Comprehensive overview of the anesthesiology research landscape: A machine Learning Analysis of 737 NIH-funded anesthesiology primary Investigator's publication trends.

Background: Anesthesiology plays a crucial role in perioperative care, critical care, and pain management, impacting patient experiences and clinical outcomes. However, our understanding of the anesthesiology research landscape is limited. Accordingly, we initiated a data-driven analysis through topic modeling to uncover research trends, enabling informed decision-making and fostering progress within the field. Methods: The easyPubMed R package was used to collect 32,300 PubMed abstracts spanning from 2000 to 2022. These abstracts were authored by 737 Anesthesiology Principal Investigators (PIs) who were recipients of National Institute of Health (NIH) funding from 2010 to 2022. Abstracts were preprocessed, vectorized, and analyzed with the state-of-the-art BERTopic algorithm to identify pillar topics and trending subtopics within anesthesiology research. Temporal trends were assessed using the Mann-Kendall test. Results: The publishing journals with most abstracts in this dataset were Anesthesia & Analgesia 1133, Anesthesiology 992, and Pain 671. Eight pillar topics were identified and categorized as basic or clinical sciences based on a hierarchical clustering analysis. Amongst the pillar topics, "Cells & Proteomics" had both the highest annual and total number of abstracts. Interestingly, there was an overall upward trend for all topics spanning the years 2000-2022. However, when focusing on the period from 2015 to 2022, topics "Cells & Proteomics" and "Pulmonology" exhibit a downward trajectory. Additionally, various subtopics were identified, with notable increasing trends in "Aneurysms", "Covid 19 Pandemic", and "Artificial intelligence & Machine Learning". Conclusion: Our work offers a comprehensive analysis of the anesthesiology research landscape by providing insights into pillar topics, and trending subtopics. These findings contribute to a better understanding of anesthesiology research and can guide future directions.

Long-term prognosis of patients with gallbladder carcinoma after curative-intent resection based on changes in the ratio of carbohydrate antigen 19-9 to total bilirubin (CA19-9/TB): a multicenter retrospective cohort study.

BACKGROUND: The prognostic value of carbohydrate antigen 19-9 (CA19-9) is known to be affected by elevated bilirubin levels in patients with gallbladder carcinoma (GBC). The clinical significance of changes in the ratio of CA19-9 levels to total bilirubin (TB) levels in patients with GBC after curative-intent resection remains unknown. The aim of this study was to determine the prognostic value of changes in preoperative and postoperative CA19-9/TB ratio in these patients. METHODS: Prospectively colleced data on consecutive patients who underwent curative-intent resection for GBC between January 2015 and December 2020 stored in a multicenter database from 10 hospitals were analysed in this retrospective cohort study. Based on the adjusted CA19-9 defined as the ratio of CA19-9 to TB, and using 2×103 U/µmol as the upper normal value, patients were divided into a normal group (with normal preoperative and postoperative adjusted CA19-9), a normalization group (with abnormal preoperative but normal postoperative adjusted CA19-9), and a non-normalization group (with abnormal postoperative adjusted CA19-9). The primary outcomes were overall survival (OS) and recurrence-free survival (RFS). The log-rank test was used to compare OS and RFS among the groups. The Cox regression model was used to determine factors independently associated with OS and RFS. RESULTS: The normal group (n=179 patients) and the normalization group (n=73 patients) had better OS and RFS than the non-normalization group (n=65 patients) (the 3-year OS rates 72.0%, 58.4% and 24.2%, respectively; the RFS rates 54.5%, 25.5% and 11.8%, respectively; both P<0.001). There were no significant differences between the normal and the normalization groups in OS and RFS (OS, P=0.255; RFS, P=0.130). Cox regression analysis confirmed that the non-normalization group was independently associated with worse OS and RFS. Subgroup analysis revealed that the non-normalization group of patients who received adjuvant therapy had significantly improved OS and RFS as compared to those who did not receive adjuvant therapy (OS, P=0.025; RFS, P=0.003). CONCLUSIONS: Patients with GBC who underwent curative-intent surgical resection with postoperative abnormal levels of adjusted CA19-9 (the CA19-9/TB ratio) were associated with poorer long-term survival outcomes. Adjuvant therapy after surgery improved the long-term outcomes of these patients.

