Effects of post-curing light intensity on the trueness, compressive strength, and resin polymerization characteristics of 3D-printed 3-unit fixed dental prostheses.

PURPOSE: To investigate the effect of different post-curing light intensities on the trueness, compressive strength, and resin polymerization of 3D-printed 3-unit fixed dental prostheses (FPD). MATERIALS AND METHODS: A total of 60 specimens were prepared to support a 3-unit FDP with a deep chamfer marginal design, utilizing computer-aided design and computer-aided manufacturing (CAD-CAM) technology. Light-polymerizing FDP resin with varying light intensities (105, 210, 420, and 840 mW/cm2) was employed for 10 min. Subsequently, trueness assessment, fracture load testing, scanning electron microscopy (SEM) surface examination, and Fourier-Transform Infrared (FTIR) analysis were conducted. A one-way analysis of variance (ANOVA) was performed to ascertain the differences between the experimental groups (p < 0.05). RESULTS: The group exposed to 210 mW/cm2 showed the highest trueness (57.6 ± 2.1 µm), while the 840 mW/cm2 group had the highest deviation (79.3 ± 2.7 µm) (p < 0.001). Significant differences in fracture resistance were found between groups (p < 0.001), with mean fracture strengths of 1149.77 ± 67.81 N, 1264.92 ± 39.06 N, 1331.34 ± 53.62 N, and 1439.93 ± 34.58 N for light intensities of 105, 210, 420, and 840 mW/cm2, respectively (p < 0.001). The resin polymerization analysis shows a peak intensity surge at 3579 cm-1 for O-H and C-H stretching vibrations, except in samples exposed to 105 mw/cm2 light, with the lowest peak at 2890 cm-1. The performance of resin polymerization is most significant under the condition of 840 mW/cm2. CONCLUSION: The light intensity of 210 mW/cm2 exhibited the highest trueness, while the 840 mW/cm2 group showed the highest deviation. However, the light intensity of 840 mW/cm2 demonstrated the highest compressive strength. Furthermore, polymerization occurred at all post-treatment light intensities except 105 mW/cm2. These findings indicate that while low-intensity usage offers greater trueness, high-intensity usage provides better compressive strength and polymerization. Therefore, 210 mW/cm2 could be the recommended solution for post-curing.

The impact of different censoring methods for analyzing survival using real-world data with linked mortality information: a simulation study.

BACKGROUND: Evaluating outcome reliability is critical in real-world evidence studies. Overall survival is a common outcome in these studies; however, its capture in real-world data (RWD) sources is often incomplete and supplemented with linked mortality information from external sources. Conflicting recommendations exist for censoring overall survival in real-world evidence studies. This simulation study aimed to understand the impact of different censoring methods on estimating median survival and log hazard ratios when external mortality information is partially captured. METHODS: We used Monte Carlo simulation to emulate a non-randomized comparative effectiveness study of two treatments with RWD from electronic health records and linked external mortality data. We simulated the time to death, the time to last database activity, and the time to data cutoff. Death events after the last database activity were attributed to linked external mortality data and randomly set to missing to reflect the sensitivity of contemporary real-world data sources. Two censoring schemes were evaluated: (1) censoring at the last activity date and (2) censoring at the end of data availability (data cutoff) without an observed death. We assessed the performance of each method in estimating median survival and log hazard ratios using bias, coverage, variance, and rejection rate under varying amounts of incomplete mortality information and varying treatment effects, length of follow-up, and sample size. RESULTS: When mortality information was fully captured, median survival estimates were unbiased when censoring at data cutoff and underestimated when censoring at the last activity. When linked mortality information was missing, censoring at the last activity date underestimated the median survival, while censoring at the data cutoff overestimated it. As missing linked mortality information increased, bias decreased when censoring at the last activity date and increased when censoring at data cutoff. CONCLUSIONS: Researchers should consider the completeness of linked external mortality information when choosing how to censor the analysis of overall survival using RWD. Substantial bias in median survival estimates can occur if an inappropriate censoring scheme is selected. We advocate for RWD providers to perform validation studies of their mortality data and publish their findings to inform methodological decisions better.

