Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS.

Introduction: Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. Methods: Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. Results: A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. Discussion: This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

In vitro studies on the effects of cryopreserved platelet-rich plasma on cells related to wound healing.

Platelet-rich plasma (PRP) holds promise as a therapeutic modality for wound healing; however, immediate utilization encounters challenges related to volume, concentration, and consistency. Cryopreservation emerges as a viable solution, preserving PRP's bioactive components and extending its shelf life. This study explores the practicality and efficacy of cryopreserved platelet-rich plasma (cPRP) in wound healing, scrutinizing both cellular mechanisms and clinical implications. Fresh PRP and cPRP post freeze-thaw underwent assessment in macrophage, fibroblast, and endothelial cell cultures. The impact of cPRP on active component release and cell behavior pertinent to wound healing was evaluated. Varied concentrations of cPRP (1%, 5%, 10%) were examined for their influence on cell polarization, migration, and proliferation. The results showed minimal changes in cPRP's IL-1ß levels, a slight decrease in PDGF-BB, and superior effects on macrophage M2 polarization and fibroblast migration, while no statistical significance was observed in endothelial cell angiogenesis and proliferation. Remarkably, 5% PRP exhibited the most significant stimulation among all cPRP concentrations, notably impacting cell proliferation, angiogenesis, and migration. The discussion underscores that cPRP maintains platelet phenotype and function over extended periods, with 5% cPRP offering the most favorable outcomes, providing a pragmatic approach for cold storage to extend post-thaw viability and amplify therapeutic effects.

What is the context? Platelet-rich plasma (PRP) is a potential bioactive material for wound healing, but using it immediately faces issues like volume, concentration, and consistency.Low-temperature freezing is a method employed to preserve PRP. However, the current understanding of the effects of the freezing-thawing process on the components of PRP and its impact on cells relevant to wound healing remains unclear.What is new? This study explores the feasibility and effectiveness of using cryopreserved PRP at −80°C for promoting wound healing. This research stands out for its focus on cellular responses and practical implications in therapeutic contexts.To understand their distinct impact on different cell types relevant to wound healing, the study meticulously examined various final concentrations of cPRP (1%, 5%, 10%).The study identified the superior effects of 5% cPRP on crucial cellular activities, notably in cell polarization, proliferation, angiogenesis, and migration.What is the impact? Low-temperature freezing can be considered an effective method for PRP preservation.Some bioactive components in cPRP exhibit subtle changes; however, these changes result in better effects on certain cell types related to healing.The study illustrates that all concentrations of cPRP effectively enhance cell proliferation, migration, and differentiation, emphasizing the comparable efficacy of cryopreserved PRP to non-cryopreserved PRP.

Discovery of novel melatonin-mydroxyquinoline hybrids as multitarget strategies for Alzheimer's disease therapy.

Alzheimer's disease (AD) is a neurodegenerative disease that seriously affects human health, and current treatment strategies are far from meeting clinical needs. Inspired by multi-target drug design strategies, a series of novel natural products-based melatonin-hydroxyquinoline hybrids were designed and synthesized, targeting anti-oxidation and metal-chelating at the same time. Most of the compounds showed significant oxygen radical absorbance capacity and Aß1-42 aggregation inhibition. Moreover, the compounds possess good blood-brain barrier permeability. 6b and 6c have a good ability to alleviate oxidative stress induced by hydrogen peroxide. 6b and 6c possess metal-chelating properties with the chelation ratio being 2:1. Furthermore, 6b can significantly mitigate metal-induced Aß aggregation. This work may provide a new multi-target treatment strategy for Alzheimer's disease.

PCBP1 interacts with the HTLV-1 Tax oncoprotein to potentiate NF-κB activation.

Human T-cell leukemia virus type 1 (HTLV-1) is the etiological agent of adult T-cell leukemia/lymphoma. The HTLV-1 Tax constitutively activates nuclear factor-κB (NF-κB) to promote the survival and transformation of HTLV-1-infected T cells. Despite extensive study of Tax, how Tax interacts with host factors to regulate NF-κB activation and HTLV-1-driven cell proliferation is not entirely clear. Here, we showed that overexpression of Poly (rC)-binding protein 1 (PCBP1) promoted Tax-mediated IκB kinase (IKK)-NF-κB signaling activation, whereas knockdown of PCBP1 attenuated Tax-dependent IKK-NF-κB activation. However, Tax activation of HTLV-1 long terminal repeat was unaffected by PCBP1. Furthermore, depletion of PCBP1 led to apoptosis and reduced proliferation of HTLV-1-transformed cells. Mechanistically, PCBP1 interacted and co-localized with Tax in the cytoplasm, and PCBP1 KH3 domain was indispensable for the interaction between PCBP1 and Tax. Moreover, PCBP1 facilitated the assembly of Tax/IKK complex. Collectively, our results demonstrated that PCBP1 may exert an essential effect in Tax/IKK complex combination and subsequent NF-κB activation, which provides a novel insight into the pathogenetic mechanisms of HTLV-1.

