Vision Screening Research Articles

Abstract We103: Integration of deep learning assisted high-content screening and deep tissue-phenotyping to identify cardioprotective compounds in dilated cardiomyopathy

With a prevalence of 4:10,000, dilated cardiomyopathy (DCM) is the most common hereditary heart disease, characterized by dilatation of one or both ventricles and impaired systolic and diastolic function. Numerous mutations have been identified to cause DCM. TITIN-truncating variants (TTNtv) are commonly observed in 20% of the genetic DCM cases. Progress in drug discovery for DCM has been hampered by the lack of robust high-throughput/high-content analysis pipelines of disease-specific cell and tissue platforms for deep structural and functional phenotyping. To address this challenge, we have developed a two-tiered human induced pluripotent stem cell (iPSC)-based screening approach, comprised of high-content cardiomyocyte imaging with artificial intelligence (AI)-driven image and data analyses as well as deep tissue phenotyping in engineered heart muscle (EHM) models. As a DCM use case, we have developed several isogenic human iPSC-lines with and without a previously reported and pathologically relevant A-band-TTNtv mutation (c.70692_70693insAT; p.T23565SfsX5; Gerull et al. 11788824, Gramlich et al. 25759365, Fomin et al. 34731013) Using fixed weights from a convolutional deep neural network trained on ImageNet, we generated unbiased deep embeddings from each 2D cell model and applied these to train machine learning (ML) models to detect morphological disease phenotypes. Our ML model is able to confidently separate healthy controls from TTNtv cells with high accuracy (>93%), specificity (WT >79%) across different batches/plate layouts and generate concentration-response curves, demonstrating platform robustness and sensitivity. Building upon this work, we will present our latest efforts applying the platform technology for a chemogenomic screening campaign to identify novel cardioprotective drugs using a library of 7,100 bioactive compounds and validation assays, including measuring functional changes in EHMs. The phenotypic profiling platform, as presented here, can be readily adapted to other disease-relevant cell types and pathologies. Our results demonstrate the power of combining iPSC-CMs with cytological profiling and deep learning as well as tissue-level phenotyping to accelerate drug discovery for patients with DCM.

Understanding patient-derived tumor organoid growth through an integrated imaging and mathematical modeling framework.

Patient-derived tumor organoids (PDTOs) are novel cellular models that maintain the genetic, phenotypic and structural features of patient tumor tissue and are useful for studying tumorigenesis and drug response. When integrated with advanced 3D imaging and analysis techniques, PDTOs can be used to establish physiologically relevant high-throughput and high-content drug screening platforms that support the development of patient-specific treatment strategies. However, in order to effectively leverage high-throughput PDTO observations for clinical predictions, it is critical to establish a quantitative understanding of the basic properties and variability of organoid growth dynamics. In this work, we introduced an innovative workflow for analyzing and understanding PDTO growth dynamics, by integrating a high-throughput imaging deep learning platform with mathematical modeling, incorporating flexible growth laws and variable dormancy times. We applied the workflow to colon cancer organoids and demonstrated that organoid growth is well-described by the Gompertz model of growth. Our analysis showed significant intrapatient heterogeneity in PDTO growth dynamics, with the initial exponential growth rate of an organoid following a lognormal distribution within each dataset. The level of intrapatient heterogeneity varied between patients, as did organoid growth rates and dormancy times of single seeded cells. Our work contributes to an emerging understanding of the basic growth characteristics of PDTOs, and it highlights the heterogeneity in organoid growth both within and between patients. These results pave the way for further modeling efforts aimed at predicting treatment response dynamics and drug resistance timing.

Phytochemical Composition and Bioactivities of Some Hydrophytes: Antioxidant, Antiparasitic, Antibacterial, and Anticancer Properties and Mechanisms.

