Sympathetic ophthalmia: epidemiology and cohort-based assessment of clinical outcomes.

BACKGROUND: The purpose of this study was to report the incidence, time after inciting event, aetiology and risk after specific intraocular procedures and the visual outcomes associated with sympathetic ophthalmia (SO) occurrence. METHODS: This study reports data from multiple retrospective cohorts: retrospective population-based data were extracted from the TRICARE service network (between 2017 and 2021) and retrospective case-based data from the Ocular Autoimmune Systemic Inflammatory Infectious Study (OASIS) database (cohorts from the UK, South India and North India). RESULTS: There were 159 patients with SO identified. The length of time from sensitising event to SO occurrence was a median of 151 days (range: 6-9100 days).In the TRICARE database, 2 patients developed SO after open globe trauma and primary repair (of 615 eyes, rate 0.33%; 95% CI 1.26% to 1.30%). None developed SO after vitrectomy (total of 23 903 events; 95% CI 0% to 0.012%). The combined North Indian and UK cohorts reported 78.6% (81 patients) after trauma, 18.45% (19 patients) after elective surgery.Visual outcomes were reported in the OASIS database for 98.01% of patients (155 of 157 patients). The median presenting and final best corrected visual acuity (BCVA) for the inciting eye were no perception of light, the median presenting and final BCVA for the sympathising eye were 0.65 and 0.3 logMAR, respectively. CONCLUSION: This study identified 159 cases of SO. With poor visual outcomes in the inciting eye, early diagnosis and management are crucial for optimising visual outcomes in the sympathising eye.

Immunophenotyping schizophrenia subtypes stratified by antipsychotic response.

Immune dysfunction has been proposed to play a role in the pathophysiology behind the development and persistence of psychosis. Current immunophenotyping studies are limited by small sample sizes and the number of immune markers investigated. Pharmacological subtypes in schizophrenia based on antipsychotic response have been proposed, but few studies have investigated immunophenotypes in treatment-resistant schizophrenia. In this study, we perform comprehensive immunophenotyping on 196 subjects comprising 147 schizophrenia patients stratified by antipsychotic response (49 antipsychotic-responsive, 70 clozapine-responsive, 28 clozapine-resistant) and 49 healthy controls. We aim to identify significant immune cell populations associated with schizophrenia and increasing treatment resistance, as potential modulators of underlying psychosis and/or treatment response. Patients with schizophrenia were recruited and assessed on the Clinical Global Impression - Schizophrenia (CGI-SCH). Treatment response was defined as a rating of three (mild severity) or less on the CGI-SCH positive symptom item after at least 8 weeks of adequate antipsychotic or clozapine treatment. Peripheral blood mononuclear cells were collected and flow cytometry was performed to identify 66 immune cell populations. Differences in cell population proportions were compared between schizophrenia cases and controls, and across all 4 groups, with post-hoc pairwise comparisons. Mucosal-associated invariant T (MAIT) cells (specifically CD8 + and DN double-negative subsets), total, exhausted and memory CD8 + T cells, VD1 + Ï’δ T cells, plasmablasts, IgG + B cells and conventional dendritic cells 2 (cDC2) were among the top cell populations downregulated in schizophrenia. We observed increased downregulation with increasing treatment resistance. Conversely, naïve and exhausted CD4 + T cells, CD4/CD8 ratio and CCR5 + CCR2 + HLA DR + Myeloid cells were found to be upregulated in schizophrenia - we observed increased upregulation with increasing treatment resistance. We show significant immunophenotypic differences between schizophrenia cases and healthy controls, and consistent trend differences across varying degrees of antipsychotic resistance. We also examined immune cell populations not previously reported in schizophrenia. Future studies may explore immune markers identified as potential biomarkers of treatment resistance, and clarify on the relationship between immunological changes and pharmacological subtypes in schizophrenia.

Web-based vs. conventional: a comprehensive analysis of visual acuity assessment using the PocDoc tool in a tertiary eye care centre.