miR-329b-5p Affects Sheep Intestinal Epithelial Cells against Escherichia coli F17 Infection.

Diarrhea is the most common issue in sheep farms, typically due to pathogenic Escherichia coli (E. coli) infections, such as E. coli F17. microRNA, a primary type of non-coding RNA, has been shown to be involved in diarrhea caused by pathogenic E. coli. To elucidate the profound mechanisms of miRNA in E. coli F17 infections, methods such as E. coli F17 adhesion assay, colony counting assay, relative quantification of bacterial E. coli fimbriae gene expression, indirect immune fluorescence (IF), Cell Counting Kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU), Western blotting (WB), and scratch assay were conducted to investigate the effect of miR-329b-5p overexpression/knock-down on E. coli F17 susceptibility of sheep intestinal epithelial cells (IECs). The findings indicated that miR-329b-5p enhances the E. coli F17 resistance of sheep IECs to E.coli F17 by promoting adhesion between E. coli F17 and IEC, as well as IEC proliferation and migration. In summary, miR-329b-5p plays a crucial role in the defense of sheep IECs against E. coli F17 infection, providing valuable insights into its mechanism of action.

GDSL Lipase Gene HTA1 Negatively Regulates Heat Tolerance in Rice Seedlings by Regulating Reactive Oxygen Species Accumulation.

High temperature is a significant environmental stress that limits plant growth and agricultural productivity. GDSL lipase is a hydrolytic enzyme with a conserved GDSL sequence at the N-terminus, which has various biological functions, such as participating in plant growth, development, lipid metabolism, and stress resistance. However, little is known about the function of the GDSL lipase gene in the heat tolerance of rice. Here, we characterized a lipase family protein coding gene HTA1, which was significantly induced by high temperature in rice. Rice seedlings in which the mutant hta1 was knocked out showed enhanced heat tolerance, whereas the overexpressing HTA1 showed more sensitivity to heat stress. Under heat stress, hta1 could reduce plant membrane damage and reactive oxygen species (ROS) levels and elevate the activity of antioxidant enzymes. Moreover, real-time quantitative PCR (RT-qPCR) analysis showed that mutant hta1 significantly activated gene expression in antioxidant enzymes, heat response, and defense. In conclusion, our results suggest that HTA1 negatively regulates heat stress tolerance by modulating the ROS accumulation and the expression of heat-responsive and defense-related genes in rice seedlings. This research will provide a valuable resource for utilizing HTA1 to improve crop heat tolerance.

Ent-eudesmane sesquiterpenoids with anti-neuroinflammatory activity from the marine-derived fungus Eutypella sp. F0219.

In this study, twenty-three ent-eudesmane sesquiterpenoids (1-23) including fifteen previously undescribed ones, named eutypelides A-O (1-15) were isolated from the marine-derived fungus Eutypella sp. F0219. Their planar structures and relative configurations were established by HR-ESIMS and extensive 1D and 2D NMR investigations. The absolute configurations of the previously undescribed compounds were determined by single-crystal X-ray diffraction analyses, modified Mosher's method, and ECD calculations. Structurally, eutypelide A (1) is a rare 1,10-seco-ent-eudesmane, whereas 2-15 are typically ent-eudesmanes with 6/6/-fused bicyclic carbon nucleus. The anti-neuroinflammatory activity of all isolated compounds (1-23) was accessed based on their ability to NO production in LPS-stimulated BV2 microglia cells. Compound 16 emerged as the most potent inhibitor. Further mechanistic investigation revealed that compound 16 modulated the inflammatory response by decreasing the protein levels of iNOS and increasing ARG 1 levels, thereby altering the iNOS/ARG 1 ratio and inhibiting macrophage polarization. qRT-PCR analysis showed that compound 16 reversed the LPS-induced upregulation of pro-inflammatory cytokines, including iNOS, TNF-α, IL-6, and IL-1ß, at both the transcriptional and translational levels. These effects were linked to the inhibition of the NF-κB pathway, a key regulator of inflammation. Our findings suggest that compound 16 may be a potential structure basis for developing neuroinflammation-related disease therapeutic agents.

