Prenatal detection of chromosome 7q deletion with duplication: A case report and literature review.

RATIONALE: With advances in prenatal diagnostic techniques, chromosomal microdeletions and microduplications have become the focus of prenatal diagnosis. 7q partial monosomy or trisomy due to a deletion or duplication of the 7q end is relatively rare and usually originates from parents carrying a balanced translocation. PATIENT CONCERNS: Noninvasive prenatal screening (NIPT) showed a fetus with partial deletion and duplication of chromosome 7q. It was not possible to determine whether the fetus was normal. DIAGNOSES: Conventional chromosome G-banding and chromosome microarray analysis (CMA) were performed on fetal amniotic fluid samples and parental peripheral blood samples. INTERVENTIONS: The pregnant women were given detailed genetic counseling by clinicians. OUTCOMES: The fetal karyotype was 46, XY on conventional G-banding analysis. The CMA test results showed a deletion of approximately 7.8 Mb in the 7q36.1q36.3 region and a duplication of 6.6Mb in the 7q35q36.1 region. The parents' karyotype analysis and CMA results were normal, indicating a new mutation. LESSONS: CMA molecular diagnostic analysis can effectively detect chromosomal microdeletions or microduplications, clarify the relationship between fetal genotype and clinical phenotype, and provide a reference for prenatal diagnosis of chromosomal microdeletion-duplication syndrome.

Prenatal diagnosis of a trisomy 7 mosaic case: CMA, CNV-seq, karyotyping, interphase FISH, and MS-MLPA, which technique to choose?

OBJECTIVE: This study aims to perform a prenatal genetic diagnosis of a high-risk fetus with trisomy 7 identified by noninvasive prenatal testing (NIPT) and to evaluate the efficacy of different genetic testing techniques for prenatal diagnosis of trisomy mosaicism. METHODS: For prenatal diagnosis of a pregnant woman with a high risk of trisomy 7 suggested by NIPT, karyotyping and chromosomal microarray analysis (CMA) were performed on an amniotic fluid sample. Low-depth whole-genome copy number variation sequencing (CNV-seq) and fluorescence in situ hybridization (FISH) were used to clarify the results further. In addition, methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) was performed to analyze the possibility of uniparental disomy(UPD). RESULTS: Amniotic fluid karyotype analysis revealed a 46, XX result. Approximately 20% mosaic trisomy 7 was detected according to the CMA result. About 16% and 4% of mosaicism was detected by CNV-seq and FISH, respectively. MS-MLPA showed no methylation abnormalities. The fetal ultrasound did not show any detectable abnormalities except for mild intrauterine growth retardation seen at 39 weeks of gestation. After receiving genetic counseling, the expectant mother decided to continue the pregnancy, and follow-up within three months of delivery was normal. CONCLUSION: In high-risk NIPT diagnosis, a combination of cytogenetic and molecular genetic techniques proves fruitful in detecting low-level mosaicism. Furthermore, the exclusion of UPD on chromosome 7 remains crucial when NIPT indicates a positive prenatal diagnosis of trisomy 7.

Prenatal diagnosis of fetuses with absent/hypoplastic nasal bone in second-trimester using chromosomal microarray analysis.

BACKGROUND: Pathogenic copy number variants (pCNVs) are associated with fetal ultrasound anomalies, which can be efficiently identified through chromosomal microarray analysis (CMA). The primary objective of the present study was to enhance understanding of the genotype-phenotype correlation in fetuses exhibiting absent or hypoplastic nasal bones using CMA. METHODS: Enrolled in the present study were 94 cases of fetuses with absent/hypoplastic nasal bone, which were divided into an isolated absent/hypoplastic nasal bone group (n = 49) and a non-isolated group (n = 45). All pregnant women enrolled in the study underwent karyotype analysis and CMA to assess chromosomal abnormalities in the fetuses. RESULTS: Karyotype analysis and CMA detection were successfully performed in all cases. The results of karyotype and CMA indicate the presence of 11 cases of chromosome aneuploidy, with trisomy 21 being the most prevalent among them. A small supernumerary marker chromosome (sSMC) detected by karyotype analysis was further interpreted as a pCNV by CMA. Additionally, CMA detection elicited three cases of pCNVs, despite normal findings in their karyotype analysis results. Among them, one case of Roche translocation was identified to be a UPD in chromosome 15 with a low proportion of trisomy 15. Further, a significant difference in the detection rate of pCNVs was observed between non-isolated and isolated absent/hypoplastic nasal bone (24.44% vs. 8.16%, p < .05). CONCLUSION: The present study enhances the utility of CMA in diagnosing the etiology of absent or hypoplastic nasal bone in fetuses. Further, isolated cases of absent or hypoplastic nasal bone strongly suggest the presence of chromosomal abnormalities, necessitating genetic evaluation through CMA.