Impact of seasonal changes and environmental conditions on suspended and inhalable microplastics in urban air.

Microplastics (MPs) are ubiquitous environmental pollutants extensively detected in atmospheric environments. Airborne MPs have raised concerns due to their transport and potential health risks of inhalation exposure. However, the factors influencing airborne MPs, particularly their concentrations and shapes suspended in urban air, remain unclear. We investigated MPs in total suspension particles with one-year measurements in Taipei City and identified their features using Nile Red staining combined with fluorescence microscopy and micro-Fourier transform infrared (µFTIR) spectroscopy. This study quantified the mean number concentration of total MPs as approximately 6.0 #/m³. We observed that MP abundance varied seasonally, with higher levels in the warm season than in the cold. A similar trend was noted for polymer types. Fragment-like MPs were the predominant shape, mainly found in polystyrene (PS), polyethylene (PE), and polypropylene (PP), while fibrous MPs, detected mostly as polyethylene terephthalate (PET) and polyamide (PA), were primarily observed at sizes greater than 300 µm. Both fiber and fragment-like MPs were positively associated with particle mass concentration, temperature, ultraviolet (UV) index, and wind speed, but negatively correlated with relative humidity and rainfall. Fibrous MPs were more affected by environmental factors than fragment-like MPs. Meteorological changes significantly influenced suspended MPs more than human activity within the city.

Factors Associated With the Use of Digital Technology Among Youth in Zimbabwe: Findings From a Cross-Sectional Population-Based Survey.

BACKGROUND: Globally, the increasing use of digital technologies such as mobile phones and the internet has allowed for the development of innovative mobile health interventions, particularly for reaching and engaging with youth. However, there is a risk that using such technologies may exclude those who lack access to them. OBJECTIVE: In this study, we investigated the sociodemographic factors associated with mobile phone ownership, internet use, and social media use among youth in Zimbabwe. METHODS: A population-based prevalence survey was conducted in 24 urban and periurban communities across 3 provinces of Zimbabwe (Harare, Mashonaland East, and Bulawayo). Youths aged 18 to 24 years resident in randomly selected households in the study communities completed an interviewer-administered questionnaire. The primary outcomes were mobile phone ownership and current internet and social media use. A household wealth indicator was developed using principal components analysis, based on household asset ownership. Multivariable logistic regression was used to investigate the factors associated with each primary outcome. Age, sex, and province were considered a priori confounders. Household wealth, marital status, education level, employment status, time lived at current address, and HIV status were included in the final multivariable model if there was an age-, sex-, and province-adjusted association with a primary outcome on univariable analysis at a significance level of P<.10. RESULTS: Of the 17,636 participants assessed for the primary outcome, 16,370 (92.82%) had access to a mobile phone, and 15,454 (87.63%) owned a mobile phone. Among participants with access to a mobile phone, 58.61% (9594/16,370) and 57.79% (9460/16,370), respectively, used internet and social media at least weekly. Older age (adjusted odds ratio [aOR] 1.76, 95% CI 1.55-2.00), increasing wealth (ranging from aOR 1.85, 95% CI 1.58-2.16, for wealth quintile 2 to aOR 3.80, 95% CI 3.00-4.80, for wealth quintile 5, with quintile 1 as reference), and higher education level (secondary: aOR 1.96, 95% CI 1.60-2.39; tertiary: aOR 8.36, 95% CI 5.29-13.20) were associated with mobile phone ownership. Older age, male sex, increasing wealth, having never been married, higher education level, being in education or formal employment, and having lived at the same address for ≥2 years were associated with higher levels of internet and social media use. CONCLUSIONS: While mobile phone ownership was near-universal, over one-third of youths in urban and periurban settings did not have access to the internet and social media. Access to the internet and social media use were strongly associated with household wealth and education level. Mobile health interventions must ensure that they do not amplify existing inequalities in access to health care. Such interventions must be accompanied by alternative strategies to engage and enroll individuals without internet or social media access to prevent the exclusion of young people by sex and socioeconomic status.

