Ergothioneine Protects Against UV-Induced Oxidative Stress Through the PI3K/AKT/Nrf2 Signaling Pathway.

Background: Ergothioneine (EGT) is an antioxidant, which could be detected in human tissues, and human skin cells could utilize EGT and play an anti-oxidative role in keratinocytes. And in this study we are going to elucidate whether EGT could protect the skin from photoaging by Ultraviolet (UV) exposure in mice and its molecule pathway. Methods: Histological analysis was performed for evaluating the skin structure change. Malondialdehyde (MDA) and superoxide dismutase (SOD) levels were measured with biological assay for evaluating oxidative and antioxidative ability of skin exposed to UV light. And the level of marker molecules in mouse skin were detected by hydroxyproline (Hyp) assay, immunohistochemical analysis, Western blot, and quantitative real-time PCR (qRT-PCR). The markers of skin aging and cell death were tested by cell culture and treatment, Western blot and qRT-PCR. Results: EGT decreased the levels of inflammatory factors induced by UV exposure in mouse skin. MDA and SOD activity detection showed that EGT decreased MDA levels, increased SOD activity, and upregulated PI3K/Akt/Nrf2 signals in mouse skin exposed to UV, which further activated Nrf2 in the nucleus and enhanced the expression of Nrf2 target genes. In the cell model, we revealed that EGT could inhibit the increase in senescence-associated ß-galactosidase-positive cells and p16 and γ-H2A.X positive cells induced by etoposide and activate PI3K/Akt/Nrf2 signaling. Moreover, a PI3K inhibitor blocked EGT protection against etoposide-induced cell death. Conclusion: The study showed EGT may play an important protective role against cell damage or death through the PI3K/Akt/Nrf2 signaling pathway in skin.

Comprehensive Assessment of Ischemic Stroke in Nonhuman Primates: Neuroimaging, Behavioral, and Serum Proteomic Analysis.

Ischemic strokes, prevalence and impactful, underscore the necessity of advanced research models closely resembling human physiology. Our study utilizes nonhuman primates (NHPs) to provide a detailed exploration of ischemic stroke, integrating neuroimaging data, behavioral outcomes, and serum proteomics to elucidate the complex interplay of factors involved in stroke pathophysiology. We observed a consistent pattern in infarct volume, peaking at 1-month postmiddle cerebral artery occlusion (MCAO) and then stabilized. This pattern was strongly correlated to notable changes in motor function and working memory performance. Using diffusion tensor imaging (DTI), we detected significant alterations in fractional anisotropy (FA) and mean diffusivity (MD) values, signaling microstructural changes in the brain. These alterations closely correlated with the neurological and cognitive deficits that we observed, highlighting the sensitivity of DTI metrics in stroke assessment. Behaviorally, the monkeys exhibited a reliance on their unaffected limb for compensatory movements, a common response to stroke impairment. This adaptation, along with consistent DTI findings, suggests a significant impact of stroke on motor function and spatial perception. Proteomic analysis through MS/MS functional enrichment identified two distinct groups of proteins with significant changes post-MCAO. Notably, MMP9, THBS1, MB, PFN1, and YWHAZ were identified as potential biomarkers and therapeutic targets for ischemic stroke. Our results underscore the complex nature of stroke and advocate for an integrated approach, combining neuroimaging, behavioral studies, and proteomics, for advancing our understanding and treatment of this condition.

A small-scale external quality assessment for PCR detection of group B streptococcus in China.

