IL-22, a vital cytokine in autoimmune diseases.

Interleukin-22 (IL-22) is a vital cytokine that is dysregulated in various autoimmune conditions including rheumatoid arthritis (RA), multiple sclerosis (MS), and Alzheimer's disease (AD). As the starting point for the activation of numerous signaling pathways, IL-22 plays an important role in the initiation and development of autoimmune diseases. Specifically, imbalances in IL-22 signaling can interfere with other signaling pathways, causing cross regulation of target genes which ultimately leads to the development of immune disorders. This review delineates the various connections between the IL-22 signaling pathway and autoimmune disease, focusing on the latest understanding of the cellular sources of IL-22 and its effects on various cell types. We further explore progress with pharmacological interventions related to targeting IL-22, describing how such therapeutic strategies promise to usher in a new era in the treatment of autoimmune disease.

ImmunoPET imaging of Trop2 expression in solid tumors with nanobody tracers.

PURPOSE: The high expression of the transmembrane glycoprotein trophoblast cell-surface antigen 2 (Trop2) was strongly associated with the progression of solid tumors, including pancreatic and gastric cancers. Our study aimed to construct Trop2-specific immuno-positron emission tomography (immunoPET) probes and assess the diagnostic abilities in preclinical pancreatic and gastric cancer models. METHODS: The expression of Trop2 in pancreatic cancer was determined by single-cell sequencing and immunohistochemistry on tissue microarray (TMA). Flow cytometry was used to screen the expression of Trop2 in pancreatic cancer cell lines. Two nanobodies (i.e., RTD98 and RTD01) targeting Trop2 were developed and labeled with gallium-68 (68Ga, T1/2 = 1.1 h) to construct immunoPET imaging probes. The agents were researched in cell-derived pancreatic and patient-derived gastric cancer models expressing varying Trop2. RESULTS: Single-cell sequencing results showed high expression of Trop2 in pancreatic ductal cells as well as acinar cells and immunohistochemical staining of TMA from pancreatic cancers showed significantly higher expression of Trop2 in cancerous than in paracancerous tissues. ImmunoPET utilizing [68Ga]Ga-NOTA-RTD98 could clearly delineate subcutaneous tumors, both in cell-derived pancreatic cancer models and patient-derived gastric cancer models, superior to imaging using [18F]-FDG or a non-specific probe [68Ga]Ga-NOTA-RTD161. Another probe with improved pharmacokinetics targeting Trop2, [68Ga]Ga-NOTA-RTD01, was further prepared and showed advantageous diagnostic capabilities in preclinical pancreatic cancer models. CONCLUSION: In the work, we reported two nanobody tracers targeting human Trop2 which may facilitate better use of Trop2-targeted therapeutics by noninvasively displaying expression dynamics of the target.

miRNA-143 as a potential biomarker in the detection of bladder cancer: a meta-analysis.

Aim: This study aimed to systematically evaluate the value of miRNA-143 in the early detection of bladder cancer (BCa). Methods: CNKI, WanFang, PubMed and Wiley Online Library databases were explored according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. A random-effects model was used to obtain pooled sensitivity, specificity and other related indicates. Results: Six studies were included for analysis. The overall pooled sensitivity and specificity were 0.80 (95% CI: 0.74-0.85) and 0.85 (95% CI: 0.78-0.91), and the area under the curve was 0.88 (95% CI: 0.85-0.91). Coupled with miR-100, it showed better diagnostic power (area under the curve: 0.95). Conclusion: miRNA-143 may serve as a promising noninvasive tool for the early detection of BCa.

Bladder cancer (BCa) is a common and deadly malignant tumor worldwide; however, noninvasive diagnosis can significantly improve the prognosis of patients. Recently, miRNAs have emerged as potential diagnostic biomarkers for BCa. Among them, miRNA-143 has shown promising results in several studies. This meta-analysis aimed to evaluate the overall diagnostic accuracy of miRNA-143 for BCa through a systematic review and meta-analysis of six published articles. Excitingly, the results of this meta-analysis suggest that miRNA-143 has potential diagnostic value in BCa. Particularly, miRNA-143 combined with miRNA-100 maintained better competence. Besides, miRNA-143 in plasma exhibited better diagnostic strength than that in urine. The authors believe that their study provides valuable insights into the use of miRNA-143 as a diagnostic biomarker for BCa.

