The connection between tricarboxylic acid cycle enzyme mutations and pseudohypoxic signaling in pheochromocytoma and paraganglioma

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from chromaffin cells, holding significant clinical importance due to their capacity for excessive catecholamine secretion and associated cardiovascular complications. Roughly 80% of cases are associated with genetic mutations. Based on the functionality of these mutated genes, PPGLs can be categorized into distinct molecular clusters: the pseudohypoxia signaling cluster (Cluster-1), the kinase signaling cluster (Cluster-2), and the WNT signaling cluster (Cluster-3). A pivotal factor in the pathogenesis of PPGLs is hypoxia-inducible factor-2α (HIF2α), which becomes upregulated even under normoxic conditions, activating downstream transcriptional processes associated with pseudohypoxia. This adaptation provides tumor cells with a growth advantage and enhances their ability to thrive in adverse microenvironments. Moreover, pseudohypoxia disrupts immune cell communication, leading to the development of an immunosuppressive tumor microenvironment. Within Cluster-1a, metabolic perturbations are particularly pronounced. Mutations in enzymes associated with the tricarboxylic acid (TCA) cycle, such as succinate dehydrogenase (SDHx), fumarate hydratase (FH), isocitrate dehydrogenase (IDH), and malate dehydrogenase type 2 (MDH2), result in the accumulation of critical oncogenic metabolic intermediates. Notable among these intermediates are succinate, fumarate, and 2-hydroxyglutarate (2-HG), which promote activation of the HIFs signaling pathway through various mechanisms, thus inducing pseudohypoxia and facilitating tumorigenesis. SDHx mutations are prevalent in PPGLs, disrupting mitochondrial function and causing succinate accumulation, which competitively inhibits α-ketoglutarate-dependent dioxygenases. Consequently, this leads to global hypermethylation, epigenetic changes, and activation of HIFs. In FH-deficient cells, fumarate accumulation leads to protein succination, impacting cell function. FH mutations also trigger metabolic reprogramming towards glycolysis and lactate synthesis. IDH1/2 mutations generate D-2HG, inhibiting α-ketoglutarate-dependent dioxygenases and stabilizing HIFs. Similarly, MDH2 mutations are associated with HIF stability and pseudohypoxic response. Understanding the intricate relationship between metabolic enzyme mutations in the TCA cycle and pseudohypoxic signaling is crucial for unraveling the pathogenesis of PPGLs and developing targeted therapies. This knowledge enhances our comprehension of the pivotal role of cellular metabolism in PPGLs and holds implications for potential therapeutic advancements

Lipid and glucose metabolism in senescence

Senescence is an inevitable biological process. Disturbances in glucose and lipid metabolism are essential features of cellular senescence. Given the important roles of these types of metabolism, we review the evidence for how key metabolic enzymes influence senescence and how senescence-related secretory phenotypes, autophagy, apoptosis, insulin signaling pathways, and environmental factors modulate glucose and lipid homeostasis. We also discuss the metabolic alterations in abnormal senescence diseases and anti-cancer therapies that target senescence through metabolic interventions. Our work offers insights for developing pharmacological strategies to combat senescence and cancer

Neuraminidase and Hemagglutinin Matching Patterns of a Highly Pathogenic Avian and Two Pandemic H1N1 Influenza A Viruses

BACKGROUND: Influenza A virus displays strong reassortment characteristics, which enable it to achieve adaptation in human infection. Surveying the reassortment and virulence of novel viruses is important in the prevention and control of an influenza pandemic. Meanwhile, studying the mechanism of reassortment may accelerate the development of anti-influenza strategies. METHODOLOGY/PRINCIPAL FINDINGS: The hemagglutinin (HA) and neuraminidase (NA) matching patterns of two pandemic H1N1 viruses (the 1918 and current 2009 strains) and a highly pathogenic avian influenza A virus (H5N1) were studied using a pseudotyped particle (pp) system. Our data showed that four of the six chimeric HA/NA combinations could produce infectious pps, and that some of the chimeric pps had greater infectivity than did their ancestors, raising the possibility of reassortment among these viruses. The NA of H5N1 (A/Anhui/1/2005) could hardly reassort with the HAs of the two H1N1 viruses. Many biological characteristics of HA and NA, including infectivity, hemagglutinating ability, and NA activity, are dependent on their matching pattern. CONCLUSIONS/SIGNIFICANCE: Our data suggest the existence of an interaction between HA and NA, and the HA NA matching pattern is critical for valid viral reassortment

