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Aminoglycosides (AGs) are a class of antibiotics with a broad spectrum of activity. However, their use is limited by safety concerns associated with nephrotoxicity and ototoxicity, as well as drug resistance. To address these issues, semi-synthetic approaches for modifying natural AGs have generated new generations of AGs, however, with limited types of modification due to significant challenges in synthesis. This study explores a novel approach that harness the bacterial biosynthetic machinery of gentamicins and kanamycins to create hybrid AGs. This was achieved by glycodiversification of gentamicins via swapping the glycosyltransferase (GT) in their producer with the GT from kanamycins biosynthetic pathway and resulted in the creation of a series of novel AGs, therefore referred to as genkamicins (GKs). The manipulation of the hybrid biosynthetic pathway enabled the targeted accumulation of different GK species and the isolation and characterization of six GK components. These compounds display retained antimicrobial activity against a panel of World Health Organization (WHO) critical priority pathogens, and GK-C2a, in particular, demonstrates low ototoxicity compared to clinical drugs in zebrafish embryos. This study provides a new strategy for diversifying the structure of AGs and a potential avenue for developing less toxic AG drugs to combat infectious diseases.

Abstract Respiratory failure, intracranial hemorrhage and infection were more common in hyperleukocytic acute myeloid leukemia patients than in non-hyperleukocytic leukemia patients. Compared with non-apheresis treatment, the white blood cells decreased significantly and the infection rate decreased after apheresis treatment. However, the treatment time of leukapheresis in patients with hyperleukocytic leukemia is very long, while it is more damaging to cells. In this study, which conducted a retrospective analysis on patients with hyperleukocytic acute myeloid leukemia, the process of centrifugation of normal cells and patients’ cells by apheresis machine was simulated in vitro. Through selecting 5 healthy persons and 11 patients with hyperleukocytic acute myeloid leukemia, extracting their blood samples and performing in vitro centrifugation at different speeds or duration, we observed the changes of the numbers and morphology of peripheral blood cells in healthy people and patients, so as to explore the optimal centrifugation parameters during leukapheresis. The cells obtained by the optimal centrifugation parameters were cryopreserved and two groups of mice (10 mice in each group) were used to establish leukemia animal models. Through the research, it is found that when the centrifugal speed is below 6000 rpm, the damage to blood cells in healthy people and in patients with hyperleukocytic leukemia is not obvious. When the centrifugal speed is above 6000 rpm, the platelets will be damaged significantly. The cells obtained under the optimal centrifugation parameters can be successfully cryopreserved and used to establish leukemia animal models. This study is of great significance for improving the efficiency and reducing the side effects of leukapheresis, and is helpful to improve the treatment of white blood cells reduction.

Abstract Base editing (BE) faces protospacer adjacent motif (PAM) constraints and off-target effects in both eukaryotes and prokaryotes. For Streptomyces, renowned as one of the most prolific bacterial producers of antibiotics, the challenges are more pronounced due to its diverse genomic content and high GC content. Here, we develop a base editor named eSCBE3-NG-Hypa, tailored with both high efficiency and -fidelity for Streptomyces. Of note, eSCBE3-NG-Hypa recognizes NG PAM and exhibits high activity at challenging sites with high GC content or GC motifs, while displaying minimal off-target effects. To illustrate its practicability, we employ eSCBE3-NG-Hypa to achieve precise key amino acid conversion of the dehydratase (DH) domains within the modular polyketide synthase (PKS) responsible for the insecticide avermectins biosynthesis, achieving domains inactivation. The resulting DH-inactivated mutants, while ceasing avermectins production, produce a high yield of oligomycin, indicating competitive relationships among multiple biosynthetic gene clusters (BGCs) in Streptomyces avermitilis. Leveraging this insight, we use eSCBE3-NG-Hypa to introduce premature stop codons into competitor gene cluster of ave in an industrial S. avermitilis, with the mutant Δolm exhibiting the highest 4.45-fold increase in avermectin B1a compared to the control. This work provides a potent tool for modifying biosynthetic pathways and advancing metabolic engineering in Streptomyces.

