Deep learning-based reconstruction enhances image quality and improves diagnosis in magnetic resonance imaging of the shoulder joint.

Background: Accelerated magnetic resonance imaging sequences reconstructed using the vendor-provided Recon deep learning algorithm (DL-MRI) were found to be more likely than conventional magnetic resonance imaging (MRI) sequences to detect subacromial (SbA) bursal thickening. However, the extent of this thickening was not extensively explored. This study aimed to compare the image quality of DL-MRI with conventional MRI sequences reconstructed via conventional pipelines (Conventional-MRI) for shoulder examinations and evaluate the effectiveness of DL-MRI in accurately demonstrating the degree of SbA bursal and subcoracoid (SC) bursal thickening. Methods: This prospective cross-sectional study enrolled 41 patients with chronic shoulder pain who underwent 3-T MRI (including both Conventional-MRI and accelerated MRI sequences) of the shoulder between December 2022 and April 2023. Each protocol consisted of oblique axial, coronal, and sagittal images, including proton density-weighted imaging (PDWI) with fat suppression (FS) and oblique coronal T1-weighted imaging (T1WI) with FS. The image quality and degree of artifacts were assessed using a 5-point Likert scale for both Conventional-MRI and DL-MRI. Additionally, the degree of SbA and SC bursal thickening, as well as the relative signal-to-noise ratio (rSNR) and relative contrast-to-noise ratio (rCNR) were analyzed using the paired Wilcoxon test. Statistical significance was defined as P<0.05. Results: The utilization of accelerated sequences resulted in a remarkable 54.7% reduction in total scan time. Overall, DL-MRI exhibited superior image quality scores and fewer artifacts compared to Conventional-MRI. Specifically, DL-MRI demonstrated significantly higher measurements of SC bursal thickenings in the oblique sagittal PDWI sequence compared to Conventional-MRI [3.92 (2.83, 5.82) vs. 3.74 (2.92, 5.96) mm, P=0.028]. Moreover, DL-MRI exhibited higher detection of SbA bursal thickenings in the oblique coronal PDWI sequence [2.61 (1.85, 3.46) vs. 2.48 (1.84, 3.25) mm], with a notable trend towards significant differences (P=0.071). Furthermore, the rSNRs of the muscle in DL-MRI images were significantly higher than those in Conventional-MRI images across most sequences (P<0.001). However, the rSNRs of bone on Conventional-MRI of oblique axial and oblique coronal PDWI sequences showed adverse results [oblique axial: 1.000 (1.000, 1.000) vs. 0.444 (0.367, 0.523); and oblique coronal: 1.000 (1.000, 1.000) vs. 0.460 (0.387, 0.631); all P<0.001]. Additionally, all DL-MRI images exhibited significantly greater rSNRs and rCNRs compared to accelerated MRI sequences reconstructed using traditional pipelines (P<0.001). Conclusions: In conclusion, the utilization of DL-MRI enhances image quality and improves diagnostic capabilities, making it a promising alternative to Conventional-MRI for shoulder imaging.

MRI-guided cell membrane-camouflaged bimetallic coordination nanoplatform for combined tumor phototherapy.

Nanotechnology for tumor diagnosis and optical therapy has attracted widespread interest due to its low toxicity and convenience but is severely limited due to uncontrollable tumor targeting. In this work, homologous cancer cell membrane-camouflaged multifunctional hybrid metal coordination nanoparticles (DRu/Gd@CM) were prepared for MRI-guided photodynamic therapy (PDT) and photothermal therapy (PTT) of tumors. Bimetallic coordination nanoparticles are composed of three functional modules: dopamine, Ru(dcbpy)3Cl2 and GdCl3, which are connected through 1,4-Bis[(1H-imidazole-1-yl)methyl]benzene (BIX). Their morphology can be easily controlled by adjusting the ratio of precursors. Optimistically, the intrinsic properties of the precursors, including the photothermal properties of polydopamine (PDA), the magnetic resonance (MR) response of Gd3+, and the singlet oxygen generation of Ru(dcbpy)3Cl2, are well preserved in the hybrid metal nanoparticles. Furthermore, the targeting of homologous cancer cell membranes enables these coordinated nanoparticles to precisely target tumor cells. The MR imaging capabilities and the combination of PDT and PTT were demonstrated in in vitro experiments. In addition, in vivo experiments indicated that the nanoplatform showed excellent tumor accumulation and therapeutic effects on mice with subcutaneous tumors, and could effectively eliminate tumors within 14 days. Therefore, it expanded the new horizon for the preparation of modular nanoplatform and imaging-guided optical therapy of tumors.

