Methionine biosynthetic genes and methionine sulfoxide reductase A are required for Rhizoctonia solani AG1-IA to cause sheath blight disease in rice.

Rhizoctonia solani is a polyphagous necrotrophic fungal pathogen that causes sheath blight disease in rice. It deploys effector molecules as well as carbohydrate-active enzymes and enhances the production of reactive oxygen species for killing host tissues. Understanding R. solani ability to sustain growth under an oxidative-stress-enriched environment is important for developing disease control strategies. Here, we demonstrate that R. solani upregulates methionine biosynthetic genes, including Rs_MET13 during infection in rice, and double-stranded RNA-mediated silencing of these genes impairs the pathogen's ability to cause disease. Exogenous treatment with methionine restores the disease-causing ability of Rs_MET13-silenced R. solani and facilitates its growth on 10 mM H2O2-containing minimal-media. Notably, the Rs_MsrA gene that encodes methionine sulfoxide reductase A, an antioxidant enzyme involved in the repair of oxidative damage of methionine, is upregulated upon H2O2 treatment and also during infection in rice. Rs_MsrA-silenced R. solani is unable to cause disease, suggesting that it is important for the repair of oxidative damage in methionine during host colonization. We propose that spray-induced gene silencing of Rs_MsrA and designing of antagonistic molecules that block MsrA activity can be exploited as a drug target for effective control of sheath blight disease in rice.

Anaphylactic Shock After Intramuscular Diclofenac Sodium: A Case Report.

Diclofenac sodium is a commonly used nonsteroidal anti-inflammatory drug. It is widely used for acute and chronic pain management. Side effects, such as fixed drug eruption, asthmatic attack, and vasospastic angina, are commonly seen after the use of diclofenac sodium. However, anaphylaxis and anaphylactic shock secondary to injection of diclofenac sodium are rare. Our main aim in reporting this adverse event is to alert healthcare professionals to this potentially life-threatening adverse effect of diclofenac sodium and prompt use of adrenaline for treatment.

Acute Pyelonephritis by Scrub Typhus: A Rare Condition.

Scrub typhus is prevalent in tropical countries and can have a varied spectrum of presentations from pneumonia, gastroenteritis, lymphadenitis, meningitis, encephalitis, and acute kidney injury to multi-organ dysfunction syndrome. Urinary tract infections like cystitis and pyelonephritis are rarely reported. Here we present an atypical presentation of a 53-year-old female with diabetes mellitus who came to the outpatient department with complaints of high-grade fever, burning micturition, and left flank pain for three days and was initially treated outpatient basis with oral antibiotics. However, her deteriorating condition landed her in an emergency in a state of septic shock. She was initially treated with broad-spectrum conventional antibiotics with other supportive medications. Even after confirmation of the diagnosis of left acute pyelonephritis with septic shock, with appropriate antibiotics, her condition was deteriorating. A sterile urine culture raised suspicion of atypical organisms causing the infection. Proper analysis of her history and readily available investigations of IgM against scrub typhus antigen led to a diagnosis of scrub typhus-related left acute pyelonephritis with septic shock. She was treated adequately with an injection of doxycycline, followed by oral tablets of the same, after which she showed drastic improvement in her symptoms, and then she was discharged. Thus, atypical organisms causing urinary tract infections should be kept always in mind, which can be treated easily and if untreated, can lead to life-threatening consequences.

Macrophage Polarizations in the Placenta and Lung are Associated with Bronchopulmonary Dysplasia.

