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Abstract In therapeutic diagnostics, early diagnosis and monitoring of heart disease is dependent on fast time-series MRI data processing. Robust encryption techniques are necessary to guarantee patient confidentiality. While deep learning (DL) algorithm have improved medical imaging, privacy and performance are still hard to balance. In this study, a novel approach for analyzing homomorphivally-encrypted (HE) time-series MRI data is introduced: The Multi-Faceted Long Short-Term Memory (MF-LSTM). This method includes privacy protection. The MF-LSTM architecture protects patient’s privacy while accurately categorizing and forecasting cardiac disease, with accuracy (97.5%), precision (96.5%), recall (98.3%), and F1-score (97.4%). While segmentation methods help to improve interpretability by identifying important region in encrypted MRI images, Generalized Histogram Equalization (GHE) improves image quality. Extensive testing on selected dataset if encrypted time-series MRI images proves the method’s stability and efficacy, outperforming previous approaches. The finding shows that the suggested technique can decode medical image to expose visual representation as well as sequential movement while protecting privacy and providing accurate medical image evaluation.

Governments and industries are developing aggressive policies to reduce carbon emissions and shift from fossil fuels to renewable energy. On the other hand, industries struggle to reduce energy consumption and depend on production lot sizes to control energy requirements. In this regard, energy-efficient processing through CNC machine tools can potentially influence energy demand and requires energy-aware power consumption strategies for machining processes. For manufacturing a single product, predicting energy demand can be decisive in determining parametric control and other factors. Previously analytical models have been largely used to model machining requirements and energy demand. However, these models largely depend on parameterization and do not facilitate the integration of external sub-systems. Therefore, in this paper, an artificial intelligence-based power reduction strategy is developed and implemented on single material (Inconel 718), four control parameters (cutting speed, feed rate, depth of cut and flow rate) and two sub-systems (minimum quantity lubrication (MQL) and nanofluids-based minimum quantity lubrication (NF-MQL)). The paper employs four machine learning algorithms,’ K-Nearest Neighbor’, ‘Gaussian Regression’, ‘Decision Tree’, and ‘Logistic Regression’, to evaluate their functionality in predicting power consumption (Pc) of CNC machining systems using a real experimental data set. As per evaluation based on five performance metrics (R-square, MSE, RMSE, MAE, and MedAE), ‘Decision Tree’ has achieved the most accurate power consumption predictions. The comparative results highlight ‘Decision Tree’ as the most better predictor with the optimal max_depth of 2 showing Pc MQL R2 of 0.915 and Pc NF-MQL R2 of 0.931.

The escalating global prevalence of chronic and lifestyle-related illnesses presents substantial societal and economic challenges. This work delves into an extensive review of healthcare monitoring systems tailored for chronic and lifestyle disorders. Subsequently, we propose a pioneering Smart Patient Monitoring and Recommendation (SPMR) framework, leveraging Deep Learning (DL) and cloud-based analytics. SPMR ensures continuous monitoring and predictive insights into a patient’s authentic health status using data from vital signs and contextual activities collected via Ambient Assisted Living devices. Within the predictive DL component of the LIP module, we employ Categorical Cross Entropy (CCE) Optimization to forecast real-world health conditions using unbalanced datasets derived from Chronic Blood Pressure Disorder case studies. Significantly, SPMR’s capability to deliver real-time preventive measures and treatments persists even without Internet or cloud connectivity. This circumvents the need to replicate Machine Learning (ML) models and associated procedures in local setups, thus streamlining operations. Comparative analysis against analogous models showcases the considerable effectiveness of our proposed model, notably enhancing accuracy by up to 8 to 18 percent. Moreover, both the overall F-score and the emergency class F-score exhibit marked improvements of 17% and 36%, respectively. These outcomes underscore SPMR’s pivotal role, especially during crises, emphasizing its significance in healthcare monitoring systems.

Abstract Background Mosaic loss of Y chromosome (LOY) is the most common chromosomal alteration in aging men. Here, we use single-cell RNA and ATAC sequencing to show that LOY is present in the kidney and increases with age and chronic kidney disease. Results The likelihood of a cell having LOY varies depending on its location in the nephron. Cortical epithelial cell types have a greater proportion of LOY than medullary or glomerular cell types, which may reflect their proliferative history. Proximal tubule cells are the most abundant cell type in the cortex and are susceptible to hypoxic injury. A subset of these cells acquires a pro-inflammatory transcription and chromatin accessibility profile associated with expression of HAVCR1, VCAM1, and PROM1. These injured epithelial cells have the greatest proportion of LOY and their presence predicts future kidney function decline. Moreover, proximal tubule cells with LOY are more likely to harbor additional large chromosomal gains and express pro-survival pathways. Spatial transcriptomics localizes injured proximal tubule cells to a pro-fibrotic microenvironment where they adopt a secretory phenotype and likely communicate with infiltrating immune cells. Conclusions We hypothesize that LOY is an indicator of increased DNA damage and potential marker of cellular senescence that can be applied to single-cell datasets in other tissues.

The growing demand for fiber-reinforced polymer (FRP) in industrial applications has prompted the exploration of natural fiber-based composites as a viable alternative to synthetic fibers. Using jute–rattan fiber-reinforced composite offers the potential for environmentally sustainable waste material decomposition and cost reduction compared to conventional fiber materials. This article focuses on the impact of different machining constraints on surface roughness and delamination during the drilling process of the jute–rattan FRP composite. Inspired by this unexplored research area, this article emphasizes the influence of various machining constraints on surface roughness and delamination in drilling jute–rattan FRP composite. Response surface methodology designs the experiment using drill bit material, spindle speed, and feed rate as input variables to measure surface roughness and delamination factors. The technique of order of preference by similarity to the ideal solution method is used to optimize the machining parameters, and for predicting surface roughness and delamination, two machine learning-based models named random forest (RF) and support vector machine (SVM) are utilized. To evaluate the accuracy of the predicted values, the correlation coefficient (R2), mean absolute percentage error, and mean squared error were used. RF performed better in comparison with SVM, with a higher value of R2 for both testing and training datasets, which is 0.997, 0.981, and 0.985 for surface roughness, entry delamination, and exit delamination, respectively. Hence, this study presents an innovative methodology for predicting surface roughness and delamination through machine learning techniques.

