Unveiling the Intrinsic Photophysics in Quasi-Two-Dimensional Perovskites.

The two-dimensional (2D) perovskites have drawn intensive attention due to their unique stability and outstanding optoelectronic properties. However, the debate surrounding the spatial phase distribution and band alignment among different 2D phases in the quasi-2D perovskite has created complexities in understanding the carrier dynamics, hindering material and device development. In this study, we employed highly sensitive transient absorption spectroscopy to investigate the carrier dynamics of (BA)2(MA)n-1PbnI3n+1 quasi-2D Ruddlesden-Popper perovskite thin films, nominally prepared as n = 4. We observed the carrier-density-dependent electron and hole transfer dynamics between the 2D and three-dimensional (3D) phases. Under a low carrier density within the linear response range, we successfully resolved three ultrafast processes of both electron and hole transfers, spanning from hundreds of femtoseconds to several picoseconds, tens to hundreds of picoseconds, and hundreds of picoseconds to several nanoseconds, which can be attributed to lateral-epitaxial, partial-epitaxial, and disordered-interface heterostructures between 2D and 3D phases. By considering the interplay among the phase structure, band alignment, and carrier dynamics, we have proposed material synthesis strategies aimed at enhancing the carrier transport. Our results not only provide deep insights into an accurate intrinsic photophysics of quasi-2D perovskites but also inspire advancements in the practical application of these materials.

Synergetic Electrostatic and Steric Effects in α-FAPbI3 Single Crystals For X-Ray Detection and Imaging.

It is still challenging to stabilize α-FAPbI3 perovskite for high performance optoelectrical devices. Herein, a novel strategy is proposed utilizing the synergetic electrostatic and steric effect to stabilize the α-FAPbI3 phase and suppress the ion migration. Dimethylamine (DMA+) cations are chosen as the dopant to fabricate FA0.96DMA0.04PbI3 single crystals (SCs). DFT calculations reveal that DMA+ cations can improve the stability of α-FAPbI3 phase in both thermodynamics (lower Gibbs free energy) and kinetics (higher defect formation and migration energy). The resulting SCs exhibit an environmental stability over 100 days and an extraordinary low dark current drift of 3.7 × 10-7 nA cm-1 s-1 V-1, comparable to 2D perovskite SCs. The X-ray detectors have also achieved the-state-of-the-art performance in X-ray detection and imaging. This work demonstrates the significance of electrostatic and steric effects in improving the phase and operational stability of perovskites.

X-Site Substituted 2D Cs2 Pb(SCN)2 Br2 Perovskites for X-Ray Detection.

2D Ruddlesden-Popper (RP) perovskites have been intensively investigated due to their superior stability and outstanding optoelectrical properties. However, investigations on 2D RP perovskites are mainly focused on A-site substituted perovskites and few reports are on X-site substituted perovskites especially in X-ray detection field. Here, X-site substituted 2D RP perovskite Cs2 Pb(SCN)2 Br2 polycrystalline wafers are prepared and systematically studied for X-ray detection. The obtained wafers show a large resistivity of 2.0 × 1010 Ω cm, a high ion activation energy of 0.75 eV, a small current drift of 2.39 × 10-6 nA cm-1 s-1 V-1 , and charge carrier mobility-lifetime product under X-ray as high as 1.29 × 10-4 cm2 V-1 . These merits enable Cs2 Pb(SCN)2 Br2 wafer detectors with a sensitivity of 216.3 µC Gyair -1 cm-2 , a limit of detection of 42.4 nGyair s-1 , and good imaging ability with high spatial resolution of 1.08 lp mm-1 . In addition, Cs2 Pb(SCN)2 Br2 wafer detectors demonstrate excellent operational stability under high working field up to 2100 V cm-1 after continuous X-ray irradiation with a total dose of 45.2 Gyair . The promising features such as short octahedral spacing and weak ion migration will open up a new perspective and opportunity for SCN-based 2D perovskites in X-ray detection.

Driver mutations in ADGRL3 are involved in the evolution of ependymoma.

