4CMenB Vaccination to Prevent Meningococcal B Disease in Vietnam: Expert Review and Opinion.

An advisory board meeting was held with experts in Vietnam (Hanoi, August 2022), to review the evidence on invasive meningococcal disease (IMD) epidemiology, clinical management, and meningococcal vaccines to reach a consensus on recommendations for meningococcal vaccination in Vietnam. IMD is a severe disease, with the highest burden in infants and children. IMD presents as meningitis and/or meningococcemia and can progress extremely rapidly. Almost 90% of deaths in children occur within the first 24 h, and disabling sequelae (e.g., limb amputations and neurological damage) occur in up to 20% of survivors. IMD patients are often hospitalized late, due to mild and nonspecific early symptoms and misdiagnosis. Difficulties related to diagnosis and antibiotic misuse mean that the number of reported IMD cases in Vietnam is likely to be underestimated. Serogroup B IMD is predominant in many regions of the world, including Vietnam, where 82% of IMD cases were due to serogroup B (surveillance data from 2012 to 2021). Four component meningococcal B vaccine (4CMenB) is used in many countries (and is part of the pediatric National Immunization Program in 13 countries), with infant vaccination starting from two months of age, and a 2 + 1 dosing schedule. Experts recommend 4CMenB vaccination as soon as possible in Vietnam, starting from two months of age, with a 2 + 1 dosing schedule, and at least completing one dose before 6 months of age.

Prevalence of and risk factors for sarcopenia in community-dwelling people: The Vietnam Osteoporosis Study.

BACKGROUND: Sarcopenia is a geriatric disease characterized by the progressive and generalized loss of skeletal lean mass and strength with age. The prevalence of sarcopenia in the Vietnamese population is unknown. This study sought to estimate the prevalence of and risk factors for sarcopenia among community-dwelling individuals in Vietnam. METHODS: This cross-sectional study is part of the ongoing Vietnam Osteoporosis Study project. The study involved 1308 women and 591 men aged 50 years and older as at 2015 (study entry). Whole-body dual-energy X-ray absorptiometry was used to measure the appendicular skeletal lean mass. Anthropometric and clinical data were collected using a structured questionnaire. Sarcopenia was defined according to the criteria proposed by the Asian Working Group for Sarcopenia in 2019. Logistic regression analysis was used to determine the association between potential risk factors and sarcopenia. RESULTS: The prevalence of sarcopenia in women and men was 14% (n = 183) and 16% (n = 83), respectively. Age (odds ratio [OR] per 10 years = 1.37; 95% confidence interval [CI] 1.26-1.48) and being underweight (OR = 1.61; 95% CI 1.00-2.58) were independently associated with increased risk of sarcopenia. The combination of low physical activity, being underweight and advancing age accounted for ~27% of sarcopenic patients. However, most of the attributable fraction was due to ageing. CONCLUSIONS: Sarcopenia is common in community-dwelling Vietnamese adults, particularly those with advancing age, who are underweight and with low physical activity.

Deductive automated pollen classification in environmental samples via exploratory deep learning and imaging flow cytometry.

Pollen and tracheophyte spores are ubiquitous environmental indicators at local and global scales. Palynology is typically performed manually by microscopic analysis; a specialised and time-consuming task limited in taxonomical precision and sampling frequency, therefore restricting data quality used to inform climate change and pollen forecasting models. We build on the growing work using AI (artificial intelligence) for automated pollen classification to design a flexible network that can deal with the uncertainty of broad-scale environmental applications. We combined imaging flow cytometry with Guided Deep Learning to identify and accurately categorise pollen in environmental samples; here, pollen grains captured within c. 5500 Cal yr BP old lake sediments. Our network discriminates not only pollen included in training libraries to the species level but, depending on the sample, can classify previously unseen pollen to the likely phylogenetic order, family and even genus. Our approach offers valuable insights into the development of a widely transferable, rapid and accurate exploratory tool for pollen classification in 'real-world' environmental samples with improved accuracy over pure deep learning techniques. This work has the potential to revolutionise many aspects of palynology, allowing a more detailed spatial and temporal understanding of pollen in the environment with improved taxonomical resolution.

