Biology subjects

Bao, J.

Publications and source records attributed to Bao, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. MethodsParticipants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. ResultsA total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1. ConclusionThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICIs efficacy. Context summaryO_ST_ABSKey objectiveC_ST_ABSNot all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC. Knowledge generatedModels submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response. Relevance

cancer biology↗

bioRxiv2022

A gene essentiality signature for studying the mechanism of action of drugs

Cancer drugs often kill cells independent of their putative targets, suggesting the limitation of existing knowledge on the mechanisms of action. In this study, we explored whether the integration of loss-of-function genetic and drug sensitivity screening data can define a gene essentiality signature to better understand the drug target interactions. We showed that our gene essentiality signature can predict drug targets more accurately than chemical fingerprints and drug-perturbated gene expression signatures. We further showed how gene essentiality signature can help identify mechanisms of action of drugs de novo, including the EGFR inhibitor lapatinib, and drugs associated with DNA mismatch repair. Finally, we established gene essentiality signatures for noncancer drugs and used them to predict their anticancer targets. We have successfully validated the target predictions for multiple noncancer drugs, using cell-based drug target deconvolution by the proteome integral solubility alteration assay. Our study provides a novel signature of drugs that may facilitate the rational design of drug repurposing.

systems biology↗

bioRxiv2022

Integrated Network Pharmacology and Experimental Analysis Unveil Modulation of EGFR/MAPK Signaling Cascades in Acute Cerebral Ischemia-Reperfusion Injury by Qing-Tong-Hua-Yu Decoction

ObjectiveBased on network pharmacology, the response of Qing-tong-hua-yu Decoction (QTHY) to the regulation of EGFR/MAPK signaling cascade in cerebral ischemia-reperfusion injury was discussed and the possible mechanism of the protective effect of QTHY on the cerebral ischemia-reperfusion injury was studied. MethodsA compound-target disease-function-pathway network was established and analyzed based on the network pharmacology approach used in Chinese medicine. The correlation, which is between effect of the components of QTHY Decoction against CI/RI with EGFR/MAPK signalling cascade response, was observed. And then the degree of neurological deficits in each group was assessed after cerebral ischemia for 2 hours and reperfusion for 3 hours, 24 hours, 3 days and 7 days. Expression levels of EGFR and p44/42MAPK in ischemic brain tissue at different time points in various groups of rats were tested by Western bolt (WB), real-time quantitative PCR (RT-qPCR) and immunohistochemistry (IHC). ResultsNetwork pharmacology analysis revealed that QTHY-mediated treatment involved 439 key targets, in which the effect of QTHY groups against CI/RI was associated with EGFR/MAPK signaling cascade. QTHY treatment reduced neurological deficit scores and improved ischemic changes in rats. In addition, QTHY promoted EGFR and p44/42MAPK expression in the SVZ through the EGFR/MAPK signaling cascade, with varying degrees of improvement at different time points. ConclusionQTHY can better improve cerebral ischemia injury in CI / RI rats and exert the neuroprotective effect of cerebral ischemia-reperfusion injury. This may be related to the potential of QTHY to activate the EGFR / MAPK signaling cascade, which is consistent with the results of network pharmacology analysis.

neuroscience↗

bioRxiv2022

Osteosarcoma-enriched transcripts paradoxically generate osteosarcoma-suppressing extracellular proteins

Osteosarcoma (OS) is the common primary bone cancer that affects mostly children and young adults. To augment the standard-of-care chemotherapy, we examined the possibility of protein-based therapy using mesenchymal stem cells (MSCs)-derived proteomes and osteosarcoma-elevated proteins. While a conditioned medium (CM), collected from MSCs, did not present tumor-suppressing ability, the activation of PKA converted MSCs into induced tumor-suppressing cells (iTSCs). In a mouse model, the direct and hydrogel-assisted administration of CM inhibited tumor-induced bone destruction, and its effect was additive with Cisplatin. CM was enriched with proteins such as Calreticulin, which acted as an extracellular tumor suppressor by interacting with CD47. Notably, the level of Calr transcripts was elevated in OS tissues, together with other tumor-suppressing proteins, including histone H4, and PCOLCE. PCOLCE acted as an extracellular tumor-suppressing protein by interacting with amyloid precursor protein (APP), a prognostic OS marker with poor survival. The results supported the possibility of employing a paradoxical strategy of utilizing OS transcriptomes for the treatment of OS.