Uric acid to albumin ratio as a novel predictor for coronary slow flow phenomenon in patients with chronic coronary syndrome and non-obstructive coronary arteries.

BACKGROUND: The plasma uric acid to albumin ratio (UAR) is considered as a novel indicator for Inflammation. However, the association between UAR and coronary slow flow phenomenon (CSFP) remains unclear. METHODS: A total of 1328 individuals with chronic coronary syndrome (CCS) receiving coronary angiography (CAG) and found no obvious obstructive stenosis (< 40%) were included in this study. 79 individuals developed CSFP and were divided into CSFP group. The 1:2 age-matched patients with normal coronary blood flow were allocated to the control group (n = 158). The clinical characteristics, laboratory parameters including uric acid, albumin ratio, UAR and the angiographic characteristics were compared between the two groups. RESULTS: Patients with CSFP had a higher level of uric acid (392.3 ± 85.3 vs. 273.8 ± 71.5, P < 0.001), UAR (10.7 ± 2.2 vs. 7.2 ± 1.9, P < 0.001), but a lower level of plasma albumin (36.9 ± 4.2 vs. 38.5 ± 3.6, P = 0.003). Moreover, UAR increased as the numbers of vessels involved in CSFP increased. The logistic regression analysis demonstrated that UAR was independent predictors for CSFP. The Receiver operating characteristic (ROC) curve analysis showed that when UAR was more than 7.9, the AUC was 0.883 (95% CI: 0.840-0.927, p < 0.001), with the sensitivity and specificity were 78.2% and 88.2% respectively. CONCLUSION: Combined uric acid with plasma albumin, UAR could serve as an independent predictor for CSFP.

The clinical profile, genetic basis and survival of childhood cardiomyopathy: a single-center retrospective study.

Cardiomyopathy (CM) is a heterogeneous group of myocardial diseases in children. This study aimed to identify demographic features, clinical presentation and prognosis of children with CM. Clinical characteristics and prognostic factors associated with mortality were evaluated by Cox proportional hazards regression analyses. Genetic testing was also conducted on a portion of patients. Among the 317 patients, 40.1%, 25.2%, 24.6% and 10.1% were diagnosed with dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), left ventricular noncompaction cardiomyopathy (LVNC) and restrictive cardiomyopathy (RCM), respectively. The most common symptom observed was dyspnea (84.2%). Except for HCM, the majority of patients were classified as NYHA/Ross class III or IV. The five-year survival rates were 75.5%, 67.3%, 74.1% and 51.1% in DCM, HCM, LVNC and RCM, respectively. The ten-year survival rates were 60.1%, 56.1%, 57.2% and 41.3% in DCM, HCM, LVNC and RCM, respectively. Survival was inversely related to NYHA/Ross class III or IV in patients with DCM, HCM and RCM. Out of 42 patients, 32 were reported to carry gene mutations. CONCLUSIONS: This study demonstrates that CM, especially RCM, is related to a high incidence of death. NYHA/Ross class III or IV is a predictor of mortality in the patients and gene mutations may be a common cause. TRIAL REGISTRATION: MR-50-23-011798. WHAT IS KNOWN: • Cardiomyopathy (CM) is a heterogeneous group of myocardial diseases and one of the leading causes of heart failure in children due to the lack of effective treatments. • There remains scarce data on Asian pediatric populations though emerging studies have assessed the clinical characteristics and outcomes of CM. WHAT IS NEW: • A retrospective study was conducted and the follow-up records were established to investigate the clinical characteristics, the profile of gene mutations and prognostic outcomes of children with CM in Western China. • CM, especially RCM, is related to a high incidence of death. NYHA/Ross class III or IV is a predictor of mortality in the patients and gene mutations may be a common cause.

Rare variants regulate expression of nearby individual genes in multiple tissues.

