bluuebunny/crossref_metadata_2025_split huggingface dataset:
A dual source switched-capacitors multilevel inverter topology with extended voltage levels and voltage gain
Authors: Al-Tameemi Weam , Babaei Ebrahim , Sabahi Mehran 
Published: January 2024

Abstract
The switched-capacitors multi-level inverters (SCMLI) are widely used in renewable energy resources for enhancing the quality and reliability of generated power. This paper suggests a new topology of extendable voltage levels and voltage gain units using switched capacitors SC with a dual DC source. The proposed unit can be extended by a modular pattern to increase the output voltage levels and voltage-boosting gain of the inverter. The main feature of this work is presenting a unit topology that utilizes multiple and modular sub-cells to increase the voltage gain at the output by increasing the number of the sub-cell components. A ternary relationship of the voltage magnitudes between the two asymmetrical DC sources is mandatory. Furthermore, all the capacitors are self-balanced, so there is no need for any additional and complex control circuit. Moreover, to decrease the cost factor of the inverter, a low IGBT switch count is taken into consideration and no passive diodes are used in the proposed structure. The H-bridge is connected to the unit to achieve bipolar voltage at the output. The operational analysis of the inverter is delineated in detail. A comparative study with state-of-art MLIs in different terms such as the number of components, the total standing voltage, the cost factor, and the gain shows the particularity of the proposed topology. The simulation of the proposed MLI is performed using PSCAD-EMTDC software. An experimental prototype is built to validate the simulation results.
Deep kernel methods learn better: from cards to process optimization
Authors: Valleti Mani , Vasudevan Rama K , Ziatdinov Maxim A , Kalinin Sergei V 
Published: January 2024

Abstract
The ability of deep learning methods to perform classification and regression tasks relies heavily on their capacity to uncover manifolds in high-dimensional data spaces and project them into low-dimensional representation spaces. In this study, we investigate the structure and character of the manifolds generated by classical variational autoencoder (VAE) approaches and deep kernel learning (DKL). In the former case, the structure of the latent space is determined by the properties of the input data alone, while in the latter, the latent manifold forms as a result of an active learning process that balances the data distribution and target functionalities. We show that DKL with active learning can produce a more compact and smooth latent space which is more conducive to optimization compared to previously reported methods, such as the VAE. We demonstrate this behavior using a simple cards dataset and extend it to the optimization of domain-generated trajectories in physical systems. Our findings suggest that latent manifolds constructed through active learning have a more beneficial structure for optimization problems, especially in feature-rich target-poor scenarios that are common in domain sciences, such as materials synthesis, energy storage, and molecular discovery. The Jupyter Notebooks that encapsulate the complete analysis accompany the article.
SilenceREIN: seeking silencers on anchors of chromatin loops by deep graph neural networks
Authors: Pan Jian-Hua , Du Pu-Feng 
Published: January 2024

Abstract
Silencers are repressive cis-regulatory elements that play crucial roles in transcriptional regulation. Experimental methods for identifying silencers are always costly and time-consuming. Computational methods, which relies on genomic sequence features, have been introduced as alternative approaches. However, silencers do not have significant epigenomic signature. Therefore, we explore a new way to computationally identify silencers, by incorporating chromatin structural information. We propose the SilenceREIN method, which focuses on finding silencers on anchors of chromatin loops. By using graph neural networks, we extracted chromatin structural information from a regulatory element interaction network. SilenceREIN integrated the chromatin structural information with linear genomic signatures to find silencers. The predictive performance of SilenceREIN is comparable or better than other states-of-the-art methods. We performed a genome-wide scanning to systematically find silencers in human genome. Results suggest that silencers are widespread on anchors of chromatin loops. In addition, enrichment analysis of transcription factor binding motif support our prediction results. As far as we can tell, this is the first attempt to incorporate chromatin structural information in finding silencers. All datasets and source codes of SilenceREIN have been deposited in a GitHub repository (https://github.com/JianHPan/SilenceREIN).
Initial steps towards developing a predictive algorithm of disease progression for hidradenitis suppurativa (HS): results from a Cox proportional hazard regression analysis on disease progression among a cohort of 335 Danish patients with HS
Authors: Kjærsgaard Andersen Rune , Pedersen Ole , Eidsmo Liv , Jemec Gregor , Saunte Ditte 
Published: January 2024

Abstract

Background
Hidradenitis suppurativa (HS) is a chronic inflammatory and scarring disease with a wide spectrum of disease severity. The amount of scarring is proportional to the preceding tissue damage and poses a challenge to patients. Severe HS is most often treatment recalcitrant, but hypothetically avoidable through early biologic treatment. Early prediction of individual risk of disease progression is therefore essential for patient management.