Although there have been recent advances in the molecular pathology of ependymomas, little is known about the underlying molecular evolution during its development. Here, we assessed the clinical, pathological and molecular evolutionary process of ependymoma recurrence in a 9-year-old patient who had seven recurrences of supratentorial ependymoma and died from intracranial multiregional recurrences at the age of 19 years old. Whole-genome sequencing (WGS) of 7 tumor samples (1 primary and 6 subsequent recurrent tumors) was performed to elucidate the mutation landscape and identify potential driver mutations for tumor evolution. The genetic profiles of the seven tumor specimens showed significant heterogeneity and suggested a highly branched evolutionary pattern. The mutational signatures and chromothripsis changed with treatments. Strikingly, adhesion G protein-coupled receptor L3 (ADGRL3, also known as Latrophilins 3, LPNH3) was found to be consistently mutated during the entire disease process. However, Sanger sequencing of other 78 ependymoma patients who underwent surgery at our institution showed no genetic alteration of ADGRL3, as found in the present case. The mRNA levels of ADGRL3 were significantly lower in ependymomas (n = 36), as compared with normal brain tissue (n = 3). Grade III ependymomas had the lowest ADGRL3 expression. Moreover, ependymomas with lower mRNA level of ADGRL3 had shorter overall survival. Our findings, therefore, demonstrate a rare evolutionary process of ependymoma involving ADGRL3.

Fault Early Warning Model for High-Speed Railway Train Based on Feature Contribution and Causal Inference.

The demands for model accuracy and computing efficiency in fault warning scenarios are increasing as high-speed railway train technology continues to advance. The black box model is difficult to interpret, making it impossible for this technology to be widely adopted in the railway industry, which has strict safety regulations. This paper proposes a fault early warning machine learning model based on feature contribution and causal inference. First, the contributions of the features are calculated through the Shapley additive explanations model. Then, causal relationships are discovered through causal inference models. Finally, data from causal and high-contribution time series are applied to the model. Ablation tests are conducted with the Naïve Bayes, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and other models in order to confirm the efficiency of the method based on early warning data regarding the on-site high-speed train traction equipment circuit board failure. The findings indicate that the strategy improves the evaluation markers, including the early warning accuracy, precision, recall, and F1 score, by an average of more than 10%. There is a 35% improvement in the computing efficiency, and the model can provide feature causal graph verification for expert product decision-making.

High-sensitivity fiber-optic X-ray detectors employing gadolinium oxysulfide composites.

Radiation detection technologies have been applied in broad fields such as security inspection, medical diagnosis, environment monitoring and scientific analysis. Fiber-optic radiation detectors exhibit unique advantages including miniaturization, resistance to water, remote monitoring, and distributable detection. However, the low sensitivity and the high limit-of-detection limit its practical applications. Herein we demonstrated high-performance fiber-optic X-ray detectors with scintillating composites consisting of UV glue and uniformly distributed gadolinium oxysulfide (GADOX) powders. The impacts of the length, thickness and GADOX weight ratio of the composite coating upon the detector performance, were systematically investigated in terms of the generation and the coupling efficiency of radio-luminescence. Besides the high-performance scintillator, the scattering loss and the geometric factor greatly affected the detector performance. A higher sensitivity and lower limit-of-detection could be achieved by increasing the GADOX weight ratio and decreasing the thickness simultaneously. The optimal detector with the highest GADOX weight ratio (70%), exhibited a linear sensitivity to the X-ray dose rate within 31-1575 µGyair/s, and a low limit-of-detection of ∼0.26 µGyair/s at a tube voltage of 120 kV. The mechanism discussed here will provide insightful guidance for further development of fiber-optic radiation detectors and these promising results demonstrate the potential applications of fiber-optic detectors.

Skp2 modulates proliferation, senescence and tumorigenesis of glioma.

