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Abstracts Idiopathic pulmonary fibrosis (IPF) is a chronic disease of unknown etiology that lacks a specific treatment. In IPF, macrophages play a key regulatory role as a major component of the lung immune system, especially during inflammation and fibrosis. However, our understanding of the cellular heterogeneity and molecular characterization of macrophages in IPF, as well as their relevance in the clinical setting, is relatively limited. In this study, we analyzed in-depth single-cell transcriptome sequencing (scRNA-seq) data from lung tissues of IPF patients, identified macrophage subpopulations in IPF, and probed their molecular characteristics and biological functions. hdWGCNA identified co-expressed gene modules of a subpopulation of IPF-associated macrophages (IPF-MΦ), and probed the IPF-MΦ by a machine-learning approach. hdWGCNA identified a subpopulation of IPF-associated macrophage subpopulations and probed the IPF-MΦ signature gene (IRMG) for its prognostic value, and a prediction model was developed on this basis. In addition, IPF-MΦ was obtained after recluster analysis of macrophages in IPF lung tissues. Coexpressed gene modules of IPF-MΦ were identified by hdWGCNA. Then, a machine learning approach was utilized to reveal the characteristic genes of IPF-MΦ, and a prediction model was built on this basis. In addition, we discovered a type of macrophage unique to IPF lung tissue named ATP5-MΦ. Its characteristic gene encodes a subunit of the mitochondrial ATP synthase complex, which is closely related to oxidative phosphorylation and proton transmembrane transport, suggesting that ATP5-MΦ may have higher ATP synthesis capacity in IPF lung tissue. This study provides new insights into the pathogenesis of IPF and provides a basis for evaluating disease prognosis and predictive medicine in IPF patients. Graphical Abstract

Abstract Purpose Severe community-acquired pneumonia (SCAP) is a common respiratory system disease with rapid development and high mortality. Exploring effective biomarkers for early detection and development prediction of SCAP is of urgent need. The function of miR-486-5p in SCAP diagnosis and prognosis was evaluated to identify a promising biomarker for SCAP. Patients and methods The serum miR-486-5p in 83 patients with SCAP, 52 healthy individuals, and 68 patients with mild CAP (MCAP) patients were analyzed by PCR. ROC analysis estimated miR-486-5p in screening SCAP, and the Kaplan-Meier and Cox regression analyses evaluated the predictive value of miR-486-5p. The risk factors for MCAP patients developing SCAP were assessed by logistic analysis. The alveolar epithelial cell was treated with Klebsiella pneumonia to mimic the occurrence of SCAP. The targeting mechanism underlying miR-486-5p was evaluated by luciferase reporter assay. Results Upregulated serum miR-486-5p screened SCAP from healthy individuals and MCAP patients with high sensitivity and specificity. Increasing serum miR-486-5p predicted the poor outcomes of SCAP and served as a risk factor for MCAP developing into SCAP. K. pneumonia induced suppressed proliferation, significant inflammation and oxidative stress in alveolar epithelial cells, and silencing miR-486-5p attenuated it. miR-486-5p negatively regulated FOXO1, and the knockdown of FOXO1 reversed the effect of miR-486-5p in K. pneumonia-treated alveolar epithelial cells. Conclusion miR-486-5p acted as a biomarker for the screening and monitoring of SCAP and predicting the malignancy of MCAP. Silencing miR-486-5p alleviated inflammation and oxidative stress induced by K. pneumonia via negatively modulating FOXO1.

The surface plasmon resonance (SPR) biosensor technology is a novel optical analysis method for studying intermolecular interactions. Owing to in-depth research on traditional Chinese medicine (TCM) in recent years, comprehensive and specific identification of components and target interactions has become key yet difficult tasks. SPR has gradually been used to analyze the active components of TCM owing to its high sensitivity, strong exclusivity, large flux, and real-time monitoring capabilities. This review sought to briefly introduce the active components of TCM and the principle of SPR, and provide historical and new insights into the application of SPR in the analysis of the active components of TCM.

Background: Idiopathic pulmonary fibrosis (IPF) is an irreversible lung disease with unclear pathological mechanisms. In this study, we utilized bidirectional Mendelian randomization (MR) to analyze the relationship between serum metabolites and IPF, and conducted metabolic pathway analysis. Aim: To determine the causal relationship between serum metabolites and IPF using MR analysis. Methods: A two-sample MR analysis was conducted to evaluate the causal relationship between 824 serum metabolites and IPF. The inverse variance weighted (IVW) method was used to estimate the causal relationship between exposure and results. Sensitivity analysis was conducted using MR Egger, weighted median, and maximum likelihood to eliminate pleiotropy. Additionally, metabolic pathway analysis was conducted to identify potential metabolic pathways. Results: We identified 12 serum metabolites (6 risks and 6 protective) associated with IPF from 824 metabolites. Among them, 11 were known and 1 was unknown. 1-Eicosatrienoylglycophorophospholine and 1-myristoylglycophorophospholine were bidirectional MR positive factors, with 1-myristoylglycophorophospholine being a risk factor (1.0013, 1.0097) and 1-eicosatrienoylglycophorine being a protective factor (0.9914, 0.9990). The four lipids (1-linoleoylglycerophoethanolamine*, total cholesterol in large high-density lipoprotein [HDL], cholesterol esters in very large HDL, and phospholipids in very large HDL) and one NA metabolite (degree of unsaturation) were included in the known hazardous metabolites. The known protective metabolites included three types of lipids (carnitine, 1-linoleoylglycerophoethanolamine*, and 1-eicosatrienoylglycerophophophorine), one amino acid (hypoxanthine), and two unknown metabolites (the ratio of omega-6 fatty acids to omega-3 fatty acids, and the ratio of photoshopids to total lipids ratio in chylomicrons and extremely large very low-density lipoprotein [VLDL]). Moreover, sn-Glycerol 3-phosphate and 1-Acyl-sn-glycero-3-phosphocline were found to be involved in the pathogenesis of IPF through metabolic pathways such as Glycerolide metabolism and Glycerophospholipid metabolism. Conclusion: Our study identified 6 causal risks and 6 protective serum metabolites associated with IPF. Additionally, 2 metabolites were found to be involved in the pathogenesis of IPF through metabolic pathways, providing a new perspective for further understanding the metabolic pathway and the pathogenesis of IPF.

Abstract Background Tactile and mechanical pain are crucial to our interaction with the environment, yet the underpinning molecular mechanism is still elusive. Endophilin A2 (EndoA2) is an evolutionarily conserved protein that is documented in the endocytosis pathway. However, the role of EndoA2 in the regulation of mechanical sensitivity and its underlying mechanisms are currently unclear. Methods Male and female C57BL/6 mice (8–12 weeks) and male cynomolgus monkeys (7–10 years old) were used in our experiments. Nerve injury-, inflammatory-, and chemotherapy-induced pathological pain models were established for this study. Behavioral tests of touch, mechanical pain, heat pain, and cold pain were performed in mice and nonhuman primates. Western blotting, immunostaining, co-immunoprecipitation, proximity ligation and patch-clamp recordings were performed to gain insight into the mechanisms. Results The results showed that EndoA2 was primarily distributed in neurofilament-200-positive (NF200+) medium-to-large diameter dorsal root ganglion (DRG) neurons of mice and humans. Loss of EndoA2 in mouse NF200+ DRG neurons selectively impaired the tactile and mechanical allodynia. Furthermore, EndoA2 interacted with the mechanically sensitive ion channel Piezo2 and promoted the membrane trafficking of Piezo2 in DRG neurons. Moreover, as an adaptor protein, EndoA2 also bound to kinesin family member 5B (KIF5B), which was involved in the EndoA2-mediated membrane trafficking process of Piezo2. Loss of EndoA2 in mouse DRG neurons damaged Piezo2-mediated rapidly adapting mechanically activated currents, and re-expression of EndoA2 rescued the MA currents. In addition, interference with EndoA2 also suppressed touch sensitivity and mechanical hypersensitivity in nonhuman primates. Conclusions Our data reveal that the KIF5B/EndoA2/Piezo2 complex is essential for Piezo2 trafficking and for sustaining transmission of touch and mechanical hypersensitivity signals. EndoA2 regulates touch and mechanical allodynia via kinesin-mediated Piezo2 trafficking in sensory neurons. Our findings identify a potential new target for the treatment of mechanical pain.

