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With the development of wide orientation, wide band, and high-density acquisition and processing technology, the original 3D (time, line number, and track number) seismic data have expanded to two dimensions — the addition of offset distance information and azimuth information, resulting in 5D seismic data. In this paper, we explore three aspects. Identifying microfaults through subazimuth superposition and poststack coherent body techniques; predicting fractures by means of prestack anisotropy, poststack dip, azimuth, coherence, and curvature; and inscribing river channels with pure longitudinal wave near-zero incidence angle reflection information — that is, the exploration of 5D seismic prediction techniques. Field applications in different types of geological bodies in the Lujiabao Depression and Ordos Basin proved that the 5D seismic prediction technology greatly improved the accuracy of reservoir prediction and the degree of implementation of microfaults, effectively guiding the deployment of wells and improving the drilling success rates.

Mechanical properties of the anterior anatomical structures of the eye, such as the cornea and ciliary body, play a key role in the ocular function and homeostasis. However, measuring the biomechanical properties of the anterior ocular structures, especially deeper structures, such as the ciliary body, remains a challenge due to the lack of high-resolution imaging tools. Herein, we implement a mechanical shaker-based high-frequency ultrasound elastography technique that can track the induced elastic wave propagation to assess the linear and nonlinear elastic properties of anterior ocular structures. The findings of this study advance our understanding of the role of anterior ocular structures in the pathogenesis of different ocular disorders, such as glaucoma.

Graphene oxide (GO) is regarded as a promising candidate to construct solar absorbers for addressing freshwater crisis, but the easy delamination of GO in water poses a critical challenge for practical solar desalination. Herein, we improve the stability of GO membranes by a self-crosslinking poly (ionic liquid) (PIL) in a mild condition, which crosslinks neighbouring GO nanosheets without blemishing the hydrophilic structure of GO. By further adding carbon nanotubes (CNTs), the sandwiched GO/CNT@PIL (GCP) membrane displays a good stability in pH = 1 or 13 solution even for 270 days. The molecular dynamics simulation results indicate that the generation of water nanofluidics in nanochannels of GO nanosheets remarkably reduces the water evaporation enthalpy in GCP membrane, compared to bulk water. Consequently, the GCP membrane exhibits a high evaporation rate (1.87 kg m−2 h−1) and displays stable evaporation rates for 14 h under 1 kW m−2 irradiation. The GCP membrane additionally works very well when using different water sources (e.g., dye-polluted water) or even strong acidic solution (pH = 1) or basic solution (pH = 13). More importantly, through bundling pluralities of GCP membrane, an efficient solar desalination device is developed to produce drinkable water from seawater. The average daily drinkable water amount in sunny day is 10.1 kg m−2, which meets with the daily drinkable water needs of five adults. The high evaporation rate, long-time durability and good scalability make the GCP membrane an outstanding candidate for practical solar seawater desalination.

Background & Aims Heavy alcohol consumption and genetic factors represent the two major etiologies of chronic pancreatitis (CP). However, little is so far known about the clinical features and genetic basis of light-to-moderate alcohol consumption-related CP (LMA-CP).\ud\udMethods\udA cross-sectional analysis was performed upon 1061 Chinese CP patients between 2010 and 2015. CP was classified as classical alcoholic CP (ACP; n=206), LMA-CP (n=154), and idiopathic CP (ICP; n=701). Clinical features and genetic characteristics (PRSS1, SPINK1, CTRC, CFTR variant status) were compared between the different groups. Odds ratios (OR) with 95% confidence intervals were calculated to ascertain the combinatorial effect of alcohol consumption and gene mutation.\ud \ud Results\ud Compared with ICP, the clinical features of LMA-CP were characterized by higher rates of developing pancreatic stones, pseudocyst, diabetes, and steatorrhea, which were similar to those associated with ACP. The prevalence of CP-related gene variants in LMA-CP was 38.3%, similar to ACP (39.8%), although significantly lower than ICP (56.2%). Alcohol consumption enhanced the risk of a poor clinical outcome whilst genetic factors amplified alcohol’s effects. Compared to ICP, LMA-CP and ACP were associated with a high risk of pancreatic stones (patients-without-variants, OR=2.01 and 2.54; patients-with-variants, OR=2.17 and 1.07), pseudocyst (patients-without-variants, OR=1.03 and 1.43; patients-with-variants, OR=1.67 and 2.14), diabetes mellitus (patients-without-variants, OR=0.86 and 1.31; patients-with-variants, OR=2.05 and 1.55) and steatorrhea (patients-without-variants, OR=1.56 and 2.10; patients-with-variants, OR=2.11 and 1.60).\ud \udConclusions\ud Evidence was presented to show that LMA-CP was clinically and genetically similar to ACP but significantly different from ICP. Our findings provide support to the growing view that there is no safe level of alcohol consumption.