An effective method for establishing a regeneration and genetic transformation system for Actinidia arguta

The all-red A. arguta (Actinidia arguta) is an anthocyanin-rich and excellent hardy fruit. Many studies have focused on the green-fleshed A. arguta, and fewer studies have been conducted on the all-red A. arguta. Here we reported a regeneration and Agrobacterium-mediated transformation protocol by using leaves of all-red A. arguta as explants. Aseptic seedling leaves of A. arguta were used as callus-inducing materials. MS medium supplemented with 0.3 mg·L-1 2,4-D and 1.0 mg·L-1 BA was the optimal medium for callus induction of leaves, and medium supplemented with 3 mg·L-1 tZ and 0.5 mg·L-1 IAA was optimal for adventitious shoot regeneration. The best proliferation medium for adventitious buds was MS + 1.0 mg·L-1 BA + 0.3 mg·L-1 NAA. The best rooting medium was 1/2MS + 0.7 mg·L-1 IBA with a 100% rooting rate. For the red flesh hardy kiwi variety ‘Purpurna Saduwa’ (A. arguta var. purpurea), leaves are receptors for Agrobacterium (EHA105)-mediated transformation. The orthogonal experiment was used for the optimization of each genetic transformation parameter and the genetic transformation of the leaves was 21% under optimal conditions. Our study provides technical parameters for applying genetic resources and molecular breeding of kiwifruit with red flesh

Characterization of Neuraminidases from the Highly Pathogenic Avian H5N1 and 2009 Pandemic H1N1 Influenza A Viruses

To study the precise role of the neuraminidase (NA), and its stalk region in particular, in the assembly, release, and entry of influenza virus, we deleted the 20-aa stalk segment from 2009 pandemic H1N1 NA (09N1) and inserted this segment, now designated 09s60, into the stalk region of a highly pathogenic avian influenza (HPAI) virus H5N1 NA (AH N1). The biological characterization of these wild-type and mutant NAs was analyzed by pseudotyped particles (pseudoparticles) system. Compared with the wild-type AH N1, the wild-type 09N1 exhibited higher NA activity and released more pseudoparticles. Deletion/insertion of the 09s60 segment did not alter this relationship. The infectivity of pseudoparticles harboring NA in combination with the hemagglutinin from HPAI H5N1 (AH H5) was decreased by insertion of 09s60 into AH N1 and was increased by deletion of 09s60 from 09N1. When isolated from the wild-type 2009H1N1 virus, 09N1 existed in the forms (in order of abundance) dimer>>tetramer>monomer, but when isolated from pseudoparticles, 09N1 existed in the forms dimer>monomer>>>tetramer. After deletion of 09s60, 09N1 existed in the forms monomer>>>dimer. AH N1 from pseudoparticles existed in the forms monomer>>dimer, but after insertion of 09s60, it existed in the forms dimer>>monomer. Deletion/insertion of 09s60 did not alter the NA glycosylation pattern of 09N1 or AH N1. The 09N1 was more sensitive than the AH N1 to the NA inhibitor oseltamivir, suggesting that the infectivity-enhancing effect of oseltamivir correlates with robust NA activity

