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Abstract Background Universal Health Coverage (UHC) is a common health policy objective outlined in the Sustainable Development Goals. With provincial governments taking the initiative, Pakistan has implemented and extended UHC program amid a complex public health landscape. In this context, we assess Pakistan’s progress toward achieving UHC at the national and subnational level. Methods We use data from the Demographic and Health Surveys and the Household Integrated Economic Survey to construct a UHC index at the national and subnational level for 2007, 2013, and 2018. Furthermore, we use Concentration Index (CI) and CI decomposition methodologies to assess the primary drivers of inequality in accessing medical services. Logistic regression and Sartori’s two-step model are applied to examine the key determinants of catastrophic health expenditure (CHE). Results Our analysis underscores Pakistan’s steady progress toward UHC, while revealing significant provincial disparities in UHC progress. Provinces with lower poverty rate achieve higher UHC index, which highlights the synergy of poverty alleviation and UHC expansion. Among the examined indicators, child immunization remains a key weakness that one third of the children are not fully vaccinated and one sixth of these not-fully-vaccinated children have never received any vaccination. Socioeconomic status emerges as a main contributor to disparities in accessing medical services, albeit with a declining trend over time. Household socioeconomic status is negatively correlated with CHE incidence, indicating that wealthier households are less susceptible to CHE. For individuals experiencing CHE, medicine expenditure takes the highest share of their health spending, registering a staggering 70% in 2018. Conclusion Pakistan’s progress toward UHC aligns closely with its economic development trajectory and policy efforts in expanding UHC program. However, economic underdevelopment and provincial disparities persist as significant hurdles on Pakistan’s journey toward UHC. We suggest continued efforts in UHC program expansion with a focus on policy consistency and fiscal support, combined with targeted interventions to alleviate poverty in the underdeveloped provinces.

To investigate the difference of the components and antioxidant activity between the Se-enriched and the common chlorella extract, as well as the correlation between the components and antioxidant activity. This study determined the content of total nitrogen, total sugar, polyphenols, flavonoids, saponins, total selenium, polysaccharide and polysaccharide selenium in selenium-enriched and common chlorella extract and their ability to reduce Fe3+, scavenge DPPH·, ABTS+·, ·OH and O2−·, as well as the correlation between the content and antioxidant capacity. The results showed that compared with common chlorella extract, selenium-enriched chlorella extract contained more content of total sugar, polyphenol, flavonoid, total selenium, polysaccharide and polysaccharide selenium (P

Abstract Objective The primary objective of this study was to explore the clinical characteristics of apoplectic intratumoral hemorrhage in gliomas and offer insights for improving the diagnosis and treatment of this disease. Methods We analyzed the clinical data of 35 patients with glioma and hemorrhage. There were eight cases of multiple cerebral lobe involvement, and 22 cases involved a single lobe. Twenty-one patients had a preoperative Glasgow Coma Scale (GCS) score of ≥ 9 and had a craniotomy with tumor resection and hematoma evacuation after undergoing preoperative preparation. A total of 14 patients with GCS

Abstract Background To explore and compare the values of 3.0T magnetic resonance imaging (MRI) T2 mapping in evaluating the degree of acetabular cartilage degeneration in hip replacement surgery. Methods A total of 26 elderly patients with femoral neck fractures who were scanned in 3.0T MRI T2 mapping quantification technique were included. Basing on MRI images, the degree of acetabular cartilage degeneration was classified into Grade 0, 1, 2, 3 and 4, according to the International Cartilage Repair Society (ICRS) scores. In addition, 8 healthy volunteers were included for control group. Results By comparison with health population, T2 relaxation values in the anterior, superior, and posterior regions of acetabular cartilage in patients with femoral neck fracture were obviously increased (P 0.05). Importantly, acetabular cartilage degeneration can be detected through signal changes of T2 mapping pseudo-color images. Conclusion 3.0T MRI T2 mapping technology can be used to determine the degree of acetabular cartilage degeneration, which can effectively monitor the disease course.

Background: Osteomyelitis (OM) is an inflammatory condition of bone characterized by cortical bone devascularization and necrosis. Dysregulation of bone remodelling is triggered by OM. Bone remodelling is precisely coordinated by bone resorption and formation via a reversal phase. However, the cellular and molecular mechanisms underlying bone remodelling failure after osteomyelitis remain elusive. Methods: To elucidate the cellular and molecular mechanism underlying bone healing after osteomyelitis, we employed single-cell RNA sequencing (scRNA-seq) to depict the atlas of human cortical bone in normal, infected and reconstructed states. Dimensionality reduction by t-stochastic neighbourhood embedding (t-SNE) and graph-based clustering were applied to analyse the detailed clusters of osteoclast lineages. After trajectory analysis of osteoclast lineages over pseudotime, real-time PCR and immunofluorescence (IF) staining were applied to identify marker gene expression of various osteoclast lineages in the osteoclast induction model and human bone sections, respectively. The potential function and communication of osteoclasts were analysed via gene set enrichment analysis (GSEA) and CellChat. The chemotactic ability of mesenchymal stem cells (MSCs) and osteoclast lineage cells in various differentiation states was determined by transwell assays and coculture assays. The effects of various osteoclast lineages on the osteogenic differentiation potential of MSCs were also determined by using this coculture system. A normal mouse tibia fracture model and an osteomyelitis-related tibia fracture model were generated via injection of luciferase-labelled Staphylococcus aureus to verify the relationships between a novel osteoclast lineage and MSCs. Then, the infection was detected by a bioluminescence imaging system. Finally, immunofluorescence staining was used to detect the expression of markers of MSCs and novel osteoclast lineages in different remodelling phases in normal and infected bone remodelling models. Results: In this study, we constructed a cell atlas encompassing normal, infected, and reconstructed cortical bone. Then, we identified a novel subset at the earlier stage of the osteoclast lineage that exhibited increased expression of IDO1, CCL3, and CCL4. These IDO1highCCL3highCCL4high cells, termed osteostaticytes (OSCs), were further regarded as the reservoir of osteoclasts in the reversal phase. Notably, OSCs exhibited the highest chemotactic activity, surpassing other lineage subsets. We also discovered that cells at the earlier stage of the osteoclast lineage play a significant role in recruiting mesenchymal stem cells (MSCs). Finally, the data revealed that OSCs might be positively related to the occurrence of bone MSCs and the contribution of bone remodelling. Conclusion: Collectively, our findings revealed a novel stage (OSC) within the osteoclast lineage, potentially representing elusive bone reversal cells due to its increased chemotactic ability towards MSCs and potential contribution to bone remodelling. This study provides valuable insights into the intricate mechanisms of the reversal phase during bone remodelling and unveils potential therapeutic strategies for diseases associated with bone uncoupling. Translational potential of this article: This study identified a new subset, referred to as IDO1(plus symbol) CCL3(plus symbol) CCL4(plus symbol) osteostaticytes which displayed the highest chemotactic activity among all osteoclast lineages and may serve as reversal cells in bone remodelling. These findings offer new insights and insights for understanding bone reversal-related diseases and may serve as novel therapeutic targets for conditions such as osteomyelitis and delayed bone healing.

Copper is an essential trace element for the human body. Abnormalities in copper metabolism can lead to bone defects, mainly by directly affecting the viability of osteoblasts and osteoclasts and their bone remodeling function, or indirectly regulating bone metabolism by influencing enzyme activities as cofactors. Copper ions released from biological materials can affect osteoblasts and osteoclasts, either directly or indirectly by modulating the inflammatory response, oxidative stress, and rapamycin signaling. This review presents an overview of recent progress in the impact of copper on bone metabolism.Translational potential of this article: The impact of copper on bone metabolism can provide insights into clinical application of copper-containing supplements and biomaterials.

