Uniform Set Research Articles

Exploring the links among brain iron accumulation, cognitive performance, and dietary intake in older adults: A longitudinal MRI study

This study evaluated longitudinal brain iron accumulation in older adults, its association with cognition, and the role of specific nutrients in mitigating iron accumulation. MRI-based, quantitative susceptibility mapping estimates of brain iron concentration were acquired from seventy-two healthy older adults (47 women, ages 60–86) at a baseline timepoint (TP1) and a follow-up timepoint (TP2) 2.5–3.0 years later. Dietary intake was evaluated at baseline using a validated questionnaire. Cognitive performance was assessed at TP2 using the uniform data set (Version 3) neuropsychological tests of episodic memory (MEM) and executive function (EF). Voxel-wise, linear mixed-effects models, adjusted for longitudinal gray matter volume alterations, age, and several non-dietary lifestyle factors revealed brain iron accumulation in multiple subcortical and cortical brain regions, which was negatively associated with both MEM and EF performance at T2. However, consumption of specific dietary nutrients at TP1 was associated with reduced brain iron accumulation. Our study provides a map of brain regions showing iron accumulation in older adults over a short 2.5-year follow-up and indicates that certain dietary nutrients may slow brain iron accumulation.

MUTUAL RECOGNITION IN PRISON RULES AND PRE -TRIAL DETENTION AND DETENTION IN EU

The purpose of this study is to highlight the important aspects on the creation of a criminal justice section inside prisons, as well as the creation of minimum requirements for jail and detention settings and a uniform set of rights for all EU inmates. The Council of Europe believes that efforts should be taken to improve mutual trust and to more effectively implement the concept of mutual recognition in custody, as stated in the Stockholm Program, which calls for the Council to address detention and related concerns. Among the instruments of mutual recognition of terms of incarceration that may be affected we mention the European Arrest Warrant issued by the Council, the transfer of prisoners, the mutual recognition of alternative sanctions and judicial proceedings, and the European supervision order. Following the analysis and empirical research, the paper summarizes that without mutual trust in detention, the European Union's mutual recognition instruments affecting detention will not work properly, as one Member State is unwilling to recognize and implement a decision taken by the authorities of another Member State. Without greater efforts to improve detention conditions and promote alternatives to detention, it may be difficult to develop closer judicial cooperation between Member States.

Evolving Paradigms in Automated Program Repair: Taxonomy, Challenges, and Opportunities

With the rapid development and large-scale popularity of program software, modern society increasingly relies on software systems. However, the problems exposed by software have also come to the fore. The software bug has become an important factor troubling developers. In this context, Automated Program Repair (APR) techniques have emerged, aiming to automatically fix software bug problems and reduce manual debugging work. In particular, benefiting from the advances in deep learning, numerous learning-based APR techniques have emerged in recent years, which also bring new opportunities for APR research. To give researchers a quick overview of APR techniques’ complete development and future opportunities, we review the evolution of APR techniques and discuss in depth the latest advances in APR research. In this article, the development of APR techniques is introduced in terms of four different patch generation schemes: search-based, constraint-based, template-based, and learning-based. Moreover, we propose a uniform set of criteria to review and compare each APR tool and then discuss the current state of APR development. Finally, we analyze current challenges and future directions, especially highlighting the critical opportunities that large language models bring to APR research.

Multiphase Viscoelastic Non‐Newtonian Fluid Simulation

AbstractWe propose an SPH‐based method for simulating viscoelastic non‐Newtonian fluids within a multiphase framework. For this, we use mixture models to handle component transport and conformation tensor methods to handle the fluid's viscoelastic stresses. In addition, we consider a bonding effects network to handle the impact of microscopic chemical bonds on phase transport. Our method supports the simulation of both steady‐state viscoelastic fluids and discontinuous shear behavior. Compared to previous work on single‐phase viscous non‐Newtonian fluids, our method can capture more complex behavior, including material mixing processes that generate non‐Newtonian fluids. We adopt a uniform set of variables to describe shear thinning, shear thickening, and ordinary Newtonian fluids while automatically calculating local rheology in inhomogeneous solutions. In addition, our method can simulate large viscosity ranges under explicit integration schemes, which typically requires implicit viscosity solvers under earlier single‐phase frameworks.

