bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neurovascular coupling impairment as a mechanism for cognitive deficits in COVID-19
Authors: Owens Cameron D , Bonin Pinto Camila , Detwiler Sam , Olay Lauren , Pinaffi-Langley Ana Clara da C , Mukli Peter , Peterfi Anna , Szarvas Zsofia , James Judith A , Galvan Veronica , Tarantini Stefano , Csiszar Anna , Ungvari Zoltan , Kirkpatrick Angelia C , Prodan Calin I , Yabluchanskiy Andriy 
Published: March 2024

Abstract
Components that comprise our brain parenchymal and cerebrovascular structures provide a homeostatic environment for proper neuronal function to ensure normal cognition. Cerebral insults (e.g. ischaemia, microbleeds and infection) alter cellular structures and physiologic processes within the neurovascular unit and contribute to cognitive dysfunction. COVID-19 has posed significant complications during acute and convalescent stages in multiple organ systems, including the brain. Cognitive impairment is a prevalent complication in COVID-19 patients, irrespective of severity of acute SARS-CoV-2 infection. Moreover, overwhelming evidence from in vitro, preclinical and clinical studies has reported SARS-CoV-2-induced pathologies in components of the neurovascular unit that are associated with cognitive impairment. Neurovascular unit disruption alters the neurovascular coupling response, a critical mechanism that regulates cerebromicrovascular blood flow to meet the energetic demands of locally active neurons. Normal cognitive processing is achieved through the neurovascular coupling response and involves the coordinated action of brain parenchymal cells (i.e. neurons and glia) and cerebrovascular cell types (i.e. endothelia, smooth muscle cells and pericytes). However, current work on COVID-19-induced cognitive impairment has yet to investigate disruption of neurovascular coupling as a causal factor. Hence, in this review, we aim to describe SARS-CoV-2's effects on the neurovascular unit and how they can impact neurovascular coupling and contribute to cognitive decline in acute and convalescent stages of the disease. Additionally, we explore potential therapeutic interventions to mitigate COVID-19-induced cognitive impairment. Given the great impact of cognitive impairment associated with COVID-19 on both individuals and public health, the necessity for a coordinated effort from fundamental scientific research to clinical application becomes imperative. This integrated endeavour is crucial for mitigating the cognitive deficits induced by COVID-19 and its subsequent burden in this especially vulnerable population.
Understanding the determinants of household cooking-fuel choice in sub-Saharan Africa: evidence from Nigeria
Authors: Aminu Raheem Olatunji , Dzudzor Maxwell Adizor , Oyawole Funminiyi Peter , Afolayan Samson Oluwaseyi 
Published: March 2024

AbstractOverreliance on traditional cooking fuels by agricultural households poses a significant obstacle to achieving the United Nations Sustainable Development Goal 7 by 2030 in Nigeria. Despite the emerging recognition of remittances as a crucial factor influencing cooking-fuel choices in the energy-transition literature, there is a paucity of studies examining this influence in Nigeria. Using data from 4400 agricultural households sourced from the fourth wave of the Nigerian Living Standard Measurement Survey data sets, this study examined the influence of remittances on cooking-fuel choices, among other factors in Nigeria. Employing descriptive statistics and the multinomial logit regression model, the analysis reveals that traditional cooking fuels, including wood, crop residue and animal dung, continue to dominate the cooking-fuel landscape. The empirical result of the multinomial logit model showed that households that receive remittances are more likely to use modern cooking fuels. Furthermore, wealthier, more educated households with access to electricity are more likely to use modern and transitional cooking fuels than traditional cooking fuels. Based on the findings, the study suggests the incentivization of remittances into the country through the reduction in associated transaction costs and accelerated public infrastructural investment in affordable electricity and good road networks to connect rural areas to gas-supply networks to drive the transition to modern cooking energy. Additionally, educational and awareness campaigns about the health risks associated with traditional cooking energy, particularly indoor air pollution, should be encouraged, especially in rural areas.
α2-Antiplasmin is associated with macrophage activation and fibrin deposition in a macrophage activation syndrome mouse model
Authors: Kanno Yosuke , Toyama Kinomi , Shibata Haruna , Matsuo Osamu , Ozaki Kei-ichi 
Published: March 2024

