Establishment of canine mammary gland tumor cell lines harboring PI3K/Akt activation as a therapeutic target.

Canine mammary gland tumors (MGT) have a poor prognosis in intact female canines, posing a clinical challenge. This study aimed to establish novel canine mammary cancer cell lines from primary tumors and characterize their cellular and molecular features to find potential therapeutic drugs. The MGT cell lines demonstrated rapid cell proliferation and colony formation in an anchorage-independent manner. Vimentin and α-SMA levels were significantly elevated in MGT cell lines compared to normal canine kidney (MDCK) cells, while CDH1 expression was either significantly lower or not detected at all, based on quantitative real-time PCR (qRT-PCR) analysis. Functional annotation and enrichment analysis revealed that epithelial-mesenchymal transition (EMT) phenotypes and tumor-associated pathways, particularly the PI3K/Akt signaling pathway, were upregulated in MGT cells. BYL719 (Alpelisib), a PI3K inhibitor, was also examined for cytotoxicity on the MGT cell lines. The results show that BYL719 can significantly inhibit the proliferation of MGT cell lines in vitro. Overall, our findings suggest that the MGT cell lines may be valuable for future studies on the development, progression, metastasis, and management of tumors.

Recombinant expression and tryptophan-assisted analysis of human sweet taste receptor T1R3's extracellular domain in sweetener interaction studies.

The human palate can discern multiple tastes; however, it predominantly perceives five fundamental flavors: sweetness, saltiness, sourness, bitterness, and umami. Sweetness is primarily mediated through the sweet taste receptor, a membrane-bound heterodimeric structure comprising T1R2-T1R3. However, unraveling the structural and mechanistic intricacies of the sweet taste receptor has proven challenging. This study aimed to address this knowledge gap by expressing an extracellular N-terminal domain encompassing the cysteine-rich domain of human hT1R3 (hT1R3-TMD) in Escherichia coli. The expressed protein was obtained as inclusion bodies, purified by metal affinity chromatography, and refolded using the dilution-refolding method. Through rigorous analysis, we confirmed the successful refolding of hT1R3-TMD and elucidated its structural characteristics using circular dichroism spectroscopy. Notably, the refolded protein was found to exist as either a monomer or a dimer, depending on its concentration. A tryptophan fluorescence quenching assay revealed that the dissociation constants for sucrose, sucralose, and brazzein were >9500 µM, 2380 µM and 14.3 µM, respectively. Our findings highlight the utility of this E. coli expression system for producing functional hT1R3-TMD for investigations and demonstrate the efficacy of the tryptophan fluorescence quenching assay in revealing complex interactions between sweet taste receptors and various sweeteners.

A Comparative Investigation of Functional Connectivity Utilizing Electroencephalography in Insomnia Patients with and without Restless Leg Syndrome

Objective: The current study aimed to identify distinctive functional brain connectivity characteristics that differentiate patients with restless legs syndrome (RLS) from those with primary insomnia. Methods: Quantitative electroencephalography (QEEG) was employed to analyze connectivity matrices using the phaselocking value technique. A total of 107 patients with RLS (RLS group) and 17 patients with insomnia without RLS (primary insomnia group) were included in the study. Demographic variables were compared using t tests and chi-square tests, while differences in connectivity were examined through multiple analyses of covariance. Correlation analysis was conducted to explore the relationship between connectivity and the severity of RLS. Results: The results indicated significant differences in the primary somatosensory cortex (F = 4.377, r = 0.039), primary visual cortex (F = 4.215, r = 0.042), and anterior prefrontal cortex (F = 5.439, r = 0.021) between the RLS and primary insomnia groups. Furthermore, the connectivity of the sensory cortex, including the primary somatosensory cortex (r = -0.247, p = 0.014), sensory association cortex (r = -0.238, p = 0.028), retrosplenial region (r = -0.302, p = 0.002), angular gyrus (r = -0.258, p = 0.008), supramarginal gyrus (r = -0.230, p = 0.020), primary visual cortex (r = -0.275, p = 0.005) and secondary visual cortex (r = -0.226, p = 0.025) exhibited an inverse association with RLS symptom severity. Conclusion: The prefrontal cortex, primary somatosensory cortex, and visual cortex showed potential as diagnostic biomarkers for distinguishing RLS from primary insomnia. These findings indicate that QEEG-based functional connectivity analysis shows promise as a valuable diagnostic tool for RLS and provides insights into its underlying mechanisms. Further research is needed to explore this aspect further.