BACKGROUND: Visual acuity (VA) represents a fundamental measure of visual function. The significant prevalence of underdiagnosed ocular disorders underscores the importance of effective VA assessment. This study evaluates the efficacy of a web-based VA assessment tool ("PocDoc") versus conventional VA testing. METHODS: Prospective observational study including 353 participants recruited from various eye clinics in a tertiary referral centre. Age, diagnosis, and VA related information (i.e. VA measurements from PocDoc and conventional VA test [Snellen chart], test type, etc) were collected. Spearman's rank correlation, Intraclass Correlation, and Bland-Altman plot compared outcomes of both tests. One-way ANOVA and paired-T test were used to compare means. RESULTS: Most patients were males (59.2%) with a mean age of 52.2 ± 20.6 years. PocDoc had moderate positive correlation to conventional testing (rho = 0.50, p < 0.001). PocDoc led to higher logMAR scores compared to conventional testing (mean logMAR 0.19 and 0.13 respectively, p < 0.01). Moreover, PocDoc demonstrated a sensitivity of 82.8% and specificity of 79% for detecting visual impairment. The discrepancy between PocDoc and conventional VA testing increased with higher logMAR values, indicating greater inconsistency between the tests for patients with poorer VA. Age, test type, and disease type contributed to this variability. CONCLUSIONS: The concordance between PocDoc and conventional testing for VA measurement across various ages and conditions makes it a suitable screening tool. Future technological inventions should consider age, test type, and disease type as critical factors related to the level of agreement and correlation between digital and conventional VA testing methods.

Lgr5 marks stem/progenitor cells contributing to epithelial and muscle development in the mouse esophagus.

The existence and function of Lgr5+ cells within the developing esophagus remains unknown. Here, we document multiple discrete Lgr5+ populations in the developing mouse esophagus, predominantly within nascent epithelial and external muscle layers. Lgr5 expression initially emerges in the developing proximal embryonic epithelium, but progressively extends distally and persists within the distal epithelium of neonates. Fate mapping and ablation analyses reveal a long-term contribution of epithelial Lgr5+ cells to esophageal organogenesis. Additionally, Lgr5-expressing cells are present in the developing external muscle layer, particularly during the development of the striated component. Fate mapping reveals a significant contribution of these embryonic Lgr5+ cells to the adult muscle layer. Embryonic Lgr5+ epithelial cells are also found to be important for regulating epithelial development, serving as a key source of Wnt6, among other ligands, to promote epithelial cell proliferation and formation of epithelial layers. These findings significantly enhance our understanding of esophageal development and shed light on the involvement of Lgr5+ stem/progenitor cells during organogenesis. Importantly, this study lays the foundation for investigating esophageal diseases related to the Lgr5+ stem/progenitor cell pool.

Association between alcohol flushing syndrome and cancer: A systematic review and meta-analysis.

Introduction: Alcohol flushing syndrome (AFS) is experienced by up to 46% of East Asians. This study aimed to review the risk of cancers in AFS patients, elucidate an exposure-response relationship, and understand risk associated with alcohol intake and cancer. Method: An electronic database search of PubMed, Embase, Scopus and Cochrane Library was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. Observational studies on AFS' effects and all cancers risk were included. Studies including patients with existing malignancy were excluded. Dichotomous variables were pooled using the Mantel-Haenszel method with a random effects model. Sensitivity and subgroup analyses were performed. PROSPERO (CRD42023392916) protocol was followed. Results: A total of 18 articles were included in the final analysis with a total of 387,521 participants. AFS was associated with an increased risk of all cancers (odds ratio [OR] 1.19, 95% confidence interval [CI] 1.06-1.34), esophageal squamous cell carcinoma (OR 1.47, 95% CI 1.05-2.05) and gastric adenocarci-noma (OR 1.40, 95% CI 1.14-1.72). Men with AFS exhibited an increased risk of all cancers (OR 1.34, 95% CI 1.13-1.59). However, this was not observed in women. All cancers risk was associated with AFS in those who consumed drink (i.e. consumed alcohol) more than 200 g of pure ethanol/week (OR 1.68, 95% CI 1.20-2.37) but not those who consumed less than 200 g of pure ethanol/week (OR 1.27, 95% CI 0.90-1.79) or non-drinkers (OR 0.99, 95% CI 0.67-1.47). Conclusion: AFS is associated with an increased risk of all cancers, particularly esophageal squamous cell carcinoma and gastric adenocarcinoma.