The rapid decrease in sequencing cost has enabled genetic studies to discover rare variants associated with complex diseases and traits. Once this association is identified, the next step is to understand the genetic mechanism of rare variants on how the variants influence diseases. Similar to the hypothesis of common variants, rare variants may affect diseases by regulating gene expression, and recently, several studies have identified the effects of rare variants on gene expression using heritability and expression outlier analyses. However, identifying individual genes whose expression is regulated by rare variants has been challenging due to the relatively small sample size of expression quantitative trait loci studies and statistical approaches not optimized to detect the effects of rare variants. In this study, we analyze whole-genome sequencing and RNA-seq data of 681 European individuals collected for the Genotype-Tissue Expression (GTEx) project (v8) to identify individual genes in 49 human tissues whose expression is regulated by rare variants. To improve statistical power, we develop an approach based on a likelihood ratio test that combines effects of multiple rare variants in a nonlinear manner and has higher power than previous approaches. Using GTEx data, we identify many genes regulated by rare variants, and some of them are only regulated by rare variants and not by common variants. We also find that genes regulated by rare variants are enriched for expression outliers and disease-causing genes. These results suggest the regulatory effects of rare variants, which would be important in interpreting associations of rare variants with complex traits.

Rare variants in the endocytic pathway are associated with Alzheimer's disease, its related phenotypes, and functional consequences.

Late-onset Alzheimer's disease (LOAD) is the most common type of dementia causing irreversible brain damage to the elderly and presents a major public health challenge. Clinical research and genome-wide association studies have suggested a potential contribution of the endocytic pathway to AD, with an emphasis on common loci. However, the contribution of rare variants in this pathway to AD has not been thoroughly investigated. In this study, we focused on the effect of rare variants on AD by first applying a rare-variant gene-set burden analysis using genes in the endocytic pathway on over 3,000 individuals with European ancestry from three large whole-genome sequencing (WGS) studies. We identified significant associations of rare-variant burden within the endocytic pathway with AD, which were successfully replicated in independent datasets. We further demonstrated that this endocytic rare-variant enrichment is associated with neurofibrillary tangles (NFTs) and age-related phenotypes, increasing the risk of obtaining severer brain damage, earlier age-at-onset, and earlier age-of-death. Next, by aggregating rare variants within each gene, we sought to identify single endocytic genes associated with AD and NFTs. Careful examination using NFTs revealed one significantly associated gene, ANKRD13D. To identify functional associations, we integrated bulk RNA-Seq data from over 600 brain tissues and found two endocytic expression genes (eGenes), HLA-A and SLC26A7, that displayed significant influences on their gene expressions. Differential expressions between AD patients and controls of these three identified genes were further examined by incorporating scRNA-Seq data from 48 post-mortem brain samples and demonstrated distinct expression patterns across cell types. Taken together, our results demonstrated strong rare-variant effect in the endocytic pathway on AD risk and progression and functional effect of gene expression alteration in both bulk and single-cell resolution, which may bring more insight and serve as valuable resources for future AD genetic studies, clinical research, and therapeutic targeting.

Relationship between the expression of PD-L1 and 18F-FDG uptake in pancreatic ductal adenocarcinoma.

BACKGROUND: PD-L1 promotes glycolysis in tumour cells. We observed a correlation between high PD-L1 expression and high 18F-FDG uptake in patients with pancreatic ductal adenocarcinoma (PDAC) in a previous study. This study aims to determine the usefulness of 18F-FDG PET/CT for evaluating the PD-L1 status in PDAC and to elucidate its rationality by integrated analyses. METHODS: For bioinformatics analysis, WGCNA, GSEA and TIMER were applied to analyse the pathways and hub genes associated with PD-L1 and glucose uptake. 18F-FDG uptake assay was used to determine the glucose uptake rate of PDAC cells in vitro. Related genes expression were verified by RT-PCR and western blot. A retrospective analysis was performed on 47 patients with PDAC who had undergone 18F-FDG PET/CT. Maximum standardised uptake values (SUVmax) were determined. The usefulness of SUVmax for evaluating PD-L1 status was determined by receiver operating characteristic (ROC) curve analysis. RESULTS: Bioinformatics analysis showed that several signalling pathways are associated with both PD-L1 expression and tumour glucose uptake, among which JAK-STAT may be an important one. By in vitro experiments, the regulatory role of PD-L1 on glucose uptake was demonstrated, and its dependency on the JAK-STAT pathway was also verified by the rescue study. The SUVmax of PD-L1-positive patients was significantly higher than PD-L1-negative in tumour cells (TCs) (6.1 ± 2.3 vs. 11.1 ± 4.2; P < 0.001), and in tumour-infiltrating immune cells (TIICs) (6.4 ± 3.2 vs. 8.4 ± 3.5; P < 0.001). In a multivariate analysis, SUVmax was significantly associated with PD-L1 expression in TCs and TIICs (P < 0.001 and P = 0.018, respectively). Using SUVmax cut-off values of 8.15 and 7.75, PD-L1 status in TCs and TIICs could be predicted with accuracies of 91.5% and 74.5%, respectively. CONCLUSION: Higher 18F-FDG uptake by PDAC is associated with elevated PD-L1 expression. JAK-STAT is an important pathway that mediates PD-L1 to promote glucose uptake in PDAC.

