Search

Objective In acupuncture therapy, the accurate location of acupoints is essential for its effectiveness. The advanced language understanding capabilities of large language models (LLMs) like Generative Pre-trained Transformers (GPTs) and Llama present a significant opportunity for extracting relations related to acupoint locations from textual knowledge sources. This study aims to explore the performance of LLMs in extracting acupoint-related location relations and assess the impact of fine-tuning on GPT's performance. Materials and Methods We utilized the World Health Organization Standard Acupuncture Point Locations in the Western Pacific Region (WHO Standard) as our corpus, which consists of descriptions of 361 acupoints. Five types of relations ("direction_of", "distance_of", "part_of", "near_acupoint", and "located_near") (n  = 3174) between acupoints were annotated. Four models were compared: pre-trained GPT-3.5, fine-tuned GPT-3.5, pre-trained GPT-4, as well as pretrained Llama 3. Performance metrics included micro-average exact match precision, recall, and F1 scores. Results Our results demonstrate that fine-tuned GPT-3.5 consistently outperformed other models in F1 scores across all relation types. Overall, it achieved the highest micro-average F1 score of 0.92. Discussion The superior performance of the fine-tuned GPT-3.5 model, as shown by its F1 scores, underscores the importance of domain-specific fine-tuning in enhancing relation extraction capabilities for acupuncture-related tasks. In light of the findings from this study, it offers valuable insights into leveraging LLMs for developing clinical decision support and creating educational modules in acupuncture. Conclusion This study underscores the effectiveness of LLMs like GPT and Llama in extracting relations related to acupoint locations, with implications for accurately modeling acupuncture knowledge and promoting standard implementation in acupuncture training and practice. The findings also contribute to advancing informatics applications in traditional and complementary medicine, showcasing the potential of LLMs in natural language processing. [ABSTRACT FROM AUTHOR]

The over-track complex structures are driven by transit-oriented urban development, leading to the necessity for advanced seismic performance upgrades. An innovative solution is presented in this study, involving the negative-stiffness amplification system-enabled isolation system (NSAS-IS) with nonlinear viscous damping to establish a flexible isolation layer beneath over-track buildings. The multi-benefit-based design procedure and easy-to-use formula are developed. Its effectiveness and comparative superiority over conventional ones, particularly in mitigating negative effects of over-track buildings on lower podiums, is confirmed by case studies. NSAS-IS with an optimized nonlinear viscous damping exponent exhibits a significant reduction in isolation-layer displacement and robustness against earthquakes. [ABSTRACT FROM AUTHOR]

Background: Shengxuebao mixture (SXBM) is a novel herbal drug approved by China State Food and Drug Administration for the treatment of Leukopenia and iron deficiency anemia caused by radiotherapy and chemotherapy. Methods: To explore the mechanism of SXBM in treating blood deficiency syndrome (BDS). Firstly, network pharmacology and in vivo experiments were used to screen candidate targets and important signaling pathways of SXBM, GO functional enrichment and KEGG pathway analysis were performed. Secondly, a BDS rat model was established to verify the results of the analysis of network pharmacological enrichment. Histopathology and routine peripheral blood examination were observed. The expressions of tumor necrosis factor-α, interleukin (IL)-6, HIF-1α and NF-κB were detected by Western blot, and the expressions of IL-6, IL-1β were detected by ELISA. Results: 62 bioactive components, 66 potential targets and 131 signaling pathways of BDS were successfully identified by network pharmacology. Molecular docking simulation techniques showed that key targets tumor necrosis factor-α, IL-6, IL-1β can dock well with crucial components, and the BDS-related signaling pathways HIF-1 and JAK-STAT play a vital role. The combined model experiment of acetylphenylhydrazine and cyclophosphamide showed that the model group had obvious blood deficiency, and the histopathology and blood routine were effectively restored after administration. Our findings indicate that SXBM's therapeutic effect on BDS primarily involves the mediation of the HIF-1α/NF-κB signaling pathway and the regulation of hematopoietic factor expression. Conclusion: This study not only affirmed the protective properties of SXBM against BDS but also provided insights into a potential mechanism for blood replenishment in the treatment of BDS using SXBM. [ABSTRACT FROM AUTHOR]

Advanced glycation end products (AGEs) play a pivotal role in the aging process, regarded as a hallmark of aging. Despite their significance, the absence of adequate monitoring tools has hindered the exploration of the relationship between AGEs and aging. Here, we present a novel AGE-selective probe, AGO, for the first time. AGO exhibited superior sensitivity in detecting AGEs compared to the conventional method of measuring autofluorescence from AGEs. Furthermore, we validated AGO's ability to detect AGEs based on kinetics, demonstrating a preference for ribose-derived AGEs. Lastly, AGO effectively visualized glycation products in a collagen-based mimicking model of glycation. We anticipate that this study will enhance the molecular tool sets available for comprehending the physiological processes of AGEs during aging. [ABSTRACT FROM AUTHOR]

To investigate how effectively systemic immune-inflammation index (SII) and Monocyte-to-HDL-cholesterol ratio (MHR) predict the development of early cardio-cerebral complications in elderly patients who have experienced acute severe carbon monoxide poisoning (ASCMP). A retrospective analysis was conducted on 77 elderly patients with ASCMP admitted to the emergency department of Harrison International Peace Hospital from November 2020 to March 2022. The prevalence of early-onset complications among the 77 individuals was 38.96%. Binary Logistics regression analysis showed that SII and MHR were independent influencing factors of early cardio-cerebral complications in elderly patients with ASCMP. The complication group had a longer length of stay, a greater mortality rate, and a higher incidence of delayed encephalopathy after acute carbon monoxide poisoning (p <.05) than the non-complication group. The area under the curve (AUC) of SII and MHR in predicting early cardio-cerebral complications in elderly patients with ASCMP were 0.724 and 0.796, respectively, with 80.0% and 63.3% sensitivity, and 61.7% and 87.2% specificity. The incidence of early cardio-cerebral complications in elderly patients who had ASCMP is high and the prognosis is poor. SII and MHR can be utilized as independent predictors of early cardio-cerebral complications in elderly patients with ASCMP, allowing doctors to diagnose and treat cardio-cerebral complications earlier and improve prognosis. [ABSTRACT FROM AUTHOR]