Ir3 is reported to photodegrade CAIX under hypoxia, which improve the cancer immune microenvironment, and induce immunogenic pyroptosis through lipid peroxidation under hypoxia.

Selective laser melting technique is a viable alternative to fabricating metal matrix composites with controllable structures; however, its implementation remains challenging because of the unpredicted defects arising from the reinforcement.

The integration of renewable solar energy-driven interfacial evaporation and photocatalysis has recently emerged as one of the most promising technologies for simultaneous freshwater production and pollutant removal. However, the construction of an advanced integrated system with the merit of a fast supply of water and pollutant molecules remains challenging for efficient solar-driven evaporation and photocatalytic performance. Herein, inspired by the transpiration of plants, we fabricate a biomimetic, vertically channeled polypyrrole/foam-like carbon nitride/poly(vinyl alcohol) hydrogel (PCH) by directional freeze-drying. We prove that the vertically aligned channels not only reduce heat loss and improve energy conversion efficiency but also facilitate the transport of water and organic pollutants to the air-water interface. Benefiting from the advantages above, the PCH evaporator presents a high solar evaporation efficiency of 92.5%, with the evaporation rate achieving 2.27 kg m

International audience; We discuss JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo via detecting inverse beta decay reactions of electron anti-neutrinos resulting from the annihilation. We study possible backgrounds to the signature, including the reactor neutrinos, diffuse supernova neutrino background, charged- and neutral-current interactions of atmospheric neutrinos, backgrounds from muon-induced fast neutrons and cosmogenic isotopes. A fiducial volume cut, as well as the pulse shape discrimination and the muon veto are applied to suppress the above backgrounds. It is shown that JUNO sensitivity to the thermally averaged dark matter annihilation rate in 10 years of exposure would be significantly better than the present-day best limit set by Super-Kamiokande and would be comparable to that expected by Hyper-Kamiokande.

MYH9 encodes the heavy chain of nonmuscle myosin IIA, a ubiquitously expressed cytoplasmic myosin that regulates the actin cytoskeleton, cell migration, cell polarization, and signal transduction in cancer cells. Here, we investigated the role of MYH9 in cancer stem cells (CSCs) associated with esophageal cancer (EC). The subcellular localization of MYH9 was investigated in SKGT-4 cells through immunofluorescent analysis. MYH9+ and MYH9- spheroid cells were derived from SKGT-4 cells by flow cytometry and compared for self-renewal capacity, tumorigenicity, CD133 positivity, cisplatin resistance, and phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) activity. MYH9 messenger RNA expression was assessed in 30 EC patients by quantitative reverse transcription-polymerase chain reaction. Kaplan-Meier curves were plotted to explore the influence of MYH9 on EC survival. MYH9 localized to the plasma membrane, cytoplasm, and nucleus of SKGT-4 cells. Spheroid cells displayed higher MYH9 expression and positivity compared to parental SKGT-4 cells. MYH9+ cells showed strong CSC characteristics, including in vivo tumorigenicity, migration, invasion, cisplatin resistance, and CD133+ positivity. MYH9 activated the PI3K/AKT/mTOR axis in CSCs and was upregulated in EC patients with poor survival. Collectively, these data show that MYH9 significantly promotes tumorigenesis by regulating PI3K/AKT/mTOR signaling in EC. MYH9 expression remarkably correlates with poor prognosis and represents a novel biomarker and drug target for the diagnosis and treatment of EC.

