bluuebunny/crossref_metadata_2025_split huggingface dataset:
X-ray chemical imaging for assessing redox microsites within soils and sediments
Authors: Noël Vincent , Boye Kristin , Naughton Hannah R. , Lacroix Emily M. , Aeppli Meret , Kumar Naresh , Fendorf Scott , Webb Samuel M. 
Published: February 2024

Redox reactions underlie several biogeochemical processes and are typically spatiotemporally heterogeneous in soils and sediments. However, redox heterogeneity has yet to be incorporated into mainstream conceptualizations and modeling of soil biogeochemistry. Anoxic microsites, a defining feature of soil redox heterogeneity, are non-majority oxygen depleted zones in otherwise oxic environments. Neglecting to account for anoxic microsites can generate major uncertainties in quantitative assessments of greenhouse gas emissions, C sequestration, as well as nutrient and contaminant cycling at the ecosystem to global scales. However, only a few studies have observed/characterized anoxic microsites in undisturbed soils, primarily, because soil is opaque and microsites require µm-cm scale resolution over cm-m scales. Consequently, our current understanding of microsite characteristics does not support model parameterization. To resolve this knowledge gap, we demonstrate through this proof-of-concept study that X-ray fluorescence (XRF) 2D mapping can reliably detect, quantify, and provide basic redox characterization of anoxic microsites using solid phase “forensic” evidence. First, we tested and developed a systematic data processing approach to eliminate false positive redox microsites, i.e., artefacts, detected from synchrotron-based multiple-energy XRF 2D mapping of Fe (as a proxy of redox-sensitive elements) in Fe-“rich” sediment cores with artificially injected microsites. Then, spatial distribution of FeII and FeIII species from full, natural soil core slices (over cm-m lengths/widths) were mapped at 1–100 µm resolution. These investigations revealed direct evidence of anoxic microsites in predominantly oxic soils such as from an oak savanna and toeslope soil of a mountainous watershed, where anaerobicity would typically not be expected. We also revealed preferential spatial distribution of redox microsites inside aggregates from oak savanna soils. We anticipate that this approach will advance our understanding of soil biogeochemistry and help resolve “anomalous” occurrences of reduced products in nominally oxic soils.
Ratio of hemoglobin to red cell distribution width: an inflammatory predictor of survival in AIDS-related DLBCL
Authors: Chen Juanjuan , Wu Yihua , Zhao Han , Ruan Guangjing , Qin Shanfang 
Published: February 2024

BackgroundDespite the introduction of combined antiretroviral therapy, AIDS-related diffuse large B-cell lymphoma (AR-DLBCL) remains a prominent cancer among individuals living with HIV with a suboptimal prognosis. Identifying independent prognostic markers could improve risk stratification.MethodsIn this multicenter retrospective cohort study spanning years 2011 to 2019, 153 eligible patients with AR-DLBCL were examined. Overall survival (OS) factors were analyzed using Kaplan–Meier curves, and univariate and multivariate Cox proportional hazards models. The discriminatory ability of the risk score was evaluated by examining the area under the receiver operating characteristic curve.ResultsThe study included 153 patients with a median age of 47 years (interquartile range [IQR] 39–58), 83.7% of whom were men. The median follow-up was 12.0 months (95% confidence interval [CI], 8.5–15.5), with an OS rate of 35.9%. Among the potential inflammatory markers examined, only the ratio of hemoglobin (g/dL) to red cell distribution width (%) (Hb/RDW) emerged as an independent prognostic parameter for OS in the training (hazard ratios [HR] = 2.645, 95% CI = 1.267–5.522, P = 0.010) and validation cohorts (HR = 2.645, 95% CI = 1.267–5.522, P = 0.010). A lower Hb/RDW ratio was strongly correlated with adverse clinical factors, including advanced Ann Arbor stage, increased extranodal sites, reduced CD4 count, elevated lactate dehydrogenase levels, poorer Eastern Cooperative Oncology Group performance status (ECOG PS), and a higher International Prognostic Index (IPI) score. The addition of the Hb/RDW ratio to the IPI produced a highly discriminatory prognostic composite score, termed Hb/RDW-IPI.ConclusionWe identified a cost-effective and readily available inflammatory biomarker, the Hb/RDW ratio, as an independent predictor of outcomes in patients with AR-DLBCL. Its integration into the IPI score partially improves prognostic accuracy.
Genomic insights and antimicrobial resistance profiles of CRKP and non-CRKP isolates in a Beijing geriatric medical center: emphasizing the blaKPC-2 carrying high-risk clones and their spread
Authors: Ge Xin , Zhou Yu , Jin Hang , Liu Kangkang , Zhu Kunpeng , Yu Yulong , Xue Jingzhuang , Wang Qi , Du Xinying , Wang Hui , Xiang Ying , Li Wenjun , Tian Sai , Yan Zhongqiang , Qiu Shaofu 
Published: February 2024

