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Pancreatic carcinoma is being recognized to be responsible for an increasing number of cancer-related deaths, especially in the western world. A deluge of risk factors have been described in the literature. Some of the important ones include smoking, alcohol and metabolic diseases like obesity. It also poses challenges in diagnosis and treatment despite recent advances in diagnostic, surgical and other therapeutic advancements. This is a narrative review of the findings of multiple studies that were retrieved from electronic databases like PubMed, Google Scholar, Scopus, Medline, Embase, and Cochrane databases. We summarize the current knowledge regarding the epidemiology and various risk factors for the development of pancreatic carcinoma.

This work investigates the structure, rheological properties, and film performance of wheat flour hydrocolloids and their comparison with that of a wheat starch (WS)–gluten blend system. The incorporation of gluten could decrease inter-chain hydrogen bonding of starch, thereby reducing the viscosity and solid-like behavior of the film-forming solution and improving the frequency-dependence, but reducing the surface smoothness, compactness, water vapor barrier performance, and mechanical properties of the films. However, good compatibility between starch and gluten could improve the density of self-similar structure, the processability of the film-forming solution, and film performance. The films based on wheat flours showed a denser film structure, better mechanical properties, and thermal stability that was no worse than that based on WS–gluten blends. The knowledge gained from this study could provide guidance to the development of other flour-based edible packaging materials, thereby promoting energy conservation and environmental protection.

Green technology innovation is a crucial factor in the global quest for sustainability. In 2017, China approved the establishment of pilot zones for green financial reform and innovations to build and improve the green financial system. Using a Difference-in-Difference (DID) model, this paper examines the impact of this pilot policy on corporate green technology innovation and its transmission mechanism based on the data of green patents of Chinese A-share listed manufacturing companies between 2014 and 2019. It finds that pilot zones for green financial reform and innovations have contributed to the growth of green technology innovations. This conclusion was confirmed after a series of robustness tests. The pilot policy’s promotion of green technology innovations is mainly reflected in the application of corporate green invention patents. However, it is more significant for non-heavy polluting enterprises, high-tech certified enterprises and large enterprises. The paper also finds that the pilot policy promotes corporate green technology innovation by promoting social financing, talent support and government financial support.

A novel ratiometric fluorescence probe was designed for the determination of Al

Acidic water electrolysis is of great importance for boosting the development of renewable energy. However, it severely suffers from the trade-off between high activity and long lifespan for oxygen evolution catalysts on the anode side. This is because the sluggish kinetics of oxygen evolution reaction necessitates the application of a high overpotential to achieve considerable current, which inevitably drives the catalysts far away from their thermodynamic equilibrium states. Here we demonstrate a new oxygen evolution model catalyst-hierarchical palladium (Pd) whose performance even surpasses the benchmark Ir- and Ru-based materials. The Pd catalyst displays an ultralow overpotential (196 mV), excellent durability and mitigated degradation (66 μV h−1) at 10 mA cm−2 in 1 M HClO4. Tensile strain on Pd (111) facets weakens the binding of oxygen species on electrochemical etching-derived hierarchical Pd and thereby leads to two orders of magnitudes of enhancement of mass activity in comparison to the parent Pd bulk materials. Furthermore, the Pd catalyst displays the bifunctional catalytic properties for both oxygen and hydrogen evolutions and can deliver a current density of 2 A cm–2 at a low cell voltage of 1.771 V when fabricated into polymer electrolyte membrane electrolyser.

With the gradual expansion of the development of sports, the level of sports has been rapidly improved. Athletes have to carry out high-intensity and systemic technical movements in training and competition. Some sports have the greatest burden on the shoulder joint. From the observation and investigation of the injured parts of athletes, it is found that the shoulder joint is the most common sports injury, which is the most typical sports injury. Based on the problem of insufficient strength and endurance reserve after rehabilitation of shoulder external rotator injury, it will cause muscle tension and poor extensibility. To prove the improvement effect of functional training and posture index calibration on the poor posture of the shoulder, considering the measurement of global passive torque, this paper uses a limited set of joint angles and corresponding passive torque data in the upper arm lifting trajectory to train the neural network and uses the trained network to predict the passive torque in other upper arm trajectories. The kinematics model of the shoulder joint is established, and the human-computer interaction experiment is designed on the platform of the gesture index manipulator. The passive and active torque components of the shoulder joint in the human-computer interaction process are calculated by measuring the man-machine interaction force of the subjects in the motion state, which is used as the basis for evaluating the active motion intention of the subjects. Surface electromyography (SEMG) was used to calibrate and verify the attitude index of shoulder active torque. The method proposed in this paper is helpful to achieve more efficient on-demand assisted rehabilitation training exercises, which is of great significance to improve the level of rehabilitation training.