In the western mining area, coal mining is characterized by shallow burial depth, thin bedrock, multi coal seam mining, and a fragile surface environment. To address the limitations of traditional observation methods for mining-induced subsidence, such as small coverage, high operation intensity, and low automation, unmanned aerial vehicle （UAV） photogrammetry technology has been introduced to observe and analyze the surface subsidence patterns of a coal mine working face. The results show that: the UAV photogrammetry method achieves a centimeter-level observation accuracy, with a median error of 4.4 cm, which meets the overall observation requirements for surface subsidence. A surface subsidence model of the entire mining area within a 2.53 km² survey area was obtained using the UAV photogrammetry method. This model accurately reflects the subsidence area and amplitude of the surface in the mining area. Due to the influence of multiple coal seams mining, the surface subsidence model exhibits an uneven basin shape. The subsidence curves along the strike and dip of the working face show asymmetry, with a maximum subsidence value of 3.18 m.

Abstract With the changes of people's lifestyle, hyperlipidemia and hyperglycemia which were induced from a diet high in both fat and sugar have become serious health concerns. Tree peony seed oil (PSO) is a novel kind of edible oil that shows great potential in the food industry because of its high constituent of unsaturated fatty acids. Based 16S rRNA and gut untargeted metabolomics, this study elucidated that the mechanism of PSO regulating blood glucose (Glu) and lipids. The impact of PSO on gut microbiota balance and gut metabolites of mice with a high‐fat diet (HFD) was evaluated. The findings indicated that PSO decreased HFD mice's body weight and fat accumulation, ameliorating the levels of blood lipid, reduced liver fat vacuole levels. What's more PSO modulated the proportion of gut microbiota in HFD mice and enhanced the abundance of probiotics. Furthermore, untargeted metabolomic analysis revealed that PSO not only impacted the generation of short‐chain fatty acids (SCFAs) by gut microorganism and altered metabolic pathway but exerted influence on secondary bile acids (BA), amino acid metabolism, and various other metabolites. These results suggested that PSO has the potential function for mitigating HFD‐induced hyperlipidemia and hyperglycemia by regulating gut microbiota and host metabolism.

Abstract Background Primary vitreous cyst is a clinical variant delineated by the existence of a vesicle within the vitreous cavity from birth. This particular disease tends to be uncommon, and the underlying mechanisms contributing to its pathogenesis remain obscure. Case presentation A 37-year-old male patient manifested blurry vision and floaters in his right eye, a symptomology first noticed three months prior. Upon slit-lamp examination, a pigmented, round, 1 papilla diameter-sized mass was discerned floating in the vitreous. A meticulous examination of the floaters was conducted using an array of multimodal imaging techniques. Other potential conditions, including cysticercosis, toxoplasmosis, and tumors, were conclusively excluded through comprehensive diagnostic tests such as blood examinations, liver ultrasound, and cranial magnetic resonance imaging (MRI), resulting in the diagnosis of a primary vitreous cyst. The patient did not report any other discomforts and did not receive any subsequent interventions or treatments. Conclusion We furnish an exhaustive case report of a patient diagnosed with a primary vitreous cyst. The incorporation of multimodal images in the characterization of the disease anticipates facilitating an enriched comprehension by medical practitioners.

Abstract Electrochromic devices are applied extensively to camouflages, smart windows, heat insulation layers, and automobile rearview mirrors, etc. The amorphous WO3 is a very attractive electrochromic material, whereas it suffers from degradation of optical modulation and reversibility on ion exchange owing to those deep trapped ions with irreversible reaction behavior. Herein, we designed and, by using magnetron sputtering, prepared a composite film with TiO2/WO3/TiO2 double heterojunctions, which is capable of eliminating the deep trapped ions by itself under ultraviolet light (UV) assistance. The electrochromic device based on this composite film, after being recovery by short-time UV irradiation, can maintain a high transmission modulation of 94.72% after 7000 cycles of the voltammetry measurement. This feature allows the device to maintain its initial electrochromic performance after prolonged use. Moreover, the double heterojunction structure can reduce colouring time and enormously improve the colouration efficiency (CE) of electrochromic devices. Experimental research shows that when the thickness of the bottom and upper TiO2 layer of the WO3 film was 145.5 nm and 97.0 nm, respectively, the CE of electrochromic devices reached a perfectly high value (479.3 cm2/C), being much higher than that of WO3 devices (69.5 cm2/C). Functions of the TiO2/WO3/TiO2 double heterojunction in electrochromic device were investigated by combining theoretical analysis and experiment validation, and these results provide a general framework for developing and designing superior electrochromic materials and devices.

Abstract In this study, a newly developed composite of biochar-poly(m-phenylenediamine) (BC-PmPD) exhibiting a distinct skeletal structure was synthesized for the purpose of extracting Cr(VI) from aqueous solutions. BC was employed as a supportive carrier onto which PmPD nanoparticles were uniformly affixed through in-situ polymerization and oxidation synthesis, both within and outside the layered configuration of BC. The structural stability and morphologies of BC-PmPD were assessed utilizing Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy, thermogravimetric analysis, analysis of specific surface area and pore size, X-ray photoelectron spectroscopy (XPS), and X-ray diffraction. In comparison to other modified BCs reported, BC-PmPD exhibited the highest Cr(VI) removal rate. Specifically, at 303 K, BC-PmPD achieved a maximum Cr(VI) removal capacity of 775 mg g−1, surpassing the capabilities of unmodified BC and PmPD by 10.4 and 2.13 times, respectively. Analyses involving XPS, FTIR, and density functional theory calculation confirmed that proton transfer happened between protonated amine (−NH2) functional group within the structure of BC-PmPD and HCrO4 − before the formation of hydrogen bond. Subsequently, environmentally persistent free radicals facilitated the reduction of the adsorbed Cr(VI). Quantification of the functional groups indicated that the amino group was responsible for 93.0% of the Cr(VI) adsorption in BC-PmPD. BC-PmPD displayed potent adsorption and reduction capabilities, alongside notable stability, repeatability, and promising potential for application in the remediation for high concentrations of Cr(VI) in electroplating wastewater scenarios. Graphical Abstract

Recently, the Mg–Ag binary alloy has gained much attention as an antibacterial biomaterial. However, the relationships between the extrusion parameters, microstructure, and mechanical properties of Mg–Ag alloys haven't been clearly established. Therefore, in this paper, the effects of silver (Ag) content (0, 3, 6 wt%) and extrusion (as cast, extrusion ratio (ER) 7.1 and 72.2) on the microstructure and mechanical properties of Mg–Ag alloys are systematically investigated. The results indicate that for the Mg–Ag alloys with the same extrusion ratio, as the Ag increased from 0 to 3 wt%, Mg4Ag and Mg54Ag17 precipitated, leading to significant precipitation strengthening and an increase in the yield strength by over 137%. As the Ag increased to 6 wt%, the yield strength increased by only ∼20%, attributable to Ag promoting dynamic recrystallization, resulting in less grain refinement, a slower amount increase and a smaller size reduction of the precipitate. For the Mg–Ag alloys with the same Ag content, as the extrusion ratio increased to 7.1, the yield strength increased significantly by over 37%, since the grain boundary strengthening and precipitation strengthening were significantly enhanced as the grains were refined, a large number of precipitates appeared, and their sizes significantly reduced. When the extrusion ratio increased to 72.2, the yield strength increased by only ∼10%, due to the weakening of both grain boundary strengthening and precipitation strengthening as the recrystallization further improved, leading to an increase in grain sizes, the redissolution of precipitates, and a lesser reduction in their sizes.

