BackgroundMeasurable residual disease (MRD) assessment using multicolor flow cytometry (MFC) has become the center point of pediatric B‐cell precursor acute lymphoblastic leukemia (BCP‐ALL) risk stratification and therapeutic management. The addition of new markers can improve the accuracy and applicability of MFC‐based MRD assay further. Herein, we evaluated the utility of a new marker, CD304/neuropilin‐1, in the assessment of MFC‐based MRD.MethodsExpression patterns of CD304 were studied in leukemic blasts from BCP‐ALL patients and in normal precursor B cells (NPBC) from uninvolved non‐BCP‐ALL bone marrow samples using 10‐color MFC. MRD was monitored at end‐of‐induction (EOI; Days 35–40) and end‐of‐consolidation (Day 78–80) time points.ResultsWe studied CD304 expression in 300 pediatric BCP‐ALL patients and found it positive in BCP‐ALL blasts in 41.7% of diagnostic samples. It was significantly associated with ETV6‐RUNX1 (p < .001) as well as BCR‐ABL1 (p = .019) and inversely associated with TCF3‐PBX1 fusion gene (p = .0012). It was found clearly negative in NPBC. EOI‐MRD was detectable in 152/300 (50.7%; ≥0.01% in 35.33% and <0.01% in 15.33%) samples, in which CD304 was positive in 72/152 (47.4%) diagnostic and 63/152 (41.4%) MRD samples. It was positive in 45.7% (21/46) of low‐level (<0.01%) MRD samples. In comparison with diagnostic samples, its expression was retained in 68.06% (49/72), lost in 31.94% (23/72), and gained in 14/80 (17.5%) of EOI‐MRD samples.ConclusionsCD304 is commonly expressed in leukemic blasts of BCP‐ALL. It is very useful in distinguishing residual disease from hematogones and is a fairly dependable marker. Hence, it is a valuable addition for enhancing the sensitivity and applicability of MFC‐based MRD assay in BCP‐ALL.

A fall of an older adult often leads to severe injuries and is found to be a significant reason for the death due to post-traumatic complications. Many falls happen in the home atmosphere and prevail unrecognized. Thus, the need for reliable early fall detection is necessary for fast help. Lately, the emergence of wearables, smartphones, IoT, etc., made it possible to develop systems fall detection which aids in the remote monitoring of the elderly. The goal is to allow intelligent algorithms and smartphones to detect falls for elderly care and to monitor them regularly. This work presents the Artificial Intelligence of Things for Fall Detection (AIOTFD) system using a slime mould algorithm (SMA) to optimize the final data. The features extracted using SqueezeNet further CNN based SMA used for data optimization. The validation of the AIOTFD model performance is evaluated through the Multiple Cameras Fall Dataset (MCFD) and UR Fall Detection dataset (URFD). The empirical results accentuated the assuring realization of the model compared to other state-of the art methods.The obtained results shows our proposed AIOTFD attains accuracy of 99.82% and 99.79% and databases can be used for additional investigation and optimizations to increase the recognition rate to enhance the independent life of the elderly.

Background Many novel therapies are being evaluated for the treatment of Multiple myeloma (MM). The cell‐surface protein B‐cell maturation antigen (BCMA, CD269) has recently emerged as a promising target for CAR‐T cell and monoclonal‐antibody therapies in MM. However, the knowledge of the BCMA expression‐pattern in myeloma patients from the Indian subcontinent is still not available. We present an in‐depth study of BCMA expression‐pattern on abnormal plasma cells (aPC) in Indian MM patients. Methods We studied BM samples from 217 MM patients (211‐new and 6‐relapsed) with a median age of 56 years (range, 30–78 years & M:F‐2.29) and 20 control samples. Expression levels/patterns of CD269 (clone‐19f2) were evaluated in aPCs from MM patients and in normal PCs (nPC) from uninvolved staging bone marrow samples (controls) using multicolor flow cytometry (MFC). Expression‐level of CD269 was determined as a ratio of mean fluorescent intensity (MFI‐R) of CD269 in PCs to that of non‐B‐lymphocytes and expression‐pattern (homogenous/heterogeneous) as coefficient‐of‐variation of immunofluorescence (CVIF). Results Median (range) percentage of CD269‐positive abnormal‐PCs in total PCs was 71.6% (0.49–99.29%). The MFI‐R (median, range) of CD269 was significantly higher in aPCs (4.13, 1.12–26.88) than nPCs (3.33, 1.23–12.87), p < .0001. Median (range) MFI of CD269 at diagnosis and relapse were 2.39 (0.77–9.57) and 2.66 (2.15–3.23) respectively. CD269 levels were similar at diagnosis and relapse, p = .5529. Conclusions We demonstrated that BCMA/CD269 is highly expressed in aPCs from a majority of MM patients, both at diagnosis and relapse. Thus, BCMA is a valuable target for therapy for Indian MM patients.