Differentiation of confluent hepatic fibrosis and infiltrative hepatocellular carcinoma on MR imaging.

BACKGROUND: To identify reliable magnetic resonance imaging (MRI) features that can differentiate confluent fibrosis (CF) from infiltrative hepatocellular carcinoma (HCC). METHODS: A retrospective analysis was conducted on Twenty CF patients and 28 infiltrative HCC patients who underwent upper abdomen MRI scans. The imaging features of lesions were analyzed, and the apparent diffusion coefficient (ADC) of lesions were measured. Accuracy, sensitivity and specificity for the diagnosis of CF were calculated for each category individually and combined. RESULTS: Compared to infiltrative HCC, hepatic capsular retraction at the site of lesion, hepatic volume loss at the site of lesion and "nodular surround sign" were more common in patients with CF (all P < 0.001). Hepatic volume loss at the site of lesion, no or mild enhancement in arterial phase, and hyper-enhancing in delayed phase to the background parenchyma showed superior diagnostic accuracy (83.3%, 85.4%, 97.9%, respectively). When the lesion exhibited hepatic volume loss at the site of lesion or no or mild enhancement in arterial phase or hyper-enhancing in delayed phase, a sensitivity of 100.0% for the diagnosis of CF was achieved. When the lesion was positive for any two of three categories, or positive for all three categories, a specificity of 100.0% was achieved. The ADC values of CF were higher than those of infiltrative HCC (P < 0.001). CONCLUSION: The combination of the hepatic volume loss at the site of lesion, no or mild enhancement in arterial phase, and hyper-enhancing in delayed phase to the background parenchyma can be considered reliable MR features for the diagnosis of CF, as they allow differentiation from infiltrative HCC.

The ENG/VEGFα Pathway Is Likely Affected by a Nonsense Variant of Endoglin (ENG)/CD105, Causing Hereditary Hemorrhagic Telangiectasia Type 1 (HHT1) in a Chinese Family.

Hereditary hemorrhagic telangiectasia (HHT), also called Rendu-Osler syndrome, is a group of rare genetic diseases characterized by autosomal dominance, multisystemic vascular dysplasia, and age-related penetrance. This includes arteriovenous malformations (AVMs) in the skin, brain, lung, liver, and mucous membranes. The correlations between the phenotype and genotype for HHT are not clear. An HHT Chinese pedigree was recruited. Whole exome sequencing (WES) analysis, Sanger verification, and co-segregation were conducted. Western blotting was performed for monitoring ENG/VEGFα signaling. As a result, a nonsense, heterozygous variant for ENG/CD105: c.G1169A:p. Trp390Ter of the proband with hereditary hemorrhagic telangiectasia type 1 (HHT1) was identified, which co-segregated with the disease in the M666 pedigree. Western blotting found that, compared with the normal levels associated with non-carrier family members, the ENG protein levels in the proband showed approximately a one-half decrease (47.4% decrease), while levels of the VEGFα protein, in the proband, showed approximately a one-quarter decrease (25.6% decrease), implying that ENG haploinsufficiency, displayed in the carrier of this variant, may affect VEGFα expression downregulation. Pearson and Spearman correlation analyses further supported TGFß/ENG/VEGFα signaling, implying ENG regulation in the blood vessels. Thus, next-generation sequencing including WES should provide an accurate strategy for gene diagnosis, therapy, genetic counseling, and clinical management for rare genetic diseases including that in HHT1 patients.

Precisely Patterned Channels in a Vertical Organic Electrochemical Transistor with a Diazirine Photo-Crosslinker.