Objective To examine the levels of systemic inflammatory response index (SIRI) and serum lipoprotein-associated phospholipase A2 (Lp-PLA2) in patients with acute carbon monoxide poisoning (ACOP), and to explore the predictive value of SIRI, Lp-PLA2 and their combination for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP). Methods Total 265 patients with ACOP diagnosed and treated in Harrison International Peace Hospital of Hebei Medical University, The Second People's Hospital of Hengshui and The No.4 People's Hospital of Hengshui from March 2020 to March 2023 were included. SIRI and serum Lp-PLA2 levels were measured. According to the occurrence of DEACMP, they were divided into DEACMP group (n = 32) and non -DEACMP group (n = 233), while according to the degree of poisoning, they were divided into mild poisoning group (n = 20), moderate poisoning group (n = 107) and severe poisoning group (n = 138). Univariate and multivariate Logistic regression analyses were used to screen the risk factors of DEACMP in patients with ACOP, and the receiver operating characteristic (ROC) curve was drawn to evaluate the predictive efficacy of SIRI, Lp - PLA2 and their combination for DEACMP. Results The levels of SIRI (t = 13.068, P = 0.000) and serum Lp-PLA2 (t = 8.208, P = 0.000) in DEACMP group were higher than those in non-DEACMP group, and their levels gradually increased with the severity of poisoning, the levels of SIRI (t = 8.764, P = 0.000; t = 4.586, P = 0.000) and Lp-PLA2 (t = 3.726, P = 0.000; t = 2.038, P = 0.044) in the severe poisoning group and moderate poisoning group were higher than those in the mild poisoning group, and the levels of SIRI and serum Lp-PLA2 in the severe poisoning group were also higher than those in the moderate poisoning group (t = 10.294, P = 0.000; t = 2.700, P = 0.007). Logistic regression analysis showed the severe poisoning (OR = 11.695, 95%CI: 4.893-39.994; P = 0.000), SIRI increased (OR = 1.600, 95%CI: 1.033-2.476; P = 0.001) and Lp-PLA2 increased (OR = 11.302, 95%CI: 1.486-38.933; P = 0.000) were risk factors of DEACMP in patients with ACOP. ROC curve showed that area under the curve (AUC) predicted by Lp-PLA2, SIRI and their combination were 0.82 (95%CI: 0.754-0.894, P = 0.000), 0.82 (95%CI: 0.739-0.895, P = 0.000) and 0.87 (95%CI: 0.805-0.934, P = 0.000), sensitivity were 0.66, 0.72 and 0.84, specificity were 0.85, 0.88 and 0.90, respectively. The prediction efficiency of Lp-PLA2 combined with SIRI was better than that of Lp- PLA2 (t = 2.198, P = 0.027) or SIRI (t = 2.268, P = 0.023) alone. Conclusions DEACMP is easy to occur when SIRI and serum Lp-PLA2 were high in patients with ACOP. The combined detection of Lp-PLA2 and SIRI can be used for early screening of DEACMP. [ABSTRACT FROM AUTHOR]

The extensive use of antibiotics in the medical and aquaculture industries has led to antibiotic resistance, be a global public health concern. Compared with soil and water, there are few reports on antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the air. To provide theoretical support for scientific and effective response to the cross-media migration of microbial resistance, this paper comprehensively reviewed the occurrence status, influencing factors and transmission mechanism of ARB and ARGs in different types of ambient air at home and abroad. The results showed that the abundance of ARB and ARGs in the air was affected by environmental conditions and sampling factors. The pollution was more serious in typical polluted areas such as animal farms, sewage treatment plants and hospitals. The dominant types of ARGs in the above environment were tetracyclines, sulfonamides and β-lactams. Among them, the abundance of ARGs in the air of animal farms was about 2-3 orders of magnitude higher than that in other environments. The highest abundance was found in pig farm compared to other animal houses. At present, there was still no standard for the sampling requirements of ARB and ARGs in the air. The sampling season, duration, particle size and coexisting pollutants all affected their detection. Air pollution, soil water content, rainfall and air mass movement were proved to play a certain role in affecting the spread of ARB and ARGs in the air. Based on it, the research on the migration mechanism of ARB and ARGs at the soil-air interface needs to be further intensified. The review aimed to comprehensively reveal the occurrence characteristics of ARB and ARGs in the air, and provide theoretical support for the scientific and effective response to the cross-media migration of microbial resistance. [ABSTRACT FROM AUTHOR]

Yucca belongs to the Yucca genus of the Agave family and is a versatile plant that is edible, medicinal, and ornamental. Yucca extract contains rich saponins, polyphenols and polysaccharides as well as other active ingredients. As a natural, green and safe new feed additive, Yucca extract can fulfill a variety of biological functions in animal production, such as promoting growth, improving reproductive performance, improving feed conversion, regulating the gastrointestinal environment, improving the breeding environment, etc., and has good application prospects in the field of animal husbandry. The article introduces the main active ingredients, chemical structure, biological functions of Yucca extract and its application in animal production, and discusses the possible problems of Yucca extract feed additives, to provide references for further research and application of Yucca extract in animal production. [ABSTRACT FROM AUTHOR]

Although Vibrio parahaemolyticus (V. parahaemolyticus) is a pathogen frequently found in seafood, there is a possibility of its presence in other foods, such as dairy products. The main virulence factors of V. parahaemolyticus are thermostable direct hemolysins (TDHs) which are lethal toxins, so it is necessary to establish qualitative and quantitative methods for determining TDHs. HPLC-ESI-TOF was employed to establish a method for identifying TDHs. The identification and quantification ions of TDHs were confirmed by HPLC-ESI-TOF. The method was developed for detecting TDHs in milk powder using HPLC-ESI-TOF in this paper, and limits of detection (were between 0.20 and 0.40 mg/kg, limits of quantitation were between 0.5 and 1.0 mg/kg and recoveries of all TDHs were between from 78% to 94% with relative standard deviation lower than 10%. This research will provide a reference for developing methods of HPLC-MS/MS to detect TDHs in food samples, which can provide a tool for the government to monitor TDHs contamination in foods. [ABSTRACT FROM AUTHOR]

The synergization of 3D graphene with magnetic nanoparticles provides effective strategies to shield electromagnetic waves. However, the uniform distribution of magnetic nanoparticles within the 3D graphene network still remains a great challenge, owing to the agglomeration tendency of the magnetic nanoparticles. Herein, we report a facile method to in situ fabricate 3D graphene decorated with highly dispersed nickel nanoparticles (Ni NPs) by laser conversion from the polyimide/Ni(II) precursor film. In this process, 3D graphene was generated by CO2 laser scribing of the polyimide film, accompanied by carbothermal reduction of Ni(II) to form Ni NPs. Significantly, in the precursor film, carboxylate ions were introduced to complex with Ni(II), leading to a uniform dispersion of Ni(II), thus Ni NPs with high dispersibility in 3D graphene networks were achieved after laser fabrication. As a result, massive heterogeneous interfaces and dense magnetic coupling networks were realized in the graphene/Ni composite, which is conducive to improving polarization loss and magnetic loss for the dissipation of incident electromagnetic waves. Combined with the multiple electromagnetic wave dissipation paths provided by 3D graphene, the graphene/Ni composite exhibits absorption-dominated electromagnetic interference shielding effectiveness (EMI SE). At an Ni content of 5.3 wt%, the EMI SE of the double-layer graphene/Ni composite was 94 dB with an adsorption ratio of 91% in the X-band. Such a high EMI SE value will pave the way for practical applications of 3D graphene in EMI shielding. [ABSTRACT FROM AUTHOR]

Fluorescent bioprobes are invaluable tools for visualizing live cells and deciphering complex biological processes by targeting intracellular biomarkers without disrupting cellular functions. In addition to protein-binding concepts, fluorescent probes utilize various mechanisms, including membrane, metabolism, and gating-oriented strategies. This study introduces a novel fluorescent mechanism distinct from existing ways. Here, we developed a B cell selective probe, CDrB, with unique transport mechanisms. Through SLC-CRISPRa screening, we identified two transporters, SLCO1B3 and SLC25A41, by sorting out populations exhibiting higher and lower fluorescence intensities, respectively, demonstrating contrasting activities. We confirmed that SLCO1B3, with comparable expression levels in T and B cells, facilitates the transport of CDrB into cells, while SLC25A41, overexpressed in T lymphocytes, actively exports CDrB. This observation suggests that SLC25A41 plays a crucial role in discriminating between T and B lymphocytes. Furthermore, it reveals the potential for the reversible localization of SLC25A41 to demonstrate its distinct activity. This study is the first report to unveil a novel strategy of SLC by exporting the probe. We anticipate that this research will open up new avenues for developing fluorescent probes. [ABSTRACT FROM AUTHOR]

