Explore the vast range of titles available.

Pancreatic stellate cells (PSCs) contribute to pancreatic ductal adenocarcinoma (PDAC) progression and therapeutic resistance, yet their detailed functions remain unclear. This study combined RNA sequencing and assay for transposase‐accessible chromatin using sequencing (ATAC‐seq) on sorted PSCs from adjacent normal and PDAC tissues to investigate their transcriptional and epigenetic activation. PSCs heterogeneity and functions are characterized through bulk, single‐cell, and spatial transcriptomes, as well as in situ sequencing. The clinical relevance of PSCs in immunotherapy is assessed using an in‐house immune‐checkpoint blockade (ICB) treatment cohort. Findings showed that stress and hypoxia signaling activated PSCs in PDAC. Three common PSCs (CPSCs) and four tumor‐associated PSCs (TPSCs) are identified, each with distinct functions. CPSCs differentiated into CCL19+ TPSCs in immune‐enriched regions, MYH11+ TPSCs in the stromal region, and PLXDC1+ TPSCs, which exhibited cancer‐associated myofibroblasts (myCAFs) phenotype linked to poor prognosis. Notably, PLXDC1+ TPSCs, located near aggressive LRRC15+ myCAFs and SPP1+ macrophages, formed a desmoplastic and immunosuppressive niche around the tumor boundary, promoting CD8 T cell exhaustion. Single‐cell transcriptomics of PDAC patients treated with ICB revealed that PLXDC1+ TPSCs correlated with poor immunotherapy efficacy. Overall, this study provides key insights into PSCs in PDAC and potential therapeutic targets. This study uncovers the activation, heterogeneity, and regulatory roles of pancreatic stellate cells (PSCs) at single‐cell and spatial levels. It further identifies PLXDC1+ PSCs near aggressive LRRC15+ cancer‐associated myofibroblasts and SPP1+ macrophages, forming a desmoplastic and immunosuppressive tumor niche that promotes CD8+ T cell exhaustion, contributing to poor immunotherapy outcomes in pancreatic cancer.

Organometallic halide perovskite solar cells (PSCs) have shown great promise as a low-cost, high-efficiency photovoltaic technology. Structural and electro-optical properties of the perovskite absorber layer are most critical to device operation characteristics. Here we present a facile fabrication of high-efficiency PSCs based on compact, large-grain, pinhole-free CH 3 NH 3 PbI 3−x Br x (MAPbI 3− x Br x ) thin films with high reproducibility. A simple methylammonium bromide (MABr) treatment via spin-coating with a proper MABr concentration converts MAPbI 3 thin films with different initial film qualities (for example, grain size and pinholes) to high-quality MAPbI 3− x Br x thin films following an Ostwald ripening process, which is strongly affected by MABr concentration and is ineffective when replacing MABr with methylammonium iodide. A higher MABr concentration enhances I–Br anion exchange reaction, yielding poorer device performance. This MABr-selective Ostwald ripening process improves cell efficiency but also enhances device stability and thus represents a simple, promising strategy for further improving PSC performance with higher reproducibility and reliability. Organolead halide perovskite optoelectronic devices require high material quality. Here, Yang et al . show that methylammonium lead iodide films can undergo Ostwald ripening and become mixed-halide films using methylammonium bromide treatment. This processing increases both the device efficiency and stability.

[This corrects the article DOI: 10.3389/fimmu.2024.1452195.].