Prenatal diagnosis of chromosomal aberrations by chromosomal microarray analysis and pregnancy outcomes of fetuses with polyhydramnios.

OBJECTIVES: To explore the prenatal clinical utility of chromosome microarray analysis (CMA) for polyhydramnios and evaluate the short and long-term prognosis of fetuses with polyhydramnios. METHODS: A total of 600 singleton pregnancies with persistent polyhydramnios from 2014 to 2020 were retrospectively enrolled in this study. All cases received amniocentesis and were subjected to CMA results. All cases were categorized into two groups: isolated polyhydramnios and non-isolated polyhydramnios [with soft marker(s) or with sonographic structural anomalies]. All fetuses were followed up from 6 months to five years after amniocentesis to acquire short and long-term prognosis. RESULTS: The detection rates of either aneuploidy or pathogenic copy number variants in fetuses with non-isolated polyhydramnios were significantly higher than those with isolated polyhydramnios (5.0 vs. 1.5%, p = 0.0243; 3.6 vs. 0.8%, p = 0.0288). The detection rate of total chromosomal abnormalities in the structural abnormality group was significantly higher than that in the isolated group (10.0 vs. 2.3%, p = 0.0003). In the CMA-negative cases, the incidence of termination of pregnancy, neonatal and childhood death, and non-neurodevelopmental disorders in fetuses combined with structural anomalies was significantly higher than that in fetuses with isolated polyhydramnios (p < 0.05). We did not observe any difference in the prognosis between the isolated group and the combined group of ultrasound soft markers. In addition, the risk of postnatal neurodevelopmental disorders was also consistent among the three groups (1.6 vs. 1.3 vs. 1.8%). CONCLUSION: For low-risk pregnancies, invasive prenatal diagnosis of isolated polyhydramnios might be unnecessary. CMA should be considered for fetuses with structural anomalies. In CMA-negative cases, the prognosis of fetuses with isolated polyhydramnios was good, and polyhydramnios itself did not increase the risk of postnatal neurological development disorders. The worse prognosis mainly depends on the combination of polyhydramnios with structural abnormalities.

The yield of SNP microarray analysis for fetal ultrasound cardiac abnormalities.

BACKGROUND: Chromosomal microarray analysis (CMA) has emerged as a critical instrument in prenatal diagnostic procedures, notably in assessing congenital heart diseases (CHD). Nonetheless, current research focuses solely on CHD, overlooking the necessity for thorough comparative investigations encompassing fetuses with varied structural abnormalities or those without apparent structural anomalies. OBJECTIVE: This study sought to assess the relation of single nucleotide polymorphism-based chromosomal microarray analysis (SNP-based CMA) in identifying the underlying causes of fetal cardiac ultrasound abnormalities. METHODS: A total of 2092 pregnant women who underwent prenatal diagnosis from 2017 to 2022 were included in the study and divided into four groups based on the presence of ultrasound structural abnormalities and the specific type of abnormality. The results of the SNP-Array test conducted on amniotic fluid samples from these groups were analyzed. RESULTS: Findings from the study revealed that the non-isolated CHD group exhibited the highest incidence of aneuploidy, overall chromosomal abnormalities, and trisomy 18, demonstrating statistically significant differences from the other groups (p < 0.001). Regarding the distribution frequency of copy number variation (CNV) segment size, no statistically significant distinctions were observed between the isolated CHD group and the non-isolated CHD group (p > 0.05). The occurrence rates of 22q11.2 and 15q11.2 were also not statistically different between the isolated CHD group and the non-isolated congenital heart defect group (p > 0.05). CONCLUSION: SNP-based CMA enhances the capacity to detect abnormal CNVs in CHD fetuses, offering valuable insights for diagnosing chromosomal etiology and facilitating genetic counseling. This research contributes to the broader understanding of the utility of SNP-based CMA in the context of fetal cardiac ultrasound abnormalities.