The intricate interplay between macrophage polarization and placenta vascular dysfunction has garnered increasing attention in the context of placental inflammatory diseases. This study delves into the complex relationship between macrophage polarization within the placenta and its potential impact on the development of vascular dysfunction and inflammatory conditions. The placenta, a crucial organ in fetal development, relies on a finely tuned balance of immune responses for proper functioning. Disruptions in this delicate equilibrium can lead to pathological conditions, including inflammatory diseases affecting the fetus and newborn infant. We explored the interconnectedness between placental macrophage polarization and its relevance to lung macrophages, particularly in the context of early life lung development. Bronchopulmonary dysplasia (BPD), the most common chronic lung disease of prematurity, has been associated with abnormal immune responses, and understanding the role of macrophages in this context is pivotal. The investigation aims to shed light on how alterations in placental macrophage polarization may contribute to lung macrophage behavior and, consequently, influence the development of BPD. By unraveling the intricate mechanisms linking macrophage polarization, placental dysfunction and BPD, this research seeks to provide insights that could pave the way for targeted therapeutic interventions. The findings may offer novel perspectives on preventing and managing placental and lung-related pathologies, ultimately contributing to improved maternal and neonatal health outcomes.

C1QA is an invariant biomarker for tissue macrophages.

Macrophages play a pivotal role in immune responses, particularly in the context of combating microbial threats within tissues. The identification of reliable biomarkers associated with macrophage function is essential for understanding their diverse roles in host defense. This study investigates the potential of C1QA as an invariant biomarker for tissue macrophages, focusing on its correlation with the anti-microbial pathway. C1QA, a component of the complement system, has been previously implicated in various immune functions. Our research delves into the specific association of C1QA with tissue-resident macrophages and its implications in the context of anti-microbial responses. Through comprehensive systems biology and Boolean analysis of gene expression, we aim to establish C1QA as a consistent and reliable marker for identifying tissue macrophages. Furthermore, we explore the functional significance of C1QA in the anti-microbial pathway. This research seeks to provide valuable insights into the molecular mechanisms underlying the anti-microbial functions of tissue macrophages, with C1QA emerging as a potential key player in this intricate regulatory network. Understanding the relationship between C1QA, tissue macrophages, and the anti-microbial pathway could pave the way for the development of targeted therapeutic strategies aimed at enhancing the host's ability to combat infections. Ultimately, our findings contribute to the expanding knowledge of macrophage biology and may have implications for the diagnosis and treatment of infectious diseases.

Quantitative mRNA expression measurement at home.

mRNA measurement is dominated by RT-PCR, which requires expensive laboratory equipment and personnel with advanced degrees. Loop-mediated isothermal amplification (LAMP) is a versatile technique for detecting target DNA and RNA. The sensitivity of LAMP in early reports has been below that of the standard RT-PCR tests. Here, we report the use of a fluorescence-based RT-LAMP protocol to measure CDX2 expression patterns, which match extremely well to the standards of sophisticated RT-PCR techniques (r = 0.99, p < 0.001). The assay works on diverse sample types such as cDNA, mRNA, and direct tissue sample testing in 25 min compared to more than 3 h for RT-PCR. We have developed a new protocol for designing RT-LAMP primers that reduce false positives due to self-amplification and improve quantification. A simple device with a 3D-printed box enables the measurement of mRNA expression at home, outdoors, and point-of-care setting.

Machine-Learning Identifies a Strategy for Differentiation Therapy in Solid Tumors.

