bluuebunny/crossref_metadata_2025 huggingface dataset:
Core outcome set for clinical trials of stent implantation in coronary heart disease -- a systematic review and mixed-method consensus study
Authors: Wan Xingli , Wang Xinyi , Li Xia , Long Youlin , Li Zhengchi , Du Liang
Published: July 2024

Background

Although various types of stent interventions have been found in clinical trials to be effective in treating coronary heart disease, researchers often use heterogeneous outcome measures. This can preclude the comparison of results across studies and prevent effective meta-analyses from answering important clinical questions. The need to standardize outcome measure reporting is urgent. This study aims to produce a core outcome set(COS) for coronary stent implantation research.

Methods

We performed a systematic review via the PubMed and EMBASE databases and then synthesized recommendations from international standardized endpoint definitions and consensus documents to generate a list of potential outcomes. We conducted a two-round Delphi survey, achieving the iterative selection of potential outcomes. A multidisciplinary panel of experts and patients with coronary stent implantation experience rated the importance of candidate outcomes on a 9-point Likert scale. To be provisionally accepted, outcomes needed to be critical important (score 7-9, with 9 being the maximum) by 70% of each stakeholder group. Finally, we held a consensus meeting to discuss and generate the COS.

Results

A total of seventy-two potential outcomes were identified by systematic literature review. We obtained nine key consensus documents to inform the standardized definitions of the outcomes. After duplication and combination of similar outcomes, 26 of the 72 outcomes assigned into five outcome domains were included in the Delphi surveys. Twenty outcomes were provisionally accepted. Following the consensus meetings, the agreement was reached on a twelve-item COS.

Conclusion

We developed a COS for coronary stent implantation in coronary heart disease. Its implementation will facilitate the standardization reporting of clinical trials and reduce the heterogeneity in assessment in future research. Further research may help determine the specific, validated measurement instruments to assess each outcome.

What is Known

Coronary stent implantation is consider to be the primary method for treating coronary heart disease.

Many trials use heterogeneous effectiveness and safety outcome measures with different defined and non-patient concerned outcome measures, which would largely prevent meta-analyses and contribute to selective reporting bias.

What the Study Adds

We initially develop the first core outcome set(COS) of coronary stent implantation intervention for China to facilitate the standardization reporting of clinical trials and enable meta-analysis.

In our study, patient concerned outcome measure were thoroughly discussed and included in the COS by extensively involved patient representatives in every step of the project.

Although we used rigorous method to development the COS, it should be updated as new evidence emerges in this rapidly evolving field.
Eastern Diet - a healthful dietary pattern from Eastern China: Its characteristics and relation to adiposity, cardiometabolic diseases, mortality, and gut microbiota
Authors: Shi Yuwei , Kan Juntao , Li Xinmei , Yu Yuji , Yuan Changzheng , Jiang Ying , Wu Qiaoyu , Hao Yufan , Wang Ningling , Wang Wenjie , Huang Emma Yunzhi , Zheng Weifang , Yang Fei , Wu Joyce , Myers April , Hsing Ann W. , Du Jun , He Wei , Zhu Shankuan
Published: July 2024

Aim

The dietary pattern in the downstream Yangtze River region of Eastern China has garnered widespread attention for its potential health benefits but lacks empirical evidence. This study aimed to identify and characterize this dietary pattern, develop a dietary pattern index, and evaluate its associations with adiposity, cardiometabolic diseases (CMDs), mortality, and gut microbiota.

Methods

This study used data from 8665 participants aged 18-80 years in the WELL-China cohort (2016-2019, Hangzhou, Eastern China) as the discovery cohort. K-means clustering identified an “Eastern Diet” (EastDiet) pattern and an adherence index based on the 12 food groups and flavor preferences were developed. Adiposity was measured using dual-energy X-ray absorptiometry. Incident CMDs and mortality were tracked through June 2024. Validation involved two external cohorts.

Results

The EastDiet pattern was identified characterizing by high plant-based and aquatic food consumption, low refined grains and red meat intake, and a high preference for light-flavored. EastDiet index was favorably associated with lower adiposity. Comparing the highest to the lowest adherence tertiles, hazard ratios (HRs) for CMDs, type 2 diabetes, and cardiovascular diseases were 0.75 (95% CI: 0.62-0.90), 0.76 (0.60-0.96), and 0.71 (0.53-0.94), respectively. All-cause mortality was similarly reduced. Gut microbiota profiles associated with higher EastDiet adherence were linked to improved adiposity and reduced CMDs risk. Validation cohorts replicated these findings.