Next-Generation swimming pool drowning prevention strategy integrating AI and IoT technologies.

Drowning, as a leading cause of unintentional injury-related deaths worldwide, is a major public health concern. Swimming pool drowning is the main cause of most drowning incidents, and even with preventive measures such as surveillance cameras and lifeguards, tens of thousands of lives are lost to drowning every year. To address this issue, technology is being utilized to prevent drowning accidents and provide timely alerts for rescue. This paper explores the use of drowning prevention technology in embedded systems within enclosed environments, artificial intelligence (AI), and the Internet of Things (IoT) to decrease the likelihood of drowning incidents. Embedded systems play a critical role in such technology, enabling real-time monitoring, identification of dangerous situations, and prompt alerting. Due to their ease of installation and technical implementation, embedded devices are especially effective as drowning prevention devices. The image recognition capabilities of drowning prevention systems are enhanced through computer vision. Swimming pool drowning situations can be identified with the help of cameras and deep learning technologies, thereby increasing rescue efficiency. Finally, the IoT endows drowning prevention systems with comprehensive intelligence by connecting various devices and communication tools. Real-time alert transmission and analysis have become possible, enabling the early prediction of dangerous situations and the implementation of preventive measures, significantly reducing drowning incidents. In summary, the integration of these three types of drowning prevention technologies represents significant progress. The flexibility, accuracy, and intelligence of drowning prevention systems are enhanced through the incorporation of these technologies, providing robust support for safeguarding human lives and thus potentially saving tens of thousands of lives each year.

Characteristics and Prevalence of Vancomycin-variable Enterococcus faecium bacteremia in southern Taiwan.

BACKGROUND: Vancomycin-variable enterococci (VVE) are vanA-carrying Enterococcus faecium that are phenotypically susceptible to vancomycin and can only be detected using molecular methods, leading to the possibility of treatment failure and posing threats to infection control. This study aimed to determine the prevalence of VVE and its associated clinical risk factors. METHODS: This retrospective study was conducted in two hospitals in southern Taiwan. Patients with phenotypically vancomycin-susceptible E. faecium bacteremia were enrolled between 2017 and 2021. VVEs were defined as isolates harboring the vanA gene that were phenotypically susceptible to vancomycin. Vancomycin-susceptible E. faecium (VSE) isolates were phenotypically susceptible to vancomycin and lacked vanA or vanB genes. RESULTS: Of the 142 enrolled patients, 121 (85.2%) had VSE and 21 (14.8%) had VVE. Resistance rates to penicillin, tetracycline, and fosfomycin were higher in VVE isolates. Malignancy (adjusted odds ratio [aOR] = 4.87; 95% confidence interval [CI] 1.54-15.41, p = 0.007) and central venous catheter usage (aOR = 4.69; 95% CI 1.49-14.78, p = 0.008) were the independent risk factors associated with VVE bacteremia. Being male (aOR = 0.12, CI 0.03-0.44, p = 0.002) was less likely to be associated with VVE bacteremia. Although VVE was not associated with 30-day mortality (38.1% [VVE] vs. 35.5% [VSE], p = 0.822), one case of subsequent vancomycin-resistant enterococci infection in the VVE group with vancomycin treatment (4.8%, 1/21) was identified, which led to subsequent mortality. CONCLUSIONS: The prevalence of VVE was high among E. faecium isolates with vancomycin-susceptible phenotypes in southern Taiwan. Although the current study revealed that VVE bacteremia was not associated with poor clinical outcome, further multicenter surveillance survey is recommended to evaluate the possible impact of VVE on public health in Taiwan.

Evaluating TRAIL and IP-10 alterations in vaccinated pregnant women after COVID-19 diagnosis and their correlation with neutralizing antibodies.

