Spatio-temporal differentiation characteristics and the influencing factors of PM2.5 emissions from coal consumption in Central Plains Urban Agglomeration.

Central Plains urban agglomeration (CPUA) had developed rapidly, but its air pollution was also serious. Despite advances in study on China's PM2.5 emissions from coal consumption (CC), the differentiation characteristics and the affecting variables of PM2.5 in CPUA required further investigation. This paper computed the PM2.5 emissions of each city from 2000 to 2020 using CC data from CPUA, evaluated its spatio-temporal fluctuation characteristics using the spatial autocorrelation and analyzed its influencing factors by combining various indicators through the spatial Durbin model (SDM). The results verified that: (1) There was a trend of rapid increase of PM2.5 emissions from CC; (2) The Moran's I of the PM2.5 emissions from CC showed a significant agglomeration effect; (3) PM2.5 emissions from CC had a strong spillover effect. The recommendations were in this following: (1) The urban pollution regulation and the pace of industrial green transformation should be Strengthened; (2) Close linkages between cities should be established and attention should be paid to pollution management; (3) The spillover of PM2.5 emissions from CC should be lessened and development of environmental governance technology should be enhanced.

Evaluating tooth segmentation accuracy and time efficiency in CBCT images using artificial intelligence: A systematic review and Meta-analysis.

OBJECTIVES: This systematic review and meta-analysis aimed to assess the current performance of artificial intelligence (AI)-based methods for tooth segmentation in three-dimensional cone-beam computed tomography (CBCT) images, with a focus on their accuracy and efficiency compared to those of manual segmentation techniques. DATA: The data analyzed in this review consisted of a wide range of research studies utilizing AI algorithms for tooth segmentation in CBCT images. Meta-analysis was performed, focusing on the evaluation of the segmentation results using the dice similarity coefficient (DSC). SOURCES: PubMed, Embase, Scopus, Web of Science, and IEEE Explore were comprehensively searched to identify relevant studies. The initial search yielded 5642 entries, and subsequent screening and selection processes led to the inclusion of 35 studies in the systematic review. Among the various segmentation methods employed, convolutional neural networks, particularly the U-net model, are the most commonly utilized. The pooled effect of the DSC score for tooth segmentation was 0.95 (95 %CI 0.94 to 0.96). Furthermore, seven papers provided insights into the time required for segmentation, which ranged from 1.5 s to 3.4 min when utilizing AI techniques. CONCLUSIONS: AI models demonstrated favorable accuracy in automatically segmenting teeth from CBCT images while reducing the time required for the process. Nevertheless, correction methods for metal artifacts and tooth structure segmentation using different imaging modalities should be addressed in future studies. CLINICAL SIGNIFICANCE: AI algorithms have great potential for precise tooth measurements, orthodontic treatment planning, dental implant placement, and other dental procedures that require accurate tooth delineation. These advances have contributed to improved clinical outcomes and patient care in dental practice.

Enantioselectivity regulation of antibody against chiral herbicide metolachlor based on interaction at chiral center.

Enantioselective antibodies have emerged as great potential biomaterials in the fields of immunoassays and chiral separation. However, cross-reactivity of antibodies to the distomer may severely restrict the application. Comprehending the interaction mechanism between antibodies and enantiomers could be beneficial to produce superior enantioselective antibodies. In this study, a pair of recombinant antibodies (RAbs) against metolachlor enantiomers at chiral carbon (αSS-MET and αSR-MET) were generated and characterized. The αSS-MET-RAb and αSR-MET-RAb showed comparable sensitivity and specificity to the parental monoclonal antibodies by icELISA, with IC50 values of 3.45 and 223.77 ng/mL, respectively. Moreover, the complex structures of RAbs and corresponding eutomer were constructed and analyzed, and site-specific mutagenesis was utilized to verify the reliability of the enantioselective mechanism elucidated. It demonstrated that the strength of the interaction between the chiral center region of eutomer and the antibody was the key factor for the enantioselectivity of antibody. Increasing this interaction could limit the conformational adjustment of the distomer in a specific chiral recognition cavity, thus decreasing the affinity of the antibody to the distomer. This work provided the in-depth analysis of enantioselective mechanism for two RAbs and paved the way to regulate antibody enantioselective performance for immunoassays of chiral compounds.

