A bio-fabricated tesla valves and ultrasound waves-powered blood plasma viscometer.

Introduction: There is clinical evidence that the fresh blood viscosity is an important indicator in the development of vascular disorder and coagulation. However, existing clinical viscosity measurement techniques lack the ability to measure blood viscosity and replicate the in-vivo hemodynamics simultaneously. Methods: Here, we fabricate a novel digital device, called Tesla valves and ultrasound waves-powered blood plasma viscometer (TUBPV) which shows capacities in both viscosity measurement and coagulation monitoring. Results: Based on the Hagen-Poiseuille equation, viscosity analysis can be faithfully performed by a video microscopy. Tesla-like channel ensured unidirectional liquid motion with stable pressure driven that was triggered by the interaction of Tesla valve structure and ultrasound waves. In few seconds the TUBPV can generate an accurate viscosity profile on clinic fresh blood samples from the flow time evaluation. Besides, Tesla-inspired microchannels can be used in the real-time coagulation monitoring. Discussion: These results indicate that the TUBVP can serve as a point-of-care device in the ICU to evaluate the blood's viscosity and the anticoagulation treatment.

Using machine learning algorithms based on patient admission laboratory parameters to predict adverse outcomes in COVID-19 patients.

Amidst the global COVID-19 pandemic, the urgent need for timely and precise patient prognosis assessment underscores the significance of leveraging machine learning techniques. In this study, we present a novel predictive model centered on routine clinical laboratory test data to swiftly forecast patient survival outcomes upon admission. Our model integrates feature selection algorithms and binary classification algorithms, optimizing algorithmic selection through meticulous parameter control. Notably, we developed an algorithm coupling Lasso and SVM methodologies, achieving a remarkable area under the ROC curve of 0.9277 with the use of merely 8 clinical laboratory parameters collected upon admission. Our primary contribution lies in the utilization of straightforward laboratory parameters for prognostication, circumventing data processing intricacies, and furnishing clinicians with an expeditious and precise prognostic assessment tool.

International consensus guidelines for the definition, detection, and interpretation of autophagy-dependent ferroptosis.

Macroautophagy/autophagy is a complex degradation process with a dual role in cell death that is influenced by the cell types that are involved and the stressors they are exposed to. Ferroptosis is an iron-dependent oxidative form of cell death characterized by unrestricted lipid peroxidation in the context of heterogeneous and plastic mechanisms. Recent studies have shed light on the involvement of specific types of autophagy (e.g. ferritinophagy, lipophagy, and clockophagy) in initiating or executing ferroptotic cell death through the selective degradation of anti-injury proteins or organelles. Conversely, other forms of selective autophagy (e.g. reticulophagy and lysophagy) enhance the cellular defense against ferroptotic damage. Dysregulated autophagy-dependent ferroptosis has implications for a diverse range of pathological conditions. This review aims to present an updated definition of autophagy-dependent ferroptosis, discuss influential substrates and receptors, outline experimental methods, and propose guidelines for interpreting the results.Abbreviation: 3-MA:3-methyladenine; 4HNE: 4-hydroxynonenal; ACD: accidentalcell death; ADF: autophagy-dependentferroptosis; ARE: antioxidant response element; BH2:dihydrobiopterin; BH4: tetrahydrobiopterin; BMDMs: bonemarrow-derived macrophages; CMA: chaperone-mediated autophagy; CQ:chloroquine; DAMPs: danger/damage-associated molecular patterns; EMT,epithelial-mesenchymal transition; EPR: electronparamagnetic resonance; ER, endoplasmic reticulum; FRET: Försterresonance energy transfer; GFP: green fluorescent protein;GSH: glutathione;IF: immunofluorescence; IHC: immunohistochemistry; IOP, intraocularpressure; IRI: ischemia-reperfusion injury; LAA: linoleamide alkyne;MDA: malondialdehyde; PGSK: Phen Green™ SK;RCD: regulatedcell death; PUFAs: polyunsaturated fatty acids; RFP: red fluorescentprotein;ROS: reactive oxygen species; TBA: thiobarbituricacid; TBARS: thiobarbituric acid reactive substances; TEM:transmission electron microscopy.

Linc00673-V3 positively regulates autophagy by promoting Smad3-mediated LC3B transcription in NSCLC.

