Search

Abstract This study aimed to evaluate the effect of Astragalus polysaccharides (PG2) on reducing chemotherapy-induced fatigue (CIF) and toxicity, thereby encouraging compliance to chemotherapy. This was a randomized, placebo-controlled, phase 2 study. Patients with stage II/III early breast cancer planning to undergo adjuvant anthracycline-based chemotherapy were randomly assigned to receive PG2 500 mg or placebo on days 1, 3, and 8 every 21 days. The fatigue global score (FGS) was assessed using the brief fatigue inventory (BFI)-Taiwan. The Breast Cancer-Specific Module of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaires-Core30 evaluated the health-related quality of life during the first four cycles of adjuvant chemotherapy. Overall, 66 eligible patients were equally randomized into the PG2 and placebo groups between March 01, 2018, and March 09, 2021. The mean change in the FGS and fatigue intensity did not significantly differ between both groups. However, the FGS and fatigue intensity were less aggravated in the first four cycles in the premenopausal-PG2 group than in the placebo group. Our study concluded PG2 combined with adjuvant chemotherapy can reduce CIF, insomnia, the negative effect on future perspectives, and improve global health status, especially for premenopausal patients with breast cancer. Trial registration number: NCT03314805 registered on 19/10/2017.

Abstract This study aims to present age-stratified prevalence of women with lower urinary tract symptoms (LUTS) but without cystocele and predict detrusor underactivity (DU) or bladder outlet obstruction (BOO). Between 2005 and 2020, we reviewed women who visited the medical center with LUTS but without cystocele. Positive voiding dysfunction (VD) symptoms were defined as any one or more of the positive descriptions of weak urinary stream, intermittency, strain to urination, and sensation of not emptying. A total of 1,886 women were included in this study. 189 (10.0%) women were diagnosed with DU, and 77 (4.1%) women had BOO. Multivariate logistic regression analysis found that voided volume and VD symptoms were independent predictors for BOO. ROC curve analyses could predict BOO by voided volume ≤ 220 mL derived from uroflowmetry and the presence of VD symptoms with an area under a curve of 0.83. Age and voided volume could predict DU with an area under a curve of 0.82. We found a higher percentage of BOO in women with positive VD symptoms. A non-invasive uroflowmetry with voided volume (≤ 220 mL) and the presence of VD symptoms can predict BOO. DU could be predicted by age and voided volume.

Abstract Androgen receptor (AR) overexpression has been identified in gliomas and its stem cells, suggesting that AR plays an important role in tumor carcinogenesis. The prognostic significance of AR overexpression in gliomas remains unknown. AR mRNA expression in gliomas and relevant clinical data were obtained from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. AR expression levels were compared across gliomas of different histopathologic grades and molecular subtypes. Kaplan–Meier analyses in patients with different AR expression levels were investigated for the potential prognostic values of AR. Compared with normal brain tissue, gliomas show significantly higher AR mRNA expression (p

Abstract A mismatch in footprints of cervical total disc arthroplasty (CTDA) implants occasionally occurred in Asian population and it had been attributed solely to ethnic factor. Yet, cervical degeneration process may play a role. Our purpose was to compare the cervical vertebra morphometric data with and without degeneration. The study included patients with CT scans of cervical spine from our hospital between January, 2019, and September, 2021. The total cervical degenerative index (TCDI) of each patient were collected by adding CDI score for 5 disc-levels. Patients were categorized into normal (TCDI 0–5) and degeneration groups (TCDI 6–60). Various measurements of the C3–C7 vertebral body and endplate were taken. Forty-nine patients in the normal group and 55 in the degeneration group were included. No significant difference was noted in gender, BH, BW, or BMI except age and TCDI (p

Distinguishing indolent from clinically significant localized prostate cancer is a major clinical challenge and influences clinical decision-making between treatment and active surveillance. The development of novel predictive biomarkers will help with risk stratification, and clinical decision-making, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2 is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study. We demonstrate that elevated Trop2 expression is correlated with worse clinical features including Gleason score, age, and pre-operative PSA levels. More importantly, we demonstrate that elevated Trop2 expression at radical prostatectomy predicts worse overall survival in men undergoing radical prostatectomy. Additionally, we detect shed Trop2 in urine from men with clinically significant prostate cancer. Our study identifies Trop2 as a novel tissue prognostic biomarker and a candidate non-invasive marker for prostate cancer.

Abstract Understanding and controlling the ground stress in deep coalfield mining is crucial for ensuring mine safety and efficiency. This study aims to address two unresolved scientific issues in ground stress research: the selection of optimal excavation plans and the large-scale rapid acquisition of ground stress data. A novel computational model is proposed for key rock layer control under different crustal stress conditions. The model considers the complexity and uncertainty of ground stress distribution by simplifying the key rock strata into a fixed-fixed beam model and calculating their safety through mechanical methods. Introducing an innovative approach for acquiring large-scale stress fields using GPS data. By inverting large-scale strain fields in the coalfield area, combined with World Stress Map (WSM) and measured data, accurate stress fields are obtained. The proposed optimal excavation plan can be applied to various coalfield locations worldwide, providing a scientific basis for safe and efficient mining operations. Additionally, the innovative use of GPS data in obtaining large-scale stress fields offers a valuable tool for assessing ground stress variation.

Abstract Underwater target detection technology is very important for Marine resources detection and underwater environment perception. The problems of low-quality underwater images, a large amount of calculation, and low accuracy of target detection models still need to be solved. Firstly, a new underwater image enhancement algorithm based on multi-scale fusion is proposed. The algorithm combines the improved white balance algorithm and the improved CLAHE (Contrast Limited Adaptive Histogram Equalization) and realizes the multi-scale fusion strategy by introducing different weight maps, aiming to improve the visual effect and quality of underwater images. Secondly, to further improve the accuracy and efficiency of underwater target detection, an improved YOLOv5s lightweight underwater target detection algorithm is proposed. The algorithm combines the Ghost convolution module, EMA(Efficient Multi-Scale Attention) mechanism, and CARAFE (Content-Aware ReAssembly of FEatures) up-sampling mode. The comparison on the URPC(Underwater Robot Perception Challenge) public dataset shows that the proposed algorithm has achieved significant improvement in terms of model size, parameter amount, calculation amount, and mAP@0.5. Thirdly, to verify the effectiveness of the image enhancement algorithm and underwater target detection algorithm proposed in this paper, the ROV(Remote Operated Vehicle) is used to conduct experiments in the experimental pool. By designing underwater target detection experiments before and after image enhancement, the results show that the enhanced image significantly improves the detection ability of underwater targets. Finally, underwater target detection software is developed to provide strong support for the application of underwater-related fields.