Few researches have explored the production of pharmaceuticals from aquatic plants. Therefore, this study explored, for the first time, the phytochemical composition and bioactivities of ten aquatic plants. Aquatic plant shoots from various Nile River canals were collected, dried, and ground for aqueous extract preparation. Phytochemical composition and antioxidant capacity were assessed using DPPH assays. Extracts were tested for antiparasitic, antibacterial, anti-biofilm, and anticancer activities through standard in vitro assays, measuring IC50 values, and evaluating mechanisms of action, including cell viability and high-content screening assays. The results showed that the aquatic plants were rich in pharmaceutical compounds. The antioxidant capacity of these extracts exceeded that of vitamin C. The extracts showed promising antiparasitic activity against pathogens like Opisthorchis viverrini and Plasmodium falciparum, with IC50 values between 0.7 and 2.5 µg/mL. They also demonstrated low MICs against various pathogenic bacteria, causing DNA damage, increased plasma membrane permeability, and 90% biofilm inhibition. In terms of anticancer activity, extracts were effective against a panel of cancer cell lines, with Ludwigia stolonifera exhibiting the highest efficacy. Its IC50 ranged from 0.5 µg/mL for pancreatic, esophageal, and colon cancer cells to 1.5 µg/mL for gastric cancer cells. Overall, IC50 values for all extracts were below 6 µg/mL, showing significant apoptotic activity, increased nuclear intensity, plasma membrane permeability, mitochondrial membrane permeability, and cytochrome c release, and outperforming doxorubicin. This study highlights the potential of aquatic plants as sources for new, safe, and effective drugs with strong antiparasitic, antibacterial, and anticancer properties.

Towards Trustworthy AI-Enabled Decision Support Systems: Validation of the Multisource AI Scorecard Table (MAST)

The Multisource AI Scorecard Table (MAST) is a checklist tool to inform the design and evaluation of trustworthy AI systems based on the U.S. Intelligence Community’s analytic tradecraft standards. In this study, we investigate whether MAST can be used to differentiate between high and low trustworthy AI-enabled decision support systems (AI-DSSs). Evaluating trust in AI-DSSs poses challenges to researchers and practitioners. These challenges include identifying the components, capabilities, and potential of these systems, many of which are based on the complex deep learning algorithms that drive DSS performance and preclude complete manual inspection. Using MAST, we developed two interactive AI-DSS testbeds. One emulated an identity-verification task in security screening, and another emulated a text-summarization system to aid in an investigative task. Each testbed had one version designed to reach low MAST ratings, and another designed to reach high MAST ratings. We hypothesized that MAST ratings would be positively related to the trust ratings of these systems. A total of 177 subject-matter experts were recruited to interact with and evaluate these systems. Results generally show higher MAST ratings for the high-MAST compared to the low-MAST groups, and that measures of trust perception are highly correlated with the MAST ratings. We conclude that MAST can be a useful tool for designing and evaluating systems that will engender trust perceptions, including for AI-DSS that may be used to support visual screening or text summarization tasks. However, higher MAST ratings may not translate to higher joint performance, and the connection between MAST and appropriate trust or trustworthiness remains an open question.

Luteolin promotes neuronogenesis in hippocampus of chronic unpredictable mild stress rats and primary hippocampus of fetal rats.