BACKGROUND: Gliomas represent the largest class of primary central nervous system neoplasms, many subtypes of which exhibit poor prognoses. Surgery followed by radiotherapy and chemotherapy has been used as a standard strategy but yielded unsatisfactory improvements in patient survival outcomes. The S-phase kinase protein 2 (Skp2), a critical component of the E3-ligase SCF complex, has been documented in tumorigenesis in various cancer types but its role in glioma has yet to be fully clarified. In this study, we investigated the function of Skp2 in the proliferation, stem cell maintenance, and drug sensitivity to temozolomide (TMZ) of glioma. METHODS: To investigate the role of Skp2 in the prognosis of patients with glioma, we first analyzed data in databases TCGA and GTEx. To further clarify the effect of Skp2 on glioma cell proliferation, we suppressed its level in glioblastoma (GBM) cell lines through knockdown and small molecule inhibitors (lovastatin and SZL-P1-41). We then detected cell growth, colony formation, sphere formation, drug sensitivity, and in vivo tumor formation in xenograft mice model. RESULTS: Skp2 mRNA level was higher in both low-grade glioma and GBM than normal brain tissues. The knockdown of Skp2 increased cell sensitivity to TMZ, decreased cell proliferation and tumorigenesis. In addition, Skp2 level was found increased upon stem cells enriching, while the knockdown of Skp2 led to reduced sphere numbers. Downregulation of Skp2 also induced senescence. Repurposing of lovastatin and novel compound SZL-P1-41 suppressed Skp2 effectively, and enhanced glioma cell sensitivity to TMZ in vitro and in vivo. CONCLUSION: Our data demonstrated that Skp2 modulated glioma cell proliferation in vitro and in vivo, stem cell maintenance, and cell sensitivity to TMZ, which indicated that Skp2 could be a potential target for long-term treatment.

Transferrin receptor 1 targeted optical imaging for identifying glioma margin in mouse models.

OBJECTIVE: Optical molecular imaging technology that indiscriminately detects intracranial glioblastoma (GBM) can help neurosurgeons effectively remove tumor masses. Transferrin receptor 1 (TfR 1) is a diagnostic and therapeutic target in GBM. A TfR 1-targeted peptide, CRTIGPSVC (CRT), was shown to cross the blood brain barrier (BBB) and accumulate at high levels in GBM tissues. In this study, we synthesized a TfR 1-targeted near-infrared fluorescent (NIRF) probe, Cy5-CRT, for identifying the GBM tissue margin in mouse models. METHODS: We initially confirmed the overexpression of TfR 1 in GBM and the tumor-specific homing ability of Cy5-CRT in subcutaneous and orthotopic GBM mouse models. We then examined the feasibility of Cy5-CRT for identifying the tumor margin in orthotopic GBM xenografts. Finally, we compared Cy5-CRT with the clinically used fluorescein sodium in identifying tumor margins. RESULTS: Cy5-CRT specifically accumulated in GBM tissues and detected the tumor burden with exceptional contrast in mice with orthotopic GBM, enabling fluorescence-guided GBM resection under NIRF live imaging conditions. Importantly, Cy5-CRT recognized the GBM tissue margin more clearly than fluorescein sodium. CONCLUSIONS: The TfR 1-targeted optical probe Cy5-CRT specifically differentiates tumor tissues from the surrounding normal brain with high sensitivity, indicating its potential application for the precise surgical removal of GBM.

Circular RNA hsa_circ_0076248 promotes oncogenesis of glioma by sponging miR-181a to modulate SIRT1 expression.