Since its first discovery, long noncoding RNA Linc00673 has been linked to carcinogenesis and metastasis of various human cancers. Linc00673 had five transcriptional isoforms and their biological functions remained to be explored. Here we have reported that Linc00673-V3, one of the isoforms of Linc00673, promoted non-small cell lung cancer chemoresistance, and increased Linc00673-V3 expression level was associated with enhanced autophagy. Mechanistically, we discerned the existence of a stem-loop configuration engendered by the 1-100-nt and 2200-2275-nt fragments within Linc00673-V3. This structure inherently interacted with Smad3, thereby impeding its ubiquitination and subsequent degradation orchestrated by E3 ligase STUB1. The accumulation of Smad3 contributed to autophagy via up-regulation of LC3B transcription and ultimately conferred chemoresistance in NSCLC. Our results revealed a novel transcriptional regulation network between Linc00673-V3, Smad3, and LC3B, which provided an important insight into the interplay between autophagy regulation and non-canonical function of Smad3. Furthermore, the results from in vivo experiments suggested Linc00673-V3 targeted antisense oligonucleotide as a promising therapeutic strategy to overcome chemotherapy resistance in NSCLC.

A Randomized Trial Comparing Standard of Care to Bayesian Warfarin Dose Individualization.

The quality of warfarin treatment may be improved if management is guided by the use of models based upon pharmacokinetic-pharmacodynamic theory. A prospective, two-armed, single-blind, randomized controlled trial compared management aided by a web-based dose calculator (NextDose) with standard clinical care. Participants were 240 adults receiving warfarin therapy following cardiac surgery, followed up until the first outpatient appointment at least 3 months after warfarin initiation. We compared the percentage of time spent in the international normalized ratio acceptable range (%TIR) during the first 28 days following warfarin initiation, and %TIR and count of bleeding events over the entire follow-up period. Two hundred thirty-four participants were followed up to day 28 (NextDose: 116 and standard of care: 118), and 228 participants (114 per arm) were followed up to the final study visit. Median %TIR tended to be higher for participants receiving NextDose guided warfarin management during the first 28 days (63 vs. 56%, P = 0.13) and over the entire follow-up period (74 vs. 71%, P = 0.04). The hazard of clinically relevant minor bleeding events was lower for participants in the NextDose arm (hazard ratio: 0.21, P = 0.041). In NextDose, there were 89.3% of proposed doses accepted by prescribers. NextDose guided dose management in cardiac surgery patients requiring warfarin was associated with an increase in %TIR across the full follow-up period and fewer hemorrhagic events. A theory-based, pharmacologically guided approach facilitates higher quality warfarin anticoagulation. An important practical benefit is a reduced requirement for clinical experience of warfarin management.

CircUSP1 as a novel marker promotes gastric cancer progression via stabilizing HuR to upregulate USP1 and Vimentin.

Circular RNAs (circRNAs) play a crucial role in regulating various tumors. However, their biological functions and mechanisms in gastric cancer (GC) have not been well understood. Here, we discovered a stable cytoplasmic circRNA named circUSP1 (hsa_circ_000613) in GC. CircUSP1 upregulation in GC tissues was correlated with tumor size and differentiation. We observed that circUSP1 promoted GC growth and metastasis. Mechanistically, circUSP1 mainly interacted with the RRM1 domain of an RNA-binding protein (RBP) called HuR, stabilizing its protein level by inhibiting ß-TrCP-mediated ubiquitination degradation. The oncogenic properties of HuR mediated promotive effects of circUSP1 in GC progression. Moreover, we identified USP1 and Vimentin as downstream targets of HuR in post-transcriptional regulation, mediating the effects of circUSP1. The parent gene USP1 also enhanced the viability and mobility of GC cells. Additionally, tissue-derived circUSP1 could serve as an independent prognostic factor for GC, while plasma-derived circUSP1 showed promise as a diagnostic biomarker, outperforming conventional markers including serum alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA) and carbohydrate antigen 199 (CA19-9). Our study highlights that circUSP1 promotes GC progression by binding to and stabilizing oncogenic HuR, thereby facilitating the upregulation of USP1 and Vimentin at the post-transcriptional level. These findings suggest that circUSP1 could be a potential therapeutic target and a diagnostic and prognostic biomarker for GC.