To investigate the effects of luteolin on chronic unpredictable mild stress (CUMS)-induced depressive rats and corticosterone (CORT)-induced depressive primary hippocampal neurons, and to elucidate the mechanism behind the action. The antidepressant mechanism of luteolin was studied by using CUMS rat model and primary hippocampal neurons in fetal rats. In vivo, novelty suppressed feeding, open-field and sucrose preference tests as well as Morris water maze were evaluated. The content of brain derived neurotrophic factor (BDNF), 5-hydroxytryptamine (5-HT), norepinephrine (NE), and dopamine (DA) in serum were detected by enzyme-linked immunosorbent assay. The mechanisms of luteolin were explored based on neurotrophin and hippocampal neurogenesis, and proliferation. Survival of the septo-temporal axis in hippocampus was assayed using the 5-bromo-2-deoxyuridine (BrdU), the expression of BDNF, neurotrophin-3 (NT-3), and nerve growth factor (NGF) in hippocampus dentate gyrus region were measured by Western-blotting. In vitro, BDNF, NT-3, tropomyosin receptor kinase B (TrkB), and phosphorylated cyclic adenosine monophosphate responsive element binding protein (p-CREB) were detected through the high content analysis (HCA) to investigate neurotrophin and apoptosis. Induction of CUMS in rats induced depressive symptoms, while luteolin significantly enhanced sucrose consumption, decreased feeding latency, increased locomotor activity, escape latency, distance of target quadrant and regulated the content of depressive-like biomarkers. Histology analysis revealed that luteolin increased the abundance of new born neurons that had been labeled with BrdU, BrdU + neuronal nuclear antigen, and BrdU + doublecortin in septo-temporal axis of S2 (mid-septal) and T3 (mid-temporal). Moreover, expression of BDNF, NT-3, and NGF increased significantly in the septo-temporal axis of S2 and T3. HCA showed increased expression of BDNF, NT-3, TrkB and p-CREB in primary hippocampal neurons. The results provided direct evidence that luteolin has an antidepressant effect and could effectively promote the regeneration of the septotemporal axis nerve and hippocampal neuronutrition, which suggested that the antidepressant effect of luteolin may be related to hippocampal neurogenesis.

Overcoming ABCB1 mediated multidrug resistance in castration resistant prostate cancer

Prostate cancer (PCa) is the second leading cause of cancer-related death in American men. PCa that relapses after hormonal therapies, referred to as castration resistant PCa (CRPC), often presents with metastases (mCRPC) that are the major cause of mortality. The few available therapies for mCRPC patients include taxanes docetaxel (DTX) and cabazitaxel (CBZ). However, development of resistance limits their clinical use. Mechanistically, resistance arises through upregulation of multidrug resistance (MDR) proteins such as MDR1/ABCB1, making ABCB1 an attractive therapeutic target. Yet, ABCB1 inhibitors failed to be clinically useful due to low specificity and toxicity issues. To study taxanes resistance, we produced CBZ resistant C4-2B cells (RC4-2B) and documented resistance to both CBZ and DTX in cell culture and in 3D prostaspheres settings. RNAseq identified increased expression of ABCB1 in RC4-2B, that was confirmed by immunoblotting and immunofluorescent analysis. ABCB1-specific inhibitor elacridar reversed CBZ and DTX resistance in RC4-2B cells, confirming ABCB1-mediated resistance mechanism. In a cell-based screen using a curated library of cytotoxic drugs, we found that DNA damaging compounds Camptothecin (CPT) and Cytarabine (Ara-C) overcame resistance as seen by similar cytotoxicity in parental C4-2B and resistant RC4-2B. Further, these compounds were cytotoxic to multiple PC cells resistant to taxanes with high ABCB1 expression and, therefore, can be used to conquer the acquired resistance to taxanes in PCa. Finally, inhibition of cyclin-dependent kinases 4/6 (CDK4/6) with small molecule inhibitors (CDK4/6i) potentiated cytotoxic effect of CPT or Ara-C in both parental and resistant cells. Overall, our findings indicate that DNA damaging agents CPT and Ara-C alone or in combination with CDK4/6i can be suggested as a new treatment regimen in CRPC patients, including those that are resistant to taxanes.

Prevalence of Amblyogenic Risk Factors Among School Children in India Using the Spot Vision Screener.