Abstract
Macrophage activation syndrome (MAS) is a life-threatening condition, characterized by cytopenia, multi-organ dysfunction, and coagulopathy associated with excessive activation of macrophages. In this study, we investigated the roles of alpha2-antiplasmin (α2AP) in the progression of MAS using fulminant MAS mouse model induced by toll-like receptor-9 agonist (CpG) and D-(+)-galactosamine hydrochloride (DG). α2AP deficiency attenuated macrophage accumulation, liver injury, and fibrin deposition in the MAS model mice. Interferon-γ (IFN-γ) is associated with macrophage activation, including migration, and plays a pivotal role in MAS progression. α2AP enhanced the IFN-γ-induced migration, and tissue factor production. Additionally, we showed that fibrin-induced macrophage activation and tumor necrosis factor-α production. Moreover, the blockade of α2AP by neutralizing antibodies attenuated macrophage accumulation, liver injury, and fibrin deposition in the MAS model mice. These data suggest that α2AP may regulate IFN-γ-induced responses and be associated with macrophage activation and fibrin deposition in the MAS progression.
Validation of the Klinrisk chronic kidney disease progression model in the FIDELITY population
Authors: Tangri Navdeep , Ferguson Thomas , Leon Silvia J , Anker Stefan D , Filippatos Gerasimos , Pitt Bertram , Rossing Peter , Ruilope Luis M , Farjat Alfredo E , Farag Youssef M K , Schloemer Patrick , Lawatscheck Robert , Rohwedder Katja , Bakris George L 
Published: March 2024

ABSTRACTBackgroundChronic kidney disease (CKD) affects &gt;800 million individuals worldwide and is often underrecognized. Early detection, identification and treatment can delay disease progression. Klinrisk is a proprietary CKD progression risk prediction model based on common laboratory data to predict CKD progression. We aimed to externally validate the Klinrisk model for prediction of CKD progression in FIDELITY (a prespecified pooled analysis of two finerenone phase III trials in patients with CKD and type 2 diabetes). In addition, we sought to identify evidence of an interaction between treatment and risk.MethodsThe validation cohort included all participants in FIDELITY up to 4 years. The primary and secondary composite outcomes included a ≥40% decrease in estimated glomerular filtration rate (eGFR) or kidney failure, and a ≥57% decrease in eGFR or kidney failure. Prediction discrimination was calculated using area under the receiver operating characteristic curve (AUC). Calibration plots were calculated by decile comparing observed with predicted risk.ResultsAt time horizons of 2 and 4 years, 993 and 1795 patients experienced a primary outcome event, respectively. The model predicted the primary outcome accurately with an AUC of 0.81 for 2 years and 0.86 for 4 years. Calibration was appropriate at both 2 and 4 years, with Brier scores of 0.067 and 0.115, respectively. No evidence of interaction between treatment and risk was identified for the primary composite outcome (P = .31).ConclusionsOur findings demonstrate the accuracy and utility of a laboratory-based prediction model for early identification of patients at the highest risk of CKD progression.
Enhancing systematic reviews in orthodontics: a comparative examination of GPT-3.5 and GPT-4 for generating PICO-based queries with tailored prompts and configurations
Authors: Demir Gizem Boztaş , Süküt Yağızalp , Duran Gökhan Serhat , Topsakal Kübra Gülnur , Görgülü Serkan 
Published: March 2024

Summary

Objectives
The rapid advancement of Large Language Models (LLMs) has prompted an exploration of their efficacy in generating PICO-based (Patient, Intervention, Comparison, Outcome) queries, especially in the field of orthodontics. This study aimed to assess the usability of Large Language Models (LLMs), in aiding systematic review processes, with a specific focus on comparing the performance of ChatGPT 3.5 and ChatGPT 4 using a specialized prompt tailored for orthodontics.

