Identification of Causal Relationship between Amyloid-beta Accumulation and Alzheimer's Disease Progression via Counterfactual Inference

Alzheimer's disease (AD) is a neurodegenerative disorder that is beginning with amyloidosis, followed by neuronal loss and deterioration in structure, function, and cognition. The accumulation of amyloid-beta in the brain, measured through 18F-florbetapir (AV45) positron emission tomography (PET) imaging, has been widely used for early diagnosis of AD. However, the relationship between amyloid-beta accumulation and AD pathophysiology remains unclear, and causal inference approaches are needed to uncover how amyloid-beta levels can impact AD development. In this paper, we propose a graph varying coefficient neural network (GVCNet) for estimating the individual treatment effect with continuous treatment levels using a graph convolutional neural network. We highlight the potential of causal inference approaches, including GVCNet, for measuring the regional causal connections between amyloid-beta accumulation and AD pathophysiology, which may serve as a robust tool for early diagnosis and tailored care

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

The association between erector spinae muscle content and chronic heart failure and its severity

Abstract Aims Previous studies have shown a significant reduction in skeletal muscle content in patients with chronic heart failure (CHF). The present study focused on the erector spinae muscle (ESM) to determine whether ESM content is associated with the development and severity of CHF. Methods and results A total of 652 patients were included in this trial for the study. According to the diagnostic criteria of CHF, 652 patients were divided into two groups, namely, the control group (268 patients) and the CHF group (384 patients). Meanwhile, to assess whether the ESM is associated with the severity of CHF, patients in the CHF group were divided into two groups according to left ventricular ejection fraction (LVEF) values: heart failure with preserved ejection fraction (HFpEF, LVEF ≥50%, 256 patients) and heart failure with reduced ejection fraction (HFrEF, LVEF ≤40%, 68 patients). Receiver operating curve analysis was performed to assess whether ESM content could predict CHF and determine its severity. Compared with the control group, the patients in the CHF group were older, the prevalence of coronary heart disease (CHD) and atrial fibrillation was higher, the colour ultrasound results showed that LVEF decreased significantly, and the left ventricular end‐diastolic internal diameter and left ventricular end‐systolic internal diameter increased significantly. Besides, patients in the CHF group had significantly lower ESM content, and ESM is an independent predictor of heart failure, with an odds ratio of 0.713 (CHF group vs. control group, 95% confidence interval 0.626–0.811, P < 0.001). Compared with the HFpEF group, the HFrEF group has a lower prevalence of CHD, LVEF decreased significantly, the left ventricular end‐diastolic internal diameter and left ventricular end‐systolic internal diameter increased significantly, also patients in the HFrEF group had significantly lower ESM content compared with patients in the HFpEF group, and ESM is an independent predictor of the severity of heart failure, with an odds ratio of 0.514 (HFrEF group vs. HFpEF group, 95% confidence interval (0.418–0.633, P < 0.05). The results of receiver operating curve analysis showed that the sensitivity and specificity of ESM content for the diagnosis of CHF were 65.6% and 71.6%, respectively, while the sensitivity and specificity of ESM content for predicting the severity of CHF were 47.1% and 89.1%, respectively. Conclusions The ESM is of great value in predicting the onset and severity of CHF

Identification of immune cell infiltration and effective biomarkers of polycystic ovary syndrome by bioinformatics analysis

Abstract Background Patients with polycystic ovary syndrome (PCOS) exhibit a chronic inflammatory state, which is often accompanied by immune, endocrine, and metabolic disorders. Clarification of the pathogenesis of PCOS and exploration of specific biomarkers from the perspective of immunology by evaluating the local infiltration of immune cells in the follicular microenvironment may provide critical insights into disease pathogenesis. Methods In this study, we evaluated immune cell subsets and gene expression in patients with PCOS using data from the Gene Expression Omnibus database and single-sample gene set enrichment analysis. Results In total, 325 differentially expressed genes were identified, among which TMEM54 and PLCG2 (area under the curve = 0.922) were identified as PCOS biomarkers. Immune cell infiltration analysis showed that central memory CD4+ T cells, central memory CD8+ T cells, effector memory CD4+ T cells, γδ T cells, and type 17 T helper cells may affect the occurrence of PCOS. In addition, PLCG2 was highly correlated with γδ T cells and central memory CD4+ T cells. Conclusions Overall, TMEM54 and PLCG2 were identified as potential PCOS biomarkers by bioinformatics analysis. These findings established a basis for further exploration of the immunological mechanisms of PCOS and the identification of therapeutic targets

A high-throughput dual system to screen polyphosphate kinase mutants for efficient ATP regeneration in L-theanine biocatalysis

Abstract ATP, an important cofactor, is involved in many biocatalytic reactions that require energy. Polyphosphate kinases (PPK) can provide energy for ATP-consuming reactions due to their cheap and readily available substrate polyphosphate. We determined the catalytic properties of PPK from different sources and found that PPK from Cytophaga hutchinsonii (ChPPK) had the best catalytic activity for the substrates ADP and polyP6. An extracellular–intracellular dual system was constructed to high-throughput screen for better catalytic activity of ChPPK mutants. Finally, the specific activity of ChPPKD82N-K103E mutant was increased by 4.3 times. Therefore, we focused on the production of L-theanine catalyzed by GMAS as a model of ATP regeneration. Supplying 150 mM ATP, GMAS enzyme could produce 16.8 ± 1.3 g/L L-theanine from 100 mM glutamate. When 5 mM ATP and 5 U/mL ChPPKD82N-K103E were added, the yield of L-theanine was 16.6 ± 0.79 g/L with the conversion rate of 95.6 ± 4.5% at 4 h. Subsequently, this system was scaled up to 200 mM and 400 mM glutamate, resulting in the yields of L-theanine for 32.3 ± 1.6 g/L and 62.7 ± 1.1 g/L, with the conversion rate of 92.8 ± 4.6% and 90.1 ± 1.6%, respectively. In addition, we also constructed an efficient ATP regeneration system from glutamate to glutamine, and 13.8 ± 0.2 g/L glutamine was obtained with the conversion rate of 94.4 ± 1.4% in 4 h after adding 6 U/ mL GS enzyme and 5 U/ mL ChPPKD82N-K103E, which further laid the foundation from glutamine to L-theanine catalyzed by GGT enzyme. This proved that giving the reaction an efficient ATP supply driven by the mutant enzyme enhanced the conversion rate of substrate to product and maximized the substrate value. This is a positively combination of high yield, high conversion rate and high economic value of enzyme catalysis. The mutant enzyme will further power the ATP-consuming biocatalytic reaction platform sustainably