Amblyopia is a common cause of preventable visual impairment in children, affecting 1% to 6% globally. This study assesses amblyopia prevalence and risk factors among school children in rural Telangana, India, using the Spot Vision Screener (Welch Allyn, Inc., Skaneateles Falls, New York, USA), a portable, noninvasive device recommended for automated vision screening. A cross-sectional study was conducted on 714 schoolchildren aged 5-10 years. Screening was performed using the Spot Vision Screener, evaluating refractive errors, ocular alignment, and other amblyopia risk factors. Children identified with potential amblyogenic factors were referred for comprehensive ophthalmological evaluation to confirm diagnosis. Out of 714 children screened, 84 were referred by the Spot Vision Screener for further evaluation. Subsequent examination by ophthalmologists confirmed amblyopia in 65 children, resulting in a prevalence of 9.10%. Myopic refractive error was the most prevalent (69.23%), followed by astigmatism (21.53%) and hypermetropia (9.23%) among amblyopia cases. The Spot Vision Screener proved to be a reliable tool for identifying amblyopia risk factors in school children, facilitating early detection and referral for appropriate management. This study underscores the importance of implementing effective vision screening programs in rural settings to mitigate preventable childhood blindness.

Inside the Brain: Cerebrospinal Fluid Insights in Meningitis.

Background Our study focused on meningitis, an infection that can spread through the bloodstream as a primary or secondary infection from other body parts, such as sinuses, ears, and lungs. It can affect patients who have experienced trauma or surgery, as well as those with congenital defects like spina bifida. Specifically, we examined bacterial, viral, and tuberculous meningitis (TBM) cases. The primary method for confirming the diagnosis of these types of meningitis is to analyze the cerebrospinal fluid (CSF). Early diagnosis can utilize cytological and biochemical parameters. Our objective is to determine CSF's cytological and biochemical profile in patients with these specific types of meningitis. Methods A study was carried out at the central pathology lab from October 24, 2017, to April 24, 2018.CSF samples from suspected meningitis patients were examined for various parameters, including hematological, biochemical, microbiological, and cytomorphological aspects and specific tests for bacterial, fungal, and TBM. The study focused on patients aged 16 and above, excluding those under 16, non-compliant patients, and individuals with specific health conditions. Data were analyzed using IBM SPSS Statistics for Windows, Version 20 (Released 2011; IBM Corp., Armonk, New York, United States), and the results were presented through the use of mean, standard deviation, and percentages. Statistical tests were utilized to compare categorical variables and mean, with a significance level of p<0.05. Results We included a total of 156 cases, with the mean age of presentation being 56.628 years. The male-to-female ratio was 1.0526:1. Of the patients, 81 (52.1%) had been diagnosed with TBM, had elevated adenosine deaminase (ADA) levels of 48.8733±37.43740 IU/L, and CSF lymphocytosis (99%). Additionally, cases of bacterial meningitis showed markedly raised mean total leukocyte count (TLC) of 2085.50±445.47727 cells/mm3 and mean CSF protein levels of 349.45±113.73105 mg/dL. The study found a significant increase in protein levels and a decrease in glucose levels in the CSF of TBM and bacterial meningitis patients compared to those with other causes of meningitis (p<0.001). Guillain-Barre syndrome (GBS)and multiple sclerosis (MS) patients had TLC and ADA within normal limits.CSF ADA level greater than 6 IU/L showed a sensitivity of 97.53% and a specificity of 96.0%, making it the most specific test. A protein level in the CSF greater than 45 mg/dL demonstrated a sensitivity of 98.78% and a specificity of 24.32%, indicating it is sensitive but less specific in diagnosing TBM. Lymphocytic predominance, defined as TLCof more than 5 cells/mm3 with at least 50% of the cells being lymphocytes in the CSF of TBM patients, showed a sensitivity of 97.53% and a specificity of 6.67%. CSF glucose had a sensitivity of 38.27%, making it the least reliable indicator for diagnosing meningitis. Conclusion The CSF analysis is the primary diagnostic method for detecting meningitis. Its cost-effectiveness is a key factor, especially for patients from lower socioeconomic backgrounds in government medical colleges in India, where access to expensive diagnostic tests is limited. The efficiency of CSF analysis for early diagnosing different types of meningitis aids in management, helping to prevent complications and fatal outcomes.