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The intracellular serine/threonine interleukin 1 receptor-associated kinase 4 (IRAK4) is necessary for most signaling by activated Toll-like receptors (TLRs). Activation of IRAK4 drives activation of nuclear factor kappa B (NF-κB) and so promotes cell survival, inflammation, and other aspects of the adaptive immune response. However, the IRAK4 pathway can be coopted by cancers and lead to the survival and proliferation of malignant cells. Inappropriate IRAK4 activity has been linked with the progression of myelodysplastic syndrome (MDS), other hematologic malignancies, and some solid tumors, and preclinical cancer models indicate that IRAK4 inhibition has anti-tumor effects. As such, inhibition of IRAK4 is an emerging and attractive target for tumor suppression. The growing interest in IRAK4 motivated the 1st Symposium on IRAK4 in Cancer held in October 2022 to bring together IRAK4 researchers and clinicians to discuss new insights into the biology of IRAK4 and development of IRAK4 inhibitors. Presentations and discussions at the meeting provided updates on the biology of IRAK4 and its links with mutations in the spliceosome, new outcomes from preclinical models that indicate synergy between inhibitors of IRAK4 and FLT3 and BTK inhibitors, and an update on the clinical development of the investigational IRAK4 inhibitor emavusertib, currently being assessed in ongoing phase 1/2 clinical studies in hematologic cancers and several solid tumors.

Alzheimer’s disease is a chronic clinical condition that is predominantly seen in age groups above 60 years. The early detection of the disease through image classification aids in effective diagnosis and suitable treatment. The magnetic resonance imaging (MRI) data on Alzheimer’s disease have been collected from Kaggle which is a freely available data source. These datasets are divided into training and validation sets. The present study focuses on training MRI datasets using TinyNet architecture that suits small-scale image classification problems by overcoming the disadvantages of large convolutional neural networks. The architecture is designed such that convergence time is reduced and overall generalization is improved. Though the number of parameters used in this architecture is lesser than the existing networks, still this network can provide better results. Training MRI datasets achieved an accuracy of 98% with the method used with a 2% error rate and 80% for the validation MRI datasets with a 20% error rate. Furthermore, to validate the model-supporting data collected from Kaggle and other open-source platforms, a comparative analysis is performed to substantiate TinyNet’s applicability and is projected in the discussion section. Transfer learning techniques are employed to infer the differences and to improve the model’s efficiency. Furthermore, experiments are included for fine-tuning attempts at the TinyNet architecture to assess how the nuances in convolutional neural networks have an impact on its performance.

Aluminium (Al) Alloy-6061/TiB2 was developed with Squeeze casting while varying composite quantities with titanium diboride (TiB2). The metallographic structure of the composite was investigated using EDS and scanning electron microscopy (SEM). The machining of developed composite is challenging with the conventional methods due to higher tool wear and surface roughness (Ra). This study analyses the output responses, and machinability of TiB2 of 15% volume reinforced AA6061 composites using Electrical Discharge Machining (EDM). The EDM operation variables such as current, pulse on time, and voltage gap were utilized to examine material removal rate (MRR), tool wear rate (TWR) and Ra employing Box–Behnken design of experiments. The MRR, TWR and Ra data acquired from various experiments were optimized considering single and multiple objectives by a hybrid approach. Machine learning (ML) was applied to predict responses using linear regression (LR), decision tree (DT) and random forest (RF). The samples' recast layer was examined using SEM, and the thickness of the recast layer was also documented. The Al6061 alloy's SEM micrographs reveal deep equiaxed dimples on its fracture surface, indicating a high level of plastic deformation before failure. TiB2 is evenly distributed as darker particles in the Al-matrix alloy with no directional-orientation. The Al6061-15 wt% TiB2 composites' fracture surfaces display deep dimples, ductile-fracture for Al6061 alloy due to higher plastic deformation, and cleavage facets in some areas. The aluminum alloy's wear pattern depicts long, extensive ploughing grooves with short cracks parallel to the sliding direction at the grooves' bottom. SEM micrographs in recast-layer formation have reported that molten metal ligaments break into droplets during flushing, exposing fresh surfaces. The aluminum alloy's groove width is larger compared to the composites. Thus, it can be observed that the wear tracks on the base Al6061 alloy are larger and deeper in comparison to the Al- 15 wt% TiB2 surface composites due to the presence of hard TiB2 particles. Also, the recast layer may be advantageous due to its wear-resistant properties. TiB2 has importance in an industry where components slide with each other it is used in disc brakes in automobiles. Compared to industry standards, single-objective optimization considerably enhanced the outcomes: MRR increased by 10.61%, TWR enriched by 25.91%, and Ra increased by 17.60%. According to an ANOVA, peak current contributed 87.88%, 98.18%, and 95.80% respectively to MRR, TWR, and Ra. It is requisite to investigate multi-objective optimization for EDM of Al6061-15 wt% TiB2 composites' owing to the diverse optimal factor combinations for responses. Ra was slightly increased by 1.14% due to simultaneous optimization utilizing hybrid techniques with Equal and Entropy weights, which diminished TWR by 11.74% and increased MRR by 11.66%. ML, particularly DT, improves machining performance by assisting productivity, durability, and cost-efficiency under changeable circumstances and raising forthcoming study possibilities.

Abstract Eltrombopag has been previously shown to be effective in reversing azacitidine‐mediated thrombocytopenia. This was further investigated in the SUPPORT trial, a phase III study assessing the efficacy/safety of eltrombopag plus azacitidine in patients with intermediate‐ to high‐risk myelodysplastic syndromes and thrombocytopenia. The results did not support a clinical benefit for the addition of eltrombopag to azacitidine. We investigated if the somatic mutational profiles in the patient cohort were associated with treatment outcomes. Based on the available data, we observed no imbalance in the mutational profiles between treatment arms or a clear association between identified somatic mutations and clinical outcomes.

Abstract Dysregulation of the innate immune system and inflammatory-related pathways has been implicated in hematopoietic defects in the bone marrow microenvironment and associated with aging, clonal hematopoiesis, myelodysplastic syndromes (MDS), and acute myeloid leukemia (AML). As the innate immune system and its pathway regulators have been implicated in the pathogenesis of MDS/AML, novel approaches targeting these pathways have shown promising results. Variability in expression of Toll like receptors (TLRs), abnormal levels of MyD88 and subsequent activation of NF-κβ, dysregulated IL1-receptor associated kinases (IRAK), alterations in TGF-β and SMAD signaling, high levels of S100A8/A9 have all been implicated in pathogenesis of MDS/AML. In this review we not only discuss the interplay of various innate immune pathways in MDS pathogenesis but also focus on potential therapeutic targets from recent clinical trials including the use of monoclonal antibodies and small molecule inhibitors against these pathways.

