Genome-wide identification and expression pattern analysis of WRKY transcription factors in response to biotic and abiotic stresses in tea plants (Camellia sinensis).

Plants would encounter various biotic and abiotic stresses during the growth and development. WRKY transcription factors (TFs) as plant-specific TFs, play an important role in responding to various adverse circumstances. Despite some advances were achieved in functional studies of WRKY TFs in tea plants, systematic analysis of the involvement of CsWRKY TFs when facing cold, salt, drought stresses and pathogen and insect attack was lacked. In present study, a total of 78 CsWRKY TFs were identified following the genomic and transcript databases. The expression patterns of CsWRKYs in various organs of tea plants and the expression profiles in response to biotic and abiotic stresses were investigated by examining representative RNA-seq data. Moreover, the effects of hormone treatments (SA and MeJA) on the transcription levels of WRKY TFs were also investigated. The phylogenetic tree of CsWRKY TFs from different species indicated the functional diversity of WRKY TFs was not closely related to their protein classification. Concurrently, CsWRKY70-2 TF was identified as a positive regulator in response to drought stress. This study provided solid and valuable information, helping us better understand the functional diversity of CsWRKY TFs, and laid the foundation for further research on the function of key WRKY genes in tea plants.

Effect of Maternal Pre-Pregnancy Body Mass Index on Longitudinal Fetal Growth and Mediating Role of Maternal Fasting Plasma Glucose: A Retrospective Cohort Study.

Purpose: To assess the impact of maternal pre-pregnancy body mass index (BMI) on longitudinal fetal growth, and the potential mediation effect of the maternal fasting plasma glucose in first trimester. Methods: In this retrospective cohort study, we collected pre-pregnancy BMI data and ultrasound measurements during pregnancy of 3879 singleton pregnant women who underwent antenatal examinations and delivered at Peking Union Medical College Hospital. Generalized estimation equations, linear regression, and logistic regression were used to examine the association between pre-pregnancy BMI with fetal growth and adverse neonatal outcomes. Mediation analyses were also used to examine the mediating role of maternal fasting plasma glucose (FPG) in first trimester. Results: A per 1 Kg/m² increase in pre-pregnancy BMI was associated with increase fetal body length Z-score (ß 0.010, 95% CI 0.001, 0.019) and fetal body weight (ß 0.017, 95% CI 0.008, 0.027). In mid pregnancy, pre-pregnancy BMI also correlated with an increase Z-score of fetal abdominal circumference, femur length (FL). Pre-pregnancy BMI was associated with an increased risk of large for gestational age and macrosomia. Mediation analysis indicated that the associations between pre-pregnancy BMI and fetal weight in mid and late pregnancy, and at birth were partially mediated by maternal FPG in first trimester (mediation proportion: 5.0%, 8.3%, 1.6%, respectively). Conclusion: Maternal pre-pregnancy BMI was associated with the longitudinal fetal growth, and the association was partly driven by maternal FPG in first trimester. The study emphasized the importance of identifying and managing mothers with higher pre-pregnancy BMI to prevent fetal overgrowth.

The relationship between fear of missing out and mobile phone addiction among college students: the mediating role of depression and the moderating role of loneliness.

Background: Mobile phone addiction has adverse influences on the physical and mental health of college students. However, few studies shed light on the effect of fear of missing out on mobile phone addiction and the underlying mechanisms among college students. Methods: To explore their associations, the present study used the Fear of Missing Out Scales (FoMOS), Loneliness Scale (USL-8), Mobile Phone Addiction Index Scale (MPAI), and Depression-Anxiety-Stress Questionnaire (DASS-21) to investigate 750 college students. Results: The results suggested that fear of missing out significantly positively predicted mobile phone addiction. This direct effect could be mediated by depression, and the indirect effect of fear of missing out on mobile phone addiction could be moderated by loneliness. Specifically, the indirect effect was stronger for students with high levels of loneliness. Conclusion: This study provides a theoretical basis for developing future interventions for mobile phone addiction in higher education students.