Identification and Typing of Human Enterovirus: A Genomic Barcode Approach

Identification and typing of human enterovirus (HEVs) are important to pathogen detection and therapy. Previous phylogeny-based typing methods are mainly based on multiple sequence alignments of specific genes in the HEVs, but the results are not stable with respect to different choices of genes. Here we report a novel method for identification and typing of HEVs based on information derived from their whole genomes. Specifically, we calculate the k-mer based barcode image for each genome, HEV or other human viruses, for a fixed k, 1<k<7, where a genome barcode is defined in terms of the k-mer frequency distribution across the whole genome for all combinations of k-mers. A phylogenetic tree is constructed using a barcode-based distance and a neighbor-joining method among a set of 443 representative non-HEV human viruses and 395 HEV sequences. The tree shows a clear separation of the HEV viruses from all the non-HEV viruses with 100% accuracy and a separation of the HEVs into four distinct clads with 93.4% consistency with a multiple sequence alignment-based phylogeny. Our detailed analyses of the HEVs having different typing results by the two methods indicate that our results are in better agreement with known information about the HEVs

Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma

Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown.Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR).Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p &lt; 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro.Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients

A novel glycolysis-related gene signature for predicting the prognosis of multiple myeloma

Background: Metabolic reprogramming is an important hallmark of cancer. Glycolysis provides the conditions on which multiple myeloma (MM) thrives. Due to MM’s great heterogeneity and incurability, risk assessment and treatment choices are still difficult.Method: We constructed a glycolysis-related prognostic model by Least absolute shrinkage and selection operator (LASSO) Cox regression analysis. It was validated in two independent external cohorts, cell lines, and our clinical specimens. The model was also explored for its biological properties, immune microenvironment, and therapeutic response including immunotherapy. Finally, multiple metrics were combined to construct a nomogram to assist in personalized prediction of survival outcomes.Results: A wide range of variants and heterogeneous expression profiles of glycolysis-related genes were observed in MM. The prognostic model behaved well in differentiating between populations with various prognoses and proved to be an independent prognostic factor. This prognostic signature closely coordinated with multiple malignant features such as high-risk clinical features, immune dysfunction, stem cell-like features, cancer-related pathways, which was associated with the survival outcomes of MM. In terms of treatment, the high-risk group showed resistance to conventional drugs such as bortezomib, doxorubicin and immunotherapy. The joint scores generated by the nomogram showed higher clinical benefit than other clinical indicators. The in vitro experiments with cell lines and clinical subjects further provided convincing evidence for our study.Conclusion: We developed and validated the utility of the MM glycolysis-related prognostic model, which provides a new direction for prognosis assessment, treatment options for MM patients

Applications of Nanomaterials in Electrogenerated Chemiluminescence Biosensors

Electrogenerated chemiluminescence (also called electrochemiluminescence and abbreviated ECL) involves the generation of species at electrode surfaces that then undergo electron-transfer reactions to form excited states that emit light. ECL biosensor, combining advantages offered by the selectivity of the biological recognition elements and the sensitivity of ECL technique, is a powerful device for ultrasensitive biomolecule detection and quantification. Nanomaterials are of considerable interest in the biosensor field owing to their unique physical and chemical properties, which have led to novel biosensors that have exhibited high sensitivity and stability. Nanomaterials including nanoparticles and nanotubes, prepared from metals, semiconductor, carbon or polymeric species, have been widely investigated for their ability to enhance the efficiencies of ECL biosensors, such as taking as modification electrode materials, or as carrier of ECL labels and ECL-emitting species. Particularly useful application of nanomaterials in ECL biosensors with emphasis on the years 2004-2008 is reviewed. Remarks on application of nanomaterials in ECL biosensors are also surveyed

Strategies for digital transformation in SMEs: the impact of timing and speed

Digital transformation (DT) has emerged as a critical concept in organizational contexts, driven by the adoption and implementation of digital technologies. This paper aims to explore the challenges faced by small and medium-sized enterprises (SMEs) in successfully implementing digital transformation and identify strategic options available to them. Preliminary results from a systematic literature review is presented, focusing on empirical evidence on the integration of digital technologies in SMEs. The review revealed key challenges in strategizing for digital transformation and categorized them accordingly. Additionally, the study sheds light on digital strategies for SMEs. The findings contribute to the understanding of why some DT initiatives fail and provide insights into how SMEs can leverage digital transformation for success. By addressing the challenges and exploring strategic options, this research aims to assist SMEs in navigating the complex process of digital transformation