Myelodysplastic syndrome (MDS) is a heterogeneous group of bone marrow stem cell disorders characterized by ineffective hematopoiesis and cytopenias, most commonly anemia. Red cell transfusion therapy for anemia in MDS results in iron overload, correlating with reduced overall survival. Whether the treatment of iron overload benefits MDS patients remains controversial. We evaluate underlying iron-related pathophysiology and the effect of iron chelation using deferiprone on erythropoiesis in NUP98-HOXD13 transgenic mice, a highly penetrant well-established MDS mouse model. Our results characterize an iron overload phenotype with aberrant erythropoiesis in these mice which was reversed by deferiprone-treatment. Serum erythropoietin levels decreased while erythroblast erythropoietin receptor expression increased in deferiprone-treated MDS mice. We demonstrate, for the first time, normalized expression of the iron chaperones Pcbp1 and Ncoa4 and increased ferritin stores in late-stage erythroblasts from deferiprone-treated MDS mice, evidence of aberrant iron trafficking in MDS erythroblasts. Importantly, erythroblast ferritin is increased in response to deferiprone, correlating with decreased erythroblast ROS. Finally, we confirmed increased expression of genes involved in iron uptake, sensing, and trafficking in stem and progenitor cells from MDS patients. Taken together, our findings provide evidence that erythroblast-specific iron metabolism is a novel potential therapeutic target to reverse ineffective erythropoiesis in MDS.

Over the past two decades, there have been significant advances in the treatment of multiple myeloma which has led to an improvement in overall survival.1,2 However, a notable proportion of patients continue to experience early mortality (EM), defined as 2 years from the time of diagnosis. This raises the possibility that improvements in myeloma survival have not extended equally to all groups. Using the latest data drawn from the Surveillance Epidemiology and End Results database of patients in the United States spanning 2000-2019, we study impact of important sociodemographic factors on EM. Through regression modeling, we demonstrate that patients diagnosed from 2000-2005, of older age, male sex, and of certain racial minority status (non-Hispanic Black and Hispanic) have higher odds of EM. Of these factors, minority status contributed to worse 2-year overall survival as well. We evaluate whether income, as a surrogate to access to care, could potentially explain this finding, but find that race has a distinct relationship with EM that is not modified by income. This is further reinforced by subgroup analysis. After characterizing groups vulnerable to EM, we examine reasons for these disparities and potential avenues to address them.

PURPOSE: The purpose of this study was to evaluate the effect of nutritional-deficiency anemia (NDA) on peripapillary retinal nerve fiber layer thickness (PPRNFLT) using spectral-domain optical coherence tomography and to determine any correlation arising thereof. This was a single-center, cross-sectional, observational study. MATERIALS AND METHODS: A total 115 eyes of 115 NDA patients (50 of each with iron-deficiency anemia [IDA] and Vitamin B12-deficiency anemia [BDA], and 15 with folic acid-deficiency anemia [FDA]) aged 18–65 years were compared with a total 100 eyes of 50 age- and sex-matched healthy controls. All subjects underwent comprehensive clinical, ophthalmic, and hematological evaluation, followed by PPRNFLT assessment for the mean total, superior, inferior, nasal, and temporal quadrants. RESULTS: PPRNFLT for the mean total and all four quadrants in IDA patients, for the mean total, inferior, nasal, and temporal quadrants in BDA patients, and for the mean total, inferior, and nasal quadrants, in FDA patients, was significantly lower as compared to the controls (P < 0.05). The mean total PPRNFLT of all NDA patients correlated significantly (P < 0.05) with their relevant hematological parameters with Pearson's coefficient (r) value of 0.613, 0.610, 0.336, 0.295, 0.337, 0.374, and − 0.509, respectively, for serum haemoglobin (Hb), iron, ferritin, mean corpuscular volume (MCV), mean cell hemoglobin, mean corpuscular hemoglobin concentration, and total iron binding capacity in IDA; 0.310, 0.435, and − 0.386, respectively, for serum Hb%, Vitamin B12, and MCV in BDA; and 0.557, 0.358, and − 0.294 for Hb%, folate, and MCV, respectively, in FDA cases. Mean total retinal nerve fiber layer thinning of all NDA patients showed progression with the increasing severity grades of anemia, except in very severe BDA where an inverse relationship was documented. CONCLUSION: Our study revealed that PPRNFLT is significantly thinner in all NDA patients (total and all four quadrants in IDA; total, inferior, nasal, and temporal in BDA; and total, inferior, and nasal in FDA) correlating well with their relevant hematological parameters. Early detection of this may be crucial in preventing potential blinding sequelae and differentiating glaucomatous and other neuro-ophthalmic disorders.

Objective We sought to compare the incidence of early-onset sepsis (EOS) in infants ≥34 weeks’ gestation identified >24 hours after birth, in hospitals using the Kaiser Permanente Sepsis Risk Calculator (SRC) with hospitals using the National Institute for Health and Care Excellence (NICE) guidance.Design and setting Prospective observational population-wide cohort study involving all 26 hospitals with neonatal units colocated with maternity services across London (10 using SRC, 16 using NICE).Participants All live births ≥34 weeks’ gestation between September 2020 and August 2021.Outcome measures EOS was defined as isolation of a bacterial pathogen in the blood or cerebrospinal fluid (CSF) culture from birth to 7 days of age. We evaluated the incidence of EOS identified by culture obtained >24 hours to 7 days after birth. We also evaluated the rate empiric antibiotics were commenced >24 hours to 7 days after birth, for a duration of ≥5 days, with negative blood or CSF cultures.Results Of 99 683 live births, 42 952 (43%) were born in SRC hospitals and 56 731 (57%) in NICE hospitals. The overall incidence of EOS (24 hours was 2.3/100 000 (n=1) for SRC vs 7.1/100 000 (n=4) for NICE (OR 0.5, 95% CI (0.1 to 2.7)). This corresponded to (1/20) 5% (SRC) vs (4/45) 8.9% (NICE) of EOS cases (χ=0.3, p=0.59). Empiric antibiotics were commenced >24 hours to 7 days after birth in 4.4/1000 (n=187) for SRC vs 2.9/1000 (n=158) for NICE (OR 1.5, 95% CI (1.2 to 1.9)). 3111 (7%) infants received antibiotics in the first 24 hours in SRC hospitals vs 8428 (15%) in NICE hospitals.Conclusion There was no significant difference in the incidence of EOS identified >24 hours after birth between SRC and NICE hospitals. SRC use was associated with 50% fewer infants receiving antibiotics in the first 24 hours of life.