Cognitive dispersion and its functional relevance in behavioral variant frontotemporal dementia and prodromal behavioral variant frontotemporal dementia.

Executive dysfunction is characteristic of behavioral variant frontotemporal dementia (bvFTD) but can be challenging to detect. Dispersion-based intraindividual variability (IIV-d) is hypothesized to reflect a sensitive index of executive dysfunction and has demonstrated relevance to functional decline but has not been evaluated in bvFTD. We report on 477 demographically matched participants (159 cognitively healthy [CH], 159 clinical Alzheimer's disease [AD], 159 clinical bvFTD/prodromal bvFTD) who completed the Uniform Data Set 3.0 Neuropsychological Battery. IIV-d was measured using the coefficient of variance (CoV; raw and demographically adjusted) across 12 Uniform Data Set 3.0 Neuropsychological Battery indicators and the informant-rated Functional Activities Questionnaire assessed daily functioning. Analysis of covariance showed that participants in the bvFTD/prodromal bvFTD group exhibited higher raw and demographically adjusted CoV compared to CH participants, at a very large effect size (d = 1.28-1.47). Demographically adjusted (but not raw) CoV was lower in the bvFTD/prodromal bvFTD group than the AD group, though the effect size was small (d = .38). Both CoV metrics accurately differentiated the bvFTD/prodromal bvFTD and CH groups (areas under the curve = .84), but not bvFTD/prodromal bvFTD and AD groups (areas under the curve = .59). Regression analyses in the bvFTD/prodromal bvFTD group indicated that higher IIV-d on both metrics was associated with greater daily functioning impairment, over and above covariates. Compared to healthy adults, individuals with bvFTD/prodromal bvFTD show greater levels of performance variability across a battery of neuropsychological measures, which interferes with everyday functioning. These data demonstrate the clinical utility and ecological validity of IIV-d in bvFTD/prodromal bvFTD, though these findings should be replicated in more diverse samples. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

B - 107 Is the Flynn Effect Present in a Veteran Outpatient Clinic Sample?

Abstract Objective The Flynn Effect refers to improvement in cognitive scores over time due to advancements in education quality, nutrition, and socioenvironmental variables. Recent studies suggest cognitive scores may plateau or decline over time. Characterization of cohort effects in cognitive performance has implications for normative group selection and identification of brain illness. This study examines cognitive performances of veterans using older and newer versions of normative data to determine if a Flynn effect is present. Method Veterans (N = 189) who passed TOMM and completed the Trail-Making Test (TMT), Animal Naming, and California Verbal Learning Test-II (CVLT-II) were selected for inclusion. The sample was 81% male, racially diverse (49% White/Caucasian, 31% Black/African American, 16% Hispanic/Latino, 4% other), and diagnostically diverse (13% no diagnosis, 33% cognitive disorder, 54% psychiatric diagnosis). Normative scores were calculated from CVLT-II/CVLT-3 manuals for Trial 1, Trial 5, and LDFR; ADC Uniform Data Sets (UDS) were used for TMT-A/B and Animals. Wilcoxon matched-pairs signed rank tests examined differences in z-scores across older and newer normative data. Results Median z-scores were significantly lower using updated UDS norms for TMT-A (z = −11.60, p < 0.001), TMT-B (z = −10.41, p < 0.001), and Animals (z = −11.76, p < 0.001), while CVLT Trial 1 z-scores were significantly higher using CVLT-3 norms (z = 11.24, p < 0.001). CVLT Trial 5 and LDFR medians did not differ. Conclusion Findings demonstrate the need to examine cohort differences in normative reference groups to ensure accurate detection of brain illness. Furthermore, the Flynn Effect may not apply uniformly across domains within a period.