Splenic marginal zone B cells restrict Mycobacterium tuberculosis infection by shaping the cytokine pattern and cell-mediated immunity.

Understanding the role of B cells in tuberculosis (TB) is crucial for developing new TB vaccines. However, the changes in B cell immune landscapes during TB and their functional implications remain incompletely explored. Using high-dimensional flow cytometry to map the immune landscape in response to Mycobacterium tuberculosis (Mtb) infection, our results show an accumulation of marginal zone B (MZB) cells and other unconventional B cell subsets in the lungs and spleen, shaping an unconventional B cell landscape. These MZB cells exhibit activated and memory-like phenotypes, distinguishing their functional profiles from those of conventional B cells. Notably, functional studies show that MZB cells produce multiple cytokines and contribute to systemic protection against TB by shaping cytokine patterns and cell-mediated immunity. These changes in the immune landscape are reversible upon successful TB chemotherapy. Our study suggests that, beyond antibody production, targeting the regulatory function of B cells may be a valuable strategy for TB vaccine development.

Proteomics profiling and association with cardiorenal complications in type 2 diabetes subtypes in Asian population.

AIM: Among multi-ethnic Asians, type 2 diabetes (T2D) clustered in three subtypes; mild obesity-related diabetes (MOD), mild age-related diabetes with insulin insufficiency (MARD-II) and severe insulin-resistant diabetes with relative insulin insufficiency (SIRD-RII) had differential cardio-renal complication risk. We assessed the proteomic profiles to identify subtype specific biomarkers and its association with diabetes complications. METHODS: 1448 plasma proteins at baseline were measured and compared across the T2D subtypes. Multivariable cox regression was used to assess associations between significant proteomics features and cardio-renal complications. RESULTS: Among 645 T2D participants (SIRD-RII [19%], MOD [45%], MARD-II [36%]), 295 proteins expression differed significantly across the groups. These proteins were enriched in cell adhesion, neurogenesis and inflammatory response processes. In SIRD-RII group, ADH4, ACY1, THOP1, IGFBP2, NEFL, ENTPD2, CALB1, HAO1, CTSV, ITGAV, SCLY, EDA2R, ERBB2 proteins significantly associated with progressive CKD and LILRA5 protein with incident heart failure (HF). In MOD group, TAFA5, RSPO3, EDA2R proteins significantly associated with incident HF. In MARD-II group, FABP4 protein significantly associated with progressive CKD and PTPRN2 protein with major adverse cardiovascular events. Genetically determined NEFL and CALB1 were associated with kidney function decline. CONCLUSIONS: Each T2D subtype has unique proteomics signature and association with clinical outcomes and underlying mechanisms.

Managing a patient with uveitis in the era of artificial intelligence: Current approaches, emerging trends, and future perspectives.

The integration of artificial intelligence (AI) with healthcare has opened new avenues for diagnosing, treating, and managing medical conditions with remarkable precision. Uveitis, a diverse group of rare eye conditions characterized by inflammation of the uveal tract, exemplifies the complexities in ophthalmology due to its varied causes, clinical presentations, and responses to treatments. Uveitis, if not managed promptly and effectively, can lead to significant visual impairment. However, its management requires specialized knowledge, which is often lacking, particularly in regions with limited access to health services. AI's capabilities in pattern recognition, data analysis, and predictive modelling offer significant potential to revolutionize uveitis management. AI can classify disease etiologies, analyze multimodal imaging data, predict outcomes, and identify new therapeutic targets. However, transforming these AI models into clinical applications and meeting patient expectations involves overcoming challenges like acquiring extensive, annotated datasets, ensuring algorithmic transparency, and validating these models in real-world settings. This review delves into the complexities of uveitis and the current AI landscape, discussing the development, opportunities, and challenges of AI from theoretical models to bedside application. It also examines the epidemiology of uveitis, the global shortage of uveitis specialists, and the disease's socioeconomic impacts, underlining the critical need for AI-driven approaches. Furthermore, it explores the integration of AI in diagnostic imaging and future directions in ophthalmology, aiming to highlight emerging trends that could transform management of a patient with uveitis and suggesting collaborative efforts to enhance AI applications in clinical practice.

