bluuebunny/crossref_metadata_2025 huggingface dataset:
Hospital Readmission in Patients With Diabetic Foot Ulcers: Prevalence, Causes, and Outcomes
Authors: Meloni Marco , Andreadi Aikaterini , Ruotolo Valeria , Romano Maria , Bellizzi Ermanno , Giurato Laura , Bellia Alfonso , Uccioli Luigi , Lauro Davide
Published: October 2023

The aim of the current study was to evaluate the rate of readmission in patients affected by diabetes and foot ulcers (DFUs), and causes and outcomes of patients requiring a new hospitalization. The current study is a retrospective observational study including patients who have required hospitalization since January 2019 to September 2022 due to a DFU. Once patients were discharged, they were regularly followed as outpatients. Within 6 months of follow-up, the rate of hospital readmission for a diabetic foot problem was recorded. According to the readmission or not, patients were divided into 2 groups, readmitted and not readmitted patients, respectively. Hence, all patients were followed for 6 months more and outcomes of the 2 groups were analyzed and compared. Overall, 310 patients were included. The mean age was 68  ±  12 years, the majority of patients reported type 2 diabetes (>90%), and the mean diabetes duration was approximately 20 years. Sixty-eight (21.9%) patients were readmitted. The main reason for hospital readmission was the presence of critical limb ischemia (CLI) in the contralateral limb (6.1%), the recurrence of CLI in the previous treated limb (4.5%), and the onset of new infected DFU in the contralateral foot (4.5%). Readmitted patients reported lower rate of healing (51.5% vs 89.2%, P < .0001) and higher rate of major amputation (10.3% vs 4.5%, P  =  .2) in comparison to not readmitted patients. Critical limb ischemia resulted in the only independent predictor of hospital readmission. Hospital readmission is a frequent issue among patients with DFUs, and readmitted patients showed a lower chance of wound healing. Critical limb ischemia resulted in the main cause of new hospitalization.
Gentiopicroside alleviates acute myocardial infarction injury in rats by disrupting Nrf2/NLRP3 signaling
Authors: Li Fei , Zhu Hongxiang , Chang Zijuan , Li Ying
Published: October 2023

The objective of the present investigation was to assess the protective impact of gentiopicroside (GPS) on acute myocardial infarction (AMI) through the modulation of NF-E2-related factor 2 (Nrf2)/nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain-containing 3 (NLRP3) signaling. H9c2 cells were subjected to varying concentrations of GPS, and subsequently, the cells and Sprague–Dawley (SD) rats were segregated into control, model, GPS, t-BHQ (an Nrf2 activator), and GPS + ML385 (an Nrf2 inhibitor) groups. The levels of superoxide dismutase (SOD) and malondialdehyde (MDA) were analyzed. Reactive oxygen species (ROS) and cell apoptosis were assessed, while Nrf2 and the expression of the NLRP3 inflammatory body signal pathway were evaluated using western blot and immunofluorescence techniques. The infarct area and pathological changes were also examined. Treatment with varying doses of GPS resulted in increased viability of H9c2 cells. Notably, the model group exhibited significantly elevated levels of cell apoptosis, MDA, and ROS compared to the control group, while SOD and Nrf2 levels were significantly reduced. Furthermore, the expression of NLRP3, cleaved caspase-1, interleukin (IL)-1β, and IL-18 were found to be augmented. Following the implementation of GPS in cells and animals, there was a notable reduction in MDA and ROS levels, a decrease in the rate of cellular apoptosis, and a mitigation of inflammation scores. In addition, there was an increase in the expression of SOD and Nrf2. However, the protective effects of GPS were negated when co-administered with ML385. GPS exhibits therapeutic properties in AMI rats by activating Nrf2 expression, thereby reducing the NLRP3 inflammatory body and alleviating the inflammatory response and oxidative stress of myocardial cells. GPS may hold promise as a potential drug for the treatment of AMI.
The Launch of the iCoDE-2 Standard Project: Integration of Connected Diabetes Device Data Into the Electronic Health Record
Authors: Aaron Rachel E. , Tian Tiffany , Yeung Andrea M. , Huang Jingtong , Klonoff David C. , Espinoza Juan C.
Published: October 2023

Introduction:

Diabetes Technology Society virtually hosted the first meeting of the Integration of Connected Diabetes Device Data Into the Electronic Health Record #2 (iCoDE-2) Standards Project on May 31, 2023, via Zoom.

Methods:

Clinicians, patients, data aggregators, informaticists, manufacturers, attorneys, and cybersecurity experts discussed dosing data currently available from insulin delivery devices and data aggregators and the types of information that patients and clinicians want to see. This information along with technical and regulatory aspects of (1) data standards and (2) integration into the electronic health record (EHR) are the basis of iCoDE-2.

Results:

Six sessions were hosted discussing themes including (1) What’s Currently Available: The Continuous Glucose Monitor Experience; (2) What’s Currently Available: The Aggregator Experience; (3) What’s Currently Available: The Insulin Pump Experience; (4) What’s Currently Available: The Insulin Pen Experience; (5) What Do Clinicians and Patients Want Out of iCoDE-2 Data?; and (6) Technical and Regulatory Aspects of Data Aggregation.

