Transcriptional Dysregulation Study Reveals a Core Network Involving the Progression of Alzheimer's Disease

Background: The pathogenesis of Alzheimer's disease is associated with dysregulation at different levels from transcriptome to cellular functioning. Such complexity necessitates investigations of disease etiology to be carried out considering multiple aspects of the disease and the use of independent strategies. The established works more emphasized on the structural organization of gene regulatory network while neglecting the internal regulation changes.Methods: Applying a strategy different from popularly used co-expression network analysis, this study investigated the transcriptional dysregulations during the transition from normal to disease states.Results: Ninety- seven genes were predicted as dysregulated genes, which were also associated with clinical outcomes of Alzheimer's disease. Both the co-expression and differential co-expression analysis suggested these genes to be interconnected as a core network and that their regulations were strengthened during the transition to disease states. Functional studies suggested the dysregulated genes to be associated with aging and synaptic function. Further, we checked the conservation of the gene co-expression and found that human and mouse brain might have divergent transcriptional co-regulation even when they had conserved gene expression profiles.Conclusion: Overall, our study reveals a core network of transcriptional dysregulation associated with the progression of Alzheimer's disease by affecting the aging and synaptic functions related genes; the gene regulation is not conserved in the human and mouse brains

Evolution of the vertebrate Y RNA cluster

Relatively little is known about the evolutionary histories of most classes of non-protein coding RNAs. Here we consider Y RNAs, a relatively rarely studied group of related pol-III transcripts. A single cluster of functional genes is preserved throughout tetrapod evolution, which however exhibits clade-specific tandem duplications, gene-losses, and rearrangements

Increasing Area and Decreasing Depth: Climate Change Influence on Snow Variations in the Qilian Mountains

The Qilian Mountains serve as a critical water source for the Yellow River and various inland rivers, playing a pivotal role in regulating the regional climate. Given their significance as one of the foremost water resources in the area, the spatial and temporal dynamics of the snow are crucial for understanding potential impacts on regional hydrology and ecology. This study examines the characteristics of spatial and temporal variations in snow-covered extent (SCE), snow depth (SD), snow-covered days (SCD), snow onset date (SOD), and snow end date (SED) within the Qilian Mountains region. We investigate the hydrological and ecological implications utilizing snow area and phenology data, alongside SD data. The findings indicate that: (1) the distribution of snow across the Qilian Mountains mainly splits between the central and western areas, with the central region showing deeper snow than both the eastern and western parts; (2) the area covered by snow in the Qilian Mountains is growing, but the depth of the snow is on a decline, especially in the central area; (3) in terms of snow phenology, most of the region is witnessing an earlier start of SOD, a longer SCD, and an earlier SED. An overall increase in precipitation is identified as the key factor behind the expanded SCE in the Qilian Mountains, while rising temperatures are pinpointed as the primary cause for the reduction in SD. As global climate change intensifies, the observed alterations in the snow of the Qilian Mountains present emerging challenges for regional water security and ecological equilibrium

Comparisons between simulated and in-situ measured speech intelligibility based on (binaural) room impulse responses

This study systematically compares acoustic simulation and in-situ measurement in terms of speech transmission index (STI), speech intelligibility scores and relationship curves when considering (binaural) room impulse response and four general room conditions, namely, an office, a laboratory, a multimedia lecture hall and a semi-anechoic chamber. The results reveal that STI can be predicted accurately by acoustic simulation (using room acoustics software ODEON) when there is a good agreement between the virtual models and the real rooms and that different reverberation time (RT) and signal-to-noise ratio (SNR) may exert less significant influence on the simulated STI. However, subjective intelligibility may be overestimated when using acoustic simulation due to the head-related transfer function (HRTF) filter used, and the score bias may be minimal and difficult to detect in everyday situations. There is no obvious score tendency caused by different RT, though with the decrease in the SNR, score bias may increase. Overall, considering that the accurate acoustic modelling of rooms is often problematic, it is difficult to obtain accurate speech intelligibility prediction results using a simulation technique, especially when the room has not yet been built

Distinguishing Emission-Associated Ambient Air PM2.5 Concentrations and Meteorological Factor-Induced Fluctuations