Organic electrochemical transistors (OECTs) rely on both efficient ionic doping/de-doping process and carrier transport in the mixed ionic-electronic channel under the modulation of gate bias. Moreover, channels that hold photopatterning capability are highly desired to minimize parasitic capacitance and simplify the fabrication process/cost. However, yielding photo-patternable channels with both precise/robust patterning capability and controllable ionic-electronic coupling is still challenging. Herein, double-end trifluoromethyl diazirines (DtFDA) with different chain lengths are introduced in the OECT channel to act as both photo-crosslinker and medium to regulate ionic-electronic transport. Specifically, high-resolution patterns with a minimum line width/gap of 2 µm are realized in p(g2T-T) or Homo-gDPP based channels by introducing DtFDA. Maximum transconductances of 68.6 mS and 81.6 mS, current on/off ratio of 106 and 107 (under a drain voltage of only ±0.1 V), are achieved in p- and n-type vertical OECTs (vOECTs), respectively, along with current densities exceeding 1 kA cm-2 and good cycling stability of more than 100,000 cycles (2000 seconds). This work provides a new and facile strategy for the fabrication of vOECT channels with high resolution and high performance via the introduction of a simple and efficient crosslinker.

Facile synthesis of Gd/Ru-doped fluorescent carbon dots for fluorescent/MR bimodal imaging and tumor therapy.

Functional metal doping endows fluorescent carbon dots with richer physical and chemical properties, greatly expanding their potential in the biomedical field. Nonetheless, fabricating carbon dots with integrated functionality for diagnostic and therapeutic modalities remains challenging. Herein, we develop a simple strategy to prepare Gd/Ru bimetallic doped fluorescent carbon dots (Gd/Ru-CDs) via a one-step microwave-assisted method with Ru(dcbpy)3Cl2, citric acid, polyethyleneimine, and GdCl3 as precursors. Multiple techniques were employed to characterize the morphology and properties of the obtained carbon dots. The Gd/Ru-CDs are high mono-dispersity, uniform spherical nanoparticles with an average diameter of 4.2 nm. Moreover, X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared (FTIR) confirmed the composition and surface properties of the carbon dots. In particular, the successful doping of Gd/Ru enables the carbon dots not only show considerable magnetic resonance imaging (MRI) performance but also obtain better fluorescence (FL) properties, especially in the red emission area. More impressively, it has low cytotoxicity, excellent biocompatibility, and efficient reactive oxygen species (ROS) generation ability, making it an effective imaging-guided tumor treatment reagent. In vivo experiments have revealed that Gd/Ru-CDs can achieve light-induced tumor suppression and non-invasive fluorescence/magnetic resonance bimodal imaging reagents to monitor the treatment process of mouse tumor models. Thus, this simple and efficient carbon dot manufacturing strategy by doping functional metals has expanded avenues for the development and application of multifunctional all-in-one theranostics.

High-performance presurgical differentiation of glioblastoma and metastasis by means of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics.

OBJECTIVES: To evaluate the performance of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics in distinguishing between glioblastoma (Gb) and solitary brain metastasis (SBM). MATERIALS AND METHODS: In this retrospective study, NODDI images were curated from 109 patients with Gb (n = 57) or SBM (n = 52). Automatically segmented multiple volumes of interest (VOIs) encompassed the main tumor regions, including necrosis, solid tumor, and peritumoral edema. Radiomics features were extracted for each main tumor region, using three NODDI parameter maps. Radiomics models were developed based on these three NODDI parameter maps and their amalgamation to differentiate between Gb and SBM. Additionally, radiomics models were constructed based on morphological magnetic resonance imaging (MRI) and diffusion imaging (diffusion-weighted imaging [DWI]; diffusion tensor imaging [DTI]) for performance comparison. RESULTS: The validation dataset results revealed that the performance of a single NODDI parameter map model was inferior to that of the combined NODDI model. In the necrotic regions, the combined NODDI radiomics model exhibited less than ideal discriminative capabilities (area under the receiver operating characteristic curve [AUC] = 0.701). For peritumoral edema regions, the combined NODDI radiomics model achieved a moderate level of discrimination (AUC = 0.820). Within the solid tumor regions, the combined NODDI radiomics model demonstrated superior performance (AUC = 0.904), surpassing the models of other VOIs. The comparison results demonstrated that the NODDI model was better than the DWI and DTI models, while those of the morphological MRI and NODDI models were similar. CONCLUSION: The NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM. CLINICAL RELEVANCE STATEMENT: The NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM, and radiomics features can be incorporated into the multidimensional phenotypic features that describe tumor heterogeneity. KEY POINTS: • The neurite orientation dispersion and density imaging (NODDI) radiomics model showed promising performance for preoperative discrimination between glioblastoma and solitary brain metastasis. • Compared with other tumor volumes of interest, the NODDI radiomics model based on solid tumor regions performed best in distinguishing the two types of tumors. • The performance of the single-parameter NODDI model was inferior to that of the combined-parameter NODDI model.

