The impact of GLP-1 receptor agonist shortages on glycaemic Control: Findings from an Australian specialist diabetes clinic.

There have been shortages of glucagon-like peptide-1 receptor agonists (GLP-1 RA) for type 2 diabetes (T2D) care. Analyses of data from 811 T2D adults at an Australian specialist diabetes clinic (1/2019-10/2023) who received ≥ 2 GLP-1 RA prescriptions before and during the shortage showed median HbA1c levels significantly increased by 0.3 %.

Growth of Size-Tunable Ag2O Polyhedra and Revelation of Their Bulk and Surface Lattices.

By primarily adjusting the reagent amounts, particularly the volume of AgNO3 solution introduced, Ag2O cubes with decreasing sizes from 440 to 79 nm, octahedra from 714 to 106 nm, and rhombic dodecahedra from 644 to 168 nm are synthesized. 733 nm cuboctahedra are also prepared for structural analysis. With in-house X-ray diffraction (XRD) peak calibration, shape-related peak shifts are recognizable. Synchrotron XRD measurements at 100 K reveal the presence of bulk and surface layer lattices. Bulk cell constants also deviate slightly. They show a negative thermal expansion behavior with shrinking cell constants at higher temperatures. The Ag2O crystals exhibit size- and facet-dependent optical properties. Bandgaps red-shift continuously with increasing particle sizes. Optical facet effect is also observable. Moreover, synchrotron XRD peaks of a mixture of Cu2O rhombicuboctahedra and edge- and corner-truncated cubes exposing all three crystal faces can be deconvoluted into three components with the bulk and the [111] microstrain phase as the major component. Interestingly, while the unheated Cu2O sample shows clear diffraction peak asymmetry, annealing the sample to 450 K yields nearly symmetric peaks even when returning the sample to room temperature, meaning even moderately high temperatures can permanently change the crystal lattice.

MCCM: multi-scale feature extraction network for disease classification and recognition of chili leaves.

Currently, foliar diseases of chili have significantly impacted both yield and quality. Despite effective advancements in deep learning techniques for the classification of chili leaf diseases, most existing classification models still face challenges in terms of accuracy and practical application in disease identification. Therefore, in this study, an optimized and enhanced convolutional neural network model named MCCM (MCSAM-ConvNeXt-MSFFM) is proposed by introducing ConvNeXt. The model incorporates a Multi-Scale Feature Fusion Module (MSFFM) aimed at better capturing disease features of various sizes and positions within the images. Moreover, adjustments are made to the positioning, activation functions, and normalization operations of the MSFFM module to further optimize the overall model. Additionally, a proposed Mixed Channel Spatial Attention Mechanism (MCSAM) strengthens the correlation between non-local channels and spatial features, enhancing the model's extraction of fundamental characteristics of chili leaf diseases. During the training process, pre-trained weights are obtained from the Plant Village dataset using transfer learning to accelerate the model's convergence. Regarding model evaluation, the MCCM model is compared with existing CNN models (Vgg16, ResNet34, GoogLeNet, MobileNetV2, ShuffleNet, EfficientNetV2, ConvNeXt), and Swin-Transformer. The results demonstrate that the MCCM model achieves average improvements of 3.38%, 2.62%, 2.48%, and 2.53% in accuracy, precision, recall, and F1 score, respectively. Particularly noteworthy is that compared to the original ConvNeXt model, the MCCM model exhibits significant enhancements across all performance metrics. Furthermore, classification experiments conducted on rice and maize disease datasets showcase the MCCM model's strong generalization performance. Finally, in terms of application, a chili leaf disease classification website is successfully developed using the Flask framework. This website accurately identifies uploaded chili leaf disease images, demonstrating the practical utility of the model.

Isolated Traumatic Subarachnoid Hemorrhage on Head Computed Tomography Scan May Not Be Isolated: A Transforming Research and Clinical Knowledge in Traumatic Brain Injury Study (TRACK-TBI) Study.