cancer biology↗

bioRxiv2022

Genetic, clinical underpinnings of subtle early brain change along Alzheimer's dimensions

Alzheimers disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised clustering technique known as Surreal-GAN, through which we identified two dominant dimensions of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the "diffuse-AD" (R1) dimension shows widespread brain atrophy, and the "MTL-AD" (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE {varepsilon}4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were "druggable genes" for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE {varepsilon}4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction - driven by genes different from APOE - which may collectively contribute to the early pathogenesis of AD.

bioengineering↗

bioRxiv2022

Development of an adenosquamous carcinoma histopathology-selective lung cancer graft model

Preclinical tumor models with native tissue microenvironments provide essential tools to understand how heterogeneous tumor phenotypes relate to drug response. Here, we present syngeneic graft models of aggressive, metastasis-prone histopathology-specific NSCLC tumor types driven by KRAS mutation and loss of LKB1 (KL): adenosquamous carcinoma (ASC) and adenocarcinoma (AC). We show that subcutaneous injection of primary KL-ASC cells results in squamous cell carcinoma (SCC) tumors with high levels of stromal infiltrates, lacking the source heterogeneous histotype. Despite forming subcutaneous tumors, intravenously injected KL-AC cells were unable to form lung tumors. In contrast, intravenous injection of KL-ASC cells leads to their lung re-colonization and lesions recapitulating the mixed AC and SCC histopathology, tumor immune suppressive microenvironment and oncogenic signaling profile of source tumors, demonstrating histopathology-selective phenotypic dominance over genetic drivers. Pan-ERBB inhibition increased survival, while selective ERBB1/EGFR inhibition did not, suggesting a role of ERBB network crosstalk in resistance to ERBB1/EGFR. This immunocompetent NSCLC lung colonization model hence phenocopies key properties of the metastasis-prone ASC histopathology, and serves as a preclinical model to dissect therapy responses and metastasis-associated processes.

cancer biology↗

bioRxiv2022

Tracing back primed resistance in cancer via sister cells

Exploring non-genetic evolution of cell states during cancer treatments has become attainable by recent advances in lineage-tracing methods. However, transcriptional changes that drive cells into resistant fates may be subtle, necessitating high resolution analysis. We developed ReSisTrace that uses shared transcriptomic features of synchronised sister cells to predict the states that prime treatment resistance. We applied ReSisTrace in ovarian cancer cells perturbed with olaparib, carboplatin or natural killer (NK) cells. The pre-resistant phenotypes were defined by cell cycle and proteostatic features, reflecting the traits enriched in the upcoming subclonal selection. Furthermore, DNA repair deficiency rendered cells susceptible to both DNA damaging agents and NK killing in a context-dependent manner. Finally, we leveraged the pre-resistance profiles to predict and validate small molecules driving cells to sensitive states prior to treatment. In summary, ReSisTrace resolves pre-existing transcriptional features of treatment vulnerability, facilitating both molecular patient stratification and discovery of synergistic pre-sensitizing therapies.

cancer biology↗

bioRxiv2021

Efficient CRISPR/Cas12a-based genome editing toolbox for metabolic engineering in Methanococcus maripaludis

The rapid-growing and genetically tractable methanogen Methanococcus maripaludis is a promising host organism for the biotechnological conversion of carbon dioxide and renewable hydrogen to fuels and value-added products. Expansion of its product scope through metabolic engineering necessitates reliable and efficient genetic tools, particularly for genome edits to the primary metabolism that affect cell growth. Here, we have designed a genome editing toolbox by utilizing Cas12a from Lachnospiraceae bacterium ND2006 (LbCas12a) in combination with the homology-directed repair machinery endogenously present in M. maripaludis. Remarkably, this toolbox can knock out target genes with a success rate of up to 95%, despite the hyper-polyploidy of M. maripaludis. For the purposes of demonstrating a large-sized deletion, we have replaced the flagellum operon (ca. 8.9 kbp) by the {beta}-glucuronidase gene. To facilitate metabolic engineering and flux balancing in M. maripaludis, the relative strength of 15 different promoters were quantified in the presence of the two common growth substrates, formate or carbon dioxide and hydrogen. This CRISPR/LbCas12a toolbox can be regarded as a reliable and fast method for genome editing in a methanogen.

bioengineering↗

bioRxiv2021

Discovery of nanobodies against SARS-CoV-2 and an uncommon neutralizing mechanism