Interactions between Schwann cell and extracellular matrix in peripheral nerve regeneration.

Peripheral nerve injuries, caused by various reasons, often lead to severe sensory, motor, and autonomic dysfunction or permanent disability, posing a challenging problem in regenerative medicine. Autologous nerve transplantation has been the gold standard in traditional treatments but faces numerous limitations and risk factors, such as donor area denervation, increased surgical complications, and diameter or nerve bundle mismatches. The extracellular matrix (ECM) is a complex molecular network synthesized and released into the extracellular space by cells residing in tissues or organs. Its main components include collagen, proteoglycans/glycosaminoglycans, elastin, laminin, fibronectin, etc., providing structural and biochemical support to surrounding cells, crucial for cell survival and growth. Schwann cells, as the primary glial cells in the peripheral nervous system, play various important roles. Schwann cell transplantation is considered the gold standard in cell therapy for peripheral nerve injuries, making ECM derived from Schwann cells one of the most suitable biomaterials for peripheral nerve repair. To better understand the mechanisms of Schwann cells and the ECM in peripheral nerve regeneration and their optimal application, this review provides an overview of their roles in peripheral nerve regeneration.

[Different concentrations of adapalene induce differentiation and apoptosis of SH-SY5Y cells]. / 不同浓度阿达帕林诱导SH-SY5Y细胞的分化及凋亡.

OBJECTIVES: To investigate the effects of different concentrations of adapalene on the morphology and functions of neuroblastoma cell line SH-SY5Y, as well as its role in inducing cell differentiation and apoptosis. METHODS: SH-SY5Y cells were divided into control group, low concentration (0.1 µM and 1 µM) adapalene groups, and high concentration (10 µM) adapalene group. Time-lapse microscopy was used to observe the morphological changes of SH-SY5Y cells. Immunofluorescence staining was performed to detect the expression of neuronal specific marker ßIII-tubulin and mature neuronal marker neurofilament heavy polypeptide (NFH). Multi-electrode array was used to record the electrophysiological features of SH-SY5Y cells. Cell apoptosis was evaluated using a cell apoptosis detection kit. RESULTS: Low concentrations of adapalene promoted the formation of neurite outgrowth in SH-SY5Y cells, with the neurites interconnected to form a network. Spontaneous discharge activity was observed in SH-SY5Y cells treated with low concentrations of adapalene. Compared to the control group, the expression of ßIII-tubulin and NFH increased in the 1 µM adapalene group, while the level of cell apoptosis increased in the high concentration adapalene group (P<0.05). CONCLUSIONS: Low concentrations of adapalene can induce differentiation of SH-SY5Y cells into mature functional neurons, while high concentrations of adapalene can induce apoptosis in SH-SY5Y cells.

Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester.

BACKGROUND: This study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CUPID performance of experienced senior and junior radiologists. MATERIALS AND METHODS: This prospective cross-sectional study was conducted at Shenzhen University General Hospital between September 2022 and June 2023, and focused on mid-trimester fetuses. All ultrasound images of the six standard planes, that enabled the evaluation of nine biometric measurements, were included to compare the performance of CUPID through subjective and objective assessments. RESULTS: There were 642 fetuses with a mean (±SD) age of 22 ± 2.82 weeks at enrollment. In the subjective quality assessment, out of 642 images representing nine biometric measurements, 617-635 images (90.65-96.11%) of CUPID caliper placements were determined to be accurately placed and did not require any adjustments. Whereas, for the junior category, 447-691 images (69.63-92.06%) were determined to be accurately placed and did not require any adjustments. In the objective measurement indicators, across all nine biometric parameters and estimated fetal weight (EFW), the intra-class correlation coefficients (ICC) (0.843-0.990) and Pearson correlation coefficients (PCC) (0.765-0.978) between the senior radiologist and CUPID reflected good reliability compared with the ICC (0.306-0.937) and PCC (0.566-0.947) between the senior and junior radiologists. Additionally, the mean absolute error (MAE), percentage error (PE), and average error in days of gestation were lower between the senior and CUPID compared to the difference between the senior and junior radiologists. The specific differences are as follows: MAE (0.36-2.53 mm, 14.67 g) compared to (0.64- 8.13 mm, 38.05 g), PE (0.94-9.38%) compared to (1.58-16.04%), and average error in days (3.99-7.92 days) compared to (4.35-11.06 days). In the time-consuming task, CUPID only takes 0.05-0.07 s to measure nine biometric parameters, while senior and junior radiologists require 4.79-11.68 s and 4.95-13.44 s, respectively. CONCLUSIONS: CUPID has proven to be highly accurate and efficient software for automatically measuring fetal biometry, gestational age, and fetal weight, providing a precise and fast tool for assessing fetal growth and development.