MulTFBS: A Spatial-Temporal Network with Multichannels for Predicting Transcription Factor Binding Sites.

Revealing the mechanisms that influence transcription factor binding specificity is the key to understanding gene regulation. In previous studies, DNA double helix structure and one-hot embedding have been used successfully to design computational methods for predicting transcription factor binding sites (TFBSs). However, DNA sequence as a kind of biological language, the method of word embedding representation in natural language processing, has not been considered properly in TFBS prediction models. In our work, we integrate different types of features of DNA sequence to design a multichanneled deep learning framework, namely MulTFBS, in which independent one-hot encoding, word embedding encoding, which can incorporate contextual information and extract the global features of the sequences, and double helix three-dimensional structural features have been trained in different channels. To extract sequence high-level information effectively, in our deep learning framework, we select the spatial-temporal network by combining convolutional neural networks and bidirectional long short-term memory networks with attention mechanism. Compared with six state-of-the-art methods on 66 universal protein-binding microarray data sets of different transcription factors, MulTFBS performs best on all data sets in the regression tasks, with the average R2 of 0.698 and the average PCC of 0.833, which are 5.4% and 3.2% higher, respectively, than the suboptimal method CRPTS. In addition, we evaluate the classification performance of MulTFBS for distinguishing bound or unbound regions on TF ChIP-seq data. The results show that our framework also performs well in the TFBS classification tasks.

Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures.

The metabolic signature identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and improve patient survival. Here, we combined an untargeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry and the machine learning approach to analyze metabolites in 173 pairs of cancer samples and matched normal tissue samples to build robust metabolic signature models for diagnostic purposes. Screening and independent validation of metabolic signatures from colorectal cancers via machine learning methods (Logistic Regression_L1 for feature selection and eXtreme Gradient Boosting for classification) was performed to generate a panel of seven signatures with good diagnostic performance (the accuracy of 87.74%, sensitivity of 85.82%, and specificity of 89.66%). Moreover, seven signatures were evaluated according to their ability to distinguish between cancer and normal tissues, with the metabolic molecule PC (30:0) showing good diagnostic performance. In addition, genes associated with PC (30:0) were identified by multiomics analysis (combining metabolic data with transcriptomic data analysis) and our results showed that PC (30:0) could promote the proliferation of colorectal cancer cell SW480, revealing the correlation between genetic changes and metabolic dysregulation in cancer. Overall, our results reveal potential determinants affecting metabolite dysregulation, paving the way for a mechanistic understanding of altered tissue metabolites in colorectal cancer and design interventions for manipulating the levels of circulating metabolites.

Genomic Inbreeding and Runs of Homozygosity Analysis of Cashmere Goat.

Cashmere goats are valuable genetic resources which are famous worldwide for their high-quality fiber. Runs of homozygosity (ROHs) have been identified as an efficient tool to assess inbreeding level and identify related genes under selection. However, there is limited research on ROHs in cashmere goats. Therefore, we investigated the ROH pattern, assessed genomic inbreeding levels and examined the candidate genes associated with the cashmere trait using whole-genome resequencing data from 123 goats. Herein, the Inner Mongolia cashmere goat presented the lowest inbreeding coefficient of 0.0263. In total, we identified 57,224 ROHs. Seventy-four ROH islands containing 50 genes were detected. Certain identified genes were related to meat, fiber and milk production (FGF1, PTPRM, RERE, GRID2, RARA); fertility (BIRC6, ECE2, CDH23, PAK1); disease or cold resistance and adaptability (PDCD1LG2, SVIL, PRDM16, RFX4, SH3BP2); and body size and growth (TMEM63C, SYN3, SDC1, STRBP, SMG6). 135 consensus ROHs were identified, and we found candidate genes (FGF5, DVL3, NRAS, KIT) were associated with fiber length or color. These findings enhance our comprehension of inbreeding levels in cashmere goats and the genetic foundations of traits influenced by selective breeding. This research contributes significantly to the future breeding, reservation and use of cashmere goats and other goat breeds.

The effects of long-term high-altitude exposure on cognition: A meta-analysis.