SARS-CoV-2 and its variants continue to threaten public health. The virus recognizes the host cell by attaching its Spike receptor-binding domain (RBD) to the host receptor ACE2. Therefore, RBD is a primary target for neutralizing antibodies and vaccines. Here we report the isolation, and biological and structural characterization of two single-chain antibodies (nanobodies, DL4 and DL28) from RBD-immunized alpaca. Both nanobodies bind Spike with affinities that exceeded the detection limit (picomolar) of the biolayer interferometry assay and neutralize the original SARS-CoV- 2 strain with IC50 of 0.086 g mL-1 (DL4) and 0.385 g mL-1 (DL28). DL4 and a more potent, rationally designed mutant, neutralizes the Alpha variant as potently as the original strain but only displays marginal activity against the Beta variant. By contrast, the neutralizing activity of DL28, when in the Fc-fused divalent form, was less affected by the mutations in the Beta variant (IC50 of 0.414 g mL-1 for Alpha, 1.060 g mL-1 for Beta). Crystal structure studies reveal that DL4 blocks ACE2-binding by direct competition, while DL28 neutralizes SARS-CoV-2 by an uncommon mechanism through which DL28 distorts the receptor-binding motif in RBD and hence prevents ACE2-binding. Our work provides two neutralizing nanobodies for potential therapeutic development and reveals an uncommon mechanism to design and screen novel neutralizing antibodies against SARS-CoV-2.

biochemistry↗

bioRxiv2021

Comprehensive Analysis of Spatial Architecture in Primary Liver Cancer

Heterogeneity is the major challenge for cancer prevention and therapy. Here, we firstly constructed high-resolution spatial transcriptomes of primary liver cancers (PLCs) containing 84,823 spots within 21 tissues from 7 patients. The sequential comparison of spatial tumor microenvironment (TME) characteristics from non-tumor to leading-edge to tumor regions revealed that the tumor capsule potentially affects intratumor spatial cluster continuity, transcriptome diversity and immune cell infiltration. Locally, we found that the bidirectional ligand-receptor interactions at the 100 m wide cluster-cluster boundary contribute to maintaining intratumor architecture. Our study provides novel insights for diverse tumor ecosystem of PLCs and has potential benefits for cancer intervention.

cancer biology↗

bioRxiv2021

DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal

Combinatorial therapies that target multiple pathways have shown great promises for treating complex diseases. DrugComb (https://drugcomb.org/) is a web-based portal for the deposition and analysis of drug combination screening datasets. Since its first release, DrugComb has received continuous updates on the coverage of data resources, as well as on the functionality of the web server to improve the analysis, visualization and interpretation of drug combination screens. Here we report significant updates of DrugComb, including: 1) manual curation and harmonization of more comprehensive drug combination and monotherapy screening data, not only for cancers but also for other diseases such as malaria and COVID-19; 2) enhanced algorithms for assessing the sensitivity and synergy of drug combinations; 3) network modelling tools to visualize the mechanisms of action of drugs or drug combinations for a given cancer sample; and 4) state-of-the-art machine learning models to predict drug combination sensitivity and synergy. These improvements have been provided with more user-friendly graphical interface and faster database infrastructure, which make DrugComb the most comprehensive web-based resources for the study of drug sensitivities for multiple diseases.

pharmacology and toxicology↗

bioRxiv2021

Facilitating the design of combination therapy in cancer using multipartite network models: Emphasis on acute myeloid leukemia

From the drug discovery perspective, combination therapy is recommended in cancer due to efficiency and safety compared to the common cytotoxic and single-targeted monotherapies. However, identifying effective drug combinations is time- and cost-consuming. Here, we offer a novel strategy of predicting potential drug combinations and patient subclasses by constructing multipartite networks using drug response data on patient samples. In the present study, we used Beat AML and GDSC, two comprehensive datasets based on patient-derived and cell line-based samples, to show the potential of multipartite network modeling in cancer combinatorial therapy. We used the median values of cell viability to compare drug potency and reconstruct a weighted bipartite network, which models the interaction of drugs and biological samples. Then, clusters of network communities were identified in two projected networks based on the topological structure of networks. Chemical structures, drug-target networks, protein-protein interactions, and signaling networks were used to corroborate the intra-cluster homogeneity. We further leveraged the community structures within the drug-based multipartite networks to discover effective multi-targeted drug combinations, and the synergy levels which were supported with more evidence using the DrugComb and the ALMANAC databases. Furthermore, we confirmed the potency of selective combinations of drugs against monotherapy in vitro experiment using three acute myeloid leukemia (AML) cell lines. Taken together, this study presents an innovative data-driven strategy based on multipartite networks to suggest potential drug combinations to improve treatment of AML.

systems biology↗

bioRxiv2020

The role of SOX9 in non-small cell lung cancer progression is histopathology-selective.