Conclusion

This study identified and characterized the EastDiet pattern from Eastern China and determined its health benefits. Our findings highlighted the potential of the EastDiet as a healthful dietary pattern for Chinese population.
Discrete mechanistic pathways underlying genetic predisposition to atrial fibrillation are associated with different intermediate cardiac phenotypes and risk of cardioembolic stroke
Authors: Gajendragadkar Parag R , Von Ende Adam , Murgia Federico , Offer Alison , Camm Christian Fielder , Wijesurendra Rohan S , Casadei Barbara , Hopewell Jemma C
Published: July 2024

Background Genome-wide association studies (GWAS) have clustered candidate genes associated with atrial fibrillation (AF) into biological pathways reflecting different pathophysiological mechanisms. We investigated whether these pathways associate with distinct intermediate phenotypes and confer differing risks of cardioembolic stroke. Methods Three distinct subsets of AF-associated genetic variants, each representing a different mechanistic pathway, i.e., the cardiac muscle function and integrity pathway (15 variants), the cardiac developmental pathway (25 variants), and the cardiac ion channels pathway (12 variants), were identified from a previous AF GWAS. Using genetic epidemiological methods and large-scale datasets such as UK Biobank, deCODE, and GIGASTROKE, we investigated the associations of these pathways with AF-related cardiac intermediate phenotypes, which included ECG parameters (~16,500 ECGs), left atrial and ventricular size and function (~36,000 cardiac MRI scans), and relevant plasma biomarkers (NT-proBNP, ~70,000 samples; high-sensitivity troponin I and T, ~87,000 samples), as well as with subtypes of ischaemic stroke (~11,000 cases). Results Genetic variants representing distinct AF-related mechanistic pathways had significantly different effects on several AF-related phenotypes. In particular, the muscle pathway was associated with a longer PR interval (P for heterogeneity between pathways [Phet] = 1 × 10-10), lower LA emptying fraction (Phet = 5 × 10-5), and higher NT-proBNP (Phet = 2 × 10-3) per log odds higher risk of AF compared to the developmental and ion channel pathways. By contrast, the ion channel pathway was associated with a lower risk of cardioembolic stroke (Phet = 0.04 in European, and 7 × 10-3 in multi-ancestry populations) compared to the other pathways. Conclusions Genetic variants representing specific mechanistic pathways for AF are associated with distinct intermediate cardiac phenotypes and a different risk of cardioembolic stroke. These findings provide a better understanding of the aetiological heterogeneity underlying the development of AF and its downstream impact on disease and may offer a route to more targeted treatment strategies.
A reaction norm for flowering time plasticity reveals physiological footprints of maize adaptation
Authors: Drouault Justine , Palaffre Carine , Millet Emilie J. , Rodriguez Jonas , Martre Pierre , Johnson Kristian , Parent Boris , Welcker Claude , Wisser Randall J.
Published: July 2024

Understanding how plant phenotypes are shaped by their environments is crucial for addressing questions about crop adaptation to new environments. This study focused on analyzing the genetic variability underlying genotype-by-environment interactions and adaptation for flowering time in maize. We developed the use of a physiological reaction norm for flowering time plasticity (PRN-FTP) modeled from multi-environment trial networks, with genotype-specific parameters putatively linked to different regulatory modules for flowering time. We show how genotype-specific differences in developmental responses to temperature fluctuations condition differences in photoperiod perceived among genotypes. This occurs not only across but also within common environments, as the perception of photoperiod is altered by variation in rates of development and durations for becoming sensitized to photoperiod. Using a new metric for envirotyping sensed photoperiods for maize, it was found that, at high latitudes, different genotypes in the same environment can experience up to hours-long differences in photoperiod. This emphasizes the importance of considering genotype-specific differences in the experienced environment when investigating plasticity. Modeling the PRN-FTP for global breeding material of maize showed that tropical and temperate germplasm occupy distinct territories of the trait space for PRN-FTP parameters, supporting that the geographical spread and adaptation of maize was differentially mediated by distinct pathways for flowering time regulation. Our results have implications for understanding crop adaptation and for future crop improvement efforts.

Article Summary

Maize adjusts its flowering time across environments using genetic pathways tuned to cues like temperature and day length. This study models how different varieties perceive and respond to these factors, revealing that genotypes can perceive the same environment in distinct ways. By examining the physiological underpinnings of genetic and environmental interactions, the research highlights how maize’s historical spread and artificial selection have shaped diverse strategies for flowering time regulation in tropical and temperate varieties.
Submaximal eccentric resistance training increases serial sarcomere number and improves dynamic muscle performance in old rats
Authors: Hinks Avery , Vlemmix Ethan , Power Geoffrey A.
Published: July 2024

The age-related loss of muscle mass is partly accounted for by the loss of sarcomeres in series. Serial sarcomere number (SSN) influences muscle mechanical function including the force-length and force-velocity-power relationships, and the age-related loss of SSN contributes to declining performance. Resistance training biased to active lengthening (eccentric) contractions increases SSN in young muscle, however, we showed maximal eccentric training in old rats did not alter SSN and further worsened performance. A submaximal eccentric training stimulus may be more conducive to adaptation for aged muscle. Therefore, the purpose of this study was to assess whether submaximal eccentric training can increase SSN and improve mechanical function in old rats. Twelve 32-month-old male F344/BN rats completed 4 weeks of submaximal (60% maximum) isokinetic eccentric plantar-flexion training 3 days/week. Pre- and post-training, we assessedin-vivomaximum isometric torque at a stretched and neutral ankle angle, the passive torque-angle relationship, and the isotonic torque-angular velocity-power relationship. The soleus and MG were harvested for SSN measurements via laser diffraction, with the untrained leg as a control. SSN increased 11% and 8%, and muscle wet weight increased 14% and 13% in the soleus and MG, respectively. Maximum isometric torque and shortening velocity were unaltered, but there was a shift towards longer muscle lengths for the optimal angle of torque production, a 42% reduction of passive torque, and 23% increase in peak isotonic power. Eccentric training at 60% maximum was beneficial for aged muscle, increasing SSN and muscle mass, reducing muscle passive tension, and improving dynamic performance.

