Genome-wide analyses of member identification, expression pattern, and protein-protein interaction of EPF/EPFL gene family in Gossypium.

BACKGROUND: Epidermal patterning factor / -like (EPF/EPFL) gene family encodes a class of cysteine-rich secretory peptides, which are widelyfound in terrestrial plants.Multiple studies has indicated that EPF/EPFLs might play significant roles in coordinating plant development and growth, especially as the morphogenesis processes of stoma, awn, stamen, and fruit skin. However, few research on EPF/EPFL gene family was reported in Gossypium. RESULTS: We separately identified 20 G. raimondii, 24 G. arboreum, 44 G. hirsutum, and 44 G. barbadense EPF/EPFL genes in the 4 representative cotton species, which were divided into four clades together with 11 Arabidopsis thaliana, 13 Oryza sativa, and 17 Selaginella moellendorffii ones based on their evolutionary relationships. The similar gene structure and common motifs indicated the high conservation among the EPF/EPFL members, while the uneven distribution in chromosomes implied the variability during the long-term evolutionary process. Hundreds of collinearity relationships were identified from the pairwise comparisons of intraspecifc and interspecific genomes, which illustrated gene duplication might contribute to the expansion of cotton EPF/EPFL gene family. A total of 15 kinds of cis-regulatory elements were predicted in the promoter regions, and divided into three major categories relevant to the biological processes of development and growth, plant hormone response, and abiotic stress response. Having performing the expression pattern analyses with the basic of the published RNA-seq data, we found most of GhEPF/EPFL and GbEPF/EPFL genes presented the relatively low expression levels among the 9 tissues or organs, while showed more dramatically different responses to high/low temperature and salt or drought stresses. Combined with transcriptome data of developing ovules and fibers and quantitative Real-time PCR results (qRT-PCR) of 15 highly expressed GhEPF/EPFL genes, it could be deduced that the cotton EPF/EPFL genes were closely related with fiber development. Additionally, the networks of protein-protein interacting among EPF/EPFLs concentrated on the cores of GhEPF1 and GhEPF7, and thosefunctional enrichment analyses indicated that most of EPF/EPFLs participate in the GO (Gene Ontology) terms of stomatal development and plant epidermis development, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways of DNA or base excision repair. CONCLUSION: Totally, 132 EPF/EPFL genes were identified for the first time in cotton, whose bioinformatic analyses of cis-regulatory elements and expression patterns combined with qRT-PCR experiments to prove the potential functions in the biological processes of plant growth and responding to abiotic stresses, specifically in the fiber development. These results not only provide comprehensive and valuable information for cotton EPF/EPFL gene family, but also lay solid foundation for screening candidate EPF/EPFL genes in further cotton breeding.

Siamese-DETR for Generic Multi-Object Tracking.

The ability to detect and track the dynamic objects in different scenes is fundamental to real-world applications, e.g., autonomous driving and robot navigation. However, traditional Multi-Object Tracking (MOT) is limited to track objects belonging to the pre-defined closed-set categories. Recently, Generic MOT (GMOT) is proposed to track interested objects beyond pre-defined categories and it can be divided into Open-Vocabulary MOT (OVMOT) and Template-Image-based MOT (TIMOT). Taking the consideration that the expensive well pre-trained (vision-)language model and fine-grained category annotations are required to train OVMOT models, in this paper, we focus on TIMOT and propose a simple but effective method, Siamese-DETR. Only the commonly used detection datasets (e.g., COCO) are required for training. Different from existing TIMOT methods, which train a Single Object Tracking (SOT) based detector to detect interested objects and then apply a data association based MOT tracker to get the trajectories, we leverage the inherent object queries in DETR variants. Specifically: 1) The multi-scale object queries are designed based on the given template image, which are effective for detecting different scales of objects with the same category as the template image; 2) A dynamic matching training strategy is introduced to train Siamese-DETR on commonly used detection datasets, which takes full advantage of provided annotations; 3) The online tracking pipeline is simplified through a tracking-by-query manner by incorporating the tracked boxes in the previous frame as additional query boxes. The complex data association is replaced with the much simpler Non-Maximum Suppression (NMS). Extensive experimental results show that Siamese-DETR surpasses existing MOT methods on GMOT-40 dataset by a large margin.

