p­Phenylenediamine antioxidants in PM2.5: New markers for traffic in positive matrix factorization source apportionment.

The extensive utilization of rubber-related products can lead to a substantial release of p-phenylenediamine (PPD) antioxidants into the environment. In recent years, studies mainly focus on the pollution characteristics and health risks of PM2.5-bound PPDs. This study presents long-time scale data of PPDs and N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6PPD-Q) in PM2.5 and proposes the innovative use of PPDs as new markers for vehicular emissions in the Positive Matrix Factorization (PMF) source apportionment. The results indicate that PPDs and 6PPD-Q were detectable in 100 % of the winter PM2.5 samples, and the concentration ranges of PPDs and 6PPD-Q are 15.6-2.92 × 103 pg·m-3 and 3.90-27.4 pg·m-3, respectively, in which 6PPD and DNPD are the main compounds. Moreover, a competitive formation mechanism between sulfate, nitrate, ammonium (SNA) and 6PPD-Q was observed. The source apportionment results show that the incorporation of PPDs in PMF reduced the contribution of traffic source to PM2.5 from 13.5 % to 9.5 %. In the traffic source factor profiles, the load of IPPD, CPPD, DPPD, DNPD and 6PPD reaches 91.8 %, 91.6 %, 92.9 %, 80.6 % and 87.2 %, respectively. It`s amazing that traditional markers of traffic source, which often overlap with coal burning and industrial sources, over-estimated the contribution of vehicles by one third or more. The discovery of PPDs as specific markers for vehicular emissions holds significant utility, particularly considering the growing proportion of new energy vehicles in the future. The results may prove more accurate policy implications for pollution control. SYNOPSIS: PPDs are excellent indicators of vehicle emissions, and PMF without PPDs over-estimated the contribution of traffic source to PM2.5.

Subminimum Inhibitory Concentrations Tetracycline Antibiotics Induce Biofilm Formation in Minocycline-Resistant Klebsiella pneumonia by Affecting Bacterial Physical and Chemical Properties and Associated Genes Expression.

Biofilm formation of Klebsiella pneumoniae can protect bacteria from antibiotics and is difficult to eradicate. Thus, the influence of subinhibitory concentrations of antibiotics on bacteria is becoming increasingly important. Our study showed that subminimum inhibitory concentrations (sub-MICs) of tetracycline antibiotics can increase biofilm formation in minocycline-resistant Klebsiella pneumoniae clinical strains. However, in the bacterial adhesion and invasion experiments, the adhesion and invasion ability decreased and the survival rate of Galleria mellonella increased. Under sub-MICs of tetracycline antibiotics treatment, abnormal stretching of bacteria was observed by scanning electron microscopy. Treatment with sub-MICs of tetracyclines leads to increased surface hydrophobicity and eDNA content and decreased outer membrane permeability. The expression levels of the fimA, luxS, qseB, and qseC genes decreased, the expression level of mrkA increased, and the expression level of acrA was inconsistent under different tetracycline antibiotics treatments. Together, our results suggested that the increase in Klebsiella pneumoniae biofilm formation caused by sub-MICs of tetracycline antibiotics may occur by affecting bacterial physical and chemical properties and associated genes expression.

Role of Emerin in regulating fibroblast differentiation and migration at the substrate of stiffness coupled topology.

In hypertrophic scars, the differentiation and migration of fibroblasts are influenced by the extracellular matrix microenvironment, which includes factors such as stiffness, restraint, and tensile force. These mechanical stresses incite alterations in cell behavior, accompanied by cytoskeletal protein reorganization. However, the role of nucleo-skeletal proteins in this context remains underexplored. In this study, we use a polyacrylamide hydrogel (PAA) to simulate the mechanical stress experienced by cells in scar tissue and investigate the impact of Emerin on cell behavior. We utilize atomic force microscopy (AFM) and RNA interference technology to analyze cell differentiation, migration, and stiffness. Our findings reveal that rigid substrates and cellular restriction elevate Emerin expression and diminish differentiation. Conversely, reducing Emerin expression leads to attenuated cell differentiation, where stiffness and constraining factors exert no notable influence. Furthermore, a softening of cells and an enhanced migration rate are also markedly observed. These observations indicate that variations in nuclear skeletal proteins, prompted by diverse matrix microenvironments, play a pivotal role in the pathogenesis of hypertrophic scars (HSs). This research offers novel insights and a reference point for understanding scar fibrosis formation mechanisms and preventing fibrosis.