Objectives
To investigate risk factors associated with disease progression and to design an algorithm capable of predicting disease ­progression.

Methods
A prospective cohort study of 335 Hurley III-naïve patients with HS, not treated with biologics, was followed for a median of 2 years. Potential risk factors covered basic demographics, HS anamnestic factors and clinical HS factors collected during physical examination. Two separate Cox proportional hazard regression (CPHR) analyses were conducted. A summated ‘progression score’ was calculated and used in the predictive algorithm of severe disease. Subsequent bootstrap sampling was used to validate the predictability of the predictive algorithm.

Results
The CPHR analysis of Transition to severe disease found that active smoking [hazard ratio (HR) 4.01, 95% confidence interval (CI) 1.71–9.40, P = 0.001]; body mass index (BMI) points &gt; 25 at baseline (each point: HR 1.06, 95% CI 1.02–1.09, P &lt; 0.001); active disease in 2 (HR 4.26, 95% CI 1.23–14.84, P = 0.02) and ≥ 3 areas (HR 6.54, 95% CI 1.89–22.72, P = 0.003) all constituted substantial risk factors. Conversely, the CPHR analysis of Disease progression did not yield results of clinical relevance. A ‘progression score’ of 3.04 was used as a threshold in the predictive algorithm of Transition to severe disease and achieved the following test specifics: sensitivity = 0.51, specificity = 0.86, positive predictive value = 0.50, negative predictive value = 0.86.

Conclusions
We found a disparity between factors increasing the risk of simple Disease progression and those increasing the risk of Transition to severe disease. For the latter, active smoking, BMI points &gt; 25, active disease in 2 or ≥ 3 areas were all shown to be the clinically relevant factors that could be used to construct an algorithm that correctly predicted progression to severe HS in more than half of all instances.
Artificial intelligence: revolutionizing cardiology with large language models
Authors: Boonstra Machteld J , Weissenbacher Davy , Moore Jason H , Gonzalez-Hernandez Graciela , Asselbergs Folkert W 
Published: January 2024

Abstract
Natural language processing techniques are having an increasing impact on clinical care from patient, clinician, administrator, and research perspective. Among others are automated generation of clinical notes and discharge letters, medical term coding for billing, medical chatbots both for patients and clinicians, data enrichment in the identification of disease symptoms or diagnosis, cohort selection for clinical trial, and auditing purposes. In the review, an overview of the history in natural language processing techniques developed with brief technical background is presented. Subsequently, the review will discuss implementation strategies of natural language processing tools, thereby specifically focusing on large language models, and conclude with future opportunities in the application of such techniques in the field of cardiology.
Post-sternotomy movement strategies in adults: a scoping review
Authors: Wiens Karen , Hayden K Alix , Park Lauren , Colwell Susan , Coltman Christopher , King-Shier Kathryn M 
Published: January 2024

Abstract

Aims
Post-sternotomy movement strategies for adults should be an evidence-informed approach and support a safe, independent return to daily activity. Recent new movement strategies have emerged. The aim of this scoping review was to identify and summarize the available evidence for post-sternotomy movement strategies in adults.

Methods and results
The electronic databases searched included MEDLINE, Embase, Sport Discus, CINAHL, Academic Search Complete, the Cochrane Library, Scopus, and PEDro. The search did not have a date limit. After 2405 duplicates were removed, 2978 records were screened, and 12 were included; an additional 2 studies were identified through reference searching for a total of 14 included studies. A data extraction table was used, and the findings are summarized in a tabular and narrative form. Three post-sternotomy movement strategies were identified in the literature: sternal precautions (SP), modified SP, and Keep Your Move in the Tube (KYMITT™). The authors suggested that the practice of SP was based on expert opinion and not founded in evidence. However, the evidence from the identified articles suggested that new movement strategies are safe and allow patients to choose an increased level of activity that promotes improved functional status and confidence.