Isolated traumatic subarachnoid hemorrhage (tSAH) after traumatic brain injury (TBI) on head computed tomography (CT) scan is often regarded as a "mild" injury, with reduced need for additional workup. However, tSAH is also a predictor of incomplete recovery and unfavorable outcome. This study aimed to evaluate the characteristics of CT-occult intracranial injuries on brain magnetic resonance imaging (MRI) scan in TBI patients with emergency department (ED) arrival Glasgow Coma Scale (GCS) score 13-15 and isolated tSAH on CT. The prospective, 18-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury Study (TRACK-TBI; enrollment years 2014-2019) enrolled participants who presented to the ED and received a clinically-indicated head CT within 24 h of TBI. A subset of TRACK-TBI participants underwent venipuncture within 24 h for plasma glial fibrillary acidic protein (GFAP) analysis, and research MRI at 2-weeks post-injury. In the current study, TRACK-TBI participants age ≥17 years with ED arrival GCS 13-15, isolated tSAH on initial head CT, plasma GFAP level, and 2-week MRI data were analyzed. In 57 participants, median age was 46.0 years [quartile 1 to 3 (Q1-Q3): 34-57] and 52.6% were male. At ED disposition, 12.3% were discharged home, 61.4% were admitted to hospital ward, and 26.3% to intensive care unit. MRI identified CT-occult traumatic intracranial lesions in 45.6% (26 of 57 participants; one additional lesion type: 31.6%; 2 additional lesion types: 14.0%); of these 26 participants with CT-occult intracranial lesions, 65.4% had axonal injury, 42.3% had subdural hematoma, and 23.1% had intracerebral contusion. GFAP levels were higher in participants with CT-occult MRI lesions compared with without (median: 630.6 pg/mL, Q1-Q3: [172.4-941.2] vs. 226.4 [105.8-436.1], p = 0.049), and were associated with axonal injury (no: median 226.7 pg/mL [109.6-435.1], yes: 828.6 pg/mL [204.0-1194.3], p = 0.009). Our results indicate that isolated tSAH on head CT is often not the sole intracranial traumatic injury in GCS 13-15 TBI. Forty-six percent of patients in our cohort (26 of 57 participants) had additional CT-occult traumatic lesions on MRI. Plasma GFAP may be an important biomarker for the identification of additional CT-occult injuries, including axonal injury. These findings should be interpreted cautiously given our small sample size and await validation from larger studies.

Performance of the IMPACT and CRASH prognostic models for traumatic brain injury in a contemporary multicenter cohort: a TRACK-TBI study.

OBJECTIVE: The International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) and Corticosteroid Randomization After Significant Head Injury (CRASH) prognostic models for mortality and outcome after traumatic brain injury (TBI) were developed using data from 1984 to 2004. This study examined IMPACT and CRASH model performances in a contemporary cohort of US patients. METHODS: The prospective 18-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study (enrollment years 2014-2018) enrolled subjects aged ≥ 17 years who presented to level I trauma centers and received head CT within 24 hours of TBI. Data were extracted from the subjects who met the model criteria (for IMPACT, Glasgow Coma Scale [GCS] score 3-12 with 6-month Glasgow Outcome Scale-Extended [GOSE] data [n = 441]; for CRASH, GCS score 3-14 with 2-week mortality data and 6-month GOSE data [n = 831]). Analyses were conducted in the overall cohort and stratified on the basis of TBI severity (severe/moderate/mild TBI defined as GCS score 3-8/9-12/13-14), age (17-64 years or ≥ 65 years), and the 5 top enrolling sites. Unfavorable outcome was defined as GOSE score 1-4. Original IMPACT and CRASH model coefficients were applied, and model performances were assessed by calibration (intercept [< 0 indicated overprediction; > 0 indicated underprediction] and slope) and discrimination (c-statistic). RESULTS: Overall, the IMPACT models overpredicted mortality (intercept -0.79 [95% CI -1.05 to -0.53], slope 1.37 [1.05-1.69]) and acceptably predicted unfavorable outcome (intercept 0.07 [-0.14 to 0.29], slope 1.19 [0.96-1.42]), with good discrimination (c-statistics 0.84 and 0.83, respectively). The CRASH models overpredicted mortality (intercept -1.06 [-1.36 to -0.75], slope 0.96 [0.79-1.14]) and unfavorable outcome (intercept -0.60 [-0.78 to -0.41], slope 1.20 [1.03-1.37]), with good discrimination (c-statistics 0.92 and 0.88, respectively). IMPACT overpredicted mortality and acceptably predicted unfavorable outcome in the severe and moderate TBI subgroups, with good discrimination (c-statistic ≥ 0.81). CRASH overpredicted mortality in the severe and moderate TBI subgroups and acceptably predicted mortality in the mild TBI subgroup, with good discrimination (c-statistic ≥ 0.86); unfavorable outcome was overpredicted in the severe and mild TBI subgroups with adequate discrimination (c-statistic ≥ 0.78), whereas calibration was nonlinear in the moderate TBI subgroup. In subjects ≥ 65 years of age, the models performed variably (IMPACT-mortality, intercept 0.28, slope 0.68, and c-statistic 0.68; CRASH-unfavorable outcome, intercept -0.97, slope 1.32, and c-statistic 0.88; nonlinear calibration for IMPACT-unfavorable outcome and CRASH-mortality). Model performance differences were observed across the top enrolling sites for mortality and unfavorable outcome. CONCLUSIONS: The IMPACT and CRASH models adequately discriminated mortality and unfavorable outcome. Observed overestimations of mortality and unfavorable outcome underscore the need to update prognostic models to incorporate contemporary changes in TBI management and case-mix. Investigations to elucidate the relationships between increased survival, outcome, treatment intensity, and site-specific practices will be relevant to improve models in specific TBI subpopulations (e.g., older adults), which may benefit from the inclusion of blood-based biomarkers, neuroimaging features, and treatment data.