Cholesterol-Depletion-Induced Membrane Repair Carries a Raft Conformer of P-Glycoprotein to the Cell Surface, Indicating Enhanced Cholesterol Trafficking in MDR Cells, Which Makes Them Resistant to Cholesterol Modifications.

The human P-glycoprotein (P-gp), a transporter responsible for multidrug resistance, is present in the plasma membrane's raft and non-raft domains. One specific conformation of P-gp that binds to the monoclonal antibody UIC2 is primarily associated with raft domains and displays heightened internalization in cells overexpressing P-gp, such as in NIH-3T3 MDR1 cells. Our primary objective was to investigate whether the trafficking of this particular P-gp conformer is dependent on cholesterol levels. Surprisingly, depleting cholesterol using cyclodextrin resulted in an unexpected increase in the proportion of raft-associated P-gp within the cell membrane, as determined by UIC2-reactive P-gp. This increase appears to be a compensatory response to cholesterol loss from the plasma membrane, whereby cholesterol-rich raft micro-domains are delivered to the cell surface through an augmented exocytosis process. Furthermore, this exocytotic event is found to be part of a complex trafficking mechanism involving lysosomal exocytosis, which contributes to membrane repair after cholesterol reduction induced by cyclodextrin treatment. Notably, cells overexpressing P-gp demonstrated higher total cellular cholesterol levels, an increased abundance of stable lysosomes, and more effective membrane repair following cholesterol modifications. These modifications encompassed exocytotic events that involved the transport of P-gp-carrying rafts. Importantly, the enhanced membrane repair capability resulted in a durable phenotype for MDR1 expressing cells, as evidenced by significantly improved viabilities of multidrug-resistant Pgp-overexpressing immortal NIH-3T3 MDR1 and MDCK-MDR1 cells compared to their parents when subjected to cholesterol alterations.

Preventing Risks of Infections and Medication Errors in IV therapy (PRIME): a patient safety initiative.

BACKGROUND: Two major avoidable reasons for adverse events in hospital are medication errors and intravenous therapy-induced infections or complications. Training for clinical staff and compliance to patient safety principles could address these. METHODS: Joint Commission International (JCI) consultants created a standardised, 6-month training programme for clinical staff in hospitals. Twenty-one tertiary care hospitals from across south-east Asia took part. JCI trained the clinical consultants, who trained hospital safety champions, who trained nursing staff. Compliance and knowledge were assessed, and monthly audits were conducted. RESULTS: There was an overall increase of 29% in compliance with parameters around medication preparation and vascular access device management. CONCLUSION: The programme improved safe practice around preparing medications management and managing vascular access devices. The approach could be employed as a continuous quality improvement initiative for the prevention of medication errors and infusion-associated complications.

The impact of green intellectual capital on green innovation in Vietnamese textile and garment enterprises: mediate role of environmental knowledge and moderating impact of green social behavior and learning outcomes.

The knowledge economy system shifts focus on the significance of intellectual capital. Moreover, the concept itself has gained generous amount of recognition at global level due to the increasing pressure from competitors, stakeholders, and environmental forces. Indeed, its antecedents and consequences have been assessed by scholars. However, the assessment appears to be inexhaustive with respect to meaningful frameworks. With the help of preceding literature, the present paper designed a model which involves green intellectual capital, green innovation, environmental knowledge, green social behavior, and learning outcomes. The model stipulates that green intellectual capital makes green innovation possible which further results in competitive advantage in the presence of environmental knowledge as a mediator as green social behavior and learning outcomes as a moderator. Interestingly the model acknowledges the proposed relationship through the empirical evidence collected from 382 Vietnamese textile and garment enterprises. The findings provide deeper insights regarding the issue that how firms could extract maximum benefits from their green assets and capabilities in the form of intellectual capital and green innovation.

In vivo biodistribution and pharmacokinetics of sotrovimab, a SARS-CoV-2 monoclonal antibody, in healthy cynomolgus monkeys.