Natural Language Processing in medicine and ophthalmology: A review for the 21st-century clinician.

Natural Language Processing (NLP) is a subfield of artificial intelligence that focuses on the interaction between computers and human language, enabling computers to understand, generate, and derive meaning from human language. NLP's potential applications in the medical field are extensive and vary from extracting data from Electronic Health Records -one of its most well-known and frequently exploited uses- to investigating relationships among genetics, biomarkers, drugs, and diseases for the proposal of new medications. NLP can be useful for clinical decision support, patient monitoring, or medical image analysis. Despite its vast potential, the real-world application of NLP is still limited due to various challenges and constraints, meaning that its evolution predominantly continues within the research domain. However, with the increasingly widespread use of NLP, particularly with the availability of large language models, such as ChatGPT, it is crucial for medical professionals to be aware of the status, uses, and limitations of these technologies.

Visualising cancer in 3D: 3-Dimensional Tissue Imaging for management of cutaneous basal cell carcinoma.

Surgical management of basal cell carcinoma (BCC) typically involves surgical excision with post-operative margin assessment using the bread-loafing technique; or gold-standard Mohs micrographic surgery (MMS), where margins are iteratively examined for residual cancer after tumour removal, with additional excisions performed upon detecting residual tumour at margins. There is limited sampling of resection margins with bread loafing, with detection of positive margins 44% of the time using 2 mm intervals. To resolve this, we have developed three-dimensional (3D) Tissue Imaging for: (1) complete examination of cancer margins and (2) detection of tumour proximity to nerves and blood vessels. 3D Tissue optical clearing with a light sheet imaging protocol was developed for margin assessment in two datasets assessed by two independent evaluators: (1) 48 samples from 29 patients with varied BCC subtypes, sizes and pigmentation levels; (2) 32 samples with matching Mohs' surgeon reading of tumour margins using two-dimensional haematoxylin & eosin-stained sections. The 3D Tissue Imaging protocol permits a complete examination of deeper and peripheral margins. Two independent evaluators achieved negative predictive values of 92.3% and 88.24% with 3D Tissue Imaging. Images obtained from 3D Tissue Imaging recapitulates histological features of BCC, such as nuclear crowding, palisading and retraction clefting and provides a 3D context for recognising normal skin adnexal structures. Concurrent immunofluorescence labelling of nerves and blood vessels allows visualisation of structures closer to tumour-positive regions, which may have a higher risk for neural and vascular infiltration. Together, this method provides more information in a 3D spatial context, enabling better cancer management by clinicians.

The role of perfusion, grey matter volume and behavioural phenotypes in the data-driven classification of cognitive syndromes.

BACKGROUND: The use of structural and perfusion brain imaging in combination with behavioural information in the prediction of cognitive syndromes using a data-driven approach remains to be explored. Here, we thus examined the contribution of brain structural and perfusion imaging and behavioural features to the existing classification of cognitive syndromes using a data-driven approach. METHODS: Study participants belonged to the community-based Biomarker and Cognition Cohort Study in Singapore who underwent neuropsychological assessments, structural-functional MRI and blood biomarkers. Participants had a diagnosis of cognitively normal (CN), subjective cognitive impairment (SCI), mild cognitive impairment (MCI) and dementia. Cross-sectional structural and cerebral perfusion imaging, behavioural scale data including mild behaviour impairment checklist, Pittsburgh Sleep Quality Index and Depression, Anxiety and Stress scale data were obtained. RESULTS: Three hundred seventy-three participants (mean age 60.7 years; 56% female sex) with complete data were included. Principal component analyses demonstrated that no single modality was informative for the classification of cognitive syndromes. However, multivariate glmnet analyses revealed a specific combination of frontal perfusion and temporo-frontal grey matter volume were key protective factors while the severity of mild behaviour impairment interest sub-domain and poor sleep quality were key at-risk factors contributing to the classification of CN, SCI, MCI and dementia (p < 0.0001). Moreover, the glmnet model showed best classification accuracy in differentiating between CN and MCI cognitive syndromes (AUC = 0.704; sensitivity = 0.698; specificity = 0.637). CONCLUSIONS: Brain structure, perfusion and behavioural features are important in the classification of cognitive syndromes and should be incorporated by clinicians and researchers. These findings illustrate the value of using multimodal data when examining syndrome severity and provide new insights into how cerebral perfusion and behavioural impairment influence classification of cognitive syndromes.