Spray vaccination with a Newcastle disease virus (NDV)-vectored infectious laryngotracheitis (ILT) vaccine protects commercial chickens from ILT in the presence of maternally-derived antibodies.

Infectious laryngotracheitis (ILT) poses a significant threat to the poultry industry, and vaccines play an important role in protection. However, due to the increasing scale of poultry production, there is an urgent need to develop vaccines that are suitable for convenient immunization methods such as spraying. Previous studies have shown that Newcastle disease virus (NDV)-ILT vaccines administered via intranasal and intraocular routes to commercial chickens carrying maternally-derived antibodies (MDAs) are still protective against ILT. In this study, a recombinant NDV (rNDV) was generated to express infectious laryngotracheitis virus (ILTV) glycoprotein B (gB), named rLS-gB, based on a full-length cDNA clone of the LaSota strain. The protective effect of different doses of rLS-gB administered by spray vaccination to commercial chickens at 1 d of age (doa) was evaluated. The chickens were exposed to 160-µm aerosol particles for 10 min for spray vaccination, and no adverse reactions were observed after vaccination. Despite the presence of anti-NDV MDAs and anti-ILTV MDAs in chickens, the ILTV- and NDV-specific antibody titres were significantly greater in the vaccinated groups than in the unvaccinated group. After challenge with a virulent ILTV strain, no clinical signs were observed in the 107 EID50/ml group compared to the other groups. Furthermore, vaccination with 107 EID50/ml rLS-gB significantly reduced the ILTV viral load and ameliorated gross and microscopic lesions in the trachea of chickens. Overall, these results suggested that rLS-gB is a safe and efficient candidate spray vaccine for ILT and is especially suitable for scaled chicken farms.

Blood Urine Nitrogen Trajectories of Acute Pancreatitis Patients in Intensive Care Units.

Objective: To identify subclasses of acute pancreatitis (AP) patients in the intensive care unit (ICU) by analyzing blood urea nitrogen (BUN) trajectories. Methods: AP patients in West China Hospital System (development cohort) and three public databases in the United States (validation cohort) were included. Latent class trajectory modelling was used to identify subclasses based on BUN trajectories within the first 21 days after ICU admission. Clinical characteristics and outcomes were compared, and results were externally validated. Results: The study comprised 2971 and 930 patients in the development and validation cohorts, respectively, with five subclasses: Class 1 ("Moderate-azotemia, slow decreasing"), Class 2 ("Non-azotemia"), Class 3 ("Severe-azotemia, slow decreasing"), Class 4 ("Moderate-azotemia, rapid increasing"), and Class 5 ('Moderate-azotemia, slow increasing) identified. Azotemia patients showed significantly higher 30-day mortality risk in development and validation cohorts. Specifically, Class 4 patients exhibited notably highest mortality risk in both the development cohort (HR 5.32, 95% CI 2.62-10.82) and validation cohort (HR 6.23, 95% CI 2.93-13.22). Regarding clinical characteristics, AP patients in Class 4 showed lower mean arterial pressure and a higher proportion of renal disease. We also created an online early classification model to further identify Class 4 patients among all patients with moderate azotemia at baseline. Conclusion: This multinational study uncovers heterogeneity in BUN trajectories among AP patients. Patients with "Moderate-azotemia, rapid increasing" trajectory, had a higher mortality risk than patients with severe azotemia at baseline. This finding complements studies that solely rely on baseline BUN for risk stratification and enhanced our understanding of longitudinal progression of AP.