A nomogram for predicting the risk of cancer-related cognitive impairment in breast cancer patients based on a scientific symptom model.

Cancer-related cognitive impairment is a significant clinical challenge observed in patients with breast cancer, manifesting during or after treatment. This impairment leads to deteriorations in memory, processing speed, attention, and executive functioning, which profoundly impact patients' occupational performance, daily living activities, and overall quality of life. Grounded in the Symptom Science Model 2.0, this study investigates the contributing factors to Cancer-related cognitive impairment in breast cancer patients and develops a predictive nomogram for this demographic. Employing both univariate and multivariate logistic regression analyses, this investigation delineates the predictive factors influencing outcomes in breast cancer patients. A nomogram was constructed leveraging these identified predictive factors, accompanied by internal validation through bootstrap resampling methodology (1000 bootstrap samples). The efficacy of the predictive model was assessed by employing the Hosmer-Lemeshow goodness-of-fit test and calibration curves. The prevalence of cognitive impairment in breast cancer patients was identified to be 45.83%.Multivariate logistic regression analysis identified the independent predictors of Cancer-related cognitive impairment in breast cancer patients as place of residence, educational level, chemotherapy, benefit finding, post-traumatic growth, anxiety, fear of cancer progression, and fasting blood glucose levels. these factors were integrated into the nomogram. The Hosmer-Lemeshow goodness-of-fit test demonstrated that the prediction model was appropriately calibrated (χ2 = 11.520, P = 0.174). Furthermore, the model exhibited an area under the curve of 0.955 (95% CI 0.939 to 0.971) and a sensitivity of 0.906, evidencing its robust discriminative capacity and accuracy. Utilizing the Symptom Science Model 2.0 as a framework, this study comprehensively examines the multifaceted factors influencing Cancer-related cognitive impairment in breast cancer patients, spanning five critical domains: complex symptoms, phenotypic characterization, biobehavioral factors, social determinants of health, and patient-centered experiences. A predictive nomogram model was established, demonstrating satisfactory predictive accuracy and capability. This model is capable of identifying breast cancer patients with cognitive impairments with high precision. The findings furnish empirical evidence in support of the early detection, diagnosis, and intervention strategies for high-risk breast cancer patients afflicted with Cancer-related cognitive impairment.

Genome-wide identification and expression-pattern analysis of sulfate transporter (SULTR) gene family in cotton under multiple abiotic stresses and fiber development.

Sulfate transporter (SULTR) proteins are in charge of the transport and absorption on sulfate substances, and have been reported to play vital roles in the biological processes of plant growth and stress response. However, there were few reports of genome-wide identification and expression-pattern analysis of SULTRs in Hibiscus mutabilis. Gossypium genus is a ideal model for studying the allopolyploidy, therefore two diploid species (G. raimondii and G. arboreum) and two tetraploid species (G. hirsutum and G. barbadense) were chosen in this study to perform bioinformatic analyses, identifying 18, 18, 35, and 35 SULTR members, respectively. All the 106 cotton SULTR genes were utilized to construct the phylogenetic tree together with 11 Arabidopsis thaliana, 13 Oryza sativa, and 8 Zea mays ones, which was divided into Group1-Group4. The clustering analyses of gene structures and 10 conserved motifs among the cotton SULTR genes showed the consistent evolutionary relationship with the phylogenetic tree, and the results of gene-duplication identification among the four representative Gossypium species indicated that genome-wide or segment duplication might make main contributions to the expansion of SULTR gene family in cotton. Having conducted the cis-regulatory element analysis in promoter region, we noticed that the existing salicylic acid (SA), jasmonic acid (JA), and abscisic acid (ABA) elements could have influences with expression levels of cotton SULTR genes. The expression patterns of GhSULTR genes were also investigated on the 7 different tissues or organs and the developing ovules and fibers, most of which were highly expressed in root, stem, sepal, receptacel, ovule at 10 DPA, and fiber at 20 and 25 DPA. In addition, more active regulatory were observed in GhSULTR genes responding to multiple abiotic stresses, and 12 highly expressed genes showed the similar expression patterns in the quantitative Real-time PCR experiments under cold, heat, salt, and drought treatments. These findings broaden our insight into the evolutionary relationships and expression patterns of the SULTR gene family in cotton, and provide the valuable information for further screening the vital candidate genes on trait improvement.