New & Noteworthy

Four weeks of submaximal (60% of maximum) eccentric resistance training increased serial sarcomere number and muscle mass in old rats

Increased serial sarcomere number corresponded to broadening of the torque-angle relationship following training, which contributed to increased peak isotonic power

Submaximal eccentric training also led to a large reduction in passive torque throughout the range of motion
High-throughput drug screening for inhibition of influenza A virus infection based on human SIRT1 promoter and Genipin suppressing influenza A virus by activation of AMPK-SIRT1-PGC-1α signaling pathway
Authors: Ye Jinghan , Liu Dekun , Wang Qianwen , Dai Jianping
Published: July 2024

The energy metabolism crisis is considered an important risk factor for severe influenza A virus (IAV) infection. During virus replication, the host cell’s “metabolic reprogramming” is beneficial for increasing the energy demand of the virus. SIRT1 plays a major role in altering metabolic reprogramming, and upregulation of SIRT1 expression can defend against viral infection. This study established a high-throughput drug screening method for human SIRT1 promoter. Nine natural medicines were selected from 134 traditional Chinese medicines. Among them, the activity ofGardenia jasminoidesEllis was relatively high. Further research has found that the plant extract and its active compound Genipin and its derivatives can significantly inhibit IAV replication, improve the survival rate of infected mice, and inhibit pneumonia. In addition, Genipin significantly increased the levels of energy metabolism core regulatory factors SIRT1, PPAR γ, PGC-1 α, and p-AMPK, inhibited IAV induced activation of MAPKs and NF-κB, and alleviated inflammatory response. The pharmacological antagonists of SIRT1 and PGC-1 α, as well as siRNA, significantly counteracted the effects of Genipin on IAV replication and inflammation. In summary, we found that Genipin and its derivatives could significantly inhibit IAV replication and inflammation, possibly by activating the AMPK-SIRT1-PGC-1α signaling pathway and altering metabolic reprogramming.
Effects of clinically relevant radionuclides on the activation of a type I interferon response by radiopharmaceuticals in syngeneic murine tumor models
Authors: Kerr Caroline P. , Sheehan-Klenk Julia , Grudzinski Joseph J. , Adam David P. , Nguyen Thanh Phuong T. , Ferreira Carolina A. , Bates Amber M. , Jin Won Jong , Kwon Ohyun , Olson Aeli P. , Lin Wilson , Hyun Meredith , Jagodinsky Justin C. , Powers Maria , Sriramaneni Raghava N. , Clark Paul A. , Shea Amanda G. , Rojas Hansel Comas , Choi Cynthia , Massey Christopher F. , Zangl Luke M. , Pinchuk Anatoly N. , Aluicio-Sarduy Eduardo , Kim KyungMann , Engle Jonathan W. , Hernandez Reinier , Bednarz Bryan P. , Weichert Jamey P. , Morris Zachary S.
Published: July 2024

Radiopharmaceutical therapies (RPT) activate a type I interferon (IFN1) response in tumor cells. We hypothesized that the timing and amplitude of this response varies by isotope. We compared equal doses delivered by90Y,177Lu, and225Acin vitroas unbound radionuclides andin vivowhen chelated to NM600, a tumor-selective alkylphosphocholine. Response in murine MOC2 head and neck carcinoma and B78 melanoma was evaluated by qPCR and flow cytometry. Therapeutic response to225Ac-NM600+anti-CTLA4+anti-PD-L1 immune checkpoint inhibition (ICI) was evaluated in wild-type and stimulator of interferon genes knockout (STING KO) B78. The timing and magnitude of IFN1 response correlated with radionuclide half-life and linear energy transfer. CD8+/Treg ratios increased in tumors 7 days after90Y- and177Lu-NM600 and day 21 after225Ac-NM600.225Ac-NM600+ICI improved survival in mice with WT but not with STING KO tumors, relative to monotherapies. Immunomodulatory effects of RPT vary with radioisotope and promote STING-dependent enhanced response to ICIs in murine models.

Teaser

This study describes the time course and nature of tumor immunomodulation by radiopharmaceuticals with differing physical properties.
CrypToth: Cryptic pocket detection through mixed-solvent molecular dynamics simulations based topological data analysis
Authors: Koseki Jun , Motono Chie , Yanagisawa Keisuke , Kudo Genki , Yoshino Ryunosuke , Hirokawa Takatsugu , Imai Kenichiro
Published: July 2024