Abstract Genetic testing is crucial for precision cancer medicine. However, detecting multiple same-site insertions or deletions (indels) is challenging. Here, we introduce CoHIT (Cas12a-based One-for-all High-speed Isothermal Test), a one-pot CRISPR-based assay for indel detection. Leveraging an engineered AsCas12a protein variant with high mismatch tolerance and broad PAM scope, CoHIT can use a single crRNA to detect multiple NPM1 gene c.863_864 4-bp insertions in acute myeloid leukemia (AML). After optimizing multiple parameters, CoHIT achieves a detection limit of 0.01% and rapid results within 30 minutes, without wild-type cross-reactivity. It successfully identifies NPM1 mutations in 30 out of 108 AML patients and demonstrates potential in monitoring minimal residual disease (MRD) through continuous sample analysis from three patients. The CoHIT method is also competent for detecting indels of KIT, BRAF, and EGFR genes. Integration with lateral flow test strips and microfluidic chips highlights CoHIT’s adaptability and multiplexing capability, promising significant advancements in clinical cancer diagnostics.

Abstract Background Anemia is a common complication of HIV/AIDS, particularly in adolescents and young adults across various countries and regions. However, little is known about the changing prevalence trends of anemia impairment in this population over time. Methods Data on anemia in adolescents and young adults with HIV/AIDS from 1990 to 2019 were collected from the Global Burden of Disease. Prevalence was calculated by gender, region, and country for individuals aged 10–24, and trends were measured using estimating annual percentage changes (EAPC). Results Globally, the prevalence of adolescents and young adults with HIV/AIDS increased from 103.95 per 100,000 population in 1990 to 203.78 in 2019. However, anemia impairment has decreased over the past three decades, with a global percentage decreasing from 70.6% in 1990 to 34.7% in 2019, mainly presenting as mild to moderate anemia and significantly higher in females than males. The largest decreases were observed in Central Sub-Saharan Africa, North America, and Eastern Sub-Saharan Africa, with EAPCs of -2.8, -2.34, and -2.17, respectively. Tajikistan (78.76%) and Madagascar (74.65%) had the highest anemia impairment percentage in 2019, while China (16.61%) and Iceland (13.73%) had the lowest. Anemia impairment was closely related to sociodemographic index (SDI) levels, with a high proportion of impairment in low SDI regions but a stable decreasing trend (EAPC = -0.37). Conclusion Continued anemia monitoring and management are crucial for patients with HIV, especially in high-prevalence regions and among females. Public health policies and interventions can improve the quality of life and reduce morbidity and mortality.

Abstract A serous effusion is a buildup of extra fluid in the serous cavities including pleural, peritoneal, and pericardial cavities. It is important to distinguish benign reactive effusions from effusions caused by malignant proliferation in cytopathology since different diagnoses can lead to completely different disease staging and therapeutic choices. The conventional cytopathology procedure has the disadvantages of low throughput and low objectivity. To enhance the efficiency and accuracy of malignant serous effusion diagnosis, in this paper, an imaging flow cytometry, called optofluidic time‐stretch microscopy is first employed, to image the cells in the serous effusion at an event rate of 100 000 events per second and with a spatial resolution better than 1 µm. The acquired cellular images are then analyzed using a convolutional neural network, by which the malignant cells are accurately detected. The performance of the method is validated with 18 clinical samples, including 14 malignant and 4 benign ones. The results show that the method can detect malignant cells at an accuracy of 90.53%. The high throughput, high accuracy, and high convenience of the method make it a potential solution for malignant serous effusion diagnosis in various scenarios.

Abstract Background Studies have revealed that acute myeloid leukemia (AML) patients are prone to combined cardiac injury. We aimed to identify hematological risk factors associated with cardiac injury in newly diagnosed AML patients before chemotherapy and develop a personalized predictive model. Methods The population baseline, blood test, electrocardiogram, echocardiograph, and genetic and cytogenetic data were collected from newly diagnosed AML patients. The data were subdivided into training and validation cohorts. The independent risk factors were explored by univariate and multivariate logistic regression analysis respectively, and data dimension reduction and variable selection were performed using the least absolute shrinkage and selection operator (LASSO) regression models. The nomogram was generated and the reliability and generalizability were verified by receiver operating characteristic (ROC) curves, the area under the curve (AUC) and calibration curves in an external validation cohort. Results Finally, 499 AML patients were included. After univariate logistic regression, LASSO regression and multivariate logistic regression analysis, abnormal NT-proBNP, NPM1 mutation, WBC, and RBC were independent risk factors for cardiac injury in AML patients (all P

