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Existing capacity-based network pricing uses discounted cash flows to calculate costs, unable to reflect the uncertainties and flexibilities in distribution networks. Such shortcoming could distort the cost-reflectivity of pricing signals, particularly those for renewables and flexible technologies, causing more constraints and curtailment issues in networks. This paper proposes a new pricing method, Incremental Cost Network Pricing based on Real Options (ICOC), which can reflect network user uncertainties on network investment by using real options. Under this concept, network operators can delay investment for a certain period by paying waiting cost based on options value until more information is available, thus avoiding non-reversible investment due to uncertainties. The options cost will be levied on network users as i) rewards if they can provide flexibilities to the system; or ii) waiting costs if they present uncertainties to the system. The reward or cost is determined by a binomial tree pricing under a risk-neutral condition, which is added onto asset present value as the total cost to be recovered. Such cost is allocated to network users based on their nodal incremental costs. The proposed method is demonstrated on a practical network with different users, i) uncertain, ii) flexible; iii) certain and nonflexible.

The study takes all listed companies in Xinjiang Uyghur Autonomous Region in the three years from 2018 to 2020 as the research sample, establishes the evaluation index system of the competitiveness of listed companies in Xinjiang, collects and organizes the values of each index using the data disclosed by listed companies in Xinjiang, assigns weights to the evaluation indexes at all levels using AHP-entropy weighting method, and combines TOPSIS method to evaluate the comprehensive competitiveness of listed companies in Xinjiang. The ranking of the comprehensive competitiveness of listed companies in Xinjiang in 2018, 2019 and 2020 is obtained respectively, and the comprehensive competitiveness of listed companies in Xinjiang is evaluated and analyzed from four dimensions of scale strength, development potential, operation capacity and social responsibility of each enterprise, in order to reflect the current situation, characteristics and trends of the development of listed companies in Xinjiang in the pressure of economic downturn of the new crown epidemic.

The long-term uncertainty of multi-energy demand poses significant challenges to the coordinated pricing of multiple energy systems (MES). This paper proposes an integrated network pricing methodology for MES based on the long-run-incremental cost (LRIC) to recover network investment costs, affecting the siting and sizing of future distributed energy resources (DERs) and incentivizing the efficient utilization of MES. The stochasticity of multi-energy demand growth is captured by the Geometric Brownian Motion (GBM)-based model. Then, it is integrated with a system operation model to minimize operation costs, considering low-carbon targets and flexible demand. Thereafter, the kernel density estimation (KDE) method is used to perform the probabilistic optimal energy flow (POEF) to obtain energy flows under uncertain load conditions. Based on the probability density functions (PDFs) of energy flows, an LRIC-based network pricing model is designed, where Tail Value at Risk (TVaR) is used to model the risks of loading levels of branches and pipelines. The performance of the proposed methodology is validated on a typical MES. The proposed pricing method can stimulate cost-effective planning and utilization of MES infrastructures under long-term uncertainty, thus helping reduce low-carbon transition costs.

Human pluripotent stem cells (hPSCs) have great potential for disease modeling, drug discovery, and regenerative medicine as they can differentiate into many different functional cell types via directed differentiation. However, the application of disease modeling is limited due to a time-consuming and labor-intensive process of introducing known pathogenic mutations into hPSCs. Base editing is a newly developed technology that enables the facile introduction of point mutations into specific loci within the genome of living cells without unwanted genome injured. We describe an optimized stepwise protocol to introduce disease-specific mutations of long QT syndrome (LQTs) into hPSCs. We highlight technical issues, especially those associated with introducing a point mutation to obtain isogenic hPSCs without inserting any resistance cassette and reproducible cardiomyocyte differentiation. Based on the protocol, we succeeded in getting hPSCs carrying LQTs pathogenic mutation with excellent efficiency (31.7% of heterozygous clones, 9.1% of homozygous clones) in less than 20 days. In addition, we also provide protocols to analyze electrophysiological of hPSC-derived cardiomyocytes using multi-electrode arrays. This protocol is also applicable to introduce other disease-specific mutations into hPSCs. Graphical abstract

