Infect Agent Cancer. 2023 Jul 31;18(1):46. doi: 10.1186/s13027-023-00521-y.

ABSTRACT

BACKGROUND AND AIMS: Colorectal Cancer (CRC) is a frequent malignancy with a high mortality rate. Specific inherited and environmental influences can affect CRC. Oncolytic viruses and bacteria in treating CRC are one of the innovative therapeutic options. This study aims to determine whether mesenchymal stem cells (MSCs) infected with the Newcastle Disease Virus (NDV) in combination with Lactobacillus casei extract (L. casei) have a synergistic effects on CRC cell line growth.

MATERIALS AND METHODS: MSCs taken from the bone marrow of BALB/c mice and were infected with the 20 MOI of NDV. Then, using the CT26 cell line in various groups as a single and combined treatment, the anticancer potential of MSCs containing the NDV and L. casei extract was examined. The evaluations considered the CT26 survival and the rate at which LDH, ROS, and levels of caspases eight and nine were produced following various treatments.

RESULTS: NDV, MSCs-NDV, and L. casei in alone or combined treatment significantly increased apoptosis percent, LDH, and ROS production compared with the control group (P˂0.05). Also, NDV, in free or capsulated in MSCs, had anticancer effects, but in capsulated form, it had a delay compared with free NDV. The findings proved that L. casei primarily stimulates the extrinsic pathway, while NDV therapy promotes apoptosis through the activation of both intrinsic and extrinsic apoptosis pathways.

CONCLUSIONS: The results suggest that MSCs carrying oncolytic NDV in combination with L. casei extract as a potentially effective strategy for cancer immunotherapy by promoting the generation of LDH, ROS, and apoptosis in the microenvironment of the CT26 cell line.

PMID:37525229 | DOI:10.1186/s13027-023-00521-y

BMC Med Inform Decis Mak. 2023 Jul 31;23(1):143. doi: 10.1186/s12911-023-02209-0.

ABSTRACT

BACKGROUND: Diagnoses are crucial assets of clinical work and provide the foundation for treatment and follow up. They should be informative and customized to the patient's problem. Common prefixes, morphemes, and suffixes may aid the implementation of expressions that generate diagnoses.

RESULTS: Apt choices of symbols plays a major role in science. In this study, the variables e, o, and p are assigned to names of an etiological agent, a disorder, and a pathogenetic mechanism, respectively. The suffix -itis designates infections, allergies, inflammation, and/or immune reactions. Diagnoses (d) are generated by the formula d:= e&o&p where '&' means concatenation and ':= ' means assignment. Thus, with e:= 'Staphylococcus aureus ', o:= 'endocard', and p:= 'itis', d:= e&o&p generates the diagnosis d = 'Staphylococcus aureus endocarditis'. Diagnoses formed this way comply with common clinical diagnoses. Certain extensions generate complete, systematic medical diagnoses that are applicable to all medical specialties. For example, common medical prefixes, morphemes, and suffixes give rise to o = 'hypothyroidism', o = 'tachycardia', and o = 'hypophagocytosis'. The formula scales well with the developments in clinical medicine, systems biology, molecular biology, and microbiology. The diagnosis generating formula d:= e&o&p requires meticulous analysis of the components of diagnoses plus the introduction of appropriate variables and terms. Terms partition on established clinical categories and adhere to established clinical nomenclature. The syntax generates universal medical diagnoses.

CONCLUSIONS: The present study concerns a universal diagnosis syntax (UDS) that generates diagnoses using the formula d:= e&o&p with several extensions described in the study. The formula is easy to learn and covers diagnoses in all medical specialties. The present work succeeded in creating diagnoses from the formula. The fundamental insight is that no matter how complicated a diagnosis is it can be generated by a systematic process, which adds terms one by one. UDS may have implications for medical education and classifications. The formula lays a foundation for structured clinical decision-making. Formulas are hallmarks of hard science. So, d:= e&o&p anticipates a scientific medical revolution.

