Environ Sustain (Singap). 2021;4(3):579-584. doi: 10.1007/s42398-021-00175-9. Epub 2021 May 20.

ABSTRACT

Coronavirus disease (COVID-19) has emerged as a major global challenge since 2019. With the fast rise in the infected cases and deaths worldwide, many environmental and climate-related myths and fallacies spreaded fast. These fallacies include virus cannot spread in hot and humid conditions, cold weather can inhibit the virus, drinking hot water and sunlight can help cure the COVID-19, ultraviolet (UV) disinfectant lamps and UV rays from sunlight can kill the virus, use of hairdryers and hot showers for virus prevention, etc. Social norms and mindset of the people in the world towards a pandemic are quite similar. The primary purpose of this article is to enlighten the readers regarding these climatological misconceptions and social fallacies, helping spread proper knowledge and manage the outbreak of this deadly pandemic.

PMID:38624610 | PMC:PMC8136260 | DOI:10.1007/s42398-021-00175-9

iScience. 2024 Mar 27;27(4):109601. doi: 10.1016/j.isci.2024.109601. eCollection 2024 Apr 19.

ABSTRACT

Stereotactic radiosurgery (SRS) has been shown to be efficacious for the treatment of limited brain metastasis (BM); however, the effects of SRS on human brain metastases have yet to be studied. We performed genomic analysis on resected brain metastases from patients whose resected lesion was previously treated with SRS. Our analyses demonstrated for the first time that patients possess a distinct genomic signature based on type of treatment failure including local failure, leptomeningeal spread, and radio-necrosis. Examination of the center and peripheral edge of the tumors treated with SRS indicated differential DNA damage distribution and an enrichment for tumor suppressor mutations and DNA damage repair pathways along the peripheral edge. Furthermore, the two clinical modalities used to deliver SRS, LINAC and GK, demonstrated differential effects on the tumor landscape even between controlled primary sites. Our study provides, in human, biological evidence of differential effects of SRS across BM's.

PMID:38623341 | PMC:PMC11016778 | DOI:10.1016/j.isci.2024.109601

Acta Biomater. 2024 Apr 13:S1742-7061(24)00192-2. doi: 10.1016/j.actbio.2024.04.019. Online ahead of print.

ABSTRACT

Bacterial infection remains a significant problem associated with orthopaedic surgeries leading to surgical site infection (SSI). This unmet medical need can become an even greater complication when surgery is due to malignant bone tumor. In the present study, we evaluated in vitro titanium (Ti) implants subjected to gallium (Ga) and silver (Ag)-doped thermochemical treatment as strategy to prevent SSI and improve osteointegration in bone defects caused by diseases such as osteoporosis, bone tumor, or bone metastasis. Firstly, as Ga has been reported to be an osteoinductive and anti-resorptive agent, its performance in the mixture was proved by studying human mesenchymal stem cells (hMSC) and pre-osteoclasts (RAW264.7) behaviour. Then, the antibacterial potential provided by Ag was assessed by resembling "The Race for the Surface" between hMSC and Pseudomonas aeruginosa in two co-culture methods. Moreover, the presence of quorum sensing molecules in the co-culture was evaluated. The results highlighted the suitability of the mixture to induce osteodifferentiation and reduce osteoclastogenesis in vitro. Furthermore, the GaAg surface promoted strong survival rate and retained osteoinduction potential of hMSCs even after bacterial inoculation. Therefore, GaAg-modified titanium may be an ideal candidate to repair bone defects caused by excessive bone resorption, in addition to preventing SSI. STATEMENT OF SIGNIFICANCE: This article provides important insights into titanium for fractures caused by osteoporosis or bone metastases with high incidence in surgical site infection (SSI) because in this situation bacterial infection can become a major disaster. In order to solve this unmet medical need, we propose a titanium implant modified with gallium and silver to improve osteointegration, reduce bone resorption and avoid bacterial infection. For that aim, we study osteoblast and osteoclast behavior with the main novelty focused on the antibacterial evaluation. In this work, we recreate "the race for the surface" in long-term experiments and study bacterial virulence factors (quorum sensing). Therefore, we believe that our article could be of great interest, providing a great impact on future orthopedic applications.