Transformer based Pluralistic Image Completion with Reduced Information Loss.

Transformer based methods have achieved great success in image inpainting recently. However, we find that these solutions regard each pixel as a token, thus suffering from an information loss issue from two aspects: 1) They downsample the input image into much lower resolutions for efficiency consideration. 2) They quantize 2563 RGB values to a small number (such as 512) of quantized color values. The indices of quantized pixels are used as tokens for the inputs and prediction targets of the transformer. To mitigate these issues, we propose a new transformer based framework called "PUT". Specifically, to avoid input downsampling while maintaining computation efficiency, we design a patch-based auto-encoder P-VQVAE. The encoder converts the masked image into non-overlapped patch tokens and the decoder recovers the masked regions from the inpainted tokens while keeping the unmasked regions unchanged. To eliminate the information loss caused by input quantization, an Un-quantized Transformer is applied. It directly takes features from the P-VQVAE encoder as input without any quantization and only regards the quantized tokens as prediction targets.Furthermore, to make the inpainting process more controllable, we introduce semantic and structural conditions as extra guidance. Extensive experiments show that our method greatly outperforms existing transformer based methods on image fidelity and achieves much higher diversity and better fidelity than state-of-the-art pluralistic inpainting methods on complex large-scale datasets (e.g., ImageNet). Codes are available at https://github.com/liuqk3/PUT.

Exploring the Application of Large-Scale Pre-Trained Models on Adverse Weather Removal.

Image restoration under adverse weather conditions (e.g., rain, snow, and haze) is a fundamental computer vision problem that has important implications for various downstream applications. Distinct from early methods that are specially designed for specific types of weather, recent works tend to simultaneously remove various adverse weather effects based on either spatial feature representation learning or semantic information embedding. Inspired by various successful applications incorporating large-scale pre-trained models (e.g., CLIP), in this paper, we explore their potential benefits for leveraging large-scale pre-trained models in this task based on both spatial feature representation learning and semantic information embedding aspects: 1) spatial feature representation learning, we design a Spatially Adaptive Residual (SAR) encoder to adaptively extract degraded areas. To facilitate training of this model, we propose a Soft Residual Distillation (CLIP-SRD) strategy to transfer spatial knowledge from CLIP between clean and adverse weather images; 2) semantic information embedding, we propose a CLIP Weather Prior (CWP) embedding module to enable the network to adaptively respond to different weather conditions. This module integrates the sample-specific weather priors extracted by the CLIP image encoder with the distribution-specific information (as learned by a set of parameters) and embeds these elements using a cross-attention mechanism. Extensive experiments demonstrate that our proposed method can achieve state-of-the-art performance under various and severe adverse weather conditions. The code will be made available.

Decoding the guardians of cotton resilience: A comprehensive exploration of the ßCA genes and its role in Verticillium dahliae resistance.