Research on a Critical Link Discovery Method for Network Security Situational Awareness.

Network security situational awareness (NSSA) aims to capture, understand, and display security elements in large-scale network environments in order to predict security trends in the relevant network environment. With the internet's increasingly large scale, increasingly complex structure, and gradual diversification of components, the traditional single-layer network topology model can no longer meet the needs of network security analysis. Therefore, we conduct research based on a multi-layer network model for network security situational awareness, which is characterized by the three-layer network structure of a physical device network, a business application network, and a user role network. Its network characteristics require new assessment methods, so we propose a multi-layer network link importance assessment metric: the multi-layer-dependent link entropy (MDLE). On the one hand, the MDLE comprehensively evaluates the connectivity importance of links by fitting the link-local betweenness centrality and mapping entropy. On the other hand, it relies on the link-dependent mechanism to better aggregate the link importance contributions in each network layer. The experimental results show that the MDLE has better ordering monotonicity during critical link discovery and a higher destruction efficacy in destruction simulations compared to classical link importance metrics, thus better adapting to the critical link discovery requirements of a multi-layer network topology.

Boosting oxygen reduction durability by embedding Co9S8 nanoparticles into Co single atoms anchored porous carbon frameworks.

Developing an efficient and low-cost oxygen reduction electrocatalyst is essential for the application of aqueous zinc-air batteries (ZABs). Herein, we report a facile adsorption-confined pyrolysis strategy to fabricate the hybrid electrocatalyst (denoted as Co9S8/CoSA-PC) by embedding Co9S8 nanoparticles into Co single atoms (Co-SAs) anchored porous carbon sheets for boosting oxygen reduction reaction (ORR) durability. In this strategy, the Co2+ ions are first absorbed into oxygen-rich porous carbon nanosheets and further form the Co-SAs with the help of thiourea in the following pyrolysis procedure, which is believed to be able to confine the generated Co9S8 nanoparticles into carbon frameworks due to their interface interaction. Benefiting from the synergistic effect of different components, the obtained Co9S8/CoSA-PC electrocatalyst for ORR exhibits outstanding catalytic activity with a half-wave potential of 0.82 V and a distinguished long-term durability with a current retention of 80 % after cycling 80 h under alkaline conditions, which is superior to commercial Pt/C. Moreover, the assembled ZABs with Co9S8/CoSA-PC as cathodic catalyst deliver a high specific capacity of 764 mAh gZn-1 at 10 mA cm-2 and the outstanding peak power density of up to 221.4 mW cm-2. This work provides a novel structure design strategy to prepare transition metal sulfide-based electrocatalysts with superior durability for ORR.

Case report: Metastatic choriocarcinoma in the second trimester of a viable pregnancy with successful delivery and outcome after chemotherapy.

Metastatic choriocarcinoma during viable pregnancy is rare worldwide, and neonate survival following pregnancy termination in the second trimester is uncommon. Here, we report the successful delivery of a pregnancy by a patient with metastatic choriocarcinoma, who received three courses of etoposide, methotrexate, actinomycin D, cyclophosphamide, and vincristine (EMA-CO) chemotherapy in the second trimester. After multidisciplinary discussions, she was administered paclitaxel and carboplatin (TC) chemotherapy. Regular contractions occurred during her first paclitaxel infusion, and a healthy infant was delivered by cesarean section at 26+4 gestational weeks. Choriocarcinoma was not detected in the placenta. Following delivery of the pregnancy, the patient underwent total treatment comprising one cycle of TC, seven cycles of EMA-CO, and five courses of etoposide, cisplatin, methotrexate, and dactinomycin chemotherapy; her serum level of beta-human chorionic gonadotropin gradually fell after chemotherapy. Uterine and pulmonary metastases shrank, and no distant metastasis or recurrence were found until the eighth course of maintenance treatment with immunotherapy. The patient received periodic chemotherapy for recurrence at the time of publishing this case report. The child was disease-free 15+ months after delivery. Despite serious metastases and complications, metastatic choriocarcinoma diagnosed in the second trimester of pregnancy can be successfully treated with minimal delay by multidisciplinary medical and nursing management.