PMID:37525189 | DOI:10.1186/s12911-023-02209-0

Adv Exp Med Biol. 2023;1423:235-236. doi: 10.1007/978-3-031-31978-5_22.

ABSTRACT

Breast milk is the ideal food for the premature and mature babies and has undoubtedly immediate and ultimate benefits. Among other things, it protects against infections, reduces the risk of necrotizing enterocolitis and retinopathy of the premature babies, improves neurodevelopmental outcome, and reduces the risk of obesity and metabolic syndrome later in life. In the present study, breast milk will be studied with all the available omics technologies. More specifically, functional genomics, comparative genomics, transcriptomics, sequencing, proteomics, and metabolomics will be performed. The above results and this multidimensional information will be coordinated under the framework of a holistic approach of systems biology and bioinformatic analysis. Important IncRNAs and protein molecules will be validated as candidate biomarkers in exosomes of a larger group of breast milk and blood/serum samples. Validated ncRNAs/proteins will be analyzed in exudates of breast milk and bovine, goat, and sheep milk to explore new ways to improve milk synthesis. Expression of ncRNAs, unlike mRNAs, is a direct indicator of their functional presence. The information to be generated in this study will be analyzed by mining and data combining techniques and algorithms. After defining breast milk molecular fingerprinting, an attempt will be made to enhance the commercial product. The benefits of breast milk are attributed to its various components, including nutrients, hormones, growth factors, immune cells, antibodies, cytokines, antimicrobial peptides, and extracellular vesicles.

PMID:37525049 | DOI:10.1007/978-3-031-31978-5_22

Adv Exp Med Biol. 2023;1423:215-224. doi: 10.1007/978-3-031-31978-5_20.

ABSTRACT

Gene regulatory network (GRN) inference from gene expression data is a highly complex and challenging task in systems biology. Despite the challenges, GRNs have emerged, and for complex diseases such as neurodegenerative diseases, they have the potential to provide vital information and identify key regulators. However, every GRN method produced predicts results based on its assumptions, providing limited biological insights. For that reason, the current work focused on the development of an ensemble method from individual GRN methods to address this issue. Four state-of-the-art GRN algorithms were selected to form a consensus GRN from their common gene interactions. Each algorithm uses a different construction method, and for a more robust behavior, both static and dynamic methods were selected as well. The algorithms were applied to a scRNA-seq dataset from the CK-p25 mus musculus model during neurodegeneration. The top subnetworks were constructed from the consensus network, and potential key regulators were identified. The results also demonstrated the overlap between the algorithms for the current dataset and the necessity for an ensemble approach. This work aims to demonstrate the creation of an ensemble network and provide insights into whether a combination of different GRN methods can produce valuable results.

PMID:37525047 | DOI:10.1007/978-3-031-31978-5_20

Adv Exp Med Biol. 2023;1423:149-160. doi: 10.1007/978-3-031-31978-5_12.

ABSTRACT

Parkinson's disease (PD) is the second most common neurodegenerative disorder, affecting millions of people worldwide. Despite considerable efforts, the underlying pathological mechanisms remain elusive, and yet, no treatment has been developed to efficiently reverse or modify disease progression. Thus, new experimental models are required to provide insights into the pathology of PD. Small-molecule neural precursor cells (smNPCs) are ideal for the study of neurodegenerative disorders due to their neural identity and stem cell properties. Cytoplasmic aggregates of α-synuclein (αSyn) are considered a hallmark of PD and a point mutation in the gene encoding p.A53T is responsible for a familial PD form with earlier and robust symptom onset. In order to study the cellular pathology of PD, we genetically modified smNPCs to inducibly overexpress EYFP-SNCA A53T. This cellular model was biochemically characterized, while dysregulated biological pathways and key regulators of PD pathology were identified by computational analyses. Our study indicates three novel genes, UBA52, PIP5K1A, and RPS2, which may mediate PD cellular pathology.

PMID:37525039 | DOI:10.1007/978-3-031-31978-5_12

Acta Neuropathol. 2023 Jul 31. doi: 10.1007/s00401-023-02609-6. Online ahead of print.