Homotopic functional connectivity disruptions in schizophrenia and their associated gene expression.

It has been revealed that abnormal voxel-mirrored homotopic connectivity (VMHC) is present in patients with schizophrenia, yet there are inconsistencies in the relevant findings. Moreover, little is known about their association with brain gene expression profiles. In this study, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control VMHC differences from both the discovery (meta-analysis, including 9 studies with a total of 386 patients and 357 controls) and replication (separate group-level comparisons within two datasets, including a total of 258 patients and 287 controls) phases were performed to identify genes associated with VMHC alterations. Enrichment analyses were conducted to characterize the biological functions and specific expression of identified genes, and Neurosynth decoding analysis was performed to examine the correlation between cognitive-related processes and VMHC alterations in schizophrenia. In the discovery and replication phases, patients with schizophrenia exhibited consistent VMHC changes compared to controls, which were correlated with a series of cognitive-related processes; meta-regression analysis revealed that illness duration was negatively correlated with VMHC abnormalities in the cerebellum and postcentral/precentral gyrus. The abnormal VMHC patterns were stably correlated with 1287 genes enriched for fundamental biological processes like regulation of cell communication, nervous system development, and cell communication. In addition, these genes were overexpressed in astrocytes and immune cells, enriched in extensive cortical regions and wide developmental time windows. The present findings may contribute to a more comprehensive understanding of the molecular mechanisms underlying VMHC alterations in patients with schizophrenia.

Al-MOF-derived porous carbon-modified Pt/C catalyst for constructing a high-performance super fuel cell via an ORR + EDLC parallel-discharge mechanism.

In order to reduce the high polarization caused by the hysteresis effect of O2 diffusion and boost the power density of oxygen cathodes under a transient heavy load, an Al-MOF-derived porous carbon-modified Pt/C catalyst is proposed as a new capacitive ORR catalyst to construct super fuel cells (SFCs) via an ORR + EDLC dual-discharge parallel process. Herein, a capacitive porous carbon material (BTCC-2) with a large specific surface area (SSA) and high graphitization was synthesized via one-step carbonization of Al-MOFs (Al-BTC). After compounding BTCC-2 with commercial Pt/C catalysts, electrochemical tests were performed and revealed that the composite with 40% BTCC-2 provided the highest transient discharge performance. Moreover, the composite had a higher onset potential and limiting current density (5.236 mA cm-2) than Pt/C and a half-wave potential (0.833 V) comparable to that of Pt/C. The abundant pore structure and large surface of BTCC-2 greatly increased the interaction between oxygen and the catalyst surface. Besides, the contained BTCC-2 serve as a significant power bank to remarkably buffer and relieve the rapidly decreasing output voltage under an instant heavy load owing to the oxygen deficiencies in a Zn-air battery through the ORR + EDLC dual-parallel-discharge process. The proposed SFC design has potential as a universal method to solve the sluggish ORR process and provide high transient power density for fuel cell-driven vehicles.