Kinetics-based inference of environment-dependent microbial interactions and their dynamic variation.

Microbial communities in nature are dynamically evolving as member species change their interactions subject to environmental variations. Accounting for such context-dependent dynamic variations in interspecies interactions is critical for predictive ecological modeling. In the absence of generalizable theoretical foundations, we lack a fundamental understanding of how microbial interactions are driven by environmental factors, significantly limiting our capability to predict and engineer community dynamics and function. To address this issue, we propose a novel theoretical framework that allows us to represent interspecies interactions as an explicit function of environmental variables (such as substrate concentrations) by combining growth kinetics and a generalized Lotka-Volterra model. A synergistic integration of these two complementary models leads to the prediction of alterations in interspecies interactions as the outcome of dynamic balances between positive and negative influences of microbial species in mixed relationships. The effectiveness of our method was experimentally demonstrated using a synthetic consortium of two Escherichia coli mutants that are metabolically dependent (due to an inability to synthesize essential amino acids) but competitively grow on a shared substrate. The analysis of the E. coli binary consortium using our model not only showed how interactions between the two amino acid auxotrophic mutants are controlled by the dynamic shifts in limiting substrates but also enabled quantifying previously uncharacterizable complex aspects of microbial interactions, such as asymmetry in interactions. Our approach can be extended to other ecological systems to model their environment-dependent interspecies interactions from growth kinetics.IMPORTANCEModeling environment-controlled interspecies interactions through separate identification of positive and negative influences of microbes in mixed relationships is a new capability that can significantly improve our ability to understand, predict, and engineer the complex dynamics of microbial communities. Moreover, the prediction of microbial interactions as a function of environmental variables can serve as valuable benchmark data to validate modeling and network inference tools in microbial ecology, the development of which has often been impeded due to the lack of ground truth information on interactions. While demonstrated against microbial data, the theory developed in this work is readily applicable to general community ecology to predict interactions among macroorganisms, such as plants and animals, as well as microorganisms.

Driving towards digital biomanufacturing by CHO genome-scale models.

Genome-scale metabolic models (GEMs) of Chinese hamster ovary (CHO) cells are valuable for gaining mechanistic understanding of mammalian cell metabolism and cultures. We provide a comprehensive overview of past and present developments of CHO-GEMs and in silico methods within the flux balance analysis (FBA) framework, focusing on their practical utility in rational cell line development and bioprocess improvements. There are many opportunities for further augmenting the model coverage and establishing integrative models that account for different cellular processes and data for future applications. With supportive collaborative efforts by the research community, we envisage that CHO-GEMs will be crucial for the increasingly digitized and dynamically controlled bioprocessing pipelines, especially because they can be successfully deployed in conjunction with artificial intelligence (AI) and systems engineering algorithms.

Machine Learning-Based Prediction of Suicidality in Adolescents With Allergic Rhinitis: Derivation and Validation in 2 Independent Nationwide Cohorts.

BACKGROUND: Given the additional risk of suicide-related behaviors in adolescents with allergic rhinitis (AR), it is important to use the growing field of machine learning (ML) to evaluate this risk. OBJECTIVE: This study aims to evaluate the validity and usefulness of an ML model for predicting suicide risk in patients with AR. METHODS: We used data from 2 independent survey studies, Korea Youth Risk Behavior Web-based Survey (KYRBS; n=299,468) for the original data set and Korea National Health and Nutrition Examination Survey (KNHANES; n=833) for the external validation data set, to predict suicide risks of AR in adolescents aged 13 to 18 years, with 3.45% (10,341/299,468) and 1.4% (12/833) of the patients attempting suicide in the KYRBS and KNHANES studies, respectively. The outcome of interest was the suicide attempt risks. We selected various ML-based models with hyperparameter tuning in the discovery and performed an area under the receiver operating characteristic curve (AUROC) analysis in the train, test, and external validation data. RESULTS: The study data set included 299,468 (KYRBS; original data set) and 833 (KNHANES; external validation data set) patients with AR recruited between 2005 and 2022. The best-performing ML model was the random forest model with a mean AUROC of 84.12% (95% CI 83.98%-84.27%) in the original data set. Applying this result to the external validation data set revealed the best performance among the models, with an AUROC of 89.87% (sensitivity 83.33%, specificity 82.58%, accuracy 82.59%, and balanced accuracy 82.96%). While looking at feature importance, the 5 most important features in predicting suicide attempts in adolescent patients with AR are depression, stress status, academic achievement, age, and alcohol consumption. CONCLUSIONS: This study emphasizes the potential of ML models in predicting suicide risks in patients with AR, encouraging further application of these models in other conditions to enhance adolescent health and decrease suicide rates.