Blind QSO reconstruction challenge: exploring methods to reconstruct the Ly α emission line of QSOs

ABSTRACT Reconstructing the intrinsic Ly $\alpha$ line flux from high-z QSOs can place constraints on the neutral hydrogen content of the intergalactic medium during reionization. There are now $\gtrsim 10$ different Ly $\alpha$ reconstruction pipelines using different methodologies to predict the Ly $\alpha$ line flux from correlations with the spectral information redwards of Ly $\alpha$. However, there have been few attempts to directly compare the performance of these pipelines. Therefore, we devised a blind QSO challenge to compare these reconstruction pipelines on a uniform set of objects. Each author was provided de-identified, observed rest-frame QSO spectra with spectral information only redwards of 1260 Å rest-frame to ensure unbiased reconstruction. We constructed two samples of 30 QSOs, from X-Shooter and Sloan Digital Sky Survey (SDSS) both spanning $3.5\lt z\lt 4.5$. Importantly, the purpose of this comparison study was not to champion a single, best-performing reconstruction pipeline but rather to explore the relative performance of these pipelines over a range of QSOs with broad observational characteristics to infer general trends. In summary, we find machine-learning approaches in general provide the strongest ‘best guesses’ but underestimate the accompanying statistical uncertainty, although these can be recalibrated, while pipelines that decompose the spectral information, for example principal component or factor analysis, generally perform better at predicting the Ly $\alpha$ profile. Further, we found that reconstruction pipelines trained on SDSS QSOs performed similarly on average for both the X-Shooter and SDSS samples indicating no discernible biases owing to differences in the observational characteristics of the training set or QSO being reconstructed, although the recovered distributions of reconstructions for X-Shooter were broader likely due to an increased fraction of outliers.

Traumatic Brain Injury, Seizures, and Cognitive Impairment Among Older Adults

Traumatic brain injury (TBI), seizures, and dementia increase with age. There is a gap in understanding the associations of TBI, seizures, and medications such as antiseizure and antipsychotics with the progression of cognitive impairment across racial and ethnic groups. To investigate the association of TBI and seizures with the risk of cognitive impairment among cognitively normal older adults and the role of medications in moderating the association. This multicenter cohort study was a secondary analysis of the Uniform Data Set collected between June 1, 2005, and June 30, 2020, from the National Alzheimer's Coordination Center. Statistical analysis was performed from February 1 to April 3, 2024. Data were collected from participants from 36 Alzheimer's Disease Research Centers in the US who were 65 years or older at baseline, cognitively normal at baseline (Clinical Dementia Rating of 0 and no impairment based on a presumptive etiologic diagnosis of AD), and had complete information on race and ethnicity, age, sex, educational level, and apolipoprotein E genotype. Health history of TBI, seizures, or both conditions. Progression to cognitive impairment measured by a Clinical Dementia Rating greater than 0. Among the cohort of 7180 older adults (median age, 74 years [range, 65-102 years]; 4729 women [65.9%]), 1036 were African American or Black (14.4%), 21 were American Indian or Alaska Native (0.3%), 143 were Asian (2.0%), 332 were Hispanic (4.6%), and 5648 were non-Hispanic White (78.7%); the median educational level was 16.0 years (range, 1.0-29.0 years). After adjustment for selection basis using propensity score weighting, seizure was associated with a 40% higher risk of cognitive impairment (hazard ratio [HR], 1.40; 95% CI, 1.19-1.65), TBI with a 25% higher risk of cognitive impairment (HR, 1.25; 95% CI, 1.17-1.34), and both seizure and TBI were associated with a 57% higher risk (HR, 1.57; 95% CI, 1.23-2.01). The interaction models indicated that Hispanic participants with TBI and seizures had a higher risk of cognitive impairment compared with other racial and ethnic groups. The use of antiseizure medications (HR, 1.23; 95% CI, 0.99-1.53), antidepressants (HR, 1.32; 95% CI, 1.17-1.50), and antipsychotics (HR, 2.15; 95% CI, 1.18-3.89) was associated with a higher risk of cognitive impairment, while anxiolytic, sedative, or hypnotic use (HR, 0.88; 95% CI, 0.83-0.94) was associated with a lower risk. This study highlights the importance of addressing TBI and seizures as risk factors for cognitive impairment among older adults. Addressing the broader social determinants of health and bridging the health divide across various racial and ethnic groups are essential for the comprehensive management and prevention of dementia.