Abstract Due to its challenging manufacturing and intricate morphology, the aluminum alloy transmission intermediate shell used in vehicle transmission has been the focus of many academic studies. In this study, the three-dimensional cutting model is condensed to a two-dimensional cutting model and utilized to simulate the finishing process of an aluminum alloy workpiece using the finite element modeling program DEFORM-3D. Through orthogonal testing and range analysis, the impact of integral end mill side edge parameters on cutting performance was investigated. It is determined that tool chamfering has a greater impact on cutting performance than tool rake and relief angles, that chamfering width has the most impact on cutting force, and that chamfering angle has the greatest impact on cutting temperature. The workpiece's surface roughness is tested during a cutting experiment, and an analysis of the data reveals that the finite element simulation model is accurate and the orthogonal test method is reasonable. The tool chamfer has a greater impact on roughness than the tool rake angle and relief angle. The tool settings are further optimized using the firefly method. By examining the data, it is determined that the prediction model is correct and the optimization model is reasonable. The cutting efficiency is higher and the surface quality is better when the chamfer width is 0.17 mm and the chamfer angle is 7.3° or 18.3°. Therefore, optimizing the side edge parameters of the integral end mill during the finishing process of a thin-walled aluminum alloy shell has practical technical value.

Abstract Sweeping gas membrane distillation (SGMD) is considered a membrane distillation configuration. It uses an air stream to collect the water vapour. A 2D mathematical model is prepared in the current study to predict the effect of various operating parameters on the SGMD performance. Also, the temperature distribution in the SGMD was obtained. The effect of air inlet temperature, salt concentration, feed and air flowrate on air and salted solution outlet temperature and vapour flux through the membrane is investigated. There was good agreement between experimental data and modelling outputs. It was found that increase in air inlet temperature from 40 to 72 °C was increased the outlet temperature of air stream and cold solution from 37 to 63 °C and 38 to 65 °C respectively. Furthermore, increase in air inlet temperature led to the enhancement of vapour flux in the membrane distillation. Also, the salt concentration and feed flow rate did not have meaningful influence on the outlet temperatures, however, the flux was increased by increasing feed flowrate.

Abstract Background The spinal inflammatory signal often spreads to distant segments, accompanied by widespread pain symptom under neuropathological conditions. Multiple cytokines are released into the cerebrospinal fluid (CSF), potentially inducing the activation of an inflammatory cascade at remote segments through CSF flow. However, the detailed alteration of CSF in neuropathic pain and its specific role in widespread pain remain obscure. Methods A chronic constriction injury of the infraorbital nerve (CCI-ION) model was constructed, and pain-related behavior was observed on the 7th, 14th, 21st, and 28th days post surgery, in both vibrissa pads and hind paws. CSF from CCI-ION rats was transplanted to naïve rats through intracisternal injection, and thermal and mechanical allodynia were measured in hind paws. The alteration of inflammatory cytokines in CCI-ION’s CSF was detected using an antibody array and bioinformatic analysis. Pharmacological intervention targeting the changed cytokine in the CSF and downstream signaling was performed to evaluate its role in widespread pain. Results CCI-ION induced local pain in vibrissa pads together with widespread pain in hind paws. CCI-ION’s CSF transplantation, compared with sham CSF, contributed to vibrissa pad pain and hind paw pain in recipient rats. Among the measured cytokines, interleukin-6 (IL-6) and leptin were increased in CCI-ION’s CSF, while interleukin-13 (IL-13) was significantly reduced. Furthermore, the concentration of CSF IL-6 was correlated with nerve injury extent, which gated the occurrence of widespread pain. Both astrocytes and microglia were increased in remote segments of the CCI-ION model, while the inhibition of astrocytes in remote segments, but not microglia, significantly alleviated widespread pain. Mechanically, astroglial signal transducer and activator of transcription 3 (STAT3) in remote segments were activated by CSF IL-6, the inhibition of which significantly mitigated widespread pain in CCI-ION. Conclusion IL-6 was induced in the CSF of the CCI-ION model, triggering widespread pain via activating astrocyte STAT3 signal in remote segments. Therapies targeting IL-6/STAT3 signaling might serve as a promising strategy for the widespread pain symptom under neuropathological conditions. Graphical abstract

Abstract Background This study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CUPID performance of experienced senior and junior radiologists. Materials and methods This prospective cross-sectional study was conducted at Shenzhen University General Hospital between September 2022 and June 2023, and focused on mid-trimester fetuses. All ultrasound images of the six standard planes, that enabled the evaluation of nine biometric measurements, were included to compare the performance of CUPID through subjective and objective assessments. Results There were 642 fetuses with a mean (±SD) age of 22 ± 2.82 weeks at enrollment. In the subjective quality assessment, out of 642 images representing nine biometric measurements, 617-635 images (90.65-96.11%) of CUPID caliper placements were determined to be accurately placed and did not require any adjustments. Whereas, for the junior category, 447-691 images (69.63-92.06%) were determined to be accurately placed and did not require any adjustments. In the objective measurement indicators, across all nine biometric parameters and estimated fetal weight (EFW), the intra-class correlation coefficients (ICC) (0.843-0.990) and Pearson correlation coefficients (PCC) (0.765-0.978) between the senior radiologist and CUPID reflected good reliability compared with the ICC (0.306-0.937) and PCC (0.566-0.947) between the senior and junior radiologists. Additionally, the mean absolute error (MAE), percentage error (PE), and average error in days of gestation were lower between the senior and CUPID compared to the difference between the senior and junior radiologists. The specific differences are as follows: MAE (0.36-2.53 mm, 14.67 g) compared to (0.64- 8.13 mm, 38.05 g), PE (0.94-9.38%) compared to (1.58-16.04%), and average error in days (3.99-7.92 days) compared to (4.35-11.06 days). In the time-consuming task, CUPID only takes 0.05-0.07 s to measure nine biometric parameters, while senior and junior radiologists require 4.79-11.68 s and 4.95-13.44 s, respectively. Conclusions CUPID has proven to be highly accurate and efficient software for automatically measuring fetal biometry, gestational age, and fetal weight, providing a precise and fast tool for assessing fetal growth and development.

Long-term chronic stress is an important factor in the poor prognosis of cancer patients. Chronic stress reduces the tissue infiltration of immune cells in the tumor microenvironment (TME) by continuously activating the adrenergic signaling, inhibits antitumor immune response and tumor cell apoptosis while also inducing epithelial-mesenchymal transition (EMT) and tumor angiogenesis, promoting tumor invasion and metastasis. This review first summarizes how adrenergic signaling activates intracellular signaling by binding different adrenergic receptor (AR) heterodimers. Then, we focused on reviewing adrenergic signaling to regulate multiple functions of immune cells, including cell differentiation, migration, and cytokine secretion. In addition, the article discusses the mechanisms by which adrenergic signaling exerts pro-tumorigenic effects by acting directly on the tumor itself. It also highlights the use of adrenergic receptor modulators in cancer therapy, with particular emphasis on their potential role in immunotherapy. Finally, the article reviews the beneficial effects of stress intervention measures on cancer treatment. We think that enhancing the body's antitumor response by adjusting adrenergic signaling can enhance the efficacy of cancer treatment.

