bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the Impact of Various Treatments on Gene Expression in Olive (Olea europaeaL.) Drupes Affected byPhytophthora oleae: Insights from RNA sequencing-based transcriptome analysis
Authors: Conti Taguali Sebastiano , Riolo Mario , La Spada Federico , Dionisio Giuseppe , Cacciola Santa Olga 
Published: July 2024

AbstractPhytophthora oleaeis a pathogen recently reported to cause fruit rot on olive orchards in Italy and root rot in a natural wild-olive forest in Spain. RNAseq analysis was conducted to gain insight into the molecular mechanisms that trigger a plant defense response upon the inoculation of drupes withP. oleaeand the pre- treatment with the antagonistic yeastCandida oleophilaor with culture filtrates of the antagonistic filamentous fungusTrichoderma atroviride. Both treatments were applied to the olive drupe 24 h before the inoculation with the pathogen. Although no full resistance was observed, the virulence ofP. oleaewas reduced when the drupes were co-inoculated with the yeast or treated with culture filtrates ofTrichoderma. Severity ofPhytophthorarots in olive drupes was assessed at 24, 72, and 168 hours post pathogen inoculation (hpi) and rated based on an empirical scale. The most effective in reducing the disease severity ofP. oleaeinfection on olive fruit was the treatment withT. atroviridefiltrate (56% reduction), followed byC. oleophila(52%). Results showed that 2,466, 1,883, and 1,757 genes were differentially expressed in response toP. oleae, to the binary pathosystemC. oleophilaandP. oleae, andT. atrovirideandP. oleae, respectively, as compared to wound. Differential RNAseq by DESeq2, performed at 72 hours post-inoculation, and qPCR validation, at 24, 72, and 168 hpi, of the top differentially expressed genes defined a new pattern of plant defense mechanisms involving both PAMP and ETI immunity, with production of ROS and PRs.
The Impact of a Primary Aldosteronism Predictive Model in Secondary Hypertension Decision Support
Authors: Mack Peter B. , Cole Casey , Lee Mintaek , Peterson Lisa , Lundy Matthew , Hegarty Karen , Espinoza William 
Published: July 2024

AbstractObjectiveTo determine whether the addition of a primary aldosteronism (PA) predictive model to a secondary hypertension decision support tool increases screening for PA in a primary care setting.Materials and Methods153 primary care clinics were randomized to receive a secondary hypertension decision support tool with or without an integrated predictive model between August 2023 and April 2024.ResultsFor patients with risk scores in the top 1 percentile, 63/2,896 (2.2%) patients where the alert was displayed in model clinics had the order set launched while 12/1,210 (1.0%) in no model clinics had the order set launched (P = 0.014). 19/2,896 (0.66%) of these highest risk patients in model clinics had an ARR ordered compared to 0/1,210 (0.0%) patients in no model clinics (P = 0.010). For patients with scores not in the top 1 percentile, 438/20,493 (2.1%) patients in model clinics had the order set launched compared to 273/17,820 (1.5%) in no model clinics (P < 0.001). 124/20,493 (0.61%) in model clinics had an ARR ordered compared to 34/17,820 (0.19%) in the no model clinics (P < 0.001).DiscussionThe addition of a PA predictive model to secondary hypertension alert displays and triggering criteria along with order set displays and order preselection criteria results in a statistically and clinically significant increase in screening for PA, a condition that clinicians insufficiently screen for currently.ConclusionAddition of a predictive model for an under-screened condition to traditional clinical decision support may increase screening for these conditions.
Preventable maternal deaths in England and Wales, 2013-2023: a systematic case series of coroners’ reports
Authors: Jindal Jessy , Launer David , Richards Georgia C. , Dernie Francesco 
Published: July 2024