Abstract An elevated risk of myeloma precursor disease, monoclonal gammopathy of undetermined significance (MGUS), was identified among Fire Department of the City of New York (FDNY) World Trade Center (WTC)-exposed firefighters. Further investigation was needed to determine if these findings were reproducible in a more heterogeneous WTC-exposed rescue/recovery workers cohort, the Stony Brook University-General Responder Cohort GRC (SBU-GRC). MGUS risk was compared between the cohorts and to published general population estimates from Olmsted County, MN, USA. In this observational seroprevalence study, odds ratios (OR) and age-standardized risk ratios (RR) of MGUS (M-spike and light-chain-MGUS combined), M-spike, and light-chain-MGUS were estimated using logistic regression. Age-standardized prevalences were calculated for white males aged 50–79; RRs were estimated by comparing risk in the WTC-exposed cohort with the Olmsted County screened cohort. SBU-GRC had elevated odds of MGUS compared with FDNY (OR = 1.38; 95%CI = 1.00–1.89). The age-standardized prevalence of MGUS was 9.0/100 persons (95%CI = 7.5–10.6), over two-fold higher than the general population (RR = 2.08; 95%CI = 1.72–2.51); the age-standardized prevalence of light-chain-MGUS was 3.5-fold higher (RR = 3.54; 95%CI = 2.52–4.97). This study adds to mounting evidence supporting an association between WTC/environmental exposures and MGUS among rescue/recovery workers. Access to MGUS screenings for the entire WTC-exposed cohort could allow for treatment interventions that improve survival.

The hydrothermal method was successfully used in the current work to fabricate YCeO nanocomposites, a novel hydrogen (H2) gas sensor. XRD, FE-SEM, and AFM were performed to determine the crystal structure and morphology of as prepared nanocomposite. The cubic structure of space group Fm3m with a density of 6.74 gmcm−3, a volume of 157.81 106 pm3, and a crystallite size of 18.66 nm is obtained in the XRD pattern of YCeO in this instance. Furthermore, the granular structure and roughness of the surface can be seen in FE-SEM and AFM studies. Additionally, hydrogen sensing was performed at a temperature of 28 °C with a hydrogen concentration of 20–120 ppm. The sensor response for hydrogen gas at 20 and 120 ppm was measured to be 1.41 and 2.09, respectively. At 20 ppm, we came to know that the recovery times and rapid response were 75.54 s and 40.81 s, respectively. The long-term stability was also checked for 40 days and the change in sensor response at 20 and 40 days was 1.40 and 1.39, respectively. The investigated sensor device also demonstrates the benefits of a straightforward fabrication procedure, a basic structure, and a very affordable hydrogen detection sensor.

Abstract Advanced pancreatic ductal adenocarcinoma (PDAC) is usually an incurable malignancy that needs newer therapeutic targets. Interleukin-1 receptor accessory protein (IL1RAP) is an innate immune mediator that regulates activation of pro-inflammatory and mitogenic signaling pathways. Immunohistochemistry on tissue microarrays demonstrated expression of IL1RAP in majority of human PDAC specimens and in murine pancreatic tumors from K-RasG122D/p53R172H/PDXCre (KPC) mice. Single cell RNA-Seq analysis of human primary pre-neoplastic lesions and adenocarcinoma specimens indicated that overexpression occurs during carcinogenesis. IL1RAP overexpression was associated with worse overall survival. IL1RAP knockdown significantly reduced cell viability, invasiveness, and clonogenic growth in pancreatic cancer cell lines. Inhibition of the downstream interleukin-1 receptor-associated kinase 4 (IRAK4) using two pharmacologic inhibitors, CA-4948 and PF06650833, resulted in reduced growth in pancreatic cancer cell lines and in xenograft models.

Background: Cancer patients show increased morbidity with COVID-19 and need effective immunization strategies. Many healthcare regulatory agencies recommend administering ‘booster’ doses of COVID-19 vaccines beyond the standard two-dose series, for this group of patients. Therefore, studying the efficacy of these additional vaccine doses against SARS-CoV-2 and variants of concern is of utmost importance in this immunocompromised patient population Methods: We conducted a prospective single arm clinical trial enrolling patients with cancer that had received two doses of mRNA or one dose of AD26.CoV2.S vaccine and administered a third dose of mRNA vaccine. We further enrolled patients that had no or low responses to three mRNA COVID vaccines and assessed the efficacy of a fourth dose of mRNA vaccine. Efficacy was assessed by changes in anti-spike antibody, T-cell activity, and neutralization activity, which were again assessed at baseline and 4 weeks. Results: We demonstrate that a third dose of COVID-19 vaccine leads to seroconversion in 57% of patients that were seronegative after primary vaccination series. The immune response is durable as assessed by anti-SARS-CoV-2 (anti-S) antibody titers, T-cell activity, and neutralization activity against wild-type (WT) SARS-CoV2 and BA1.1.529 at 6 months of follow-up. A subset of severely immunocompromised hematologic malignancy patients that were unable to mount an adequate immune response (titer

Abstract Background Cancer is characterized by the rampant proliferation, growth, and infiltration of malignantly transformed cancer cells past their normal boundaries into adjacent tissues. It is the leading cause of death worldwide, responsible for approximately 19.3 million new diagnoses and 10 million deaths globally in 2020. In the United States alone, the estimated number of new diagnoses and deaths is 1.9 million and 609 360, respectively. Implementation of currently existing cancer diagnostic techniques such as positron emission tomography (PET), X‐ray computed tomography (CT), and magnetic resonance spectroscopy (MRS), and molecular diagnostic techniques, have enabled early detection rates and are instrumental not only for the therapeutic management of cancer patients, but also for early detection of the cancer itself. The effectiveness of these cancer screening programs are heavily dependent on the rate of accurate precursor lesion identification; an increased rate of identification allows for earlier onset treatment, thus decreasing the incidence of invasive cancer in the long‐term, and improving the overall prognosis. Although these diagnostic techniques are advantageous due to lack of invasiveness and easier accessibility within the clinical setting, several limitations such as optimal target definition, high signal to background ratio and associated artifacts hinder the accurate diagnosis of specific types of deep‐seated tumors, besides associated high cost. In this review we discuss various imaging, molecular, and low‐cost diagnostic tools and related technological advancements, to provide a better understanding of cancer diagnostics, unraveling new opportunities for effective management of cancer, particularly in low‐ and middle‐income countries (LMICs). Recent Findings Herein we discuss various technological advancements that are being utilized to construct an assortment of new diagnostic techniques that incorporate hardware, image reconstruction software, imaging devices, biomarkers, and even artificial intelligence algorithms, thereby providing a reliable diagnosis and analysis of the tumor. Also, we provide a brief account of alternative low cost‐effective cancer therapy devices (CryoPop®, LumaGEM®, MarginProbe®) and picture archiving and communication systems (PACS), emphasizing the need for multi‐disciplinary collaboration among radiologists, pathologists, and other involved specialties for improving cancer diagnostics. Conclusion Revolutionary technological advancements in cancer imaging and molecular biology techniques are indispensable for the accurate diagnosis and prognosis of cancer.