Investigating the potential of Juglans regia phytoconstituents for the treatment of cervical cancer utilizing network biology and molecular docking approach.

The fourth most frequent type of cancer in women and the leading cause of mortality for females worldwide is cervical cancer. Traditionally, medicinal plants have been utilized to treat various illnesses and ailments. The molecular docking method is used in the current study to look into the phytoconstituents of Juglans regia's possible anticancer effects on cervical cancer target proteins. This work uses the microarray dataset analysis of GSE63678 from the NCBI Gene Expression Omnibus database to find differentially expressed genes. Furthermore, protein-protein interactions of differentially expressed genes were constructed using network biology techniques. The top five hub genes (IGF1, FGF2, ESR1, MYL9, and MYH11) are then determined by computing topological parameters with Cytohubba. In addition, molecular docking research was performed on Juglans regia phytocompounds that were extracted from the IMPPAT database versus hub genes that had been identified. Utilizing molecular dynamics, simulation confirmed that prioritized docked complexes with low binding energies were stable.

Diagnostic yield of the chromosomal microarray analysis in turkish patients with unexplained development delay/intellectual disability(ID), autism spectrum disorders and/or multiple congenital anomalies and new clinical findings.

BACKGROUND: Chromosomal microarray analysis is an essential tool for copy number variants detection in patients with unexplained developmental delay/intellectual disability, autism spectrum disorders, and multiple congenital anomalies. The study aims to determine the clinical significance of chromosomal microarray analysis in this patient group. Another crucial aspect is the evaluation of copy number variants detected in terms of the diagnosis of patients. METHODS AND RESULTS: A Chromosomal microarray analysis was was conducted on a total of 1227 patients and phenotype-associated etiological diagnosis was established in 135 patients. Phenotype-associated copy number variants were detected in 11% of patients. Among these, 77 patients 77 (57%, 77/135) were diagnosed with well-recognized genetic syndromes and phenotype-associated copy number variants were found in 58 patients (42.9%, 58/135). The study was designed to collect data of patients in Kocaeli Derince Training and Research Hospital retrospectively. In our study, we examined 135 cases with clinically significant copy number variability among all patients. CONCLUSIONS: In this study, chromosomal microarray analysis revealed pathogenic de novo copy number variants with new clinical features. Chromosomal microarray analysis in the Turkish population has been reported in the largest patient cohort to date.

Glycosaminoglycan microarrays for studying glycosaminoglycan-protein systems.

More than 3000 proteins are now known to bind to glycosaminoglycans (GAGs). Yet, GAG-protein systems are rather poorly understood in terms of selectivity of recognition, molecular mechanism of action, and translational promise. High-throughput screening (HTS) technologies are critically needed for studying GAG biology and developing GAG-based therapeutics. Microarrays, developed within the past two decades, have now improved to the point of being the preferred tool in the HTS of biomolecules. GAG microarrays, in which GAG sequences are immobilized on slides, while similar to other microarrays, have their own sets of challenges and considerations. GAG microarrays are rapidly becoming the first choice in studying GAG-protein systems. Here, we review different modalities and applications of GAG microarrays presented to date. We discuss advantages and disadvantages of this technology, explain covalent and non-covalent immobilization strategies using different chemically reactive groups, and present various assay formats for qualitative and quantitative interpretations, including selectivity screening, binding affinity studies, competitive binding studies etc. We also highlight recent advances in implementing this technology, cataloging of data, and project its future promise. Overall, the technology of GAG microarray exhibits enormous potential of evolving into more than a mere screening tool for studying GAG - protein systems.

[Prenatal diagnosis of fetal microdeletion and microduplication syndromes among pregnant women with advanced maternal ages].

