Westergaardborregaard1669
After literature review, a total of 58 FPLD3 patients were identified and we found no difference in clinical features between the DBD group and LBD group (all P > 0.05).
A Chinese FPLD3 patient with a novel
gene mutation is described. Our case emphasized the importance of physical examination and genetic testing in young patients with severe metabolic syndromes.
A Chinese FPLD3 patient with a novel PPARG gene mutation is described. Our case emphasized the importance of physical examination and genetic testing in young patients with severe metabolic syndromes.Adipose tissue is essential for energy storage and endocrine regulation of metabolism. Imbalance in energy intake and expenditure result in obesity causing adipose tissue dysfunction. This alters cellular composition of the stromal cell populations and their function. Moreover, the individual cellular composition of each adipose tissue depot, regulated by environmental factors and genetics, determines the ability of the depots to expand and maintain its endocrine and storage function. Thus, stromal cells modulate adipocyte function and vice versa. In this mini-review we discuss heterogeneity in terms of composition and fate of adipose progenitor subtypes and their interactions with and regulation by different immune cell populations. Immune cells are the most diverse cell populations in adipose tissue and play essential roles in regulating adipose tissue function via interaction with adipocytes but also with adipocyte progenitors. We specifically discuss the role of macrophages, mast cells, innate lymphoid cells and T cells in the regulation of adipocyte progenitor proliferation, differentiation and lineage commitment. Understanding the factors and cellular interactions regulating preadipocyte expansion and fate decision will allow the identification of novel mechanisms and therapeutic strategies to promote healthy adipose tissue expansion without systemic metabolic impairment.Diabetic retinopathy (DR) is an important complication with a high incidence of 34.6% in the diabetic populations. DR could finally lead to vision impairment without effective interventions, during which, diabetic macular edema (DME) is a key phase causing visual loss. Up to date, antivascular endothelial growth factor (anti-VEGF) therapy is the first-line treatment for DME which has achieved relatively better clinical outcomes than traditional treatments. However, there are several kinds of anti-VEGF medicines, and patients are sensitive to different anti-VEGF treatments. In addition, its effectiveness is unstable. Considering the patients' need to accept continual anti-VEGF treatments and its price is comparatively high, it is clinically important to predict the prognosis after different anti-VEGF treatments. In our research, we used the demographic and clinical data of 254 DME patients and 2,763 optical coherence tomography (OCT) images from three countries to predict the fundus structural and functional parameters and treatment plan in 6 months after different anti-VEGF treatments. Eight baseline features combined with 11 models were applied to conduct seven prediction tasks. Accuracy (ACC), the area under curve (AUC), mean absolute error (MAE), and mean square error (MSE) were respectively used to evaluate the classification and regression tasks. The ACC and AUC of structural predictions of retinal pigment epithelial detachment were close to 1.000. The MAE and MSE of visual acuity predictions were nearly 0.3 to 0.4 logMAR. The ACC of treatment plan regarding continuous injection was approaching 70%. Our research has achieved great performance in the predictions of fundus structural and functional parameters as well as treatment plan, which can help ophthalmologists improve the treatment compliance of DME patients.Obesity is associated with systemic inflammation and immune cell recruitment to metabolic tissues. Sex differences have been observed where male mice challenged with high fat diet (HFD) exhibit greater adipose tissue inflammation than females demonstrating a role for sex hormones in differential inflammatory responses. Circulating monocytes that respond to dietary lipids and chemokines and produce cytokines are the primary source of recruited adipose tissue macrophages (ATMs). In this study, we investigated sexual dimorphism in biological pathways in HFD-fed ATMs from male and female mice by RNA-seq. We also conducted chemotaxis assays to investigate sex differences in the migration of monocytes isolated from bone marrow from male and female mice toward a dietary saturated lipid - palmitate (PA), and a chemokine - monocyte chemoattractant protein 1 (MCP1), factors known to stimulate myeloid cells in obesity. ATM RNA-Seq demonstrated sex differences of both metabolic and inflammatory activation, including pathways for chemokine signaling and leukocyte trans-endothelial migration. In vivo monocyte transfer studies demonstrated that male monocytes traffic to female adipose tissue to generate ATMs more readily. In chemotaxis assays, lean male monocytes migrated in greater numbers than females toward PA and MCP1. With short-term HFD, male and female monocytes migrated similarly, but in chronic HFD, male monocytes showed greater migration than females upon PA and MCP1 stimulation. Studies with monocytes from toll-like receptor 4 knockout mice (Tlr4-/- ) demonstrated that both males and females showed decreased migration than WT in response to PA and MCP1 implying a role for TLR4 in monocyte influx in response to meta-inflammation. Overall, these data demonstrate the role of sexual dimorphism in monocyte recruitment and response to metabolic stimuli that may influence meta-inflammation in obesity.
Lung cancer has been a prominent research focus in recent years due to its role in cancer-related fatalities globally, with lung adenocarcinoma (LUAD) being the most prevalent histological form. Nonetheless, no signature of lactate metabolism-related long non-coding RNAs (LMR-lncRNAs) has been developed for patients with LUAD. Accordingly, we aimed to develop a unique LMR-lncRNA signature to determine the prognosis of patients with LUAD.