ABSTRACT

Malignant brain tumors, known as H3K27-altered diffuse midline glioma (DMG) and H3G34-mutant diffuse hemispheric glioma (DHG), can affect individuals of all ages and are classified as CNS WHO grade 4. We comprehensively characterized 390 H3F3A-mutant diffuse gliomas (201 females, 189 males) arising in pediatric patients (under 20 years old) and adults (20 years and older) evaluated by the CGP program at Foundation Medicine between 2013 and 2020. We assessed information from pathology reports, histopathology review, and clinical data. The cohort included 304 H3K27M-mutant DMG (156 females, 148 males) and 86 H3G34-mutant DHG (45 females, 41 males). Median patient age was 20 years (1-74 years). The frequency of H3K27M-mutant DMG was similar in both pediatric and adult patients in our cohort-48.6% of the patients were over 20 years old, 31.5% over 30, and 18% over 40 at initial diagnosis. FGFR1 hotspot point mutations (N546K and K656E) were exclusively identified in H3K27M-mutant DMG tumors (64/304, 21%; p = 0.0001); these tend to occur in older patients (median age: 32.5 years) and mainly arose in the diencephalon. H3K27M-mutant DMG had higher rates of mutations in NF1 (31.0 vs 8.1%; p = 0.0001) and PIK3CA/PIK3R1 (27.9% vs 15.1%; p = 0.016) compared to H3G34-mutant DHG. However, H3G34-mutant DHG had higher rates of targetable alterations in cell-cycle pathway genes (CDK4 and CDK6 amplification; CDKN2A/B deletion) (27.0 vs 9.0%). Potentially targetable PDGFRA alterations were identified in ~ 20% of both H3G34-mutant DHG and H3K27M-mutant DMG. Overall, in the present study H3K27M-mutant DMG occurred at similar rates in both adult and patient patients. Through our analysis, we were able to identify molecular features characteristic of DMG and DHG. By identifying the recurrent co-mutations including actionable FGFR1 point mutations found in nearly one-third of H3K27M-mutant DMG in young adults, our findings can inform clinical translational studies, patient diagnosis, and clinical trial design.

PMID:37524847 | DOI:10.1007/s00401-023-02609-6

Nat Commun. 2023 Jul 31;14(1):4591. doi: 10.1038/s41467-023-40217-w.

ABSTRACT

Herpes simplex virus 1 (HSV-1) infection and stress responses disrupt transcription termination by RNA Polymerase II (Pol II). In HSV-1 infection, but not upon salt or heat stress, this is accompanied by a dramatic increase in chromatin accessibility downstream of genes. Here, we show that the HSV-1 immediate-early protein ICP22 is both necessary and sufficient to induce downstream open chromatin regions (dOCRs) when transcription termination is disrupted by the viral ICP27 protein. This is accompanied by a marked ICP22-dependent loss of histones downstream of affected genes consistent with impaired histone repositioning in the wake of Pol II. Efficient knock-down of the ICP22-interacting histone chaperone FACT is not sufficient to induce dOCRs in ΔICP22 infection but increases dOCR induction in wild-type HSV-1 infection. Interestingly, this is accompanied by a marked increase in chromatin accessibility within gene bodies. We propose a model in which allosteric changes in Pol II composition downstream of genes and ICP22-mediated interference with FACT activity explain the differential impairment of histone repositioning downstream of genes in the wake of Pol II in HSV-1 infection.

PMID:37524699 | DOI:10.1038/s41467-023-40217-w

Nat Commun. 2023 Jul 31;14(1):4600. doi: 10.1038/s41467-023-40314-w.