Medicaid Insurance is a Predictor of Prolonged Hospital Length of Stay After Traumatic Brain Injury: A Stratified National Trauma Data Bank Cohort Analysis of 552 949 Patients.

BACKGROUND AND OBJECTIVES: Hospital length of stay (HLOS) is a metric of injury severity, resource utilization, and healthcare access. Recent evidence has shown an association between Medicaid insurance and increased HLOS after traumatic brain injury (TBI). This study aims to validate the association between Medicaid and prolonged HLOS after TBI using the National Trauma Data Bank. METHODS: National Trauma Data Bank Trauma Quality Programs Participant Use Files (2003-2021) were queried for adult patients with TBI using traumatic intracranial injury ICD-9/ICD-10 codes. Patients with complete HLOS, age, sex, race, insurance payor, Glasgow Coma Scale, Injury Severity Score, and discharge disposition data were included (N = 552 949). Analyses were stratified by TBI severity using Glasgow Coma Scale. HLOS was coded into Tiers according to percentiles within TBI severity categories (Tier 1: 1-74th; 2: 75-84th; 3: 85-94th; 4: 95-99th). Multivariable logistic regressions evaluated associations between insurance payor and prolonged (Tier 4) HLOS, controlling for sociodemographic, Injury Severity Score, cranial surgery, and discharge disposition variables. Adjusted odds ratios (aOR) and 95% CI were reported. RESULTS: HLOS Tiers consisted of 0-19, 20-27, 28-46, and ≥47 days (Tiers 1-4, respectively) in severe TBI (N = 103 081); 0-15, 16-21, 22-37, and ≥38 days in moderate TBI (N = 39 904); and 0-7, 8-10, 11-19, and ≥20 days in mild TBI (N = 409 964). Proportion of Medicaid patients increased with Tier ([Tier 1 vs Tier 4] severe: 16.0% vs 36.1%; moderate: 14.1% vs 31.6%; mild TBI: 10.2% vs 17.4%; all P < .001). On multivariable analyses, Medicaid was associated with prolonged HLOS (severe TBI: aOR = 2.35 [2.19-2.52]; moderate TBI: aOR = 2.30 [2.04-2.61]; mild TBI: aOR = 1.75 [1.67-1.83]; reference category: private/commercial). CONCLUSION: This study supports Medicaid as an independent predictor of prolonged HLOS across TBI severity strata. Reasons may include different efficacies in care delivery and reimbursement, which require further investigation. Our findings support the development of discharge coordination pathways and policies for Medicaid patients with TBI.

