Search

[This corrects the article DOI: 10.1371/journal.pone.0301909.].

Ciprofol is a novel short-acting intravenous anaesthetic developed in China that is mainly metabolized by cytochrome P450 2B6 (CYP2B6) and uridine diphosphate glucuronosyltransferase 1A9 (UGT1A9). Currently, insufficient evidence is available to support drug‒drug interactions between ciprofol and CYP2B6 inactivators. Here, we established a high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method to assess the concentration of ciprofol and investigated the effects of psoralen and clopidogrel on the metabolism of ciprofol in liver microsomes and rats. In rat and human liver microsomes, the median inhibitory concentration (IC50) values of psoralen were 63.31 μmol·L-1 and 34.05 μmol·L-1, respectively, showing mild inhibitory effects on ciprofol metabolism, whereas the IC50 values of clopidogrel were 6.380 μmol·L-1 and 2.565 μmol·L-1, respectively, with moderate inhibitory effects. SD rats were randomly divided into three groups: psoralen (27 mg·kg-1), clopidogrel (7.5 mg·kg-1), and the same volume of 0.5% carboxy methyl cellulose. After 7 days, all rats were injected with 2.4 mg·kg-1 ciprofol. Compared with the control group, the AUC and MRT values of ciprofol in the psoralen and clopidogrel groups were significantly greater, whereas the CL values were significantly lower. In addition, the durations of loss of righting reflex (LORR) in the psoralen and clopidogrel groups were 16.1% and 23.0% longer than that in the control group, respectively. In conclusion, psoralen and clopidogrel inhibit ciprofol metabolism to different degrees and prolong the duration of LORR in rats.

Fibrotic skin diseases, such as keloids, are pathological results of aberrant tissue healing and are characterized by overgrowth of dermal fibroblasts. Remdesivir (RD), an antiviral drug, has been reported to have pharmacological activities in a wide range of fibrotic diseases. However, whether RD function on skin fibrosis remains unclear. Therefore, in our study, we explored the potential effect and mechanisms of RD on skin fibrosis both in vivo and in vitro. As expected, the results demonstrated that RD alleviated BLM-induced skin fibrosis and attenuates the gross weight of keloid tissues in vivo. Further studies suggested that RD suppressed fibroblast activation and autophagy both in vivo and in vitro. In addition, mechanistic research showed that RD attenuated fibroblasts activation by the TGF-β1/Smad signaling pathway and inhibited fibroblasts autophagy by the PI3K/Akt/mTOR signaling pathway. In summary, our results demonstrate therapeutic potential of RD for skin fibrosis in the future.

Serial correlations within temperature time series serve as indicators of the temporal consistency of climate events. This study delves into the serial correlations embedded in global surface air temperature (SAT) data. Initially, we preprocess the SAT time series to eradicate seasonal patterns and linear trends, resulting in the SAT anomaly time series, which encapsulates the inherent variability of Earth's climate system. Employing diverse statistical techniques, we identify three distinct types of serial correlations: short-term, long-term, and nonlinear. To identify short-term correlations, we utilize the first-order autoregressive model, AR(1), revealing a global pattern that can be partially attributed to atmospheric Rossby waves in extratropical regions and the Eastern Pacific warm pool. For long-term correlations, we adopt the standard detrended fluctuation analysis, finding that the global pattern aligns with long-term climate variability, such as the El Niño-Southern Oscillation (ENSO) over the Eastern Pacific. Furthermore, we apply the horizontal visibility graph (HVG) algorithm to transform the SAT anomaly time series into complex networks. The topological parameters of these networks aptly capture the long-term correlations present in the data. Additionally, we introduce a novel topological parameter, Δσ, to detect nonlinear correlations. The statistical significance of this parameter is rigorously tested using the Monte Carlo method, simulating fractional Brownian motion and fractional Gaussian noise processes with a predefined DFA exponent to estimate confidence intervals. In conclusion, serial correlations are universal in global SAT time series and the presence of these serial correlations should be considered carefully in climate sciences.

Low-carbon pilot city (LCPC) plays a pivotal role in stimulating green innovation among enterprises. However, relying solely on policy often proves less effective, necessitating support from financial development. Yet, current research frequently overlooks the impact of financial development on LCPC policy. Drawing on economic, management, and organizational psychology theories, we investigate the influence of the financial development level on enterprise green innovation in LCPC, utilizing data from listed companies between 2010 and 2018. The main finding is that LCPC facilitates institutional-level green innovation. Concurrently, financial development augments the effectiveness of LCPC policy, further expediting green innovation activities among enterprises in these pilot cities. Heterogeneity analyses reveal that financial development significantly promotes green innovation, particularly among state-owned enterprises, those with myopic management, non-high technology industries, and businesses in the southern region within LCPC. Mechanism tests identify enterprises' financing constraints and R&D investment levels as key pathways through which financial development fosters green economic development in LCPC. This study provides micro-level evidence from China elucidating the effects of environmental policies and offers practical implications for the low-carbon transformation of the manufacturing sector amid peak emissions and carbon-neutral targets. Additionally, it provides valuable guidance for other emerging economies seeking enhanced resource and environmental protection through the implementation of energy-saving and emission-reduction fiscal policy.