OBJECTIVE: To assess the value of combined chromosomal karyotyping and chromosomal microarray analysis (CMA) and/or copy number variation sequencing (CNV-seq) for the prenatal diagnosis for women with advanced maternal ages, and to explore the challenges of prenatal genetic counseling brought by the types of fetal CNVs and uncertainty of related phenotypes. METHODS: A retrospective analysis was carried out on 1 841 women with advanced maternal age who underwent interventional prenatal diagnosis at the Prenatal Diagnosis Center of Xiamen University Affiliated Women and Children's Hospital from January 2017 to December 2020. Routine chromosomal karyotyping analysis and CMA/CNV-seq detection were carried out. RESULTS: CMA/CNV-seq had detected pathogenic variants in 2 cases which had failed karyotyping analysis. Two hundred and twenty one fetal chromosomal abnormalities were detected by karyotyping analysis, among which 187 were detected by CMA/CNV-seq. CMA/CNV-seq analysis of 23 cases with balanced chromosome structural aberrations and 10 cases with low proportion mosaicisms (including a marker chromosome) had yielded a negative result. In addition, 26 cases (26/1 841, 1.4%) with pathogenic CNVs were discovered among those with a normal karyotype, of which 13 (50.0%) were recurrent CNVs associated with neurocognitive impairment, with 22q11.21 microdeletions and microduplications being the most common types (26.92%). CONCLUSION: The combination of karyotyping analysis and CMA/CNV-seq not only increased the rate of prenatal diagnosis, but also complemented with each other, which has facilitated genetic counseling and formulation of prenatal diagnosis strategy for the affected families.

Honeycomb-Inspired Surface-Enhanced Raman Scattering Microarray for Large-Area Automated Testing of Urease in Saliva Samples.

Surface-enhanced Raman scattering (SERS) technology, as an important analytical tool, has been widely applied in the field of chemical and biomedical sensing. Automated testing is often combined with biochemical analysis technologies to shorten the detection time and minimize human error. The present SERS substrates for sample detection are time-consuming and subject to high human error, which are not conducive to the combination of SERS and automated testing. Here, a novel honeycomb-inspired SERS microarray is designed for large-area automated testing of urease in saliva samples to shorten the detection time and minimize human error. The honeycomb-inspired SERS microarray is decorated with hexagonal microwells and a homogeneous distribution of silver nanostars. Compared with the other four common SERS substrates, the optimal honeycomb-inspired SERS microarray exhibits the best SERS performance. The RSD of 100 SERS spectra continuously collected from saliva samples is 6.56%, and the time of one detection is reduced from 5 min to 10 s. There is a noteworthy linear relationship with a R2 of 0.982 between SERS intensity and urease concentration, indicating the quantitative detection capability of the urease activity in saliva samples. The honeycomb-inspired SERS microarray, combined with automated testing, provides a new way in which SERS technology can be widely used in biomedical applications.

Prenatal chromosomal microarray analysis and karyotyping in fetuses with isolated choroid plexus cyst: A retrospective case-control study.

OBJECTIVES: To evaluate the the diagnostic yield of chromosomal microarray analysis (CMA) in fetuses with isolated CPC (iCPC). METHODS: A total of 315 fetuses with iCPC (iCPC group) and 364 fetuses without abnormal ultrasound findings (control group) were recruited between July 2014 to March 2018. RESULTS: The overall diagnostic yield of chromosomal abnormalities by CMA and karyotyping in iCPC group was up to 4.1 %, higher than 1.4 % in the control group, p < 0.05. The detection rate of pathogenic or likely pathogenic copy number variants (CNVs) with clinical significance by CMA in iCPC group (1.3 %) was higher than in control group (0 %), p < 0.05. According to the type of chromosome abnormalities, the missed diagnosis rate of non-invasive prenatal testing (NIPT) was 1.6 % in our study. CONCLUSIONS: The presence of iCPC on ultrasound examination suggests a potential indication for genetic counseling. Karyotyping and chromosomal microarray analysis may be considered for fetuses with iCPC. It is important to be aware of the limitations of non-invasive prenatal testing, as there is a possibility of residual risk.

Gene Expression Profiling Reveals Fundamental Sex-Specific Differences in SIRT3-Mediated Redox and Metabolic Signaling in Mouse Embryonic Fibroblasts.