On the issues of global environment protection, the renewable energy systems have been widely considered. The photovoltaic (PV) system converts solar power into electricity and significantly reduces the consumption of fossil fuels from environment pollution. Besides introducing new materials for the solar cells to improve the energy conversion efficiency, the maximum power point tracking (MPPT) algorithms have been developed to ensure the efficient operation of PV systems at the maximum power point (MPP) under various weather conditions. The integration of reinforcement learning and deep learning, named deep reinforcement learning (DRL), is proposed in this paper as a future tool to deal with the optimization control problems. Following the success of deep reinforcement learning (DRL) in several fields, the deep Q network (DQN) and deep deterministic policy gradient (DDPG) are proposed to harvest the MPP in PV systems, especially under a partial shading condition (PSC). Different from the reinforcement learning (RL)-based method, which is only operated with discrete state and action spaces, the methods adopted in this paper are used to deal with continuous state spaces. In this study, DQN solves the problem with discrete action spaces, while DDPG handles the continuous action spaces. The proposed methods are simulated in MATLAB/Simulink for feasibility analysis. Further tests under various input conditions with comparisons to the classical Perturb and observe (P&O) MPPT method are carried out for validation. Based on the simulation results in this study, the performance of the proposed methods is outstanding and efficient, showing its potential for further applications.

Mesenchymal stem cells (MSCs) possess a broad spectrum of therapeutic applications and have been used in clinical trials. MSCs are mainly retrieved from adult or fetal tissues. However, there are many obstacles with the use of tissue-derived MSCs, such as shortages of tissue sources, difficult and invasive retrieval methods, cell population heterogeneity, low purity, cell senescence, and loss of pluripotency and proliferative capacities over continuous passages. Therefore, other methods to obtain high-quality MSCs need to be developed to overcome the limitations of tissue-derived MSCs. Pluripotent stem cells (PSCs), including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), are considered potent sources for the derivation of MSCs. PSC-derived MSCs (PSC-MSCs) may surpass tissue-derived MSCs in proliferation capacity, immunomodulatory activity, and in vivo therapeutic applications. In this review, we will discuss basic as well as recent protocols for the production of PSC-MSCs and their in vitro and in vivo therapeutic efficacies. A better understanding of the current advances in the production of PSC-MSCs will inspire scientists to devise more efficient differentiation methods that will be a breakthrough in the clinical application of PSC-MSCs.

The vector autoregressive (VAR) model has been widely used for modeling temporal dependence in a multivariate time series. For large (and even moderate) dimensions, the number of the AR coefficients can be prohibitively large, resulting in noisy estimates, unstable predictions, and difficult-to-interpret temporal dependence. To overcome such drawbacks, we propose a two-stage approach for fitting sparse VAR (sVAR) models in which many of the AR coefficients are zero. The first stage selects nonzero AR coefficients based on an estimate of the partial spectral coherence (PSC) together with the use of BIC. The PSC is useful for quantifying the conditional relationship between marginal series in a multivariate process. A refinement second stage is then applied to further reduce the number of parameters. The performance of this two-stage approach is illustrated with simulation and real data examples. Supplementary materials for this article are available online.

Background There is continued uncertainty regarding the risks of hepato‐pancreato‐biliary cancers in patients with inflammatory bowel disease (IBD) with or without concomitant primary sclerosing cholangitis (PSC). Objective To give updated estimates on risk of hepato‐pancreato‐biliary cancers in patients with IBD, including pancreatic cancer, hepatocellular carcinoma, gall bladder cancer, and intra – and extrahepatic cholangiocarcinoma. Methods In a population‐based cohort study, we included all patients diagnosed with IBD in Norway and Sweden from 1987 to 2016. The cohort comprised of 141,960 patients, identified through hospital databases and the National Patient Register. Participants were followed through linkage to national cancer, cause of death, and population registries. We calculated absolute risk and standardized incidence ratios (SIRs) of hepato‐pancreato‐biliary cancers by PSC and other clinical characteristics. Results Of the 141,960 IBD patients, 3.2% were diagnosed with PSC. During a median follow‐up of 10.0 years, we identified 443 biliary tract cancers (SIR 5.2, 95% confidence interval [CI] 4.8–5.7), 161 hepatocellular carcinomas (SIR 2.4, 95% CI 2.0–2.7) and 282 pancreatic cancers (SIR 1.3, 95% CI 1.2–1.5). The relative risks were considerably higher in PSC‐IBD patients, with SIR of 140 (95% CI 123–159) for biliary tract, 38.6 (95% CI 29.2–50.0) for hepatocellular, and 9.0 (95% CI 6.3–12.6) for pancreatic cancer. The SIRs were still slightly increased in non‐PSC‐IBD patients, compared to the general population. For biliary tract cancer, the cumulative probability at 25 years was 15.6% in PSC‐IBD patients, and 0.4% in non‐PSC‐IBD patients. Conclusions The dramatically increased risks of hepato‐pancreato‐biliary cancers in PSC‐IBD patients support periodic surveillance for these malignancies. While much lower, the excess relative risks in non‐PSC‐IBD patients were not trivial compared to non‐IBD related risk factors.

