Clinically Stable COVID-19 Patients Presenting to Acute Unscheduled Episodic Care Venues Have Increased Risk of Hospitalization: Secondary Analysis of a Randomized Control Trial

BACKGROUND: Assessment for risks associated with acute stable COVID-19 is important to optimize clinical trial enrollment and target patients for scarce therapeutics. To assess whether healthcare system engagement location is an independent predictor of outcomes we performed a secondary analysis of the ACTIV-4B Outpatient Thrombosis Prevention trial. METHODS: A secondary analysis of the ACTIV-4B trial that was conducted at 52 US sites between September 2020 and August 2021. Participants were enrolled through acute unscheduled episodic care (AUEC) enrollment location (emergency department, or urgent care clinic visit) compared to minimal contact (MC) enrollment (electronic contact from test center lists of positive patients).We report the primary composite outcome of cardiopulmonary hospitalizations, symptomatic venous thromboembolism, myocardial infarction, stroke, transient ischemic attack, systemic arterial thromboembolism, or death among stable outpatients stratified by enrollment setting, AUEC versus MC. A propensity score for AUEC enrollment was created, and Cox proportional hazards regression with inverse probability weighting (IPW) was used to compare the primary outcome by enrollment location. RESULTS: Among the 657 ACTIV-4B patients randomized, 533 (81.1%) with known enrollment setting data were included in this analysis, 227 from AUEC settings and 306 from MC settings. In a multivariate logistic regression model, time from COVID test, age, Black race, Hispanic ethnicity, and body mass index were associated with AUEC enrollment. Irrespective of trial treatment allocation, patients enrolled at an AUEC setting were 10-times more likely to suffer from the adjudicated primary outcome, 7.9% vs. 0.7%; p \u3c 0.001, compared with patients enrolled at a MC setting. Upon Cox regression analysis adjustment patients enrolled at an AUEC setting remained at significant risk of the primary composite outcome, HR 3.40 (95% CI 1.46, 7.94). CONCLUSIONS: Patients with clinically stable COVID-19 presenting to an AUEC enrollment setting represent a population at increased risk of arterial and venous thrombosis complications, hospitalization for cardiopulmonary events, or death, when adjusted for other risk factors, compared with patients enrolled at a MC setting. Future outpatient therapeutic trials and clinical therapeutic delivery programs of clinically stable COVID-19 patients may focus on inclusion of higher-risk patient populations from AUEC engagement locations

Accumulation of Anthocyanidins Determines Leaf Color of Liquidambar Formosana as Revealed by Transcriptome Sequencing and Metabolism Analysis

Liquidambar formosana is important for its ornamental value in China; it is increasingly used for landscaping and gardening trees due to its diverse leaf colors and seasonal changes. Varieties including either a fixed leaf color, the purplish ‘Fuluzifeng’ (ZF), or seasonal changes in leaf color, the reddish ‘Nanlinhong’ (NLH) have been bred and registered as new plant varieties under the International Union for the Protection of New Plant Varieties (UPOV) system. To gain practical insights into the anthocyanin biosynthetic process, transcriptome sequencing (Illumina) was performed to clarify the metabolic pathways present in the three seasonal changes in leaf colors in NLH and in the springtime purple-red color of ZF. qRT-PCR was used to verify the speculation. Based on the differentially expressed genes and flavonoids analyses, the spring, summer, and autumn leaves of NLH were compared to study the seasonal differences. NLH and ZF were compared to study the formation mechanism of the two leaf colors in spring. Transcriptome sequencing produced a total of 121,216 unigenes from all samples, where 48 unigenes were differentially expressed and associated with the anthocyanidin pathway. The expression levels of LfDFR and LfANS genes corresponded to the accumulation of concentrations of cyanidins in spring (NLHC) and autumn leaves (NLHQ), respectively, with different shades of red. Moreover, the LfF3′5′H gene corresponded to the accumulation of flavonols and delphinidins in purple-red leaves (ZFC). Cyanidin and peonidin were the key pigments in red and dark-red leaves, and purple-red leaves were co-pigmented by cyanidins, pelargonidins, and delphinidins

Structural Study of the Thermoelectric Work Units Encapsulated with Cement Paste for Building Energy Harvesting

Cement-based material encapsulation is a method of encapsulating electronic devices in highly thermally conductive cement-based materials to improve the heat dissipation performance of electronic components. In the field of construction, a thermoelectric generator (TEG) encapsulated with cement-based materials used in the building envelope has significant potential for waste heat energy recovery. The purpose of this study was to investigate the effect of cement-based materials integrated with aluminum heatsinks on the heat dissipation of the TEG composite structure. In this work, three types of thermoelectric work units encapsulated with cement paste were proposed. Moreover, we explored the effect of encapsulated structure, heat dissipation area, the height of thermoelectric single leg, and heat input temperature on maintaining the temperature difference between the two sides of the thermoelectric single leg with COMSOL Multiphysics. The numerical simulation results showed that under the conditions of a heat source temperature of 313.15 K and ambient temperature of 298.15 K, the temperature difference between the two sides of the internal thermoelectric single leg of Type-III can maintain a stable temperature difference of 7.77 K, which is 32.14% higher than that of Type-I and Type-II (5.88 K), and increased by 26.82% in the actual experiment. This work provides a reference for the selection and application of TEG composite structures of cement-based materials combined with aluminum heatsinks

RumorLLM: A Rumor Large Language Model-Based Fake-News-Detection Data-Augmentation Approach

