Glial cells outnumber neurons in the brain and play important roles in the neuroinflammation that accompanies brain damage in neurodegenerative diseases. In Parkinson’s disease (PD), dopaminergic ...neuronal loss is accompanied by inflammatory changes in microglia, astrocytes, innate immune cells, and infiltrating peripheral immune cells. Neuroinflammation is probably a fundamental immune response to protect neurons from harm and compensate for neuronal damage, but at the same time, its neurotoxic effects exacerbate neuron damage. Furthermore, neuroinflammatory response is regulated by immune cells, such as microglia, astrocytes, and peripheral immune cells, and by cytokines and chemokines. Accordingly, it is crucial that we understand how such immune cells in the brain regulate neuroinflammatory responses in PD pathology. This review describes the roles played by glia-mediated neuroinflammation in PD, both good and bad, and the therapeutic strategies used to treat PD.
Organic solar cells have obtained a prodigious amount of attention in photovoltaic research due to their unique features of light weight, low cost, eco-friendliness, and semitransparency. A rising ...trend in this field is the development of all-small-molecules organic solar cells (ASM-OSCs) due to their merits of excellent batch-to-batch reproducibility, well-defined structures, and simple purification. Among the numerous organic photovoltaic (OPV) materials, benzodithiophene (BDT)-based small molecules have come to the fore in achieving outstanding power conversion efficiency (PCE) and breaking the 17% efficiency barrier in single-junction OPV devices, indicating the significant potential of this class of materials in commercial photovoltaic applications. This review specially focuses on up-to-date information about improvements in BDT-based ASM-OSCs since 2011 and provides an outlook on the most significant challenges that remain in the field. We believe there will be more exciting BDT-based photovoltaic materials and devices developed in the near future.
Sensitive detection of near‐infrared (NIR) light enables many important applications in both research and industry. Current organic photodetectors suffer from low NIR sensitivity typically due to ...early absorption cutoff, low responsivity, and/or large dark/noise current under bias. Herein, organic photodetectors based on a novel ultranarrow‐bandgap nonfullerene acceptor, CO1‐4Cl, are presented, showcasing a remarkable responsivity over 0.5 A W−1 in the NIR spectral region (920–960 nm), which is the highest among organic photodiodes. By effectively delaying the onset of the space charge limited current and suppressing the shunt leakage current, the optimized devices show a large specific detectivity around 1012 Jones for NIR spectral region up to 1010 nm, close to that of a commercial Si photodiode. The presented photodetectors can also be integrated in photoplethysmography for real‐time heart‐rate monitoring, suggesting its potential for practical applications.
Highly efficient near‐infrared (NIR) detection is realized with solution‐processed bulk‐heterojunction organic photodetectors based on a novel ultranarrow‐bandgap nonfullerene acceptor. The photodetectors show extraordinary responsivity in the NIR region of 920–940 nm, good linearity, and fast response. The photodetectors also compete favorably in detectivity with a commercial silicon photodiode and are applicable to photoplethysmography.
Mental stress can lead to traffic accidents by reducing a driver's concentration or increasing fatigue while driving. In recent years, demand for methods to detect drivers' stress in advance to ...prevent dangerous situations increased. Thus, we propose a novel method for detecting driving stress using nonlinear representations of short-term (30 s or less) physiological signals for multimodal convolutional neural networks (CNNs). Specifically, from hand/foot galvanic skin response (HGSR, FGSR) and heart rate (HR) short-term input signals, first, we generate corresponding two-dimensional nonlinear representations called continuous recurrence plots (Cont-RPs). Second, from the Cont-RPs, we use multimodal CNNs to automatically extract FGSR, HGSR, and HR signal representative features that can effectively differentiate between stressed and relaxed states. Lastly, we concatenate the three extracted features into one integrated representation vector, which we feed to a fully connected layer to perform classification. For the evaluation, we use a public stress dataset collected from actual driving environments. Experimental results show that the proposed method demonstrates superior performance for 30-s signals, with an overall accuracy of 95.67%, an approximately 2.5-3% improvement compared with that of previous works. Additionally, for 10-s signals, the proposed method achieves 92.33% classification accuracy, which is similar to or better than the performance of other methods using long-term signals (over 100 s).
Recent research efforts on solution‐processed semitransparent organic solar cells (OSCs) are presented. Essential properties of organic donor:acceptor bulk heterojunction blends and electrode ...materials, required for the combination of simultaneous high power conversion efficiency (PCE) and average visible transmittance of photovoltaic devices, are presented from the materials science and device engineering points of view. Aspects of optical perception, charge generation–recombination, and extraction processes relevant for semitransparent OSCs are also discussed in detail. Furthermore, the theoretical limits of PCE for fully transparent OSCs, compared to the performance of the best reported semitransparent OSCs, and options for further optimization are discussed.
Flexible bandgap engineering is a crucial material science achievement that opens possibilities in the design of organic bulk heterojunctions for semitransparent photovoltaics. An additional feature of novel polymer:nonfullerene acceptor blends is efficient free‐charge‐carrier generation at small energetic offsets. These material properties are considered in conjunction with achievements in device physics and engineering of organic semitransparent solar cells.
Precision medicine approaches in pancreatic ductal adenocarcinoma (PDAC) are imperative for improving disease outcomes. With molecular subtypes of PDAC gaining relevance in the context of therapeutic ...stratification, the ability to characterize heterogeneity of cancer-specific gene expression patterns is of great interest. In addition, understanding patterns of immune evasion within PDAC is of importance as novel immunotherapeutic strategies are developed.