The impact of market-based environmental regulation on corporate ESG performance: A quasi-natural experiment based on China's carbon emission trading scheme.

At present, there are few studies exploring the impact of market-based environmental regulation on ESG performance based on the perspective of carbon emission trading scheme (CETS). This paper aims to supplement this research field through empirical analysis. Taking Shanghai-Shenzhen A-share listed companies from 2012 to 2022 as the research object, this paper studies the impact of CETS, a market-based environmental regulation tool, on the ESG performance of enterprises by constructing a time-varying DID model and examines the mediating roles of green technology innovation, agency cost and analyst attention. The results show that the implementation of CETS can significantly boost ESG performance, and green technology innovation, agency cost, and analyst attention play a partial intermediary role between the two, while the mediating effects of green total factor productivity and green total factor energy efficiency are not significant. In terms of heterogeneity analysis, the study shows that CETS implementation has a more substantial promotion effect on ESG performance in non-state-owned enterprises, non-politically connected enterprises and non-high-tech enterprises. In this paper, the robustness test was carried out through PSM-DID, placebo test and replacement of explained variables, and the test results further supported the hypothesis in this paper. This study enriched the research on the impact of market-based environmental regulation on ESG from the perspective of CETS. It provided enlightenment for enterprises to improve ESG performance to a strategic level, improve the level of green technology innovation, and the government to implement differentiated environmental governance policies.

Crustal permeability generated through microearthquakes is constrained by seismic moment.

We link changes in crustal permeability to informative features of microearthquakes (MEQs) using two field hydraulic stimulation experiments where both MEQs and permeability evolution are recorded simultaneously. The Bidirectional Long Short-Term Memory (Bi-LSTM) model effectively predicts permeability evolution and ultimate permeability increase. Our findings confirm the form of key features linking the MEQs to permeability, offering mechanistically consistent interpretations of this association. Transfer learning correctly predicts permeability evolution of one experiment from a model trained on an alternate dataset and locale, which further reinforces the innate interdependency of permeability-to-seismicity. Models representing permeability evolution on reactivated fractures in both shear and tension suggest scaling relationships in which changes in permeability ( Δ k ) are linearly related to the seismic moment ( M ) of individual MEQs as Δ k ∝ M . This scaling relation rationalizes our observation of the permeability-to-seismicity linkage, contributes to its predictive robustness and accentuates its potential in characterizing crustal permeability evolution using MEQs.

Bending creep behaviour of various polymer films analysed by surface strain measurement.

Understanding the temporal bending deformation of polymer films is key to designing mechanically durable flexible electronic devices. However, such creep behaviour under persistent bending remains unclear due to a lack of precise and accurate bending strain analysis methods. Herein, we quantitatively analysed the bending creep behaviour of various polymeric films using our developed strain measurement method that can precisely measure surface strain from optical diffraction. The surface strain measurement reveals that bending creep deformation differs depending on the polymer structure. The four-element Burgers model was employed to model the temporal strain increase on the bending surface successfully. By fitting the four-element model to the time course of the measured surface strain, we found that each polymer film has a different threshold surface strain for the appearance of bending creep deformation. Such disparity in the bending creep behaviour can be explained by the difference in strain energy density between the polymer films and their elastic model; polymer films with a small strain energy density difference show small bending creep deformation. The results obtained in this study contribute to the elucidation of the bending creep behaviour of polymer films and the development of flexible electronic devices operated under persistent bending.

Tyrosine kinase inhibitors for radioiodine refractory differentiated thyroid cancer: A systematic review and meta-analysis.