Two isostructural Zn/Co-MOFs with penetrating structures: multifunctional properties of both luminescence sensing and conversion of CO2 into cyclic carbonates.

Two new metal-organic frameworks (MOFs), namely, {[Zn(HL)(bpea)]·DMF}n (Zn-MOF-1) and {[Co(HL)(bpea)]·DMF}n (Co-MOF-2) (H3L = 3-(3,5-dicarboxybenzyloxy)benzoic acid, bpea = 1,2-di(pyridyl)ethane), were obtained by the reaction of H3L and N-containing ligand bpea with Zn(NO3)2·6H2O and Co(NO3)2·6H2O, respectively. The isomorphic Zn-MOF-1 and Co-MOF-2 featured a 3D penetrating framework with different stabilities, luminescence, and catalytic properties. Luminescence measurement indicated that Zn-MOF-1 could be used to detect Al3+ through a turn-on effect with a detection limit of 0.42 µM. The sensing mechanism experiments showed that the enhanced luminescence of Zn-MOF-1 toward Al3+ may be due to the weak interaction between Al3+ and Zn-MOF-1 and the absorbance-caused enhancement (ACE) mechanism. Meanwhile, both Zn-MOF-1 and Co-MOF-2 showed interesting CO2 adsorption properties and could catalyze the cycloaddition of CO2 to epoxides resulting in 96 and 92% ideal products within 12 hours, respectively. They can be cycled up to 5 times without significant loss of catalytic efficiency.

Controllable Modulation of the Electronic Properties of a Two-Dimensional Ambipolar Semiconductor by Interface Ferroelectric Polarization.

Precise control of charge carrier type and density of two-dimensional (2D) ambipolar semiconductors is the prerequisite for their applications in next-generation integrated circuits and electronic devices. Here, by fabricating a heterointerface between a 2D ambipolar semiconductor (hydrogenated germanene, GeH) and a ferroelectric substrate (PbMg1/3Nb2/3O3-PbTiO3, PMN-PT), fine-tuning of charge carrier type and density of GeH is achieved. Due to ambipolar properties, proper band gap, and high carrier mobility of GeH, by applying the opposite local bias (±8 V), a lateral polarization in GeH is constructed with a change of work function by 0.6 eV. Besides, the built-in polarization in GeH nanoflake could promote the separation of photoexcited electron-hole pairs, which lead to 4 times enhancement of the photoconductivity after poling by 200 V. In addition, a gradient regulation of the work function of GeH from 4.94 to 5.21 eV by adjusting the local substrate polarization is demonstrated, which could be used for data storage at the micrometer size by forming p-n homojunctions. This work of constructing such heterointerfaces provides a pathway for applying 2D ambipolar semiconductors in nonvolatile memory devices, photoelectronic devices, and next-generation integrated circuit.

Metformin enhanced the effect of pirfenidone on pulmonary fibrosis in mice.

BACKGROUND: The aim of the study is to observe the anti-inflammatory and antioxidative stress effects of metformin on bleomycin (BLM)-induced pulmonary fibrosis in mice. METHODS: Mice with BLM-induced pulmonary fibrosis were treated with pirfenidone, metformin, pirfenidone plus metformin and the NADPH oxidase 4 (NOX4) inhibitor diphenyleneiodonium chloride (DPI). Pathological changes and hydroxyproline (HPO) levels were examined in the lung tissue of mice with pulmonary fibrosis. Superoxide dismutase (SOD) activity and malonaldehyde (MDA) levels in lung tissue were determined. RESULTS: Compared with pirfenidone, pirfenidone plus metformin could reduce alveolar damage and collagen fibre deposition and alleviate BLM-induced pulmonary fibrosis. Lung HPO levels were significantly lower in the PFD + MET group than in the BLM group (p < 0.05). SOD levels in the lungs of mice were increased in the PFD + MET group than in the BLM group (p < 0.05). Metformin and pirfenidone plus metformin can reduce MDA levels (p < 0.05). Pirfenidone plus metformin could reduce HPO levels, increase SOD levels, and reduce MDA levels in the lungs of mice. There was a significant correlation between the HPO level and the Ashcroft score (r = 0.520, p < 0.001). CONCLUSION: Metformin enhanced the antifibrotic effects of pirfenidone on BLM-treated mice. Moreover, these findings provide an experimental basis for examining whether metformin can improve the antifibrotic effects of pirfenidone on patients with idiopathic pulmonary fibrosis (IPF). It has broad therapeutic prospects for patients with IPF.