PMID:38621600 | DOI:10.1016/j.actbio.2024.04.019

Lancet Microbe. 2024 Apr 11:S2666-5247(23)00399-3. doi: 10.1016/S2666-5247(23)00399-3. Online ahead of print.

ABSTRACT

BACKGROUND: Sequencing of SARS-CoV-2 from rapid diagnostic tests (RDTs) can bolster viral genomic surveillance efforts; however, approaches to maximise and standardise pathogen genome recovery from RDTs remain underdeveloped. We aimed to systematically optimise the elution of genetic material from RDT components and to evaluate the efficacy of RDT sequencing for outbreak investigation.

METHODS: In this laboratory and cohort-based study we seeded RDTs with inactivated SARS-CoV-2 to optimise the elution of genomic material from RDT lateral flow strips. We measured the effect of changes in buffer type, time in buffer, and rotation on PCR cycle threshold (Ct) value. We recruited individuals older than 18 years residing in the greater Boston area, MA, USA, from July 18 to Nov 5, 2022, via email advertising to students and staff at Harvard University, MA, USA, and via broad social media advertising. All individuals recruited were within 5 days of a positive diagnostic test for SARS-CoV-2; no other relevant exclusion criteria were applied. Each individual completed two RDTs and one PCR swab. On Dec 29, 2022, we also collected RDTs from a convenience sample of individuals who were positive for SARS-CoV-2 and associated with an outbreak at a senior housing facility in MA, USA. We extracted all returned PCR swabs and RDT components (ie, swab, strip, or buffer); samples with a Ct of less than 40 were subject to amplicon sequencing. We compared the efficacy of elution and sequencing across RDT brands and components and used RDT-derived sequences to infer transmission links within the outbreak at the senior housing facility. We conducted metagenomic sequencing of negative RDTs from symptomatic individuals living in the senior housing facility.

FINDINGS: Neither elution duration of greater than 10 min nor rotation during elution impacted viral titres. Elution in Buffer AVL (Ct=31·4) and Tris-EDTA Buffer (Ct=30·8) were equivalent (p=0·34); AVL outperformed elution in lysis buffer and 50% lysis buffer (Ct=40·0, p=0·0029 for both) as well as Universal Viral Transport Medium (Ct=36·7, p=0·079). Performance of RDT strips was poorer than that of matched PCR swabs (mean Ct difference 10·2 [SD 4·3], p<0·0001); however, RDT swabs performed similarly to PCR swabs (mean Ct difference 4·1 [5·2], p=0·055). No RDT brand significantly outperformed another. Across sample types, viral load predicted the viral genome assembly length. We assembled greater than 80% complete genomes from 12 of 17 RDT-derived swabs, three of 18 strips, and four of 11 residual buffers. We generated outbreak-associated SARS-CoV-2 genomes using both amplicon and metagenomic sequencing and identified multiple introductions of the virus that resulted in downstream transmission.

INTERPRETATION: RDT-derived swabs are a reasonable alternative to PCR swabs for viral genomic surveillance and outbreak investigation. RDT-derived lateral flow strips yield accurate, but significantly fewer, viral reads than matched PCR swabs. Metagenomic sequencing of negative RDTs can identify viruses that might underlie patient symptoms.

FUNDING: The National Science Foundation, the Hertz Foundation, the National Institute of General Medical Sciences, Harvard Medical School, the Howard Hughes Medical Institute, the US Centers for Disease Control and Prevention, the Broad Institute and the National Institute of Allergy and Infectious Diseases.

PMID:38621394 | DOI:10.1016/S2666-5247(23)00399-3

Eur J Med Res. 2024 Apr 15;29(1):234. doi: 10.1186/s40001-024-01777-9.

ABSTRACT

BACKGROUND: Influenza is an acute respiratory infection caused by influenza virus. Maxing Shigan Decoction (MXSGD) is a commonly used traditional Chinese medicine prescription for the prevention and treatment of influenza. However, its mechanism remains unclear.