Sirt-3 is an important regulator of mitochondrial function and cellular energy homeostasis, whose function is associated with aging and various pathologies such as Alzheimer's disease, Parkinson's disease, cardiovascular diseases, and cancers. Many of these conditions show differences in incidence, onset, and progression between the sexes. In search of hormone-independent, sex-specific roles of Sirt-3, we performed mRNA sequencing in male and female Sirt-3 WT and KO mouse embryonic fibroblasts (MEFs). The aim of this study was to investigate the sex-specific cellular responses to the loss of Sirt-3. By comparing WT and KO MEF of both sexes, the differences in global gene expression patterns as well as in metabolic and stress responses associated with the loss of Sirt-3 have been elucidated. Significant differences in the activities of basal metabolic pathways were found both between genotypes and between sexes. In-depth pathway analysis of metabolic pathways revealed several important sex-specific phenomena. Male cells mount an adaptive Hif-1a response, shifting their metabolism toward glycolysis and energy production from fatty acids. Furthermore, the loss of Sirt-3 in male MEFs leads to mitochondrial and endoplasmic reticulum stress. Since Sirt-3 knock-out is permanent, male cells are forced to function in a state of persistent oxidative and metabolic stress. Female MEFs are able to at least partially compensate for the loss of Sirt-3 by a higher expression of antioxidant enzymes. The activation of neither Hif-1a, mitochondrial stress response, nor oxidative stress response was observed in female cells lacking Sirt-3. These findings emphasize the sex-specific role of Sirt-3, which should be considered in future research.

PTGS2: A potential immune regulator and therapeutic target for chronic spontaneous urticaria.

AIMS: Chronic spontaneous urticaria (CSU) is a common and debilitating skin disease that is difficult to control with existing treatments, and the pathogenesis of CSU has not been fully revealed. The aim of this study was to explore the underlying mechanisms of CSU and identify potential treatments. MATERIALS AND METHODS: Microarray datasets of CSU were obtained from Gene Expression Omnibus database. Differentially expressed genes between skin lesions of CSU and normal controls (LNS-DEGs) were identified, and the enrichment analyses of LNS-DEGs were performed. Hub genes of LNS-DEGs were selected by protein-protein interaction analysis. The co-expression and transcriptional regulatory networks of hub genes were conducted using GeneMANIA and TRRUST database, respectively. CIBERSORT was utilized for immune cell infiltration analysis. Experimental validation was performed by ß-hexosaminidase release examination and passive cutaneous anaphylaxis (PCA) mouse model. KEY FINDINGS: A total of 247 LNS-DEGs were identified, which were enriched in cell migration, cell chemotaxis, and inflammatory pathways such as TNF and interleukin (IL) -17 signaling pathway. Among LNS-DEGs, seven upregulated (PTGS2, CCL2, IL1B, CXCL1, IL6, VCAM1, ICAM1) and one downregulated hub gene (PECAM1) were selected. Immune infiltration analysis identified eight different immune cells, such as activated/resting mast cells and neutrophils. Furthermore, PTGS2, encoding cyclooxygenase 2 (COX2), was selected for further validation. COX2 inhibitor, celecoxib, significantly inhibited mast cell degranulation, and reduced vascular permeability and inflammatory cytokine expression in PCA mouse model. SIGNIFICANCE: PTGS2 may be a potential regulator of immunity and inflammation in CSU. Targeting PTGS2 is a new perspective for CSU treatment.

Optical Genome Mapping as a Potential Routine Clinical Diagnostic Method.

Chromosome analysis (CA) and chromosomal microarray analysis (CMA) have been successfully used to diagnose genetic disorders. However, many conditions remain undiagnosed due to limitations in resolution (CA) and detection of only unbalanced events (CMA). Optical genome mapping (OGM) has the potential to address these limitations by capturing both structural variants (SVs) resulting in copy number changes and balanced rearrangements with high resolution. In this study, we investigated OGM's concordance using 87 SVs previously identified by CA, CMA, or Southern blot. Overall, OGM was 98% concordant with only three discordant cases: (1) uncalled translocation with one breakpoint in a centromere; (2) uncalled duplication with breakpoints in the pseudoautosomal region 1; and (3) uncalled mosaic triplication originating from a marker chromosome. OGM provided diagnosis for three previously unsolved cases: (1) disruption of the SON gene due to a balanced reciprocal translocation; (2) disruption of the NBEA gene due to an inverted insertion; (3) disruption of the TSC2 gene due to a mosaic deletion. We show that OGM is a valid method for the detection of many types of SVs in a single assay and is highly concordant with legacy cytogenomic methods; however, it has limited SV detection capabilities in centromeric and pseudoautosomal regions.