Distribution and roles of Ligilactobacillus murinus in hosts.

Ligilactobacillus murinus, a member of the Ligilactobacillus genus, holds significant potential as a probiotic. While research on Ligilactobacillus murinus has been relatively limited compared to well-studied probiotic lactic acid bacteria such as Limosilactobacillus reuteri and Lactobacillus gasseri, a mounting body of evidence highlights its extensive involvement in host intestinal metabolism and immune activities. Moreover, its abundance exhibits a close correlation with intestinal health. Notably, beyond the intestinal context, Ligilactobacillus murinus is gaining recognition for its contributions to metabolism and regulation in the oral cavity, lungs, and vagina. As such, Ligilactobacillus murinus emerges as a potential probiotic candidate with a pivotal role in supporting host well-being. This review delves into studies elucidating the multifaceted roles of Ligilactobacillus murinus. It also examines its medicinal potential and associated challenges, underscoring the imperative to delve deeper into unraveling the mechanisms of its actions and exploring its health applications.

Silver nanoparticles induce iron accumulation-associated cognitive impairment via modulating neuronal ferroptosis.

Silver nanoparticles (AgNPs) are widely used in daily life and medical fields owing to their unique physicochemical properties. Daily exposure to AgNPs has become a great concern regarding their potential toxicity to human beings, especially to the central nervous system. Ferroptosis, a newly recognized programmed cell death, was recently reported to be associated with the neurodegenerative process. However, whether and how ferroptosis contributes to AgNPs-induced neurotoxicity remain unclear. In this study, we investigated the role of ferroptosis in neurotoxic effects induced by AgNPs using in vitro and in vivo models. Our results showed that AgNPs induced a notable dose-dependent cytotoxic effect on HT-22 cells and cognitive impairment in mice as indicated by a decline in learning and memory and brain tissue injuries. These findings were accompanied by iron overload caused by the disruption of the iron transport system and activation of NCOA4-mediated autophagic degradation of ferritin. The excessive free iron subsequently induced GSH depletion, loss of GPX and SOD activities, differential expression of Nrf2 signaling pathway elements, down-regulation of GPX4 protein and production of lipid peroxides, initiating ferroptosis cascades. The mitigating effects of ferrostatin-1 and deferoxamine on iron overload, redox imbalance, neuronal cell death, impairment of mice learning and memory, Aß deposition and synaptic plasticity reduction suggested ferroptosis as a potential molecular mechanism in AgNPs-induced neurotoxicity. Taken together, these results demonstrated that AgNPs induced neuronal cell death and cognitive impairment with Aß deposition and reduction of synaptic plasticity, which were mediated by ferroptosis caused by iron-mediated lipid peroxidation. Our study provides new insights into the underlying mechanisms of AgNPs-induced neurotoxicity and predicts potential preventive strategies.

Continuous renal replacement therapy improves indicators and short-term survival in people with AIDS manifesting sepsis and acute kidney injury.

Acquired immune deficiency syndrome (AIDS) is susceptible to numerous complications such as sepsis and acute kidney injury (AKI), leading to adverse outcomes. Continuous renal replacement therapy (CRRT) is becoming increasingly popular in the treatment of sepsis and AKI. This study aimed to verify the effectiveness of CRRT in the treatment of AIDS with sepsis and AKI, to provide new directions for the treatment of severe AIDS. Data of 74 people with AIDS, sepsis and AKI were collected. They were divided into CRRT and non-CRRT groups. There was no difference in indicators between the two groups at admission. Vital signs, PH, serum potassium, renal function, blood lactate, APACHE II score, and SOFA score in CRRT group demonstrated significant improvements over those in the non-CRRT group both 24 and 72 hours after admission (P＜0.05). Level of Interleukin 6 and procalcitonin declined more significantly in CRRT group 72 hours after admission (P＜0.05). CRRT group had a higher 28-day survival rate (P＜0.05). CRRT improves the clinical indicators and increases the short-term survival rate of people with AIDS, sepsis and AKI.

Prevalence and causes of blindness and distance visual impairment in Chinese adult population in 2022 during the COVID-19 pandemic: a cross-sectional study.