ABSTRACT

Neuropathy is a feature more frequently observed in pancreatic ductal adenocarcinoma (PDAC) than other tumors. Schwann cells, the most prevalent cell type in peripheral nerves, migrate toward tumor cells and associate with poor prognosis in PDAC. To unveil the effects of Schwann cells on the neuro-stroma niche, here we perform single-cell RNA-sequencing and microarray-based spatial transcriptome analysis of PDAC tissues. Results suggest that Schwann cells may drive tumor cells and cancer-associated fibroblasts (CAFs) to more malignant subtypes: basal-like and inflammatory CAFs (iCAFs), respectively. Moreover, in vitro and in vivo assays demonstrate that Schwann cells enhance the proliferation and migration of PDAC cells via Midkine signaling and promote the switch of CAFs to iCAFs via interleukin-1α. Culture of tumor cells and CAFs with Schwann cells conditioned medium accelerates PDAC progression. Thus, we reveal that Schwann cells induce malignant subtypes of tumor cells and CAFs in the PDAC milieu.

PMID:37524695 | DOI:10.1038/s41467-023-40314-w

Anal Chem. 2023 Jul 31. doi: 10.1021/acs.analchem.3c01630. Online ahead of print.

ABSTRACT

Ribonuclease (RNA) modifications can alter cellular function and lead to differential immune responses by acting as discriminators between RNAs from different phyla. RNA glycosylation has recently been observed at the cell surface, and its dysregulation in disease may change RNA functions. However, determining which RNA substrates can be glycosylated remains to be explored. Here, we develop a solid-phase chemoenzymatic method (SPCgRNA) for targeting glycosylated RNAs, by which glycosylated RNA substrates can be specifically recognized. We found the differential N-glycosylation of small RNAs in hTERT-HPNE and MIA PaCa-2 cancer cells using SPCgRNA. RNA-Seq showed that the changes in glyco-miRNAs prepared from SPCgRNA were consistent with those of traditional methods. The KEGG signaling pathway analysis revealed that differential miRNA glycosylation can affect tumor cell proliferation and survival. Further studies found that NGI-1 significantly inhibited the proliferation, migration, and circulation of MIA PaCa-2 and promoted cell apoptosis. In addition, β-1,4-galactosyltransferase 1 (B4GALT1) not only affected the expression level of glycosylated miRNAs hsa-miR-21-5p but also promoted cell apoptosis and inhibited the cell cycle possibly through the p53 signaling pathway, while B4GALT1 and p53 were also affected following the hsa-miR-21-5p increase. These results suggest that B4GALT1 may catalyze miRNAs glycosylation, which further promotes cancer cell progression.

PMID:37524653 | DOI:10.1021/acs.analchem.3c01630

Cardiovasc Res. 2023 Jul 31:cvad118. doi: 10.1093/cvr/cvad118. Online ahead of print.

ABSTRACT

Atrial fibrillation (AF), the most prevalent clinical arrhythmia, is associated with atrial remodeling manifesting as acute and chronic alterations in expression, function, and regulation of atrial electrophysiological and Ca2+-handling processes. These AF-induced modifications crosstalk and propagate across spatial scales creating a complex pathophysiological network, which renders AF resistant to existing pharmacotherapies that predominantly target transmembrane ion channels. Developing innovative therapeutic strategies requires a systems approach to disentangle quantitatively the proarrhythmic contributions of individual AF-induced alterations. Here, we built a novel computational framework for simulating electrophysiology and Ca2+-handling in human atrial cardiomyocytes and tissues, and their regulation by key upstream signaling pathways (i.e., protein kinase A, PKA, and Ca2+/calmodulin-dependent protein kinase II, CaMKII) involved in AF-pathogenesis. Populations of atrial cardiomyocyte models were constructed to determine the influence of subcellular ionic processes, signaling components, and regulatory networks on atrial arrhythmogenesis. Our results reveal a novel synergistic crosstalk between PKA and CaMKII that promotes atrial cardiomyocyte electrical instability and arrhythmogenic triggered activity. Simulations of heterogeneous tissue demonstrate that this cellular triggered activity is further amplified by CaMKII- and PKA-dependent alterations of tissue properties, further exacerbating atrial arrhythmogenesis. Our analysis reveals potential mechanisms by which the stress-associated adaptive changes turn into maladaptive proarrhythmic triggers at the cellular and tissue levels and identifies potential anti-AF targets. Collectively, our integrative approach is powerful and instrumental to assemble and reconcile existing knowledge into a systems network for identifying novel anti-AF targets and innovative approaches moving beyond the traditional ion channel-based strategy.