BACKGROUND: Although differentiation therapy can cure some hematologic malignancies, its curative potential remains unrealized in solid tumors. This is because conventional computational approaches succumb to the thunderous noise of inter-/intratumoral heterogeneity. Using colorectal cancers (CRCs) as an example, here we outline a machine learning(ML)-based approach to track, differentiate, and selectively target cancer stem cells (CSCs). METHODS: A transcriptomic network was built and validated using healthy colon and CRC tissues in diverse gene expression datasets (~5,000 human and >300 mouse samples). Therapeutic targets and perturbation strategies were prioritized using ML, with the goal of reinstating the expression of a transcriptional identifier of the differentiated colonocyte, CDX2, whose loss in poorly differentiated (CSC-enriched) CRCs doubles the risk of relapse/death. The top candidate target was then engaged with a clinical-grade drug and tested on 3 models: CRC lines in vitro, xenografts in mice, and in a prospective cohort of healthy (n = 3) and CRC (n = 23) patient-derived organoids (PDOs). RESULTS: The drug shifts the network predictably, induces CDX2 and crypt differentiation, and shows cytotoxicity in all 3 models, with a high degree of selectivity towards all CDX2-negative cell lines, xenotransplants, and PDOs. The potential for effective pairing of therapeutic efficacy (IC50) and biomarker (CDX2-low state) is confirmed in PDOs using multivariate analyses. A 50-gene signature of therapeutic response is derived and tested on 9 independent cohorts (~1700 CRCs), revealing the impact of CDX2-reinstatement therapy could translate into a ~50% reduction in the risk of mortality/recurrence. CONCLUSIONS: Findings not only validate the precision of the ML approach in targeting CSCs, and objectively assess its impact on clinical outcome, but also exemplify the use of ML in yielding clinical directive information for enhancing personalized medicine.

The DNA glycosylase NEIL2 is protective during SARS-CoV-2 infection.

SARS-CoV-2 infection-induced aggravation of host innate immune response not only causes tissue damage and multiorgan failure in COVID-19 patients but also induces host genome damage and activates DNA damage response pathways. To test whether the compromised DNA repair capacity of individuals modulates the severity of COVID-19 infection, we analyze DNA repair gene expression in publicly available patient datasets and observe a lower level of the DNA glycosylase NEIL2 in the lungs of severely infected COVID-19 patients. This observation of lower NEIL2 levels is further validated in infected patients, hamsters and ACE2 receptor-expressing human A549 (A549-ACE2) cells. Furthermore, delivery of recombinant NEIL2 in A549-ACE2 cells shows decreased expression of proinflammatory genes and viral E-gene, as well as lowers the yield of viral progeny compared to mock-treated cells. Mechanistically, NEIL2 cooperatively binds to the 5'-UTR of SARS-CoV-2 genomic RNA to block viral protein synthesis. Collectively, these data strongly suggest that the maintenance of basal NEIL2 levels is critical for the protective response of hosts to viral infection and disease.

Clinicopathologic Significance of Heat Shock Protein 60 as a Survival Predictor in Colorectal Cancer.

The role of heat shock protein 60 (HSP60), a mitochondrial chaperone, in tumor progression or its anti-tumor effects remains controversial. This study aimed to confirm the possibility of using HSP60 as a prognostic marker in patients with colorectal cancer (CRC), considering TNM classification for precise prediction. HSP60 expression increased with differentiation and p53 mutations in patients. However, compared to patients with high HSP60 expression, patients with low HSP60 expression had event-free survival and disease-specific survival hazard ratios (HRs) of 1.42 and 1.69, respectively. Moreover, when the survival rate was analyzed by combining TNM classification and HSP60 expression, the prognosis was poor, particularly when HSP60 expression was low in the late/advanced stage. This pattern was also observed with HSP family D member 1, HSPD1, the gene that encodes HSP60. Low HSPD1 expression was linked to lower overall survival and relapse-free survival rates, with HRs of 1.80 and 1.87, respectively. When TNM classification and HSPD1 expression were considered, CRC patients with low HSPD1 expression and advanced malignancy had a poorer prognosis than those with high HSPD1 expression. Thus, HSPD1/HSP60 can be a useful biomarker for a sophisticated survival prediction in late- and advanced-stage CRC, allowing the design of individualized treatment strategies.

An AI-assisted Investigation of Tumor-Associated Macrophages and their Polarization in Colorectal Cancer.