METHOD: The mice model of influenza A virus pneumonia was established by nasal inoculation. After 3 days of intervention, the lung index was calculated, and the pathological changes of lung tissue were detected by HE staining. Firstly, transcriptomics technology was used to analyze the differential genes and important pathways in mouse lung tissue regulated by MXSGD. Then, real-time fluorescent quantitative PCR (RT-PCR) was used to verify the changes in mRNA expression in lung tissues. Finally, intestinal microbiome and intestinal metabolomics were performed to explore the effect of MXSGD on gut microbiota.

RESULTS: The lung inflammatory cell infiltration in the MXSGD group was significantly reduced (p < 0.05). The results of bioinformatics analysis for transcriptomics results show that these genes are mainly involved in inflammatory factors and inflammation-related signal pathways mediated inflammation biological modules, etc. Intestinal microbiome showed that the intestinal flora Actinobacteriota level and Desulfobacterota level increased in MXSGD group, while Planctomycetota in MXSGD group decreased. Metabolites were mainly involved in primary bile acid biosynthesis, thiamine metabolism, etc. This suggests that MXSGD has a microbial-gut-lung axis regulation effect on mice with influenza A virus pneumonia.

CONCLUSION: MXSGD may play an anti-inflammatory and immunoregulatory role by regulating intestinal microbiome and intestinal metabolic small molecules, and ultimately play a role in the treatment of influenza A virus pneumonia.

PMID:38622728 | DOI:10.1186/s40001-024-01777-9

Brief Bioinform. 2024 Mar 27;25(3):bbae175. doi: 10.1093/bib/bbae175.

ABSTRACT

Community cohesion plays a critical role in the determination of an individual's health in social science. Intriguingly, a community structure of gene networks indicates that the concept of community cohesion could be applied between the genes as well to overcome the limitations of single gene-based biomarkers for precision oncology. Here, we develop community cohesion scores which precisely quantify the community ability to retain the interactions between the genes and their cellular functions in each individualized gene network. Using breast cancer as a proof-of-concept study, we measure the community cohesion score profiles of 950 case samples and predict the individualized therapeutic targets in 2-fold. First, we prioritize them by finding druggable genes present in the community with the most and relatively decreased scores in each individual. Then, we pinpoint more individualized therapeutic targets by discovering the genes which greatly contribute to the community cohesion looseness in each individualized gene network. Compared with the previous approaches, the community cohesion scores show at least four times higher performance in predicting effective individualized chemotherapy targets based on drug sensitivity data. Furthermore, the community cohesion scores successfully discover the known breast cancer subtypes and we suggest new targeted therapy targets for triple negative breast cancer (e.g. KIT and GABRP). Lastly, we demonstrate that the community cohesion scores can predict tamoxifen responses in ER+ breast cancer and suggest potential combination therapies (e.g. NAMPT and RXRA inhibitors) to reduce endocrine therapy resistance based on individualized characteristics. Our method opens new perspectives for the biomarker development in precision oncology.

PMID:38622359 | DOI:10.1093/bib/bbae175

Sci Rep. 2024 Apr 15;14(1):8685. doi: 10.1038/s41598-024-59355-2.

ABSTRACT

To understand the effect of protein fusion on the recognition of a peptide-tag by an antibody, we fused a CCR5-derived peptide-tag (pep1) to GFP and investigated its recognition by an anti-pep1 antibody, 4B08. First, to characterize the thermodynamic properties associated with the pep1-4B08 binding, isothermal titration calorimetry experiments were conducted. It was found that pep1 fused to the C-terminus of GFP (GFP-CT) enhanced the enthalpic gain by 2.1 kcal mol-1 and the entropic loss only by 0.9 kcal mol-1, resulting in an 8-fold increase in the binding affinity compared to the unfused pep1. On the other hand, pep1 fused to the N-terminus of GFP (GFP-NT) enhanced the enthalpic gain by 3.0 kcal mol-1 and the entropic loss by 3.2 kcal mol-1, leading to no significant enhancement of the binding affinity. To gain deeper insights, molecular dynamics simulations of GFP-NT, GFP-CT, and pep1 were performed. The results showed that the location of the fusion point sensitively affects the interaction energy, the solvent accessible surface area, and the fluctuation of pep1 in the unbound state, which explains the difference in the experimental thermodynamic properties.