Abstract Colorectal cancer is a grievous health concern, we have proved long non-coding RNA LINC00689 is considered as a potential diagnosis biomarker for colorectal cancer, and it is necessary to further investigate its upstream and downstream mechanisms. Here, we show that KLF15, a transcription factor, exhibits the reduced expression in colorectal cancer. KLF15 suppresses the proliferative and metastatic capacities of colorectal cancer cells both in vitro and in vivo by transcriptionally activating LINC00689. Subsequently, LINC00689 recruits PTBP1 protein to enhance the stability of LATS2 mRNA in the cytoplasm. This stabilization causes the suppression of the YAP1/β-catenin pathway and its target downstream genes. Our findings highlight a regulatory network involving KLF15, LINC00689, PTBP1, LATS2, and the YAP1/β-catenin pathway in colorectal cancer, shedding light on potential therapeutic targets for colorectal cancer therapy.

Abstract The Omicron variant of the severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) infected a substantial proportion of Chinese population, and understanding the factors underlying the severity of the disease and fatality is valuable for future prevention and clinical treatment. We recruited 64 patients with invasive ventilation for COVID-19 and performed metatranscriptomic sequencing to profile host transcriptomic profiles, plus viral, bacterial, and fungal content, as well as virulence factors and examined their relationships to 28-day mortality were examined. In addition, the bronchoalveolar lavage fluid (BALF) samples from invasive ventilated hospital/community-acquired pneumonia patients (HAP/CAP) sampled in 2019 were included for comparison. Genomic analysis revealed that all Omicron strains belong to BA.5 and BF.7 sub-lineages, with no difference in 28-day mortality between them. Compared to HAP/CAP cohort, invasive ventilated COVID-19 patients have distinct host transcriptomic and microbial signatures in the lower respiratory tract; and in the COVID-19 non-survivors, we found significantly lower gene expressions in pathways related viral processes and positive regulation of protein localization to plasma membrane, higher abundance of opportunistic pathogens including bacterial Alloprevotella, Caulobacter, Escherichia-Shigella, Ralstonia and fungal Aspergillus sydowii and Penicillium rubens. Correlational analysis further revealed significant associations between host immune responses and microbial compositions, besides synergy within viral, bacterial, and fungal pathogens. Our study presents the relationships of lower respiratory tract microbiome and transcriptome in invasive ventilated COVID-19 patients, providing the basis for future clinical treatment and reduction of fatality.

Research on evapotranspiration and its drivers in the Aksu River Basin from the perspectives of climate change and land use is of great significance for promoting the efficient use and precise allocation of its water resources. Theil-Sen median trend analysis (T-S) and the Mann–Kendall nonparametric test (M-K), in addition to correlation analysis, partial correlation analysis, complex correlation analysis, and driving-factor zoning principles, were used to examine the characteristics of the spatiotemporal changes in evapotranspiration and to explore the driving mechanism of the changes in evapotranspiration. The results indicated that the range of fluctuations in the multiyear average evapotranspiration in the Aksu River Basin from 2001 to 2020 was between 481.58 and 772.37 mm/a, which showed the spatial distribution characteristics of being high in the west and central part of the basin, and low in the north and south of the basin. The positive correlation between evapotranspiration and precipitation was stronger, and the negative correlations with temperature and relative humidity were stronger. The change in evapotranspiration in cultivated land is mainly driven by precipitation and relative humidity × precipitation; for grassland, the main drivers were relative humidity and precipitation × relative humidity; for woodland, the main drivers were relative humidity and other climatic factors; and for other land types, the main drivers were other climatic factors.

N6-methyladenosine (m6A) is a crucial RNA modification affecting skeletal muscle development. Rhein, an anti-inflammatory extract, inhibits FTO, a key demethylase in m6A metabolism. Our study showed that during muscle fiber formation, FTO and ALKBH5 expression increased while m6A levels decreased. After muscle injury, FTO and ALKBH5 expression initially rose but later fell, while m6A levels initially dropped and then recovered. Inhibition of FTO by Rhein reduced MyHC and MyoG expression, indicating myoblast differentiation suppression. In a mouse model, Rhein decreased MyHC expression and muscle fiber cross-sectional area, delaying muscle regeneration. Rhein’s ability to increase RNA m6A modification delays skeletal muscle remodeling post-injury, suggesting a new medicinal application for this plant extract.

The titanium alloy open integral micro impeller has a strong material strength and high removal rate in the field of multi-axis CNC machining. The flow channel is tiny and the blades are thin and highly twisted. It is difficult to control the surface accuracy and prone to overcutting and undercutting. The NX2212 software post-processing module plans two distinct blade finishing process routes and verifies them using virtual machine tool simulation, taking into account the technical challenges of micro impeller machining. Following verification, the tool path machining code is imported into MATLAB for data fitting. The workpiece surface working condition is determined based on the simulation findings, the blade surface roughness value is calculated, and a physical simulation model of blade finishing is created in the finite element analysis software. The outcomes demonstrate how well the “segmented and sub-regional cutting” processing method may raise blade accuracy. The leading and trailing edges of the blade both had surface roughness increases of 4.86% and 4.19%. The surface morphology of the micro impeller is measured using a white light interferometer, and it is CNC machined using two distinct process methods. The findings demonstrate that there is a significant difference between the value calculated by the finite element analysis software and the surface roughness value measured experimentally which together make up less than 5%. An investigation of the impact of cutting parameters on the surface roughness of micro-structure components is carried out using a three factor, three-level BBD experiment that is founded on the second-order response surface method. The findings indicate that the feed per tooth influences surface roughness more significantly than cutting depth and cutting speed for a reasonable range of cutting parameters; Surface roughness will rise with lower or higher cutting speeds; Raising the feed per tooth and the cutting speed simultaneously may reduce surface roughness; Surface roughness can be accurately predicted and controlled using the second-order response surface method.

Introduction Social status, which encompasses various psychosocial dimensions, such as income, education and social relationships, can have a significant impact on physical and mental health outcomes. The study aims to explore the association among subjective social status, health and well-being among individuals aged 55 years and older in China and South Korea.Participants Sample population included individuals aged 55 years and older: China (n=1779) and South Korea (n=421).Outcome measures Outcome measures included self-reported health status and well-being which were assessed by life satisfaction and general happiness.Results The percentage of participants who reported a ‘very good’ health condition was higher in South Korea (14.5%) than in China (11.0%). The percentage of participants who reported feeling very satisfied (14.7%) with their life was lower in South Korea (11.8%). In China, 6.7% of the respondents reported their health as ‘very bad’ (rating 5), while in South Korea, this percentage was higher at 18.1%. Regression analysis revealed an inverse association among higher social status and poorer health, lower life satisfaction and lower happiness levels. For example, individuals who placed themselves in the highest social status category had 0.26 times lower odds (95% CI=0.13 to 0.55) of reporting poorer self-rated health status than those in the lowest category. Similarly, compared with individuals who place themselves in the lowest social status category, those who place themselves in the highest social status category have 0.03 times lower odds of reporting lower life satisfaction (95% CI=0.02 to 0.07).Conclusion Overall, the results highlight a significant association among social status, subjective health, life satisfaction and general happiness in both the countries. Health policymakers should identify effective strategies to promote healthy ageing and reduce disparities in health and well-being outcomes among older adults from different social backgrounds.