Association between modified frailty index and postoperative delirium in patients after cardiac surgery: A cohort study of 2080 older adults.

AIM: To evaluate the association between frailty and postoperative delirium (POD) in elderly cardiac surgery patients. METHODS: A retrospective study was conducted of older patients admitted to the intensive care unit after cardiac surgery at a tertiary academic medical center in Boston from 2008 to 2019. Frailty was measured using the Modified Frailty Index (MFI), which categorized patients into frail (MFI ≥3) and non-frail (MFI = 0-2) groups. Delirium was identified using the confusion assessment method for the intensive care unit and nursing notes. Logistic regression models were used to examine the association between frailty and POD, and odds ratios (OR) with 95% confidence intervals (CI) were calculated. RESULTS: Of the 2080 patients included (median age approximately 74 years, 30.9% female), 614 were frail and 1466 were non-frail. The incidence of delirium was significantly higher in the frail group (29.2% vs. 16.4%, p < 0.05). After adjustment for age, sex, race, marital status, Acute Physiology Score III (APSIII), sequential organ failure assessment (SOFA), albumin, creatinine, hemoglobin, white blood cell count, type of surgery, alcohol use, smoking, cerebrovascular disease, use of benzodiazepines, and mechanical ventilation, multivariate logistic regression indicated a significantly increased risk of delirium in frail patients (adjusted OR: 1.61, 95% CI: 1.23-2.10, p < 0.001, E-value: 1.85). CONCLUSIONS: Frailty is an independent risk factor for POD in older patients after cardiac surgery. Further research should focus on frailty assessment and tailored interventions to improve outcomes.

Plasmonic Bound States in the Continuum Metasurface-Semiconductor-Metal Architecture Enables Efficient Hot-Electron-Based Photodetector.

Plasmonic hot-electron-based photodetectors (HEB-PDs) have received widespread attention for their ability to realize effective carrier collection under sub-bandgap illumination. However, due to the low hot electron emission probability, most of the existing HEB-PDs exhibit poor responsivity, which significantly restricts their practical applications. Here, by employing the binary-pore anodic alumina oxide template technique, we proposed a compact plasmonic bound state in continuum metasurface-semiconductor-metal-based (BIC M-S-M) HEB-PD. The symmetry-protected BIC can manipulate a strong gap surface plasmon in the stacked M-S-M structure, which effectively enhances light-matter interactions and improves the photoresponse of the integrated device. Notably, the optimal M-S-M HEB-PD with near-unit absorption (∼90%) around 800 nm delivers a responsivity of 5.18 A/W and an IPCE of 824.23% under 780 nm normal incidence (1 V external bias). Moreover, the ultrathin feature of BIC M-S-M (∼150 nm) on the flexible substrate demonstrates excellent stability under a wide range of illumination angles from -40° to 40° and at the curvature surface from 0.05 to 0.13 mm-1. The proposed plasmonic BIC strategy is very promising for many other hot-electron-related fields, such as photocatalysis, biosensing, imaging, and so on.

LiveLattice: Real-time visualization of tilted light-sheet microscopy data using a memory-efficient transformation algorithm.