Conclusion:

Additional working group meetings to discuss data standard and clinical workflow will be held to create additional technical specifications and clinical workflows to aid in insulin dosing data integration into the EHR. A mid-project meeting will convene in the second half of 2023.
Does a diagnosis of depression influence observer ratings of pain severity? The mediating role of causal attributions of pain and pain genuineness
Authors: Turcotte Kara , Holtzman Susan
Published: October 2023

Researchers have been increasingly investigating observer and patient characteristics that may influence the assessment of pain in others. While rates of psychiatric conditions are high in chronic pain populations, surprisingly little attention has been given to if (and why) a comorbid psychiatric diagnosis may influence the estimation of pain in others. Using an experimental vignette paradigm, the current study examined whether a diagnostic label of major depressive disorder (MDD) would impact observer pain estimates of a woman with chronic pain, and whether causal attributions of pain and pain genuineness might help explain these effects. Participants ( n = 188) were given a vignette describing a female patient with chronic pain (who either had MDD or no mental health concerns), viewed a brief video clip of the patient, and then were asked to provide a variety of ratings about the woman’s pain. Results of a serial multiple mediation analysis revealed that participants in the MDD condition made greater psychological attributions for the woman’s pain, which was associated with lower perceptions of pain genuineness, which was then associated with lower estimates of pain intensity. These findings suggest that a diagnosis of depression may indirectly influence observer estimates of another person’s pain by heightening psychological attributions of pain, and making their pain seem less genuine. Further research is needed to elucidate the complex processes underlying pain estimation, including patient and observer characteristics, biases, and heuristics, in order to improve quality of care for those living with persistent pain.’
Progress and Institutional Challenges on Local Governments Performance Accountability System Reform in Indonesia
Authors: Salomo Roy Valiant , Rahmayanti Krisna Puji
Published: October 2023

This study analyses, firstly, the achievement of local governments’ reform based on their Performance Accountability System (SAKIP) as part of the national administrative reform program in Indonesia. Secondly, this paper examines factors that have been affecting reform output. The study uses a mixed method perspective by analyzing the whole population of local governments from SAKIP data (2016–2019; quantitative) and applies the qualitative method of in-depth interviews with key informants. The study finds that, although there were improvements in the performance accountability system, the improvement processes have been slow and dominated by formalism at provincial and regency/city levels. Several determining factors affected the implementation of the local government performance accountability system, that is, the regulations’ arrangements, the norms, the cognitive culture, and management problems. Thus, this study confirms the theory of institutional change that considers cultural factors, political commitment, and organizational aspects that influence the dynamic of bureaucratic reform implementation.
The Role of Population Aging in High-Quality Economic Development: Mediating Role of Technological Innovation
Authors: Gao Wenqun , Chen Yang , Xu Shaorui , Lyulyov Oleksii , Pimonenko Tetyana
Published: October 2023

This paper aims to research the relationship between population aging, technological innovation, and high-quality economic development. The study applies the spatial econometric model and the intermediary effect model. The object of investigation is 31 provinces in China from 2013 to 2020. The results show that population aging has a significant effect on technological innovation and high-quality economic development. In addition, population aging promotes technological innovation and is further conducive to high-quality economic development. In addition, the impact of population aging on high-quality economic development is regionally heterogeneous. Thus, population aging in the eastern and central regions stimulates technological innovation to have a positive impact on high-quality economic development. Population aging in the western region inhibits technological innovation and has a negative impact on high-quality economic development. Based on this, the study proposes countermeasures to promote high-quality economic development.
Navigating Migration Risks: The Role of Risk Perception and Information Engagement Among Moldovans
Authors: Bogdan Ludmila
Published: October 2023

Executive Summary

This study examines migration risk perception and information engagement by potential migrants from Moldova. Employing a qualitative interview approach ( N = 30), it explores the behaviors, intentions, and perceptions that underpin how potential migrants understand labor migration risks. It establishes a robust connection between risk perception and the active pursuit of pertinent information.

The study offers a matrix that illustrates the interplay between migration risk perception (high vs. low) and type of risk (individual vs. systemic). It finds that respondents in the High Risk — Systemic group refrain from seeking information, viewing all migration as inherently highly risky due to systemic factors beyond their control. The Low Risk — Systemic group believes migration carries relatively low risks, but that these risks are not individually manageable. The Low Risk — Individual group engages passively with safe migration information because of their perception of low risk. The High Risk — Individual group actively seeks information about safe migration, believing that they can overcome potential risks.

In short, the study finds that potential migrants’ perception and understanding of risk shapes their engagement with safe migration information. The study also highlights gender disparities in risk perception and response. While women emphasize concerns tied to sexual exploitation and separation from family, men are more likely to fear fatal accidents and industry-specific exploitation. The study’s findings should inform the development of policy frameworks and migration information campaigns that reflect diverse perceptions and understandings of migration risk.