The development of a small‐molecule probe designed to selectively target neurons would enhance the exploration of intricate neuronal structures and functions. Among such probes, NeuO stands out as the pioneer and has gained significant traction in the field of research. Nevertheless, neither the mechanism behind neuron‐selectivity nor the cellular localization has been determined. Here, we introduce NeuM, a derivative of NeuO, designed to target neuronal cell membranes. Furthermore, we elucidate the mechanism behind the selective neuronal membrane trafficking that distinguishes neurons. In an aqueous buffer, NeuM autonomously assembles into micellar structures, leading to the quenching of its fluorescence (Φ=0.001). Upon exposure to neurons, NeuM micelles were selectively internalized into neuronal endosomes via clathrin‐mediated endocytosis. Through the endocytic recycling pathway, NeuM micelles integrate into neuronal membrane, dispersing fluorescent NeuM molecules in the membrane (Φ=0.61). Molecular dynamics simulations demonstrated that NeuM, in comparison to NeuO, possesses optimal lipophilicity and molecular length, facilitating its stable incorporation into phospholipid layers. The stable integration of NeuM within neuronal membrane allows the prolonged monitoring of neurons, as well as the visualization of intricate neuronal structures. [ABSTRACT FROM AUTHOR]

The development of a small‐molecule probe designed to selectively target neurons would enhance the exploration of intricate neuronal structures and functions. Among such probes, NeuO stands out as the pioneer and has gained significant traction in the field of research. Nevertheless, neither the mechanism behind neuron‐selectivity nor the cellular localization has been determined. Here, we introduce NeuM, a derivative of NeuO, designed to target neuronal cell membranes. Furthermore, we elucidate the mechanism behind the selective neuronal membrane trafficking that distinguishes neurons. In an aqueous buffer, NeuM autonomously assembles into micellar structures, leading to the quenching of its fluorescence (Φ=0.001). Upon exposure to neurons, NeuM micelles were selectively internalized into neuronal endosomes via clathrin‐mediated endocytosis. Through the endocytic recycling pathway, NeuM micelles integrate into neuronal membrane, dispersing fluorescent NeuM molecules in the membrane (Φ=0.61). Molecular dynamics simulations demonstrated that NeuM, in comparison to NeuO, possesses optimal lipophilicity and molecular length, facilitating its stable incorporation into phospholipid layers. The stable integration of NeuM within neuronal membrane allows the prolonged monitoring of neurons, as well as the visualization of intricate neuronal structures. [ABSTRACT FROM AUTHOR]

Hybrid genomes usually harbor asymmetrical parental contributions. However, it is challenging to infer the functional significance of asymmetrical retention of parental alleles in hybrid populations of conifer trees. Here we investigated the diversity in the glutathione S‐transferase (GST) gene family in a hybrid pine Pinus densata and its parents (Pinus tabuliformis and Pinus yunnanensis). Plant GSTs play major roles in protecting plants against biotic and abiotic stresses. In this study, 19 orthologous groups of GST genes were identified and cloned from these three species. We examined their expression in different tissues, and then purified the corresponding proteins to characterize their enzymatic activities and specificities toward different substrates. We found that among the 19 GST orthologous groups, divergence in gene expression and in enzymatic activities toward different substrates was prevalent. P. densata preferentially retained P. yunnanensis‐like GSTs for 17 out of the 19 gene loci. We determined the first GST crystal structure from conifer species at a resolution of 2.19 Å. Based on this structure, we performed site‐directed mutagenesis to replace amino acid residuals in different wild‐types of GSTs to understand their functional impacts. Reciprocal replacement of amino acid residuals in native GSTs of P. densata and P. tabuliformis demonstrated significant changes in enzyme functions and identified key sites controlling GSTs activities. This study illustrates an approach to evaluating the functional significance of sequence variations in conifer genomes. Our study also sheds light on plausible mechanisms for controlling the selective retention of parental alleles in the P. densata genome. [ABSTRACT FROM AUTHOR]

Currently, there are still no definitive consensus in the treatment of intrahepatic cholangiocarcinoma (iCCA). This study aimed to build a clinical decision support tool based on machine learning using the Surveillance, Epidemiology, and End Results (SEER) database and the data from the Fifth Medical Center of the PLA General Hospital in China. 4,398 eligible patients from the SEER database and 504 eligible patients from the hospital data, who presented with histologically proven iCCA, were enrolled for modeling by cross-validation based on machine learning. All the models were trained using the open-source Python library scikit-survival version 0.16.0. Shapley additive explanations method was used to help clinicians better understand the obtained results. Permutation importance was calculated using library ELI5. All involved treatment modalities could contribute to a better prognosis. Three models were derived and tested using different data sources, with concordance indices of 0.67, 0.69, and 0.73, respectively. The prediction results were consistent with those under actual situations involving randomly selected patients. Model 2, trained using the hospital data, was selected to develop an online tool, due to its advantage in predicting short-term prognosis. The prediction model and tool established in this study can be applied to predict the prognosis of iCCA after treatment by inputting the patient's clinical parameters or TNM stages and treatment options, thus contributing to optimal clinical decisions. A prognostic model related to disease staging and treatment mode was conducted using the method of machine learning, based on the big data of multi centers. The online calculator can predict the short-term survival prognosis of intrahepatic cholangiocarcinoma, thus, help to make the best clinical decision. The online calculator built to calculate the mortality risk and overall survival can be easily obtained and applied. [ABSTRACT FROM AUTHOR]

Agile hardware design is gaining increasing momentum and bringing new chips in larger quantities to the market faster. However, it also takes new challenges for compiler developers to retarget existing compilers to these new chips in shorter time than ever before. Currently, retargeting a compiler backend, e.g., an LLVM backend to a new target, requires compiler developers to write manually a set of target description files (totalling 10 300+ lines of code (LOC) for RISC-V in LLVM), which is error-prone and time-consuming. In this paper, we introduce a new approach, Automatic Target Description File Generation (ATG), which accelerates the generation of a compiler backend for a new target by generating its target description files automatically. Given a new target, ATG proceeds in two stages. First, ATG synthesizes a small list of target-specific properties and a list of code-layout templates from the target description files of a set of existing targets with similar instruction set architectures (ISAs). Second, ATG requests compiler developers to fill in the information for each instruction in the new target in tabular form according to the list of target-specific properties synthesized and then generates its target description files automatically according to the list of code-layout templates synthesized. The first stage can often be reused by different new targets sharing similar ISAs. We evaluate ATG using nine RISC-V instruction sets drawn from a total of 1 029 instructions in LLVM 12.0. ATG enables compiler developers to generate compiler backends for these ISAs that emit the same assembly code as the existing compiler backends for RISC-V but with significantly less development effort (by specifying each instruction in terms of up to 61 target-specific properties only). [ABSTRACT FROM AUTHOR]

