bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trends and Disparities in Glycemic Control and Severe Hyperglycemia Among US Adults With Diabetes Using Insulin, 1988-2020
Authors: Venkatraman Siddharth , Echouffo-Tcheugui Justin B. , Selvin Elizabeth , Fang Michael 
Published: December 2022

ImportanceThere have been major advances in insulin delivery and formulations over the past several decades. It is unclear whether these changes have resulted in improved glycemic control for patients with diabetes.ObjectiveTo characterize trends and disparities in glycemic control and severe hyperglycemia in US adults with diabetes using insulin.Design, Setting, and ParticipantsThis serial population-based cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) between 1988-1994 and 1999-2020. Participants were nonpregnant US adults aged 20 years or older who had a diagnosis of diabetes and were currently using insulin.ExposuresDiabetes diagnosis and use of insulin.Main Outcomes and MeasuresTrends in glycemic control (glycated hemoglobin [HbA1c] level &amp;lt;7%) and severe hyperglycemia (HbA1c level &amp;gt;10%; to convert percentage of total hemoglobin to proportion of total hemoglobin, multiply by 0.01; to convert to millimoles per mole, multiply by 10.93 and subtract by 23.50) overall and by age, race and ethnicity, and indicators of socioeconomic status were evaluated using logistic regression. Analyses incorporated sample weights to account for oversampling of certain populations and survey nonresponse.ResultsThere were 2482 participants with diabetes using insulin included in the analyses (mean [SD] age, 59.8 [0.4] years); 51.3% were men, 7.0% were Mexican American individuals, 17.9% were non-Hispanic Black individuals, and 65.2% were non-Hispanic White individuals. From 1988-1994 to 2013-2020, the proportion of patients with diabetes who received insulin and achieved glycemic control did not significantly change, from 29.2% (95% CI, 22.6%-36.8%) to 27.5% (95% CI, 21.7%-34.2%). Mexican American adults who received insulin were less likely than non-Hispanic White adults to achieve glycemic control, and disparities increased during the study period. The proportion of adults with severe hyperglycemia did not significantly change and was 14.6% (95% CI, 12.0-17.5) in 2013-2020. Adults who were Mexican American or non-Hispanic Black, were uninsured, or had low family income had the highest prevalence of severe hyperglycemia.Conclusions and RelevanceIn this population-based cross-sectional study of NHANES data over the past 3 decades, glycemic control stagnated and racial and ethnic disparities increased among US adults with diabetes who received insulin. Efforts to improve access to insulin may optimize glycemic control and reduce disparities in this population.
Composite adaptive finite‐time fuzzy control for switched nonlinear systems with preassigned performance
Authors: Sun Peng , Song Xiaona , Song Shuai , Stojanovic Vladimir 
Published: December 2022

SummaryThis article investigates the composite adaptive fuzzy finite‐time prescribed performance control issue of switched nonlinear systems subject to the unknown external disturbance and performance requirement. First, by utilizing the compensation and prediction errors, the piecewise switched composite parameter update law is employed to improve the approximation accuracy of the unknown nonlinearity. Then, the improved fractional‐order filter and error compensation signal are introduced to cope with the influences caused by the explosive calculation and filter error, respectively. Meanwhile, the effect of the compound disturbances consisting of the unknown disturbances and approximation errors is reduced appropriately by designing the piecewise switched nonlinear disturbance observer. Moreover, stability analysis results prove that the proposed preassigned performance control scheme not only ensures that all states of the closed‐loop system are practical finite‐time bounded, but also that the tracking error converges to a preassigned area with a finite time. Ultimately, the simulation examples are given to demonstrate the effectiveness of the proposed control strategy.
Molten Salt Strategy for Reproducible Evaporation of Efficient Perovskite Solar Cells
Authors: Li Hang , Tan Liguo , Jiang Chaofan , Li Minghao , Zhou Junjie , Ye Yiran , Liu Yue , Yi Chenyi 
Published: December 2022

