Bioinformatics Analysis Research Articles

Quantitative proteomics analysis reveals the pathogenesis of obstructed defecation syndrome caused by abnormal expression of dystrophin

BACKGROUND Obstructed defecation syndrome (ODS) represents the most prevalent form of chronic constipation, affecting a diverse patient population, leading to numerous complications, and imposing a significant burden on healthcare resources. Most ODS patients have insufficient rectal propulsion, but the exact mechanism underlying the pathogenesis of ODS remains unclear. AIM To explore the molecular mechanism underlying the pathogenesis of ODS. METHODS A total of 30 pairs of rectal samples were collected from patients with ODS (ODS group) or grade IV prolapsed hemorrhoids without constipation (control group) for quantitative proteomic and bioinformatic analysis. Subsequently, 50 pairs of paraffin-embedded rectal specimens were selected for immunohistochemistry and immunofluorescence studies to validate the analysis results. Human intestinal smooth cell contractile function experiments and electrophysiological experiments were conducted to verify the physiological functions of target proteins. Cellular ultrastructure was detected using transmission electron microscopy. RESULTS In comparison to the control group, the expression level of dystrophin (DMD) in rectal specimens from ODS patients was markedly reduced. This finding was corroborated using immunohistochemistry and immunofluorescence techniques. The diminished expression of DMD compromised the contractile function of intestinal smooth muscle cells. At the molecular level, nucleoporin protein 153 and L-type voltage-gated calcium channel were found to be overexpressed in intestinal smooth muscle cells exhibiting downregulated DMD expression. Electrophysiological experiments confirmed an excessive influx of calcium ions into these cells. Moreover, vacuolar-like structures which may be associated with excessive calcium influx were observed in the cells by transmission electron microscopy. CONCLUSION Decreased DMD expression in intestinal smooth muscle may upregulate L-type voltage-gated calcium channel expression, leading to excessive calcium influx which may cause a decrease in rectal propulsion, thereby contributing to the pathogenesis of ODS.

Epigenetic Suppression of miR-137 Induces RNF4 Expression, Facilitating Wnt Signaling in Colorectal Cancer.

Colorectal cancer (CRC) is a significant health issue worldwide. Recent studies highlight the critical role of miRNAs in CRC development, particularly miR-137, which acts as a key tumor suppressor. Despite its known role, further exploration of miR-137's downstream signaling is needed to understand its biology and therapeutic potential. We examined the methylation status of miR-137 using one TCGA data and three GEO data sets. A clinical validation cohort of 78 samples was analyzed using MSP for miR-137 promoter methylation. Various in vitro molecular/cellular and animal experiments were conducted to elucidate miR-137's role in CRC. Bioinformatic analysis indicated frequent methylation of miR-137 in CRC tissues, correlating with suppressed expression. EZH2-mediated H3K27 trimethylation silences miR-137 in CRC cells by increasing chromatin compaction, reversible by EZH2 siRNA or inhibitor GSK343. miR-137 inhibits CRC cell proliferation, migration, invasion, and xenograft tumor growth, confirming its tumor-suppressive role. Using the miRWalk repository showed that miR-137 regulates the Wnt signaling pathway by reducing typical protein expression in HCT116 and SW480 cells. miR-137 directly targets RNF4, leading to its downregulation at transcriptional and protein levels, with an observed inverse correlation in CRC tissues. miR-137 accelerates c-Myc and β-catenin degradation by inhibiting RNF4, impacting protein stability and Wnt pathway inhibition. miR-137 is epigenetically silenced through DNA methylation and EZH2-mediated H3K27 trimethylation. It regulates the Wnt signaling pathway by targeting RNF4, leading to c-Myc and β-catenin destabilization. Restoring miR-137 or inhibiting RNF4 suppresses CRC cell proliferation, migration, invasion, and tumor growth, highlighting its therapeutic potential in CRC.

Ampelopsis japonica enhances the effect of radiotherapy in non-small cell lung cancer.