Decoding cellular mechanism of recombinant adeno-associated virus (rAAV) and engineering host-cell factories toward intensified viral vector manufacturing.

Recombinant adeno-associated virus (rAAV) is one of the prominent gene delivery vehicles that has opened promising opportunities for novel gene therapeutic approaches. However, the current major viral vector production platform, triple transfection in mammalian cells, may not meet the increasing demand. Thus, it is highly required to understand production bottlenecks from the host cell perspective and engineer the cells to be more favorable and tolerant to viral vector production, thereby effectively enhancing rAAV manufacturing. In this review, we provided a comprehensive exploration of the intricate cellular process involved in rAAV production, encompassing various stages such as plasmid entry to the cytoplasm, plasmid trafficking and nuclear delivery, rAAV structural/non-structural protein expression, viral capsid assembly, genome replication, genome packaging, and rAAV release/secretion. The knowledge in the fundamental biology of host cells supporting viral replication as manufacturing factories or exhibiting defending behaviors against viral production is summarized for each stage. The control strategies from the perspectives of host cell and materials (e.g., AAV plasmids) are proposed as our insights based on the characterization of molecular features and our existing knowledge of the AAV viral life cycle, rAAV and other viral vector production in the Human embryonic kidney (HEK) cells.

N-recognins UBR1 and UBR2 as central ER stress sensors in mammals.

In eukaryotes, a primary protein quality control (PQC) process involves the destruction of conformationally misfolded proteins through the ubiquitin-proteasome system. Because approximately one-third of eukaryotic proteomes fold and assemble within the endoplasmic reticulum (ER) before being sent to their destinations, the ER plays a crucial role in PQC. The specific functions and biochemical roles of several E3 ubiquitin ligases involved in ER-associated degradation in mammals, on the other hand, are mainly unknown. We identified 2 E3 ligases, ubiquitin protein ligase E3 component N-recognin 1 (UBR1) and ubiquitin protein ligase E3 component N-recognin 2 (UBR2), which are the key N-recognins in the N-degron pathway and participate in the ER stress response in mammalian cells by modulating their stability. Cells lacking UBR1 and UBR2 are hypersensitive to ER stress-induced apoptosis. Under normal circumstances, these proteins are polyubiquitinated through Lys48-specific linkages and are then degraded by the 26S proteasome. In contrast, when cells are subjected to ER stress, UBR1 and UBR2 exhibit greater stability, potentially as a cellular adaptive response to stressful conditions. Although the precise mechanisms underlying these findings require further investigation, our findings show that cytoplasmic UBR1 and UBR2 have anti-ER stress activities and contribute to global PQC in mammals. These data also reveal an additional level of complexity within the mammalian ER-associated degradation system, implicating potential involvement of the N-degron pathway.

Exploring metabolic effects of dipeptide feed media on CHO cell cultures by in silico model-guided flux analysis.