Active Dwarf Galaxy Database. I. Overlap between Active Galactic Nuclei Selected by Different Techniques

We assemble a sample of 733 dwarf galaxies (M * ≤ 109.5 M ⊙) with signatures of active galactic nuclei (AGN) and explore the intersection between different AGN-selection techniques. Objects in our database are compiled from previous studies that identify AGN in dwarf galaxies through spectroscopy, X-ray emission, infrared colors, and optical photometric variability. We apply a uniform set of AGN diagnostic tools to the database using archival data. We find that any single selection method captures no more than half of the overall AGN population, and there is a general disagreement among the AGN-selection methods in this stellar-mass regime. The largest overlap between methods is found when both methods use optical spectroscopic data. In contrast, the populations of AGN intersect the least when comparing those methods that use photometric data at different wavelengths. These results can be used to better constrain the active fraction in dwarf galaxies, which is in turn an important constraint for black hole seed formation models. In a follow-up paper, we will explore links between the effectiveness of each selection technique and host galaxy properties.

One‐Pot Catalytic Cascade for the Depolymerization of the Lignin β‐O‐4 Motif to Non‐phenolic Dealkylated Aromatics

Aromatic monomers obtained by selective depolymerization of the lignin β‐O‐4 motif are typically phenolic and contain (oxygenated) alkyl substitutions. This work reveals the potential of a one‐pot catalytic lignin β‐O‐4 depolymerization cascade strategy that yields a uniform set of methoxylated aromatics without alkyl side‐chains. This cascade consists of selective acceptorless dehydrogenation of the γ‐hydroxy group, subsequent retro‐aldol reaction cleaving the Cα–Cβ bond followed by in situ acceptorless decarbonylation of the formed aldehydes. This three‐step cascade reaction, catalyzed by an iridium(I)‐BINAP complex, resulted in 75% 1,2‐dimethoxybenzene from G‐type lignin dimers alongside syngas (CO:H2 ≈ 1.4:1). Applying this method to a synthetic G‐type polymer, 11 wt% 1,2‐dimethoxybenzene was obtained. This versatile compound can be easily transformed into 3,4‐dimethoxyphenol, a valuable precursor for pharmaceutical synthesis, through enzymatic catalytic approach. Moreover, the hydrodeoxygenation potential of 1,2‐dimethoxybenzene offers a pathway to produce valuable cyclohexane or benzene derivatives, presenting enticing opportunities for sustainable chemical transformations without the necessity for phenolic mixture upgrading via dealkylation.

One-Pot Catalytic Cascade for the Depolymerization of the Lignin β-O-4 Motif to Non-phenolic Dealkylated Aromatics.

Aromatic monomers obtained by selective depolymerization of the lignin β-O-4 motif are typically phenolic and contain (oxygenated) alkyl substitutions. This work reveals the potential of a one-pot catalytic lignin β-O-4 depolymerization cascade strategy that yields a uniform set of methoxylated aromatics without alkyl side-chains. This cascade consists of selective acceptorless dehydrogenation of the γ-hydroxy group, subsequent retro-aldol reaction cleaving the Cα-Cβ bond followed by in situ acceptorless decarbonylation of the formed aldehydes. This three-step cascade reaction, catalyzed by an iridium(I)-BINAP complex, resulted in 75% 1,2-dimethoxybenzene from G-type lignin dimers alongside syngas (CO:H2 ≈ 1.4:1). Applying this method to a synthetic G-type polymer, 11 wt% 1,2-dimethoxybenzene was obtained. This versatile compound can be easily transformed into 3,4-dimethoxyphenol, a valuable precursor for pharmaceutical synthesis, through enzymatic catalytic approach. Moreover, the hydrodeoxygenation potential of 1,2-dimethoxybenzene offers a pathway to produce valuable cyclohexane or benzene derivatives, presenting enticing opportunities for sustainable chemical transformations without the necessity for phenolic mixture upgrading via dealkylation.

A partial decomposition cutting method with CF-discrepancy for points selection in stochastic seismic analysis of structures

The probability density evolution method is renowned for its effectiveness in conducting stochastic seismic response analyses of structures with uncertain parameters. Within this method, the points selection strategy, particularly in high-dimensional problems, is of paramount importance to achieving a balance between accuracy and efficiency. This paper proposes a novel point selection method designed to capture the probabilistic response of structural dynamic systems. The method starts by generating an initial uniform point set within a unit cube, using an improved number-theoretical method with a large number size. It then employs a partial decomposition cutting method to select a small number of samples from this initial uniform point set, which are subsequently scaled to the unit cube to serve as the representative points. These representative points are then transformed into the original random-variate space, and the corresponding assigned probabilities are computed accordingly. To enhance accuracy, a characteristic function-based discrepancy is proposed and applied to rearrange the representative points in the original random-variate space. The effectiveness of this method is demonstrated through two numerical examples, along with comparisons to results obtained using Monte Carlo Simulation and other comparable point sets.