Conclusion
More prospective cohort studies and multi-centred randomized control trials are needed; however, the current evidence suggests that modified SP and KYMITT™ are as safe as SP and can promote a patient-centred approach.

Registration
University of Calgary’s Digital Repository PRISM http://hdl.handle.net/1880/115439.
Psychometric testing of the Care Dependency Scale in patients with heart failure and their caregivers
Authors: Durante Angela , Vellone Ercole , Younas Ahtisham , Juarez-Vela Raul , Boyne Josiane , Piredda Michela , De Maria Maddalena 
Published: January 2024

Abstract

Aims
This study aims to (i) test the validity and reliability of the Care Dependency Scale (CDS) for patients with heart failure (HF) and (ii) test the validity and reliability of the proxy version of the CDS assessing informal caregivers’ perception of the dependency level of individuals with HF.

Methods and results
Secondary data analysis was conducted of transnational multicentre cross-sectional design study. A convenience sample comprised of HF patients–informal caregivers’ dyads in three European countries. The CDS was administered to patients and the proxy version to informal caregivers. Factorial validity was tested for each scale using confirmatory factor analysis. Reliability was evaluated with the composite coefficient and Cronbach’s alpha. Construct validity was tested via known group differences. Measurement error was tested to assess responsiveness to changes. A total of 229 patients and 208 caregivers were recruited. Confirmatory factor analysis supported the two-factor structure (Physical Care Dependency and Psychosocial Care Dependency) of the CDS in both HF patients and their caregiver. Reliability estimates were adequate for all reliability coefficients. Construct validity was supported. The measurement error was adequate.

Conclusion
The scale shows acceptable validity and reliability and can be useful for care dependency assessment of patients with HF and their informal caregivers. Further research is needed for assessing the validity and reliability in other cross-cultural settings. The use of the CDS has the potential to effectively enable the development of pertinent care plans, taking dependency into consideration including the perspective of both members of the dyad as a whole.
Allelic combinations of Hd1, Hd16, and Ghd7 exhibit pleiotropic effects on agronomic traits in rice
Authors: Lee Seung Young , Jeung Ji-Ung , Mo Youngjun 
Published: January 2024

Abstract
Heading date is a critical agronomic trait that significantly affects grain yield and quality in rice. As early heading is typically associated with reduced yield due to shorter growth duration, it is essential to harness optimum heading date genes and their allelic combinations to promote heading while minimizing yield penalties. In this study, we identified quantitative trait loci (QTLs) for heading date and other major agronomic traits in a recombinant inbred line (RIL) population derived from a cross between Koshihikari and Baegilmi. Analyses on 3 major QTLs for heading date and their underlying genes (Hd1, Hd16, and Ghd7) revealed their pleiotropic effects on culm length, panicle length, and head rice percentage. Additionally, Ghd7 exhibited pleiotropic effects on panicle number and grain size. Among 8 different types of allelic combinations of the 3 heading date genes, RILs carrying a single nonfunctional hd16 or ghd7 under the functional background of the other 2 genes (Hd1hd16Ghd7 and Hd1Hd16ghd7) showed potential for maintaining yield and quality-related traits while accelerating heading. These results provide valuable insights for fine-tuning heading dates in rice breeding programs.
Effects of Cumulative Cognitive Function Within 1 Year of Discharge on Subsequent Mortality Among Patients Hospitalized for Acute Heart Failure: A Nationwide Prospective Cohort Study
Authors: Wang Wei , Peng Yue , He Guangda , Li Yan , Liu Yanchen , Lei Lubi , Li Jingkuo , Pu Boxuan , Yu Yanwu , Zhang Lihua , Guo Yuanlin 
Published: January 2024

Abstract

Background
To examine the association between cumulative cognitive function and subsequent mortality among patients hospitalized for acute heart failure (AHF).

Methods
Based on a prospective cohort of patients hospitalized for AHF, cognitive function was measured using Mini-Cog test at admission, 1- and 12-month following discharge. Cumulative cognitive function was interpreted by cumulative Mini-Cog score and cumulative times of cognitive impairment. Outcomes included subsequent all-cause and cardiovascular mortality.