Lipopolysaccharide (LPS)‐induced sepsis‐associated acute kidney injury (SA‐AKI) is a model of clinical serious care syndrome, with high morbidity and mortality. Tacrolimus (TAC), a novel immunosuppressant that inhibits inflammatory response, plays a pivotal role in kidney diseases. In this study, LPS treated mice and cultured podocytes were used as the models of SA‐AKI in vivo and in vitro, respectively. Medium‐ and high‐dose TAC administration significantly attenuated renal function and renal pathological manifestations at 12, 24 and 48 h after LPS treatment in mice. Moreover, the Toll‐like receptor 4 (TLR4)/myeloid differential protein‐88 (MyD88)/nuclear factor‐kappa (NF‐κB) signalling pathway was also dramatically inhibited by medium‐ and high‐dose TAC administration at 12, 24 and 48 h of LPS treatment mice. In addition, TAC reversed LPS‐induced podocyte cytoskeletal injury and podocyte migratory capability. Our findings indicate that TAC has protective effects against LPS‐induced AKI by inhibiting TLR4/MyD88/NF‐κB signalling pathway and podocyte dysfunction, providing another potential therapeutic effects for the LPS‐induced SA‐AKI.

The high renewables penetration results in increased imbalance volumes and balancing actions due to system stability requirements. The balancing market (BM) primarily turns down renewable generation and turns up traditional carbon-intensive generation in response to real-time energy imbalance. Existing dual-stage market mechanisms conflict with the carbon reduction trajectory by implementing balancing actions regardless of their carbon footprint. This paper proposes a novel carbon-oriented BM model to coordinate the environmental targets in the dayahead (DA) and real-time BMs. The emissions of dispatchable generators and flexible loads are distinguished by their operation modes and flexibility types, respectively. Carbon signals are incorporated into their bid/offer prices through the proposed carbon emission flow (CEF) model. By integrating these carbon incentives, the dual-stage market model is formulated to minimize economic and environmental costs. Simulation results demonstrate that, overall, although the proposed BM mechanism results in an increased cost of balancing services (159.10 m£), there is a concurrent larger drop in carbon costs (294.14 m£), resulting in a reduction in total cost. It enables system operators to incentivize decarbonized energy resources in DA scheduling and real-time balancing actions.

(1) Background: There are few studies on people at high risk for clinical pancreatic cancer (PC). We aimed to explore the risk factors of PC and establish a scale for identifying high-risk populations of clinical PC. (2) Methods: We conducted a matched case-control study, retrospectively collecting demographic data and common clinical indicators from all subjects. Logistic regression was used to explore the risk factors of PC. Based on these factors, we created a high-risk population rating scale, which showed a higher diagnostic value. (3) Results: 385 cases and 428 controls were finally enrolled in our study. Multivariate analysis showed that body mass index (BMI) below 18.5 kg/m2 (OR 5.944, 95%CI: 1.759~20.084), smoking (OR 2.745, 95%CI: 1.555~4.844), new-onset diabetes (OR 5.239, 95%CI: 2.091~13.125), low high-density lipoprotein cholesterol (HDL-C) levels (OR 1.790, 95%CI: 1.044~3.069), and carbohydrate antigen 19-9 (CA19-9) levels no less than 35 U/mL (OR 160.328, 95%CI: 83.392~308.243) were associated with an increased risk of PC, whereas high total cholesterol (TC) levels were related to a lower risk of PC (OR 0.392, 95%CI: 0.211~0.730). The high-risk population scale, whose area under the receiver operating curve reached 0.948 (p < 0.001), showed a greater clinical diagnostic value. (4) Conclusions: Smoking history, new-onset diabetes, BMI, TC, HDL-C, and CA19-9 levels were associated with the risk of PC. The high-risk population rating scale might be used for early clinical PC screening.