Genome-Wide Gene Birth-Death Dynamics Are Associated with Diet Breadth Variation in Lepidoptera.

Comparative analyses of gene birth-death dynamics have the potential to reveal gene families that played an important role in the evolution of morphological, behavioral, or physiological variation. Here, we used whole genomes of 30 species of butterflies and moths to identify gene birth-death dynamics among the Lepidoptera that are associated with specialist or generalist feeding strategies. Our work advances this field using a uniform set of annotated proteins for all genomes, investigating associations while correcting for phylogeny, and assessing all gene families rather than a priori subsets. We discovered that the sizes of several important gene families (e.g. those associated with pesticide resistance, xenobiotic detoxification, and/or protein digestion) are significantly correlated with diet breadth. We also found 22 gene families showing significant shifts in gene birth-death dynamics at the butterfly (Papilionoidea) crown node, the most notable of which was a family of pheromone receptors that underwent a contraction potentially linked with a shift to visual-based mate recognition. Our findings highlight the importance of uniform annotations, phylogenetic corrections, and unbiased gene family analyses in generating a list of candidate genes that warrant further exploration.

Costs of diagnosing early Alzheimer's disease in three European memory clinic settings: Results from the precision medicine in Alzheimer's disease project.

The implementation of disease-modifying treatments for Alzheimer's Disease (AD) will require cost-effective diagnostic processes. As part of The Precision Medicine In AD consortium (PMI-AD) project, the aim is to analyze the baseline costs of diagnosing early AD at memory clinics in Norway, Slovenia, and the Netherlands. The costs of cognitive testing and a clinical examination, apolipoprotein E, magnetic resonance imaging (MRI), cerebrospinal fluid (CSF), positron emission tomography and blood-based biomarkers (BBM), which are used in different combinations in the three countries, were analyzed. Standardized unit costs, adjusted for GDP per capita and based on Swedish conditions were applied. The costs were expressed in euros (€) as of 2019. A diagnostic set comprising clinical examination, cognitive testing, MRI and CSF was defined as the gold standard, with MRI mainly used as an exclusion filter. Cost data were available for 994 persons in Norway, 169 in Slovenia and 1015 in the Netherlands. The mean diagnostic costs were 1478 (95% confidence interval 1433-1523) € in Norway, 851 (731-970) € in Slovenia and 1184 (1135-1232) € in the Netherlands. Norway had the highest unit costs but also the greatest use of tests. With a uniform diagnostic test set applied, the diagnostic costs were 1264 (1238-1291) €, in Norway, 843 (771-914) € in Slovenia and 1184 (1156-1213) € in the Netherlands. There were no major cost differences between the final set of diagnoses. The total costs for setting a diagnosis of AD varied somewhat in the three countries, depending on unit costs and use of tests. These costs are relatively low in comparison to the societal costs of AD.