Abstract Circulating tumor cell separation has been the focus of numerous studies owing to its importance in the diagnosis, prognosis, and therapy of cancer. This study reports a highly efficient microfluidic device that integrates a specialized dielectrophoresis configuration, namely the facing-electrode configuration dielectrophoresis (FEC-DEP) structure, to isolate circulating tumor cells (CTCs) from various blood components, including red blood cells, white blood cells, and platelets. The FEC-DEP design features a bottom-slanted electrode array positioned parallel to a basic rectangular top electrode. A non-homogeneous electric field is produced between these parallel electrodes, generating dielectrophoretic forces acting on cells. Consequently, when the FEC-DEP is integrated into a flow, it can direct various biological objects in the flow along separate trajectories. As a result, cells with comparable characteristics might move together within a similar path. This configuration may simplify the microfabrication process and lessen dependency on particle position within the microchannel. The separation process was numerically analyzed using the finite element method, and device parameters were optimized to obtain high-efficiency and high-purity cell separation. The simulations show that the microfluidic device may effectively enrich tumor cells in a label-free and non-invasive manner, with a high-efficiency rate of almost 80%.

Abstract Understanding the properties of explosives is the basis for investigating and analyzing explosion cases. To date, due to the strict legal control of standard explosives and initiators, homemade pyrotechnics composed of oxidizers and fuels have become popular explosive sources of improvised explosive devices (IEDs) threatening greatly social stability and personal safety. The reactivity of pyrotechnics strongly depends on their intrinsic characteristics and operating conditions, which determine the efficiencies of heat and mass transfer between the reaction zone and the unreacted zone. Herein, the tests of thermodynamics, pressurization characteristics, and combustion propagation behaviors are conducted to explore the effects of oxidizer species, particle size, and loading density on the reactivity of homemade binary aluminum-based pyrotechnics. The results show that the pyrotechnics with potassium chlorate (KClO3) have the strongest reactivity with the highest pressurization rate (dp/dt) and the shortest combustion duration. Compared with their counterparts based on aluminum microparticles(mAl), pyrotechnics consisting of Al nanoparticles (nAl) possess superior reactivity as expected, which results from the relatively short heat and mass transfer distances. The nAl-based pyrotechnics have a low reaction exothermic peak temperature, great heat release, great aluminothermic reaction completeness, and high produced peak pressure with several orders of magnitude higher pressurization rate. Increasing the loading density of the pyrotechnics over a certain value can change the dominant mode of heat transfer from convective to conduction, sharply decreasing the pressurization characteristics and combustion front propagation velocities (v p ). The results of theoretical calculations using the NASA-CEA codes show that loading density can alter the reaction process of the pyrotechnics, leading to a decrease in the predicted pressure per unit mass for Al/KNO3 or Al/AP, and an increase for Al/KClO3. For nAl/potassium nitrate (KNO3), the density is between 1.0 and 1.25 g cm−3, across which dp/dt decreases by one order of magnitude from 0.148 to 0.014 MPa ms−1. In addition, v p decreases by three orders of magnitude from 0.040 to 0.078 m s−1. Distinct pressurization behaviors of nAl/AP are observed at a density of 1.5 g cm−3, while the variation in nAl/KClO3 reactivity fluctuates. These results are beneficial for the damage assessment of scenes caused by an explosion and for inversely calculating charge parameters.

Abstract Brain tumor diagnosis is an important task in prognosing and treatment planning of the patients with brain cancer. in the meantime, using the Magnetic Resonance Imaging (MRI) as a commonly used non-invasive imaging technique provide the experts a helpful view for detecting the brain tumors. While deep learning methods have shown significant success in analyzing medical images, they often require careful design of architecture and tuning of hyperparameters to achieve optimal results. This study presents a new approach for diagnosing brain tumors in MRI scans using deep learning, focusing on Residual/Shuffle Networks. The designed network structures offer efficient results when compared to traditional deep learning models. To enhance the proposed network for brain tumor classification, a modified metaheuristic algorithm named Augmented Falcon Finch Optimization (AFFO) is introduced. AFFO utilizes bio-inspired principles to effectively search for the best hyperparameter configurations, thereby enhancing the reliability and accuracy of the deep learning model. The performance of the proposed method is evaluated on a standard brain tumor MRI dataset and compared with existing techniques, including ResNet, AlexNet, VGG-16, Inception V3, and U-Net to illustrate the effectiveness of combining Residual/Shuffle Networks with AFFO for brain tumor diagnosis.

Abstract Determining the optimal timing for subsequent water flooding in Alkali-Surfactant-Polymer (ASP) flooding is essential to maximizing both the technical and economic outcomes of oilfield blocks. This study identified eight critical parameters that influence the benefits of ASP flooding and established parameter ranges based on data from completed blocks and actual field measurements. The optimal timing for subsequent water flooding was determined by evaluating cumulative net profit variations throughout the ASP flooding lifecycle. Given the complexity and high-dimensional nature of evaluating multiple parameters across diverse blocks, a machine learning-driven optimization model was developed. This model enhances work efficiency by automating complex analyses. However, predictive uncertainties and limitations remain due to the variability in oilfield development and the potential for unpredictable changes in reservoir conditions, external market factors and so on, which may affect the model’s results. The model was applied to six blocks in the Daqing oilfield currently in the chemical flooding phase, where injection schemes, such as extending the polymer slug, were adjusted according to the model’s optimized results. These adjustments yielded an increase in cumulative net profit of 224.9 million CNY compared to the original scheme, with a potential total increase of 752.1 million CNY by the end of the flooding process.

Abstract Internal phosphorus loading (IPL), as an important part of lake phosphorus cycle and the key to solve the eutrophication problem, is still an important cause of regional and seasonal algal blooms for some mesotrophic lakes located in plateau areas. We investigated the composition, distribution of P fractions in sediments and suspended particulate matter (SPM) of Erhai Lake, southwest China, and explored the relationships between environmental variables and spatial-temporal variations of P fractions. The total P (TP) in surface sediments ranged from 817 to 1216 mg/kg, with inert Ca-P (32%) and Res-P (24%) predominating, at a moderate level. The comparison of short-term release fluxes (0.08 mg/(m2·d)) and long-term release fluxes (0.09 mg/(m2·d)) reflected that the northern region was recovering slowly from the previous P pollution. Mobile-P (the sum of loosely adsorbed P, iron bound P, and organic P) accounted for 52.3% of the TP in SPM and showed high spatial-temporal variations, which were closely related to the growth of algae throughout the investigation. The results suggested that sediments could make a sustained contribution to IPL, and that the P in SPM was highly active and significantly contributed to eutrophication in Erhai Lake especially at the time of seasonal alternations. Our data provided important theoretical bases for the relationship between internal phosphorus loading and eutrophication in plateau lakes.