PMID:37523735 | DOI:10.1093/cvr/cvad118

Proc Natl Acad Sci U S A. 2023 Aug 8;120(32):e2307451120. doi: 10.1073/pnas.2307451120. Epub 2023 Jul 31.

ABSTRACT

Cell-type-specific tools facilitate the identification and functional characterization of the distinct cell types that form the complexity of neuronal circuits. A large collection of existing genetic tools in Drosophila relies on enhancer activity to label different subsets of cells and has been extremely useful in analyzing functional circuits in adults. However, these enhancer-based GAL4 lines often do not reflect the expression of nearby gene(s) as they only represent a small portion of the full gene regulatory elements. While genetic intersectional techniques such as the split-GAL4 system further improve cell-type-specificity, it requires significant time and resources to screen through combinations of enhancer expression patterns. Here, we use existing developmental single-cell RNA sequencing (scRNAseq) datasets to select gene pairs for split-GAL4 and provide a highly efficient and predictive pipeline (scMarco) to generate cell-type-specific split-GAL4 lines at any time during development, based on the native gene regulatory elements. These gene-specific split-GAL4 lines can be generated from a large collection of coding intronic MiMIC/CRIMIC lines or by CRISPR knock-in. We use the developing Drosophila visual system as a model to demonstrate the high predictive power of scRNAseq-guided gene-specific split-GAL4 lines in targeting known cell types, annotating clusters in scRNAseq datasets as well as in identifying novel cell types. Lastly, the gene-specific split-GAL4 lines are broadly applicable to any other Drosophila tissue. Our work opens new avenues for generating cell-type-specific tools for the targeted manipulation of distinct cell types throughout development and represents a valuable resource for the Drosophila community.

PMID:37523539 | DOI:10.1073/pnas.2307451120

PLoS Comput Biol. 2023 Jul 31;19(7):e1010832. doi: 10.1371/journal.pcbi.1010832. Online ahead of print.

ABSTRACT

Despite extensive research efforts, reconstruction of gene regulatory networks (GRNs) from transcriptomics data remains a pressing challenge in systems biology. While non-linear approaches for reconstruction of GRNs show improved performance over simpler alternatives, we do not yet have understanding if joint modelling of multiple target genes may improve performance, even under linearity assumptions. To address this problem, we propose two novel approaches that cast the GRN reconstruction problem as a blend between regularized multivariate regression and graphical models that combine the L2,1-norm with classical regularization techniques. We used data and networks from the DREAM5 challenge to show that the proposed models provide consistently good performance in comparison to contenders whose performance varies with data sets from simulation and experiments from model unicellular organisms Escherichia coli and Saccharomyces cerevisiae. Since the models' formulation facilitates the prediction of master regulators, we also used the resulting findings to identify master regulators over all data sets as well as their plasticity across different environments. Our results demonstrate that the identified master regulators are in line with experimental evidence from the model bacterium E. coli. Together, our study demonstrates that simultaneous modelling of several target genes results in improved inference of GRNs and can be used as an alternative in different applications.

PMID:37523414 | DOI:10.1371/journal.pcbi.1010832

PLoS Negl Trop Dis. 2023 Jul 31;17(7):e0011514. doi: 10.1371/journal.pntd.0011514. Online ahead of print.

ABSTRACT

BACKGROUND: Human African trypanosomiasis is a parasitic disease caused by trypanosomes among which Trypanosoma brucei gambiense is responsible for a chronic form (gHAT) in West and Central Africa. Its elimination as a public health problem (EPHP) is being achieved. Côte d'Ivoire was one of the first countries to be validated by WHO in 2020 and this was particularly challenging as the country still reported around a hundred cases a year in the early 2000s. This article describes the strategies implemented including a mathematical model to evaluate the reporting results and infer progress towards sustainable elimination.