Patients with epilepsy (PWE) may experience seizure emergencies including acute repetitive seizures despite chronic treatment with daily antiseizure medications. Seizures may adversely impact routine daily activities and/or healthcare utilization and may impair the quality of life of patients with epilepsy and their caregivers. Seizures often occur at home, school, or work in a community setting. Appropriate treatment that is readily accessible for patients with seizure urgencies and emergencies is essential outside the hospital setting. When determining the best acute antiseizure therapy for PWE, clinicians need to consider all of the available rescue medications and their routes of administration including the safety and efficacy profiles. Benzodiazepines are a standard of care as a rescue therapy, yet there are several misconceptions about their use and safety. Reevaluating potential misconceptions and formulating best practices are necessary to maximize usage for each available option of acute therapy. We examine common beliefs associated with traditional use of acute seizure therapies to refute or support them based on the current level of evidence in the published literature.

The impact of convection and radiation on the thermal distribution of the wavy porous fin is examined in the present study. A hybrid model that combines the differential evolution (DE) algorithm with an artificial neural network (ANN) is proposed for predicting the heat transfer of the wavy porous fin. The equation representing the thermal variation in the wavy porous fin is reduced to its dimensionless arrangement and is numerically solved using Rung, e-Kutta-Fehlberg’s fourth-fifth order method (RKF-45). The study demonstrates the effectiveness of this hybrid model, and the results indicate that the proposed approach outperforms the ANN model with parameters obtained through grid search (GS), showcasing the superiority of the hybrid DE-ANN model in terms of accuracy and performance. This research highlights the potential of utilizing DE with ANN for improved predictive modeling in the heat transfer sector. The originality of this study is that it addresses the heat transfer problem by optimizing the selection of parameters for the ANN model using the DE algorithm.

In the present article, we investigate the free convective flow of a ternary hybrid nanofluid in a two-phase inclined channel saturated with a porous medium. The flow has been propelled using the pressure gradient, thermal radiation, and buoyancy force. The flow model’s governing equations are resolved using the regular perturbation approach. The governing equations are solved with the help of the regular perturbation method. Polyethylene glycol and water (at a ratio of 50%:50%) fill up Region I, while a ternary hybrid nanofluid based on zirconium dioxide, magnesium oxide, and carbon nanotubes occupies Region II. The ternary hybrid nanofluids are defined with a mixture model in which three different shapes of nanoparticles, namely spherical, platelet, and cylindrical, are incorporated. The consequences of the most significant variables have been examined using both visual and tabular data. The main finding of this work is that utilising a ternary hybrid nanofluid at the plate y = 1 increases the rate of heat transfers by 753%, demonstrating the potential thermal efficiency. The overall heat and volume flow rates are amplified by buoyant forces and viscous dissipations and dampened by the thermal radiation parameter. The optimum enhancement of temperature is achieved by the influence of buoyancy forces. A ternary nanofluid region experiences the maximum temperature increase compared to a clear fluid region. To ensure the study’s efficiency, we validated it with prior studies.

Abstract Anti-CD19 chimeric antigen receptor T-cell therapies have shown striking clinical activity in diffuse large B-cell lymphoma but robust biomarkers predictive of responsiveness are still needed. We treated a multi-ethnic cohort of 31 diffuse large B-cell lymphoma patients with axicabtagene ciloleucel with an overall response rate of 71%. Analysis of various biomarkers identified a significant decrease in overall survival with elevated lactate dehydrogenase, measured both at time of cell infusion and before lymphodepletion. Lactate dehydrogenase was prognostic in a multivariate analysis [HR = 1.47 (1.1–2.0)] and a value of 400 U/L at time of infusion and a value of 440 U/L before lymphodepletion provided the best prognostic cutoffs for overall survival in our cohort. These data demonstrate efficacy of anti-CD19 chimeric antigen receptor T-cell therapy in a diverse inner city population and demonstrate novel lactate dehydrogenase cutoffs as prognostic biomarkers.

Abstract Background Calreticulin (CRT), an endoplasmic reticulum–resident protein generally overexpressed in cancer cells, is associated with radiation resistance. CRT shows higher transacetylase activity, as shown by us earlier, in the presence of the polyphenolic acetates (like 7, 8‐diacetoxy‐4‐methylcoumarin, DAMC) and modifies the activity of a number of proteins, thereby influencing cell signaling. Aim To investigate the relationship between CRT expression and radiation response in a human glioma cell line and to evaluate the radiomodifying effects of DAMC. Methods and results Studies were carried out in an established human glioma cell line (BMG‐1) and its isogenic clone overexpressing CRT (CROE, CRT‐overexpressing cells) by analyzing clonogenic survival, cell proliferation, micronuclei analysis, and protein levels by Western blotting as parameters of responses. CRT overexpression conferred resistance against radiation‐induced cell death in CROE cells (D37 = 7.35 Gy, D10 = 12.6 Gy and D0 = 7.25 Gy) as compared to BMG‐1 cells (D37 = 5.70 Gy, D10 = 9.2 Gy and D0 = 5.6 Gy). A lower level of radiation‐induced micronuclei formation observed in CROE cells suggested that reduced induction and/or enhanced DNA repair partly contributed to the enhanced radioresistance. Consistent with this suggestion, we noted that CRT‐mediated radioresistance was coupled with enhanced grp78 level and reduced P53 activation–mediated prodeath signaling, while no changes were noted in acetylation of histone H4. DAMC‐enhanced radiation–induced delayed (secondary) apoptosis, which was higher in CROE cells. Conclusion CRT overexpression confers resistance against radiation‐induced death of human glioma cells, which can be overcome by the polyphenolic acetate DAMC.