Radiomics using CT images for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma: a multi-centric study.

OBJECTIVES: To develop a CT-based radiomics model for preoperative prediction of lymph node (LN) metastasis in perihilar cholangiocarcinoma (pCCA). METHODS: The study enrolled consecutive pCCA patients from three independent Chinese medical centers. The Boruta algorithm was applied to build the radiomics signature for the primary tumor and LN. The k-means algorithm was employed to cluster the selected LNs based on the radiomics signature LN. Support vector machines were used to construct the prediction models. The diagnostic efficiency was measured by the area under the receiver operating characteristic curve (AUC). The optimal model was evaluated in terms of calibration, clinical usefulness, and prognostic value. RESULTS: A total of 214 patients were included in the study (mean age: 61.6 years ± 9.4; 130 male). The selected LNs were classified into two clusters, which were significantly correlated with LN metastasis in all cohorts (p < 0.001). The model incorporated the clinical risk factors, radiomics signature primary tumor, and the LN cluster obtained the best discrimination, with AUC values of 0.981 (95% CI: 0.962-1), 0.896 (95% CI: 0.810-0.982), and 0.865 (95% CI: 0.768-0.961) in the training, internal validation, and external validation cohorts, respectively. High-risk patients predicted by the optimal model had shorter overall survival than low-risk patients (median, 13.7 vs. 27.3 months, p < 0.001). CONCLUSIONS: The study proposed a radiomics model with good performance to predict LN metastasis in pCCA. As a noninvasive preoperative prediction tool, this model may help in patient risk stratification and personalized treatment. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics model accurately predicts lymph node metastasis in perihilar cholangiocarcinoma patients. This noninvasive preoperative tool can aid in patient risk stratification and personalized treatment, potentially improving patient outcomes. KEY POINTS: • The radiomics model based on contrast-enhanced CT is a useful tool for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma. • Radiomics features extracted from lymph nodes show great potential for predicting lymph node metastasis. • The study is the first to identify a lymph node phenotype with a high probability of metastasis based on radiomics.

Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy.

OBJECTIVES: To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR). METHODS: In this prospective study, two groups of 40 participants each underwent abdominal contrast-enhanced scans with full-dose SECT (120-kVp images, DLIR and IR algorithms) or reduced-dose DECT (40- to 60-keV virtual monochromatic images [VMIs], DLIR algorithm), with 122 and 106 metastases, respectively. Groups were matched by age, sex ratio, body mass index, and cross-sectional area. Noise power spectrum of liver images and task-based transfer function of metastases were calculated to assess the noise texture and low-contrast resolution. The image noise, signal-to-noise ratios (SNR) of liver and portal vein, liver-to-lesion contrast-to-noise ratio (LLR), lesion conspicuity, lesion detection rate, and the subjective image quality metrics were compared between groups on 1.25-mm reconstructed images. RESULTS: Compared to 120-kVp images with IR, 40- and 50-keV VMIs with DLIR showed similar noise texture and LLR, similar or higher image noise and low-contrast resolution, improved SNR and lesion conspicuity, and similar or better perceptual image quality. When compared to 120-kVp images with DLIR, 50-keV VMIs with DLIR had similar low-contrast resolution, SNR, LLR, lesion conspicuity, and perceptual image quality but lower frequency noise texture and higher image noise. For the detection of hepatic metastases, reduced-dose DECT by 34% maintained observer lesion detection rates. CONCLUSION: DECT assisted with DLIR enables a 34% dose reduction for detecting hepatic metastases while maintaining comparable perceptual image quality to full-dose SECT. CLINICAL RELEVANCE STATEMENT: Reduced-dose dual-energy CT with deep learning image reconstruction is as accurate as standard-dose single-energy CT for the detection of liver metastases and saves more than 30% of the radiation dose. KEY POINTS: • The 40- and 50-keV virtual monochromatic images (VMIs) with deep learning image reconstruction (DLIR) improved lesion conspicuity compared with 120-kVp images with iterative reconstruction while providing similar or better perceptual image quality. • The 50-keV VMIs with DLIR provided comparable perceptual image quality and lesion conspicuity to 120-kVp images with DLIR. • The reduction of radiation by 34% by DLIR in low-keV VMIs is clinically sufficient for detecting low-contrast hepatic metastases.