Dual-plasmonic Au@Cu7S4 yolk@shell nanocrystals for photocatalytic hydrogen production across visible to near infrared spectral region.

Near infrared energy remains untapped toward the maneuvering of entire solar spectrum harvesting for fulfilling the nuts and bolts of solar hydrogen production. We report the use of Au@Cu7S4 yolk@shell nanocrystals as dual-plasmonic photocatalysts to achieve remarkable hydrogen production under visible and near infrared illumination. Ultrafast spectroscopic data reveal the prevalence of long-lived charge separation states for Au@Cu7S4 under both visible and near infrared excitation. Combined with the advantageous features of yolk@shell nanostructures, Au@Cu7S4 achieves a peak quantum yield of 9.4% at 500 nm and a record-breaking quantum yield of 7.3% at 2200 nm for hydrogen production in the absence of additional co-catalysts. The design of a sustainable visible- and near infrared-responsive photocatalytic system is expected to inspire further widespread applications in solar fuel generation. In this work, the feasibility of exploiting the localized surface plasmon resonance property of self-doped, nonstoichiometric semiconductor nanocrystals for the realization of wide-spectrum-driven photocatalysis is highlighted.

The Impact of a Student-Led Health Education Clinic on the Health Literacy and Behaviors of a Rural Community in the State of Pennsylvania, USA.

Rural populations experience a number of disparities that place them at increased risk of morbidity and mortality related to chronic disease, including lower health literacy and greater distance to medical care. Community-based free healthcare education can offer targeted preventive care to these vulnerable populations; however, limited quantitative research exists measuring their impact, specifically on health literacy and likelihood for behavior change. To investigate this, a student-led health education clinic was held in January 2023 in the rural community of Lykens, Pennsylvania by the Student-run and Collaborative Outreach Program for Health Equity (SCOPE). Fifty-five pre- and post-clinic surveys using Likert-style questions measured the knowledge and likelihood of behavioral change for several preventive health topics, including hypertension, diabetes mellitus, cancer screenings, childhood vaccinations, skin cancer, mental health, addiction, and nutrition. From pre- to post-clinic, there was a significant increase in knowledge of hypertension (p = 0.023) and diabetes (p = 0.014), likelihood of attending cancer screenings (p = 0.038), and confidence in identifying cancerous moles (p = < 0.001). There was a non-significant increase in understanding of mental health and nutrition, and no change in understanding of addiction or childhood vaccinations. It is likely that the level of interaction in education provided and relevance of information to participants contributed to effective uptake of information. The results demonstrate an immediate impact on health literacy and likelihood of behavioral change for several important preventive health topics, and advocate for the use of student-run healthcare interventions in addressing the prevalence of chronic disease in rural communities.

Use of matrix-assisted laser desorption ionization time of flight (MALDI-TOF) to detect antibiotic resistance in bacteria: A scoping review.

OBJECTIVES: Matrix-assisted laser desorption ionization time of flight (MALDI-TOF) has revolutionized clinical microbiology laboratories, enabling the identification of microorganisms in minutes. Although this advancement has significantly enhanced patient care by providing early diagnosis, the use of MALDI-TOF for routine detection of antimicrobial resistance (AMR) remains an ongoing area of research. The purpose of this scoping review was to identify and summarize the existing literature on MALDI-TOF-based methodologies for detecting AMR. METHODS: The PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature databases were searched for articles published up to July 2023. Publications were carefully screened, and inclusion was based on their relevance to the topic and detailed explanations of the methodologies employed. RESULTS: We reviewed 49 articles and identified various MALDI-TOF-based approaches for detecting AMR that we grouped in 2 main categories: (1) bacterial growth detection following a brief incubation with antibiotics and (2) identification of specific mass spectral profiles associated with drug resistance. Recently, the use of machine learning algorithms has been explored to detect characteristic patterns associated with AMR. Thorough evaluation of each study's procedures was conducted to determine their potential for implementation in clinical laboratories. CONCLUSIONS: MALDI-TOF shows promise as a tool for AMR detection, but its readiness for wider clinical adoption relies on ongoing research, development of algorithms and software for automated interpretation of mass spectra, and validation efforts. Its role in routine clinical practice may evolve as technology and knowledge progress.