Plant Carbonic anhydrases (Cas) have been shown to be stress-responsive enzymes that may play a role in adapting to adverse conditions. Cotton is a significant economic crop in China, with upland cotton (Gossypium hirsutum) being the most widely cultivated species. We conducted genome-wide identification of the ßCA gene in six cotton species and preliminary analysis of the ßCA gene in upland cotton. In total, 73 ßCA genes from six cotton species were identified, with phylogenetic analysis dividing them into five subgroups. GHßCA proteins were predominantly localized in the chloroplast and cytoplasm. The genes exhibited conserved motifs, with motifs 1, 2, and 3 being prominent. GHßCA genes were unevenly distributed across chromosomes and were associated with stress-responsive cis-regulatory elements, including those responding to light, MeJA, salicylic acid, abscisic acid, cell cycle regulation, and defence/stress. Expression analysis indicated that GHßCA6, GHßCA7, GHßCA10, GHßCA15, and GHßCA16 were highly expressed under various abiotic stress conditions, whereas GHßCA3, GHßCA9, GHßCA10, and GHßCA18 had higher expression patterns under Verticillium dahliae infection at different time intervals. In Gossypium thurberi, GthßCA1, GthßCA2, and GthßCA4 showed elevated expression across stress conditions and tissues. Silencing GHßCA10 through VIGS increased Verticillium wilt severity and reduced lignin deposition compared to non-silenced plants. GHßCA10 is crucial for cotton's defense against Verticillium dahliae. Further research is needed to understand the underlying mechanisms and develop strategies to enhance resistance against Verticillium wilt.

Inhibition of ANXA2 activity attenuates epileptic susceptibility and GluA1 phosphorylation.

INTRODUCTION: Annexin A2 (ANXA2) participates in the pathology of a variety of diseases. Nevertheless, the impact of ANXA2 on epilepsy remains to be clarified. AIMS: Hence, the study aimed at investigating the underlying role of ANXA2 in epilepsy through behavioral, electrophysiological, and pathological analyses. RESULTS: It was found that ANXA2 was markedly upregulated in the cortical tissues of temporal lobe epilepsy patients (TLE), kainic acid (KA)-induced epilepsy mice, and in a seizure-like model in vitro. ANXA2 silencing in mice suppressed first seizure latency, number of seizures, and seizure duration in behavioral analysis. In addition, abnormal brain discharges were less frequent and shorter in the hippocampal local field potential (LFP) record. Furthermore, the results showed that the frequency of miniature excitatory postsynaptic currents was decreased in ANXA2 knockdown mice, indicating that the excitatory synaptic transmission is reduced. Co-immunoprecipitation (COIP) experiments demonstrated that ANXA2 interacted with the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) subunit GluA1. Moreover, ANXA2 knockdown decreased GluA1 expression on the cell surface and its phosphorylation onserine 831 and serine 845, related to the decreased phosphorylation levels mediated by protein kinases A and C (PKA and PKC). CONCLUSIONS: This study covers a previously unknown and key function of ANXA2 in epilepsy. These findings indicate that ANXA2 can regulate excitatory synaptic activity mediated by AMPAR subunit GluA1 to improve seizure activity, which can provide novel insights for the treatment and prevention of epilepsy.

Genome-Wide Identification and Characterization of the PPO Gene Family in Cotton (Gossypium) and Their Expression Variations Responding to Verticillium Wilt Infection.

Polyphenol oxidases (PPOs) are copper-binding metalloproteinases encoded by nuclear genes, ubiquitously existing in the plastids of microorganisms, plants, and animals. As one of the important defense enzymes, PPOs have been reported to participate in the resistant processes that respond to diseases and insect pests in multiple plant species. However, PPO gene identification and characterization in cotton and their expression patterns under Verticillium wilt (VW) treatment have not been clearly studied. In this study, 7, 8, 14, and 16 PPO genes were separately identified from Gossypium arboreum, G. raimondii, G. hirsutum, and G. barbadense, respectively, which were distributed within 23 chromosomes, though mainly gathered in chromosome 6. The phylogenetic tree manifested that all the PPOs from four cotton species and 14 other plants were divided into seven groups, and the analyses of the conserved motifs and nucleotide sequences showed highly similar characteristics of the gene structure and domains in the cotton PPO genes. The dramatically expressed differences were observed among the different organs at various stages of growth and development or under the diverse stresses referred to in the published RNA-seq data. Quantitative real-time PCR (qRT-PCR) experiments were also performed on the GhPPO genes in the roots, stems, and leaves of VW-resistant MBI8255 and VW-susceptible CCRI36 infected with Verticillium dahliae V991, proving the strong correlation between PPO activity and VW resistance. A comprehensive analysis conducted on cotton PPO genes contributes to the screening of the candidate genes for subsequent biological function studies, which is also of great significance for the in-depth understanding of the molecular genetic basis of cotton resistance to VW.