Development and Evaluation of a Cesarean Hysterectomy Simulation Model

Introduction: Cesarean hysterectomy is a life-saving procedure considered during postpartum hemorrhage in cases of uterine atony refractory to management, placenta accreta spectrum, or other obstetric complications. The procedure has high morbidity and mortality despite the rising rates of worldwide and in the United States. A high percentage of OB/GYN residents graduate without preparedness to perform this procedure post-residency, citing insufficient residency exposure as the primary contributor. This study aims to use evaluation and assessment tools to validate a low-cost, low-fidelity cesarean hysterectomy model at multiple OB/GYN residency training sites across the United States to increase resident confidence and proficiency in performing this critical procedure. Materials and Methods: Model Design and Development: Gynecologic surgeons from two OB/GYN residencies reviewed the literature for cesarean hysterectomy education and simulation. A low fidelity, anatomically accurate model was developed for cesarean hysterectomy simulation purposes. Efforts were made to optimize for anatomic layout and realistic feel, particularly for the anatomic structures relevant to cesarean hysterectomy: uterine vessels, anterior and posterior peritoneum, relation of anterior uterus to the bladder and ureters. Study Design: The study received institutional board review exemption at the Loyola University Medical Center (LUMC) and the University of Toledo (UT). During the last two months of the academic calendar, OB/GYN residents were offered the opportunity to perform a cesarean hysterectomy on the model. Demographics were collected in addition to the number of cesarean and abdominal hysterectomies performed as well as the confidence in cesarean hysterectomies independently. A uniform set of surgical instruments with both appropriate and inappropriate tools were made available for residents to choose from. Throughout the simulation, residents were asked to verbalize each step being performed. One faculty rater at each institution was trained to use the objective and standardized assessment tools and had completed an inter- and intra-rater reliability assessment. All residents were evaluated using the same two objective assessment tools. The two validated assessment tools used to evaluate resident performance using the model were the Task Specific Checklist and the Global Rating Scale. The former assessed residents on a “performed or not” basis on 14 surgical steps specific to cesarean hysterectomy. The latter used a scale of 1 to 5, with higher values representing more advanced skill, to evaluate respect for tissue handling, time and motion, instrument handing, knowledge of instrument selection, operation flow, assistant use, and familiarity with the procedure. Results: A total of 26 residents, 18 of 19 at LUMC and 8 of 17 at UT, completed the cesarean hysterectomy simulation between May and June 2022. At LUMC, no graduating residents had performed a cesarean hysterectomy in their residency. At UT, graduating residents had performed up to 2. All of the residents, including PGY-4s, stated that they either disagree or strongly disagree with the statement “I feel confident performing cesarean hysterectomy independently.” As hypothesized, the median resident scores on the Task Specific Checklist and Global Rating scale correlated with increasing PGY level. The combined TSC+GRS score was a median of 40 out of 49 total for the PGY-4 class, while the PGY-1 class had a median combined TSC+GRS score of 12 of 49. The PGY-2 and -3 class had TSC+GRS scores of 14 and 28 respectively. The simulation model was well-received with a median 4/5 rating for improving comfort level with cesarean hysterectomy and a median 4/5 rating for model realism. Each uterine model cost $6.00 and took approximately 20 minutes to build. The optional base constructed for supporting the model, cost a one-time fee of $160. All materials used for construction were easily available online. Discussion: This study validated an affordable, easily reproducible model that highlights the most important anatomy relevant to a cesarean hysterectomy. The model was developed, produced, and tested at two residency programs with a total of 26 residents participating in the study. This is the first low-fidelity cesarean hysterectomy model inclusive of relevant surgical steps and offers near-real visceral feel that has been developed and assessed for validity. This multisite study created a realistic model with high reproducibility at a low cost. Limitations of this study included the fact that only 27 residents participated in the study from only two institutions. In addition, faculty evaluators were not blinded to the residents they rated. The model is a reliable and affordable way to introduce this procedure at residency programs, particularly those that do not perform a substantial number of cesarean hysterectomies.

Goal-based angular adaptivity with contributon theory for the discrete ordinates transport equation

A goal-based angular adaptivity has been described for solving the discrete ordinates transport equation. This method uses the linear discontinuous finite element quadrature sets, allowing for local angular refinement across space-energy dimensions. Anisotropy quantified factor derived by contributon theory is introduced in this adaptivity to locate spatial regions that require more angular unknowns in every energy group for a given goal region. The goal-based error metric is considered to trigger local refinement in angle, which requires the solutions of the contributon transport equation to determine the importance to a user-defined functional. Several problems that include both one-group and multi-group transport calculations are displayed to demonstrate the effectiveness of this method. Results indicate that our goal-based adaptivity can significantly reduce computational expenses in terms of angular unknowns and computational times for a similar accuracy, as compared to uniform quadrature sets. It is expected that this adaptivity has the potential to enhance the efficiency of an even wider range of transport problems.

