Long-term effects of Pfizer-BioNTech COVID-19 vaccinations on platelets.

There is a global concern about the safety of COVID-19 vaccines associated with platelet function. However, their long-term effects on overall platelet activity remain poorly understood. Here we address this problem by image-based single-cell profiling and temporal monitoring of circulating platelet aggregates in the blood of healthy human subjects, before and after they received multiple Pfizer-BioNTech (BNT162b2) vaccine doses over a time span of nearly 1 year. Results show no significant or persisting platelet aggregation trends following the vaccine doses, indicating that any effects of vaccinations on platelet turnover, platelet activation, platelet aggregation, and platelet-leukocyte interaction was insignificant.

Real-time intelligent classification of COVID-19 and thrombosis via massive image-based analysis of platelet aggregates.

Microvascular thrombosis is a typical symptom of COVID-19 and shows similarities to thrombosis. Using a microfluidic imaging flow cytometer, we measured the blood of 181 COVID-19 samples and 101 non-COVID-19 thrombosis samples, resulting in a total of 6.3 million bright-field images. We trained a convolutional neural network to distinguish single platelets, platelet aggregates, and white blood cells and performed classical image analysis for each subpopulation individually. Based on derived single-cell features for each population, we trained machine learning models for classification between COVID-19 and non-COVID-19 thrombosis, resulting in a patient testing accuracy of 75%. This result indicates that platelet formation differs between COVID-19 and non-COVID-19 thrombosis. All analysis steps were optimized for efficiency and implemented in an easy-to-use plugin for the image viewer napari, allowing the entire analysis to be performed within seconds on mid-range computers, which could be used for real-time diagnosis.

Dynamic modulations of urinary sphingolipid and glycerophospholipid levels in COVID-19 and correlations with COVID-19-associated kidney injuries.

BACKGROUND: Among various complications of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), renal complications, namely COVID-19-associated kidney injuries, are related to the mortality of COVID-19. METHODS: In this retrospective cross-sectional study, we measured the sphingolipids and glycerophospholipids, which have been shown to possess potent biological properties, using liquid chromatography-mass spectrometry in 272 urine samples collected longitudinally from 91 COVID-19 subjects and 95 control subjects without infectious diseases, to elucidate the pathogenesis of COVID-19-associated kidney injuries. RESULTS: The urinary levels of C18:0, C18:1, C22:0, and C24:0 ceramides, sphingosine, dihydrosphingosine, phosphatidylcholine, lysophosphatidylcholine, lysophosphatidic acid, and phosphatidylglycerol decreased, while those of phosphatidylserine, lysophosphatidylserine, phosphatidylethanolamine, and lysophosphatidylethanolamine increased in patients with mild COVID-19, especially during the early phase (day 1-3), suggesting that these modulations might reflect the direct effects of infection with SARS-CoV-2. Generally, the urinary levels of sphingomyelin, ceramides, sphingosine, dihydrosphingosine, dihydrosphingosine L-phosphate, phosphatidylcholine, lysophosphatidic acid, phosphatidylserine, lysophosphatidylserine, phosphatidylethanolamine, lysophosphatidylethanolamine, phosphatidylglycerol, lysophosphatidylglycerol, phosphatidylinositol, and lysophosphatidylinositol increased, especially in patients with severe COVID-19 during the later phase, suggesting that their modulations might result from kidney injuries accompanying severe COVID-19. CONCLUSIONS: Considering the biological properties of sphingolipids and glycerophospholipids, an understanding of their urinary modulations in COVID-19 will help us to understand the mechanisms causing COVID-19-associated kidney injuries as well as general acute kidney injuries and may prompt researchers to develop laboratory tests for predicting maximum severity and/or novel reagents to suppress the renal complications of COVID-19.

Decrease in serum levels of autotaxin in COVID-19 patients.