Staphylococcal enterotoxins (SEs) secreted by Staphylococcus aureus (S. aureus) can cause foodborne disease, nausea, vomiting and diarrhea, and even death. Regulation of SE expression is related to accessory gene regulators (Agr). It is important to reveal which environmental factors influence regulation of SE expression to prevent SE food poisoning outbreak. Hence, natural environmental factors which may have an impact on SE expression were selected, such as temperature, food types, strains, and competing strains. Seven strains of S. aureus carrying different SE genes were collected from the Chinese Academy of Inspection and Quarantine (CAIQ) strain bank for study. Strains were cultured with different conditions. Temperature was 8 °C, 22 °C, and 30 °C. Food type was milk powder and nutrient broth. Competing strains were Vibrio parahaemolyticus (V. parahaemolyticus), Escherichia coli (E. coli), and Bacillus cereus (B. cereus). The expression culture solution was pretreated by centrifugation, then determined by using SDS-PAGE, and distinguished SEs apart from each other by HPLC-ESI-TOF. There are 168 samples collected from SE expression culture; the result of SDS-PAGE suggests 23 samples were positive for SEs, and the other 145 samples were negative for SEs. The result of HPLC-ESI-TOF suggests that SEs with similar molecular weight can be distinguished in terms of m/z. The most important factor contributing to regulate expression of SEs was estimated by logistic regressive analysis. The result shows that McFadden R2 is 0.213; p value is 0.000 (p < 0.05); this result illustrates that the model is valid and meaningful. Strains, food types, temperature, and competing strands can explain the 21% change in SE expression. Temperature (z = 3.029, p = 0.002 < 0.01), strains (z = − 3.132, p = 0.002 < 0.01), and food types (z = − 2.415, p = 0.016 < 0.05) have significant impact on SE expression, and the competing strains (z = 1.230, p = 0.219 > 0.05) have no impact on the SE expression. More important impact on SE expression was estimated by OR value; the result shows that strength of temperature influencing on SE expression is bigger than strains and food types in terms of values of OR, temperature (OR = 2.862), strains (OR = 0.641), and food types (OR = 0.561); consequently, temperature is a key factor for stimulating SE expression and had high expression at 30 °C. Therefore, food easily contaminated with S. aureus should be monitored intensively at early and late summer, when proper temperature for expressing SEs may result in S. aureus food poisoning prevalence. [ABSTRACT FROM AUTHOR]

Background: With the global spread of COVID-19, detecting high-risk countries/regions timely and dynamically is essential; therefore, we sought to develop automatic, quantitative and scalable analysis methods to observe and estimate COVID-19 spread worldwide and further generate reliable and timely decision-making support for public health management using a comprehensive modeling method based on multiple mathematical models. Methods: We collected global COVID-19 epidemic data reported from January 23 to September 30, 2020, to observe and estimate its possible spread trends. Countries were divided into three outbreak levels: high, middle, and low. Trends analysis was performed by calculating the growth rate, and then country grouping was implemented using group-based trajectory modeling on the three levels. Individual countries from each group were also chosen to further disclose the outbreak situations using two predicting models: the logistic growth model and the SEIR model. Results: All 187 observed countries' trajectory subgroups were identified using two grouping strategies: with and without population consideration. By measuring epidemic trends and predicting the epidemic size and peak of individual countries, our study found that the logistic growth model generally estimated a smaller epidemic size than the SEIR model. According to SEIR modeling, confirmed cases in each country would take an average of 9–12 months to reach the outbreak peak from the day the first case occurred. Additionally, the average number of cases at the peak time will reach approximately 10–20% of the countries' populations, and the countries with high trends and a high predicted size must pay special attention and implement public health interventions in a timely manner. Conclusions: We demonstrated comprehensive observations and predictions of the COVID-19 outbreak in 187 countries using a comprehensive modeling method. The methods proposed in this study can measure COVID-19 development from multiple perspectives and are generalizable to other epidemic diseases. Furthermore, the methods also provide reliable and timely decision-making support for public health management. [ABSTRACT FROM AUTHOR]

The fluorescent probe pair, NBD-B2 and Styryl-51F, selectively detects NMN over citric acid. NBD-B2 exhibits increased fluorescence, while Styryl-51F shows decreased fluorescence upon NMN addition. Their ratiometric fluorescence change enables highly sensitive and wide-range detection of NMN, effectively distinguishing it not only from citric acid but also other NAD boosters. [ABSTRACT FROM AUTHOR]

The Rayleigh–Bénard convection (RBC) with viscoelastic fluids has captured wide attention in the past decades, caused by its ubiquitous uses in the heat transfer process. However, the numerical technique for simulating the viscoelastic fluid flows developed slowly until recent years because of the numerical instability raised by the hyperbolic characteristics of the viscoelastic constitutive equation. In the present work, a novel numerical scheme was developed to simulate the three-dimension (3D) RBC with viscoelastic fluids, where the quasi-linear treatment was applied to the hyperbolic terms of the momentum equation and the viscoelastic constitutive equation. The in-house solver was also optimized in the aspect of time cost. The results show that the critical value of convection onset in 3D is near to that in the two-dimension (2D); however, the flow pattern displays the wave characteristics in the horizontal direction. The viscoelastic kinetic energy budget of oscillating convection in 3D still conforms to the energy transport law of that in 2D [Zheng et al., Phys. Rev. Fluids 8, 023303 (2023)]. [ABSTRACT FROM AUTHOR]

Enhancing the energy storage capacity of carbon electrodes is a key challenge to developing high-performance supercapacitors. In this study, we design an oxygen-enriched hierarchical nanoporous carbon electrode using laser fabrication and subsequent electrochemical activation, which demonstrates superior energy storage capacity. The carbon electrode is first obtained through the carbonization of phenolic resin under instantaneous high temperature induced by laser, resulting in multiple ion transport channels and a specific capacitance of 64.17 mF cm–2 at the current density of 0.2 mA cm–2. To further improve the performance, electrochemical activation is successfully conducted, leading to a 12.1-fold increase of the specific capacitance of the carbon electrodes. It is found that O–CO-containing functional groups formed during the activation process significantly contribute to the high capacitance enhancement. In a 1 M H2SO4 electrolyte, the activated hierarchical nanoporous carbon electrode delivers a high specific capacitance of 778.3 mF cm–2 under the same test conditions. Additionally, the abundant porous structure and excellent reversibility of redox reaction of the oxygen-containing functional groups enable the assembled supercapacitor to obtain a specific capacitance of 45.3 mF cm–2 at the current density of 0.4 mA cm–2 and maintain a capacitance retention rate of 93.6% after 10,000 charge–discharge tests. This study presents a strategy to prepare carbon electrode materials with both high performance and excellent stability. [ABSTRACT FROM AUTHOR]

Background: Previous studies have shown that cortical superficial siderosis (cSS) can increase hematoma volume and predict poor outcomes following primary intracerebral hemorrhage (ICH). Objective: We aimed to determine whether a large hematoma volume was the essential factor contributing to worse outcomes of cSS. Methods: Patients with spontaneous ICH underwent a CT scan within 48 h after ictus. Evaluation of cSS was performed using magnetic resonance imaging (MRI) within 7 days. The 90-day outcome was assessed using the modified Rankin Scale (mRS). In addition, we investigated the correlation between cSS, hematoma volume, and 90-day outcomes using multivariate regression and mediation analyses. Results: Among the 673 patients with ICH [mean (SD) age, 61 (13) years; 237 female subjects (35.2%); median (IQR) hematoma volume, 9.0 (3.0-17.6) ml], 131 (19.5%) had cSS. There was an association between cSS and larger hematoma volume (β = 4.449, 95% CI 1.890-7.009, p < 0.001) independent of hematoma location and was also related to worse 90-day mRS (β = 0.333, 95% CI 0.008-0.659, p = 0.045) in multivariable regression. In addition, mediation analyses revealed that hematoma volume was an essential factor mediating the effect of cSS on unfavorable 90-day outcomes (proportion mediated:66.04%, p = 0.01). Conclusion: Large hematoma volume was the major charge of directing cSS to worse outcomes in patients with mild to moderate ICH, and cSS was related to a larger hematoma in both lobar and non-lobar areas. [ABSTRACT FROM AUTHOR]