Light-sheet fluorescence microscopy (LSFM), a prominent fluorescence microscopy technique, offers enhanced temporal resolution for imaging biological samples in four dimensions (4D; x, y, z, time). Some of the most recent implementations, including inverted selective plane illumination microscopy (iSPIM) and lattice light-sheet microscopy (LLSM), rely on a tilting of the sample plane with respect to the light sheet of 30-45 degrees to ease sample preparation. Data from such tilted-sample-plane LSFMs require subsequent deskewing and rotation for proper visualization and analysis. Such transformations currently demand substantial memory allocation. This poses computational challenges, especially with large datasets. The consequence is long processing times compared to data acquisition times, which currently limits the ability for live-viewing the data as it is being captured by the microscope. To enable the fast preprocessing of large light-sheet microscopy datasets without significant hardware demand, we have developed WH-Transform, a novel GPU-accelerated memory-efficient algorithm that integrates deskewing and rotation into a single transformation, significantly reducing memory requirements and reducing the preprocessing run time by at least 10-fold for large image stacks. Benchmarked against conventional methods and existing software, our approach demonstrates linear scalability. Processing large 3D stacks of up to 15 GB is now possible within one minute using a single GPU with 24 GB of memory. Applied to 4D LLSM datasets of human hepatocytes, human lung organoid tissue, and human brain organoid tissue, our method outperforms alternatives, providing rapid, accurate preprocessing within seconds. Importantly, such processing speeds now allow visualization of the raw microscope data stream in real time, significantly improving the usability of LLSM in biology. In summary, this advancement holds transformative potential for light-sheet microscopy, enabling real-time, on-the-fly data processing, visualization, and analysis on standard workstations, thereby revolutionizing biological imaging applications for LLSM, SPIM and similar light microscopes.

A Deep Learning Approach to Predict Recanalization First-Pass Effect following Mechanical Thrombectomy in Patients with Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Following endovascular thrombectomy in patients with large-vessel occlusion stroke, successful recanalization from 1 attempt, known as the first-pass effect, has correlated favorably with long-term outcomes. Pretreatment imaging may contain information that can be used to predict the first-pass effect. Recently, applications of machine learning models have shown promising results in predicting recanalization outcomes, albeit requiring manual segmentation. In this study, we sought to construct completely automated methods using deep learning to predict the first-pass effect from pretreatment CT and MR imaging. MATERIALS AND METHODS: Our models were developed and evaluated using a cohort of 326 patients who underwent endovascular thrombectomy at UCLA Ronald Reagan Medical Center from 2014 to 2021. We designed a hybrid transformer model with nonlocal and cross-attention modules to predict the first-pass effect on MR imaging and CT series. RESULTS: The proposed method achieved a mean 0.8506 (SD, 0.0712) for cross-validation receiver operating characteristic area under the curve (ROC-AUC) on MR imaging and 0.8719 (SD, 0.0831) for cross-validation ROC-AUC on CT. When evaluated on the prospective test sets, our proposed model achieved a mean ROC-AUC of 0.7967 (SD, 0.0335) with a mean sensitivity of 0.7286 (SD, 0.1849) and specificity of 0.8462 (SD, 0.1216) for MR imaging and a mean ROC-AUC of 0.8051 (SD, 0.0377) with a mean sensitivity of 0.8615 (SD, 0.1131) and specificity 0.7500 (SD, 0.1054) for CT, respectively, representing the first classification of the first-pass effect from MR imaging alone and the first automated first-pass effect classification method in CT. CONCLUSIONS: Results illustrate that both nonperfusion MR imaging and CT from admission contain signals that can predict a successful first-pass effect following endovascular thrombectomy using our deep learning methods without requiring time-intensive manual segmentation.

miRNA-206-3p alleviates LPS-induced acute lung injury via inhibiting inflammation and pyroptosis through modulating TLR4/NF-κB/NLRP3 pathway.