AbstractObjectiveCoroners in England and Wales have a duty to write Prevention of Future Deaths (PFDs) reports when they believe that action should be taken to prevent similar deaths. We aimed to characterise learnings from reports involving maternal deaths.DesignSystematic case seriesSettingEngland and WalesPopulation or SampleDatabase of all coroners’ PFDs published between July 2013 and 1 August 2023. There were 4435 reports at the time of data collection.MethodsA reproducible computer code developed from the Preventable Deaths Tracker (https://preventabledeathstracker.net/) was used to download all published PFDs from the Judiciary website. Reports were searched for keywords related to maternal deaths. Case information was extracted into pre-specified domains and compared to other data on maternal deaths.Main Outcome MeasuresCase demographics, causes of deaths, risk factors, coroner concerns and organisational responses.ResultsTwenty nine reports involved a maternal death. The median age at death was 33.5 years (IQR 29-36 years) and 76% of deaths occurred in hospitals. The most common cause of death was haemorrhage. Coroners frequently voiced concerns around failure to provide appropriate treatment (57%), and failure of timely escalation (38%). Only 38% of PFDs had published responses. When organisations did respond to the coroner, 80% reported that they implemented changes, including publishing new local policies, increasing training, or committing to increased staffing.ConclusionsPFDs highlight gaps in obstetric care which, if appropriately addressed, and regularly and routinely monitored, could prevent similar deaths.FundingNone
Multinational evaluation of anthropometric age (AnthropoAge) as a measure of biological age in the USA, England, Mexico, Costa Rica, and China: a population-based longitudinal study
Authors: Fermín-Martínez Carlos A. , Ramírez-García Daniel , Antonio-Villa Neftali Eduardo , Espinosa Jerónimo Perezalonso , Aguilar-Ramírez Diego , García-Peña Carmen , Gutiérrez-Robledo Luis Miguel , Seiglie Jacqueline A. , Bello-Chavolla Omar Yaxmehen 
Published: July 2024

ABSTRACTOBJECTIVETo validate AnthropoAge, a new metric of biological age (BA), for prediction of all-cause mortality and age-related outcomes and characterize population-specific aging patterns using multinational longitudinal cohorts.METHODSWe analyzed harmonized multinational data from the Gateway to Global Aging, including studies from the US, England, Mexico, Costa Rica, and China. We used body mass index and waist-to-height ratio to estimate AnthropoAge and AnthropoAgeAccel in participants aged 50-90 years old as proxies of BA and age acceleration, respectively. We compared the predictive capacity for all-cause mortality of AnthropoAge and chronological age (CA) using Cox models, described aging trends in all countries and explored the utility of longitudinal assessments of AnthropoAgeAccel to predict new-onset functional decline and age-related diseases using generalized estimating equations (GEE).FINDINGSUsing data from 55,628 participants, we found AnthropoAge (c-statistic 0.772) outperformed CA (0.76) for prediction of mortality independently of comorbidities, sex, race/ethnicity, education, and lifestyle; this result was replicated in most countries individually except for Mexico. Individuals with accelerated aging had a ∼39% higher risk of death, and AnthropoAge also identified trends of faster biological aging per year. In longitudinal analyses, higher AnthropoAgeAccel values were independently predictive of self-reported health deterioration and new-onset deficits in basic/instrumental activities of daily living (ADL/IADL), diabetes, hypertension, cancer, chronic lung disease, myocardial infarction, and stroke.CONCLUSIONSAnthropoAge is a robust and reproducible BA metric associated with age-related outcomes. Its implementation could facilitate modeling trends of biological aging acceleration in different populations, although recalibration may enhance its utility in underrepresented populations such as individuals from Latin America.
Safety and efficacy of a modular digital psychotherapy for social anxiety: A randomized controlled trial
Authors: Garvert Mona M. , McFadyen Jessica , Linke Stuart , McCloud Tayla , Meyer Sofie S. , Sobanska Sandra , Sharp Paul B. , Long Alex , Huys Quentin J. M. , Ahmadi Mandana 
Published: July 2024