Selective degradation of PL2L60 by metabolic stresses­induced autophagy suppresses multi­cancer growth.

It has been reported that PL2L60 proteins, a product of PIWIL2 gene which might be activated by an intragenic promoter, could mediate a common pathway specifically for tumorigenesis. In the present study, it was further identified by using western blot assay that the PL2L60 proteins could be degraded in cancer cells through a mechanism of selective autophagy in response to oxidative stress. The PL2L60 was downregulated in various types of cancer cells under the hypoxic condition independently of HIF­1α, resulting in apoptosis of cancer cells. Inhibition of autophagy by small interfering RNA targeting of either Beclin­1 (BECN1) or Atg5 resulted in restoration of PL2L60 expression in hypoxic cancer cell. The hypoxic degradation of PL2L60 was also blocked by the attenuation of the autophagosome membrane protein Atg8/microtubule­associated protein 1 light chain 3 (LC3) or autophagy cargo protein p62 expression. Surprisingly, Immunofluorescence analysis demonstrated that LC3 could be directly bound to PL2L60 and was required for the transport of PL2L60 from the nucleus to the cytoplasm for lysosomal flux under basal or activated autophagy in cancer cells. Moreover, flow cytometric analysis displayed that knocking down of PL2L60 mRNA but not PIWIL2 mRNA effectively inhibited cancer cell proliferation and promoted apoptosis of cancer cells. The similar results were obtained from in vivo tumorigenic experiment, in which PL2L60 downregulation in necroptosis areas was confirmed by immunohistochemistry. These results suggested that various cancer could be suppressed by promoting autophagy. The present study revealed a key role of autophagic degradation of PL2L60 in hypoxia­induced cancer cell death, which could be used as a novel therapeutic target of cancer.

Intra- and post-pandemic impact of the COVID-19 outbreak on Stanford Health Care.

Stanford Health Care, which provides about 7% of overall healthcare to approximately 9 million people in the San Francisco Bay Area, has undergone significant changes due to the opening of a second hospital in late 2019 and, more importantly, the COVID-19 pandemic. We examine the impact of these events on anatomic pathology (AP) cases, aiming to enhance operational efficiency in response to evolving healthcare demands. We extracted historical census, admission, lab tests, operation, and AP data since 2015. An approximately 45% increase in the volume of laboratory tests (P < 0.0001) and a 17% increase in AP cases (P < 0.0001) occurred post-pandemic. These increases were associated with progressively increasing (P < 0.0001) hospital census. Census increase stemmed from higher admission through the emergency department (ED), and longer lengths of stay mostly for transfer patients, likely due to the greater capability of the new ED and changes in regional and local practice patterns post-pandemic. Higher census led to overcapacity, which has an inverted U relationship that peaked at 103% capacity for AP cases and 114% capacity for laboratory tests. Overcapacity led to a lower capability to perform clinical activities, particularly those related to surgical procedures. We conclude by suggesting parameters for optimal operations in the post-pandemic era.

A generalizable and easy-to-use COVID-19 stratification model for the next pandemic via immune-phenotyping and machine learning.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians. Methods: Three COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity. Results: Patients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4+ central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively. Conclusion: Overall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics.

Mitochondrial complex I subunit MT-ND1 mutations affect disease progression.

Mitochondrial respiratory chain complex I is an important component of the oxidative respiratory chain, with the mitochondrially encoded NADH:ubiquinone oxidoreductase core subunit 1 (MT-ND1) being one of the core subunits. MT-ND1 plays a role in the assembly of complex I and its enzymatic function. MT-ND1 gene mutation affects pathophysiological processes, such as interfering with the early assembly of complex I, affecting the ubiquinone binding domain and proton channel of complex I, and affecting oxidative phosphorylation, thus leading to the occurrence of diseases. The relationship between MT-ND1 gene mutation and disease has been has received increasing research attention. Therefore, this article reviews the impact of MT-ND1 mutations on disease progression, focusing on the impact of such mutations on diseases and their possible mechanisms, as well as the application of targeting MT-ND1 gene mutations in disease diagnosis and treatment. We aim to provide a new perspective leading to a more comprehensive understanding of the relationship between MT-ND1 gene mutations and diseases.