Both environmental factors, such as alcohol consumption and smoking, and genetic factors are strongly associated with the risk of developing chronic pancreatitis (CP). However, comprehensive understanding of their impacts on the progression of CP remains elusive.A prospective cohort study was performed on a large cohort of CP patients with known genetic backgrounds. The cumulative incidence of pancreatic insufficiency after the onset of CP was analyzed using Kaplan-Meier survival curves. Multivariate Cox proportional hazards regression analysis also was performed.A total of 798 patients were enrolled in the study and followed up for 10.5 years. Rare pathogenic genotypes in the SPINK1, PRSS1, CTRC, or CFTR genes were identified in 410 (51.4%) patients. The development of pancreatic insufficiency was significantly earlier in patients with a history of smoking and/or alcohol consumption in both the positive (P.001) and negative (P = .001) gene mutation groups. However, the development of pancreatic insufficiency did not differ significantly between patients with and without gene mutations despite alcohol and/or smoking status, with P values of .064 and .115, respectively. Multivariate Cox regression analysis showed that age at onset of CP (hazard ratio, [HR], 1.02; P.001) and alcohol consumption (HR, 1.86; P.001) were independent risk factors for the development of diabetes, while male sex (HR, 1.84; P = .022) and smoking (HR, 1.56; P = .028) were predictors of steatorrhea.Although rare pathogenic mutations in the 4 major susceptibility genes for CP were not correlated significantly with the development of pancreatic insufficiency, environmental factors (either alcohol consumption or smoking) significantly accelerated disease progression (ClinicalTrials.gov: NCT04574297).

Sustainable conversion of waste plastics into valuable carbon materials for diverse applications provides a promising strategy to dispose the municipal and industrial waste plastics. However, it remains a challenge to precisely control the crosslinking reaction for transforming waste polyesters into N-doped porous carbon (NPC) with well-defined microstructures. Herein, we put forwards a strategy of stepwise crosslinking using melamine and ZnCl2/NaCl eutectic salts to convert poly (ethylene terephthalate) (PET) into NPC at 550 °C. We prove that firstly melamine reacts with PET degradation products to form a crosslinking structure, and subsequently ZnCl2/NaCl promote the dehydration and decarboxylation of the crosslinking structure to generate a more thermally stable crosslinking structure. The coordination of two tandem crosslinking reactions is critical to control the microstructure of NPC. Without activations, NPC shows large specific surface area of 1173 m2 g−1, abundant N dopants, and rich oxygen-containing groups. These combined features endure NPC with excellent performance in CO2 capture and solar steam generation, e.g., high CO2 adsorption capacity of 6.47 mmol g−1 and evaporation rate of 1.62 kg m−2 h−1. More importantly, NPC is compared to or prevails over previous carbon-based CO2 adsorbents or photothermal materials. This work will advance the research on “green” reutilization of low-cost polyester wastes to prepare sustainable carbon for solar energy conversion, environmental protection, etc.

Surface defect classification is one of key points in the field of steel manufacturing. It remains challenging primarily due to the rare occurrence of defect samples and the similarity between different defects. In this paper, a multi-level semantic method based on residual adversarial learning with Wasserstein divergence is proposed to realize sample augmentation and automatic classification of various defects simultaneously. Firstly, the residual module is introduced into model structure of adversarial learning to optimize the network structure and effectively improve the quality of samples generated by model. By substituting original classification layer with multiple convolution layers in the network framework, the feature extraction capability of model is further strengthened, enhancing the classification performance of model. Secondly, in order to better capture different semantic information, we design a multi-level semantic extractor to extract rich and diverse semantic features from real-world images to efficiently guide sample generation. In addition, the Wasserstein divergence is introduced into the loss function to effectively solve the problem of unstable network training. Finally, high-quality defect samples can be generated through adversarial learning, effectively expanding the limited training samples for defect classification. The experimental results substantiate that our proposed method can not only generate high-quality defect samples, but also accurately achieve the classification of defect detection samples.