Policy Recommendations: To mitigate migration risks and promote safer practices, policymakers at various levels, including the Moldovan government, international agencies (e.g., IOM, UNHCR, and ILO), non-governmental organizations (like LaStrada), and EU bodies, should:

Tailor public education and communication campaigns for diverse risk factors, using different messaging for varying risk perceptions. Address gender-specific concerns with practical advice and resources. Develop comprehensive risk awareness programs covering physical, emotional, and psychological challenges. Use diverse channels (hotlines, online platforms, and workshops) to reach a broader audience. Strengthen embassy services, ensuring staff are informed about migration risks, challenges, and effective outreach and education strategies. Collaborate with mental health professionals to provide psychosocial support. Engage returnee migrants as credible sources of information and advice. Include migration topics in school curricula to enhance migration risk preparedness.

By acknowledging risk perception and adapting information strategies accordingly, policymakers at international, regional, and local levels can create effective initiatives and communicating strategies for secure migration.
On the Value of Data in Industrial Services: How to Optimize Value Creation by Reconfiguration of Operant Resources
Authors: Meierhofer Jürg , Heitz Christoph
Published: October 2023

The background to this article is a quantitative model for data-driven value creation that conceptually explains a holistic approach to finding optimal data-driven service configurations along the customer lifecycle by modeling both provider and customer value and identifying the optimum on the Pareto front. This model, which provides an artifact for service optimization in an iterative design process, is characterized by different inputs that model the costs and benefits of providers and customers depending on different intensities of data usage for services in the respective phases of the lifecycle. In this article, we analyse empirical industrial service configurations by applying the quantitative model and derive insights for optimizing value creation. The analysis shows that this optimization leads to solutions that are not simply achieved by maximizing the intensity of data usage of individual services, but by specifically optimizing the reconfiguration of operant resources along the lifecycle. This enables an overall optimization in a designoriented, iterative approach that differs significantly from standard models that target ascending levels of intensity and maturity of digitization.
Toward a more socially equitable stormwater management fee: The case of Corpus Christi in Texas, USA
Authors: Lee Jim , Zhang Hua , Huang Yuxia
Published: October 2023

This study evaluates a popular approach to assessing stormwater utility fees in the context of social equity. Analyses are based on comparing single-family land parcels in different neighborhoods of Corpus Christi, a U.S. city in the state of Texas that recently introduced a stormwater fee program. The stormwater fees are based on the same stormwater runoff factor for all single-family residential land parcels. We instead derive stormwater runoff estimates from parcel-scale impervious area measurements through the application of a machine-learning model to high-resolution remote sensing data. The difference between the official runoff factor and our estimate tends to be larger among land parcels in census tracts with proportionally more low-income and Hispanic households. This finding at odds with the ability-to-pay principle is attributable to the association of different neighborhoods’ sociodemographic compositions with their housing development patterns. Our work not only contributes to the design of a stormwater fee program that better characterizes the generation of stormwater runoff but it also helps city officials alleviate social inequity for homeowners in economically disadvantaged communities.
Minimally Invasive Cardiac Surgery
Authors: Soma Murali Mohan , Saikiran K V S S , Mannam Gopi C
Published: October 2023

Minimally invasive cardiac surgery is performed for cardiac procedures through a small incision similar to laparoscopy for abdominal surgeries to facilitate faster wound healing, early recovery, better cosmesis, and early resumption of work. Minimally invasive cardiac surgery needs longer instruments, training in specialized centers, a prolonged learning curve, and prolonged cardiopulmonary bypass and aortic cross-clamp time. This article is a brief review of minimally invasive cardiac surgery.
Fostering new vertical and horizontal IoT applications with intelligence everywhere
Authors: Cao Hung , Wachowicz Monica , Richard Rene , Hsu Ching-Hsien
Published: October 2023

Intelligence Everywhere is predicated on the seamless integration of INTERNET of Things (IoT) networks transporting a vast amount of data streams through many computing resources across an edge-to-cloud continuum, relying on the orchestration of distributed machine learning models. The result is an interconnected and collective intelligent ecosystem where devices, systems, services, and users work together to support IoT applications. This paper discusses the state-of-the-art research and the principles of the Intelligence Everywhere framework for enhancing IoT applications in vertical sectors such as Digital Health, Infrastructure, and Transportation/Mobility in the context of intelligent society (Society 5.0). It also introduces a novel perspective for the development of horizontal IoT applications, capable of running across various IoT networks while fostering collective intelligence across diverse sectors. Finally, this paper provides comprehensive insights into the challenges and opportunities for harnessing collective knowledge from real-time insights, leading to optimised processes and better overall collaboration across different IoT sectors.
Employee Group Coaching Program for University and Hospital Employees During COVID-19: A Feasibility Study
Authors: Westervelt Karen , Rose Gail L. , Avery Scott , Celley Alisha , Cho Josh , Donoghue Rory , Goodrich Brennan
Published: October 2023

Background

Workplace wellbeing programs can be beneficial but range widely in approach. A group coaching model offers numerous benefits.