Research Progress on the Geomechanical Properties of Block-in-Matrix Rocks.

The differences in geomechanical properties and the uncertainty in the spatial distribution of Bimrock pose significant challenges to the construction and disaster prediction of geotechnical engineering. To clarify the geomechanical characteristics of Bimrock, this paper summarizes the basic concepts and classification methods of Bimrock at home and abroad. It discusses the methods and characteristics of determining the geometric features of Bimrock blocks and explores the influencing factors and laws of failure modes and strength under different stress states of Bimrock. The study finds that the failure mode of Bimrock is mainly influenced by factors such as block proportion, degree of welding between blocks and matrix, strength ratio between blocks and matrix, and geometric properties of blocks. Among these factors, block proportion is the most significant, and the degree of welding is a controlling factor. However, due to the complexity of Bimrock structures, there is a lack of applicable methods and mechanical models for the evaluation of geomechanical characteristics of Bimrock in engineering practice. This article also explores the influence and research methods of the geological characteristics of Bimrock in slope and tunnel engineering and, finally, provides prospects for the future research trends relating to Bimrock.

Identification of transcription factor genes responsive to MeJA and characterization of a LaMYC2 transcription factor positively regulates lycorine biosynthesis in Lycoris aurea.

Jasmonates (JAs) are among the main phytohormones, regulating plant growth and development, stress responses, and secondary metabolism. As the major regulator of the JA signaling pathway, MYC2 also plays an important role in plant secondary metabolite synthesis and accumulation. In this study, we performed a comparative transcriptome analysis of Lycoris aurea seedlings subjected to methyl jasmonate (MeJA) at different treatment times. A total of 31,193 differentially expressed genes (DEGs) were identified by RNA sequencing. Among them, 732 differentially expressed transcription factors (TFs) comprising 51 TF families were characterized. The most abundant TF family was WRKY proteins (80), followed by AP2/ERF-EFR (67), MYB (59), bHLH (52), and NAC protein (49) families. Subsequently, by calculating the Pearson's correlation coefficient (PCC) between the expression level of TF DEGs and the lycorine contents, 41 potential TF genes (|PCC| >0.8) involved in lycorine accumulation were identified, including 36 positive regulators and 5 negative regulators. Moreover, a MeJA-inducible MYC2 gene (namely LaMYC2) was cloned on the basis of transcriptome sequencing. Bioinformatic analyses revealed that LaMYC2 proteins contain the bHLH-MYC_N domain and bHLH-AtAIB_like motif. LaMYC2 protein is localized in the cell nucleus, and can partly rescue the MYC2 mutant in Arabidopsis thaliana. LaMYC2 protein could interact with most LaJAZs (especially LaJAZ3 and LaJAZ4) identified previously. Transient overexpression of LaMYC2 increased lycorine contents in L. aurea petals, which might be associated with the activation of the transcript levels of tyrosine decarboxylase (TYDC) and phenylalanine ammonia lyase (PAL) genes. By isolating the 887-bp-length promoter fragment upstream of the start codon (ATG) of LaTYDC, we found several different types of E-box motifs (CANNTG) in the promoter of LaTYDC. Further study demonstrated that LaMYC2 was indeed able to bind the E-box (CACATG) present in the LaTYDC promoter, verifying that the pathway genes involved in lycorine biosynthesis could be regulated by LaMYC2, and that LaMYC2 has positive roles in the regulation of lycorine biosynthesis. These findings demonstrate that LaMYC2 is a positive regulator of lycorine biosynthesis and may facilitate further functional research of the LaMYC2 gene, especially its potential regulatory roles in Amaryllidaceae alkaloid accumulation in L. aurea.

The application of the propensity score matching method in stock prediction among stocks within the same industry.