The rapidly growing discipline of artificial intelligence (AI) seeks to develop software and computers that can do tasks that have historically required the intelligence of people. Machine learning (ML) is a subfield of AI that makes use of algorithms to "learn" from data's innate statistical patterns and structures to extrapolate information that is otherwise hidden. A growing emphasis on cosmetic dentistry has coincided with ZrO2‘s rise to prominence as a result of its improved biocompatibility, visually pleasant look, strong oxidation resistance, better mechanical properties, and lack of documented allergic responses. Advances in the field of AI and ML have led to novel applications of ZrO2 in dental devices for biological objectives. Artificial intelligence (AI) technologies have attracted a lot of attention in ZrO2-related research and therapeutic applications due to their ability to analyze data and discover connections between seemingly unrelated events. Specifically, their incorporation into zirconia is largely responsible for this. Zirconia's versatility in the scientific community means that how AI is used in the area varies with the specific directions in which zirconia is utilized. Therefore, this article primarily focuses on the use of AI in the biomedical use of ZrO2 in dentistry.

Abstract Even though genetic perturbations and mutations are important for the development of myeloid malignancies, the effects of an inflammatory microenvironment are a critical modulator of carcinogenesis. Activation of the innate immune system through various ligands and signaling pathways is an important driver of myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). The DAMPs, or alarmins, which activate the inflammasome pathway via the TLR4/NLR signaling cascade causes the lytic cell death of hematopoietic stem and progenitor cells (HSPCs), ineffective hematopoiesis, and β-catenin-induced proliferation of cancer cells, leading to the development of MDS/AML phenotype. It is also associated with other myeloid malignancies and involved in the pathogenesis of associated cytopenias. Ongoing research suggests the interplay of inflammasome mediators with immune modulators and transcription factors to have a significant role in the development of myeloid diseases, and possibly therapy resistance. This review discusses the role and importance of inflammasomes and immune pathways in myeloid malignancies, particularly MDS/AML, to better understand the disease pathophysiology and decipher the scope of therapeutic interventions.

Abstract The BCL2-inhibitor, Venetoclax (VEN), has shown significant anti-leukemic efficacy in combination with the DNMT-inhibitor, Azacytidine (AZA). To explore the mechanisms underlying the selective sensitivity of mutant leukemia cells to VEN and AZA, we used cell-based isogenic models containing a common leukemia-associated mutation in the epigenetic regulator ASXL1. KBM5 cells with CRISPR/Cas9-mediated correction of the ASXL1 G710X mutation showed reduced leukemic growth, increased myeloid differentiation, and decreased HOXA and BCL2 gene expression in vitro compared to uncorrected KBM5 cells. Increased expression of the anti-apoptotic gene, BCL2, was also observed in bone marrow CD34+ cells from ASXL1 mutant MDS patients compared to CD34+ cells from wild-type MDS cases. ATAC-sequencing demonstrated open chromatin at the BCL2 promoter in the ASXL1 mutant KBM5 cells. BH3 profiling demonstrated increased dependence of mutant cells on BCL2. Upon treatment with VEN, mutant cells demonstrated increased growth inhibition. In addition, genome-wide methylome analysis of primary MDS samples and isogenic cell lines demonstrated increased gene-body methylation in ASXL1 mutant cells, with consequently increased sensitivity to AZA. These data mechanistically link the common leukemia-associated mutation ASXL1 to enhanced sensitivity to VEN and AZA via epigenetic upregulation of BCL2 expression and widespread alterations in DNA methylation.

In this article, we come up with a novel numerical scheme based on Haar wavelet (HW) along with nonstandard ‎finite difference (NSFD) scheme to solve time-fractional Burgers’ equation with variable diffusion coefficient and ‎time delay. In the solution process, we discretize the fractional time derivative by NSFD ‎ formula and spatial ‎derivative by HWs series expansion. We use the quasilinearisation process to linearize the nonlinear term. Also, ‎the convergence of the scheme is discussed. The efficiency and correctness of the proposed scheme are assessed ‎by ‎L∞-error and L2‎ ‎-error norms.‎

Myelodysplastic syndromes (MDS) are age-related myeloid neoplasms with increased risk of progression to acute myeloid leukemia (AML). The mechanisms of transformation of MDS to AML are poorly understood, especially in relation to the aging microenvironment. We previously established an mDia1/miR-146a double knockout (DKO) mouse model phenocopying MDS. These mice develop age-related pancytopenia with oversecretion of proinflammatory cytokines. Here, we found that most of the DKO mice underwent leukemic transformation at 12–14 months of age. These mice showed myeloblast replacement of fibrotic bone marrow and widespread leukemic infiltration. Strikingly, depletion of IL-6 in these mice largely rescued the leukemic transformation and markedly extended survival. Single-cell RNA sequencing analyses revealed that DKO leukemic mice had increased monocytic blasts that were reduced with IL-6 knockout. We further revealed that the levels of surface and soluble IL-6 receptor (IL-6R) in the bone marrow were significantly increased in high-risk MDS patients. Similarly, IL-6R was also highly expressed in older DKO mice. Blocking of IL-6 signaling significantly ameliorated AML progression in the DKO model and clonogenicity of CD34-positive cells from MDS patients. Our study establishes a mouse model of progression of age-related MDS to AML and indicates the clinical significance of targeting IL-6 signaling in treating high-risk MDS.