Trimethylamine N-oxide (TMAO), a gut microbiota-dependent metabolite, has been shown to aggravate cardiovascular disease. However, the mechanisms of TMAO in the setting of cardiovascular disease progress remain unclear. Here, we aim to investigate the effects of TMAO on atherosclerosis (AS) development and the underlying mechanisms. Apoe –/– mice received choline or TMAO supplementation in a normal diet and a western diet for 12 weeks. Choline or TMAO supplementation in both normal diet and western diet significantly promoted plaque progression in Apoe–/– mice. Besides, serum lipids levels and inflammation response in the aortic root were enhanced by choline or TMAO supplementation. In particular, choline or TMAO supplementation in the western diet changed intestinal microbiota composition and bile acid metabolism. Therefore, choline or TMAO supplementation may promote AS by modulating gut microbiota in mice fed with a western diet and by other mechanisms in mice given a normal diet, even choline or TMAO supplementation in a normal diet can promote AS. [ABSTRACT FROM AUTHOR]

Oxidative stress is an important pathogenic factor in ulcerative colitis (UC) and colitis-associated colorectal cancer (CAC), further impairing the entire colon. Intestinal epithelial cells (IECs) are crucial components of innate immunity and play an important role in maintaining intestinal barrier function. Recent studies have indicated that microRNA-222-3p (miR-222-3p) is increased in colon of UC and colorectal cancer (CRC) patients, and miR-222-3p is a crucial regulator of oxidative stress. However, whether miR-222-3p influences IEC oxidative stress in UC and CAC remains unknown. This study investigated the effect of miR-222-3p on the regulation of IEC oxidative stress in UC and CAC. An in vitro inflammation model was established in NCM460 colonic cells, mouse UC and CAC models were established in vivo, and IECs were isolated. The biological role and mechanism of miR-222-3p-mediated oxidative stress in UC and CAC were determined. We demonstrated that miR-222-3p expression was notably increased in dextran sulfate sodium (DSS)-induced NCM460 cells and IECs from UC and CAC mice. In vitro, these results showed that the downregulation of miR-222-3p reduced oxidative stress, caspase-3 activity, IL-1b and TNF-a in DSS-induced NCM460 cells. We further identified BRG1 as the target gene of miR-222-3p, and downregulating miR-222-3p alleviated DSS-induced oxidative injury via promoting BRG1-mediated activation Nrf2/HO-1 signaling in NCM460 cells. The in vivo results demonstrated that inhibiting miR-222-3p in IECs significantly relieved oxidative stress and inflammation in the damaged colons of UC and CAC mice, as evidenced by decreases in ROS, MDA, IL-1b and TNF-a levels and increases in GSH-Px levels. Our study further demonstrated that inhibiting miR-222-3p in IECs attenuated oxidative damage by targeting BRG1 to activate the Nrf2/HO-1 signaling. In summary, inhibiting miR-222-3p in IECs attenuates oxidative stress by targeting BRG1 to activate the Nrf2/HO-1 signaling, thereby reducing colonic inflammation and tumorigenesis. [ABSTRACT FROM AUTHOR]

We investigate visual aesthetic style in user-generated content (UGC)—the brand selfie—across cultures (China, Russia, United States), which reflect cultural variations in thinking style (analytic, holistic). Consumers composed three types of brand selfies that differed in perceptual focus, which were later analyzed for aesthetics related to cultural thinking style. Results of two studies show that consumers in these markets tended to design selfies in accordance with culturally ascribed thinking style. Consideration of culture remains important as technology continues to shape consumers' UGC and brand engagement. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the existing computer vision detection technology is difficult to comprehensively and carefully detect the damage status of large wind turbine blades due to the limitation of the field of view, this paper proposes a refined and multi-scale detection method for large-scale wind turbine blades by combining an image stitching algorithm and a deep learning network. First of all, combining the image stitching algorithm with image weighted fusion, images of large wind turbine blades shot in close range are stitched together, so as to realize the clear restoration of the full size and defects of the blades. On this basis, an improved Unet network VGG16Unet is proposed. Combined with transfer learning, the classification and detection of various defects on wind turbine blades under the condition of small dataset training are realized. Finally, by the aid of the combination of the image stitching algorithm and the semantic segmentation network, the refined damage detection of the overall structure of large wind turbine blades is implemented. The research shows that the mean pixel accuracy and the mean intersection over union of the VGG16Unet model are 95.33% and 85.20%, respectively, which is better than the classical semantic segmentation models, fully convolutional neural network model and Unet model. The combination of the VGG16Unet model and the image stitching algorithm not only realizes the global detection of the entire structure but also ensures the detailed detection of each local area, which makes the detection of large wind turbine blades more comprehensive and refined. [ABSTRACT FROM AUTHOR]

The effect of viscoelasticity on the flow and heat transport in the Rayleigh–Bénard convection (RBC), a frequently encountered phenomenon in nature and industry, in a rectangular enclosure with horizontal periodic boundary is investigated via direct numerical simulation. The working fluid is described by a finitely extensible nonlinear elastic-Peterlin constitutive model almost all important features of viscoelastic fluid flow. Numerical simulations are conducted at a low concentration β = 0.9 , where β = μ s / μ 0 , μs is the solvent viscosity, and μ 0 = μ s + μ p is the sum of μs and the polymer viscosity μp. A parametric analysis is performed to understand the influence of the Weissenberg number Wi, the viscosity ratio β, and the extension length L on the oscillating mode of the viscoelastic RBC. The results indicate that both Wi and β weakly inhibit the convection onset and the transition from steady to oscillatory convection. The amplitude and frequency of the oscillations in the oscillatory flow regime are both suppressed. However, the strongly elastic nonlinearity makes the flow transition irregular and even brings about the relaminarization or lead to the convection cells traveling in the horizontal direction. The increasing extension length L induces multiple pairs of roll flow patterns at a specific setting of (Ra, Wi). Heat transport is reduced (up to 8.5%) by elasticity but still obeys the power law with Ra if the flow pattern has one pair of rolls. However, heat transfer enhancement occurs if multiple pairs of rolls are induced. [ABSTRACT FROM AUTHOR]

Collaborative innovation can promote scientific productivity and the development of clean technology and thus has a great potential in constraining the ecological footprint. However, current studies on the impact of collaborative innovation on ecological footprint are insufficient, and results remain controversial. To better understand these impacts, this paper took Guangdong-Hong Kong-Macao Greater Bay Area of China as a case, estimated the ecological footprint at the municipal level from 2008 to 2018, measured collaborative innovation both from four dimensions and from a composite approach, then applied threshold regression models to compare the impact of collaborative innovation on the ecological footprint across different economic intervals. The findings showed that: the ecological footprint of the Greater Bay Area displayed an overall upward trend with prominent spatial heterogeneity. The impact of collaborative innovation on the ecological footprint presented a double-threshold effect when examined with different indicators. Among which, the flow of scientific personnel and capital boosted the ecological footprint, which intensified with economic development, while collaboration in technology exerted significant inhibitory effects on ecological footprint, and the influence of inter-city knowledge collaboration was limited. Overall, collaborative innovation inhibited ecological footprint when measured by a composite index. This might inspire policymakers to adopt sustainable strategies depending on the type of collaborative innovation and the economic status of the city to constrain growth of the ecological footprint, thus minimizing the pressures of human activities on the environment and moving towards a more carbon neutral society. [ABSTRACT FROM AUTHOR]