The changes in mechanical properties of glass fiber reinforced plastic cross-ply laminates as a result of hydrothermal aging were studied theoretically. The composite specimens have been immersed in distilled water at 25, 40, and 70 °C for 60 days for aging testing. Based on Fick’s law and the Arrhenius theorem, the moisture absorption data under different environments was analyzed, and the method for determining the diffusivity and the equilibrium moisture content was obtained. The relationship model between the moisture absorption behavior of the composite material and the ambient temperature was proposed and verified by finite element analysis. The mechanical behavior of the composites was studied by tensile, compression, and three-point bending tests. Under the condition of ultimate moisture absorption, the tensile, compressive, and bending strengths of the composite decreased by 31.663%, 12.948%, and 26.985%, respectively. A variety of empirical models were used for data analysis, which confirmed the strong correlation between strength degradation and moisture absorption of composite cross-ply laminates. The scanning electron microscope observation results of different moisture absorption levels showed that matrix cracking and fiber/matrix interface debonding caused by moisture absorption are the fundamental reasons for the strength degradation of the composites.

Over the last decades, porous organic materials (POMs) have been extensively employed in various industrial approaches including gas separation, catalysis and energy production due to possessing indisputable advantages like great surface area, high permeability, controllable pore size, appropriate functionalization and excellent processability compared to traditional substances like zeolites, Alumina and polymers. This review presents the recent breakthroughs in the multifunctional POMs for potential use in the membrane-based CO2 separation. Some examples of highly-selective membranes using multifunctional POMs are described. Moreover, various classifications of POMs following with their advantages and disadvantages in CO2 separation processes are explained. Apart from reviewing the state-of-the-art POMs in CO2 separation, the challenges/limitations of POMs with tailored structures for reasonable application are discussed.

Monolayer group IVA metal halides have attracted intensive attention for their excellent thermoelectric performance. Recently, the CdI2-type SnI2 monolayer has been successfully fabricated by molecular beam epitaxy for the first time. The universal two-dimensional growth behavior on different substrates, motivates strain engineering on its thermoelectric performance. Herein, the structure stability and thermoelectric properties of SnI2 monolayer under different strains are systematically investigated, based on first-principles calculations combined with Boltzmann transport theory. The investigation shows that the tensile strain can simultaneously induce phonon mode softening and band convergence, resulting in a significant enhancement in thermoelectric performance. The phonon mode softening for ZA and optical branches further enhances lattice anharmonicity and a reduced thermal conductivity of ∼0.14 Wm−1K−1 at 300 K (∼0.05 Wm−1K−1, 800 K) can be obtained. Additionally, band convergence in valence band improves the Seebeck coefficient and increases power factor. Under +2 % tensile strain, the optimal ZT values of SnI2 monolayer for p-type doping are substantially enhanced up to 3.05 (300 K) and 5.06 (800 K), which are increased by ∼98 % and ∼50 % compared to the case without strain. Our results reveal the close relationship between the phonon mode softening and enhanced anharmonicity, and provide the physical insights into the understanding of the modulation of thermoelectric properties of monolayer SnI2, shedding light on substantially optimizing the thermoelectric performance of monolayer group IVA metal halides family.

Diabetic Peripheral Neuropathy (DPN) poses an escalating threat to public health, profoundly impacting well-being and quality of life. Despite its rising prevalence, the pathogenesis of DPN remains enigmatic, and existing clinical interventions fall short of achieving meaningful reversals of the condition. Notably, neurostimulation techniques have shown promising efficacy in alleviating DPN symptoms, underscoring the imperative to elucidate the neurobiochemical mechanisms underlying DPN. This study employs an integrated multi-omics approach to explore DPN and its response to neurostimulation therapy. Our investigation unveiled a distinctive pattern of vesicular glutamate transporter 2 (VGLUT2) expression in DPN, rigorously confirmed through qPCR and Western blot analyses in DPN C57 mouse model induced by intraperitoneal Streptozotocin (STZ) injection. Additionally, combining microarray and qPCR methodologies, we revealed and substantiated variations in the expression of the Amyloid Precursor Protein (APP) family in STZ-induced DPN mice. Analyzing the transcriptomic dataset generated from neurostimulation therapy for DPN, we intricately explored the differential expression patterns of VGLUT2 and APPs. Through correlation analysis, protein-protein interaction predictions, and functional enrichment analyses, we predicted the key biological processes involving VGLUT2 and the APP family in the pathogenesis of DPN and during neurostimulation therapy. This comprehensive study not only advances our understanding of the pathogenesis of DPN but also provides a theoretical foundation for innovative strategies in neurostimulation therapy for DPN. The integration of multi-omics data facilitates a holistic view of the molecular intricacies of DPN, paving the way for more targeted and effective therapeutic interventions.

ABSTRACT: In poultries, muscle growth is a quantitative trait controlled by multiple genes. The regulatory mechanisms governing muscle tissue growth and development in poultry, particularly during the early stages of growth, are intricate. Through the examination of leg muscle transcripts from Yili geese during various stages of development, this study offers valuable insights into the molecular mechanisms underlying the growth and development of Yili geese. This study aimed to perform a comparative analysis of the histological characteristics of leg muscles and the mRNA expression profiles of leg muscles in Yili geese at different ages (2, 4, 6, 8, and 10 wk). The objective was to identify differentially expressed genes related to muscle development in Yili geese and utilize bioinformatics to predict the potential biological functions of these genes. Through histological studies on leg muscle tissues, it was discerned that male geese at 4 wk exhibit a significantly reduced muscle fiber density in comparison to females (P < 0.01). In contrast, by the time they reach 6, 8, and 10 wk, their muscle fiber diameter and cross-sectional dimensions significantly outpace the females (P < 0.01). With the advancement in age, muscle fiber density tends to decrease. It is worth noting that 4- and 6-wk-old male geese have a substantially elevated muscle fiber density when matched against females (P < 0.01). Conversely, at the age of 10 wk, their muscle fiber density is notably inferior to the females (P < 0.01). Furthermore, male geese exhibit the most rapid increase in muscle fiber diameter and cross-sectional area between 4 and 6 wk of age. The density of muscle fibers in these geese significantly decreases from 4 to 8 wk. In contrast, female geese show the most pronounced growth in muscle fiber diameter and cross-sectional area between 2 and 6 wk, with a swift decline in density following the 6-wk mark, accompanied by a gradual reduction in the rate of muscle fiber growth. A comprehensive analysis of the leg muscle mRNA expression profiles from 12 Yili geese generated a cumulative total of 502,065,268 valid sequence reads, corresponding to a data volume of 75.30 Gb. In a comparative analysis between 4-wk-old and 2-wk-old groups (T4 vs. T2), 8-wk-old and 2-wk-old groups (T8 vs. T2), and 8-wk-old and 4-wk-old groups (T8 vs. T4), we identified 1,700, 1,583, and 221 differentially expressed genes (DEGs), respectively. Differentially expressed genes were significantly enriched in Gene Ontology (GO) terms such as organelle organization, cytoskeletal protein binding, cation transport, myosin complex, and actin cytoskeleton. Among the significantly enriched signaling pathways, 5 pathways were found to be significantly related to growth and development: adhesion patch, extracellular matrix receptor interaction, tight junction, TGF-β signaling pathway, and MAPK signaling pathway, with a total of 38 differentially differentiated genes contained in these 5 pathways, and it was hypothesized that the above pathways as well as the DEGs in the pathways played an important role in the regulation of early growth and development of the Yili goose. This investigation serves as a foundational reference for elucidating the molecular regulatory mechanisms involved in the development of goose muscle. Furthermore, it contributes to the expansion of the theoretical framework concerning the genetic regulation of muscle growth in geese.