Abnormal effective connectivity of reward network in first-episode schizophrenia with auditory verbal hallucinations.

OBJECTIVE: Auditory verbal hallucinations (AVHs) in schizophrenia is proved to be associated with dysfunction of mesolimbic-cortical circuits, especially during abnormal salient and internal verbal resource monitoring processing procedures. However, the information flow among areas involved in coordinated interaction implicated the pathophysiology of AVHs remains unclear. METHODS: We used spectral dynamic causal modeling (DCM) to quantify connections among eight critical hubs of reward network in 86 first-episode drug-naïve schizophrenia patients with AVHs (AVH), 93 patients without AVHs (NAVH), and 88 matched normal controls (NC) using resting-state functional magnetic resonance imaging. Group-level connection coefficients, between-group differences and correlation analysis between image measures and symptoms were performed. RESULT: DCM revealed weaker effective connectivity (EC) from right ventral striatum (RVS) to ventral tegmental area (VTA) in AVH compared to NAVH. AVH showed stronger EC from left anterior insula (AI) to RVS, stronger EC from RVS to anterior cingulate cortex (ACC), and stronger EC from VTA to posterior cingulate cortex (PCC) compared to NC. The correlation analysis results were mostly visible in the negative correlation between EC from right AI to ACC and positive sub-score, P1 sub-score, and P3 sub-score of PNASS in group-level. CONCLUSION: These findings suggest that neural causal interactions between the reward network associated with AVHs are disrupted, expanding the evidence for potential neurobiological mechanisms of AVHs. Particularly, dopamine-dependent salience attribution and top-down monitoring impairments and compensatory effects of enhanced excitatory afferents to ACC, which may provide evidence for a therapeutic target based on direct in vivo of AVHs in schizophrenia.

Radiomic profiling for insular diffuse glioma stratification with distinct biologic pathway activities.

Current literature emphasizes surgical complexities and customized resection for managing insular gliomas; however, radiogenomic investigations into prognostic radiomic traits remain limited. We aimed to develop and validate a radiomic model using multiparametric magnetic resonance imaging (MRI) for prognostic prediction and to reveal the underlying biological mechanisms. Radiomic features from preoperative MRI were utilized to develop and validate a radiomic risk signature (RRS) for insular gliomas, validated through paired MRI and RNA-seq data (N = 39), to identify core pathways underlying the RRS and individual prognostic radiomic features. An 18-feature-based RRS was established for overall survival (OS) prediction. Gene set enrichment analysis (GSEA) and weighted gene coexpression network analysis (WGCNA) were used to identify intersectional pathways. In total, 364 patients with insular gliomas (training set, N = 295; validation set, N = 69) were enrolled. RRS was significantly associated with insular glioma OS (log-rank p = 0.00058; HR = 3.595, 95% CI:1.636-7.898) in the validation set. The radiomic-pathological-clinical model (R-P-CM) displayed enhanced reliability and accuracy in prognostic prediction. The radiogenomic analysis revealed 322 intersectional pathways through GSEA and WGCNA fusion; 13 prognostic radiomic features were significantly correlated with these intersectional pathways. The RRS demonstrated independent predictive value for insular glioma prognosis compared with established clinical and pathological profiles. The biological basis for prognostic radiomic indicators includes immune, proliferative, migratory, metabolic, and cellular biological function-related pathways.

T1 mapping as a quantitative imaging biomarker for diagnosing cervical cancer: a comparison with diffusion kurtosis imaging.