BACKGROUND: The poor overall prognosis of radioiodine refractory thyroid cancer is an inevitable challenge in managing this disease. A series of trials have demonstrated the antitumor activity of tyrosine kinase inhibitors (TKIs) in radioiodine refractory differentiated thyroid cancer (RAIR-DTC). However, the available evidence cannot determine the optimal choice of TKI in RAIR-DTC. METHODS: This study searched PubMed, EMBASE, Cochrane databases, and the ClinicalTrials website. The Cochrane bias risk tool was used to assess the risk of bias, and to evaluate randomized clinical trials (RCT) of RAIR-DTC patients treated with the TKI system. Outcomes, including progression-free survival (PFS), overall survival (OS), and adverse events (AEs) were reported. RESULTS: Seven studies involving 1310 patients with RAIR-DTC was conducted to compare the PFS and OS of various TKI monotherapies with placebo. The results showed that all TKI monotherapies had a statistically significant benefit in terms of PFS compared with placebo, with lenvatinib demonstrating the greatest benefit (hazard ratio [HR] 0.19, 95% credible interval [CrI] 0.14-0.25). In terms of OS, only apatinib (HR 0.42, 95% CrI 0.18-0.97) and anlotinib (HR 0.36, 95% CrI 0.18-0.73) showed statistically significant benefits compared with placebo. TKIs also had a higher incidence of AEs of grade 3 or higher compared with placebo. The findings suggest that lenvatinib may be the preferred TKI for the treatment of RAIR-DTC, although its high incidence of AEs should be considered. The results also indicate that TKI treatment may be similarly effective in RAIR-DTC patients with BRAF or RAS mutations and in those with papillary or follicular subtypes of the disease, regardless of prior TKI treatment. CONCLUSIONS: The results of this meta-analysis suggest that targeted therapy with TKIs may be beneficial for patients with radioiodine-refractory advanced or metastatic differentiated thyroid cancer. Among the TKIs analyzed, lenvatinib appeared to be the most effective at improving PFS, although it also had the highest incidence of AEs. Further research through direct randomized controlled trials is needed to determine the optimal choice of TKI for treating patients with RAIR-DTC. This study is beneficial for formulating patients' treatment plans and guides clinicians' decision-making.

Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters.

OBJECTIVE: To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS: Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT-Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve. RESULTS: Computed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT-Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT-Radiology nomogram was established based on the DECT-Radiology model, which showed the highest net benefit and satisfactory consistency. CONCLUSIONS: The DECT-Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients. CRITICAL RELEVANCE STATEMENT: The DECT-Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression. KEY POINTS: • Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). • The DECT-Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression. • The nomogram may help screen out PDAC patients with high Ki-67 expression.

Propolis alleviates ulcerative colitis injury by inhibiting the protein kinase C - transient receptor potential cation channel subfamily V member 1 - calcitonin gene-related peptide/substance P (PKC-TRPV1-CGRP/SP) signaling axis.

This study investigated the protective effect of water-soluble propolis (WSP) on colonic tissues in ulcerative colitis (UC) and the role of the protein kinase C - transient receptor potential cation channel subfamily V member 1 - calcitonin gene-related peptide/substance P (PKC-TRPV1-CGRP/SP) signaling pathway. Male SD rats were divided into a control group, a UC model group, various WSP groups (Low-WSP, Medium-WSP, and High-WSP) with UC, and a salazosulfapyridine (SASP) positive control group with UC. After UC was established, the WSP and SASP groups were treated with WSP or SASP, respectively, for 7 d. Each day, body weight measurements were obtained, and the disease activity index (DAI) was recorded by observing fecal characteristics and blood in the stool. After the experiment, hematoxylin and eosin (HE) colonic tissue staining was performed to observe pathological changes, western blotting and immunohistochemistry were performed to detect PKC, TRPV1, CGRP, and SP expression in colonic tissues, and laser confocal microscopy was performed to observe the fluorescence colocalization of PKC/TRPV1, TRPV1/CGRP, and TRPV1/SP. HE staining showed significant colonic tissue structure disruption and inflammatory infiltration in the UC group. Western blotting and immunohistochemistry showed that the expression of PKC, TRPV1, CGRP, and SP in the colonic tissues of the UC group increased significantly compared with that of the control group. Compared with the UC group, the expression of PKC, TRPV1, CGRP, and SP in colonic tissues was significantly reduced in the High-WSP, Medium-WSP, and SASP groups. Immunofluorescence showed the colocalized expression of PKC/TRPV1, TRPV1/CGRP, and TRPV1/SP proteins in the colon tissue of the UC group was significantly reduced after WSP and SASP interventions compared with that of the control group. The results suggest that the mechanism of UC alleviation by propolis may inhibit the PKC-TRPV1-CGRP/SP signaling pathway and the release of inflammatory mediators, thus alleviating inflammation.