Abstract Patients with diabetes are susceptible to acute kidney injury (AKI) as compared to counterparts without diabetes. However, data on the long-term clinical outcome of AKI specifically in people with diabetes are still scarce. We sought to study risk factors for and adverse cardio-renal outcomes of AKI in multi-ethnic Southeast Asian people with type 2 diabetes. 1684 participants with type 2 diabetes from a regional hospital were followed an average of 4.2 (SD 2.0) years. Risks for end stage kidney disease (ESKD), major adverse cardiovascular events (MACE) and all-cause death after AKI were assessed by survival analyses. 219 participants experienced at least one AKI episode. Age, cardiovascular disease history, minor ethnicity, diuretics usage, HbA1c, baseline eGFR and albuminuria independently predicted risk for AKI with good discrimination. Compared to those without AKI, participants with any AKI episode had a significantly high risk for ESKD, MACE and all-cause death after adjustment for multiple risk factors including baseline eGFR and albuminuria. Even AKI defined by a mild serum creatinine elevation (0.3 mg/dL) was independently associated with a significantly high risk for premature death. Therefore, individuals with diabetes and any episode of AKI deserve intensive surveillance for cardio-renal dysfunction.

Abstract Intraventricular hemorrhage (IVH) occurs in approximately 30–50% patients with spontaneous intracerebral hemorrhage (ICH), with a high 30-day mortality rate. Excess accumulation of parenchymal or ventricular blood associated with the development of acute hydrocephalus leads to poor outcomes. The prediction of shunt dependency is important to identify patients susceptible to requiring permanent shunt placement and benefit from the diversion. This retrospective analytical study aimed to establish a predictive model of shunt dependency in patients with IVH. This study included 179 patients with primary IVH with supratentorial origin or spontaneous ICH with extension into the ventricles between 2015 and 2021. Patients were grouped into “shunt required” and “shunt not required” groups. Variables, including age, sex, preexisting hypertension and diabetes, initial Glasgow Coma Scale scores, ICH location and volume, urokinase administration, modified Graeb score (mGraeb score), and bicaudate index, were analyzed. The shunt required group had significantly higher mGraeb scores (12.0 (6.5–15.0) vs. 7.0 (4.0–12.0), p = 0.001) and higher bicaudate index (0.20 (0.17–0.23) vs. 0.16 (0.13–0.18), P

Abstract Acanthopanax senticosus belongs to Araliaceae family and is traditionally used as a tonic. The roots and stems are mainly used as treatments for hypodynamia, rheumatism, and hypertension, but their frequent use may lead to extinction. However, comprehensive and simultaneous analysis of the remaining parts were still limited. There is a need to reorganize them for standardization of functional foods. In this study, 50 phenolic compounds and 82 triterpenoid saponins from the shoots, leaves, fruits, and stems of were characterized using UPLC-QTOF-MS and UPLC-QTRAP-MS/MS. Among them, 52 compounds were newly determined as the cis and malonyl-bound phenolic acids and were found to be structural isomers of Acanthopanax flavonoids and saponins. All compounds were absolutely/relatively quantified, and shoots had the highest content. Peroxynitrite and α-glucosidase inhibitory activities were performed, followed by evaluation of structure-activity relationships. Particularly, hederasaponin B and ciwujianoside B showed remarkable efficacy, which were affected by the C-23 hydroxylation, the C-20(29) double bond, and the presence of rhamnose. These detailed profiling can be used as fundamental data for increasing the utilization of A. senticosus and developing them into functional foods.

Abstract It remains unclear whether pulmonary fibrosis-like changes differ in patients with different SARS-CoV-2 variants. This study aimed to compare pulmonary fibrotic changes between two SARS-CoV-2 variant periods (delta vs. pre-delta) in critically ill patients with SARS-CoV-2 pneumonia. Clinical data and chest CT images of patients with SARS-CoV-2 pneumonia receiving mechanical ventilation were collected from 10 hospitals in South Korea over two periods: delta (July-December, 2021; n = 64) and pre-delta (February, 2020-June, 2021; n = 120). Fibrotic changes on chest CT were evaluated through visual assessment. Of 184 patients, the mean age was 64.6 years, and 60.5% were ale. Fibrosis-like changes on chest CT (median 51 days from enrollment to follow up CT scan, interquartile range 27–76 days) were identified in 75.3%. Delta group showed more fibrosis-like changes (≥ 2) (69.8% vs. 43.1%, P = 0.001) and more frequent reticulation and architectural distortion+/-parenchymal band than pre-delta group. Even after propensity score matching with clinical variables, delta group had more severe (≥ 2) fibrosis-like changes (71.4% vs. 38.8%, P = 0.001), and more frequent reticulation and architectural distortion+/-parenchymal band than pre-delta group. Our data suggest that critically ill patients with SARS-CoV-2 in delta period had more severe pulmonary fibrosis-like changes than those in pre-delta period.

Abstract Detecting EGFR mutations in plasma using droplet digital PCR (ddPCR) assay offers a promising diagnostic tool for lung cancer patients. The performance of plasma-based ddPCR assay relative to traditional EGFR mutation testing in tissue biopsies among Asian patients with suspected lung cancer remains underexplored. Consecutive patients admitted for diagnostic workup for suspected lung cancer were recruited. Peripheral blood samples were collected on the same day of tissue biopsies. Tissue samples were subjected to EGFR mutation analysis via real-time PCR, whereas plasma samples were processed for ddPCR assay to evaluate for EGFR mutation status. The tissue re-biopsy rate was 43.8% while 0.7% of patients failed blood taking. Despite repeat biopsy, 15.2% of patients could not achieve histological diagnosis. Of the 202 patients newly diagnosed with lung cancer, EGFR mutations were detected in 13.4% of plasma samples, compared to 44.3% in tissue samples. Plasma ddPCR for EGFR mutations detection were barely detectable in stages I and II non-small cell lung cancer (NSCLC), but the sensitivity was 25.0%, 56.3%, and 75.0% in stages III, IVA, and IVB NSCLC, respectively. Plasma EGFR mutations were highly specific among all stages of lung cancer. Concordance rates of plasma ddPCR assay also rose with more advanced stages, recorded at 41.9% for stages I and II, 71.9% for stage III, 86.3% for stage IV. In stage IV lung cancer, the false negative rate for the plasma ddPCR assay was 34.4%, whereas that for the tissue testing was 19.2% due to insufficient tissue samples. Plasma-based EGFR genotyping using ddPCR is a non-invasive method that offers early diagnosis and serves as a valuable adjunct to tissue-based testing for patients with advanced-stage lung cancer. However, its usefulness is limited in the context of early-stage lung cancer, indicating a need for further research to improve its accuracy in these patients.