High penetration of renewable energy generation (REG) in the distribution system increases both the power uncertainty at a given interval and the power variation between two intervals. Reserve markets addressing power uncertainty have been widely investigated. However, there is a lack of market mechanisms regarding the power variation of the load and REGs. This paper thus defines a planned ramping (PR) product to follow the net load variation and extends the local energy market to including the trading of PR products. Players are economically compensated for their PR products. Bidding models of dispatchable generators and flexible load aggregators in the joint market are investigated. To solve the market problem in polynomial time, a distributed market clearing method is developed based on the ADMM algorithm. The joint market is tested on a modified IEEE 33-bus system. It verifies that introducing the PR market can encourage flexible loads to provide more PR service to accommodate the net load variation. As such, the ramping cost of dispatchable generators is reduced by 29.09% in the test case. The planned energy curtailment from REG is also reduced. The computational efficiency of the proposed distributed clearing method is validated by comparing it with a centralized method.

International audience; In order to solve the problem of control performance degradation caused by time delay in the wave compensation control system, the vessel heave motion displacement needs multi-step predictability because different wave compensation control systems have different delay response times. Inspired by the flexible and powerful optimization capability of the Particle Swarm Optimization (PSO) algorithm, this paper proposes a hybrid model of PSO algorithm and autoregressive moving average (ARMA) model to predict the vessel heave motion at different sea states. The fitness function for the ARMA model parameter optimization problem is formulated through the error function created by residuals squares sum, and the optimization of the ARMA prediction model parameter value is carried out with an effective global search technique based on the PSO algorithm. Simulations are performed with filed data, the results show that the PSO algorithm optimizing the ARMA model parameters to predict vessel heave motion is effective and it can get satisfying precision. In addition, the PSO_ARMA prediction model has excellent robustness, it can not only adapt to the prediction of vessel heave motion under certain conditions but also adapt to the prediction of various sea states.

Objective: We investigated the influence of the coronavirus disease (COVID-19) pandemic on the number of patients with acute ischemic stroke who received intravenous thrombolytic therapy (ITT) in Dalian, China, in 2020. Methods: This retrospective descriptive study examined 13 stroke emergency map-participating hospitals in Dalian from February 1, 2020, to August 31, 2020. In this “stroke emergency map” of China, patients follow the official WeChat “Stroke Map” account and dial 120 for emergency medical services. We analyzed the number of patients with acute ischemic stroke who underwent ITT. In particular, we examined the onset-to-door time, door-to-needle time (DNT), onset-to-needle time, modes of transportation to the hospital, and National Institutes of Health Stroke Scale (NIHSS) scores before and after ITT. Data were collected for the aforementioned period and compared with the 2021 baseline data from the same period. The Mann‒Whitney U test was performed for data analysis. Results: Compared with the data from 2020, the number of patients with acute ischemic stroke who underwent ITT increased (from 739 to 1719 cases) in 2021, as did the DNT (from 59 to 45 minutes; P=0.002). Moreover, 83.9% of patients presented to the hospital without ambulance transport versus 81.1% of patients in the 2021 non-COVID-19 pandemic period. Patients with NIHSS scores of 6-14 were more likely to call an ambulance for transport to the hospital than to self-admit to the emergency department. Conclusions: During the 2020 COVID-19 pandemic, the DNT increased owing to increased surveillance of fever. Furthermore, the number of patients with acute ischemic stroke who underwent ITT also increased in 2021. However, these increases benefited from both the “stroke emergency map” of China and the “green channel,” a novel treatment approach that focuses on the rational design of the rescue process.

This study aimed to identify the association of protein coding and long non coding RNA genes with immunotherapy response in melanoma. Based on RNA sequencing data of melanoma specimens, the expression levels of protein coding and long non coding RNA genes were calculated using the Kallisto RNA-seq quantification method, and differently expressed genes were detected using the DESeq2 method. Cox proportional hazards regression was used to evaluate the effects of gene expression on survival. According to the clinical data of 14 patients with drug response and 11 patients without drug response, 18 protein coding genes and 14 long non coding RNAs showed differential expressions (multiple of difference > 2 and P < 0.01 after correction), among which the coding genes of differential expression were significantly enriched through the process of cell adhesion (P < 0.01). The results of survival analysis showed that 18 coding genes and 14 long non coding RNA genes had significant effects on patient survival (P < 0.01). In this study, magnetic nanoparticles can be used to extract genomic DNA and total RNA due to their paramagnetism and biocompatibility, then transcriptome high-throughput sequencing was performed. The method has the advantages of removing dangerous reagents such as phenol and chloroform, replacing inorganic coating such as silica with organic oil, and shortening reaction time. Protein coding and long non coding RNA genes as well as magnetic nanoparticles may serve as potential cancer immune biomarker targets for developing future oncological treatments.