Objectives: Employee work engagement, job satisfaction, quality of care, and intent to leave are critical indicators for healthcare organizational performance. This study aimed to analyze the current state of nurses’ work engagement and its factors to examine the associations among nurses’ work engagement, job satisfaction, quality of care, and intent to leave in the United States (US). Methods: This is a quantitative descriptive cross-section design. Data were collected online from the US registered nurses from March to September 2022. Measures comprised the Utrecht Work Engagement Scale, the demographics, and questions regarding job satisfaction, perceived quality of care, and intent to leave. Results: Nine hundred nurses participated in the online survey. Among the participants, 79.2% reported holding a specialty certification, 59.4% scored high/very high on job satisfaction, 82.2% expressed high/very high on the perceived quality of nursing care, and 28.4% conveyed likely/very likely to leave in the following year. Nurses’ work engagement was positively associated with nurses’ job satisfaction and their perceived quality of care but negatively associated with intent to leave. More certified nurses reported high or very high job satisfaction than non-certified nurses. As for demographics, the linear regression analysis showed that nurses who were older, identified as White, and held doctorate degrees reported higher levels of work engagement in comparison to their counterparts. Conclusions: This study shows that nurses’ work engagement is associated with their job satisfaction, perceived quality of care, and intent to leave. Nurses’ work engagement in this study is lower than in other studies, especially before the COVID-19 pandemic, which may indicate a possible association with the COVID-19 impact. Because nurses’ work engagement is significantly associated with job satisfaction, nurse leaders need to find ways to promote nurses’ job satisfaction and retention.

Objectives: To examine the influence of heart failure high-fidelity simulation education based on the National League for Nursing (NLN) Jeffries Simulation Framework in prelicensure nursing education. Methods: A heart failure high-fidelity simulation (HFHFS) education pilot project was carried out at Carrington College Sacramento. Twenty-three students participated in the study. This study used a quasi-experimental design. Students’ Self-Efficacy, Satisfaction, and Knowledge in Heart Failure Clinical Knowledge were measured pre- and post-HFHFS education. Results: The results of the high-fidelity simulation education for heart failure showed that students achieved a mean score of 45.39 (SD = 7.88) in self-efficacy, 18.70 (SD = 3.38) in satisfaction, and 64.09 (SD = 10.86) in knowledge after the intervention. The paired-sample t-test significantly improved between the pre- and post-intervention scores (P

Abstract Background To study the validity of an artificial intelligence (AI) model for measuring fetal facial profile markers, and to evaluate the clinical value of the AI model for identifying fetal abnormalities during the first trimester. Methods This retrospective study used two-dimensional mid-sagittal fetal profile images taken during singleton pregnancies at 11–13+ 6 weeks of gestation. We measured the facial profile markers, including inferior facial angle (IFA), maxilla-nasion-mandible (MNM) angle, facial-maxillary angle (FMA), frontal space (FS) distance, and profile line (PL) distance using AI and manual measurements. Semantic segmentation and landmark localization were used to develop an AI model to measure the selected markers and evaluate the diagnostic value for fetal abnormalities. The consistency between AI and manual measurements was compared using intraclass correlation coefficients (ICC). The diagnostic value of facial markers measured using the AI model during fetal abnormality screening was evaluated using receiver operating characteristic (ROC) curves. Results A total of 2372 normal fetuses and 37 with abnormalities were observed, including 18 with trisomy 21, 7 with trisomy 18, and 12 with CLP. Among them, 1872 normal fetuses were used for AI model training and validation, and the remaining 500 normal fetuses and all fetuses with abnormalities were used for clinical testing. The ICCs (95%CI) of the IFA, MNM angle, FMA, FS distance, and PL distance between the AI and manual measurement for the 500 normal fetuses were 0.812 (0.780–0.840), 0.760 (0.720–0.795), 0.766 (0.727-0.800), 0.807 (0.775–0.836), and 0.798 (0.764–0.828), respectively. IFA clinically significantly identified trisomy 21 and trisomy 18, with areas under the ROC curve (AUC) of 0.686 (95%CI, 0.585–0.788) and 0.729 (95%CI, 0.621–0.837), respectively. FMA effectively predicted trisomy 18, with an AUC of 0.904 (95%CI, 0.842–0.966). MNM angle and FS distance exhibited good predictive value in CLP, with AUCs of 0.738 (95%CI, 0.573–0.902) and 0.677 (95%CI, 0.494–0.859), respectively. Conclusions The consistency of fetal facial profile marker measurements between the AI and manual measurement was good during the first trimester. The AI model is a convenient and effective tool for the early screen for fetal trisomy 21, trisomy 18, and CLP, which can be generalized to first-trimester scanning (FTS).

Abstract User–item interactions on e-commerce platforms involve various intents, such as browsing and purchasing, which require fine-grained intent recognition. Existing recommendation methods incorporate latent intent into user–item interactions; however, they overlook important considerations. First, they fail to integrate intents with semantic information in knowledge graphs, neglecting intent interpretability. Second, they do not exploit the structural information from multiple views of latent intents in user–item interactions. This study established the intent with knowledge-aware multiview contrastive learning (IKMCL) model for explanation in recommendation systems. The proposed IKMCL model converts latent intent into fine-grained intent, calculates intent weights, mines latent semantic information, and learns the representation of user–item interactions through multiview intent contrastive learning. In particular, we combined fine-grained intents with a knowledge graph to calculate intent weights and capture intent semantics. The IKMCL model performs multiview intent contrastive learning at both coarse-grained and fine-grained levels to extract semantic relationships in user–item interactions and provide intent recommendations in structural and semantic views. In addition, an intent-relational path was designed based on multiview contrastive learning, enabling the capture of semantic information from latent intents and personalized item recommendations with interpretability. Experimental results using large benchmark datasets indicated that the proposed model outperformed other advanced methods, significantly improving recommendation performance.

The primary causes of satellite breakups are hypervelocity impact and explosion, the research on satellite breakup can be used not only to evaluate the influence of breakup event on the space environment, but also to trace whether the satellite has been deliberately attacked. It is of great significance in both civil and military aspects. The study of satellite breakup behaviors and model is reviewed to summarize the research progress and insufficiency in recent decades, including the satellite breakup experiment, measurement and characterization of fragments, distribution characteristics of breakup fragments, satellite breakup model, etc. The classical studies are introduced in detail, and the limitations of the current research are pointed out. According to the current research results, the contemporary challenges and future directions for satellite breakup study are presented. The research on satellite breakup is developing in two directions: the miniaturization of satellite size and the complexity of satellite component. The study on satellite breakup needs to be explored and deepened on improving the experimental launch speed, expanding the model application range and breakup revealing the results under combined effect of impact and explosion.

A finite element model based on elastic–plastic theory was conducted to study the densification process of iron-based powder metallurgy during high velocity compaction (HVC). The densification process of HVC at different heights was simulated using MSC Marc 2020 software with the Shima–Oyane model, and compared with the experimental results. The numerical simulation results were consistent with the experimental results, proving the reliability of the finite element model. Through finite element analysis and theoretical calculation, the high-speed impact molding process of metal powder was analyzed, and the optimal empirical compaction equation for iron-based powder high-speed impact molding was obtained. At the same time, the influence of impact velocity and impact energy on the relative density distribution cloud map and numerical values of the compact was analyzed.

MYB is a common transcription factors widely involved in the regulation of anthocyanidin biosynthesis. In order to explore the regulatory role of MYB transcription factors in the biosynthesis of common buckwheat anthocyanidins, we screened and cloned a MYB gene associated with anthocyanin biosynthesis from the transcriptomic data of common buckwheat varieties of safflower common buckwheat and Beizaosheng, and named it FeR2R3-MYB, GenBank login number was MT151381.1. The sequence was analyzed by bioinformatics analysis and qRT-PCR was used to analyze the expression characteristics of FeR2R3-MYB gene in Beizaosheng and safflower common buckwheat. The results were as follows: (1) FeR2R3-MYB gene was 831 bp in total length, encoding 276 amino acids. The relative molecular mass of the protein was 30.95 kD, the theoretical isoelectric point (pI) was 8.73, and the instability index of the protein was 69.64, which belonged to the unstable protein. The total hydrophobic value was -0.679, and the whole peptide chain showed hydrophilic characteristics. (2) FeR2R3-MYB had a typical R2R3-MYB domain and belonged to the R2R3-MYB subfamily. (3) FeR2R3-MYB was closely related to common buckwheat and knotweed, belonging to the same family. (4) The promoter sequence of FeR2R3-MYB contained a total of nine light corresponding elements, 12 transcription factor binding sites, four abiotic corresponding elements and two hormone response elements. (5) Subcellular localization found that FeR2R3-MYB was only expressed in the nucleus. (6) The expression of FeR2R3-MYB gene of safflower common buckwheat was higher than that of Beizaosheng in leaves and inflorescences, and it was further speculated that FeR2R3-MYB gene could positively regulate the biosynthesis of common buckwheat anthocyanin. In summary, these results lay a foundation for further deepening the research on the function and expression regulation of FeR2R3-MYB gene in the biosynthetic pathway of common buckwheat anthocyanin.