Semantic Probability Distribution Modeling for Diverse Semantic Image Synthesis.

Semantic image synthesis, translating semantic layouts to photo-realistic images, is a one-to-many mapping problem. Though impressive progress has been recently made, diverse semantic synthesis that can efficiently produce semantic-level or even instance-level multimodal results, still remains a challenge. In this article, we propose a novel diverse semantic image synthesis framework from the perspective of semantic class distributions, which naturally supports diverse generation at both semantics and instance level. We achieve this by modeling class-level conditional modulation parameters as continuous probability distributions instead of discrete values, and sampling per-instance modulation parameters through instance-adaptive stochastic sampling that is consistent across the network. Moreover, we propose prior noise remapping, through linear perturbation parameters encoded from paired references, to facilitate supervised training and exemplar-based instance style control at test time. To further extend the user interaction function of the proposed method, we also introduce sketches into the network. In addition, specially designed generator modules, Progressive Growing Module and Multi-Scale Refinement Module, can be used as a general module to improve the performance of complex scene generation. Extensive experiments on multiple datasets show that our method can achieve superior diversity and comparable quality compared to state-of-the-art methods. Codes are available at https://github.com/tzt101/INADE.git.

Circular Optical Phased Array with Large Steering Range and High Resolution.

Light detection and ranging systems based on optical phased arrays and integrated silicon photonics have sparked a surge of applications over the recent years. This includes applications in sensing, free-space communications, or autonomous vehicles, to name a few. Herein, we report a design of two-dimensional optical phased arrays, which are arranged in a grid of concentric rings. We numerically investigate two designs composed of 110 and 820 elements, respectively. Both single-wavelength (1550 nm) and broadband multi-wavelength (1535 nm to 1565 nm) operations are studied. The proposed phased arrays enable free-space beam steering, offering improved performance with narrow beam divergences of only 0.5° and 0.22° for the 110-element and 820-element arrays, respectively, with a main-to-sidelobe suppression ratio higher than 10 dB. The circular array topology also allows large element spacing far beyond the sub-wavelength-scaled limits that are present in one-dimensional linear or two-dimensional rectangular arrays. Under a single-wavelength operation, a solid-angle steering between 0.21π sr and 0.51π sr is obtained for 110- and 820-element arrays, respectively, while the beam steering spans the range of 0.24π sr and 0.57π sr for a multi-wavelength operation. This work opens new opportunities for future optical phased arrays in on-chip photonic applications, in which fast, high-resolution, and broadband beam steering is necessary.

The Prevention and Reversal of a Phenytoin-Resistant Model by N-acetylcysteine Therapy Involves the Nrf2/P-Glycoprotein Pathway at the Blood-Brain Barrier.

The transporter hypothesis is one of the most popular hypotheses of drug-resistant epilepsy (DRE). P-glycoprotein (P-gp), a channel protein at the blood-brain barrier (BBB), plays an important role in the transport of some anti-seizure drugs from brain tissue into vessels, which reduces drug concentrations and diminishes the effects of drug treatment. We performed this study to test whether P-gp is overexpressed in DRE and identify ways to prevent and reverse DRE. In this study, we established a phenytoin (PHT)-resistant mouse model and revealed that P-gp was overexpressed at the BBB in PHT-resistant mice. The P-gp inhibitor nimodipine decreased the resistance of phenytoin. Antioxidative preventive treatment with N-acetylcysteine (NAC) prevented the mice from entering a PHT-resistant state, and NAC therapy tended to reverse PHT resistance into sensitivity. We were also able to induce PHT resistance by activating the Nrf2/P-gp pathway, which indicates that oxidative stress plays an important role in drug resistance. Taken together, these findings suggest that antioxidative therapy may be a promising strategy for overcoming DRE.