This cross-sectional study aims to investigate the prevalence and causes of visual impairment (VI) and blindness in Jiangsu Province, China in 2022 during the COVID-19 pandemic. Participants (n = 13,208, aged 18-93) underwent comprehensive ocular examinations. The prevalence and causes of binocular VI (presenting visual acuity [VA] ≥ 20/400 and < 20/63 in the better eye) and blindness (presenting VA < 20/400 in the better eye) were assessed according to the World Health Organization (WHO) criteria. The estimation of refractive error prevalence was conducted using the following classification: myopia ≤ - 0.50 diopters (D), high myopia ≤ - 6.00 D, hyperopia ≥ 0.50 D, and anisometropia ≥ 1.00 D. The overall prevalence of binocular VI and blindness was 21.04% (95% confidence interval [CI] 20.35-21.74%) and 0.47% (95% CI 0.37-0.60%). The highest prevalence of binocular VI was in the population aged 18-24 years old (46.29%, [95% CI 44.30-48.28%]), those with education at university and above (43.47%, [95% CI 41.93-45.02%]), students (54.96%, [95% CI 52.73-57.17%]). Uncorrected refractive error (URE) was the leading cause of presenting binocular VI (93.40%) and blindness (50.79%). The prevalence of myopia was 54.75% (95% CI 53.90-55.60%). Actions are needed to control URE and myopia within the adult Chinese population, with a particular emphasis on the younger, well-educated demographic.

FBP1 inhibits NSCLC stemness by promoting ubiquitination of Notch1 intracellular domain and accelerating degradation.

The existence of cancer stem cells is widely acknowledged as the underlying cause for the challenging curability and high relapse rates observed in various tumor types, including non-small cell lung cancer (NSCLC). Despite extensive research on numerous therapeutic targets for NSCLC treatment, the strategies to effectively combat NSCLC stemness and achieve a definitive cure are still not well defined. The primary objective of this study was to examine the underlying mechanism through which Fructose-1,6-bisphosphatase 1 (FBP1), a gluconeogenic enzyme, functions as a tumor suppressor to regulate the stemness of NSCLC. Herein, we showed that overexpression of FBP1 led to a decrease in the proportion of CD133-positive cells, weakened tumorigenicity, and decreased expression of stemness factors. FBP1 inhibited the activation of Notch signaling, while it had no impact on the transcription level of Notch 1 intracellular domain (NICD1). Instead, FBP1 interacted with NICD1 and the E3 ubiquitin ligase FBXW7 to facilitate the degradation of NICD1 through the ubiquitin-proteasome pathway, which is independent of the metabolic enzymatic activity of FBP1. The aforementioned studies suggest that targeting the FBP1-FBXW7-NICD1 axis holds promise as a therapeutic approach for addressing the challenges of NSCLC recurrence and drug resistance.

Improving Efficiency of Iso-Surface Extraction on Implicit Neural Representations Using Uncertainty Propagation.

Implicit Neural representations (INRs) are widely used for scientific data reduction and visualization by modeling the function that maps a spatial location to a data value. Without any prior knowledge about the spatial distribution of values, we are forced to sample densely from INRs to perform visualization tasks like iso-surface extraction which can be very computationally expensive. Recently, range analysis has shown promising results in improving the efficiency of geometric queries, such as ray casting and hierarchical mesh extraction, on INRs for 3D geometries by using arithmetic rules to bound the output range of the network within a spatial region. However, the analysis bounds are often too conservative for complex scientific data. In this paper, we present an improved technique for range analysis by revisiting the arithmetic rules and analyzing the probability distribution of the network output within a spatial region. We model this distribution efficiently as a Gaussian distribution by applying the central limit theorem. Excluding low probability values, we are able to tighten the output bounds, resulting in a more accurate estimation of the value range, and hence more accurate identification of iso-surface cells and more efficient iso-surface extraction on INRs. Our approach demonstrates superior performance in terms of the iso-surface extraction time on four datasets compared to the original range analysis method and can also be generalized to other geometric query tasks.

A New and Practical Model of Human-like Ascending Aorta Aneurysm in Rats.