Nanomaterials-based immunochromatographic assays (ICAs) have gained great commercial success in real-life point-of-care testing (POCT). Exploring novel carriers of ICAs with improved signaling and sustained activity favors the development of sensitive POCT. Herein a potent signal biotag, colored Staphylococcus aureus (SA), was created for ICA carriers through a mild self-assembly strategy, providing high luminance and abundant specific binding sites for immobilization of monoclonal antibodies (mAbs). The biocompatible SA-dyes (SADs) retained both an intact surface structure for mAbs labeling (Fc portion) and the superior bioactivity of immobilized mAbs (affinity constant was about 109 M-1), thus waiving the intrinsic limitations of traditional nanomaterials and endowing high sensitivity. Proof-of-concept was demonstrated by employing Congo red- or/and fluorescein isothiocyanate-embedded SA (SACR, SAFITC, and SACR-SAFITC) as ICA carriers to detect zearalenone (ZEN) through colorimetric or/and fluorimetric signals. Furthermore, the ICAs satisfied the clinical requirement perfectly, including limit of detection (0.013 ng/mL, which was at least an 85-fold improvement over that of traditional gold nanoparticles-based ICA), linearity (R2 > 0.98), reproducibility (RSD < 8%), selectivity, and stability. Importantly, the proposed biosensors could be well-applied in four real samples for ZEN monitoring with satisfactory recoveries, correlating well with the results from liquid chromatography-tandem mass spectrometry (LC-MS). This work also proved a universal design for tailoring coloration bands for SAD-ICA detection of multiple analytes.

Three-dimensional (3D) object detection based on point cloud data plays a critical role in the perception system of autonomous driving. However, this task presents a significant challenge in terms of its practical implementation due to the absence of point cloud data from automotive-grade hybrid solid-state LiDAR, as well as the limitations regarding the generalization ability of data-driven deep learning methods. In this paper, we introduce SimoSet, the first vehicle view 3D object detection dataset composed of automotive-grade hybrid solid-state LiDAR data. The dataset was collected from a university campus, contains 52 scenes, each of which are 8 s long, and provides three types of labels for typical traffic participants. We analyze the impact of the installation height and angle of the LiDAR on scanning effect and provide a reference process for the collection, annotation, and format conversion of LiDAR data. Finally, we provide baselines for LiDAR-only 3D object detection.

Single-photon emitters based on intrinsic defects in silicon carbide (SiC) are promising as solid-state qubits for the quantum information storage, whereas defect engineering in a controllable manner still remains challenging. Herein, the thermally-driven defect dynamic reaction in the ion implanted 4H-SiC has been exploited through the optical emission spectra of defects. For the heavy-ion (Si or Ar) implanted samples with abundant Frenkel pairs, the silicon vacancies (VSi) are energetically converted into the carbon antisite-vacancy pair (CSi-VC) upon annealing till 1300 °C for 30 min, accompanied with the gradual lattice recovery and local strain relaxation. The further temperature elevation dissociates the metastable CSi-VC into carbon antisite (CSi) and carbon vacancy (VC), as supported by the consequent quenching of the (CSi-VC)-related emission at 700 nm. Thus, the whole defect reaction is probed as the vacancy interconversion from VSi to VC with the byproduct of stacking faults. In contrast, the intermediate CSi-VC complexes are not energetically favorable during the annealing of the H-implanted sample, which results from the negligible generation of Frenkel pairs, as supported by the x-ray diffraction patterns and Raman scattering analysis. These findings provide guidance for defect engineering in SiC toward the creation of reliable single photon emitters.