PURPOSE: Sotrovimab (VIR-7831), a human IgG1κ monoclonal antibody (mAb), binds to a conserved epitope on the SARS-CoV-2 spike protein receptor binding domain (RBD). The Fc region of VIR-7831 contains an LS modification to promote neonatal Fc receptor (FcRn)-mediated recycling and extend its serum half-life. Here, we aimed to evaluate the impact of the LS modification on tissue biodistribution, by comparing VIR-7831 to its non-LS-modified equivalent, VIR-7831-WT, in cynomolgus monkeys. METHODS: 89Zr-based PET/CT imaging of VIR-7831 and VIR-7831-WT was performed up to 14 days post injection. All major organs were analyzed for absolute concentration as well as tissue:blood ratios, with the focus on the respiratory tract, and a physiologically based pharmacokinetics (PBPK) model was used to evaluate the tissue biodistribution kinetics. Radiomics features were also extracted from the PET images and SUV values. RESULTS: SUVmean uptake in the pulmonary bronchi for 89Zr-VIR-7831 was statistically higher than for 89Zr-VIR-7831-WT at days 6 (3.43 ± 0.55 and 2.59 ± 0.38, respectively) and 10 (2.66 ± 0.32 and 2.15 ± 0.18, respectively), while the reverse was observed in the liver at days 6 (5.14 ± 0.80 and 8.63 ± 0.89, respectively), 10 (4.52 ± 0.59 and 7.73 ± 0.66, respectively), and 14 (4.95 ± 0.65 and 7.94 ± 0.54, respectively). Though the calculated terminal half-life was 21.3 ± 3.0 days for VIR-7831 and 16.5 ± 1.1 days for VIR-7831-WT, no consistent differences were observed in the tissue:blood ratios between the antibodies except in the liver. While the lung:blood SUVmean uptake ratio for both mAbs was 0.25 on day 3, the PBPK model predicted the total lung tissue and the interstitial space to serum ratio to be 0.31 and 0.55, respectively. Radiomics analysis showed VIR-7831 had mean-centralized PET SUV distribution in the lung and liver, indicating more uniform uptake than VIR-7831-WT. CONCLUSION: The half-life extended VIR-7831 remained in circulation longer than VIR-7831-WT, consistent with enhanced FcRn binding, while the tissue:blood concentration ratios in most tissues for both drugs remained statistically indistinguishable throughout the course of the experiment. In the bronchiolar region, a higher concentration of 89Zr-VIR-7831 was detected. The data also allow unparalleled insight into tissue distribution and elimination kinetics of mAbs that can guide future biologic drug discovery efforts, while the residualizing nature of the 89Zr label sheds light on the sites of antibody catabolism.

Immuno-PET Monitoring of CD8+ T Cell Infiltration Post ICOS Agonist Antibody Treatment Alone and in Combination with PD-1 Blocking Antibody Using a 89Zr Anti-CD8+ Mouse Minibody in EMT6 Syngeneic Tumor Mouse.

