bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical outcomes of clostridioides difficile infection in the very elderly
Authors: Kassem Sameer , Hijazi Nizar , Stein Nili , Zaina Adnan , Ganaim Mohammad 
Published: April 2024

Abstract
Background
Clostridioides difficile infection (CDI) causes considerable morbidity, mortality, and economic cost. Advanced age, prolonged stay in healthcare facility, and exposure to antibiotics are leading risk factors for CDI. Data on CDI clinical outcomes in the very elderly patients are limited.

Methods
A retrospective cohort study of patients hospitalized between 2016 and 2018 with CDI. We evaluated demographic clinical and laboratory parameters. Major clinical outcomes were evaluated including duration of hospital stay, admission to intensive care unit (ICU), in-hospital mortality, 30 days post-discharge mortality, and readmission/mortality composite outcome. We compared patients aged up to 80 years (elderly) to those of 80 years old or more (very elderly).

Results
Of 196 patients included in the study, 112 (57%) were very elderly with a mean age of 86 versus 67 years in the elderly group. The duration of hospital stays, and intensive care unit admission frequency were significantly reduced in the very elderly (13 vs. 22 days p = 0.003 and 1.8% vs. 10.7% p = 0.01, respectively). No significant difference was found in the frequencies of in-hospital and in 30 days post-discharge mortality.

Conclusions
In our cohort, the duration of hospital stay seemed to be shorter in the very elderly with no increase of in-hospital and post-discharge mortality. Although admitted less frequently to ICU, the in-hospital survival of the very elderly was not adversely affected compared to the elderly, suggesting that very advanced age per se should not be a major factor to consider in determining the prognosis of a patient with CDI.
Seasonal exploitation of intertidal resources at El Mazo (N Iberia) reveals optimized human subsistence strategies during the Mesolithic in Atlantic Europe
Authors: García-Escárzaga Asier , Gutiérrez-Zugasti Igor , Arniz-Mateos Rosa , Cuenca-Solana David , González-Morales Manuel R. , Ilgner Jana , Lucas Mary , Colonese André C. , Roberts Patrick 
Published: April 2024

AbstractOver the last few decades, research has significantly enhanced our understanding of the role played by shellfish in human subsistence during the Mesolithic period along the Atlantic coast of Europe. Instrumental to this advance has been the analysis of stable oxygen isotope measurements (δ18O) from mollusc shells, which offers valuable insights into the seasonality of shellfish exploitation. The δ18O values serve as reliable indicators of past seasonal seawater temperature variations experienced by the molluscs, enabling us to accurately determine the time of year when past humans collected them. Recent studies using this approach have successfully identified seasonal exploitation patterns of the topshell Phorcus lineatus (da Costa, 1778) in Atlantic Europe. However, uncertainties remain regarding the exploitation schedule of Patella depressa Pennant 1777, one of the most abundantly collected species in Mesolithic sites. Here we used shell δ18O values of P. depressa from the Mesolithic sites of El Mazo (Northern Iberia) to determine its seasonality of exploitation. Our study reveals that P. depressa was prevalently exploited during colder months. Modern specimens of the same limpet species were also collected during two annual cycles to assess potential seasonal changes in meat yield return. Results obtained has profound implications for better understanding how last coastal foragers managed available littoral resources throughout the year.
Distributed versus centralized computing of coverage in mobile crowdsensing
Authors: Girolami Michele , Kocian Alexander , Chessa Stefano 
Published: April 2024

AbstractThe expected spatial coverage of a crowdsensing platform is an important parameter that derives from the mobility data of the crowdsensing platform users. We tackle the challenge of estimating the anticipated coverage while adhering to privacy constraints, where the platform is restricted from accessing detailed mobility data of individual users. Specifically, we model the coverage as the probability that a user detours to a point of interest if the user is present in a certain region around that point. Following this approach, we propose and evaluate a centralized as well as a distributed implementation model. We examine real-world mobility data employed for assessing the coverage performance of the two models, and we show that the two implementation models provide different privacy requirements but are equivalent in terms of their outputs.
Reliability-based sizing of islanded multi-energy microgrid: a conic chance-constrained optimization approach
Authors: Camargo-Berrueco Juan Camilo , Mejía-Giraldo Diego Adolfo , Lemos-Cano Santiago 
Published: April 2024