As no unified treatment protocol or evidence yet exists for plasmapheresis without plasma, this study explored the outcomes of using 4% human albumin (ALB) solution as a replacement solution in patients undergoing plasma exchange for multiple myeloma (MM) patients with acute kidney injury (AKI). This study was prospectively registered (ChiCTR2000030640 and NCT05251896). Bortezomib-based chemotherapy plus therapeutic plasmapheresis (TPP) with 4% human ALB solution was assessed for three years in patients with MM aged >18 years, with AKI according to the Kidney Disease Improving Global Outcomes criteria, and without previous renal impairment from other causes. The primary endpoints were changes in renal function over 18 weeks and survival outcomes at 36 months. The secondary endpoints were the incidence of adverse reactions and symptom improvement. Among the 119 patients included in the analysis, 108 experienced renal reactions. The M protein (absolute changes: median −12.12%, interquartile ranges (IQRs) −18.62 to −5.626) and creatine (median −46.91 μmol/L, IQR −64.70 to −29.12) levels decreased, whereas the estimated glomerular filtration rate (eGFR) increased (median 20.66 mL/(min·1.73 m2), IQR 16.03–25.29). Regarding patient survival, 68.1% and 35.3% of patients survived for >12 and >36 months, respectively. The three symptoms with the greatest relief were urine foam, poor appetite, and blurred vision. All 11 patients (7.6%) who experienced mild adverse reactions achieved remission. In conclusion, in MM patients with AKI, plasma-free plasmapheresis with 4% human ALB solution and bortezomib-based chemotherapy effectively alleviated light chain damage to kidney function while improving patient quality of life.

Abstract Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method — multiple genetic abnormality sequencing (MGA-Seq) — to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification. Additionally, by utilizing MGA-Seq, we map focal amplification and oncogene coamplification, thus facilitating the exploration of ecDNA’s transcriptional regulatory function.

Abstract Base editors, which enable targeted locus nucleotide conversion in genomic DNA without double‐stranded breaks, have been engineered as powerful tools for biotechnological and clinical applications. However, the application of base editors is limited by their off‐target effects. Continuously expressed deaminases used for gene editing may lead to unwanted base alterations at unpredictable genomic locations. In the present study, blue‐light‐activated base editors (BLBEs) are engineered based on the distinct photoswitches magnets that can switch from a monomer to dimerization state in response to blue light. By fusing the N‐ and C‐termini of split DNA deaminases with photoswitches Magnets, efficient A‐to‐G and C‐to‐T base editing is achieved in response to blue light in prokaryotic and eukaryotic cells. Furthermore, the results showed that BLBEs can realize precise blue light‐induced gene editing across broad genomic loci with low off‐target activity at the DNA‐ and RNA‐level. Collectively, these findings suggest that the optogenetic utilization of base editing and optical base editors may provide powerful tools to promote the development of optogenetic genome engineering.

Abstract Background Endometrial Cancer (EC) is one of the most prevalent malignancies that affect the female population globally. In the context of immunotherapy, Tumor Mutation Burden (TMB) in the DNA polymerase epsilon (POLE) subtype of this cancer holds promise as a viable therapeutic target. Methods We devised a method known as NEM-TIE to forecast the TMB status of patients with endometrial cancer. This approach utilized a combination of the Network Evolution Model, Transfer Information Entropy, Clique Percolation (CP) methodology, and Support Vector Machine (SVM) classification. To construct the Network Evolution Model, we employed an adjacency matrix that utilized transfer information entropy to assess the information gain between nodes of radiomic-clinical features. Subsequently, using the CP algorithm, we unearthed potentially pivotal modules in the Network Evolution Model. Finally, the SVM classifier extracted essential features from the module set. Results Upon analyzing the importance of modules, we discovered that the dependence count energy in tumor volumes-of-interest holds immense significance in distinguishing TMB statuses among patients with endometrial cancer. Using the 13 radiomic-clinical features extracted via NEM-TIE, we demonstrated that the area under the receiver operating characteristic curve (AUROC) in the test set is 0.98 (95% confidence interval: 0.95–1.00), surpassing the performance of existing techniques such as the mRMR and Laplacian methods. Conclusions Our study proposed the NEM-TIE method as a means to identify the TMB status of patients with endometrial cancer. The integration of radiomic-clinical data utilizing the NEM-TIE method may offer a novel technology for supplementary diagnosis.