PURPOSE: The presence and functional competence of intratumoral CD8+ T cells is often a barometer for successful immunotherapeutic responses in cancer. Despite this understanding and the extensive number of clinical-stage immunotherapies focused on potentiation (co-stimulation) or rescue (checkpoint blockade) of CD8+ T cell antitumor activity, dynamic biomarker strategies are often lacking. To help fill this gap, immuno-PET nuclear imaging has emerged as a powerful tool for in vivo molecular imaging of antibody targeting. Here, we took advantage of immuno-PET imaging using 89Zr-IAB42M1-14, anti-mouse CD8 minibody, to characterize CD8+ T-cell tumor infiltration dynamics following ICOS (inducible T-cell co-stimulator) agonist antibody treatment alone and in combination with PD-1 blocking antibody in a model of mammary carcinoma. PROCEDURES: Female BALB/c mice with established EMT6 tumors received 10 µg, IP of either IgG control antibodies, ICOS agonist monotherapy, or ICOS/PD-1 combination therapy on days 0, 3, 5, 7, 9, 10, or 14. Imaging was performed at 24 and 48 h post IV dose of 89Zr IAB42M1-14. In addition to 89Zr-IAB42M1-14 uptake in tumor and tumor-draining lymph node (TDLN), 3D radiomic features were extracted from PET/CT images to identify treatment effects. Imaging mass cytometry (IMC) and immunohistochemistry (IHC) was performed at end of study. RESULTS: 89Zr-IAB42M1-14 uptake in the tumor was observed by day 11 and was preceded by an increase in the TDLN as early as day 4. The spatial distribution of 89Zr-IAB42M1-14 was more uniform in the drug treated vs. control tumors, which had spatially distinct tracer uptake in the periphery relative to the core of the tumor. IMC analysis showed an increased percentage of cytotoxic T cells in the ICOS monotherapy and ICOS/PD-1 combination group compared to IgG controls. Additionally, temporal radiomics analysis demonstrated early predictiveness of imaging features. CONCLUSION: To our knowledge, this is the first detailed description of the use of a novel immune-PET imaging technique to assess the kinetics of CD8+ T-cell infiltration into tumor and lymphoid tissues following ICOS agonist and PD-1 blocking antibody therapy. By demonstrating the capacity for increased spatial and temporal resolution of CD8+ T-cell infiltration across tumors and lymphoid tissues, these observations underscore the widespread potential clinical utility of non-invasive PET imaging for T-cell-based immunotherapy in cancer.

Virtual screening for small-molecule pathway regulators by image-profile matching.

Identifying the chemical regulators of biological pathways is a time-consuming bottleneck in developing therapeutics and research compounds. Typically, thousands to millions of candidate small molecules are tested in target-based biochemical screens or phenotypic cell-based screens, both expensive experiments customized to each disease. Here, our uncustomized, virtual, profile-based screening approach instead identifies compounds that match to pathways based on the phenotypic information in public cell image data, created using the Cell Painting assay. Our straightforward correlation-based computational strategy retrospectively uncovered the expected, known small-molecule regulators for 32% of positive-control gene queries. In prospective, discovery mode, we efficiently identified new compounds related to three query genes and validated them in subsequent gene-relevant assays, including compounds that phenocopy or pheno-oppose YAP1 overexpression and kill a Yap1-dependent sarcoma cell line. This image-profile-based approach could replace many customized labor- and resource-intensive screens and accelerate the discovery of biologically and therapeutically useful compounds.

Endoscopic transcanal myringoplasty with anterior tab flap underlay technique: An analysis of 35 cases.

Introduction: The repair of the tympanic membrane can present a problem, especially in anterior perforation, because the anterior portion was not enough to inadequate contact between tympanic membrane remnant and graft. Various surgical techniques were recommended to achieve an acceptable graft success rate in anterior perforation. Endoscopic transcanal myringoplasty with anterior tab flap could provide the better stability of the graft. Objective: The aim of this study was to report the minimally invasive technique for the anterior tympanic membrane perforation closure and investigate the graft success rate of this technique. Patients and methods: We performed a prospective, randomized study of 35 patients who consulted the otorhinolaryngology department at the university hospital for surgery of perforation tympanic membrane repair. Results: The average age was 35.1 ± 11.9 years. The size of the perforation was dominant at small-size and large-size, 51.4%, 34.3%, respectively. There was a significant difference between the Preoperative air conduction of small and large perforations (34.44 8.68 and 49.79 14.54, respectively). Of 35 patients, 31 (88.6%) had closure of their perforations. The mean preoperative ABG was 24.11 ± 10.79 dB, while The mean postoperative ABG was 13.97 ± 10.03 dB (p < 0.05). Approximately 34.3% patients had ABG within 20 dB preoperatively, which increased to 82.9% after intervention (p < 0.05). Conclusions: The endoscopic transcanal myringoplasty with anterior tab flap underlay technique is a safe, suitable and effective method for cases with anterior tympanic membrane perforations, and showed improvement in postoperative hearing.