Integrating network pharmacology with microRNA microarray analysis to identify the role of miRNAs in thrombosis treated by the Dahuang Zhechong pill.

BACKGROUND: Thrombotic diseases are the leading causes of death worldwide, urging for improvements in treatment strategies. Dahuang Zhechong pill (DHZCP) is a traditional Chinese medicine widely used for treating thrombotic diseases; however, the underlying mechanisms remain unclear. This study aimed to explore the potential mechanisms of DHZCP in treating thrombosis with a focus on bioinformatics and miRNAs. METHODS: We used network pharmacology to explore the targets of thrombosis treated with DHZCP and performed microarray analysis to acquire miRNA profiles and predict the target genes in thrombin-stimulated MEG-01 cells treated with DHZCP. Based on the overlapping of targets, we carried out a component-target-miRNA network and enrichment analysis and validated the selected miRNAs and mRNAs using quantitative reverse transcription-polymerase chain reaction. RESULTS: Our data showed 850 targets of 230 active ingredients of DHZCP and 1214 thrombosis-related genes; 235 targets were common. We identified 32 miRNAs that were regulated by thrombin stimulation but regulated reversely by DHZCP treatment in MEG-01 cells, and predicted 1846 targets with function annotation. We analyzed conjointly 23 integrating targets from network pharmacology and microarray. HIF1A, PIK3CA, MAPK1 and BCL2L1 emerged as key nodes in the network diagrams. We confirmed the differential expression of seven miRNAs, one mRNA (BCL2L1) and platelet surface protein. CONCLUSIONS: This study showed that miRNAs and their targets, such as BCL2L1, played crucial roles in platelet activation during DHZCP intervention in thrombosis, highlighting their potential to alleviate platelet activation and increase cell apoptosis. The study's findings could help develop new strategies for improving thrombosis treatment.

Feature-specific quantile normalization and feature-specific mean-variance normalization deliver robust bi-directional classification and feature selection performance between microarray and RNAseq data.

BACKGROUND: Cross-platform normalization seeks to minimize technological bias between microarray and RNAseq whole-transcriptome data. Incorporating multiple gene expression platforms permits external validation of experimental findings, and augments training sets for machine learning models. Here, we compare the performance of Feature Specific Quantile Normalization (FSQN) to a previously used but unvalidated and uncharacterized method we label as Feature Specific Mean Variance Normalization (FSMVN). We evaluate the performance of these methods for bidirectional normalization in the context of nested feature selection. RESULTS: FSQN and FSMVN provided clinically equivalent bidirectional model performance with and without feature selection for colon CMS and breast PAM50 classification. Using principal component analysis, we determine that these methods eliminate batch effects related to technological platforms. Without feature selection, no statistical difference was identified between the performance of FSQN and FSMVN of cross-platform data compared to within-platform distributions. Under optimal feature selection conditions, balanced accuracy was FSQN and FSMVN were statistically equivalent to the within-platform distribution performance in multivariable linear regression analysis. FSQN and FSMVN also provided similar performance to within-platform distributions as the number of selected genes used to create models decreases. CONCLUSIONS: In the context of generating supervised machine learning classifiers for molecular subtypes, FSQN and FSMVN are equally effective. Under optimal modeling conditions, FSQN and FSMVN provide equivalent model accuracy performance on cross-platform normalization data compared to within-platform data. Using cross-platform data should still be approached with caution as subtle performance differences may exist depending on the classification problem, training, and testing distributions.

A high-throughput DNA analysis method based on isothermal amplification on a suspension microarray for detecting mpox virus and viruses with comparable symptoms.