Laser Frequency Modulation and PM-to-AM Noise Conversion in Atomic Clocks.

Laser wavelength stability is a necessity in present-day chip-scale atomic clocks (CSACs), in next-generation atomic clocks planned for Global Navigation Satellite Systems (GNSSs), and in many other atomic devices that generate their signals with lasers. Routinely, this is accomplished by modulating the laser's frequency about an atomic or molecular resonance, which in turn induces modulated laser-light absorption. The modulated absorption then generates a correction signal that stabilizes the laser wavelength. However, in addition to creating absorption modulation for laser wavelength stabilization, the modulated laser frequency can produce a time-dependent variance in transmitted laser intensity noise because of laser phase-noise (PM) to transmitted laser intensity-noise (AM) conversion. Here, we show that the time-varying PM-to-AM conversion can have a significant influence on the short-term frequency stability of vapor-cell atomic clocks. If diode-laser enabled vapor-cell atomic clocks are to break into the [Formula: see text] frequency-stability range, the amplitude of laser frequency modulation for wavelength stabilization will need to be chosen judiciously.

Augmenting an electronic Ising machine to effectively solve boolean satisfiability.

With the slowdown of improvement in conventional von Neumann systems, increasing attention is paid to novel paradigms such as Ising machines. They have very different approach to solving combinatorial optimization problems. Ising machines have shown great potential in solving binary optimization problems like MaxCut. In this paper, we present an analysis of these systems in boolean satisfiability (SAT) problems. We demonstrate that, in the case of 3-SAT, a basic architecture fails to produce meaningful acceleration, largely due to the relentless progress made in conventional SAT solvers. Nevertheless, careful analysis attributes part of the failure to the lack of two important components: cubic interactions and efficient randomization heuristics. To overcome these limitations, we add proper architectural support for cubic interaction on a state-of-the-art Ising machine. More importantly, we propose a novel semantic-aware annealing schedule that makes the search-space navigation much more efficient than existing annealing heuristics. Using numerical simulations, we show that such an "Augmented" Ising Machine for SAT is projected to outperform state-of-the-art software-based, GPU-based and conventional hardware SAT solvers by orders of magnitude.

Vertebral Tortuosity Is Associated With Increased Rate of Cardiovascular Events in Vascular Ehlers-Danlos Syndrome.

Background Arterial tortuosity is associated with adverse events in Marfan and Loeys-Dietz syndromes but remains understudied in Vascular Ehlers-Danlos syndrome. Methods and Results Subjects with a pathogenic COL3A1 variant diagnosed at age <50 years were included from 2 institutions and the GenTAC Registry (National Registry of Genetically Triggered Thoracic Aortic Aneurysms and Cardiovascular Conditions). Height-adjusted vertebral artery tortuosity index (VTI-h) using magnetic resonance or computed tomography angiography was calculated. Associations between VTI-h and outcomes of (1) cardiovascular events (arterial dissection/rupture, aneurysm requiring intervention, stroke), or (2) hollow organ collapse/rupture at age <50 years were evaluated using receiver operator curve analysis (using outcome by age 30 years) and mixed-effects Poisson regression for incidence rate ratios. Of 65 subjects (54% male), median VTI-h was 12 (interquartile range, 8-16). Variants were missense in 46%, splice site in 31%, and null/gene deletion in 14%. Thirty-two subjects (49%) had 59 events, including 28 dissections, 5 arterial ruptures, 4 aneurysms requiring intervention, 4 strokes, 11 hollow organ ruptures, and 7 pneumothoraces. Receiver operator curve analysis suggested optimal discrimination at VTI-h ≥15.5 for cardiovascular events (sensitivity 70%, specificity 76%) and no association with noncardiovascular events (area under the curve, 0.49 [95% CI, 0.22-0.78]). By multivariable analysis, older age was associated with increased cardiovascular event rate while VTI-h ≥15.5 was not (incidence rate ratios, 1.79 [95% CI, 0.76-4.24], P=0.185). However, VTI-h ≥15.5 was associated with events among those with high-risk variants <40 years (incidence rate ratios, 4.14 [95% CI, 1.13-15.10], P=0.032), suggesting effect modification by genotype and age. Conclusions Increased arterial tortuosity is associated with a higher incidence rate of cardiovascular events in Vascular Ehlers-Danlos syndrome. Vertebral tortuosity index may be a useful biomarker for prognosis when evaluated in conjunction with genotype and age.