Circular Optical Phased Arrays with Radial Nano-Antennas.

On-chip optical phased arrays (OPAs) are the enabling technology for diverse applications, ranging from optical interconnects to metrology and light detection and ranging (LIDAR). To meet the required performance demands, OPAs need to achieve a narrow beam width and wide-angle steering, along with efficient sidelobe suppression. A typical OPA configuration consists of either one-dimensional (1D) linear or two-dimensional (2D) rectangular arrays. However, the presence of grating sidelobes from these array configurations in the far-field pattern limits the aliasing-free beam steering, when the antenna element spacing is larger than half of a wavelength. In this work, we provide numerical analysis for 2D circular OPAs with radially arranged nano-antennas. The circular array geometry is shown to effectively suppress the grating lobes, expand the range for beam steering and obtain narrower beamwidths, while increasing element spacing to about 10 µm. To allow for high coupling efficiency, we propose the use of a central circular grating coupler to feed the designed circular OPA. Leveraging radially positioned nano-antennas and an efficient central grating coupler, our design can yield an aliasing-free azimuthal field of view (FOV) of 360°, while the elevation angle FOV is limited by the far-field beamwidth of the nano-antenna element and its array arrangement. With a main-to-sidelobe contrast ratio of 10 dB, a 110-element OPA offers an elevation FOV of 5° and an angular beamwidth of 1.14°, while an 870-element array provides an elevation FOV up to 20° with an angular beamwidth of 0.35°. Our analysis suggests that the performance of the circular OPAs can be further improved by integrating more elements, achieving larger aliasing-free FOV and narrower beamwidths. Our proposed design paves a new way for the development of on-chip OPAs with large 2D beam steering and high resolutions in communications and LIDAR systems.

Protoplast Dissociation and Transcriptome Analysis Provides Insights to Salt Stress Response in Cotton.

As one of the pioneer crops widely planted in saline-alkaline areas, Gossypium provides daily necessities, including natural fiber, vegetable proteins, and edible oils. However, cotton fiber yield and quality are highly influenced by salt stress. Therefore, elucidating the molecular mechanisms of cotton in response to salinity stress is importance to breed new cultivars with high tolerance. In this study, we first developed a method for single-cell RNA-seq based on isolating protoplast from cotton root tips; then, we studied the impact of salinity stress on gene expression profiling and their dynamic changes using the developed high-efficiency method for protoplast dissociation suitable for single-cell RNA-seq. A total of 3391 and 2826 differentially expressed genes (DEGs) were identified in salt-treated samples before and after protoplast dissociation, respectively, which were enriched into several molecular components, including response to stimulus, response to stress, and cellular macromolecule metabolic process by gene ontology (GO) analysis. Plant hormone signal transduction, phenylpropanoid biosynthesis, and MAPK signaling pathway were found to be enriched via Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Twenty-two and nine salinity-responsive DEGs participated in plant hormone signaling and MAPK signaling in roots, before and after protoplast dissociation, respectively; six upregulated DEGs were involved in ABA signaling transduction, namely, Ga04G2111, Ga07G0142, Ga09G2061, Ga10G0262, Ga01G0063, and Ga08G1915 which indicates their potential functions on plants adapting to salt stress. Additionally, 384 and 257 transcription factors (TFs) were differentially expressed in salt-stress roots before and after protoplast dissociation, respectively, of which significantly up-regulated TFs mainly belonged to the AP2/ERF-ERF family, which implied their potential roles responding to salt stress. These results not only provide novel insights to reveal the regulatory networks in plant's root response to salt stress, but also lay the solid foundation for further exploration on cellular heterogeneity by single-cell transcriptome sequencing.