Background: This study evaluates tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and interferon-γ-induced protein-10 (IP-10) in pregnant women with COVID-19 and their newborns, exploring the effects of antiviral treatments and vaccine-induced neutralizing antibody (Nab) inhibition on these key viral infection biomarkers. Methods: We studied 61 pregnant women with past COVID-19 and either three (n=56) or four (n=5) doses of vaccination, and 46 without COVID-19 but vaccinated. We analyzed them and their newborns' blood for TRAIL, IP-10, and Nab levels using enzyme-linked immunosorbent assays (ELISA), correlating these with other clinical factors. Results: Our study found lower TRAIL but higher IP-10 levels in maternal blood than neonatal cord blood, irrespective of past COVID-19 diagnosis. Cases diagnosed with COVID-19 < 4 weeks previously had higher maternal blood TRAIL levels (16.49 vs. 40.81 pg/mL, p=0.0064) and IP-10 (154.68 vs. 225.81 pg/mL, p=0.0170) than those never diagnosed. Antiviral medication lowered TRAIL and IP-10 in maternal blood without affecting Nab inhibition (TRAIL: 19.24 vs. 54.53 pg/mL, p=0.028; IP-10: 158.36 vs. 255.47 pg/mL, p=0.0089). TRAIL and IP-10 levels were similar with three or four vaccine doses, but four doses increased Nab inhibition (p=0.0363). Previously COVID-19 exposed pregnant women had higher Nab inhibition (p < 0.0001). No obvious correlation was found among TRAIL, IP-10, and Nab inhibition level. Conclusions: Our study suggests that lower maternal TRAIL and higher IP-10 levels compared to neonatal cord blood coupled with a rise in both markers following COVID-19 diagnosis that could be reduced by antivirals indicates a correlation to infection severity. Higher vaccine doses enhance Nab inhibition, irrespective of antiviral medication use and independent of TRAIL or IP-10 levels, highlighting the significance and safety of adequate vaccination and antiviral use post-diagnosis in pregnant women.

Development of Machine Learning-Based Quantitative Structure-Activity Relationship Models for Predicting Plasma Half-Lives of Drugs in Six Common Food Animal Species.

Plasma half-life is a crucial pharmacokinetic parameter for estimating extralabel withdrawal intervals of drugs to ensure the safety of food products derived from animals. This study focuses on developing a quantitative structure-activity relationship (QSAR) model incorporating multiple machine learning and artificial intelligence algorithms, and aims to predict the plasma half-lives of drugs in six food animals, including cattle, chickens, goats, sheep, swine, and turkeys. By integrating four machine learning algorithms with five molecular descriptor types, 20 QSAR models were developed using data from the Food Animal Residue Avoidance Databank (FARAD) Comparative Pharmacokinetic Database. The deep neural network (DNN) algorithm demonstrated the best prediction ability of plasma half-lives. The DNN model with all descriptors achieved superior performance with a high coefficient of determination (R  2) of 0.82±0.19 in 5-fold cross-validation on the training sets and a R  2 of 0.67 on the independent test set, indicating accurate predictions and good generalizability. The final model was converted to a user-friendly web dashboard to facilitate its wide application by the scientific community. This machine learning-based QSAR model serves as a valuable tool for predicting drug plasma half-lives and extralabel withdrawal intervals in six common food animals based on physicochemical properties. It also provides a foundation to develop more advanced models to predict the tissue half-life of drugs in food animals.

Influence of increasing noise at the offshore wind farm area on fish vocalization phenology: A long-term marine acoustical monitoring off the foremost offshore wind farm in Taiwan.

The rapid increase of offshore projects at Taiwan Strait in recent decade has been debated for elevated noise levels. However, there are no studies on long-term assessment of noise levels and impact of noise on marine organisms. The passive acoustic monitoring was conducted at the foremost wind farm area in Taiwan to assess the sound levels and the impact of noise on fish vocalization behavior. Predominately, in the soundscape around the Taiwan Strait, two chorusing types (Type 1 and Type 2) from the Sciaenid family of fishes exist. Ambient sound levels significantly increased from 2014 to 2019, while the chorusing Types 1 and 2 were observed in a lower percentage of the recordings. Additionally, chorusing peak intensity and duration significantly reduced over the years for both choruses. This is the first field-based evidence to demonstrate the consequences of increasing anthropogenic noise having the potential to alter the vocalization behavior of the fish.

Impacts of polystyrene nanoplastics on microgel formation from effluent organic matter.

