Computer Simulation of Noise Effects of the Neighborhood of Stimulus Threshold for a Mathematical Model of Homeostatic Regulation of Sleep-Wake Cycles

The noise effects on a homeostatic regulation of sleep-wake cycles’ neuronal mathematical model determined by the hypocretin/orexin and the local glutamate interneurons spatiotemporal behaviors are studied within the neighborhood of stimulus threshold in this work; the neuronal noise added to the stimulus, the conductance, and the activation variable of the modulation function are investigated, respectively, based on a circadian input skewed in sine function. The computer simulation results suggested that the increased amplitude of external current input will lead to the fact that awakening time is advanced but the sleepy time remains the same; for the bigger conductance and modulation noise, the regulatory mechanism of the model sometimes will be collapsed and the coupled two neurons of the model show very irregular activities; the falling asleep or wake transform appears at nondeterminate time

CRAFITY score benefits hepatocellular carcinoma patients treated with transarterial chemoembolization and lenvatinib

Abstract Background The CRAFITY score serves as a simple and effective predictive model for individuals diagnosed with hepatocellular carcinoma (HCC) and subjected to treatment with atezolizumab and bevacizumab (Atez/Bev). However, no large sample size studies have reported the application of the CRAFITY score among HCC patients undergoing transarterial chemoembolization (TACE) in conjunction with lenvatinib. This research aims to assess the prognostic role of the CRAFITY score in the context of individuals with HCC receiving TACE in combination with lenvatinib. Methods This retrospective analysis encompassed 314 individuals diagnosed with HCC who underwent the combination of TACE and lenvatinib at two medical facilities in China from August 2019 to August 2022 (comprising a training cohort of n = 172 and a validation cohort of n = 142). We investigated the prognostic values of overall survival (OS), progression‐free survival (PFS), disease control rate, and objective response rate in the training cohort based on the CRAFITY scores. Furthermore, the predictive capacity of the model was corroborated through validation using an external cohort. Results We included 174 and 142 patients treated with TACE plus lenvatinib in the training and validation cohorts, correspondingly. PFS and OS differed across all three groups in all training and validation cohorts, based on the CRAFITY score (p < 0.001). In both cohorts, the CRAFITY score effectively predicted tumor response (p < 0.001). Moreover, among the 121 patients who received TACE, lenvatinib, and immunotherapy, the CRAFITY score showed promising predictive efficacy in PFS and OS. Conclusions The CRAFITY score, utilizing C‐reactive protein and alpha‐fetoprotein values, emerges as a dependable and pragmatic instrument for forecasting the effectiveness of TACE plus lenvatinib in individuals with unresectable HCC. This scoring system holds the potential to assist oncologists in making informed clinical decisions

Stereological Study on the Positive Effect of Running Exercise on the Capillaries in the Hippocampus in a Depression Model

Running exercise is an effective method to improve depressive symptoms when combined with drugs. However, the underlying mechanisms are not fully clear. Cerebral blood flow perfusion in depressed patients is significantly lower in the hippocampus. Physical activity can achieve cerebrovascular benefits. The purpose of this study was to evaluate the impacts of running exercise on capillaries in the hippocampal CA1 and dentate gyrus (DG) regions. The chronic unpredictable stress (CUS) depression model was used in this study. CUS rats were given 4 weeks of running exercise from the fifth week to the eighth week (20 min every day from Monday to Friday each week). The sucrose consumption test was used to measure anhedonia. Furthermore, stereological methods were used to investigate the capillary changes among the control group, CUS/Standard group and CUS/Running group. Sucrose consumption significantly increased in the CUS/Running group. Running exercise has positive effects on the capillaries parameters in the hippocampal CA1 and DG regions, such as the total volume, total length and total surface area. These results demonstrated that capillaries are protected by running exercise in the hippocampal CA1 and DG might be one of the structural bases for the exercise-induced treatment of depression-like behavior. These results suggest that drugs and behavior influence capillaries and may be considered as a new means for depression treatment in the future

A Combination of Let-7d, Let-7g and Let-7i Serves as a Stable Reference for Normalization of Serum microRNAs

<div><p>Recent studies have indicated that circulating microRNAs (miRNAs) in serum and plasma are stable and can serve as biomarkers of many human diseases. Measurement of circulating miRNAs with sufficient sensitivity and precision, however, faces some special challenges, among which proper normalization is the most critical but often an underappreciated issue. The primary aim of this study was to identify endogenous reference genes that maintain consistent levels under various conditions to serve as an internal control for quantification of serum miRNAs. We developed a strategy combining Illumina’s sequencing by synthesis (SBS) technology, reverse transcription quantitative polymerase chain reaction (RT-qPCR) assay, literature screening and statistical analysis to screen and validate the most suitable reference genes. A combination of let-7d, let-7g and let-7i is selected as a reference for the normalization of serum miRNAs and it is statistically superior to the commonly used reference genes U6, RNU44, RNU48 and miR-16. This has important implications for proper experimental design and accurate data interpretation.</p> </div

Characterization of the absolute concentration and the stability of let-7d/g/i in serum.