Revisiting the pericarp as a barrier restricting water entry/loss from cotyledons and embryonic axis of temperate desiccation-sensitive Quercus acorns.

MAIN CONCLUSIONS: Fully mature acorns of Quercus variabilis, Q. aliena, Q. mongolica, and Q. glandulifera are desiccation-sensitive. X-ray computer tomography showed that cotyledons shrink during drying, but embryos are protected. Information available on recalcitrant acorns of tropical and sub-tropical species of Quercus suggests that an impermeable pericarp, which limits the entry and loss of water only through the hilum (scar), is the underlying mechanism that prevents drying of the embryo axis following dispersal until the germination season. However, there is a lack of consensus supporting this proposition across species, and it is not well understood if such mechanisms occur in temperate Quercus species. This study investigated the significance of the acorn pericarp for temperate oak species and presents an ecological framework based on the post-dispersal climatic conditions. Using Quercus variabilis, Q. aliena, Q. mongolica, and Q. glandulifera acorns, the relationship between moisture content (MC) and germination was established, and X-ray computed tomography (X-ray CT) was used to understand the internal structural changes of cotyledons and embryonic axis occurring during desiccation. Water entry and exit routes through the scar, pericarp and apex were determined by imbibition and drying experiments. Climatic data and acorn morphological characteristics and germination were subjected to a principal component analysis (PCA). Freshly dispersed acorns of all species had a moisture content (MC) above 35% fresh weight (FW) basis, but drying to 15-10% MC resulted in complete loss of viability, implying recalcitrance behaviour. X-ray CT images suggested that the pericarp offers some protection to cotyledons and embryonic axis during desiccation, but it is contingent on MC. Extensive drying to a low MC with the scar and apex covered with vaseline resulted in internal tissues shrinkage, corresponding with viability loss. Water could enter or exit through the pericarp, albeit at a much slower rate than through the scar. A combination of factors including acorn anatomy, moisture content at the time of dispersal, microhabitat, the position of acorns in the soil prevent embryo desiccation below the critical MC and thus promotes survival of acorns on/in the soil during winter in temperate regions. Pericarp anatomy, to some extent, prevents excessive drying of the embryonic axis by slowing water movement, but prolonged drying or predatory pressure could result in pericarp cracks, favouring the absorption of water during sporadic rain. In the latter case, the survival of acorns possibly depends extensively on the continuous erratic rainfall, i.e. continuous wet-dry cycle, but in-situ experiments are yet to be performed to test this hypothesis.

Metabolic kinetic modeling of [11C]methionine based on total-body PET in multiple myeloma.

PURPOSE: Multiple myeloma (MM) is a malignant disease characterized by the secretion of monoclonal immunoglobulins and has a high demand for amino acids. [11C]methionine total-body PET is capable of noninvasive dynamic monitoring of radiotracer in vivo, thus providing a way to reveal the dynamic changes of myeloma metabolism. This study aims to analyze the metabolic process of [11C]methionine based on kinetic modeling, and to preliminary reveal its application value in MM. METHODS: Dynamic total-body [11C]methionine PET/CT was conducted with uEXPLORER in 12 subjects (9 MM patients and 3 controls). The tissue time activity curves (TACs) of organs and bone marrows were extracted. Model fitting of TACs was operated using PMOD Kinetic Modeling. After validation by Goodness of fit (GOF), the reversible two-tissue compartment model (2T4k) was used to further analysis. R software was used to analyze the correlation between kinetic parameters and clinical indicators. RESULTS: The 2T4k has passed the criterion of GOF and was used to fit the data of 0-20 minutes. The [11C]methionine net uptake rate (Ki) was significantly higher in the MM lesions than in the non-myeloma controls (control: 0.040±0.007 mL/g/min, MM: 0.171±0.108 mL/g/min, p=0.009). The Ki values were found to be correlated with M protein levels in MM patients. MM patients with t(4;14) translocations had an elevated k4 value compared with t(4;14) negative patients. CONCLUSION: MM lesions have a propensity for uptake of [11C]methionine. The serum levels of M protein are correlated with [11C]methionine uptake rate in myeloma. Metabolic classification based on the k4 value may be a promising strategy for risk stratification in MM.

