Automated Interstitial Lung Abnormality Probability Prediction at CT: A Stepwise Machine Learning Approach in the Boston Lung Cancer Study.

Background It is increasingly recognized that interstitial lung abnormalities (ILAs) detected at CT have potential clinical implications, but automated identification of ILAs has not yet been fully established. Purpose To develop and test automated ILA probability prediction models using machine learning techniques on CT images. Materials and Methods This secondary analysis of a retrospective study included CT scans from patients in the Boston Lung Cancer Study collected between February 2004 and June 2017. Visual assessment of ILAs by two radiologists and a pulmonologist served as the ground truth. Automated ILA probability prediction models were developed that used a stepwise approach involving section inference and case inference models. The section inference model produced an ILA probability for each CT section, and the case inference model integrated these probabilities to generate the case-level ILA probability. For indeterminate sections and cases, both two- and three-label methods were evaluated. For the case inference model, we tested three machine learning classifiers (support vector machine [SVM], random forest [RF], and convolutional neural network [CNN]). Receiver operating characteristic analysis was performed to calculate the area under the receiver operating characteristic curve (AUC). Results A total of 1382 CT scans (mean patient age, 67 years ± 11 [SD]; 759 women) were included. Of the 1382 CT scans, 104 (8%) were assessed as having ILA, 492 (36%) as indeterminate for ILA, and 786 (57%) as without ILA according to ground-truth labeling. The cohort was divided into a training set (n = 96; ILA, n = 48), a validation set (n = 24; ILA, n = 12), and a test set (n = 1262; ILA, n = 44). Among the models evaluated (two- and three-label section inference models; two- and three-label SVM, RF, and CNN case inference models), the model using the three-label method in the section inference model and the two-label method and RF in the case inference model achieved the highest AUC, at 0.87. Conclusion The model demonstrated substantial performance in estimating ILA probability, indicating its potential utility in clinical settings. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Zagurovskaya in this issue.

A Novel Instruction Driven 1-D CNN Processor for ECG Classification.

Electrocardiography (ECG) has emerged as a ubiquitous diagnostic tool for the identification and characterization of diverse cardiovascular pathologies. Wearable health monitoring devices, equipped with on-device biomedical artificial intelligence (AI) processors, have revolutionized the acquisition, analysis, and interpretation of ECG data. However, these systems necessitate AI processors that exhibit flexible configuration, facilitate portability, and demonstrate optimal performance in terms of power consumption and latency for the realization of various functionalities. To address these challenges, this study proposes an instruction-driven convolutional neural network (CNN) processor. This processor incorporates three key features: (1) An instruction-driven CNN processor to support versatile ECG-based application. (2) A Processing element (PE) array design that simultaneously considers parallelism and data reuse. (3) An activation unit based on the CORDIC algorithm, supporting both Tanh and Sigmoid computations. The design has been implemented using 110 nm CMOS process technology, occupying a die area of 1.35 mm2 with 12.94 µW power consumption. It has been demonstrated with two typical ECG AI applications, including two-class (i.e., normal/abnormal) classification and five-class classification. The proposed 1-D CNN algorithm performs with a 97.95% accuracy for the two-class classification and 97.9% for the five-class classification, respectively.

Gene Reprogramming Armed Macrophage Membrane-Camouflaged Nanoplatform Enhances Bionic Targeted Drug Delivery to Solid Tumor for Synergistic Therapy.

Efficient drug delivery to solid tumors remains a challenge. HER2-positive (HER2+) tumors are an aggressive cancer subtype with a resistance to therapy, high risk of relapse, and poor prognosis. Although nanomedicine technology shows obvious advantages in tumor treatment, its potential clinical translation is still impeded by the unsatisfactory delivery and therapeutic efficacy. In this study, a gene reprogramming macrophage membrane-encapsulated drug-loading nanoplatform was developed for HER2+ cancer therapy based on the co-assembly of poly (lactic-co-glycolic acid) (PLGA) nanoparticles and engineered modified macrophage membranes. In this nanoplatform, near-infrared (NIR) fluorescent dye ICG or chemotherapeutic drug doxorubicin (DOX) was loaded into the PLGA cores, and an anti-HER2 affibody was stably expressed on the membrane of macrophages. In comparison to the nanoparticles with conventional macrophage membrane coating, the ICG/DOX@AMNP nanoparticles armed with anti-HER2 affibody showed excellent HER2-targeting ability both in vitro and in vivo. Small animal imaging studies confirmed the improved pharmacokinetics of drug delivery and specific distribution of the ICG/DOX@AMNPs in HER2+ tumors. Mechanistically, compared with DOX@NPs or DOX@MNPs nanoparticles, DOX@AMNPs exhibited synergistic inhibition of HER2+ cancer cells or mice tumor growth by inducing apoptosis and blocking the PI3K/AKT signaling pathway. Altogether, this study proposes a promising biomimetic nanoplatform for the efficient targeted delivery of chemotherapeutic agents to HER2+ tumors, demonstrating its great potential for solid tumor therapy.