High-density lipoprotein cholesterol subfraction HDL2 is associated with improved endothelial function in systemic lupus erythematosus.

OBJECTIVE: Patients with systemic lupus erythematosus (SLE) have increased risk of premature atherosclerosis but the exact mechanisms remains unclear. Flow-mediated dilatation (FMD) is an established non-invasive assessment of vascular endothelial function. Lipoprotein subfractions may be better predictors of FMD than conventional cholesterol measurements. We tested the hypothesis that lipoprotein subfractions are independently associated with FMD. METHODS: Forty-one consecutive adult patients with SLE without known cardiovascular risk factors or disease were recruited in this cross-sectional study. Endothelial function and early atherosclerosis were assessed by brachial FMD and common carotid artery (CCA) intima-media thickness (IMT). High-density lipoprotein (HDL)/low-density lipoprotein (LDL) subfractions were measured. Machine learning models were also constructed to predict FMD and CCA IMT. RESULTS: Median FMD was 4.48% (IQR 5.00%) while median IMT was 0.54 mm (IQR 0.12 mm). Univariate analysis showed lower LDL1 (r=-0.313, p<0.05) and higher HDL2 subfractions (r=0.313, p<0.05) were significantly associated with higher log-transformed FMD. In a multiple linear regression model, HDL2 (ß=0.024, SE=0.012, p<0.05) remained an independent predictor of higher FMD after adjusting for age, body mass index, LDL1 and systolic blood pressure. The machine learning model included parameters such as HDL2 (positive association), prednisolone dose, LDL cholesterol and LDL1 for prediction of FMD (r=0.433, p<0.01). Age, LDL cholesterol and systolic blood pressure were independently associated with higher CCA IMT after adjusting for body mass index and HDL2. CONCLUSIONS: HDL 2, a large HDL particle, was independently associated with greater FMD and may be a biomarker of vascular health in SLE.

Longitudinal single cell atlas identifies complex temporal relationship between type I interferon response and COVID-19 severity.

Due to the paucity of longitudinal molecular studies of COVID-19, particularly those covering the early stages of infection (Days 1-8 symptom onset), our understanding of host response over the disease course is limited. We perform longitudinal single cell RNA-seq on 286 blood samples from 108 age- and sex-matched COVID-19 patients, including 73 with early samples. We examine discrete cell subtypes and continuous cell states longitudinally, and we identify upregulation of type I IFN-stimulated genes (ISGs) as the predominant early signature of subsequent worsening of symptoms, which we validate in an independent cohort and corroborate by plasma markers. However, ISG expression is dynamic in progressors, spiking early and then rapidly receding to the level of severity-matched non-progressors. In contrast, cross-sectional analysis shows that ISG expression is deficient and IFN suppressors such as SOCS3 are upregulated in severe and critical COVID-19. We validate the latter in four independent cohorts, and SOCS3 inhibition reduces SARS-CoV-2 replication in vitro. In summary, we identify complexity in type I IFN response to COVID-19, as well as a potential avenue for host-directed therapy.

Combining multimodal magnetic resonance brain imaging and machine learning to unravel neurocognitive function in non-neuropsychiatric systemic lupus erythematosus.