METHODS: The control methods used combined both exhaustive and targeted medical screening strategies including the follow-up of seropositive subjects considered as potential asymptomatic carriers to diagnose and treat cases as well as vector control to reduce the risk of transmission in the most at-risk areas. A mechanistic model was used to estimate the number of underlying infections and the probability of elimination of transmission (EoT) between 2000-2021 in two endemic and two hypo-endemic health districts.

RESULTS: Between 2015 and 2019, nine gHAT cases were detected in the two endemic health districts of Bouaflé and Sinfra in which the number of cases/10,000 inhabitants was far below 1, a necessary condition for validating the EPHP. Modelling estimated a slow but steady decline in transmission across the four health districts, bolstered in the two endemic health districts by the introduction of vector control. The decrease in underlying transmission in all health districts corresponds to a high probability that EoT has already occurred in Côte d'Ivoire.

CONCLUSION: This success was achieved through a multi-stakeholder and multidisciplinary one health approach where research has played a major role in adapting tools and strategies to this large epidemiological transition to a very low prevalence. This integrated approach will need to continue to reach the verification of EoT in Côte d'Ivoire targeted by 2025.

PMID:37523361 | DOI:10.1371/journal.pntd.0011514

Hum Mol Genet. 2023 Jul 31:ddad122. doi: 10.1093/hmg/ddad122. Online ahead of print.

ABSTRACT

Aggregation of TAR DNA-binding protein 43 kDa (TDP-43) is thought to drive the pathophysiology of ALS and some Frontotemporal dementias. TDP-43 is normally a nuclear protein that in neurons translocates to the cytoplasm and can form insoluble aggregates upon activation of the integrated stress response (ISR). Viruses evolved to control the ISR. In the case of Herpesvirus 8, the protein ORF57 acts to bind protein kinase R, inhibit phosphorylation of eIF2α and reduce activation of the ISR. We hypothesized that ORF57 might also possess the ability to inhibit aggregation of TDP-43. ORF57 was expressed in the neuronal SH-SY5Y line and its effects on TDP-43 aggregation characterized. We report that ORF57 inhibits TDP-43 aggregation by 55% and elicits a 2.45-fold increase in the rate of dispersion of existing TDP-43 granules. These changes were associated with a 50% decrease in cell death. Proteomic studies were carried out to identify the protein interaction network of ORF57. We observed that ORF57 directly binds to TDP-43 as well as interacts with many components of the ISR, including elements of the proteostasis machinery known to reduce TDP-43 aggregation. We propose that viral proteins designed to inhibit a chronic ISR can be engineered to remove aggregated proteins and dampen a chronic ISR.

PMID:37522762 | DOI:10.1093/hmg/ddad122

Eur Rev Med Pharmacol Sci. 2023 Jul;27(14):6876-6881. doi: 10.26355/eurrev_202307_33159.

ABSTRACT

OBJECTIVE: This retrospective study aimed at ascertaining the clinical usefulness of nebulized myo-inositol in the management of patients affected by bronchiectasis.

PATIENTS AND METHODS: 19 patients, aged between 63 and 73 years old, with bronchiectasis, were treated for 15 days with nebulized myo-inositol or placebo. Lung functionality [forced expiratory volume in the 1st second (FEV1)], solid content of expectorate, and surfactant tension were analyzed.

RESULTS: All patients treated with nebulized myo-inositol had a significant decrease in the percentage of solid content in the expectorate (T0 7.9±2.8% vs. T1 5.2±2.7%; p<0.001) and surfactant tension (T0 81.5±6.9 mN/m vs. T1 77.4±7.2 mN/m; p<0.001). Among treated patients, these variations correlated with FEV1 (rs=- 0.79; p<0.01) and forced expiratory flow at 25-75% of FVC (FEF25-75%) (rs=-0.81; p<0.01) scores. Also, variation of surfactant tension correlated with FEV1 (rs= -0.74; p<0.05) score.