INTRODUCTION: In order to identify therapeutic targets in Coronavirus disease 2019 (COVID-19), it is important to identify molecules involved in the biological responses that are modulated in COVID-19. Lysophosphatidic acids (LPAs) are involved in the pulmonary inflammation and fibrosis are one of the candidate molecules. The aim of this study was to evaluate the association between the serum levels of autotaxin (ATX), which are enzymes involved in the synthesis of lysophosphatidic acids. MATERIAL AND METHODS: We enrolled 134 subjects with COVID-19 and 58 normal healthy subjects for the study. We measured serum ATX levels longitudinally in COVID-19 patients and investigated the time course and the association with severity and clinical parameters. RESULTS: The serum ATX levels were reduced in all patients with COVID-19, irrespective of the disease severity, and were negatively associated with the serum CRP, D-dimer, and anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody levels. DISCUSSION: Considering the biological properties of LPAs in the pulmonary inflammation and fibrosis, modulation of ATX might be compensatory biological responses to suppress immunological overreaction especially in the lung, which is an important underlying mechanism for the mortality of the disease. CONCLUSIONS: COVID-19 patients showed a decrease in the serum levels of ATX, irrespective of the disease severity. Key MessagesAutotaxin (ATX) is an enzyme involved in the synthesis of lysophosphatidic acid (LPA), which has been reported to be involved in pulmonary inflammation and fibrosis. Patients with COVID-19 show decrease in the serum levels of ATX. Modulation of ATX might be compensatory biological responses to suppress immunological overreaction.

Dynamic modulations of sphingolipids and glycerophospholipids in COVID-19.

BACKGROUND: A heterogeneous clinical phenotype is a characteristic of coronavirus disease 2019 (COVID-19). Therefore, investigating biomarkers associated with disease severity is important for understanding the mechanisms responsible for this heterogeneity and for developing novel agents to prevent critical conditions. This study aimed to elucidate the modulations of sphingolipids and glycerophospholipids, which have been shown to possess potent biological properties. METHODS: We measured the serum sphingolipid and glycerophospholipid levels in a total of 887 samples from 215 COVID-19 subjects, plus 115 control subjects without infectious diseases and 109 subjects with infectious diseases other than COVID-19. RESULTS: We observed the dynamic modulations of sphingolipids and glycerophospholipids in the serum of COVID-19 subjects, depending on the time course and severity. The elevation of C16:0 ceramide and lysophosphatidylinositol and decreases in C18:1 ceramide, dihydrosphingosine, lysophosphatidylglycerol, phosphatidylglycerol and phosphatidylinositol were specific to COVID-19. Regarding the association with maximum severity, phosphatidylinositol and phosphatidylcholine species with long unsaturated acyl chains were negatively associated, while lysophosphatidylethanolamine and phosphatidylethanolamine were positively associated with maximum severity during the early phase. Lysophosphatidylcholine and phosphatidylcholine had strong negative correlations with CRP, while phosphatidylethanolamine had strong positive ones. C16:0 ceramide, lysophosphatidylcholine, phosphatidylcholine and phosphatidylethanolamine species with long unsaturated acyl chains had negative correlations with D-dimer, while phosphatidylethanolamine species with short acyl chains and phosphatidylinositol had positive ones. Several species of phosphatidylcholine, phosphatidylethanolamine and sphingomyelin might serve as better biomarkers for predicting severe COVID-19 during the early phase than CRP and D-dimer. Compared with the lipid modulations seen in mice treated with lipopolysaccharide, tissue factor, or histone, the lipid modulations observed in severe COVID-19 were most akin to those in mice administered lipopolysaccharide. CONCLUSION: A better understanding of the disturbances in sphingolipids and glycerophospholipids observed in this study will prompt further investigation to develop laboratory testing for predicting maximum severity and/or novel agents to suppress the aggravation of COVID-19.

Urine sediment findings were milder in patients with COVID-19-associated renal injuries than in those with non-COVID-19-associated renal injuries.

BACKGROUND: Acute renal injury is an important complication of coronavirus disease 2019 (COVID-19). Both COVID-19-specific mechanisms, such as damage to the renal parenchyma by direct infection, and non-specific mechanisms, such as the pre-renal injury factors, have been proposed to be involved in COVID-19-associated renal injuries. In this study, we aimed to elucidate the characteristics of COVID-19-associated renal injuries, focusing mainly on urine sediment findings. METHODS: We compared the urine sediment findings and their associations with renal functions or urinary clinical parameters between subjects with COVID-19 and subjects without COVID-19 with acute renal injuries. RESULTS: We found that the number of urine sediment particles and the levels of N-acetyl-ß-D-glucosaminidase, α1-microglobulin, liver type fatty acid-binding protein, and neutrophil gelatinase-associated lipocalin were associated with the severity of COVID-19. In addition, we observed that the number of granular casts, epithelial casts, waxy casts, and urinary chemical marker levels were lower in the subjects with COVID-19 than subjects without COVID-19 with acute renal injuries when the subjects were classified according to their renal function. CONCLUSIONS: These results suggest that pre-renal injury factors might be largely involved in the pathogenesis of COVID-19-associated renal injuries compared with non-COVID-19-associated renal injuries arising from surgery or sepsis.