With the rapid development of the Internet and social media, false information, rumors, and misleading content have become pervasive, posing significant threats to public opinion and social stability, and even causing serious societal harm. This paper introduces a novel solution to address the challenges of fake news detection, presenting the “Rumor Large Language Models” (RumorLLM), a large language model finetuned with rumor writing styles and content. The key contributions include the development of RumorLLM and a data-augmentation method for small categories, effectively mitigating the issue of category imbalance in real-world fake-news datasets. Experimental results on the BuzzFeed and PolitiFact datasets demonstrate the superiority of the proposed model over baseline methods, particularly in F1 score and AUC-ROC. The model’s robust performance highlights its effectiveness in handling imbalanced datasets and provides a promising solution to the pressing issue of false-information proliferation

Clinically stable covid-19 patients presenting to acute unscheduled episodic care venues have increased risk of hospitalization: secondary analysis of a randomized control trial

Abstract Background Assessment for risks associated with acute stable COVID-19 is important to optimize clinical trial enrollment and target patients for scarce therapeutics. To assess whether healthcare system engagement location is an independent predictor of outcomes we performed a secondary analysis of the ACTIV-4B Outpatient Thrombosis Prevention trial. Methods A secondary analysis of the ACTIV-4B trial that was conducted at 52 US sites between September 2020 and August 2021. Participants were enrolled through acute unscheduled episodic care (AUEC) enrollment location (emergency department, or urgent care clinic visit) compared to minimal contact (MC) enrollment (electronic contact from test center lists of positive patients).We report the primary composite outcome of cardiopulmonary hospitalizations, symptomatic venous thromboembolism, myocardial infarction, stroke, transient ischemic attack, systemic arterial thromboembolism, or death among stable outpatients stratified by enrollment setting, AUEC versus MC. A propensity score for AUEC enrollment was created, and Cox proportional hazards regression with inverse probability weighting (IPW) was used to compare the primary outcome by enrollment location. Results Among the 657 ACTIV-4B patients randomized, 533 (81.1%) with known enrollment setting data were included in this analysis, 227 from AUEC settings and 306 from MC settings. In a multivariate logistic regression model, time from COVID test, age, Black race, Hispanic ethnicity, and body mass index were associated with AUEC enrollment. Irrespective of trial treatment allocation, patients enrolled at an AUEC setting were 10-times more likely to suffer from the adjudicated primary outcome, 7.9% vs. 0.7%; p < 0.001, compared with patients enrolled at a MC setting. Upon Cox regression analysis adjustment patients enrolled at an AUEC setting remained at significant risk of the primary composite outcome, HR 3.40 (95% CI 1.46, 7.94). Conclusions Patients with clinically stable COVID-19 presenting to an AUEC enrollment setting represent a population at increased risk of arterial and venous thrombosis complications, hospitalization for cardiopulmonary events, or death, when adjusted for other risk factors, compared with patients enrolled at a MC setting. Future outpatient therapeutic trials and clinical therapeutic delivery programs of clinically stable COVID-19 patients may focus on inclusion of higher-risk patient populations from AUEC engagement locations. Trial Registration ClinicalTrials.gov Identifier: NCT04498273

Quantitative Observation of Threshold Defect Behavior in Memristive Devices with <i>Operando</i> X‑ray Microscopy

Memristive devices are an emerging technology that enables both rich interdisciplinary science and novel device functionalities, such as nonvolatile memories and nanoionics-based synaptic electronics. Recent work has shown that the reproducibility and variability of the devices depend sensitively on the defect structures created during electroforming as well as their continued evolution under dynamic electric fields. However, a fundamental principle guiding the material design of defect structures is still lacking due to the difficulty in understanding dynamic defect behavior under different resistance states. Here, we unravel the existence of threshold behavior by studying model, single-crystal devices: resistive switching requires that the pristine oxygen vacancy concentration reside near a critical value. Theoretical calculations show that the threshold oxygen vacancy concentration lies at the boundary for both electronic and atomic phase transitions. Through <i>operando</i>, multimodal X-ray imaging, we show that field tuning of the local oxygen vacancy concentration below or above the threshold value is responsible for switching between different electrical states. These results provide a general strategy for designing functional defect structures around threshold concentrations to create dynamic, field-controlled phases for memristive devices

Folding Simulations of a De Novo Designed Protein with a βαβ Fold

βαβ structural motifs are commonly used building blocks in protein structures containing parallel β-sheets. However, to our knowledge, no stand-alone βαβ structure has been observed in nature to date. Recently, for the first time that we know of, a small protein with an independent βαβ structure (DS119) was successfully designed in our laboratory. To understand the folding mechanism of DS119, in the study described here, we carried out all-atom molecular dynamics and coarse-grained simulations to investigate its folding pathways and energy landscape. From all-atom simulations, we successfully observed the folding event and got a stable folded structure with a minimal root mean-square deviation of 2.6 Å with respect to the NMR structure. The folding process can be described as a fast collapse phase followed by rapid formation of the central helix, and then slow formation of a parallel β-sheet. By using a native-centric Gō-like model, the cooperativity of the system was characterized in terms of the calorimetric criterion, sigmoidal transitions, conformation distribution shifts, and free-energy profiles. DS119 was found to be an incipient downhill folder that folds more cooperatively than a downhill folder, but less cooperatively than a two-state folder. This may reflect the balance between the two structural elements of DS119: the rapidly formed α-helix and the slowly formed parallel β-sheet. Folding times estimated from both the all-atom simulations and the coarse-grained model were at microsecond level, making DS119 another fast folder. Compared to fast folders reported previously, DS119 is, to the best of our knowledge, the first that exhibits a parallel β-sheet