Background: Mutations in the SF3B1 splicing factor are commonly seen in myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML), yet the specific oncogenic pathways activated by mis-splicing have not been fully elucidated. Inflammatory immune pathways have been shown to play roles in the pathogenesis of MDS, though the exact mechanisms of their activation in splicing mutant cases are not well understood. Methods: RNA-seq data from SF3B1 mutant samples was analyzed and functional roles of interleukin-1 receptor-associated kinase 4 (IRAK4) isoforms were determined. Efficacy of IRAK4 inhibition was evaluated in preclinical models of MDS/AML. Results: RNA-seq splicing analysis of SF3B1 mutant MDS samples revealed retention of full-length exon 6 of IRAK4, a critical downstream mediator that links the Myddosome to inflammatory NF-kB activation. Exon 6 retention leads to a longer isoform, encoding a protein (IRAK4-long) that contains the entire death domain and kinase domain, leading to maximal activation of NF-kB. Cells with wild-type SF3B1 contain smaller IRAK4 isoforms that are targeted for proteasomal degradation. Expression of IRAK4-long in SF3B1 mutant cells induces TRAF6 activation leading to K63-linked ubiquitination of CDK2, associated with a block in hematopoietic differentiation. Inhibition of IRAK4 with CA-4948, leads to reduction in NF-kB activation, inflammatory cytokine production, enhanced myeloid differentiation in vitro and reduced leukemic growth in xenograft models. Conclusions: SF3B1 mutation leads to expression of a therapeutically targetable, longer, oncogenic IRAK4 isoform in AML/MDS models. Funding: This work was supported by Cincinnati Children’s Hospital Research Foundation, Leukemia Lymphoma Society, and National Institute of Health (R35HL135787, RO1HL111103, RO1DK102759, RO1HL114582), Gabrielle’s Angel Foundation for Cancer Research, and Edward P. Evans Foundation grants to DTS. AV is supported by Edward P. Evans Foundation, National Institute of Health (R01HL150832, R01HL139487, R01CA275007), Leukemia and Lymphoma Society, Curis and a gift from the Jane and Myles P. Dempsey family. AP and JB are supported by Blood Cancer UK (grants 13042 and 19004). GC is supported by a training grant from NYSTEM. We acknowledge support of this research from The Einstein Training Program in Stem Cell Research from the Empire State Stem Cell Fund through New York State Department of Health Contract C34874GG. MS is supported by a National Institute of Health Research Training and Career Development Grant (F31HL132420).

The Quadratic Unconstrained Binary Optimization (QUBO) modeling and solution framework is a requirement for quantum and digital annealers. However optimality for QUBO problems of any practical size is extremely difficult to achieve. In order to incorporate the problem-specific insights, a diverse set of solutions meeting an acceptable target metric or goal is the preference in high level decision making. In this paper, we present two alternatives for goal-seeking QUBO for minimizing the deviation from a given target as well as a range of values around a target. Experimental results illustrate the efficacy of the proposed approach over Constraint Programming for quickly finding a satisficing set of solutions.

Emerging technological advancements in brachytherapy, when used alone or combined with conventional therapies have improved the therapeutic efficacy, leading to enhanced patient survival. Advancements in the use of various isotopes, delivery methods, incorporation of 3D imaging, and 3D printing, have significantly optimized the treatment planning and increased dose delivery accuracy, achieving high target volume irradiation and low normal tissue exposure. Real-time guidance during the implanting of radiation source into the tumor tissue has shown the promising outcome of brachytherapy. Integration of precise in vivo dosimetry methods have reduced the deviations in the measured dose, and associated operational errors, ensuring brachytherapy is accurate, and delivering more targeted doses over the course of the treatment. The use of new forms of radiation sources such as needles, pellets, tubes, overcomes the risk of source clumping and migration. Personalized applicators, biodegradable brachytherapy systems, injectable radiolabeled thermoresponsive polymers offer yet another promising brachytherapy approaches. Here we describe the recent technological innovations in brachytherapy and discuss various strategies adopted to overcome the associated challenges in preclinical and clinical settings.

Abstract The large-scale application of organic pollutants (OPs) has contaminated the air, soil, and water. Persistent OPs enter the food supply chain and create several hazardous effects on living systems. Thus, there is a need to manage the environmental levels of these toxicants. Microbial glycoconjugates pave the way for the enhanced degradation of these toxic pollutants from the environment. Microbial glycoconjugates increase the bioavailability of these OPs by reducing surface tension and creating a solvent interface. To date, very little emphasis has been given to the scope of glycoconjugates in the biodegradation of OPs. Glycoconjugates create a bridge between microbes and OPs, which helps to accelerate degradation through microbial metabolism. This review provides an in-depth overview of glycoconjugates, their role in biofilm formation, and their applications in the bioremediation of OP-contaminated environments.

Abstract This work investigates the vibrational power that may potentially be delivered by electron-emitted phonons at the terminals of a device with a 1D material as the active channel. Electrons in a 1D material traversing a device excite phase-limited acoustic and optical phonon modes as they undergo streaming motion. At ultra-low temperature (4 K in this study, for example), in the near absence of background phonon activity, the emitted traveling phonons may potentially be collected at the terminals before they decay. Detecting those phonons is akin to hearing electrons within the device. Results here show that traveling acoustic phonons can deliver up to a fraction of a nW of vibrational power at the terminals, which is within the sensitivity range of modern instruments. The total vibrational power from traveling optical and acoustic phonons is found to be in order of nW. In this work, Ensemble Monte Carlo (EMC) simulations are used to model the behavior of a gate-all-around (GAA) field-effect transistor (FET), with a single-wall semiconducting carbon nanotube (SWCNT) as the active channel, and a free-hanging SWCNT between two contacts. Electronic band structure of the SWCNT is calculated within the framework of a tight-binding (TB) model. The principal scattering mechanisms are due to electron–phonon interactions using 1st order perturbation theory. A continuum model is used to determine the longitudinal acoustic (LA) and optical (LO) phonons, and a single lowest radial breathing mode (RBM) phonon is considered.

Abstract Optimal treatment of acute myeloid leukemia (AML) arising in elderly patients remains a challenge. FDA approval of Ivosidenib and Enasidenib, small molecule inhibitors of isocitrate dehydrogenase enzymes (IDH1 and 2) have opened new avenues of treatment. We present a 60-year-old woman with refractory AML, achieving complete response to the combination therapy of hypomethylating agent, Azacytidine with the IDH2 inhibitor, Enasidenib, and BCL2 inhibitor, Venetoclax. To our knowledge, this is the first case report of a patient with IDH2 mutated refractory AML achieving complete response to combination therapy with azacytidine, enasidenib and venetoclax.

Potato is one of the major cultivated crops and provides occupations and livelihoods for numerous people across the globe. It also contributes to the economic growth of developing and underdeveloped countries. However, potato blight is one of the major destroyers of potato crops worldwide. With the introduction of neural networks to agriculture, many researchers have contributed to the early detection of potato blight using various machine and deep learning algorithms. However, accuracy and computation time remain serious issues. Therefore, considering these challenges, we customised a convolutional neural network (CNN) to improve accuracy with fewer trainable parameters, less computation time, and reduced information loss. We compared the performance of the proposed model with various machine and deep learning algorithms used for potato blight classification. The proposed model outperformed the others with an overall accuracy of 99% using 839,203 trainable parameters in 183 s of training time.