Tumor microenvironment (TME) is a complex dynamic system with many tumor-interacting components including tumor-infiltrating leukocytes (TILs), cancer associated fibroblasts, blood vessels, and other stromal constituents. It intrinsically affects tumor development and pharmacology of oncology therapeutics, particularly immune-oncology (IO) treatments. Accurate measurement of TME is therefore of great importance for understanding the tumor immunity, identifying IO treatment mechanisms, developing predictive biomarkers, and ultimately, improving the treatment of cancer. Here, we introduce a mouse-IO NGS-based (NGSmIO) assay for accurately detecting and quantifying the mRNA expression of 1080 TME related genes in mouse tumor models. The NGSmIO panel was shown to be superior to the commonly used microarray approach by hosting 300 more relevant genes to better characterize various lineage of immune cells, exhibits improved mRNA and protein expression correlation to flow cytometry, shows stronger correlation with mRNA expression than RNAseq with 10x higher sequencing depth, and demonstrates higher sensitivity in measuring low-expressed genes. We describe two studies; firstly, detecting the pharmacodynamic change of interferon-γ expression levels upon anti-PD-1: anti-CD4 combination treatment in MC38 and Hepa 1-6 tumors; and secondly, benchmarking baseline TILs in 14 syngeneic tumors using transcript level expression of lineage specific genes, which demonstrate effective and robust applications of the NGSmIO panel.

BackgroundShort-term poor uterine involution manifests as uterine contraction weakness. This is one of the important causes of postpartum hemorrhage, posing a serious threat to the mother's life and safety. The study aims to investigate whether low-intensity focused ultrasound (LIFUS) can effectively shorten lochia duration, alleviate postpartum complications, and accelerate uterine involution compared with the sham treatment.MethodsA multicenter, concealed, randomized, blinded, and sham-controlled clinical trial was conducted across three medical centers involving 176 subjects, utilizing a parallel group design. Enrollment occurred between October 2019 and September 2020, with a 42-day follow-up period. Participants meeting the inclusion and exclusion criteria based on normal prenatal examinations were randomly divided into the LIFUS group or the sham operation group via computer-generated randomization. Patients in the LIFUS group received usual care with the LIFUS protocol, wherein a LIFUS signal was transmitted to the uterine site through coupling gel, or sham treatment, where no low-intensity ultrasound signal output was emitted. The primary outcome, lochia duration, was assessed via weekly telephonic follow-ups post-discharge. The involution of the uterus, measured by uterine fundus height, served as the secondary outcome.ResultsAmong the 256 subjects screened for eligibility, 176 subjects were enrolled and randomly assigned to either the LIFUS group (n = 88) or the Sham group (n = 88). Data on the height of the uterine fundus were obtained from all the patients, with 696 out of 704 measurements (99%) successfully recorded. Overall, a statistically significant difference was noted in time to lochia termination (hazard ratio: 2.65; 95% confidence interval [CI]: 1.82-3.85; P < 0.001). The decline in fundal height exhibited notable discrepancies between the two groups following the second treatment session (mean difference: -1.74; 95% CI: -1.23 to -2.25; P < 0.001) and the third treatment session (mean difference: -3.26; 95% CI: -2.74 to -3.78; P < 0.001) after delivery. None of the subjects had any adverse reactions, such as skin damage or allergies during the treatment.ConclusionsThis study found that LIFUS treatment can promote uterine involution and abbreviate the duration of postpartum lochia. Ultrasound emerges as a safe and effective intervention, poised to address further clinical inquiries in the domain of postpartum rehabilitation.

With the predicament of sustainable improvement in traditional cities, the low-carbon city pilot policy (LCCPP), as a novel development mode, provides thinking for resolving the tensions of green development, resource conservation and environmental protection among firms. Using Chinese A-share listed companies panel data during 2007-2019, this study adopts the difference-in-differences model to explore the impact of LCCPP on firm green innovation. Based on theoretical analysis, LCCPP-driven environmental rules have the impact of encouraging business green innovation. The relationship between LCCPP and green innovation is strengthened by external media attention and organizational redundancy resources. The mechanism study shows that the incentive effect of LCCPP on firm green innovation is mainly due to the improvement of enterprises' green total factor productivity and financial stability. In addition, the heterogeneity analysis shows that the LCCPP has significantly positive effects in promoting green innovation in high-carbon industries and state-owned enterprises. This research contributes to the understanding of city-level low-carbon policies as a driving force for corporate green innovation, offering practical implications for policymakers and businesses striving for sustainability.

ObjectiveThe purpose of this study was to investigate whether the combination of abnormal systemic immune-inflammation index (SII) levels and hyperglycemia increased the risk of cognitive function decline and reduced survival rate in the United States.MethodsThis cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) database from 2011-2014 and enrolled 1,447 participants aged 60 years or older. Restricted cubic splines (RCS), linear regression and kaplan-meier(KM) curve were employed to explore the combined effects of abnormal SII and hyperglycemia on cognitive function and survival rate, and subgroup analysis was also conducted.ResultsThe RCS analysis revealed an inverted U-shaped relationship between lgSII levels and cognitive function. Linear regression analysis indicated that neither abnormal SII nor diabetes alone significantly contributed to the decline in cognitive function compared to participants with normal SII levels and blood glucose. However, when abnormal SII coexisted with diabetes (but not prediabetes), it resulted to a significant decline in cognitive function. After adjusting for various confounding factors, these results remained significant in Delayed Word Recall (β:-0.76, PConclusionThe findings suggest that the impact of diabetes on cognitive function/survival rate is correlated with SII levels, indicating that their combination enhances predictive power.

BackgroundPrevious cross-sectional studies have identified multiple potential risk factors for functional dyspepsia (FD). However, the causal associations between these factors and FD remain elusive. Here we aimed to fully examine the causal relationships between these factors and FD utilizing a two-sample MR framework.MethodsA total of 53 potential FD-related modifiable factors, including those associated with hormones, metabolism, disease, medication, sociology, psychology, lifestyle and others were obtained through a comprehensive literature review. Independent genetic variants closely linked to these factors were screened as instrumental variables from genome-wide association studies (GWASs). A total of 8875 FD cases and 320387 controls were available for the analysis. The inverse variance weighted (IVW) method was employed as the primary analytical approach to assess the relationship between genetic variants of risk factors and the FD risk. Sensitivity analyses were performed to evaluate the consistency of the findings using the weighted median model, MR-Egger and MR-PRESSO methods.ResultsGenetically predicted depression (OR 1.515, 95% confidence interval (CI) 1.231 to 1.865, p = 0.000088), gastroesophageal reflux disease (OR 1.320, 95%CI 1.153 to 1.511, p = 0.000057) and years of education (OR 0.926, 95%CI 0.894 to 0.958, p = 0.00001) were associated with risk for FD in univariate MR analyses. Multiple medications, alcohol consumption, poultry intake, bipolar disorder, mood swings, type 1 diabetes, elevated systolic blood pressure and lower overall health rating showed to be suggestive risk factors for FD (all pConclusionsOur comprehensive MR study demonstrated that depression and lower educational attainment were causal factors for FD at the genetic level.