AIM: To explore the long-term efficacy, safety, and optical mechanism of orthokeratology with increased compression factor in adolescent myopia control. METHODS: A prospective, double-masked, and randomized clinical trial was performed from May 2016 to June 2020. Subjects aged between 8 and 16y, with myopia (-5.00 to -1.00 D), low astigmatism (≥-1.50 D) and anisometropia (≤1.00 D), were stratified into low (-2.75 to -1.00 D) and moderate (-5.00 to -3.00 D) myopia groups. Then they were randomly assigned to wear either increased compression factor (ICF; 1.75 D) orthokeratology or conventional compression factor (CCF; 0.75 D) orthokeratology. The data were recorded including axial length (AL), spherical equivalent (SE), best corrected visual acuity (BCVA), near visual acuity (NVA), corneal staining (using Efron grading scales), corneal hysteresis (CH), corneal resistance factor (CRF), higher-order aberrations (HOAs, expressed as root mean square, RMS(h)), and subfoveal choroidal thickness (SFChT) in the 2-year follow-up period. Pearson's correlation coefficient was conducted to analyze the association between the changes in AL and RMS(h), SFChT. RESULTS: At the 2-year visit, there were no statistical differences in all the parameters between the ICF group and the CCF group in low myopia subjects (P>0.05). For the moderate myopia subjects, the ICF group had shorter AL elongation (0.23±0.08 vs 0.30±0.11 mm, P=0.015), higher RMS(h) (1.94±0.50 vs 1.65±0.51 µm, P=0.041), and higher SFChT (279.04±35.72 vs 254.08±29.60 µm, P=0.008) than those in CCF group. The change in AL was negatively correlated with RMS(h) (r=-0.687, P

The existing estimators for the drift coefficient in the diffusion model with jumps involve jump components and possess larger boundary error. How to effectively estimate the drift function is an important issue that faces challenges and has theoretical significance. In this paper, the gamma asymmetric kernel for boundary correction and threshold function eliminating jump impacts are combined to estimate the unknown drift coefficient in the jump diffusion process of interest rate. The asymptotic large sample property and the better finite sample property through the Monte Carlo numerical simulation experiment and the empirical analysis of SHIBOR and LIBOR for the corresponding estimator are considered in detail. It is found that the estimator proposed in this paper can correct the estimation error near or far away from the origin point, which provides a more asymptotic unbiased estimator for the drift function in diffusion models with jumps.

Quantum errors subject to noisy environments remain a major obstacle to advancing quantum information technology. Solutions to this issue include robust quantum control at the pulse level and error correction or mitigation techniques at the circuit level. We develop a geometric method to unify the treatments of noises at both levels to understand noisy dynamics and reduce errors. We illustrate the error's random walk in the geometric space to explain how coherent noises are tailored into stochastic Pauli errors by randomized compiling. We obtain analytical formulas for the noise parameters and show how robust quantum control techniques can further improve circuit fidelity. We demonstrate the efficacy of our approach using numerical simulations, showcasing its potential for advancing quantum information processing., 6 pages

Recent work demonstrates that images from various chest X-ray datasets contain visual features that are strongly correlated with protected demographic attributes like race and gender. This finding raises issues of fairness, since some of these factors may be used by downstream algorithms for clinical predictions. In this work, we propose a framework, using generative adversarial networks (GANs), to visualize what features are most different between X-rays belonging to two demographic subgroups., Medical Imaging with Deep Learning(MIDL) 2023 short paper track

Recent research demonstrates that deep learning models are capable of precisely extracting bio-information (e.g. race, gender and age) from patients' Chest X-Rays (CXRs). In this paper, we further show that deep learning models are also surprisingly accurate at recognition, i.e., distinguishing CXRs belonging to the same patient from those belonging to different patients. These findings suggest potential privacy considerations that the medical imaging community should consider with the proliferation of large public CXR databases.

MT-EGFR expression in HBEC cells is associated with dramatically elevated levels of replication factors.

MT-EGFR expression reduces survival in NSCLCs and HBEC cells.

Camptothecin and hydroxyurea have differing effects on RPA associated H2AX foci in WT-EGFR expressing S-phase cells.

Supplementary Figure Legends.

Ectopic MT-EGFR expression significantly reduces hypoxia-associated radiation resistance in A549 NSCLC cells.

MT-EGFR expression has marginal effects on endogenous reducing environment in NSCLCs or HBEC.