Advanced non-small-cell lung cancer treated with first-line pembrolizumab plus chemotherapy: tumor response dynamics as a marker for survival.

OBJECTIVES: The study investigated tumor burden dynamics on computed tomography (CT) scans in patients with advanced non-small-cell lung cancer (NSCLC) during first-line pembrolizumab plus chemotherapy, to provide imaging markers for overall survival (OS). METHODS: The study included 133 patients treated with first-line pembrolizumab plus platinum-doublet chemotherapy. Serial CT scans during therapy were assessed for tumor burden dynamics during therapy, which were studied for the association with OS. RESULTS: There were 67 responders, with overall response rate of 50%. The tumor burden change at the best overall response ranged from - 100.0% to + 132.1% (median of - 30%). Higher response rates were associated with younger age (p < 0.001) and higher programmed cell death-1 (PD-L1) expression levels (p = 0.01). Eighty-three patients (62%) showed tumor burden below the baseline burden throughout therapy. Using an 8-week landmark analysis, OS was longer in patients with tumor burden below the baseline burden in the first 8 weeks than in those who experienced ≥ 0% increase (median OS: 26.8 vs. 7.6 months, hazard ratio (HR): 0.36, p < 0.001). Tumor burden remained below their baseline throughout therapy was associated with significantly reduced hazards of death (HR: 0.72, p = 0.03) in the extended Cox models, after adjusting for other clinical variables. Pseudoprogression was noted in only one patient (0.8%). CONCLUSIONS: Tumor burden staying below the baseline burden throughout the therapy was predictive of prolonged overall survival in patients with advanced NSCLC treated with first-line pembrolizumab plus chemotherapy, and may be used as a practical marker for therapeutic decisions in this widely used combination regimen. CLINICAL RELEVANCE STATEMENT: The analysis of tumor burden dynamics on serial CT scans in reference to the baseline burden can provide an additional objective guide for treatment decision making in patients treated with first-line pembrolizumab plus chemotherapy for their advanced NSCLC. KEY POINTS: • Tumor burden remaining below baseline burden during therapy predicted longer survival during first-line pembrolizumab plus chemotherapy. • Pseudoprogression was noted in 0.8%, demonstrating the rarity of the phenomenon. • Tumor burden dynamics may serve as an objective marker for treatment benefit to guide treatment decisions during first-line pembrolizumab plus chemotherapy.

Genotype by Temperature Interaction for Plasma Physiological Indexes in Turbot (Scophthalmus maximus) under Acute Heat Stress─Exploring a Method for Screening Physiological Biomarkers of Nontoxic Stress in Aquatic Environments.

This paper presents a method for exploring the genetic mechanism underlying the plasma physiological indexes under heat stress in aquatic environments and for screening reliable stress biomarkers based on split-split-plot analysis (SSP), additive main effects and multiplicative interaction (AMMI) analysis, and genotype main effects and genotype × environment interaction (GGE) biplot analysis. The methodology developed was illustrated by applying it to a specific turbot heat stress case study. Five plasma physiological indexes (epinephrine, cortisol, alkaline phosphatase, superoxide dismutase, and blood glucose levels) were measured in turbot (Scophthalmus maximus) under acute heat stress at four temperatures (18, 21, 24, and 27 °C) for various exposure times (3, 6, 9, 12, 24, 48, and 72 h). The SSP analysis showed that exposure time and temperature × gene interactions had significant (P < 0.01) effects on the activity/content of turbot plasma physiological indexes. The AMMI analysis showed the following: (1) that at each exposure time, the genotype effect > the genotype × temperature interaction > the temperature effect; (2) that during the whole experiment, the change trend of the contribution of the genotype × temperature interactions was similar to that of the temperature effect, and the changing trends of the contributions of the genotype × temperature interaction and the genotype effect were clearly completely reversed; and (3) that the 3-24-h period was the key period for the changes in the physiological indexes due to acute heat stress. The GGE biplot analysis showed that blood glucose and cortisol levels were reliable biomarkers and could be used as early warning markers for numerical simulations of physiological behavior.