Body Mass Index is Associated with blood pressure and vital capacity in medical students.

BACKGROUND: The widely reported associations between body mass index (BMI) and various chronic diseases, such as hypertension and asthma, have garnered significant attention. Nonetheless, there remains a dearth of research dedicated to understanding the health impacts of medical school on the students, who experience considerable academic pressure. In that context, this study was driven by the goal of investigating the intricate interplay between BMI, blood pressure (BP), and vital capacity among medical students. METHODS: This study included a cohort of 843 medical students enrolled at Southern Medical University who were selected through random cluster sampling. Within this cohort, measurements of height, weight, BP, and vital capacity were taken. Subsequently, both BMI and vital capacity index (VCI) were calculated for each participant. By categorizing the subjects into four groups according to BMI classifications, a comprehensive analysis that included correlation assessments and binomial logistic regression was conducted. RESULTS: Within the participant pool, 9.4% and 3.8% of participants were classified as overweight and obese, respectively. Additionally, the prevalence of prehypertension, hypertension, and poor VCI was 18.1%, 2.7%, and 13.5%, respectively. Notably, male students exhibited a higher prevalence of the aforementioned health issues than their female counterparts. Correlation analysis revealed that BMI displayed positive associations with systolic blood pressure (SBP), diastolic blood pressure (DBP), and vital capacity (r = 0.372, 0.257, 0.428; P < 0.001). However, an inverse correlation emerged between BMI and VCI (r = -0.284, P < 0.001). Further analysis revealed that overweight and obese individuals faced an elevated risk of high blood pressure ([OR 2.05, 95% CI 1.15-3.67] and [OR 5.44, 95% CI 2.28-13.02], respectively) compared to their normal-weight counterparts. Moreover, these groups also exhibited a higher risk of poor VCI ([OR 5.25, 95% CI 3.04-9.06] and [OR 15.61, 95% CI 6.81-35.81], respectively), while underweight subjects experienced a reduced risk ([OR 0.19, 95% CI 0.07-0.52]). CONCLUSIONS: BMI demonstrated a notably strong positive correlation with both BP and vital capacity and a negative correlation with VCI. Therefore, for medical students as well as the daily health care of patients, weight control is recommended to better combat obesity-related diseases, for example, cardiopulmonary diseases, gout and diabetes.

Profile probing of suspended particles in water by Stokes vector polarimetry.

Suspended particles are the important components of natural water. In this paper, a method based on polarized light scattering is proposed for profile probing of the particulate components in water. The profile probing is achieved by a polarized light sheet illuminating the suspension and the Stokes vector imaging system at a 120° backscattering angle, receiving the scattered light of the particles in the scattering volume. Each Stokes vector image (SVI) includes hundreds of star-studded particles whose Stokes vectors are used to retrieve the numbers of each particulate component in water. Experiments of typical particles are conducted. The classifications of these particles powered by the convolutional neural network (CNN) are demonstrated. The particulate components in mixed samples are successfully recognized and quantitatively compared. Considering at least 10 SVIs every second, the concentrations of each particulate component in water are effectively evaluated. The concept of profile probing the particulate components in water is proved to be powerful, by which we can measure up to almost 8000 particles per second. These results encourage the development of in-situ tools with this concept for particle profiling in future field surveying.

Statistical Mueller matrix driven discrimination of suspended particles.

An effective method to calculate the statistical Mueller matrix (SMM) of suspended particles based on polarized light scattering is presented that takes advantage of the Stokes vectors measurement of individual particles. The calculation method of the SMM is derived based on statistics. Experimental results of Microcystis samples confirm that the SMM can characterize cells of different states. Then, pairwise contrast experiments indicate the great prospect of the SMM applied on the discrimination of suspended particles. It helps to find the optimal incident polarization state to discriminate suspended particles, and it has optimal discrimination ability. The parameter derived from the SMM can simultaneously discriminate particles including microalgae, microplastics, and sand-like particles.

PD-L1 correlated gene expression profiles and tumor infiltrating lymphocytes in pancreatic cancer.