Monoclonal antibody based colloidal gold immunochromatographic assay for the visual and rapid screening of profenofos

Profenofos (PFF) is a commonly used organophosphorus insecticide that requires strict monitoring due to its potential environmental, ecological, and human health risks originating from residues in soil and water systems, as well as accumulation in crops. In this study, a novel monoclonal antibody (mAb) specific to PFF was prepared for the first time and the recognition mechanism was investigated through molecular simulation. Subsequently, a mAb-based colloidal gold immunochromatographic assay (GICA) was developed for the rapid screening of PFF in fruit and vegetable samples. The mAb exhibited an IC50 value of 12.9 ng/mL, and limit of detection (LOD) of 4.6 ng/mL, respectively in indirect competitive immunosorbent enzyme-linked immunosorbent assay (ic-ELISA). After optimization, the developed GICA exhibited a visual limit of detection (vLOD) of 20 ng/mL and a quantitative of detection (qLOD) of 5.2 ng/mL, with a linear range from 10.0 to 83.8 ng/mL. Good correlation was observed between the results of GICA and standard Gas Chromatography-Tandem Mass Spectrometry (GC-MS/MS) in matrix and recovery test. The developed GICA can be used for rapid sample detection within 15 min, which is an excellent tool for screening PFF in foods and environmental samples.

MEDICAL-RELATED RISK FACTORS FOR AGE-RELATED MACULAR DEGENERATION AMONG PATIENTS ATTENDING EYE CARE CLINIC AT JINJA REGIONAL REFERRAL HOSPITAL. A CROSS-SECTIONAL STUDY.

Background: Patients with AIDS have an increased age-adjusted prevalence of intermediate-stage AMD compared with that found in a non-HIV-infected cohort evaluated with similar methods suggesting a potential risk that AIDs and other medical conditions could have towards Age-Related Macular Degeneration. The study aims to assess the medical-related risk factors for Age-Related Macular Degeneration. Methodology: A Cross-sectional descriptive study utilizing quantitative data collection methods. The study population comprised all patients receiving eye care services for Age-related Macular Degeneration conditions at the eye unit of Jinja Regional Referral Hospital for a period of 6 months from October 2022 to March 2023. Non-probability sampling was used to select 50 participants. Results: Half 25/50(50%) of the total number of respondents were between 61-70 years and the minority 02/50 (04 %) were 31-40 years. Most respondents 21/50 (42%) were peasants while 10/50 (20%) were Business personnel. The majority 18/50(36%) Strongly agreed that cataracts are a risk factor for Age-related Macular degeneration, followed by 17/50(34%) respondents who agreed. More respondents 39/50 (78%) indicated they had an intra-ocular surgery than 11/50(22%) respondents had not had an intra-ocular surgery. Most respondents 28/50 (56%) indicated they had a chronic disease while 22/50 (44%) respondents did not. A higher number of respondents 31/50(62%) were HIV Positive than 19/50(38%) who were found to be HIV negative. Conclusion: The medical-related risk factors for Age-related Macular Degeneration were having HIV/AIDs, chronic systemic diseases, Cataracts, and intra-ocular surgeries. Recommendations: Similarly, Health workers especially ophthalmologists and ophthalmic clinical officers should provide health education to the patients and the public and carry out regular outreach for eye vision screening.