Imaging flow cytometry: a primer.

Imaging flow cytometry combines the high throughput nature of flow cytometry with the advantages of single cell image acquisition associated with microscopy. The measurement of large numbers of features from the resulting images provides rich datasets which have resulted in a wide range of novel biomedical applications. In this primer we discuss the typical imaging flow instrumentation, the form of data acquired and the typical analysis tools that can be applied to this data. Using examples from the literature we discuss the progression of the analysis methods that have been applied to imaging flow cytometry data. These methods start from the use of simple single image features and multiple channel gating strategies, followed by the design and use of custom features for phenotype classification, through to powerful machine and deep learning methods. For each of these methods, we outline the processes involved in analyzing typical datasets and provide details of example applications. Finally we discuss the current limitations of imaging flow cytometry and the innovations which are addressing these challenges.

MRI/PET multimodal imaging of the innate immune response in skeletal muscle and draining lymph node post vaccination in rats.

The goal of this study was to utilize a multimodal magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging approach to assess the local innate immune response in skeletal muscle and draining lymph node following vaccination in rats using two different vaccine platforms (AS01 adjuvanted protein and lipid nanoparticle (LNP) encapsulated Self-Amplifying mRNA (SAM)). MRI and 18FDG PET imaging were performed temporally at baseline, 4, 24, 48, and 72 hr post Prime and Prime-Boost vaccination in hindlimb with Cytomegalovirus (CMV) gB and pentamer proteins formulated with AS01, LNP encapsulated CMV gB protein-encoding SAM (CMV SAM), AS01 or with LNP carrier controls. Both CMV AS01 and CMV SAM resulted in a rapid MRI and PET signal enhancement in hindlimb muscles and draining popliteal lymph node reflecting innate and possibly adaptive immune response. MRI signal enhancement and total 18FDG uptake observed in the hindlimb was greater in the CMV SAM vs CMV AS01 group (↑2.3 - 4.3-fold in AUC) and the MRI signal enhancement peak and duration were temporally shifted right in the CMV SAM group following both Prime and Prime-Boost administration. While cytokine profiles were similar among groups, there was good temporal correlation only between IL-6, IL-13, and MRI/PET endpoints. Imaging mass cytometry was performed on lymph node sections at 72 hr post Prime and Prime-Boost vaccination to characterize the innate and adaptive immune cell signatures. Cell proximity analysis indicated that each follicular dendritic cell interacted with more follicular B cells in the CMV AS01 than in the CMV SAM group, supporting the stronger humoral immune response observed in the CMV AS01 group. A strong correlation between lymph node MRI T2 value and nearest-neighbor analysis of follicular dendritic cell and follicular B cells was observed (r=0.808, P<0.01). These data suggest that spatiotemporal imaging data together with AI/ML approaches may help establish whether in vivo imaging biomarkers can predict local and systemic immune responses following vaccination.

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning.

The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25-5.0 µg/mL) and/or carbendazim (0.8-1.6 µg/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the "DeepFlow" neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for 'mononucleates', 'binucleates', 'mononucleates with MN' and 'binucleates with MN', respectively. Successful classifications of 'trinucleates' (90%) and 'tetranucleates' (88%) in addition to 'other or unscorable' phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful (≤ 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent concentration regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.

Deepometry, a framework for applying supervised and weakly supervised deep learning to imaging cytometry.

Deep learning offers the potential to extract more than meets the eye from images captured by imaging flow cytometry. This protocol describes the application of deep learning to single-cell images to perform supervised cell classification and weakly supervised learning, using example data from an experiment exploring red blood cell morphology. We describe how to acquire and transform suitable input data as well as the steps required for deep learning training and inference using an open-source web-based application. All steps of the protocol are provided as open-source Python as well as MATLAB runtime scripts, through both command-line and graphic user interfaces. The protocol enables a flexible and friendly environment for morphological phenotyping using supervised and weakly supervised learning and the subsequent exploration of the deep learning features using multi-dimensional visualization tools. The protocol requires 40 h when training from scratch and 1 h when using a pre-trained model.