Abstract Although many dyes have been introduced into cellulose, whether bound to its backbone or within a cellulose matrix, few studies have determined whether the backbone statically or dynamically quenches the photoluminescence of the dye. To advance cellulosic fluorescent films, the influence of the cellulose backbone on photoluminescence must be understood. We determined the fluorescence properties of fluorescein isothiocyanate (FITC) and fluorescein-labeled cellulose (FLC) in water and alcohol, including their quantum yields $$\boldsymbol{\phi}_{\textit{\textbf{PL}}}$$ , lifetimes $${\boldsymbol{\tau}}$$ , and rates of radiative $${\textit{\textbf{k}}}_{\textit{\textbf{r}}}$$ and nonradiative $${\textit{\textbf{k}}}_{\textit{\textbf{nr}}}$$ decay. Dissolved FLC had a ~ 30× lower $$\boldsymbol{\phi}_{\textit{\textbf{PL}}}$$ than FITC, suggesting that incorporating FITC into the cellulose backbone remarkably reduces the fluorescence efficiency. The FLC solutions had a six-fold lower $${\textit{\textbf{k}}}_{\textit{\textbf{r}}}$$ than their FITC counterparts but a 10–20 times higher $${\textit{\textbf{k}}}_{\textit{\textbf{nr}}}$$ . Presumably, this was because the cellulose backbone interacted weakly with the fluorescein moieties, suggesting a quenching mechanism that can be termed quasi-static, corresponding to static quenching between the fluorescein moieties and cellulose backbone, in addition to the fluorescence quenching caused by the intramolecular nonradiative processes of fluorescein, as observed in conventional molecules. Using the Strickler‒Berg formula, we deduced the analytical radiative decay rate constants $${\textit{\textbf{k}}}_{\textit{\textbf{r}}}^{\textit{\textbf{S.B.}}}$$ and eventually estimated the number of very short-lived fluorescein moieties per single fluorescent fluorescein moiety, corresponding well with static quenching.

Abstract The transplantation of CD34+ hematopoietic stem-progenitor cells (HSPCs) derived from cord blood serves as the standard treatment for selected hematological, oncological, metabolic, and immunodeficiency disorders, of which the dose is pivotal to the clinical outcome. Based on numerous maternal and neonatal parameters, we evaluated the predictive power of mathematical pipelines to the proportion of CD34+ cells in the final cryopreserved cord blood product adopting both parametric and non-parametric algorithms. Twenty-four predictor variables associated with the cord blood processing of 802 processed cord blood units randomly sampled in 2020–2022 were retrieved and analyzed. Prediction models were developed by adopting the parametric (multivariate linear regression) and non-parametric (random forest and back propagation neural network) statistical models to investigate the data patterns for determining the single outcome (i.e., the proportion of CD34+ cells). The multivariate linear regression model produced the lowest root-mean-square deviation (0.0982). However, the model created by the back propagation neural network produced the highest median absolute deviation (0.0689) and predictive power (56.99%) in comparison to the random forest and multivariate linear regression. The predictive model depending on a combination of continuous and discrete maternal with neonatal parameters associated with cord blood processing can predict the CD34+ dose in the final product for clinical utilization. The back propagation neural network algorithm produces a model with the highest predictive power which can be widely applied to assisting cell banks for optimal cord blood unit selection to ensure the highest chance of transplantation success.

Abstract The current diagnostic criteria for gestational diabetes (GDM) were based on data from women after 24 weeks of gestation, but this may not be equally applicable for earlier gestation. There is insufficient data regarding early pregnancy glycaemia and the associated complications. We retrospectively reviewed 39,483 deliveries and 12,918 with risk factors for GDM underwent oral glucose tolerance test (OGTT) before 24 weeks of gestation. A strong and progressively positive association was observed with any pregnancy complications in both fasting glucose (FG) and 2 h glucose (2hG). The increased risk of developing any pregnancy complications started from FG 4.5–4.7 mmol/L and 2hG of 6.2–6.9mmol/L. Every increase by 1 mmol/L in FG or 2 hG levels increased the risk of developing any complications (aOR 1.614 for FG and 1.131 for 2hG), pre-eclampsia (aOR 1.472 for FG and 1.143 for 2hG), maternal insulin use (aOR 12.821 for FG and 2.366 for 2hG), primary Caesarean section(aOR 1.274 for FG and 1.099 for 2hG), shoulder dystocia (aOR 1.941 for FG and 1.282 for 2hG), macrosomia(aOR 2.203 for FG and 1.072 for 2hG), and large for gestation age(aOR 2.157 for FG and 1.074 for 2hG). Therefore, glycaemic levels in early pregnancy among high-risk women positively associated with pregnancy complications, even at levels below the current recommended diagnostic criteria for GDM.

Abstract Postural orthostatic tachycardia syndrome (POTS) presents excessive orthostatic tachycardia and orthostatic intolerance. POTS is a common and therapeutically challenging condition affecting numerous people worldwide. As many disease entities can be confused with POTS, it becomes critical to identify this syndrome. Moreover, unbalanced autonomic nervous activity can induce cardiovascular diseases and influence the bio-feedback mechanism: Baroreflex (BR) and cerebral autoregulation (CA). BR and CA are important bio-mechanisms that maintain a stable circulatory system via the autonomic nervous system. Therefore, an impaired autonomic nervous system would lead to imbalanced BRS and CA. Consequently, we propose an advanced cross-correlation function (ACCF) time-domain approach to analyze baroreflex and cerebral autoregulation using physiological signals. This study assesses relation changes in BR and CA using ACCF in POTS for early clinical detection and diagnosis. The ACCF analysis results has thresholds that reveal that the BR of healthy and POTS groups present significantly different maximum CCF values (p

Abstract NO previous studies have examined the simultaneous effects of obstructive sleep apnea (OSA), hypertension, and the SNP rs68430822 on stroke. We aimed to explore whether these elements together, play a role as risk factors for stroke. Data was obtained from the Taiwan Biobank and the National Health Insurance database. We used logistic regression analysis to investigate the effect of OSA and hypertension as a risk factor for stroke in different genotypes. We found that OSA and hypertension was associated with stroke in those with the rs6843082 genotype. People with OSA and hypertension together with the rs6843082 genotype (GA + AA) showed a statistically significant difference as a risk for stroke (OR,2.57; 95% CI,1.53 to 4.33). However, there was no statistically significant difference in those people with OSA but without hypertension (OR, 0.53; 95% CI,0.13 to 2.25). After further stratification by combination of OSA and hypertension, those with genotype rs6843082 (GG) had higher risk odds than those with OSA and those with hypertension alone (OR,5.46, 95% CI,3.46 to 8.60). Individuals with genotype rs6843082(GA + AA), OSA and hypertension together had the highest risk for stroke (OR,6.25, 95% CI,3.63 to 10.76) and those with OSA and no hypertension (OR,0.57, 95% CI,0.14 to 2.36) had no significant risk. Our findings showed that people with genotype rs6843082 (GG), with or without hypertension had OSA as a risk factor for stroke. For individuals with the genotype rs6843082 (GA + AA), those with hypertension, OSA is a risk factor for stroke, and for those without hypertension, OSA is not associated with stroke.