Radiotherapy is widely used in the clinical treatment of non-small cell lung cancer (NSCLC); however, its effectiveness often proves unsatisfactory. Ampelopsis japonica (AJ) is atraditional Chinese herb with anti-inflammatory and anticancer activities. However, whether AJ could enhance the effect of radiotherapy in NSCLC needs to be further explored. In vivo, BALB/c nude mice were used for axenograft tumor model to explore whether AJ could enhance the effect of radiation therapy (RT) in NSCLC. In vitro, human NSCLC cell lines HCC827 and H1299 were used to explore the effect of AJ on the cell proliferation and apoptosis of RT-treated NSCLC. Moreover, bioinformatic analysis was performed to analyze the signaling pathways regulated by AJ. Ampelopsis japonica enhanced the inhibitory effect of RT on NSCLC tumor growth in vivo. Simultaneously, AJ further enhanced the inhibitory effect of RT on NSCLC proliferation and the promoting effect of RT on NSCLC apoptosis. Bioinformatic analysis showed that AJ regulated the PI3K-Akt signaling pathway. We confirmed that AJ decreased the protein levels of the PI3K-Akt signaling pathway. Furthermore, the combination of AJ and RT suppressed activation of the PI3K-Akt signaling pathway. Ampelopsis japonica augmented the inhibitory impact of RT on NSCLC cell proliferation and tumor growth by suppressing the PI3K-Akt signaling pathway.

Machine learning-based analysis of programmed cell death types and key genes in intervertebral disc degeneration.

Intervertebral disc degeneration (IVDD) is intricately associated with various forms of programmed cell death (PCD). Identifying key PCD types and associated genes is essential for understanding the molecular mechanisms underlying IVDD and discovering potential therapeutic targets. This study aimed to elucidate core PCD types, related genes, and potential drug interactions in IVDD using comprehensive bioinformatic and experimental approaches. Using datasets GSE167199, GSE176205, GSE34095, GSE56081, and GSE70362, relevant gene expression and clinical data were analyzed. Differential expression gene (DEG) analysis identified upregulated genes linked to 15 PCD types. Gene Set Variation Analysis (GSVA) was employed to pinpoint key PCD types contributing to disc degeneration. Core genes were identified through machine learning techniques, while immune infiltration and single-cell analysis helped identify apoptosis-related cell types. Molecular docking, along with in vivo and in vitro experiments using a murine IVDD model, validated potential drug interactions. The results identified apoptosis, autophagy, ferroptosis, and necroptosis as key PCD types in IVDD. A gene module associated with apoptosis showed a strong correlation with the severity of disc degeneration, revealing 34 central genes in the gene network. Drug screening identified Glibenclamide as effectively interacting with PDCD6 and UBE2K. Subsequent in vitro and in vivo experiments demonstrated that Glibenclamide reduced apoptosis and delayed disc degeneration progression. This study provides a comprehensive bioinformatics analysis of PCD in IVDD, identifying four primary PCD types contributing to the disease's progression. The findings offer novel insights into the molecular pathology of disc degeneration and suggest promising therapeutic strategies for future treatment development.

REV-ERBα Inhibits Osteoclastogenesis and Protects against Alveolar Bone Loss.

Circadian rhythm disruption is thought to be associated with periodontitis, and molecular clock genes play critical roles in regulating bone homeostasis. However, the specific contribution of molecular clock genes to alveolar bone resorption caused by periodontitis is poorly understood. In this study, we introduced a novel Periodontitis Circadian Rhythm Score (PeriCRS) model that was established through machine learning using periodontal transcriptomic data from periodontitis clinical cohorts in the Gene Expression Omnibus (GEO) database. This approach revealed the potential regulatory role of circadian rhythm disruption in periodontitis and identified key molecular clock genes associated with alveolar bone destruction. Moreover, we established an experimental periodontitis model with circadian rhythm disturbance via periodontal ligation in mice exposed to a 6-h advanced LD12:12 cycle every 2 d. Our bioinformatics analysis revealed that NR1D1, which encodes REV-ERBα, is a pivotal factor in the impact of circadian rhythm disruption on periodontitis in periodontal tissues. Next, we confirmed the abnormal expression of the molecular clock gene Rev-erbα in inflammatory periodontal tissue in mice and confirmed that circadian rhythm disruption altered REV-ERBα expression. Furthermore, the activation of REV-ERBα with the agonist SR9009 notably decreased RANKL-induced osteoclast differentiation and suppressed the expression of osteoclast-related factors. Subsequent in vivo experiments demonstrated that SR9009 mitigated alveolar bone loss caused by periodontitis. Mechanistically, we found that the IL-22-STAT3 pathway inhibited REV-ERBα expression and modulated RANKL-induced osteoclast differentiation in vitro. Our results elucidate the role of REV-ERBα in osteoclastogenesis and suggest a potential new therapeutic avenue for addressing alveolar bone resorption associated with periodontitis.