Some functional proteins undergo conformational changes to expose hidden binding sites when a binding molecule approaches their surface. Such binding sites are called cryptic sites and are important targets for drug discovery. However, it is still difficult to correctly predict cryptic sites. Therefore, we introduce a new method, CrypToth, for the precise identification of cryptic sites utilizing the persistent homology method. This method integrates topological data analysis and mixed-solvent molecular dynamics (MSMD) simulations. To identify hotspots corresponding to cryptic sites, we conducted MSMD simulations using six probes with different chemical properties: benzene, isopropanol, phenol, imidazole, acetonitrile, and ethylene glycol. Subsequently, we applied our topological data analysis method to rank hotspots based on the possibility of harboring cryptic sites. Evaluation of CrypToth using nine target proteins containing well-defined cryptic sites revealed its superior performance compared to recent machine-learning methods. As a result, in 7 out of 9 cases, hotspots associated with cryptic sites were ranked highest. CrypToth can explore hotspots on the protein surface favorable to ligand binding using MSMD simulations with six different probes and then identify hotspots corresponding to cryptic sites by assessing the protein’s conformational variability using the topological data analysis. This synergistic approach facilitates the prediction of cryptic sites with high accuracy.
Platelet integrin αIIbβ3 plays a key role in venous thrombogenesis in a mouse model
Authors: Adair Brian D. , Field Conroy O. , Alonso José L. , Xiong Jian-Ping , Deng Shi-Xian , Ahn Hyun Sook , Mashin Eivgeni , Clish Clary B. , van Agthoven Johannes , Yeager Mark , Guo Youzhong , Tess David A , Landry Donald W , Poncz Mortimer , Arnaout M. Amin
Published: July 2024

Abstract

Venous thrombosis (VT) is a common vascular disease associated with reduced survival and a high recurrence rate. Previous studies have shown that the accumulation of platelets and neutrophils at sites of endothelial cell activation is a primary event in VT, but a role for platelet αIIbβ3 in the initiation of venous thrombosis has not been established. This task has been complicated by the increased bleeding linked to partial agonism of current αIIbβ3 inhibitory drugs such as tirofiban (Aggrastat®). Here, we show that m-tirofiban, an engineered version of tirofiban, is not a partial agonist of αIIbβ3. This is based on its cryo-EM structure in complex with human full-length αIIbβ3 and its inability to increase expression of an activation-sensitive epitope on platelet αIIbβ3. m-tirofiban abolished agonist-induced platelet aggregationex vivoat concentrations that preserved clot retraction and markedly suppressed the accumulation of platelets, neutrophils, and fibrin on thrombin-activated endothelium in real-time using intravital microscopy in a mouse model of venous thrombogenesis. Unlike tirofiban, however, m-tirofiban did not increase bleeding at the thrombosis-inhibitory dose. These findings establish a key role for αIIbβ3 in the initiation of VT, provide a guiding principle for designing potentially safer inhibitors for other integrins, and suggest that pure antagonists of αIIbβ3 like m-tirofiban merit further consideration as potential thromboprophylaxis agents in patients at high-risk for VT and hemorrhage.
I2Bot: an open-source tool for multi-modal and embodied simulation of insect navigation
Authors: Sun Xuelong , Mangan Michael , Peng Jigen , Yue Shigang
Published: July 2024

Achieving a comprehensive understanding of animal intelligence demands an integrative approach that acknowledges the interplay between an organism’s brain, body, and environment. Insects like ants, despite their limited computational resources, demonstrate remarkable abilities in navigation. Existing computational models often fall short in faithfully replicating the morphology of real insects and their interactions with the environment, hindering validation and practical application in robotics. To address these gaps, we present I2Bot, a novel simulation tool based on the morphological characteristics of desert ants. This tool empowers robotic models with dynamic sensory capabilities, realistic modelling of insect morphology, physical dynamics, and sensory capacity. By integrating gait controllers and computational models into I2Bot, we have implemented classical embodied navigation behaviours and revealed some fundamental navigation principles. By open-sourcing I2Bot, we aim to accelerate the understanding of insect intelligence and foster advances in the development of autonomous robotic systems.
Genome-wide meta-analyses of non-response to antidepressants identify novel loci and potential drugs
Authors: Koch Elise , Jurgenson Tuuli , Einarsson Gudmundur , Mitchell Brittany , Harder Arvid , Garcia-Marin Luis M , Krebs Kristi , Lin Yuhao , Xiong Ying , Research Team Estonian Biobank , Lu Yi , Hagg Sara , Renteria Miguel E , Medland Sarah E , Wray Naomi R , Martin Nicholas G , Huebel Christopher , Breen Gerome , Thorgeirsson Thorgeir , Stefansson Hreinn , Stefansson Kari , Milani Lili , Andreassen Ole A , O'Connell Kevin S
Published: July 2024

Antidepressants exhibit a considerable variation in efficacy, and increasing evidence suggests that individual genetics contribute to antidepressant treatment response. Here, we combined data on antidepressant non-response measured using rating scales for depressive symptoms, questionnaires of treatment effect, and data from electronic health records, to increase statistical power to detect genomic loci associated with non-response to antidepressants in a total sample of 135,471 individuals prescribed antidepressants. We performed genome-wide association meta-analyses, leave-one-out polygenic prediction, and bioinformatics analyses for genetically informed drug prioritization. We identified two novel loci associated with non-response to antidepressants and showed significant polygenic prediction in independent samples. In addition, we investigated drugs that target proteins likely involved in mechanisms underlying antidepressant non-response, and shortlisted drugs that warrant further replication and validation of their potential to reduce depressive symptoms in individuals who do not respond to first-line antidepressant medications. These results suggest that meta-analyses of GWAS utilizing real-world measures of treatment outcomes can increase sample sizes to improve the discovery of variants associated with non-response to antidepressants.
Unbiased functional genetic screens reveal essential RNA modifications in human cancer and drug resistance
Authors: Pauli Cornelius , Kienhöfer Michael , Blank Maximilian Felix , Begik Oguzhan , Rohde Christian , Heid Daniel , Xu Fu , Zimmermann Sarah Miriam Naomi , Weidenauer Katharina , Delaunay Sylvain , Krall Nadja , Trunk Katrin , Zhao Duoduo , Zhou Fengbiao , Heit-Mondrzyk Anke , Platzbecker Uwe , Baldus Claudia , Serve Hubert , Bornhäuser Martin , Vågbø Cathrine Broberg , Aznar Benitah Salvador , Krijgsveld Jeroen , Novoa Eva Maria , Müller-Tidow Carsten , Frye Michaela
Published: July 2024

