Virtual-freezing fluorescence imaging flow cytometry with 5-aminolevulinic acid stimulation and antibody labeling for detecting all forms of circulating tumor cells.

Circulating tumor cells (CTCs) are precursors to cancer metastasis. In blood circulation, they take various forms such as single CTCs, CTC clusters, and CTC-leukocyte clusters, all of which have unique characteristics in terms of physiological function and have been a subject of extensive research in the last several years. Unfortunately, conventional methods are limited in accurately analysing the highly heterogeneous nature of CTCs. Here we present an effective strategy for simultaneously analysing all forms of CTCs in blood by virtual-freezing fluorescence imaging (VIFFI) flow cytometry with 5-aminolevulinic acid (5-ALA) stimulation and antibody labeling. VIFFI is an optomechanical imaging method that virtually freezes the motion of fast-flowing cells on an image sensor to enable high-throughput yet sensitive imaging of every single event. 5-ALA stimulates cancer cells to induce the accumulation of protoporphyrin (PpIX), a red fluorescent substance, making it possible to detect all cancer cells even if they show no expression of the epithelial cell adhesion molecule, a typical CTC biomarker. Although PpIX signals are generally weak, VIFFI flow cytometry can detect them by virtue of its high sensitivity. As a proof-of-principle demonstration of the strategy, we applied cancer cells spiked in blood to the strategy to demonstrate image-based detection and accurate classification of single cancer cells, clusters of cancer cells, and clusters of a cancer cell(s) and a leukocyte(s). To show the clinical utility of our method, we used it to evaluate blood samples of four breast cancer patients and four healthy donors and identified EpCAM-positive PpIX-positive cells in one of the patient samples. Our work paves the way toward the determination of cancer prognosis, the guidance and monitoring of treatment, and the design of antitumor strategies for cancer patients.

COVID-19 and Thrombosis: Clinical Aspects.

In coronavirus disease 2019 (COVID-19), thrombus formation is related to the pathogenesis of acute respiratory distress syndrome (ARDS) and the progression of clinical symptoms. Severe damage to vascular endothelial cells and the associated cytokine storm after SARS-CoV-2 infection cause thrombogenesis and contribute to the development of more severe and unique thromboses compared to other infectious diseases. Thromboses occur more often in critically ill patients. In addition to pulmonary thromboembolism (PE) and deep vein thrombosis, acute myocardial infarction, peripheral arterial thrombosis, and aortic thrombosis have also been reported. In PE, thrombi develop in both pulmonary arteries and alveolar capillaries. These, together with intraalveolar fibrin deposition, interfere with effective gaseous exchange in the lungs and exacerbate the clinical symptoms of ARDS in patients with COVID-19. Pharmacological thromboprophylaxis is recommended for all hospitalized patients to prevent both thrombosis and aggravation of ARDS, and other organ failures. Although the pediatric population is mostly asymptomatic or develops mild disease after SARS-CoV-2 infection, a new inflammatory disorder affecting the cardiovascular system, multisystem inflammatory syndrome in children (MIS-C), has been reported. Similar to Kawasaki disease, acute myocarditis, coronary vasculitis, and aneurysms are typically seen in MISC, although these two are now considered distinct entities. A similar acute myocarditis is also observed in young male adults, in which a hyperinflammatory state after SARS-CoV-2 infection seems to be involved. Several side effects following vaccination against COVID-19 have been reported, including vaccine-induced immune thrombotic thrombocytopenia and acute myocarditis. Although these could be serious and life-threatening, the cases are very rare, thus, the benefits of immunization still outweigh the risks.

Time of Day of Vaccination Does Not Associate With SARS-CoV-2 Antibody Titer Following First Dose of mRNA COVID-19 Vaccine.

The immune system exhibits circadian rhythms, and its response to viral infection is influenced by the circadian clock system. Previous studies have reported associations between the time of day of vaccination against COVID-19 and production of anti-SARS-CoV-2 antibody titer. We examined the effect of vaccination time of day on anti-SARS-CoV-2 antibody titer after the first dose of vaccination with the mRNA-1273 (Moderna) COVID-19 vaccine in an adult population. A total of 332 Japanese adults participated in the present study. All participants were not infected with SARS-CoV-2 and had already received the first dose of mRNA-1273 2 to 4 weeks prior to participating in the study. The participants were asked to provide basic demographic characteristics (age, sex, medical history, allergy, medication, and mean sleep duration), the number of days after the first dose of vaccination, and the time of day of vaccination. Blood was collected from the participants, and SARS-CoV-2 antibody titers were measured. Ordinary least square regression was used for assessing the relationship between basic demographic characteristics, number of days after vaccination, time of day of vaccination, and the log10-transformed normalized antibody titer. The least square mean of antibody titers was not associated with the vaccination time and sleep durations. The least square means of antibody titers was associated with age; the antibody titers decreased in people aged 50 to 59 years and 60 to 64 years. The present findings demonstrate that the vaccination time with mRNA-1273 was not associated with the SARS-CoV-2 antibody titer in an adult population, suggesting that these results do not support restricting vaccination to a particular time of day. The present findings may be useful in optimizing SARS-CoV-2 vaccination strategies.