G-alpha interacting protein interacting protein, C terminus 1 regulates epileptogenesis by increasing the expression of metabotropic glutamate receptor 7.

AIMS: It has been reported that the G-alpha interacting protein (GAIP) interacting protein, C terminus 1 (GIPC1/GIPC) engages in vesicular trafficking, receptor transport and expression, and endocytosis. However, its role in epilepsy is unclear. Therefore, in this study, we aimed to explore the role of GIPC1 in epilepsy and its possible underlying mechanism. METHODS: The expression patterns of GIPC1 in patients with temporal lobe epilepsy (TLE) and in mice with kainic acid (KA)-induced epilepsy were detected. Behavioral video monitoring and hippocampal local field potential (LFP) recordings were carried out to determine the role of GIPC1 in epileptogenesis after overexpression of GIPC1. Coimmunoprecipitation (Co-IP) assay and high-resolution immunofluorescence staining were conducted to investigate the relationship between GIPC1 and metabotropic glutamate receptor 7 (mGluR7). In addition, the expression of mGluR7 after overexpression of GIPC1 was measured, and behavioral video monitoring and LFP recordings after antagonism of mGluR7 were performed to explore the possible mechanism mediated by GIPC1. RESULTS: GIPC1 was downregulated in the brain tissues of patients with TLE and mice with KA-induced epilepsy. After overexpression of GIPC1, prolonged latency period, decreased epileptic seizures and reduced seizure severity in behavioral analyses, and fewer and shorter abnormal brain discharges in LFP recordings of KA-induced epileptic mice were observed. The result of the Co-IP assay showed the interaction between GIPC1 and mGluR7, and the high-resolution immunofluorescence staining also showed the colocalization of these two proteins. Additionally, along with GIPC1 overexpression, the total and cell membrane expression levels of mGluR7 were also increased. And after antagonism of mGluR7, increased epileptic seizures and aggravated seizure severity in behavioral analyses and more and longer abnormal brain discharges in LFP recordings were observed. CONCLUSION: GIPC1 regulates epileptogenesis by interacting with mGluR7 and increasing its expression.

Compact and highly-efficient broadband surface grating antenna on a silicon platform.

We present a compact silicon-based surface grating antenna design with a high diffraction efficiency of 89% (-0.5 dB) and directionality of 0.94. The antenna is designed with subwavelength-based L-shaped radiating elements in a 300-nm silicon core, maintaining high efficiency with a compact footprint of 7.6 µm × 4.5 µm. The reflectivity remains below -10 dB over the S, C and L optical communication bands. A broad 1-dB bandwidth of 230 nm in diffraction efficiency is achieved with a central wavelength of 1550 nm.

On-Chip Mid-Infrared Supercontinuum Generation from 3 to 13 µm Wavelength.

Midinfrared spectroscopy is a universal way to identify chemical and biological substances. Indeed, when interacting with a light beam, most molecules are responsible for absorption at specific wavelengths in the mid-IR spectrum, allowing to detect and quantify small traces of substances. On-chip broadband light sources in the mid-infrared are thus of significant interest for compact sensing devices. In that regard, supercontinuum generation offers a mean to efficiently perform coherent light conversion over an ultrawide spectral range, in a single and compact device. This work reports the experimental demonstration of on-chip two-octave supercontinuum generation in the mid-infrared wavelength, ranging from 3 to 13 µm (that is larger than 2500 cm-1) and covering almost the full transparency window of germanium. Such an ultrawide spectrum is achieved thanks to the unique features of Ge-rich graded SiGe waveguides, which allow second-order dispersion tailoring and low propagation losses over a wide wavelength range. The influence of the pump wavelength and power on the supercontinuum spectra has been studied. A good agreement between the numerical simulations and the experimental results is reported. Furthermore, a very high coherence is predicted in the entire spectrum. These results pave the way for wideband, coherent, and compact mid-infrared light sources by using a single device and compatible with large-scale fabrication processes.