Background: Infected pancreatic necrosis (IPN) accounts for 30% mortality in severe acute pancreatitis (SAP). Early prediction of IPN occurrence is critical for prophylactic measures to be taken. This study aimed to evaluate the predicting value for IPN of combined markers at early stages of SAP. Methods: The clincial records of 324 SAP patients admitted within 48 hours after disease onset were retrospectively analyzed. As potential predictors, the neutrophil to lymphocyte ratio (NLR), blood procalcitonin concentration (PCT) on the 1st, 4th and 7th day post admission, as well as modified computerized tomography severity index (MCTSI) on the 5 – 7th day post admission, were extracted. Correlations between these features with IPN were analyzed using logistic regression, and predictive values were estimated using the Receiver operating characteristic (ROC) curve analyses. Results: NLR, PCT, body mass index (BMI) and MCTSI were significantly higher in IPN group (p < 0.001) compared to the control, among which NLR, PCT and MCTSI were identified as independent predictors for IPN in logistic regression model. Combination of these parameters yielded signficant predicting valuse with an area under curve (AUC) of 0.92, sensitivity of 97.2% and specificity of 77.2% in ROC curve analysis. Conclusion: Combination of NLR, PCT, MCTSI might facilitate the prediction of IPN occurrence in SAP patients.

Background Anxiety and depression are common psychological comorbidities in patients with chronic pancreatitis (CP). There is still a lack of epidemiological studies on anxiety and depression in Chinese CP patients. This study aimed to identify the incidence and related factor of anxiety and depression among East Chinese CP patients and explore the relationship between anxiety, depression, and coping styles. Methods This prospective observational study was conducted from June 1, 2019 to March 31, 2021 in Shanghai, China. Patient diagnosed with CP were interviewed using the sociodemographic and clinical characteristics questionnaire, Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS), and Coping Style Questionnaire (CSQ). Multivariate logistic regression analysis was conducted to identify the related factors of anxiety and depression. Correlation test was preformed to analyze the correlation between anxiety, depression, and coping styles. Results The incidence of anxiety and depression in East Chinese CP patients was 22.64% and 38.61%, respectively. Patients’ previous health status, level of disease coping, frequency of abdominal pain episodes, and pain severity were significantly associated with anxiety and depression. Mature coping styles (Problem solving, Seeking for help) had a positive impact on anxiety and depression, while immature coping styles (Self-blame, Fantasy, Repression, Rationalization) had negative effects on anxiety and depression. Conclusion Anxiety and depression were common in patients with CP in China. The factors identified in this study may provide references for the management of anxiety and depression in CP patients.

With the increasingly serious burden of osteoarthritis (OA) on modern society, it is urgent to propose novel diagnostic biomarkers and differentiation models for OA. 7-methylguanosine (m7G), as one of the most common base modification forms in post transcriptional regulation, through which the seventh position N of guanine (G) of messenger RNA is modified by methyl under the action of methyltransferase; it has been found that it plays a crucial role in different diseases. Therefore, we explored the relationship between OA and m7G. Based on the expression level of 18 m7G-related regulators, we identified nine significant regulators. Then, via a series of methods of machine learning, such as support vector machine recursive feature elimination, random forest and lasso-cox regression analysis, a total of four significant regulators were further identified (DCP2, EIF4E2, LARP1 and SNUPN). Additionally, according to the expression level of the above four regulators, two different m7G-related clusters were divided via consensus cluster analysis. Furthermore, via immune infiltration, differential expression analysis and enrichment analysis, we explored the characteristic of the above two different clusters. An m7G-related scoring model was constructed via the PCA algorithm. Meanwhile, there was a different immune status and correlation for immune checkpoint inhibitors between the above two clusters. The expression difference of the above four regulators was verified via real-time quantitative polymerase chain reaction. Overall, a total of four biomarkers were identified and two different m7G-related subsets of OA with different immune microenvironment were obtained. Meanwhile, the construction of m7G-related Scoring model may provide some new strategies and insights for the therapy and diagnosis of OA patients.