BACKGROUND: Mpox is a zoonotic disease caused by mpox virus (MPXV) infection. Since May 2022, there has been a marked increase in human mpox cases in different regions. Rash, fever, and sore throat are typical signs of mpox. However, other viruses, such as the B virus (BV), herpes simplex virus types 1 (HSV-1), herpes simplex virus types 2 (HSV-2), and varicella zoster virus (VZV), can also infect people and cause comparable symptoms. Therefore, clinical symptoms and signs alone make distinguishing MPXV from these viruses difficult. RESULTS: In this study, we combined suspension microarray technology with recombinase-aided amplification technology (RAA) to establish a high-throughput, sensitive, and quantitative method for detecting MPXV and other viruses that can cause similar symptoms. The experimental results confirmed that the technique has outstanding sensitivity, with a minimum detection limit (LOD) of 0.1 fM and a linear range of 0.3 fM to 20 pM, spanning five orders of magnitude. The approach also exhibits exquisite selectivity, as the amplified signal can only be detected when the target virus nucleic acid is present. Additionally, serum recoveries ranging from 80.52% to 119.09% suggest that the detection outcomes are generally considered reliable. Moreover, the time required for detection using this high-throughput method is very short. After DNA extraction, the detection signal amplified by isothermal amplification on the bead array can be obtained in just 1 h. SIGNIFICANCE AND NOVELTY: Our research introduces a new technique that utilizes suspension microarray technology and isothermal amplification to create a high-throughput nucleic acid assay. This innovative method offers multiple benefits compared to current techniques, such as being cost-effective, time-efficient, highly sensitive, and having high throughput capabilities. Furthermore, the assay is applicable not only for detecting MPXV and viruses with similar symptoms, but also for clinical diagnostics, food safety, and environmental monitoring, rendering it an effective tool for screening harmful microorganisms.

Critical roles of S100A12, MMP9, and PRTN3 in sepsis diagnosis: Insights from multiple microarray data analyses.

BACKGROUND: Sepsis, characterized by systemic inflammatory response syndrome and life-threatening organ dysfunction, remains a significant global cause of disability and death. Despite its impact, reliable biomarkers for sepsis diagnosis are yet to be identified. OBJECTIVE: This study aims to investigate and identify key genes and pathways in sepsis through the analysis of multiple microarray datasets, providing potential treatment targets for future clinical trials. METHODS: Two independent gene expression profiles (GSE54514 and GSE69528) were downloaded from the Gene Expression Omnibus (GEO) database. After merging and batch normalization, differentially expressed genes (DEGs) were obtained using the "limma" package. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were performed using "R" software. A Protein-Protein Interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING). The top 10 hub genes were identified using Cytoscape. A Nomogram model for predicting sepsis occurrence was constructed and evaluated. RESULTS: Bioinformatic analysis of 210 sepsis and 91 control blood samples identified 72 DEGs. GO analyses revealed associations with immune response processes. GSEA indicated involvement in key signaling pathways. S100A12, MMP9, and PRTN3 were identified as independent risk factors for sepsis. CONCLUSION: This study unveils critical genes and pathways in sepsis through bioinformatic methods. S100A12, MMP9, and PRTN3 may play essential roles in the immune response to infection, influencing sepsis prognosis.

Hybrid whale algorithm with evolutionary strategies and filtering for high-dimensional optimization: Application to microarray cancer data.

The standard whale algorithm is prone to suboptimal results and inefficiencies in high-dimensional search spaces. Therefore, examining the whale optimization algorithm components is critical. The computer-generated initial populations often exhibit an uneven distribution in the solution space, leading to low diversity. We propose a fusion of this algorithm with a discrete recombinant evolutionary strategy to enhance initialization diversity. We conduct simulation experiments and compare the proposed algorithm with the original WOA on thirteen benchmark test functions. Simulation experiments on unimodal or multimodal benchmarks verified the better performance of the proposed RESHWOA, such as accuracy, minimum mean, and low standard deviation rate. Furthermore, we performed two data reduction techniques, Bhattacharya distance and signal-to-noise ratio. Support Vector Machine (SVM) excels in dealing with high-dimensional datasets and numerical features. When users optimize the parameters, they can significantly improve the SVM's performance, even though it already works well with its default settings. We applied RESHWOA and WOA methods on six microarray cancer datasets to optimize the SVM parameters. The exhaustive examination and detailed results demonstrate that the new structure has addressed WOA's main shortcomings. We conclude that the proposed RESHWOA performed significantly better than the WOA.