INTRODUCTION: Ascending aortic aneurysm is a serious health risk. In order to study ascending aortic aneurysms, elastase and calcium ion treatment for aneurysm formation are mainly used, but their aneurysm formation time is long, the aneurysm formation rate is low. Thus, this study aimed to construct a rat model of ascending aorta aneurysm with a short modeling time and high aneurysm formation rate, which may mimic the pathological processes of human ascending aorta aneurysm. METHODS: Cushion needles with different pipe diameters (1.0, 1.2, 1.4 and 1.6 mm) were used to establish a human-like rat model of ascending aortic aneurysm by narrowing the ascending aorta of rats and increasing the force of blood flow on the vessel wall. The vascular diameters were evaluated using color Doppler ultrasonography after two weeks. The characteristics of ascending aortic aneurysm in rats were detected by Masson's trichrome staining, Verhoeff's Van Gieson staining and hematoxylin and eosin staining while RT-PCR were utilized to assess the total RNA of cytokine interleukin-1ß, interleukin 6, transforming growth factor-beta1 and metalloproteinase 2. RESULTS: Two weeks after surgery, the ultrasound images and the statistical analysis demonstrated that the diameter of the ascending aorta in rats increased more than 1.5 times, similar to that in humans, indicating the success of animal modeling of ascending aortic aneurysm. Moreover, the optimal constriction diameter of the ascending aortic aneurysm model is 1.4 mm by the statistical analysis of the rate of ascending aortic aneurysm and mortality rate in rats with different constriction diameters. CONCLUSIONS: The human-like ascending aortic aneurysm model developed in this study can be used for the studies of the pathological processes and mechanisms in ascending aortic aneurysm in a more clinically relevant fashion.

Emerging horizons and prospects of polysaccharide-constructed gels in the realm of wound healing.

Polysaccharides, with the abundant availability, biodegradability, and inherent safety, offer a vast array of promising applications. Leveraging the remarkable attributes of polysaccharides, biomimetic and multifunctional hydrogels have emerged as a compelling avenue for efficacious wound dressing. The gels emulate the innate extracellular biomatrix as well as foster cellular proliferation. The distinctive structural compositions and profusion of functional groups within polysaccharides confer excellent physical/chemical traits as well as distinct restorative involvements. Gels crafted from polysaccharide matrixes serve as a robust defense against bacterial threats, effectively shielding wounds from harm. This comprehensive review delves into wound physiology, accentuating the significance of numerous polysaccharide-based gels in the wound healing context. The discourse encompasses an exploration of polysaccharide hydrogels tailored for diverse wound types, along with an examination of various therapeutic agents encapsulated within hydrogels to facilitate wound repair, incorporating recent patent developments. Within the scope of this manuscript, the perspective of these captivating gels for promoting optimal healing of wounds is vividly depicted. Nevertheless, the pursuit of knowledge remains ongoing, as further research is warranted to bioengineer progressive polysaccharide gels imbued with adaptable features. Such endeavors hold the promise of unlocking substantial potential within the realm of wound healing, propelling us toward multifaceted and sophisticated solutions.

Precision cardiac targeting: empowering curcumin therapy through smart exosome-mediated drug delivery in myocardial infarction.

Nanoparticle-mediated drug delivery has emerged as a highly promising and effective therapeutic approach for addressing myocardial infarction. However, clinical translation tends to be a failure due to low cardiac retention as well as liver and spleen entrapment in previous therapies. Herein, we report a two-step exosome delivery system, which precludes internalization by the mononuclear phagocyte system before the delivery of therapeutic cardiac targeting exosomes (ExoCTP). Importantly, curcumin released by ExoCTP diminishes reactive oxygen species over-accumulation in ischemic myocardium, as well as serum levels of lactate dehydrogenase, malonyldialdehyde, superoxide dismutase and glutathione, indicating better antioxidant capacity than free curcumin. Finally, our strategy was proven to greatly potentiate the delivery and therapeutic efficacy of curcumin without systemic toxicity. Taken together, our smart exosome-mediated drug delivery strategy can serve either as therapeutics alone or in combination with other drugs for effective heart targeting and subsequent wound healing.

Development of a Magnetically-Assisted SERS Biosensor for Rapid Bacterial Detection.