AbstractBackgroundSocial anxiety disorder is a common mental health condition characterized by an intense fear of social situations which can lead to significant impairment in daily life. Cognitive behavioral therapy (CBT) has been recognized as an effective treatment; however, access to therapists is limited and the fear of interacting with therapists can delay treatment seeking. Furthermore, not all individuals respond. Tailoring modular treatments to individual cognitive profiles may improve efficacy. We developed a novel digital adaptation of CBT for social anxiety that is both modular and fully digital without therapist in the loop and implemented it in a smartphone app.ObjectiveTo evaluate the safety, acceptability and efficacy of the new treatment in online participants with symptoms of social anxietyMethodsTwo online randomized controlled trials comparing individuals with access to the treatment through the app to waitlist. Participants were recruited online and reported Social Phobia Inventory (SPIN) total scores >= 30. Primary outcomes were safety and efficacy over 6 weeks in 102 women aged 18-35 (RCT #1) and symptom reduction (Social Phobia Inventory total scores) after 8 weeks in 267 men and women aged 18-75 (RCT #2).ResultsIn RCT #1, active and control arm adverse event frequency and severity was not distinguishable. App acceptability was high. Secondary outcomes suggested greater symptom reduction in the active (-9.83 ± 12.80) than the control arm (-4.13 ± 11.59, t90= -2.23, pFDR= .037, Cohen’s d = 0.47). In RCT #2, there was a higher symptom reduction in the active arm (-12.89 ± 13.87) than the control arm (-7.48 ± 12.24, t227= - 3.13, pFDR= .008, Cohen’s d = 0.42).ConclusionsThe online-only, modular social anxiety CBT program appears safe, acceptable and efficacious in an online patient group with self-reported symptoms of social anxiety.Trial RegistrationRCT #1: ClinicalTrials.govNCT05858294, RCT #2: ClinicalTrials.govNCT05987969
Kisspeptin System and Menarcheal Age as Predictors of Primary Female Infertility: A Case-Control Study Among Nigerian Women
Authors: Okafor Izuchukwu Azuka , Saanu Oluseun Olugbenga , Olayemi Oladapo , Omigbodun Akinyinka O. 
Published: July 2024

AbstractBackgroundThe Kisspeptin system plays a critical regulatory role in female reproductive functions. However, its role is not yet investigated in primary female infertility (PFI).Materials and MethodsThis is a case-control study of consenting primarily infertile (54) and fertile (50) Nigerian females aged between 20 and 44 years who sought consult at University College Hospital, Ibadan. Basic clinical and demographic data were obtained from the participants using a clinical proforma. Five ml of blood were collected by venepuncture for kisspeptin, KISS1, and KISS1R gene expression analysis within the plasma using ELISA and RT-qPCR techniques. The menarcheal age and BMI of the cases and controls were also investigated as possible predictors of PFI.ResultThere was no significant change in the relative expression of Kisspeptin, KISS1, and KISS1R genes (p>0.05) in the plasma of the primarily infertile women (PIW) compared to the fertile women (FW). PIW with early menarche showed a significantly lower level of Kisspeptin compared to PIW with normal menarche (p=0.03). Plasma Kisspeptin levels in PIW showed a weak negative correlation (r = −.305; p=0.039) and a good predictive model for KISS1 gene expression (p=0.001; r=0.458). There was a significant difference in KISS1 gene expression in PIW when compared based on their menarcheal age categories (p=0.04).ConclusionKisspeptin levels, KISS1, and KISS1R gene expression levels in the blood may not be useful for diagnosing PFI. However, menarcheal age should be investigated as an additional diagnostic indicator for PFI.
Exploring the power of MRI and clinical measures in predicting Alzheimer’s disease neuropathology
Authors: Kamal Farooq , Morrison Cassandra , Oliver Michael D. , Dadar Mahsa 
Published: July 2024