Recently, the nature of viscoelastic drag-reducing turbulence (DRT), especially the maximum drag reduction (MDR) state, has become a focus of controversy. It has long been regarded as polymer-modulated inertial turbulence (IT), but is challenged by the newly proposed concept of elasto-inertial turbulence (EIT). This study is to repicture DRT in parallel plane channels by introducing dynamics of EIT through statistical, structural and budget analysis for a series of flow regimes from the onset of drag reduction to EIT. Some underlying mechanistic links between DRT and EIT are revealed. Energy conversion between velocity fluctuations and polymers as well as pressure redistribution effects are of particular concern, based on which a new energy self-sustaining process (SSP) of DRT is repictured. The numerical results indicate that at low Reynolds number (Re), weak IT flow is replaced by a laminar regime before the barrier of EIT dynamics is established with the increase of elasticity, whereas, at moderate Re, EIT-related SSP can get involved and survive from being relaminarized. This further explains the reason why relaminarization phenomenon is observed for low Re while the flow directly enters MDR and EIT at moderate Re. Moreover, with the proposed energy picture, the newly discovered phenomenon that streamwise velocity fluctuations lag behind those in the wall-normal direction can be well explained. The repictured SSP certainly justifies the conjecture that IT nature is gradually replaced by that of EIT in DRT with the increase of elasticity. [ABSTRACT FROM AUTHOR]

This paper adopts the approach of the Internet fusion digital media to conduct in-depth research and analysis on the interaction and communication of traditional culture. This structural information can be used to express and describe the Internet requirements. With the increasing demand for the Internet applications, the number of objects in the network and the complexity of the structure are also growing, so we can design suitable clustering algorithms to obtain more reasonable network structure information by using different semantic information in the heterogeneous information network. Firstly, the caching scheme is transformed into a backpack problem, and the storage scheme is obtained recursively by using dynamic programming, after which the computational task is optimized based on this storage scheme by using the whale algorithm to make it the least costly. The exact balance between the connotation essence of traditional culture and the emotional resonance in modern life has not yet been found, and the visual language belonging to cultural aesthetics under the combination of traditional and modern aesthetics needs to be explored for a long time. From an objective point of view, the digital art communication of cultural elements still suffers from five problems: lack of communication cultivation and stratification of target audiences, low quality of transcription of digital artworks, unbalanced economic and cultural values, uneven development of digital art communication forms, and low degree of Internet adaptation. A ranking algorithm based on fusing multiple meta-paths is proposed to better reflect the ranking values of different object distributions of the Internet data in heterogeneous information networks, which can obtain better clustering, while better clustering can be calculated to obtain more reasonable rankings, and finally, the types of the Internet-oriented applications are divided into multiple reasonable clusters. The effects of selecting different meta-paths on the clustering algorithm and the effects of fused meta-paths versus single meta-paths on the clustering results are given in the experimental results section. Also compared with other clustering algorithms, the I-RankClus algorithm can better achieve the data clustering classification for the Internet application scenarios. [ABSTRACT FROM AUTHOR]

With the rapid development of artificial intelligence (AI) technologies, and the large amount of pharmacovigilance-related data stored in an electronic manner, data-driven automatic methods need to be urgently applied to all aspects of pharmacovigilance to assist healthcare professionals. However, the quantity and quality of data directly affect the performance of AI, and there are particular challenges to implementing AI in limited-resource settings. Analyzing challenges and solutions for AI-based pharmacovigilance in resource-limited settings can improve pharmacovigilance frameworks and capabilities in these settings. In this review, we summarize the challenges into four categories: establishing a database for an AI-based pharmacovigilance system, lack of human resources, weak AI technology and insufficient government support. This study also discusses possible solutions and future perspectives on AI-based pharmacovigilance in resource-limited settings. [ABSTRACT FROM AUTHOR]

Objective: Cognitive impairment is prevalent in schizophrenia. Macrophage migration inhibitory factor which is released into the circulation under stress or inflammation, is associated with cognition and also plays an important role in immunity. However, no study has investigated the relationship between macrophage migration inhibitory factor and cognitive function in first-episode schizophrenia patients at baseline or after treatment. This study investigated the pre- and post-risperidone treatment correlations between serum macrophage migration inhibitory factor levels and cognitive function in first-episode schizophrenia patients. Methods: A total of 83 first-episode schizophrenia patients who received risperidone monotherapy and 57 healthy controls – matched for sex, age, smoking status, education (years), marital status and waist-to-hip ratio – were included. Macrophage migration inhibitory factor levels were measured before and 10 weeks after treatment in the patient group and at baseline in the controls. Pre- and post-treatment cognitive functions in patients were assessed using the MATRICS Consensus Cognitive Battery. Results: At baseline, macrophage migration inhibitory factor levels were significantly higher in first-episode schizophrenia patients than those in healthy controls (p < 0.01) and decreased in patients after 10 weeks of risperidone treatment compared with baseline (p < 0.05). The MATRICS Consensus Cognitive Battery total score and the sub-scores for the Trail Making Test, Symbol Coding, Letter Number Sequence, Maze and Brief Visuospatial Memory Test–Revised improved significantly after risperidone treatment. After controlling for age, sex, education, waist-to-hip ratio and smoking status, partial correlation analysis showed a positive correlation between baseline macrophage migration inhibitory factor levels and patients' baseline MATRICS Consensus Cognitive Battery verbal memory scores (r = 0.29, p = 0.01). Macrophage migration inhibitory factor changes correlated negatively with verbal memory changes (r = −0.26, p = 0.04). Multiple linear regression analysis identified a definite correlation between the changes in word memory test score and macrophage migration inhibitory factor level (β = −0.09, p = 0.04). Conclusion: Macrophage migration inhibitory factor may be involved in the process of cognitive impairment in first-episode schizophrenia and repair mechanisms following risperidone treatment. [ABSTRACT FROM AUTHOR]

Urate oxidase is an important enzyme that is applied as diagnostic reagent in the therapy of gout and detection of uric acid. Therefore, it is of great significance to produce uricase that meets the clinical requirements. A gene that encoded extracellular uricase from Bacillus subtilis BS04 was successfully cloned and inserted into the pET28a (+) expression vector. The recombinant protein was purified to determine its activity by UV spectrophotometry. The purified enzyme of 56.63 kDa was optimally active at pH 9.0 and 45 °C with a specific activity of 4.97 U/mg. The enzyme activity increased by 137.12 % by Mn2+ and inhibited by 95.42 % by Cu2+. Furthermore, four Cys-directed mutants were constructed to analyze the effect of Cys on the pH and temperature dependence of the enzyme. Activity measurements revealed that the enzyme activity was impaired in all mutants, but mutant C489A exhibited higher alkali resistance and thermostability than native uricase. Our findings illustrate the relationship between Cys substitution and increased thermal resistance of uricase and provide insights to improve enzyme therapeutic development. [ABSTRACT FROM AUTHOR]