The main task of the Top Tracker detector of the neutrino reactor experiment Jiangmen Underground Neutrino Observatory (JUNO) is to reconstruct and extrapolate atmospheric muon tracks down to the central detector. This muon tracker will help to evaluate the contribution of the cosmogenic background to the signal. The Top Tracker is located above JUNO's water Cherenkov Detector and Central Detector, covering about 60% of the surface above them. The JUNO Top Tracker is constituted by the decommissioned OPERA experiment Target Tracker modules. The technology used consists in walls of two planes of plastic scintillator strips, one per transverse direction. Wavelength shifting fibres collect the light signal emitted by the scintillator strips and guide it to both ends where it is read by multianode photomultiplier tubes. Compared to the OPERA Target Tracker, the JUNO Top Tracker uses new electronics able to cope with the high rate produced by the high rock radioactivity compared to the one in Gran Sasso underground laboratory. This paper will present the new electronics and mechanical structure developed for the Top Tracker of JUNO along with its expected performance based on the current detector simulation., 20 pages

Coronary artery bypass graft surgery (CABG) is an impactful treatment for coronary heart disease. Intimal hyperplasia is the central reason for the restenosis of vein grafts after CABG. The introduction of external vascular sheaths around VGs (VGs) can effectively inhibit intimal hyperplasia and ensure the patency of VGs. In this study, the well-known biodegradable copolymer poly (e-caprolactone-co-L, L-lactide) (PLCL) was electrospun into high porosity external sheaths. The prednisone loaded in the PLCL sheath was slowly released during the degradation process of PLCL. Under the combined effects of sheath and prednisone, intimal hyperplasia was inhibited. For the cell experiments, all sheaths show low cytotoxicity to L929 cells at different concentrations at different time intervals. The ultrasonography and histological results showed prominent dilation and intimal hyperplasia of VG without sheath after two months of surgery. But there was no dilation in PLCL and PLCLPrednisone groups. Notably, the prednisone-loaded sheath group exhibited efficacy in inhibiting intimal hyperplasia and ensured graft patency.

Steatorrhea, a sign of severe pancreatic exocrine insufficiency (PEI), is related to consequences caused by pancreatitis. This study aimed to identify predictors and to construct a nomogram for steatorrhea in idiopathic chronic pancreatitis (ICP).ICP patients admitted to our hospital from January 2000 to December 2013 were enrolled in this retrospective-prospective cohort study and randomly assigned to the training and validation cohorts. The cumulative rate of steatorrhea was calculated. A Cox proportional hazard regression model was used to identify predictors for steatorrhea and construct the nomogram. Internal and external validation of the nomogram was then performed.There were 1633 ICP patients enrolled, with a median follow-up duration of 9.8 years and 20.8% (339/1633) of patients developed steatorrhea following onset of ICP. Steatorrhea was observed in 93, 115, and 133 patients at 1, 3, and 5 years following diagnosis of CP, with a cumulative rate of 6.5% (95% confidence interval [CI] 5.1%-7.9%), 8.0% (95% CI 6.2%-9.8%), and 9.3% (95% CI 6.6%-12.0%), respectively. Male sex (hazard ratio [HR] 2.479, P 0.001), diabetes mellitus at/before diagnosis of ICP (HR 2.274, P = 0.003), and aged less than 18 years at onset of ICP (HR 0.095, P 0.001) were identified risk factors for steatorrhea. Initial manifestations were associated with development of steatorrhea. The nomogram was proven to have good concordance indexes.We identified predictors and developed a nomogram for predicting steatorrhea in ICP. It was recommended that high-risk populations be followed up closely, which might contribute to the early diagnosis and treatment of PEI.

Big data analytics has become increasingly vital in many modern enterprise applications such as user profiling and business process optimization. Today’s big data processing systems, such as Hadoop MapReduce, Spark, and Hive, treat big data applications as a batch of jobs for scheduling. Existing schedulers in production systems often maintain fair allocation without considering application performance and resource utilization simultaneously. It is challenging to perform job scheduling in big data systems to achieve both low turnaround time and high resource utilization due to the high complexity in data processing logics and the dynamic variation in workloads. In this article, we propose a performance-aware scheduler, referred to as PAS, which dynamically schedules big data jobs in Hadoop YARN and Spark and autonomously adjusts scheduling policies to improve application performance and resource utilization. Specifically, PAS schedules multiple concurrent jobs using different policies based on the predicted job completion time and employs a greedy approach and a one-step lookahead strategy to opportunistically maximize the average job performance while still maintaining a satisfactory level of resource utilization. We implement PAS in Hadoop YARN and evaluate its performance with HiBench, a well-known big data processing benchmark. Experimental results show that PAS reduces the average turnaround time by 25% and the makespan by 15% in comparison with four state-of-the-art schedulers.