Robust ERα-Targeted Near-Infrared Fluorescence Probe for Selective Hydrazine Imaging in Breast Cancer.

Breast cancer is the most common malignancy in women and may become worse when a high concentration of hydrazine is absorbed from the environment or drug metabolite. Therefore, rapid and sensitive detection of hydrazine in vivo is beneficial for people's health. In this work, a novel estrogen receptor α (ERα)-targeted near-infrared fluorescence probe was designed to detect hydrazine levels. The probe showed good ERα affinity and an excellent fluorescence response toward hydrazine. Selectivity experiments demonstrated that the probe had a strong anti-interference ability. Mechanistic studies, including mass spectrometry (MS) and density functional theory (DFT) calculation, indicated that intermolecular charge transfer (ICT) progress was hindered when the probe reacted with hydrazine, resulting in fluorescent quenching. In addition, the probe could selectively bind to MCF-7 breast cancer cells with excellent biocompatibility. The in vivo and ex vivo imaging studies demonstrated that the probe could rapidly visualize hydrazine with high contrast in MCF-7 xenograft tumors. Therefore, this probe can serve as a potential tool to robustly monitor hydrazine levels in vivo.

Genotype × ammonia interaction effects on plasma physiological indexes in turbot (Scophthalmus maximus) cultured under acute ammonia stress for different periods of times.

We evaluated six plasma physiological indexes (epinephrine, cortisol, alkaline phosphatase, superoxide dismutase, reduced glutathione, and blood glucose) in turbot (Scophthalmus maximus) cultured in five ammonia concentrations (30.28, 35.90, 42.56, 50.47, and 59.82) at different exposure times (4, 8, 12, 24, and 48 h). Then, we conducted additive main effects and multiplicative interaction (AMMI) and genotype main effects and genotype × environment interaction (GGE) biplot analyses to analyze the genotype × ammonia interaction effects on the plasma physiological indexes. The AMMI analysis results revealed that the contributions of ammonia effect first decreased sharply (4-8 h), then decreased slowly (8-24 h), and then increased slowly (24-48 h). The contributions of genotype effect first decreased sharply (4-8 h), then increased slowly (8-24 h), and then decreased slowly (24-48 h). The contributions of genotype × ammonia interactions showed a sharp rise (4-8 h), a sharp decline (8-12 h), a slow decline (12-24 h), and finally a slow increase (24-48 h). The GGE biplot analysis revealed that alkaline phosphatase and reduced glutathione contents/activities are reliable biomarkers that can be used to establish an online early warning system for behavior numerical simulation.

Structural and functional characterization of turbot pparγ: Activation during high temperature and regulation of lipid metabolism.

Transcription factors of the peroxisome proliferator-activated receptor gamma (pparγ) is a ligand-activated receptor that plays key roles in lipid metabolism and inflammation. In this study, we cloned the pparγ cDNA of turbot (Scophthalmus maximus). It has a 1659 bp coding sequence (CDS) and encodes 552 amino acids. The deduced PPARγ protein of turbot contains two highly conserved domains, a C4-type zinc finger, a nuclear hormone receptor DNA-binding region signature, and a HOLI domain (ligand-binding domain of hormone receptors) identical to that of in other species. qPCR results showed that the expression level of pparγ and the expression of the fatty acid transporters fatp and cd36 were significantly increased under high-temperature stress. This indicates that high temperatures activate the transcriptional activity of pparγ, and lipid metabolism plays an important role in turbot under high-temperature stress. In addition, RNA interference was used to explore the regulation of pparγ on lipid metabolism of turbot at high temperatures. The results showed that the mRNA level of pparγ was significantly decreased. After the expression level of pparγ was inhibited, the expression levels of fatp and cd36 were significantly decreased. At the same time, GW9662 (a pparγ antagonist) was used to inhibit pparγ activity in turbot kidney cells, and fatp and cd36 gene expressions were detected. The mRNA expression levels of pparγ, fatp, and cd36 were significantly decreased. Our results suggest that high temperatures activate pparγ in turbot and that pparγ regulates lipid transport and maintains lipid metabolism homeostasis through positive regulation of the expression of downstream genes fatp and cd36. This study further elucidates that the pparγ-mediated signaling pathway may play an important role in regulating lipid metabolism during heat stress in teleost fish.