RNA modification pathways are mis-regulated in multiple types of human cancer. To comprehensively identify cancer-relevant RNA modifications and their regulators, we screened all 150 annotated human RNA modifying proteins across 18 different normal and cancer cell lines using a CRISPR-based genetic knockout system. Fifty RNA modifying proteins were essential for survival of at least one cell type. A third of these essential genes were amplified in 38 different human primary cancer types and potentially drive cancer growth. Unexpectedly, the number of essential genes per cell line varied considerably, and this variation was not due to tissue of origin. Instead, we found that cancer cell-specific mitochondrial metabolic plasticity was responsible for the unique requirement of certain RNA modifications. For example, leukemia cells with high intrinsic drug tolerance required mitochondrial flexibility to survive treatment with the anti-leukemic drugs cytarabine and venetoclax. Synthetic lethality screens revealed that drug-resistance is abolished by deleting the mitochondrial methyltransferase TRMT5, which is responsible for the formation of N1-methylguanosine (m1G) in the tRNA anticodon loop. In summary, our study identifies cancer-relevant RNA modifying enzymes, and reveals a novel promising drug target for therapy-resistant acute myeloid leukemia.
Effect of the COVID-19 pandemic and maternal SARS-CoV-2 status on breastfeeding practices in the COMBO cohort
Authors: Walzer Lauren , Nichols Presley , Amoo-Achampong Monica K. , Glassman Melissa E. , Kyle Margaret H. , Hussain Maha , Abreu Wanda , Scripps Tessa , Khan Adrita , Hanft Erin , Xu Ruiyang L. , LoFrumento Mary Ann , Kataria Anglina , Stockwell Melissa S. , Dumitriu Dani , Fernández Cristina R.
Published: July 2024

Objectives

To investigate the role of prenatal maternal SARS-CoV-2 infection and delivery during the COVID-19 pandemic on breastfeeding practices through 6 months postpartum.

Study design

A cohort of mother-infant dyads who delivered at a large medical center in New York City and who had either documented history of prenatal SARS-CoV-2 infection, no history of SARS-CoV-2 infection, or who delivered in February 2020 prior to the COVID-19 pandemic were invited to participate in the COVID-19 Mother Baby Outcomes (COMBO) Initiative. These three groups of mothers completed surveys about their breastfeeding practices at 1, 2, 4, and/or 6 months postpartum, and responses were compared across enrollment group at each postpartum assessment period.

Results

Data from 557 mother-infant dyads was included. The SARS-CoV-2 infected group reported significantly lower rates of mostly or exclusively breastfeeding at 1 month, 2 months, and 4 months postpartum. When analyses were separated by birth timing and maternal ethnicity, these differences between infected and uninfected mothers were only significant in the second pandemic wave delivery group and in Latina mothers.

Conclusions for practice

Maternal SARS-CoV-2 infection during pregnancy was associated with lower rates of mostly or exclusively breastfeeding through 4 months postpartum. These differences may have been driven by delivery timing during the pandemic and self-reported maternal ethnicity. These results suggest a need to increase resources and support for breastfeeding during healthcare-disruptive events such as the pandemic, particularly for those belonging to groups historically underserved in healthcare.
Training community home care workers to deliver a tailored falls prevention Education and Exercise program to home care clients – TrEdEx an effectiveness-implementation study protocol
Authors: Francis-Coad Jacqueline , Hill Anne-Marie , Flicker Leon , Etherton-Beer Christopher , Burton Elissa , Wharton Philippa , Wilkinson Jo , Norman Richard , Xu Daniel , Vaz Sharmila , Jessup Vanessa
Published: July 2024

Frail, older people receiving supportive care in the home are at high risk of falls and functional decline that leads to either unplanned hospital admissions or permanent residential care, making it difficult to safely remain at home. Community home care organisations are well positioned to deliver high quality falls prevention programs if staff are suitably trained. This research aims to train community home care workers to deliver a fall prevention program to home care clients and evaluate program implementation and effectiveness.

A 2-phase hybrid effectiveness-implementation, pre- post design using a realist approach will be undertaken with a home care organisation. Home care workers, comprising community therapy assistants and community support workers, employed by the organisation will be trained to deliver the program by the organisation’s allied health professional staff using a train the trainer model. A multi-media falls prevention program (education and exercises) will be tailored to the client’s falls risk profile to raise falls awareness and promote physical activity and self-management. Clients receiving home care from the organisation will be recruited. Implementation of the program will be guided by the Consolidated Framework for Implementation Research, barriers and enablers will be identified at the client, staff, and organisation levels. Program effectiveness will be determined through client engagement, program satisfaction, knowledge acquisition, attitudes and enactment of falls prevention strategies, changes in functional mobility, falls and falls injuries and a cost-consequence analysis.