[Thrombosis with Thrombocytopenia Syndrome after ChAdOx1 nCoV-19 vaccination].

A 48-year-old Japanese man who had no previous medical history received his first dose of the ChAdOx1 nCoV-19 vaccine. Ten days after the vaccine administration, he developed a headache. Laboratory results indicated throm-bocytopenia and DIC. A head CT revealed microbleeding in the left parietal lobe. Contrast-enhanced CT showed thrombus in the left transverse sinus and left sigmoid sinus. A brain MRI demonstrated venous hemorrhagic infarction and subarachnoid hemorrhages in the left parietal lobe, and whole-body enhanced CT also revealed portal vein embolism and renal infarction. He was diagnosed with thrombosis with thrombocytopenia syndrome, and was treated according to the guideline. He has been recovering with the treatments. This is the first reported case of TTS associated with the ChAdOx1 nCoV-19 vaccine in Japan.

[Novel disease entities due to antiplatelet factor 4 antibodies: HIT, aHIT, and VITT].

Antiplatelet factor 4 (PF4) antibodies, also known as anti-PF4/heparin complex antibodies, are measured to diagnose heparin-induced thrombocytopenia (HIT). In HIT, anti-PF4 antibodies induced by heparin exposure cause thrombocytopenia and thrombosis. However, in recent years, autoimmune HIT (aHIT) that develops without heparin exposure has been getting attention. In 2021, anti-PF4 antibodies were reported to cause the fatal vaccine-induced immune thrombotic thrombocytopenia (VITT) that developed after adenoviral vector vaccination for COVID-19. HIT, aHIT, and VITT are considered to be caused by anti-PF4 antibodies, and their pathological conditions are similar. However, they have different levels of severity, and the detection sensitivity of their antibodies varies depending on the assay. Herein, we review three pathologies, namely, HIT, aHIT, and VITT, associated with anti-PF4 antibodies.

Aleukemic Extramedullary Blast Crisis as an Initial Presentation of Chronic Myeloid Leukemia with E1A3 BCR-ABL1 Fusion Transcript.

Right neck swelling and pain occurred in a 49-year-old man. A Blood count showed a slight increase in platelet count without leukemoid reaction. After a biopsy of the cervical mass and bone marrow aspiration, a diagnosis of extramedullary blast crisis (EBC) of chronic myeloid leukemia (CML) was made. Fluorescence in situ hybridization (FISH) analysis showed a BCR-ABL1 fusion signal, but results of real-time polymerase chain reaction (RT-PCR) for major and minor BCR-ABL1 transcripts were negative. We identified a rare e1a3 BCR-ABL1 fusion transcript. Administration of dasatinib resulted in disappearance of the extramedullary tumor. This is the first reported case of CML-EBC with e1a3 transcript. An aleukemic extramedullary tumor can be the initial presentation of CML.

Intelligent Platelet Morphometry.

Technological advances in image-based platelet analysis or platelet morphometry are critical for a better understanding of the structure and function of platelets in biological research as well as for the development of better clinical strategies in medical practice. Recently, the advent of high-throughput optical imaging and deep learning has boosted platelet morphometry to the next level by providing a new set of capabilities beyond what is achievable with traditional platelet morphometry, shedding light on the unexplored domain of platelet analysis. This Opinion article introduces emerging opportunities in 'intelligent' platelet morphometry, which are expected to pave the way for a new class of diagnostics, pharmacometrics, and therapeutics.

High lymphocyte counts before antithymocyte globulin administration predict acute graft-versus-host disease.