The state of the biogeometric profile of the posture of young athletes specializing in hand-to-hand combat as a prerequisite for the development of corrective and preventive measures

Purpose: The purpose of the presented scientific research was, on the basis of somatoscopic indicators, to substantiate the biological prerequisites for the introduction of corrective and preventive measures into the educational and training process of young athletes specializing in hand-to-hand combat. Material and Methods: The scientific study involved 150 athletes specializing in hand-to-hand combat, aged 8–14 years. The problems identified during the study were solved using generally accepted methods: theoretical analysis of scientific literature on the chosen research topic; the Torso program was used to determine the types of posture, visual screening of the state of the biogeometric profile of the posture of young athletes specializing in hand-to-hand combat included a focus on the tribal system and the use of a method for comparing individual posture on a photogram and methods of mathematical statistics. Results: It has been established that poor posture of various types is common among athletes aged 8-14 years, specializing in hand-to-hand combat, covering a contingent of 46.7 to 60% in different age groups. Based on the results of screening the biogeometric profile of posture of an experimental contingent of young athletes specializing in hand-to-hand combat, a general tendency was traced to a decrease in the average values of the number of points at high and medium levels of the state of the biogeometric profile of posture of martial arts athletes with normal posture, and at low and medium levels - the state of the biogeometric profile of the posture of athletes with a stooped back, flat back, round back and scoliotic posture. In addition, a generalized examination of these results showed that some of the tested athletes who had a normal type of posture received the same scores (from 19 to 21 points) as those who had a certain type of posture disorder. We define the risk zone as the zone of overlap of assessments of the level of the biogeometric profile of posture, although theoretically it may appear wider if it is determined by values below the center of the distribution for athletes with normal posture. Since the distribution of all three indicators according to the test data in the group of athletes with normal posture and with various types of musculoskeletal disorders does not correspond to Gauss’s law, its center was determined by the median, which in this case was equal to 22 points. Conclusions: Understanding the findings and results of a wide range of scientific studies reveals the recent intensification of the dynamics of the occurrence of deviations in the state of posture of young athletes. Scientists are convinced that monitoring the state of athletes’ posture will make it possible to control the effect of physical exercise on the musculoskeletal system of young athletes and minimize the risk of injury. In the course of the study, the features of the biomechanics of posture of young athletes specializing in hand-to-hand combat were determined. Differences (at the level of trends) between athletes of all ages have been identified, which indicate a certain deterioration in the state of the biogeometric profile of posture with increasing age, but such differences have not received statistical confirmation. The theoretical and practical aspects of the scientific work presented above will be the basis for the theoretical substantiation of the biological prerequisites for the introduction of corrective and preventive measures into the educational and training process of young athletes specializing in hand-to-hand combat.

Seismic Damage Prediction and Classification tool: Utilizing Adaptive Neuro-Fuzzy Inference System (ANFIS) and Geographic Information System (GIS)

Seismic damage prediction of wide range of buildings is an important prioritization and classification tool for implementation of seismic risk and vulnerability assessment. This study has developed a rapid visual screening (RVS) tool using Adaptive Neuro-Fuzzy Inference System (ANFIS) model and Geographic Information System (GIS). Hospital an d public-school buildings located in districts 5 and 6 have been selected for assessment. Technical calculation basis in the development of FEMA P- 154 was followed in formulating the model using the neuro-fuzzy tool package in MATLAB. Six (6) building para meters and their resulting output (final score) were inputted for training. Sub-clustering FIS model showed the lowest RMSE and R2 result out of the five (5) FIS models compared. The model showed effective performance in classifying the buildings’ damage grades having 0.2908, 0.8073 and 0.948 for RMSE, and for testing and overall coefficient of determination (R2) values, respectively. Performance me trics from the developed confusion matrix showed high range of values for sensitivity, specificity, precision, and accuracy, with maximum error rate and false positive rate of 0.11 and 0.25, respectively, in classifying the buildings’ damage grade. These validate the model’s performance and ability in classifying the damage grade of the buildings observed. The results were used to develop a digital mapping of the damage grade distribution of the selected buildings in the area using ArcGIS.