Abstract Hematologic malignancies are among the most common cancers, and understanding their incidence and death is crucial for targeting prevention, clinical practice improvement, and research resources appropriately. Here, we investigated detailed information on hematological malignancies for the period 1990–2019 from the Global Burden of Disease study. The age-standardized incidence rate (ASIR), the age-standardized death rate (ASDR), and the corresponding estimated annual percentage changes (EAPC) were calculated to assess temporal trends in 204 countries and territories over the past 30 years. Globally, incident cases of hematologic malignancies have been increasing since 1990, reaching 1343.85 thousand in 2019, but the ASDR for all types of hematologic malignancies has been declining. The ASDR for leukemia, multiple myeloma, non-Hodgkin lymphoma, and Hodgkin lymphoma were 4.26, 1.42, 3.19, and 0.34 per 100,000 population in 2019, respectively, with Hodgkin lymphoma showing the most significant decline. However, the trend varies by gender, age, region, and the country’s economic situation. The burden of hematologic malignancies is generally higher in men, and this gender gap decreases after peaking at a given age. The regions with the largest increasing trend in the ASIR of leukemia, multiple myeloma, non-Hodgkin lymphoma, and Hodgkin lymphoma were Central Europe, Eastern Europe, East Asia, and Caribbean, respectively. In addition, the proportion of deaths attributed to high body-mass index continued to rise across regions, especially in regions with high socio-demographic indices (SDI). Meanwhile, the burden of leukemia from occupational exposure to benzene and formaldehyde was more widespread in areas with low SDI. Thus, hematologic malignancies remain the leading cause of the global tumor burden, with growing absolute numbers but sharp among several age-standardized measures over the past three decades. The results of the study will inform analysis of trends in the global burden of disease for specific hematologic malignancies and develop appropriate policies for these modifiable risks.

Intermodular recognition in polyketide synthase (PKS) is a key prerequisite for catalysis and assembly-line engineering. Here, the authors present a specific domain interaction between modules and an evolution-oriented strategy for PKS engineering derived from the enoylreduction module of azalomycin F.

Introduction: T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy of the lymphoid progenitor cells, contributing to ∼ 20% of the total ALL cases, with a higher prevalence in adults than children. Despite the important role of human T-ALL cell lines in understanding the pathobiology of the disease, a detailed comparison of the tumorigenic potentials of two commonly used T-ALL cell lines, MOLT4 and JURKAT cells, is still lacking.Methodology: In the present study, NOD-PrkdcscidIL2rgdull (NTG) mice were intravenously injected with MOLT4, JURKAT cells, and PBS as a control. The leukemiac cell homing/infiltration into the bone marrow, blood, liver and spleen was investigated for bioluminescence imaging, flow cytometry, and immunohistochemistry staining. Gene expression profiling of the two cell lines was performed via RNA-seq to identify the differentially expressed genes (DEGs). CCR9 identified as a DEG, was further screened for its role in invasion and metastasis in both cell lines in vitro. Moreover, a JURKAT cell line with overexpressed CCR9 (Jurkat-OeCCR9) was investigated for T-ALL formation in the NTG mice as compared to the GFP control. Jurkat-OeCCR9 cells were then subjected to transcriptome analysis to identify the genes and pathways associated with the upregulation of CCR9 leading to enhanced tumirogenesis. The DEGs of the CCR9-associated upregulation were validated both at mRNA and protein levels. Simvastatin was used to assess the effect of cholesterol biosynthesis inhibition on the aggressiveness of T-ALL cells.Results: Comparison of the leukemogenic potentials of the two T-ALL cell lines showed the relatively higher leukemogenic potential of MOLT4 cells, characterized by their enhanced tissue infiltration in NOD-PrkdcscidIL2rgdull (NTG) mice. Transcriptmoe analysis of the two cell lines revealed numerous DEGs, including CCR9, enriched in vital signaling pathways associated with growth and proliferation. Notably, the upregulation of CCR9 also promoted the tissue infiltration of JURKAT cells in vitro and in NTG mice. Transcriptome analysis revealed that CCR9 overexpression facilitated cholesterol production by upregulating the expression of the transcriptional factor SREBF2, and the downstream genes: MSMO1, MVD, HMGCS1, and HMGCR, which was then corroborated at the protein levels. Notably, simvastatin treatment reduced the migration of the CCR9-overexpressing JURKAT cells, suggesting the importance of cholesterol in T-ALL progression.Conclusions: This study highlights the distinct tumorigenic potentials of two T-ALL cell lines and reveals CCR9-regulated enhanced cholesterol biosynthesis in T-ALL.