Abstract The most common mutation in southern Chinese individuals with late-onset multiple acyl-coenzyme A dehydrogenase deficiency (MADD; a fatty acid metabolism disorder) is c.250G > A (p.Ala84Thr) in the electron transfer flavoprotein dehydrogenase gene (ETFDH). Various phenotypes, including episodic weakness or rhabdomyolysis, exercise intolerance, and peripheral neuropathy, have been reported in both muscular and neuronal contexts. Our cellular models of MADD exhibit neurite growth defects and excessive apoptosis. Given that axonal degeneration and neuronal apoptosis may be regulated by B-cell lymphoma (BCL)-2 family proteins and mitochondrial outer membrane permeabilization through the activation of proapoptotic molecules, we measured the expression levels of proapoptotic BCL-2 family proteins (e.g., BCL-2-associated X protein and p53-upregulated modulator of apoptosis), cytochrome c, caspase-3, and caspase-9 in NSC-34 cells carrying the most common ETFDH mutation. The levels of these proteins were higher in the mutant cells than in the wide-type cells. Subsequent treatment of the mutant cells with coenzyme Q10 downregulated activated protein expression and mitigated neurite growth defects. These results suggest that the activation of the BCL-2/mitochondrial outer membrane permeabilization/apoptosis pathway promotes apoptosis in cellular models of MADD and that coenzyme Q10 can reverse this effect. Our findings aid the development of novel therapeutic strategies for reducing axonal degeneration and neuronal apoptosis in MADD.

Abstract Tongue cancer is among the most prevalent head and neck cancers and is most commonly treated via surgery. We assessed the articulation differences in patients with early and advanced tongue cancer. The study included 26 postoperative tongue cancer patients. We evaluated articulation based on bilabial, labiodental, apical, posterior, laminal, apical front, and apical back speech sounds. The 26 postoperative tongue cancer patients (24 males, two females) had an average age of 54.3 (range 37–89 old) years. Twelve patients were classified as early T stage (T1/T2), while 14 were classified as advanced T stage (T3/T4). The total articulation score was not significantly related to the T stage but apical sounds were so associated. The total articulation score did not significantly differ between postoperative patients with early and advanced tongue cancer. In subgroup analysis, the apical sound was significantly impaired in postoperative patients with advanced tongue cancer.

Abstract Accumulating evidence supports that glucocorticoid treatment for viral pneumonia (VPA) can shorten the disease course and improve survival. However, currently, the use of glucocorticoids in treating VPA remains controversial. Moreover, a unified standard for the dosage and duration of glucocorticoid therapy has not been presented in published articles. A retrospective analysis was conducted in patients who were hospitalized for severe influenza virus-associated pneumonia, and they received sequential treatment with high-dose glucocorticoids and short-course oral glucocorticoids. Patients were followed up for 3 months. A total of 11 patients were included in the study (average age 56 years). There was no gender difference, but age and underlying diseases could be risk factors for severe influenza virus-associated pneumonia. The types of viruses causing pneumonia included influenza A/B. The main clinical symptoms of patients were fever, cough, sputum production, and dyspnea. Chest computed tomography showed multiple ground-glass shadows in the lobes, and the presence of bacterial and fungal infections was accompanied by consolidation shadows. After glucocorticoid therapy, the symptoms improved. None of the patients underwent tracheal intubation, and all survived. After a 3-month follow-up, lung CT absorption in all patients had reached more than 80%, and lung imaging absorption in 20% patients was complete. No serious complications occurred in any of the patients. Sequential treatment with high-dose steroids and short-course oral glucocorticoids may be helpful for reducing the tracheal intubation rate and mortality rate in patients with severe influenza virus-associated pneumonia. Additionally, short-course oral glucocorticoids may reduce pulmonary fibrosis in patients with severe influenza virus-associated pneumonia without any serious complications.

Abstract The increasing degree of urbanization has resulted in traffic and space congestion. When there is no longer any aboveground space for development, the existing space underground is excavated, and the construction of underground buildings is expected to solve the above problems. In the excavation of an underground layer, it is necessary to drive supplementary and existing piles into the soil to form a double-layer pile-supported structure. Aiming at an existing–supplementary double-layer pile-supported structure and considering the pile spacing of the supplementary piles, use of crown beams, and other factors, this study performed a series of indoor model tests and an simulation analysis in combination with finite element analysis software to reveal the bearing characteristics of this structure. The results showed that the installation of supplementary piles could effectively inhibit soil slippage after pile driving, redistribute the soil pressure load of the existing piles, and reduce the number of soil cracks between the piles. With the increase in the supplementary pile spacing, the deformation of the existing–supplementary double-stacked piles gradually intensified, and the bending moment of the pile body and the horizontal displacement at the top of the piles increased. The installation of crown beams in the existing piles could strengthen the connection between the existing and supplementary piles, reduce the number of soil cracks between these piles, and change the force mode of the pile body. Considering the geological conditions and the influence of existing buildings, the deformation laws of the supporting structure and the soil around the foundation piles during the excavation of an underground layer of an L-shaped foundation pit were revealed. The research results are expected to provide a scientific and theoretical basis for the design and construction of downward additional support structures for existing buildings, along with socio-economic significance.

Abstract Background We aimed to pinpoint biomarkers, create a diagnostic model for ulcerative colitis (UC), and delve into its immune features to better understand this autoimmune condition. Methods The sequencing data for both the UC and the control groups were obtained from GEO, including both bulk and single-cell data. Using GSE87466 as training group, we applied differential analysis, WGCNA, PPI, LASSO, RF, and SVM-RFE for biomarker selection. A neural network shaped our diagnostic model, corroborated by GSE92415 as the validation cohort with ROC assessment. Immune cell profiling was conducted using CIBERSORT. Results 53 disease-associated genes were screened. Enrichment analysis highlighted roles in complement cascades and cell adhesion. Eight biomarkers were finally identified through multiple machine learning and PPI: B4GALNT2, PDZK1IP1, FAM195A, REG4, MTMR11, FLJ35024, CD55, and CD44. The diagnostic model had AUCs of 0.984 (training group) and 0.957 (validation group). UC tissues revealed heightened plasma cells, CD8 T cells, and other immune cells. Two unique UC immune patterns emerged, with certain T and NK cells central to immune modulation. Conclusion We identified eight biomarkers of UC by various methods, constructed a diagnostic model through neural networks, and explored the immune complexity of the disease, which contributes to the diagnosis and treatment of UC.