Active peptides from Eupolyphaga sinensis walker attenuates experimental hyperlipidemia by regulating the gut microbiota and biomarkers in rats with dyslipidemia.

Eupolyphaga sinensis Walker (ESW) is a traditional Chinese medicine formulation used to treat hyperlipidemia. However, the hypolipidemic effect of the active peptides from E. sinensis Walker (APE) is incompletely understood. We studied the hypolipidemic effect of APE and explored the impact of APE on the gut microbiota (GM) in rats suffering from hyperlipidemia. APE was prepared by enzymatic digestion, and its structure was characterized using various methods. The anti-hyperlipidemic activity of APE was assessed using a high-fat diet (HFD)-induced model in zebrafish and rats. In rats, HFD administration caused abnormalities of lipid metabolism and disturbances of the GM and amino acid (AA) profile in plasma. The abundance of bacteria of the phyla Firmicutes and Bacteroides was increased significantly (p < 0.05), and the relative abundance of Lactobacillus species and Clostridium species was decreased significantly (p < 0.05). HFD therapy affected the levels of 12 AAs in vivo: 10 AAs showed increased levels and two AAs had decreased levels (p < 0.05). Similar results were demonstrated in an experiment on fecal microbiota transplantation. APE treatment dose-dependently decreased lipid factors and liver damage (p < 0.05). Sequencing of the 16 S rRNA gene indicated that APE improved the intestinal-flora structure of rats with HL markedly, and increased the relative abundance of Lactobacillus species and Clostridium species. Metabolomics analysis indicated that APE could alter the levels of 10 AAs affected by HFD consumption. Spearman correlation analysis revealed that gamma-aminobutyric acid (GABA) could be a crucial metabolite, and Lactobacillus species and Clostridium species might be important bacteria for the action of APE against hyperlipidemia. We speculate that APE exhibited an anti-hyperlipidemic effect by regulating GABA synthesis in the presence of Lactobacillus species and Clostridium species.

Study on the Biotransformation and Activities of Astragalosides from Astragali Radix In Vitro and In Vivo.

Astragalosides (AGs), as one of the main active ingredients in Astragali Radix (AR), have a series of biological activities. Previous studies have only qualitatively identified the metabolites of AGs in AR, resulting in a lack of quantification. In the present study, the original material was selected from 12 origins based on the levels of 4 AGs by high-performance liquid chromatography (HPLC). The prototype components and metabolites of total AGs (TAGs) in feces, urine, and plasma samples of rats were thoroughly screened and characterized by ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS). The fermentation reaction and metabolites were verified by human fecal TAG fermentation in vitro. The metabolites of AG I, II, and IV transformed by human feces at different times were identified using UHPLC-HRMS, and the partial metabolites were quantified by HPLC. Furthermore, the anti-inflammatory and antioxidant activities of the metabolites were evaluated based on 1,1-diphenyl-2-picrylhydrazyl (DPPH) scavenging in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells in vitro. In total, 13 AGs and 170 metabolites were identified in TAGs as well as in the plasma, urine, and feces of Sprague-Dawley (SD) rats by UHPLC-HRMS, including 28, 36, and 170 metabolites in the plasma, urine, and feces, respectively. The metabolites included the products of deglycosylation, demethylation, hydroxylation, glucuronidation, sulfation, and cysteine-binding reactions. Moreover, the TAG fermentation results in vitro showed great similarity. The human fecal incubation experiments for AG I, II, and IV demonstrated that the metabolic reaction of TAGs mainly occurred in intestinal feces and that deglycosylation, demethylation, and hydroxylation were the main pathways of their metabolism. HPLC quantitative analysis of the transformation solution at different time points showed that AGs were transformed into secondary glycosides [cycloastragenol-6-glucoside (CAG-6-glucoside)] and aglycones [cycloastragenol (CAG)] through a deglycosylation reaction. Analysis of the pharmacological activity showed that the anti-inflammatory and antioxidant activities of the metabolites were associated with the levels of the corresponding aglycones. Further, metabolic profiles of the TAGs were constructed. Overall, this study revealed the metabolic process of AGs in the intestine, providing guidance for the metabolism and pharmacological effects of other saponins.