Burden of osteoporosis in Vietnam: An analysis of population risk.

PURPOSE: To estimate the proportion of men and women aged 50 years and older who would be classified as "high risk" for fracture and eligible for anti-fracture treatment. METHODS: The study involved 1421 women and 652 men aged 50 years and older, who were recruited from the general population in Ho Chi Minh City, Vietnam. Fracture history was ascertained from each individual. Bone mineral density (BMD) was measured at the lumbar spine and femoral neck by DXA (Hologic Horizon). The diagnosis of osteoporosis was based on the T-scores ≤ -2.50 derived from either femoral neck or lumbar spine BMD. The 10-year risks of major fractureand hip fracture were estimated from FRAX version for Thai population. The criteria for recommended treatment were based on the US National Osteoporosis Foundation (NOF). RESULTS: The average age of women and men was ~60 yr (SD 7.8). Approximately 11% (n = 152) of women and 14% (n = 92) of men had a prior fracture. The prevalence of osteoporosis was 27% (n = 381; 95% CI, 25 to 29%) in women and 13% (n = 87; 95% CI, 11 to 16%) in men. Only 1% (n = 11) of women and 0.1% (n = 1) of men had 10-year risk of major fracture ≥ 20%. However, 23% (n = 327) of women and 9.5% (n = 62) of men had 10-year risk of hip fracture ≥ 3%. Using the NOF recommended criteria, 49% (n = 702; 95% CI, 47 to 52%) of women and 35% (n = 228; 95% CI, 31 to 39%) of men would be eligible for therapy. CONCLUSION: Almost half of women and just over one-third of men aged 50 years and older in Vietnam meet the NOF criteria for osteoporosis treatment. This finding can help develop guidelines for osteoporosis treatment in Vietnam.

Application of the Bethesda System for Reporting Thyroid Cytopathology in the Pediatric Population.

OBJECTIVES: We aimed to provide the Asian experience with the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) in pediatric thyroid nodules. METHODS: Consecutive thyroid fine-needle aspirates (patient age, ≤18 years) were retrospectively collected from 7 tertiary centers in 5 Asian countries. RESULTS: Of 194,364 thyroid aspirates, 0.6% were pediatric cases (mean age, 15.0 years). Among 827 nodules with accessible follow-up, the resection rate and risk of malignancy (ROM) were 36.3% and 59.0%, respectively. Malignant nodules (n = 179) accounted for 59.7% of resected nodules and 21.6% of all thyroid nodules with available follow-up. Compared with the published adult series, pediatric nodules had a higher resection rate and ROM, particularly in the indeterminate categories. CONCLUSIONS: Our study demonstrates that Asian pediatric thyroid nodules had higher ROM than those from adults. The prototypic outputs of TBSRTC may need to be adjusted in the pediatric population.

Cytotoxic components from the leaves of Erythrophleum fordii induce human acute leukemia cell apoptosis through caspase 3 activation and PARP cleavage.

Cassaine diterpenoids as erythrofordins A-C (1-3), pseudo-erythrosuamin (4), and erythrofordin U (5) isolated from the leaves of Vietnamese Erythrophleum fordii Oliver were tested cytotoxic activity against human leukemia cancer cells. The results showed that these metabolites exhibited dose-dependent cytotoxicity against human leukemia HL-60 and KG cells with IC50 values ranging from 15.2 ± 1.5 to 42.2 ± 3.6 µM. Treatment with erythrofordin B led to the apoptosis of HL-60 and KG cells due to the activation of caspase 3, caspase 9, and poly (ADP-ribose) polymerase (PARP). Erythrofordin B significantly increased Bak protein expression, but downregulated the anti-apoptotic protein Bcl-2, in HL-60 cells. In silico results demonstrated that erythrofordin B can bind to both the procaspase-3 allosteric site and the PARP-1 active site, with binding energies of -7.36 and -10.76 kcal/mol, respectively. These results indicated that the leaves of Vietnamese E. fordii, which contain cassaine diterpenoids, can induce the apoptosis of human leukemia cancer cells.