AbstractThis paper presents a methodology to optimally design a multi-energy microgrid with thermal and electric loads considering $$N-1$$

N
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1

and probabilistic regulation reserves. This methodology consists of a chance-constrained optimization that determines the optimal sizing of the microgrid. Microgrid operations are rigorously considered by modelling hourly thermal and electric demand patterns as well as technology production schedules over a year. Such schedules include both electric and thermal power balances, ramp constraints, $$N-1$$

N
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1

and regulation reserves, among others. To ensure a reliable microgrid design and operation, reserve constraints have been proposed to deal with both $$N-1$$

N
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generation contingencies, and forecast errors. $$N-1$$

N
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1

reserves guarantee that a sudden outage of any of the electric generators is strategically covered by the remaining generators in order to avoid load shedding. Additionally, nonzero-mean random forecast errors of electric load and solar production are addressed by a set of chance constraints able to schedule asymmetric up and down regulation reserves. Their levels are high enough to cover hourly random forecast errors (or intermittencies) with a high threshold probability. The proposed methodology results in a mixed integer second-order cone program. Results of microgrid designs with and without reliability reserves are carefully analysed and compared. Neglecting reliability constraints leads to a lower-cost design at the expense of exposing the microgrid to unsafe operation. Finally, sensitivity analysis to study the optimal portfolio sizing with respect to electric BESS investment cost, solar production forecast mean error, and random intermittency threshold probability are performed.
Immune-related LncRNAs scores predicts chemotherapeutic responses and prognosis in cervical cancer patients
Authors: Tian Weijie , Tan Songsong , Wang Jun , Shen Ping , Qin Qingfen , Zi Dan 
Published: April 2024

Abstract
Background
Long non-coding RNAs (LncRNAs) regulating the immune microenvironment of cancer is a hot spot. But little is known about the influence of the immune-related lncRNA (IRlncRs) on the chemotherapeutic responses and prognosis of cervical cancer (CC) patients. The purpose of the study was to identify an immune-related lncRNAs (IRlncRs)-based model for the prospective prediction of clinical outcomes in CC patients.

Methods
CC patients’ relevant data was acquired from The Cancer Genome Atlas (TCGA). Correlation analysis and Cox regression analyses were applied. A risk score formula was formulated. Prognostic factors were combined into a nomogram, while sensitivity for chemotherapy drugs was analyzed using the OncoPredict algorithm.

Results
Eight optimal IRlncRs(ATP2A1-AS1, LINC01943, AL158166.1, LINC00963, AC009065.8, LIPE-AS1, AC105277.1, AC098613.1.) were incorporated in the IRlncRs model. The overall survival (OS) of the high-risk group of the model was inferior to those in the low-risk group. Further analysis demonstrated this eight-IRlncRs model as a useful prognostic marker. The Nomogram had a concordance index of survival prediction of 0.763(95% CI 0.746–0.780) and more robust predictive accuracy. Furthermore, patients in the low-risk group were found to be more sensitive to chemotherapy, including Paclitaxel, Rapamycin, Epirubicin, Vincristine, Docetaxel and Vinorelbine.

Conclusions
An eight-IRlncRs-based prediction model was identified that has the potential to be an important tool to predict chemotherapeutic responses and prognosis for CC patients.
Bio-Chemical Sensors Based on Excessively Tilted Fiber Grating
Authors: Chen Fudan , Gu Hong , Luo Binbin , Shi Shenghui 
Published: April 2024

AbstractExcessively tilted fiber gratings (ExTFGs) are a type of special optical fiber grating device different from traditional fiber Bragg gratings, long period fiber gratings, and tilted fiber Bragg gratings. Due to the excessively tilted fiber fringe structure in the fiber core, ExTFGs could couple the light of the core mode into the high-order forward-propagating cladding modes, which would split into two sets of polarization dependent modes resulting in dual-peak resonances in the transmission spectrum. ExTFGs have the properties of the high refractive index sensitivity and low thermal crosstalk, which makes them very suitable for biochemical sensing applications. This paper will review the development of ExTFGs in terms of the mode coupling behavior, spectra characteristic, especially the refractive index sensitivity enhancement, biochemical modification methods of the sensor, and their applications in the bio-chemical sensing area, including pondus hydrogenii (pH) heavy metal ions, humidity, glucose, and immune sensing for various animal virus and biomarkers. Moreover, several composite sensing structures based on ExTFGs will be summarized.
Data driven machine learning prognostics of buckling failure modes in ballasted railway track
Authors: Wongkaew Watcharapong , Muanyoksakul Wachira , Ngamkhanong Chayut , Sresakoolchai Jessada , Kaewunruen Sakdirat 
Published: April 2024