Casticin inhibits the hedgehog signaling and leads to apoptosis in AML stem-like KG1a and mature KG1 cells

Abstract Objectives Acute myeloid leukemia (AML) is a severe blood cancer with less than 50 % long-term survival. Despite advancements in treatment options, relapse is still the major obstacle. The main reason of this problem is ineffective targeting of leukemic stem cells (LSCs), which play an important role in tumor development and relapse. In our previous studies, we found that casticin, the major polyphenolic component of Vitex trifolia’s fruit, targets both leukemic cells and LSCs without affecting healthy tissues. Therefore, in this study, we aimed to investigate the effect of casticin-mediated cell death in relation to the LSCs-favored survival pathways at gene and protein expression levels using in vitro LSC-like and parental leukemic cell models. Methods We validated the LSC character of KG1a and KG1 cells (84.55 % CD34+, CD38- and 93.55 % CD34+, CD38+, respectively) by flow cytometry. For the investigation of casticin’s mechanism of action, we employed real time-PCR, western blotting and bioinformatics analyses. Results Our results showed an increase in cleaved PARP/β-actin ratio but no change in LC3BI/II and SQSTM/β-actin ratios. Our gene expression, bioinformatics and immunoblotting analyses represented significant decrease in Shh, Gli and Wnt levels. We also elucidated a possible crosstalk between Hedgehog and other oncogenic cascades via the Gli, Notch, YAP, p38, Mcl-1, and Myc proteins in casticin mediated anti-leukemic effect. Conclusions In conclusion, we found that casticin induces apoptosis in both LSC-like and parental leukemia cells mainly by suppressing Shh signaling, which is crucial for LSC survival and AML relapse.

Efficacy of colistin-based combinations against pandrug-resistant whole-genome-sequenced Klebsiella pneumoniae isolated from hospitalized patients in Egypt: an in vitro/vivo comparative study

BackgroundColistin resistance significantly constrains available treatment options and results in the emergence of pandrug-resistant (PDR) strains. Treating PDR infections is a major public health issue. A promising solution lies in using colistin-based combinations. Despite the availability of in vitro data evaluating these combinations, the in vivo studies remain limited.ResultsThirty colistin-resistant Klebsiella pneumoniae (ColRKp) isolates were collected from hospitalized patients. Colistin resistance was detected using broth microdilution, and antimicrobial susceptibility was tested using the Kirby-Bauer method against 18 antibiotics. Extremely high resistance levels were detected, with 17% of the isolates being PDR. Virulence profiling, assessed using Anthony capsule staining, the string test, and the crystal violet assay, indicated the predominance of non-biofilm formers and non-hypermucoid strains. The isolates were screened for mcr genes using polymerase chain reaction. Whole-genome sequencing (WGS) and bioinformatics analysis were performed to characterize the genomes of PDR isolates. No plasmid-borne mcr genes were detected, and WGS analysis revealed that PDR isolates belonged to the high-risk clones: ST14 (n = 1), ST147 (n = 2), and ST383 (n = 2). They carried genes encoding extended-spectrum β-lactamases and carbapenemases, blaCTX-M-15 and blaNDM-5, on conjugative IncHI1B/IncFIB plasmids, illustrating the convergence of virulence and resistance genes. The most common mechanism of colistin resistance involved alterations in mgrB. Furthermore, deleterious amino acid substitutions were also detected within PhoQ, PmrC, CrrB, ArnB, and ArnT. Seven colistin-containing combinations were compared using the checkerboard experiment. Synergy was observed when combining colistin with tigecycline, doxycycline, levofloxacin, ciprofloxacin, sulfamethoxazole/trimethoprim, imipenem, or meropenem. The efficacy of colistin combined with either doxycycline or levofloxacin was assessed in vitro using a resistance modulation assay, and in vivo, using a murine infection model. In vitro, doxycycline and levofloxacin reversed colistin resistance in 80% and 73.3% of the population, respectively. In vivo, the colistin + doxycycline combination demonstrated superiority over colistin + levofloxacin, rescuing 80% of infected animals, and reducing bacterial bioburden in the liver and kidneys while preserving nearly intact lung histology.ConclusionsThis study represents the first comparative in vitro and in vivo investigation of the efficacy of colistin + doxycycline and colistin + levofloxacin combinations in clinical PDR ColRKp isolates characterized at a genomic level.