Stock price prediction is crucial in stock market research, yet existing models often overlook interdependencies among stocks in the same industry, treating them as independent entities. Recognizing and accounting for these interdependencies is essential for precise predictions. Propensity score matching (PSM), a statistical method for balancing individuals between groups and improving causal inferences, has not been extensively applied in stock interdependence investigations. Our study addresses this gap by introducing PSM to examine interdependence among pharmaceutical industry stocks for stock price prediction. Additionally, our research integrates Improved particle swarm optimization (IPSO) with long short-term memory (LSTM) networks to enhance parameter selection, improving overall predictive accuracy. The dataset includes price data for all pharmaceutical industry stocks in 2022, categorized into chemical pharmaceuticals, biopharmaceuticals, and traditional Chinese medicine. Using Stata, we identify significantly correlated stocks within each sub-industry through average treatment effect on the treated (ATT) values. Incorporating PSM, we match five target stocks per sub-industry with all stocks in their respective categories, merging target stock data with weighted data from non-target stocks for validation in the IPSO-LSTM model. Our findings demonstrate that including non-target stock data from the same sub-industry through PSM significantly improves predictive accuracy, highlighting its positive impact on stock price prediction. This study pioneers PSM's use in studying stock interdependence, conducts an in-depth exploration of effects within the pharmaceutical industry, and applies the IPSO optimization algorithm to enhance LSTM network performance, providing a fresh perspective on stock price prediction research.

L-Type Calcium Channel Modulates Low-Intensity Pulsed Ultrasound-Induced Excitation in Cultured Hippocampal Neurons.

As a noninvasive technique, ultrasound stimulation is known to modulate neuronal activity both in vitro and in vivo. The latest explanation of this phenomenon is that the acoustic wave can activate the ion channels and further impact the electrophysiological properties of targeted neurons. However, the underlying mechanism of low-intensity pulsed ultrasound (LIPUS)-induced neuro-modulation effects is still unclear. Here, we characterize the excitatory effects of LIPUS on spontaneous activity and the intracellular Ca2+ homeostasis in cultured hippocampal neurons. By whole-cell patch clamp recording, we found that 15 min of 1-MHz LIPUS boosts the frequency of both spontaneous action potentials and spontaneous excitatory synaptic currents (sEPSCs) and also increases the amplitude of sEPSCs in hippocampal neurons. This phenomenon lasts for > 10 min after LIPUS exposure. Together with Ca2+ imaging, we clarified that LIPUS increases the [Ca2+]cyto level by facilitating L-type Ca2+ channels (LTCCs). In addition, due to the [Ca2+]cyto elevation by LIPUS exposure, the Ca2+-dependent CaMKII-CREB pathway can be activated within 30 min to further regulate the gene transcription and protein expression. Our work suggests that LIPUS regulates neuronal activity in a Ca2+-dependent manner via LTCCs. This may also explain the multi-activation effects of LIPUS beyond neurons. LIPUS stimulation potentiates spontaneous neuronal activity by increasing Ca2+ influx.

A multi-objective optimization evaluation model for seismic performance of slopes reinforced by pile-anchor system.

The significance means of the seismic reinforcement effect of a pile-anchor system for slope reinforcement has been widely recognized. However, cases of deformation failure and instability sliding of the pile-anchor system itself and the reinforced slope under seismic action continue to be recorded. Therefore, it is crucial to evaluate the seismic performance of slopes reinforced by a pile-anchor system to prevent the system's failure. Current evaluation models of a slope reinforced by a pile-anchor system mainly focus on slope stability; however, the safety of the pile-anchor system itself is not sufficiently considered in these models. Consequently, in this study, we propose a multi-objective optimization evaluation (MOE) model for evaluating the seismic performance of slopes reinforced by a pile-anchor system that considers slope stability, safety of the pile-anchor system, and dynamic response of the slope. This model considers slope displacement, acceleration amplification factor of a slope, pile displacement, and anchor displacement as negative indexes, and anti-slide pile bending moment, shear force, and anchor axial force as intermediate indexes. The comprehensive weight of relevant indexes is obtained by combining subjective and objective weights, and the seismic reinforcement effect of the pile-anchor system is evaluated subsequently. In conclusion, the MOE model proposed in this study provides a novel solution for the optimization evaluation of a slope reinforced by a pile-anchor system in forthcoming projects.

RETRACTED: 60 Predicting chorioamnionitis using AI-based methods: a retrospective cohort study.

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal). This meeting abstract has been retracted at the request of the authors. The team determined further analysis is warranted before the formal presentation of the results.

Mechanistic regulation of FOXO transcription factors in the nucleus.