AbstractThis study explores the development and application of a machine learning (ML) approach to predict buckling failure modes in ballasted railway tracks. With the growing demand for safer and more reliable railway systems, the ability to foresee and mitigate track failures is of paramount importance. Our study focuses on harnessing advanced ML algorithms to analyse and interpret complex data sets, aiming to identify potential buckling failures before they occur. The methodology employed involves collecting extensive data from previous advanced numerical studies. Faced with the inadequacy of field data collection on track buckling and the limited availability of data related to track conditions, our study has relied on simulation data for insight and analysis. This data is then processed and analysed using sophisticated ML models, trained to recognise patterns and anomalies indicative of potential buckling failures. A novel aspect of our approach is the integration of environmental factors, acknowledging their significant influence on the likelihood of both snap-through and progressive buckling in railway tracks. We compare the effectiveness of various ML algorithms in accurately predicting these failure modes, evaluating their performance in simulated and real-world scenarios. The findings demonstrate the models' proficiency in identifying early signs of both snap-through and progressive buckling, leading to timely interventions. This capability not only improves railway safety but also aids in efficient maintenance scheduling and asset management. Additionally, a case study in Thailand's railway system demonstrates the model's effectiveness in predicting buckling failures under tropical environmental conditions. This paper contributes a novel perspective to the field of railway infrastructure maintenance. By providing a reliable method for predicting specific buckling failure modes, it paves the way for enhanced operational safety and efficiency in railway networks, particularly in the face of dynamic environmental conditions.
Rational option of optimum parameters of robust design of hybrid of PMOO with sequential uniform algorithm
Authors: Zheng Maosheng , Yu Jie 
Published: April 2024

AbstractIn this paper, reasonable regulation of optimum parameters in sequential uniform design (algorithm) is developed by means of probabilistic multi–objective optimization (PMOO) in term of total preferable probability, which aims to conduct rational option in the subsequent deep optimization with a series of provisional ″optimum status″ candidates. The provisional ″optimum statuses″ were produced in the sequential uniform algorithm of subsequent deep optimization in each step, which is in turn used to form a ″special point set″ in this study, the total preferable probability is evaluated for the ″special point set″. The final optimum status is with the highest total preferable probability of the ″special point set″ comparatively. Besides, under condition of ″target value being the best″, both discrepancy of average value $$\overline{Y}$$

Y
¯

of a response from its target value Y0 (ε =|$$\overline{Y}$$

Y
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−Y0|) and averaged deviation γ of the actual response value Y from the target value Y0 are taken as the dual individual response objectives for robust design simultaneously. Two examples are given to illuminate the proposed procedure.
What is new in acute myeloid leukemia classification?
Authors: Park Hee Sue 
Published: April 2024

AbstractRecently, the International Consensus Classification (ICC) and the 5th edition of the World Health Organization classification (WHO2022) introduced diagnostically similar yet distinct approaches, which has resulted in practical confusion. This review compares these classification systems for acute myeloid leukemia (AML), building up on the revised 4th edition of WHO (WHO2016). Both classifications retain recurrent genetic abnormalities as a primary consideration. However, they differ in terms of blast threshold. The ICC mandates a minimum of 10% blasts in the bone marrow or peripheral blood, whereas the WHO2022 does not specify a blast cut-off. AML with BCR::ABL1 requires > 20% blast count in both classifications. In WHO2022, AML with CEBPA mutation requires > 20% blasts. TP53 mutation, a new entity is exclusive to ICC, diagnosed with > 20% blasts and variant allele frequency > 10%. AML with myelodysplasia-related changes is defined by cytogenetic or gene mutation-based criteria, not morphological dysplasia. Eight genes were common to both groups: ASXL1, BCOR, EZH2, SF3B1, SRSF2, STAG2, U2AF1, and ZRSR2. An additional gene, RUNX1, was included in the ICC classification. AML cases defined by differentiation (WHO2022) and AML not otherwise specified (ICC) are categorized as lacking specific defining genetic abnormalities, WHO2022 labels this as a myeloid neoplasm post cytotoxic therapy (MN-pCT), described as an appendix after specific diagnosis. Similarly, in ICC, it can be described as “therapy-related”, without a separate AML category.
Cohort study of patients with advanced cancer: outcomes associated with duration of antibiotic therapy for non-ventilator hospital-acquired pneumonia
Authors: Lee Seohyuk , Benson Jemma , Cohen Avi , Quagliarello Vincent , Juthani-Mehta Manisha , Datta Rupak 
Published: April 2024