Glioma is one of the most common primary malignancies of the central nervous system, which has aggressive clinical behavior and a poorer prognosis. MicroRNAs (miRs) are a class of small noncoding RNAs that function as mediators of gene expression, which can be sponged by circRNA provided with a closed circular structure. Dysregulations of circular RNAs (circRNAs) and miRs have been implicated in the development and progression of glioma. In the current study, we investigated the role of circular RNA hsa_circ_0076248 in mediating the oncogenesis of glioma by sponging miR-181a to modulate silent information regulator 1 (SIRT1) expression in vitro and in vivo. The quantitative real-time polymerase chain reaction results showed that the expression of miR-181a was significantly decreased in glioma tissues and cell lines compared with normal brain tissues and normal gliocyte, respectively, and the expression of hsa_circ_0076248 and SIRT1 demonstrated the opposite. Bioinformatics analysis identified hsa_circ_0076248 could sponge miR-181a, and miR-181a could target the mRNA of SIRT1. Our results verified that downregulating hsa_circ_0076248 or upregulating miR-181a could depress the proliferation and invasion of glioma in vitro and in vivo. The experiment also showed that downregulating hsa_circ_0076248 or upregulating miR-181a could remarkably promote the temozolomide chemotherapy sensitivity. Furthermore, Western blot analysis testified that downregulating hsa_circ_0076248 or upregulating miR-181a could promote the expression of p53 and SIRT1. In summary, our study sheds light on the regulatory mechanism of hsa_circ_0076248 in glioma growth and invasion via sponging miR-181a, which downregulates the SIRT1 expression and also suggests that hsa_circ_0076248, miR-181a, and SIRT1 may serve as potential therapeutic targets for glioma.

Direct radiofrequency saturation corrected amide proton transfer tumor MRI at 3T.

PURPOSE: Amide proton transfer (APT) imaging has been increasingly applied in tumor characterization that complements diffusion and dynamic contrast-enhanced MRI. However, quantification of in vivo APT effect is challenging because of concomitant semisolid magnetization transfer (MT) and nuclear overhauser enhancement effects. A direct saturation corrected (DISC) chemical exchange saturation transfer (CEST) analysis has been recently proposed that simplifies the determination of in vivo CEST effects. Our present study aimed to extend the DISC analysis to pulsed radiofrequency CEST MRI and evaluate it at 3T. METHODS: Nine adult male Sprague-Dawley rats implanted C6 gliomas underwent multiparametric MRI of T1 , T2 , CEST, and T1 -weighted gadolinium-enhanced imaging 1 day before and 3 days after chemoradiotherapy. The routine MT asymmetry, 3-point method, and the extended DISC analysis were compared in tumor characterization with histology as a reference. Regional variations were assessed by 1-way analysis of variance. RESULTS: T1 , T2 , and MT asymmetry and the DISC CEST effects showed significant alterations in tumor/necrosis with respect to the contralateral reference (P < 0.05). The resolved APT effect revealed a significant difference among the contralateral reference (2.42 ± 0.24%), necrosis (2.86 ± 0.19%), and tumor (3.25 ± 0.15%) regions after chemoradiotherapy (P < 0.05), consistent with histological observations. Conversely, the MT asymmetry did not show tumor regional variation post-treatment (P > 0.05), whereas the 3-point method detected no regional alteration at both time points (P > 0.05). CONCLUSION: Our study translated DISC CEST MRI to 3T, evaluated it in glioma rat models, and confirmed its advantages in resolving tumor heterogeneity over the routine asymmetry and 3-point analyses.

Detection of Oil Chestnuts Infected by Blue Mold Using Near-Infrared Hyperspectral Imaging Combined with Artificial Neural Networks.

Mildew damage is a major reason for chestnut poor quality and yield loss. In this study, a near-infrared hyperspectral imaging system in the 874⁻1734 nm spectral range was applied to detect the mildew damage to chestnuts caused by blue mold. Principal component analysis (PCA) scored images were firstly employed to qualitatively and intuitively distinguish moldy chestnuts from healthy chestnuts. Spectral data were extracted from the hyperspectral images. A successive projections algorithm (SPA) was used to select 12 optimal wavelengths. Artificial neural networks, including back propagation neural network (BPNN), evolutionary neural network (ENN), extreme learning machine (ELM), general regression neural network (GRNN) and radial basis neural network (RBNN) were used to build models using the full spectra and optimal wavelengths to distinguish moldy chestnuts. BPNN and ENN models using full spectra and optimal wavelengths obtained satisfactory performances, with classification accuracies all surpassing 99%. The results indicate the potential for the rapid and non-destructive detection of moldy chestnuts by hyperspectral imaging, which would help to develop online detection system for healthy and blue mold infected chestnuts.

Non-Destructive and Rapid Variety Discrimination and Visualization of Single Grape Seed Using Near-Infrared Hyperspectral Imaging Technique and Multivariate Analysis.