BACKGROUND: T1 mapping can potentially quantitatively assess the intrinsic properties of tumors. This study was conducted to explore the ability of T1 mapping in distinguishing cervical cancer type, grade, and stage and compare the diagnostic performance of T1 mapping with diffusion kurtosis imaging (DKI). METHODS: One hundred fifty-seven patients with pathologically confirmed cervical cancer were enrolled in this prospectively study. T1 mapping and DKI were performed. The native T1, difference between native and postcontrast T1 (T1diff), mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) were calculated. Cervical squamous cell carcinoma (CSCC) and adenocarcinoma (CAC), low- and high-grade carcinomas, and early- and advanced-stage groups were compared using area under the receiver operating characteristic (AUROC) curves. RESULTS: The native T1 and MK were higher, and the MD and ADC were lower for CSCC than for CAC (all p < 0.05). Compared with low-grade CSCC, high-grade CSCC had decreased T1diff, MD, ADC, and increased MK (p < 0.05). Compared with low-grade CAC, high-grade CAC had decreased T1diff and increased MK (p < 0.05). Native T1 was significantly higher in the advanced-stage group than in the early-stage group (p < 0.05). The AUROC curves of native T1, MK, ADC and MD were 0,772, 0.731, 0.715, and 0.627, respectively, for distinguishing CSCC from CAC. The AUROC values were 0.762 between high- and low-grade CSCC and 0.835 between high- and low-grade CAC, with T1diff and MK showing the best discriminative values, respectively. For distinguishing between advanced-stage and early-stage cervical cancer, only the AUROC of native T1 was statistically significant (AUROC = 0.651, p = 0.002). CONCLUSIONS: Compared with DKI-derived parameters, native T1 exhibits better efficacy for identifying cervical cancer subtype and stage, and T1diff exhibits comparable discriminative value for cervical cancer grade.

Wall permeability on magnetic resonance imaging is associated with intracranial aneurysm symptoms and wall enhancement.

OBJECTIVES: Wall remodeling and inflammation accompany symptomatic unruptured intracranial aneurysms (UIAs). The volume transfer constant (Ktrans) of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) reflects UIA wall permeability. Aneurysmal wall enhancement (AWE) on vessel wall MRI (VWI) is associated with inflammation. We hypothesized that Ktrans is related to symptomatic UIAs and AWE. METHODS: Consecutive patients with UIAs were prospectively recruited for 3-T DCE-MRI and VWI from January 2018 to March 2023. UIAs were classified as asymptomatic and symptomatic if associated with sentinel headache or oculomotor nerve palsy. Ktrans and AWE were assessed on DCE-MRI and VWI, respectively. AWE was evaluated using the AWE pattern and wall enhancement index (WEI). Spearman's correlation coefficient and univariate and multivariate analyses were used to assess correlations between parameters. RESULTS: We enrolled 82 patients with 100 UIAs (28 symptomatic and 72 asymptomatic). The median Ktrans (2.1 versus 0.4 min-1; p < 0.001) and WEI (1.5 versus 0.4; p < 0.001) were higher for symptomatic aneurysms than for asymptomatic aneurysms. Ktrans (odds ratio [OR]: 1.60, 95% confidence interval [95% CI]: 1.01-2.52; p = 0.04) and WEI (OR: 3.31, 95% CI: 1.05-10.42; p = 0.04) were independent risk factors for symptomatic aneurysms. Ktrans was positively correlated with WEI (Spearman's coefficient of rank correlation (rs) = 0.41, p < 0.001). The combination of Ktrans and WEI achieved an area under the curve of 0.81 for differentiating symptomatic from asymptomatic aneurysms. CONCLUSIONS: Ktrans may be correlated with symptomatic aneurysms and AWE. Ktrans and WEI may provide an additional value than the PHASES score for risk stratification of UIAs. CLINICAL RELEVANCE STATEMENT: The volume transfer constant (Ktrans) from DCE-MRI perfusion is associated with symptomatic aneurysms and provides additional value above the clinical PHASES score for risk stratification of intracranial aneurysms. KEY POINTS: • The volume transfer constant is correlated with intracranial aneurysm symptoms and aneurysmal wall enhancement. • Dynamic contrast-enhanced and vessel wall MRI facilitates understanding of the pathophysiological characteristics of intracranial aneurysm walls. • The volume transfer constant and wall enhancement index perform better than the traditional PHASES score in differentiating symptomatic aneurysms.

Comprehensive analysis and immunohistochemistry localization of NRP1 expression in pancancer and normal individual tissues in relation to SARS­CoV­2 susceptibility.