Acute lung injury (ALI) is life-threatening. MicroRNAs (miRNAs) are often abnormally expressed in inflammatory diseases and are closely associated with ALI. This study investigates whether miRNA-206-3p attenuates pyroptosis in ALI and elucidates the underlying molecular mechanisms. ALI mouse and cell models were established through lipopolysaccharide (LPS) treatment for 24 h. Subsequently, the models were evaluated based on ultrasonography, the lung tissue wet/dry (W/D) ratio, pathological section assessment, electron microscopy, and western blotting. Pyroptosis in RAW264.7 cells was then assessed via electron microscopy, immunofluorescence, and western blotting. Additionally, the regulatory relationship between miRNA-206-3p and the Toll-like receptor (TLR)4/nuclear factor (NF)-κB/Nod-like receptor protein-3 (NLRP3) pathway was verified. Finally, luciferase reporter gene and RNA pull-down assays were used to verify the targeting relationship between miRNA-206-3p and TLR4. miRNA206-3p levels are significantly decreased in the LPS-induced ALI model. Overexpression of miRNA-206-3p improves ALI, manifested as improved lung ultrasound, improved pathological changes of lung tissue, reduced W/D ratio of lung tissue, release of inflammatory factors in lung tissue, and reduced pyroptosis. Furthermore, overexpression of miRNA-206-3p contributed to reversing the ALI-promoting effect of LPS by hindering TLR4, myeloid differentiation primary response 88 (MyD88), NF-κB, and NLRP3 expression. In fact, miRNA-206-3p binds directly to TLR4. In conclusion, miRNA-206-3p alleviates LPS-induced ALI by inhibiting inflammation and pyroptosis via TLR4/NF-κB/NLRP3 pathway modulation.

Serratia plymuthica HK9-3 enhances tomato resistance against Phytophthora capsici by modulating antioxidant defense systems and rhizosphere micro-ecological condition.

Tomatoes are frequently challenged by various pathogens, among which Phytophthora capsici (P. capsici) is a destructive soil-borne pathogen that seriously threatens the safe production of tomatoes. Plant growth-promoting rhizobacteria (PGPR) positively induced plant resistance against multiple pathogens. However, little is known about the role and regulatory mechanism of PGPR in tomato resistance to P. capsici. Here, we identified a new strain Serratia plymuthica (S. plymuthica), HK9-3, which has a significant antibacterial effect on P. capsici infection. Meanwhile, stable colonization in roots by HK9-3, even under P. capsici infection, improved tomato growth parameters, root system architecture, photosynthetic capacity, and boosted biomass. Importantly, HK9-3 colonization significantly alleviated the damage caused by P. capsici infection through enhancing ROS scavenger ability and inducing antioxidant defense system and pathogenesis-related (PR) proteins in leaves, as evidenced by elevating the activities of peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO), and chitinase, ß-1,3-glucanase, and increasing the transcripts of POD, SOD, CAT, APX1, PAL1, PAL2, PAL5, PPO2, CHI17 and ß-1,3-glucanase genes. Notably, HK9-3 colonization not only effectively improved soil microecology and soil fertility, but also significantly enhanced fruit yield by 44.6% and improved quality. Our study presents HK9-3 as a promising and effective solution for controlling P. capsici infection in tomato cultivation while simultaneously promoting plant growth and increasing yield, which may have implications for P. capsici control in vegetable production.

An algorithm to identify patients aged 0-3 with rare genetic disorders.

BACKGROUND: With over 7000 Mendelian disorders, identifying children with a specific rare genetic disorder diagnosis through structured electronic medical record data is challenging given incompleteness of records, inaccurate medical diagnosis coding, as well as heterogeneity in clinical symptoms and procedures for specific disorders. We sought to develop a digital phenotyping algorithm (PheIndex) using electronic medical records to identify children aged 0-3 diagnosed with genetic disorders or who present with illness with an increased risk for genetic disorders. RESULTS: Through expert opinion, we established 13 criteria for the algorithm and derived a score and a classification. The performance of each criterion and the classification were validated by chart review. PheIndex identified 1,088 children out of 93,154 live births who may be at an increased risk for genetic disorders. Chart review demonstrated that the algorithm achieved 90% sensitivity, 97% specificity, and 94% accuracy. CONCLUSIONS: The PheIndex algorithm can help identify when a rare genetic disorder may be present, alerting providers to consider ordering a diagnostic genetic test and/or referring a patient to a medical geneticist.

CAR T Cell Membrane Camouflaged Nanocatalyst Augments CAR T Cell Therapy Efficacy Against Solid Tumor.