Hyperspectral images in the spectral range of 874⁻1734 nm were collected for 14,015, 14,300 and 15,042 grape seeds of three varieties, respectively. Pixel-wise spectra were preprocessed by wavelet transform, and then, spectra of each single grape seed were extracted. Principal component analysis (PCA) was conducted on the hyperspectral images. Scores for images of the first six principal components (PCs) were used to qualitatively recognize the patterns among different varieties. Loadings of the first six PCs were used to identify the effective wavelengths (EWs). Support vector machine (SVM) was used to build the discriminant model using the spectra based on the EWs. The results indicated that the variety of each single grape seed was accurately identified with a calibration accuracy of 94.3% and a prediction accuracy of 88.7%. An external validation image of each variety was used to evaluate the proposed model and to form the classification maps where each single grape seed was explicitly identified as belonging to a distinct variety. The overall results indicated that a hyperspectral imaging (HSI) technique combined with multivariate analysis could be used as an effective tool for non-destructive and rapid variety discrimination and visualization of grape seeds. The proposed method showed great potential for developing a multi-spectral imaging system for practical application in the future.

RPA3 is a potential marker of prognosis and radioresistance for nasopharyngeal carcinoma.

Radioresistance-induced residual and recurrent tumours are the main cause of treatment failure in nasopharyngeal carcinoma (NPC). Thus, the mechanisms of NPC radioresistance and predictive markers of NPC prognosis and radioresistance need to be investigated and identified. In this study, we identified RPA3 as a candidate radioresistance marker using RNA-seq of NPC samples. In vitro studies further confirmed that RPA3 affected the radiosensitivity of NPC cells. Specifically, the overexpression of RPA3 enhanced radioresistance and the capacity for DNA repair of NPC cells, whereas inhibiting RPA3 expression sensitized NPC cells to irradiation and decreased the DNA repair capacity. Furthermore, the overexpression of RPA3 enhanced RAD51 foci formation in NPC cells after irradiation. Immunohistochemical assays in 104 NPC specimens and 21 normal epithelium specimens indicated that RPA3 was significantly up-regulated in NPC tissues, and a log-rank test suggested that in patients with NPC, high RPA3 expression was associated with shorter overall survival (OS) and a higher recurrence rate compared with low expression (5-year OS rates: 67.2% versus 86.2%; 5-year recurrence rates: 14.8% versus 2.3%). Moreover, TCGA data also indicated that high RPA3 expression correlated with poor OS and a high recurrence rate in patients with head and neck squamous cell carcinoma (HNSC) after radiotherapy. Taken together, the results of our study demonstrated that RPA3 regulated the radiosensitivity and DNA repair capacity of NPC cells. Thus, RPA3 may serve as a new predictive biomarker for NPC prognosis and radioresistance to help guide the diagnosis and individualized treatment of patients with NPC.

High-contrast wide-field evanescent wave illuminated subdiffraction imaging.

In this Letter, we show how to obtain high-contrast wide-field evanescent wave illuminated subdiffraction imaging through controlling nanoscale light-matter interaction. The light coupling, propagation, and far-field imaging processes show strong polarization selectivity and film quality dependence, which is used to improve the image-contrast-to-noise ratio (CNR) and to enlarge the field of view (FOV). We demonstrate experimentally high CNR subdiffraction imaging with lateral resolution of 122 nm and FOV of thousands of micrometers square.

Discrimination of Transgenic Maize Kernel Using NIR Hyperspectral Imaging and Multivariate Data Analysis.