Materials/Methods
Five databases were perused to curate a sample of 77 systematic reviews and meta-analyses published between 2016 and 2021. Utilizing prompt engineering techniques, the LLMs were directed to formulate PICO questions, Boolean queries, and relevant keywords. The outputs were subsequently evaluated for accuracy and consistency by independent researchers using three-point and six-point Likert scales. Furthermore, the PICO records of 41 studies, which were compatible with the PROSPERO records, were compared with the responses provided by the models.

Results
ChatGPT 3.5 and 4 showcased a consistent ability to craft PICO-based queries. Statistically significant differences in accuracy were observed in specific categories, with GPT-4 often outperforming GPT-3.5.

Limitations
The study’s test set might not encapsulate the full range of LLM application scenarios. Emphasis on specific question types may also not reflect the complete capabilities of the models.

Conclusions/Implications
Both ChatGPT 3.5 and 4 can be pivotal tools for generating PICO-driven queries in orthodontics when optimally configured. However, the precision required in medical research necessitates a judicious and critical evaluation of LLM-generated outputs, advocating for a circumspect integration into scientific investigations.
Strategies to improve atrioventricular synchrony in patients with a Micra AV leadless pacemaker
Authors: Garweg Christophe , Breitenstein Alexander , Clémenty Nicolas , De Asmundis Carlo , Iacopino Saverio , Johansen Jens Brock , Sharman David , Theis Cathrin , Prat Xavier Viñolas , Winter Stefan , Reichlin Tobias 
Published: March 2024

Abstract
The second generation of transcatheter pacing systems, called Micra AV, can provide atrioventricular (AV) synchronous pacing via a new pacing algorithm relying on sensing mechanical atrial contraction. Several novel programming parameters were introduced to enable AV synchronous pacing, including an A3 window and A4 window as well as a conduction mode switch and an activity mode switch. In addition to several automated features, manual programming optimization of some of the novel parameters is key to improving AV synchrony. A solid knowledge of the features and their programming is essential for electrophysiologists implanting or following patients with Micra AV devices. Differences in programming optimization might partially explain the high variability of AV synchrony published in real-world data reports. This article reviews the key programming parameters of Micra AV. Subsequently, optimal programming recommendations for defined patient profiles are presented. Those were established by consensus within an expert panel comprised of 11 European electrophysiologists from high-volume Micra AV centres. The patient profiles were (1) high degree AV block and slow sinus rhythm; (2) high degree AV block and fast sinus rhythm; and (3) intermittent AV block. The panel recommended to evaluate the mechanical atrial activity on transthoracic echocardiography prior to implant. It was also agreed that Auto A3 Threshold and Tracking Check should be turned off in all patients, AV conduction mode switch should be turned off in all patients with high degree AV block, and the lower rate should be programmed to 50 bpm with exceptions based on individual clinical assessment. Future studies will be useful to evaluate the strength of those recommendations to improve the AV synchrony.
Genome-Wide Polygenic Score for Muscle Strength Predicts Risk for Common Diseases and Lifespan: A Prospective Cohort Study
Authors: Herranen Päivi , Koivunen Kaisa , Palviainen Teemu , Kujala Urho M , Ripatti Samuli , Kaprio Jaakko , Sillanpää Elina , FinnGen  
Published: March 2024

Abstract

Background
We used a polygenic score for hand grip strength (PGS HGS) to investigate whether genetic predisposition for higher muscle strength predicts age-related noncommunicable diseases, survival from acute adverse health events, and mortality.

Methods
This study consisted of 342 443 Finnish biobank participants from FinnGen Data Freeze 10 (53% women) aged 40–108 with combined genotype and health registry data. Associations between PGS HGS and a total of 27 clinical endpoints were explored with linear or Cox regression models.

