Biological Significance Research Articles

Bipolar disorder: Construction and analysis of a joint diagnostic model using random forest and feedforward neural networks

BackgroundTo construct a diagnostic model for Bipolar Disorder (BD) depressive phase using peripheral tissue RNA data from patients and combining Random Forest with Feedforward Neural Network methods. MethodsDatasets GSE23848, GSE39653, and GSE69486 were selected, and differential gene expression analysis was conducted using the limma package in R. Key genes from the differentially expressed genes were identified using the Random Forest method. These key genes' expression levels in each sample were used to train a Feedforward Neural Network model. Techniques like L1 regularization, early stopping, and dropout layers were employed to prevent model overfitting. Model performance was then validated, followed by GO, KEGG, and protein-protein interaction network analyses. ResultsThe final model was a Feedforward Neural Network with two hidden layers and two dropout layers, comprising 2345 trainable parameters. Model performance on the validation set, assessed through 1000 bootstrap resampling iterations, demonstrated a specificity of 0.769 (95 % CI 0.571–1.000), sensitivity of 0.818 (95 % CI 0.533–1.000), AUC value of 0.832 (95 % CI 0.642–0.979), and accuracy of 0.792 (95 % CI 0.625–0.958). Enrichment analysis of key genes indicated no significant enrichment in any known pathways. ConclusionKey genes with biological significance were identified based on the decrease in Gini coefficient within the Random Forest model. The combined use of Random Forest and Feedforward Neural Network to establish a diagnostic model showed good classification performance in Bipolar Disorder.

Thermoregulated transcriptomics: the molecular basis and biological significance of temperature-dependent alternative splicing.

Temperature-dependent alternative splicing (AS) is a crucial mechanism for organisms to adapt to varying environmental temperatures. In mammals, even slight fluctuations in body temperature are sufficient to drive significant AS changes in a concerted manner. This dynamic regulation allows organisms to finely tune gene expression and protein isoform diversity in response to temperature cues, ensuring proper cellular function and physiological adaptation. Understanding the molecular mechanisms underlying temperature-dependent AS thus provides valuable insights into the intricate interplay between environmental stimuli and gene expression regulation. In this review, we provide an overview of recent advances in understanding temperature-regulated AS across various biological processes and systems. We will discuss the machinery sensing and translating temperature cues into changed AS patterns, the adaptation of the splicing regulatory machinery to extreme temperatures, the role of temperature-dependent AS in shaping the transcriptome, functional implications and the development of potential therapeutics targeting temperature-sensitive AS pathways.

Nasal microRNA signatures for disease severity in infants with respiratory syncytial virus bronchiolitis: a multicentre prospective study

BackgroundRespiratory syncytial virus (RSV) bronchiolitis contributes to a large morbidity and mortality burden globally. While emerging evidence suggests that airway microRNA (miRNA) is involved in the pathobiology of RSV infection,...

Phytochemical Study, Antioxidant Activity and GC-MS Analysis of Soymida febrifuga A. Juss

Objectives: To determine antioxidant activity and identify bioactive compounds present in n-Hexane & Ethyl acetate extracts of stem bark of Soymida febrifuga A. Juss. Methods: In the present study stem bark of Soymida febrifuga A. Juss was powdered and subjected to Soxhlet extraction using n-Hexane and Ethyl acetate as solvents. Extracts were analysed for the presence of phytochemicals and antioxidant activity. The Bio-active compounds were identified by Gas chromatography-mass spectrometry. Findings: The qualitative analysis revealed presence of various phytochemicals. GC-MS analysis confirmed the presence of total 28 Medicinally active compounds which included Tetradecane, Hentriacontane, Octacosane, Docosane and Eicosane in n-Hexane extract. 15 Medicinally active compounds were found in ethyl acetate extract which included Purolan, 1,2-Dipropenyl cyclobutane, Hentricontane, 2,6,7-Trimethyl decane, Tetrahydrofurfuryl propionate and Decyl propanoate. Novelty: Though the phytochemical analysis of Soymida febrifuga have been performed by some research groups but there are no reports on identification of Bio-active compounds by GC-MS. The results obtained from present study confirms presence of many compounds of biological significance that warrants further biological and pharmacological study of Soymida febrifuga A. Juss as a potential herbal drug. Keywords: Soymida febrifuga; GC-MS analysis; DPPH assay; n-Hexane; Ethyl acetate