PURPOSEHereditary breast and ovarian cancer (HBOC) syndrome is primarily characterized by mutations in the BRCA1/2 genes. There are several barriers to the implementation of genetic testing and counseling in India that may affect clinical decisions. These consensus recommendations were therefore convened as a collaborative effort to improve testing and management of HBOC in India.DESIGNRecommendations were developed by a multidisciplinary group of experts from the Indian Society of Medical and Pediatric Oncology and some invited experts on the basis of graded evidence from the literature and using a formal Delphi process to help reach consensus. PubMed and Google Scholar databases were searched to source relevant articles.RESULTSThis consensus statement provides practical insight into identifying patients who should undergo genetic counseling and testing on the basis of assessments of family and ancestry and personal history of HBOC. It discusses the need and significance of genetic counselors and medical professionals who have the necessary expertise in genetic counseling and testing. Recommendations elucidate requirements of pretest counseling, including discussions on genetic variants of uncertain significance and risk reduction options. The group of experts recommended single-site mutation testing in families with a known mutation and next-generation sequencing coupled with multiplex ligation probe amplification for the detection of large genomic rearrangements for unknown mutations. Recommendations for surgical and lifestyle-related risk reduction approaches and management using poly (ADP-ribose) polymerase inhibitors are also detailed.CONCLUSIONWith rapid strides being made in the field of genetic testing/counseling in India, more oncologists are expected to include genetic testing/counseling as part of their clinical practice. These consensus recommendations are anticipated to help homogenize genetic testing and management of HBOC in India for improved patient care.

In this article, we develop a monotone iterative technique (MI-technique) with lower and upper (L-U) solutions for a class of four-point Dirichlet nonlinear boundary value problems (NLBVPs), defined as, where , the non linear term is continuous function in x, one sided Lipschitz in ψ and Lipschitz in . To show the existence result, we construct Green’s function and iterative sequences for the corresponding linear problem. We use quasilinearization to construct these iterative schemes. We prove maximum principle and establish monotonicity of sequences of lower solution and upper solution such that Then under certain sufficient conditions we prove that these sequences converge uniformly to the solution ψ(x) in a specific region where

Walking (gait) irregularities and abnormalities are predictors and symptoms of disorder and disability. In the past, elaborate video (camera-based) systems, pressure mats, or a mix of the two has been used in clinical settings to monitor and evaluate gait. This article presents an artificial intelligence-based comprehensive investigation of ground reaction force (GRF) pattern to classify the healthy control and gait disorders using the large-scale ground reaction force. The used dataset comprised GRF measurements from different patients. The article includes machine learning- and deep learning-based models to classify healthy and gait disorder patients using ground reaction force. A deep learning-based architecture GaitRec-Net is proposed for this classification. The classification results were evaluated using various metrics, and each experiment was analysed using a fivefold cross-validation approach. Compared to machine learning classifiers, the proposed deep learning model is found better for feature extraction resulting in high accuracy of classification. As a result, the proposed framework presents a promising step in the direction of automatic categorization of abnormal gait pattern.

FDA-approved RAF inhibitors poorly inhibit BRAF dimers, which limits their clinical efficacy in tumors expressing BRAFV600E mutant monomers. Here the authors identify FDA-approved Ponatinib as an effective inhibitor of BRAF monomers and dimers and designed PHI1, an inhibitor with a unique mode of action and selectivity for oncogenic BRAF dimers.

Introduction: Proximal humerus fractures account for 4-5% of all fractures and could be managed both conservatively and surgically. As much as 85% minimally or non-displaced fractures can be managed conservatively. In spite of early union and exercise programme by conservative treatment, the problem of shoulder stiffness is common. To overcome stiffness, early mobilisation is mandatory which is not possible in conservative treatment before three weeks. Therefore, surgical intervention is needed for early mobilisation and early return of function. Aim: To compare the functional outcome between the four common methods of managing proximal humerus fractures namely locking plate, Joshi External Stabilisation System (JESS), percutaneous K-wire fixation and conservative method. Materials and Methods: Patients with proximal humerus fracture above 18 years of age between August 2011 to August 2013 were included in the study. The study population was divided into four groups viz., Group A, B, C, D depending on the mode of treatment by locking plate, external fixator, K-wire fixation and conservative method of treatment, respectively. The patients were followed-up at 3 weeks, 6 weeks, 12 weeks, 18 weeks and thereafter every 6 weeks’ interval till 9 months. After union, cases were evaluated radiologically and clinically for functional results by using the Swanson Shoulder Score and Constant Scoring System (Modified). Results: At the end of the study there were 17 patients in the Group ‘A’, 7 patients in the Group ‘B’, 7 patients in the Group ‘C’ and 11 patients in Group ‘D’. At 9 months of follow-up according to modified constant shoulder score the percentage of excellent score in group A was maximum. Group B and Group D had maximum number of good scores. The mean constant shoulder score increased in all groups at 9 months of follow-up as compared to 3 months of follow-up except in group D. Similarly, according to Swanson’s shoulder score, group A had the maximum number of excellent scores. Conclusion: From the above study it can be concluded locking plates are an excellent modality of treatment of proximal humerus fractures with excellent union rate and early mobilisation.

DNA repair mutations (BRCA1 and BRCA2) are found in metastatic castration-resistant prostate cancer (CRPC) patients. Here, we report a case of a 71-year-old male patient with metastatic CRPC along with BRCA2 and PTEN mutations. As per the genomic findings of the Foundation One report, FDA-approved therapies were available for other tumor types, such as olaparib for the loss of BRCA2 and everolimus for the loss of PTEN exons 2–9. These findings were confirmed in another novel phenotypic assay that revealed the sensitivity of olaparib and carboplatin combination therapy. After 4 cycles, our patient achieved a partial response along with a good performance status.

Abstract Axicabtagene ciloleucel (Axi-cel) is a CD-19 Chimeric Antigen Receptor T cell therapy approved for the treatment of relapsed/refractory diffuse large B cell lymphoma. We treated ten patients with DLBCL post-FDA approval in an inner-city tertiary center in the Bronx. Eight patients (80%) had received ≥ 3 lines of therapy, six patients had received prior radiation, and seven had recurrent disease after prior autologous hematopoietic stem cell transplant (AHCT). Our cohort included one patient with HIV, two patients with hepatitis B, and two patients with CNS involvement of lymphoma. Axi-cel treatment led to significant responses with 8/10 patients achieving a complete remission at 3 months, including both patients with prior CNS involvement. The treatment was generally well tolerated with 20% of patients experiencing grade ≥ 2 CRS. One patient each with HIV and hepatitis B responded without significant toxicities. In conclusion, Axi-cel led to significant efficacy with manageable toxicity in DLBCL in a real-world setting.