The transcription factor SOX9 is a key regulator of multiple developmental processes, and is frequently re-expressed in non-small cell lung cancer (NSCLC). Its precise role in the progression of NSCLC histopathologies has however remained elusive. We show that SOX9 expression relates to poor outcome and invasive histopathology in human adenocarcinomas, and is absent in murine early minimally invasive and human in situ adenocarcinoma. Interestingly, despite wide SOX9 expression across advanced NSCLC histotypes, its genetic deletion in the murine KrasG12D;Lkb1-/- model selectively disrupted only the growth of papillary NSCLC, without affecting the initiation of precursor lesions or growth of mucinous or squamous tissue. Spatial tissue phenotyping indicated a requirement of SOX9 expression for the progression of surfactant protein C-expressing progenitor cells, which gave rise to papillary tumours. Intriguingly, while SOX9 expression was dispensable for squamous tissue formation, its loss in fact led to enhanced squamous tumour metastasis, which was associated with altered collagen IV deposition in the basement membrane. Our work therefore demonstrates histopathology-selective roles for SOX9 in NSCLC progression, namely a requirement for papillary adenocarcinoma progression, but opposing metastasis-suppressing function in squamous histotype tissue. This attests to a pleiotropic SOX9 function, linked to the cell of origin and microenvironmental tissue contexts.

cancer biology↗

bioRxiv2020

Functional diagnostics using fresh uncultured lung tumor cells to guide personalized treatments

Functional profiling of a cancer patients tumor cells holds potential to tailor personalized cancer treatment. Here we report the utility of Fresh Uncultured Tumor-derived EpCAM+ epithelial Cells (FUTC) for ex vivo drug response interrogation. Analysis of murine Kras mutant FUTCs demonstrated pharmacological and adaptive signaling profiles comparable to subtype-matched cultured cells. Applying FUTC profiling on non-small cell lung cancer patient samples, we generated robust drug response data in 18 of 19 cases, where the cells exhibited targeted drug sensitivities corresponding to their oncogenic drivers. In one of these cases, an EGFR mutant lung adenocarcinoma patient refractory to osimertinib, FUTC profiling was used to guide compassionate treatment. FUTC profiling identified selective sensitivity to disulfiram and the combination of carboplatin plus etoposide and the patient received substantial clinical benefit from the treatment with these agents. We conclude that FUTC profiling provides a robust, rapid, and actionable assessment of personalized cancer treatment options.

cancer biology↗

bioRxiv2020

FertilityOnline, a straight pipeline for functional gene annotation and disease mutation discovery, identifies novel infertility causative mutations in SYCE1 and STAG3

Exploring the genetic basis of human infertility is currently under intensive investigation. However, only a handful of genes are validated in animal models as disease-causing genes in infertile men. Thus, to better understand the genetic basis of spermatogenesis in human and to bridge the knowledge gap between human and other animal species, we have constructed FertilityOnline database, which is a resource that integrates the functional genes reported in literature related to spermatogenesis into an existing spermatogenic database, SpermatogenesisOnline 1.0. Additional features like functional annotation and statistical analysis of genetic variants of human genes, are also incorporated into FertilityOnline. By searching this database, users can focus on the top candidate genes associated with infertility and can perform enrichment analysis to instantly refine the number of candidates in a user-friendly web interface. Clinical validation of this database is established by the identification of novel causative mutations in SYCE1 and STAG3 in azoospermia men. In conclusion, FertilityOnline is not only an integrated resource for analysis of spermatogenic genes, but also a useful tool that facilitates to study underlying genetic basis of male infertility. AvailabilityFertilityOnline can be freely accessed at http://mcg.ustc.edu.cn/bsc/spermgenes2.0/index.html.

genetics↗

bioRxiv2020

Generation of nonhuman primate retinitis pigmentosa model by in situ knockout of RHO in rhesus macaque retina