Municipal effluents discharged from wastewater treatment plants (WWTPs) are considered major contributors of nanoplastics (NPs) and dissolved effluent organic matter (dEfOM) to environments. Due to their small sizes, NPs can travel easily in waterways and evade wastewater treatment processes, and may directly interact with dEfOM, altering their environmental fates. However, although much research has examined the impact of natural organic matter on NPs, the interactions between NPs and dEfOM remain unexplored. This study investigated the influences of NPs on the behavior and capacity of dEfOM aggregation and surface granularity, and identified the possible aggregation mechanism. We also adjusted the salinity of water samples to simulate scenarios based on WWTP-sea continuums. Our data suggest that dEfOM can self-assemble with 55 nm polystyrene NPs to form microgels, particularly under high salinity conditions. NPs accelerates the formation speed and number of dEfOM aggregates, but the sizes of the aggregates remain largely unchanged. The relative particle counts at a salinity of 34 psu increased by 300 % compared to the control group. The potential mechanism behind NPs-microgels aggregation is likely driven by the synergistic effect of the divalent ion crosslinking and hydrophobic interactions between EfOM and NPs. Notably, NPs incorporation into microgels decreases the surface granularity, thereby possibly affecting settling velocity and colonization of aggregates, as well as microbial attachment and community diversity. Overall, our findings demonstrate the potential influence of NPs on dEfOM assembly and surface properties following effluent discharge, and can inspire further relevant studies on microorganism interactions, removal technologies, and the environmental transport of NPs.

Characterization of a Lewis adduct in its inner and outer forms.

The entrance channel of bimolecular reactions sometimes involves the formation of outer complexes as weakly bound, fleeting intermediates. Here, we characterize such an outer complex in a system that models the bimolecular, C-O bond-forming reaction of a phosphine oxide Lewis base with a carbenium Lewis acid. Crystallographic studies show that the C-O distance in the outer form exceeds that of the final or inner adduct by 1.1 angstroms. As the system samples the two forms of the complex, which correspond to minima on the corresponding potential energy surface, the C-O linkage switches from a secondary interaction in the outer complex to a dative bond in the inner complex. This phenomenon is harnessed as a functional feature to stabilize xanthylium-based photoredox catalysts.

A case report on the atypical metastatic pathway of prostate cancer to the kidney and stomach.

Prostate cancer rarely metastasizes to the stomach and kidneys. We report a 73-year-old male with such spread, highlighting significant clinical challenges. Initially diagnosed via biopsy and imaging, he received hormone therapy and cytoreductive radical prostatectomy. Despite initial management, the cancer progressed to metastatic castration-resistant prostate cancer, with gastric and renal metastases confirmed by imaging and biopsy. This case emphasizes the need for awareness of rare metastatic sites, comprehensive diagnostic evaluations, and further research into these atypical metastases to improve patient outcomes and develop better treatment strategies for managing advanced prostate cancer effectively.

Bone Tissue Engineering with Adipose-Derived Stem Cells in Polycaprolactone/Graphene Oxide/Dexamethasone 3D-Printed Scaffolds.

We fabricated three-dimensional (3D)-printed polycaprolactone (PCL) and PCL/graphene oxide (GO) (PGO) scaffolds for bone tissue engineering. An anti-inflammatory and pro-osteogenesis drug dexamethasone (DEX) was adsorbed onto GO and a 3D-printed PGO/DEX (PGOD) scaffold successfully improved drug delivery with a sustained release of DEX from the scaffold up to 1 month. The physicochemical properties of the PCL, PGO, and PGOD scaffolds were characterized by various analytical techniques. The biological response of these scaffolds was studied for adherence, proliferation, and osteogenic differentiation of seeded rabbit adipose-derived stem cells (ASCs) from DNA assays, alkaline phosphatase (ALP) production, calcium quantification, osteogenic gene expression, and immunofluorescence staining of osteogenic marker proteins. The PGOD scaffold was demonstrated to be the best scaffold for maintaining cell viability, cell proliferation, and osteogenic differentiation of ASCs in vitro. In vivo biocompatibility of PGOD was confirmed from subcutaneous implantation in nude mice where ASC-seeded PGOD can form ectopic bones, demonstrated by microcomputed tomography (micro-CT) analysis and immunofluorescence staining. Furthermore, implantation of PGOD/ASCs constructs into critical-sized cranial bone defects in rabbits form tissue-engineered bones at the defect site, observed using micro-CT and histological analysis.