There is a growing interest in perfusion or continuous processes to achieve higher productivity of biopharmaceuticals in mammalian cell culture, specifically Chinese hamster ovary (CHO) cells, towards advanced biomanufacturing. These intensified bioprocesses highly require concentrated feed media in order to counteract their dilution effects. However, designing such condensed media formulation poses several challenges, particularly regarding the stability and solubility of specific amino acids. To address the difficulty and complexity in relevant media development, the biopharmaceutical industry has recently suggested forming dipeptides by combining one from problematic amino acids with selected pairs to compensate for limitations. In this study, we combined one of the lead amino acids, L-tyrosine, which is known for its poor solubility in water due to its aromatic ring and hydroxyl group, with glycine as the partner, thus forming glycyl-L-tyrosine (GY) dipeptide. Subsequently, we investigated the utilization of GY dipeptide during fed-batch cultures of IgG-producing CHO cells, by changing its concentrations (0.125 × , 0.25 × , 0.5 × , 1.0 × , and 2.0 ×). Multivariate statistical analysis of culture profiles was then conducted to identify and correlate the most significant nutrients with the production, followed by in silico model-guided analysis to systematically evaluate their effects on the culture performance, and elucidate metabolic states and cellular behaviors. As such, it allowed us to explain how the cells can more efficiently utilize GY dipeptide with respect to the balance of cofactor regeneration and energy distribution for the required biomass and protein synthesis. For example, our analysis results uncovered specific amino acids (Asn and Gln) and the 0.5 × GY dipeptide in the feed medium synergistically alleviated the metabolic bottleneck, resulting in enhanced IgG titer and productivity. In the validation experiments, we tested and observed that lower levels of Asn and Gln led to decreased secretion of toxic metabolites, enhanced longevity, and elevated specific cell growth and titer. KEY POINTS: • Explored the optimal Tyr dipeptide for the enhanced CHO cell culture performance • Systematically analyzed effects of dipeptide media by model-guided approach • Uncovered synergistic metabolic utilization of amino acids with dipeptide.

Treatment of postural headache occurred 26 days after spinal pain procedure - A case report.

BACKGROUND: Cerebrospinal fluid (CSF) leakage may cause intracranial hypotension and postural headache. Secondary intracranial hypotension may result from an iatrogenic dural puncture or traumatic injury associated with pain procedures. CASE: A 45-year-old male developed a headache 26 days after spinal pain procedure. Headache was characterized as postural, worsening with standing or sitting and improving while lying down. The pain did not resolve despite the administration of oral and intravenous analgesics. A spinal magnetic resonance imaging revealed epidural venous congestion and a suspicious CSF leak around the left L4/5 level. The patient received an epidural blood patch (EBP), the headache improved dramatically, and the patient was discharged. CONCLUSIONS: Delayed postural headaches may not be directly related to pain management. Nevertheless, intracranial hypotension related to pain management should be suspected even in this case. If confirmed, quickly applying an EBP is an effective treatment option.

Suboptimal hepatobiliary phase image in gadoxetic acid-enhanced liver MRI for the evaluation of the HCC: Predictive factors.

To determine the relevant laboratory values for hepatobiliary phase (HBP) imaging and predictive factors for suboptimal HBP images on gadoxetic acid-enhanced liver magnetic resonance imaging (MRI) for the evaluation of hepatocellular carcinoma (HCC) in patients with chronic liver disease (CLD). This study included 307 patients with CLD who underwent gadoxetic acid-enhanced liver MRI for HCC evaluation. The liver-portal vein contrast ratio and liver-spleen contrast ratio were calculated from the measurements of the HBP images. In this study, a suboptimal HBP image was defined as the presence of a bright portal vein or a liver-spleen contrast ratio of <1.5. Correlation, comparison, and receiver operating characteristic analyses were performed between the measured parameters on the HBP images and hepatic and renal function tests. The estimated glomerular filtration rate did not correlate with any measured or calculated values on the HBP images. On receiver operating characteristic analysis, the optimal cutoff value for the bright portal vein was an albumin level of 4.05 g/dL (area under the curve, 0.971; sensitivity, 65%; specificity, 82%). The optimal cutoff value of the suboptimal HBP image was a serum direct bilirubin level of 0.83 mg/dL (area under the curve, 0.830; sensitivity, 69%; specificity, 84%). On gadoxetic acid-enhanced MRI for the evaluation of HCC in patients with CLD, suboptimal HBP images were most strongly correlated with serum direct bilirubin levels. Renal function was not associated with suboptimal HBP imaging. Although the sensitivity is low, suboptimal HBP images can be predicted before gadoxetic acid-enhanced liver MRI can be performed.

GSTT1 as a Predictive Marker and Enhancer for Osteogenic Potential of Human Adipose-Derived Stromal/Stem Cells.