The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to derive the lncRNA expression patterns. Selleck 1-Naphthyl PP1 Identification of LMR-lncRNAs was accomplished by analyzing the co-expression patterns between lncRNAs and LMR genes. Subsequently, the association between lncRNA levels and survival outcomes was determined to develop an effective signature. In the TCGA cohort, Cox regression was enlisted to build an innovative signature consisting of three LMR-lncRNAs, which was validated in the GEO validation cohort. GSEA and immune infiltration analysis werrified a new LMR-lncRNA signature useful for anticipating the survival of patients with LUAD. This signature could give potentially critical insight for immunotherapy interventions in patients with LUAD.
We developed and verified a new LMR-lncRNA signature useful for anticipating the survival of patients with LUAD. This signature could give potentially critical insight for immunotherapy interventions in patients with LUAD.The etiology of Parkinson's disease (PD) is unknown, but evidence is increasing that there is a prominent inflammatory component to the illness. Epidemiological, genetic, and preclinical evidence support a role for gut-derived sterile inflammation. Pro-inflammatory bacteria are over-represented in the PD gut microbiota. There is evidence for decreased gut barrier function and leak of bacterial antigen across the gut epithelium with sub-mucosal inflammation and systemic exposure to the bacterial endotoxin lipopolysaccharide. Preclinical evidence supports these clinical findings and suggests that systemic inflammation can affect the CNS through vagal pathways or the systemic circulation. We will review recent preclinical and clinical evidence to support this mechanism and suggest possible treatments directed at the gut-brain axis.There is an urgent need for more informative quantitative techniques that non-invasively and objectively assess strategies for epilepsy surgery. Invasive intracranial electroencephalography (iEEG) remains the clinical gold standard to investigate the nature of the epileptogenic zone (EZ) before surgical resection. However, there are major limitations of iEEG, such as the limited spatial sampling and the degree of subjectivity inherent in the analysis and clinical interpretation of iEEG data. Recent advances in network analysis and dynamical network modeling provide a novel aspect toward a more objective assessment of the EZ. The advantage of such approaches is that they are data-driven and require less or no human input. Multiple studies have demonstrated success using these approaches when applied to iEEG data in characterizing the EZ and predicting surgical outcomes. However, the limitations of iEEG recordings equally apply to these studies-limited spatial sampling and the implicit assumption that iEEG electrodes, whether strip, grid, depth or stereo EEG (sEEG) arrays, are placed in the correct location. Therefore, it is of interest to clinicians and scientists to see whether the same analysis and modeling techniques can be applied to whole-brain, non-invasive neuroimaging data (from MRI-based techniques) and neurophysiological data (from MEG and scalp EEG recordings), thus removing the limitation of spatial sampling, while safely and objectively characterizing the EZ. This review aims to summarize current state of the art non-invasive methods that inform epilepsy surgery using network analysis and dynamical network models. We also present perspectives on future directions and clinical applications of these promising approaches.
Parental migration has been associated with a higher risk of cognitive and behavioral abnormalities in left-behind children (LBC). This study aimed to explore the spontaneous brain activity in LBC and reveal the mechanisms underlying behavioral and cognitive abnormalities.
Involved LBC (
= 36) and non-LBC (
= 22) underwent resting-state functional MRI (fMRI) examination and cognitive and behavioral assessment. The fMRI-based amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) were assessed to analyze the spontaneous brain activity pattern. The relationships among abnormal spontaneous brain activity, behavioral and cognitive deficits and altered family environment were assessed by partial correlation analysis.
Compared with non-LBC, LBC exhibited increased amplitude of low-frequency fluctuations in the right lingual gyrus (LING), while a decreased ALFF was observed in the bilateral insula and right orbital part of the middle frontal gyrus (ORBmid) (two-tailed voxel-level
<rovided empirical evidence that the lack of direct parental care during early childhood could affect brain function development involving cognition, behavior, and emotion. Our findings emphasized that intellectual and emotional cares are essential for LBC.Seizures are reported to be important factors contributing to poor prognosis in patients with cerebral venous sinus thrombosis (CVST). However, the predictive factors for concurrent early onset seizures in patients with CVST remain unclear. To identify the predictive factors of early seizures in patients with CVST, this study retrospectively evaluated the clinical data of patients diagnosed with CVST at two centers from January 2011 to December 2020 and analyzed the relationship between admission characteristics and early onset seizures. A total of 112 CVST patients (63 men and 49 women; mean age 39.82 ± 15.70 years) were enrolled in this study, of whom 34 (30.36%) had seizures. For patients with seizures, cerebral hemorrhage, cortical vein thrombosis, anterior superior sagittal sinus (SSS) thrombosis, middle SSS thrombosis, CVST score, modified Rankin Scale, National Institute of Health Stroke Scale (NIHSS) score, neutrophil percentage, and D-dimer level were more severe than those without seizures. Logistic regression analysis showed that cerebral hemorrhage (P = 0.