The clinical significance and anti-tumor role of PRKG1 in bladder cancer.

cGMP-dependent protein kinase 1 (PRKG1) has shown to be associated with some tumorigenesis, while the role of PRKG1 in bladder cancer is unclear. To investigate the biological and clinical significance of PRKG1 in bladder cancer, we detected the expression of PRKG1 and explored the function of PRKG1 in bladder cancer cells. The PRKG1 transcripts data was downloaded from The Cancer Genome Atlas (TCGA) database, and immunohistochemistry staining was conducted on formalin-fixed paraffin-embedded (FFPE) sample tissues. Relationship between clinical characteristics of patients and expression of PRKG1 was analyzed in FFPE samples, TCGA database, and GSE19423 dataset. PRKG1 was over-expressed, and cell proliferation, migration, invasion, apoptosis, and spheroidizing ability were then detected. Chemosensitivity to cisplatin was detected with cell viability, and half-maximal drug inhibitory concentration (IC50) was calculated. In addition, the relation between PRKG1 expression and the infiltration level of tumor immune cells in tumor microenvironment were analyzed. The results showed expression of PRKG1 was lower in bladder cancer, compared with normal tissues both at protein and transcript levels. Lower PRKG1 expression was related to higher tumor grade, T stage, and muscle invasion, also predicted worse overall survival and recurrence free survival in patients treated with Bacillus Calmette-Guerin (BCG) intravesical immunotherapy. Analysis of tumor immune cells infiltration showed lower PRKG1 was associated with non-inflamed tumor microenvironment. The present study firstly identified the anti-tumor role and tumor immune regulatory role of PRKG1, also found loss of PRKG1 could be used as a prognosis factor. The present study provided a potential biomarker and therapy target to bladder cancer.

Novel molecular subtypes of METex14 non-small cell lung cancer with distinct biological and clinical significance

Not all MET exon 14 skipping (METex14) NSCLC patients benefited from MET inhibitors. We hypothesized an inter-tumoral heterogeneity in METex14 NSCLC. Investigations at genomic and transcriptomic level were conducted in METex14 NSCLC samples from stage I-III and recurrent/metastatic patients as discovery and validation cohort. Four molecular subtypes were discovered. MET-Driven subtype, with the worst prognosis, displayed MET overexpression, enrichment of MET-related pathways, and higher infiltration of fibroblast and regulatory T cells. Immune-Activated subtype having the most idea long-term survival, had higher tertiary lymphoid structures, spatial co-option of PD-L1+ cancer cells, and GZMK+ CD8+ T cell. FGFR- and Bypass-Activated subtypes displayed FGFR2 overexpression and enrichments of multiple oncogenic pathways respectively. In the validation cohort, patients with MET-Driven subtype had better response to MET inhibitors than those with MET overexpression. Thus, molecular subtypes of METex14 NSCLC with distinct biological and clinical significance may indicate more precise therapeutic strategies for METex14 NSCLC patients.

Development and interpretation of a multimodal predictive model for prognosis of gastrointestinal stromal tumor

Gastrointestinal stromal tumor (GIST) is the most common mesenchymal original tumor in gastrointestinal (GI) tract and is considered to have varying malignant potential. With the advancement of computer science, radiomics technology and deep learning had been applied in medical researches. It’s vital to construct a more accurate and reliable multimodal predictive model for recurrence-free survival (RFS) aiding for clinical decision-making. A total of 254 patients underwent surgery and pathologically diagnosed with GIST in The First Hospital of China Medical University from 2019 to 2022 were included in the study. Preoperative contrast enhanced computerized tomography (CE-CT) and hematoxylin/eosin (H&E) stained whole slide images (WSI) were acquired for analysis. In the present study, we constructed a sum of 11 models while the multimodal model (average C-index of 0.917 on validation set in 10-fold cross validation) performed the best on external validation cohort with an average C-index of 0.864. The multimodal model also reached statistical significance when validated in the external validation cohort (n = 42) with a p-value of 0.0088 which pertained to the recurrence-free survival (RFS) comparison between the high and low groups using the optimal threshold on the predictive score. We also explored the biological significance of radiomics and pathomics features by visualization and quantitative analysis. In the present study, we constructed a multimodal model predicting RFS of GIST which was prior over unimodal models. We also proposed hypothesis on the correlation between morphology of tumor cell and prognosis.