OBJECTIVE: To study whether multimodal brain MRI comprising permeability and perfusion measures coupled with machine learning can predict neurocognitive function in young patients with SLE without neuropsychiatric manifestations. METHODS: SLE patients and healthy controls (HCs) (≤40 years of age) underwent multimodal structural brain MRI that comprised voxel-based morphometry (VBM), magnetization transfer ratio (MTR) and dynamic contrast-enhanced (DCE) MRI in this cross-sectional study. Neurocognitive function assessed by Automated Neuropsychological Assessment Metrics was reported as the total throughput score (TTS). Olfactory function was assessed. A machine learning-based model (i.e. glmnet) was constructed to predict TTS. RESULTS: Thirty SLE patients and 10 HCs were studied. Both groups had comparable VBM, MTR, olfactory bulb volume (OBV), olfactory function and TTS. While after correction for multiple comparisons the uncorrected increase in the blood-brain barrier (BBB) permeability parameters compared with HCs did not remain evident in SLE patients, DCE-MRI perfusion parameters, notably an increase in right amygdala perfusion, was positively correlated with TTS in SLE patients (r = 0.636, false discovery rate P < 0.05). A machine learning-trained multimodal MRI model comprising alterations of VBM, MTR, OBV and DCE-MRI parameters mainly in the limbic system regions predicted TTS in SLE patients (r = 0.644, P < 0.0005). CONCLUSION: Multimodal brain MRI demonstrated increased right amygdala perfusion that was associated with better neurocognitive performance in young SLE patients without statistically significant BBB leakage and microstructural abnormalities. A machine learning-constructed multimodal model comprising microstructural, perfusion and permeability parameters accurately predicted neurocognitive performance in SLE patients.

Platelet TLR7 is essential for the formation of platelet-neutrophil complexes and low-density neutrophils in lupus nephritis.

OBJECTIVES: Platelets and low-density neutrophils (LDNs) are major players in the immunopathogenesis of SLE. Despite evidence showing the importance of platelet-neutrophil complexes (PNCs) in inflammation, little is known about the relationship between LDNs and platelets in SLE. We sought to characterize the role of LDNs and Toll-like receptor 7 (TLR7) in clinical disease. METHODS: Flow cytometry was used to immunophenotype LDNs from SLE patients and controls. The association of LDNs with organ damage was investigated in a cohort of 290 SLE patients. TLR7 mRNA expression was assessed in LDNs and high-density neutrophils (HDNs) using publicly available mRNA sequencing datasets and our own cohort using RT-PCR. The role of TLR7 in platelet binding was evaluated in platelet-HDN mixing studies using TLR7-deficient mice and Klinefelter syndrome patients. RESULTS: SLE patients with active disease have more LDNs, which are heterogeneous and more immature in patients with evidence of kidney dysfunction. LDNs are platelet bound, in contrast to HDNs. LDNs settle in the peripheral blood mononuclear cell (PBMC) layer due to the increased buoyancy and neutrophil degranulation from platelet binding. Mixing studies demonstrated that this PNC formation was dependent on platelet-TLR7 and that the association results in increased NETosis. The neutrophil:platelet ratio is a useful clinical correlate for LDNs, and a higher NPR is associated with past and current flares of LN. CONCLUSIONS: LDNs sediment in the upper PBMC fraction due to PNC formation, which is dependent on the expression of TLR7 in platelets. Collectively, our results reveal a novel TLR7-dependent crosstalk between platelets and neutrophils that may be an important therapeutic opportunity for LN.

Improving Access to Eye Care in Rural Communities: PocDoc's Web-Based Visual Acuity Screening Tool.

Objective: Visual acuity (VA) testing is crucial for early intervention in cases of visual impairment, especially in rural health care. This study aimed to determine the potential of a web-based VA test (PocDoc) in addressing the unique health care needs of rural areas through the comparison in its effectiveness against the conventional VA test in identifying visual impairment among an Indian rural population. Methods: Prospective comparative study conducted in December 2022 at a tertiary referral eye care center in central India. We evaluated all patients with the PocDoc VA tests using three device types, and the conventional VA test. Bland-Altman plot (BAP) compared PocDoc and conventional VA tests. Fisher's exact tests evaluated associations between categorical parameters. Kruskal-Wallis tests followed by post hoc Dunn's tests identified association between categorical parameters and numerical parameters. Results: We evaluated 428 patients (792 measurements of VA) with mean age 36.7 (±23.3) years. PocDoc resulted in slightly worse VA scores (mean logMAR: 0.345) than conventional (mean logMAR: 0.315). Correlation coefficient between the conventional and PocDoc logMAR VA values was rho = 0.845 and rho2 = 0.7133 (p = 6.617 × 10-215; adjusted p = 2.205 × 10-214). Most data points fell within the interchangeable range of ±0.32 on BAP. Difference between the two methods increased with higher logMAR values, indicating poorer agreement for worse VA scores. Conclusions: Identifying and addressing the unique health care needs of rural populations is critical, including access to appropriate and effective VA testing methods. Validating and improving VA testing methods can ensure early intervention and improve the quality of life for individuals with visual impairment.