The accurate distribution of countercations (Rb+ and Sr2+ ) around a rigid, spherical, 2.9-nm size polyoxometalate cluster, {Mo132 }42- , is determined by anomalous small-angle X-ray scattering. Both Rb+ and Sr2+ ions lead to shorter diffuse lengths for {Mo132 } than prediction. Most Rb+ ions are closely associated with {Mo132 } by staying near the skeleton of {Mo132 } or in the Stern layer, whereas more Sr2+ ions loosely associate with {Mo132 } in the diffuse layer. The stronger affinity of Rb+ ions towards {Mo132 } than that of Sr2+ ions explains the anomalous lower critical coagulation concentration of {Mo132 } with Rb+ compared to Sr2+ . The anomalous behavior of {Mo132 } can be attributed to majority of negative charges being located at the inner surface of its cavity. The longer anion-cation distance weakens the Coulomb interaction, making the enthalpy change owing to the breakage of hydration layers of cations more important in regulating the counterion-{Mo132 } interaction.

We report herein that dendron-shaped macromolecules ABn crystallize into well-ordered pyramid-like structures from mixed solvents, instead of spherical motifs with curved structures, as found in the bulk. The design of the asymmetric molecular architecture and the choice of mixed solvents are applied as strategies to manipulate the crystallization process. In mixed solvents, the solvent selection for the Janus macromolecule and the existence of dominant crystalline clusters contribute to the formation of flat nanosheets. Whereas during solvent evaporation, the bulkiness of the asymmetric macromolecules easily creates defects within 2D nanosheets which lead to their spiral growth through screw dislocation. The size of the nanosheets and the growth into 2D nanosheets or 3D pyramidal structures can be regulated by the solvent ratio and solvent compositions. Moreover, macromolecules of higher asymmetry generate polycrystals of lower orderliness, probably due to higher localized stress., The dendron-shaped macromolecules ABn crystallize into well-ordered pyramid-like structures from mixed solvents, which is on the contrary to spherical motifs with curved structures in bulk.

Antibacterial wound dressings can effectively avoid the residual of antibacterial nanomaterials for injection in vivo, reduce their biological toxicity to normal cells and tissues, making them be widely applied in biomedical field. Herein, an approach of combining ion-crosslinking, in-situ reduction and microwave-assisted methods was employed to prepare chitosan-copper-gallic acid nanocomposites (CS-Cu-GA NCs) with dual-functional nano-enzyme characteristics (oxidase- and peroxidase-like functions). The oxidase-like activity of CS-Cu-GA NCs can facilitate the production of hydrogen peroxide (H2O2) when it contacted with physiologically relevant antioxidants (AH2) in bacteria. Subsequently, H2O2 was catalyzed to generate hydroxyl radicals (OH) under the peroxidase-like activity of CS-Cu-GA NCs. Furthermore, CS-Cu-GA NCs integrate the inherent antibacterial properties of chitosan, Cu NPs and Cu2+. Animal experiments revealed that the antibacterial dressing incorporating CS-Cu-GA NCs exhibited its effective promotion of S. aureus-infected wounds healing, as well as no damage to normal tissues. Besides, the antibacterial dressing was prepared to a band aid with excellent water swelling and antibacterial properties, which was further fixed in a medical tape to construct a portable antibacterial product that can be applied to the surface of human skin and showed excellent waterproof performance, providing a new insight for the construction of clinical antibacterial wound healing products.

We study single-machine bicriteria scheduling problems with position-dependent weights. Due date costs and penalty costs can affect the decision-maker’s profit. Therefore, how to optimize the benefits and balance of these costs for decision-makers is the focus of this research. This paper discusses three models: weighted-sum scheduling problem, constrained scheduling problem, Pareto scheduling problem. It analyzes the properties of bicriteria schedule, determines the optimal due dates (usually referred to as different due dates: DIF), and gives the corresponding polynomial solvable algorithms.

Variants in the tau gene (MAPT) region are associated with breast cancer in women and Alzheimer's disease (AD) among persons lacking apolipoprotein E ε4 (ε4-).To identify novel genes associated with tau-related pathology, we conducted two genome-wide association studies (GWAS) for AD, one among 10,340 ε4- women in the Alzheimer's Disease Genetics Consortium (ADGC) and another in 31 members (22 women) of a consanguineous Hutterite kindred.We identified novel associations of AD with MGMT variants in the ADGC (rs12775171, odds ratio [OR] = 1.4, P = 4.9 × 10These findings suggest that epigenetically regulated MGMT expression is involved in AD pathogenesis, especially in women.