Enigmatic Pachytene PIWI-Interacting RNAs.

PIWI-interacting RNAs (piRNAs), a class of small RNAs, are renowned for their roles in sequencing-dependent targeting and suppressing transposable elements (TEs). Nevertheless, a majority of mammalian piRNAs, expressing at pachytene stage of meiosis, known as pachytene piRNAs, are devoid of discernible targets, casting a veil of enigma over their functional significance. Overturning the notion that this unusual class of piRNAs functions beyond TE silencing, we recently demonstrated that pachytene piRNAs play an essential and conserved role in silencing young and actively transposing TEs across amniotes. However, only 1% of pachytene piRNAs target active TEs. The biological significance of the abundant non-TE piRNAs, coproduced from the same precursors as TE piRNAs, remains unclear. Here, we provide a comprehensive summary of the potential roles of non-TE piRNAs, and thus propose that these non-TE piRNAs either bolster the action of TE piRNAs or provide the host genome a preexisting mechanism to suppress the potential invasion of novel TEs in the future.

Label-free surface-enhanced Raman spectroscopy analysis method for liquid biopsy and its application in serum-based lung cancer diagnosis and classification

Liquid biopsy offers promise for the diagnosis of malignant tumors or their precancerous lesions at the subclinical stage, which is crucial for improving the survival rate of cancer. Label-free surface-enhanced Raman spectroscopy (SERS) has become an emerging detection method in liquid biopsy. The accuracy of SERS-based diagnosis relies on both precise measurement and effective data analysis. In our previous study, a large laser spot SERS method was proposed for the precise detection of complex liquids. In this work, a logical Raman data analysis method was developed, to address the lack of Raman characteristics and biological significance in current SERS-based diagnosis data analysis. The measured Raman data is classified to obtain a weighting matrix of classification criteria, and this matrix is used to establish a material correspondence with the Raman spectra, extract key Raman peaks, determine corresponding biomolecules and biological processes, thus enabling a logical analysis of the data. This method has been used to analyze the SERS data of lung cancer, it can not only show exceptional performance in diagnosing lung cancer and differentiating small cell lung cancer, but also obtain the Raman diagnostic and classification criteria with clear numerical values and reasonable biological significance, demonstrating its great potential value in precise biosensing.

Machine-learning-coined noise induces energy-saving synchrony.

Noise-induced synchronization is a pervasive phenomenon observed in a multitude of natural and engineering systems. Here, we devise a machine learning framework with the aim of devising noise controllers to achieve synchronization in diverse complex physical systems. We find the implicit energy regularization phenomenon of the formulated framework that engenders energy-saving artificial noise and we rigorously elucidate the underlying mechanism driving this phenomenon. We substantiate the practical feasibility and efficacy of this framework by testing it across various representative systems of physical and biological significance, each influenced by distinct constraints reflecting real-world scenarios.

Long Non-Coding RNA AGAP2-AS1: A Comprehensive Overview on Its Biological Functions and Clinical Significances in Human Cancers.