Developing a machine learning-based rapid visual screening method for seismic assessment of existing buildings on a case study data from the 2015 Gorkha, Nepal earthquake

Developing a machine learning-based rapid visual screening method for seismic assessment of existing buildings on a case study data from the 2015 Gorkha, Nepal earthquake

Fourier-domain-compressed optical time-stretch quantitative phase imaging flow cytometry

Optical time-stretch (OTS) imaging flow cytometry offers a promising solution for high-throughput and high-precision cell analysis due to its capabilities of high-speed, high-quality, and continuous imaging. Compressed sensing (CS) makes it practically applicable by significantly reducing the data volume while maintaining its high-speed and high-quality imaging properties. To enrich the information of the images acquired with CS-equipped OTS imaging flow cytometry, in this work we propose and experimentally demonstrate Fourier-domain-compressed OTS quantitative phase imaging flow cytometry. It is capable of acquiring intensity and quantitative phase images of cells simultaneously from the compressed data. To evaluate the performance of our method, static microparticles and a corn root cross section are experimentally measured under various compression ratios. Furthermore, to show how our method can be applied in practice, we utilize it in the drug response analysis of breast cancer cells. Experimental results show that our method can acquire high-quality intensity and quantitative phase images of flowing cells at a flowing speed of 1 m/s and a compression ratio of 30%. Combined with machine-learning-based image analysis, it can distinguish drug-treated and drug-untreated cells with an accuracy of over 95%. We believe our method can facilitate cell analysis in both scientific research and clinical settings where both high-throughput and high-content cell analysis is required.

Ethical Considerations for Introducing School-Based Hearing and Vision Screening in the Pacific Islands: A Samoan Case Study.

Ethical Considerations for Introducing School-Based Hearing and Vision Screening in the Pacific Islands: A Samoan Case Study.

Identification of new correctors for traffic-defective ABCB4 variants by a high-content screening approach

ABCB4 is located at the canalicular membrane of hepatocytes and is responsible for the secretion of phosphatidylcholine into bile. Genetic variations of this transporter are correlated with rare cholestatic liver diseases, the most severe being progressive familial intrahepatic cholestasis type 3 (PFIC3). PFIC3 patients most often require liver transplantation. In this context of unmet medical need, we developed a high-content screening approach to identify small molecules able to correct ABCB4 molecular defects. Intracellularly-retained variants of ABCB4 were expressed in cell models and their maturation, cellular localization and function were analyzed after treatment with the molecules identified by high-content screening. In total, six hits were identified by high-content screening. Three of them were able to correct the maturation and canalicular localization of two distinct intracellularly-retained ABCB4 variants; one molecule was able to significantly restore the function of two ABCB4 variants. In addition, in silico molecular docking calculations suggest that the identified hits may interact with wild type ABCB4 residues involved in ATP binding/hydrolysis. Our results pave the way for their optimization in order to provide new drug candidates as potential alternative to liver transplantation for patients with severe forms of ABCB4-related diseases, including PFIC3.

Automated High Content Imaging and Analysis of Spheroids Using Clearing and Deep Learning for Volumetric Quantification

Automated High Content Imaging and Analysis of Spheroids Using Clearing and Deep Learning for Volumetric Quantification

An Omni-Mesoscope for multiscale high-throughput quantitative phase imaging of cellular dynamics and high-content molecular characterization.

The mesoscope has emerged as a powerful imaging tool in biomedical research, yet its high cost and low resolution have limited its broader application. Here, we introduce the Omni-Mesoscope, a cost-effective high-spatial-temporal, multimodal, and multiplex mesoscopic imaging platform built from cost-efficient off-the-shelf components. This system uniquely merges the capabilities of quantitative phase microscopy to capture live-cell dynamics over a large cell population with highly multiplexed fluorescence imaging for comprehensive molecular characterization. This integration facilitates simultaneous tracking of live-cell morphodynamics across thousands of cells, alongside high-content molecular analysis at the single-cell level. Furthermore, the Omni-Mesoscope offers a mesoscale field of view of approximately 5 mm 2 with a high spatial resolution down to 700 nm, enabling the capture of information-rich images with detailed sub-cellular features. We demonstrate such capability in delineating molecular characteristics underlying rare dynamic cellular phenomena, such as cancer cell responses to chemotherapy and the emergence of polyploidy in drug-resistant cells. Moreover, the cost-effectiveness and the simplicity of our Omni-Mesoscope democratizes mesoscopic imaging, making it accessible across diverse biomedical research fields. To further demonstrate its versatility, we integrate expansion microscopy to enhance 3D volumetric super-resolution imaging of thicker tissues, opening new avenues for biological exploration at unprecedented scales and resolutions.