Aberrant expression of miR-16, B12 and CD272 in peripheral blood mononuclear cells from patients with active tuberculosis.

Tuberculosis (TB) immunity is affected by complex immune regulation processes, which involve various immune cells, immune molecules, and cytokines. Here, we evaluated the expression of B12, CD272 and miR-16 in peripheral blood mononuclear cells (PBMC) of patients with active pulmonary tuberculosis. The results showed that monocytes expressing CD272 or B12 were down-regulated in patients with tuberculosis. The expression of B12 and CD272 in T cells and monocytes is related to tuberculosis. In TB patients, the up-regulation of miR-16 was negatively correlated with B12 mRNA expression, miR-16 was mainly expressed in CD14+ monocytes, and CD272 mRNA was mainly expressed in CD19+ B cells. It is worth noting that the overexpression of miR-16 inhibits the expression of CD272 and B12 in monocytes of TB patients. After BCG stimulation, miR-16 expression of CD14+ monocytes was up-regulated and B12 mRNA and CD272 mRNA expressions were down-regulated in TB patients. Finally, we found that miR-16 may participate in the TB immunization process through targeted regulation of B12 expression. These studies indicate that the expression of B12, CD272 and miR-16 in PBMC may be related to tuberculosis.

Porf-2 Inhibits Tumor Cell Migration Through the MMP-2/9 Signaling Pathway in Neuroblastoma and Glioma.

Tumor migration and invasion are key pathological processes that contribute to cell metastasis as well as treatment failure in patients with malignant tumors. However, the mechanisms governing tumor cell migration remain poorly understood. By analyzing the tumor-related database and tumor cell lines, we found that preoptic regulatory factor-2 (Porf-2) is downexpressed in both neuroblastoma and glioma. Using in vitro assays, our data demonstrated that the expression of Porf-2 inhibits tumor cell migration both in neuroblastoma and glioma cell lines. Domain-mutated Porf-2 plasmids were then constructed, and it was found that the GAP domain, which plays a role in the inactivation of Rac1, is the functional domain for inhibiting tumor cell migration. Furthermore, by screening potential downstream effectors, we found that Porf-2 can reduce MMP-2 and MMP-9 expression. Overexpression of MMP-2 blocked the inhibitory effect of Porf-2 in tumor cell migration both in vitro and in vivo. Taken together, we show for the first time that Porf-2 is capable of suppressing tumor cell migration via its GAP domain and the downregulation of MMP-2/9, suggesting that targeting Porf-2 could be a promising therapeutic strategy for nervous system tumors.

Ge-rich graded SiGe waveguides and interferometers from 5 to 11†µm wavelength range.

The mid-infrared (mid-IR) wavelength range hosts unique vibrational and rotational resonances of a broad variety of substances that can be used to unambiguously detect the molecular composition in a non-intrusive way. Mid-IR photonic-integrated circuits (PICs) are thus expected to have a major impact in many applications. Still, new challenges are posed by the large spectral width required to simultaneously identify many substances using the same photonic circuit. Ge-rich graded SiGe waveguides have been proposed as a broadband platform approach for mid-IR PICs. In this work, ultra-broadband waveguides are experimentally demonstrated within unprecedented wavelength range, efficiently guiding light from 5 to 11 µm. Interestingly, losses from 0.5 to 1.2 dB/cm are obtained between 5.1 and 8 µm wavelength, and values below 3 dB/cm are measured from 9.5 to 11.2 µm wavelength. An increase of propagation losses is seen between 8 and 9.5 µm; however, values stay below 4.6 dB/cm in the entire wavelength range. A detailed analysis of propagation losses is reported, supported by secondary ion mass spectrometry measurement, and different contributions are analyzed: silicon substrate absorption, oxygen impurities, free carrier absorption by residual doping, sidewall roughness and multiphonon absorption. Finally, Mach-Zehnder interferometers are characterized, and wideband operation is experimentally obtained from 5.5 to 10.5 µm wavelength.