Natural disasters such as landslides often occur on soil slopes in seasonally frozen areas that undergo freeze‒thaw cycling. Ecological slope protection is an effective way to prevent such disasters. To explore the change in the mechanical properties of soil under the influence of both root reinforcement and freeze‒thaw cycles and its influence on slope stability, the Baijiabao landslide in the Three Gorges Reservoir area was taken as an example. The mechanical properties of soil under different confining pressures, vegetation coverages (VCs) and numbers of freeze‒thaw cycles were studied via mechanical tests, such as triaxial compression tests, wave velocity tests and FLAC3D simulations. The results show that the shear strength of a root-soil composite increases with increasing confining pressure and VC and decreases with increasing number of freeze‒thaw cycles. Bermuda grass roots and confining pressure jointly improve the durability of soil under freeze‒thaw conditions. However, with an increase in the number of freeze‒thaw cycles, the resistance of root reinforcement to freeze‒thaw action gradually decreases. The observed effect of freeze‒thaw cycles on soil degradation was divided into three stages: a significant decrease in strength, a slight decrease in strength and strength stability. Freeze‒thaw cycles and VC mainly affect the cohesion of the soil and have little effect on the internal friction angle. Compared with that of a bare soil slope, the safety factor of a slope covered with plants is larger, the maximum displacement of a landslide is smaller, and it is less affected by freezing and thawing. These findings can provide a reference for research on ecological slope protection technology.

ObjectiveTo evaluate the accuracy of 10 formulas for calculating intraocular lens (IOL) power in cataract eye with an axial length (AL) of more than 28.0 mm.MethodsWe searched scientific databases including PubMed, EMBASE, Web of Science and Cochrane Library for research published over the past 5 years, up to Sept 2023. The inclusion criteria were case series studies that compared different formulas (Barrett II, EVO, Kane, Hill-RBF, Haigis, Hoffer Q, Holladay 1, SRK/T, Holladay 1 w-k and SRK/T w-k), in patients with extremely long AL undergoing uncomplicated cataract surgery with IOL implantation. The mean difference (MD) of mean absolute error (MAE) and the odds ratio (OR) of both the percentage of eyes within ±0.50D of prediction error (PPE±0.50D) and the percentage of eyes within ±1.00D of prediction error (PPE±1.00D) among different formulas were pooled using meta-analysis.ResultsA total of 11 studies, involving 1376 eyes, were included to evaluate the 10 formulas mentioned above. Among these formulas, Barrett II, EVO, Kane, and Hill-RBF demonstrated significantly lower MAE values compared to SRK/T. Furthermore, Kane and Hill-RBF had lower MAE values than EVO. Additionally, Barrett II and Kane yielded significantly lower MAE values than Haigis while Hill-RBF showed significantly lower MAE values than Holladay 1. Moreover, Hill-RBF showed the highest values for both PPE±0.50D and PPE±1.00D, followed by Kane. Both EVO and Kane had higher values of PPE±0.50D and PPE±1.00D compared to Haigis and SRK/T.ConclusionThe Wang-Koch adjusted formulas and new-generation formulas have shown potential for higher accuracy in predicting IOL power for cataract patients with extremely long AL compared to traditional formulas. Based on the current limited clinical studies, Hill-RBF and Kane formulas seem to be a better choice for eyes with extremely long AL.

BackgroundThis study aims to study the possible action mechanism of T-cell immunoglobulin and mucin domain 3 (TIM3) on the migratory and invasive abilities of thyroid carcinoma (TC) cells.MethodsGSE104005 and GSE138198 datasets were downloaded from the GEO database for identifying differentially expressed genes (DEGs). Functional enrichment analysis and protein-protein interaction (PPI) analysis were performed on the common DEGs in GSE104005 and GSE138198 datasets. Subsequently, in order to understand the effect of a common DEG (TIM3) on TC cells, we performed in vitro experiments using FRO cells. The migratory and invasive abilities of FRO cells were detected by wound scratch assay and Transwell assay. Proteins expression levels of the phosphorylated (p)-extracellular signal-regulated kinase (ERK)1/2, matrix metalloproteinase-2 (MMP-2) and MMP-9 were determined via Western blotting after ERK1/2 inhibition in TIM3-NC group and TIM3-mimic group.Results316 common DEGs were identified in GSE104005 and GSE138198 datasets. These DEGs were involved in the biological process of ERK1 and ERK2 cascade. TIM3 was significantly up-regulated in TC. In vitro cell experiments showed that TIM3 could promote migration and invasion of TC cells. Moreover, TIM3 may affect the migration, invasive abilities of TC cells by activating the ERK1/2 pathway.ConclusionThe above results indicate that TIM3 may affect the migratory and invasive of TC cells by activating the ERK1/2 pathway.

Pharmacy Intravenous Admixture Services (PIVAS) are places dedicated to the centralized dispensing of intravenous drugs, usually managed and operated by professional pharmacists and pharmacy technicians, and are an integral part of modern healthcare. However, the workflow of PIVAS has some problems, such as low efficiency and error-prone. This study aims to improve the efficiency of drug dispensing, reduce the rate of manual misjudgment, and minimize drug errors by conducting an in-depth study of the entire workflow of PIVAS and applying image recognition technology to the drug checking and dispensing process. Firstly, through experimental comparison, a target detection model suitable for drug category recognition is selected in the drug-checking process of PIVAS, and it is improved to improve the recognition accuracy and speed of intravenous drug categories. Secondly, a corner detection model for drug dosage recognition was studied in the drug dispensing stage to further increase drug dispensing accuracy. Then the PIVAS drug category recognition system and PIVAS drug dosage recognition system were designed and implemented.