Long non-coding RNAs (lncRNAs) are well known for their oncogenic or anti-oncogenic roles in cancer development. AGAP2-AS1, a new lncRNA, has been extensively demonstrated as an oncogenic lncRNA in various cancers. Abundant experimental results have proved the aberrantly high level of AGAP2-AS1 in a great number of malignancies, such as glioma, colorectal, lung, ovarian, prostate, breast, cholangiocarcinoma, bladder, colon and pancreatic cancers. Importantly, the biological functions of AGAP2-AS1 have been extensively demonstrated. It could promote the proliferation, migration and invasion of cancer cells. Simultaneously, the clinical significances of AGAP2-AS1 were also illustrated. AGAP2-AS1 was exceptionally overexpressed in various cancer tissues. Clinical studies disclosed that the abnormal overexpression of AGAP2-AS1 was tightly connected with overall survival (OS), lymph nodes metastasis (LNM), clinical stage, tumor infiltration, high histological grade (HG), serous subtype and PFI times. However, to date, the biological actions and clinical significances of AGAP2-AS1 have not been systematically reviewed in human cancers. In the present review, the authors overviewed the biological actions, potential mechanisms and clinical features of AGAP2-AS1 according to the previous studies. In summary, AGAP2-AS1, as a vital oncogenic gene, is a promising biomarker and potential target for carcinoma prognosis and therapy.

Recent synthetic strategies for N-arylation of pyrrolidines: a potential template for biologically active molecules.

The chemistry of nitrogen-containing heterocyclic compounds has been a multifaceted area of research for an extended period due to their varied therapeutic and biological significance. N-Aryl pyrrolidine formed by condensation of aryl group with nitrogen atom of pyrrolidine is present in a wide array of compounds. Various significant activities shown by N-arylated pyrrolidine include anti-Alzheimer, antihypoxic, anticancer, plant activator, analgesic effect, and hepatitis C inhibitor. This review summarizes different synthetic approaches, e.g., transition-metal catalyzed and transition-metal-free synthesis, decarboxylation reaction, reductive amination, nucleophilic cyclization, Ullmann-Goldberg amidation, Buchwald-Hartwig reaction, Chan-Evans-Lam coupling, addition to benzyne, multistep reaction, green synthesis, rearrangement reaction, and multicomponent reaction, to afford the derivatives of N-aryl pyrrolidine. It encompasses synthetic strategies documented from 2015 to 2023.

Exploring the Role of Neuropeptide PACAP in Cytoskeletal Function Using Spectroscopic Methods.

The behavior and presence of actin-regulating proteins are characteristic of various clinical diseases. Changes in these proteins significantly impact the cytoskeletal and regenerative processes underlying pathological changes. Pituitary adenylate cyclase-activating polypeptide (PACAP), a cytoprotective neuropeptide abundant in the nervous system and endocrine organs, plays a key role in neuron differentiation and migration by influencing actin. This study aims to elucidate the role of PACAP as an actin-regulating polypeptide, its effect on actin filament formation, and the underlying regulatory mechanisms. We examined PACAP27, PACAP38, and PACAP6-38, measuring their binding to actin monomers via fluorescence spectroscopy and steady-state anisotropy. Functional polymerization tests were used to track changes in fluorescent intensity over time. Unlike PACAP27, PACAP38 and PACAP6-38 significantly reduced the fluorescence emission of Alexa488-labeled actin monomers and increased their anisotropy, showing nearly identical dissociation equilibrium constants. PACAP27 showed weak binding to globular actin (G-actin), while PACAP38 and PACAP6-38 exhibited robust interactions. PACAP27 did not affect actin polymerization, but PACAP38 and PACAP6-38 accelerated actin incorporation kinetics. Fluorescence quenching experiments confirmed structural changes upon PACAP binding; however, all studied PACAP fragments exhibited the same effect. Our findings indicate that PACAP38 and PACAP6-38 strongly bind to G-actin and significantly influence actin polymerization. Further studies are needed to fully understand the biological significance of these interactions.