Objective

To evaluate feasibility of group coaching for employees during COVID-19.

Methods

Employees (n = 29) at a university and university hospital underwent a 12-week group coaching program. Measurements of feasibility -- including enrollment, attendance at sessions goal attainment and satisfaction -- and exploratory outcomes including perceived physical and mental health and stress were administered at beginning, middle, and end of the program, plus 2 follow-ups.

Results

Twenty-six of the 29 program enrollees (96% women; 65% university employees) opted to complete surveys at 1 or more time points, and 9 individuals completed surveys at all 5 time points. Median attendance was 9 sessions. Participants opted to focus on movement, nutrition and mind/body goals and all participants reported making progress toward their goal during the program. Exploratory wellness outcomes showed meaningful improvements in perceived physical and mental health and reduced stress during the program, with return to near baseline 12 weeks after program completion. Perceptions of workplace wellness culture varied by employer.

Conclusion

Despite pandemic-related disruptions to life, work, and health, online group coaching is feasible and acceptable to participants. The program should be replicated to evaluate whether the improvements in exploratory wellness outcomes observed during the program are statistically significant. The apparent return to baseline levels by 24 weeks suggests that post-program maintenance support may be helpful.
The Ability for Teaching Self-Efficacy by Clinical Preceptors in Diagnostic Medical Sonography
Authors: Peak Katherine
Published: October 2023

Objective:

This study was designed to explore the teaching self-efficacy, by clinical preceptors instructing sonography students, in bachelor’s degree-accredited sonography programs.

Materials and Methods:

A survey was provided to sonography clinical preceptors, to gauge their level of teaching self-efficacy. The survey instrument, Sonography Preceptor Teaching Self-Efficacy Inventory (SPTSEI) was used. The intent of the survey was to gauge, holistically, sonography preceptors’ perceptions of influencing student learning, in a clinical setting.

Results:

The survey respondents suggested that they had a high level of confidence in their skill to transmit knowledge and abilities to students. However, it was found that preceptors who had received some type of professional development, as preceptor, had a statistically significant higher level of teaching self-efficacy than those who had not received any type of training.

Conclusion:

Clinical preceptors are skilled health care professionals in their chosen discipline but may have little to no teaching experience. If preceptors do not fully understand their role in the educational process, both they and their students may not attain educational goals. It is therefore critically important that proper training and education, to support clinical preceptors, be provided for them. This survey would suggest that clinical preceptors, with training, can better perform their educational roles and better handle any challenges that might arise, as a part of providing clinical education.
The Flow Volume and Resistance Index of Patent Arteriovenous Fistulas, With Proper Function, Compared to Unhealthy Arteriovenous Fistulas, Using Spectral Doppler
Authors: Heydari Negar , Akhoundi Neda , Shakeri-Bavil Abdolhassan , Jalili Javad , Heydari Elnaz , Siami Alireza , Etemadi Jalal , Sedghian Sonia , Naseri Zahra , Pourasghary Sajjad
Published: October 2023

Objective:

This study was designed to use sonography and evaluate arteriovenous fistulas (AVFs) in dialysis patients. The aim was to determine criteria for distinguishing between patent AVFs with proper function (healthy) and unhealthy AVFs.

Materials and Methods:

This study enrolled 106 dialysis patients with an AVF. All fistulas were evaluated using spectral Doppler and grayscale sonography, assessing parameters such as draining vein diameter, distance of the venous vein from the skin surface, feeding artery diameter, presence of thrombosis, and fistula stenosis. Subsequently, Doppler criteria such as flow volume (FV) and resistance index (RI) were measured and compared between healthy and unhealthy AVFs.

Results:

This cohort’s spectral Doppler findings demonstrated lower FV and higher RI, in unhealthy AVFs, compared to healthy ones (283.5 ± 101.26 mL/min vs 1383.43 ± 756.76 mL/min; P = .006) and (0.55 ± 0.33 vs 0.37 ± 0.14; P = .004) respectively.

Conclusion:

The spectral Doppler and grayscale sonographic imaging made it possible to evaluate AVF performance and determine its quality. In this cohort, a decreased FV, increased RI, and decreased draining vein diameter were observed in unhealthy AVFs. These results would suggest that sonographers and clinicians should pay close attention to these parameters when assessing the function of an AVF, for patients undergoing hemodialysis.
A Comparative Study on Kinematic Calibration for a 3-DOF Parallel Manipulator Using the Complete-Minimal, Inverse-Kinematic and Geometric-Constraint Error Models
Authors: Wu Haiyu , Kong Lingyu , Li Qinchuan , Wang Hao , Chen Genliang
Published: October 2023

