privacy-preserving record linkage (PPRL): insurance claims and retail pharmacy COVID-19 vaccination data. We assessed the presence of COVID-19 diagnosis during January 1-March 31, 2022 in: (1) any claim, (2) outpatient claim, (3) emergency department (ED) claim, (4) inpatient claim, and (5) inpatient claim with intensive care unit (ICU) admission. rVE for each outcome comparing three recipient cohorts (reference: two Ad26.COV2.S doses) was estimated from adjusted Cox proportional hazards models.

Results

Compared with two Ad26.COV2.S doses, Ad26.COV2.S+mRNA and three mRNA doses were more effective against all COVID-19 outcomes, including 57% (95% CI: 52–62) and 62% (95% CI: 58–65) rVE against an ED visit; 44% (95% CI: 34–52) and 54% (95% CI: 48–59) rVE against hospitalization; and 48% (95% CI: 22–66) and 66% (95% CI: 53–75) rVE against ICU admission, respectively.

Conclusions

This study demonstrated that Ad26.COV2.S + mRNA doses were as good as three doses of mRNA, and better than two doses of Ad26.COV2.S. Vaccination continues to be an important preventive measure for reducing the public health impact of COVID-19.
Mitral valve repair update: simple, intuitive and physiological techniques, using running sutures (part II)
Authors: Kofidis Theo
Published: February 2023

Modern mitral valve techniques are variable and, mostly, well-validated. However, they are skill dependent, and some lack of standardization, regarding the number and positioning of the cords, or the management of the targeted pathology. We continue the introduction of novel, perhaps more intuitive, aiming to simplify mitral valve repair, while achieving a reproducible result, of which some we have already verified.
Serum testosterone and sex hormone–binding globulin are inversely associated with leucocyte telomere length in men: a cross-sectional analysis of the UK Biobank study
Authors: Marriott Ross J , Murray Kevin , Budgeon Charley A , Codd Veryan , Hui Jennie , Arscott Gillian M , Beilby John P , Hankey Graeme J , Wittert Gary A , Wu Frederick C W , Yeap Bu B
Published: February 2023

Objective

Older men on an average have lower testosterone concentrations, compared with younger men, and more age-related comorbidities. Whether lower testosterone concentrations contribute to biological ageing remains unclear. Shorter telomeres are a marker for biological age. We tested the hypothesis that testosterone concentrations are associated with leucocyte telomere length (LTL), in middle- to older-aged men.

Design

Cross-sectional analysis of the UK Biobank study, involving community-dwelling men aged 40-69 years.

Methods

Serum testosterone and sex hormone–binding globulin (SHBG) were assayed. Free testosterone was calculated (cFT). Leucocyte telomere length was measured using polymerase chain reaction. Multivariable models were used to assess associations of hormones with standardised LTL.

Results

In 167 706 men, median age 58 years, adjusting for sociodemographic, lifestyle, and medical factors, total testosterone was inversely associated with standardised LTL, which was 0.09 longer (95% confidence interval [CI], 0.08-0.10, P < .001) in men with total testosterone at median of lowest quintile [Q1] vs highest [Q5]. This relationship was attenuated after additional adjustment for SHBG (0.03 longer, CI = 0.02-0.05, P = .003). The association between cFT and LTL was similar in direction but lower in magnitude. In multivariable analysis, SHBG was inversely associated with standardised LTL, which was 0.12 longer (CI = 0.10-0.13, P < .001) for SHBG at median Q1 vs Q5. Results were similar with testosterone included in the model (0.10 longer, CI = 0.08-0.12, P < .001).

Conclusions

Total testosterone and SHBG were independently and inversely associated with LTL. Men with higher testosterone or SHBG had shorter telomeres, arguing against a role for testosterone to slow biological ageing in men.
Family building after diagnosis of premature ovarian insufficiency: a cross-sectional survey in 324 women
Authors: Cambray Solange , Dubreuil Sophie , Tejedor Isabelle , Dulon Jérôme , Touraine Philippe
Published: February 2023

Objective

The diagnosis of premature ovarian insufficiency (POI) is a traumatic event for many patients that involves poor fertility prognosis. After such diagnosis, spontaneous pregnancies are rare. The alternatives for building a family are oocyte donation, embryo donation, and adoption. However, we have few information on how many women with POI finally built a family after the diagnosis and which alternative they chose.