Objective: To study the expression and clinical value of PD-L1 gene in pancreatic cancer, and to predict the role of PD-L1 gene in the development of pancreatic cancer. Methods: The pancreatic cancer datasets were downloaded from the Cancer Genome Atlas (TCGA) and the Oncomine to obtain the PD-L1 gene expression profile and clinical information. Bioinformatics methods were used to analyze the correlation between the expression level of PD-L1 gene in pancreatic cancer and clinicopathological indicators, as well as its influence on prognosis. GSEA and WGCNA analysis was performed to predict the possible pathways of PD-L1 gene regulation in pancreatic cancer. TIMER and MCP-counter were used for PD-L1 with immune infiltration. The genes interact with PD-L1 were also investigated by STING and immunoco-precipitation combined with mass spectrometry analysis (IP-MS). Results: In TCGA database, the overall survival of patients with high expression of PD-L1 gene was significantly lower than that of patients with low expression of PD-L1 gene (χ2 = 12.52, P < 0.001). The samples with high expression of PD-L1 gene showed enrichment of 8 pathways including toll-like receptor signaling pathway and NOD receptor signaling pathway (P < 0.01, FDR < 0.05). Immune infiltration analysis suggested that PD-L1 were associated with monocytic lineage (r = 0.5). The proteins interacting with PD-L1 are mainly concentrated in RNA binding, ribosome, spliceosome and other biological processes or pathways. Conclusion: PD-L1 gene may play an important role in the development of pancreatic cancer and is expected to be a prognostic indicator of pancreatic cancer.

Monitoring particulate composition changes during the flocculation process using polarized light scattering.

Monitoring the particulate composition changes during the flocculation process is still challenging for the research community. We use an experimental setup based on polarized light scattering to measure the polarization states of the scattered light of the individual particles. We build a classifier based on the support vector machine and feed it with the measured parameters. Results show that the classifier can effectively classify the particulate compositions, such as the sediment particles, flocculants, and flocs, which can be used to monitor the particulate composition changes during the flocculation process. Discussions on the intensity and polarization parameters find that the polarization parameters play a vital role in the classification of the particulate compositions in the flocculation suspensions. Additionally, the further analysis of the experimental data and the related simulations show that the degree of polarization can be an indicator of the flocculation process. We prove that the method based on polarized light scattering may be a potential in situ monitoring tool in the future for the study of the flocculation process.

Optimized Classification of Suspended Particles in Seawater by Dense Sampling of Polarized Light Pulses.

Suspended particles affect the state and vitality of the marine ecosystem. In situ probing and accurately classifying the suspended particles in seawater have an important impact on ecological research and environmental monitoring. Individual measurement of the optical polarization parameters scattered by the suspended particles has been proven to be a powerful tool to classify the particulate compositions in seawater. In previous works, the temporal polarized light pulses are sampled and averaged to evaluate the polarization parameters. In this paper, a method based on dense sampling of polarized light pulses is proposed and the experimental setup is built. The experimental results show that the dense sampling method optimizes the classification and increases the average accuracy by at least 16% than the average method. We demonstrate the feasibility of dense sampling method by classifying the multiple types of particles in mixed suspensions and show its excellent generalization ability by multi-classification of the particles. Additional analysis indicates that the dense sampling method basically takes advantage of the high-quality polarization parameters to optimize the classification performance. The above results suggest that the proposed dense sampling method has the potential to probe the suspended particles in seawater in red-tide early warning, as well as sediment and microplastics monitoring.

ForestQC: Quality control on genetic variants from next-generation sequencing data using random forest.

Next-generation sequencing technology (NGS) enables the discovery of nearly all genetic variants present in a genome. A subset of these variants, however, may have poor sequencing quality due to limitations in NGS or variant callers. In genetic studies that analyze a large number of sequenced individuals, it is critical to detect and remove those variants with poor quality as they may cause spurious findings. In this paper, we present ForestQC, a statistical tool for performing quality control on variants identified from NGS data by combining a traditional filtering approach and a machine learning approach. Our software uses the information on sequencing quality, such as sequencing depth, genotyping quality, and GC contents, to predict whether a particular variant is likely to be false-positive. To evaluate ForestQC, we applied it to two whole-genome sequencing datasets where one dataset consists of related individuals from families while the other consists of unrelated individuals. Results indicate that ForestQC outperforms widely used methods for performing quality control on variants such as VQSR of GATK by considerably improving the quality of variants to be included in the analysis. ForestQC is also very efficient, and hence can be applied to large sequencing datasets. We conclude that combining a machine learning algorithm trained with sequencing quality information and the filtering approach is a practical approach to perform quality control on genetic variants from sequencing data.