PMID:38622354 | DOI:10.1038/s41598-024-59355-2

Nat Genet. 2024 Apr;56(4):721-731. doi: 10.1038/s41588-024-01695-w. Epub 2024 Apr 15.

ABSTRACT

Coffea arabica, an allotetraploid hybrid of Coffea eugenioides and Coffea canephora, is the source of approximately 60% of coffee products worldwide, and its cultivated accessions have undergone several population bottlenecks. We present chromosome-level assemblies of a di-haploid C. arabica accession and modern representatives of its diploid progenitors, C. eugenioides and C. canephora. The three species exhibit largely conserved genome structures between diploid parents and descendant subgenomes, with no obvious global subgenome dominance. We find evidence for a founding polyploidy event 350,000-610,000 years ago, followed by several pre-domestication bottlenecks, resulting in narrow genetic variation. A split between wild accessions and cultivar progenitors occurred ~30.5 thousand years ago, followed by a period of migration between the two populations. Analysis of modern varieties, including lines historically introgressed with C. canephora, highlights their breeding histories and loci that may contribute to pathogen resistance, laying the groundwork for future genomics-based breeding of C. arabica.

PMID:38622339 | DOI:10.1038/s41588-024-01695-w

Nat Commun. 2024 Apr 15;15(1):3220. doi: 10.1038/s41467-024-47427-w.

ABSTRACT

Induced oncoproteins degradation provides an attractive anti-cancer modality. Activation of anaphase-promoting complex (APC/CCDH1) prevents cell-cycle entry by targeting crucial mitotic proteins for degradation. Phosphorylation of its co-activator CDH1 modulates the E3 ligase activity, but little is known about its regulation after phosphorylation and how to effectively harness APC/CCDH1 activity to treat cancer. Peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1)-catalyzed phosphorylation-dependent cis-trans prolyl isomerization drives tumor malignancy. However, the mechanisms controlling its protein turnover remain elusive. Through proteomic screens and structural characterizations, we identify a reciprocal antagonism of PIN1-APC/CCDH1 mediated by domain-oriented phosphorylation-dependent dual interactions as a fundamental mechanism governing mitotic protein stability and cell-cycle entry. Remarkably, combined PIN1 and cyclin-dependent protein kinases (CDKs) inhibition creates a positive feedback loop of PIN1 inhibition and APC/CCDH1 activation to irreversibly degrade PIN1 and other crucial mitotic proteins, which force permanent cell-cycle exit and trigger anti-tumor immunity, translating into synergistic efficacy against triple-negative breast cancer.

PMID:38622115 | DOI:10.1038/s41467-024-47427-w

Biochemistry (Mosc). 2024 Feb;89(2):377-391. doi: 10.1134/S0006297924020160.

ABSTRACT

High prevalence of human brain disorders necessitates development of the reliable peripheral biomarkers as diagnostic and disease-monitoring tools. In addition to clinical studies, animal models markedly advance studying of non-brain abnormalities associated with brain pathogenesis. The zebrafish (Danio rerio) is becoming increasingly popular as an animal model organism in translational neuroscience. These fish share some practical advantages over mammalian models together with high genetic homology and evolutionarily conserved biochemical and neurobehavioral phenotypes, thus enabling large-scale modeling of human brain diseases. Here, we review mounting evidence on peripheral biomarkers of brain disorders in zebrafish models, focusing on altered biochemistry (lipids, carbohydrates, proteins, and other non-signal molecules, as well as metabolic reactions and activity of enzymes). Collectively, these data strongly support the utility of zebrafish (from a systems biology standpoint) to study peripheral manifestations of brain disorders, as well as highlight potential applications of biochemical biomarkers in zebrafish models to biomarker-based drug discovery and development.