AbstractVacuum evaporation is promising for the scalable fabrication of perovskite solar cells (PSCs). Nevertheless, the poor thermal conductivity of metal halide powder leads to unfavorable temperature inhomogeneity, which destabilizes the evaporation rate, posing a major challenge to the reproducible deposition of perovskite films, particularly by coevaporation. Herein, a molten salt strategy is reported for sequentially vacuum evaporation of PSCs. The molten salt increases the thermal conductivity of metal halides and greatly homogenizes the temperature, which stabilizes the evaporation rate and the composition of the resulting perovskite films. The PSCs yield power conversion efficiencies (PCEs) of ≈24% with exceptional reproducibility. The unencapsulated PSCs maintain 85% of the initial PCE after 3600 h of maximum power point tracking and maintain 85% of the initial PCE after being heated at 60 °C for 3000 h. The molten salt strategy opens a new avenue for the application of evaporation in perovskite optoelectronics.
Delivering mRNA to Secondary Lymphoid Tissues by Phosphatidylserine‐Loaded Lipid Nanoparticles
Authors: Gomi Masaki , Sakurai Yu , Sato Minami , Tanaka Hiroki , Miyatake Yumi , Fujiwara Koichi , Watanabe Mizuki , Shuto Satoshi , Nakai Yuta , Tange Kota , Hatakeyama Hiroto , Akita Hidetaka 
Published: December 2022

AbstractLipid nanoparticles (LNPs) are one of the most successful technologies in messenger RNA (mRNA) delivery. While the liver is the most frequent target for LNP delivery of mRNA, technologies for delivering mRNA molecules to extrahepatic tissues are also important. Herein, it is reported on the development of an LNP that targets secondary lymphoid tissues. New types of alcohol‐soluble phosphatidylserine (PS) derivatives are designed as materials that target immune cells and then incorporated into LNPs using a microfluidic technique with a high degree of scalability and reproducibility. The resulting LNP that contained the synthesized PS delivered mRNA to the spleen much more efficiently compared to a control LNP. A sub‐organ analysis revealed that the PS‐loaded LNP is extensively taken up by tissue‐resident macrophages in the red pulp and the marginal zone of the spleen. Thus, the PS‐loaded LNP reported in this study will be a promising strategy for clinical applications that involve delivering mRNA to the spleen.
Perspectives of 2D MXene Tribology
Authors: Rosenkranz Andreas , Righi Maria Clelia , Sumant Anirudha V. , Anasori Babak , Mochalin Vadym N. 
Published: December 2022

AbstractThe large and rapidly growing family of 2D early transition metal carbides, nitrides, and carbonitrides (MXenes) raises significant interest in the materials science and chemistry of materials communities. Discovered a little more than a decade ago, MXenes have already demonstrated outstanding potential in various applications ranging from energy storage to biology and medicine. The past two years have witnessed increased experimental and theoretical efforts toward studying MXenes’ mechanical and tribological properties when used as lubricant additives, reinforcement phases in composites, or solid lubricant coatings. Although research on the understanding of the friction and wear performance of MXenes under dry and lubricated conditions is still in its early stages, it has experienced rapid growth due to the excellent mechanical properties and chemical reactivities offered by MXenes that make them adaptable to being combined with other materials, thus boosting their tribological performance. In this perspective, the most promising results in the area of MXene tribology are summarized, future important problems to be pursued further are outlined, and methodological recommendations that could be useful for experts as well as newcomers to MXenes research, in particular, to the emerging area of MXene tribology, are provided.
Anisotropic Nanoparticle Arrays Guided by Ordered Nanowire Films Enhance Surface‐Enhanced Raman Scattering
Authors: Sheng Si‐Zhe , Zheng Shi‐Qiao , Feng Xue‐Fei , Zhou Ling‐Ran , Tao Zhen‐Chao , Liu Jian‐Wei 
Published: December 2022