Tumor-associated Macrophages (or TAMs) are amongst the most common cells that play a significant role in the initiation and progression of colorectal cancer (CRC). Recently, Ghosh et al. proposed distinguishing signatures for identifying macrophage polarization states, namely, immuno-reactive and immuno-tolerant, using the concept of Boolean implications and Boolean networks. Their signature, called the Signature of Macrophage Reactivity and Tolerance (SMaRT), comprises of 338 human genes (equivalently, 298 mouse genes). However, SMaRT was constructed using datasets that were not specialized towards any particular disease. In this paper, (a) we perform a comprehensive analysis of the SMaRT signature on single-cell human and mouse colorectal cancer RNA-seq datasets; (b) we then adopt a technique akin to transfer learning to construct a "refined" SMaRT signature for investigating TAMs and their polarization in the CRC tumor microenvironment. Towards validation of our refined gene signature, we use (a) 5 pseudo-bulk RNA-seq datasets derived from single-cell human datasets; and (b) 5 large-cohort microarray datasets from humans. Furthermore, we investigate the translational potential of our refined gene signature in problems related to MSS/MSI (4 datasets) and CIMP+/CIMP- status (4 datasets). Overall, our refined gene signature and its extensive validation provide a path for its adoption in clinical practice in diagnosing colorectal cancer and associated attributes.

Rescue of Alzheimer's disease phenotype in a mouse model by transplantation of wild-type hematopoietic stem and progenitor cells.

Alzheimer's disease (AD) is the most prevalent cause of dementia; microglia have been implicated in AD pathogenesis, but their role is still matter of debate. Our study showed that single systemic wild-type (WT) hematopoietic stem and progenitor cell (HSPC) transplantation rescued the AD phenotype in 5xFAD mice and that transplantation may prevent microglia activation. Indeed, complete prevention of memory loss and neurocognitive impairment and decrease of ß-amyloid plaques in the hippocampus and cortex were observed in the WT HSPC-transplanted 5xFAD mice compared with untreated 5xFAD mice and with mice transplanted with 5xFAD HSPCs. Neuroinflammation was also significantly reduced. Transcriptomic analysis revealed a significant decrease in gene expression related to "disease-associated microglia" in the cortex and "neurodegeneration-associated endothelial cells" in the hippocampus of the WT HSPC-transplanted 5xFAD mice compared with diseased controls. This work shows that HSPC transplant has the potential to prevent AD-associated complications and represents a promising therapeutic avenue for this disease.

Machine learning identifies signatures of macrophage reactivity and tolerance that predict disease outcomes.

BACKGROUND: Single-cell transcriptomic studies have greatly improved organ-specific insights into macrophage polarization states are essential for the initiation and resolution of inflammation in all tissues; however, such insights are yet to translate into therapies that can predictably alter macrophage fate. METHOD: Using machine learning algorithms on human macrophages, here we reveal the continuum of polarization states that is shared across diverse contexts. A path, comprised of 338 genes accurately identified both physiologic and pathologic spectra of "reactivity" and "tolerance", and remained relevant across tissues, organs, species, and immune cells (>12,500 diverse datasets). FINDINGS: This 338-gene signature identified macrophage polarization states at single-cell resolution, in physiology and across diverse human diseases, and in murine pre-clinical disease models. The signature consistently outperformed conventional signatures in the degree of transcriptome-proteome overlap, and in detecting disease states; it also prognosticated outcomes across diverse acute and chronic diseases, e.g., sepsis, liver fibrosis, aging, and cancers. Crowd-sourced genetic and pharmacologic studies confirmed that model-rationalized interventions trigger predictable macrophage fates. INTERPRETATION: These findings provide a formal and universally relevant definition of macrophage states and a predictive framework (http://hegemon.ucsd.edu/SMaRT) for the scientific community to develop macrophage-targeted precision diagnostics and therapeutics. FUNDING: This work was supported by the National Institutes for Health (NIH) grant R01-AI155696 (to P.G, D.S and S.D). Other sources of support include: R01-GM138385 (to D.S), R01-AI141630 (to P.G), R01-DK107585 (to S.D), and UG3TR003355 (to D.S, S.D, and P.G). D.S was also supported by two Padres Pedal the Cause awards (Padres Pedal the Cause/RADY #PTC2017 and San Diego NCI Cancer Centers Council (C3) #PTC2017). S.S, G.D.K, and D.D were supported through The American Association of Immunologists (AAI) Intersect Fellowship Program for Computational Scientists and Immunologists. We also acknowledge support from the Padres Pedal the Cause #PTC2021 and the Torey Coast Foundation, La Jolla (P.G and D.S). D.S, P.G, and S.D were also supported by the Leona M. and Harry B. Helmsley Charitable Trust.