Traditional system investment decision is costly and hard to reverse. This is aggravated by uncertainties from flexible load and renewables (FLR), which impact the accuracy of network investment decisions and could trigger a high asset risk. Thus, system operators have the incentive to postpone network reinforcement, and ‘wait and see’ whether the request of investment can be reduced or delayed with new information. This paper proposes a novel method to evaluate network investment horizon deferral based on the trade-off between waiting profit and waiting cost under FLR uncertainties. Although deferring investment leads to waiting cost, it is worthy to wait if the cost is smaller than the waiting profits. To capture the impact of FLR uncertainties on system investment, nodal uncertainties are converted into branch flow uncertainties based on a combined cumulant and Gram-Charlier expansion method. The waiting cost is quantified by the options’ cost based on real options method and waiting profit is from asset present value reduction due to the deferral. Thus, by paying waiting cost, current investment cost can be reserved until uncertainties are reduced to an acceptable level. The waiting time is evaluated by Sharp ratio and expected return, determined by the waiting cost and uncertainty level. The results show that paying waiting cost is an economical way to reduce the impact of uncertainty and avoid hastily investment.

Objective To explore the features and risk factors of bacterial skin infections (BSIs) in hospitalized patients with bullous pemphigoid (BP). Methods Records were retrospectively reviewed for 110 hospitalized patients with BP admitted to Peking University First Hospital between 2013 and 2019. Bacterial species and drug resistance were assessed, and then the underlying risk factors for BSIs were evaluated. Results Infections were present in 40% (44/110) of the patients. Staphylococcus aureus (72.7%, 32/44) was the most common bacterium, and it was highly resistant to penicillin (81.3%, 26/32), erythromycin (62.5%, 20/32), and clindamycin (56.3%, 18/32), but 100.0% sensitive to vancomycin and tigecycline. Coronary heart disease (P = .02; odds ratio [OR], 12.68), multisystem comorbidities (P = .02; OR, 3.67), hypoalbuminemia (P = .04; OR, 3.70), high levels of anti-BP180 antibodies (>112.4 U/mL; P = .003; OR, 6.43), and season (spring: reference; summer: P = .002; OR, 23.58; autumn: P = .02; OR, 12.19; winter: P = .02; OR, 13.19) were significantly associated with BSIs. Conclusions Hospitalized patients with BP had a high incidence of BSIs, and those patients with underlying risk factors require careful management to prevent and control BSIs.

We present the first gridded and temporally continuous quantitative pollen-based plant-cover reconstruction for temperate and northern sub-tropical China over the Holocene (11.7 ka BP to present) using the Regional Estimates of Vegetation Abundance from Large Sites (REVEALS) model. The objective is to provide a dataset of pollen-based land cover for the last ca. twelve millennia suitable for palaeoclimate modeling and evaluation of simulated past vegetation cover from dynamic vegetation models and anthropogenic land-cover change (ALCC) scenarios. The REVEALS reconstruction was achieved using 94 selected pollen records from lakes and bogs at a 1°×1° spatial scale and a temporal resolution of 500 years between 11.7 and 0.7 ka BP, and three recent time windows (0.7–0.35 ka BP, 0.35–0.1 ka BP, and 0.1 ka BP–present). The dataset includes REVEALS estimates of cover and their standard errors (SEs) for 27 plant taxa in 75 1°×1° grid cells distributed within the study region. The 27 plant taxa were also grouped into six plant functional types and three land-cover types (coniferous trees CT, broadleaved trees BT, and C3 herbs C3H/open land OL), and their REVEALS estimates of cover and related SEs were calculated. We describe the protocol used for the selection of pollen records and the REVEALS application (with parameter setting), and explain the major rationales behind the protocol. As an illustration we present, for eight selected time windows, gridded maps of the pollen-based REVEALS estimates of cover for the three land-cover types (CT, BT, and C3H/OL). We then discuss the reliability and limitations of the Chinese dataset of Holocene gridded REVEALS plant-cover, and its current and potential uses. The dataset is available at the National Tibetan Plateau Data Center (TPDC; https://data.tpdc.ac.cn/en/disallow/d18d2b7e-25fe-49da-b1bd-2be6014162b0/).