Identification and validation of cigarette smoking-related genes in predicting prostate cancer development through bioinformatic analysis and experiments

The morbidity and mortality rates of prostate cancer (PCa) are high among elderly men worldwide. Several factors, such as heredity, obesity, and environment are associated with the occurrence of PCa. Cigarette smoking, which is also an important factor in the development of PCa, can lead to genetic alterations and consequently promote PCa development. However, the smoking-induced genetic alterations in PCa are unclear. This study aimed to identify the potential smoking-related genes associated with PCa development. The smoking-related differentially expressed genes (DEGs) were identified using the Gene Expression Omnibus (GEO) which included lots of PCa datasets. DEGs were subjected to protein–protein interaction (PPI) network analysis to identify the hub genes. The pathways in which these hub genes were enriched were identified. The Cancer Genome Atlas (TCGA) dataset was used to examine the expression of smoking-related genes in PCa samples and estimate their value in predicting tumor progression and prognosis. In total, 110 smoking-related DEGs were got from GSE68135 dataset which included microarray data of PCa patients with smoking or not and 14 smoking-related key genes associated with PCa were identified from PPI network. The expression of the following seven key genes was altered in TCGA PCa patients: EWSR1, SRSF6, COL6A3, FBLN1, DCN, CYP2J2, and PLA2G2A. EWSR1, SRSF6, FBLN1, and CYP2J2 also influenced PCa progression. Additionally, EWSR1 influenced disease-free survival. In the logistic regression model, CYP2J2, which exhibited the highest risk scores, was identified as the risk gene for PCa. We also found one of the smoking-related genes: EWSR1 was truly upregulated in clinical PCa patients and influenced PCa cells invasion and proliferation. This study identified the function of smoking-related genes involved in the progression of PCa.

Polyphosphate Kinase from Burkholderia cenocepacia, One Enzyme Catalyzing a Two-Step Cascade Reaction to Synthesize ATP from AMP

This study characterizes a novel polyphosphate kinase from Burkholderia cenocepacia (BcPPK2-III), an enzyme with potential applications in ATP regeneration processes. Bioinformatic and structural analyses confirmed the presence of conserved motifs characteristic of PPK2 enzymes, including Walker A and B motifs, and the subclass-specific residue E137. Molecular docking simulations showed AMP had the highest binding affinity (−7.0 kcal/mol), followed by ADP (−6.5 kcal/mol), with ATP having the lowest affinity (−6.3 kcal/mol). It was overexpressed in Escherichia coli, after purification enzymatic activity assays revealed that BcPPK2-III needed divalent cations (Mg2⁺, Mn2⁺, Co2⁺) as cofactors to be active. Functional assays revealed its ability to synthesize ATP from AMP through a stepwise phosphorylation mechanism, forming ADP as an intermediate, achieving 70% ATP conversion (TTN 4354.7) after 24 h. Kinetic studies indicated cooperative behavior and substrate preference, with AMP phosphorylation to ADP being the most efficient step. The enzyme demonstrated high thermostability (T50 = 62 °C) and a broad pH stability range (pH 6.0–9.0), making it suitable for diverse biocatalytic applications. The study highlights BcPPK2-III as a robust and versatile candidate for cost-effective ATP regeneration, offering advantages in industrial processes requiring stoichiometric amounts of ATP.

Experimental Evolution of Poxviruses.

Experimental evolution is the process of exposing virus populations to defined selective pressures in a laboratory setting to identify adaptive changes. Coupled with deep sequencing, this experimental approach allows for nucleotide-level resolution of poxvirus adaptive strategies over time. Here, we present a general method of poxvirus experimental evolution, Illumina-based deep sequencing, and bioinformatic analyses to identify structural changes (e.g., gene duplication) as well as local adaptive changes (e.g., small indels and single nucleotide polymorphisms).