Genetic Mechanism of Tissue-Specific Expression of PPAR Genes in Turbot (Scophthalmus maximus) at Different Temperatures.

In this study, we used PCR to measure the levels of the peroxisome proliferator activated receptor genes PPARα1, PPARα2, PPARß, and PPARγ in the intestine, liver, gill, heart, kidney, brain, muscle, spleen, skin, and stomach of turbot (Scophthalmus maximus) cultured under different temperature conditions (14, 20, 23, 25, and 28 °C). We used split-split-plot (SSP) analysis of variance, additive main effects and multiplicative interaction (AMMI) analysis, and genotype main effects and genotype × environment interaction (GGE) biplot analysis to evaluate the genotype × tissue interaction effects on gene expression. The results of the SSP analysis of variance showed that temperature and tissue × gene have highly significant (p < 0.01) effect on the expression of S. maximus PPAR genes. The AMMI analysis results revealed that the expression of PPAR genes at the appropriate temperature (14 °C) mainly depended on genotype × tissue interaction and tissue effects. Under stress temperatures, genotype effects, tissue effects, and genotype × tissue interaction, all had significant effects on the expression of PPAR genes. The contribution of the genotype effect slowly increased with increasing temperature; it increased faster at 20 °C and then slowly declined at 25 °C. The contribution of the tissue effect slowly increased from 14 to 20 °C, where it sharply decreased, and then it stabilized after a slight fluctuation. The contribution of the genotype × tissue interaction effect showed a fluctuating upward trend throughout the experiment, and it had a significant impact on PPAR gene expression. The key temperature at which the three effects changed was 20 °C, indicating that it is the limit temperature for active lipid metabolism under high-temperature stress. The GGE biplot analysis results showed that under suitable water temperature, the expression difference of PPAR genes in the liver was the largest; at 20 and 23 °C, the expression difference in the gill was the largest; and at 25 and 28 °C, the expression difference in the brain was the largest. Overall, our results suggest that the mechanism responsible for PPAR gene expression under the three high temperatures (23, 25, and 28 °C) was relatively consistent, but it differed from that at 20 °C.

Dissection of genotype × tissue interactions for immunological factors in turbot (Scophthalmus maximus) infected with Vibrio anguillarum.

Seven immune factors, lysozyme, hepcidin, heat-shock protein (HSP) 70, HSP90, immunoglobulin M, C-type lectin, and Lily-type lectin, were measured by PCR in the livers, spleens, and head kidneys of turbot infected with Vibrio anguillarum. Additive main effects and multiplicative interaction (AMMI) and genotype main effects and genotype × environment interaction (GGE) biplot analysis were used to analyze genotype × tissue interactions for immunological factors. The AMMI analysis revealed that immune factor expression was significantly affected by genotype, tissue, and genotype × tissue interactions. Genotype (65.85%) was the major contributor to the total variation in immune factor expression in comparison to tissue effects (7.54%) and genotype × tissue interactions (12.52%). GGE biplot analysis revealed differences in the ranking of the seven immune factors in the three tissues; head kidney possessed the strongest ability to distinguish the seven immune factors. The test tissue locations were divided into liver-spleen and head kidneys regions; HSP70 was expressed the highest in the liver-spleen regions, and lysozyme had the highest expression in the head kidney region. Overall, HSP70 and HSP90 had the best expression and stability in the three tissues.

Genetic parameter estimates for three antioxidant factors in cultured Takifugu rubripes.

Genetic parameters of three antioxidant factors, including superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPX), were evaluated in liver samples from 840 Takifugu rubripes individuals from 28 full-sib families. Heritability values of SOD, CAT, and GPX were 0.17, 0.18, and 0.14, respectively, and the full-sib family effect values for these antioxidant factors were 0.46, 0.47, and 0.49, respectively. The ranges of phenotypic and genetic correlations among the three immune factors were 0.748-0.848 and 0.726-0.806, respectively. Considering the low heritability and high full-sib family effect of the three antioxidant indexes, the use of both genome-wide selection and clustered regularly interspaced short palindromic repeats (CRISPR) is promising for genetically improving the three antioxidant indexes in cultured fish. In addition, given positive phenotypic and genetic correlations among the three antioxidant enzymes SOD, CAT and GPX, the antioxidant competence of Takifugu rubripes can be improved by genetically improving these three antioxidant traits via multi-trait integrated breeding technology or indirect selection.