Construction of pan-cancer regulatory networks based on causal inference

The pan-cancer initiative aims to study the origin patterns of cancer cell, the processes of carcinogenesis, and the signaling pathways from a perspective that spans across different types of cancer. The construction of the pan-cancer related gene regulatory network is helpful to excavate the commonalities in regulatory relationships among different types of cancers. It also aids in understanding the mechanisms behind cancer occurrence and development, which is of great scientific significance for cancer prevention and treatment. In light of the high dimension and large sample size of pan-cancer omics data, a causal pan-cancer gene regulation network inference algorithm based on stochastic complexity is proposed. With the network construction strategy of local first and then global, the stochastic complexity is used in the conditional independence test and causal direction inference for the candidate adjacent node set of the target nodes. This approach aims to decrease the time complexity and error rate of causal network learning. By applying this algorithm to the sample data of seven types of cancers in the TCGA database, including breast cancer, lung adenocarcinoma, and so on, the pan-cancer related causal regulatory networks are constructed, and their biological significance is verified. The experimental results show that this algorithm can eliminate the redundant regulatory relationships effectively and infer the pan-cancer regulatory network more accurately (https://github.com/LindeEugen/CNI-SC).

Biological and computational exploration of a hydrogen-bonded charge transfer complex between 8-Hydroxyquinoline and Benzene-1,4-diol in different polar solvents: Synthesis and spectrophotometric analysis

The formation and characterization of a charge transfer complex (CTC) between 8-Hydroxyquinoline and Benzene-1,4-diol (Quinol) in various polar solvents. CTCs, marked by weak yet significant interactions, are pivotal in understanding electron transfer processes and molecular recognition phenomena. The choice of 8-Hydroxyquinoline (8HQ) as the donor and Quinol (Q) as the acceptor facilitates the investigation of their interaction, given their respective electron-rich and electron-poor properties. The spectroscopic analysis, including Fourier-transform infrared (FTIR) and UV-visible spectroscopy, reveals shifts in molecular vibrations and electronic transitions, indicating the formation of the CTC. Additionally, thermal analysis techniques, such as thermogravimetric analysis (TGA) and differential thermal analysis (DTA), provide insights into the thermal stability and decomposition behavior of the CTC. Powder X-ray diffraction (PXRD) analysis offers data on the crystalline structure and morphology of the complex. Furthermore, the manuscript explores the biological significance of the synthesized CTC, including its antioxidant, antibacterial, and antifungal activities. Conductivity measurements and computational studies, such as Density Functional Theory (DFT) and molecular docking, provide further insights into the electronic properties and structural characteristics of the CTC. Overall, the study contributes to advancing the understanding of CTCs and their applications, particularly in the context of novel donor-acceptor systems. The insights gained have implications in diverse fields, including materials science, biomedical engineering, and fundamental chemistry, paving the way for tailored molecular design and functional applications.

Triflic acid-promoted Friedel–Crafts-type carbocyclization of alkenylated biphenyl derivatives: Synthesis and photophysical studies of novel 9,10-dihydrophenanthrenes

An efficient metal-free, triflic acid-promoted intramolecular Friedel–Crafts-type carbocyclization of alkenylated biphenyl derivatives is discussed. This method provides an elegant route for the construction of 9,10-dihydrophenanthrenes of biological significance in good to excellent yields. The carbocyclization reaction is likely to proceeds via activation of terminal CC bond of alkenylated biphenyl derivatives followed by subsequent aromatic electrophilic substitution to give desired carbocyclic products. Single crystal X-ray diffraction analysis of compound 10d revealed that the crystals are packed in AB-AB layer packing, where the molecules are aligned in anti-parallel fashion. Notably, all of the synthesized 9,10-dihydrophenanthrenes exhibited blue to greenish yellow fluorescence with λmax = 418–481 nm range. The stokes shift, quantum yield and optical band gap of tricyclic products were computed using their absorption and emission spectra. A significant positive solvatochromic effect was observed for 9,10-dihydrophenanthrene derivative 10l, which is a characteristic of ICT interactions.

Synthesis, Characterization, DNA Binding, Biological Significance, and Molecular Docking Approaches of a Palladium(II) Complex with Ciprofloxacin for More Efficient Therapy.