Abstract NVS-ZP7-4 was identified as a novel chemical reagent targeting the zinc input protein ZIP7, which accounts for the zinc surge from the apparatus to the cytoplasm. Since zinc dysregulation is related to multiple diseases, in this study, we aimed to identify the anti-tumor effects of NVS-ZP7-4 and explore the molecular mechanisms of NVS-ZP7-4 in hepatocellular carcinoma (HCC) progression. We found that NVS-ZP7-4 inhibited cell viability, caused cell cycle arrest, induced apoptosis, and inhibited the proliferation, migration, and invasion of HCCLM3 and Huh7 cells. We further investigated the inhibited activation of the phosphatidylinositol 3-kinase (PI3K)/Akt pathway was involved in the antitumor effect of NVS-ZP7-4 in HCC. Furthermore, NVS-ZP7-4 inhibited HCC tumor growth in vivo. The present study demonstrated that NVS-ZP7-4 is a promising therapeutic target for HCC by regulating PI3K/AKT signaling.

Objective To analyze differences of eplets between the patient who generated HLA allele-specific antibodies after platelet transfusion with donors. Methods The HLA genotypes of the patient and donors were detected by PCR-SBT, and the Luminex single antigen beads coating was used to screen HLA-Ⅰ antibodies in the patient’s serum. HLA Matchmaker was utilized to analyze different amino acids and eplets. Results The patient carried HLA-A*02∶03 allele, and HLA-A2 antibodies were found in his serum after platelet transfusion (A*02∶01, A*02∶06, and A*02∶07). Sequence alignment showed that the patient′s A*02∶03 has a difference in position 149, which resulted in a different eplet between A*02∶03 and A*02∶01, A*02∶06, A*02∶07 and then induced the production of antibodies. Conclusion HLA antibodies are specific for HLA epitopes that have structural differences due to amino acid differences between HLA alleles, suggesting that high-resolution typing of HLA-A, -B need to be conducted in patients and donors, and the acceptable mismatch of HLA should be determined based on epitopes rather than antigens, so as to reduce alloimmune response and improve platelet count after transfusion.

Abstract Online recommendation systems process large amounts of information to make personalized recommendations. There has been some progress in research on incorporating knowledge graphs in reinforcement learning for recommendation; however, some challenges still remain. First, in these approaches, an agent cannot switch paths intelligently, because of which, the agent cannot cope with multi-entities and multi-relations in knowledge graphs. Second, these methods do not have predefined targets and thus cannot discover items that are closely related to user-interacted items and latent rich semantic relationships. Third, contemporary methods do not consider long rational paths in knowledge graphs. To address these problems, we propose a deep knowledge reinforcement learning (DKRL) framework, in which path-guided intelligent switching was implemented over knowledge graphs incorporating reinforcement learning; this model integrates predefined target and long logic paths over knowledge graphs for recommendation systems. Specifically, the designed novel path-based intelligent switching algorithm with predefined target enables an agent to switch paths intelligently among multi-entities and multi-relations over knowledge graphs. In addition, the weight of each path is calculated, and the agent switches paths between multiple entities according to path weights. Furthermore, the long logic path has better recommendation performance and interpretability. Extensive experiments with actual data demonstrate that our work improves upon existing methods.The experimental results indicated that DKRL improved the baselines of NDCG@10 by 3.7%, 9.3%, and 4.7%; of HR@10 by 12.39%, 20.8%, and 13.86%; of Prec@10 by 5.17%, 3.57%, 6.2%; of Recall@10 by 3.01%, 4.2%, and 3.37%. The DKRL model achieved more effective recommendation performance using several large benchmark data sets compared with other advanced methods.

In order to further study the cushioning performance of concave hexagonal cores (CHCs) and expand their application range, the in-plane finite element model of CHCs is established in this paper. A dynamic cushioning coefficient method was proposed to characterize the cushioning performance of CHCs. The dynamic cushioning coefficient curve and minimum dynamic cushioning coefficient (MDCC) of CHCs with different impact velocities and structural parameters are obtained. The influence rules of structural parameters and impact velocities on the MDCC are analyzed; the deformation mode and transformation empirical formula are also obtained. The results show that when other parameters are constant, the MDCC of CHCs decreases with the increase of impact velocity, increases with the increase of wall thickness and side length ratio, and decreases with the increase of expansion angle. The theoretical analysis is consistent with the finite element results, which further verifies the reliability of the model. This paper provides a solid theoretical basis for the industrial application of the cushioning performance of CHCs and forms a key technical support.

(1) backgroundThis study explores the coupling and coordinated development of new urbanization and eco-efficiency and their interaction mechanisms from the perspective of efficiency, and it has significant implications for promoting high-quality development and surpassing in China's regional development.(2) objectiveThe study aims to investigate the spatiotemporal distribution pattern of new urbanization efficiency and eco-efficiency and its coupling and coordinated development relationship.(3) methodsUsing panel data from 2010 to 2020 for nine cities in Fujian Province, this study employs the undesired super-efficiency SBM model to measure the efficiency of new urbanization and eco-efficiency. Additionally, a spatial panel Durbin model is constructed to analyze the interaction effect between the two efficiencies.(4) resultsDuring the study period, both new urbanization efficiency and eco-efficiency in Fujian Province showed a fluctuating upward trend, with higher efficiency in the southeast than the northwest, exhibiting significant spatial agglomeration effects. Despite high double efficiency coupling, coordinated development was low, evolving from near-disorder to barely coordinated. The high coupling and coordination areas were mainly concentrated in the southeast, with gaps between different regions gradually narrowing. There was positive interaction between dual efficiency in the same region, with new urbanization efficiency showing a positive spatial spillover effect on eco-efficiency. Conversely, the spatial spillover effect of eco-efficiency on new urbanization efficiency was not significant.

A possible approach to addressing the challenges of energy scarcity and the effects of global warming through the decrease of greenhouse gases is the manufacture of hydrocarbons, particularly fuel from the photoreduction of CO2. Here, the determination of activity/selectivity of produced hydrocarbons, hydrogen, and oxygen in the gas phase was demonstrated in the absence and presence of O2 in an aqueous slurry on TiO2. The conversion increases with reaction time up to the first hour but then begins to become unchanged in the presence of oxygen, suggesting catalyst deactivation. In contrast, the reaction rate and CO2 conversion increased over 4 h when there was no oxygen, demonstrating that oxygen can be the cause of TiO2 deactivation. Intriguingly, light-induced O2 uptake rather than evolution was seen during optical oxygen detection investigations in photoreactions with a peak region of O2/CO2. H2 production is suppressed by the presence of oxygen. Additionally, the sudden increase in hydrogen generation when oxygen is absent demonstrated that oxygen consumption and hydrogen production are taking place at the reduction site. The availability of oxygen reduced hydrocarbon productivity and H2 production.