Deep learning reconstruction vs standard reconstruction for abdominal CT: the influence of BMI.

OBJECTIVE: This study aimed to evaluate the image quality and lesion conspicuity of the deep learning image reconstruction (DLIR) algorithm compared with standard image reconstruction algorithms on abdominal enhanced computed tomography (CT) scanning with a wide range of body mass indexes (BMIs). METHODS: A total of 112 participants who underwent contrast-enhanced abdominal CT scans were divided into three groups according to BMIs: the 80-kVp group (BMI ≤ 23.9 kg/m2), 100-kVp group (BMI 24-28.9 kg/m2), and 120-kVp group (BMI ≥ 29 kg/m2). All images were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction-V of 50% level (IR), and DLIR at low, medium, and high levels (DL, DM, and DH, respectively). Subjective noise, artifact, overall image quality, and low- and high-contrast hepatic lesion conspicuity were all graded on a 5-point scale. The CT attenuation value (in HU), image noise, and contrast-to-noise ratio (CNR) were quantified and compared. RESULTS: DM and DH improved the qualitative and quantitative parameters compared with FBP and IR for all three BMI groups. DH had the lowest image noise and highest CNR value, while DM had the highest subjective overall image quality and low- and high-contrast lesion conspicuity scores for the three BMI groups. Based on the FBP, the improvement in image quality and lesion conspicuity of DM and DH images was greater in the 80-kVp group than in the 100-kVp and 120-kVp groups. CONCLUSION: For all BMIs, DLIR improves both image quality and hepatic lesion conspicuity, of which DM would be the best choice to balance both. CLINICAL RELEVANCE STATEMENT: The study suggests that utilizing DLIR, particularly at the medium level, can significantly enhance image quality and lesion visibility on abdominal CT scans across a wide range of BMIs. KEY POINTS: • DLIR improved the image quality and lesion conspicuity across a wide range of BMIs. • DLIR at medium level had the highest subjective parameters and lesion conspicuity scores among all reconstruction levels. • On the basis of the FBP, the 80-kVp group had improved image quality and lesion conspicuity more than the 100-kVp and 120-kVp groups.

Decreased FAM13B Expression Increases Atrial Fibrillation Susceptibility by Regulating Sodium Current and Calcium Handling.

A specific genetic variant associated with atrial fibrillation risk, rs17171731, was identified as a regulatory variant responsible for controlling FAM13B expression. The atrial fibrillation risk allele decreases FAM13B expression, whose knockdown alters the expression of many genes in stem cell-derived cardiomyocytes, including SCN2B, and led to pro-arrhythmogenic changes in the late sodium current and Ca2+ cycling. Fam13b knockout mice had increased P-wave and QT interval duration and were more susceptible to pacing-induced arrhythmias vs control mice. FAM13B expression, its regulation, and downstream effects are potential targets for investigation of patient-specific therapeutics.