AbstractBackgroundThe ability to predict Alzheimer’s disease (AD) before diagnosis is a topic of intense research. Early diagnosis would aid in improving treatment and intervention options, however, there are no current methods that can accurately predict AD years in advance. This study examines a novel machine learning approach that integrates the combined effects of vascular (white matter hyperintensities, WMHs), and structural brain changes (gray matter, GM) with clinical factors (cognitive status) to predict post-mortem neuropathological outcomes.MethodsHealthy older adults, participants with mild cognitive impairment, and AD from the Alzheimer’s Disease Neuroimaging Initiative dataset with both post-mortem neuropathology data and antemortem MRI and clinical data were included. Longitudinal data were analyzed across three intervals before death (post-mortem data): 0-4 years, 4-8 years, and 8-14 years. Additionally, cross-sectional data at the last visit or interval (within four years, 0-4 years) before death were also examined. Machine learning models including gradient boosting, bagging, support vector regression, and linear regression were implemented. These models were applied towards feature selection of the top seven MRI, clinical, and demographic data to identify the best performing set of variables that could predict postmortem neuropathology outcomes (i.e., neurofibrillary tangles, neuritic plaques, diffuse plaques, senile/amyloid plaques, and amyloid angiopathy).ResultsA total of 94 participants (55-90 years of age) were included in the study. At last visit, the best-performing model included total and temporal lobe WMHs and achievedr=0.87(RMSE=0.62) during cross-validation for neuritic plaques. For longitudinal assessments across different intervals, the best-performing model included regional GM (i.e., hippocampus, amygdala, caudate) and frontal lobe WMH and achievedr=0.93(RMSE=0.59) during cross-validation for neurofibrillary tangles. For MRI and clinical predictors and clinical-only predictors,t-tests demonstrated significant differences at all intervals before death (t[-13.60-7.90],p-values<0.001). Overall, post-mortem neuropathology outcome were predicted up to 14 years before death with high accuracies (∼90%).ConclusionsPrediction accuracy was higher for post-mortem neuropathology outcomes that included MRI (WMHs, GM) and clinical features compared to clinical-only features. These findings highlight that MRI features are critical to successfully predict AD-related pathology years in advance which will improve participant selection for clinical trials, treatments, and intervention options.
Sex-specific GABAergic microcircuits that switch vulnerability into resilience to stress and reverse the effects of chronic stress exposure
Authors: Jiang Tong , Feng Mengyang , Hutsell Alexander , Luscher Bernhard 
Published: July 2024

ABSTRACTClinical and preclinical studies have identified somatostatin (SST)-positive interneurons as key elements that regulate the vulnerability to stress-related psychiatric disorders. Conversely, disinhibition of SST neurons in mice results in resilience to the behavioral effects of chronic stress. Here we established a low-dose chronic chemogenetic protocol to map these changes in positively and negatively motivated behaviors to specific brain regions. AAV-hM3Dq mediated chronic activation of SST neurons in the prelimbic cortex (PLC) had antidepressant drug-like effects on anxiety- and anhedonia-like motivated behaviors in male but not female mice. Analogous manipulation of the ventral hippocampus (vHPC) had such effects in female but not male mice. Moreover, activation of SST neurons in the PLC of male and the vHPC of female mice resulted in stress resilience. Activation of SST neurons in the PLC reversed prior chronic stress-induced defects in motivated behavior in males but was ineffective in females. Conversely, activation of SST neurons in the vHPC reversed chronic stress-induced behavioral alterations in females but not males. Quantitation of c-Fos+and FosB+neurons in chronic stress-exposed mice revealed that chronic activation of SST neurons leads to a paradoxical increase in pyramidal cell activity. Collectively, these data demonstrate that GABAergic microcircuits driven by dendrite targeting interneurons enable sex- and brain-region-specific neural plasticity that promotes stress resilience and reverses stress-induced anxiety- and anhedonia-like motivated behavior. Our studies provide a mechanistic rationale for antidepressant efficacy of dendrite-targeting, low-potency GABAAreceptor agonists, independent of sex and despite striking sex differences in the relevant brain substrates.
Relaxed selection can speed the evolution of complex adaptations
Authors: Draghi Jeremy , Ogbunugafor C. Brandon , Zaman Luis , Parsons Todd L. 
Published: July 2024

AbstractNatural selection drives adaptive evolution and removes deleterious mutations; these effects are countervailing when a complex adaptation requires mutations that are initially deleterious when they arise, but beneficial in combination. While many models of this dynamic consider how genetic drift or other influences can aid valley crossing by weakening selection, we lack a general, analytical treatment of when relaxed selection might speed this type of adaptation. Here we use simulation and analysis to show that relaxed selection is generally favorable for valley-crossing when adaptive pathways require more than a single deleterious step. We also demonstrate that spatial heterogeneity in selection pressures could, by relaxing selection, allow populations to cross valleys much more rapidly than expected. These results relate to several applications of evolutionary theory to complex systems ranging from host-pathogen evolution to search algorithms in computer science.
Shaping the future of work: how labour market intermediaries (LMIs) use institutional work to transition to triadic, project-based employment relationships
Authors: Schneider Anna 
Published: July 2024