Kinematic calibration is a reliable way to improve the accuracy of parallel manipulators, while the error model dramatically affects the accuracy, reliability, and stability of identification results. In this paper, a comparison study on kinematic calibration for a 3-DOF parallel manipulator with three error models is presented to investigate the relative merits of different error modeling methods. The study takes into consideration the inverse-kinematic error model, which ignores all passive joint errors, the geometric-constraint error model, which is derived by special geometric constraints of the studied RPR-equivalent parallel manipulator, and the complete-minimal error model, which meets the complete, minimal, and continuous criteria. This comparison focuses on aspects such as modeling complexity, identification accuracy, the impact of noise uncertainty, and parameter identifiability. To facilitate a more intuitive comparison, simulations are conducted to draw conclusions in certain aspects, including accuracy, the influence of the S joint, identification with noises, and sensitivity indices. The simulations indicate that the complete-minimal error model exhibits the lowest residual values, and all error models demonstrate stability considering noises. Hereafter, an experiment is conducted on a prototype using a laser tracker, providing further insights into the differences among the three error models. The results show that the residual errors of this machine tool are significantly improved according to the identified parameters, and the complete-minimal error model can approach the measurements by nearly 90% compared to the inverse-kinematic error model. The findings pertaining to the model process, complexity, and limitations are also instructive for other parallel manipulators.
Genomic prediction based on selective linkage disequilibrium pruning of low-coverage whole-genome sequence variants in a pure Duroc population
Authors: Zhu Di , Zhao Yiqiang , Zhang Ran , Wu Hanyu , Cai Gengyuan , Wu Zhenfang , Wang Yuzhe , Hu Xiaoxiang
Published: October 2023

Background

Although the accumulation of whole-genome sequencing (WGS) data has accelerated the identification of mutations underlying complex traits, its impact on the accuracy of genomic predictions is limited. Reliable genotyping data and pre-selected beneficial loci can be used to improve prediction accuracy. Previously, we reported a low-coverage sequencing genotyping method that yielded 11.3 million highly accurate single-nucleotide polymorphisms (SNPs) in pigs. Here, we introduce a method termed selective linkage disequilibrium pruning (SLDP), which refines the set of SNPs that show a large gain during prediction of complex traits using whole-genome SNP data.

Results

We used the SLDP method to identify and select markers among millions of SNPs based on genome-wide association study (GWAS) prior information. We evaluated the performance of SLDP with respect to three real traits and six simulated traits with varying genetic architectures using two representative models (genomic best linear unbiased prediction and BayesR) on samples from 3579 Duroc boars. SLDP was determined by testing 180 combinations of two core parameters (GWAS P-value thresholds and linkage disequilibrium r2). The parameters for each trait were optimized in the training population by five fold cross-validation and then tested in the validation population. Similar to previous GWAS prior-based methods, the performance of SLDP was mainly affected by the genetic architecture of the traits analyzed. Specifically, SLDP performed better for traits controlled by major quantitative trait loci (QTL) or a small number of quantitative trait nucleotides (QTN). Compared with two commercial SNP chips, genotyping-by-sequencing data, and an unselected whole-genome SNP panel, the SLDP strategy led to significant improvements in prediction accuracy, which ranged from 0.84 to 3.22% for real traits controlled by major or moderate QTL and from 1.23 to 11.47% for simulated traits controlled by a small number of QTN.

Conclusions

The SLDP marker selection method can be incorporated into mainstream prediction models to yield accuracy improvements for traits with a relatively simple genetic architecture, however, it has no significant advantage for traits not controlled by major QTL. The main factors that affect its performance are the genetic architecture of traits and the reliability of GWAS prior information. Our findings can facilitate the application of WGS-based genomic selection.
Artificial Intelligence based wrapper for high dimensional feature selection
Authors: Jain Rahi , Xu Wei
Published: October 2023

Background

Feature selection is important in high dimensional data analysis. The wrapper approach is one of the ways to perform feature selection, but it is computationally intensive as it builds and evaluates models of multiple subsets of features. The existing wrapper algorithm primarily focuses on shortening the path to find an optimal feature set. However, it underutilizes the capability of feature subset models, which impacts feature selection and its predictive performance.

Method and Results

This study proposes a novel Artificial Intelligence based Wrapper (AIWrap) algorithm that integrates Artificial Intelligence (AI) with the existing wrapper algorithm. The algorithm develops a Performance Prediction Model using AI which predicts the model performance of any feature set and allows the wrapper algorithm to evaluate the feature subset performance in a model without building the model. The algorithm can make the wrapper algorithm more relevant for high-dimensional data. We evaluate the performance of this algorithm using simulated studies and real research studies. AIWrap shows better or at par feature selection and model prediction performance than standard penalized feature selection algorithms and wrapper algorithms.