Purification and functional characterization of novel human skeletal stem cell lineages.

Human skeletal stem cells (hSSCs) hold tremendous therapeutic potential for developing new clinical strategies to effectively combat congenital and age-related musculoskeletal disorders. Unfortunately, refined methodologies for the proper isolation of bona fide hSSCs and the development of functional assays that accurately recapitulate their physiology within the skeleton have been lacking. Bone marrow-derived mesenchymal stromal cells (BMSCs), commonly used to describe the source of precursors for osteoblasts, chondrocytes, adipocytes and stroma, have held great promise as the basis of various approaches for cell therapy. However, the reproducibility and clinical efficacy of these attempts have been obscured by the heterogeneous nature of BMSCs due to their isolation by plastic adherence techniques. To address these limitations, our group has refined the purity of individual progenitor populations that are encompassed by BMSCs by identifying defined populations of bona fide hSSCs and their downstream progenitors that strictly give rise to skeletally restricted cell lineages. Here, we describe an advanced flow cytometric approach that utilizes an extensive panel of eight cell surface markers to define hSSCs; bone, cartilage and stromal progenitors; and more differentiated unipotent subtypes, including an osteogenic subset and three chondroprogenitors. We provide detailed instructions for the FACS-based isolation of hSSCs from various tissue sources, in vitro and in vivo skeletogenic functional assays, human xenograft mouse models and single-cell RNA sequencing analysis. This application of hSSC isolation can be performed by any researcher with basic skills in biology and flow cytometry within 1-2 days. The downstream functional assays can be performed within a range of 1-2 months.

Inverse agonists of retinoic acid receptor/retinoid X receptor signaling as lineage-specific antitumor agents against human adenoid cystic carcinoma.

BACKGROUND: Adenoid cystic carcinoma (ACC) is a lethal malignancy of exocrine glands, characterized by the coexistence within tumor tissues of 2 distinct populations of cancer cells, phenotypically similar to the myoepithelial and ductal lineages of normal salivary epithelia. The developmental relationship linking these 2 cell types, and their differential vulnerability to antitumor treatments, remains unknown. METHODS: Using single-cell RNA sequencing, we identified cell-surface markers (CD49f, KIT) that enabled the differential purification of myoepithelial-like (CD49fhigh/KITneg) and ductal-like (CD49flow/KIT+) cells from patient-derived xenografts (PDXs) of human ACCs. Using prospective xenotransplantation experiments, we compared the tumor-initiating capacity of the 2 cell types and tested whether one could differentiate into the other. Finally, we searched for signaling pathways with differential activation between the 2 cell types and tested their role as lineage-specific therapeutic targets. RESULTS: Myoepithelial-like cells displayed higher tumorigenicity than ductal-like cells and acted as their progenitors. Myoepithelial-like and ductal-like cells displayed differential expression of genes encoding for suppressors and activators of retinoic acid signaling, respectively. Agonists of retinoic acid receptor (RAR) or retinoid X receptor (RXR) signaling (all-trans retinoic acid, bexarotene) promoted myoepithelial-to-ductal differentiation, whereas suppression of RAR/RXR signaling with a dominant-negative RAR construct abrogated it. Inverse agonists of RAR/RXR signaling (BMS493, AGN193109) displayed selective toxicity against ductal-like cells and in vivo antitumor activity against PDX models of human ACC. CONCLUSIONS: In human ACCs, myoepithelial-like cells act as progenitors of ductal-like cells, and myoepithelial-to-ductal differentiation is promoted by RAR/RXR signaling. Suppression of RAR/RXR signaling is lethal to ductal-like cells and represents a new therapeutic approach against human ACCs.