BackgroundProviding intensive care is increasingly expensive, and the aim of this study was to construct a risk column line graph (nomograms)for prolonged length of stay (LOS) in the intensive care unit (ICU) for patients with chronic obstructive pulmonary disease (COPD).MethodsThis study included 4,940 patients, and the data set was randomly divided into training (n = 3,458) and validation (n = 1,482) sets at a 7:3 ratio. First, least absolute shrinkage and selection operator (LASSO) regression analysis was used to optimize variable selection by running a tenfold k-cyclic coordinate descent. Second, a prediction model was constructed using multifactorial logistic regression analysis. Third, the model was validated using receiver operating characteristic (ROC) curves, Hosmer-Lemeshow tests, calibration plots, and decision-curve analysis (DCA), and was further internally validated.ResultsThis study selected 11 predictors: sepsis, renal replacement therapy, cerebrovascular disease, respiratory failure, ventilator associated pneumonia, norepinephrine, bronchodilators, invasive mechanical ventilation, electrolytes disorders, Glasgow Coma Scale score and body temperature. The models constructed using these 11 predictors indicated good predictive power, with the areas under the ROC curves being 0.826 (95%CI, 0.809–0.842) and 0.827 (95%CI, 0.802–0.853) in the training and validation sets, respectively. The Hosmer-Lemeshow test indicated a strong agreement between the predicted and observed probabilities in the training (χ2 = 8.21, p = 0.413) and validation (χ2 = 0.64, p = 0.999) sets. In addition, decision-curve analysis suggested that the model had good clinical validity.ConclusionThis study has constructed and validated original and dynamic nomograms for prolonged ICU stay in patients with COPD using 11 easily collected parameters. These nomograms can provide useful guidance to medical and nursing practitioners in ICUs and help reduce the disease and economic burdens on patients.

N6-Methyladenosine (m6A) is the most abundant modification in eukaryotic mRNA, and plays important biological functions via regulating RNA fate determination. Recent studies have shown that m6A modification plays a key role in hematologic malignancies, including acute myeloid leukemia. The current growth of epitranscriptomic research mainly benefits from technological progress in detecting RNA m6A modification in a transcriptome-wide manner. In this review, we first briefly summarize the latest advances in RNA m6A biology by focusing on writers, readers, and erasers of m6A modification, and describe the development of high-throughput methods for RNA m6A mapping. We further discuss the important roles of m6A modifiers in acute myeloid leukemia, and highlight the identification of potential inhibitors for AML treatment by targeting of m6A modifiers. Overall, this review provides a comprehensive summary of RNA m6A biology in acute myeloid leukemia.

Background: Thrombocytopenia is a common hematological manifestation in people living with human immunodeficiency virus (HIV) or acquired immune deficiency syndrome (AIDS; PLWHA). Data on the prognostic relationship and associated factors of thrombocytopenia and HIV infection in China are limited. Objectives: We assessed the prevalence of thrombocytopenia, its association with prognosis, and analyzed the associated risk factors among demographic characteristics, comorbidities, hematological and bone marrow indicators. Design: We collected patients identified as PLWHA in Zhongnan Hospital. The patients were divided into two groups: the thrombocytopenia group and the non-thrombocytopenia group. We analyzed and compared demographic characteristics, comorbidities, peripheral blood cells, lymphocyte subpopulations, infection indicators, bone marrow cytology, and bone marrow morphology of the two groups. Then we analyzed the risk factors for thrombocytopenia and the effect of platelet (PLT) values on the prognosis of patients. Methods: Demographic characteristics and laboratory results were obtained from medical records. In contrast to other studies, we included bone marrow cytology and morphology in this study. Data were analyzed with multivariate logistic regression analysis. The Kaplan–Meier method was used to plot 60-month survival curves for the severe, mild, and non-thrombocytopenia groups. The value p