If successful, home care clients may enhance their functional mobility and reduce their risk of falling, allowing them to stay safely at home. Home care organisations could positively contribute to the sustainable development of a well-trained workforce delivering evidence-based programs.
GWAS and 3D chromatin mapping identifies multicancer risk genes associated with hormone-dependent cancers
Authors: Rivera Isela Sarahi , French Juliet D. , Bitar Mainá , Sivakumaran Haran , Nair Sneha , Kaufmann Susanne , Hillman Kristine M. , Marjaneh Mahdi Moradi , Beesley Jonathan , Edwards Stacey L.
Published: July 2024

Hormone-dependent cancers (HDCs) share several risk factors, suggesting a common aetiology. Using data from genome-wide association studies, we showed spatial clustering of risk variants across four HDCs (breast, endometrial, ovarian and prostate cancers), contrasting with genetically uncorrelated traits. We identified 44 multi-HDC risk regions across the genome, defined as overlapping risk regions for at least two HDCs: two regions contained risk variants for all four HDCs, 13 for three HDCs and 28 for two HDCs. Integrating GWAS data, epigenomic profiling and high-resolution promoter capture HiC maps from diverse cell line models, we annotated 53 candidate risk genes at 22 multi-HDC risk regions. These targets were enriched for established genes from the COSMIC Cancer Gene Census, but many had no previously reported pleiotropic roles. Additionally, we pinpointed lncRNAs as potential HDC targets and identified risk alleles in several regions that altered transcription factors motifs, suggesting regulatory mechanisms. Known drug targets were over-represented among the candidate multi-HDC risk genes, implying that some may serve as targets for therapeutic development or facilitate the repurposing of existing treatments for HDC. Our comprehensive approach provides a framework for identifying common target genes driving complex traits and enhances understanding of HDC susceptibility.

AUTHOR SUMMARY

While hormone-dependent cancers (HDCs) share several risk factors, our understanding of the complex genetic interactions contributing to their development is limited. In this study, we leveraged large-scale genetic studies of cancer risk, high-throughput sequencing methods and computational analyses to identify genes associated with four HDCs: breast, endometrial, ovarian and prostate cancers. We identified known cancer genes and discovered many that were not previously linked to cancer. These findings are significant because identifying genes associated with risk of multiple cancer types can enhance the gene mapping accuracy and highlight new therapeutic targets.
Catecholaminergic modulation of large-scale network dynamics is tied to the reconfiguration of corticostriatal connectivity
Authors: Hill Justine A. , Korponay Cole , Salmeron Betty Jo , Ross Thomas J. , Janes Amy C.
Published: July 2024

Large-scale brain network function is critical for healthy cognition, yet links between such network function, neurochemistry, and smaller-scale neurocircuitry are unclear. Here, we evaluated 59 healthy individuals using resting-state fMRI to determine how network-level temporal dynamics were impacted by two well-characterized pharmacotherapies targeting catecholamines: methylphenidate (20mg) and haloperidol (2mg). Network dynamic changes were tested for links with drug-induced alterations in complex corticostriatal connections as this circuit is a primary site of action for both drugs. A randomized, double-blind, placebo-controlled design was used. Methylphenidate enhanced time spent in the default mode network (DMN p<0 .001) and dorsal attention network (DAN p<0.001) and reduced time in the frontoparietal network (p<0.01). Haloperidol increased time in a sensory motor-DMN state (p<0.01). The magnitude of change in network dynamics induced by methylphenidate vs. placebo was correlated with the magnitude of methylphenidate-induced rearrangement of complex corticostriatal connectivity (R=0.32, p=0.014). Haloperidol did not alter complex corticostriatal connectivity. Methylphenidate increased time in networks involved in internal (DMN) and external attention (DAN), aligning with methylphenidate’s established role in attention. Methylphenidate also significantly changed complex corticostriatal connectivity by altering the relative strength between multiple corticostriatal connections, indicating that methylphenidate may shift which corticostriatal connections are prioritized relative to others. Findings further show that these local circuit changes are linked with large scale network function. Collectively, these findings provide a deeper understanding of large-scale network function, set a stage for mechanistic understanding of network engagement, and provide needed information to potentially guide medication use based on network-level effects.
Histology-informed microstructural diffusion simulations for MRI cancer characterisation — the Histo-μSim framework
Authors: Grigoriou Athanasios , Macarro Carlos , Palombo Marco , Navarro-Garcia Daniel , Voronova Anna , Bernatowicz Kinga , Barba Ignasi , Escriche Alba , Greco Emanuela , Abad María , Simonetti Sara , Serna Garazi , Mast Richard , Merino Xavier , Roson Núria , Escobar Manuel , Vieito Maria , Nuciforo Paolo , Toledo Rodrigo , Garralda Elena , Sala-Llonch Roser , Fieremans Els , Novikov Dmitry S. , Perez-Lopez Raquel , Grussu Francesco
Published: July 2024