Conclusion

AIWrap approach provides an alternative algorithm to the existing algorithms for feature selection. The current study focuses on AIWrap application in continuous cross-sectional data. However, it could be applied to other datasets like longitudinal, categorical and time-to-event biological data.
Asterics: a simple tool for the ExploRation and Integration of omiCS data
Authors: Maigné Élise , Noirot Céline , Henry Julien , Adu Kesewaah Yaa , Badin Ludovic , Déjean Sébastien , Guilmineau Camille , Krebs Arielle , Mathevet Fanny , Segalini Audrey , Thomassin Laurent , Colongo David , Gaspin Christine , Liaubet Laurence , Vialaneix Nathalie
Published: October 2023

Background

The rapid development of omics acquisition techniques has induced the production of a large volume of heterogeneous and multi-level omics datasets, which require specific and sometimes complex analyses to obtain relevant biological information. Here, we present ASTERICS (version 2.5), a publicly available web interface for the analyses of omics datasets.

Results

ASTERICS is designed to make both standard and complex exploratory and integration analysis workflows easily available to biologists and to provide high quality interactive plots. Special care has been taken to provide a comprehensive documentation of the implemented analyses and to guide users toward sound analysis choices regarding some specific omics data. Data and analyses are organized in a comprehensive graphical workflow within ASTERICS workspace to facilitate the understanding of successive data editions and analyses leading to a given result.

Conclusion

ASTERICS provides an easy to use platform for omics data exploration and integration. The modular organization of its open source code makes it easy to incorporate new workflows and analyses by external contributors. ASTERICS is available athttps://asterics.miat.inrae.frand can also be deployed using provided docker images.
Exogenous auxin regulates the growth and development of peach fruit at the expansion stage by mediating multiple-hormone signaling
Authors: Zhang Yanping , Su Ziwen , Luo Linjia , Wang Pengkai , Zhu Xudong , Liu Jiecai , Wang Chen
Published: October 2023

Background

Fruit expansion stage is crucial to fruit yield and quality formation, and auxin plays a significant role by mediating multi-hormone signals during fruit expansion. However, till now, it is still unclear of the molecular regulatory network during auxin-mediated peach fruit expansion.

Results

Here, exogenous NAA application markedly increased IAA content and drastically decreased ABA content at the fruit expansion stage. Correspondingly, NAA mainly induced the auxin biosynthesis gene (1 PpYUCCA) and early auxin-responsive genes (7PpIAA, 3 PpGH3, and 14 PpSAUR); while NAA down-regulated ABA biosynthesis genes (2 PpNCED, 1 PpABA3, and 1 PpAAO3). In addition, many DEGs involved in other plant hormone biosynthesis and signal transduction were significantly enriched after NAA treatment, including 7 JA, 7 CTK, 6 ETH, and 3 GA. Furthermore, we also found that NAA treatment down-regulated most of genes involved in the growth and development of peach fruit, including the cell wall metabolism-related genes (PpEG), sucrose metabolism-related genes (PpSPS), phenylalanine metabolism-related genes (PpPAL, Pp4CL, and PpHCT), and transcription factors (PpNAC, PpMADS-box, PpDof, PpSBP, and PpHB).

Conclusion

Overall, NAA treatment at the fruit expansion stage could inhibit some metabolism processes involved in the related genes in the growth and development of peach fruit by regulating multiple-hormone signaling networks. These results help reveal the short-term regulatory mechanism of auxin at the fruit expansion stage and provide new insights into the multi-hormone cascade regulatory network of fruit growth and development.
Detecting influential subjects in intensive longitudinal data using mixed-effects location scale models
Authors: Zhang Xingruo , Hedeker Donald
Published: October 2023

Background

Collection of intensive longitudinal health outcomes allows joint modeling of their mean (location) and variability (scale). Focusing on the location of the outcome, measures to detect influential subjects in longitudinal data using standard mixed-effects regression models (MRMs) have been widely discussed. However, no existing approach enables the detection of subjects that heavily influence the scale of the outcome.

Methods

We propose applying mixed-effects location scale (MELS) modeling combined with commonly used influence measures such as Cook’s distance and DFBETAS to fill this gap. In this paper, we provide a framework for researchers to follow when trying to detect influential subjects for both the scale and location of the outcome. The framework allows detailed examination of each subject’s influence on model fit as well as point estimates and precision of coefficients in different components of a MELS model.

Results

We simulated two common scenarios in longitudinal healthcare studies and found that influence measures in our framework successfully capture influential subjects over 99% of the time. We also re-analyzed data from a health behavior study and found 4 particularly influential subjects, among which two cannot be detected by influence analyses via regular MRMs.

Conclusion

The proposed framework can help researchers detect influential subject(s) that will be otherwise overlooked by influential analysis using regular MRMs and analyze all data in one model despite influential subjects.
Comparing methods to predict baseline mortality for excess mortality calculations
Authors: Ferenci Tamás
Published: October 2023

Background

The World Health Organization (WHO)’s excess mortality estimates presented in May 2022 stirred controversy, due in part to the high estimate provided for Germany, which was later attributed to the spline model used. This paper aims to reproduce the problem using synthetic datasets, thus allowing the investigation of its sensitivity to parameters, both of the mortality curve and of the used method, thereby shedding light on the conditions that gave rise to this error and identifying possible remedies.

Methods

A negative binomial model was used accounting for long-term change, seasonality, flu seasons, and heat waves. Simulated mortality curves from this model were then analysed using simple methods (mean, linear trend), the WHO method, and the method of Acosta and Irizarry.