PMID:38622104 | DOI:10.1134/S0006297924020160

Trends Biotechnol. 2024 Apr 15:S0167-7799(24)00086-6. doi: 10.1016/j.tibtech.2024.03.007. Online ahead of print.

ABSTRACT

Ogataea (Hansenula) polymorpha is a nonconventional yeast with some unique characteristics, including fast growth, thermostability, and broad substrate spectrum. Other than common applications for protein production, O. polymorpha is attracting interest for chemical and protein production from methanol; a promising feedstock for the next-generation biomanufacturing due to its abundant sources and excellent characteristics. Benefiting from the development of synthetic biology, it has been engineered to produce value-added chemicals by extensively rewiring cellular metabolism. This Review discusses recently developed synthetic biology tools of O. polymorpha. The advances of chemicals production and systems biology were reviewed comprehensively. Finally, we look ahead to the developments of biomanufacturing in O. polymorpha to make an overall understanding of this chassis for academia and industry.

PMID:38622041 | DOI:10.1016/j.tibtech.2024.03.007

Annu Rev Genomics Hum Genet. 2024 Apr 15. doi: 10.1146/annurev-genom-120622-020615. Online ahead of print.

ABSTRACT

The last five years have seen impressive progress in deep learning models applied to protein research. Most notably, sequence-based structure predictions have seen transformative gains in the form of AlphaFold2 and related approaches. Millions of missense protein variants in the human population lack annotations, and these computational methods are a valuable means to prioritize variants for further analysis. Here, we review the recent progress in deep learning models applied to the prediction of protein structure and protein variants, with particular emphasis on their implications for human genetics and health. Improved prediction of protein structures facilitates annotations of the impact of variants on protein stability, protein-protein interaction interfaces, and small-molecule binding pockets. Moreover, it contributes to the study of host-pathogen interactions and the characterization of protein function. As genome sequencing in large cohorts becomes increasingly prevalent, we believe that better integration of state-of-the-art protein informatics technologies into human genetics research is of paramount importance.

PMID:38621234 | DOI:10.1146/annurev-genom-120622-020615

Genomics Proteomics Bioinformatics. 2005;3(3):194-196. doi: 10.1016/S1672-0229(05)03025-1. Epub 2016 Nov 28.

NO ABSTRACT

PMID:38620188 | PMC:PMC5172556 | DOI:10.1016/S1672-0229(05)03025-1

Acta Microbiol Immunol Hung. 2024 Apr 15. doi: 10.1556/030.2024.02265. Online ahead of print.

ABSTRACT

Prosthetic joint infection (PJI) and aseptic loosening (AL) are common complications of total joint arthroplasty. An accumulation of evidence indicates the presence of microbial communities on prosthetic implants, but the overall microbial profile is unclear. In this study, we aimed to investigate the differences in the microbial composition of prosthetic implants obtained from PJI and AL patients using the 16S rRNA sequencing method. Patients who underwent revision hip, knee, or shoulder arthroplasty caused by PJI (n = 20) or AL (n = 10) were enrolled in the study. 16S rRNA sequencing targeting the V3-V4 region was performed on the microbial specimens collected from synovial fluid, periprosthetic deep-tissue, and biofilm during the revision surgery. The sequenced raw data were analysed for microbial composition and ecological and differential abundance analyses using bioinformatics tools. The AL group had relatively balanced and higher diversity, with Staphylococcus, Streptococcus, and Veillonella being prominent. In the PJI group, Staphylococcus and Pseudomonas were predominant, especially in deep-tissue samples and biofilm samples, respectively. The differential abundance analysis identified 15 and 2 distinctive taxa in the AL and PJI groups, respectively. Our findings provided preliminary insights supporting the existence of periprosthetic microbiota in orthopedic implants and explaining the differences in microbial composition between the AL and PJI groups.

PMID:38619882 | DOI:10.1556/030.2024.02265

Mol Neurobiol. 2024 Apr 15. doi: 10.1007/s12035-024-04139-y. Online ahead of print.

