Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer’s disease

Alzheimer’s disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer’s Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD

Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer’s disease

Alzheimer’s disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer’s Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD

Crafting a Personalized Prognostic Model for Malignant Prostate Cancer Patients Using Risk Gene Signatures Discovered through TCGA-PRAD Mining, Machine Learning, and Single-Cell RNA-Sequencing

Background: Prostate cancer is a significant clinical issue, particularly for high Gleason score (GS) malignancy patients. Our study aimed to engineer and validate a risk model based on the profiles of high-GS PCa patients for early identification and the prediction of prognosis. Methods: We conducted differential gene expression analysis on patient samples from The Cancer Genome Atlas (TCGA) and enriched our understanding of gene functions. Using the least absolute selection and shrinkage operator (LASSO) regression, we established a risk model and validated it using an independent dataset from the International Cancer Genome Consortium (ICGC). Clinical variables were incorporated into a nomogram to predict overall survival (OS), and machine learning was used to explore the risk factor characteristics’ impact on PCa prognosis. Our prognostic model was confirmed using various databases, including single-cell RNA-sequencing datasets (scRNA-seq), the Cancer Cell Line Encyclopedia (CCLE), PCa cell lines, and tumor tissues. Results: We identified 83 differentially expressed genes (DEGs). Furthermore, WASIR1, KRTAP5-1, TLX1, KIF4A, and IQGAP3 were determined to be significant risk factors for OS and progression-free survival (PFS). Based on these five risk factors, we developed a risk model and nomogram for predicting OS and PFS, with a C-index of 0.823 (95% CI, 0.766–0.881) and a 10-year area under the curve (AUC) value of 0.788 (95% CI, 0.633–0.943). Additionally, the 3-year AUC was 0.759 when validating using ICGC. KRTAP5-1 and WASIR1 were found to be the most influential prognosis factors when using the optimized machine learning model. Finally, the established model was interrelated with immune cell infiltration, and the signals were found to be differentially expressed in PCa cells when using scRNA-seq datasets and tissues. Conclusions: We engineered an original and novel prognostic model based on five gene signatures through TCGA and machine learning, providing new insights into the risk of scarification and survival prediction for PCa patients in clinical practice

HLA-DR Helps to Differentiate Erythrodermic Cutaneous T-cell Lymphoma from Erythrodermic Inflammatory Dermatoses in Flow Cytometry

Differential diagnosis of erythroderma is challenging in dermatology, especially in differentiating erythrodermic cutaneous T-cell lymphoma from erythrodermic inflammatory dermatoses. This study retrospectively reviewed the peripheral blood flow cytometric results of 73 patients diagnosed with erythroderma at Peking University First Hospital from 2014 to 2019. The flow cytometry antibody panel included white blood cell markers, T-cell markers, B-cell markers, T-cell activation markers, and T helper cell differentiation markers. Features of the cell surface antigens were compared between 34 patients with erythrodermic cutaneous T-cell lymphoma and 39 patients with erythrodermic inflammatory dermatoses. The percentage of HLA-DR+/CD4+T cells was the most pronounced marker to distinguish erythrodermic cutaneous T-cell lymphoma from erythrodermic inflammatory dermatoses, with a threshold of 20.85% (sensitivity 96.77%, specificity 70.37%, p = 0.000, area under the curve (AUC) 0.882), suggesting its potential capability in the differential diagnosis of erythrodermic cutaneous T-cell lymphoma from erythrodermic inflammatory dermatoses. Moreover, in contrast to erythrodermic inflammatory dermatoses, the percentage of Th17 cells was significantly downregulated in erythrodermic cutaneous T-cell lymphoma (p = 0.001), demonstrating a dysregulated immune environment in erythrodermic cutaneous T-cell lymphoma

Experimental Study on Axial Impact Mitigating Stick-Slip Vibration with a PDC Bit

