Identifying essential genes in a given organism is important for research on their fundamental roles in organism survival. Furthermore, if possible, uncovering the links between core functions or ...pathways with these essential genes will further help us obtain deep insight into the key roles of these genes. In this study, we investigated the essential and non-essential genes reported in a previous study and extracted gene ontology (GO) terms and biological pathways that are important for the determination of essential genes. Through the enrichment theory of GO and KEGG pathways, we encoded each essential/non-essential gene into a vector in which each component represented the relationship between the gene and one GO term or KEGG pathway. To analyze these relationships, the maximum relevance minimum redundancy (mRMR) was adopted. Then, the incremental feature selection (IFS) and support vector machine (SVM) were employed to extract important GO terms and KEGG pathways. A prediction model was built simultaneously using the extracted GO terms and KEGG pathways, which yielded nearly perfect performance, with a Matthews correlation coefficient of 0.951, for distinguishing essential and non-essential genes. To fully investigate the key factors influencing the fundamental roles of essential genes, the 21 most important GO terms and three KEGG pathways were analyzed in detail. In addition, several genes was provided in this study, which were predicted to be essential genes by our prediction model. We suggest that this study provides more functional and pathway information on the essential genes and provides a new way to investigate related problems.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Colorectal cancer is the third most common cancer in males and second in females. This disease can be caused by genetic and acquired/environmental factors. Microsatellite instability (MSI) is one of ...the major mechanisms in colorectal cancer. This mechanism is a specific condition of genetic hyper mutability that results from incompetent DNA mismatch repair. MSI has been applied to classify different colorectal cancer subtypes. However, the effects of MSI status on gene expression are largely unknown. In our study, we integrated the gene expression profile and MSI status of all CRC samples from the TCGA database, and then categorized the CRC samples into three subgroups, namely, MSI‐stable, MSI‐low, and MSI‐high, according to the MSI status. We applied a novel computational method based on machine learning and screened the genes specifically expressed for the different colorectal cancer subtypes. The results showed the distinct mechanisms of the different colorectal cancer subtypes with MSI status and provided the genes that may be the optimal standards to further classify the various molecular subtypes of colorectal cancer with distinct MSI status.
What's new?
Microsatellite instability (MSI), a key genetic mechanism implicated in colorectal cancer (CRC), is linked to drug reactivity and sensitivity in CRC patients and is useful for CRC subtype classification. Yet, little is known about the identity of MSI‐associated genes or their role in CRC. Here, combined analysis of datasets on gene‐expression profile and MSI status enabled the investigation of a number of differentially expressed genes from CRC samples. Genes optimal for the classification of CRC subtypes with different MSI statuses were identified. The gene panel could facilitate the discovery of biomarkers specific for CRCs with known MSI status.
Since the outbreak in late December 2019 in Wuhan, China, coronavirus disease-2019 (COVID-19) has become a global pandemic. We analyzed and compared the clinical, laboratory, and radiological ...characteristics between survivors and non-survivors and identify risk factors for mortality.
Clinical and laboratory variables, radiological features, treatment approach, and complications were retrospectively collected in two centers of Hubei province, China. Cox regression analysis was conducted to identify the risk factors for mortality.
A total of 432 patients were enrolled, and the median patient age was 54 years. The overall mortality rate was 5.09% (22/432). As compared with the survivor group (n = 410), those in the non-survivor group (n = 22) were older, and they had a higher frequency of comorbidities and were more prone to suffer from dyspnea. Several abnormal laboratory variables indicated that acute cardiac injury, hepatic damage, and acute renal insufficiency were detected in the non-survivor group. Non-surviving patients also had a high computed tomography (CT) score and higher rate of consolidation. The most common complication causing death was acute respiratory distress syndrome (ARDS) (18/22, 81.8%). Multivariate Cox regression analysis revealed that hemoglobin (Hb) <90 g/L (hazard ratio, 10.776; 95% confidence interval, 3.075-37.766; p<0.0001), creatine kinase (CK-MB) >8 U/L (9.155; 2.424-34.584; p = 0.001), lactate dehydrogenase (LDH) >245 U/L (5.963; 2.029-17.529; p = 0.001), procalcitonin (PCT) >0.5 ng/ml (7.080; 1.671-29.992; p = 0.008), and CT score >10 (39.503; 12.430-125.539; p<0.0001) were independent risk factors for the mortality of COVID-19.