Enhanced focal cortical dysplasia detection in pediatric frontal lobe epilepsy with asymmetric radiomic and morphological features.

Objective: Focal cortical dysplasia (FCD) is the most common pathological cause for pediatric epilepsy, with frontal lobe epilepsy (FLE) being the most prevalent in the pediatric population. We attempted to utilize radiomic and morphological methods on MRI and PET to detect FCD in children with FLE. Methods: Thirty-seven children with FLE and 20 controls were included in the primary cohort, and a five-fold cross-validation was performed. In addition, we validated the performance in an independent site of 12 FLE children. A two-stage experiments including frontal lobe and subregions were employed to detect the lesion area of FCD, incorporating the asymmetric feature between the left and right hemispheres. Specifically, for the radiomics approach, we used gray matter (GM), white matter (WM), GM and WM, and the gray-white matter boundary regions of interest to extract features. Then, we employed a Multi-Layer Perceptron classifier to achieve FCD lesion localization based on both radiomic and morphological methods. Results: The Multi-Layer Perceptron model based on the asymmetric feature exhibited excellent performance both in the frontal lobe and subregions. In the primary cohort and independent site, the radiomics analysis with GM and WM asymmetric features had the highest sensitivity (89.2 and 91.7%) and AUC (98.9 and 99.3%) in frontal lobe. While in the subregions, the GM asymmetric features had the highest sensitivity (85.6 and 79.7%). Furthermore, relying on the highest sensitivity of GM and WM asymmetric features in frontal lobe, when integrated with the subregions results, our approach exhibited overlaps with GM asymmetric features (55.4 and 52.4%), as well as morphological asymmetric features (54.4 and 53.8%), both in the primary cohort and at the independent site. Significance: This study demonstrates that a two-stage design based on the asymmetry of radiomic and morphological features can improve FCD detection. Specifically, incorporating regions of interest for GM, WM, GM, and WM, and the gray-white matter boundary significantly enhances the localization capabilities for lesion detection within the radiomics approach.

Clinical and functional consequences of GRIA variants in patients with neurological diseases.

AMPA receptors are members of the glutamate receptor family and mediate a fast component of excitatory synaptic transmission at virtually all central synapses. Thus, their functional characteristics are a critical determinant of brain function. We evaluate intolerance of each GRIA gene to genetic variation using 3DMTR and report here the functional consequences of 52 missense variants in GRIA1-4 identified in patients with various neurological disorders. These variants produce changes in agonist EC50, response time course, desensitization, and/or receptor surface expression. We predict that these functional and localization changes will have important consequences for circuit function, and therefore likely contribute to the patients' clinical phenotype. We evaluated the sensitivity of variant receptors to AMPAR-selective modulators including FDA-approved drugs to explore potential targeted therapeutic options.

Constructing a prognostic model for head and neck squamous cell carcinoma based on glucose metabolism related genes.

Background: Glucose metabolism (GM) plays a crucial role in cancer cell proliferation, tumor growth, and survival. However, the identification of glucose metabolism-related genes (GMRGs) for effective prediction of prognosis in head and neck squamous cell carcinoma (HNSC) is still lacking. Methods: We conducted differential analysis between HNSC and Normal groups to identify differentially expressed genes (DEGs). Key module genes were obtained using weighted gene co-expression network analysis (WGCNA). Intersection analysis of DEGs, GMRGs, and key module genes identified GMRG-DEGs. Univariate and multivariate Cox regression analyses were performed to screen prognostic-associated genes. Independent prognostic analysis of clinical traits and risk scores was implemented using Cox regression. Gene set enrichment analysis (GSEA) was used to explore functional pathways and genes between high- and low-risk groups. Immune infiltration analysis compared immune cells between the two groups in HNSC samples. Drug prediction was performed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Quantitative real-time fluorescence PCR (qRT-PCR) validated the expression levels of prognosis-related genes in HNSC patients. Results: We identified 4973 DEGs between HNSC and Normal samples. Key gene modules, represented by black and brown module genes, were identified. Intersection analysis revealed 76 GMRG-DEGs. Five prognosis-related genes (MTHFD2, CDKN2A, TPM2, MPZ, and DNMT1) were identified. A nomogram incorporating age, lymph node status (N), and risk score was constructed for survival prediction in HNSC patients. Immune infiltration analysis showed significant differences in five immune cell types (Macrophages M0, memory B cells, Monocytes, Macrophages M2, and Dendritic resting cells) between the high- and low-risk groups. GDSC database analysis identified 53 drugs with remarkable differences between the groups, including A.443654 and AG.014699. DNMT1 and MTHFD2 were up-regulated, while MPZ was down-regulated in HNSC. Conclusion: Our study highlights the significant association of five prognosis-related genes (MTHFD2, CDKN2A, TPM2, MPZ, and DNMT1) with HNSC. These findings provide further evidence of the crucial role of GMRGs in HNSC.