Introduction: Ultrasensitive bacterial detection methods are crucial to ensuring accurate diagnosis and effective clinical monitoring, given the significant threat bacterial infections pose to human health. The aim of this study is to develop a biosensor with capabilities for broad-spectrum bacterial detection, rapid processing, and cost-effectiveness. Methods: A magnetically-assisted SERS biosensor was designed, employing wheat germ agglutinin (WGA) for broad-spectrum recognition and antibodies for specific capture. Gold nanostars (AuNSs) were sequentially modified with the Raman reporter molecules and WGA, creating a versatile SERS tag with high affinity for a diverse range of bacteria. Staphylococcus aureus (S. aureus) and Pseudomonas aeruginosa (P. aeruginosa) antibody-modified Fe3O4 magnetic gold nanoparticles (MGNPs) served as the capture probes. Target bacteria were captured by MGNPs and combined with SERS tags, forming a "sandwich" composite structure for bacterial detection. Results: AuNSs, with a core size of 65 nm, exhibited excellent storage stability (RSD=5.6%) and demonstrated superior SERS enhancement compared to colloidal gold nanoparticles. Efficient binding of S. aureus and P. aeruginosa to MGNPs resulted in capture efficiencies of 89.13% and 85.31%, respectively. Under optimized conditions, the developed assay achieved a limit of detection (LOD) of 7 CFU/mL for S. aureus and 5 CFU/mL for P. aeruginosa. The bacterial concentration (10-106 CFU/mL) showed a strong linear correlation with the SERS intensity at 1331 cm-1. Additionally, high recoveries (84.8% - 118.0%) and low RSD (6.21% - 11.42%) were observed in spiked human urine samples. Conclusion: This study introduces a simple and innovative magnetically-assisted SERS biosensor for the sensitive and quantitative detection of S. aureus or P. aeruginosa, utilizing WGA and antibodies. The developed biosensor enhances the capabilities of the "sandwich" type SERS biosensor, offering a novel and effective platform for accurate and timely clinical diagnosis of bacterial infections.

Adaptively Placed Multi-Grid Scene Representation Networks for Large-Scale Data Visualization.

Scene representation networks (SRNs) have been recently proposed for compression and visualization of scientific data. However, state-of-the-art SRNs do not adapt the allocation of available network parameters to the complex features found in scientific data, leading to a loss in reconstruction quality. We address this shortcoming with an adaptively placed multi-grid SRN (APMGSRN) and propose a domain decomposition training and inference technique for accelerated parallel training on multi-GPU systems. We also release an open-source neural volume rendering application that allows plug-and-play rendering with any PyTorch-based SRN. Our proposed APMGSRN architecture uses multiple spatially adaptive feature grids that learn where to be placed within the domain to dynamically allocate more neural network resources where error is high in the volume, improving state-of-the-art reconstruction accuracy of SRNs for scientific data without requiring expensive octree refining, pruning, and traversal like previous adaptive models. In our domain decomposition approach for representing large-scale data, we train an set of APMGSRNs in parallel on separate bricks of the volume to reduce training time while avoiding overhead necessary for an out-of-core solution for volumes too large to fit in GPU memory. After training, the lightweight SRNs are used for realtime neural volume rendering in our open-source renderer, where arbitrary view angles and transfer functions can be explored. A copy of this paper, all code, all models used in our experiments, and all supplemental materials and videos are available at https://github.com/skywolf829/APMGSRN.

PSRFlow: Probabilistic Super Resolution with Flow-Based Models for Scientific Data.

Although many deep-learning-based super-resolution approaches have been proposed in recent years, because no ground truth is available in the inference stage, few can quantify the errors and uncertainties of the super-resolved results. For scientific visualization applications, however, conveying uncertainties of the results to scientists is crucial to avoid generating misleading or incorrect information. In this paper, we propose PSRFlow, a novel normalizing flow-based generative model for scientific data super-resolution that incorporates uncertainty quantification into the super-resolution process. PSRFlow learns the conditional distribution of the high-resolution data based on the low-resolution counterpart. By sampling from a Gaussian latent space that captures the missing information in the high-resolution data, one can generate different plausible super-resolution outputs. The efficient sampling in the Gaussian latent space allows our model to perform uncertainty quantification for the super-resolved results. During model training, we augment the training data with samples across various scales to make the model adaptable to data of different scales, achieving flexible super-resolution for a given input. Our results demonstrate superior performance and robust uncertainty quantification compared with existing methods such as interpolation and GAN-based super-resolution networks.