Long-term high altitudes (HA) exposure's impact on cognition has yielded inconsistent findings in previous research. To address this, we conducted a meta-analysis of 49 studies (6191 individuals) to comprehensively evaluate this effect. Moderating factors such as cognitive task type, altitude (1500-2500 m, 2500-4000 m, and above 4000 m), residential type (chronic and lifelong), adaptation level and demographic factors were analyzed. Cognitive tasks were classified into eight categories: perceptual processes, psychomotor function, long-term memory, working memory, inhibitory control, problem-solving, language, and others. Results revealed a moderate negative effect of HA on cognitive performance (g = -.40, SE =.18, 95% CI = -.76 to -.05). Psychomotor function and long-term memory notably experience the most pronounced decline, while working memory and language skills show moderate decreases due to HA exposure. However, perceptual processes, inhibitory control, and problem-solving abilities remain unaffected. Moreover, residing at altitudes above 4000 m and being a HA immigrant are associated with significant cognitive impairment. In summary, our findings indicate a selective adaptation of cognitive performance to HA conditions.

Innate lymphoid cell subsets in the pathogenesis of primary biliary cholangitis.

BACKGROUND AND AIM: Primary biliary cholangitis (PBC) is an autoimmune liver disease characterized by destructive lymphocytic cholangitis and specific anti-mitochondrial antibodies. Innate lymphoid cells (ILCs) have been reported to play a role in liver homeostasis and autoimmunity. METHODS: We evaluated the features of peripheral ILC1s and ILC3 in patients with PBC and hepatic ILC1 and ILC3 in two different PBC mouse models (dominant-negative transforming growth factor-beta receptor II [dnTGFßRII] and 2-octynoic acid-bovine serum albumin [2OA-BSA]). RESULTS: A total of 115 patients and 18 healthy controls were enrolled in the study. Decreased circulating ILC1/3s were observed in early-stage PBC patients, and the numbers of ILC1/3s were negatively correlated with specific parameters and the proportion of T-helper (Th) 1 and Th17 cells. Reduced numbers of ILC1s were observed in PBC mouse models with different etiologies. ILC1-deficient mice had more severe hepatic inflammation after inducing the 2OA-BSA model. Continuous low-dose injections of lipopolysaccharide (LPS) reduced ILC1 levels in mice, consistent with the lower level of ILC1s in PBC patients with high LPS (> 50 ng/mL), and aggravated hepatic lymphocyte infiltration. CONCLUSION: Patients with PBC had decreased ILC1s, which were negatively correlated with CD4+ T cells. Deficient ILC1 populations led to disease exacerbations in mice. Our results indicated that ILC1s may participate in the pathogenesis of PBC.

Dose-effect of exercise intervention on heart rate variability of acclimatized young male lowlanders at 3,680 m.

This study investigated whether exercise could improve the reduced HRV in an environment of high altitude. A total of 97 young, healthy male lowlanders living at 3,680 m for >1 year were recruited. They were randomized into four groups, of which three performed-low-, moderate-, and high-intensity (LI, MI, HI) aerobic exercise for 4 weeks, respectively. The remaining was the control group (CG) receiving no intervention. For HI, compared to other groups, heart rate (p = 0.002) was significantly decreased, while standard deviation of RR intervals (p < 0.001), SD2 of Poincaré plot (p = 0.046) and the number of successive RR interval pairs that differ by > 50 ms divided by total number of RR (p = 0.032), were significantly increased after intervention. For MI, significantly increase of trigonometric interpolation in NN interval (p = 0.016) was observed after exercise. Further, a decrease in systolic blood pressure (SBP) after high-intensity exercise was found significantly associated with an increase in SD2 (r = - 0.428, p = 0.042). These results indicated that there was a dose effect of different intensities of aerobic exercise on the HRV of acclimatized lowlanders. Moderate and high-intensity aerobic exercise would change the status of the autonomic nervous system (ANS) and decrease the blood pressure of acclimatized lowlanders exposed to high altitude.

Intrinsic tensile ductility in strain hardening multiprincipal element metallic glass.