Prognostic significance of CNNM4 in ovarian cancer: a comprehensive bioinformatics analysis

BackgroundOvarian cancer (OV) is a common malignancy in the female reproductive system, characterized by poor prognosis and high recurrence rates. The discovery of dependable molecular markers is crucial for improving the timeliness of detection, diagnosis, and treatment, ultimately aiming to lower fatality rates. CNNM4 (cyclin and CBS domain divalent metal cation transport mediator 4), a member of the CNNM (Cyclin M) family, binds to PRL (prolactin) to regulate magnesium homeostasis and influence tumor cell proliferation. Although CNNM4 is implicated in various cancers, its role in OV remains unclear.MethodsIn vitro experiments assessed CNNM4 expression and its impact on the proliferation and migration of OV cells. Comparisons of TCGA and GTEx data were used to identify correlations between clinical features and outcomes. The role of CNNM4 in OV was further explored through comprehensive bioinformatics analyses.ResultsElevated levels of CNNM4 expression were observed in OV cells and tissues, and were linked to a poor prognosis. CNNM4 could modulate the proliferation and migration of various OV cell lines, including IOSE-80, SKOV-3, and A2780. Through involvement in multiple signaling pathways, evidenced by GSVA and GSEA, CNNM4 was implicated in OV progression. CNNM4 positively regulated the infiltration level of Macrophages M2, T cells CD4 memory resting and NK cells resting, and had a negative regulation effect on NK cells activated and T cells gamma delta. Moreover, CNNM4 is related to drug sensitivity of OV. A prediction model based on CNNM4 expression and clinical symptoms was constructed to predict OV prognosis.ConclusionCNNM4 may affect the progression of OV and is associated with a poor prognosis. It has potential as a biomarker for predicting survival and as a target for therapeutic interventions in OV patients.

Surgery-induced neuroinflammatory transcriptional programs in medial prefrontal cortex of mice during early phase of perioperative neurocognitive disorders

Patients receiving anesthesia and surgery may experience cognitive dysfunction, memory deficits, and mental disturbances, which are referred to as perioperative neurocognitive disorders (PND). The function of the medial prefrontal cortex (mPFC) is disrupted during early phase of PND. To gain insight into the mechanisms of PND, we collected mouse mPFC tissues 6 h post-surgery and performed RNA sequencing analysis. In total, 178 differentially expressed genes (DEGs) were identified, including 105 upregulated and 73 downregulated genes. Bioinformatic analysis highlighted the significant enrichment of these DEGs in several immune-related biological processes and signaling pathways, suggesting that pronounced neuroinflammatory transcriptional programming in the mPFC was evoked during early phase of PND. Interleukin-6 level increased in both serum and mPFC, while the mRNA levels of Il-6, Tnf-α, and Il-1β remained unchanged. Taken together, our findings suggest that a distinct and acute neuroinflammatory response in the mPFC is evoked after peripheral surgery, which might play a key role in the development of PND.

GLP-1RA improves diabetic renal injury by alleviating glomerular endothelial cells pyrotosis via RXRα/circ8411/miR-23a-5p/ABCA1 pathway.

Lipotoxicity has been implicated in diabetic kidney disease (DKD). However, the role of high glucose levels in DKD and the underlying renal protective mechanisms of GLP-1 receptor agonists (GLP-1RAs) remain unclear. To investigate cholesterol accumulation, pyroptosis in glomerular endothelial cells (GEnCs), and the renal protective mechanisms of GLP-1RAs, we used various techniques, including RT-qPCR, Oil Red O staining, Western blotting, lactate dehydrogenase (LDH) activity assays, circRNA microarrays, bioinformatics analysis, gain and loss-of-function experiments, rescue experiments, and luciferase assays. Additionally, in vivo experiments were conducted using C57BL/6J and ApoE-deficient (ApoE-/-) mice. GEnCs exposed to high glucose exhibited reduced cholesterol efflux, which was accompanied by downregulation of ATP-binding cassette transporter A1 (ABCA1) expression, cholesterol accumulation, and pyroptosis. Circ8411 was identified as a regulator of ABCA1, inhibiting miR-23a-5p through its binding to the 3'UTR. Additionally, higher glucose levels decreased circ8411 expression by inhibiting RXRα. GLP-1RAs effectively reduced cholesterol accumulation and cell pyroptosis by targeting the RXRα/circ8411/miR-23a-5p/ABCA1 pathway. In diabetic ApoE-/- mice, renal structure and function were impaired, with resulted in increased cholesterol accumulation and pyroptosis; however, GLP-1RAs treatment reversed these detrimental changes. These findings suggest that the RXRα/circ8411/miR-23a-5p/ABCA1 pathway mediates the contribution of high glucose to lipotoxic renal injury. Targeting this pathway may represent a potential therapeutic strategy for patients with DKD and hypercholesterolemia. Moreover, GLP-1RAs may provide renal protective effects by activating this pathway.