CONCLUSIONS: Nebulized myo-inositol increases lung functionality and mucus clearance in patients affected by bronchiectasis.

PMID:37522700 | DOI:10.26355/eurrev_202307_33159

Plant J. 2023 Jul 31. doi: 10.1111/tpj.16406. Online ahead of print.

ABSTRACT

Diurnal dark to light transition causes profound physiological changes in plant metabolism. These changes require distinct modes of regulation as a unique feature of photosynthetic lifestyle. The activities of several key metabolic enzymes are regulated by light-dependent post-translational modifications (PTM) and have been studied at depth at the level of individual proteins. In contrast, a global picture of the light-dependent PTMome dynamics is lacking, leaving the response of a large proportion of cellular function undefined. Here, we investigated the light-dependent metabolome and proteome changes in Arabidopsis rosettes in a time resolved manner to dissect their kinetic interplay, focusing on phosphorylation, lysine acetylation, and cysteine-based redox switches. Of over 24 000 PTM sites that were detected, more than 1700 were changed during the transition from dark to light. While the first changes, as measured 5 min after onset of illumination, occurred mainly in the chloroplasts, PTM changes at proteins in other compartments coincided with the full activation of the Calvin-Benson cycle and the synthesis of sugars at later timepoints. Our data reveal connections between metabolism and PTM-based regulation throughout the cell. The comprehensive multiome profiling analysis provides unique insight into the extent by which photosynthesis reprograms global cell function and adds a powerful resource for the dissection of diverse cellular processes in the context of photosynthetic function.

PMID:37522418 | DOI:10.1111/tpj.16406

Med Phys. 2023 Jul 31. doi: 10.1002/mp.16655. Online ahead of print.

ABSTRACT

BACKGROUND: Alzheimer's disease (AD) is a heterogeneous, multifactorial neurodegenerative disorder characterized by three neurobiological factors beta-amyloid, pathologic tau, and neurodegeneration. There are no effective treatments for AD at a late stage, urging for early detection and prevention. However, existing statistical inference approaches in neuroimaging studies of AD subtype identification do not take into account the pathological domain knowledge, which could lead to ill-posed results that are sometimes inconsistent with the essential neurological principles.

PURPOSE: Integrating systems biology modeling with machine learning, the study aims to assist clinical AD prognosis by providing a subpopulation classification in accordance with essential biological principles, neurological patterns, and cognitive symptoms.

METHODS: We propose a novel pathology steered stratification network (PSSN) that incorporates established domain knowledge in AD pathology through a reaction-diffusion model, where we consider non-linear interactions between major biomarkers and diffusion along the brain structural network. Trained on longitudinal multimodal neuroimaging data, the biological model predicts long-term evolution trajectories that capture individual characteristic progression pattern, filling in the gaps between sparse imaging data available. A deep predictive neural network is then built to exploit spatiotemporal dynamics, link neurological examinations with clinical profiles, and generate subtype assignment probability on an individual basis. We further identify an evolutionary disease graph to quantify subtype transition probabilities through extensive simulations.

RESULTS: Our stratification achieves superior performance in both inter-cluster heterogeneity and intra-cluster homogeneity of various clinical scores. Applying our approach to enriched samples of aging populations, we identify six subtypes spanning AD spectrum, where each subtype exhibits a distinctive biomarker pattern that is consistent with its clinical outcome.

CONCLUSIONS: The proposed PSSN (i) reduces neuroimage data to low-dimensional feature vectors, (ii) combines AT[N]-Net based on real pathological pathways, (iii) predicts long-term biomarker trajectories, and (iv) stratifies subjects into fine-grained subtypes with distinct neurological underpinnings. PSSN provides insights into pre-symptomatic diagnosis and practical guidance on clinical treatments, which may be further generalized to other neurodegenerative diseases.