The identification and quantitation of S-nitrosothiols (RSNO) has aroused enormous levels of attention, due to RSNO have many roles in vivo. Here, we synthesized the nanocomposites of ultrafine Cu

On account of the excessive residues and serious detriments, it is imminent to develop an efficient method to determine tetracyclines (TCs) for protecting human health. In this work, a novel ratiom...

This article considers the flow shop problem of minimising the total weighted completion time in which the processing times of jobs are variable according to general position weighted learning effe...

The China Fusion Engineering Test Reactor (CFETR) tritium plant has to deal with a larger amount of tritium than ITER. The tritium source term is one of the key issues for safety assessment and ope...

The Jenkinson‐Collison (JC) classification method was applied to wintertime daily mean sea level pressure (MSLP) data across southeastern China. The results indicate that the WTs that include easterly wind components are more conducive to precipitation generation. The study implies that whether a weather type is easy to produce precipitation can be judged by wind direction. This will help us better understand the physical mechanism of precipitation generation in this area.

Social Q&A community provides a new way for users to acquire, exchange and share information, so it is of great significance to study user’s knowledge sharing behavior in social Q&A community. Based on the theory of social exchange, this paper takes Zhihu community as the research object, analyzes the factors that affect user’s knowledge sharing behavior in the social Q&A community, and conducts quantitative research through negative binomial regression. The results show that in Zhihu community, self-display, user recognition, social learning and other dimensions have a significant positive impact on user’s knowledge sharing behavior, but the degree of impact is different. Finally, according to the empirical results, the paper puts forward relevant suggestions and measures to better promote user’s knowledge sharing behavior.

Estimating individual tree structures from 3-D space may improve the biomass statistics of the urban forest and provide tree-level information for ecological studies. The existing delineation algorithms developed for 3-D point clouds have difficulty in the tree mapping from nonvertical stems or overlapping crowns, and may fail to detect incomplete or occluded branches. Besides, those methods either focus on the individual tree segmentation or crown delineation from the forest, which inadequately estimates the growth fitting of urban street trees. The goal of this article is to present a framework for estimating the growth fitting of street trees’ diameter at breast height and under branch height. Tree stems are identified from the achieved street trees’ nonphotosynthetic components, including main stems and branches, over different urban trees from mobile laser scanning point clouds. To extract nonphotosynthetic components, a clustering method is proposed to group points from the same stem or branch. The proposed work was validated in both wearable laser scanning data and vehicle laser scanning data, and the experimental scenes contain a range of roadside trees in different structures. In the identification of tree stems, the achieved correctness and completeness are 94.5% and 92.5%, respectively. In the growth fitting, this article calculates a Gaussian model, with the R -square up to 0.81, to describe the growth fitting of Platanus acerifolia . Results show that the proposed approach succeeds in offering applicability over varying street tree types and the improvement for overlapping individual tree information extraction.

OBJECTIVE To investigate the potential prognostic value of necroptosis-associated lncRNAs (NALncRNAs)in patients with ovarian cancer. METHODS Gene expression data from ovarian cancer patients with clinical data were downloaded from TCGA database. This is the base data for screening NALncRNAs that represent different survival times.lncRNA risk models were constructed by Cox regression analysis and evaluated for their prognostic value. The link between lncRNA signatures and related pathways, immune cell activity, immunological checkpoints, m6A-related genes, and gene mutations was also investigated. RESULTS In this study, eight NALncRNAs including USP30-AS1, MINCR, LINC01096, DNM3OS, LINC02574, DTNB-AS1, ACAP2-IT1, and ILVBL-AS1, all of which were well represented for the outcome of ovarian cancer patients. Noemogram after calibration curve validation has good clinical utility. Risk signatures were shown to be abundant in various pathways related to immunology and cell proliferation, according to gene set enrichment analysis. Patients' late survival outcome corresponds to differences in immune cells, immune checkpoints, immune function, etc.A better immune microenvironment would facilitate late survival, but inexplicably patients with long survival times have a higher immune escape. Patients with high mutations in genes appear to have better survival outcomes. CONCLUSION This study identified eight NALncRNAs markers for the first time, providing a valuable basis for more accurate prediction of ovarian cancer prognosis.