Red tourism is a distinctive form of tourism in China. Its network attention serves as a typical indicator to measure the level of promotion and publicity for red tourism, as well as an important reflection of its influence. Understanding the network structure of red tourism is of significant importance for optimizing the spatial pattern of tourism and promoting the development of the tourism industry. Based on this, this study takes the classic red tourism attractions in Shaanxi province, China as an example and constructs a multi-source data network attention evaluation index. Additionally, it employs social network theory to explore the network attention and tourist flow characteristics of the case study area. Research shows that: (1) Overall, the network attention to case-based destinations is relatively low, and there are significant differences in network attention among different attractions. Spatially, the distribution of network attention is uneven. This is manifested by higher network attention to attractions in Yan'an city and lower network attention to attractions in other regions. (2) There are differences in the network attention of different types of attractions. High-level attractions have a higher level of online attention, while low-level attractions have a lower level of network attention. Additionally, archaeological sites tend to receive a higher level of online attention. (3) The network density of tourist flow is low, and the tourism connections between nodes are not closely linked. The linkage between core nodes and edge nodes in tourism is poor. Developed tourism routes only exist in core nodes. (4) Nodes such as Zaoyuan revolution site, Yangjialing revolution site, and Wangjiaping revolution site have a significant influence in the network structure. In addition, the integration and development between red nodes and non-red nodes have been achieved. (5) There is a correlation between network attention and tourist flow, as well as a 'misplacement' feature. Based on the characteristics of attractions, they can be divided into four types: bright-star attractions, cash-cow attractions, thin-dog attractions, and question attractions. Based on the above conclusions, this study proposes targeted development recommendations.

BackgroundType 2 diabetes mellitus (T2DM) is a common condition that is characterized by metabolic impairments. Exercise therapy has proven effective in improving the physiological and psychological states of patients with T2DM; however, the influence of different exercise modalities on metabolic profiles is not fully understood. This study first aimed to investigate the metabolic changes associated with T2DM among patients and then to evaluate the potential physiological effects of different exercise modalities (Tai Chi and brisk walking) on their metabolic profiles.MethodsThis study included 20 T2DM patients and 11 healthy subjects. Patients were randomly allocated to either the Tai Chi or walking group to perform Dijia simplified 24-form Tai Chi or brisk walking (80-100 m/min), with 90 minutes each time, three times per week for 12 weeks, for a total of 36 sessions. The healthy group maintained daily living habits without intervention. Glycemic tests were conducted at the baseline and after 12 weeks. Serum and urine samples were collected for untargeted metabolomic analyses at baseline and 12 weeks to examine the differential metabolic profiles between T2DM and healthy subjects, and the metabolic alterations of T2DM patients before and after exercise therapy.ResultsCompared to the healthy group, T2DM patients exhibited metabolic disturbances in carbohydrates (fructose, mannose, galactose, glycolysis/gluconeogenesis), lipids (inositol phosphate), and amino acids (arginine, proline, cysteine, methionine, valine, leucine, and isoleucine) metabolism, including 20 differential metabolites in the serum and six in the urine. After exercise, the glycemic results showed insignificant changes. However, patients who practiced Tai Chi showed significant improvements in their post-treatment metabolic profiles compared to baseline, with nine serum and six urine metabolites, including branch-chained amino acids (BCAAs); while those in the walking group had significantly altered nine serum and four urine metabolites concerning steroid hormone biosynthesis and arachidonic acid metabolism compared to baseline.ConclusionT2DM patients displayed impaired carbohydrate, lipid, and amino acid metabolism, and exercise therapy improved their metabolic health. Different modalities may act through different pathways. Tai Chi may improve disrupted BCAAs metabolism, whereas brisk walking mainly regulates steroid hormone biosynthesis and arachidonic acid metabolism.

As a product of combining digital technology and traditional finance, digital inclusive finance plays a vital role in economic growth. This paper deeply analyzes the impact of digital inclusive finance on economic growth and the specific transmission path. This research selects the municipal panel data of Beijing-Tianjin-Hebei from 2011 to 2020 and empirically studies the impact of digital inclusive finance on economic growth. From the perspectives of industrial structure transformation speed, industrial structure upgrading, and industrial structure rationalization, this study analyzes the role of industrial structure in the impact of digital inclusive finance on economic growth and tests the heterogeneity of the impact of digital inclusive finance on economic growth. The results show that digital inclusive finance has a significant role in promoting economic growth. The depth of use of digital inclusive finance has the most significant impact, followed by the breadth of coverage, and the degree of digitization is the smallest. The industrial structure transformation speed and the industrial structure rationalization play a significant intermediary role in the economic growth effect of digital inclusive finance, and the industrial structure upgrading has no significant impact on the economic growth effect of digital inclusive finance; the promotion effect of digital inclusive finance on economic growth is bigger in the economically developed group, the higher digital inclusive finance group and the technologically developed group, and the promotion effect is smaller in the economically underdeveloped group, the lower digital inclusive finance group and the technologically underdeveloped group. The results provide a strong reference for policy formulation to promote the development of digital inclusive finance and economic growth.