BackgroundThe escalating resistance of Klebsiella pneumoniae, a prevalent pathogen in healthcare settings, especially its carbapenem-resistant K. pneumoniae (CRKP), to a wide array of antibiotics, notably β-lactams, constitutes a formidable challenge for healthcare and global public health management.MethodsThis research compared the resistance phenotypes and genomic profiles of CRKP and Non-CRKP isolates in a Beijing hospital, focusing on high-risk blaKPC-2 gene-bearing CRKP clones and the structure of mobile genetic elements facilitating their spread across hospital departments. Forty K. pneumoniae isolates were collected from various departments of the hospital and subjected to antimicrobial susceptibility testing and whole-genome sequencing to analyze their resistance phenotypes and genomic features.ResultsThe study revealed that among the 31 CRKP isolates, ST11 is the most common sequence type, with K47 and OL101 being the dominant capsule types, primarily observed in the respiratory department. In terms of antimicrobial susceptibility: 87.5% of the isolates exhibited multidrug resistance (MDR), with a high resistance rate of 30% against tigecycline. All CRKP isolates demonstrated resistance to multiple drug classes (≥5 CLSI classes). Non-CRKP isolates also showed high resistance rates to minocycline and doxycycline (77.8%). the ST11-KL47-OL101 type emerged as the predominant clone among the CRKP isolates carrying the blaKPC-2 gene. This dominance appears to be mediated by the pKpnR03_2 plasmid, which harbors not only blaKPC-2 and rmtb but also gene clusters pertinent to iron transport and arsenic resistance. These isolates, clustering in the C3 clade of the phylogenetic tree, exhibited minor genetic variations and close evolutionary relationships, suggesting a plasmid-driven spread across various hospital departments.ConclusionIn summary, our study highlights the extensive spread of antibiotic-resistant K. pneumoniae across various departments in our hospital, with a particular emphasis on the dominant clonal proliferation of the ST11-KL47-OL101 CRKP strain. This finding underscores the significant role of plasmid-mediated gene transfer in the evolution and dissemination of resistant strains within hospital environments. The study emphasizes the necessity for ongoing surveillance of antibiotic resistance and genomic analysis in hospital settings to effectively monitor and manage these challenges.
Identifying clinical phenotypes of frontotemporal dementia in post-9/11 era veterans using natural language processing
Authors: Panahi Samin , Mayo Jamie , Kennedy Eamonn , Christensen Lee , Kamineni Sreekanth , Sagiraju Hari Krishna Raju , Cooper Tyler , Tate David F. , Rupper Randall , Pugh Mary Jo 
Published: February 2024