Results
1 454 patients hospitalized for AHF with median follow-up of 4.76 (interquartile range [IQR]: 4.18–5.07) years were included. Tertile 1 of cumulative Mini-Cog score had the highest risk of all-cause (hazard ratio [HR]: 1.52, 95% confidence interval [CI]: 1.14–2.03) and cardiovascular mortality (HR: 1.40, 95% CI: 1.02–1.93) compared with Tertile 3; patients with ≥2 times of cognitive impairment had the highest risk of all-cause (HR: 1.34, 95% CI: 1.03–1.73) and cardiovascular mortality (HR: 1.25, 95% CI: 0.93–1.67) compared with patients without any cognitive impairment. Cumulative Mini-Cog score provided the highest incremental prognostic ability in predicting all-cause (C-statistics: 0.64, 95% CI: 0.61–0.66) and cardiovascular mortality (C-statistics: 0.63, 95% CI: 0.60–0.67) risk on the basis of Get With The Guidelines-Heart Failure score.

Conclusions
Poor cumulative cognitive function was associated with increased risk of subsequent mortality and provided incremental prognostic ability for the outcomes among patients with AHF. Longitudinal assessment and monitoring of cognitive function among patients with AHF would be of great importance in identifying patients at greater risk of self-care absence for optimizing personal disease management in clinical practice.
Programmatic quality measures: a new model to promote surgical quality
Authors: Peters Xane , Sage Jill , Collins Courtney , Opelka Frank , Ko Clifford 
Published: January 2024

Abstract
Health care performance metrics are offered predominantly in terms of outcomes, processes, or structural components of health care delivery. However, measurement is limited by variability in data sources, definitions, and workarounds. The American College of Surgeons has recently developed a new type of performance metric known as a “programmatic measure”. These metrics align structures, processes, and outcomes to better coordinate quality measurement with support of frontline care teams. In this multifaceted way, these measures differ from current “single” measures such as targeting surgical site infection. The thematic focus of these measures and alignment of structure-resource components to support processes and outcomes also sets these measures apart from contemporary composite measures. Importantly, structural elements of these measures reflect minimum resources required for patient care, addressing staffing and resource barriers felt by local institutions in addressing numerous existing quality metrics. These metrics will streamline quality reporting to improve care navigation for patients. Clinicians will find more appropriately aligned goals and responsibilities, resulting in increased teamwork and communication. These measures are designed to address the current burdens of overabundant metrics, priority misalignment, and low resources in a patient-centric fashion to better align health care quality and measurement.
miR156b-targeted VvSBP8/13 functions downstream of the abscisic acid signal to regulate anthocyanins biosynthesis in grapevine fruit under drought
Authors: Guo Shuihuan , Zhang Meng , Feng Mingxin , Liu Guipeng , Torregrosa Laurent , Tao Xiaoqing , Ren Ruihua , Fang Yulin , Zhang Zhenwen , Meng Jiangfei , Xu Tengfei 
Published: January 2024

Abstract
Anthocyanins are the primary color components of grapevine berries and wines. In cultivation practices, a moderate water deficit can promote anthocyanin accumulation in red grape skins. Our previous study showed that abscisic acid (ABA) plays a key role in this process. Herein, we identified a microRNA, vv-miR156b, that is generated in grapevine berries in response to drought stress, along with increasing anthocyanin content and biosynthetic structural gene transcripts. In contrast, vv-miR156b short tandem target mimic (STTM) function-loss callus exhibits the opposite phenotype. Results from in vivo and in vitro experiments revealed that the ABA-signaling-regulated transcription factor VvAREB2 binds directly to the ABA-responsive element (ABRE) of the MIR156b promoter and activates miR156b expression. Furthermore, two miR156b downstream targets, VvSBP8 and VvSBP13, exhibited reduced grape anthocyanin content in their overexpressors but there was a contrary result in their CRISPR-edited lines, the decrease in anthocyanin content was rescued in miR156b and SBP8/13 double overexpressors. We further demonstrated that both VvSBP8 and VvSBP13, encoding transcriptional repressors, displayed sufficient ability to interact with VvMYC1 and VvMYBA1, thereby interfering with MYB-bHLH-WD (MBW) repeat transcriptional complex formation, resulting in the repression of anthocyanin biosynthesis. Our findings demonstrate a direct functional relationship between ABA signaling and the miR156-SBP-MBW complex regulatory module in driving drought-induced anthocyanin accumulation in grape berries.
A natural mutation in the promoter of the aconitase gene ZjACO3 influences fruit citric acid content in jujube
Authors: Liu Hanxiao , Zhao Xiangning , Bi Jingxin , Dong Xiaochang , Zhang Chunmei 
Published: January 2024