Measurement of SARS-CoV-2 Antibody Titers Improves the Prediction Accuracy of COVID-19 Maximum Severity by Machine Learning in Non-Vaccinated Patients.

Numerous studies have suggested that the titers of antibodies against SARS-CoV-2 are associated with the COVID-19 severity, however, the types of antibodies associated with the disease maximum severity and the timing at which the associations are best observed, especially within one week after symptom onset, remain controversial. We attempted to elucidate the antibody responses against SARS-CoV-2 that are associated with the maximum severity of COVID-19 in the early phase of the disease, and to investigate whether antibody testing might contribute to prediction of the disease maximum severity in COVID-19 patients. We classified the patients into four groups according to the disease maximum severity (severity group 1 (did not require oxygen supplementation), severity group 2a (required oxygen supplementation at low flow rates), severity group 2b (required oxygen supplementation at relatively high flow rates), and severity group 3 (required mechanical ventilatory support)), and serially measured the titers of IgM, IgG, and IgA against the nucleocapsid protein, spike protein, and receptor-binding domain of SARS-CoV-2 until day 12 after symptom onset. The titers of all the measured antibody responses were higher in severity group 2b and 3, especially severity group 2b, as early as at one week after symptom onset. Addition of data obtained from antibody testing improved the ability of analysis models constructed using a machine learning technique to distinguish severity group 2b and 3 from severity group 1 and 2a. These models constructed with non-vaccinated COVID-19 patients could not be applied to the cases of breakthrough infections. These results suggest that antibody testing might help physicians identify non-vaccinated COVID-19 patients who are likely to require admission to an intensive care unit.

Association of the Serum Levels of the Nucleocapsid Antigen of SARS-CoV-2 With the Diagnosis, Disease Severity, and Antibody Titers in Patients With COVID-19: A Retrospective Cross-Sectional Study.

Background: Several types of laboratory tests for COVID-19 have been established to date; however, the clinical significance of the serum SARS-CoV-2 nucleocapsid (N) antigen levels remains to be fully elucidated. In the present study, we attempted to elucidate the usefulness and clinical significance of the serum N antigen levels. Methods: We measured the serum N antigen levels in 391 serum samples collected from symptomatic patients with a confirmed diagnosis of COVID-19 and 96 serum samples collected from patients with non-COVID-19, using a fully automated chemiluminescence immunoassay analyzer. Results: Receiver operating characteristic analysis identified the optimal cutoff value of the serum N antigen level (cutoff index, based on Youden's index) as 0.255, which yielded a sensitivity and specificity for the diagnosis of COVID-19 of 91.0 and 81.3%, respectively. The serum N antigen levels were significantly higher in the patient groups with moderate and severe COVID-19 than with mild disease. Moreover, a significant negative correlation was observed between the serum N antigen levels and the SARS-CoV-2 IgG antibody titers, especially in patients with severe COVID-19. Conclusion: Serum N antigen testing might be useful both for the diagnosis of COVID-19 and for obtaining a better understanding of the clinical features of the disease.

Response kinetics of different classes of antibodies to SARS-CoV2 infection in the Japanese population: The IgA and IgG titers increased earlier than the IgM titers.

To better understand the immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in individuals with COVID-19, it is important to investigate the kinetics of the antibody responses and their associations with the clinical course in different populations, since there seem to be considerable differences between Western and Asian populations in the clinical features and spread of COVID-19. In this study, we serially measured the serum titers of IgM, IgG and IgA antibodies generated against the nucleocapsid protein (NCP), S1 subunit of the spike protein (S1), and receptor-binding domain in the S1 subunit (RBD) of SARS-CoV-2 in Japanese individuals with COVID-19. Among the IgM, IgG, and IgA antibodies, IgA antibodies against all of the aforementioned viral proteins were the first to appear after the infection, and IgG and/or IgA seroconversion often preceded IgM seroconversion. In regard to the timeline of the antibody responses to the different viral proteins (NCP, S1 and RBD), IgA against NCP appeared than IgA against S1 or RBD, while IgM and IgG against S1 appeared earlier than IgM/IgG against NCP or RBD. The IgG responses to all three viral proteins and responses of all three antibody classes to S1 and RBD were sustained for longer durations than the IgA/IgM responses to all three viral proteins and responses of all three antibody classes to NCP, respectively. The seroconversion of IgA against NCP occurred later and less frequently in patients with mild COVID-19. These results suggest possible differences in the antibody responses to SARS-CoV-2 antigens between the Japanese and Western populations.