Low Hb, high LDH, PCT, and CT score on admission were the predictors for mortality and could assist clinicians in early identification of poor prognosis among COVID-19 patients.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Synthetic lethality is the synthesis of mutations leading to cell death. Tumor‐specific synthetic lethality has been targeted in research to improve cancer therapy. With the advances of techniques in ...molecular biology, such as RNAi and CRISPR/Cas9 gene editing, efforts have been made to systematically identify synthetic lethal interactions, especially for frequently mutated genes in cancers. However, elucidating the mechanism of synthetic lethality remains a challenge because of the complexity of its influencing conditions. In this study, we proposed a new computational method to identify critical functional features that can accurately predict synthetic lethal interactions. This method incorporates several machine learning algorithms and encodes protein‐coding genes by an enrichment system derived from gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways to represent their functional features. We built a random forest‐based prediction engine by using 2120 selected features and obtained a Matthews correlation coefficient of 0.532. We examined the top 15 features and found that most of them have potential roles in synthetic lethality according to previous studies. These results demonstrate the ability of our proposed method to predict synthetic lethal interactions and provide a basis for further characterization of these particular genetic combinations.
A computational analysis of synthetic lethality was performed in this study. Synthetic lethality gene pairs were encoded via enrichment theory of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Advanced computational methods were adopted to build an optimal prediction model and extract important features.
Smart thermal interface materials must exhibit self-healability and high thermal conductivity (k) and elastic deformation as they can experience repeated compression and undergo sudden damage. ...However, it remains challenging to ensure high phonon mobility/efficient phonon transfer, self-healing, and good elasticity by optimizing its molecular orientation or cross-links. Herein, a self-healing and elastic polyimide copolymer (EMPI) cross-linked by flexible and rigid segments is uniformly filled into the gaps of a forest of vertically aligned carbon nanotubes (VACNTs). The EMPI@VACNTs composite exhibits a high k value at 10.83 ± 0.22 W m−1 K−1, low interfacial thermal resistance at 6.83 ± 0.15 K mm2 W−1, high elastic compressive deformation (30% at 2.5 MPa), and strong surface adhesion (0.3 MPa). Further, it could recover 90.8% of its elastic modulus and 92% of its thermal resistance after self-healing at 80 °C for 80 h. An EMPI@VACNTs-Cu device exhibits efficient heat conduction not only by recovering after gradient compressive strains of up to 30% but also by self-healing its damage or reforming the interface with Cu. Thus, the thermally conductive, self-healing, and elastic EMPI@VACNTs composite opens new avenues for smart thermal management in various high-power/intelligent devices.
Efficient heat conduction across the complex interface between two types of materials is essential for thermal management in advanced systems. The self-healable, elastic EMPI@VACNTs composite opens new avenues for smart thermal management, and it exhibits a high thermal conductivity, low interfacial thermal resistance, high elastic compressive deformation, and strong surface adhesion. Display omitted
Melatonin is a pleiotropic signaling molecule that provides physiological protection against diverse environmental stresses in plants. Nonetheless, the mechanisms for melatonin‐mediated ...thermotolerance remain largely unknown. Here, we report that endogenous melatonin levels increased with a rise in ambient temperature and that peaked at 40°C. Foliar pretreatment with an optimal dose of melatonin (10 μmol/L) or the overexpression of N‐acetylserotonin methyltransferase (ASMT) gene effectively ameliorated heat‐induced photoinhibition and electrolyte leakage in tomato plants. Both exogenous melatonin treatment and endogenous melatonin manipulation by overexpression of ASMT decreased the levels of insoluble and ubiquitinated proteins, but enhanced the expression of heat‐shock proteins (HSPs) to refold denatured and unfolded proteins under heat stress. Meanwhile, melatonin also induced expression of several ATG genes and formation of autophagosomes to degrade aggregated proteins under the same stress. Proteomic profile analyses revealed that protein aggregates for a large number of biological processes accumulated in wild‐type plants. However, exogenous melatonin treatment or overexpression of ASMT reduced the accumulation of aggregated proteins. Aggregation responsive proteins such as HSP70 and Rubisco activase were preferentially accumulated and ubiquitinated in wild‐type plants under heat stress, while melatonin mitigated heat stress‐induced accumulation and ubiquitination of aggregated proteins. These results suggest that melatonin promotes cellular protein protection through induction of HSPs and autophagy to refold or degrade denatured proteins under heat stress in tomato plants.
Coronavirus disease 2019 (COVID-19) is a new respiratory and systemic disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The purpose of the present study was to ...investigate the association between cytokine profiles and lung injury in COVID-19 pneumonia.
This retrospective study was conducted in COVID-19 patients. Demographic characteristics, symptoms, signs, underlying diseases, and laboratory data were collected. The patients were divided into COVID-19 with pneumonia and without pneumonia. CT severity score and PaO
/FiO
ratio were used to assess lung injury.
106 patients with 12 COVID-19 without pneumonia and 94 COVID-19 with pneumonia were included. Compared with COVID-19 without pneumonia, COVID-19 with pneumonia had significantly higher serum interleukin (IL)-2R, IL-6, and tumor necrosis factor (TNF)-α. Correlation analysis showed that CT severity score and PaO
/FiO
were significantly correlated with age, presence of any coexisting disorder, lymphocyte count, procalcitonin, IL-2R, and IL-6. In multivariate analysis, log IL6 was the only independent explanatory variables for CT severity score (β = 0.397, p < 0.001) and PaO
/FiO
(β = - 0.434, p = 0.003).