Herein, a cost-effective, simple and sensitive electrochemical sensing platform was established based on aptamer - target recognition and target-triggering signal amplification strategy for protein detection. Due to the high affinity between the aptamer and target, the assistant DNA1 (a1) could release from a1-aptamer duplex and trigger the following DNA circuits. The strand displacement and branch migration reaction brought assistant DNA3 (a3) released. Eventually, a large number of duplex structures of a3-Hairpin DNA3 were formed on the surface of electrode. Consequently, the capture DNA on the surface of platinum nanoparticles could hybridize with the unfolded DNA fragment of Hairpin DNA3 on the sensor surface, resulting in the electrochemical signal readout of H

Crataegus bretschnesideri C. K. Schneid. originated in Northeast China, it has excellent characteristics of cold resistance and early maturity. However, the taxonomic status of C. bretschnesideri has been controversial due to the intra-specific hybridization and apomixes. Comparative assessment of phenotypic and molecular evaluations used to explore genetic diversity of C. bretschneideri and relative species. Qualitative and quantitative traits of C. bretschneideri and relative species were evaluated. Genetic diversity and population structure of several Crataegus species were analyzed by thirteen reported and five newly designed SCoT markers. Leaf traits of Crataegus had a higher Shannon-wiener index than fruit and flower traits; Fruit contained diverse traits among seven Crataegus species by principal component analysis. SCoT markers amplified 148 polymorphic bands with 94.87% polymorphic loci. Crataegus individuals clustered into five clades, and C. bretschneideri had a closer relationship with C. pinnatifida Bge. and C. hupehensis Sarg.. Population structure suggested that investigated the mixed gene pool appeared in C. bretschneideri. There had variation among Crataegus species, and part of the C. bretschneideri individuals may be a hybrid origin compared to the phenotypic and molecular evaluations. Newly designed SCoT markers were practical for Crataegus diversity analyses.

S-Nitrosothiols (RSNOs) which are important intermediates in circulating reservoirs of nitric oxide (NO), transport and numerous NO signaling pathways play intricate roles in the etiology of several pathologies. However, it is still a challenge to control the release of NO from nitrosylated compounds under physiological pH. In this paper, for the first time, we report the catalytic activity and kinetic study for the modulation of NO release from RSNOs by an array of metal-organic frameworks (MOFs) (M-MOF (M'); M=Zr, Cu; and M'=Cu, Pd, no metal) under physiological conditions via time-dependent absorbance spectra. The result showed that metal active sites as well as the morphology and pore size of MOFs exhibited different activities toward RSNOs. The order of catalytic activity of these MOFs toward RSNOs is ordered in the decreasing sequence: Cu-MOF(Pd)Cu-MOF(Cu)Cu-MOF(no metal)Zr-MOF(Pd)Zr-MOF(Cu)Zr-MOF(no metal). In addition, Zr-MOF(Pd) was as model for cell experiment, demonstrated Zr-MOF(Pd) could react with RSNOs to generate NO in the complex environment of cell. Collectively, these findings establish a platform for MOFs-based, highly catalyze RSNOs in biological samples, a powerful tool for expanding the knowledge of the biology and chemistry of NO-mediated phenomena.

S-nitrosothiols (RSNO) as the potential nitric oxide (NO) storage, transfer and delivery vehicles under physiological condition have been identified as important in a number of disease states. However, a detection and quantification of RSNO method with simple and sensitive in biological media is currently lacking. A novel electrochemical sensing platform based on ionic liquid (IL) and copper porphyrin (PorCu) decorated cuprous oxide (Cu

Aiming at the difficulty of network management due to the coexistence of traditional BGP network and new SDN network, this paper proposes a routing update algorithm with clear interdomain structure and network exception handling ability. By defining SDN, BGP-SDN fusion and BGP three network domains, a packet transmission path with route discovery and update capability were formed through the three network domains in sequence. On the premise of reducing the communication delay range, the route update delay is set, and the exception handling mechanism is introduced. Specify the master controller to make the Interzone routing control rules and make routing updates a key parameter in the data flow table of border switches. The algorithm firstly ensures the absolute unimpeded communication between network domains, provides a reliable time guarantee for network exception handling, enhances the connection between control servers between network domains and between control servers and boundary switches, and improves the synchronization of multiple links in network communication. By using Mininet to build a simulation experiment platform, the reliability and feasibility of the proposed algorithm are verified from the perspectives of data packet loss and Interzone route update delay, and it is suitable for application and implementation in the current Internet environment.