METTL3-Induced m6A Modification Enhances Hsa_Circ_0136959 Expression to Impair the Tumor Characteristics of Papillary Thyroid Carcinoma via Accelerating Ferroptosis.

The number of cases of papillary thyroid cancer (PTC) has gone up significantly in recent years, with high recurrence. Numerous reports have highlighted the participation of circular RNAs (circRNAs) in regulating the advancement of cancers, including PTC. Furthermore, recent studies suggest that N6-methyladenosine (m6A) modified circRNAs play pivotal roles in cancer progression. Hence, we studied the potential role of a novel circRNA, hsa_circ_0136959, and its regulatory mechanism on m6A modification by methyltransferase-like 3 (METTL3) in the tumor characteristics of PTC. The expressions of hsa_circ_0136959 and METTL3 were evaluated in PTC samples and cell lines via quantitative real-time polymerase chain reaction. The effect of hsa_circ_0136959 on the malignant properties of PTC was analyzed by performing Cell Counting Kit-8, colony formation, and transwell assays. In addition, its effects on the levels of markers related to ferroptosis (reactive oxygen species, Fe2+, and iron) in PTC cells were also assessed. Bioinformatics analysis was done to determine the hsa_circ_0136959 expression and m6A modification sites on it in PTC. The m6A level of hsa_circ_0136959 was analyzed through methylated (m6A) RNA immunoprecipitation. The hsa_circ_0136959 was observed to be downregulated in both PTC samples and cells. In vitro experiments showed that its overexpression impeded the malignant properties of PTC cells. Moreover, hsa_circ_0136959 overexpression increased the levels of ferroptosis-related markers in PTC cells. We also found that METTL3 was notably reduced in PTC samples and was positively correlated with hsa_circ_0136959. Mechanistically, METTL3 enhanced hsa_circ_0136959 expression through m6A modification. Our results demonstrate that METTL3-mediated m6A modification elevated hsa_circ_0136959 expression and subsequently restricted the tumor characteristics of PTC by accelerating ferroptosis.

Identification and Analysis of Autophagy-Related Genes as Diagnostic Markers and Potential Therapeutic Targets for Tuberculosis Through Bioinformatics.

According to the World Health Organization, Mycobacterium tuberculosis infections affect approximately 25% of the world's population. There is mounting evidence linking autophagy and immunological dysregulation to tuberculosis (TB). As a result, this research set out to discover TB-related autophagy-related biomarkers and prospective treatment targets. We used five autophagy databases to get genes linked to autophagy and Gene Expression Omnibus databases to get genes connected to TB. Then, functional modules associated with autophagy were obtained by analyzing them using weighted gene co-expression network analysis. Both Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used to examine the autophagy-related genes (ATGs) of important modules. Limma was used to identify differentially expressed ATGs (DE-ATGs), and the external datasets were used to further confirm their identification. We used DE-ATGs and a protein-protein interaction network to search the hub genes. CIBERSORT was used to estimate the kinds and amounts of immune cells. After that, we built a drug-gene interaction network and a network that included messenger RNA, small RNA, and DNA. At last, the differential expression of hub ATGs was confirmed by RT-qPCR, immunohistochemistry, and western blotting. The diagnostic usefulness of hub ATGs was evaluated using receiver operating characteristic curve analysis. Including 508 ATGs, four of the nine modules strongly linked with TB were deemed essential. Interleukin 1B (IL1B), CAPS1, and signal transducer and activator of transcription 1 (STAT1) were identified by intersection out of 22 DE-ATGs discovered by differential expression analysis. Research into immune cell infiltration found that patients with TB had an increased proportion of plasma cells, CD8 T cells, and M0 macrophages. A competitive endogenous RNA network utilized 10 long non-coding RNAs and 2 miRNAs. Then, the IL1B-targeted drug Cankinumad was assessed using this network. During bioinformatics analysis, three hub genes were validated in mouse and macrophage infection models. We found that IL1B, CASP1, and STAT1 are important biomarkers for TB. As a result, these crucial hub genes may hold promise as TB treatment targets.