Stick-slip vibration reduces the drilling rate of penetration, causes early wear of bits, and threatens the safety of downhole tools. Therefore, it is necessary to study suppression methods of stick-slip vibration to achieve efficient and safe drilling. Field tests show that the use of downhole axial impactors is helpful to mitigate stick-slip vibration and improve rock-breaking efficiency. However, there are many deficiencies in the study of how axial impact load affects stick-slip vibration of a PDC bit. In this paper, based on the two-degrees-of-freedom spring-mass-damper model and similarity theory, a laboratory experiment device for suppressing stick-slip vibration of a PDC bit under axial impact load has been developed, and systematic experimental research has been carried out. The results show that the axial impact force can suppress the stick-slip vibration by reducing the amplitude of weight on bit and torque fluctuations and by increasing the main frequency of torque. The amplitude of impact force affects the choice of the optimal back-rake angle. The impact frequency is negatively correlated with the fluctuation amplitude of the rotary speed. When the impact frequency is greater than 100 Hz, the fluctuation amplitude of the rotary speed will not decrease

Tau burden is associated with cross-sectional and longitudinal neurodegeneration in the medial temporal lobe in cognitively normal individuals

Background: Neurofibrillary tangle pathology is thought to drive neurodegeneration in beta-amyloid positive (A+) cognitively normal (CN) individuals, i.e., preclinical Alzheimer’s disease (AD).However, in beta-amyloid negative (A-) CN, the contribution of tau pathology [primary age-related tauopathy (PART)] to neurodegeneration remains uncertain. We investigate the correlation between tau burden measured by PET in the medial temporal lobe (MTL) and MRI-derived cross-sectional and longitudinal structural atrophy in these cohorts. Methods: 420 CN (A-/A+: 294/101, Table 1) individuals from ADNI with AV1451 PET and T1-weighted MRI acquired within one year were included. Bilateral anterior/posterior hippocampal volume and thickness of entorhinal cortex (ERC), Brodmann areas 35/36 (BA35/BA36) and parahipocampal cortex (PHC) were obtained from baseline MRI scans. Bilateral MTL tau burden was computed as AV1451 uptake across ERC and BA35. Beta-amyloid status was determined with PET by standard cut-offs (Florbetapir: 1.11; Florbetaben: 1.08). In a subset of participants with prospective longitudinal MRI scans (up to 4.5 years), annualized volume change rate of each MTL subregion was estimated. Intracranial volume and MRI follow-up time were additional covariates for cross-sectional and longitudinal analysis respectively. We performed the analysis separately for each hemisphere in the whole CN cohort and its A+ and A- subgroups. Results: Tau burden was significantly associated with cross-sectional left BA35/36 thickness in the whole cohort and bilateral volume in both A+ CN and the whole cohort (Table 2, Figure 1), but not in in A- CN. Stronger correlations between MTL tau burden and longitudinal atrophy, despite smaller sample size, was observed in almost all the MTL subregions regardless of amyloid status (Table 3, Figure 1). In general, effects from the left hemisphere were stronger than those from the right hemisphere. All significant correlations were maintained when corrected for beta-amyloid PET SUVR. Conclusions: The results demonstrated that elevated tau predicts subsequent neurodegeneration in early Braak regions in CN subjects regardless of amyloid status. This indicates that PART may be an important driver of neurodegeneration already during normal ageing in cognitively normal individuals

Medial Temporal Lobe Networks in Alzheimer's Disease : Structural and Molecular Vulnerabilities

The medial temporal lobe (MTL) is connected to the rest of the brain through two main networks: the anterior-temporal (AT) and the posterior-medial (PM) systems. Given the crucial role of the MTL and networks in the physiopathology of Alzheimer's disease (AD), the present study aimed at (1) investigating whether MTL atrophy propagates specifically within the AT and PM networks, and (2) evaluating the vulnerability of these networks to AD proteinopathies. To do that, we used neuroimaging data acquired in human male and female in three distinct cohorts: (1) resting-state functional MRI (rs-fMRI) from the aging brain cohort (ABC) to define the AT and PM networks (n = 68); (2) longitudinal structural MRI from Alzheimer's disease neuroimaging initiative (ADNI)GO/2 to highlight structural covariance patterns (n = 349); and (3) positron emission tomography (PET) data from ADNI3 to evaluate the networks' vulnerability to amyloid and tau (n = 186). Our results suggest that the atrophy of distinct MTL subregions propagates within the AT and PM networks in a dissociable manner. Brodmann area (BA)35 structurally covaried within the AT network while the parahippocampal cortex (PHC) covaried within the PM network. In addition, these networks are differentially associated with relative tau and amyloid burden, with higher tau levels in AT than in PM and higher amyloid levels in PM than in AT. Our results also suggest differences in the relative burden of tau species. The current results provide further support for the notion that two distinct MTL networks display differential alterations in the context of AD. These findings have important implications for disease spread and the cognitive manifestations of AD.SIGNIFICANCE STATEMENT The current study provides further support for the notion that two distinct medial temporal lobe (MTL) networks, i.e., anterior-temporal (AT) and the posterior-medial (PM), display differential alterations in the context of Alzheimer's disease (AD). Importantly, neurodegeneration appears to occur within these networks in a dissociable manner marked by their covariance patterns. In addition, the AT and PM networks are also differentially associated with relative tau and amyloid burden, and perhaps differences in the relative burden of tau species [e.g., neurofibriliary tangles (NFTs) vs tau in neuritic plaques]. These findings, in the context of a growing literature consistent with the present results, have important implications for disease spread and the cognitive manifestations of AD in light of the differential cognitive processes ascribed to them

