The Regulation of ROS- and BECN1-Mediated Autophagy by Human Telomerase Reverse Transcriptase in Glioblastoma

Glioblastoma (GBM) is the most common and aggressive malignant brain tumor with high morbidity and mortality. Human telomerase reverse transcriptase (hTERT), the catalytic subunit of human telomerase, is overexpressed in most cancers including GBM. It is well known that hTERT can compensate telomere shortening to immortalize cells. However, in addition to the canonical function, hTERT has the roles beyond canonical telomere maintenance. To further understand the effects of hTERT on glioblastoma progression, we investigated the role of hTERT in regulating autophagy—a conserved pathway, by which cells deliver cellular organic material and impaired organelles to the lysosomes for degradation and recycle these cargos to produce energy under a stressful condition. Our results showed that downregulation of hTERT impaired autophagy levels by suppressing BECN1/beclin-1 and induced an increase of reactive oxygen species (ROS), which resulted in cell death ultimately. On the contrary, overexpression of BECN1 or treating cells with the antioxidant N-acetylcysteine (NAC) could restore the survival of hTERT knockdown cells. Our study will provide an additional basis of telomerase-targeting therapy for future clinical anticancer treatment

Accurate Characterization of the Properties of the Rare-Earth-Doped Crystal for Laser Cooling

We present a method for calibrating a commercial thermal camera adopted to accurately measure the temperature change of the sample in a laser-induced temperature modulation spectrum (LITMoS) test, which is adopted for measuring two crucial parameters of the external quantum efficiency ηext and the background absorption coefficient αb for assessing the laser cooling grade of the rare-earth-doped materials. After calibration, the temperature resolution of the calibrated thermal camera is better than 0.1 K. For the cooling grade Czochralski-grown 5% Yb3+:LuLiF4 crystal, the corresponding values of ηext and αb are LITMoS = measured to be ηext=99.4 (±0.1)% and αb=1.5 (±0.1)×10−4 cm−1, respectively

Accurate Characterization of the Properties of the Rare-Earth-Doped Crystal for Laser Cooling

We present a method for calibrating a commercial thermal camera adopted to accurately measure the temperature change of the sample in a laser-induced temperature modulation spectrum (LITMoS) test, which is adopted for measuring two crucial parameters of the external quantum efficiency ηext and the background absorption coefficient αb for assessing the laser cooling grade of the rare-earth-doped materials. After calibration, the temperature resolution of the calibrated thermal camera is better than 0.1 K. For the cooling grade Czochralski-grown 5% Yb3+:LuLiF4 crystal, the corresponding values of ηext and αb are LITMoS = measured to be ηext=99.4 (±0.1)% and αb=1.5 (±0.1)×10−4 cm−1, respectively

Microfabricated Glow Discharge Plasma (MFGDP) for Ambient Desorption/Ionization Mass Spectrometry

A novel ambient ionization technique for mass spectrometry, microfabricated glow discharge plasma (MFGDP), is reported. This device is made of a millimeter-sized ceramic cavity with two platinum electrodes positioned face-to-face. He or Ar plasma can be generated by a direct current voltage of several hundreds of volts requiring a total power below 4 W. The thermal plume temperature of the He plasma was measured and found to be between 25 and 80 °C at a normal discharge current. Gaseous, liquid, creamy, and solid samples with molecular weights up to 1.5 kDa could be examined in both positive and negative mode, giving limits of detection (LOD) at or below the fg/mm² level. The relative standard deviation (RSD) of manual sampling ranged from 10% to ∼20%, while correlation coefficients of the working curve (<i>R</i>²) are all above 0.98 with the addition of internal standards. The ionization mechanisms are examed via both optical and mass spectrometry. Due to the low temperature characteristics of the microplasma, nonthermal momentum desorption is considered to dominate the desorption process

Factors associated with burnout among frontline nurses in the post-COVID-19 epidemic era: a multicenter cross-sectional study