Cervical cancer poses a significant health challenge in developing countries, emphasizing the need for appropriate screening strategies to accelerate the elimination of this disease. This study summarized the results of a large-scale community-based cervical cancer screening program conducted in Chengdu, China, to understand the prevalence of HPV infection and cervical lesions in the population, and to compare the real-world effectiveness of two different screening methods implemented in the program. From January 2021 to December 2022, a total of 363,376 women aged 35-64 years in Chengdu received free screenings. Among these participants, 70.1% received cytology screening and 29.9% received HPV testing combined with 16/18 genotyping and cytology triage. Ultimately, 824 cases of high-grade lesions and cervical cancer were detected, with a total detection rate of cervical cancer and precancerous lesions of 226.8 per 100,000. The follow-up rate of patients with high-grade lesions and above was 98.9%, and the treatment rate was 86.6%. The overall high-risk HPV infection rate was 11.7%, with the HPV 16/18 infection rate of 1.4%. The rate of abnormal cytology results was 2.8%. The attendance rates for colposcopy and histopathology were 71.6% and 86.1%, respectively. By calculating the age-standardized rates to eliminate the different age composition between the two group, the HPV-based screening strategy had a higher rate of primary screening abnormalities (3.4% vs. 2.8%, P

In the context of extensive disciplinary integration, researchers worldwide have increasingly focused on musical ability. However, despite the wide range of available music ability tests, there remains a dearth of validated tests applicable to China. The Music Ear Test (MET) is a validated scale that has been reported to be potentially suitable for cross-cultural distribution in a Chinese sample. However, no formal translation and cross-cultural reliability/validity tests have been conducted for the Chinese population in any of the studies using the Music Ear Test. This study aims to assess the factor structure, convergence, predictiveness, and validity of the Chinese version of the MET, based on a large sample of Chinese participants (n≥1235). Furthermore, we seek to determine whether variables such as music training level, response pattern, and demographic data such as gender and age have intervening effects on the results. In doing so, we aim to provide clear indications of musical aptitude and expertise by validating an existing instrument, the Music Ear Test, and provide a valid method for further understanding the musical abilities of the Chinese sample.

Digital technology innovation is the core driving force for the high-quality development of the digital economy, and in-depth exploration of the regional distribution pattern and formation mechanism of digital technology innovation in China is conducive to the rational layout and coordinated development of the inter-provincial digital economy. Based on the Reference Relationship Table of the Classification of Core Industries of Digital Economy and the International Patent Classification (2023), the patent authorization data of digital technology from 2012 to 2022 were obtained, and the spatiotemporal situation of China's digital technology innovation was analyzed by using ArcGIS software, Dagum's Gini coefficient, and Moran's I index, and the spatial Dubin panel model was used to explore the influencing factors of digital technology innovation. It is found that: (1) the scale and vitality of China's digital technology innovation have increased significantly, and there are obvious spatial differentiation characteristics, and the innovation level of "eastern coastal-central and western interior" is decreasing, forming a cluster distribution pattern in the Yangtze River Delta region, Beijing, Guangdong, and other places, and the degree of agglomeration is decreasing. (2) The overall regional differences in China's digital technology innovation are large, the differences between the East and the West dominate the interregional differences, and the net differences between regions are the main factors leading to regional differences. (3) There is a significant positive spatial correlation between the scale and vitality of digital technology innovation, which has a significant spatial spillover effect. (4) The results confirm that the level of economic development, digital access, financial scientific and technological support, technology market development level, and R&D intensity have a significant positive impact on the scale and vitality of digital technology innovation; The investment in scientific and technological talents has a significant positive impact on the scale of digital technology innovation, but has no significant impact on the vitality of digital technology innovation.

Streptomycin-resistant (SM-resistant) Mycobacterium tuberculosis (M. tuberculosis) is a major concern in tuberculosis (TB) treatment. However, the mechanisms underlying streptomycin resistance remain unclear. This study primarily aimed to perform preliminary screening of genes associated with streptomycin resistance through conjoint analysis of multiple genomics. Genome-wide methylation, transcriptome, and proteome analyses were used to elucidate the associations between specific genes and streptomycin resistance in M. tuberculosis H37Rv. Methylation analysis revealed that 188 genes were differentially methylated between the SM-resistant and normal groups, with 89 and 99 genes being hypermethylated and hypomethylated, respectively. Furthermore, functional analysis revealed that these 188 differentially methylated genes were enriched in 74 pathways, with most of them being enriched in metabolic pathways. Transcriptome analysis revealed that 516 genes were differentially expressed between the drug-resistant and normal groups, with 263 and 253 genes being significantly upregulated and downregulated, respectively. KEGG analysis indicated that these 516 genes were enriched in 79 pathways, with most of them being enriched in histidine metabolism. The methylation level was negatively related to mRNA abundance. Proteome analysis revealed 56 differentially expressed proteins, including 14 upregulated and 42 downregulated proteins. Moreover, three hub genes (coaE, fadE5, and mprA) were obtained using synthetic analysis. The findings of this study suggest that an integrated DNA methylation, transcriptome, and proteome analysis can provide important resources for epigenetic studies in SM-resistant M. tuberculosis H37Rv.

The extraction of roadways from remote sensing imagery constitutes a pivotal task, with far-reaching implications across diverse domains such as urban planning, management of transportation systems, emergency response initiatives, and environmental monitoring endeavors. Satellite images captured during daytime have customarily served as the primary resource for this extraction process. However, the emergence of Nighttime Light (NTL) remote sensing data introduces an innovative dimension to this arena. The exploration of NTL data for road extraction remains in its nascent stage, and this study seeks to bridge this gap. We present a refined U-Net model (CA U-Net) integrated with Cross-Attention Mechanisms, meticulously designed to extract roads from Yangwang-1 NTL images. This model incorporates several enhancements, thereby improving its proficiency in identifying and delineating road networks. Through extensive experimentation conducted in the urban landscape of Wenzhou City, the model delivers highly accurate results, achieving an F1 score of 84.46%. These outcomes significantly surpass the performance benchmarks set by Support Vector Machines (SVM) and the Optimal Threshold (OT) method. This promising development paves the way towards maximizing the utility of NTL data for comprehensive mapping and analysis of road networks. Furthermore, the findings underscore the potential of utilizing Yangwang-1 data as a reliable source for road extraction and reaffirm the viability of deploying deep learning frameworks for road extraction tasks utilizing NTL data.