PMID:37522278 | DOI:10.1002/mp.16655

Front Endocrinol (Lausanne). 2023 Jul 13;14:1223931. doi: 10.3389/fendo.2023.1223931. eCollection 2023.

NO ABSTRACT

PMID:37522132 | PMC:PMC10374356 | DOI:10.3389/fendo.2023.1223931

Egypt J Med Hum Genet. 2022;23(1):146. doi: 10.1186/s43042-022-00360-3. Epub 2022 Oct 20.

ABSTRACT

BACKGROUND: Worldwide, COVID-19's death rate is about 2%, considering the incidence and mortality. However, the information on its complications in other organs, specifically the liver and its disorders, is limited in mild or severe cases. In this study, we aimed to computationally investigate the typical relationships between liver-related diseases [i.e., hepatocellular carcinoma (HCC), and chronic hepatitis B (CHB)] and COVID-19, considering the involved significant genes and their molecular mechanisms.

METHODS: We investigated two GEO microarray datasets (GSE164805 and GSE58208) to identify differentially expressed genes (DEGs) among the generated four datasets for mild/severe COVID-19, HCC, and CHB. Then, the overlapping genes among them were identified for GO and KEGG enrichment analyses, protein-protein interaction network construction, hub genes determination, and their associations with immune cell infiltration.

RESULTS: A total of 22 significant genes (i.e., ACTB, ATM, CDC42, DHX15, EPRS, GAPDH, HIF1A, HNRNPA1, HRAS, HSP90AB1, HSPA8, IL1B, JUN, POLR2B, PTPRC, RPS27A, SFRS1, SMARCA4, SRC, TNF, UBE2I, and VEGFA) were found to play essential roles among mild/severe COVID-19 associated with HCC and CHB. Moreover, the analysis of immune cell infiltration revealed that these genes are mostly positively correlated with tumor immune and inflammatory responses.

CONCLUSIONS: In summary, the current study demonstrated that 22 identified DEGs might play an essential role in understanding the associations between the mild/severe COVID-19 patients with HCC and CHB. So, the HCC and CHB patients involved in different types of COVID-19 can benefit from immune-based targets for therapeutic interventions.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s43042-022-00360-3.

PMID:37521843 | PMC:PMC9584277 | DOI:10.1186/s43042-022-00360-3

One Health Adv. 2023;1(1):12. doi: 10.1186/s44280-023-00012-0. Epub 2023 Apr 30.

ABSTRACT

Potent neutralizing antibodies (nAbs) against SARS-CoV-2 are a promising therapeutic against the ongoing COVID-19 pandemic. However, the continuous emergence of neutralizing antibody escape variants makes it challenging for antibody therapeutics based on monospecific nAbs. Here, we generated an IgG-like bispecific antibody (bsAb), Bi-Nab, based on a pair of human neutralizing antibodies targeting multiple and invariant sites of the spike receptor binding domain (RBD): 35B5 and 32C7. We demonstrated that Bi-Nab exhibited higher binding affinity to the Delta spike protein than its parental antibodies and presented an extended inhibition breadth of preventing RBD binding to angiotensin-converting enzyme 2 (ACE2), the cellular receptor of SARS-CoV-2. In addition, pseudovirus neutralization results showed that Bi-Nab improved the neutralization potency and breadth with a lower half maximum inhibitory concentration (IC50) against wild-type SARS-CoV-2, variants being monitored (VBMs) and variants of concern (VOCs). Notably, the IgG-like Bi-Nab enhanced the neutralizing activity against Omicron variants with potent capabilities for transmission and immune evasion in comparison with its parental monoclonal antibody (mAb) 32C7 and a cocktail (with the lowest IC50 values of 31.6 ng/mL against the Omicron BA.1 and 399.2 ng/mL against the Omicron BA.2), showing evidence of synergistic neutralization potency of Bi-Nab against the Omicron variants. Thus, Bi-Nab represents a feasible and effective strategy against SARS-CoV-2 variants of concern.

PMID:37521533 | PMC:PMC10173222 | DOI:10.1186/s44280-023-00012-0