Dynamic altruistic cooperation within breast tumors.

BACKGROUND: Social behaviors such as altruism, where one self-sacrifices for collective benefits, critically influence an organism's survival and responses to the environment. Such behaviors are widely exemplified in nature but have been underexplored in cancer cells which are conventionally seen as selfish competitive players. This multidisciplinary study explores altruism and its mechanism in breast cancer cells and its contribution to chemoresistance. METHODS: MicroRNA profiling was performed on circulating tumor cells collected from the blood of treated breast cancer patients. Cancer cell lines ectopically expressing candidate miRNA were used in co-culture experiments and treated with docetaxel. Ecological parameters like relative survival and relative fitness were assessed using flow cytometry. Functional studies and characterization performed in vitro and in vivo include proliferation, iTRAQ-mass spectrometry, RNA sequencing, inhibition by small molecules and antibodies, siRNA knockdown, CRISPR/dCas9 inhibition and fluorescence imaging of promoter reporter-expressing cells. Mathematical modeling based on evolutionary game theory was performed to simulate spatial organization of cancer cells. RESULTS: Opposing cancer processes underlie altruism: an oncogenic process involving secretion of IGFBP2 and CCL28 by the altruists to induce survival benefits in neighboring cells under taxane exposure, and a self-sacrificial tumor suppressive process impeding proliferation of altruists via cell cycle arrest. Both processes are regulated concurrently in the altruists by miR-125b, via differential NF-κB signaling specifically through IKKß. Altruistic cells persist in the tumor despite their self-sacrifice, as they can regenerate epigenetically from non-altruists via a KLF2/PCAF-mediated mechanism. The altruists maintain a sparse spatial organization by inhibiting surrounding cells from adopting the altruistic fate via a lateral inhibition mechanism involving a GAB1-PI3K-AKT-miR-125b signaling circuit. CONCLUSIONS: Our data reveal molecular mechanisms underlying manifestation, persistence and spatial spread of cancer cell altruism. A minor population behave altruistically at a cost to itself producing a collective benefit for the tumor, suggesting tumors to be dynamic social systems governed by the same rules of cooperation in social organisms. Understanding cancer cell altruism may lead to more holistic models of tumor evolution and drug response, as well as therapeutic paradigms that account for social interactions. Cancer cells constitute tractable experimental models for fields beyond oncology, like evolutionary ecology and game theory.

Chatbots Vs. Human Experts: Evaluating Diagnostic Performance of Chatbots in Uveitis and the Perspectives on AI Adoption in Ophthalmology.

PURPOSE: To assess the diagnostic performance of two chatbots, ChatGPT and Glass, in uveitis diagnosis compared to renowned uveitis specialists, and evaluate clinicians' perception about utilizing artificial intelligence (AI) in ophthalmology practice. METHODS: Six cases were presented to uveitis experts, ChatGPT (version 3.5 and 4.0) and Glass 1.0, and diagnostic accuracy was analyzed. Additionally, a survey about the emotions, confidence in utilizing AI-based tools, and the likelihood of incorporating such tools in clinical practice was done. RESULTS: Uveitis experts accurately diagnosed all cases (100%), while ChatGPT achieved a diagnostic success rate of 66% and Glass 1.0 achieved 33%. Most attendees felt excited or optimistic about utilizing AI in ophthalmology practice. Older age and high level of education were positively correlated with increased inclination to adopt AI-based tools. CONCLUSIONS: ChatGPT demonstrated promising diagnostic capabilities in uveitis cases and ophthalmologist showed enthusiasm for the integration of AI into clinical practice.