Objective: To investigate the diagnostic value of D-dimer, platelet-lymphocyte rate (PLR) and CT signs for intestinal ischemia in patients with bowel obstruction. Methods: We retrospectively analyzed the clinical and imaging data of 105 patients diagnosed with bowel obstruction, and performed univariate and multivariate analyses to determine the independent risk factors for intestinal ischemia in patients with bowel obstruction. Moreover, the receiver operating characteristic curve (ROC) was plotted to examine the diagnostic value of D-dimer, PLR and CT signs in patients with bowel obstruction. Besides, Kappa tests were used to assess inter-observer agreement. Results: We included 56 men (53%) and 49 women (47%) with mean age of 66.05 ± 16 years. Univariate and multivariate analyses showed that D-dimer, PLR and two significant CT signs (i.e., increased unenhanced bowel-wall attenuation and mesenteric haziness) were independent risk factors for intestinal ischemia in patients with bowel obstruction. ROC analysis showed that the combined use of D-dimer, PLR and the said two CT signs had better performance than single indicators in predicting intestinal ischemia in patients with bowel obstruction. The area under the curve (AUC) of the joint model III was 0.925 [95%CI: 0.876–0.975], with a sensitivity of 79.2% [95CI%: 67.2–91.1] and a specificity of 91.2% [95%CI: 83.7–98.9]. Conclusion: The combined use of D-dimer, PLR and CT signs has high diagnostic value for intestinal ischemia in patients with bowel obstruction and will prompt surgical exploration to evaluate intestinal blood flow. [ABSTRACT FROM AUTHOR]

The livestock industry is one of the main contributors to greenhouse gas emissions and there is an increasing demand for the industry to reduce its carbon footprint. Several studies have shown that feed additives 3-nitroxypropanol and nitrate to be effective in reducing enteric methane emissions. The objective of this study was to estimate the net mitigating effect of using 3-nitroxypropanol and nitrate on total greenhouse gas emissions in California dairy industry. A life cycle assessment approach was used to conduct a cradle-to-farm gate environmental impact analysis based on dairy production system in California. Emissions associated with crop production, feed additive production, enteric methane, farm management, and manure storage were calculated and expressed as kg CO2 equivalents (CO2e) per kg of energy corrected milk. The total greenhouse gas emissions from baseline, 3-nitroxypropanol and nitrate offered during lactation were 1.12, 0.993, and 1.08 kg CO2e/kg energy corrected milk, respectively. The average net reduction rates for 3-nitroxypropanol and nitrate were 11.7% and 3.95%, respectively. In both cases, using the feed additives on the whole herd slightly improved overall carbon footprint reduction compared to limiting its use during lactation phase. Although both 3-nitroxypropanol and nitrate had effects on decreasing the total greenhouse gas emission, the former was much more effective with no known safety issues in reducing the carbon footprint of dairy production in California.

Accurate RNA quantification at the single-cell level is critical for understanding the dynamics of gene expression and regulation across space and time. Single molecule FISH (smFISH), such as RNAscope, provides spatial and quantitative measurements of individual transcripts, therefore, can be used to explore differential gene expression among a heterogeneous cell population if combined with cell identify information. However, such analysis is not straightforward, and existing image analysis pipelines cannot integrate both RNA transcripts and cellular staining information to automatically output cell type-specific gene expression. We developed an efficient and customizable analysis method, Single-Molecule Automatic RNA Transcription Quantification (SMART-Q), to enable the analysis of gene transcripts in a cell type-specific manner. SMART-Q efficiently infers cell identity information from multiplexed immuno-staining and quantifies cell type-specific transcripts using a 3D Gaussian fitting algorithm. Furthermore, we have optimized SMART-Q for user experiences, such as flexible parameters specification, batch data outputs, and visualization of analysis results. SMART-Q meets the demands for efficient quantification of single-molecule RNA and can be widely used for cell type-specific RNA transcript analysis.

Due to low labeling efficiency and structural heterogeneity in fluorescence-based single-molecule localization microscopy (SMLM), image alignment and quantitative analysis is often required to make accurate conclusions on the spatial relationships between proteins. Cryo-electron microscopy (EM) image alignment procedures have been applied to average structures taken with super-resolution microscopy. However, unlike cryo-EM, the much larger cellular structures analyzed by super-resolution microscopy are often heterogeneous, resulting in misalignment. And the light-microscopy image library is much smaller, which makes classification challenging. To overcome these two challenges, we developed a method to deform semi-flexible ring-shaped structures and then align the 3D structures without classification. These algorithms can register semi-flexible structures with an accuracy of several nanometers in short computation time and with greatly reduced memory requirements. We demonstrated our methods by aligning experimental Stochastic Optical Reconstruction Microscopy (STORM) images of ciliary distal appendages and simulated structures. Symmetries, dimensions, and locations of protein complexes in 3D are revealed by the alignment and averaging for heterogeneous, tilted, and under-labeled structures.

The amount of data in the globe is increasing at an exponential rate, and the role of digital technology and data elements in the modern growth of China's sports business is becoming more significant. Disputes over sports data rights have grown in the international arena, with a special focus on how to preserve the sports data rights of key stakeholders. This study begins from the standpoint of stakeholders, constructs a tripartite evolutionary game model of the government, sports enterprises, and the public around the issue of sports data rights protection, investigates the behavioral evolutionary characteristics of each stakeholder and its stabilization strategies, simulates and analyzes the evolutionary stabilization strategies of the stakeholders in various situations using MATLAB, and proposes a compatible institution. According to the findings of this study, the cost of sports data governance, the cost of sports data sharing, the degree of sports data compliance use, the government incentive system, and the government regulation mechanism are the important elements impacting each stakeholder's behavioral decision-making. Based on the foregoing, the study proposes corresponding institutional strategies for governments to respond to the issue of sports data rights, which will be more conducive to the safe use of data for development and humanitarian action, as well as contribute to global sustainable development.