Accurate prediction of colorectal cancer diagnosis using machine learning based on immunohistochemistry pathological images

Colorectal cancer (CRC) ranks as the third most prevalent tumor and the second leading cause of mortality. Early and accurate diagnosis holds significant importance in enhancing patient treatment and prognosis. Machine learning technology and bioinformatics have provided novel approaches for cancer diagnosis. This study aims to develop a CRC diagnostic model based on immunohistochemical staining image features using machine learning methods. Initially, CRC disease-specific genes were identified through bioinformatics analysis, SVM-RFE and Random Forest algorithm utilizing RNA-seq data from both GEO and TCGA databases. Subsequently, verification of these genes was performed using proteomics data from CPTAC and HPA database, resulting in identification of target proteins (AKR1B10, CA2, DHRS9, and ZG16) for further investigation. SVM and CNN were then employed to analyze and integrate the characteristics of immunohistochemical images to construct a reliable CRC diagnostic model. During the training and validation process of this model, cross-validation along with external validation methods were implemented to ensure accuracy and reliability. The results demonstrate that the established diagnostic model exhibits excellent performance in distinguishing between CRC and normal controls (accuracy rate: 0.999), thereby presenting potential prospects for clinical application. These findings are expected to provide innovative perspectives as well as methodologies for personalized diagnosis of CRC while offering more precise references for promising treatment.

Identification of immune-related hub genes and potential molecular mechanisms involved in COVID-19 via integrated bioinformatics analysis

COVID-19, caused by the SARS-CoV-2 virus, poses significant health challenges worldwide, particularly due to severe immune-related complications. Understanding the molecular mechanisms and identifying key immune-related genes (IRGs) involved in COVID-19 pathogenesis is critical for developing effective prevention and treatment strategies. This study employed computational tools to analyze biological data (bioinformatics) and a method for inferring causal relationships based on genetic variations, known as Mendelian randomization (MR), to explore the roles of IRGs in COVID-19. We identified differentially expressed genes (DEGs) from datasets available in the Gene Expression Omnibus (GEO), comparing COVID-19 patients with healthy controls. IRGs were sourced from the ImmPort database. We conducted functional enrichment analysis, pathway analysis, and immune infiltration assessments to determine the biological significance of the identified IRGs. A total of 360 common differential IRGs were identified. Among these genes, CD1C, IL1B, and SLP1 have emerged as key IRGs with potential protective effects against COVID-19. Pathway enrichment analysis revealed that CD1C is involved in terpenoid backbone biosynthesis and Th17 cell differentiation, while IL1B is linked to B-cell receptor signaling and the NF-kappa B signaling pathway. Significant correlations were observed between key genes and various immune cells, suggesting that they influence immune cell modulation in COVID-19. This study provides new insights into the immune mechanisms underlying COVID-19, highlighting the crucial role of IRGs in disease progression. These findings suggest that CD1C and IL1B could be potential therapeutic targets. The integrated bioinformatics and MR analysis approach offers a robust framework for further exploring immune responses in COVID-19 patients, as well as for targeted therapy and vaccine development.

PHP-Family Diesterase from Novosphingobium with Broad Specificity and High Catalytic Efficiency against Organophosphate Flame-Retardant Derived Diesters.