To evaluate the biotransformation and the mechanism of binding as well as the biological impact of metal-based- drugs involving Pd(II), known to have high potency and low toxicity for use as anticancer therapeutics, in the present study, a newly synthesized palladium (II) complex, [Pd(CPF)(OH2)2]2+ (where CPF is ciprofloxacin), has been synthesized and characterized and thoroughly evaluated for its antimicrobial properties. The interaction of the diaqua complex with CT-DNA and BSA was studied through various techniques, including UV-vis spectroscopy, thermal denaturation, viscometry, gel electrophoresis, ethanol precipitation, and molecular docking studies. The results indicate that the complex exhibits a robust binding interaction with CT-DNA, possibly via minor groove binding and (or) electrostatic interactions. Furthermore, the complex displays good binding affinity towards BSA, indicating its potential as a target for DNA and BSA in biological media. The invitro cytotoxicity assay reveals that this complex can be classified as a promising cell growth inhibitor against MCF-7, HT-29, and A549. Thus, this newly synthesized palladium (II) complex is a promising candidate for further exploration as a potential anticancer therapeutic.

Symmetric and asymmetric DNA N6-adenine methylation regulates different biological responses in Mucorales

DNA N6-adenine methylation (6mA) has recently gained importance as an epigenetic modification in eukaryotes. Its function in lineages with high levels, such as early-diverging fungi (EDF), is of particular interest. Here, we investigated the biological significance and evolutionary implications of 6mA in EDF, which exhibit divergent evolutionary patterns in 6mA usage. The analysis of two Mucorales species displaying extreme 6mA usage reveals that species with high 6mA levels show symmetric methylation enriched in highly expressed genes. In contrast, species with low 6mA levels show mostly asymmetric 6mA. Interestingly, transcriptomic regulation throughout development and in response to environmental cues is associated with changes in the 6mA landscape. Furthermore, we identify an EDF-specific methyltransferase, likely originated from endosymbiotic bacteria, as responsible for asymmetric methylation, while an MTA-70 methylation complex performs symmetric methylation. The distinct phenotypes observed in the corresponding mutants reinforced the critical role of both types of 6mA in EDF.

Dynamical analysis of a stochastic maize streak virus epidemic model with logarithmic Ornstein-Uhlenbeck process.

To describe the transmission dynamics of maize streak virus infection, in the paper, we first formulate a stochastic maize streak virus infection model, in which the stochastic fluctuations are depicted by a logarithmic Ornstein-Uhlenbeck process. This approach is reasonable to simulate the random impacts of main parameters both from the biological significance and the mathematical perspective. Then we investigate the detailed dynamics of the stochastic system, including the existence and uniqueness of the global solution, the existence of a stationary distribution, the exponential extinction of the infected maize and infected leafhopper vector. Especially, by solving the five-dimensional algebraic equations corresponding to the stochastic system, we obtain the specific expression of the probability density function near the quasi-endemic equilibrium of the stochastic system, which provides valuable insights into the stationary distribution. Finally, the model is discretized using the Milstein higher-order numerical method to illustrate our theoretical results numerically. Our findings provide a groundwork for better methods of preventing the spread of this type of virus.

Efficient synthetic strategies for fused pyrimidine and pyridine derivatives: A review

AbstractPyrimidine and its derivatives play a paramount role in drug discovery as privileged pharmacophores with considerable chemical and biological significance and its presence in genes. This review aims to assemble a systematic evaluation of synthetic tactics of various fused pyrimidine derivatives containing nitrogen heterocycles such as pyridopyridines, pyridopyrimidines, and pyrimidopyrimidine from a pharmacological point of view and deliver an overview of methodologies presenting the chemistry of fused pyrimidine derivatives. The review details the importance of various catalysts and ring substitution using various electrophilic and nucleophilic reagents. These synthetic strategies were elaborated based on the different synthetic routes that lead to the specific type of pyrimidine and pyridine fused derivatives. The literature accumulates various developments in one‐pot condensation, the Knoevenagel–Michael addition mechanism, microwave and ultrasound irradiation, intramolecular cyclization, nano‐catalytic reactions, and so forth. Short reaction times, catalyst reusability, solvent‐free conditions, excellent yields, and stereo‐selectivity are some of the benefits of certain synthetic approaches.