Objective assessment of stored blood quality by deep learning.

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often assessed by microscopic examination or biochemical and biophysical assays, which are complex, time-consuming, and destructive to fragile cells. Here we demonstrate the use of label-free imaging flow cytometry and deep learning to characterize RBC lesions. Using brightfield images, a trained neural network achieved 76.7% agreement with experts in classifying seven clinically relevant RBC morphologies associated with storage lesions, comparable to 82.5% agreement between different experts. Given that human observation and classification may not optimally discern RBC quality, we went further and eliminated subjective human annotation in the training step by training a weakly supervised neural network using only storage duration times. The feature space extracted by this network revealed a chronological progression of morphological changes that better predicted blood quality, as measured by physiological hemolytic assay readouts, than the conventional expert-assessed morphology classification system. With further training and clinical testing across multiple sites, protocols, and instruments, deep learning and label-free imaging flow cytometry might be used to routinely and objectively assess RBC storage lesions. This would automate a complex protocol, minimize laboratory sample handling and preparation, and reduce the impact of procedural errors and discrepancies between facilities and blood donors. The chronology-based machine-learning approach may also improve upon humans' assessment of morphological changes in other biomedically important progressions, such as differentiation and metastasis.

Development of a model for identification of individuals with high risk of osteoporosis.

Many developing countries, including Vietnam, lack DXA resources for the diagnosis of osteoporosis, which poses difficulties in the treatment and prevention of osteoporosis at the individual level. We have developed and validated a prediction model for individualized assessment of osteoporosis based on age and body weight for men and women. PURPOSE: To estimate the prevalence of osteoporosis and to develop and validate a prediction model for estimating the absolute risk of osteoporosis in the Vietnamese population. METHODS: The study involved 1477 women and 669 men aged 50 years and older, who were recruited from the general population in Ho Chi Minh City (Vietnam). Bone mineral density (BMD) at the femoral neck, total hip, and lumbar spine was measured by DXA (Hologic Horizon). The diagnosis of osteoporosis was based on BMD T-score (T-score ≤ - 2.5) at the femoral neck or lumbar spine which was derived from a published reference range for the Vietnamese population. The logistic regression model was used to develop the prediction model for men and women separately. The bootstrap method was used to evaluate the model performance using 3 indices: the area under the receiver's operating characteristic curve (AUC), Brier score, and R-squared values. RESULTS: The prevalence of osteoporosis at any site was 28.3% in women and 15.5% in men. The best predictors of osteoporosis risk were age and body weight. Using these indices, a cut-off of 0.195 for women yielded an AUC of 0.825, Brier score = 0.112, and it explained 33.8% of total variance in risk of osteoporosis between individuals. Similarly, in men, the internal validation with a cut-off of 0.09 yielded good accuracy, with AUC = 0.858, Brier score = 0.040, and R-squared = 30.3%. CONCLUSION: We have developed and validated a prediction model for individualized assessment of osteoporosis. In settings without DXA, this model can serve as a useful screening tool to identify high-risk individuals for DXA scan.

Label-Free Leukemia Monitoring by Computer Vision.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. While there are a number of well-recognized prognostic biomarkers at diagnosis, the most powerful independent prognostic factor is the response of the leukemia to induction chemotherapy (Campana and Pui: Blood 129 (2017) 1913-1918). Given the potential for machine learning to improve precision medicine, we tested its capacity to monitor disease in children undergoing ALL treatment. Diagnostic and on-treatment bone marrow samples were labeled with an ALL-discriminating antibody combination and analyzed by imaging flow cytometry. Ignoring the fluorescent markers and using only features extracted from bright-field and dark-field cell images, a deep learning model was able to identify ALL cells at an accuracy of >88%. This antibody-free, single cell method is cheap, quick, and could be adapted to a simple, laser-free cytometer to allow automated, point-of-care testing to detect slow early responders. Adaptation to other types of leukemia is feasible, which would revolutionize residual disease monitoring. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.