BackgroundAcute myeloid leukemia (AML) is a common hematologic malignancy characterized by poor prognoses and high recurrence rates. Mitochondrial metabolism has been increasingly recognized to be crucial in tumor progression and treatment resistance. The purpose of this study was to examined the role of mitochondrial metabolism in the immune regulation and prognosis of AML.MethodsIn this study, mutation status of 31 mitochondrial metabolism-related genes (MMRGs) in AML were analyzed. Based on the expression of 31 MMRGs, mitochondrial metabolism scores (MMs) were calculated by single sample gene set enrichment analysis. Differential analysis and weighted co-expression network analysis were performed to identify module MMRGs. Next, univariate Cox regression and the least absolute and selection operator regression were used to select prognosis-associated MMRGs. A prognosis model was then constructed using multivariate Cox regression to calculate risk score. We validated the expression of key MMRGs in clinical specimens using immunohistochemistry (IHC). Then differential analysis was performed to identify differentially expressed genes (DEGs) between high- and low-risk groups. Functional enrichment, interaction networks, drug sensitivity, immune microenvironment, and immunotherapy analyses were also performed to explore the characteristic of DEGs.ResultsGiven the association of MMs with prognosis of AML patients, a prognosis model was constructed based on 5 MMRGs, which could accurately distinguish high-risk patients from low-risk patients in both training and validation datasets. IHC results showed that MMRGs were highly expressed in AML samples compared to normal samples. Additionally, the 38 DEGs were mainly related to mitochondrial metabolism, immune signaling, and multiple drug resistance pathways. In addition, high-risk patients with more immune-cell infiltration had higher Tumor Immune Dysfunction and Exclusion scores, indicating poor immunotherapy response. mRNA-drug interactions and drug sensitivity analyses were performed to explore potential druggable hub genes. Furthermore, we combined risk score with age and gender to construct a prognosis model, which could predict the prognosis of AML patients.ConclusionOur study provided a prognostic predictor for AML patients and revealed that mitochondrial metabolism is associated with immune regulation and drug resistant in AML, providing vital clues for immunotherapies.

Dietary risk has always been a major risk factor for colorectal cancer (CRC). However, the contribution of dietary risk factors to CRC at the level of region, gender, and age has not been fully characterized. Based on the Global Burden of Disease (GBD) 2019 study, the death rates, age-standardized mortality rates (ASDRs), and estimated annual percentage changes (EAPCs) were calculated to assess the trends of CRC attributable to dietary risk factors over the past 30 years. Globally, the death cases of CRC increased to 1,085,797 in 2019, and the number of deaths attributed to dietary risk factors increased to 365,752 in 2019, representing approximately one-third of all CRC-related fatalities. Overall, the ASDR attributable to dietary risks was 4.61 per 100,000 in 2019, with a slight downward trend (EAPC = −0.29). Notably, there is a rising trend in early-onset colorectal cancer mortality associated with dietary factors. To alleviate CRC burdens, it is recommended to elevate the intake of whole grains, milk, calcium, and fiber while reducing consumption of red and processed meats. The results will improve the understanding, and provide guidance on the diet of CRC in different regions, gender, and age groups worldwide.

Inborn errors of immunity (IEIs) are a group of inherited disorders caused by mutations in the protein-coding genes involved in innate and/or adaptive immunity. Hematopoietic stem cell transplantation (HSCT) is a mainstay definitive therapy for many severe IEIs. However, the lack of HLA-matched donors increases the risk of developing severe immunological complications. Gene therapy provides long-term clinical benefits and could be an attractive therapeutic strategy for IEIs. In this review, we describe the development and evolution of clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated proteins (Cas) gene-editing systems, including double-strand break (DSB)-based gene editing and DSB-free base editing or prime editing systems. Here, we discuss the advances in and issues associated with CRISPR/Cas gene editing tools and their potential as therapeutic alternatives for IEIs. We also highlight the progress of preclinical studies for the treatment of human genetic diseases, including IEIs, using CRISR/Cas and ongoing clinical trials based on this versatile technology.