Design and synthesis of a library of C8-substituted sulfamidoadenosines to probe bacterial permeability

Gram-negative bacteria pose a major challenge in antibiotic drug discovery because their cell envelope presents a permeability barrier that affords high intrinsic resistance to small-molecule drugs. The identification of correlations between chemical structure and Gram-negative permeability would thus enable development of predictive tools to facilitate antibiotic discovery. Toward this end, have advanced a library design paradigm in which various chemical scaffolds are functionalized at different regioisomeric positions using a uniform reagent set. This design enables decoupling of scaffold, regiochemistry, and substituent effects upon Gram-negative permeability of these molecules. Building upon our recent synthesis of a library of C2-substituted sulfamidoadenosines, we have now developed an efficient synthetic route to an analogous library of regioisomeric C8-substituted congeners. The C8 library samples a region of antibiotic-relevant chemical space that is similar to that addressed by the C2 library, but distinct from that sampled by a library of analogously substituted oxazolidinones. Selected molecules were tested for accumulation in Escherichia coli in a pilot analysis, setting the stage for full comparative evaluation of these libraries in the future.

A Systematic Review of Sustainability Criteria in Infrastructure Development

This paper explores the immediate need of infrastructure stakeholders for practical guidance promoting sustainable infrastructure development that aligns with the United Nations Sustainable Development Goals (SDGs) and European Union (EU) regulations. Despite overarching definitions, there is a noticeable absence of a uniform set of sustainability criteria, which delays the integration of sustainability principles into infrastructure planning, development, and operations. Through a targeted content analysis of the systematically selected literature from the Web of Science, this study seeks to clarify the characteristics of sustainable infrastructure. In the systematic review of 106 sources, carefully selected through a structured exclusion process described in the Open Science Framework register, the authors construct a comprehensive set of 43 sustainable infrastructure characteristics. Subsequently, these indicators undergo evaluation by sector experts through focus group discussions on the relevance of the proposed sustainable infrastructure criteria to local planning contexts. The focus group’s results demonstrate the adequacy of the proposed criteria, albeit with variations in perceived importance. Additionally, participants in the focus group suggest conducting field tests of the criteria in a municipal setting before scaling up to national policy frameworks.

Robust integration of secondary outcomes information into primary outcome analysis in the presence of missing data.

In clinical and observational studies, secondary outcomes are frequently collected alongside the primary outcome for each subject, yet their potential to improve the analysis efficiency remains underutilized. Moreover, missing data, commonly encountered in practice, can introduce bias to estimates if not appropriately addressed. This article presents an innovative approach that enhances the empirical likelihood-based information borrowing method by integrating missing-data techniques, ensuring robust data integration. We introduce a plug-in inverse probability weighting estimator to handle missingness in the primary analysis, demonstrating its equivalence to the standard joint estimator under mild conditions. To address potential bias from missing secondary outcomes, we propose a uniform mapping strategy, imputing incomplete secondary outcomes into a unified space. Extensive simulations highlight the effectiveness of our method, showing consistent, efficient, and robust estimators under various scenarios involving missing data and/or misspecified secondary models. Finally, we apply our proposal to the Uniform Data Set from the National Alzheimer's Coordinating Center, exemplifying its practical application.

Clinical validity of the Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB) in Mild Cognitive Impairment and Alzheimer’s Disease

BackgroundThe identification and staging of Alzheimer’s Disease (AD) represent a challenge, especially in the prodromal stage of Mild Cognitive Impairment (MCI), when cognitive changes can be subtle. Worldwide efforts were dedicated to select and harmonize available neuropsychological instruments. In Italy, the Italian Network of Neuroscience and Neuro-Rehabilitation has promoted the adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB), collecting normative data from 433 healthy controls (HC).Here, we aimed to explore the ability of I-UDSNB to differentiate between a) MCI and HC, b) AD and HC, c) MCI and AD.MethodsOne hundred thirty-seven patients (65 MCI, 72 AD) diagnosed after clinical-neuropsychological assessment, and 137 HC were included. We compared the I-UDSNB scores between a) MCI and HC, b) AD and HC, c) MCI and AD, with t-tests. To identify the test(s) most capable of differentiating between groups, significant scores were entered in binary logistic and in stepwise regressions, and then in Receiver Operating Characteristic curve analyses.ResultsTwo episodic memory tests (Craft Story and Five Words test) differentiated MCI from HC subjects; Five Words test, Semantic Fluency (vegetables), and TMT-part B differentiated AD from, respectively, HC and MCI.ConclusionsOur findings indicate that the I-UDSNB is a suitable tool for the harmonized and concise assessment of patients with cognitive decline, showing high sensitivity and specificity for the diagnosis of MCI and AD.