Background and objective: Mild cognitive impairment (MCI) is a cognitive dysfunction syndrome defined mostly by memory or other cognitive impairments, and may serve as a precursor to Alzheimer's disease (AD). In recent years, acupuncture has gained recognition as a potential intervention for MCI, attracting significant attention as a promising and well-established therapy. In this study, we critically evaluate the clinical efficacy and safety of an innovative acupuncture approach, termed “Kidney Nourishment and Spirit Regulation”, as a therapeutic modality for MCI in geriatric populations. Methods: A prospective, randomized, single-blind, placebo-controlled, single-center clinical trial design where patients will be allocated in acupuncture, placebo (sham acupuncture sessions), or blank for eight weeks. The blank group will receive health education over the same eight-week period and will be offered compensatory acupuncture therapy after this period. The selected acupoints for this investigation include GV20, EX-HN1, GV24, GV29, CV6, CV4, PC6, KI3, LI4, LR3, HT7 and SP6. The primary outcome measure will be the Montreal Cognitive Assessment (MoCA), while secondary outcomes include the Mini Mental State Examination (MMSE), Activity of Daily Living (ADL), and Electroencephalogram (EEG). Discussion: This study seeks to provide an optimum regimen for acupuncture therapy in elderly MCI patients and to provide considerable theoretical evidence for its popularization and future broad adoption. We thus postulate that the current trial data might enlighten and potentially guide future research in terms of study design refinement.

BNIP3 (BCL2/adenovirus e1B 19 kDa protein interacting protein 3) is a mitochondrial outer membrane protein that is sensitive to hypoxia and mediates mitophagy, a process important for mitochondrial quality control and to maintain energetic and redox homeostasis under hypoxia. It has been reported that up-regulation of BNIP3, which acts as mitophagy receptor, promotes mitophagy. In our recent study, we found that the post-translational modification of BNIP3 is crucial to induce mitophagy, and that a crosstalk between phosphorylation/dephosphorylation and ubiquitination acts as a switch to control BNIP3-mediated mitophagy under hypoxia. We demonstrated that the phosphorylation of BNIP3 at S60 and T66 by MAPK8/9 (mitogen-activated protein kinase 8/9) under hypoxia blocks the degradation of BNIP3 via the ubiquitin-proteasome pathway and enhances its interaction with MAP1LC3 (microtubule associated protein 1 light chain 3), thereby promoting mitophagy. In contrast, dephosphorylation of BNIP3 by members of the PP1/2A (protein phosphatase PP1 and PP2A) phosphatase subfamily under hypoxia accelerates degradation of BNIP3 via the ubiquitin-proteasome pathway, thereby suppressing mitophagy. Altogether, these findings provide knowledge necessary to devise intervention strategies for hypoxia-related diseases and/or hypoxia-related developmental processes. Abbreviations: BCL2: BCL2 apoptosis regulator; BCL2L1: BCL2 like 1; BECN1: beclin 1, autophagy related; BH3: BCL2 homology 3; BNIP3: BCL2/adenovirus e1B 19 kDa protein interacting protein 3; LIR: MAP1LC3-interacting region; MAP1LC3: microtubule associated protein 1 light chain 3; MAPK8: mitogen-activated protein kinase 8; MAPK9: mitogen-activated protein kinase 9; PEST: rich in amino acids P, E, S, T, and D; PP1: protein phosphatase 1; PP2A: protein phosphatase 2A; PEST: rich in amino acids P, E, S, T, and D;

Abstract The pyrolysis oil fraction is highly attractive for pyrolysis products. A simulated flowsheet model of a waste tire pyrolysis process is presented in this paper. A kinetic rate-based reaction model and equilibrium separation model are created in the Aspen Plus simulation package. The simulation model is effectively proven against experimental data of literature at temperatures of 400, 450, 500, 600 and 700 °C. Also, the developed model was employed to investigate the impact of temperature on the pyrolysis procedure and demonstrated that there is an optimum temperature for chain fractions. The optimum temperature to have the highest amount of limonene (as a precious chemical product of waste tire pyrolysis process) was found 500 °C. The findings indicated that the pyrolysis process is ecologically benign, although there is still space for development. In addition, a sensitivity analysis was carried out to see how altering the heating fuel in the process would affect the non-condensable gases produced in the process. Reactors and distillation columns in the Aspen Plus® simulation model was developed to assess the technical functioning of the process (e.g., upgrading the waste tires into limonene). Furthermore, this work focuses on the optimization of the operating and structure parameters of the distillation columns in the product separation unit. The PR-BM, as well as NRTL property models, were applied in the simulation model. The calculation of non-conventional components in the model was determined using HCOALGEN and DCOALIGT property models.

Background: This study aims to investigate the association between nine tag single nucleotide polymorphisms (SNPs) in the C3 gene locus and the risk of coronary artery disease (CAD) as well as lipid levels in the Chinese population, and to further explore the interactions between SNPs and environmental factors that may be associated with CAD risk. Methods: A case-control study was conducted to investigate the association between CAD and C3 gene polymorphisms in a hospital setting. The study consisted of 944 CAD patients with a mean age of 55.97 ± 10.182 years and 897 non-CAD controls with a mean age of 55.94 ± 9.162 years. There were 565 males and 288 females in the CAD group and 583 males and 314 females in the control group. TagSNPs in the C3 gene were identified by employing the improved multiplex ligation detection reaction (iMLDR) technique, and multifactor dimensionality reduction (MDR) analysis was utilized to investigate the C3 gene–environment and gene–gene interactions in relation to the risk of CAD. Results: Results of the polymorphism study indicated that the CC genotype of rs7257062 was more frequent in the CAD group compared to the control group (10.9% vs 7.7%), with a statistically significant difference (p = 0.009). Moreover, the TT and CC + CT genotype groups of rs7257062 in the CAD subgroup showed a significant difference in terms of serum triglyceride levels (2.326 ± 1.889 vs 2.059 ± 1.447, p = 0.019). Analysis of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A (ApoA), and apolipoprotein B (ApoB) levels revealed no significant differences between the TT and CC + CT genotypes. Furthermore, no significant differences in serum lipid levels were observed between genotypes of the other SNPs. Multivariable logistic analysis, controlling for gender, age, body mass index (BMI), triglycerides (TG), TC, HDL-C, LDL-C, ApoA and ApoB, demonstrated that rs7257062 was still an independent risk factor of CAD (OR = 1.499, 95% CI: 1.036–2.168, p = 0.032). MDR analysis revealed that the rs7257062 interacted significantly with environmental factors such as smoking, diabetes, hypertension, BMI, and TG (p < 0.05). Conclusions: The rs7257062 variation of the C3 gene could be linked to both lipid balance and the risk of CAD. It is conceivable that the interplay between C3 polymorphisms and environmental elements could account for the etiology of CAD.