Longitudinal Recovery Following Repetitive Traumatic Brain Injury.

Importance: One traumatic brain injury (TBI) increases the risk of subsequent TBIs. Research on longitudinal outcomes of civilian repetitive TBIs is limited. Objective: To investigate associations between sustaining 1 or more TBIs (ie, postindex TBIs) after study enrollment (ie, index TBIs) and multidimensional outcomes at 1 year and 3 to 7 years. Design, Setting, and Participants: This cohort study included participants presenting to emergency departments enrolled within 24 hours of TBI in the prospective, 18-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study (enrollment years, February 2014 to July 2020). Participants who completed outcome assessments at 1 year and 3 to 7 years were included. Data were analyzed from September 2022 to August 2023. Exposures: Postindex TBI(s). Main Outcomes and Measures: Demographic and clinical factors, prior TBI (ie, preindex TBI), and functional (Glasgow Outcome Scale-Extended [GOSE]), postconcussive (Rivermead Post-Concussion Symptoms Questionnaire [RPQ]), psychological distress (Brief Symptom Inventory-18 [BSI-18]), depressive (Patient Health Questionnaire-9 [PHQ-9]), posttraumatic stress disorder (PTSD; PTSD Checklist for DSM-5 [PCL-5]), and health-related quality-of-life (Quality of Life After Brain Injury-Overall Scale [QOLIBRI-OS]) outcomes were assessed. Adjusted mean differences (aMDs) and adjusted relative risks are reported with 95% CIs. Results: Of 2417 TRACK-TBI participants, 1572 completed the outcomes assessment at 1 year (1049 [66.7%] male; mean [SD] age, 41.6 [17.5] years) and 1084 completed the outcomes assessment at 3 to 7 years (714 [65.9%] male; mean [SD] age, 40.6 [17.0] years). At 1 year, a total of 60 participants (4%) were Asian, 255 (16%) were Black, 1213 (77%) were White, 39 (2%) were another race, and 5 (0.3%) had unknown race. At 3 to 7 years, 39 (4%) were Asian, 149 (14%) were Black, 868 (80%) were White, 26 (2%) had another race, and 2 (0.2%) had unknown race. A total of 50 (3.2%) and 132 (12.2%) reported 1 or more postindex TBIs at 1 year and 3 to 7 years, respectively. Risk factors for postindex TBI were psychiatric history, preindex TBI, and extracranial injury severity. At 1 year, compared with those without postindex TBI, participants with postindex TBI had worse functional recovery (GOSE score of 8: adjusted relative risk, 0.57; 95% CI, 0.34-0.96) and health-related quality of life (QOLIBRI-OS: aMD, -15.9; 95% CI, -22.6 to -9.1), and greater postconcussive symptoms (RPQ: aMD, 8.1; 95% CI, 4.2-11.9), psychological distress symptoms (BSI-18: aMD, 5.3; 95% CI, 2.1-8.6), depression symptoms (PHQ-9: aMD, 3.0; 95% CI, 1.5-4.4), and PTSD symptoms (PCL-5: aMD, 7.8; 95% CI, 3.2-12.4). At 3 to 7 years, these associations remained statistically significant. Multiple (2 or more) postindex TBIs were associated with poorer outcomes across all domains. Conclusions and Relevance: In this cohort study of patients with acute TBI, postindex TBI was associated with worse symptomatology across outcome domains at 1 year and 3 to 7 years postinjury, and there was a dose-dependent response with multiple postindex TBIs. These results underscore the critical need to provide TBI prevention, education, counseling, and follow-up care to at-risk patients.

Mitochondrial DNA copy number in adults with and without Type 1 diabetes.