<p>(<b>A</b>) Dynamic range and sensitivity of the RT-qPCR assay for measuring let-7d/g/i (n = 5). Synthetic single-stranded let-7d/g/i ranging from 0.01 attomole (0.0033 attomole each, equivalent to 6×10³ copies in total) to 10 pmol (3.3 pmol each) were serially diluted over ten orders of magnitude and were assessed by the RT-qPCR assay. The resulting C_q values were plotted versus the amount of input let-7d/g/i to generate a standard curve. An assay using water instead of RNA for reverse-transcription was included as a negative control. (<b>B</b>) Correlation of serum volume to the C_q values (n = 5). Total RNA was extracted from different volumes of serum ranging from 10 µL to 400 µL. The levels of serum let-7d/g/i were assessed by RT-qPCR. The resulting C_q values were plotted versus the serum volume used for RNA extraction. An assay using water instead of RNA for reverse-transcription was included as a negative control. (<b>C</b>) Stability of let-7d/g/i in serum after extended storage (n = 5). Serum samples were equally divided and stored at room temperature, 4°C, -20°C or -80°C for 1, 2, 3, 7, 14 or 30 days. For each time point, total RNA was isolated and let-7d/g/i was measured by RT-qPCR assay. Storage at room temperature for 30 days yielded no apparent increase in C_q values. (<b>D</b>) Instability of other RNAs in serum (n = 5). Serum samples were equally divided and stored at room temperature for 1 to 24 h. For each time point, total RNA was isolated, and the levels of some large molecular weight RNA (β-actin, GAPDH and 28S rRNA) and snRNA/snoRNA (U6, RNU44, RNU48, SNORD24, SNORD38B, SNORD43, SNORA66 and SNORA74A) were measured by RT-qPCR. Storage at room temperature for 24 h resulted in an apparent increase of C_q values for these RNAs. (<b>E</b>) Stability of let-7d/g/i in serum after RNase digestion (n = 5). Serum samples were treated with 10 U/ml RNase A and 400 U/ml RNase T1 for 4 h at 37°C. After the treatment, the RNA was extracted from the serum, and the levels of let-7d/g/i were assessed by RT-qPCR. (<b>F</b>) Instability of other RNAs in serum after RNase digestion (n = 5). Serum samples were treated with 10 U/ml RNase A and 400 U/ml RNase T1 for 1, 2 or 4 h at 37°C. After the treatment, the RNA was extracted and the levels of the indicated RNAs were assessed by RT-qPCR assay. (<b>G</b> and <b>H</b>) Stability of let-7d/g/i under acidic or alkaline conditions (n = 5). Serum samples were incubated for 1 h under acidic (pH 2) or alkaline (pH 12) conditions. The levels of let-7d/g/i were assessed by RT-qPCR. (<b>I</b>) Stability of let-7d/g/i in serum following re-freezing and re-thawing of the samples (n = 6). Serum samples were subjected to eight freeze-thaw cycles.</p

Strategy for the identification of stable reference genes for normalizing serum miRNAs.

<p>Strategy for the identification of stable reference genes for normalizing serum miRNAs.</p

Selection of the most stable reference genes by SBS technology.

<p>(<b>A</b>) Sera from cancer patients and healthy participants were pooled separately as described above, and miRNA levels were determined using SBS technology. SBS reads were converted to the log₂ scale. The average log₂-transformed read of each miRNA was plotted against the standard deviation of the log₂-transformed read. MiRNAs highlighted in red are those with higher abundance (log₂-transformed reads > 10) and lower standard deviations (< 1) in the dataset. (<b>B</b>) The average expression values (SBS reads ± standard errors) of the selected miRNAs were plotted. (<b>C</b>) Selection of the most stable reference genes from a panel of 25 genes using geNorm. The geNorm program calculates the average expression stability value (M) for each gene. Genes with the lowest M values are considered the most stable. The least stable gene with the highest M value was automatically excluded for the next calculation round. The x-axis from left to right indicates the ranking of the reference genes according to their expression stability from the least to the most stable, and the y-axis represents the M values of the remaining reference genes. (<b>D</b>) Identification of the optimal number of reference genes for accurate normalization using geNorm. V is the pairwise variation (V_n/V_n+1) between two sequential normalization factors (NF_n and NF_n+1). The magnitude of the change in the normalization factor after the inclusion of an additional reference gene reflects the improvement that is obtained. The authors of geNorm suggest that V > 0.15 should be considered the threshold for including an extra reference gene in the assay, and the least number of genes for each V < 0.15 is selected as the optimal set of genes for normalization. (<b>E</b>) Selection of the most stable reference gene or gene combinations using geNorm. In this case, geNorm indicated that the combination of let-7d, let-7g and let-7i was statistically superior to other combinations or each individually. (<b>F</b>) Identification of the most stable reference genes using NormFinder. The NormFinder algorithm ranks the set of candidate normalization genes according to their expression stability in different groups (e.g., disease versus normal). According to this algorithm, lower stability values of the individual genes indicate greater gene stability. In this case, 23 samples were divided into two groups (12 normal controls and 11 cancer patients). Blue bars represent the stability values of the candidate genes. </p

Effect of different normalization approaches on the levels of serum miRNAs.

<p>(<b>A</b>) Serum samples from healthy controls, ulcerative colitis patients and colon cancer patients were divided into three groups (n =5 in each group). After the initial denaturation steps, 1, 2 and 4 attomole of synthetic artificial miRNA (5’-GUGGAUUCCGUCUCGUUAG-3’) were spiked into 100 μL of serum of each group (1 attomole for control group, 2 attomole for ulcerative colitis group and 4 attomole for colon cancer group). After isolation of total RNA, the levels of artificial miRNA were assessed by RT-qPCR assay and were normalized to serum volume, let-7d/g/i, U6 or miR-191, respectively. Relative levels were calculated using the 2^-△△Cq method and were shown by dot plots. Significance was calculated by t-test. (<b>B</b>) Expression levels of miR-25, miR-214, miR-223 and miR-483-5p were measured in serum from cancer patients (n = 84) and healthy controls (n = 41) by RT-qPCR and were normalized to serum volume, let-7d/g/i, U6 or miR-191. Relative levels were calculated using the 2^-△△Cq method and are presented as mean fold changes ± standard errors. Significance was calculated by t-test.</p