ABSTRACT

Glioblastoma (GBM) is the highest grade of glioma for which no effective therapy is currently available. Despite extensive research in diagnosis and therapy, there has been no significant improvement in GBM outcomes, with a median overall survival continuing at a dismal 15-18 months. In recent times, glioblastoma stem cells (GSCs) have been identified as crucial drivers of treatment resistance and tumor recurrence, and GBM therapies targeting GSCs are expected to improve patient outcomes. We used a multistep in silico screening strategy to identify repurposed candidate drugs against selected therapeutic molecular targets in GBM with potential to concomitantly target GSCs. Common differentially expressed genes (DEGs) were identified through analysis of multiple GBM and GSC datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). For identification of target genes, we selected the genes with most significant effect on overall patient survival. The relative mRNA and protein expression of the selected genes in TCGA control versus GBM samples was also validated and their cancer dependency scores were assessed. Drugs targeting these genes and their corresponding proteins were identified from LINCS database using Connectivity Map (CMap) portal and by in silico molecular docking against each individual target using FDA-approved drug library from the DrugBank database, respectively. The molecules thus obtained were further evaluated for their ability to cross blood brain barrier (BBB) and their likelihood of resulting in drug resistance by acting as p-glycoprotein (p-Gp) substrates. The growth inhibitory effect of these final shortlisted compounds was examined on a panel of GBM cell lines and compared with temozolomide through the drug sensitivity EC50 values and AUC from the PRISM Repurposing Secondary Screen, and the IC50 values were obtained from GDSC portal. We identified RPA3, PSMA2, PSMC2, BLVRA, and HUS1 as molecular targets in GBM including GSCs with significant impact on patient survival. Our results show GSK-2126458/omipalisib, linifanib, drospirenone, eltrombopag, nilotinib, and PD198306 as candidate drugs which can be further evaluated for their anti-tumor potential against GBM. Through this work, we identified repurposed candidate therapeutics against GBM utilizing a GSC inclusive targeting approach, which demonstrated high in vitro efficacy and can prospectively evade drug resistance. These drugs have the potential to be developed as individual or combination therapy to improve GBM outcomes.

PMID:38619743 | DOI:10.1007/s12035-024-04139-y

Clin Cancer Res. 2024 Apr 15:OF1-OF13. doi: 10.1158/1078-0432.CCR-23-1674. Online ahead of print.

ABSTRACT

PURPOSE: The inherent genetic heterogeneity of acute myeloid leukemia (AML) has challenged the development of precise and effective therapies. The objective of this study was to elucidate the genomic basis of drug resistance or sensitivity, identify signatures for drug response prediction, and provide resources to the research community.

EXPERIMENTAL DESIGN: We performed targeted sequencing, high-throughput drug screening, and single-cell genomic profiling on leukemia cell samples derived from patients with AML. Statistical approaches and machine learning models were applied to identify signatures for drug response prediction. We also integrated large public datasets to understand the co-occurring mutation patterns and further investigated the mutation profiles in the single cells. The features revealed in the co-occurring or mutual exclusivity pattern were further subjected to machine learning models.

RESULTS: We detected genetic signatures associated with sensitivity or resistance to specific agents, and identified five co-occurring mutation groups. The application of single-cell genomic sequencing unveiled the co-occurrence of variants at the individual cell level, highlighting the presence of distinct subclones within patients with AML. Using the mutation pattern for drug response prediction demonstrates high accuracy in predicting sensitivity to some drug classes, such as MEK inhibitors for RAS-mutated leukemia.

CONCLUSIONS: Our study highlights the importance of considering the gene mutation patterns for the prediction of drug response in AML. It provides a framework for categorizing patients with AML by mutations that enable drug sensitivity prediction.

PMID:38619278 | DOI:10.1158/1078-0432.CCR-23-1674

J Vis Exp. 2024 Mar 29;(205). doi: 10.3791/66225.