Abstract
Jujube (Ziziphus jujuba Mill.) is the most economically important fruit tree of the Rhamnaceae and was domesticated from wild or sour jujube (Z. jujuba Mill. var. spinosa Hu). During the process of domestication, there was a substantial reduction in the content of organic acids, particularly malate and citrate, which greatly influence the taste and nutritional value of the fruit. We previously demonstrated that ZjALMT4 is crucial for malate accumulation. However, the mechanism of citrate degradation in jujube remains poorly understood. In the present study, aconitase ZjACO3 was shown to participate in citric acid degradation in the cytoplasm through the GABA pathway. Interestingly, we discovered an E-box mutation in the ZjACO3 promoter (−484A &gt; G; CAAGTG in sour jujube mutated to CAGGTG in cultivated jujube) that was strongly correlated with fruit citrate content; ‘A’ represented a high-citrate genotype and ‘G’ represented a low-citrate genotype. We developed and validated an ACO-based Kompetitive allele-specific PCR (KASP) marker for determining citric acid content. Yeast one-hybrid screening, transient dual-luciferase assays, and overexpression analyses showed that the transcription factor ZjbHLH113 protein directly binds to CAGGTG in the promoter of ZjACO3 in cultivated jujube plants, transcriptionally activating ZjACO3 expression, and enhancing citric acid degradation. Conversely, binding ability of the ZjbHLH113 protein to CAAGTG was weakened in sour jujube, thereby promoting citrate accumulation in the fruit. These findings will assist in elucidating the mechanism by which ZjACO3 modulates citrate accumulation in sour jujube and its cultivars.
Clinical effectiveness of robotic-assisted compared to open or video-assisted lobectomy in Germany: a real-world data analysis
Authors: Eichhorn Martin , Bernauer Eva , Rotärmel Andre , Heurich Manuel , Winter Hauke 
Published: January 2024

Abstract

OBJECTIVES
Despite robotic-assisted thoracic surgery (RATS) lobectomy being on the rise in Europe, the majority of lobectomies in Germany are still performed with an open or thoracoscopic [video-assisted thoracic surgery (VATS)] approach. Empirical evidence in favour of RATS lobectomy is inconsistent. This retrospective cohort study investigates the impact of RATS lobectomy compared with open thoracic surgery (OPEN) and VATS lobectomy on short-term outcomes in Germany using multicentre real-world data.

METHODS
Anonymized routine data from Germany from 2018 to 2020 were retrospectively analysed. These data were provided by 61 German hospitals. Propensity score matching with subsequent generalized linear models was performed for statistical analysis. Additionally, in order to test the robustness of the results, multivariable regression analyses with cluster-robust standard errors were used.

RESULTS
A total of 2498 patients with lobectomy were identified: in 1345 patients OPEN, in 983 VATS and 170 a RATS lobectomy was performed. RATS—compared to OPEN and VATS—reduced length of stay (LOS) by 28% or 4.2 days [confidence interval: 2.9; 5.4] and by 13% or 1.6 days [confidence interval: 0.2; 3.0], respectively. The risk of pneumonia was reduced by 5.3 percentage points in the RATS group compared to both OPEN and VATS (P = 0.07/0.01). RATS—compared to an open approach—reduces the risk of blood transfusions by 8.8 percentage points (P &lt; 0.001) and LOS on the intensive care unit (P &lt; 0.001).

CONCLUSIONS
This study provides strong support that RATS lobectomy outperforms OPEN or VATS lobectomy in terms of hospital LOS, and short-term in-hospital postoperative complications in the real-world scenario in Germany.