Retinitis pigmentosa (RP) is a form of inherited retinal degenerative disease that ultimately involves the macula, which is present in primates but not in the rodents. Therefore, creating nonhuman primate (NHP) models of RP is of critical importance to study its mechanism of pathogenesis and to evaluate potential therapeutic options in the future. Here we applied adeno-associated virus (AAV)-delivered CRISPR/SaCas9 technology to knockout the RHO gene in the retinae of the adult rhesus macaque (Macaca mulatta) to investigate the hypothesis whether non-germline mutation of the RHO gene is sufficient to recapitulate RP. Through a series of studies, we were able to demonstrate successful somatic editing of the RHO gene and reduced RHO protein expression. More importantly, the mutant macaque retinae displayed clinical RP phenotypes, including photoreceptor degeneration, retinal thinning, abnormal rod subcellular structures, and reduced photoresponse. Therefore, we suggest somatic editing of the RHO gene is able to phenocopy RP, and the reduced time span in generating NHP mutant accelerates RP research and expands the utility of NHP model for human disease study.

neuroscience↗

bioRxiv2020

Potent synthetic nanobodies against SARS-CoV-2 and molecular basis for neutralization

SARS-CoV-2, the causative agent of COVID-191, recognizes host cells by attaching its receptor-binding domain (RBD) to the host receptor ACE22-7. Neutralizing antibodies that block RBD-ACE2 interaction have been a major focus for therapeutic development8-18. Llama-derived single-domain antibodies (nanobodies, [~]15 kDa) offer advantages including ease of production and possibility for direct delivery to the lungs by nebulization19, which are attractive features for bio-drugs against the global respiratory disease. Here, we generated 99 synthetic nanobodies (sybodies) by in vitro selection using three libraries. The best sybody, MR3 bound to RBD with high affinity (KD = 1.0 nM) and showed high neutralization activity against SARS-CoV-2 pseudoviruses (IC50 = 0.40 g mL-1). Structural, biochemical, and biological characterization of sybodies suggest a common neutralizing mechanism, in which the RBD-ACE2 interaction is competitively inhibited by sybodies. Various forms of sybodies with improved potency were generated by structure-based design, biparatopic construction, and divalent engineering. Among these, a divalent MR3 conjugated with the albumin-binding domain for prolonged half-life displayed highest potency (IC50 = 12 ng mL-1) and protected mice from live SARS-CoV-2 challenge. Our results pave the way to the development of therapeutic nanobodies against COVID-19 and present a strategy for rapid responses for future outbreaks.

biochemistry↗

bioRxiv2020

Mico-Community associated with ectomycorrhizal Russula symbiosis and sporocarp-producing Russula in Fagaceae dominant nature areas in southern China

Russula griseocarnosa, an ectomycorrhizal (ECM) fungus, is a species of precious wild edible mushrooms with very high market value in southern China. Its yield is affected by many factors including the tree species and environmental conditions such as soil microbiome, humidity. How the microbiome promotes the ECM fungus symbiosis with Fagaceae plants and sporocarp-producing has never been studied. In this study, we collected rhizosphere samples from Fujian province, the microbiota in the root and mycorrhizal rhizosphere were identified by Illumina MiSeq high-throughput sequencing. First, we compared three types of fungal communities: root tips infected with ECM Russula (type 1), tips with Russula sporocarp (type 2) and tips without ECM (type 3). Our results showed that the fungal richness was negatively correlated with Russula. Russula, Tomentella and Lactarius were common in Fagaceae ECM roots. As to the mycorrhizal interactions, Boletus may be considered as an indicator species for sporocarp-producing Russula, and Acremonium, Cladophialophora were associated with Russula symbiosis. Second, we analyzed the fungal and bacterial communities in rhizosphere soils from the corresponding to previously three types (type 1, 2, 3). Dacryobolus and Acidocella may be considered as an indicator species for sporocarp-producing Russula. Fungi Tomentella, Saitozyma, Elaphomyces and bacteria Acidicaldus, Bryobacter, Sorangium and Acidobacterium occurred more frequently in the ECM Russula rhizosphere. Furthermore, the indicators Elaphomyces, Tomentella, Sorangium had a positive correlation with Russula symbiosis by network analyses. Overall, our results suggest a relationship between micro-community and ECM Russula formation and Russula sporocarp, which may provide new strategies for improving Russula symbiosis rate and sporocarp production.

ecology↗