Adipose-derived stromal/stem cells (ASCs) have been extensively studied as cell sources for regenerative medicine for bone because of their excellent proliferative capacity and the ability to obtain a large number of cells with minimal donor morbidity. On the other hand, the differentiation potential of ASCs is generally lower than that of bone marrow-derived stromal/stem cells and varies greatly depending on donors. In this study, we mined a marker that can predict the osteogenic potential of ASC clones and also investigated the usefulness of the molecule as the enhancer of osteogenic differentiation of ASCs as well as its mechanism of action. Through RNA-seq gene analysis, we discovered that GSTT1 (Glutathione S-transferase theta-1) was the most distinguished gene marker between highly osteogenic and poorly osteogenic ASC clones. Knockdown of GSTT1 in high osteogenic ASCs by siGSTT1 treatment reduced mineralized matrix formation. On the other hand, GSTT1 overexpression by GSTT1 transfection or GSTT1 recombinant protein treatment enhanced osteogenic differentiation of low osteogenic ASCs. Metabolomic analysis confirmed significant changes of metabolites related to bone differentiation in ASCs transfected with GSTT1. A high total antioxidant capacity, low levels of cellular reactive oxygen species, and increased GSH/GSSG ratios were also detected in GSTT1-transfected ASCs. When the in vivo effect of GSTT1-transfected ASCs on bone regeneration was investigated with segmental long-bone defect model in rats, bone regeneration was significantly better after implantation of GSTT1-transfected ASCs compared with that of control vector-transfected ASCs. In conclusion, GSTT1 can be a useful marker to screen the highly osteogenic ASC clones and also a therapeutic factor to enhance the osteogenic differentiation of poorly osteogenic ASC clones. © 2023 American Society for Bone and Mineral Research (ASBMR).

Functional significance of serine 13 in the active site of glutathione S-transferase F3 from Oryza sativa.

Plant glutathione S-transferase (GST, EC 2.5.1.18) is an enzyme that detoxifies various electrophilic compounds including herbicides and organic pollutants by catalyzing the formation of conjugates with reduced glutathione (GSH). Although the structure and function of the GST subunits in rice, an important food in Asia, are not well understood, they are crucial for herbicide development. To investigate the role of active site residues in rice Phi-class GSTF3 (OsGSTF3), evolutionarily conserved serine residues were replaced with alanine using site-directed mutagenesis to obtain the mutants S13A, S38A, S69A, and S169A. These four mutants were expressed in Escherichia coli and purified to electrophoretic homogeneity using immobilized GSH affinity chromatography. Mutation of Ser13 to Ala resulted in substantial reductions in specific activities and kcat/Km values for the GSH-[1-chloro-2,4-dinitrobenzene (CDNB)] conjugation reaction. In contrast, mutations of Ser38, Ser69, and Ser169 to Ala had little effect on the activities and kinetic parameters. Additionally, the mutation of Ser13 to Ala significantly affected the KmGSH and I50 values of S-hexylglutathione and S-(2,4-dinitrophenyl)glutathione, which compete with GSH and the product of GSH-CDNB conjugation, respectively. A pH-log (kcat/KmCDNB) plot was used to estimate the pKa value of GSH in the enzyme-GSH complex of the wild-type enzyme, which was approximately 6.9. However, the pKa value of GSH in the enzyme-GSH complex of the S13A mutant was approximately 8.7, which was about 1.8 pK units higher than that of the wild-type enzyme. OsGSTF3 was also crystallized for crystallographic study, and the structure analyses revealed that Ser13 is located in the active site and that its side chain is in close proximity to the thiol group of glutathione bound in the enzyme. Based on these substitution effects on kinetic parameters, the dependence of kinetic parameters on the pH and 3-dimensional structure, it was suggested that Ser13 in rice OsGSTF3 is the residue responsible for catalytic activity by lowering the pKa of GSH in the enzyme-GSH complex and enhancing the nucleophilicity of the GSH thiol in the active site.

Debottlenecking and reformulating feed media for improved CHO cell growth and titer by data-driven and model-guided analyses.