Diffusion Magnetic Resonance Imaging (dMRI) simulations in geometries mimicking the complexity of human tissues at the microscopic scale enable the development of innovative biomarkers with unprecedented fidelity to histology. To date, approaches of this kind have focussed heavily on brain imaging. Nevertheless, simulation-informed dMRI has huge potential also in other applications, as for example in body cancer imaging, where new non-invasive biomarkers are still sought. This article fills this gap by introducing a Monte Carlo diffusion simulation framework informed by histology, for enhanced body dMR microstructural imaging — theHisto-μSimapproach. We generate dictionaries of synthetic dMRI signals with coupled tissue properties from virtual cancer environments, reconstructed from hematoxylin-eosin stains of human liver biopsies. These enable the data-driven estimation of innovative microstructural tissue properties, such as the intrinsic extra-cellular diffusivity, or cell size (CS) distribution moments. We compareHisto-μSimto metrics from well-established analytical multi-compartment modelsin silico, on fixed mouse tissues scannedex vivo(kidneys, spleens, and breast tumours) and in cancer patientsin vivo. Results suggest thatHisto-μSimis feasible in clinical settings, and that it delivers metrics that more accurately reflect the underlying histology as compared to analytical models. In conclusion,Histo-μSimoffers histologically-meaningful tissue descriptors that may increase the specificity of dMRI towards cancer, and thus play a crucial role in precision oncology.
Multi-omics characterization of type 2 diabetes associated genetic variation
Authors: Mandla Ravi , Lorenz Kim , Yin Xianyong , Bocher Ozvan , Huerta-Chagoya Alicia , Arruda Ana Luiza , Piron Anthony , Horn Susanne , Suzuki Ken , Hatzikotoulas Konstantinos , Southam Lorraine , Taylor Henry , Yang Kaiyuan , Hrovatin Karin , Tong Yue , Lytrivi Maria , Rayner Nigel W. , Meigs James B. , McCarthy Mark I. , Mahajan Anubha , Udler Miriam S. , Spracklen Cassandra N. , Boehnke Michael , Vujkovic Marijana , Rotter Jerome I. , Eizirik Decio L. , Cnop Miriam , Lickert Heiko , Morris Andrew P. , Zeggini Eleftheria , Voight Benjamin F. , Mercader Josep M.
Published: July 2024

Discerning the mechanisms driving type 2 diabetes (T2D) pathophysiology from genome-wide association studies (GWAS) remains a challenge. To this end, we integrated omics information from 16 multi-tissue and multi-ancestry expression, protein, and metabolite quantitative trait loci (QTL) studies and 46 multi-ancestry GWAS for T2D-related traits with the largest, most ancestrally diverse T2D GWAS to date.

Of the 1,289 T2D GWAS index variants, 716 (56%) demonstrated strong evidence of colocalization with a molecular or T2D-related trait, implicating 657cis-effector genes, 1,691 distal-effector genes, 731 metabolites, and 43 T2D-related traits. We identified 773 of thesecis-and distal-effector genes using either expression QTL data from understudied ancestry groups or inclusion of T2D index variants enriched in underrepresented populations, emphasizing the value of increasing population diversity in functional mapping. Linking these variants, genes, metabolites, and traits into a network, we elucidated mechanisms through which T2D-associated variation may impact disease risk. Finally, we showed that drugs targeting effector proteins were enriched in those approved to treat T2D, highlighting the potential of these results to prioritize drug targets for T2D.

These results represent a leap in the molecular characterization of T2D-associated genetic variation and will aid in translating genetic findings into novel therapeutic strategies.
Early combination of sotrovimab with nirmatrelvir/ritonavir or remdesivir is associated with low rate of persisting SARS CoV-2 infection in immunocompromised outpatients with mild-to-moderate COVID-19: a prospective single center study
Authors: Gentile I. , Viceconte G. , Cuccurullo F. , Pietroluongo D. , D’Agostino A. , Silvitelli M. , Mercinelli S. , Scotto R. , Grimaldi F. , Palmieri S. , Gravetti A. , Trastulli F. , Moccia M. , Buonomo A.R.
Published: July 2024

Background

Immunocompromised patients are at high risk of developing persisting/prolonged COVID-19 Data concerning early combined use of antivirals and monoclonal antibodies in this population are scarce.

Research design and methods

We performed an observational, prospective study, enrolling immunocompromised outpatient adults with mild-to-moderate COVID-19 treated with a combination of sotrovimab plus one antiviral (remdesivir or nirmatrelvir/ritonavir) within 7 days from symptoms’ onset.

Results

We enrolled 52 patients. No patient was hospitalized within 30 days from the disease onset, needed oxygen administration or died within 60 days, or experienced a reinfection or a clinical relapse within 90 days.

Clearance rates were 67% and 97% at 14th day after the end of therapy and at the end of follow-up, respectively.