Abstract Background The COVID-19 pandemic has significantly increased the risk of burnout among frontline nurses. However, the prevalence of burnout and its associated factors in the post-pandemic era remain unclear. This research aims to investigate burnout prevalence among frontline nurses in the post-pandemic period and pinpoint associated determinants in China. Methods From April to July 2023, a cross-sectional study was carried out across multiple centers, focusing on frontline nurses who had been actively involved in the COVID-19 pandemic. The data collection was done via an online platform. The Maslach Burnout Inventory-Human Services Survey was utilized to evaluate symptoms of burnout. A multivariable logistic regression analysis was used to pinpoint factors associated with burnout. Results Of the 2210 frontline nurses who participated, 75.38% scored over the cut-off for burnout. Multivariable logistic regression revealed that factors like being female [odds ratio (OR) = 0.41, 95%CI = 0.29–0.58] and exercising 1–2 times weekly[OR = 0.53, 95%CI = 0.42–0.67] were protective factors against burnout. Conversely, having 10 or more night shifts per month[OR = 1.99, 95%CI = 1.39–2.84], holding a master’s degree or higher[OR = 2.86, 95% CI = 1.59–5.15], poor health status[OR = 2.43, 95% CI = 1.93–3.08] and [OR = 2.82, 95%CI = 1.80–4.43], under virus infection[OR = 7.12, 95%CI = 2.10-24.17], and elevated work-related stress[OR = 1.53, 95% CI = 1.17-2.00] were all associated with an elevated risk of burnout. Conclusion Our findings indicate that post-pandemic burnout among frontline nurses is influenced by several factors, including gender, monthly night shift frequency, academic qualifications, weekly exercise frequency, health condition, and viral infection history. These insights can inform interventions aimed at safeguarding the mental well-being of frontline nurses in the post-pandemic period

Association between Days Open and Parity, Calving Season or Milk Spectral Data

Milk spectral data on 2118 cows from nine herds located in northern China were used to access the association of days open (DO). Meanwhile, the parity and calving season of dairy cows were also studied to characterize the difference in DO between groups of these two cow-level factors. The result of the linear mixed-effects model revealed that no significant differences were observed between the parity groups. However, a significant difference in DO exists between calving season groups. The interaction between parity and calving season presented that primiparous cows always exhibit lower DO among all calving season groups, and the variation in DO among parity groups was especially clearer in winter. Survival analysis revealed that the difference in DO between calving season groups might be caused by the different P/AI at the first TAI. In addition, the summer group had a higher chance of conception in the subsequent services than other groups, implying that the micro-environment featured by season played a critical role in P/AI. A weak linkage between DO and wavenumbers ranging in the mid-infrared region was detected. In summary, our study revealed that the calving season of dairy cows can be used to optimize the reproduction management. The potential application of mid-infrared spectroscopy in dairy cows needs to be further developed

Additional file 1 of Identification of potential crucial genes and therapeutic targets for epilepsy

Additional file 1: Table S1. 91 DEGs were identified in GSE44031 series

A novel method revealing animal evolutionary relationships based on milk Mid-infrared

AbstractMid-infrared spectra (MIRS) can effectively reflect the chemical bonds in milk, which has been widely used in dairy herd improvement. However, the relationship between MIRS and animal evolution remains largely unclear. This study firstly found great differences in MIRS and the components of milk by analyzing MIRS information of 12 different mammal species. A five-level discriminant model of evolutionary level based on MIRS was established with a test set kappa coefficient >0.97. In addition, a regression model of genetic distance was also established to estimate the genetic distance of different animal species with a correlation coefficient of R >0.94. These results showed that this method could be used for accurate mammalian evolutionary relationship assessment. We further clarified the potential relationship between MIRS and genes, such as PPP3CA and SCD that could change MIRS by regulating specific milk components. In conclusion, we expand the application of MIRS in animal species identification and evolution research and provide new perspectives for the research on the formation mechanism of different animal milk special components