Traditional metallic glasses (MGs), based on one or two principal elements, are notoriously known for their lack of tensile ductility at room temperature. Here, we developed a multiprincipal element MG (MPEMG), which exhibits a gigapascal yield strength, significant strain hardening that almost doubles its yield strength, and 2% uniform tensile ductility at room temperature. These remarkable properties stem from the heterogeneous amorphous structure of our MPEMG, which is composed of atoms with significant size mismatch but similar atomic fractions. In sharp contrast to traditional MGs, shear banding in our glass triggers local elemental segregation and subsequent ordering, which transforms shear softening to hardening, hence resulting in shear-band self-halting and extensive plastic flows. Our findings reveal a promising pathway to design stronger, more ductile glasses that can be applied in a wide range of technological fields.

The neuroimmune pathway of high-altitude adaptation: influence of erythrocytes on attention networks through inflammation and the autonomic nervous system.

Introduction: Many studies have shown that the functional adaptation of immigrants to high-altitude is closely related to oxygen transport, inflammatory response and autonomic nervous system. However, it remains unclear how human attention changes in response to hypoxia-induced neurophysiological activity during high-altitude exposure. Methods: In the present study, we analyzed the relationship between hypoxic-induced neurophysiological responses and attention networks in 116 immigrants (3,680 m) using an attention network test to simultaneously record electroencephalogram and electrocardiogram in combination with specific routine blood markers. Results: Our analysis revealed that red blood cells exert an indirect influence on the three attention networks, mediated through inflammatory processes and heart rate variability. Discussion: The present study provides experimental evidence for the role of a neuroimmune pathway in determining human attention performance at high- altitude. Our findings have implications for understanding the complex interactions between physiological and neurocognitive processes in immigrants adapting to hypoxic environments.

Accuracy of Genomic prediction for fleece traits in Inner Mongolia Cashmere goats.

The fleece traits are important economic traits of goats. With the reduction of sequencing and genotyping cost and the improvement of related technologies, genomic selection for goats has become possible. The research collect pedigree, phenotype and genotype information of 2299 Inner Mongolia Cashmere goats (IMCGs) individuals. We estimate fixed effects, and compare the estimates of variance components, heritability and genomic predictive ability of fleece traits in IMCGs when using the pedigree based Best Linear Unbiased Prediction (ABLUP), Genomic BLUP (GBLUP) or single-step GBLUP (ssGBLUP). The fleece traits considered are cashmere production (CP), cashmere diameter (CD), cashmere length (CL) and fiber length (FL). It was found that year of production, sex, herd and individual ages had highly significant effects on the four fleece traits (P < 0.01). All of these factors should be considered when the genetic parameters of fleece traits in IMCGs are evaluated. The heritabilities of FL, CL, CP and CD with ABLUP, GBLUP and ssGBLUP methods were 0.26 ~ 0.31, 0.05 ~ 0.08, 0.15 ~ 0.20 and 0.22 ~ 0.28, respectively. Therefore, it can be inferred that the genetic progress of CL is relatively slow. The predictive ability of fleece traits in IMCGs with GBLUP (56.18% to 69.06%) and ssGBLUP methods (66.82% to 73.70%) was significantly higher than that of ABLUP (36.73% to 41.25%). For the ssGBLUP method is significantly (29% ~ 33%) higher than that with ABLUP, and which is slightly (4% ~ 14%) higher than that of GBLUP. The ssGBLUP will be as an superiors method for using genomic selection of fleece traits in Inner Mongolia Cashmere goats.

Noninvasive tests maintain high accuracy for advanced fibrosis in chronic hepatitis B patients with different nomenclatures of steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a new nomenclature proposed in 2023. We aimed to compare the diagnostic efficacy of noninvasive tests (NITs) for advanced fibrosis under different nomenclatures in patients with chronic hepatitis B (CHB). A total of 844 patients diagnosed with CHB and concurrent steatotic liver disease (SLD) by liver biopsy were retrospectively enrolled and divided into four groups. The performances of fibrosis-4 (FIB-4), gamma-glutamyl transpeptidase to platelet ratio index (GPRI), aspartate aminotransferase to platelet ratio index (APRI), and liver stiffness measurement (LSM) were compared among the four groups. The four NITs showed similar diagnostic efficacy for nonalcoholic fatty liver disease (NAFLD), MASLD, and metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with CHB with advanced fibrosis. LSM showed the most stable accuracy for NAFLD (AUC = 0.842), MASLD (AUC = 0.846), and MAFLD (AUC = 0.863) compared with other NITs (p < 0.05). Among the four NITs, APRI (AUC = 0.841) and GPRI (AUC = 0.844) performed best in patients with CHB & MetALD (p < 0.05). The cutoff value for GPRI in patients with CHB & MetALD was higher than that in the other three groups, while further comparisons of NITs at different fibrosis stages showed that the median GPRI of CHB & MetALD (1.113) at F3-4 was higher than that in the CHB & MASLD group (0.508) (p < 0.05). Current NITs perform adequately in patients with CHB and SLD; however, alterations in cutoff values for CHB & MetALD need to be noted.

8-Cl-Ado and 8-NH2-Ado synergize with venetoclax to target the methionine-MAT2A-SAM axis in acute myeloid leukemia.

Targeting the metabolic dependencies of acute myeloid leukemia (AML) cells is a promising therapeutical strategy. In particular, the cysteine and methionine metabolism pathway (C/M) is significantly altered in AML cells compared to healthy blood cells. Moreover, methionine has been identified as one of the dominant amino acid dependencies of AML cells. Through RNA-seq, we found that the two nucleoside analogs 8-chloro-adenosine (8CA) and 8-amino-adenosine (8AA) significantly suppress the C/M pathway in AML cells, and methionine-adenosyltransferase-2A (MAT2A) is one of most significantly downregulated genes. Additionally, mass spectrometry analysis revealed that Venetoclax (VEN), a BCL-2 inhibitor recently approved by the FDA for AML treatment, significantly decreases the intracellular level of methionine in AML cells. Based on these findings, we hypothesized that combining 8CA or 8AA with VEN can efficiently target the Methionine-MAT2A-S-adenosyl-methionine (SAM) axis in AML. Our results demonstrate that VEN and 8CA/8AA synergistically decrease the SAM biosynthesis and effectively target AML cells both in vivo and in vitro. These findings suggest the promising potential of combining 8CA/8AA and VEN for AML treatment by inhibiting Methionine-MAT2A-SAM axis and provide a strong rationale for our recently activated clinical trial.

Detection method for unrecognized spatial disorientation based on optical flow stimuli.

BACKGROUND: Flight accidents caused by spatial disorientation (SD) greatly affect flight safety. OBJECTIVE: Few studies have been devoted to the evaluation of SD. METHODS: 10 pilots and 10 non-pilots were recruited for the experimental induction of SD. Videos for giving optical flow stimuli were played at two different flow speeds to induce SD. Subjective judgment and center of foot pressure (CoP) data were collected from the tests. The data were combined to determine the occurrence of SD and analyze the SD types. RESULTS: The number of self-reported SD events was slightly smaller in the pilots than in the non-pilots. The average upper bound of the confidence interval for the standard deviation of CoP was 0.32 ± 0.09 cm and 0.38 ± 0.12 cm in the pilots and non-pilots, respectively. This indicator was significantly lower in the pilots than in the non-pilots (P= 0.03). The success rate of the experimental induction of unrecognized SD was 26.7% and 45.0% in the pilots and non-pilots, respectively. CONCLUSION: The method offered a new to analyze unrecognized SD. We could determine the occurrence unrecognized SD. This is an essential means of reducing flight accidents caused by unrecognized SD.

STCGRU: A hybrid model based on CNN and BiGRU for mild cognitive impairment diagnosis.

BACKGROUND AND OBJECTIVE: Early diagnosis of mild cognitive impairment (MCI) is one of the essential measures to prevent its further development into Alzheimer's disease (AD). In this paper, we propose a hybrid deep learning model for early diagnosis of MCI, called spatio-temporal convolutional gated recurrent unit network (STCGRU). METHODS: The STCGRU comprises three bespoke convolutional neural network (CNN) modules and a bi-directional gated recurrent unit (BiGRU) module, which can effectively extract the spatial and temporal features of EEG and obtain excellent diagnostic results. We use a publicly available EEG dataset that has not undergone pre-processing to verify the robustness and accuracy of the model. Ablation experiments on STCGRU are conducted to showcase the individual performance improvement of each module. RESULTS: Compared with other state-of-the-art approaches using the same publicly available EEG dataset, the results show that STCGRU is more suitable for early diagnosis of MCI. After 10-fold cross-validation, the average classification accuracy of the hybrid model reached 99.95 %, while the average kappa value reached 0.9989. CONCLUSIONS: The experimental results show that the hybrid model proposed in this paper can directly extract compelling spatio-temporal features from the raw EEG data for classification. The STCGRU allows for accurate diagnosis of patients with MCI and has a high practical value.