The graduate admissions process is time-consuming, subjective, and complicated by the need to combine information from diverse data sources. Letters of recommendation (LORs) are particularly difficult to evaluate and it is unclear how much impact they have on admissions decisions. This study addresses these concerns by building machine learning models to predict admissions decisions for two STEM graduate programs, with a focus on examining the contribution of LORs in the decision-making process. We train our predictive models leveraging information extracted from structured application forms (e.g., undergraduate GPA, standardized test scores, etc.), applicants' resumes, and LORs. A particular challenge in our study is the different modalities of application data (i.e., text vs. structured forms). To address this issue, we converted the textual LORs into features using a commercial natural language processing product and a manual rating process that we developed. By analyzing the predictive performance of the models using different subsets of features, we show that LORs alone provide only modest, but useful, predictive signals to admission decisions; the best model for predicting admissions decisions utilized both LOR and non-LOR data and achieved 89% accuracy. Our experiments demonstrate promising results in the utility of automated systems for assisting with graduate admission decisions. The findings confirm the value of LORs and the effectiveness of our feature engineering methods from LOR text. This study also assesses the significance of individual features using the SHAP method, thereby providing insight into key factors affecting graduate admission decisions.

This study focuses on effectively controlling landslides at the boundary of a soft rock open-pit dump while ensuring safe increases in the dump's capacity and optimal utilization of external dump sites. To achieve this, the adoption of a local filling method for the dump base is proposed. By leveraging the concepts of limit equilibrium theory and equivalent shear strength parameters, the mathematical expression of the slope stability coefficient in the Morgenstern-Price method is derived and improved. This improved method is then applied to a real engineering example to determine the optimal basement replacement rate required to maintain slope stability. The findings reveal that the local filling of the base is well-suited for slopes susceptible to potential landslides associated with cutting layers, bedding layers, and swelling. For practical ease, it is advisable to choose the lowest step in the dump's slope for construction convenience. As the local replacement rate of the base increases, the slope's stability coefficient gradually improves, with the K-Fs ratio showing a prominent role in this process. Additionally, numerical simulation methods are employed to elucidate the mechanism of the dump's landslide following local basement replacement, thereby providing comprehensive evidence of the engineering applicability of this method. The research results demonstrate a promising practical application prospect for effectively controlling the stability of soft base dump slopes.

Image dehazing models are critical in improving the recognition and classification capabilities of image-related artificial intelligence systems. However, existing methods often ignore the limitations of receptive field size during feature extraction and the loss of important information during network sampling, resulting in incomplete or structurally flawed dehazing outcomes. To address these challenges, we propose a multi-level perception fusion dehazing network (MPFDN) that effectively integrates feature information across different scales, expands the perceptual field of the network, and fully extracts the spatial background information of the image. Moreover, we employ an error feedback mechanism and a feature compensator to address the loss of features during the image dehazing process. Finally, we subtract the original hazy image from the generated residual image to obtain a high-quality dehazed image. Based on extensive experimentation, our proposed method has demonstrated outstanding performance not only on synthesizing dehazing datasets, but also on non-homogeneous haze datasets.

Self-reported tiredness or low energy, often referred to as fatigue, has been linked to lifestyle factors, although data from randomized-controlled trials are lacking. We investigate whether modifiable lifestyle factors including smoking and alcohol intake related exposures (SAIEs) are causal factors for fatigue using Mendelian randomization (MR). A two-sample MR study was performed by using genome-wide association summary results from UK Biobank (UKBB), and each of the sample size is more than 100,000. We used the inverse variance weighted method, and sensitivity analyses (MR Egger, weighted median, penalized median estimators, and multivariable MR) to account for pleiotropy. The two-sample MR analyses showed inverse causal effect of never-smoking status and positive effect of current smoking status on the risk of fatigue. Similarly, genetically predicted alcoholic intake was positively associated with fatigue. The results were consistent across the different MR methods. Our Mendelian randomization analyses do support that the cessation of smoking and alcohol can decrease the risk of fatigue, and limit alcohol intake frequency can also reduce the risk.

Based on the panel data of 16 cities in Anhui from 2010-2018, this paper measures the index system of fiscal structure and high-quality economic development in Anhui using the entropy weight method, and empirically analyzes the coordinated development level of fiscal structure and high-quality economic development in Anhui using coupled coordination degree model. The study finds that: (1) the overall structure of Anhui's fiscal expenditure is characterized by "service-oriented and investment-oriented", and there is a phenomenon that contradicts "Wagner Principle", and there are also spatial and temporal differences in Anhui's tax structure. (2) The level of high-quality development of Anhui economy shows a steady upward trend, but is still at a low level. (3) The level of coordinated development of fiscal structure and high-quality economic development is still low, and the overall situation is "on the verge of disorder" or "barely coordinated". (4) Regionally, the overall coordination of fiscal expenditure structure, tax structure, and high-quality economic development in southern Anhui shows a decreasing trend, while the overall coordination in central and northern Anhui shows an increasing trend, so that southern Anhui has been or will be surpassed by northern and middle Anhui, and the growth rate of middle Anhui is faster than that of northern Anhui.