Massive image-based single-cell profiling reveals high levels of circulating platelet aggregates in patients with COVID-19.

A characteristic clinical feature of COVID-19 is the frequent incidence of microvascular thrombosis. In fact, COVID-19 autopsy reports have shown widespread thrombotic microangiopathy characterized by extensive diffuse microthrombi within peripheral capillaries and arterioles in lungs, hearts, and other organs, resulting in multiorgan failure. However, the underlying process of COVID-19-associated microvascular thrombosis remains elusive due to the lack of tools to statistically examine platelet aggregation (i.e., the initiation of microthrombus formation) in detail. Here we report the landscape of circulating platelet aggregates in COVID-19 obtained by massive single-cell image-based profiling and temporal monitoring of the blood of COVID-19 patients (n = 110). Surprisingly, our analysis of the big image data shows the anomalous presence of excessive platelet aggregates in nearly 90% of all COVID-19 patients. Furthermore, results indicate strong links between the concentration of platelet aggregates and the severity, mortality, respiratory condition, and vascular endothelial dysfunction level of COVID-19 patients.

Interpretations of SARS-CoV-2 IgM and IgG antibody titers in the seroepidemiological study of asymptomatic healthy volunteers.

INTRODUCTION: The usefulness of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests in asymptomatic individuals has not been well validated, although they have satisfied sensitivity and specificity in symptomatic patients. In this study, we investigated the significance of IgM and IgG antibody titers against SARS-CoV-2 in the serum of asymptomatic healthy subjects. METHODS: From June 2020, we recruited 10,039 participants to the project named the University of Tokyo COVID-19 Antibody Titer Survey (UT-CATS), and measured iFlash-SARS-CoV-2 IgM and IgG (YHLO IgM and IgG) titers in the collected serum. For the samples with increased IgM or IgG titers, we performed additional measurements using Elecsys Anti-SARS-CoV-2 Ig (Roche total Ig) and Architect SARS-CoV-2 IgG (Abbott IgG) and investigated the reactivity to N, S1, and receptor binding domain (RBD) proteins. RESULTS: After setting the cutoff value at 5 AU/mL, 61 (0.61%) were positive for YHLO IgM and 104 (1.04%) for YHLO IgG. Few samples with elevated YHLO IgM showed reactivity to S1 or RBD proteins, and IgG titers did not increase during the follow-up in any samples. The samples with elevated YHLO IgG consisted of two groups: one reacted to S1 or RBD proteins and the other did not, which was reflected in the results of Roche total Ig. CONCLUSIONS: In SARS-CoV-2 seroepidemiological studies of asymptomatic participants, sufficient attention should be given to the interpretation of the results of YHLO IgM and IgG, and the combined use of YHLO IgG and Roche total Ig might be more reliable.

Epidemiological study using IgM and IgG antibody titers against SARS-CoV-2 in The University of Tokyo, Japan (UT-CATS).

INTRODUCTION: The worldwide pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued to date. Given that some of the patients with coronavirus disease 2019 (COVID-19) are asymptomatic, antibody tests are useful to determine whether there is a previous infection with SARS-CoV-2. In this study, we measured IgM and IgG antibody titers against SARS-CoV-2 in the serum of asymptomatic healthy subjects in The University of Tokyo, Japan. METHODS: From June 2020, we recruited participants, who were students, staff, and faculty members of The University of Tokyo in the project named The University of Tokyo COVID-19 Antibody Titer Survey (UT-CATS). Following blood sample collection, participants were required to answer an online questionnaire about their social and health information. We measured IgG and IgM titers against SARS-CoV-2 using iFlash-SARS-CoV-2 IgM and IgG detection kit which applies a chemiluminescent immunoassay (CLIA) for the qualitative detection. RESULTS: There were 6609 volunteers in this study. After setting the cutoff value at 10 AU/mL, 32 (0.48%) were positive for IgG and 16 (0.24%) for IgM. Of six participants with a history of COVID-19, five were positive for IgG, whereas all were negative for IgM. The median titer of IgG was 0.40 AU/mL and 0.39 AU/mL for IgM. Both IgG and IgM titers were affected by gender, age, smoking status, and comorbidities. CONCLUSIONS: Positive rates of IgG and IgM titers were relatively low in our university. Serum levels of these antibodies were affected by several factors, which might affect the clinical course of COVID-19.