The immunosuppressive tumor microenvironment (TME) reduces the chimeric antigen receptor (CAR) T-cell therapy against solid tumors. Here, a CAR T cell membrane-camouflaged nanocatalyst (ACSP@TCM) is prepared to augment CAR T cell therapy efficacy against solid tumors. ACSP@TCM is prepared by encapsulating core/shell Au/Cu2- xSe and 3-bromopyruvate with a CAR T cell membrane. It is demonstrated that the CAR T cell membrane camouflaging has much better-targeting effect than the homologous tumors cell membrane camouflaging. ACSP@TCM has an appealing synergistic chemodynamic/photothermal therapy (CDT/PTT) effect that can induce the immunogenic cell death (ICD) of NALM 6 cells. Moreover, 3-bromopyruvate can inhibit the efflux of lactic acid by inhibiting the glycolysis process, regulating the acidity of TME, and providing a more favorable environment for the survival of CAR T cells. In addition, the photoacoustic (PA) imaging and computed tomography (CT) imaging performance can guide the ACSP@TCM-mediated tumor therapy. The results demonstrated that the ACSP@TCM significantly enhanced the CAR T cell therapy efficacy against NALM 6 solid tumor mass, and completely eliminated tumors. This work provides an effective tumor strategy for CAR T cell therapy in solid tumors.

Acinetobacter baumannii biofilm was inhibited by tryptanthrin through disrupting its different stages and genes expression.

Biofilm formation plays a significant role in antibiotic resistance, necessitating the search for alternative therapies against biofilm-associated infections. This study demonstrates that 20 µg/mL tryptanthrin can hinder biofilm formation above 50% in various A. baumannii strains. Tryptanthrin impacts various stages of biofilm formation, including the inhibition of surface motility and eDNA release in A. baumannii, as well as an increase in its sensitivity to H202. RT-qPCR analysis reveals that tryptanthrin significantly decreases the expression of the following genes: abaI (19.07%), abaR (33.47%), bfmR (43.41%), csuA/B (64.16%), csuE (50.20%), ompA (67.93%), and katE (72.53%), which are related to biofilm formation and quorum sensing. Furthermore, tryptanthrin is relatively safe and can reduce the virulence of A. baumannii in a Galleria mellonella infection model. Overall, our study demonstrates the potential of tryptanthrin in controlling biofilm formation and virulence of A. baumannii by disrupting different stages of biofilm formation and intercellular signaling communication.

Learning data distribution of three-dimensional ocean sound speed fields via diffusion models.

The probability distribution of three-dimensional sound speed fields (3D SSFs) in an ocean region encapsulates vital information about their variations, serving as valuable data-driven priors for SSF inversion tasks. However, learning such a distribution is challenging due to the high dimensionality and complexity of 3D SSFs. To tackle this challenge, we propose employing the diffusion model, a cutting-edge deep generative model that has showcased remarkable performance in diverse domains, including image and audio processing. Nonetheless, applying this approach to 3D ocean SSFs encounters two primary hurdles. First, the lack of publicly available well-crafted 3D SSF datasets impedes training and evaluation. Second, 3D SSF data consist of multiple 2D layers with varying variances, which can lead to uneven denoising during the reverse process. To surmount these obstacles, we introduce a novel 3D SSF dataset called 3DSSF, specifically designed for training and evaluating deep generative models. In addition, we devise a high-capacity neural architecture for the diffusion model to effectively handle variations in 3D sound speeds. Furthermore, we employ state-of-the-art continuous-time-based optimization method and predictor-corrector scheme for high-performance training and sampling. Notably, this paper presents the first evaluation of the diffusion model's effectiveness in generating 3D SSF data. Numerical experiments validate the proposed method's strong ability to learn the underlying data distribution of 3D SSFs, and highlight its effectiveness in assisting SSF inversion tasks and subsequently characterizing the transmission loss of underwater acoustics.

Braden score can independently predict 90-day mortality in critically ill patients with dementia.