Classification of marine microalgae using low-resolution Mueller matrix images and convolutional neural network.

In this paper, we used a convolutional neural network to study the classification of marine microalgae by using low-resolution Mueller matrix images. Mueller matrix images of 12 species of algae from 5 families were measured by a Mueller matrix microscopy with an LED light source at 514 nm wavelength. The data sets of seven resolution levels were generated by the bicubic interpolation algorithm. We conducted two groups of classification experiments; one group classified the algae into 12 classes according to species category, and the other group classified the algae into 5 classes according to family category. In each group of classification experiments, we compared the classification results of the Mueller matrix images with those of the first element (M11) images. The classification accuracy of Mueller matrix images declines gently with the decrease of image resolution, while the accuracy of M11 images declines sharply. The classification accuracy of Mueller matrix images is higher than that of M11 images at each resolution level. At the lowest resolution level, the accuracy of 12-class classification and 5-class classification of full Mueller matrix images is 29.89% and 35.83% higher than those of M11 images, respectively. In addition, we also found that the polarization information of different species had different contributions to the classification. These results show that the polarization information can greatly improve the classification accuracy of low-resolution microalgal images.

Probing the Cyanobacterial Microcystis Gas Vesicles after Static Pressure Treatment: A Potential In Situ Rapid Method.

The vertical migration trend of cyanobacterial cells with gas vesicles in water ecosystems can reflect the changes in the natural environment, such as temperature, nutrients, light conditions, etc. The static pressure treatment is one of the most important approaches to study the properties of the cyanobacterial cell and its gas vesicles. In this paper, a polarized light scattering method is used to probe the collapse and regeneration of the cyanobacterial gas vesicles exposed to different static pressures. During the course, both the axenic and wild type strain of cyanobacterial Microcystis were first treated with different static pressures and then recovered on the normal light conditions. Combining the observation of transmission electron microscopy and floating-sinking photos, the results showed that the collapse and regeneration of the cyanobacterial gas vesicles exposed to different static pressures can be characterized by the polarization parameters. The turbidity as a traditional indicator of gas vesicles but subjected to the concentration of the sample was also measured and found to be correlated with the polarization parameters. More analysis indicated that the polarization parameters are more sensitive and characteristic. The polarized light scattering method can be used to probe the cyanobacterial gas vesicles exposed to different static pressures, which has the potential to provide an in situ rapid and damage-free monitoring tool for observing the vertical migration of cyanobacterial cells and forecasting cyanobacterial blooms.

Pyruvate kinase M2 interacts with nuclear sterol regulatory element-binding protein 1a and thereby activates lipogenesis and cell proliferation in hepatocellular carcinoma.

Dysregulation of lipid metabolism is common in cancer cells, but the underlying mechanisms are poorly understood. Sterol regulatory element-binding proteins (SREBPs) stimulate lipid biosynthesis through transcriptional activation of lipogenic enzymes. However, SREBPs' roles and potential interacting partners in cancer cells are not fully defined. Using a biochemical approach, we found here that pyruvate kinase M2 (PKM2) physically interacts with the nuclear form of SREBP-1a (nBP1a), by binding to amino acids 43-56 in nBP1a. We also found that PKM2 activates SREBP target gene expression and lipid biosynthesis by stabilizing nBP1a proteins. Using a competitive peptide inhibitor to block the formation of the SREBP-1a/PKM2 complex, we observed that this blockade inhibited lipogenic gene expression. Of note, nBP1a phosphorylation at Thr-59 enhanced the binding to PKM2 and promoted cancer cell growth. Moreover, we show that PKM2 phosphorylates Thr-59 in vitro Lastly, in human patients with hepatocellular carcinoma, nBP1a phosphorylation at Thr-59 was negatively correlated with clinical outcomes. Together, our results reveal that nBP1a/PKM2 interaction activates lipid metabolism genes in cancer cells and that Thr-59 phosphorylation of SREBP-1a plays an important role in cancer cell proliferation.