Characterization of Ucp1-iCre Knockin Mice Reveals the Recombination Activity in Male Germ Cells.

Ucp1 promoter-driven Cre transgenic mice are useful in the manipulation of gene expression specifically in thermogenic adipose tissues. However, the wildly used Ucp1-Cre line was generated by random insertion into the genome and showed ectopic activity in some tissues beyond adipose tissues. Here we characterized a knockin mouse line Ucp1-iCre generated by targeting IRES-Cre cassette immediately downstream the stop codon of the Ucp1 gene. The Cre insertion had little to no effect on UCP1 protein levels in brown adipose tissue. Ucp1-iCre mice of both genders exhibited normal thermogenesis and cold tolerance. When crossed with Rosa-tdTomato reporter mice, Ucp1-iCre mice showed robust Cre activity in thermogenic adipose tissues. Additionally, limited Cre activity was sparsely present in the hypothalamus (VMH), choroid plexus, kidney, adrenal glands, ovary, and testis in Ucp1-iCre mice, albeit to a much lesser extent and with reduced intensity compared to the conventional Ucp1-Cre line. Single-cell transcriptome analysis revealed UCP1 mRNA expression in male spermatocytes. Moreover, male Ucp1-iCre mice displayed a high frequency of Cre-mediated recombination in the germline, whereas no such effect was observed in female Ucp1-iCre mice. These findings suggest that Ucp1-iCre mice offer promising utility in the context of conditional gene manipulation in thermogenic adipose tissues, while also highlighting the need for caution in mouse mating and genotyping procedures.

Mediation analysis for TNF-α as a mediator between multiple metal exposure and kidney function.

The association between metal mixtures and kidney function has been reported. However, reports on the mechanism of metal toxicity were limited. Oxidative stress was reported as a possible cause. This study aimed to determine the association between of kidney function and metals, such as arsenic (As), cadmium (Cd), cobalt (Co), copper (Cu), lead (Pb), selenium (Se), and zinc (Zn), and to explore the possible mediating role of tumor necrosis factor alpha (TNF-α) between metal toxicity and kidney function. In this study, we recruited 421 adults from a health examination. The concentration of blood metals was analyzed using inductively coupled plasma mass spectrometry. We used linear regression models to assess the association between metals and TNF-α. Then, mediation analysis was applied to investigate the relationship between metal exposure, TNF-α, and kidney function. In univariate linear regression, blood As, Cd, Co, Cu, Pb, and Zn levels significantly increased TNF-α and decreased kidney function. Higher blood As and Pb levels significantly increased TNF-α in multivariable linear regressions after adjusting for covariates. We found that blood levels of As (coefficients = -0.021, p = 0.011), Pb (coefficients = -0.060, p < 0.001), and Zn (coefficients = -0.230, p < 0.001) showed a significant negative association with eGFR in the multiple-metal model. Furthermore, mediation analysis showed that TNF-α mediated 41.7 %, 38.8 %, and 20.8 % of blood Cd, As and Pb, respectively. Among the essential elements, TNF-α mediated 24.5 %, 21.5 % and 19.9 % in the effects of blood Co, Cu, and Zn on kidney function, respectively. TNF-α, acting as a mediator, accounted for 20.1 % of the contribution between the WQS score of metal mixtures and the eGFR (p < 0.001). This study suggested that TNF-α may be a persuasive pathway mediating the association between metals and kidney function. Inflammation and kidney injury could be the underlying mechanisms of metal exposure. However, there is still a need to clarify the biochemical mechanism in follow-up studies.

Applications of Lightsheet Fluorescence Microscopy by High Numerical Aperture Detection Lens.