Unsaturated fatty acid perturbation combats emerging triazole antifungal resistance in the human fungal pathogen Aspergillus fumigatus.

Contemporary antifungal therapies utilized to treat filamentous fungal infections are inhibited by intrinsic and emerging drug resistance. Consequently, there is an urgent need to develop novel antifungal compounds that are effective against drug-resistant filamentous fungi. Here, we utilized an Aspergillus fumigatus cell-based high-throughput screen to identify small molecules with antifungal activity that also potentiated triazole activity. The screen identified 16 hits with promising activity against A. fumigatus. A nonspirocyclic piperidine, herein named MBX-7591, exhibited synergy with triazole antifungal drugs and activity against pan-azole-resistant A. fumigatus isolates. MBX-7591 has additional potent activity against Rhizopus species and CO2-dependent activity against Cryptococcus neoformans. Chemical, genetic, and biochemical mode of action analyses revealed that MBX-7591 increases cell membrane saturation by decreasing oleic acid content. MBX-7591 has low toxicity in vivo and shows good efficacy in decreasing fungal burden in a murine model of invasive pulmonary aspergillosis. Taken together, our results suggest MBX-7591 is a promising hit with a novel mode of action for further antifungal drug development to combat the rising incidence of triazole-resistant filamentous fungal infections.IMPORTANCEThe incidence of infections caused by fungi continues to increase with advances in medical therapies. Unfortunately, antifungal drug development has not kept pace with the incidence and importance of fungal infections, with only three major classes of antifungal drugs currently available for use in the clinic. Filamentous fungi, also called molds, are particularly recalcitrant to contemporary antifungal therapies. Here, a recently developed Aspergillus fumigatus cell reporter strain was utilized to conduct a high-throughput screen to identify small molecules with antifungal activity. An emphasis was placed on small molecules that potentiated the activity of contemporary triazole antifungals and led to the discovery of MBX-7591. MBX-7591 potentiates triazole activity against drug-resistant molds such as A. fumigatus and has activity against Mucorales fungi. MBX-7591's mode of action involves inhibiting the conversion of saturated to unsaturated fatty acids, thereby impacting fungal membrane integrity. MBX-7591 is a novel small molecule with antifungal activity poised for lead development.

A Visual Acuity Assessment System Based on Static Gesture Recognition and Naive Bayes Classifier

Visual Acuity (VA) assessment is crucial for early vision screening, yet traditional methods are manual and time-consuming. Despite the advancements in human-computer interaction (HCI), there is no existing system fully addresses accuracy, efficiency and adaptability. This study introduces an intelligent VA assessment system that combines MediaPipe-based static gesture recognition with a novel Naive Bayes Classifier (NBC)-based VA Thresholds Determination (VATD) scheme. This integration offers a non-contact, user-friendly approach for rapid and precise VA testing. The VATD scheme is designed to significantly reduce the number of test trials; thereby, substantially improving the efficiency. Experimental validation confirms the system's high accuracy (96.72%) within a ±0.1 deviation from standard methods, achieves a 68% reduction in test time compared to traditional methods, and offers a 27% efficiency improvement over ANN-based systems. This system promises to enhance VA assessments, particularly for children and adolescents, with its speed, accuracy, and broader applicability.