There are possible environmental risks related to gene flow from genetically engineered organisms. It is important to find accurate, fast, and inexpensive methods to detect and monitor the presence of genetically modified (GM) organisms in crops and derived crop products. In the present study, GM maize kernels containing both cry1Ab/cry2Aj-G10evo proteins and their non-GM parents were examined by using hyperspectral imaging in the near-infrared (NIR) range (874.41-1733.91 nm) combined with chemometric data analysis. The hypercubes data were analyzed by applying principal component analysis (PCA) for exploratory purposes, and support vector machine (SVM) and partial least squares discriminant analysis (PLS-DA) to build the discriminant models to class the GM maize kernels from their contrast. The results indicate that clear differences between GM and non-GM maize kernels can be easily visualized with a nondestructive determination method developed in this study, and excellent classification could be achieved, with calculation and prediction accuracy of almost 100%. This study also demonstrates that SVM and PLS-DA models can obtain good performance with 54 wavelengths, selected by the competitive adaptive reweighted sampling method (CARS), making the classification processing for online application more rapid. Finally, GM maize kernels were visually identified on the prediction maps by predicting the features of each pixel on individual hyperspectral images. It was concluded that hyperspectral imaging together with chemometric data analysis is a promising technique to identify GM maize kernels, since it overcomes some disadvantages of the traditional analytical methods, such as complex and monotonous sampling.

Machine learning for the prediction of L. chinensis carbon, nitrogen and phosphorus contents and understanding of mechanisms underlying grassland degradation.

The grasslands of Western Jilin Province in China have experienced severe degradation during the last 50 years. Radial basis function neural networks (RBFNN) and support vector machines (SVM) were used to predict the carbon, nitrogen, and phosphorus contents of Leymus chinensis (L. chinensis) and explore the degree of grassland degradation using the matter-element extension model. Both RBFNN and SVM demonstrated good prediction accuracy. The results indicated that there was severe degradation, as samples were mainly concentrated in the 3rd and 4th levels. The growth of L. chinensis was shown to be limited by either nitrogen, phosphorus, or both during different stages of degradation. The soil chemistry changed noticeably as degradation aggravated, which represents a destabilization of L. chinensis community homeostasis. Soil salinization aggravates soil nutrient loss and decreases the bioavailability of soil nutrients. This, along with the destabilization of C/N, C/P and N/P ratios, weakens the photosynthetic ability and productivity of L. chinensis. This conclusion was supported by observations that L. chinensis is gradually being replaced by a Chloris virgata, Puccinellia tenuiflora and Suaeda acuminate mixed community.

The effect of traditional stir-frying process on hydrophilic and lipophilic antioxidant capacities of pine nut kernels.

The effect of traditional stir-frying process at different heating temperatures (50-150 °C) and time periods (5-20 min) on hydrophilic part (total and individual phenolics), lipophilic part (tocopherol and phytosterol compounds) and their corresponding antioxidant capacities in pine nut kernels were investigated. The concentrations of total phenolics, phenolic acids, tocopherols and phytosterols in raw pine nut kernels were 15.76 mg gallic acid equivalents/100 g dry weight (mg GAE/100 g DW), 12.15 mg/100 g DW, 28.67 mg/100 g DW and 198.81 mg/100 g DW, respectively. Stir-frying at low temperatures over short time periods led to an increase of phenolics, phytosterols and hydrophiliic antioxidant capacities. However, these values decreased under the longer heating time and the higher temperature. Tocopherols and lipophilic antioxidant capacities did not show clear changes at lower heating temperatures or shorter heating times, while they had an apparent decreasing trend at higher heating temperatures or longer heating times. Gallic acid might be the main component, which is responsible for the hydrophilic antioxidant capacity (R(2 )= 0.84, 0.81 and 0.81 using DPPH, FRAP and H-ORAC assays), and tocopherols might be the main antioxidant components in the lipophilic part (R(2 )= 0.87 and 0.89 using DPPH and L-ORAC assays).

Multi-phenotype response and cadmium detection of rice stem under toxic cadmium exposure.