Neuropilin 1 (NRP1/CD304) is a typical membrane-bound co-receptor for vascular endothelial growth factor, semaphorin family members and viral severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, NRP1 expression levels across cancer types and the potential role of SARS-CoV-2 infection in patients with cancer are not clear. Online databases, such as The Cancer Genome Atlas database of Human Protein Atlas, Gene Expression Profiling Interactive Analysis and cBioPortal were used for the expression analysis in this study. Immunohistochemical (IHC) staining for NRP1 was performed in the tissues of patients with non-small cell carcinoma. As a result, it was found that NRP1 mRNA and protein expression levels were highest in the female reproductive tissues and the respiratory system, specifically in the nasopharynx, bronchus and fallopian tube, as well as in adipocytes, hepatic stellate cells, Sertoli cells, endothelial cells and dendritic cells. IHC showed that the NRP1 protein was mainly localized to the cytoplasm and membrane in the tissues of patients with non-small cell carcinoma, demonstrating its role in lung infection by SARS-CoV-2, due to invasion of cell membranes by the virus. Levels of NRP1 mRNA were significantly increased in lymphoid neoplasm diffuse large B-cell lymphoma, esophageal carcinoma, glioblastoma multiforme, head and neck squamous cell carcinoma, kidney renal clear cell carcinoma (KIRC), pancreatic adenocarcinoma, stomach adenocarcinoma and thymoma, and significantly decreased in cervical squamous cell carcinoma and endocervical adenocarcinoma, kidney chromophobe, lung squamous cell carcinoma, ovarian serous cystadenocarcinoma, uterine corpus endometrial carcinoma and uterine carcinosarcoma, compared with corresponding healthy tissues in pancancer, indicating roles for viral invasion in most cancer types. Moreover, low NRP1 expression was significantly associated with long overall survival (OS) time in adrenocortical carcinoma, brain lower grade glioma, stomach adenocarcinoma and uveal melanoma, but with short OS time in KIRC only. The ENST00000374867.6 (NRP1-202) isoform is most highly expressed in most cancer types and thus could be involved in tumorigenesis and SARS-CoV-2 invasion in cancer patients. NRP1 may be involved in SARS-CoV-2 invasion in patients with cancer, including those with lung cancer.

A multicenter study of cervical cancer using quantitative diffusion-weighted imaging.

BACKGROUND: Parameters from diffusion-weighted imaging (DWI) have been increasingly used as imaging biomarkers for the diagnosis and monitoring of treatment responses in cancer. The consistency of DWI measurements across different centers remains uncertain, which limits the widespread use of quantitative DWI in clinical settings. PURPOSE: To investigate the consistency of quantitative metrics derived from DWI between different scanners in a multicenter clinical setting. MATERIAL AND METHODS: A total of 193 patients with cervical cancer from four scanners (MRI1, MRI2, MRI3, and MRI4) at three centers were included in this retrospective study. DWI data were processed using the mono-exponential and intravoxel incoherent motion (IVIM) model, yielding the following parameters: apparent diffusion coefficient (ADC); true diffusion coefficient (D); pseudo-diffusion coefficient (D*); perfusion fraction (f); and the product of f and D* (fD*). Various parameters of cervical cancer obtained from different scanners were compared. RESULTS: The parameters D and ADC derived from MRI1 and MRI2 were significantly different from those derived from MRI3 or MRI4 (P <0.01 for all comparisons). However, there was no significant difference in cervical cancer perfusion parameters (D* and fD*) between the different scanners (P >0.05). The P values of comparisons of all DWI parameters (D, D*, fD*, and ADC) between MRI3 and MRI4 (same vendor in different centers) for cervical cancer were all >0.05, except for f (P = 0.05). CONCLUSION: Scanners of the same model by the same vendor can yield close measurements of the ADC and IVIM parameters. The perfusion parameters showed higher consistency among the different scanners.

Biochemotaxis-Oriented Engineering Bacteria Expressing GLP-1 Enhance Diabetes Therapy by Regulating the Balance of Immune.

Glucagon like peptide-1 (GLP-1) is an effective hypoglycemic drug that can repair the pancreas ß cells and promote insulin secretion. However, GLP-1 has poor stability and lacks of target ability, which makes it difficult to reach the site of action to exert its efficacy. Here, GLP-1-expressing plasmids are introduced into the Escherichia coli Nissle 1917 (EcN) and a lipid membrane is formed through simple self-assembly on its surface, resulting in an oral delivery system (LEG) capable of resisting the harsh environment of the gastrointestinal tract. The system utilizes the chemotactic properties of probiotics to achieve efficient enrichment at the pancreatic site, and protects islet ß cells from destruction by regulating the balance of immune cells. More interestingly, LEG not only continuously produces GLP-1 to restore pancreatic islet ß cell function and secrete insulin to control blood sugar levels, but also regulates the intestinal flora and increases the richness and diversity of probiotics. In mice diabetes models, oral administration of LEG only once every other day has good biosafety and compliance, and achieves long-term control of blood glucose. Therefore, this strategy not only provides an oral delivery platform for pancreatic targeting, but also opens up new avenues for reversing diabetes.