COMPARISONS BETWEEN DIGITAL-GUIDED AND NONDIGITAL PROTOCOL IN IMPLANT PLANNING, PLACEMENT, AND RESTORATIONS: A SYSTEMATIC REVIEW AND META-ANALYSIS OF RANDOMIZED CONTROLLED TRIALS.

OBJECTIVES: The present study aimed to systematically review the current randomized clinical trials (RCTs) with respect to computer-aided design/computer-aided manufactured (CAD/CAM) techniques in the process of implant planning, placement, and rehabilitation. MATERIALS AND METHODS: Four independent reviewers conducted an electronic and manual literature search using several databases, including the National Library of Medicine (MEDLINE-PubMed), Cochrane Central Register of Controlled Trials (CENTRAL), and EMBASE. Articles were included if they were RCTs involving the interventions regarding the computer-guided impression, placement, and manufacturing process. The outcomes of interest include clinical and patient-reported outcomes and time efficiency. A meta-analysis was conducted to evaluate the time efficiency, pain severity, accuracy of implant placement, and postsurgery marginal bone level. RESULTS: A total of 39 and 25 articles were included in the qualitative and quantitative analysis, respectively. The results of the meta-analysis showed that significantly less time was spent performing the digital impression procedure than the conventional impression (P = .002). In addition, the average adjustment time of the final prosthesis was significantly less than the nondigital fabricated prosthesis (P = .0005). Computer-guided groups reported significantly lower painkiller consumption compared to control groups (P = .03). CONCLUSIONS: Digital impressions and CAD/CAM procedures are time-saving and provide stable and predictable outcomes. Moreover, computer-guided surgery can effectuate an accurate implant placement and less postsurgery discomfort.

Development of a CT radiomics nomogram for preoperative prediction of Ki-67 index in pancreatic ductal adenocarcinoma: a two-center retrospective study.

OBJECTIVES: To develop and validate a contrast-enhanced computed tomography (CECT)-based radiomics nomogram for the preoperative evaluation of Ki-67 proliferation status in pancreatic ductal adenocarcinoma (PDAC). METHODS: In this two-center retrospective study, a total of 181 patients (95 in the training cohort; 42 in the testing cohort, and 44 in the external validation cohort) with PDAC who underwent CECT examination were included. Radiomic features were extracted from portal venous phase images. The radiomics signatures were built by using two feature-selecting methods (relief and recursive feature elimination) and four classifiers (support vector machine, naive Bayes, linear discriminant analysis (LDA), and logistic regression (LR)). Multivariate LR was used to build a clinical model and radiomics-clinical nomogram. The predictive performances of the models were evaluated using area under receiver operating characteristic curve (AUC) and decision curve analysis (DCA). RESULTS: The relief selector and LDA classifier using twelve features built the optimal radiomics signature, with AUCs of 0.948, 0.927, and 0.824 in the training, testing, and external validation cohorts, respectively. The radiomics-clinical nomogram incorporating the optimal radiomics signature, CT-reported lymph node status, and CA19-9 showed better predictive performance with AUCs of 0.976, 0.955, and 0.882 in the training, testing, and external validation cohorts, respectively. The calibration curve and DCA demonstrated goodness-of-fit and improved benefits in clinical practice of the nomogram. CONCLUSIONS: The radiomics-clinical nomogram is an effective and non-invasive computer-aided tool to predict the Ki-67 expression status in patients with PDAC. CLINICAL RELEVANCE STATEMENT: The radiomics-clinical nomogram is an effective and non-invasive computer-aided tool to predict the Ki-67 expression status in patients with pancreatic ductal adenocarcinoma. KEY POINTS: The radiomics analysis could be helpful to predict Ki-67 expression status in patients with pancreatic ductal adenocarcinoma (PDAC). The radiomics-clinical nomogram integrated with the radiomics signature, clinical data, and CT radiological features could significantly improve the differential diagnosis of Ki-67 expression status. The radiomics-clinical nomogram showed satisfactory calibration and net benefit for discriminating high and low Ki-67 expression status in PDAC.