AIMS: Mitochondrial damage is implicated in diabetes pathogenesis and complications. Mitochondrial DNA copy number (mtDNA-cn) in human Type 1 diabetes (T1D) studies are lacking. We related mtDNA-cn in T1D and non-diabetic adults (CON) with diabetes complications and risk factors. METHODS: Cross-sectional study: 178 T1D, 132 non-diabetic controls. Associations of whole blood mtDNA-cn (qPCR) with complications, inflammation, and C-peptide. RESULTS: mtDNA-cn (median (LQ, UQ)) was lower in: T1D vs. CON (271 (189, 348) vs. 320 (264, 410); p < 0.0001); T1D with vs. without kidney disease (238 (180, 309) vs. 294 (198, 364); p = 0.02); and insulin injection vs. pump-users (251 (180, 340) vs. 322 (263, 406); p = 0.008). Significant univariate correlates of mtDNA-cn: T1D: (positive) HDL-C; (negative) fasting glucose, white cell count (WCC), sVCAM-1, sICAM-1; CON: (negative) WHR (waist-hip-ratio). Detectable C-peptide in T1D increased with lowest-highest mtDNA-cn tertiles (54%, 69%, 79%, p = 0.02). Independent determinants of mtDNA-cn: T1D: (positive) HDL-C; (negative) age, sICAM-1; AUROC 0.71; CON: WCC (negative), never smoking, (positive) female, pulse pressure; AUROC 0.74. CONCLUSIONS: mtDNA-cn is lower in T1D vs. CON, and in T1D kidney disease. In T1D, mtDNA-cn correlates inversely with age and inflammation, and positively with HDL-C, detectable C-peptide and pump use. Further clinical and basic science studies are merited.

GTM-decon: guided-topic modeling of single-cell transcriptomes enables sub-cell-type and disease-subtype deconvolution of bulk transcriptomes.

Cell-type composition is an important indicator of health. We present Guided Topic Model for deconvolution (GTM-decon) to automatically infer cell-type-specific gene topic distributions from single-cell RNA-seq data for deconvolving bulk transcriptomes. GTM-decon performs competitively on deconvolving simulated and real bulk data compared with the state-of-the-art methods. Moreover, as demonstrated in deconvolving disease transcriptomes, GTM-decon can infer multiple cell-type-specific gene topic distributions per cell type, which captures sub-cell-type variations. GTM-decon can also use phenotype labels from single-cell or bulk data to infer phenotype-specific gene distributions. In a nested-guided design, GTM-decon identified cell-type-specific differentially expressed genes from bulk breast cancer transcriptomes.

Airway soluble CSF1R predicts progression in patients with idiopathic pulmonary fibrosis.

This study provides the first evidence for a role of airway sCSF1R in IPF https://bit.ly/3KTBrCA.

Socioeconomic and clinical factors associated with prolonged hospital length of stay after traumatic brain injury.

BACKGROUND: Hospital length of stay (HLOS) after traumatic brain injury (TBI) is a metric of injury severity, resource utilization, and access to services. This study aimed to evaluate socioeconomic and clinical factors associated with prolonged HLOS after TBI. METHODS: Retrospective data from adult hospitalized patients diagnosed with acute TBI at a US Level 1 trauma center between August 1, 2019 - April 1, 2022 were extracted from the electronic health record. HLOS was stratified by Tier (1: 1-74th percentile; 2: 75-84th; 3: 85-94th; 4: 95-99th). Demographic, socioeconomic, injury severity, and level-of-care factors were compared by HLOS. Multivariable logistic regressions evaluated associations between socioeconomic and clinical variables and prolonged HLOS, using multivariable odds ratios (mOR) and [95% confidence intervals]. Estimated daily charges were calculated for a subset of medically-stable inpatients awaiting placement. Statistical significance was assessed at p < 0.05. RESULTS: In 1443 patients, median HLOS was 4 days (interquartile range 2-8; range 0-145). HLOS Tiers were 0-7, 8-13, 14-27, and ≥28 days (Tiers 1-4, respectively). Patients with Tier 4 HLOS differed significantly from others, with increased Medicaid insurance (53.4% vs. 30.3-33.1%, p = 0.003), severe TBI (Glasgow Coma Scale 3-8: 38.4% vs. 8.7-18.2%, p < 0.001), younger age (mean 52.3-years vs. 61.1-63.7-years, p = 0.003), low socioeconomic status (53.4% vs. 32.0-33.9%, p = 0.003), and need for post-acute care (60.3% vs. 11.2-39.7%, p < 0.001). Independent factors associated with prolonged (Tier 4) HLOS were Medicaid (mOR = 1.99 [1.08-3.68], vs. Medicare/commercial), moderate and severe TBI (mOR = 3.48 [1.61-7.56]; mOR = 4.43 [2.18-8.99], respectively, vs. mild TBI), and need for post-acute placement (mOR = 10.68 [5.74-19.89], while age was protective (per-year mOR = 0.98 [0.97-0.99]). Estimated daily charges for a medically-stable inpatient was $17126. CONCLUSIONS: Medicaid insurance, moderate/severe TBI, and need for post-acute care were independently associated with prolonged HLOS ≥28 days. Medically-stable inpatients awaiting placement accrue immense daily healthcare costs. At-risk patients should be identified early, receive care transitions resources, and be prioritized for discharge coordination pathways.