Abstract As a crucial biophysical property, red blood cell (RBC) deformability is pathologically altered in numerous disease states, and biochemical and structural changes occur over time in stored samples of otherwise normal RBCs. However, there is still a gap in applying it further to point-of-care blood devices due to the large external equipment (high-resolution microscope and microfluidic pump), associated operational difficulties, and professional analysis. Herein, we revolutionarily propose a smart optofluidic system to provide a differential diagnosis for blood testing via precise cell biophysics property recognition both mechanically and morphologically. Deformation of the RBC population is caused by pressing the hydrogel via an integrated mechanical transfer device. The biophysical properties of the cell population are obtained by the designed smartphone algorithm. Artificial intelligence-based modeling of cell biophysics properties related to blood diseases and quality was developed for online testing. We currently achieve 100% diagnostic accuracy for five typical clinical blood diseases (90 megaloblastic anemia, 78 myelofibrosis, 84 iron deficiency anemia, 48 thrombotic thrombocytopenic purpura, and 48 thalassemias) via real-world prospective implementation; furthermore, personalized blood quality (for transfusion in cardiac surgery) monitoring is achieved with an accuracy of 96.9%. This work suggests a potential basis for next-generation blood smart health care devices.

Abstract CAR T cell therapy has shown dramatic clinical success in relapsed or refractory B-ALL and other hematological malignancies. However, the loss of specific antigens, cell fratricide, T cell aplasia, and normal T cell separation are challenges in treating T cell leukemia/lymphoma with CAR T therapy. CD99 is a promising antigen to target T-ALL and AML as it is strongly expressed on the majority of T-ALL and AML. Here, we isolated a low-affinity CD99 (12E7) antibody, which specifically recognizes leukemia cells over normal blood cells. Moreover, T cells transduced with an anti-CD99-specific CAR that contained the 12E7 scFv expanded with minor fratricide and without normal blood cells toxicity. We observed that our anti-CD99 CAR T cells showed robust cytotoxicity specifically against CD99+ T-ALL cell lines and primary tumor cells in vitro and significantly prolonged cell line-derived xenografts (CDXs) or patient-derived xenografts (PDXs) models survival in vivo. Together, our results demonstrate that anti-CD99 CAR T cells could specifically recognize and efficiently eliminate CD99+ leukemia cells.

Background: The clinical risk classification of acute myelocytic leukemia (AML) is largely based on cytogenetic and molecular genetic detection. However, the optimal treatment for intermediate-risk AML patients remains uncertain. Further refinement and improvement of prognostic stratification are therefore necessary. Objectives: The aim of this study was to identify serum protein biomarkers to refine risk stratification in AML patients. Design: This study is a retrospective study. Methods: Label-free proteomics was used to identify the differential abundance of serum proteins in AML patients. Transcriptomic data were combined to identify key altered markers that could indicate the risk rank of AML patients. The survival status was assessed by Kaplan–Meier and multivariate Cox regression analyses. Results: We delineated serum protein expression in a population of AML patients. Many biological processes were influenced by the identified differentially expressed proteins. Association analysis of transcriptome data showed that intercellular adhesion molecule-2 (ICAM2) had a higher survival prediction value in the intermediate-risk AML group. ICAM2 was detrimental for intermediate-risk AML, regardless of whether patients received bone marrow transplantation. ICAM2 well distinguishes the intermediate group of patients, whose probability of survival is comparable to that of patients with the ELN-2017 according to the reference classification. In addition, newly established stratified clinical features were associated with leukemia stem cell scores. Conclusion: The inclusion of ICAM2 expression into the AML risk classification according to ELN-2017 was a good way to transfer patients from three to two groups. Thus, providing more information for clinical decision-making to improve intermediate-risk stratification in AML patients.