Clot waveform of APTT has abnormal patterns in subjects with COVID-19.

In Coronavirus disease 2019 (COVID-19) subjects, recent evidence suggests the presence of unique coagulation abnormalities. In this study, we performed clot waveform analyses to investigate whether specific modulations are observed in COVID-19 subjects. We analyzed the second derivative of the absorbance in routine APTT tests performed using an ACL-TOP system. We observed high frequencies of abnormal patterns in APTT second-derivative curves that could be classified into an early shoulder type, a late shoulder type, or a biphasic type, high maximum first-derivative and second-derivative peak levels, and a low minimum second-derivative peak level in COVID-19 subjects. These modulations were not observed in subjects with disseminated intravascular coagulation. These abnormal patterns are also observed in patients with lupus anticoagulant, hemophilia, or factor IX deficiency. The plasma fibrinogen levels might also be involved in the abnormal APTT waveforms, especially the high maximum first-derivative and second-derivative peak levels. The abnormal patterns in the APTT second-derivative curves appear with highest frequency at around 2 weeks after the onset of COVID-19 and were not associated with the severity of COVID-19. These results suggest the possible presence of a specific abnormal coagulopathy in COVID-19.

Validation of a new automated chemiluminescent anti-SARS-CoV-2 IgM and IgG antibody assay system detecting both N and S proteins in Japan.

PCR methods are presently the standard for the diagnosis of Coronavirus disease 2019 (COVID-19), but additional methodologies are needed to complement PCR methods, which have some limitations. Here, we validated and investigated the usefulness of measuring serum antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using the iFlash3000 CLIA analyzer. We measured IgM and IgG titers against SARS-CoV-2 in sera collected from 26 PCR-positive COVID-19 patients, 53 COVID-19-suspected but PCR-negative patients, and 20 and 100 randomly selected non-COVID-19 patients who visited our hospital in 2020 and 2017, respectively. The repeatability and within-laboratory precision were obviously good in validations, following to the CLSI document EP15-A3. Linearity was also considered good between 0.6 AU/mL and 112.7 AU/mL for SARS-CoV-2 IgM and between 3.2 AU/mL and 55.3 AU/mL for SARS-CoV-2 IgG, while the linearity curves plateaued above the upper measurement range. We also confirmed that the seroconversion and no-antibody titers were over the cutoff values in all 100 serum samples collected in 2017. These results indicate that this measurement system successfully detects SARS-CoV-2 IgM/IgG. We observed four false-positive cases in the IgM assay and no false-positive cases in the IgG assay when 111 serum samples known to contain autoantibodies were evaluated. The concordance rates of the antibody test with the PCR test were 98.1% for SARS-CoV-2 IgM and 100% for IgG among PCR-negative cases and 30.8% for SARS-CoV-2 IgM and 73.1% for SARS-CoV-2 IgG among PCR-positive cases. In conclusion, the performance of this new automated method for detecting antibody against both N and S proteins of SARS-CoV-2 is sufficient for use in laboratory testing.

Time course of the sensitivity and specificity of anti-SARS-CoV-2 IgM and IgG antibodies for symptomatic COVID-19 in Japan.

The accurate and prompt diagnosis of SARS-CoV-2 infection is required for the control and treatment of the coronavirus infection disease 2019 (COVID-19). In this study, we aimed to investigate the time courses of the anti-severe acute corona respiratory syndrome coronavirus 2 (SARS-CoV-2) IgM and IgG titers and to evaluate the sensitivity and specificity of such tests according to the specific day after the onset of COVID-19 among a patient population in Japan. We measured the titers of SARS-CoV-2 IgM and IgG in sera from 105 subjects, including 26 symptomatic COVID-19 patients, using chemiluminescent immunoassay (CLIA) methods utilizing magnetic beads coated with SARS-CoV-2 nucleocapsid protein and spike protein. The results of a ROC analysis suggested the possibility that the cutoff values in Japan might be lower than the manufacturer's reported cutoff (10 AU/mL): 1  AU/mL for IgM and 5  AU/mL for IgG. The sensitivity of the test before Day 8 after symptom onset was less than 50%; at Days 9-10, however, we obtained a much higher sensitivity of 81.8% for both IgM and IgG. At 15 days or later after symptom onset, the SARS-CoV-2 IgG test had a sensitivity of 100%. These results suggest that if the number of days since disease onset is taken into consideration, these antibody tests could be very useful for the diagnosis of COVID-19 and similar diseases.