Organophosphate flame retardants have been widely used in plastic products since the early 2000s. Unfortunately, these compounds leach out of the plastics over time and are carcinogenic, developmental toxins, and endocrine disruptors. Due to the high usage levels and stable nature of the compounds, widespread contamination of the environment has now been observed. Despite their recent introduction into the environment, bacteria from the Sphingomonadaceae family have evolved a three-step hydrolytic pathway to utilize these compounds. The second step in this pathway in Sphingobium sp. TCM1 is catalyzed by Sb-PDE, which is a member of the polymerase and histidinol phosphatase (PHP) family of phosphatases. This enzyme is only the second case of a PHP-family enzyme capable of hydrolyzing phosphodiesters. Bioinformatics analysis has now been used to identify a second PHP diesterase from Novosphingobium sp. EMRT-2 (No-PDE). Kinetic characterization of Sb-PDE and No-PDE with authentic organophosphate flame-retardant diesters demonstrates that these enzymes are true diesterases with more than 1000-fold selectivity for the diesterase activity seen in some cases. Synthesis of a wide array of authentic flame-retardant diesters has allowed the substrate specificity of these enzymes to be determined, and mutagenic analysis of the active site residues has identified key residues that give rise to the high levels of diesterase activity. Despite high sequence identity, No-PDE is found to have a broader substrate specificity against flame-retardant derived diesters, and kcat/Km values greater than 104 M-1 s-1 are seen with the best substrates.

Transcriptomic analysis of regulatory mechanisms in the telogen-anagen transition of ovine hair follicles

BackgroundDorper sheep are celebrated for their fast maturation and superior meat quality, with some shedding their wool each spring. Wool shedding occurs naturally due to the hair follicle (HF) cycle, but its regulatory mechanisms remain unclear and need further investigation.ResultsIn this study, shedding and non-shedding sheep were selected from the same Dorper flock. Skin samples were collected in September of the first year and January and March of the following years. RNA sequencing was performed on these samples. Principal component analysis (PCA) was used to assess the results. A total of 2536 differentially expressed genes (DEGs) were identified. Using a clustering heatmap and fuzzy clustering analysis three distinct gene expression patterns were identified: A pattern (high expression in anagen), T1 pattern, and T2 pattern (high expression in telogen). For each pattern, differentially expressed genes (DEGs) were analyzed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Combining this with pathway expression analysis, six A-pattern and fourteen T-pattern pathways linked to telogen-anagen transition in the HF cycle were identified. Networks of key pathways were then constructed. Additionally, key genes were identified in the telogen-anagen transition, including one A-pattern gene and seven T-pattern (T1, 1; T2, 6) genes, using the Maximal Clique Centrality (MCC) tool in Cytoscape. Predicted transcription factors (TFs) involved in key pathways, such as LEF and STAT5B, were identified. Finally, RNA-seq results were confirmed by RT-qPCR.ConclusionThis study highlights critical genes and pathways in the telogen-anagen transition, and transcriptome sequencing along with bioinformatics analysis provides new insights into the regulatory mechanisms of the HF cycle and development.

Circ_0000972 Inhibits Hepatocellular Carcinoma Cell Stemness by Targeting miR-96-5p/PFN1.

Previous study has identified circRNAs as an important factor in cancer stem cells (CSCs) progression, which contributes to tumor initiation and progression. This study aspired to uncover the mechanisms of circ_0000972 on hepatocellular carcinoma (HCC) CSCs. RT-qPCR was utilized to quantify circ_0000972, miR-96-5p, and profilin 1(PFN1) expression in HCC tissues and cells. To evaluate the in vivo functions of circ_0000972, HCC cells with circ_0000972 overexpression were utilized to establish xenograft model through subcutaneous injection. The cell colony and sphere formation assays were adopted to evaluate the impact of circ_0000972 on the stemness characteristics of HCC cells. Additionally, the interaction between circ_0000972, miR-96-5p, and PFN1 was determined through bioinformatics analysis, dual-luciferase reporter assays, and rescue experiments. Circ_0000972 and PFN1 expression was significantly downregulated in HCC tissues and cells, while miR-96-5p exhibited an increased expression level. The overexpression of circ_0000972 was observed to inhibit the cell colony, sphere formation, and EMT of HCC CSCs. In xenograft model, circ_0000972 overexpression restrained the tumor volume and weight. Mechanistically, circ_0000972 stimulated PFN1 expression through the inhibition of miR-96-5p. More importantly, circ_0000972 overexpression could promote PFN1 expression and inhibit the stemness of HCC CSCs. Interestingly, the effect of circ_0000972 overexpression on such progresses was reversed by PFN1 silencing. This study elucidates that circ_0000972, an antitumor factor, sponges miR-96-5p to inhibit oncogenic cellular process in HCC by mediating PFN1 expression.