Identifying two distinct neuroanatomical subtypes of first-episode depression using heterogeneity through discriminative analysis.

BACKGROUND: Neurobiological heterogeneity in depression remains largely unknown, leading to inconsistent neuroimaging findings. METHODS: Here, we adopted a novel proposed machine learning method ground on gray matter volumes (GMVs) to investigate neuroanatomical subtypes of first-episode treatment-naïve depression. GMVs were obtained from high-resolution T1-weighted images of 195 patients with first-episode, treatment-naïve depression and 78 matched healthy controls (HCs). Then we explored distinct subtypes of depression by employing heterogeneity through discriminative analysis (HYDRA) with regional GMVs as features. RESULTS: Two prominently divergent subtypes of first-episode depression were identified, exhibiting opposite structural alterations compared with HCs but no different demographic features. Subtype 1 presented widespread increased GMVs mainly located in frontal, parietal, temporal cortex and partially located in limbic system. Subtype 2 presented widespread decreased GMVs mainly located in thalamus, cerebellum, limbic system and partially located in frontal, parietal, temporal cortex. Subtype 2 had smaller TIV and longer illness duration than Subtype 1. And TIV in Subtype 1 was positively correlated with age of onset while not in Subtype 2, probably implying the different potential neuropathological mechanisms. LIMITATIONS: Despite results obtained in this study were validated by employing another brain atlas, the conclusions were acquired from a single dataset. CONCLUSIONS: This study revealed two distinguishing neuroanatomical subtypes of first-episode depression, which provides new insights into underlying biological mechanisms of the heterogeneity in depression and might be helpful for accurate clinical diagnosis and future treatment.

MRI Assessment of Intrinsic Neural Timescale and Gray Matter Volume in Parkinson's Disease.

BACKGROUND: Numerous studies have indicated altered temporal features of the brain function in Parkinson's disease (PD), and the autocorrelation magnitude of intrinsic neural signals, called intrinsic neural timescales, were often applied to estimate how long neural information stored in local brain areas. However, it is unclear whether PD patients at different disease stages exhibit abnormal timescales accompanied with abnormal gray matter volume (GMV). PURPOSE: To assess the intrinsic timescale and GMV in PD. STUDY TYPE: Prospective. POPULATION: 74 idiopathic PD patients (44 early stage (PD-ES) and 30 late stage (PD-LS), as determined by the Hoehn and Yahr (HY) severity classification scale), and 73 healthy controls (HC). FIELD STRENGTH/SEQUENCE: 3.0 T MRI scanner; magnetization prepared rapid acquisition gradient echo and echo planar imaging sequences. ASSESSMENT: The timescales were estimated by using the autocorrelation magnitude of neural signals. Voxel-based morphometry was performed to calculate GMV in the whole brain. Severity of motor symptoms and cognitive impairments were assessed using the unified PD rating scale, the HY scale, the Montreal cognitive assessment, and the mini-mental state examination. STATISTICAL TEST: Analysis of variance; two-sample t-test; Spearman rank correlation analysis; Mann-Whitney U test; Kruskal-Wallis' H test. A P value <0.05 was considered statistically significant. RESULTS: The PD group had significantly abnormal intrinsic timescales in the sensorimotor, visual, and cognitive-related areas, which correlated with the symptom severity (ρ = -0.265, P = 0.022) and GMV (ρ = 0.254, P = 0.029). Compared to the HC group, the PD-ES group had significantly longer timescales in anterior cortical regions, whereas the PD-LS group had significantly shorter timescales in posterior cortical regions. CONCLUSION: This study suggested that PD patients have abnormal timescales in multisystem and distinct patterns of timescales and GMV in cerebral cortex at different disease stages. This may provide new insights for the neural substrate of PD. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 1.

Positive Progesterone Receptor Expression in Meningioma May Increase the Transverse Relaxation: First Prospective Clinical Trial Using Single-Shot Ultrafast T2 Mapping.