Elevation of circulating cytokines was significantly associated with presence of pneumonia in COVID-19 and the severity of lung injury in COVID-19 pneumonia. Circulating IL-6 independently predicted the severity of lung injury in COVID-19 pneumonia.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Melatonin regulates broad aspects of plant responses to various biotic and abiotic stresses, but the upstream regulation of melatonin biosynthesis by these stresses remains largely unknown. Herein, ...we demonstrate that transcription factor heat‐shock factor A1a (HsfA1a) conferred cadmium (Cd) tolerance to tomato plants, in part through its positive role in inducing melatonin biosynthesis under Cd stress. Analysis of leaf phenotype, chlorophyll content, and photosynthetic efficiency revealed that silencing of the HsfA1a gene decreased Cd tolerance, whereas its overexpression enhanced plant tolerance to Cd. HsfA1a‐silenced plants exhibited reduced melatonin levels, and HsfA1a overexpression stimulated melatonin accumulation and the expression of the melatonin biosynthetic gene caffeic acid O‐methyltransferase 1 (COMT1) under Cd stress. Both an in vitro electrophoretic mobility shift assay and in vivo chromatin immunoprecipitation coupled with qPCR analysis revealed that HsfA1a binds to the COMT1 gene promoter. Meanwhile, Cd stress induced the expression of heat‐shock proteins (HSPs), which was compromised in HsfA1a‐silenced plants and more robustly induced in HsfA1a‐overexpressing plants under Cd stress. COMT1 silencing reduced HsfA1a‐induced Cd tolerance and melatonin accumulation in HsfA1a‐overexpressing plants. Additionally, the HsfA1a‐induced expression of HSPs was partially compromised in COMT1‐silenced wild‐type or HsfA1a‐overexpressing plants under Cd stress. These results demonstrate that HsfA1a confers Cd tolerance by activating transcription of the COMT1 gene and inducing accumulation of melatonin that partially upregulates expression of HSPs.
Summary
Fusarium head blight (FHB) and Fusarium seedling blight (FSB) of wheat, caused by Fusarium pathogens, are devastating diseases worldwide. We report the expression of RNA interference (RNAi) ...sequences derived from an essential Fusarium graminearum (Fg) virulence gene, chitin synthase (Chs) 3b, as a method to enhance resistance of wheat plants to fungal pathogens. Deletion of Chs3b was lethal to Fg; disruption of the other Chs gene family members generated knockout mutants with diverse impacts on Fg. Comparative expression analyses revealed that among the Chs gene family members, Chs3b had the highest expression levels during Fg colonization of wheat. Three hairpin RNAi constructs corresponding to the different regions of Chs3b were found to silence Chs3b in transgenic Fg strains. Co‐expression of these three RNAi constructs in two independent elite wheat cultivar transgenic lines conferred high levels of stable, consistent resistance (combined type I and II resistance) to both FHB and FSB throughout the T3 to T5 generations. Confocal microscopy revealed profoundly restricted mycelia in Fg‐infected transgenic wheat plants. Presence of the three specific short interfering RNAs in transgenic wheat plants was confirmed by Northern blotting, and these RNAs efficiently down‐regulated Chs3b in the colonizing Fusarium pathogens on wheat seedlings and spikes. Our results demonstrate that host‐induced gene silencing of an essential fungal chitin synthase gene is an effective strategy for enhancing resistance in crop plants under field test conditions.
Adult neural stem cells (NSCs) are a group of multi‐potent, self‐renewing progenitor cells that contribute to the generation of new neurons and oligodendrocytes. Three subtypes of NSCs can be ...isolated based on the stages of the NSC lineage, including quiescent neural stem cells (qNSCs), activated neural stem cells (aNSCs) and neural progenitor cells (NPCs). Although it is widely accepted that these three groups of NSCs play different roles in the development of the nervous system, their molecular signatures are poorly understood. In this study, we applied the Monte‐Carlo Feature Selection (MCFS) method to identify the gene expression signatures, which can yield a Matthews correlation coefficient (MCC) value of 0.918 with a support vector machine evaluated by ten‐fold cross‐validation. In addition, some classification rules yielded by the MCFS program for distinguishing above three subtypes were reported. Our results not only demonstrate a high classification capacity and subtype‐specific gene expression patterns but also quantitatively reflect the pattern of the gene expression levels across the NSC lineage, providing insight into deciphering the molecular basis of NSC differentiation.
The program of MCFS method produced six IF‐THEN rules for identification of different subtypes of NSCs. The performance of these IF‐THEN rules is quite good and these rules provide a more clear picture for the classification of each NSC.