Designing and selecting cell culture media along with their feeding are a key strategy to maximize culture performance in biopharmaceutical processes. However, the sensitivity of mammalian cells to their culture environment necessitates specific nutritional requirements for their growth and the production of high-quality proteins such as antibodies, depending on the cell lines and operational conditions employed. In this regard, previously we developed a data-driven and in-silico model-guided systematic framework to investigate the effect of growth media on Chinese hamster ovary (CHO) cell culture performance, allowing us to design and reformulate basal media. To expand our exploration for media development research, we evaluated two chemically defined feed media, A and B, using a monoclonal antibody-producing CHO-K1 cell line in ambr15 bioreactor runs. We observed a significant impact of the feed media on various aspects of cell culture, including growth, longevity, viability, productivity, and the production of toxic metabolites. Specifically, the concentrated feed A was inadequate in sustaining prolonged cell culture and achieving high titers when compared to feed B. Within our framework, we systematically investigated the major metabolic bottlenecks in the tricarboxylic acid cycle and relevant amino acid transferase reactions. This analysis identified target components that play a crucial role in alleviating bottlenecks and designing highly productive cell cultures, specifically the addition of glutamate to feed A and asparagine to feed B. Based on our findings, we reformulated the feeds by adjusting the amounts of the targeted amino acids and successfully validated the effectiveness of the strategy in promoting cell growth, life span, and/or titer.

Genome-scale metabolic modeling and in silico analysis of opportunistic skin pathogen Cutibacterium acnes.

Cutibacterium acnes, one of the most abundant skin microbes found in the sebaceous gland, is known to contribute to the development of acne vulgaris when its strains become imbalanced. The current limitations of acne treatment using antibiotics have caused an urgent need to develop a systematic strategy for selectively targeting C. acnes, which can be achieved by characterizing their cellular behaviors under various skin environments. To this end, we developed a genome-scale metabolic model (GEM) of virulent C. acnes, iCA843, based on the genome information of a relevant strain from ribotype 5 to comprehensively understand the pathogenic traits of C. acnes in the skin environment. We validated the model qualitatively by demonstrating its accuracy prediction of propionate and acetate production patterns, which were consistent with experimental observations. Additionally, we identified unique biosynthetic pathways for short-chain fatty acids in C. acnes compared to other GEMs of acne-inducing skin pathogens. By conducting constraint-based flux analysis under endogenous carbon sources in human skin, we discovered that the Wood-Werkman cycle is highly activated under acnes-associated skin condition for the regeneration of NAD, resulting in enhanced propionate production. Finally, we proposed potential anti-C. acnes targets by using the model-guided systematic framework based on gene essentiality analysis and protein sequence similarity search with abundant skin microbiome taxa.

Rifampin - Risperidone and Divalproex Drug-drug Interaction: A Case Report.

Rifampin is a potent hepatic cytochrome enzyme inducer, promoting the metabolism of many drugs. Here, we describe a case wherein rifampin-induced drug interactions affected the clinical improvement of a patient on psychiatric drugs for bipolar disorder. He was administered divalproex, risperidone, quetiapine, and clonazepam, along with anti-tuberculosis drugs HERZ, containing 600 mg rifampin. Despite taking 900 mg/day divalproex, his serum valproate levels were below 2 µg/ml, and his manic symptom persisted. Therefore, the antipsychotic risperidone (5 mg) was replaced with olanzapine (20 mg). Following this, his manic symptoms improved rapidly. Rifampin is a potent CYP3A and CYP2D6 inducer and is known to significantly reduce serum risperidone levels. Thus, even a high dose of risperidone did not induce a significant clinical effect, which was observed immediately after replacing with olanzapine. Therefore, drug interactions may have had a significant effect on clinical outcomes. Clinicians should be cognizant of drug interactions when treating psychiatric patients on rifampin therapy. The case has been sufficiently revised to protect the patient's personal information.

Data-driven prediction models for forecasting multistep ahead profiles of mammalian cell culture toward bioprocess digital twins.

Recently, the advancement in process analytical technology and artificial intelligence (AI) has enabled the generation of enormous culture data sets from biomanufacturing processes that produce various recombinant therapeutic proteins (RTPs), such as monoclonal antibodies (mAbs). Thus, now it is very important to exploit them for the enhanced reliability, efficiency, and consistency of the RTP-producing culture processes and for the reduced incipient or abrupt faults. It is achievable by AI-based data-driven models (DDMs), which allow us to correlate biological and process conditions and cell culture states. In this work, we provide practical guidelines for choosing the best combination of model elements to design and implement successful DDMs for given hypothetical in-line data sets during mAb-producing Chinese hamster ovary cell culture, as such enabling us to forecast dynamic behaviors of culture performance such as viable cell density, mAb titer as well as glucose, lactate and ammonia concentrations. To do so, we created DDMs that balance computational load with model accuracy and reliability by identifying the best combination of multistep ahead forecasting strategies, input features, and AI algorithms, which is potentially applicable to implementation of interactive DDM within bioprocess digital twins. We believe this systematic study can help bioprocess engineers start developing predictive DDMs with their own data sets and learn how their cell cultures behave in near future, thereby rendering proactive decision possible.