Defective Differentiation of Adipose Precursor Cells from Lipodystrophic Mice Lacking Perilipin 1

<div><p>Perilipin 1 (Plin1) localizes at the surface of lipid droplets to regulate triglyceride storage and hydrolysis in adipocytes. Plin1 defect leads to low adiposity in mice and partial lipodystrophy in human. This study investigated the roles of Plin1 in adipocyte differentiation. Plin1 null (-/-) mice showed plenty of multilocular adipocytes and small unilocular adipocytes in adipose tissue, along with lack of a subpopulation of adipose progenitor cells capable of in vivo adipogenesis and along with downregulation of adipogenic pathway. Before initiation of differentiation, adipose stromal-vascular cells (SVCs) from Plin1-/- mice already accumulated numerous tiny lipid droplets, which increased in number and size during the first 12-h induction but thereafter became disappeared at day 1 of differentiation. The adipogenic signaling was dysregulated despite protein level of PPARγ was near normal in Plin1-/- SVCs like in Plin1-/- adipose tissue. Heterozygous Plin1+/- SVCs were able to develop lipid droplets, with both the number and size more than in Plin1-/- SVCs but less than in Plin1+/+ SVCs, indicating that Plin1 haploinsufficiency accounts for attenuated adipogenesis. Aberrant lipid droplet growth and differentiation of Plin1-/- SVCs were rescued by adenoviral Plin1 expression and were ameliorated by enhanced or prolonged adipogenic stimulation. Our finding suggests that Plin1 plays an important role in adipocyte differentiation and provides an insight into the pathology of partial lipodystrophy in patients with Plin1 mutation.</p></div

Co-expression of fibroblast growth factor receptor 3 with mutant p53, and its association with worse outcome in oropharyngeal squamous cell carcinoma.

Fibroblast growth factor receptor 3 (FGFR3) is expressed in squamous cell carcinoma of the head and neck (SCCHN) including oropharyngeal squamous cell carcinoma (OPSCC) and is a potential therapeutic target. However, information on its correlation with other relevant cancer related proteins stratified by p16 status and its prognostic significance in OPSCC is limited. We examined FGFR3 expression and its correlation with clinical characteristics, p16 status, and mutant p53 (mp53) among 220 retrospectively collected OPSCC cases and 40 prospectively collected SCCHN cases, including a majority of OPSCC. Correlations of FGFR3 Weighted Index (WI) with p16 status and mp53 WI as well as its association with disease-free survival (DFS) and overall survival (OS) were evaluated. FGFR3 expression was detected in 61% and 70% of cases in cohorts 1 and 2, respectively. FGFR3 level was significantly higher in p16-negative tumors in both cohorts (p<0.001 and 0.006). FGFR3 expression was highly correlated with mp53 expression in both p16 + and p16- OPSCC (p<0.0001 and p = 0.0006, respectively). In cohort 1, univariate analysis showed that FGFR3 was associated with DFS but not OS. Kaplan-Meier analysis showed that higher FGFR3 and mp53 level correlated with worse DFS (p = 0.025) and OS (p = 0.009). As expected, p16 positive status was associated with improved OS and DFS (p<0.001 for both). Our results suggest that high FGFR3 expression is associated with p16 negative status and mp53 expression in OPSCC and correlates with a worse clinical outcome. The biological relationship between FGFR3 and mp53 in OPSCC deserves further investigation

Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer's disease.

Alzheimer's disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer's Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD