Post-endovascular treatment, blood-brain barrier disruption, predicts patient outcomes better than pre-treatment status.

OBJECTIVES: Blood-brain barrier (BBB) disruption is an important pathological change after cerebral infarction that exacerbates brain injury. We aimed to investigate and compare the predictive utility of pre-treatment BBB permeability (BBBP) and BBBP within 1 h after endovascular treatment (EVT) for hemorrhagic transformation (HT) and 90-day prognosis. METHODS: Patients underwent preoperative computed tomography perfusion (CTP) and non-contrast CT (NCCT) within 1 h after EVT. Preoperative BBBP was determined by the relative permeability surface area product (rPS) in the hypoperfusion area. Postoperative BBBP was determined by the post-EVT Alberta Stroke Program Early CT Score (Post-ASPECTS), which is based on brain parenchymal hyperdensity on the postoperative NCCT. OUTCOMES: We included 100 patients. Univariate logistic regression analysis revealed correlations of preoperative rPS with HT, poor outcomes, and death. However, these correlations were not observed in multivariate logistic regression. A Post-ASPECTS ≤7 and could independently predict poor outcomes, while Post-ASPECTS ≤6 could independently predict death and HT. The baseline National Institutes of Health Stroke Scale (NIHSS) score could independently predict poor outcomes and death but not HT. A combined model using the baseline NIHSS and Post-ASPECTS scores had better predictive performance for poor outcomes and death than baseline NIHSS score alone; however, it was not superior to the predictive performance of the Post-ASPECTS score. CONCLUSION: The preoperative rPS cannot independently predict clinical outcomes in EVT-treated patients; contrastingly, the Post-ASPECTS score could independently predict poor outcomes, death, and HT. This parameter could inform prompt postoperative treatment decisions.

Autophagy inhibitors 3-MA and BAF may attenuate hippocampal neuronal necroptosis after global cerebral ischemia-reperfusion injury in male rats by inhibiting the interaction of the RIP3/AIF/CypA complex.

Our previous study found that receptor interacting protein 3 (RIP3) and apoptosis-inducing factor (AIF) were involved in neuronal programmed necrosis during global cerebral ischemia-reperfusion (I/R) injury. Here, we further studied its downstream mechanisms and the role of the autophagy inhibitors 3-methyladenine (3-MA) and bafilomycin A1 (BAF). A 20-min global cerebral I/R injury model was constructed using the 4-vessel occlusion (4-VO) method in male rats. 3-MA and BAF were injected into the lateral ventricle 1 h before ischemia. Spatial and activation changes of proteins were detected by immunofluorescence (IF), and protein interaction was determined by immunoprecipitation (IP). The phosphorylation of H2AX (γ-H2AX) and activation of mixed lineage kinase domain-like protein (p-MLKL) occurred as early as 6 h after reperfusion. RIP3, AIF, and cyclophilin A (CypA) in the neurons after I/R injury were spatially overlapped around and within the nucleus and combined with each other after reperfusion. The survival rate of CA1 neurons in the 3-MA and BAF groups was significantly higher than that in the I/R group. Autophagy was activated significantly after I/R injury, which was partially inhibited by 3-MA and BAF. Pretreatment with both 3-MA and BAF almost completely inhibited nuclear translocation, spatial overlap, and combination of RIP3, AIF, and CypA proteins. These findings suggest that after global cerebral I/R injury, RIP3, AIF, and CypA translocated into the nuclei and formed the DNA degradation complex RIP3/AIF/CypA in hippocampal CA1 neurons. Pretreatment with autophagy inhibitors could reduce neuronal necroptosis by preventing the formation of the RIP3/AIF/CypA complex and its nuclear translocation.

Effects of Mind-Body Exercises for Osteoporosis in Older Adults: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

Introduction: Osteoporosis is a major cause of fractures and even life-threatening fractures in the elderly. Mind-body exercise is a beneficial intervention to improve flexibility, control body balance and reduce pain. We aimed to evaluate the effects of physical and mental exercise on osteoporosis in the elderly. Methods: Randomized controlled trials (RCTs) focusing on mind-body exercises for osteoporosis were included. Web of Science, PubMed, Science Direct, Medline, Cochrane Library, China National Knowledge Infrastructure (CNKI), and Wanfang were searched from inception to January 2023. Outcomes included bone mineral density (BMD), bone mineral content (BMC), body balance (BB), pain, indicators of bone metabolism (BMI), lower extremity function, fearing level, and quality of life (QOL). The quality of study reporting was rated by 2 reviewers independently, and Review Manager software (version 5.3) was used for meta-analysis. Results: Thirty-nine trials with 2325 participants were included. The pooled results showed that mind-body exercises have encouraging effect on elderly people with osteoporosis, especially in aspects of BMD, BMC, QOL, improving the function of lower extremity, reducing pain and fearing level. While, dance and eight-section brocade could not improve the quality of life,or dance and eight-section brocade have no effect on BMD. Conclusions: Mind-body exercises may have potential efficacy for osteoporosis in the elderly. However, due to the poor methodological quality of the included trials, more clinical trials with precise methodological design and rigorous reporting are needed.

Identification and functional analysis of non-coding regulatory small RNA FenSr3 in Bacillus amyloliquefaciens LPB-18.

Bacillus amyloliquefaciens is an interesting microbe in the food processing and manufacturing industries. Non-coding small RNAs (sRNAs) have been shown to play a crucial role in the physiology and metabolism of bacteria by post-transcriptionally regulating gene expression. This study investigated the function of novel sRNA FenSr3 by constructing fenSr3 deficient strain and complementary strains in B. amyloliquefaciens LPB-18 , which were named LPN-18N and LPB-18P, respectively. The result showed significant differences in fengycin yield between strain LPB -18N and LPB-18P. The production of fengycin was significantly enhanced in B. amyloliquefaciens LPB-18N, compared with that of the strain LPB-18 from 190.908 mg/L to 327.598 mg/L. Moreover, the production of fengycin decreased from 190.464 mg/L to 38.6 mg/L in B . amyloliquefaciens LPB-18P. A comparative transcriptome sequencing was carried out to better understand the complex regulatory mechanism. Transcription analysis revealed that 1037 genes were differentially expressed between B. amyloliquefaciens LPB-18 and B. amyloliquefaciens LPB-18N, including the key regulatory genes in fatty acid, amino acid biosynthesis, and central carbon metabolism, which could provide sufficient quantities of building precursors for fengycin biosynthesis. The biofilm formation and sporulation was also enhanced in the strain LPB-18N, which indicates that FenSr3 could play a vital role in stress resistance and promotes survival in B. amyloliquefaciens. Some sRNAs involved in stress response have been identified in the literature, but their regulatory roles in fengycin production remain unclear. The study will contribute a novel perspective to the regulation mechanism of biosynthesis and the optimization of key metabolites of B. amyloliquefaciens.

A new application of multiplex PCR combined with membrane biochip assay for rapid detection of 9 common pathogens in sepsis.

Rapid and accurate identification of specific sepsis pathogens is critical for patient treatment and disease control. This study aimed to establish a new application for the rapid identification of common pathogens in patients with suspected sepsis and evaluate its role in clinical application. A multiplex PCR assay was designed to simultaneously amplify specific conserved regions of nine common pathogenic microorganisms in sepsis, including Acinetobacter baumannii, Escherichia coli, Klebsiella pneumonia, Pseudomonas aeruginosa, Enterococcus faecalis, Staphylococcus aureus, Staphylococcus epidermidis, Streptococcus pneumonia, and Candida albicans. The PCR products were analyzed by a membrane biochip. The analytical sensitivity of the assay was determined at a range of 5-100 copies/reaction for each standard strain, and the detection range was 20-200 cfu/reaction in a series dilution of simulated clinical samples at different concentrations. Out of the 179 clinical samples, the positive rate for pathogens detected by the membrane biochip assay and blood culture method was 20.11% (36/179) and 18.44% (33/179), respectively. However, by comparing the positive rate of the nine common pathogens we detected, the membrane biochip assay tended to be more sensitive than the blood culture method (20.11% vs 15.64%). The clinical sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the membrane biochip assay were 92.9%, 93.2%, 72.2% and 98.6%, respectively. Generally, this multiplex PCR combined membrane biochip assay can be used to detect major sepsis pathogens, and is useful for early initiation of effective antimicrobial treatment, and is feasible for sepsis pathogens identification in routine clinical practice.

Direction of arrival estimation method for ground source based on optimally polarized Rayleigh waves.

This paper points out a critical issue in the study of estimating the azimuth of ground sources by using the polarization characteristics of Rayleigh waves: even if the signal quality is good, the degree of polarization of Rayleigh waves varies across different frequency bands, and the band with the strongest energy is not the one with the lowest azimuth error. A direction of arrival estimation method for ground sources based on optimally polarized Rayleigh waves using a single three-component geophone is presented in this paper. First, the reciprocal ellipse rate, flatness coefficient, and the angle between the semi-minor axes and the horizontal plane are selected as the polarization parameters of this method according to two quantitative principles. Then the frequency band range of the optimal polarization Rayleigh wave is determined by analyzing the sum of the weights of the three polarization parameters in different frequency bands. After filtering and combining with the existing surface wave analysis method, the actual data bearing estimation result with an average error of only 4.95 degrees and a standard deviation of only 1.82 degrees is obtained. It is also found that the signal-to-noise ratio approximates the exponential decay of the direction of arrival error obtained by this method.

Left-Censored Missing Value Imputation Approach for MS-Based Proteomics Data with GSimp.

Missing values caused by the limit of detection or quantification (LOD/LOQ) were widely observed in mass spectrometry (MS)-based omics studies and could be recognized as missing not at random (MNAR). MNAR leads to biased statistical estimations and jeopardizes downstream analyses. Although a wide range of missing value imputation methods was developed for omics studies, a limited number of methods were designed appropriately for the situation of MNAR. To facilitate MS-based omics studies, we introduce GSimp, a Gibbs sampler-based missing value imputation approach, to deal with left-censor missing values in MS-proteomics datasets. In this book, we explain the MNAR and elucidate the usage of GSimp for MNAR in detail.

Acoustic-seismic coupling model for the Short-Distance detection of Ultra-Low-Altitude aircraft.

When using seismic signals to detect ultra-low-altitude aircraft at short distances, inappropriately designed filters reduce the signal quality and detection accuracy. To solve this problem, continuous acoustic signals generated by standard sound sources were used to induce vibrations in soil. Based on the assumed incidence of spherical wavefronts, we found that frequency bands of strengthened and weakened coupling are caused by interference between acoustic coupled waves and precursory seismic waves. We estimated the seismic properties at the experimental site by scanning various parameters to optimize the similarity coefficient. Based on the model, we discussed the relationship among soil velocities, layer thicknesses, and the amplitude of the coupled signal with frequency and provided a basis for the design of filters for detecting ultra-low-altitude aircraft.

Post-ASPECTS based on hyperdensity in NCCT immediately after thrombectomy is an ultra-early predictor of hemorrhagic transformation and prognosis.

Background and Purpose: Almost half of the patients exhibit futile recanalization after thrombectomy; however, the early postoperative predictors of futile recanalization remain unclear. We analyzed the relationship of post-thrombectomy ASPECTS (Post-ASPECTS) with 90-day prognosis and hemorrhagic transformation (HT). Methods: We collected data from patients with acute ischemic stroke (AIS) with anterior-circulation large vessel occlusion (ACLVO) who were treated via thrombectomy within 10 h in 3 hospitals. Successful endovascular recanalization was achieved (modified thrombolysis in cerebral ischemia [mTICI] 2b/3). Non-contrast computed tomography (NCCT) examination was performed immediately (within 1 h) after thrombectomy. Post-ASPECTS were scored based on the brain parenchymal hyperdensity in NCCT according to the ASPECTS scoring method. HT was defined according to the ECASS II classification criteria. Linear correlation, logistic regression, and receiver operating characteristic curve analyses were used to determine the influencing factors and best predictive value of 90-day prognosis, 90-day death, and HT. Results: A total of 231 patients were enrolled. The good prognosis rate, mortality rate, and HT rate were 57.1, 9.5, and 38.3%, respectively. The Post-ASPECTS affected poor prognosis, death, and HT. The best predictive value of Post-ASPECTS for poor prognosis, death, and HT was 7. The specificities of Post-ASPECTS for predicting HT, poor prognosis, and death were 87.6% (AUC, 0.811; P < 0.001), 87.1% (AUC, 0.768; P < 0.001), and 73.7% (AUC, 0.748; P < 0.001), with positive predictive values of 74.2, 75.7, and 21.4%, respectively. Conclusion: Post-ASPECTS predicted 90-day prognosis, death, and HT with high specificity and high positive predictive value in patients with AIS with ACLVO. Post-ASPECTS may be an ultra-early predictor of prognosis after thrombectomy.

RIPK3-Dependent Necroptosis Activates MCP-1-Mediated Inflammation in Mice after Intracerebral Hemorrhage.

BACKGROUND: Recent studies have reported that receptor-interacting protein kinase 3 (RIPK3)-dependent necroptosis is related to the pathological process of intracerebral hemorrhage (ICH). Some studies support the view that inhibiting necroptosis is a key mechanism preventing inflammation. Inflammation is a crucial factor contributing to neurological injuries and unfavorable outcomes after ICH. The aim of this study was to clarify the association between necroptosis and monocyte chemoattractant protein-1 (MCP-1)-mediated inflammation and identify a new target for the treatment of ICH. METHODS: An ICH model was established in C57BL/6 mice by injecting collagenase IV into the right basal ganglia. The RIPK3 inhibitor GSK872 was administered through intraventricular injection. Then, we assessed brain edema and neurobehavioral function. Western blotting was employed to detect changes in RIPK3, phospho-mixed lineage kinase domain-like protein (p-MLKL), MCP-1, phospho-c-Jun N-terminal kinase (p-JNK) and interleukin 6 (IL-6) levels in the brain tissue. The localization of RIPK3 and MCP-1 was observed using immunofluorescence staining. Co-immunoprecipitation was performed to determine the interaction between RIPK3 and MCP-1. RESULTS: Compared with the sham group, the levels of RIPK3, p-MLKL, MCP-1, p-JNK and IL-6 were increased post-ICH. GSK872 pretreatment significantly reduced RIPK3, p-MLKL, MCP-1, p-JNK and IL-6 expression, accompanied by mitigated cerebral edema and neurobehavioral defects. RIPK3 and MCP-1 colocalized in the perinuclear region after ICH. We detected the formation of the RIPK3-MCP-1 complex in ICH brain tissue. CONCLUSIONS: There exerted an association between RIPK3 and MCP-1. The inhibition of RIPK3 alleviated MCP-1-mediated inflammation following ICH.

Enzyme-Induced Transformable Peptide Nanocarriers with Enhanced Drug Permeability and Retention to Improve Tumor Nanotherapy Efficacy.

Temporal persistence is as important for nanocarriers as spatial accuracy. However, because of the insufficient aggreagtion and short retention time of chemotherapy drugs in tumors, their clinical application is greatly limited. A drug delivery approach dependent on the sensitivity to an enzyme present in the microenvironment of the tumor is designed to exhibit different sizes in different sites, achieving enhanced drug permeability and retention to improve tumor nanotherapy efficacy. In this work, we report a small-molecule peptide drug delivery system containing both tumor-targeting groups and enzyme response sites. This system enables the targeted delivery of peptide nanocarriers to tumor cells and a unique response to alkaline phosphatase (ALP) in the tumor microenvironment to activate morphological transformation and drug release. The amphiphilic peptide AYR self-aggregated into a spherical nanoparticle structure after encapsulating the lipid-soluble model drug doxorubicin (DOX) and rapidly converted to nanofibers via the induction of ALP. This morphological transformation toward a high aspect ratio allowed rapid, as well as effective drug release to tumor location while enhancing specific toxicity to tumor cells. Interestingly, this "transformer"-like drug delivery strategy can enhance local drug accumulation and effectively inhibit drug efflux. In vitro along with in vivo experiments further proved that the permeability and retention of antitumor drugs in tumor cells and tissues were significantly enhanced to reduce toxic side effects, and the therapeutic effect was remarkably improved compared with that of nondeformable drug-loaded peptide nanocarriers. The developed AYR nanoparticles with the ability to undergo morphological transformation in situ can improve local drug aggregation and retention time at the tumor site. Our findings provide a new and simple method for nanocarrier morphology transformation in novel cancer treatments.

LncRNA LINC01857 promotes cell growth and diminishes apoptosis via PI3K/mTOR pathway and EMT process by regulating miR-141-3p/MAP4K4 axis in diffuse large B-cell lymphoma.

LINC01857 has been proven to be involved in glioma and breast cancer. However, the biological function of LINC01857 in diffuse large B-cell lymphoma (DLBCL) is poorly investigated. By accessing to the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEX), LINC01857 expression was found upregulated in both DLBCL tissues and cells. Cell proliferation and flow cytometry assays showed that LINC01857 promoted proliferation and cell cycle, but suppressed apoptosis in DLBCL cells. Bioinformatics analysis and luciferase reporter assay confirmed that LINC01857 may serve as a sponge for miR-141-3p and miR-141-3p may target MAP4K4. Mechanically, the regulatory action of miR-141-3p/MAP4K4 on DLBCL cellular behaviors was regulated by LINC01857. In addition, LINC01857 could increase the activity of PI3K/mTOR pathway and facilitate the EMT process in a miR-141-3p-mediated manner in DLBCL. Our data illustrated that the LINC01857/miR-141-3p/MAP4K4 might function as a promising therapeutic avenue for DLBCL treatment.

Peripheral serum metabolomic profiles inform central cognitive impairment.

The incidence of Alzheimer's disease (AD) increases with age and is becoming a significant cause of worldwide morbidity and mortality. However, the metabolic perturbation behind the onset of AD remains unclear. In this study, we performed metabolite profiling in both brain (n = 109) and matching serum samples (n = 566) to identify differentially expressed metabolites and metabolic pathways associated with neuropathology and cognitive performance and to identify individuals at high risk of developing cognitive impairment. The abundances of 6 metabolites, glycolithocholate (GLCA), petroselinic acid, linoleic acid, myristic acid, palmitic acid, palmitoleic acid and the deoxycholate/cholate (DCA/CA) ratio, along with the dysregulation scores of 3 metabolic pathways, primary bile acid biosynthesis, fatty acid biosynthesis, and biosynthesis of unsaturated fatty acids showed significant differences across both brain and serum diagnostic groups (P-value < 0.05). Significant associations were observed between the levels of differential metabolites/pathways and cognitive performance, neurofibrillary tangles, and neuritic plaque burden. Metabolites abundances and personalized metabolic pathways scores were used to derive machine learning models, respectively, that could be used to differentiate cognitively impaired persons from those without cognitive impairment (median area under the receiver operating characteristic curve (AUC) = 0.772 for the metabolite level model; median AUC = 0.731 for the pathway level model). Utilizing these two models on the entire baseline control group, we identified those who experienced cognitive decline in the later years (AUC = 0.804, sensitivity = 0.722, specificity = 0.749 for the metabolite level model; AUC = 0.778, sensitivity = 0.633, specificity = 0.825 for the pathway level model) and demonstrated their pre-AD onset prediction potentials. Our study provides a proof-of-concept that it is possible to discriminate antecedent cognitive impairment in older adults before the onset of overt clinical symptoms using metabolomics. Our findings, if validated in future studies, could enable the earlier detection and intervention of cognitive impairment that may halt its progression.

Serum metabolite profiles are associated with the presence of advanced liver fibrosis in Chinese patients with chronic hepatitis B viral infection.

BACKGROUND: Accurate and noninvasive diagnosis and staging of liver fibrosis are essential for effective clinical management of chronic liver disease (CLD). We aimed to identify serum metabolite markers that reliably predict the stage of fibrosis in CLD patients. METHODS: We quantitatively profiled serum metabolites of participants in 2 independent cohorts. Based on the metabolomics data from cohort 1 (504 HBV associated liver fibrosis patients and 502 normal controls, NC), we selected a panel of 4 predictive metabolite markers. Consequently, we constructed 3 machine learning models with the 4 metabolite markers using random forest (RF), to differentiate CLD patients from normal controls (NC), to differentiate cirrhosis patients from fibrosis patients, and to differentiate advanced fibrosis from early fibrosis, respectively. RESULTS: The panel of 4 metabolite markers consisted of taurocholate, tyrosine, valine, and linoelaidic acid. The RF models of the metabolite panel demonstrated the strongest stratification ability in cohort 1 to diagnose CLD patients from NC (area under the receiver operating characteristic curve (AUROC) = 0.997 and the precision-recall curve (AUPR) = 0.994), to differentiate fibrosis from cirrhosis (0.941, 0.870), and to stage liver fibrosis (0.918, 0.892). The diagnostic accuracy of the models was further validated in an independent cohort 2 consisting of 300 CLD patients with chronic HBV infection and 90 NC. The AUCs of the models were consistently higher than APRI, FIB-4, and AST/ALT ratio, with both greater sensitivity and specificity. CONCLUSIONS: Our study showed that this 4-metabolite panel has potential usefulness in clinical assessments of CLD progression in patients with chronic hepatitis B virus infection.

Laterality of Attentional Networks in Patients With Cerebral Small Vessel Disease.

Introduction: Problems with attention are common in patients with cerebral small vessel disease (CSVD). The normal human brain exhibits functional and structural asymmetry. However, it is unknown whether there is lateralization of attention in patients with CSVD. Objective: This study aims to investigate attention separately in both cerebral hemispheres in patients with CSVD using the computer-based Lateralized Attention Network Test-Revised (LANT-R). Methods: The total number of subjects included was 58, which includes the CSVD (N = 35) and healthy control (HC, N = 23) groups. All subjects completed the LANT-R paradigm and neuropsychological background tests. Results: The results indicate that there is an left hemisphere (LH) lateralization in orienting network efficiency in the HC group. However, this lateralization was not apparent in the CSVD group. Furthermore, the difference between groups was significant (interaction P = 0.02). In addition, the scores of subjects in the CSVD group are lower in several cognitive domains, including attention function, memory function, information processing speed, and executive function, compared with the controls. Conclusion: Patients with CSVD change in the lateralization of attention compared with the normal elderly. The decrease in attention in patients with CSVD might be caused by the reduced ability of selecting useful information in the LH.

Strategy for Intercorrelation Identification between Metabolome and Microbiome.

Accumulating evidence points to the strong and complicated associations between the metabolome and the microbiome, which play diverse roles in physiology and pathology. Various correlation analysis approaches were applied to identify microbe-metabolite associations. Given the strengths and weaknesses of the existing methods and considering the characteristics of different types of omics data, we designed a special strategy, called Generalized coRrelation analysis for Metabolome and Microbiome (GRaMM), for the intercorrelation discovery between the metabolome and microbiome. GRaMM can properly deal with two types of omics data, the effect of confounders, and both linear and nonlinear correlations by integrating several complementary methods such as the classical linear regression, the emerging maximum information coefficient (MIC), the metabolic confounding effect elimination (MCEE), and the centered log-ratio transformation (CLR). GRaMM contains four sequential computational steps: (1) metabolic and microbial data preprocessing, (2) linear/nonlinear type identification, (3) data correction and correlation detection, and (4) p value correction. The performances of GRaMM, including the accuracy, sensitivity, specificity, false positive rate, applicability, and effects of preprocessing and confounder adjustment steps, were evaluated and compared with three other methods in multiple simulated and real-world datasets. To our knowledge, GRaMM is the first strategy designed for the intercorrelation analysis between metabolites and microbes. The Matlab function and an R package were developed and are freely available for academic use (comply with GNU GPL.V3 license).

LINC01232 exerts oncogenic activities in pancreatic adenocarcinoma via regulation of TM9SF2.

Pancreatic adenocarcinoma (PAAD), one of the most prevailing malignant tumors in digestive system, is identified as one of the main culprits of cancer-associated mortality. Despite long intergenic non-protein coding RNA 1232 (LINC01232) is found to be upregulated in TCGA PAAD tissues and associated with poor prognosis, the potential of LINC01232 in PAAD progression still needs more explorations. In this study, LINC01232 was chosen to be the research object in PAAD cellular processes. Functionally, loss-of function assays were carried out and the experimental results indicated that suppression of LINC01232 hindered the deterioration of PAAD by affecting cell proliferation and migration. Furthermore, relationship between LINC01232 and its nearby gene transmembrane 9 superfamily member 2 (TM9SF2) was investigated. The same expression pattern of TM9SF2 in TCGA PAAD samples was observed. It was found that upregulation of LINC01232 could be a crucial factor for the dysregulation of TM9SF2. Mechanistically, LINC01232 recruited EIF4A3 to boost TM9SF2 mRNA stability. Besides, our findings demonstrated that the transcriptional activation of LINC01232 and TM9SF2 was mediated by SP1. Therefore, we concluded that LINC01232 executed carcinogenic properties in PAAD progression via regulation of TM9SF2. In conclusion, this study was the first to unveil the role and molecular mechanism of LINC01232, suggesting LINC01232 as a promising molecular target for pancreatic cancer treatment.

MicroRNA-449b-5p Suppresses Proliferation, Migration, and Invasion of Osteosarcoma by Targeting c-Met.

BACKGROUND The aim of this study was to clarify the biological function of microRNA-449b-5p in the progression of osteosarcoma (OS) and to define the underlying mechanism. MATERIAL AND METHODS Relative levels of microRNA-449b-5p in OS tissues and cell lines was determined by quantitative real-time polymerase chain reaction (qRT-PCR). The correlation between microRNA-449b-5p level and pathological characteristics of OS patients was analyzed by chi-square test. Kaplan-Meier analysis was used for survival analysis of OS patients based on their expression level of microRNA-449b-5p. Regulatory effects of microRNA-449b-5p on cellular behaviors of OS cells were evaluated by cell counting kit-8 (CCK-8) and Transwell assay. The binding relationship between microRNA-449b-5p and c-Met was verified through dual-luciferase reporter gene assay, and their interaction in OS progression was further examined through a series of rescue experiments. RESULTS MicroRNA-449b-5p was expressed at low levels in OS. Lower levels of microRNA-449b-5p were seen in OS tissues with worse tumor grade or histological differentiation. OS patients with low levels of microRNA-449b-5p had worse overall survival relative to those with high level of microRNA-449b-5p. Overexpression of microRNA-449b-5p markedly attenuated proliferative, migratory, and invasive abilities of OS cells. C-Met is the downstream target of microRNA-449b-5p, and its level was inhibited in OS cells overexpressing microRNA-449b-5p. Importantly, c-Met partially rescued the inhibitory effects of microRNA-449b-5p on behavior of OS cells. CONCLUSIONS MicroRNA-449b-5p is downregulated in OS, which alleviates the malignant progression of OS by targeting c-Met.

Illumination-Guided Video Composition via Gradient Consistency Optimization.

Video composition aims at cloning a patch from the source video into the target scene to create a seamless and harmonious blending frame sequence. Previous work in video composition usually suffer from artifacts around the blending region and spatial-temporal consistency when illumination intensity varies in the input source and target video. We propose an illumination-guided video composition method via a unified spatial and temporal optimization framework. Our method can produce globally consistent composition results and maintain the temporal coherency. We first compute a spatial-temporal blending boundary iteratively. For each frame, the gradient field of the target and source frames are mixed adaptively based on gradients and inter-frame color difference. The temporal consistency is further obtained by optimizing luminance gradients throughout all the composition frames. Moreover, we extend the mean-value cloning by smoothing discrepancies between the source and target frames, then eliminate the color distribution overflow exponentially to reduce falsely blending pixels. Various experiments have shown the effectiveness and high-quality performance of our illumination-guided composition.

Evaluation of metabolite-microbe correlation detection methods.

Different correlation detection methods have been specifically designed for the microbiome data analysis considering the compositional data structure and different sequencing depths. Along with the speedy development of omics studies, there is an increasing interest in discovering the biological associations between microbes and host metabolites. This raises the need of finding proper statistical methods that facilitate the correlation analysis across different omics studies. Here, we comprehensively evaluated six different correlation methods, i.e., Pearson correlation, Spearman correlation, Sparse Correlations for Compositional data (SparCC), Correlation inference for Compositional data through Lasso (CCLasso), Mutual Information Coefficient (MIC), and Cosine similarity methods, for the correlations detection between microbes and metabolites. Three simulated and two real-world data sets (from public databases and our lab) were used to examine the performance of each method regarding its specificity, sensitivity, similarity, accuracy, and stability with different sparsity. Our results indicate that although each method has its own pros and cons in different scenarios, Spearman correlation and MIC outperform the others with their overall performances. A strategic guidance was also proposed for the correlation analysis between microbe and metabolite.