Results
A higher PGS HGS was associated with a reduced risk of selected common noncommunicable diseases and mortality by 2%–10%. The risk for these medical conditions decreased by 5%–23% for participants in the highest PGS HGS quintile compared to those in the lowest PGS HGS quintile. A 1 standard deviation (SD) increase in the PGS HGS predicted a lower body mass index (β = −0.112 kg/m2, standard error [SE] = 0.017, p = 1.69E-11) in women but not in men (β = 0.004 kg/m2, p = .768). PGS HGS was not associated with better survival after acute adverse health events compared to the nondiseased period.

Conclusions
The genotype that supports higher muscle strength appears to protect against future health adversities, albeit with modest effect sizes. Further research is needed to investigate whether or how a favorable lifestyle modifies this intrinsic capacity to resist diseases, and if the impacts of lifestyle behavior on health differs due to genetic predisposition for muscle strength.
Surprising Gendered Age Differences in Rural Malawians’ Early COVID-19 Pandemic Prevention Efforts
Authors: Myroniuk Tyler W , Kohler Hans-Peter , Mwapasa Victor , Mwera James , Kohler Iliana V 
Published: March 2024

Abstract

Objectives
We assess how age, the presence of mature adults aged 45+ years, and recent deaths in rural households are associated with coronavirus disease 2019 (COVID-19) preventative actions and the likelihood of getting vaccinated against the virus in Malawi during early stages of the pandemic.

Methods
We draw upon data from 2,187 rural Malawians who participated in a 2020 COVID-19 Phone Survey. We estimate the log odds of engaging in “low-cost” and “high-cost” COVID-19 preventative actions based on age, gender, household composition, and recent household deaths. Low-cost prevention efforts were washing hands with soap and water frequently, avoiding close contact with people when going out, and avoiding shaking hands. High-cost actions included staying at home and decreasing time spent close to people not living in their household. We also estimate the chances of acquiring the COVID-19 vaccine in early stages of its availability.

Results
Mature women (45+ years) in general and younger men (&lt;45 years)—living with at least one mature adult in the household—were less likely than others to comply with low-cost actions. Mature men were more likely than younger men (&lt;45 years) to take on high-cost actions. To some extent, individuals who experienced a recent family death were more likely to engage in high-cost COVID-19 preventative actions as well as getting vaccinated.

Discussion
Gendered age differences in preventing the transmission of COVID-19 offer hints of larger social norms affecting protective efforts. The analyses also inform future COVID-19 public health outreach efforts in Malawi and other rural SSA contexts.
Representation and interpretation about underwater sound speed gradient field in the GNSS-A observation
Authors: Yokota Yusuke , Ishikawa Tadashi , Watanabe Shun-ichi , Nakamura Yuto , Nagae Koya 
Published: March 2024

SUMMARY
The Global Navigation Satellite System—Acoustic ranging combination technique (GNSS-A) is a seafloor geodetic observation technique that achieves an accuracy of centimetres by combining high-rate GNSS data with acoustic ranging. The technique determines the seafloor position by acoustic ranging between the sea surface and multiple seafloor stations, using GNSS data from the sea surface station. Here, the gradient state of the underwater sound speed structure (SSS) is a significant source of error. The open-source software GARPOS can reduce the effect from underwater gradient structures by retrieving the underwater disturbance as a parameter projected onto the sea surface and seafloor. To evaluate the effects of underwater disturbances, a quantitative comparison of the model parameters is necessary. In this study, we developed a representation method to evaluate features of the ocean field. Here, the expression method was described in the order of a formulation and an interpretation in the case of a 2-D cross-section and extension to the case of an actual 3-D field. This method makes it possible to evaluate SSS states in the GNSS-A observations. As an example, we showed the correlation between the anomaly of the expressed ocean state and the anomaly of the seafloor station position, showing that this expression method is an effective index for correcting bias errors. Additionally, we used the data from sites located in the Kuroshio area, a strong current near Japan, to show that the ocean state can be quantitatively interpreted using this expression method.
Indirect joint petrophysical inversion of shallow-seismic and multi-offset ground-penetrating radar field data
Authors: Qin Tan , Bohlen Thomas , Pan Yudi 
Published: March 2024