FOXO proteins represent evolutionarily conserved transcription factors (TFs) that play critical roles in responding to various physiological signals or pathological stimuli, either through transcription-dependent or -independent mechanisms. Dysfunction of these proteins have been implicated in numerous diseases, including cancer. Although the regulation of FOXO TFs shuttling between the cytoplasm and the nucleus has been extensively studied and reviewed, there's still a lack of a comprehensive review focusing on the intricate interactions between FOXO, DNA, and cofactors in the regulation of gene expression. In this review, we aim to summarize recent advances and provide a detailed understanding of the mechanism underlying FOXO proteins binding to target DNA. Additionally, we will discuss the challenges associated with pharmacological approaches in modulating FOXO function, and explore the dynamic association between TF, DNA, and RNA on chromatin. This review will contribute to a better understanding of mechanistic regulations of eukaryotic TFs within the nucleus.

MYB transcription factors encoded by diversified tandem gene clusters cause varied Morella rubra fruit color.

Chinese bayberry (Morella rubra) is a fruit tree with a remarkable variation in fruit color, ranging from white to dark red as determined by anthocyanin content. In dark red 'Biqi' (BQ), red 'Dongkui' (DK), pink 'Fenhong' (FH), and white 'Shuijing' (SJ), we identified an anthocyanin-related MYB transcription factor-encoding gene cluster of four members, i.e., MrMYB1.1, MrMYB1.2, MrMYB1.3, and MrMYB2. Collinear analysis revealed that the MYB tandem cluster may have occurred in a highly conserved regions of many eudicot genomes. Two alleles of MrMYB1.1 were observed; MrMYB1.1-1 (MrMYB1.1n) was a full-length allele and homozygous in 'BQ', MrMYB1.1-2 (MrMYB1.1d) was a nonfunctional allele with a single base deletion and homozygous in 'SJ', and MrMYB1.1n/MrMYB1.1d were heterozygous in 'DK' and 'FH'. In these four cultivars, expression of MrMYB1.1, MrMYB1.2 and MrMYB2 was enhanced during ripening. Both alleles were equally expressed in MrMYB1.1n/MrMYB1.1d heterozygous cultivars as revealed by a cleaved amplified polymorphic sequence (CAPS) marker. Expression of MrMYB1.3 was restricted to some dark red cultivars only. Functional characterization revealed that MrMYB1.1n and MrMYB1.3 can induce anthocyanin accumulation while MrMYB1.1d, MrMYB1.2, and MrMYB2 cannot. DNA-protein interaction assays indicated that MrMYB1.1n and MrMYB1.3 can directly bind to and activate the promoters of anthocyanin-related genes via interaction with a MYC-like basic helix-loop-helix protein MrbHLH1. We concluded that the specific genotype of MrMYB1.1 alleles, as well as the exclusive expression of MrMYB1.3 in some dark red cultivars, contributes to fruit color variation. The study provides insights into the mechanisms for regulation of plant anthocyanin accumulation by MYB tandem clusters.

Screening radiation-differentially expressed circular RNAs and establishing dose classification models in the human lymphoblastoid cell line AHH-1.

PURPOSE: In the event of a large-scale radiological accident, rapid and high-throughput biodosimetry is the most vital basis in medical resource allocation for the prompt treatment of victims. However, the current biodosimeter is yet to be rapid and high-throughput. Studies have shown that ionizing radiation modulates expressions of circular RNAs (circRNAs) in healthy human cell lines and tumor tissue. circRNA expressions can be quantified rapidly and high-throughput. However, whether circRNAs are suitable for early radiation dose classification remains unclear. METHODS: We employed transcriptome sequencing and bioinformatics analysis to screen for radiation-differentially expressed circRNAs in the human lymphoblastoid cell line AHH-1 at 4 h following exposure to 0, 2, and 5 Gy 60Co γ-rays. The dose-response relationships between differentially expressed circRNA expressions and absorbed doses were investigated using real-time polymerase chain reaction and linear regression analysis at 4 h, 24 h, and 48 h post-exposure to 0, 2, 4, 6, and 8 Gy. Six distinct dose classification models of circRNA panels were established and validated by receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 11 radiation-differentially expressed circRNAs were identified and validated. Based on dose-response effects, those circRNAs changed in a dose-responsive or dose-dependent manner were combined into panels A through F at 4 h, 24 h, and 48 h post-irradiation. ROC curve analysis showed that panels A through C had the potential to effectively classify exposed and non-exposed conditions, which area under the curve (AUC) of these three panels were all 1.000, and the associate p values were .009. Panels D through F excellently distinguished between different dose groups (AUC = 0.963-1.000, p < .05). The validation assay showed that panels A through F demonstrated consistent excellence in sensitivity and specificity in dose classification. CONCLUSIONS: Ionizing radiation can indeed modulate the circRNA expression profile in the human lymphoblastoid cell line AHH-1. The differentially expressed circRNAs exhibit the potential for rapid and high-throughput dose classification.

let-7g sensitized liver cancer cells to 5-fluorouracil by downregulating ABCC10 expression.