This study monitored the presence of SARS-Cov-2 RNA on environmental surfaces in hospital wards housing patients with mild, severe, and convalescent Coronavirus Disease 2019 (COVID-19), respectively. From 29 October to 4 December 2021, a total of 787 surface samples were randomly collected from a General Ward, Intensive Care Unit, and Convalescent Ward at a designated hospital for COVID-19 patients in China. All of the samples were used for SARS-Cov-2 detection. Descriptive statistics were generated and differences in the positivity rates between the wards were analyzed using Fisher's exact tests, Yates chi-squared tests, and Pearson's chi-squared tests. During the study period, 787 surface samples were collected, among which, 46 were positive for SARS-Cov-2 RNA (5.8%). The positivity rate of the contaminated area in the Intensive Care Unit was higher than that of the General Ward (23.5% vs. 10.4%, P0.05). In the clean area, only one sample was positive in the Intensive Care Unit (0.5%). None of the samples were positive in the Convalescent Ward. These findings reveal that the SARS-Cov-2 RNA environmental pollution in the Intensive Care Unit was more serious than that in the General Ward, while the pollution in the Convalescent Ward was the lowest. Strict disinfection measures, personal protection, and hand hygiene are necessary to limit the spread of SARS-Cov-2.

Breast cancer ranks first among female cancers and has become a major public health problem in the current society. More studies indicated that these cancers are related to the change in the gut microbiome that can cause metabolic and immune system disorders in the body. However, there are few studies on the changes in gut microbiome caused by the onset of breast cancer, and the relationship between breast cancer and gut microbiome needs to be further clarified. In this study, we inoculated 4T1 breast cancer cells to induce breast cancer tumorigenesis in mice and collected their feces samples at different stages during this process. These intestinal florae were analyzed using 16S rRNA gene amplicon sequencing, and the results showed that at the phylum level, the ratio of Firmicutes/Bacteroidetes decreased with the development of the tumor; at the family level, the intestinal microbiome had obvious variations of Lachnospiraceae, Bacteroidaceae, Erysipelotrichaceae, etc. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and COG annotation demonstrated that decreased abundance of cancer-related signaling pathways. This study elucidated the relationship between breast cancer and intestinal microbiome, and the research results can be used as an important biomarker for the diagnosis of breast cancer.

Salmonella, one of the major causes of foodborne infections, can cause bacterial foodborne illness. We investigated the serotype distribution, multidrug resistance (MDR), and β-lactamase resistance genes of human Salmonella isolates collected from clinical specimens in Guizhou, China, between 2013 and 2018. A total of 363 Salmonella isolates were collected from clinical specimens at 17 surveillance hospitals. Twenty-four serotypes were identified by sliding agglutination test. S. Enteritidis (33.9%), Salmonella 4,[5],12:i:- (24.0%), S. Typhimurium (16.3%), S. London (6.3%), and S. Derby (3.9%) were the top five serotypes. In 2018, the most common serotype changed from S. Enteritidis to S. Typhimurium. Among the 363 Salmonella isolates, 97.5% of isolates were resistant to at least one class of antimicrobial agents. For cephalosporins, ceftriaxone had the highest resistance rate of 10.5%, and cefepime and cefoxitin were 8.0% and 2.2%, respectively. Three hundred and one (82.9%) Salmonella isolates showed MDR. Salmonella 4,[5],12:i:- had the highest MDR rate with 94.2%, followed by S. London (91.3%) and S. Typhimurium (88.1%). Multidrug resistance rates of Salmonella isolates in Guizhou from 2013 to 2017 increased from 75.8% to 86.7%. Sixteen isolates (4.4%) showed extensive drug resistance. One hundred thirty-four antimicrobial resistance patterns were found. Two hundred and forty-one (66.4%) isolates carried at least one β-lactamase resistance gene. The blaTEM gene (61.2%) was the most prevalent resistant gene in all Salmonella isolates, followed by the blaCTX-M gene (6.1%) and blaOXA-1 gene (4.1%). Our findings showed that the MDR rate of Salmonella isolates from Guizhou province increased year by year. Therefore, systematic and long-term surveillance on MDR Salmonella isolates from clinical patients should be further strengthened.

Technically, symptom of offspring asthma is also closely reliant on its maternal high-fiber diet as well as the intestinal microbiome. Fruits and vegetables are abundant in inulin, and this naturally soluble dietary fiber is endowed with a potential value on offspring asthma control through the maternal intake, but the mechanism now remains less studied. In this study, rats were given with inulin-included drinking water, whereas in normal group rats were allowed with normal water. Afterwards, we analyzed both the formations of the offspring intestinal microbiome ahead of asthma model establishment and of the maternal intestinal microbiome through high throughput sequence and the short-chain fatty acids (SCFAs) by metabolomic analysis. Subsequently, lung inflammation indexes were detected by Elisa, and the expression of short-chain fatty acid receptors (GPR41, GPR43) in the offspring of asthma models were evaluated through qPCR assay. Inulin intake resulted in altered maternal intestinal microbiome composition, with a significant increase in SCFAs-producing bacteria (mainly Bifidobacterium), attenuating the asthmatic inflammatory response in the offspring. Meanwhile, inulin intake during pregnancy modulates the composition of the intestinal microbiome of the offspring, and this alteration appears before the onset of asthma, hence, there should be further studies onto the impacts of offspring's intestinal microbiome on asthma procession.

From the perspective of generalized technological progress, this study investigates the energy rebound effects on China’s domestic overall and the country’s various industries using 2005–2017 data. The results showed that the rebound effect of the domestic overall is driven mainly by the secondary sector. The domestic overall and high-energy-consuming industries decrease the rebound effects, whereas low-energy-consuming industries increase the rebound effects. As China’s industrial structure does not lean toward high-energy-consuming industries, this implies that the Industrial Restructuring Initiative that began in the Chinese government’s “Eleventh Five-Year Plan” has effectively slowed down the rebound effects of high-energy-consuming industries, and the feedback effect of self-reinforcement within the economic system was offset. The results also implied that energy efficiency policies should shift to low-energy-consuming industries; the rebound effects of the energy industries could be lessened, the energy efficiency of low-energy-consuming industries could be increased, and the industrial structure could be further optimized by implementing an appropriate pricing in electricity.