Experimental Revelation of Surface and Bulk Lattices in Faceted Cu2 O Crystals.

Semiconductor crystals have generally shown facet-dependent electrical, photocatalytic, and optical properties. These phenomena have been proposed to result from the presence of a surface layer with bond-level deviations. To provide experimental evidence of this structural feature, synchrotron X-ray sources are used to obtain X-ray diffraction (XRD) patterns of polyhedral cuprous oxide crystals. Cu2 O rhombic dodecahedra display two distinct cell constants from peak splitting. Peak disappearance during slow Cu2 O reduction to Cu with ammonia borane differentiates bulk and surface layer lattices. Cubes and octahedra also show two peak components, while diffraction peaks of cuboctahedra are comprised of three components. Temperature-varying lattice changes in the bulk and surface regions also show shape dependence. From transmission electron microscopy (TEM) images, slight plane spacing deviations in surface and inner crystal regions are measured. Image processing provides visualization of the surface layer with depths of about 1.5-4 nm giving dashed lattice points instead of dots from atomic position deviations. Close TEM examination reveals considerable variation in lattice spot size and shape for different particle morphologies, explaining why facet-dependent properties are emerged. Raman spectrum reflects the large bulk and surface lattice difference in rhombic dodecahedra. Surface lattice difference can change the particle bandgap.

Effectiveness of Thoracic Wall Blocks in Video-Assisted Thoracoscopic Surgery, a Network Meta-Analysis.

Introduction: Thoracic epidural analgesia (TEA) and thoracic paravertebral blocks (PVB) are well-established techniques for pain management in thoracotomy. Here, we examine the efficacy of various thoracic fascial plane blocks vs TEA and PVB for intraoperative and postoperative analgesia for video assisted thoracoscopy surgery (VATS) with network meta-analysis. Methods: A search for prospective randomized control studies using adult patients undergoing VATS with general anesthesia. The interventions of interest were any regional anesthesia techniques used for postoperative pain control after VATS. Primary outcomes of interest were 24-hour opioid requirement and 24-hour pain scores. A Bayesian network meta-analysis was conducted. Results: We identified 42 studies that fulfilled our inclusion criteria. For patients who underwent VATS, TEA (MD = -27MME, 95% CI = -46.2 to -9MME), ESP (MD = -20MME, 95% CI -33 to -7.9MME), PVB (MD = -15MME, 95% CI = -26 to -4.5MME) demonstrated significant opioid sparing efficacy, as well as reduction in cumulative 24-hour static pain scores. However, exclusion of one study due to high risk of bias revealed that TEA did not significantly reduce opioid consumption, nor did it reduce the incidence of PONV, pulmonary complications, or LOS when compared to ESP, SAP, PVB, ICN, or PECS blocks. Conclusion: Our findings suggest that TEA did not provide superior pain relief compared to ESP, SAP, PVB, ICN, or PECS blocks following VATS. Therefore, we propose ESP as a suitable intervention for the prevention of postoperative pain after VATS.