Association between neutrophil-to-albumin ratio and long-term mortality of aneurysmal subarachnoid hemorrhage.

OBJECTIVE: The prognosis of aneurysmal subarachnoid hemorrhage (aSAH) survivors is concerning. The goal of this study was to investigate and demonstrate the relationship between the neutrophil-to-albumin ratio (NAR) and long-term mortality of aSAH survivors. METHODS: A retrospective observational cohort study was conducted at Sichuan University West China Hospital between January 2009 and June 2019. The investigation of relationship between NAR and long-term mortality was conducted using univariable and multivariable Cox regression models. To demonstrate the predictive performance of different biomarkers over time, time-dependent receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA) were created. RESULTS: In total, 3173 aSAH patients were included in this study. There was a strong and continuous relationship between NAR levels and long-term mortality (HR 3.23 95% CI 2.75-3.79, p < 0.001). After adjustment, the result was still significant (adjusted HR 1.78 95% CI 1.49-2.12). Compared with patients with the lowest quartile (< 0.15) of NAR levels, the risk of long-term mortality in the other groups was higher (0.15-0.20: adjusted HR 1.30 95% CI 0.97-1.73; 0.20-0.28: adjusted HR 1.37 95% CI 1.03-1.82; >0.28: adjusted HR 1.74 95% CI 1.30-2.32). Results in survivors were found to be still robust. Moreover, out of all the inflammatory markers studied, NAR demonstrated the highest correlation with long-term mortality. CONCLUSIONS: A high level of NAR was associated with increased long-term mortality among patients with aSAH. NAR was a promising inflammatory marker for long-term mortality of aSAH.

Enhancing fiber-coupling efficiency of beam-to-fiber links in turbulence by spatial non-uniform coherence engineering.

We present a general formula for the fiber-coupling efficiency of various types of non-uniformly correlated beams propagating in a turbulent atmosphere. With it, we calculate the fiber-coupling efficiency of a specific type of non-uniformly correlated beams, Laguerre non-uniformly correlated (LNUC) beams, to investigate how the non-uniform correlation structure plays a role in enhancing the fiber-coupling efficiency. Compared with conventional Gaussian Schell-model beams, the LNUC beams possess better coupling behavior, and the initial coherence length and beam order of such beams can be adjusted to further improve the fiber-coupling efficiency in turbulence. Our results demonstrate how non-uniformly correlated beams can be used for fiber-coupling applications, and demonstrate their intriguing potential for free-space optical communications.

Synthesis of partially coherent beams with a prescribed conjugate-model correlation structure.

Using the sum of two mutually complex conjugate functions as the integral kernel of the necessary and sufficient condition derived by Gori et al., the conjugate-model correlation structure can be constructed. Here, we introduced a general strategy for the synthesis of partially coherent beams with such correlation structures. With it, we described a specific family of such beams, called Hermite conjugate-model beams. Their focusing properties were investigated numerically and experimentally. The experimental results are consistent with the theoretical predictions, and show that the proposed beams possess novel physical features compared with well-known Schell-model beams, such as controllable intensity distributions both at the source and focal plane, which may prove useful in free-space optical communications and optical trapping.