Antithymocyte globulin (ATG) reduces severe acute and chronic graft-versus-host disease (GVHD) in allogeneic peripheral blood stem cell transplantation (PBSCT). However, risk factors for severe acute GVHD in PBSCT using ATG remain to be determined. We conducted a single-center, retrospective study to analyze the association of acute GVHD requiring systemic corticosteroid (SC-aGVHD) with absolute lymphocyte counts (ALC) before the administration of ATG or conditioning in 53 patients with HLA-matched PBSCT using low-dose thymoglobulin (2 mg/kg) after myeloablative conditioning. The cumulative incidence of SC-aGVHD was 17.0% and ALC before ATG were significantly higher in patients with SC-aGVHD compared to that in patients without it (median, 0.15 × 109/L vs 0.06 × 109/L, P = 0.047). The cumulative incidence of SC-aGVHD was significantly higher in patients with high ALC before ATG (≥ 0.15 × 109/L) than in those with low ALC (38.5% vs 10.0%, P = 0.016). Non-relapse mortality (NRM) was also significantly higher in the high ALC before ATG group than the low ALC before ATG group (2-year NRM: 23.9% vs 6.0%, P = 0.048), leading to worse survival (2-year overall survival: 69.2% vs 83.5%, P = 0.039). Our study suggested that high ALC before ATG is a risk factor for SC-aGVHD.

[Innovative activated platelet detection technology by artificial intelligence].

Although antiplatelet drugs are widely used for the prevention and treatment of atherothrombosis, clinical tests capable of evaluating their efficacy have not been established. Focusing on platelet aggregates in blood, we announced the world's first basic technology, an intelligent Image-Activated Cell Sorter (iIACS), that can exhaustively and rapidly identify cells one-by-one using image analysis with high-speed imaging and deep learning to sort specific cells according to the analysis results. This technology has even enabled the detection of single platelets with a size of 2 µm in blood samples and the quantification of the proportion of platelet aggregates by size. Furthermore, by applying this technique, we discovered different morphological features of platelet aggregates formed by different types of agonists that activate platelets. Here, we discuss this application in the early diagnosis of thrombotic microangiopathy (TMA). In the early stage of TMA, consumptive thrombocytopenia is caused by excessive platelet activation. Therefore, the detection of excessive platelet aggregates can lead to early TMA diagnosis.

Analysis of vasovagal syncope in the blood collection room in patients undergoing phlebotomy.

Vasovagal syncope (VVS) is well-known to occur in patients undergoing phlebotomy, however, there have been no large-scale studies of the incidence of VVS in the blood collection room. The aim of our present retrospective study was to investigate the conditions of phlebotomy and determine the incidence/factors predisposing to the development of VVS. We investigated 677,956 phlebotomies performed in outpatients in the blood collection room, to explore factors predisposing to the development of VVS. Our analysis revealed an overall incidence of VVS of 0.004% and suggested that use of more than 5 blood collection tubes and a waiting time of more than 15 min were associated with a higher risk of VVS. The odds ratios of these factors were 8.10 (95% CI 3.76-17.50) and 3.69 (95% CI 0.87-15.60), respectively. This is the large-scale study to analyze factors of the development of VVS in the blood collection room, and according to our results, use of a large number of blood collection tubes and a prolonged waiting time for phlebotomy may be risk factors for the development of VVS.

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.

Limitations of deuterium-labeled internal standards for quantitative electrospray ionization mass spectrometry analysis of fatty acid metabolites.

RATIONALE: The electrospray ionization mass spectrometry (ESI-MS) methodology often shows poor ionization reproducibility in the analysis of biological samples. Therefore, normalization of the measured peak intensities is essential. It is believed that quantitative data with high reproducibility can be obtained by adding a constant amount of an internal standard (IS) material labeled with stable isotopes to each sample, thus allowing the correction of the quantitative value of the target compound by that of the IS. We investigated whether the presence or absence of a labeled IS improves the accuracy of these quantitative values. METHODS: Triple quadrupole MS coupled with liquid chromatography was used to analyze fatty acid metabolites in biological samples as target compounds. Two independent systems were used to provide a measure of reproducibility in two different laboratories. RESULTS: Data having poor reproducibility in the raw peak areas were efficiently normalized using the IS, but, crucially, the IS method using stable isotopes was not always necessary. In some cases, the reproducibility was relatively good even without using the IS. In a contaminant matrix, the MS response behavior of the target compound and its stable isotope-labeled material was complicated. Since ion suppression by matrix contaminants was dependent on the concentration of the target compound, the added amounts of the ISs were also important, Furthermore, an equivalent normalization effect was obtained by using a pooled quality control sample as an external standard, thus obviating the need for labeled IS samples, which are often expensive and sometimes not commercially available. CONCLUSIONS: Our results raise the question as to whether the quantitative method using stable-isotope-labeled ISs is always necessary and beneficial. However, the results obtained in this study cannot be generalized because only fatty acid metabolites were examined using ESI-MS and only a highly substituted deuterium-labeled IS was used.

Establishment of a megakaryoblastic cell line for conventional assessment of platelet calcium signaling.