Factors associated with longer infection were initiation of therapy after 3 days from symptoms onset, and enrollment more than 180 days from the beginning of the study. However, only the latter factor was independently associated with longer SARS-CoV-2 infection, suggesting a loss of efficacy of this strategy with the evolution of SARS-CoV-2 variants

Conclusions

Early administration of combination therapy with a direct antiviral and sotrovimab seems to be effective in preventing hospitalization, progression to severe COVID-19 and the development of prolonged/persisting SARS-CoV-2 infection in immunocompromised patients.
Insights to obstructive jaundice: comprehensive analysis and machine learning-based diagnostics in over 5000 individuals
Authors: Wen Ningyuan , Wang Yaoqun , Xiong Xianze , Xu Jianrong , Wang Shaofeng , Tian Yuan , Zeng Di , Pu Xingyu , Liu Geng , Li Bei , Lu Jiong , Cheng Nansheng
Published: July 2024

Background

Obstructive jaundice is a common problem associated with diverse etiologies which has not been thoroughly investigated in large-scale cohorts. Our study involved the largest retrospective cohort of obstructive jaundice to date, exploring the spectrum of diseases while establishing a diagnostic system with machine learning (ML) methods based on routine laboratory tests.

Methods

This study involves two retrospective observational cohorts from China. The biliary surgery cohort (BS cohort, n=349) served for initial data exploration and external validation of ML models, while the large general cohort (LG cohort, n=5726) enabled comprehensive data analysis and ML model construction. Interpretable ML techniques were employed to derive insights from the models.

Results

The LG cohort exhibited a more diverse disease spectrum compared to the BS cohort, with pancreatic adenocarcinoma, common bile duct stones, distal cholangiocarcinoma, perihilar cholangiocarcinoma, and acute pancreatitis (non-calculous) identified as the top five causes of obstructive jaundice. Traditional serum markers such as CA 19-9 and CEA did not emerge as standalone diagnostic markers for obstructive jaundice. Leveraging ML techniques, we developed two models collectively named as the MOLT model: one effectively distinguishes between benign and malignant causes (AUROC=0.862), while the other provides nuanced insights by further categorizing malignancies into three tiers and benign diseases into two (ACC=0.777). Interpretable ML tools revealed key features contributing to the decision-making process of each model.

Conclusions

Through our study, we uncovered the diagnostic potential of routine laboratory tests in obstructive jaundice, enabling the development of a practical diagnostic tool based on interpretable ML models. These findings may pave the way for personalized and user-friendly diagnosis of obstructive jaundice, thereby aiding clinical decision-making.
Prevalence and associated factors of suicidal behavior among adolescents in rural Bangladesh
Authors: Mumu Rifa Tamanna , Shaikh Md Parvez , Mitra Dipak Kumar
Published: July 2024

Background

Among the four leading causes of worldwide death, suicide is one, which is prevailing especially in lower-middle-income countries. However, the number of studies is minimal based on adolescent suicidal behavior in rural Bangladesh. This study aims to identify the prevalence and associated factors of suicidal behavior in adolescents in a remote subdistrict in Bangladesh.

Method

A cross-sectional study was performed in Lohagara, a rural subdistrict in southern Bangladesh from July, 15 to August 14, 2024. 350 subjects were recruited for the study, all of whom were school-going adolescents aged 11 to 17. The Bengali-translated versions of the Suicidal Behavior-Revised Questionnaire (SBQ-R) and the Depression, Anxiety, and Stress Scale - 21 Items (DASS-21), as well as another structured questionnaire, were used to obtain data from participants. Data were analyzed by STATA version 17.

Result

The prevalence of suicidal behavior among adolescents is 12.3% (95% CI: 9.2% to 16.2%) (overall SBQ-R score of 7 or more). Having step-parents, peer conflict, stress, anxiety, and a family history of suicide are found to be significantly associated with the development of suicidal behavior in adolescents. Unmarried and single relationship status and the overprotective attitude of parents play a protective role in growing young adults’ suicidal tendencies.

Conclusion

The notable prevalence of suicidal behavior in adolescents underscores the need for screening and intervention at an early age. Different health promotional and educational programs can be organized in schools and communities. The ultimate goal is to protect adolescents with adequate counseling, care, and support.
Using a hybrid of artificial intelligence and template-based method in automatic item generation to create multiple-choice questions in medical education: Hybrid AIG
Authors: Kıyak Yavuz Selim , Kononowicz Andrzej A.
Published: July 2024

Objectives

Template-based automatic item generation (AIG) is more efficient than traditional item writing but it still heavily relies on expert effort in model development. While non-template-based AIG, leveraging artificial intelligence (AI), offers efficiency, it faces accuracy challenges. We aimed to integrate these approaches for leading to a significant rise in efficiency for AIG without sacrificing accuracy.

Material and Methods

We proposed the Hybrid AIG method that utilizes AI to generate item models (templates) and cognitive models to combine the advantages of the two AIG approaches. The Hybrid AIG consists of seven steps. The first five steps are carried out by an expert in a customized AI environment. Following a final expert review (Step 6), the content in the template can be used for item generation through a traditional (non-AI) software (Step 7). We used two multiple-choice questions for demonstration.

Results

We demonstrated that AI is capable of generating item models and cognitive models for AIG under the guidance of a human expert. Leveraging AI in template development has substantially reduced the time investment from five hours to less than 10 minutes, and made it significantly less challenging.

Conclusions

The Hybrid AIG method transcends the traditional template-based approach by marrying the “art” that comes from AI as a “black box” with the “science” of algorithmic generation under the oversight of expert as a “marriage registrar”. It does not only capitalize on the strengths of both approaches but also mitigates their weaknesses, offering a human-AI collaboration to increase efficiency in medical education.