ABSTRACT

Over the past decade, single-cell transcriptomics has significantly evolved and become a standard laboratory method for simultaneous analysis of gene expression profiles of individual cells, allowing the capture of cellular diversity. In order to overcome limitations posed by difficult-to-isolate cell types, an alternative approach aiming at recovering single nuclei instead of intact cells can be utilized for sequencing, making transcriptome profiling of individual cells universally applicable. These techniques have become a cornerstone in the study of brain organoids, establishing them as models of the developing human brain. Leveraging the potential of single-cell and single-nucleus transcriptomics in brain organoid research, this protocol presents a step-by-step guide encompassing key procedures such as organoid dissociation, single-cell or nuclei isolation, library preparation and sequencing. By implementing these alternative approaches, researchers can obtain high-quality datasets, enabling the identification of neuronal and non-neuronal cell types, gene expression profiles, and cell lineage trajectories. This facilitates comprehensive investigations into cellular processes and molecular mechanisms shaping brain development.

PMID:38619271 | DOI:10.3791/66225

Crit Rev Food Sci Nutr. 2024 Apr 15:1-26. doi: 10.1080/10408398.2024.2341266. Online ahead of print.

ABSTRACT

Inflammatory cascades of the dysregulated inflammatory pathways in COVID-19 can cause excessive production of pro-inflammatory cytokines and chemokines leading to cytokine storm syndrome (CSS). The molecular cascades involved in the pathways may be targeted for discovery of new anti-inflammatory agents. Many plant extracts have been used clinically in the management of COVID-19, however, their immunosuppressive activities were mainly investigated based on in silico activity. Dietary flavonoids of the extracts such as quercetin, luteolin, kaempferol, naringenin, isorhamnetin, baicalein, wogonin, and rutin were commonly identified as responsible for their inhibitory effects. The present review critically analyzes the anti-inflammatory effects and mechanisms of phytochemicals, including dietary compounds against cytokine storm (CS) and hyperinflammation via inhibition of the altered inflammatory pathways triggered by SARS-CoV-2, published since the emergence of COVID-19 in December 2019. Only a few phytochemicals, mainly dietary compounds such as nanocurcumin, melatonin, quercetin, 6-shagoal, kaempferol, resveratrol, andrographolide, and colchicine have been investigated either in in silico or preliminary clinical studies to evaluate their anti-inflammatory effects against COVID-19. Sufficient pre-clinical studies on safety and efficacy of anti-inflammatory effects of the phytochemicals must be performed prior to proper clinical studies to develop them into therapeutic adjuvants in the prevention and treatmemt of COVID-19 symptoms.

PMID:38619217 | DOI:10.1080/10408398.2024.2341266

Physiol Plant. 2024 Jan-Feb;176(1):e14182. doi: 10.1111/ppl.14182.

ABSTRACT

The molecular mechanisms guiding oriented cell divisions in the root vascular tissues of Arabidopsis thaliana are still poorly characterised. By overlapping bulk and single-cell transcriptomic datasets, we unveiled TETRASPANIN1 (TET1) as a putative regulator in this process. TET1 is expressed in root vascular cells, and loss-of-function mutants contain fewer vascular cell files. We further generated and characterised a CRISPR deletion mutant and showed, unlike previously described mutants, that the full knock out is additionally missing endodermal cells in a stochastic way. Finally, we show that HA-tagged versions of TET1 are functional in contrast to fluorescent TET1 translational fusions. Immunostaining using HA-TET1 lines complementing the mutant phenotype suggested a dual plasma membrane and intracellular localisation in the root vasculature and a polar membrane localisation in the young cortex, endodermal and initial cells. Taken together, we show that TET1 is involved in both vascular proliferation and ground tissue patterning. Our initial results pave the way for future work to decipher its precise mode of action.

PMID:38618986 | DOI:10.1111/ppl.14182

BMJ Nutr Prev Health. 2023 Oct 19;6(2):119-121. doi: 10.1136/bmjnph-2023-000787. eCollection 2023.

NO ABSTRACT

PMID:38618539 | PMC:PMC11009514 | DOI:10.1136/bmjnph-2023-000787