AbstractDesigning high‐efficiency surface‐enhanced Raman scattering (SERS) substrates has attracted explosive attention in recent decades for their novel and potential applications. Great achievements have been made to optimize the intrinsic activity of nanomaterial in SERS substrates, while little attention has been paid to the unique structural design of the nanomaterial building blocks. Herein, a new strategy is provided for assembling Au nanoparticles into well‐defined ordered structures by using a highly ordered arrangement nanowires template to explore the ordering effect on the SERS performance. The highly ordered Au nanoparticle arrays show a detection limit of 10−9 m that exceeds disordered Au particles by two orders of magnitude, as well as over treble enhancement factor at the same detection concentration. Importantly, this novel scientific discovery can be further confirmed in various probed molecules or nanoparticles with different diameters, which means SERS substrate design can be pushed forward further combined with traditional intrinsic activity design.
Precisely Confined AIEgens in Giant Imidazolium–Terpyridinyl Cuboctahedra with Enhanced Fluorescence for Single Supramolecule
Authors: Yu Min‐Ya , Guan Yu‐Ming , Bai Qixia , Su Peiyang , Wang Pingshan , Xie Ting‐Zheng 
Published: December 2022

AbstractTo study the fluorescent behavior of quantitatively confined aggregation‐induced emission (AIE) molecules in a giant cavity, herein a new type of coordination‐driven cuboctahedron cage is presented, with 12 AIE molecules anchored endohedrally linked with different‐length alkyl chains. The cage with confined tetraphenylethylene molecules shows strong fluorescence in highly diluted conditions (4 × 10−7 m). The fluorescence quantum yield can be altered from 3.23% up to 81.37%, upon prolonging the length of alkyl chains to C16. The study shows a great potential application in biology mimic and fluorescent microscopes utilizing confined or isolated fluorescent methods.
Data‐Driven Intelligent Manipulation of Particles in Microfluidics
Authors: Fang Wen‐Zhen , Xiong Tongzhao , Pak On Shun , Zhu Lailai 
Published: December 2022

AbstractAutomated manipulation of small particles using external (e.g., magnetic, electric and acoustic) fields has been an emerging technique widely used in different areas. The manipulation typically necessitates a reduced‐order physical model characterizing the field‐driven motion of particles in a complex environment. Such models are available only for highly idealized settings but are absent for a general scenario of particle manipulation typically involving complex nonlinear processes, which has limited its application. In this work, the authors present a data‐driven architecture for controlling particles in microfluidics based on hydrodynamic manipulation. The architecture replaces the difficult‐to‐derive model by a generally trainable artificial neural network to describe the kinematics of particles, and subsequently identifies the optimal operations to manipulate particles. The authors successfully demonstrate a diverse set of particle manipulations in a numerically emulated microfluidic chamber, including targeted assembly of particles and subsequent navigation of the assembled cluster, simultaneous path planning for multiple particles, and steering one particle through obstacles. The approach achieves both spatial and temporal controllability of high precision for these settings. This achievement revolutionizes automated particle manipulation, showing the potential of data‐driven approaches and machine learning in improving microfluidic technologies for enhanced flexibility and intelligence.
Electro‐Powerless Balloon Soft Actuator with Manually Driven Fluidic Circuit
Authors: Matsuda Ryosuke , Song Zihao , Ota Hiroki 
Published: December 2022

AbstractBalloon‐type actuators have attracted scientific attention because they allow easy control of the output intensity and a high degree‐of‐freedom regarding shape and movement. However, they require bulky external pumps and electric power suppliers. This makes miniaturization and wearable device fabrication difficult. Herein, a balloon soft actuator that does not require a pneumatic pump or electric power supplier, and that uses a finger‐operated pump based on a fluidic circuit and catalytic reaction, is proposed. This device can be driven without electric power multiple times by applying a vent valve system to exhaust the generated gas. Further, it is applied to two different types of applications—soft robots and wearable devices—by optimizing their structure and material. In conclusion, the proposed device is expected to lead to the development of a broad range of soft actuators for stand‐alone robots and wearable devices in the future.
“Faces on a screen”: A qualitative study of the virtual and in‐person conference experience
Authors: Gottlieb Michael , Sebok‐Syer Stefanie S. , Bawden Abigail , Shah Meeta , Jordan Jaime 
Published: December 2022