Effectiveness of anisodamine for the treatment of critically ill patients with septic shock: a multicentre randomized controlled trial.

BACKGROUND: Septic shock is characterized by an uncontrolled inflammatory response and microcirculatory dysfunction. There is currently no specific agent for treating septic shock. Anisodamine is an agent extracted from traditional Chinese medicine with potent anti-inflammatory effects. However, its clinical effectiveness remains largely unknown. METHODS: In a multicentre, open-label trial, we randomly assigned adults with septic shock to receive either usual care or anisodamine (0.1-0.5 mg per kilogram of body weight per hour), with the anisodamine doses adjusted by clinicians in accordance with the patients' shock status. The primary end point was death on hospital discharge. The secondary end points were ventilator-free days at 28 days, vasopressor-free days at 28 days, serum lactate and sequential organ failure assessment (SOFA) score from days 0 to 6. The differences in the primary and secondary outcomes were compared between the treatment and usual care groups with the χ2 test, Student's t test or rank-sum test, as appropriate. The false discovery rate was controlled for multiple testing. RESULTS: Of the 469 patients screened, 355 were assigned to receive the trial drug and were included in the analyses-181 patients received anisodamine, and 174 were in the usual care group. We found no difference between the usual care and anisodamine groups in hospital mortality (36% vs. 30%; p = 0.348), or ventilator-free days (median [Q1, Q3], 24.4 [5.9, 28] vs. 26.0 [8.5, 28]; p = 0.411). The serum lactate levels were significantly lower in the treated group than in the usual care group after day 3. Patients in the treated group were less likely to receive vasopressors than those in the usual care group (OR [95% CI] 0.84 [0.50, 0.93] for day 5 and 0.66 [0.37, 0.95] for day 6). CONCLUSIONS: There is no evidence that anisodamine can reduce hospital mortality among critically ill adults with septic shock treated in the intensive care unit. Trial registration ClinicalTrials.gov ( NCT02442440 ; Registered on 13 April 2015).

Cellular FADD-like IL-1ß-converting enzyme-inhibitory protein attenuates myocardial ischemia/reperfusion injury via suppressing apoptosis and autophagy simultaneously.

BACKGROUND AND AIMS: Myocardial ischemia/reperfusion injury (MI/RI) is a result of coronary revascularization, and often increases cell apoptosis and autophagy. Downregulated cellular FADD-like-IL-1ß-converting enzyme-inhibitory protein (cFLIP) was associated with development of several myocardial diseases, whether overexpression of cFLIP can attenuate MI/RI remains unclear. This study aimed to determine the effects of cFLIP on apoptosis and autophagy in MI/RI. METHODS AND RESULTS: Ischemia/reperfusion (I/R) rat model and hypoxia/reoxygenation (H/R) cardiomyocytes model were established. Both I/R injury and H/R injury down-regulated expression of two cFLIP isoforms (cFLIPL and cFLIPS), and instigated apoptosis and autophagy simultaneously. Overexpression of cFLIPL and/or cFLIPS led to a significant increase in cardiomyocytes viability in vitro, and also reduced the myocardial infarct volume in vivo, these changes were associated with suppressed apoptosis and autophagy. Mechanistically, overexpression of cFLIP significantly downregulated pro-apoptotic molecules (Caspase-3, -8, -9), and pro-autophagic molecules (Beclin-1 and LC3-II). Moreover, cFLIP significantly suppressed activity of NF-κB pathway to upregulate the expression of Bcl-2, which is the molecular of interplay of apoptosis and autophagy. CONCLUSION: Overexpression of cFLIP significantly attenuated MI/RI both in vivo and vitro via suppression of apoptosis and lethal autophagy. cFLIP can suppress activity of NF-κB pathway, and further upregulated expression of Bcl-2.

Genetic parameters of seven immune factors in turbot (Scophthalmus maximus) infected with Vibrio anguillarum.