IntroductionFrontotemporal dementia (FTD) encompasses a clinically and pathologically diverse group of neurodegenerative disorders, yet little work has quantified the unique phenotypic clinical presentations of FTD among post-9/11 era veterans. To identify phenotypes of FTD using natural language processing (NLP) aided medical chart reviews of post-9/11 era U.S. military Veterans diagnosed with FTD in Veterans Health Administration care.MethodsA medical record chart review of clinician/provider notes was conducted using a Natural Language Processing (NLP) tool, which extracted features related to cognitive dysfunction. NLP features were further organized into seven Research Domain Criteria Initiative (RDoC) domains, which were clustered to identify distinct phenotypes.ResultsVeterans with FTD were more likely to have notes that reflected the RDoC domains, with cognitive and positive valence domains showing the greatest difference across groups. Clustering of domains identified three symptom phenotypes agnostic to time of an individual having FTD, categorized as Low (16.4%), Moderate (69.2%), and High (14.5%) distress. Comparison across distress groups showed significant differences in physical and psychological characteristics, particularly prior history of head injury, insomnia, cardiac issues, anxiety, and alcohol misuse. The clustering result within the FTD group demonstrated a phenotype variant that exhibited a combination of language and behavioral symptoms. This phenotype presented with manifestations indicative of both language-related impairments and behavioral changes, showcasing the coexistence of features from both domains within the same individual.DiscussionThis study suggests FTD also presents across a continuum of severity and symptom distress, both within and across variants. The intensity of distress evident in clinical notes tends to cluster with more co-occurring conditions. This examination of phenotypic heterogeneity in clinical notes indicates that sensitivity to FTD diagnosis may be correlated to overall symptom distress, and future work incorporating NLP and phenotyping may help promote strategies for early detection of FTD.
Emerging biomarkers for improving pregnancy planning in multiple sclerosis
Authors: Cuello Juan Pablo , Meldaña Rivera Ariana , Monreal Enric , Gómez Lozano Ana , García Cano Ana Maria , García Domínguez Jose Manuel , Fernández Velasco José Ignacio , Costa-Frossard França Lucienne , Goicochea Haydee , Higueras Yolanda , De León-Luis Juan Antonio , Sainz De La Maza Susana , Villarrubia Noelia , Arribas Gómez Ignacio , Ruiz Perez Irene , Martinez Ginés Maria Luisa , Villar Luisa María 
Published: February 2024

BackgroundPatient disability, relapse rate, and age are used for family planning in multiple sclerosis (MS). However, the need for more accurate biomarkers is widely recognized. We aimed to explore the influence of age on neurofilament light chain (sNfL), which reflects acute inflammation; glial fibrillary acidic protein (GFAP), associated with disability progression independent of relapses; and anti-Müllerian hormone (AMH), reflecting ovarian reserve, to provide a tailored family planning strategy.MethodsThis case-control study included 95 MS patients and 61 healthy control women (HCW). sNfL and GFAP levels were measured using a sensitive single-molecule array assay. AMH levels were measured by the automated Elecsys® Anti-Müllerian Hormone Assay.ResultsWe observed no significant differences in AMH values between MS patients and the control group within any of the age-matched categories. Age exhibited a negative correlation with AMH values in both groups, as expected. Nevertheless, our findings suggest a slight tendency toward reduced ovarian reserve in MS patients (rho MS patients = −0.67, p &lt; 0.0001; rho HCW = −0.43, p = 0.0006). Interestingly, among the 76 MS participants under 40 years old, we identified ten individuals (13.1%) with AMH levels below 0.7 ng/ml, indicative of a low ovarian reserve, and an additional six individuals (7.8%) with AMH levels between 0.7 ng/ml and 0.9 ng/ml, suggesting a potential risk of premature ovarian failure. Conversely, sNfL and GFAP levels in the MS group exhibited high variability but showed no significant association with age intervals.ConclusionWe found no significant differences in AMH, sNfL or GFAP values between MS patients and the control group within any of the age-matched categories. The assessment of AMH, sNFL and GFAP levels at MS onset facilitates personalized therapeutic and family planning strategies for childbearing-age women.
Liquid chromatography coupled to mass spectrometry metabolomic analysis of cerebrospinal fluid revealed the metabolic characteristics of moyamoya disease
Authors: Yu Jin , Chen Tongyu , Li Xiang , Chen Jincao , Wei Wei , Zhang Jianjian 
Published: February 2024

ObjectiveMetabolomics has found extensive applications in the field of neurological diseases, significantly contributing to their diagnosis and treatment. However, there has been limited research applying metabolomics to moyamoya disease (MMD). This study aims to investigate and identify differential metabolites associated with MMD.MethodsWe employed a liquid chromatography coupled with mass spectrometry (LC-MS) approach, complemented by univariate and multivariate analyses, to discern metabolic biomarkers in cerebrospinal fluid samples. We then compared these biomarkers between MMD patients and healthy controls (Ctl).ResultsSixteen patients diagnosed with MMD via cerebral angiography and eight healthy controls were enrolled in this study. Comparative analyses, including univariate and multivariate analyses, correlation studies, heatmaps, Volcano Plots, and KEGG pathway enrichment, were performed between MMD patients and controls. As a result, we identified 129 significant differential metabolites in the cerebrospinal fluid between MMD patients and controls. These metabolic biomarkers are associated with various pathways, with notable involvement in purine and pyrimidine metabolism.ConclusionUtilizing an LC-MS-based metabolomics approach holds promise for enhancing the clinical diagnosis of MMD. The identified biomarkers offer potential avenues for the development of novel diagnostic methods for MMD and offer fresh insights into the pathogenesis of the disease.
Factors associated with older adults’ cognitive decline 6 months after gamma-variant SARS-CoV-2 infection
Authors: Peixoto Vanessa Giffoni M. N. P. , Facci Lucas Alves , Barbalho Thiago C. S. , Souza Raíssa Nascimento , Duarte Alice Mendes , dos Santos Marina Bruxel , Almondes Katie Moraes 
Published: February 2024