B lymphocyte responses in Parkinson's disease and their possible significance in disease progression.

Inflammation contributes to Parkinson's disease pathogenesis. We hypothesized that B lymphocytes are involved in Parkinson's disease progression. We measured antibodies to alpha-synuclein and tau in serum from patients with rapid eye movement sleep behaviour disorder (n = 79), early Parkinson's disease (n = 50) and matched controls (n = 50). Rapid eye movement sleep behaviour disorder cases were stratified by risk of progression to Parkinson's disease (low risk = 30, high risk = 49). We also measured B-cell activating factor of the tumour necrosis factor receptor family, C-reactive protein and total immunoglobulin G. We found elevated levels of antibodies to alpha-synuclein fibrils in rapid eye movement sleep behaviour disorder patients at high risk of Parkinson's disease conversion (ANOVA, P < 0.001) and lower S129D peptide-specific antibodies in those at low risk (ANOVA, P < 0.001). An early humoral response to alpha-synuclein is therefore detectable prior to the development of Parkinson's disease. Peripheral B lymphocyte phenotyping using flow cytometry in early Parkinson's disease patients and matched controls (n = 41 per group) revealed reduced B cells in Parkinson's disease, particularly in those at higher risk of developing an early dementia [t(3) = 2.87, P = 0.01]. Patients with a greater proportion of regulatory B cells had better motor scores [F(4,24) = 3.612, P = 0.019], suggesting they have a protective role in Parkinson's disease. In contrast, B cells isolated from Parkinson's disease patients at higher risk of dementia had greater cytokine (interleukin 6 and interleukin 10) responses following in vitro stimulation. We assessed peripheral blood lymphocytes in alpha-synuclein transgenic mouse models of Parkinson's disease: they also had reduced B cells, suggesting this is related to alpha-synuclein pathology. In a toxin-based mouse model of Parkinson's disease, B-cell deficiency or depletion resulted in worse pathological and behavioural outcomes, supporting the conclusion that B cells play an early protective role in dopaminergic cell loss. In conclusion, we found changes in the B-cell compartment associated with risk of disease progression in rapid eye movement sleep behaviour disorder (higher alpha-synuclein antibodies) and early Parkinson's disease (lower levels of B lymphocytes that were more reactive to stimulation). Regulatory B cells play a protective role in a mouse model, potentially by attenuating inflammation and dopaminergic cell loss. B cells are therefore likely to be involved in the pathogenesis of Parkinson's disease, albeit in a complex way, and thus warrant consideration as a therapeutic target.

Sprouty 1 is associated with stemness and cancer progression in glioblastoma.

Glioblastoma multiforme (GBM) is the most severe type of human brain tumor, with a poor prognosis and a low survival rate. GBM is composed of a variety of cell types, including glioma stem-like cells (GSCs), which attribute to its therapeutic resistance (Boyd et al., 2020). Sprouty1 (SPRY1) was first identified as a receptor tyrosine kinases (RTK) signaling mediator in a mammalian cell (Christofori, 2003), however, its role in GBM is unknown. Therefore, the goal of this study was to investigate the role of SPRY1 in the stemness and aggressiveness of GSCs. The mRNA expression levels of SPRY1 were confirmed using quantitative reverse transcription PCR (RT-qPCR) in normal human astrocytes (NHA), glioma cells, and glioma stem cells. SPRY1 expression was inhibited in glioma stem cells using small interference RNA (siRNAs) to examine its role in cell proliferation and tumorsphere formation. Bioinformatics analyses were also employed to investigate the association of SPRY1 expression with patient survival, tumor grade, and subtypes publicly available datasets. We demonstrated that SPRY1 is highly expressed in glioma stem cells than in NHA, glioma cells, and differentiated glioma stem cells. siRNA-mediated downregulation of SPRY1 expression decreased the stemness and self-renewal ability in GSC11. Bioinformatics results showed that high SPRY1 expression correlates with poor overall survival in glioma patients. Our findings suggest that SPRY1 contributes to the stemness and aggressiveness of GBM.