Platelet function tests utilizing agonists or patient serum are generally performed to assess platelet activation ex vivo. However, inter-individual differences in platelet reactivity and donor requirements make it difficult to standardize these tests. Here, we established a megakaryoblastic cell line for the conventional assessment of platelet activation. We first compared intracellular signaling pathways using CD32 crosslinking in several megakaryoblastic cell lines, including CMK, UT-7/TPO, and MEG-01 cells. We confirmed that CD32 was abundantly expressed on the cell surface, and that intracellular calcium mobilization and tyrosine phosphorylation occurred after CD32 crosslinking. We next employed GCaMP6s, a highly sensitive calcium indicator, to facilitate the detection of calcium mobilization by transducing CMK and MEG-01 cells with a plasmid harboring GCaMP6s under the control of the human elongation factor-1α promoter. Cells that stably expressed GCaMP6s emitted enhanced green fluorescent protein fluorescence in response to intracellular calcium mobilization following agonist stimulation in the absence of pretreatment. In summary, we have established megakaryoblastic cell lines that mimic platelets by mobilizing intracellular calcium in response to several agonists. These cell lines can potentially be utilized in high-throughput screening assays for the discovery of new antiplatelet drugs or diagnosis of disorders caused by platelet-activating substances.

Intelligent frequency-shifted optofluidic time-stretch quantitative phase imaging.

Optofluidic time-stretch quantitative phase imaging (OTS-QPI) is a powerful tool as it enables high-throughput (>10,000 cell/s) QPI of single live cells. OTS-QPI is based on decoding temporally stretched spectral interferograms that carry the spatial profiles of cells flowing on a microfluidic chip. However, the utility of OTS-QPI is troubled by difficulties in phase retrieval from the high-frequency region of the temporal interferograms, such as phase-unwrapping errors, high instrumentation cost, and large data volume. To overcome these difficulties, we propose and experimentally demonstrate frequency-shifted OTS-QPI by bringing the phase information to the baseband region. Furthermore, to show its boosted utility, we use it to demonstrate image-based classification of leukemia cells with high accuracy over 96% and evaluation of drug-treated leukemia cells via deep learning.

The role of anti-complement factor H antibodies in the development of atypical haemolytic uremic syndrome: a possible contribution to abnormality of platelet function.

Atypical haemolytic uremic syndrome (aHUS) is associated with complement system abnormality, such as production of complement factor H (CFH) autoantibodies. The growing evidence indicates complement overactivation on platelets is intimately involved in aHUS pathogenesis, besides endothelial injury. We here showed plasma from patients with anti-CFH antibodies induced aggregation of washed platelets, while purified anti-CFH antibodies suppressed aggregation. This suggested anti-CFH antibody itself suppressed thrombosis, while other plasma factor including complement factors could overactivate the platelets, leading to aggregation, which augmented the notion the state of complement activation influenced by anti-CFH antibodies is important in the aggregation of platelets in aHUS.

Profiles of Coagulation and Fibrinolysis Activation-Associated Molecular Markers of Atypical Hemolytic Uremic Syndrome in the Acute Phase.

AIM: Atypical hemolytic uremic syndrome (aHUS), characterized by thrombotic microangiopathy (TMA), is a genetic, life-threatening disease which needs many differential diagnoses. This study aimed to reveal coagulation and fibrinolysis profiles in aHUS and secondary TMA patients. Furthermore, we investigated whether aHUS patients progress to, and meet, disseminated intravascular coagulation (DIC) criteria. METHODS: The acute phase samples were available in 15 aHUS and 20 secondary TMA patients. We measured PT-ratio, activated partial thromboplastin time (APTT), fibrinogen, fibrin degradation product (FDP), fibrin monomer complex (FMC), antithrombin (AT), plasmin-α2 plasmin inhibitor complex (PIC), and von Willebrand factor antigen (VWF:Ag). We examined and compared these tests among aHUS, secondary TMA patients, and healthy volunteer (HV), and evaluated whether patients with aHUS and secondary TMA met DIC criteria. RESULTS: PT-ratio, APTT, FDP, FMC and PIC in patients with aHUS and secondary TMA were higher than those in HV. Fibrinogen and AT showed no significant difference among three groups. VWF:Ag was higher in only aHUS patients. No tests showed significant difference between aHUS and secondary TMA patients. Three aHUS patients out of 15 met DIC criteria. CONCLUSION: We revealed the profiles and distributions of coagulation and fibrinolysis tests of aHUS and secondary TMA patients. All tests were enhanced compared to HV; however, our results showed the no specificities in distinguishing aHUS from secondary TMA patients. We also clarified that some aHUS patients fulfilled DIC diagnostic criteria, indicating that DIC itself cannot be an exclusion criterion of aHUS.