SUMMARY
In near-surface surveys, shallow-seismic and ground-penetrating radar (GPR) full-waveform inversions (FWIs) have received increasing attention because of their ability to reconstruct high-resolution subsurface models. However, they have different sensitivities to the same targets and thus may yield conflicting geophysical parameter models. To solve this issue, we have developed an indirect joint petrophysical inversion (JPI) integrating shallow-seismic and multi-offset GPR data. These data are used to reconstruct porosity and saturation whereby we use only strong sensitivities between petrophysical and geophysical parameters. To promote its field application, we proposed an input strategy to avoid measuring rock matrix parameters and make indirect JPI more robust. We apply indirect JPI to the field data acquired in Rheinstetten, Germany and find that it reveals the mechanical, electrical and petrophysical properties more reliably than individual inversions. The reconstructed models are assessed by direct-push technology, borehole sample measurements and migrated GPR image. Indirect JPI can fit seismic and GPR observed data simultaneously and provide consistent multiparameter models, which are hard to achieve by FWIs and individual petrophysical inversions. We also find that the method is robust when there are uncertainties in petrophysical a priori information. Overall, the field example proves the great potential of using indirect JPI to solve real-world problems.
On the elastodynamics of rotating planets
Authors: Maitra Matthew , Al-Attar David 
Published: March 2024

SUMMARY
Equations of motion are derived for (visco)elastic, self-gravitating and variably rotating planets. The equations are written using a decomposition of the elastic motion that separates the body’s elastic deformation from its net translational and rotational motion as far as possible. This separation is achieved by introducing degrees of freedom that represent the body’s rigid motions; it is made precise by imposing constraints that are physically motivated and that should be practically useful. In essence, a Tisserand frame is introduced exactly into the equations of solid mechanics. The necessary concepts are first introduced in the context of a solid body, motivated by symmetries and conservation laws, and the corresponding equations of motion are derived. Next, it is shown how those ideas and equations of motion can readily be extended to describe a layered fluid–solid body. A possibly new conservation law concerning inviscid fluids is then stated. The equilibria and linearization of the fluid–solid equations of motion are discussed thereafter, along with new equations for use within normal-mode coupling calculations and other Galerkin methods. Finally, the extension of these ideas to the description of multiple, interacting fluid–solid planets is qualitatively discussed.
Increasing accuracy of 3-D geomechanical-numerical models
Authors: Ziegler Moritz O , Heidbach Oliver 
Published: March 2024

SUMMARY
The current crustal stress field is of key importance to understand geodynamic processes and to assess stability aspects during subsurface usage. To provide a 3-D continuous description of the stress state, linear elastic forward geomechanical-numerical models are used. These models solve the equilibrium of forces between gravitational volume forces and surfaces forces imposed mainly by plate tectonics. The latter are responsible for the horizontal stress anisotropy and impose the inverse problem to estimate horizontal displacement boundary conditions that provide a fit best to horizontal stress magnitude data within the model volume. However, horizontal stress magnitude data have high uncertainties and they are sparse, clustered and not necessarily representative for a larger rock volume. Even when Bayesian statistics are incorporated and additional stress information such as borehole failure observations or formation integrity test are used to further constrain the solution space, this approach may result in a low accuracy of the model results, that is the result is not correct. Here, we present an alternative approach that removes the dependence of the solution space based on stress magnitude data to avoid potential low accuracy. Initially, a solution space that contains all stress states that are physically reasonable is defined. Stress magnitude data and the additional stress information are then used in a Bayesian framework to evaluate which solutions are more likely than others. We first show and validate our approach with a generic truth model and then apply it to a case study of the Molasse foreland basin of the Alps in Southern Germany. The results show that the model's ability to predict a reliable stress state is increasing while the number of likely solutions may also increase, and that outlier of stress magnitude data can be identified. This alternative approach results in a substantial increase in computational speed as we perform most of the calculations analytically.