Background: We aimed to build a common terminology in the domain of cervical cancer, named Cervical Cancer Common Terminology (CCCT), that will facilitate clinical data exchange, ensure quality of data and support large scale data analysis.Methods: The standard concepts and relations of CCCT were collected from ICD-10-CM Chinese Version, ICD-9-PC Chinese Version, officially issued commonly used Chinese clinical terms, Chinese guidelines for diagnosis and treatment of cervical cancer and Chinese medical book Lin Qiaozhi Gynecologic Oncology. 2062 cervical cancer electronic medical records (EMRs) from 16 hospitals, belong to different regions and hospital tiers, were collected for terminology enrichment and building common terms and relations. Concepts hierarchies, terms and relationships were built using Protégé. The performance of natural language processing results was evaluated by average precision, recall, and F1-score. The usability of CCCT were evaluated by terminology coverage.Results: A total of 880 standard concepts, 1182 common terms, 16 relations and 6 attributes were defined in CCCT, which organized in 6 levels and 11 classes. Initial evaluation of the natural language processing results demonstrated average precision, recall, and F1-score percentages of 96%, 72.6%, and 88.5%. The average terminology coverage for three classes of terms, clinical manifestation, treatment, and pathology, were 87.22%, 92.63%, and 89.85%, respectively. Flexible Chinese expressions exist between regions, traditions, cultures, and language habits within the country, linguistic variations in different settings and diverse translation of introduced western language terms are the main reasons of uncovered terms.Conclusions: Our study demonstrated the initial results of CCCT construction. This study is an ongoing work, with the update of medical knowledge, more standard clinical concepts will be added in, and with more EMRs to be collected and analyzed, the term coverage will be continuing improved. In the future, CCCT will effectively support clinical data analysis in large scale. [ABSTRACT FROM AUTHOR]

Due to the limited number of seismic records in the soil and inefficient use of one-dimensional wave theory in the estimation of vertical components for seismic waves, this paper studies depth coherency (coherency between the surface seismic waves and that at depth) in order to describe seismic acceleration at different depths based on surface seismic acceleration signals. In this study, the authors utilized data from the KiK network to investigate the variability of seismic ground motions with depth and obtain a model to simulate coherency of depth-dependent ground motions. Furthermore, by using the methodology described in the Chinese Code for the Seismic Design of Buildings, the authors categorized a number of test locations based on the depth and shear velocity of the soil cover. Four different types of sites were defined and both the horizontal and vertical components of ground motion from strong motion seismometers were analyzed. The results show that there is no significant dependence between the estimated coherencies from different earthquake magnitudes or epicentral distance (less than 200 km). Moreover, the behavior of depth coherency is site-dependent and there are notable differences between horizontal and vertical depth coherency. In addition, existing spatial coherency models may not provide a satisfactory estimate of the variation of depth coherency. [ABSTRACT FROM AUTHOR]

The elasto-inertial turbulence (EIT) of viscoelastic fluid is induced by the interaction between elastic instability and flow inertia. The recent discovery of the EIT regime enables new insights into the maximum drag reduction phenomenon of viscoelastic fluid flows and verifies the role of elastic instability in drag-reducing turbulence. In this study, the direct numerical simulation (DNS) of EIT is carried out by using the Oldroyd-B model for the first time. EIT simulations are conducted at a fixed Weissenberg number of 60 with a Reynolds number ranging from 1000 to 6000. Based on the DNS results, the Reynolds stress and elastic stress budgets are analyzed, and the formation of sheet-like structures of polymer extension is confirmed. It indicates that EIT has a complex energy picture. The self-sustaining nature of EIT not only involves the energy transformation from streamwise elastic energy (EE) into turbulent kinetic energy (TKE), but also relies on the energy transformation of wall-normal TKE into EE, which further induces energy absorption of elastic shear stress from the mean motion and the transformation of this energy into streamwise EE. Sheet-like structures reflect the polymer extension characteristics in the streamwise direction. Their formation comes from the wall-normal extension induced by turbulence perturbations, which further generates extra nonlinear elastic shear stress that absorbs energy from the mean motion and eventually forms sheet-like structures. In the self-sustaining cycle, fluid inertia lifts the sheet-like structures of polymer extension, further inducing flow instability. [ABSTRACT FROM AUTHOR]

Two kinds of nonlinearities coexist in viscoelastic fluid flows, i.e., inertia and elasticity, which can engender different types of chaotic states including inertial turbulence (IT), drag-reducing turbulence (DRT), elastic turbulence, and elasto-inertial turbulence (EIT). The state of maximum drag reduction (MDR), the ultimate state of DRT of viscoelastic fluids, is recently regarded as EIT. This Letter quantitatively demonstrates the role of IT and EIT in drag-reducing turbulent flows passing through the parallel plane channels via the contributions of Reynolds shear stress and the nonlinear part of elastic shear stress to flow drag. The nature of DRT is reexamined under a wide range of flow conditions covering a series of flow regimes from the onset of DR to MDR with the Oldroyd-B model. We argue that EIT-related dynamics appears in DRT long before settling to MDR state and competitively coexists with IT in both spatial and temporal domains at moderate and high Reynolds number (Re). More specifically, under a low DR condition, EIT first emerges close to the channel walls. With the increase in elasticity, low-drag EIT gradually replaces a high-drag IT from channel walls to center, resulting in a drastic decrease in flow drag comparing with IT. When EIT dynamics dominates the whole channel, MDR phenomenon occurs. Our findings provide evidence that DRT phenomenon is the result of IT and EIT interaction. [ABSTRACT FROM AUTHOR]

Background: Analgesia and sedation therapy are commonly used for critically ill patients, especially mechanically ventilated patients. From the initial nonsedation programs to deep sedation and then to on-demand sedation, the understanding of sedation therapy continues to deepen. However, according to different patient's condition, understanding the individual patient's depth of sedation needs remains unclear.Methods: The public open source critical illness database Medical Information Mart for Intensive Care III was used in this study. Latent profile analysis was used as a clustering method to classify mechanically ventilated patients based on 36 variables. Principal component analysis dimensionality reduction was used to select the most influential variables. The ROC curve was used to evaluate the classification accuracy of the model.Results: Based on 36 characteristic variables, we divided patients undergoing mechanical ventilation and sedation and analgesia into two categories with different mortality rates, then further reduced the dimensionality of the data and obtained the 9 variables that had the greatest impact on classification, most of which were ventilator parameters. According to the Richmond-ASS scores, the two phenotypes of patients had different degrees of sedation and analgesia, and the corresponding ventilator parameters were also significantly different. We divided the validation cohort into three different levels of sedation, revealing that patients with high ventilator conditions needed a deeper level of sedation, while patients with low ventilator conditions required reduction in the depth of sedation as soon as possible to promote recovery and avoid reinjury.Conclusion: Through latent profile analysis and dimensionality reduction, we divided patients treated with mechanical ventilation and sedation and analgesia into two categories with different mortalities and obtained 9 variables that had the greatest impact on classification, which revealed that the depth of sedation was limited by the condition of the respiratory system. [ABSTRACT FROM AUTHOR]

Background: Regional citrate anticoagulation (RCA) is an important local anticoagulation method during bedside continuous renal replacement therapy. To improve patient safety and achieve computer assisted dose monitoring and control, we took intensive care units patients into cohort and aiming at developing a data-driven machine learning model to give early warning of citric acid overdose and provide adjustment suggestions on citrate pumping rate and 10% calcium gluconate input rate for RCA treatment.Methods: Patient age, gender, pumped citric acid dose value, 5% NaHCO3 solvent, replacement fluid solvent, body temperature value, and replacement fluid PH value as clinical features, models attempted to classify patients who received regional citrate anticoagulation into correct outcome category. Four models, Adaboost, XGBoost, support vector machine (SVM) and shallow neural network, were compared on the performance of predicting outcomes. Prediction results were evaluated using accuracy, precision, recall and F1-score.Results: For classifying patients at the early stages of citric acid treatment, the accuracy of neutral networks model is higher than Adaboost, XGBoost and SVM, the F1-score of shallow neutral networks (90.77%) is overall outperformed than other models (88.40%, 82.17% and 88.96% for Adaboost, XGBoost and SVM). Extended experiment and validation were further conducted using the MIMIC-III database, the F1-scores for shallow neutral networks, Adaboost, XGBoost and SVM are 80.00%, 80.46%, 80.37% and 78.90%, the AUCs are 0.8638, 0.8086, 0.8466 and 0.7919 respectively.Conclusion: The results of this study demonstrated the feasibility and performance of machine learning methods for monitoring and adjusting local regional citrate anticoagulation, and further provide decision-making recommendations to clinicians point-of-care. [ABSTRACT FROM AUTHOR]