The Influence of Positional Isomerism of Terminal Alkyl Chains on Mesomorphic and Photophysical Behavior of Unsymmetric α-cyanostilbene-based Tetracatenars.

Two series of unsymmetric α-cyanostilbene-based tetracatenars containing three hexadecyl chains at one end and one alkyl chain with varying lengths at the other end were prepared by using Suzuki coupling and Knoevenagel reactions. These tetracatenars with the terminal three hexadecyl chains, which are adjacent to the cyano group are non-mesogens, whereas the isomers with one alkyl chain, which is adjacent to the cyano group display transition from non-mesogens to monotropic hexagonal columnar liquid crystal upon elongation of the alkyl chain. This transition could be attributed to that the three hexadecyl chains which are adjacent to the cyano group decrease the interactions between π-conjugated rigid cores, hindering the formation of mesophase. In addition, weak slovatochromism implies weak ICT in both series tetracatenars. Both series isomers exhibit distinct AIE characteristics attributing to the presence of α-cyanostilbene, which could induce stereoisomerism and restricted intermolecular rotation in the aggregated state. Different mechanochromism behaviors could be achieved due to the positional isomerism of terminal alkyl chains. Therefore, tuning the position of terminal alkyl chains could give rise to distinct changes in the molecular aggregate, which provides a scheme to build multifunctional materials with diverse potentials.

Genome-Wide Identification and Expression Analysis of the SWEET Gene Family in Annual Alfalfa (Medicago polymorpha).

SWEET (Sugars will eventually be exported transporter) proteins are a group of sugar transporters that are involved in sugar efflux, phloem loading, reproductive development, plant senescence, and stress responses. In this study, 23 SWEET transporter members were identified in the Medicago polymorpha genome, heterogeneously distributed on seven chromosomes. These MpSWEET genes were divided into four subfamilies, which showed similar gene structure and motif composition within the same subfamily. Seventeen MpSWEET genes encode seven transmembrane helices (TMHs), and all MpSWEET proteins possess conserved membrane domains and putative serine phosphorylation sites. Four and three pairs of MpSWEET genes were predicted to be segmentally and tandemly duplicated, respectively, which may have contributed to their evolution of M. polymorpha. The results of microarray and RNA-Seq data showed that some MpSWEET genes were specifically expressed in disparate developmental stages (including seedling stage, early flowering stage, and late flowering stage) or tissues such as flower and large pod. Based on protein network interaction and expression patterns of MpSWEET genes, six MpSWEET genes were selected for further quantitative real-time PCR validation in different stress treatments. qRT-PCR results showed that MpSWEET05, MpSWEET07, MpSWEET12, MpSWEET15, and MpSWEET21 were significantly upregulated for at least two of the three abiotic stress treatments. These findings provide new insights into the complex transcriptional regulation of MpSWEET genes, which facilitates future research to elucidate the function of MpSWEET genes in M. polymorpha and other legume crops.