Although PM2.5 (particulate matter with aerodynamic diameters less than 2.5 μm) in the air originates from emissions, its concentrations are often affected by confounding meteorological effects. Therefore, direct comparisons of PM2.5 concentrations made across two periods, which are commonly used by environmental protection administrations to measure the effectiveness of mitigation efforts, can be misleading. Here, we developed a two-step method to distinguish the significance of emissions and meteorological factors and assess the effectiveness of emission mitigation efforts. We modeled ambient PM2.5 concentrations from 1980 to 2014 based on three conditional scenarios: realistic conditions, fixed emissions, and fixed meteorology. The differences found between the model outputs were analyzed to quantify the relative contributions of emissions and meteorological factors. Emission-related gridded PM2.5 concentrations excluding the meteorological effects were predicted using multivariate regression models, whereas meteorological confounding effects on PM2.5 fluctuations were characterized by probabilistic functions. When the regression models and probabilistic functions were combined, fluctuations in the PM2.5 concentrations induced by emissions and meteorological factors were quantified for all model grid cells and regions. The method was then applied to assess the historical and future trends of PM2.5 concentrations and potential fluctuations on global, national, and city scales. The proposed method may thus be used to assess the effectiveness of mitigation actions

Impacts of air pollutants from rural Chinese households under the rapid residential energy transition

Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM2.5, avoiding 130,000 (90,000-160,000) premature deaths associated with PM2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m2 in 1992 to 0.031 ± 0.008 W/m2 in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 μg/m3 to population-weighted PM2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent

Cytochalasin E, a potential agent for anti-glioma therapy, efficiently induces U87 human glioblastoma cell death

Glioblastoma is one of the most malignant brain tumors. Current treatments for glioblastoma usually make poor responses, and novel treatment strategies are extremely imperative. Cytochalasin E was reported to inhibit angiogenesis and tumor growth in some studies, but its effects on gliomas are still unknown. In this study, we found cytochalasin E inhibits U87 human glioblastoma cell growth in a very low concentration range of 10-8 to 10-6 M in a time and concentration dependent manner, and the IC50 were 1.17 ± 0.32 × 10-7 M for 48 h treatment, 6.65 ± 1.12 × 10-8 M for 72 h and 3.78 ± 1.30 × 10-8 M for 96 h. We also found cytochalasin E induces cell-cycle G2/M phase arrest (72 h-treatment of 10-6 M cytochalasin E caused 56.2 ± 6.1 % cells arrest in G2/M phase) and cell apoptosis (96 h-treatment of 10-6 M cytochalasin E induced 24.1 ± 4.2 % cells apoptosis). Thus, cytochalasin E is proposed as a potential agent for glioblastoma chemotherapy.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Substantial transition to clean household energy mix in rural China

The household energy mix has significant impacts on human health and climate, as it contributes greatly to many health- and climate-relevant air pollutants. Compared to the well-established urban energy statistical system, the rural household energy statistical system is incomplete and is often associated with high biases. Via a nationwide investigation, this study revealed high contributions to energy supply from coal and biomass fuels in the rural household energy sector, while electricity comprised ∼20%. Stacking (the use of multiple sources of energy) is significant, and the average number of energy types was 2.8 per household. Compared to 2012, the consumption of biomass and coals in 2017 decreased by 45% and 12%, respectively, while the gas consumption amount increased by 204%. Increased gas and decreased coal consumptions were mainly in cooking, while decreased biomass was in both cooking (41%) and heating (59%). The time-sharing fraction of electricity and gases (E&G) for daily cooking grew, reaching 69% in 2017, but for space heating, traditional solid fuels were still dominant, with the national average shared fraction of E&G being only 20%. The non-uniform spatial distribution and the non-linear increase in the fraction of E&G indicated challenges to achieving universal access to modern cooking energy by 2030, particularly in less-developed rural and mountainous areas. In some non-typical heating zones, the increased share of E&G for heating was significant and largely driven by income growth, but in typical heating zones, the time-sharing fraction was <5% and was not significantly increased, except in areas with policy intervention. The intervention policy not only led to dramatic increases in the clean energy fraction for heating but also accelerated the clean cooking transition. Higher income, higher education, younger age, less energy/stove stacking and smaller family size positively impacted the clean energy transition