RATIONALE AND OBJECTIVES: This project aims to investigate the diagnostic performance of multiple overlapping-echo detachment imaging (MOLED) technique-derived transverse relaxation time (T2) maps in predicting progesterone receptor (PR) and S100 expression in meningiomas. MATERIALS AND METHODS: 63 meningioma patients were enrolled from October 2021 to August 2022, who underwent a complete routine magnetic resonance imaging and T2 MOLED, which can characterize the whole brain transverse relaxation time within 32 seconds in a single scan. After the surgical resection of meningiomas, the expression levels of PR and S100 were determined by an experienced pathologist using immunohistochemistry techniques. Histogram analysis was performed in tumor parenchyma based on the parametric maps. Independent t test and Mann-Whitney U test were applied for the comparison of histogram parameters between different groups, with a significance level of P < .05. Logistic regression and receiver operating characteristic (ROC) analysis with 95% confidence interval were conducted for the diagnostic efficiency evaluation. RESULTS: PR-positive group had significantly elevated T2 histogram parameters (P = .001-.049) compared to the PR-negative group. The multivariate logistic regression model with T2 showed the highest area under the ROC curve (AUC) for predicting PR expression (AUC=0.818). Additionally, the multivariate model also had the best diagnostic performance for predicting meningioma S100 expression (AUC=0.768). CONCLUSION: The MOLED technique-derived T2 maps can distinguish PR and S100 status in meningiomas preoperatively.

Novel, pathogenic insertion variant of GSDME associates with autosomal dominant hearing loss in a large Chinese pedigree.

Nonsyndromic hearing loss (NSHL) is a genetically diverse, highly heterogeneous condition characterised by deafness, and Gasdermin E (GSDME) variants have been identified as directly inducing autosomal dominant NSHL. While many NSHL cases associated with GSDME involve the skipping of exon 8, there is another, less understood pathogenic insertion variant specifically found in Chinese pedigrees that causes deafness, known as autosomal dominant 5 (DFNA5) hearing loss. In this study, we recruited a large Chinese pedigree, conducted whole-exome and Sanger sequencing to serve as a comprehensive clinical examination, and extracted genomic DNA samples for co-segregation analysis of the members. Conservation and expression analyses for GSDME were also conducted. Our clinical examinations revealed an autosomal dominant phenotype of hearing loss in the family. Genetic analysis identified a novel insertion variant in GSDME exon 8 (GSDME: NM_004403.3: c.1113_1114insGGGGTGCAGCTTACAGGGTGGGTGT: p. P372fs*36). This variant is segregated with the deafness phenotype of this pedigree. The GSDME gene was highly conserved in the different species we analysed, and its mRNA expression was ubiquitously low in different human tissues. In conclusion, we have successfully identified a novel pathogenic insertion variant of GSDME in a Chinese pedigree that causes deafness, shedding light on the genetic basis of hearing loss within this specific family. Our findings expand the spectrum of known variants associated with GSDME-related deafness and may further support both the underlying gain-of-function mechanism and functional associations of GSDME hearing loss variants.

A facile strategy for the large-scale preparation of starch-based AIE luminescent nanoaggregates via host-guest interactions and their versatile applications.

Luminescent nanomaterials with outstanding optical properties have attracted growing interest due to their widespread applications. However, large-scale fabrication of luminescent nanomaterials with desired properties through a simple and economical process remains challenging. As a renewable natural resource, starch is non-toxic, easily accessible, and inexpensive, making it a popular choice for uses in various biomedical fields. In this work, we present a facile assembly strategy for the fabrication of starch-based luminescent nanoaggregates using starch as the host material and aggregation-induced emission luminogens (AIEgens) as guest molecules. By employing simple procedures under mild conditions, highly luminescent nanoparticles with small sizes, high water dispersibility, and low cytotoxicity are prepared on a large scale. The resulting nano-assemblies demonstrate significantly enhanced fluorescence intensities, reduced susceptibility to photobleaching and low cytotoxicity. These fluorescent supramolecular aggregates can be employed in various application fields, including the fabrication of fluorescent hydrogels, fingerprint detection, cell imaging and in vivo lymphatic system imaging. The methodology developed in this work has immense potential to greatly promote the production of high-quality nanoparticles on the industrial scale, offering a cost-effective solution that can meet the needs of various applications and pave the way for wider implementation of nanotechnology.