A critical precondition for realizing mechanized transplantation in rice cultivation is the implementation of seedling tray techniques. To augment the efficacy of seeding, a precise evaluation of the quality of rice seedling cultivation in these trays is imperative. This research centers on the analysis of rice seedling tray images, employing deep learning as the foundational technology. The aim is to construct a computational model capable of autonomously evaluating seeding quality within the ambit of intelligent seedling cultivation processes. This study proposes a virtual grid-based image segmentation preprocessing method. It involves dividing the complete image of a rice seedling tray into several grid images. These grid images are then classified and marked using an improved ResNet50 model that integrates the SE attention mechanism with the Adam optimizer. Finally, the objective of detecting missing seeding areas is achieved by reassembling the marked grid images. The experimental results demonstrate that the improved ResNet50 model, integrating the SE attention mechanism and employing an initial learning rate of 0.01 over 50 iterations, attains a test set accuracy of 95.82%. This accuracy surpasses that of the AlexNet, DenseNet, and VGG16 models by respective margins of 4.55%, 2.07%, and 2.62%. This study introduces an innovative model for the automatic assessment of rice seeding quality. This model is capable of rapidly evaluating the seeding quality during the seedling phase; precisely identifying the locations of missing seeds in individual seedling trays; and effectively calculating the missing seed rate for each tray. Such precision in assessment is instrumental for optimizing seedling processes

Soil analysis using near-infrared spectroscopy has shown great potential to be an alternative to traditional laboratory analysis, and there is continuously increasing interest in building large-scale soil spectral libraries (SSLs). However, due to issues such as high non-linearity in soil spectral data and complexity in soil spatial variation, the establishment of robust prediction models for soil spectral libraries remains a challenge. This study aimed to investigate the performance of deep learning algorithms, including long short-term memory (LSTM) and LSTM–convolutional neural networks (LSTM–CNN) integrated models, to predict the soil organic matter (SOM) of a provincial-scale SSL, and compare it to the normally used local weighted regression (LWR) model. The Hebei soil spectral library (HSSL) contains 425 topsoil samples (0–20 cm), of which every 3 soil samples were collected from dry land, irrigated land, and paddy fields, respectively, in different counties of Hebei Province, China. The results show that the accuracy of the validation dataset rank as follows: LSTM–CNN (R2p = 0.96, RMSEp = 1.66 g/kg) > LSTM (R2p = 0.83, RMSEp = 3.42 g/kg) > LWR (R2p = 0.82, RMSEp = 3.79 g/kg). The LSTM–CNN model performed the best, mainly due to its comprehensive ability to effectively extract spatial and temporal features. Meanwhile, the LSTM model achieved higher accuracy than the LWR model, owing to its built-in memory unit and its advantage of faster feature band extraction. Thus, it was suggested to use deep learning algorithms for SOM predictions in SSLs. However, their performance on larger-scale SSLs such as continental/global SSLs still needs to be further investigated.

Alzheimer’s disease (AD) is an insidious, neurodegenerative disease that no drug can prevent or cure. Folium Nelumbinis (FN) has rich functional components with neuroprotective effects. This research explored the FN chemical profile and the neuroprotective effect in vivo. Studies on the safety assessment of FN extract, effects on amyloid-β (Aβ) aggregation, oxidative stress, and acetylcholinesterase (AChE) activity were performed in Caenorhabditis elegans. Results revealed that the FN extract could delay paralysis, reduce Aβ deposition, lower oxidative stress, attenuate AChE activity, and regulate genes and proteins related to Aβ toxicity, which suggested that it exerts a dual targeting effect on Aβ and AChE simultaneously. Additionally, seven individual components from FNE were screened out with affinity ultrafiltration mass spectrum combined with molecular docking. The underlying mechanisms might be relevant to the DAF-16/FOXO signaling pathway and ACE1/ACE2 axis. In conclusion, FN is valuable in health promotion and AD prevention.

The current work objectives are providing detailed understanding of heat and mass transport in a cross-flow membrane contactor for desalination process. The numerical code was developed using MATLAB software to investigate temperature and humidity distribution in the cross-flow membrane contactor at different operating parameters. Firstly, the developed model was successfully validated by experimental data. It was found that increase in saline solution inlet temperature from 40 °C to 80 °C can enhance solution outlet temperature, outlet air temperature, and humidity of outlet air from 37.38 °C to 56.79 °C, 39.48 °C–72.33 °C, and 0.0393 kg/kg to 0.2620 kg/kg respectively. Furthermore, the results showed that increase in saline solution flowrate and its inlet temperature has significant influence on the improvement of the process performance in terms of producing more pure water. However, there was no effect on temperature and humidity profiles, vapour transport though microporous membrane with the enhancement of inlet humidity of air. It was only had small positive influence on humidity humidification efficiency at inlet temperatures in the range of 40 °C–80 °C.

In this article, an experimental study was carried out to investigate the cooling efficiency of a vortex tube equipped with a rectifier utilizing the Taguchi method for analysis. The Coefficient of Performance (COP) was determined as the quality characteristics. In the current study, the inlet pressure, distance between the rectifier and the hot end, the position of the rectifier, the height of the rectifier, the number of blades, the length of blades, the inclination angle of blades with and without ring were selected as the key control factors and levels. Taguchi L18 orthogonal array was applied to design the experiments. The Signal-to-Noise Ratio (SNR), regression, Analysis of Variance (ANOVA) and residual analysis were applied to optimise the combination for COP of the vortex tube. The tests were also conducted to validate the reliability of the predicted optimisation method. Experimental results indicated that: (i) the predicted optimal value falls within a Confidence Interval (CI) of 95%. The analysis also revealed that the length of the blades could be the most influential control factor, accounting for 36.9% of the cooling performance. (ii) the height of the rectifier shows little impact, only contributing 4.7% to the overall cooling performance. (iii) the order of other control factors on COP was inlet pressure (21%), whether the rectifiers with or without ring (12.8%), distance between the rectifier and the hot end (7.9%), the inclination angle of blades (6.2%) and the number of blades (5.3%).

Owing to the marine environmental pollution affected by cruises, the use of techniques to mitigate carbon dioxide emission (CO2) is vital. Since a quarter of the fuel energy input to the engine is lost, waste management for marine diesel engines can provide some valuable outputs by which the need for other energy conversion-based methods disappears. Hence, the current work proposes a novel model of waste heat recovery for a 1 MW marine diesel engine in a low-temperature framework by which outstanding results are predictable. The defined auxiliary model consists of an absorption power cycle and an ejector refrigeration cycle to produce useful electricity and cooling for air conditioning. This model is designed for the first time and comprehensively analyzed and optimized to set the most suitable state of operation. The potential of the model is measured through the exergy, environmental, economic, and net present value standpoints. Moreover, an advanced evolutionary algorithm based on the non-dominated sorting genetic algorithm-II is applied to reach the optimum cost and exergetic performance. The optimum state showed an exergy efficiency of 35.19 % and products’ specific cost of 53.01 $/GJ. Moreover, the optimum payback period and CO2 emission reduction equal 6.79 years and 21.5 kg/MWh, respectively.

Free convection of Fe3O4-water inside the porous enclosure was investigated in the presence of magnetic fields. The SIMPLE algorithm was employed to solve the equations based on FVM. The inner wall of enclosure was considered in the constant flux and that of outer wall were at a constant temperature, respectively. Also, two other walls are thermal insulation and the radiation reflects to inner semi-annulus. An electric current coil for producing a magnetic field is wrapped around the semi-annulus. The effects of Rap=10and1000, the concentration (φAve=0,0.01and0.03), porosities (ε=0.4and0.7) and magnetic numbers (0≤Mn≤8×107) are investigated considering first laws of thermodynamics. The findings revealed that the mean Nusselt number has direct relation with the magnetic number, porosity, Rap and concentration, respectively. Moreover, increasing volume fraction from 0.01 to 0.03 in high magnetic number enhanced the Nusselt number by 32 %.

We aimed to study the protective effects of 3-n-butylphthalide (NBP) on cerebral infarction induced by local ischemic injury and regulation mechanism of the PI3K/Akt/GSK-3β signaling pathway. One hundred male Wistar rats aged 12-15 weeks were randomly divided into 5 groups (n=20). The middle cerebral artery occlusion (MCAO) model was established. NBP, P13K specific inhibitor LY294002 and NBP plus LY294002 groups were intraperitoneally administered on the first day after modeling, once a day for 7 days. Sham operation (Sham) and model groups were intraperitoneally given equal amounts of normal saline. Neuronal damage was detected by Nissl staining. Intact neurons were counted under light microscope. The protein expressions of Akt, P-Akt, GSK-3β and P-GSK-3β were detected by Western blotting. The mNS score of NBP group decreased significantly compared with that of model group (P