Abstract
In this single-center observational study of 118 older adults with advanced cancer who developed non-ventilator hospital-acquired pneumonia, prolonged antibiotic durations (8–14 and ≥15 vs ≤7 d) were not associated with reduced adjusted odds of 90-day all-cause readmission or death. These data may inform antimicrobial stewardship efforts in palliative care settings.
Antimicrobial stewardship knowledge, attitudes, and practices (KAP) among nurses
Authors: Perez Reinaldo , Hayes Jillian E. , Winters Ali R. , Wrenn Rebekah H. , Moehring Rebekah W. 
Published: April 2024

Abstract
We performed a knowledge, attitudes, and practice (KAP) survey of bedside nurses to evaluate perceptions of antimicrobial use and aid in the design of nursing-based antimicrobial stewardship interventions. The survey highlighted discrepancies in knowledge and practice as well as opportunities to improve communication with nursing colleagues.
Thermal Response of Large Seasonally Ice‐Covered Lakes Over Tibetan Plateau to Climate Change
Authors: Wu Yang , Huang Anning , Li Xin , Wen Lijuan ,   Lazhu, Li Jingyi 
Published: April 2024

AbstractIn this study, a process‐based lake model is used to investigate the influence of climate change on the thermodynamics of 30 large lakes over Tibetan Plateau (TP). The lake model was driven by the atmospheric forcing derived from the bias‐corrected projections of three global climate models in the twenty‐first century under three Shared Socioeconomic Pathways (SSPs). The hindcasts during 2000–2014 can reasonably capture the seasonality and magnitude of satellite retrieved lake surface temperature (LST). Future projections during 2015–2100 suggest a widespread increased LST, declined ice cover, and prolonged stratification, with the severity of changes in line with the climate driver shifts under different SSPs. Under the scenario with the highest level of anthropogenic radiative forcing (SSP5‐8.5), the end‐of‐century (2086–2100) changes of LST, ice thickness, and stratification duration averaged across all studied lakes reach 4.90°C, −0.43 m, and 65.46 days, respectively. Note that the positive ice‐albedo feedback can cause excess lake warming by accelerating ice break‐up (30.07 days earlier) and stratification onset (46.83 days earlier). By the end of this century, more frequent, multi‐seasonal thermal extremes are anticipated to push nearly half of the studied lakes into a permanent heatwave state. Together with the remarkable LST increase and winter ice loss, the lakes will mix less frequently and may shift from a dimictic to warm monomict mixing regime. Hopefully, the irreversible thermal changes can be avoided if the anthropogenic radiative forcing is controlled within the envelope outlined by the stringent climate mitigation scenario SSP1‐2.6.
Deglacial Pulse of Neutralized Carbon From the Pacific Seafloor: A Natural Analog for Ocean Alkalinity Enhancement?
Authors: Green R. A. , Hain M. P. , Rafter P. A. 
Published: April 2024

AbstractThe ocean carbon reservoir controls atmospheric carbon dioxide (CO2) on millennial timescales. Radiocarbon (14C) anomalies in eastern North Pacific sediments suggest a significant release of geologic 14C‐free carbon at the end of the last ice age but without evidence of ocean acidification. Using inverse carbon cycle modeling optimized with reconstructed atmospheric CO2 and 14C/C, we develop first‐order constraints on geologic carbon and alkalinity release over the last 17.5 thousand years. We construct scenarios allowing the release of 850–2,400 Pg C, with a maximum release rate of 1.3 Pg C yr−1, all of which require an approximate equimolar alkalinity release. These neutralized carbon addition scenarios have minimal impacts on the simulated marine carbon cycle and atmospheric CO2, thereby demonstrating safe and effective ocean carbon storage. This deglacial phenomenon could serve as a natural analog to the successful implementation of gigaton‐scale ocean alkalinity enhancement, a promising marine carbon dioxide removal method.
IRE1 signaling increases PERK expression during chronic ER stress
Authors: Ong Gideon , Ragetli Rosemund , Mnich Katarzyna , Doble Bradley W. , Kammouni Wafa , Logue Susan E. 
Published: April 2024

