In terms of strong light-polarization coupling, ferroelectric materials with bulk photovoltaic effects afford a promising avenue for optoelectronic devices. However, due to severe polarization ...deterioration caused by leakage current of photoexcited carriers, most of ferroelectrics are merely capable of absorbing 8-20% of visible-light spectra. Ferroelectrics with the narrow bandgap (<2.0 eV) are still scarce, hindering their practical applications. Here, we present a lead-iodide hybrid biaxial ferroelectric, (isopentylammonium)
(ethylammonium)
Pb
I
, which shows large spontaneous polarization (~5.2 μC/cm
) and a narrow direct bandgap (~1.80 eV). Particularly, the symmetry breaking of 4/mmmFmm2 species results in its biaxial attributes, which has four equivalent polar directions. Accordingly, exceptional in-plane photovoltaic effects are exploited along the crystallographic 001 and 010 axes directions inside the crystallographic bc-plane. The coupling between ferroelectricity and photovoltaic effects endows great possibility toward self-driven photodetection. This study sheds light on future optoelectronic device applications.
Achieving white‐light emission, especially white circularly polarized luminescence (CPL) from a single‐phase material is challenging. Herein, a pair of chiral CuI coordination polymers (1‐M and 1‐P) ...have been prepared by the asymmetrical assembly of achiral ligands and Cu2I2 clusters. The compounds display dual emission bands and can be used as single‐phase white‐light phosphors, achieving a “warm”‐white‐light‐emitting diode with an ultra‐high color rendering index (CRI) of 93.4 and an appropriate correlated color temperature (CCT) of 3632 K. Meanwhile, corresponding CPL signals with maximum dissymmetry factor |glum|=8×10−3 have been observed. Hence, intrinsic white‐light emission and CPL have been realized simultaneously in coordination polymers for the first time. This work gains insight into the nature of chiral assembly from achiral units and offers a prospect for the development of single‐phase white‐CPL materials.
A pair of chiral CuI coordination polymers (1‐P/M) were produced from achiral precursors by crystallization‐driven symmetry‐breaking assembly. The enantiomers feature unique helical layered structures and tunable dual‐emission photoluminescence, achieving intrinsic “warm”‐white emitting with an ultra‐high color rendering index (93.4) and circularly polarized luminescence with a remarkable dissymmetry factor (8×10−3) simultaneously.
Sepsis-associated encephalopathy (SAE) is a common complication that leads to long-term cognitive impairments and increased mortality in sepsis survivors. The mechanisms underlying this complication ...remain unclear and an effective intervention is lacking. Accumulating evidence suggests the nucleotide-binding domain-like receptor protein3 (NLRP3)/caspase-1 pathway is involved in several neurodegenerative diseases. Thus, we hypothesized that the NLRP3/caspase-1 pathway is involved in NLRP3-mediated pyroptosis, maturation and release of inflammatory cytokines, and cognitive deficits in SAE. We used the NLRP3 inhibitor MCC950 and the caspase-1 inhibitor Ac-YVAD-CMK to study the role of the NLRP3/caspase-1 pathway in pyroptosis and cognitive deficits in a mouse model of SAE. Mice were randomly assigned to one of six groups: sham+saline, sham+MCC950, sham+Ac-YVAD-CMK, cecal ligation and puncture (CLP)+saline, CLP+MCC950, and CLP+Ac-YVAD-CMK. Surviving mice underwent behavioral tests or had hippocampal tissues collected for histochemical analysis and biochemical assays. Our results show that CLP-induced hippocampus-dependent memory deficits are accompanied by increased NLRP3 and caspase-1 positive cells, and augmented protein levels of NLRP3, caspase-1, gasdermin-D, and pro-inflammatory cytokines in the hippocampus. In addition, administration of MCC950 or Ac-YVAD-CMK rescues cognitive deficits and ameliorates increased hippocampal NLRP3-mediated neuronal pyroptosis and pro-inflammatory cytokines. Our results suggest that the NLRP3/caspase-1 pathway-induced pyroptosis mediates cognitive deficits in a mouse model of SAE.
The long-term pulmonary function and related physiological characteristics of COVID-19 survivors have not been studied in depth, thus many aspects are not understood.
COVID-19 survivors were ...recruited for high resolution computed tomography (HRCT) of the thorax, lung function and serum levels of SARS-CoV-2 IgG antibody tests 3 months after discharge. The relationship between the clinical characteristics and the pulmonary function or CT scores were investigated.
Fifty-five recovered patients participated in this study. SARS-CoV-2 infection related symptoms were detected in 35 of them and different degrees of radiological abnormalities were detected in 39 patients. Urea nitrogen concentration at admission was associated with the presence of CT abnormalities (P = 0.046, OR 7.149, 95% CI 1.038 to 49.216). Lung function abnormalities were detected in 14 patients and the measurement of D-dimer levels at admission may be useful for prediction of impaired diffusion defect (P = 0.031, OR 1.066, 95% CI 1.006 to 1.129). Of all the subjects, 47 of 55 patients tested positive for SARS-CoV-2 IgG in serum, among which the generation of Immunoglobulin G (IgG) antibody in female patients was stronger than male patients in infection rehabilitation phase.
Radiological and physiological abnormalities were still found in a considerable proportion of COVID-19 survivors without critical cases 3 months after discharge. Higher level of D-dimer on admission could effectively predict impaired DLCO after 3 months discharge. It is necessary to follow up the COVID-19 patients to appropriately manage any persistent or emerging long-term sequelae.