Dynamic changes in fibrinogen and D-dimer levels in COVID-19 patients on nafamostat mesylate.

Critical illnesses associated with coronavirus disease 2019 (COVID-19) are attributable to a hypercoagulable status. There is limited knowledge regarding the dynamic changes in coagulation factors among COVID-19 patients on nafamostat mesylate, a potential therapeutic anticoagulant for COVID-19. First, we retrospectively conducted a cluster analysis based on clinical characteristics on admission to identify latent subgroups among fifteen patients with COVID-19 on nafamostat mesylate at the University of Tokyo Hospital, Japan, between April 6 and May 31, 2020. Next, we delineated the characteristics of all patients as well as COVID-19-patient subgroups and compared dynamic changes in coagulation factors among each subgroup. The subsequent dynamic changes in fibrinogen and D-dimer levels were presented graphically. All COVID-19 patients　were classified into three subgroups: clusters A, B, and C, representing low, intermediate, and high risk of poor outcomes, respectively. All patients were alive 30 days from symptom onset. No patient in cluster A required mechanical ventilation; however, all patients in cluster C required mechanical ventilation, and half of them were treated with venovenous extracorporeal membrane oxygenation. All patients in cluster A maintained low D-dimer levels, but some critical patients in clusters B and C showed dynamic changes in fibrinogen and D-dimer levels. Although the potential of nafamostat mesylate needs to be evaluated in randomized clinical trials, admission characteristics of patients with COVID-19 could predict subsequent coagulopathy.

Intelligent classification of platelet aggregates by agonist type.

Platelets are anucleate cells in blood whose principal function is to stop bleeding by forming aggregates for hemostatic reactions. In addition to their participation in physiological hemostasis, platelet aggregates are also involved in pathological thrombosis and play an important role in inflammation, atherosclerosis, and cancer metastasis. The aggregation of platelets is elicited by various agonists, but these platelet aggregates have long been considered indistinguishable and impossible to classify. Here we present an intelligent method for classifying them by agonist type. It is based on a convolutional neural network trained by high-throughput imaging flow cytometry of blood cells to identify and differentiate subtle yet appreciable morphological features of platelet aggregates activated by different types of agonists. The method is a powerful tool for studying the underlying mechanism of platelet aggregation and is expected to open a window on an entirely new class of clinical diagnostics, pharmacometrics, and therapeutics.

Platelets are small cells in the blood that primarily help stop bleeding after an injury by sticking together with other blood cells to form a clot that seals the broken blood vessel. Blood clots, however, can sometimes cause harm. For example, if a clot blocks the blood flow to the heart or the brain, it can result in a heart attack or stroke, respectively. Blood clots have also been linked to harmful inflammation and the spread of cancer, and there are now preliminary reports of remarkably high rates of clotting in COVID-19 patients in intensive care units. A variety of chemicals can cause platelets to stick together. It has long been assumed that it would be impossible to tell apart the clots formed by different chemicals (which are also known as agonists). This is largely because these aggregates all look very similar under a microscope, making it incredibly time consuming for someone to look at enough microscopy images to reliably identify the subtle differences between them. However, finding a way to distinguish the different types of platelet aggregates could lead to better ways to diagnose or treat blood vessel-clogging diseases. To make this possible, Zhou, Yasumoto et al. have developed a method called the "intelligent platelet aggregate classifier" or iPAC for short. First, numerous clot-causing chemicals were added to separate samples of platelets taken from healthy human blood. The method then involved using high-throughput techniques to take thousands of images of these samples. Then, a sophisticated computer algorithm called a deep learning model analyzed the resulting image dataset and "learned" to distinguish the chemical causes of the platelet aggregates based on subtle differences in their shapes. Finally, Zhou, Yasumoto et al. verified iPAC method's accuracy using a new set of human platelet samples. The iPAC method may help scientists studying the steps that lead to clot formation. It may also help clinicians distinguish which clot-causing chemical led to a patient's heart attack or stroke. This could help them choose whether aspirin or another anti-platelet drug would be the best treatment. But first more studies are needed to confirm whether this method is a useful tool for drug selection or diagnosis.