Abstract Few studies have explored the association between residential noise exposure and burnout. In this study, we investigated the association between residential noise exposure and burnout prevalence among 5416 health-care workers in Taiwan from 2012 to 2017. Burnout was evaluated using the Mandarin version of the Copenhagen Burnout Inventory by considering both continuous and binary measures. We applied ordinary Kriging models to calculate the annual average residential noise exposure at an individual level. Multivariable linear regression models and logistic regression models were employed. Restricted cubic splines were used to explore dose–response relationships. The median age of the health-care workers was 31.5 years. In the multivariable linear regression models, exposure to residential noise (per 1 dBA) was associated with increases in personal burnout and work-related burnout scores by 1.59 ± 0.25 and 1.38 ± 0.20, respectively. In the multivariable logistic regression models, the adjusted odds ratios were 1.24 (95% confidence interval [CI]: 1.16, 1.32) for personal burnout and 1.19 (95% CI: 1.13, 1.26) for work-related burnout per 1-dBA increase in residential noise exposure. Linear dose–response associations of burnout with residential noise level were detected. Our findings suggest that exposure to residential noise may increase the risk of burnout among health-care workers.

Abstract Hepatitis B virus (HBV) causes hepatitis B (HB) and distinct HBV genotypes can lead to different prognoses. However, HBV genotyping is rarely done in clinics, because the traditional method by PCR-based DNA sequencing is impractical for clinical diagnosis with tedious process and low success rate. Herein, we have established an ELISA-based genotyping method to quickly determine the HBV genotypes of HB patients in China. First, two commercial antibodies, 16D12 and 6H3 specific for HBV genotypes B and C respectively, are chosen as capture antibodies, since these two genotypes dominate in China. Then two home-made genotype-specific antibodies, B19 and C04, are used as the detection antibodies for genotypes B and C in sandwiched ELISA. The ELISA kit shows high sensitivity (> 95%) and specificity (> 95%) in detecting genotypes B and C of Chinese HB patients. Moreover, the ELISA kit has demonstrated higher success rate (98.7%) than PCR-based DNA sequencing (93.5%) and a commercial PCR-based genotyping kit (92.2%) for sera with HBV DNA ≥ 1000 IU/mL and HBsAg ≥ 250 IU/mL. Such an advantage is more obvious for the sera with HBV DNA

Abstract With the global widespread preference for low-floor trams, the expectation for tram riding comfort has been increasingly heightened. This paper identifies an abnormal riding comfort problem (ARCP, characterized by an excessive and W-shaped distribution of riding comfort) during dynamic field tests on a low-floor tram. To address ARCP, a multi-body dynamics model of the tram was constructed and validated its accuracy through dynamic field tests. By integrating track irregularities and wheel-rail contact analysis, the riding comfort index was assessed and reproduced the ARCP phenomenon. Linearization and time-domain integration studies were conducted on the mechanisms and measures to resolve the ARCP. The research findings reveal that the primary cause of the deterioration in the mean comfort index is the large amplitude of the track irregularity and the low equivalent conicity of the wheel-rail contact relationship. The main reason for the W-shaped distribution of riding comfort is the weaker inter-vehicle constraints and the lack of lateral energy-absorbing devices. Finally, optimization measures were proposed, including reducing the lateral stiffness of the second suspension, altering the carbody structural parameters, and modifying the inter-vehicle connection devices. This research enriches the study of tram dynamic performance and offers insights that may contribute to the resolution of ARCP.

Abstract Antibody escape mutations pose a significant challenge to the effectiveness of vaccines and antibody-based therapies. The ability to predict these escape mutations with computer simulations would allow us to detect threats early and develop effective countermeasures, but a lack of large-scale experimental data has hampered the validation of these calculations. In this study, we evaluate the ability of the MD+FoldX molecular modeling method to predict escape mutations by leveraging a large deep mutational scanning dataset, focusing on the SARS-CoV-2 receptor binding domain. Our results show a positive correlation between predicted and experimental data, indicating that mutations with reduced predicted binding affinity correlate moderately with higher experimental escape fractions. We also demonstrate that higher precision can be achieved using affinity cutoffs tailored to distinct SARS-CoV-2 antibodies from four different classes rather than a one-size-fits-all approach. Further, we suggest that the quartile values of optimized cutoffs reported for each class in this study can serve as a valuable guide for future work on escape mutation predictions. We find that 70% of the systems surpass the 50% precision mark, and demonstrate success in identifying mutations present in significant variants of concern and variants of interest. Despite promising results for some systems, our study highlights the challenges in comparing predicted and experimental values. It also emphasizes the need for new binding affinity methods with improved accuracy that are fast enough to estimate hundreds to thousands of antibody-antigen binding affinities.

Abstract Surgical occlusion of the left atrial appendage (LAA) during cardiac surgery in patients with atrial fibrillation (AF) is known to reduce thromboembolism. However, data on the clinical significance of LAA occlusion (LAAO) in patients with mitral regurgitation (MR) are lacking. A total of 237 AF patients with chronic severe MR who underwent mitral valve (MV) surgery were retrospectively analyzed. Patients were divided into two groups according to concomitant LAAO or LAA preservation. The primary outcome was a composite of all-cause death and thromboembolic events (ischemic stroke or systemic embolism). The LAA was surgically occluded in 98 (41%) patients and preserved in 139 (59%) patients. During the follow-up period (median, 37 months), 29 primary outcomes occurred. In the Kaplan–Meyer analysis, the LAA preservation group showed a greater cumulative incidence of the primary outcome (P = 0.002) and thromboembolic events (P = 0.003) than the LAAO group. In the univariate Cox regression analysis, coronary artery disease, CHA2DS2-VASc score, a cauliflower-shaped LAA, Maze, and no LAAO were significantly associated with the primary outcome. In the multivariate Cox regression analysis, concomitant LAAO was significantly linked to the primary outcome (hazard ratio [HR]: 0.30, 95% confidence interval [CI]: 0.10–0.91, P = 0.033) and thromboembolic events (HR: 0.19, 95% CI: 0.04–0.87, P = 0.032). These benefits from LAAO were consistent, even after propensity score–matched analysis. For patients undergoing surgery for chronic MR who also have AF, concomitant surgical LAAO is associated with favorable clinical outcome.

Abstract Many ophthalmic and systemic diseases can be screened by analyzing retinal fundus images. The clarity and resolution of retinal fundus images directly determine the effectiveness of clinical diagnosis. Deep learning methods based on generative adversarial networks are used in various research fields due to their powerful generative capabilities, especially image super-resolution. Although Real-ESRGAN is a recently proposed method that excels in processing real-world degraded images, it suffers from structural distortions when super-resolving retinal fundus images are rich in structural information. To address this shortcoming, we first process the input image using a pre-trained U-Net model to obtain a structural segmentation map of the retinal vessels and use the segmentation map as the structural prior. The spatial feature transform layer is then used to better integrate the structural prior into the generation process of the generator. In addition, we introduce channel and spatial attention modules into the skip connections of the discriminator to emphasize meaningful features and accordingly enhance the discriminative power of the discriminator. Based on the original loss functions, we introduce the L1 loss function to measure the pixel-level differences between the segmentation maps of retinal vascular structures in the high-resolution images and the super-resolution images to further constrain the super-resolution images. Simulation results on retinal image datasets show that our improved algorithm results have a better visual performance by suppressing structural distortions in the super-resolution images.