Design

We performed a cross-sectional, descriptive study.

Methods

We conducted a survey of all the women who consulted for POI in the department of endocrinology and reproductive medicine at la Pitié Salpêtrière between May 31, 1991, and January 12, 2021. We included patients who continued to be followed up regularly by our department or were contacted by mail or phone between June and September 2021. We excluded patients with Turner syndrome and POI secondary to oncological treatment and patients under 18 at the time of the survey.

Results

985 patients were referred to the department for POI, and 324 patients were finally analyzed. 41% of the women who wanted to build a family had children after the diagnosis: 53.9% by oocyte donation, 1 woman by embryo donation, 5.6% after ovarian stimulation, 13.5% by adoption, and 25.8% who had spontaneous pregnancy after a mean time of 2.5 years. Spontaneous pregnancy rate was 8.6% in the whole cohort.

Conclusions

Having children after a diagnosis of POI is not uncommon but more often results from oocyte donation. This study will provide enlightened information for newly diagnosed women on the possibilities to build a family after POI diagnosis.
Effects of remote patient management on self-care behaviour in heart failure patients: results from the randomized TIM-HF2 trial
Authors: Deckwart Oliver , Koehler Kerstin , Lezius Susanne , Prescher Sandra , Koehler Friedrich , Winkler Sebastian
Published: February 2023

Aims

Remote patient management (RPM) in heart failure (HF) patients has beneficial clinical effects. This analysis investigates the effects of RPM used in the Telemedical Interventional Management in Heart Failure II (TIM-HF2) trial on HF-specific self-care.

Methods and results

From 2013 to 2017, 1538 HF outpatients (age 70.3 ± 10.5 years, 70% men, 52%/47% NYHA II/III, 65% LVEF ≤45%) with a recent HF hospitalization were included to the study and randomized to usual care (UC) plus RPM (n = 796) or UC only (n = 775), with a 12-month follow-up. Self-reported self-care behaviour at baseline and at end of study was assessed with the 9-item European Heart Failure Self-care Behaviour Scale (EHFScBS-9), obtaining 1321 patients with valid baseline and follow-up questionnaires for the analysis. EHFScBS-9 sum scores increased in the RPM group (n = 667) from 78.7 ± 17 to 84.5 ± 14 and in the UC group (n = 654) from 79.0 ± 17 to 80.0 ± 16 from baseline to 12 months [difference in means (MD) 4.58 (3.02, 6.14); P < 0.001] with highest improvement [8.66 (3.52; 13.81)] in patients living alone and having an inadequate (<70) baseline EHFScBS-9. There were differences between both groups in item ‘I weight myself every day’ [MD −1.13 (−1.24, −1.02); P < 0.001] and item ‘I take my medication as prescribed’ [MD −0.06 (−0.10, −0.01); P = 0.014]. No correlation was found between the EHFScBS-9 score and the efficacy of RPM on the TIM-HF2 primary endpoint of percentage of days lost due to unplanned cardiovascular hospitalization or death of any cause.

Conclusions

RPM improves HF-specific self-care behaviour by achieving a better adherence to recommended HF regimen.

Registration

ClinicalTrials.gov: NCT01878630
High-intensity interval training in cardiac rehabilitation: a multi-centre randomized controlled trial
Authors: McGregor Gordon , Powell Richard , Begg Brian , Birkett Stefan T , Nichols Simon , Ennis Stuart , McGuire Scott , Prosser Jonathon , Fiassam Olivier , Hee Siew Wan , Hamborg Thomas , Banerjee Prithwish , Hartfiel Ned , Charles Joanna M , Edwards Rhiannon T , Drane Aimee , Ali Danish , Osman Faizel , He Hejie , Lachlan Tom , Haykowsky Mark J , Ingle Lee , Shave Rob
Published: February 2023

Background

There is a lack of international consensus regarding the prescription of high-intensity interval training (HIIT) for people with coronary artery disease (CAD) attending cardiac rehabilitation (CR).

Aims

To assess the clinical effectiveness and safety of low-volume HIIT compared with moderate-intensity steady-state (MISS) exercise training for people with CAD.