Abstract In order to efficiently and accurately control coal dust pollution in coal mining faces, this study addresses the insufficient research on the dust generation mechanism during cutting. Firstly, a similar experimental platform for simulating coal wall cutting with a drum cutter was used to investigate the changes in coal wall fragmentation and dust generation at drum speeds of 35 r/min, 50 r/min, 65 r/min, and 80 r/min. The experimental results revealed that the degree of coal wall fragmentation and dust generation increased with the increase in rotational speed, leading to a wider range of particle size distribution and an increase in the generation of fine dust particles. A 1:1 scale discrete element simulation of coal wall cutting with a drum cutter was conducted based on the experiments. The results indicated that, under the four rotational speeds, the cracks generated during coal wall fracture were predominantly tensile cracks, accounting for over 76% of the total crack count. The total number of cracks increased from 10,600 to 11,200, the number of free single particles increased from 2555 to 2728, and the fragmentation volume increased from 0.021607 to 0.023024 m3. The range and degree of coal wall fragmentation increased with the increase in drum speed.

Abstract The tissue damage caused by transient ischemic injury is an essential component of the pathogenesis of retinal ischemia, which mainly hinges on the degree and duration of interruption of the blood supply and the subsequent damage caused by tissue reperfusion. Some research indicated that the retinal injury induced by ischemia-reperfusion (I/R) was related to reperfusion time. In this study, we screened the differentially expressed circRNAs, lncRNAs, and mRNAs between the control and model group and at different reperfusion time (24h, 72h, and 7d) with the aid of whole transcriptome sequencing technology, and the trend changes in time-varying mRNA, lncRNA, circRNA were obtained by chronological analysis. Then, candidate circRNAs, lncRNAs, and mRNAs were obtained as the intersection of differentially expression genes and trend change genes. Importance scores of the genes selected the key genes whose expression changed with the increase of reperfusion time. Also, the characteristic differentially expressed genes specific to the reperfusion time were analyzed, key genes specific to reperfusion time were selected to show the change in biological process with the increase of reperfusion time. As a result, 316 candidate mRNAs, 137 candidate lncRNAs, and 31 candidate circRNAs were obtained by the intersection of differentially expressed mRNAs, lncRNAs, and circRNAs with trend mRNAs, trend lncRNAs and trend circRNAs, 5 key genes (Cd74, RT1-Da, RT1-CE5, RT1-Bb, RT1-DOa) were selected by importance scores of the genes. The result of GSEA showed that key genes were found to play vital roles in antigen processing and presentation, regulation of the actin cytoskeleton, and the ribosome. A network included 4 key genes (Cd74, RT1-Da, RT1-Bb, RT1-DOa), 34 miRNAs and 48 lncRNAs, and 81 regulatory relationship axes, and a network included 4 key genes (Cd74, RT1-Da, RT1-Bb, RT1-DOa), 9 miRNAs and 3 circRNAs (circRNA_10572, circRNA_03219, circRNA_11359) and 12 regulatory relationship axes were constructed, the subcellular location, transcription factors, signaling network, targeted drugs and relationship to eye diseases of key genes were predicted. 1370 characteristic differentially expressed mRNAs (spec_24h mRNA), 558 characteristic differentially expressed mRNAs (spec_72h mRNA), and 92 characteristic differentially expressed mRNAs (spec_7d mRNA) were found, and their key genes and regulation networks were analyzed. In summary, we screened the differentially expressed circRNAs, lncRNAs, and mRNAs between the control and model groups and at different reperfusion time (24h, 72h, and 7d). 5 key genes, Cd74, RT1-Da, RT1-CE5, RT1-Bb, RT1-DOa, were selected. Key genes specific to reperfusion time were selected to show the change in biological process with the increased reperfusion time. These results provided theoretical support and a reference basis for the clinical treatment.

BackgroundIn the general population, primary human papillomavirus (HPV) testing is advocated for cervical cancer (CC) screening. HPV E6/E7 mRNA (Aptima HPV, AHPV) assays have garnered considerable traction due to their higher specificity when compared with HPV DNA assays. Here, we investigated age-specific primary AHPV screening assays and different triage strategies versus cytology to identify the best approach.MethodsBetween April 2018 and December 2021, we recruited female participants from 34 communities across Liaoning province and Qingdao City, China. Primary cervical screening protocols included liquid-based cytology (LBC) and AHPV assays, with females positive for any assays undergoing colposcopy. Genotyping (AHPV-GT) was conducted on all HPV-positive samples. Our primary outcomes were the identification of age-specific detection rates, colposcopy referral rates, and sensitivity and specificity values for high-grade squamous intraepithelial lesions or worse (HSIL+). AHPV and different triage strategy performances were also examined across different age cohorts.ResultsOur investigation included 9911 eligible females. Age-specific abnormal cytology rates were in the 6.1%–8.0% range, and were highest in 45–54-year olds. When compared with 35–44-or 45–54-year olds, HPV prevalence was highest in 55–64-year olds (12.2% or 11.6% vs.14.1%, P = 0.048 and P = 0.002, respectively). In 35–44-year olds, AHPV sensitivity for detecting HSIL+ was 96.6 (95% confidence interval [CI]: 89.7–100) - significantly higher than LBC sensitivity (65.5 [95% CI: 48.3–82.8], P < 0.001). When compared with LBC, HSIL+ detection rates by AHPV-GT using reflex LBC triage increased by 31.5% (9.6‰ vs. 7.3‰), and colposcopy referral rates decreased by 16.4% (5.1% vs. 6.1%). In 45–54-year olds, HSIL+ detection rates for AHPV-GT using reflex LBC triage were lower than LBC rates (6.2‰ vs. 6.6‰). In 55–64-year olds, AHPV sensitivity (97.2 [95% CI: 91.7–100.0]) was higher than LBC sensitivity (66.7 [95% CI: 50.0–80.6], P = 0.003). The area under the curve (AUC) value was not significantly different between AHPV-GT with reflex LBC triage and LBC (0.845 [95% CI: 0.771–0.920] vs. 0.812 [95% CI: 0.734–0.891], P = 0.236).ConclusionsPrimary AHPV screening using different triage strategies were different across different age cohorts. Thus, AHPV may be an appropriate primary screening method for 35–44 and 55–64 year old females, while AHPV-GT with reflex LBC triage may be more apt for 35–44 year old females.

One of the main causes of unfavorable pregnancy outcomes in expectant mothers is pregnancy-associated venous thromboembolism. Although pregnancy-related venous thromboembolism does not always manifest obvious clinical symptoms and lacks a comprehensive standard risk assessment and prediction system as well as simple and effective laboratory testing techniques, timely and accurate diagnosis can still help reduce the probability of adverse pregnancy outcomes. To aid in the early detection, diagnosis, and treatment of pregnancy- associated venous thromboembolism, we attempt to provide an overview of the radiological diagnostic techniques for various forms of the condition.

BackgroundThis study aimed to measure the accuracy of optical coherence tomography (OCT) in the early diagnosis of high-grade cervical lesions and assess its diagnostic value in the triage of high-risk HPV infection.MethodFrom Jan 2019 to Jan 2021, women who visited the gynecology clinics of 2 hospitals for colposcopy were invited to participate in this study. Women aged 35 to 64 years old who were sexually active and had an intact cervix with a diameter of more than or equal to 2 cm were included in this study. Additionally, individuals with abnormal cytology, positive HPV test results, or other clinically suspicious symptoms or signs were referred. All participants were examined before colposcopy using OCT. Biopsy and/or ECC were conducted under colposcopy. We used the results of histopathology as the gold standard and assessed the accuracy of OCT.ResultsOverall, 883 women were included in the analysis. Approximately 13.25% of women were ASCUS+ in cytological assessments, and 22.31% were positive for high-risk HPV. Nearly 15.18% of women were positive in OCT. Of them, 27 women were diagnosed with CIN2, and 33 were diagnosed with CIN3+ lesions. Among HPV-positive women, the detection rates for CIN2+ and CIN3+ were much lower for those who were negative in OCT, compared with NILM cytology (CIN2+: 20.0% vs. 30.0%, P=0.002, and CIN3+: 18.2% vs. 27.3%, P=0.013). Among women who were positive for HPV16/18, the detection rate for CIN2+ was much lower for negative OCT, compared with NILM cytology (8.3% vs.15.0%, P=0.005). Compared to HPV and cytological tests, HPV combined with OCT had higher specificity for detecting CIN2+ and CIN3+ (96.1% vs. 93.2%, P=0.002; 93.8% vs. 91.3%, P=0.013). OCT triage after HPV genotyping had the highest AUC for detecting CIN2+ and CIN3+ cases among patients with high-risk HPV infection (0.921, 0.920).ConclusionOCT is an accurate test for the early diagnosis of high-grade cervical lesions and has great diagnostic value in the triage of patients with high-risk HPV infection.