BACKGROUND: Dementia is a significant cause of death in the older population and is becoming an important public health issue as the population ages and the prevalence of dementia increases. The Braden score is one of the most commonly used clinical tools to assess the risk of skin pressure injury in patients, and some studies have reported that it may reflect the state of frailty of patients. The present study attempted to explore the association between Braden score and 90-day mortality, pressure injury, and aspiration pneumonia in older patients with dementia in the intensive care unit (ICU). METHODS: The study involved extracting crucial data from the Medical Information Market for Intensive Care IV (MIMIC-IV) database using Structured Query Language, with a license certificate obtained after completing the necessary training and examination available on the MIMIC-IV website. A retrospective analysis was performed on older patients with dementia, aged 65 or older, who were first admitted to the ICU. Ninth and tenth revision International Classification of Diseases codes were used to identify patients with dementia. The primary outcome was 90-day mortality. Cox proportional hazards models were used to determine the association between Braden score and death, and hazard ratios (HR) and 95% confidence intervals (CI) were calculated. Propensity score matching and E-value assessments were employed for sensitivity analysis. RESULTS: A total of 2892 patients with a median age of approximately 85 years (interquartile range 78.74-89.59) were included, of whom 1625 were female (56.2%). Patients had a median Braden score of 14 (interquartile range 12-15) at ICU admission. Braden score at ICU admission was inversely associated with 90-day mortality risk after adjustment for demographics, severity of illness, treatment and medications, delirium, and sepsis (adjusted HR: 0.92, 95% CI: 0.87-0.98, p = 0.006). Patients were divided into two groups with a cut-off value of 15: high-risk group and low-risk group. Compared to the low-risk group (Braden score >15), the risk of 90-day mortality was significantly increased in the high-risk group (Braden score ≤15) (adjusted HR: 1.52, 95% CI: 1.10-2.09, p = 0.011, E-value: 2.01), the risk of pressure injury (adjusted OR: 2.62, 95% CI: 2.02-3.43, E-value: 2.62) and aspiration pneumonia (adjusted OR: 2.55, 95% CI: 1.84-3.61, E-value: 2.57) was also significantly higher. CONCLUSIONS: The Braden score may be a quick and simple screening tool to identify the risk of adverse outcomes in critically ill older adults with dementia.

Enhancing the Conductivity and Thermoelectric Performance of Semicrystalline Conducting Polymers through Controlled Tie Chain Incorporation.

Conjugated polymers are promising materials for thermoelectric applications, however, at present few effective and well-understood strategies exist to further advance their thermoelectric performance. Here a new model system is reported for a better understanding of the key factors governing their thermoelectric properties: aligned, ribbon-phase poly[2,5-bis(3-dodecylthiophen-2-yl)thieno[3,2-b]thiophene] (PBTTT) doped by ion-exchange doping. Using a range of microstructural and spectroscopic methods, the effect of controlled incorporation of tie-chains between the crystalline domains is studied through blending of high and low molecular weight chains. The tie chains provide efficient transport pathways between crystalline domains and lead to significantly enhanced electrical conductivity of 4810 S cm-1, which is not accompanied by a reduction in Seebeck coefficient or a large increase in thermal conductivity. Respectable power factors of 173 µW m-1 K-2 are demonstrated in this model system. The approach is generally applicable to a wide range of semicrystalline conjugated polymers and could provide an effective pathway for further enhancing their thermoelectric properties and overcome traditional trade-offs in optimization of thermoelectric performance.

Polydopamine-mediated immobilization of BMP-2 onto electrospun nanofibers enhances bone regeneration.