Abstract Green consumption is a crucial pathway towards achieving global sustainability goals. Product-oriented green advertisements can effectively stimulate consumers’ latent needs and convert them into eventual purchasing intentions and behaviors, thereby promoting green consumption. Given that neuromarketing methods facilitate the understanding of consumers’ decision-making processes, this study combines prospect theory and need fulfillment theory, employing event-related potentials (ERPs) as measures to explore changes in consumers’ cognitive resources and emotional arousal levels when confronted with green products and advertising information. This enables inference regarding consumers’ acceptance of purchasing and their psychological processes. Behavioral results indicated that message framing influences consumers’ purchases, with consumers consuming more green in response to negatively framed advertisements. EEG results indicated that matching positive framing with utilitarian green products was effective in increasing consumers’ cognitive attention in the early cognitive stage. In the late stage of cognition negative frames stimulated consumers’ mood swings more, and the influence of product type depended on the role of message frames, and the consumption motivation induced by the product, whose influence was overridden by external evaluations such as message frames. These research findings provide an explanation for the impact of frame information on consumers’ purchasing decisions at different stages, assisting marketers in devising diverse promotional strategies based on product characteristics to foster the development and practice of green consumption. This will further embed the concept of green consumption advocated by organizations such as the United Nations Environment Programme (UNEP), World Wildlife Fund (WWF), and Greenpeace into the public consciousness.

Abstract Neonatal intensive care unit (NICU), particularly in treating developmental and epileptic encephalopathy (DEE) and metabolic epilepsy (ME), requires a deep understanding of their complex etiologies and treatment responses. After excluding treatable cases such as infectious or autoimmune encephalitis, our focus shifted to a more challenging subgroup of 59 patients for in-depth genetic analysis using exome sequencing (ES). The ES analysis identified 40 genetic abnormalities, significantly including de novo variants. Notably, we found structural variation as duplications in regions 2q24.3, including SCN1A and SCN2A were observed in 7 cases. These genetic variants, impacting ion channels, glucose transport, transcription regulation, and kinases, play a crucial role in determining medication efficacy. More than one-third (34.2%) of patients with DEE had an unfavorable response to anti-seizure medications (ASMs) in the chronic phase. However, since the ketogenic supplementary diet showed a positive effect, more than three-quarters (80%) of these drug-resistant patients improved during a 3-month follow-up. In contrast, the ME had a lower adverse reaction rate of 9.1% (2/22) to specialized medications, yet there were 5 fatalities and 10 cases with unidentified genetic etiologies. This study suggests the potential of categorizing drug-resistant variants and that a ketogenic diet could be beneficial in managing DEE and ME. It also opens new perspectives on the mechanisms of the ketogenic diet on the discovered genetic variants.

Abstract Chronic obstructive pulmonary disease (COPD), a progressive inflammatory condition of the airways, emerges from the complex interplay between genetic predisposition and environmental factors. Notably, its incidence is on the rise, particularly among the elderly demographic. Current research increasingly highlights cellular senescence as a key driver in chronic lung pathologies. Despite this, the detailed mechanisms linking COPD with senescent genomic alterations remain elusive. To address this gap, there is a pressing need for comprehensive bioinformatics methodologies that can elucidate the molecular intricacies of this link. This approach is crucial for advancing our understanding of COPD and its association with cellular aging processes. Utilizing a spectrum of advanced bioinformatics techniques, this research delved into the potential mechanisms linking COPD with aging-related genes, identifying four key genes (EP300, MTOR, NFE2L1, TXN) through machine learning and weighted gene co-expression network analysis (WGCNA) analyses. Subsequently, a precise diagnostic model leveraging an artificial neural network was developed. The study further employed single-cell analysis and molecular docking to investigate senescence-related cell types in COPD tissues, particularly focusing on the interactions between COPD and NFE2L1, thereby enhancing the understanding of COPD's molecular underpinnings. Leveraging artificial neural networks, we developed a robust classification model centered on four genes—EP300, MTOR, NFE2L1, TXN—exhibiting significant predictive capability for COPD and offering novel avenues for its early diagnosis. Furthermore, employing various single-cell analysis techniques, the study intricately unraveled the characteristics of senescence-related cell types in COPD tissues, enriching our understanding of the disease's cellular landscape. This research anticipates offering novel biomarkers and therapeutic targets for early COPD intervention, potentially alleviating the disease's impact on individuals and healthcare systems, and contributing to a reduction in global COPD-related mortality. These findings carry significant clinical and public health ramifications, bolstering the foundation for future research and clinical strategies in managing and understanding COPD.

Abstract To evaluate the efficiency, predictability, and residual astigmatism between first- and second-generation keratorefractive lenticule extraction (KLEx) surgeries in a prominent astigmatism population. A retrospective cohort study was conducted, and individuals who underwent first- and second-generation KLEx surgeries were enrolled. A total of 31 and 35 eyes were categorized into first and second KLEx groups, respectively. Visual acuity, refraction, topographic parameters, and surgical indices were recorded. Independent t tests were used to compare the postoperative uncorrected distance visual acuity (UDVA), spherical equivalent (SE), and residual astigmatism between the two groups. The difference in UDVA was not significant three months after KLEx surgery (P = 0.509), and the SEs three months after surgery also presented similar values between the two groups (P = 0.552). The first KLEx group demonstrated greater residual astigmatism than did the second KLEx group throughout the three-month follow-up period (all P

Abstract Astrocytes act as immune cells that can produce a series of chemokines to attract large numbers of leucocytes to the lesion site, where they contribute to excessive inflammation following spinal cord injury (SCI). However, the relevant regulatory mechanism involved in chemokine production by astrocytes has not been fully elucidated. In the present study, we examined the correlation between C-C motif chemokine ligand 5 (CCL5) and high mobility group box-1 protein (HMGB1) in a T8–T10 spinal cord contusion model. Our results revealed that SCI-induced CCL5 protein levels increased synchronously with the increase in HMGB1. Administration of an HMGB1-neutralizing antibody significantly reduced the protein expression of CCL5 in the context of SCI. An in vitro study revealed that HMGB1 binding with TLR2/4 receptors potently facilitates the production of CCL5 by astrocytes by activating the intracellular ERK/JNK-mediated NF-κB pathway. Furthermore, the HMGB1-induced release of CCL5 from astrocytes is involved in promoting microglia/macrophage accumulation and M1 polarization. The inhibition of HMGB1 activity reduces microglia/macrophage infiltration by decreasing the expression of CCL5 and improves motor functional recovery following SCI. Our results provide insights into the new functions of HMGB1-mediated astrocytic CCL5 production, which elicits inflammatory cell recruitment to the site of injury; this recruitment is associated with excessive inflammation activation. These data may provide a new therapeutic strategy for central nervous system (CNS) inflammation.