Tempestite has been discovered in the Lower Cambrian Canglangpu Formation in the north central Sichuan Basin. However, there has been limited research on storm sedimentation and the Lower Cambrian sedimentary environments, ancient geography, and ancient sedimentary geomorphology in this region. By conducting detailed core observations and thin section identifications, the storm sedimentation sequence and sedimentation model of the Canglangpu Formation have been investigated, revealing its geological significance. Various storm sedimentation structures, such as gravel sections, graded sections, parallel laminated sections, and hummocky cross-stratifications (HCS), are present in the Canglangpu Formation. The tempestites within this formation can be categorized into five types of storm sedimentation sequences: Sequence Ⅰ includes gravel sections (A), parallel laminatedsections (C), and HCS (D) above the fair-weather wave base (FWB). Sequence Ⅱ comprises parallel laminated section (C), HCS (D), and horizontally laminated mudstone section (E) deposited near the storm wave base (SWB). Sequence Ⅲ includes scouring-fill structures and gravel section (A), as well as a graded section (B) deposited between the fair-weather wave base (FWB) and SWB. Sequence Ⅳ is characterized by a graded section (B) and parallel laminated section (C) located far from the storm center, above and near SWB. Sequence Ⅴ consists of scouring-fill structures and gravel section (A) located between the mean sea level (MSL) and FWB, close to FWB. The analysis of tempestites in north central Sichuan Basin suggests that the initial member of the Canglangpu Formation was deposited on the shelf-ramp-platform margin and shelf, indicating that the Upper Yangtze Plate was situated in a low latitude region during the sedimentation period of the Canglangpu Formation. This information provides valuable insights into lithofacies paleogeography reconstruction. Storm events have resulted in the formation of storm mudflats in the study area, which are favorable for reservoir development. The investigation of storms in the Canglangpu Formation aids in predicting the distribution of shoal facies in the study area.

Abstract With the vigorous development of the energy Internet, all kinds of user information data are increasing day by day. How to comprehensively and deeply mine the effective information of users, develop a model to predict the behaviour characteristics of big data users, distinguish customer relationships, and provide an accurate basis for the next behaviour of users for various platforms have become one of the research hotspots of big data analysis of user behaviour. The data is sampled according to the feature vector of power user. The portrait mining of power user is conducted, and the user screening and analysis are conducted by using the measure of decision tree node purity in the model. The decision tree variable of the up–down stopping rule is generated. Then the results of the model and the Logistics model are tested and analysed, which can effectively predict the behaviour of power user. The proposed user strategy based on the characteristics of power consumption behaviour is analysed to verify the effectiveness of the scheme. The example shows that the model has a strong ability to distinguish and good stability than the traditional Logistics model, which can effectively predict the user's behaviour in advance, reduce user complaints, and help enterprises and users to form a long‐term mechanism of mutual benefit and reciprocity, which has a strong practical significance. This paper analyses the panorama of users through power big data technology and proposes a maturity model to evaluate the priority of users' electricity consumption. It emphasises the use of resources and methods provided in the power big data technology package to solve the practical problems of users' electricity consumption, and helps power companies to avoid market risks and improve service levels, which has strong practical significance.

Abstract Objectives In this meta-analysis, we conducted a comparative analysis of the safety and efficacy of hypofractionated and conventional fractionated radiotherapy in individuals who had undergone surgery for breast cancer. Methods This study involved a systematic and independent review of relevant research articles published in reputable databases such as PubMed, Embase, Cochrane Library, and Web of Science. Two investigators conducted the review, which included studies published up to January 3, 2023. The quality of the eligible studies was evaluated and data were extracted using Review Manager software 5.4 (RevMan 5.4) to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Results The analysis comprised 35 studies and encompassed a collective sample of 18,246 individuals diagnosed with breast cancer. We did not find a statistically significant disparity in efficacy between conventional fractionated (CF) radiotherapy and hypofractionated (HF) radiotherapy regarding local recurrence (LR; OR = 0.91, 95% CI: 0.76–1.09, P = 0.30), disease-free survival (DFS; OR = 1.20, 95% CI: 1.01–1.42, P = 0.03), and overall survival (OS; OR = 1.08, 95% CI: 0.93–1.26, P = 0.28). Concerning safety, there was no significant difference between the HF and CF regimens in terms of breast pain, breast atrophy, lymphedema, pneumonia, pulmonary fibrosis, telangiectasia, and cardiotoxicity. However, the HF regimen resulted in lower skin toxicity (OR = 0.43, 95% CI: 0.33—0.55, P

Abstract Retinoid-related orphan receptor gamma t (RORγt) is the lineage-specific transcription factor for T helper 17 (Th17) cells. Our previous study demonstrated that STAT3 likely participates in the activation of RORCE2 (a novel enhancer of the RORγt gene) in Th17 cells. However, the detailed mechanism is still unclear. Here, we demonstrate that both STAT3 and SOX-5 mediate the enhancer activity of RORCE2 in vitro. Deletion of the STAT3 binding site (STAT3-BS) in RORCE2 impaired RORγt expression and Th17 differentiation, resulting in reduced severity of experimental autoimmune encephalomyelitis (EAE). Mechanistically, STAT3 and SOX-5 bind the RORCE2 region and recruit the chromatin remodeling factor BRG1 to remodel the nucleosomes positioned at this region. Collectively, our data suggest that STAT3 and SOX-5 mediate the differentiation of Th17 cells through the induction of BRG1-mediated chromatin remodeling of RORCE2 in Th17 cells.

Abstract Background Malnutrition is a prevalent and major challenge among senior citizens, possibly due to the continual low-grade inflammatory state of the body. A novel inflammatory parameter, the systemic immune-inflammation index (SII), is highly valuable in evaluating and predicting the prognosis of a wide range of diseases. This study aims to explore the significance of the SII in assessing malnutrition in older inpatients. Methods This retrospective study included 500 senior hospitalized patients who met the inclusion and exclusion criteria from the Comprehensive Geriatric Assessment database of the First Hospital of Jilin University. The Mini-Nutritional Assessment (MNA) questionnaire was used to evaluate the nutritional status of patients. The SII was calculated using complete blood counts, and we performed natural logarithm transformation of the SII [ln(SII)]. Multivariable logistic regression analysis was used to identify the association between ln(SII) and malnutrition. To ensure the stability of the findings, a sensitivity analysis was conducted. Results The 500 patients had a mean age of 77.29 ± 9.85 years, and 68.6% were male. In accordance with the MNA, 30.4% of the patients were malnourished or at risk of malnutrition, and patients in this group had considerably greater levels of ln(SII) than patients with adequate nutrition (P

The fine spectral information contained in hyperspectral images (HSI) is combined with rich spatial features to provide feature qualities that serve as distinguishing variables for efficient classification performance. The task's objective is to correctly identify and categorize several object categories in the HSI, such as the ground, flora, water, and buildings, based on their spectral characteristics beneficial for a variety of applications, including mapping minerals, analyzing vegetation, and mapping urban land use. The difficulty of learning new task-specific knowledge from a limited data sample that encourages less training has not been overcome by deep learning models. The capacity of current models to generalize to new tasks on small datasets is still lacking. By learning features that are transferable to facilitate adaptation to novel tasks on small samples, metareinforcement learning (Meta-RL) shows promise in overcoming such difficulties. We proposed a Meta-RL model that decouples task inference to improve metatraining and accelerate metalearning with small HSI labeled samples for efficient classification. The model employs a capsule network for effective cooperation between spectra and spatial bands. To minimize the temporal difference error, the Apex-X Deep Q network parameter update is used to metatrain our model. The proposed model obtains an overall accuracy between 95.85% and 96.78% with computational time between 3207.9 and 7487.9 s for training and validation as well as between 21.57 and 32.98 s for testing. The experimental results prove the competitiveness of the proposed model to existing traditional deep learning, metalearning, and reinforcement learning methods in both classification accuracy and computational cost.