Patients with advanced liver cancer may benefit from 5-fluorouracil (5-FU) therapy. However, most of them eventually faced drug resistance, resulting in a poor prognosis. The present study aims to explore the potential mechanism of let-7g/ABCC10 axis in the regulation of 5-FU resistance in liver cancer cells. Huh-7 cells were used to construct 5-FU resistant Huh-7/4X cells. CCK8, flow cytometry, and TUNEL staining were used to detect the characterization of Huh-7 cells and Huh-7/4X cells. Double luciferase report, PCR, and western blot analyses were used to detect the regulatory effects between let-7g and ABCC10. The levels of biomarkers related to cell cycle progression and apoptosis were detected by western blot assays. The role of let-7g in 5-FU sensitivity of liver cancer cells was evaluated in nude mice. Compared with LX-2 cells, the expression of let-7g was decreased in Hep3B, HepG2, Huh-7, and SK-Hep1 cells, with the lowest expression in Huh-7 cells. The sensitivity of Huh-7 cell to 5-FU was positively correlated with let-7g expression. Transfection of let-7g mimics inhibited the viability of Huh-7/4X cells by prolonging the G1 phase, with the downregulation of ABCC10, PCNA, Cyclin D1, and CDK4. Meanwhile, let-7g promoted apoptosis to increase 5-FU sensitivity of Huh-7/4X by downregulating ABCC10, Bcl-XL as well as upregulating Bax, C-caspase 3, and C-PARP. Dual-luciferase assay further confirmed that let-7g inhibited ABCC10 expression by binding to the ABCC10 3'-UTR region. Furthermore, let-7g increased the sensitivity of Huh-7/4X to 5-FU in vitro and in vivo, which can be reversed by ABCC10 overexpression. In conclusion, let-7g sensitized liver cancer cells to 5-FU by downregulating ABCC10 expression.

Glucocorticoids modulate neural activity via a rapid non-genomic effect on Kv2.2 channels in the central nervous system.

Glucocorticoids are primary stress hormones that exert neuronal effects via both genomic and non-genomic signaling pathways. However, their rapid non-genomic effects and underlying mechanisms on neural activities remain elusive. In the present study, we investigated the rapid non-genomic effect of glucocorticoids on Kv2.2 channels in cultured HEK293 cells and acute brain slices including cortical pyramidal neurons and calyx-type synapses in the brain stem. We found that cortisol, the endogenous glucocorticoids, rapidly increased Kv2.2 currents by increasing the single-channel open probability in Kv2.2-expressing HEK293 cells through activation of the membrane-associated glucocorticoid receptor. Bovine serum albumin-conjugated dexamethasone, a membrane-impermeable agonist of the glucocorticoid receptor, could mimic the effect of cortisol on Kv2.2 channels. The cortisol-increased Kv2.2 currents were induced by activation of the extracellular signal-regulated protein kinase (ERK) 1/2 kinase, which could be inhibited by U0126, an antagonist of the ERK signaling pathway. In layer 2 cortical pyramidal neurons and the calyx of Held synapses, cortisol suppressed the action potential firing frequency during depolarization and reduced the successful rate upon high-frequency stimulation by activating Kv2.2 channels. We further examined the postsynaptic responses and found that cortisol did not affect the mEPSC and evoked EPSC, but increased the activity-dependent synaptic depression induced by a high-frequency stimulus train. In conclusion, glucocorticoids can rapidly activate Kv2.2 channels through membrane-associated glucocorticoid receptors via the ERK1/2 signaling pathway, suppress presynaptic action potential firing, and inhibit synaptic transmission and plasticity. This may be a universal mechanism of the glucocorticoid-induced non-genomic effects in the central nervous system.