Results

The performance of the WHO’s method with its original parametrization was indeed very poor, however it can be profoundly improved by a better choice of parameters. The Acosta–Irizarry method outperformed the WHO method despite being also based on splines, but it was also dependent on its parameters. Linear extrapolation could produce very good results, but was highly dependent on the choice of the starting year, while the average was the worst in almost all cases.

Conclusions

Splines are not inherently unsuitable for predicting baseline mortality, but caution should be taken. In particular, the results suggest that the key issue is that the splines should not be too flexible to avoid overfitting. Even after having investigated a limited number of scenarios, the results suggest that there is not a single method that outperforms the others in all situations. As the WHO method on the German data illustrates, whatever method is chosen, it remains important to visualize the data, the fit, and the predictions before trusting any result. It will be interesting to see whether further research including other scenarios will come to similar conclusions.
Lifestyle-based nomogram for identifying the Chaoshan inhabitants of China at high risk of Helicobacter pylori infection
Authors: Lin Yi-ting , Wang Pei-ru , Xue Wen-wen , Zhou Si-si , Huang Ze-yu , Li Yu-ting , Zheng Zhuo-na , Hou Wen-jing , Chen Qi-xian , Yu Jing
Published: October 2023

Background

Helicobacter pylori (HP) infection is associated with various diseases. Early detection can prevent the onset of illness. We constructed a nomogram to predict groups at high risk of HP infection.

Methods

Patients who underwent regular medical check-ups at hospital in Chaoshan, China from March to September 2022 were randomly allocated to the training and validation cohorts. Risk factors including basic characteristics and lifestyle habits associated with HP infection were analyzed by logistic regression analyses. The independent varieties were calculated and plotted into a nomogram. The nomogram was internally validated by receiver operating characteristic curve, calibration, and decision curve analyses (DCAs).

Results

Of the 945 patients, 680 were included in the training cohort and 265 in the validation cohort. 356 patients in training cohort with positive 13 C-UBT results served as the infected group, and 324 without infection were the control group. The multivariate regression analyses showed that the risk factors for HP infection included alcohol consumption (OR = 1.29, 95%CI = 0.78–2.13, P = 0.03), family history of gastric disease (OR = 4.35, 95%CI = 1.47–12.84, P = 0.01), living with an HP-positive individual (OR = 18.09, 95%CI = 10.29–31.82, P < 0.0001), drinking hot tea (OR = 1.58, 95%CI = 1.05–2.48, P = 0.04), and infection status of co-drinkers unknown (OR = 2.29, 95%CI = 1.04–5.06, P = 0.04). However, drinking tea > 3 times per day (OR = 0.56, 95%CI = 0.33–0.95, P = 0.03), using serving chopsticks (OR = 0.30, 95%CI = 0.12–0.49, P < 0.0001) were protective factors for HP infection. The nomogram had an area under the curve (AUC) of 0.85 in the training cohort. The DCA was above the reference line within a large threshold range, indicating that the model was better. The calibration analyses showed the actual occurrence rate was basically consistent with the predicted occurrence rate. The model was validated in the validation cohort, and had a good AUC (0.80), DCA and calibration curve results.

Conclusions

This nomogram, which incorporates basic characteristics and lifestyle habits, is an efficient model for predicting those at high risk of HP infection in the Chaoshan region.
Association between ICU admission (neutrophil + monocyte)/lymphocyte ratio and 30-day mortality in patients with sepsis: a retrospective cohort study
Authors: Guo Manliang , He Wanmei , Mao Xueyan , Luo Yuling , Zeng Mian
Published: October 2023

Background

Sepsis is an important public health issue, and it is urgent to develop valuable indicators to predict the prognosis of sepsis. Our study aims to assess the predictive value of ICU admission (Neutrophil + Monocyte)/lymphocyte ratio (NMLR) on the 30-day mortality of sepsis patients.

Methods

A retrospective analysis was conducted in septic patients, and the data were collected from Medical Information Mart for Intensive Care IV (MIMIC-IV). Univariate and multivariate Cox regression analyses were conducted to investigate the relation between ICU admission NMLR and 30-day mortality. Restricted cubic spline (RCS) was performed to determine the optimum cut-off value of ICU admission NMLR. Survival outcomes of the two groups with different ICU admission NMLR levels were estimated using the Kaplan-Meier method and compared by the log-rank test.

Results

Finally, 7292 patients were recruited in the study, of which 1601 died within 30 days of discharge. The non-survival group had higher ICU admission NMLR values than patients in the survival group (12.24 [6.44–23.67] vs. 8.71 [4.81–16.26], P < 0.001). Univariate and multivariate Cox regression analysis demonstrated that ICU admission NMLR was an independent prognostic predictor on 30-day mortality (Univariate: P < 0.001; multivariate: P = 0.011). The RCS model demonstrated the upturn and non-linear relationship between ICU admission NMLR and 30-day mortality (Nonlinearity: P = 0.0124). According to the KM curve analysis,30-day survival was worse in the higher ICU admission NMLR group than that in the lower ICU admission NMLR group (Log rank test, P < 0.0001).