Abstract Wu-tou decoction (WTD), a traditional Chinese medicine prescription, is used to treat rheumatoid arthritis (RA). It works by controlling intestinal flora and its metabolites, which in turn modulates the inflammatory response and intestinal barrier function. Small molecular compounds (SM) and polysaccharides (PS) were the primary constituents of WTD extract. In this work, a model of adjuvant-induced arthritis (AIA) in rats was established and treated with WTD, SM, and PS, respectively. 16S rRNA gene sequencing was used to examine the regulatory impact of the various groups on the disturbance of the gut flora induced by RA. Further, since PS cannot be absorbed into the blood, the influence of PS on the absorption and metabolism of SM was studied by examining their pharmacokinetic (PK) parameters of 23 active components in SM by UPLC-MS/MS. WTD was found to be more effective than PS and SM in alleviating arthritis in AIA rats, which may be related to changes in gut flora. The PK properties of 13 active compounds were altered after PS intervene. Based on the findings, PS may be able to manage the disruption of intestinal microbiota, enhance the intestinal environment of model animals, and hence influence SM absorption and metabolism.

The effective utilization of urban land plays a significant role in achieving the 11th goal focuses on Sustainable cities and communities. China's national special economic parks (NSEP) have undergone a remarkable process of urbanization over the past 40 years, and the land for future development is becoming increasingly scarce. In this study, a convolutional neural network with attention mechanisms was proposed for extracting built-up area boundaries of NSEP; Additionally, the urban land use efficiency (ULUE) was estimated by combining multi-source nighttime light image and statistical data from yearbooks. Furthermore, we integrate a data-driven model for predicting ULUE. The empirical research involves a comprehensive analysis of the spatial characteristics of urban land expansion by using the Taylor index and spatial analysis. This study reveals the following findings: ① Convolutional Neural Networks based on attention mechanisms can achieve high-precision extraction of urban boundaries with a Kappa value exceeding 0.92; ②There is a significant positive correlation between the brightness of nighttime light imagery and the GDP of the secondary and tertiary industries; ③ ULUE exhibits evident dependence on urban scale; ④ The density-nuclear density curve features of ULUE with the peak gradually decreasing, which indicates a continuous expansion of the distribution range of land use efficiency. This research framework aims to provide the support for the scientific management and sustainable utilization of urban land while serving as empirical reference for future policy formulation and planning.

Solanum pinnatisectum exhibits strong resistance to late blight caused by Phytophthora infestans but only an incomplete genome assembly based on short Illumina reads has been published. In this study, we generated the first chromosome-level draft genome for the wild-type potato species S. pinnatisectum in China using Oxford Nanopore technology sequencing and Hi-C technology. The high-quality assembled genome size is 664 Mb with a scaffold N50 value of 49.17 Mb, of which 65.87% was occupied by repetitive sequences, and predominant long terminal repeats (42.51% of the entire genome). The genome of S. pinnatisectum was predicted to contain 34,245 genes, of which 99.34% were functionally annotated. Moreover, 303 NBS-coding disease resistance (R) genes were predicted in the S. pinnatisectum genome to investigate the potential mechanisms of resistance to late blight disease. The high-quality chromosome-level reference genome of S. pinnatisectum is expected to provide potential valuable resources for intensively and effectively investigating molecular breeding and genetic research in the future.

BackgroundThis study aimed to investigate whether quantitative radiomics features extracted from conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) of primary breast lesions can help noninvasively predict axillary lymph nodes metastasis (ALNM) in breast cancer patients.MethodA total of 111 breast cancer patients with 111 breast lesions were prospectively enrolled. All the included patients received presurgical CUS screening and CEUS examination and were randomly assigned to the training and validation sets at a ratio of 7:3 (n = 78 versus 33). Radiomics features were respectively extracted based on CUS and CEUS using the PyRadiomics package. The max-relevance and min-redundancy (MRMR) and least absolute shrinkage and selection operator (LASSO) analyses were used for feature selection and radiomics score calculation in the training set. The variance inflation factor (VIF) was performed to check the multicollinearity among selected predictors. The best performing model was selected to develop a nomogram using binary logistic regression analysis. The calibration and clinical utility of the nomogram were assessed.ResultsThe model combining CUS reported ALN status, CUS radiomics score (CUS-radscore) and CEUS radiomics score (CEUS-radscore) exhibited the best performance. The areas under the curves (AUC) of our proposed nomogram in the training and external validation sets were 0.845 [95% confidence interval (CI), 0.739-0.950] and 0.901 (95% CI, 0.758-1). The calibration curves and decision curve analysis (DCA) demonstrated the nomogram’s robust consistency and clinical utility.ConclusionsThe established nomogram is a promising prediction tool for noninvasive prediction of ALN status. The radiomics features based on CUS and CEUS can help improve the predictive performance.

The crash severity analysis is of significant importance in traffic crash prevention and emergency resource allocation. A range of innovations offers potential traffic crash severity prediction models to improve road safety. However, the semantic information inherent in traffic crash data, which is crucial in enabling a deeper understanding of its underlying factors and impacts, has yet to be fully utilized. Moreover, traffic crash data are commonly characterized by a small sample size, which leads to sample imbalance problem resulting in prediction performance decline. To tackle these problems, we propose a semantic understanding-based data-enhanced double-layer stacking model, named EnLKtreeGBDT, for crash severity prediction. Specifically, to fully leverage the inherent semantic information within traffic crash data and analyze the factors influencing crashes, we design a semantic enhancement module for multi-dimensional feature extraction. This module aims to enhance the understanding of crash semantics and improve prediction accuracy. Then we introduce a data enhancement module that utilizes data denoising and migration techniques to address the challenge of data imbalance, reducing the prediction model's dependence on large sample crash data. Furthermore, we construct a two-layer stacking model that combines multiple linear and nonlinear classifiers. This model is designed to augment the capability of learning linear and nonlinear mixed relationships, thereby improving the accuracy of predicting the severity of crashes on complex urban roads. Experiments on historical datasets of UK road safety crashes validate the effectiveness of the proposed model, and superior performance of prediction precision is achieved compared with the state-of-the-arts. The ablation experiments on both semantic and data enhancement modules further confirm the indispensability of each module in the proposed model.

Limited by the dynamic range of the detector, saturation artifacts usually occur in optical coherence tomography (OCT) imaging for high scattering media. The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images. We proposed a deep learning-based inpainting method of saturation artifacts in this paper. The generation mechanism of saturation artifacts was analyzed, and experimental and simulated datasets were built based on the mechanism. Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs. The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility, strong generalization, and robustness.