PurposeThis paper identifies how the operations of labour market intermediaries (LMIs) transform dyadic employment relationships into triadic ones. It reveals the change dynamics that LMIs engage in to bring about this transformation and that contribute to the projectification of work.Design/methodology/approachDrawing on an institutional-work lens and using interview data from both TempX, a German-based staffing service provider, and its client organizations, the analytical framework details the dynamics by which LMIs appropriate various HR tasks and different labour-market-organizing roles and thus create these triadic employment relationships.FindingsTempX assumes a powerful position between its client organizations and workers by increasingly taking over HR tasks from its client organizations, alternating between profiting from market transactions and engaging as a buyer and seller of labour. This powerful position, gradually created through four distinct, sequential, institutional work dynamics, allows it to transform dyadic employment relationships into triadic ones and to promote project-based work.Originality/valueBy showing how LMIs capitalize on the multiple services they offer, and how they use these services to establish a powerful position in both the labour market and in their relations with client organizations, this paper contributes to research on how LMIs change their institutional environment. Second, by showing that LMIs switch between different labour-market organizing roles and HR tasks, this paper reveals how essential this switching is for LMIs to establish triadic employment relationships and to drive the projectification of work, and thus it also contributes to research on LMIs’ role in the projectification of work.
Different factors affecting the real estate market in the Egyptian context
Authors: Mustafa Nada A. , Hassan Ghada Farouk , Elrefaie Mohab Abdel Moneim , Afifi Samy 
Published: July 2024

Purpose
Real estate projects are capital-intensive and deeply intertwined with economic factors, making them subject to various influences besides local housing needs. This paper aims to comprehensively understand the dynamics of the Egyptian real estate market, examining real estate cycles, driving factors and their correlation and scale of impact.

Design/methodology/approach
The study conducts a literature review to explore real estate cycles and their driving factors, along with the relationship between real estate and macroeconomic cycles. It then delves into the dynamics of the Egyptian real estate market, followed by a time series analysis that incorporates five key indicators: economic indicator, demand indicator, supply indicator, capital flow indicator and cost indicator over a 12-year interval (2012–2023), to examine short-term cycle factors, followed by correlation and multi-linear regression analysis to elucidate interrelations among these factors.

Findings
Through measuring and comparing the prementioned indicators with different economic and social events, the study paints a comprehensive picture of the macroeconomic environment and the real estate cycle in Egypt. Where demand has been found to be more sensitive and directly affected by macroeconomic factors than the supply. With the economic factor as the factor with the highest impact, especially in times of economic fluctuations, the impact has been immediate and short-term. These findings support the idea that the demand in Egypt is speculative, laying a threat of longer recession periods in the long term and having greater and more direct impact.

Originality/value
This paper contributes to the understanding of the Egyptian real estate market by integrating insights from real estate cycles, macroeconomics and specific market dynamics. The application of time series, correlation and multi-linear regression analysis provides a nuanced understanding of the interplay between several factors shaping the real estate cycle. Ultimately, the findings offer valuable insights for decision-makers involved in urban development planning, facilitating more informed and precise decision-making processes.
AI-enabled chatbots healthcare systems: an ethical perspective on trust and reliability
Authors: Basharat Iqra , Shahid Subhan 
Published: July 2024

PurposeThe primary objective of this study is to investigate the ethical implications of deploying AI-enabled chatbots in the healthcare sector. In addition, the research underscores trust and reliability as critical factors in addressing the ethical challenges associated with these chatbots.Design/methodology/approachThis study takes a qualitative approach, conducting 13 semi-structured interviews with a diverse range of participants, including patients, healthcare professionals, academic researchers, ethicists, and legal experts. This broad spectrum of perspectives ensures a comprehensive understanding of the ethical implications of AI-enabled chatbots in healthcare. The rich exploratory data gathered from these interviews is then analysed using thematic analysis.FindingsThe findings of this study are highly significant in the context of AI-enabled healthcare chatbots. They highlight four major themes: developing trust, ensuring reliability, ethical considerations, and potential ethical implications. The interconnectedness of these themes forms a coherent narrative, highlighting the pivotal role of trust and reliability in mitigating ethical issues.Originality/valueThis study contributes to the existing literature on AI-enabled healthcare chatbots. It not only reveals potential ethical concerns associated with these technologies, such as data security, patient privacy, bias, and accountability, but it also places a significant emphasis on trust and reliability as critical elements that can boost user confidence and engagement in using AI-enabled chatbots for healthcare advice.