Metastatic effects of perfluorooctanoic acid (PFOA) on Drosophila melanogaster with metabolic reprogramming and dysrhythmia in a multigenerational exposure scenario.

Perfluorooctanoic acid (PFOA) exposure correlated with various cancers and their mortality. Its persistence in the environment made its long-term multigenerational influences of significant concerns. However, it remained unanswered whether its multigenerational exposure could influence metastasis which contributes ~90 % to cancer mortality. In the present study, long-term effects of PFOA were measured in Drosophila melanogaster over 3 consecutive generations. In the morning-eclosed (AM) adult flies, PFOA significantly promoted tumor invasion rates and distances which increased over generations. Regarding metabolic reprogramming, PFOA disturbed the expressions of Glut1 and Pdk1, activities and contents of FASN1 (fatty acid synthase), ACC (acetyl-CoA carboxylase) and SREBP1 (sterol regulatory element binding protein). Regarding antioxidant responses, PFOA exposure generated provoked oxidative stress via H2O2 and stimulated antioxidants including glutathione (GSH), catalase (CAT), melatonin, serotonin and cortisol, with downregulations on PI3K/AKT pathways and upregulations on MAPK ones. The biochemical and molecular effects altered over generations. In the afternoon-eclosed (PM) adult flies, the metastasis of PFOA was more deteriorated than in AM adults. The significant influences of dysrhythmia were also observed in the multigenerational effects of PFOA on the metabolism reprogramming and antioxidant responses. The effects on rhythm-regulating gene expressions and protein levels explained the dysrhythmia and also indicated close interactions among metabolism reprogramming, antioxidant responses and rhythm regulation. ENVIRONMENTAL IMPLICATION: Numerous emerging per- and polyfluoroalkyl substances (PFASs) are being detected. Meanwhile, the toxicities of the emerging PFASs still depend on the progress of legacy PFASs for the continuity of scientific studies. As one legacy PFAS, perfluorooctanoic acid (PFOA) exposure correlated with various cancers and their mortality. Its persistence in the environment made its long-term multigenerational influences of significant concerns. However, it remained unanswered whether its multigenerational exposure could influence metastasis which contributes ~90 % to cancer mortality. The present study performed PFOA exposure for 3 consecutive generations. Results showed that the metastasis by PFOA increased over generations, and it was further deteriorated by dysrhythmia. Further analysis demonstrated the interactive involvement of metabolism reprogramming, antioxidant responses and rhythm regulation. The findings of the present study would highlight considerate points for studying the toxicities of emerging PFASs.

Clinical application of amplification-based versus amplification-free metagenomic next-generation sequencing test in infectious diseases.

Background: Recently, metagenomic next-generation sequencing (mNGS) has been used in the diagnosis of infectious diseases (IDs) as an emerging and powerful tool. However, whether the complicated methodological variation in mNGS detections makes a difference in their clinical performance is still unknown. Here we conducted a method study on the clinical application of mNGS tests in the DNA detection of IDs. Methods: We analyzed the effect of several potential factors in the whole process of mNGS for DNA detection on microorganism identification in 98 samples of suspected ID patients by amplification-based mNGS. The amplification-based and amplification-free mNGS tests were successfully performed in 41 samples. Then we compared the clinical application of the two mNGS methods in the DNA detection of IDs. Results: We found that a higher concentration of extracted nucleic acid was more conducive to detecting microorganisms. Other potential factors, such as read depth and proportion of human reads, might not be attributed to microorganism identification. The concordance rate of amplification-based and amplification-free mNGS results was 80.5% (33/41) in the patients with suspected IDs. Amplification-based mNGS showed approximately 16.7% higher sensitivity than amplification-free mNGS. However, 4 cases with causative pathogens only detected by amplification-based mNGS were finally proved false-positive. In addition, empirical antibiotic treatments were adjusted in 18 patients following mNGS testing with unexpected pathogens. Conclusions: Amplification-based and amplification-free mNGS tests showed their specific advantages and disadvantages in the diagnosis of IDs. The clinical application of mNGS still needs more exploration from a methodological perspective. With advanced technology and standardized procedure, mNGS will play a promising role in the diagnosis of IDs and help guide the use of antibiotics.