Pluripotent stem cell (PSC)-based therapies are currently in clinical trials. However, one of the main safety concerns includes the potential for cancer formation of the PSC-derived products. Currently, the teratoma in vivo assay is accepted by regulatory agencies for identifying whether PSCs have the potential to become malignant. Yolk sac elements (YSE) are one of the elements that could arise from PSC. Whereas the other malignant element, embryonal carcinoma, is thoroughly studied, this is not the case for YSE. Therefore, more research is needed to assess the nature of YSE. We propose that it is imperative to include the formation of YSE in the safety assessment of PSC due to their close resemblance to the clinical entity of yolk sac tumor (YST), a human malignant germ cell tumor (hGCT). In this review, we extrapolate knowledge from YST to better understand YSE derived from PSC. We demonstrate that both share a similar morphology and that the same characteristic immunohistochemical markers can be used for their identification. We discuss the risk these tumors pose, thereby touching upon genetic abnormalities and gene expression that characterize them, as well as possible disease mechanisms. Integrating the molecular and immunohistochemical markers identified in this review into future research will help to better address the potential malignancy associated with PSC.

With the continuous growth of global energy demand, the development of oil and gas resources plays an increasingly important role in the international market. As a flexible mode of cooperation, joint venture plays a key role in overseas oil and gas resources development. The article introduces the purpose and significance of setting up joint ventures for overseas oil and gas resources development, and based on the main business terms and fiscal policies of the PSC (Production Sharing Contract), which is more common at the present stage, it analyzes in-depth the calculation process of the revenue distribution process and the calculation method of the efficiency indexes of the government of the resource country and the parties to the contract.

Partial shading conditions (PSC) in photovoltaic (PV) systems degrade energy harvest by generating multi-peak power-voltage (P–V) curves, trapping conventional maximum power point tracking (MPPT) algorithms at local maxima. This paper presents a Multi-Peak to Single-Peak Conversion (MSMPPT) framework that enables conventional algorithms like Perturb & Observe (P&O) and Incremental Conductance (INC) to reliably track the global maximum power point (GMPP) under PSC without structural modifications. The framework operates via two stages: dynamic estimation of optimal voltage boundaries to shrink the GMPP search space to under 10% of the original P–V range, and active voltage regulation to enforce operation within this zone, effectively transforming the multi-peak curve into a single-peak profile. The proposed MSMPP-P&O and MSMPP-INC algorithms achieve 50% faster tracking (64 ms vs. 122 ms for P&O) and near-perfect steady-state efficiency under static shading, reducing power losses below 2%. In dynamic shading scenarios with abrupt irradiance shifts, MSMPPT maintains robustness with less than 1.5 W net loss, outperforming conventional methods that incur over 30 W of power losses. By eliminating oscillations and hotspot risks through voltage regulation, the framework retains algorithmic simplicity while enhancing performance under complex shading scenarios. Validated across benchmark shading profiles, MSMPPT demonstrates fidelity without requiring additional hardware or complex optimizers. This innovation bridges the gap between conventional MPPT simplicity and partial shading resilience, offering a cost-effective, scalable solution to boost PV system reliability in shading environments.