A Living Organoid Biobank of Crohn's Disease Patients Reveals Molecular Subtypes for Personalized Therapeutics.

Crohn's disease (CD) is a complex, clinically heterogeneous disease of multifactorial origin; there is no perfect pre-clinical model, little insight into the basis for such heterogeneity, and still no cure. To address these unmet needs, we sought to explore the translational potential of adult stem cell-derived organoids that not only retain their tissue identity, but also their genetic and epigenetic disease-driving traits. We prospectively created a biobank of CD patient-derived organoid cultures (PDOs) using biopsied tissues from colons of 34 consecutive subjects representing all clinical subtypes (Montreal Classification B1-B3 and perianal disease). PDOs were generated also from healthy subjects. Comparative gene expression analyses enabled benchmarking of PDOs as tools for modeling the colonic epithelium in active disease and revealed that despite the clinical heterogeneity there are two major molecular subtypes: immune-deficient infectious-CD [IDICD] and stress and senescence-induced fibrostenotic-CD [S2FCD]. The transcriptome, genome and phenome show a surprising degree of internal consistency within each molecular subtype. The spectrum of morphometric, phenotypic, and functional changes within the "living biobank" reveals distinct differences between the molecular subtypes. These insights enabled drug screens that reversed subtype-specific phenotypes, e.g., impaired microbial clearance in IDICD was reversed using agonists for nuclear receptors, and senescence in S2FCD was rectified using senotherapeutics, but not vice versa . Phenotyped-genotyped CD-PDOs may fill the gap between basic biology and patient trials by enabling pre-clinical Phase '0' human trials for personalized therapeutics. In Brief: This work creates a prospectively biobanked phenotyped-genotyped Crohn's disease patient-derived organoids (CD-PDOs) as platforms for molecular subtyping of disease and for ushering personalized therapeutics. HIGHLIGHTS: Prospectively biobanked CD-organoids recapitulate the disease epithelium in patientsThe phenome-transcriptome-genome of CD-organoids converge on two molecular subtypesOne subtype shows impaired microbial clearance, another increased cellular senescencePhenotyped-genotyped PDOs are then used for integrative and personalized therapeutics.

Artificial intelligence-guided discovery of gastric cancer continuum.

BACKGROUND: Detailed understanding of pre-, early and late neoplastic states in gastric cancer helps develop better models of risk of progression to gastric cancers (GCs) and medical treatment to intercept such progression. METHODS: We built a Boolean implication network of gastric cancer and deployed machine learning algorithms to develop predictive models of known pre-neoplastic states, e.g., atrophic gastritis, intestinal metaplasia (IM) and low- to high-grade intestinal neoplasia (L/HGIN), and GC. Our approach exploits the presence of asymmetric Boolean implication relationships that are likely to be invariant across almost all gastric cancer datasets. Invariant asymmetric Boolean implication relationships can decipher fundamental time-series underlying the biological data. Pursuing this method, we developed a healthy mucosa → GC continuum model based on this approach. RESULTS: Our model performed better against publicly available models for distinguishing healthy versus GC samples. Although not trained on IM and L/HGIN datasets, the model could identify the risk of progression to GC via the metaplasia → dysplasia → neoplasia cascade in patient samples. The model could rank all publicly available mouse models for their ability to best recapitulate the gene expression patterns during human GC initiation and progression. CONCLUSIONS: A Boolean implication network enabled the identification of hitherto undefined continuum states during GC initiation. The developed model could now serve as a starting point for rationalizing candidate therapeutic targets to intercept GC progression.

Identification of a novel gene signature for neuroblastoma differentiation using a Boolean implication network.