Conclusion

The elevated ICU admission NMLR level is an independent risk factor for high 30-day mortality in patients with sepsis.
Hemolytic disease of the fetus and newborn: rapid review of postnatal care and outcomes
Authors: de Winter Derek P. , Kaminski Allysen , Tjoa May Lee , Oepkes Dick , Lopriore Enrico
Published: October 2023

Background

Advances in postnatal care for hemolytic disease of the fetus and newborn (HDFN) have occurred over the past decades, but little is known regarding the frequency of postnatal treatment and the clinical outcomes of affected neonates. Most studies reporting on HDFN originate from high-income countries or relatively large centers, but important differences between centers and countries may exist due to differences in prevalence and available treatment options. We therefore aimed to evaluate the postnatal treatment landscape and clinical outcomes in neonates with Rhesus factor D (Rh(D))- and/or K-mediated HDFN and to provide recommendations for future research.

Methods

We conducted a rapid literature review of case reports and series, observational retrospective and prospective cohort studies, and trials describing pregnancies or children affected by Rh(D)- or K-mediated HDFN published between 2005 and 2021. Information relevant to the treatment of HDFN and clinical outcomes was extracted. Medline, ClinicalTrials.gov and EMBASE were searched for relevant studies by two independent reviewers through title/abstract and full-text screening. Two independent reviewers extracted data and assessed methodological quality of included studies.

Results

Forty-three studies reporting postnatal data were included. The median frequency of exchange transfusions was 6.0% [interquartile range (IQR): 0.0–20.0] in K-mediated HDFN and 26.5% [IQR: 18.0–42.9] in Rh(D)-mediated HDFN. The median use of simple red blood cell transfusions in K-mediated HDFN was 50.0% [IQR: 25.0–56.0] and 60.0% [IQR: 20.0–72.0] in Rh(D)-mediated HDFN. Large differences in transfusion rates were found between centers. Neonatal mortality amongst cases treated with intrauterine transfusion(s) was 1.2% [IQR: 0–4.4]. Guidelines and thresholds for exchange transfusions and simple RBC transfusions were reported in 50% of studies.

Conclusion

Most included studies were from middle- to high-income countries. No studies with a higher level of evidence from centers in low-income countries were available. We noted a shortage and inconsistency in the reporting of relevant data and provide recommendations for future reports. Although large variations between studies was found and information was often missing, analysis showed that the postnatal burden of HDFN, including need for neonatal interventions, remains high.

Systematic review registration

PROSPERO 2021 CRD42021234940. Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021234940.
Pan-tumor survey of ROS1 fusions detected by next-generation RNA and whole transcriptome sequencing
Authors: Nagasaka Misako , Zhang Shannon S. , Baca Yasmine , Xiu Joanne , Nieva Jorge , Vanderwalde Ari , Swensen Jeffrey J. , Spetzler David , Korn Wolfgang Michael , Raez Luis E. , Liu Stephen V. , Ou Sai-Hong Ignatius
Published: October 2023

Background

TwoROS1tyrosine kinase inhibitors have been approved for ROS1 fusion positive (ROS1+) non-small cell lung cancer (NSCLC) tumors. We performed a pan-tumor analysis of the incidence ofROS1fusions to assess if more ROS1+ patients who could benefit fromROS1TKIs could be identified.

Methods

A retrospective analysis of ROS1 positive solid malignancies identified by targeted RNA sequencing and whole transcriptome sequencing of clinical tumor samples performed at Caris Life Science (Phoenix, AZ).

Results

A total of 259 ROS1+ solid malignancies were identified from approximately 175,350 tumors that underwent next-generation sequencing (12% from targeted RNA sequencing [Archer]; 88% from whole transcriptome sequencing). ROS1+ NSCLC constituted 78.8% of the ROS1+ solid malignancies, follow by glioblastoma (GBM) (6.9%), and breast cancer (2.7%). The frequency of ROS1 fusion was approximately 0.47% among NSCLC, 0.29% for GBM, 0.04% of breast cancer. The mean tumor mutation burden for all ROS1+ tumors was 4.8 mutations/megabase. The distribution of PD-L1 (22C3) expression among allROS1+ malignancies were 0% (18.6%), 1%-49% (29.4%), and ≥ 50% (60.3%) [for NSCLC: 0% (17.8%); 1–49% (27.7%); ≥ 50% (53.9%).

The most common genetic co-alterations of ROS1+ NSCLC were TP53 (29.1%), SETD2 (7.3%), ARIAD1A (6.3%), and U2AF1 (5.6%).

Conclusions

ROS1+ NSCLC tumors constituted the majority of ROS1+ solid malignancies with four major fusion partners. Given that > 20% of ROS1+ solid tumors may benefit fromROS1TKIs treatment, comprehensive genomic profiling should be performed on all solid tumors.