Dealing with bone defects is a significant challenge to global health. Electrospinning in bone tissue engineering has emerged as a solution to this problem. In this study, we designed a PVDF-b-PTFE block copolymer by incorporating TFE, which induced a phase shift in PVDF fromαtoß, thereby enhancing the piezoelectric effect. Utilizing the electrospinning process, we not only converted the material into a film with a significant surface area and high porosity but also intensified the piezoelectric effect. Then we used polydopamine to immobilize BMP-2 onto PVDF-b-PTFE electrospun nanofibrous membranes, achieving a controlled release of BMP-2. The scaffold's characters were examined using SEM and XRD. To assess its osteogenic effectsin vitro, we monitored the proliferation of MC3T3-E1 cells on the fibers, conducted ARS staining, and measured the expression of osteogenic genes.In vivo, bone regeneration effects were analyzed through micro-CT scanning and HE staining. ELISA assays confirmed that the sustained release of BMP-2 can be maintained for at least 28 d. SEM images and CCK-8 results demonstrated enhanced cell viability and improved adhesion in the experimental group. Furthermore, the experimental group exhibited more calcium nodules and higher expression levels of osteogenic genes, including COL-I, OCN, and RUNX2. HE staining and micro-CT scans revealed enhanced bone tissue regeneration in the defective area of the PDB group. Through extensive experimentation, we evaluated the scaffold's effectiveness in augmenting osteoblast proliferation and differentiation. This study emphasized the potential of piezoelectric PVDF-b-PTFE nanofibrous membranes with controlled BMP-2 release as a promising approach for bone tissue engineering, providing a viable solution for addressing bone defects.

Enhancing the Thermoelectric Properties of Conjugated Polymers by Suppressing Dopant-Induced Disorder.

Doping is a crucial strategy to enhance the performance of various organic electronic devices. However, in many cases, the random distribution of dopants in conjugated polymers leads to the disruption of the polymer microstructure, severely constraining the achievable performance of electronic devices. Here, it is shown that by ion-exchange doping polythiophene-based P[(3HT)1-x-stat-(T)x] (x = 0 (P1), 0.12 (P2), 0.24 (P3), and 0.36 (P4)), remarkably high electrical conductivity of >400 S cm-1 and power factor of >16 µW m-1 K-2 are achieved for the random copolymer P3, ranking it among highest ever reported for unaligned P3HT-based films, significantly higher than that of P1 (<40 S cm-1, <4 µW m-1 K-2). Although both polymers exhibit comparable field-effect transistor hole mobilities of ≈0.1 cm2 V-1 s-1 in the pristine state, after doping, Hall effect measurements indicate that P3 exhibits a large Hall mobility up to 1.2 cm2 V-1 s-1, significantly outperforming that of P1 (0.06 cm2 V-1 s-1). GIWAXS measurement determines that the in-plane π-π stacking distance of doped P3 is 3.44 Å, distinctly shorter than that of doped P1 (3.68 Å). These findings contribute to resolving the long-standing dopant-induced-disorder issues in P3HT and serve as an example for achieving fast charge transport in highly doped polymers for efficient electronics.

System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning.

The suprachiasmatic nucleus (SCN) is the mammalian central circadian pacemaker with heterogeneous neurons acting in concert while each neuron harbors a self-sustained molecular clockwork. Nevertheless, how system-level SCN signals encode time of the day remains enigmatic. Here we show that population-level Ca2+ signals predict hourly time, via a group decision-making mechanism coupled with a spatially modular time feature representation in the SCN. Specifically, we developed a high-speed dual-view two-photon microscope for volumetric Ca2+ imaging of up to 9000 GABAergic neurons in adult SCN slices, and leveraged machine learning methods to capture emergent properties from multiscale Ca2+ signals as a whole. We achieved hourly time prediction by polling random cohorts of SCN neurons, reaching 99.0% accuracy at a cohort size of 900. Further, we revealed that functional neuron subtypes identified by contrastive learning tend to aggregate separately in the SCN space, giving rise to bilaterally symmetrical ripple-like modular patterns. Individual modules represent distinctive time features, such that a module-specifically learned time predictor can also accurately decode hourly time from random polling of the same module. These findings open a new paradigm in deciphering the design principle of the biological clock at the system level.