Single-cell RNA sequencing (scRNA-seq) is readily applicable to limited biopsies from human primary and metastatic PDAC and identifies most cancers as being an admixture of previously described epithelial transcriptomic subtypes.
Integrative analyses of our data provide an in-depth characterization of the heterogeneity within the tumor microenvironment, including cancer-associated fibroblast subclasses, and predicts for a multitude of ligand-receptor interactions, revealing potential targets for immunotherapy approaches.
Our analysis demonstrates that the use of
biopsies from patients with PDAC paired with scRNA-seq may facilitate therapeutic prediction from limited biopsy samples.
A novel design of a double-tube steam methane reforming (SMR) reactor was evaluated in terms of conversion and reactor temperature, compared with the conventional, single-tube, fixed bed reactor. The ...heat from the reformate could be recovered through the double-tube reactor, which increased the conversion from 71.7 to 89.3% and lowered the reactor outlet temperature from 732.7 to 674.5 °C. An actual plant was then designed, wherein the entire operating process was tested using the double-tube reactor, which produced 100 N m3/h of pure hydrogen. Last, to maximize the thermal efficiency and to achieve a hydrogen-production rate of >100 N m3/h, the operating conditions were optimized with the decision variables and constraints based on actual operating experiences. Consequently, our developed optimal SMR system gave a thermal efficiency of 81.3%, higher than that of the current commercial products (approximately 70%), and achieved a hydrogen-production rate of 124.8 N m3/h.
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Photoelectrochemical water splitting is the most efficient green engineering approach to convert the sun light into hydrogen energy. The formation of high surface area core-shell ...heterojunction with enhanced light-harvesting efficiency, elevated charge separation, and transport are key parameters in achieving the ideal water splitting performance of the photoanode. Herein, we demonstrate a first green engineering interfacial growth of the BiVO4 nanoparticles onto self-assembled WO3 nanoplates forming WO3/BiVO4 core-shell heterojunction for efficient PEC water splitting performance. The three different WO3 nanostructures (nanoplates, nanobricks, and stacked nanosheets) were self-assembled on fluorine doped tin oxide glass substrates via hydrothermal route at various pH (0.8–1.2) of the solutions. In comparison to nanobricks and stacked nanosheets, WO3 nanoplates displayed considerably elevated photocurrent density. Moreover, a simple and low cost green approach of modified chemical bath deposition technique was established for the optimal decoration of a BiVO4 nanoparticles on vertically aligned WO3 nanoplates. The boosted photoelectrochemical current density of 1.7 mA cm−2 at 1.23 V vs. reversible hydrogen electrode (RHE) under AM 1.5 G illumination was achieved for the WO3/BiVO4 heterojunction which can be attributed to a suitable band alignment for the efficient charge transfer from BiVO4 to WO3, increased light harvesting capability of outer BiVO4 layer, and high charge transfer efficiency of WO3 nanoplates.
Long-lived “memory-like” NK cells have been identified in individuals infected by human cytomegalovirus (HCMV), but little is known about how the memory-like NK cell pool is formed. Here, we have ...shown that HCMV-infected individuals have several distinct subsets of memory-like NK cells that are often deficient for multiple transcription factors and signaling proteins, including tyrosine kinase SYK, for which the reduced expression was stable over time and correlated with epigenetic modification of the gene promoter. Deficient expression of these proteins was largely confined to the recently discovered FcRγ-deficient NK cells that display enhanced antibody-dependent functional activity. Importantly, FcRγ-deficient NK cells exhibited robust preferential expansion in response to virus-infected cells (both HCMV and influenza) in an antibody-dependent manner. These findings suggest that the memory-like NK cell pool is shaped and maintained by a mechanism that involves both epigenetic modification of gene expression and antibody-dependent expansion.
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•NK cells with multiple protein deficiencies are present in HCMV-infected individuals•SYK deficiency is associated with hyper-methylation of the gene promoter•Memory-like NK cells have protein deficiencies in combination with FcRγ deficiency•FcRγ-deficient NK cells expand preferentially in an antibody-dependent manner
Long-lived “memory-like” NK cells have been identified in HCMV-infected individuals at variable frequencies, but little is known about how this NK cell pool is formed. Kim and colleagues show data that support epigenetic modifications and antibody-dependent expansion as mechanisms underlying the formation of this memory-like NK cell pool.
This paper aims to investigate the robust and distinguishable pattern of heart rate variability (HRV) signals, acquired from wearable electrocardiogram (ECG) or photoplethysmogram (PPG) sensors, for ...driver drowsiness detection. As wearable sensors are so vulnerable to slight movement, they often produce more noise in signals. Thus, from noisy HRV signals, we need to find good traits that differentiate well between drowsy and awake states. To this end, we explored three types of recurrence plots (RPs) generated from the R–R intervals (RRIs) of heartbeats: Bin-RP, Cont-RP, and ReLU-RP. Here Bin-RP is a binary recurrence plot, Cont-RP is a continuous recurrence plot, and ReLU-RP is a thresholded recurrence plot obtained by filtering Cont-RP with a modified rectified linear unit (ReLU) function. By utilizing each of these RPs as input features to a convolutional neural network (CNN), we examined their usefulness for drowsy/awake classification. For experiments, we collected RRIs at drowsy and awake conditions with an ECG sensor of the Polar H7 strap and a PPG sensor of the Microsoft (MS) band 2 in a virtual driving environment. The results showed that ReLU-RP is the most distinct and reliable pattern for drowsiness detection, regardless of sensor types (i.e., ECG or PPG). In particular, the ReLU-RP based CNN models showed their superiority to other conventional models, providing approximately 6–17% better accuracy for ECG and 4–14% for PPG in drowsy/awake classification.
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