BackgroundCognitive deficits are commonly reported after COVID-19 recovery, but little is known in the older population. This study aims to investigate possible cognitive damage in older adults 6 months after contracting COVID-19, as well as individual risk factors.MethodsThis cross-sectional study involved 70 participants aged 60–78 with COVID-19 6 months prior and 153 healthy controls. Montreal Cognitive Assessment—Basic (MoCA-B) screened for cognitive impairment; Geriatric Depression Scale and Geriatric Anxiety Inventory screened for depression and anxiety. Data were collected on demographics and self-reports of comorbid conditions.ResultsThe mean age of participants was 66.97 ± 4.64 years. A higher proportion of individuals in the COVID group complained about cognitive deficits (χ2 = 3.574; p = 0.029) and presented with deficient MoCA-B scores (χ2 = 6.098, p = 0.014) compared to controls. After controlling for multiple variables, all the following factors resulted in greater odds of a deficient MoCA-B: COVID-19 6-months prior (OR, 2.44; p = 0.018), age (OR, 1.15; p &lt; 0.001), lower income (OR, 0.36; p = 0.070), and overweight (OR, 2.83; p = 0.013). Further analysis pointed to individual characteristics in COVID-19-affected patients that could explain the severity of the cognitive decline: age (p = 0.015), lower income (p &lt; 0.001), anxiety (p = 0.049), ageusia (p = 0.054), overweight (p &lt; 0.001), and absence of cognitively stimulating activities (p = 0.062).ConclusionOur study highlights a profile of cognitive risk aggravation over aging after COVID-19 infection, which is likely mitigated by wealth but worsened in the presence of overweight. Ageusia at the time of acute COVID-19, anxiety, being overweight, and absence of routine intellectual activities are risk factors for more prominent cognitive decline among those infected by COVID-19.
Digital neuropsychological measures by defense automated neurocognitive assessment: reference values and clinical correlates
Authors: Ding Huitong , Kim Minzae , Searls Edward , Sunderaraman Preeti , De Anda-Duran Ileana , Low Spencer , Popp Zachary , Hwang Phillip H. , Li Zexu , Goyal Kriti , Hathaway Lindsay , Monteverde Jose , Rahman Salman , Igwe Akwaugo , Kolachalama Vijaya B. , Au Rhoda , Lin Honghuang 
Published: February 2024

IntroductionAlthough the growth of digital tools for cognitive health assessment, there’s a lack of known reference values and clinical implications for these digital methods. This study aims to establish reference values for digital neuropsychological measures obtained through the smartphone-based cognitive assessment application, Defense Automated Neurocognitive Assessment (DANA), and to identify clinical risk factors associated with these measures.MethodsThe sample included 932 cognitively intact participants from the Framingham Heart Study, who completed at least one DANA task. Participants were stratified into subgroups based on sex and three age groups. Reference values were established for digital cognitive assessments within each age group, divided by sex, at the 2.5th, 25th, 50th, 75th, and 97.5th percentile thresholds. To validate these values, 57 cognitively intact participants from Boston University Alzheimer’s Disease Research Center were included. Associations between 19 clinical risk factors and these digital neuropsychological measures were examined by a backward elimination strategy.ResultsAge- and sex-specific reference values were generated for three DANA tasks. Participants below 60 had median response times for the Go-No-Go task of 796 ms (men) and 823 ms (women), with age-related increases in both sexes. Validation cohort results mostly aligned with these references. Different tasks showed unique clinical correlations. For instance, response time in the Code Substitution task correlated positively with total cholesterol and diabetes, but negatively with high-density lipoprotein and low-density lipoprotein cholesterol levels, and triglycerides.DiscussionThis study established and validated reference values for digital neuropsychological measures of DANA in cognitively intact white participants, potentially improving their use in future clinical studies and practice.
Novel artificial intelligence-based hypodensity detection tool improves clinician identification of hypodensity on non-contrast computed tomography in stroke patients
Authors: Santos Angela Dos , Visser Milanka , Lin Longting , Bivard Andrew , Churilov Leonid , Parsons Mark William 
Published: February 2024