Background The biological activity and regenerative medicine of bone marrow mesenchymal stem cells (BMSCs) have been focal topics in the broad fields of diabetic wound repair. However, the molecular mechanisms are still largely elusive for other cellular processes that are regulated during BMSC treatment. Our previous studies have shown that hypoxia is not only a typical pathological phenomenon of wounds but also exerts a vital regulatory effect on cellular bioactivity. In this study, the beneficial effects of hypoxic BMSCs on the cellular behaviors of epidermal cells and diabetic wound healing were investigated. Method The viability and secretion ability of hypoxic BMSCs were detected. The autophagy, proliferation and migration of HaCaT cells cultured with hypoxic BMSCs-derived conditioned medium were assessed by estimating the expression of autophagy-related proteins, MTS, EdU proliferation and scratch assays. And the role of the SMAD signaling pathway during hypoxic BMSC-evoked HaCaT cell autophagy was explored through a series of in vitro gain- and loss-of-function experiments. Finally, the therapeutic effects of hypoxic BMSCs were evaluated using full-thickness cutaneous diabetic wound model. Results First, we demonstrated that hypoxic conditions intensify HIF-1α-mediated TGF-β1 secretion by BMSCs. Then, the further data revealed that BMSC-derived TGF-β1 was responsible for the activation of epidermal cell autophagy, which contributed to the induction of epidermal cell proliferation and migration. Here, the SMAD signaling pathway was identified as downstream of BMSC-derived TGF-β1 to regulate HaCaT cell autophagy. Moreover, the administration of BMSCs to diabetic wounds increased epidermal autophagy and the rate of re-epithelialization, leading to accelerated healing, and these effects were significantly attenuated, accompanied by the downregulation of Smad2 phosphorylation levels due to TGF-β1 interference in BMSCs. Conclusion In this report, we present evidence that uncovers a previously unidentified role of hypoxic BMSCs in regulating epidermal cell autophagy. The findings demonstrate that BMSC-based treatment by restoring epidermal cell autophagy could be an attractive therapeutic strategy for diabetic wounds and that the process is mediated by the HIF-1α/TGF-β1/SMAD pathway.

The screening yield and related cost of a risk-adapted screening approach compared with established screening strategies in population-based colorectal cancer (CRC) screening are not clear.We randomly allocated 19,373 participants into 1 of the 3 screening arms in a 1:2:2 ratio: (1) one-time colonoscopy (n = 3883); (2) annual fecal immunochemical test (FIT) (n = 7793); (3) annual risk-adapted screening (n = 7697), in which, based on the risk-stratification score, high-risk participants were referred for colonoscopy and low-risk ones were referred for FIT. Three consecutive screening rounds were conducted for both the FIT and the risk-adapted screening arms. Follow-up to trace the health outcome for all the participants was conducted over the 3-year study period. The detection rate of advanced colorectal neoplasia (CRC and advanced precancerous lesions) was the main outcome. The trial was registered in the Chinese Clinical Trial Registry (number: ChiCTR1800015506).In the colonoscopy, FIT, and risk-adapted screening arms over 3 screening rounds, the participation rates were 42.4%, 99.3%, and 89.2%, respectively; the detection rates for advanced neoplasm (intention-to-treat analysis) were 2.76%, 2.17%, and 2.35%, respectively, with an odds ratio (OR)The risk-adapted approach is a feasible and cost-favorable strategy for population-based CRC screening and therefore could complement the well-established one-time colonoscopy and annual repeated FIT screening strategies. (Chinese Clinical Trial Registry; ChiCTR1800015506).