In this study, 1,800 turbot (Scophthalmus maximus) individuals from 30 full-sib families were experimentally infected with Vibrio anguillarum, and the expression levels of the immune factors lysozyme, hepcidin, heat-shock protein 70 (HSP70), HSP90, immunoglobulin M (IgM), C-type lectin and Lily-type lectin in the liver were measured by real-time PCR. Heritability values of the seven immune factors were 0.289 ± 0.087, 0.092 ± 0.024, 0.282 ± 0.043, 0.244 ± 0.027, 0.343 ± 0.081, 0.092 ± 0.011 and 0.084 ± 0.009, respectively. The ranges of phenotypic, genetic and environmental correlations were -0.889 to 0.759, -0.841 to 0.888 and -0.919 to 0.883, respectively. The heritability values of HSP70, HSP90 and IgM were moderate, and the genetic correlations between HSP70, HSP90 and IgM were moderate to highly positive, which suggests that the immunocompetence of turbot against V. anguillarum can be improved by genetically improving these three immune characters via multi-trait integrated breeding technology or indirect selection.

A Deep Learning-Based Electromagnetic Signal for Earthquake Magnitude Prediction.

The influence of earthquake disasters on human social life is positively related to the magnitude and intensity of the earthquake, and effectively avoiding casualties and property losses can be attributed to the accurate prediction of earthquakes. In this study, an electromagnetic sensor is investigated to assess earthquakes in advance by collecting earthquake signals. At present, the mainstream earthquake magnitude prediction comprises two methods. On the one hand, most geophysicists or data analysis experts extract a series of basic features from earthquake precursor signals for seismic classification. On the other hand, the obtained data related to earth activities by seismograph or space satellite are directly used in classification networks. This article proposes a CNN and designs a 3D feature-map which can be used to solve the problem of earthquake magnitude classification by combining the advantages of shallow features and high-dimensional information. In addition, noise simulation technology and SMOTE oversampling technology are applied to overcome the problem of seismic data imbalance. The signals collected by electromagnetic sensors are used to evaluate the method proposed in this article. The results show that the method proposed in this paper can classify earthquake magnitudes well.

Molecular characterization of ubiquitin-conjugating enzyme gene ube2h and siRNA-mediated regulation on targeting p53 in turbot, Scophthalmus maximus.

Ubiquitin-conjugating enzymes are key factors in the ubiquitin proteasome pathway (UPP), which play key roles in ubiquitination. These enzymes affect the efficiency of UPP during stress conditions. P53 has important control of cell cycle arrest and apoptosis in response to cellular stress; these modifications are critical for the stability and transcriptional activity of p53 as the protein activates downstream target genes that dictate the cellular response. However, few studies have investigated the effects of thermal stress in turbot (Scophthalmus maximus), specifically the UPP signaling pathway, and the crosstalk between the ube2h and p53. In this study, the rapid amplification of cDNA ends was used to obtain a full-length cDNA of the turbot UBE2H gene (Sm-ube2h) and perform bioinformatics analysis. Our results showed that the cDNA of the Sm-ube2h was 718 bp in length, encoding a 189 amino acid protein, with a theoretical isoelectric point of 4.77. It also contained a catalytic (UBCc) domain. Expression of Sm-ube2h in different tissues was detected and quantified by qPCR, which was highest in the spleen and lowest in the liver. We also investigated the Sm-ube2h expression profiles in the liver and heart after thermal stress, and changes in Sm-ube2h and p53 under thermal stress, upon RNA interference. Our data speculated that Sm-ube2h and p53 exhibited antagonistic effects under normal temperature conditions after ube2h interference, but displayed synergistic effects under thermal stress, suggesting the crosstalk between UPP and p53 signaling pathway. Our results improved our understanding of the underlying molecular mechanism of thermal tolerance in turbot.

Statistical Analysis of the Relationship between AETA Electromagnetic Anomalies and Local Earthquakes.

To verify the relationship between AETA (Acoustic and Electromagnetics to Artificial Intelligence (AI)) electromagnetic anomalies and local earthquakes, we have performed statistical studies on the electromagnetic data observed at AETA station. To ensure the accuracy of statistical results, 20 AETA stations with few data missing and abundant local earthquake events were selected as research objects. A modified PCA method was used to obtain the sequence representing the signal anomaly. Statistical results of superposed epoch analysis have indicated that 80% of AETA stations have significant relationship between electromagnetic anomalies and local earthquakes. These anomalies are more likely to appear before the earthquakes rather than after them. Further, we used Molchan's error diagram to evaluate the electromagnetic signal anomalies at stations with significant relationships. All area skill scores are greater than 0. The above results have indicated that AETA electromagnetic anomalies contain precursory information and have the potential to improve local earthquake forecasting.