Rice stem is the sole conduit for cadmium translocation from underground to aboveground. The presence of cadmium can trigger responses of rice stem multi-phenotype, affecting metabolism, reducing yield, and altering composition, which is related to crop growth, food safety, and new energy utilization. Exploring the adversity response of plant phenotypes can provide a reliable assessment of growth status. However, the phytotoxicity and mechanism of cadmium stress on rice stem remain unclear. Here, we systematically revealed the response mechanisms of cadmium accumulation, adversity physiology, and morphological characteristic in rice stem under cadmium stress for the first time with concentration gradients of CK, 5, 25, 50, and 100 µM, and duration gradients of Day 5, Day 10, Day 15, and Day 20. The results indicated that cadmium stress led to a significant increase in cadmium accumulation, accompanied by the adversity response in stem phenotypes. Specifically, cadmium can cause fluctuations in soluble protein and disturbance of malondialdehyde (MDA), which reflects lipid peroxidation induced by cadmium accumulation. Lipid peroxidation inhibited rice growth by causing (1) a reduction in stem length, diameter, and weight, (2) suppression of air cavity, vascular bundle, parenchyma, and epidermal hair, and (3) disruption of cell structure. Furthermore, rapid detection of cadmium was realized based on the combination of laser-induced breakdown spectroscopy (LIBS) and machine learning, which took less than 3 min. The established qualitative model realized the precise discrimination of cadmium stress degrees with a prediction accuracy exceeding 92 %, and the quantitative model achieved the outstanding prediction effect of cadmium, with Rp of 0.9944. This work systematically revealed the phytotoxicity of cadmium on rice stem multi-phenotype from a novel perspective of lipid peroxidation and realized the rapid detection of cadmium in rice stem, which provided the technical tool and theoretical foundation for accurate prevention and efficient control of heavy metal risks in crops.

Improving the Performance and High-Field Stability of FAPbBr3 Single Crystals in X-Ray Detection with Chenodeoxycholic Acid Additive.

Organometal halide perovskite single crystals are one of the most promising radiation detection materials due to their unique advantages of high absorption coefficient, long carrier diffusion length, and low defect density. However, the severe ion migration in perovskites deteriorates the X-ray detection performance under longtime and high-field operating conditions. This work reports an effective additive of chenodeoxycholic acid (CDCA), which can suppress the ion migration and improve the performance and the operational stability of FAPbBr3 single crystals (SCs) in X-ray detection significantl. The CDCA molecules in precursors effectively suppress the decomposition of FA ions, resulting in a better crystal orientation and stoichiometry. The trace amounts of CDCA residues in FAPbBr3 SCs improve the thermal stability and effectively suppress the ion migration. The resulting detector shows an impressive X-ray sensitivity up to 21 386.88 µC Gyair -1 cm-2 under -500 V and a detection limit of 15.23 nGyair s-1 . The response current of the detector at 225 V cm-1 field is barely changed under the 7200 s irradiation with a dose rate of 1.949 mGyair s-1 . This work provides insights for the additive selection and improving the operational stability of perovskite single crystals for commercial applications.

Function analysis of GhWRKY53 regulating cotton resistance to verticillium wilt by JA and SA signaling pathways.

WRKY transcription factors (TFs) play an important role in regulating the mechanism of plant self-defense. However, the function of most WRKY TFs in upland cotton (Gossypium hirsutum) is still unknown. Hence, studying the molecular mechanism of WRKY TFs in the resistance of cotton to Verticillium dahliae is of great significance to enhancing cotton disease resistance and improving its fiber quality. In this study, Bioinformatics has been used to characterize the cotton WRKY53 gene family. we analyzed the GhWRKY53 expression patterns in different resistant upland cotton cultivars treated with salicylic acid (SA) and methyl jasmonate (MeJA). Additionally, GhWRKY53 was silenced using a virus-induced gene silencing (VIGS) to determine the contribution of GhWRKY53 to V. dahliae resistance in cotton. The result showed that GhWRKY53 mediated SA and MeJA signal transduction pathways. After VIGS of the GhWRKY53, the ability of cotton to resist V. dahliae decreased, indicating that the GhWRKY53 could be involved in the disease resistance mechanism of cotton. Studies on the levels of SA and jasmonic acid (JA) and their related pathway genes demonstrated that the silencing of GhWRKY53 inhibited the SA pathway and activated the JA pathway, thereby reducing the resistance of plants to V. dahliae. In conclusion, GhWRKY53 could change the tolerance of upland cotton to V. dahliae by regulating the expression of SA and JA pathway-related genes. However, the interaction mechanism between JA and SA signaling pathways in cotton in response to V. dahliae requires further study.