IntroductionIn acute stroke, identifying early changes (parenchymal hypodensity) on non-contrast CT (NCCT) can be challenging. We aimed to identify whether the accuracy of clinicians in detecting acute hypodensity in ischaemic stroke patients on a non-contrast CT is improved with the use of an Artificial Intelligence (AI) based, automated hypodensity detection algorithm (HDT) using MRI-DWI as the gold standard.MethodsThe study employed a case-crossover within-clinician design, where 32 clinicians were tasked with identifying hypodensity lesions on NCCT scans for five a priori selected patient cases, before and after viewing the AI-based HDT. The DICE similarity coefficient (DICE score) was the primary measure of accuracy. Statistical analysis compared DICE scores with and without AI-based HDT using mixed-effects linear regression, with individual NCCT scans and clinicians as nested random effects.ResultsThe AI-based HDT had a mean DICE score of 0.62 for detecting hypodensity across all NCCT scans. Clinicians’ overall mean DICE score was 0.33 (SD 0.31) before AI-based HDT implementation and 0.40 (SD 0.27) after implementation. AI-based HDT use was associated with an increase of 0.07 (95% CI: 0.02–0.11, p = 0.003) in DICE score accounting for individual scan and clinician effects. For scans with small lesions, clinicians achieved a mean increase in DICE score of 0.08 (95% CI: 0.02, 0.13, p = 0.004) following AI-based HDT use. In a subgroup of 15 trainees, DICE score improved with AI-based HDT implementation [mean difference in DICE 0.09 (95% CI: 0.03, 0.14, p = 0.004)].DiscussionAI-based automated hypodensity detection has potential to enhance clinician accuracy of detecting hypodensity in acute stroke diagnosis, especially for smaller lesions, and notably for less experienced clinicians.
Cilostazol-based dual antiplatelet treatment in ischemic stroke or transient ischemic attack patients with asymptomatic carotid artery disease: a propensity score matching analysis
Authors: Thiraworawong Thon , Pathonsmith Chadawan 
Published: February 2024

BackgroundThe optimal treatment for asymptomatic atherosclerotic carotid artery disease remains controversial. Data on the efficacy of antiplatelet agents and stroke outcomes are limited. This study aimed to examine the efficacy and safety of cilostazol-based dual antiplatelet therapy in patients with ischemic stroke or transient ischemic attack and asymptomatic carotid artery disease.MethodsThis retrospective cohort study was conducted in a tertiary-care setting and included baseline characteristics and clinical outcomes of participants. The study included patients who had experienced first-ever ischemic stroke or transient ischemic attack and asymptomatic atherosclerotic carotid artery stenosis, with a minimum follow-up period of 1 year. Asymptomatic carotid artery stenosis refers to stenosis in patients without neurological symptoms referable to the carotid arteries. Propensity scores were estimated using a logistic regression model based on participants’ baseline characteristics. The efficacy outcome was the composite outcome of recurrent ischemic events and vascular-related death in patients with ischemic stroke or transient ischemic attack and asymptomatic carotid artery stenosis. The safety outcome was the occurrence of hemorrhagic complications such as intracranial hemorrhages or extracranial hemorrhages. The effectiveness of dual therapy compared to monotherapy was evaluated at various time points following the initiation of antiplatelet treatment.ResultsThis study included 516 patients with a 1-year follow-up period. At 1 year, composite events occurred in 10 (6.3%) patients in the dual antiplatelet group compared with 12 (7.6%) in the single antiplatelet group (HR, 0.74; 95% CI, 0.61–0.90; p = 0.024). Extracranial hemorrhage occurred in 12 (7.6%) patients in the dual antiplatelet group compared with nine (5.7%) in the single antiplatelet group (HR, 1.35; 95% CI, 1.13–1.48; p = 0.017). No intracranial hemorrhages were observed in this cohort.ConclusionPatients with asymptomatic carotid artery stenosis who received cilostazol-based dual antiplatelet therapy had a lower risk of composite events but a higher risk of minor extracranial hemorrhage than those who received a single antiplatelet agent.