Key Scientific Research Projects of Henan Higher Education Institutions
Semantic segmentation is a key step in scene understanding for autonomous driving. Although deep learning has significantly improved the segmentation accuracy, current high-quality models such as ...PSPNet and DeepLabV3 are inefficient given their complex architectures and reliance on multi-scale inputs. Thus, it is difficult to apply them to real-time or practical applications. On the other hand, existing real-time methods cannot yet produce satisfactory results on small objects such as traffic lights, which are imperative to safe autonomous driving. In this paper, we improve the performance of real-time semantic segmentation from two perspectives, methodology and data. Specifically, we propose a real-time segmentation model coined Narrow Deep Network (NDNet) and build a synthetic dataset by inserting additional small objects into the training images. The proposed method achieves 65.7% mean intersection over union (mIoU) on the Cityscapes test set with only 8.4G floating-point operations (FLOPs) on <inline-formula> <tex-math notation="LaTeX">1024\times 2048 </tex-math></inline-formula> inputs. Furthermore, by re-training the existing PSPNet and DeepLabV3 models on our synthetic dataset, we obtained an average 2% mIoU improvement on small objects.
Magnetic lanthanide–transition-metal hybrid materials have enjoyed increasing attraction because they not only provide examples for studying magnetic coupling involving lanthanide ions but also ...exhibit novel magnetic behavior which render them candidates for future devices for information storage and quantum computation. Herein, we review the structures and magnetic properties of lanthanide–transition-metal hybrid materials that are categorized based on the structural features and organic ligands used. The review pays special attention to the examples which show magnetic slow relaxation since these render them to be potentially applied as devices for information storage.
An unexpected rhodium-catalyzed regioselective C–H chlorination of 7-azaindoles was developed using 1,2-dichloroethane (DCE) as a chlorinating agent and 7-azaindole as the directing group. This ...protocol provides an efficient access to ortho-chlorinated azaindoles with operational simplicity, good functional group tolerance, and a wide substrate scope.
Sorafenib is one a first‐line therapeutic drugs for advanced hepatocellular carcinoma (HCC). However, only 30% of patients benefit from sorafenib due to drug resistance. We and other groups have ...revealed that nuclear factor I B (NFIB) regulates liver regeneration and carcinogenesis, but its role in drug resistance is poorly known. We found that NFIB was more upregulated in sorafenib‐resistant SMMC‐7721 cells compared to parental cells. NFIB knockdown not only sensitized drug‐resistant cells to sorafenib but also inhibited the proliferation and invasion of these cells. Meanwhile, NFIB promoted the proliferation and invasion of HCC cells in vitro and facilitated tumor growth and metastasis in vivo. Knocking down NFIB synergetically inhibited tumor growth with sorafenib. Mechanically, gene expression profiling and subsequent verification experiments proved that NFIB could bind with the promoter region of a complex I inhibitor NDUFA4L2 and promote its transcription. Transcriptional upregulation of NDUFA4L2 by NFIB could thus inhibit the sorafenib‐induced reactive oxygen species accumulation. Finally, we found that NFIB was highly expressed in HCC tissues, and high NFIB expression level was associated with macrovascular invasion, advanced tumor stage, and poor prognosis of HCC patients (n = 156). In summary, we demonstrated that NFIB could transcriptionally upregulate NDUFA4L2 to enhance both intrinsic and acquired sorafenib resistance of HCC cells by reducing reactive oxygen species induction.
NFIB could directly promote transcription of NDUFA4L2 to reduce sorafenib‐induced ROS accumulation. High NFIB expression was associated with poor prognosis of HCC patients.
Network structures based on Star‐of‐David catenanes with multiple superior functionalities have been so far elusive, although numerous topologically interesting networks are synthesized. Here, a ...metal–organic framework featuring fused Star‐of‐David catenanes is reported. Two triangular metallacycles with opposite handedness are triply intertwined forming a Star‐of‐David catenane. Each catenane fuses with its six neighbors to generate a porous twofold intercatenated gyroid framework. The compound possesses exceptional stability and exhibits multiple functionalities including highly selective CO2 capture, high proton conductivity, and coexistence of slow magnetic relaxation and long‐range ordering.
A metal–organic framework, which represents the rare networks composed of Star‐of‐David catenanes, is designed. The structural complexity of the unique framework highlights different facets of the same compound. Remarkably, the material shows highly selective CO2 capture for a molecular‐sieving effect, superionic proton conductivity, and coexistence of slow magnetic relaxation and long‐range ordering.
To develop an artificial intelligence (AI)-based algorithm which can automatically detect food items from images acquired by an egocentric wearable camera for dietary assessment.
To study human diet ...and lifestyle, large sets of egocentric images were acquired using a wearable device, called eButton, from free-living individuals. Three thousand nine hundred images containing real-world activities, which formed eButton data set 1, were manually selected from thirty subjects. eButton data set 2 contained 29 515 images acquired from a research participant in a week-long unrestricted recording. They included both food- and non-food-related real-life activities, such as dining at both home and restaurants, cooking, shopping, gardening, housekeeping chores, taking classes, gym exercise, etc. All images in these data sets were classified as food/non-food images based on their tags generated by a convolutional neural network.
A cross data-set test was conducted on eButton data set 1. The overall accuracy of food detection was 91·5 and 86·4 %, respectively, when one-half of data set 1 was used for training and the other half for testing. For eButton data set 2, 74·0 % sensitivity and 87·0 % specificity were obtained if both 'food' and 'drink' were considered as food images. Alternatively, if only 'food' items were considered, the sensitivity and specificity reached 85·0 and 85·8 %, respectively.
The AI technology can automatically detect foods from low-quality, wearable camera-acquired real-world egocentric images with reasonable accuracy, reducing both the burden of data processing and privacy concerns.
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