A Secreted Reporter for Blood Monitoring of Pyroptotic Cell Death.

Pyroptotic cell death is a phenomenon that runs through all life activities and plays an important role in physiological and pathological processes of the body's metabolism. It is of big biological significance to understand the phenomenon and nature of cell pyroptosis. In the process of cell pyroptosis, the pore-forming effector gasdermin D (GSDMD) is cleaved to form oligomers, which are inserted into the cell membrane, causing rapid cell death. However, the effective cell death induced by GSDMD complicates our ability to understand the behavior of pyroptosis. In this work, we performed molecular mutagenesis to develop a genetically encoded pyroptotic reporter, where a secreted Gaussia luciferase (Gluc) was strategically placed in the p30-p20 tolerated junction of GSDMD to support natural pyrophosphorylation and promote live imaging of cell pyroptosis. In addition, we demonstrated that this fused Gluc-GSDMD reporter executed inflammatory body-dependent pyroptosis in response to extracellular stimuli, and that the lysed p30-GSDMD can be secreted out of the cell and can be detected in the culture medium and animal blood. Therefore, our study provides a valuable tool that not only noninvasive and real-time monitoring of cell pyroptosis, but also affords a high-throughput functional screening of pyroptosis-targeted compounds in cultured cells and animal models.

Myo-inositol enhances the low-salinity tolerance of turbot (Scophthalmus maximus) by modulating cortisol synthesis.

Myo-inositol is a major intracellular osmolyte that can be accumulated to protect cells from a variety of stresses, including fluctuations in the osmolality of the environment, and cortisol is thought to be an osmotic hormone in teleost fish. In this study, dietary myo-inositol resulted in increased Na+-K+-ATPase activity and gene expression of partial ion channel genes and prolonged survival time of turbot (Scophthalmus maximus) under low salinity. The cortisol regulated by dietary myo-inositol also was correlated with these outcomes. The optimal concentrations of cortisol stimulated gill Na+-K+-ATPase activity and increased the expression of ion channel genes to enhance low salinity tolerance, as indicated by longer survival time under low salinity. When cortisol level was suppressed, myo-inositol failed to increase the survival time of turbot under low salinity, and strong correlations between cortisol concentration and Na+-K+-ATPase activity, expression of partial ion channel genes, and survival time of turbot were detected. These results showed that myo-inositol enhanced the low salinity tolerance of turbot by modulating cortisol synthesis.

Integrated molecular profiling of juvenile myelomonocytic leukemia.

Juvenile myelomonocytic leukemia (JMML), a rare and aggressive myelodysplastic/myeloproliferative neoplasm that occurs in infants and during early childhood, is characterized by excessive myelomonocytic cell proliferation. More than 80% of patients harbor germ line and somatic mutations in RAS pathway genes (eg, PTPN11, NF1, NRAS, KRAS, and CBL), and previous studies have identified several biomarkers associated with poor prognosis. However, the molecular pathogenesis of 10% to 20% of patients and the relationships among these biomarkers have not been well defined. To address these issues, we performed an integrated molecular analysis of samples from 150 JMML patients. RNA-sequencing identified ALK/ROS1 tyrosine kinase fusions (DCTN1-ALK, RANBP2-ALK, and TBL1XR1-ROS1) in 3 of 16 patients (18%) who lacked canonical RAS pathway mutations. Crizotinib, an ALK/ROS1 inhibitor, markedly suppressed ALK/ROS1 fusion-positive JMML cell proliferation in vitro. Therefore, we administered crizotinib to a chemotherapy-resistant patient with the RANBP2-ALK fusion who subsequently achieved complete molecular remission. In addition, crizotinib also suppressed proliferation of JMML cells with canonical RAS pathway mutations. Genome-wide methylation analysis identified a hypermethylation profile resembling that of acute myeloid leukemia (AML), which correlated significantly with genetic markers with poor outcomes such as PTPN11/NF1 gene mutations, 2 or more genetic mutations, an AML-type expression profile, and LIN28B expression. In summary, we identified recurrent activated ALK/ROS1 fusions in JMML patients without canonical RAS pathway gene mutations and revealed the relationships among biomarkers for JMML. Crizotinib is a promising candidate drug for the treatment of JMML, particularly in patients with ALK/ROS1 fusions.