BACKGROUND: Group B streptococcus (GBS) is considered a leading cause of maternal and infant morbidity and mortality. Molecular diagnosis is a routinely used approach for GBS screening to protect pregnant women and prevent early-onset GBS neonatal disease. The objective of this study was to identify issues and guarantee the dependability of GBS molecular diagnosis by an external quality assessment (EQA) scheme. METHODS: The EQA panel comprised eight samples spiked with 10-fold dilutions of GBS suspension (20-2,000,000 copies/mL), and 2 negative control samples. The panels were coded randomly and distributed to participating laboratories for GBS detection. RESULTS: In total, 44 participating laboratories submitted results with eight commercial GBS PCR assays and one in-house assay. Among them, 36 obtained an acceptable or higher performance score, while 8 required improvement. Among the 440 results returned, 62 (14.1 %) were incorrect, including 5 false positives and 57 false negatives. CONCLUSIONS: Our small-scale EQA showed that most participating laboratories have reliable diagnostic capacities for GBS PCR detection. Nonetheless, further improvements in the detection performance of some laboratories are required, particularly with low-concentration samples. Our survey also reinforces the use of EQA as an essential tool to evaluate the overall proficiency of clinical laboratories.

Highly accurate OAM mode detection network for ring Airy Gaussian vortex beams disturbed by atmospheric turbulence based on interferometry.

Atmospheric turbulence reduces the detection accuracy of orbital angular momentum (OAM) modes, which affects the performance of OAM optical communication. In this paper, we propose a method based on interferometry and a residual network (ResNet) to detect the OAM modes of ring Airy Gaussian vortex beams (RAGVBs) disturbed by atmospheric turbulence. The RAGVBs first interfere with spherical waves to obtain the sign features of the OAM modes, and then ResNet is employed to recognize OAM modes from the interferograms. The results demonstrate that the detection accuracy is higher than that of the OAM spectrum method under different turbulence strengths. The detection accuracy can even reach over 99% under strong fluctuations. Our research provides a reference for improving the performance of OAM optical communication through atmospheric turbulence.

BER performance of an FSOC system over atmospheric turbulence channels based on computational temporal ghost imaging.

In a free space optical communication (FSOC) system, atmospheric turbulence will increase the bit error ratio (BER) and impair FSOC link reliability. Since computational temporal ghost imaging (CTGI) has anti-interference, we present an FSOC system over atmospheric turbulence based on CTGI. The simulation results show that the BER performance of CTGI is better than on-off keying under different atmospheric turbulence regimes. To improve the performance of the CTGI scheme, the influence of the number of transmission samples and code length is analyzed. It is shown that BER performance improves with the increment of the number of samples, while code length has no impact. This scheme provides an idea for reliable communication over atmospheric turbulence and an important reference for improving wireless optical communication in an extreme environment.

Large-volume and deep brain imaging in rabbits and monkeys using COMPACT two-photon microscopy.

In vivo imaging has been widely used for investigating the structure and function of neurons typically located within ~ 800 µm below the cortical surface. Due to light scattering and absorption, it has been difficult to perform in-vivo imaging of neurons in deep cortical and subcortical regions of large animals with two-photon microscopy. Here, we combined a thin-wall quartz capillary with a GRIN lens attached to a prism for large-volume structural and calcium imaging of neurons located 2 mm below the surface of rabbit and monkey brains. The field of view was greatly expanded by rotating and changing the depth of the imaging probe inside a quartz capillary. Calcium imaging of layer 5/6 neurons in the rabbit motor cortex revealed differential activity of these neurons between quiet wakefulness and slow wave sleep. The method described here provides an important tool for studying the structure and function of neurons located deep in the brains of large animals.

The accelerated aging skin in rhino-like SHJHhr mice.

SHJHhr mice line is rhino-like mice with a nonsense Hairless (Hr) mutant, which shows the characteristic of shedding hair and wrinkled skin with increasing age. Through histological analysis and aging indexes detection, SHJHhr mice show an increased thickness skin with degraded hair follicle and dermal cysts and disorganized collagen fibres, as well as decreased level of Hyp. Meanwhile, the aging markers p16 and p21 are significantly higher in SHJHhr mouse skin than ICR mouse skin at same age. Moreover, the data of MDA and SOD show a higher oxidative stress in SHJHhr mouse skin, and the levels of Nrf2 and its targets are significantly downregulated, which suggests SHJHhr mice have a faster aging skin and its reason maybe poor antioxidative protection. Overall, this study shows SHJHhr mice with an accelerated aging skin, which suggests the role of Hr gene in skin aging.

