Measurement and prediction of the detachment of Aspergillus niger spores in turbulent flows.

Aspergillus niger (A. niger) spores can induce numerous health problems. Once the airflow-imposed drag force on an A. niger spore exceeds its binding force with the colony, the spore is detached. Turbulent flow may considerably increase the spore detachment. No method is currently available for prediction of the drag force on a spore and its detachment in turbulent flows. This investigation measured the turbulent velocities and detachment of A. niger colonies in a wind tunnel. Computational fluid dynamics (CFD) was employed to model an A. niger unit subjected to turbulent flow blowing. The top 1 % quantile instantaneous velocity of the turbulent flow was specified as the steady entry flow boundary condition for solving the peak velocity distribution and the peak drag forces onto spores. The predicted spore detachment ratios were compared with the measurement data for model validation. The results revealed that the spore detachment ratios with a turbulence intensity of 17 % to 20 % can be twice to triple the ratio with a turbulence intensity of approximately 1 %, when the average velocity for blowing remains the same. The proposed CFD model can accurately predict the detachment ratios of the A. niger spores. ENVIRONMENTAL IMPLICATION: Some people are sensitive to the Aspergillus niger (A. niger) spores, and excessive exposure can cause nasal congestion, skin tingling, coughing, and even asthma. Turbulent flow can considerably increase the spore detachment, due to the increased airflow-imposed drag force on the spores during turbulence. This investigation developed a numerical model to solve for the peak velocity distribution and the peak drag forces onto spores in turbulent flows to predict the spore detachment. With the numerical tool, the airborne fungal spore concentrations would be predictable, which paves a way for intelligent and precise control of fungal aerosol pollution.

Identification of immunogenic cell death-related genes involved in Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia worldwide, with recent studies highlighting the potential role of immunogenic cell death (ICD) in the pathogenesis of this neurodegenerative disorder. A total of 52 healthy controls and 64 patients with AD were included. Compared to the controls, the patients with AD exhibited 2392 differentially expressed genes (DEGs), of which 1015 and 1377 were upregulated and downregulated genes, respectively. Among them, nine common genes were identified by intersecting the AD-related module genes with the DEGs and ICD-associated genes. Gene ontology (GO)analysis further revealed "positive regulation of cytokine production" as the most significant term. Moreover, the enriched molecular functions were primarily related to the inflammatory body complex, while the overlapping genes were significantly enriched in lipopolysaccharide binding. Kyoto encyclopedia of genes and genomes (KEGG) analysis also indicated that these overlapping genes were mainly enriched in immunity, inflammation, and lipid metabolism pathways. Furthermore, the following four hub genes were detected using machine learning algorithms: P2RX7, HSP90AA1, NT5E, and NLRP3. These genes demonstrated significant differences in expression between the AD and healthy control groups (P < 0.05). Additionally, the area under the curve values of these four genes were all > 0.7, indicating their potential diagnostic value for AD. We further validated the protein levels of these four genes in the hippocampus of 3xTg-AD and C57BL/6J mice, showing P2RX7 and HSP90AA1 expression levels consistent with the previously analyzed trends. Finally, the single-sample gene set enrichment analysis (ssGSEA) algorithm provided additional evidence by demonstrating the crucial role of immune cell infiltration and its link with the hub genes in AD progression. Our study results suggest that ICD-mediated elevation of HSP90AA1 and P2RX7 levels and the resulting induction of tau hyperphosphorylation and neuroinflammation are vital in the AD pathogenic mechanism.

Measurement and prediction of the Aspergillus niger spore detachment from a vesicle unit subjected to air-blowing.

Detachment of fungal spores from growing colonies results in human exposure. Thus far, the distribution of the binding forces of the spores in a fungal unit is unknown, so that precise prediction of the spores detachment is quite challenging. This investigation used centrifugal separation to measure the binding forces of the spores. Aspergillus niger (A. niger) colonies on a culture plate were placed in a centrifuge, the detached spores were counted, and this number was used to obtain the distribution of binding forces. Next, the air-blowing of an A. niger unit was modeled by computational fluid dynamics (CFD). A spore was judged to be detached if the air-imposed drag force was greater than the binding force. For model validation, the predicted spore detachment ratios were compared with the ratios measured in a wind tunnel test. The results revealed that the binding forces of the spores obeyed the log-normal distribution. The binding forces of the distal spores from colonies with a growth age of 66 h ranged from 0 nN to 4.0 nN and had a mean of 0.65 nN. The CFD modeling predicted the detachment ratios of the distal spores with good accuracy.

Circadian cycle and neuroinflammation.

Circadian cycle is a fundamental characteristic of life formed in the long-term evolution of organisms and plays an important role in maintaining the proliferation, migration, and activation of immune cells. Studies have shown that circadian rhythm disorders affect the occurrence and development of neuroinflammation by inducing glial cell activation and peripheral immune responses. In this article, we briefly described the research progress of neuroinflammation and circadian rhythm in recent years and explored the effects and possible mechanism of circadian rhythmicity on microglia, astrocytes, and peripheral immune function.

A 2.66 µW Clinician-Like Cardiac Arrhythmia Watchdog Based on P-QRS-T for Wearable Applications.

A wearable electrocardiogram (ECG) device is an effective tool for managing cardiovascular diseases. This paper presents a low power clinician-like cardiac arrhythmia watchdog (CAW) for wearable ECG devices. The CAW is based on a novel P-QRS-T detection algorithm that makes use of clinical features to identify abnormalities. Implemented in 0.18 µm CMOS process, the CAW consumes 2.66 µW for 80 bpm heart rate at 1.2 V supply with an area of 0.578 mm2. Verified on QT database, the average sensitivity/positive predictivity for P-wave, QRS complex and T-wave are over 93.39%/88.55%, 99.69%/99.48%, and 97.13%/93.18% respectively, across over 190000 beats. It shows over 99.8% arrhythmia detection accuracy for 43 subjects evaluated on MIT-BIH database.