Although induction of differentiation represents an effective strategy for neuroblastoma treatment, the mechanisms underlying neuroblastoma differentiation are poorly understood. We generated a computational model of neuroblastoma differentiation consisting of interconnected gene clusters identified based on symmetric and asymmetric gene expression relationships. We identified a differentiation signature consisting of series of gene clusters comprised of 1251 independent genes that predicted neuroblastoma differentiation in independent datasets and in neuroblastoma cell lines treated with agents known to induce differentiation. This differentiation signature was associated with patient outcomes in multiple independent patient cohorts and validated the role of MYCN expression as a marker of neuroblastoma differentiation. Our results further identified novel genes associated with MYCN via asymmetric Boolean implication relationships that would not have been identified using symmetric computational approaches and that were associated with both neuroblastoma differentiation and patient outcomes. Our differentiation signature included a cluster of genes involved in intracellular signaling and growth factor receptor trafficking pathways that is strongly associated with neuroblastoma differentiation, and we validated the associations of UBE4B, a gene within this cluster, with neuroblastoma cell and tumor differentiation. Our findings demonstrate that Boolean network analyses of symmetric and asymmetric gene expression relationships can identify novel genes and pathways relevant for neuroblastoma tumor differentiation that could represent potential therapeutic targets.

AI-assisted discovery of an ethnicity-influenced driver of cell transformation in esophageal and gastroesophageal junction adenocarcinomas.

Although Barrett's metaplasia of the esophagus (BE) is the only known precursor lesion to esophageal adenocarcinomas (EACs), drivers of cellular transformation in BE remain incompletely understood. We use an artificial intelligence-guided network approach to study EAC initiation and progression. Key predictions are subsequently validated in a human organoid model, in patient-derived biopsy specimens of BE, a case-control study of genomics of BE progression, and in a cross-sectional study of 113 patients with BE and EACs. Our model classified healthy esophagus from BE and BE from EACs in several publicly available gene expression data sets (n = 932 samples). The model confirmed that all EACs must originate from BE and pinpointed a CXCL8/IL8↔neutrophil immune microenvironment as a driver of cellular transformation in EACs and gastroesophageal junction adenocarcinomas. This driver is prominent in White individuals but is notably absent in African Americans (AAs). Network-derived gene signatures, independent signatures of neutrophil processes, CXCL8/IL8 expression, and an absolute neutrophil count (ANC) are associated with risk of progression. SNPs associated with changes in ANC by ethnicity (e.g., benign ethnic neutropenia [BEN]) modify that risk. Findings define a racially influenced immunological basis for cell transformation and suggest that BEN in AAs may be a deterrent to BE→EAC progression.

Boolean implication analysis of single-cell data predicts retinal cell type markers.

BACKGROUND: The retina is a complex tissue containing multiple cell types that are essential for vision. Understanding the gene expression patterns of various retinal cell types has potential applications in regenerative medicine. Retinal organoids (optic vesicles) derived from pluripotent stem cells have begun to yield insights into the transcriptomics of developing retinal cell types in humans through single cell RNA-sequencing studies. Previous methods of gene reporting have relied upon techniques in vivo using microarray data, or correlational and dimension reduction methods for analyzing single cell RNA-sequencing data computationally. We aimed to develop a state-of-the-art Boolean method that filtered out noise, could be applied to a wide variety of datasets and lent insight into gene expression over differentiation. RESULTS: Here, we present a bioinformatic approach using Boolean implication to discover genes which are retinal cell type-specific or involved in retinal cell fate. We apply this approach to previously published retina and retinal organoid datasets and improve upon previously published correlational methods. Our method improves the prediction accuracy of marker genes of retinal cell types and discovers several new high confidence cone and rod-specific genes. CONCLUSIONS: The results of this study demonstrate the benefits of a Boolean approach that considers asymmetric relationships. We have shown a statistically significant improvement from correlational, symmetric methods in the prediction accuracy of retinal cell-type specific genes. Furthermore, our method contains no cell or tissue-specific tuning and hence could impact other areas of gene expression analyses in cancer and other human diseases.