Analytical sensitivity comparison of 14 conventional and three rapid RT-PCR assays for SARS-CoV-2 detection.

Recent reports have compared the analytical sensitivities of some SARS-CoV-2 RT-PCR assays, but differences in the viral materials used for these evaluations made comprehensive conclusions difficult. We carried out a direct comparison of the analytical sensitivities of 14 conventional and three rapid RT-PCR assays for the detection of SARS-CoV-2. The comparison was performed utilizing a certified reference material for SARS-CoV-2 RNA that was serially two-fold diluted in RNA storage solution. Our results show that the analytical sensitivities of the 17 assays varied within an 8-fold range (100-800 copies/mL). Moreover, a trend with some rapid assays yielding slightly higher analytical sensitivities (2- to 4-fold) compared with conventional assays was observed. We conclude that most of the RT-PCR assays can be used for routine COVID-19 diagnosis, but some assays with the poorest analytical sensitivities may lead to false-negative results when used to identify asymptomatic individuals who can carry a low viral load but still be infectious. These findings should be kept in mind when selecting high-sensitivity and rapid assays.

Clinical Application of Pro-Gastrin-Releasing Peptide.

BACKGROUND: The diagnostic sensitivity and specificity of serum Pro-gastrin-releasing peptide (ProGRP) in benign or malignant diseases remains controversial. METHODS: The clinical data of 6,948 patients who were examined for ProGRP from February 2015 to January 2017 in the Zhongshan Hospital of the XiaMen University, were collected. The clinical data of the different groups were analyzed by statistical methods. RESULTS: The ProGRP reference levels were 68.50 pg/mL. The percentages of abnormal ProGRP levels were 23.87%, 26.14%, 22.87%, 84.56%, 16.1%, 15.59% and 43.75% for the pneumonia, cardiovascular disease, cerebral vascular disease, renal failure, small cell lung cancer (SCLC), colorectal cancer, and prostate cancer groups, respectively. The 95th percentile of the serum ProGRP concentration levels in the renal failure group was 364.22 pg/mL. The ProGRP cutoff levels for SCLC group were 162.90 pg/mL and the area under the receiver-operating characteristic curve (AUC) was 0.940 (95% CI, 0.892 to 0.987). The parameters sensitivity, specificity, PLR (positive likelihood ratio), NLR (negative likelihood) and Kappa value for the SCLC group with the exclusion of the renal failure group were 81.10% (95% CI: 38.19% - 89.71%), 99.51% (95% CI: 99.31% - 99.66%), 167.59 (95% CI: 116.06 - 241.99), 0.19 (95% CI: 0.11 - 0.32), and 0.6830 (Sig: 0.000), respectively. In the SCLC group, significantly higher concentrations of serum ProGRP of M1 were observed compared with M0. All esophageal neoplasms with high-level ProGRP were identified as small cell neoplasms. CONCLUSIONS: The ProGRP levels were increased in a variety of benign and malignant diseases and were considered a putative marker for SCLC with the exception of the renal failure group. It may be suggested that the high ProGRP levels originated from patients with neuroendocrine tumor.

Integration of Global and Local Metrics for Domain Adaptation Learning Via Dimensionality Reduction.

Domain adaptation learning (DAL) investigates how to perform a task across different domains. In this paper, we present a kernelized local-global approach to solve domain adaptation problems. The basic idea of the proposed method is to consider the global and local information regarding the domains (e.g., maximum mean discrepancy and intraclass distance) and to convert the domain adaptation problem into a bi-object optimization problem via the kernel method. A solution for the optimization problem will help us identify a latent space in which the distributions of the different domains will be close to each other in the global sense, and the local properties of the labeled source samples will be preserved. Therefore, classic classification algorithms can be used to recognize unlabeled target domain data, which has a significant difference on the source samples. Based on the analysis, we validate the proposed algorithm using four different sources of data: synthetic, textual, object, and facial image. The experimental results indicate that the proposed method provides a reasonable means to improve DAL algorithms.