This Review explores the evolution, improvements, and recent applications of Light Sheet Fluorescence Microscopy (LSFM) in biological research using a high numerical aperture detection objective (lens) for imaging subcellular structures. The Review begins with an overview of the development of LSFM, tracing its evolution from its inception to its current state and emphasizing key milestones and technological advancements over the years. Subsequently, we will discuss various improvements of LSFM techniques, covering advancements in hardware such as illumination strategies, optical designs, and sample preparation methods that have enhanced imaging capabilities and resolution. The advancements in data acquisition and processing are also included, which provides a brief overview of the recent development of artificial intelligence. Fluorescence probes that were commonly used in LSFM will be highlighted, together with some insights regarding the selection of potential probe candidates for future LSFM development. Furthermore, we also discuss recent advances in the application of LSFM with a focus on high numerical aperture detection objectives for various biological studies. For sample preparation techniques, there are discussions regarding fluorescence probe selection, tissue clearing protocols, and some insights into expansion microscopy. Integrated setups such as adaptive optics, single objective modification, and microfluidics will also be some of the key discussion points in this Review. We hope that this comprehensive Review will provide a holistic perspective on the historical development, technical enhancements, and cutting-edge applications of LSFM, showcasing its pivotal role and future potential in advancing biological research.

Associations Between Severe Influenza-Complicated Thromboembolism Events, Intensive Care Unit Stays and Mortality, and Associated Risk Factors: A Retrospective Cohort Study.

The association between influenza infection and thromboembolism (TE) events, including cardiovascular events, cerebrovascular events, pulmonary embolism, and deep vein thrombosis, is supported by compelling evidence. However, there is a disparity in the risk factors that impact the outcomes of severe influenza-complicated TE in intensive care unit (ICU) patients. The objective of this study was to evaluate the outcomes of severe influenza-complicated TE in ICU patients and identify any associated risk factors. METHODS: A retrospective cohort study was conducted, recruiting consecutive patients with TE events admitted to the ICU between December 2015 through December 2018 at our institution in Taiwan. The study included a group of 108 patients with severe influenza and a control group of 192 patients with severe community-acquired pneumonia. Associations between complicated TE, length of ICU stay, and 90-day mortality were evaluated using logistic regression analysis, and risk factors were identified using univariate and multivariate generalized linear regression analyses. RESULTS: TE event prevalence was significantly higher in ICU patients with severe influenza than in ICU patients with severe CAP (21.3% vs. 5.7%, respectively; p < 0.05). Patients with severe influenza who developed TE experienced a significant increase in the ratio of mechanical ventilation use, length of mechanical ventilation use, ICU stay, and 90-day mortality when compared to patients without TE (all p < 0.05). The comparison of severe CAP patients with and without TE revealed no significant differences (p > 0.05). The development of thromboembolic events in patients with severe influenza or severe noninfluenza CAP is linked to influenza infection and hypertension (p < 0.05). Furthermore, complicated TE and the severity of the APACHE II score are risk factors for 90-day mortality in ICU patients with severe influenza (p < 0.05). CONCLUSIONS: Patients with severe influenza and complicated TE are more likely to have an extended ICU stay and 90-day mortality than patients with severe CAP. The risk is significantly higher for patients with a higher APACHE II score. The results of this study may aid in defining better strategies for early recognition and prevention of severe influenza-complicated TE.

Light regulates widespread plant alternative polyadenylation through the chloroplast.

Transcription of eukaryotic protein-coding genes generates immature mRNAs that are subjected to a series of processing events, including capping, splicing, cleavage, and polyadenylation (CPA), and chemical modifications of bases. Alternative polyadenylation (APA) greatly contributes to mRNA diversity in the cell. By determining the length of the 3' untranslated region, APA generates transcripts with different regulatory elements, such as miRNA and RBP binding sites, which can influence mRNA stability, turnover, and translation. In the model plant Arabidopsis thaliana, APA is involved in the control of seed dormancy and flowering. In view of the physiological importance of APA in plants, we decided to investigate the effects of light/dark conditions and compare the underlying mechanisms to those elucidated for alternative splicing (AS). We found that light controls APA in approximately 30% of Arabidopsis genes. Similar to AS, the effect of light on APA requires functional chloroplasts, is not affected in mutants of the phytochrome and cryptochrome photoreceptor pathways, and is observed in roots only when the communication with the photosynthetic tissues is not interrupted. Furthermore, mitochondrial and TOR kinase activities are necessary for the effect of light. However, unlike AS, coupling with transcriptional elongation does not seem to be involved since light-dependent APA regulation is neither abolished in mutants of the TFIIS transcript elongation factor nor universally affected by chromatin relaxation caused by histone deacetylase inhibition. Instead, regulation seems to correlate with changes in the abundance of constitutive CPA factors, also mediated by the chloroplast.