Abstract The pathophysiology of amnestic Mild Cognitive Impairment (aMCI) is largely unknown, although some papers found signs of immune activation. To assess the cytokine network in aMCI after excluding patients with major depression (MDD) and to examine the immune profiles of quantitative aMCI (qMCI) and distress symptoms of old age (DSOA) scores. A case-control study was conducted on 61 Thai aMCI participants and 60 healthy old adults (both without MDD). The Bio-Plex Pro human cytokine 27-plex test kit was used to assay cytokines/chemokines/growth factors in fasting plasma samples. aMCI is characterized by a significant immunosuppression, and reductions in T helper 1 (Th)1 and T cell growth profiles, the immune-inflammatory responses system, interleukin (IL)1β, IL6, IL7, IL12p70, IL13, GM-CSF, and MCP-1. These 7 cytokines/chemokines exhibit neuroprotective effects at physiologic concentrations. In multivariate analyses, three neurotoxic chemokines, CCL11, CCL5, and CXCL8, emerged as significant predictors of aMCI. Logistic regression showed that aMCI was best predicted by combining IL7, IL1β, MCP-1, years of education (all inversely associated) and CCL5 (positively associated). We found that 38.2% of the variance in the qMCI score was explained by IL7, IL1β, MCP-1, IL13, years of education (inversely associated) and CCL5 (positively associated). The DSOA was not associated with any immune data. An imbalance between lowered levels of neuroprotective cytokines and chemokines, and relative increases in neurotoxic chemokines are key factors in aMCI. Future MCI research should always control for the confounding effects of affective symptoms.

Abstract Traditional Finite Difference Time Domain (FDTD) approaches face challenges with increased computational demands and errors as terrain complexity and flight altitude rising. This study introduces the Crank-Nicolson-Cycle-Sweep-FDTD (CNCS-FDTD) method, enhancing airborne ground penetrating radar (GPR) simulations over undulating terrains. CNCS-FDTD, as an unconditionally stable implicit algorithm, overcomes these by allowing larger time steps without the constraints of the Courant-Friedrichs-Lewy (CFL) condition. Our research aims to assess how CNCS-FDTD can improve computational efficiency and accuracy in modeling airborne GPR responses across varied terrains. Initial simulations using a three-dimensional graben model indicate that CNCS-FDTD can maintain calculation stability with significantly larger time steps, reducing computational time by 42%. To further verify the reliability of the numerical simulation results, the paper also presents experimental tests of the undulating terrain model. By comparing the numerical and physical simulation results of models under different flight altitudes and terrain conditions, the accuracy of the simulation results is validated.

Abstract As climate change intensifies, endemic plants native to South Korea, especially those in specialized ecological niches, confront heightened risks of distribution shifts and habitat degradation. To provide a comprehensive understanding of these impacts, this study evaluates the climate-induced distribution dynamics and niche adaptation of these endemic species across the entire Korean Peninsula. Utilizing species distribution models (SDMs) for 179 plant species and incorporating environmental variables under projected future climate scenarios, our analysis identified unique distribution and niche adaptation patterns. Findings demonstrate that specialized endemic species are likely to migrate to higher altitudes and latitudes, highlighting their distinct vulnerability due to limited ecological niches. Our comparative approach underscores the necessity for refined conservation strategies that address the specific requirements of these endemic species, as opposed to those with wider distributions. This research offers valuable insights into biodiversity conservation amid climate change, proposing targeted actions such as the establishment of protected areas, habitat restoration, and the implementation of assisted migration strategies to safeguard these vital endemic plant species throughout the Korean Peninsula.

Abstract A high efficiency simulation method for propagation-based phase-contrast imaging, called directional macro-wavefront (DMWF), is developed with the aim of simulating high-energy phase-contrast imaging. This method takes both Monte Carlo and wave optical propagation into consideration. Traditional wave-optics-based simulation methods for phase-contrast imaging encounter unacceptable computational complexity when high-energy radiation is used. In contrast, this method effectively addresses this issue by using macro-wavefront integration. Several simulation examples using typical parameters of inverse Compton scattering sources are presented to illustrate the excellent energy adaptability and efficiency of the DMWF method. This method provides a more efficient approach for phase-contrast imaging simulations, which will drive the advancement of high-energy phase-contrast imaging.

Abstract Primary dysmenorrhea (PD) is a common global health concern. However, limited studies explored the association between soft drinks intake and PD among female undergraduates in China. To determine the association between soft drinks (carbonated soft drinks, etc.) as well coffee intake and the incidence/severity of PD among female undergraduates in China. We performed a cross-sectional study among 1809 female undergraduates in China from September 29, 2020 to October 22, 2020. The demographic information and menstrual information of the participants were collected by a self-administrated questionnaire. Chi-square test, ANOVA test, and logistic regression test were used to investigate the association between soft drinks intake and the incidence/severity of PD. We also conducted stratification analysis among different locations (rural or urban). The prevalence of PD was 47.1% (n = 852). There were 221 (25.9%) participants suffered from severe pain. In the participants with PD, the OR of carbonated soft drinks intake was 1.244 (95% CI 1.010–1.533). Among the participants with PD from rural areas, the OR of carbonated soft drinks intake was 1.402 (95% CI 1.045–1.881), compared with the non-carbonated soft drink group. In the participants with moderate and severe PD, the OR of coffee intake was 0.451 (95% CI 0.228–0.892), compared with the non-coffee-drinking group. There was a significant association between carbonated soft drinks intake frequency and the severity of PD (P

Abstract The blockage and the deformation and failure of the ore pass walls constitute two major problems in applying the ore passes in mines. These problems, which affect the normal operation of mine production, have attracted widespread attention worldwide. The labeled-particle layers method based on numerical simulation was used to investigate the flow characteristics of the ore-rock bulk in the ore pass under different eccentric distances of the ore-drawing port center and ore pass centerline. Moreover, the overpressure coefficient and overpressure number are used to evaluate the degree of damage to the ore-pass wall. The results show that: (1) During the ore drawing process under different eccentricities, the flow patterns of the topmost labeled-particle layers in the ore pass are always in a “—” shaped distribution, and the other layers in the ore pass gradually transition from a “—” shape to a “U” shaped distribution, and then gradually to a “V” shape closer to the drawing funnel; (2) in the range of the ore-drawing funnel, the flow pattern of the ore-rock bulk gradually changes from an upright “V” shape to an italic “V” shape with increasing eccentricity and tip slants to the drawing port, and is less affected in the shaft; and (3) the dynamic lateral pressure caused by the ore-rock flow mainly acts on the lower part of the storage section. When the eccentricity is 0.5 m, the maximum overpressure coefficient and overpressure times are the smallest, leading to the lowest damage degree of the ore pass wall.