AbstractIntroductionThe strengths and weaknesses of virtual and in‐person formats within continuing professional development (CPD) are incompletely understood. This study sought to explore attendees' perspectives across multiple specialties regarding benefits and limitations of conference formats and strategies for successful virtual and hybrid (i.e., in‐person conferences with a virtual option) conferences.MethodsFrom December 2020 to January 2021, semistructured interviews were conducted with participants who attended both virtual and in‐person CPD conferences. Purposive sampling was utilized to ensure diverse representation of gender, years in practice, location, academic rank, specialty, and practice type. Multiple specialties were intentionally sought to better understand the broader experience among physicians in general, rather than among a specific specialty. Using modified grounded theory approach with a constructivist–interpretivist paradigm, two investigators independently analyzed all interview transcripts. Discrepancies were resolved by in‐depth discussion and negotiated consensus.ResultsTwenty‐six individuals across 16 different specialties were interviewed. We identified three overarching concepts: motivations to attend conferences, benefits and limitations of different conference formats, and strategies to optimize virtual and hybrid conferences. Specific motivators included both professional and personal factors. Benefits of in person included networking/community, immersion, and wellness, while the major limitation was integration with personal life. Benefits of virtual were flexibility, accessibility, and incorporation of technology, while limitations included technical challenges, distractions, limitations for tactile learning, and communication/connection. Benefits of hybrid included more options for access, while limitations included challenges with synchrony of formats and dilution of experiences. Strategies to improve virtual/hybrid conferences included optimizing technology/production, facilitating networking and engagement, and deliberate selection of content.ConclusionsThis study identified several benefits and limitations of each medium as well as strategies to optimize virtual and hybrid CPD conferences. This may help inform future CPD conference planning for both attendees and conference planners alike.
Limbic Predominant Age‐related TDP‐43 Encephalopathy Neuropathological Change (LATE‐NC) is Associated with Lower Diffusion Anisotropy in Medial Temporal Lobe White Matter
Authors: Tazwar Mahir , Evia Arnold M , Tamhane Ashish A , Ridwan Abdur Raquib , Bennett David A , Schneider Julie A , Arfanakis Konstantinos 
Published: December 2022

AbstractBackgroundLimbic predominant age‐related TDP‐43 encephalopathy neuropathological change (LATE‐NC) is now recognized as a common neuropathological disorder of the aging brain and is associated with accelerated cognitive decline. However, the MRI signature of LATE‐NC has not been fully determined. In this work, we hypothesized that abnormalities in white matter (WM) structural integrity caused by LATE‐NC may be detected by means of diffusion tensor imaging (DTI).MethodThis study included 148 individuals participating in Rush Memory and Aging Project, and Religious Orders Study (Fig.1). Ex‐vivo DTI images were acquired using 3T scanners, followed by detailed histopathologic examination by a board‐certified neuropathologist (Fig.2). As a post‐processing step, fractional anisotropy (FA) maps generated from DTI images were aligned to an ex‐vivo FA template and projected onto the corresponding WM skeleton.Voxel‐wise analysis was performed on the WM skeleton to investigate the association of FA with LATE‐NC, controlling for Alzheimer’s disease, Lewy bodies, cerebral amyloid angiopathy, cerebral infarcts, atherosclerosis, arteriolosclerosis, age at death, sex, years of education, postmortem interval to fixation and imaging, total white matter hyperintensity volume, and scanner. Statistical significance was set at p<0.05. Using the voxels that showed significance in this analysis, (1) probable WM connections passing through them were extracted, (2) FA values were compared between LATE‐NC stages 1, 2, 3 and stage 0 (after adjusting for covariates).ResultVoxel‐wise analysis revealed lower FA for greater LATE‐NC burden in medial temporal lobe WM (Fig.3). The connections traversing this WM region included fibers connecting amygdala, temporal pole, hippocampus, entorhinal cortex, fusiform, insula, and putamen (Fig.4). No voxel showed positive association between FA and LATE‐NC. Comparison of adjusted FA values in medial temporal lobe WM across LATE‐NC stages revealed significant FA anomalies between stages 0 and 3 (ΔFA=‐0.06, FDR‐corrected p<10‐6) (Fig.5).ConclusionThe present study in autopsied brains of community‐based older adults showed lower diffusion anisotropy with greater LATE‐NC burden involving WM connections between regions consistent with the known distribution of LATE‐NC. Overall, this pattern may potentially contribute towards the development of an in‐vivo tool for the prediction of this devastating, recently recognized disease entity.
Three‐stage classification of Alzheimer's disease in MRI in clinical records of the Mass General Brigham Health Care System
Authors: Leming Matthew , Das Sudeshna , Im Hyungsoon 
Published: December 2022