Introduction:The diagnostic accuracy of traditional imaging examination in predicting ypT stage of rectal cancer after neoadjuvant therapy is significantly reduced, which would affect patients’ subsequent treatment choices. This study aimed to investigate the use of endorectal shear wave elastography (SWE) for diagnosing ypT0 stage of rectal cancer after neoadjuvant chemoradiotherapy (nCRT).Methods:Sixty patients with rectal cancer were prospectively recruited in this study. Data on endorectal ultrasound (ERUS) and SWE parameters were collected before nCRT and 6–8 weeks after nCRT. Postoperative pathological results were the gold standard for evaluating the diagnostic accuracy of SWE and ERUS in predicting the ypT0 stage of rectal cancer after nCRT. Receiver operating characteristic (ROC) curve analysis was used to determine the cut-off values of the SWE parameters that best corresponded to the ypT0 stage and analyze the sensitivity, specificity, and accuracy.Results:The diagnostic accuracies of using ERUS to predict the ypT and ypT0 stages of rectal cancer after nCRT were 58.1% (18/31) and 64.3% (9/14), respectively. The ROC curve was constructed with the lesion’s Emean, Emean corrected (EC), Emean difference (ED), Emean corrected differencede (ECD), Emean descendding rate (EDR) and Emean corrected descendding rate (ECDR) values after nCRT, the cut-off values of diagnosing the ypT0 stage were 64.40 kPa, 55.45 kPa, 72.55 kPa, 73.75 kPa, 50.15%, and 55.93%, respectively; the area under the curve (AUC) for diagnosing the ypT0 stage was 0.924, 0.933, 0.748, 0.729, 0.857 and 0.861, respectively. The EC value showed the best diagnostic performance.Conclusion:SWE could improve the accuracy of conventional ERUS in diagnosing the ypT0 stage of rectal cancer after nCRT. It is expected to become a new method to help predict pathological complete responses in clinical practice and provide new evidence for the watch-and-wait approach.

Glyphosate, ranked as one of the most widely used herbicides in the world, has raised concerns about its potential disruptive effects on sex hormones. However, limited human evidence was available, especially for children and adolescents. The present study aimed to examine the associations between exposure to glyphosate and sex hormones among participants aged 6–19 years, utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2013 and 2016. Children and adolescents who had available data on urinary glyphosate, serum sex steroid hormones, including testosterone (TT), estradiol (E2) and sex hormone binding globulin (SHBG), and covariates were selected. Additionally, the ratio of TT to E2 (TT/E2) and the free androgen index (FAI), which was calculated using TT/SHBG, were also included as sex hormone indicators. Survey regression statistical modeling was used to examine the associations between urinary glyphosate concentration and sex hormone indicators by age and sex group. Among the 964 participants, 83.71% had been exposed to glyphosate (>lower limit of detection). The survey regression revealed a marginally negative association between urinary glyphosate and E2 in the overall population, while this association was more pronounced in adolescents with a significant trend. In further sex-stratified analyses among adolescents, a significant decrease in E2, FAI, and TT (p trend

The incidence of cerebral herniation caused by intratumoral hemorrhage (ITH) in cystic oligodendroglioma (COD) is exceedingly rare. This study presents a case of cerebral herniation subsequent to cystic oligodendroglioma (COD) and sudden intratumoral hemorrhage. Following initial emergency treatment and evaluation, we successfully circumvented the solid component of the tumor and proceeded with cystic puncture and external drainage to prevent the incidence of brain herniation and mitigate the severity of associated symptoms. Based on preoperative examination results, the cystic glioma was successfully resected, and the patient experienced an uneventful recovery. According to the pathological findings, the oligodendroglioma was classified as World Health Organization (WHO) grade III. The treatment efficacy was comparable to cases of the same pathological grade, in which neither intratumoral hemorrhage nor cerebral hernia was observed.

Summary: Hepatitis B virus (HBV) infection generally elicits weak type-I interferon (IFN) immune response in hepatocytes, covering the regulatory effect of IFN-stimulated genes. In this study, low level of IFN-stimulated gene 12a (ISG12a) predicted malignant transformation and poor prognosis of HBV-associated hepatocellular carcinoma (HCC), whereas high level of ISG12a indicated active NK cell phenotypes. ISG12a interacts with TRIM21 to inhibit the phosphorylation activation of protein kinase B (PKB, also known as AKT) and β-catenin, suppressing PD-L1 expression to block PD-1/PD-L1 signaling, thereby enhancing the anticancer effect of NK cells. The suppression of PD-1-deficient NK-92 cells on HBV-associated tumors was independent of ISG12a expression, whereas the anticancer effect of PD-1-expressed NK-92 cells on HBV-associated tumors was enhanced by ISG12a and treatments of atezolizumab and nivolumab. Thus, tumor intrinsic ISG12a promotes the anticancer effect of NK cells by regulating PD-1/PD-L1 signaling, presenting the significant role of innate immunity in defending against HBV-associated HCC.

Abstract. Background:. This study aimed to determine the reasons for conversion and elucidate the safety and efficacy of transition to tenofovir alafenamide/emtricitabine/bictegravir sodium (TAF/FTC/BIC) in highly active antiretroviral therapy (HAART)-experienced HIV-infected patients in real-world settings. Methods:. We conducted a retrospective cohort study. The treatment conversion rationales, safety, and effectiveness in 1684 HIV-infected patients with previous HAART experience who switched to TAF/FTC/BIC were evaluated at Beijing Ditan Hospital from September 2021 to Auguest 2022. Results:. Regimen simplification (990/1684, 58.79%) was the most common reason for switching, followed by osteoporosis or osteopenia (375/1684, 22.27%), liver dysfunction (231/1684, 13.72%), decline in tenofovir alafenamide/emtricitabine/elvitegravir/cobicistat (TAF/FTC/EVG/c) with food restriction (215/1684, 12.77%), virological failure (116/1684, 6.89%), and renal dysfunction (90/1684, 5.34%). In patients receiving non-nucleotide reverse transcriptase inhibitors (NNRTI)-containing regimens, lipid panel changes 1 year after switching indicated a difference of 3.27 ± 1.10 mmol/L vs. 3.40 ± 1.59 mmol/L in triglyceride (P = 0.014), 4.82 ± 0.74 mmol/L vs. 4.88 ± 0.72 mmol/L in total cholesterol (P = 0.038), 3.09 ± 0.70 mmol/L vs. 3.18 ± 0.66 mmol/L in low-density lipoprotein (P

ABSTRACTRapid and accurate estimation of forest biomass are essential to drive sustainable management of forests. Field-based measurements of forest above-ground biomass (AGB) can be costly and difficult to conduct. Multi-source remote sensing data offers the potential to improve the accuracy of modelled AGB predictions. Here, four machine learning methods: Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Classification and Regression Trees (CART), and Minimum Distance (MD) were used to construct forest AGB models of Taiyue Mountain forest, Shanxi Province, China using single and multi-sourced remote sensing data and the Google Earth Engine platform. Results showed that the machine learning method that most accurately predicted AGB were GBDT and spectral index for coniferous (R2 = 0.99; RMSE = 65.52 Mg/ha), broadleaved (R2 = 0.97; RMSE = 29.14 Mg/ha), and mixed-species (R2 = 0.97; RMSE = 81.12 Mg/ha) forest types. Models constructed using bivariate variable combinations that included the spectral index improved the AGB estimation accuracy of mixed-species (R2 = 0.99; RMSE = 59.52 Mg/ha) forest types and reduced slightly the accuracy of coniferous (R2 = 0.99; RMSE = 101.46 Mg/ha) and broadleaved (R2 = 0.97; RMSE = 37.59 Mg/ha) forest AGB estimation. Overall, parameterizing machine learning algorithms with multi-source remote sensing variables can improve the prediction accuracy of mixed-species forests.