AbstractThe Unfolded Protein Response (UPR) is an essential cellular process activated by the accumulation of unfolded proteins within the Endoplasmic Reticulum (ER), a condition referred to as ER stress. Three ER anchored receptors, IRE1, PERK and ATF6 act as ER stress sensors monitoring the health of the ER. Upon detection of ER stress, IRE1, PERK and ATF6 initiate downstream signaling pathways collectively referred to as the UPR. The overarching aim of the UPR is to restore ER homeostasis by reducing ER stress, however if that is not possible, the UPR transitions from a pro-survival to a pro-death response. While our understanding of the key signaling pathways central to the UPR is well defined, the same is not true of the subtle signaling events that help fine tune the UPR, supporting its ability to adapt to varying amplitudes or durations of ER stress. In this study, we demonstrate cross talk between the IRE1 and PERK branches of the UPR, wherein IRE1 via XBP1s signaling helps to sustain PERK expression during prolonged ER stress. Our findings suggest cross talk between UPR branches aids adaptiveness thereby helping to support the plasticity of UPR signaling responses.
RNA targeting and cleavage by the type III-Dv CRISPR effector complex
Authors: Schwartz Evan A. , Bravo Jack P. K. , Ahsan Mohd , Macias Luis A. , McCafferty Caitlyn L. , Dangerfield Tyler L. , Walker Jada N. , Brodbelt Jennifer S. , Palermo Giulia , Fineran Peter C. , Fagerlund Robert D. , Taylor David W. 
Published: April 2024

AbstractCRISPR-Cas are adaptive immune systems in bacteria and archaea that utilize CRISPR RNA-guided surveillance complexes to target complementary RNA or DNA for destruction1–5. Target RNA cleavage at regular intervals is characteristic of type III effector complexes6–8. Here, we determine the structures of the Synechocystis type III-Dv complex, an apparent evolutionary intermediate from multi-protein to single-protein type III effectors9,10, in pre- and post-cleavage states. The structures show how multi-subunit fusion proteins in the effector are tethered together in an unusual arrangement to assemble into an active and programmable RNA endonuclease and how the effector utilizes a distinct mechanism for target RNA seeding from other type III effectors. Using structural, biochemical, and quantum/classical molecular dynamics simulation, we study the structure and dynamics of the three catalytic sites, where a 2′-OH of the ribose on the target RNA acts as a nucleophile for in line self-cleavage of the upstream scissile phosphate. Strikingly, the arrangement at the catalytic residues of most type III complexes resembles the active site of ribozymes, including the hammerhead, pistol, and Varkud satellite ribozymes. Our work provides detailed molecular insight into the mechanisms of RNA targeting and cleavage by an important intermediate in the evolution of type III effector complexes.
Tracing genetic diversity captures the molecular basis of misfolding disease
Authors: Zhao Pei , Wang Chao , Sun Shuhong , Wang Xi , Balch William E. 
Published: April 2024

AbstractGenetic variation in human populations can result in the misfolding and aggregation of proteins, giving rise to systemic and neurodegenerative diseases that require management by proteostasis. Here, we define the role of GRP94, the endoplasmic reticulum Hsp90 chaperone paralog, in managing alpha-1-antitrypsin deficiency on a residue-by-residue basis using Gaussian process regression-based machine learning to profile the spatial covariance relationships that dictate protein folding arising from sequence variants in the population. Covariance analysis suggests a role for the ATPase activity of GRP94 in controlling the N- to C-terminal cooperative folding of alpha-1-antitrypsin responsible for the correction of liver aggregation and lung-disease phenotypes of alpha-1-antitrypsin deficiency. Gaussian process-based spatial covariance profiling provides a standard model built on covariant principles to evaluate the role of proteostasis components in guiding information flow from genome to proteome in response to genetic variation, potentially allowing us to intervene in the onset and progression of complex multi-system human diseases.