Damage cases show that during earthquakes, the sharp stiffness mutation of subway station-tunnel junction structures can lead to dislocations at the connections. To address this, shaking table tests were conducted followed by numerical simulations of a typical junction structure with rigid connections. The modeling method was verified based on the test results. Furthermore, numerical models of junction structures with rigid and flexible connections, single stations, and single tunnels were built, and deformation modes and stress distributions were comparatively analyzed. Combining the experimental and numerical results, it is found that there exists an intensive deformation inconsistency between the stations and the tunnels responsible for the junction structures' dislocation failures. The station operates in both racking and distortion deformation modes when the tunnel undergoes ovaling deformation. The tunnel bends relative to the end wall at the connection. The junction structure with rigid connections is most at risk at the point located at the tunnel section connected to the end wall and near the bottom plate-sidewall joint. With flexible connections, the tunnels integrally translate relative to the end wall, and the stress response of the end wall openings can be larger than those with rigid connections. [ABSTRACT FROM AUTHOR]

In this paper, a new derivation process of the log-conformation governing equation for viscoelastic fluid flows is presented by using the Taylor series definition of the matrix logarithm. Based on the log-conformation representation (LCR) and standard conformation representation (CR) methods, the turbulent drag-reducing channel flow of viscoelastic fluid described by the Oldroyd-B constitutive model is simulated by the finite difference method. The comparison illustrates that the turbulent drag reduction (DR) effect under the condition of a low Weissenberg number (Wi = 1) or moderate Weissenberg number (Wi = 5) can be successfully reproduced by the CR method but is very difficult to be obtained by the LCR method at the same grid resolution if the commonly used interpolation approaches in the computing domain (i.e., log domain) are employed. Further research reveals that the interpolation method of log-conformation tensor involved is one of the dominant reasons responsible for the disability to obtain a turbulent DR effect by using the LCR method. If the interpolation is performed in a physical domain, the turbulent DR effect can be reproduced by using the LCR method. If the interpolation involved in the CR method is carried out in a log domain, the turbulent DR phenomenon can still be simulated but with a weakened DR effect. In sum, this study demonstrates that the commonly used interpolation approaches in the log domain should be responsible for the poor performance of the LCR method. [ABSTRACT FROM AUTHOR]

Background: Although protective mechanical ventilation (MV) has been used in a variety of applications, lung injury may occur in both patients with and without acute respiratory distress syndrome (ARDS). The purpose of this study is to use machine learning to identify clinical phenotypes for critically ill patients with MV in intensive care units (ICUs).Methods: A retrospective cohort study was conducted with 5013 patients who had undergone MV and treatment in the Department of Critical Care Medicine, Peking Union Medical College Hospital. Statistical and machine learning methods were used. All the data used in this study, including demographics, vital signs, circulation parameters and mechanical ventilator parameters, etc., were automatically extracted from the electronic health record (EHR) system. An external database, Medical Information Mart for Intensive Care III (MIMIC III), was used for validation.Results: Phenotypes were derived from a total of 4009 patients who underwent MV using a latent profile analysis of 22 variables. The associations between the phenotypes and disease severity and clinical outcomes were assessed. Another 1004 patients in the database were enrolled for validation. Of the five derived phenotypes, phenotype I was the most common subgroup (n = 2174; 54.2%) and was mostly composed of the postoperative population. Phenotype II (n = 480; 12.0%) led to the most severe conditions. Phenotype III (n = 241; 6.01%) was associated with high positive end-expiratory pressure (PEEP) and low mean airway pressure. Phenotype IV (n = 368; 9.18%) was associated with high driving pressure, and younger patients comprised a large proportion of the phenotype V group (n = 746; 18.6%). In addition, we found that the mortality rate of Phenotype IV was significantly higher than that of the other phenotypes. In this subgroup, the number of patients in the sequential organ failure assessment (SOFA) score segment (9,22] was 198, the number of deaths was 88, and the mortality rate was higher than 44%. However, the cumulative 28-day mortality of Phenotypes IV and II, which were 101 of 368 (27.4%) and 87 of 480 (18.1%) unique patients, respectively, was significantly higher than those of the other phenotypes. There were consistent phenotype distributions and differences in biomarker patterns by phenotype in the validation cohort, and external verification with MIMIC III further generated supportive results.Conclusions: Five clinical phenotypes were correlated with different disease severities and clinical outcomes, which suggested that these phenotypes may help in understanding heterogeneity in MV treatment effects. [ABSTRACT FROM AUTHOR]

Viscoelastic fluid naturally has both viscous and elastic properties. Therefore, there are two sources of nonlinear effects, namely inertial and elastic nonlinearities. The existence of elastic nonlinearity brings about various interesting flow phenomena in viscoelastic fluid flow, especially in microfluidics where the inertial nonlinearity can be negligible while the elastic nonlinearity can dominate the flow. Specifically, purely elasticity-induced instability and turbulence can occur in microchannels when the elastic nonlinearity is strong enough. Recently, those intriguing properties of viscoelastic fluid flow have motivated lots of researches on taking viscoelastic fluid as working fluid in different types of microfluidic devices, such as micro-mixers, micro heat exchangers, logic microfluidic circuits and particle manipulation. This paper aims to provide a state-of-the-art review of the nonlinear effect of viscoelastic fluids and its applications in the aforementioned microfluidic fields, which may provide a useful guidance for the researchers who are interested in this area. [ABSTRACT FROM AUTHOR]

In this paper, a green solvent for chitosan, plasma acid, was made and chitosan/plasma-acid solutions were prepared. An environmentally friendly chitosan/polyvinyl alcohol (PVA) nano-membrane was prepared via electrospinning due to the difficulty of electrospinning of pure chitosan/plasma-acid solutions. Two blending methods of chitosan with PVA were investigated. One way was to mix a chitosan/plasma-acid solution (1%) and a PVA/water solution (10%) with the volume ratios of 2:8, 3:7, 4:6, 5:5, 6:4, 7:3 and 8:2, respectively. The results showed that fibrous nano-membranes could start to be formed at a chitosan/PVA mixing ratio of 7:3 up to the ratio of 2:8 with increasing PVA. The average fiber diameters increased with increased adding of PVA, ranging from 74.7 nm for the 7:3 ratio to 280.7 nm for the 2:8 ratio. The other way to prepare the chitosan/PVA solutions was to put PVA and chitosan powders into the plasma acid together. Fibrous nano-membranes could also be formed at 6% PVA and 10% PVA solution, both with 1% chitosan compositions. The average diameters of the resulting nano-fibers were 144.67 nm and 300.7 nm, respectively. The Fourier transform infrared (FTIR) spectroscopy results showed that the chitosan was bonded to the PVA by hydrogen bonds in the nano-membranes (6% PVA, 1% chitosan). It is noted that both of the two blending methods permitted obtaining chitosan/PVA nano-membranes. As indicated, the PVA in the solution had a large effect on the diameters of the nano-fibers. The first method permitted obtaining nano-fibers with smaller diameter. The maximum concentration of chitosan in the solution was 0.7% (7:3 ratio). The second method was simpler and permitted increasing the chitosan concentration in the solution to 1% for both the 6% and 10% concentrations of PVA. [ABSTRACT FROM AUTHOR]