Abstract Previous research on global urban land expansion has primarily focused on accommodating the growing population without adequately considering the trade-offs between urban land and ecological services. Consequently, it is important to investigate the effect of this expansion on the ecological service system, while also examining the potential trade-offs between population growth and available urban land. Here, we quantify how different global land expansion options contribute to reconciling global population changes and to compliance with the UN Sustainable Development Goal 11 on sustainable cities and human settlements. Using an integrated framework for projecting global land consumption with the trade-off strategy between global land expansion and population under shared socioeconomic pathways (SSPs), we aim to bridge the knowledge gap in this area. The results of our study suggest that implementing a trade-off strategy between global land expansion and population growth can successfully reduce the levels of global land consumption in the future. Under the SSP1 scenario, for instance, our findings indicate that implementing trade-off policies can significantly reduce land consumption while increasing carbon sinks and protecting the global ecological service system. Specifically, converting land to forest or grassland can help decrease land consumption by 8.07% by the end of the 21st century. These insights can be valuable in designing land use policies that incorporate data-based solutions and address the challenges of sustainable urban development while also accommodating population growth.

Abstract It is well established that nighttime light brightness value, which is measured from satellites, correlates with economic prosperity across the globe. Researchers have diverged over whether economic factors cluster in coastal areas or move to interior areas. By using nighttime light data and applying the random forest algorithm to measure the proportion of global “near regions” GDP, it was seen that global GDP decreased from 67.25% in 2000 to 63.02% in 2018. This research reveals that under the continuous promotion of economic globalization, there is still a spatial imbalance of economic development between global “near regions” and “far regions”; however, economic factors are gradually shifting to interior areas and forming a “coastal remoteness” evolution pattern. Within the intercontinental range, there are obvious differences in the evolution patterns and spatial structure of economic development between the sub-regions. The reduction of overseas transportation costs and diseconomies of scale are the primary reasons for the evolution of “coastal remoteness” in global economic development. Our findings can facilitate future policymaking and the management of global coastal and interior areas, as well as establish new horizons for relevant research topics within the context of land and marine-coordinated development.

Abstract This study aimed to evaluate the safety of dump slopes in high-altitude areas subjected to severe dry–wet cycles. The slope of No. 1 and No. 2 in-service dumps in limestone mining areas for cement in high-altitude mining areas is taken as the research object. The unsaturated soil shear strength and matrix suction distribution equations were imported based on the unsaturated–saturated seepage theory. Therefore, the evolution characteristics of the unsaturated–saturated seepage field in the dump are analyzed by numerical calculation, and the safety state of the dump slope is evaluated. The results indicated the following rules: under the action of four dry–wet cycles, the surface soil of the dump slope changes from an unsaturated state to a saturated state. Furthermore, with the increase in the times of the dry–wet cycle, the maximum vertical displacement of the No. 1 and No. 2 dump slopes increased. The numerical calculations of the maximum cumulative vertical displacement of the slope were consistent with the actual monitoring data. The factor of safety of the dump slope decreased continuously with the increase in the times of dry–wet cycles. Nevertheless, it still met the safety and stability standards. It was concluded that the slope of the in-service dump remains stable after enduring four severe cycles of dry–wet.

Objectives: To investigate gadolinium deposition in the liver and brain in a rat model with liver fibrosis (LF) after intravenous administration of gadoxetate disodium (GD) and the histological effects of gadolinium deposition in the liver and brain. Methods: Adult male Sprague–Dawley rats were randomly assigned to one of the three groups: 1) LF group received intraperitoneal injection of carbon tetrachloride (CCl4) for 9 weeks alone; 2) LF&GD group received CCl4 and intravenous administration of GD (for 5 consecutive days); 3) GD group received olive oil and GD. Seven days after the final injection of GD, the deep cerebellar nuclei (DCN) and liver were excised to determine gadolinium concentrations via inductively coupled plasma mass spectrometry, and histologic staining was performed. Bonferroni's post-hoc test and Wilcoxon rank sum test were used to compare the differences between the three groups. Results: The concentrations of retained gadolinium in the liver in the LF&GD group (2.18 ± 0.44 μg/g) were significantly greater compared to the LF group (0.02 ± 0.01 μg/g, P

BackgroundDue to the widespread use of imaging techniques, the detection rate of early-stage lung cancer has increased. Video-assisted thoracoscopic surgery (VATS) sublobectomy has emerged as a prominent alternative to lobectomy, offering advantages like reduced resection range, better preservation of lung function, and enhanced postoperative quality of life. However, sublobectomy is more intricate than lobectomy, necessitating a higher level of surgical proficiency and anatomical understanding.MethodsThree electronic databases were searched to capture relevant studies from January 2016 to March 2023, which related to the application of three-dimensional(3D) technology in VATS sublobectomy.ResultsCurrently, clinical departments such as orthopedics, hepatobiliary surgery, and urology have started using 3D technology. This technology is expected to be widely used in thoracic surgery in future. Now 3D technology assists in preoperative planning, intraoperative navigation and doctor-patient communication.Conclusion3D technologies, instrumental in locating pulmonary nodules and identifying variations in target lung segmental vessels and bronchi, play pivotal roles in VATS sublobectomy, especially in preoperative planning, intraoperative navigation, and doctor-patient communication. The limitations of 3D technology in clinical application are analyzed, and the future direction of existing 3D technology development is prospected.

BackgroundMalnutrition is an often unrecognized problem, but it is common in older patients and leads to adverse outcomes.AimsThe purpose of this study is to analyze the prevalence of the risk of undernutrition in elderly patients and the correlation between CGA and nutritional status, and to determine the nutritional status of elderly patients.MethodsThis is a real-world cross-sectional study of continuously enrolled elderly patients aged 65 years or older with a complete CGA database. CGA inventory was prepared by compiling and screening general information, body composition and blood biochemical results. MNA was also conducted for each elderly patient to screen for malnutrition. A multivariable logistic regression analysis was used to determine the association between the CGA and nutritional assessment.ResultThe average age of the 211 selected elderly patients (160 men and 51 women) was 79.60 ± 9.24 years, and their ages ranged from 65 to 96 years. After controlling for confounders, patients with a history of PUD (OR = 2.353, p = 0.044), increased ADLs & IADLs scores (OR = 1.051, p = 0.042) or GDS scores (OR = 6.078, p

One patient with rifampin-resistant tuberculosis underwent emergency left pneumonectomy and thoracic gauze packing for hemoptysis due to recurrent hemoptysis after transcatheter arterial embolization. Vital signs were maintained by mechanical ventilation and medication. Tracheotomy and anti-tuberculosis treatment were performed. After half a year of follow-up, the patient's condition was stable.

Accurate bike-sharing demand prediction is crucial for bike allocation rebalancing and station planning. In bike-sharing systems, the bike borrowing and returning behavior exhibit strong spatio-temporal characteristics. Meanwhile, the bike-sharing demand is affected by the arbitrariness of user behavior, which makes the distribution of bikes unbalanced. These bring great challenges to bike-sharing demand prediction. In this study, a usage pattern similarity-based dual-network for bike-sharing demand prediction, called FF-STGCN, is proposed. Inter-station flow features and similar usage pattern features are fully considered. The model includes three modules: multi-scale spatio-temporal feature fusion module, bike usage pattern similarity learning module, and bike-sharing demand prediction module. In particular, we design a multi-scale spatio-temporal feature fusion module to address limitations in multi-scale spatio-temporal accuracy. Then, a bike usage pattern similarity learning module is constructed to capture the underlying correlated features among stations. Finally, we employ a dual network structure to integrate inter-station flow features and similar usage pattern features in the bike-sharing demand prediction module to realize the final prediction. Experiments on the Citi Bike dataset have demonstrated the effectiveness of our proposed model. The ablation experiments further confirm the indispensability of each module in the proposed model.