AbstractBackgroundDiagnostic deep learning has frequently been applied to diagnosis of Alzheimer's and Mild Cognitive Impairment in brain MRIs collected in a controlled research setting, but due to the presence of confounding factors, similar methods have rarely been applied post‐hoc to clinical MRI. Data matching, or the matching of datasets across different classes with respect to a number of confounds, is a method of finding subsets of an overall dataset, that can be used to mitigate the confounding factor problem.Method467,464 multimodal clinical MRIs of the brain from 37,311 patients in the Mass General Brigham (MGB) Healthcare System were either excluded (based on presence of neoplasms or head trauma) or labeled as AD, MCI, or control, based on a previous prescription of rivastigmine, galantamine, or donepezil (MCI), or memantine (AD), or the lack of a history of central nervous system medications. A data matching algorithm was applied to 18 technical and demographic confounding factors to isolate an unconfounded matched dataset set to train an ensemble of five 3D ResNet‐50 deep learning models. Across the ensemble, the test set totaled 287,367 files. See Figure 1.ResultIn distinguishing controls from AD/MCI on a per‐patient basis, an AUROC of 0.82 was achieved, though with lower performance in distinguishing between AD and MCI. Variations in performance were seen with MRI modality, with MPRAGE having the highest performance overall (0.859 AUROC). See Figure 2.ConclusionWhen carefully accounting for confounds, the use of deep learning models is feasible in the analysis of highly‐confounded clinical MRI.
Incorporation of plasma biomarkers for screening and diagnosis in primary care
Authors: Galasko Douglas R. , Chhatwal Jasmeer P. , Wijsman Ellen M , Rumbaugh Malia C. , Mozersky Jessica , Blacker Deborah ,   Shiley‐Marcos Alzheimer’s Disease Research Center
Published: December 2022

AbstractBackgroundPlasma biomarkers that reflect Alzheimer’s neuropathological changes are under FDA consideration for approval as diagnostic tests. Their use in primary care will become feasible, and it will be difficult to limit biomarker screening to symptomatic or high risk individuals, especially as symptoms of cognitive decline are often nonspecific.MethodsAs members of the NIA Advisory Group on Risk Evidence Education for Dementia (AGREED), we have examined analytics of AD biomarkers in asymptomatic and symptomatic contexts, as well as language used in disclosure of biomarker results in research studies. We review recent data and describe key issues in plasma screening for Alzheimer’s Disease in primary care and propose directions for future research.ResultsCritical issues include: 1. Assessing accuracy of biomarker(s) measurement, and sensitivity and specificity of cutoffs to determine presence or absence of amyloid or other AD pathology. 2. Recognizing the critical need to study biomarkers in population‐based settings and among under‐represented individuals to understand factors that may modify cutoffs and normative data, e.g., age, sex, ethnicity, renal and hepatic function. 3. Data and models regarding the value of amyloid positivity to predict the development of Mild Cognitive Impairment (MCI) or dementia in asymptomatic individuals, and for progression of MCI to dementia. 4. Disclosure of APOE genotype if it is part of a biomarker risk algorithm. 5. Selecting nuanced language for describing positive, negative or indeterminate biomarker results, with clear explanations of what the tests measure, and risks associated with positive or negative results. 6. Current plasma biomarkers do not measure other pathologies and cognitions that may contribute to MCI and dementia, e.g., a‐synuclein, TDP43 or vascular pathology; depression, medical comorbidities, sleep disorders or medications that may adversely impact cognition. Together with biomarker results, the impact of these factors on cognition should be considered and discussed. 7. Screening for cognition is underdeveloped, limited by the types of tests currently used for screening and the time typically available to assess patients in primary care.ConclusionsFurther research on these topics and support and education of primary care providers is essential for the deployment of blood‐based biomarkers in primary care.