Predicting tissue distribution and tumor delivery of nanoparticles in mice using machine learning models.

Nanoparticles (NPs) can be designed for targeted delivery in cancer nanomedicine, but the challenge is a low delivery efficiency (DE) to the tumor site. Understanding the impact of NPs' physicochemical properties on target tissue distribution and tumor DE can help improve the design of nanomedicines. Multiple machine learning and artificial intelligence models, including linear regression, support vector machine, random forest, gradient boosting, and deep neural networks (DNN), were trained and validated to predict tissue distribution and tumor delivery based on NPs' physicochemical properties and tumor therapeutic strategies with the dataset from Nano-Tumor Database. Compared to other machine learning models, the DNN model had superior predictions of DE to tumors and major tissues. The determination coefficients (R2) for the test datasets were 0.41, 0.42, 0.45, 0.79, 0.87, and 0.83 for DE in tumor, heart, liver, spleen, lung, and kidney, respectively. All the R2 and root mean squared error (RMSE) results of the test datasets were similar to the 5-fold cross validation results. Feature importance analysis showed that the core material of NPs played an important role in output predictions among all physicochemical properties. Furthermore, multiple NP formulations with greater DE to the tumor were determined by the DNN model. To facilitate model applications, the final model was converted to a web dashboard. This model could serve as a high-throughput pre-screening tool to support the design of new and efficient nanomedicines with greater tumor DE and serve as an alternative tool to reduce, refine, and partially replace animal experimentation in cancer nanomedicine research.

Upper Gastrointestinal Involvement in Crohn's Disease as an Independent Predictor of New-Onset Strictures: Insights from an Extensive Retrospective Cohort Analysis.

BACKGROUND/AIMS: Crohn's Disease (CD) can affect the entire gastrointestinal tract, including the upper sections (UGI), which is often overlooked, especially in Asian populations. There's a notable gap in research regarding the impact of UGI involvement on the intricate landscape of ensuing complications. This study aims to address this gap. METHODS: Conducting a retrospective study at Chang Gung Memorial Hospital from January 2001 to September 2023, we compared CD patients with UGI (Montreal L4) involvement against non-L4 counterparts, focusing on baseline characteristics, post-diagnosis complications, and overall outcomes. Routine UGI endoscopy was performed around the time of diagnosis in all patients followed in our inflammatory bowel disease (IBD) center, and all CD patients with adequate follow-up were included in this study. RESULTS: The study included 212 CD patients, 111 in the L4 group and 101 in the non-L4 group, with an average follow-up of 40.8 ± 15.1 months. At baseline, individuals in the L4 category demonstrated elevated smoking rates, increased Crohn's Disease Activity Index scores, a higher prevalence of strictures, and a more prevalent usage of biologics and proton pump inhibitors. Moreover, this group was characterized by reduced albumin levels. Upon concluding the follow-up, those with L4 involvement continued to show escalated CDAI scores and hospitalization frequencies, alongside heightened C-reactive protein levels and diminished albumin concentrations. Additionally, the occurrence of UGI involvement, stricturing disease at the time of diagnosis, and a younger age at the onset of CD were pinpointed as independent predictors for the development of new-onset strictures. CONCLUSIONS: CD patients with UGI involvement exhibit elevated disease activity and serve as independent predictors for the development of intestinal strictures. Thorough UGI evaluations at the time of diagnosis, coupled with assertive treatment strategies, are essential for managing these patients effectively.