The purpose of knowledge embedding is to extract entities and relations from the knowledge graph into low-dimensional dense vectors, in order to be applied to downstream tasks, such as connection prediction and intelligent classification. Existing knowledge embedding methods still have many limitations, such as the contradiction between the vast amount of data and limited computing power, and the challenge of effectively representing rare entities. This article proposed a knowledge embedding learning model, which incorporates a graph attention mechanism to integrate key node information. It can effectively aggregate key information from the global graph structure, shield redundant information, and represent rare nodes in the knowledge base independently of its own structure. We introduce a relation update layer to further update the relation based on the results of entity training. The experiment shows that our method matches or surpasses the performance of other baseline models in link prediction on the FB15K-237 dataset. The metric Hits@1 has increased by 10.9% compared to the second-ranked baseline model. In addition, we conducted further analysis on rare nodes with fewer neighborhoods, confirming that our model can embed rare nodes more accurately than the baseline models.

The transformation from authoritative to user-generated data landscapes has garnered considerable attention, notably with the proliferation of crowdsourced geospatial data. Facilitated by advancements in digital technology and high-speed communication, this paradigm shift has democratized data collection, obliterating traditional barriers between data producers and users. While previous literature has compartmentalized this subject into distinct platforms and application domains, this review offers a holistic examination of crowdsourced geospatial data. Employing a narrative review approach due to the interdisciplinary nature of the topic, we investigate both human and Earth observations through crowdsourced initiatives. This review categorizes the diverse applications of these data and rigorously examines specific platforms and paradigms pertinent to data collection. Furthermore, it addresses salient challenges, encompassing data quality, inherent biases, and ethical dimensions. We contend that this thorough analysis will serve as an invaluable scholarly resource, encapsulating the current state-of-the-art in crowdsourced geospatial data, and offering strategic directions for future interdisciplinary research and applications across various sectors.

ABSTRACT The absence of a hepatitis B virus (HBV) infection system has constrained the study of the viral life cycle and the development of antiviral drugs. We previously established a hepatocellular carcinoma cell line, HLCZ01, that can support the entire life cycle of HBV. To further optimize the model, we compared the kinetic process of HBV infection in HLCZ01 and HepG2-NTCP cells and found that HLCZ01 cells were more conducive to mimic the long-term stable infection of HBV in the natural state. By comparing the composition of the progeny virus and the differences in gene expression profiles between these two types of cells, we were able to explore the factors affecting the efficiency of virus infection. We built an experimental platform for human liver chimeric mice and established a standard surgical procedure. By transplanting HBV-infected HLCZ01 cells into mouse liver, which can be used instead of primary human hepatocytes to establish chimeric mice, this animal model can continuously produce viral particles. The establishment of these two models will facilitate the exploration of the mechanism of persistent HBV infection, the understanding of host‒virus interactions, and the determination of new targets for chronic hepatitis B therapy. IMPORTANCE Approximately 257 million people worldwide have been infected with hepatitis B virus (HBV), and HBV infection can cause chronic hepatitis, cirrhosis, and even liver cancer. The lack of suitable and effective infection models has greatly limited research in HBV-related fields for a long time, and it is still not possible to discover a method to completely and effectively remove the HBV genome. We have constructed a hepatocellular carcinoma cell line, HLCZ01, that can support the complete life cycle of HBV. This model can mimic the long-term stable infection of HBV in the natural state and can replace primary human hepatocytes for the development of human liver chimeric mice. This model will be a powerful tool for research in the field of HBV.

ObjectiveThe study aimed to use supervised machine learning models to predict the length and risk of prolonged hospitalization in PLWHs to help physicians timely clinical intervention and avoid waste of health resources.MethodsRegression models were established based on RF, KNN, SVM, and XGB to predict the length of hospital stay using RMSE, MAE, MAPE, and R2, while classification models were established based on RF, KNN, SVM, NN, and XGB to predict risk of prolonged hospital stay using accuracy, PPV, NPV, specificity, sensitivity, and kappa, and visualization evaluation based on AUROC, AUPRC, calibration curves and decision curves of all models were used for internally validation.ResultsIn regression models, XGB model performed best in the internal validation (RMSE = 16.81, MAE = 10.39, MAPE = 0.98, R2 = 0.47) to predict the length of hospital stay, while in classification models, NN model presented good fitting and stable features and performed best in testing sets, with excellent accuracy (0.7623), PPV (0.7853), NPV (0.7092), sensitivity (0.8754), specificity (0.5882), and kappa (0.4672), and further visualization evaluation indicated that the largest AUROC (0.9779), AUPRC (0.773) and well-performed calibration curve and decision curve in the internal validation.ConclusionThis study showed that XGB model was effective in predicting the length of hospital stay, while NN model was effective in predicting the risk of prolonged hospitalization in PLWH. Based on predictive models, an intelligent medical prediction system may be developed to effectively predict the length of stay and risk of HIV patients according to their medical records, which helped reduce the waste of healthcare resources.

Dynamic gravity field measurement based on the cold atom absolute gravity measurement system has important applications in geological exploration, gravity field mapping and other fields. The inertial stabilized platform is the key component of the dynamic cold atom absolute gravity measurement system, which can isolate the interference of carrier angle motion and keep the atomic gravimeter probe in the horizontal attitude during the measurement process. In this paper, according to the dynamic measurement requirements of atomic gravimeter, a high-precision two-axis inertial stabilized platform system is designed. The relationship between attitude angle and gravity measurement error is analyzed, and the stability of the system is enhanced by lead-lag method. Then the static vertical vibration power spectrum of the platform is measured to consider its influence on dynamic gravity measurement. Finally, a dynamic gravity test experiment was conducted in the Yellow Sea to verify the attitude control accuracy of the platform, and the attitude data of the platform under different heading were evaluated. The attitude standard deviation of the platform was better than 4 × 10−5 rad, and the absolute gravity standard deviation of the linear round-trip measurement reached 1.49 mGal. The experimental data show that the inertial stabilized platform can meet the dynamic measurement requirements of the cold atom gravimeter.

Abstract The pBRDF model is able to relate the properties of target materials to the polarization information of incident and reflected light, and is an important basis for obtaining polarization information of targets in space. It is an important basis for obtaining target polarization information and polarization detection of space targets. P-G model is the first strictly pBRDF model officially released, but there are still deficiencies. In this paper, we first analyze the assumption framework of the P-G model, derive the imperfections in the framework through the analysis of the assumption framework, and add scattering and phase function to enhance the existing model. On the basis of the existing P-G model and parameter inversion, the output results of the model are compared with the experimental data through simulation, and the results show that the relative error of the target's linear polarizability is reduced under the improved model, which proves the accuracy and precision of the improved model.

Abstract There is uncertainty regarding the benefits and drawbacks of various radiation protocols for the treatment of left-sided breast cancer. To address this issue, we conducted a Bayesian network analysis. First, we searched several electronic databases for eligible literature. Next, we pooled the data from twelve studies concerning three-dimensional conformal radiation therapy (3D-CRT), intensity modulated radiation therapy (IMRT), and volumetric modulated arc therapy (VMAT), combined with either deep inspiratory breath-holding (DIBH) or free-breathing (FB) modalities. The integrated cardiac and pulmonary dosimetric indexes for all included treatments were compared using Bayesian networks. A direct meta-analysis indicated that for the two methods of 3D-CRT and IMRT, DIBH technology was more effective than FB in reducing the radiation dose to the heart and lungs. Additionally, according to the network results, DIBH was superior to FB in all six treatment options, regardless of whether the plan was 3D-CRT, IMRT, or VMAT. Besides, the combined data indicated that the FB-3D-CRT regimen had the weakest dosimetric advantage of all the treatments. Excluding FB-3D-CRT, each of the other five treatments had its own specific benefits. This is the first Bayesian study of several radiotherapy regimens for breast cancer patients on the left side, and the findings can be used to select appropriate radiotherapy programs for breast cancer patients.