Methods and results

We conducted a multi-centre RCT, recruiting 382 patients from 6 outpatient CR centres. Participants were randomized to twice-weekly HIIT (n = 187) or MISS (n = 195) for 8 weeks. HIIT consisted of 10 × 1 min intervals of vigorous exercise (>85% maximum capacity) interspersed with 1 min periods of recovery. MISS was 20–40 min of moderate-intensity continuous exercise (60–80% maximum capacity). The primary outcome was the change in cardiorespiratory fitness [peak oxygen uptake (VO2 peak)] at 8 week follow-up. Secondary outcomes included cardiovascular disease risk markers, cardiac structure and function, adverse events, and health-related quality of life. At 8 weeks, VO2peak improved more with HIIT (2.37 mL.kg−1.min−1; SD, 3.11) compared with MISS (1.32 mL.kg−1.min−1; SD, 2.66). After adjusting for age, sex, and study site, the difference between arms was 1.04 mL.kg−1.min−1 (95% CI, 0.38 to 1.69; P = 0.002). Only one serious adverse event was possibly related to HIIT.

Conclusions

In stable CAD, low-volume HIIT improved cardiorespiratory fitness more than MISS by a clinically meaningful margin. Low-volume HIIT is a safe, well-tolerated, and clinically effective intervention that produces short-term improvement in cardiorespiratory fitness. It should be considered by all CR programmes as an adjunct or alternative to MISS.

Trial registration

ClinicalTrials.gov: NCT02784873. https://clinicaltrials.gov/ct2/show/NCT02784873.
MicroMundo: experimental project fostering contribution to knowledge on antimicrobial resistance in secondary school
Authors: Robredo Beatriz , Fernández-Fernández Rosa , Torres Carmen , Ladrera Rubén
Published: February 2023

Antimicrobial resistance (AMR) has become a serious global health threat. Education could play a decisive role, so the scope of innovative educational projects, such as MicroMundo, should be analysed. MicroMundo is a service-learning project for the exploration of microbial biodiversity in soils in search of new antibiotics. In order to evaluate the contribution of MicroMundo to the improvement of knowledge about AMR as well as the optimal age of the participants, an open questionnaire before and after the educational intervention (for secondary school students) and a satisfaction survey (for all participants) were carried out. Programme instruction began in university and continued through secondary school; 14 teachers (phase 1) and 137 students from three educational levels (phase 2) participated. MicroMundo was successfully implemented, showing a statistically significant improvement in knowledge about antibiotics, resistance, health and environmental consequences, and possible measures to reverse the problem, at all educational levels. Furthermore, the satisfaction surveys revealed a growing interest in research and science. Therefore, students of general branches who have not yet opted for a scientific line would be the most suitable to conduct the programme. In conclusion, MicroMundo is recommended as a training method to raise awareness about AMR and promote scientific vocations.
The Caenorhabditis elegans innexin INX-20 regulates nociceptive behavioral sensitivity
Authors: Chaubey Aditi H , Sojka Savannah E , Onukwufor John O , Ezak Meredith J , Vandermeulen Matthew D , Bowitch Alexander , Vodičková Anežka , Wojtovich Andrew P , Ferkey Denise M
Published: February 2023

Organisms rely on chemical cues in their environment to indicate the presence or absence of food, reproductive partners, predators, or other harmful stimuli. In the nematode Caenorhabditis elegans, the bilaterally symmetric pair of ASH sensory neurons serves as the primary nociceptors. ASH activation by aversive stimuli leads to backward locomotion and stimulus avoidance. We previously reported a role for guanylyl cyclases in dampening nociceptive sensitivity that requires an innexin-based gap junction network to pass cGMP between neurons. Here, we report that animals lacking function of the gap junction component INX-20 are hypersensitive in their behavioral response to both soluble and volatile chemical stimuli that signal through G protein-coupled receptor pathways in ASH. We find that expressing inx-20 in the ADL and AFD sensory neurons is sufficient to dampen ASH sensitivity, which is supported by new expression analysis of endogenous INX-20 tagged with mCherry via the CRISPR-Cas9 system. Although ADL does not form gap junctions directly with ASH, it does so via gap junctions with the interneuron RMG and the sensory neuron ASK. Ablating either ADL or RMG and ASK also resulted in nociceptive hypersensitivity, suggesting an important role for RMG/ASK downstream of ADL in the ASH modulatory circuit. This work adds to our growing understanding of the repertoire of ways by which ASH activity is regulated via its connectivity to other neurons and identifies a previously unknown role for ADL and RMG in the modulation of aversive behavior.