Lysine demethylase 6B (KDM6B) is a histone H3 lysine 27 (H3K27) demethylase that serves as a key mediator of gene transcription. Although KDM6B has been reported to modulate neuroinflammation after ischemic stroke, its role in ischemic brain injury is yet to be well elucidated. Therefore, this study aimed to thoroughly demonstrate the molecular mechanism underlying the effect of KDM6B on neurological function and astrocyte response in post-ischemic brain injury. Middle cerebral artery occlusion/reperfusion (MCAO) mouse models were constructed, while the oxygen-glucose deprivation/reperfusion (OGD/R) model was developed in astrocytes to mimic injury conditions. KDM6B was upregulated post-MCAO in mice and in astrocytes following the induction of OGD/R. Silencing of KDM6B resulted in suppressed neurological deficit, reduced cerebral infarction volume, attenuated neuronal cell apoptosis, and disrupted inflammation. Dual-luciferase reporter gene and chromatin immunoprecipitation-quantitative polymerase chain reaction assays revealed that KDM6B inhibited H3K27 trimethylation in the interferon regulatory factor 4 (IRF4) promoter region, resulting in the upregulation of IRF4 expression, which in turn bound to the Notch2 promoter region to induce its downstream factor SRY-related high-mobility group box 9 (SOX9). SOX9 knockdown reversed the effects of KDM6B overexpression on ischemia-triggered brain damage. Based on these findings, we concluded that KDM6B-mediated demethylation of IRF4 contributes to aggravation of ischemic brain injury through SOX9 activation.

The relationship between newly diagnosed acute leukemia (AL) and heart-related lesions remains unclear. This study aimed to investigate baseline cardiac function and risk of cardiovascular diseases (CVDs) in patients with new-onset AL, and provide data on cardiac management strategies for patients with AL. We retrospectively collected data on baseline characteristics, echocardiography, and biochemical blood indicators (e.g., myocardial enzymes) from 408 patients, 200 with newly diagnosed AL, 103 with coronary artery disease (CAD), and 105 controls from January 1, 2015 to August 31, 2019. The creatine kinase isoenzyme myocardial band, lactate dehydrogenase, highly sensitive troponin-I, and B-type natriuretic peptide levels and left ventricular internal diameter (LVID) were significantly higher in patients with newly diagnosed AL than in the control group. The degree of cardiac damage was lower in newly diagnosed AL patients than in CAD patients. The best predictor of heart damage was LVID (AUC [area under the curve] = 0.709; 95% CI [confidence interval]: 0.637–0.781; p < 0.001), and independent prognostic risk factors were age and ejection fraction (HR [hazard ratio] = 1.636; 95% CI: 1.039–2.575; p = 0.033). The ratio of leukemia blasts among patients with AL was positively correlated with cardiac damage. Our data indicated that newly diagnosed AL patients had certain myocardial damage before treatment. Clinicians need to pay attention to these manifestations, which may be related to the prognosis.

Abstract Acute lymphoblastic leukemia (ALL) is a hematological malignancy characterized by the malignant clonal expansion of lymphoid hematopoietic precursors. It is regulated by various signaling molecules such as cytokines and adhesion molecules in its microenvironment. Chemokines are chemotactic cytokines that regulate migration, positioning and interactions of cells. Many chemokine axes such as CXCL12/CXCR4 and CCL25/CCR9 have been proved to play important roles in leukemia microenvironment and further affect ALL outcomes. In this review, we summarize the chemokines that are involved in ALL progression and elaborate on their roles and mechanisms in leukemia cell proliferation, infiltration, drug resistance and disease relapse. We also discuss the potential of targeting chemokine axes for ALL treatments, since many related inhibitors have shown promising efficacy in preclinical trials, and some of them have entered clinical trials.

Abstract Background Myeloma bone disease (MBD) is a severe complication of multiple myeloma (MM) mainly due to an imbalance between enhanced osteoclast activity and reduced osteoblast function. Previous studies have demonstrated that miRNAs play a vital role in the osteogenic differentiation of mesenchymal stromal cells (MSCs) in MM. However, the value of miR‑302b in MBD remains to be further elucidated. The aim of this study is to explore the role of miR‑302b in the regulation of MBD osteogenic differentiation and evaluate the potential of a new therapeutic strategy for the clinical treatment of MBD. Method Our previous research demonstrated that MiR-302b belongs to the miR-302 cluster and is able to inhibit tumor growth and osteolysis in an orthotopic osteosarcoma xenograft tumor mouse model. In this study, we first transfected miR-302b mimics, miR-302b inhibitor, and miR-302b NC into MM1.S and RPMI8226 MM cells to detect the correlation between miR-302b expression in the pathological specimens and the clinicopathological features by qPCR, the target correlation between miR-302b and DKK1 by immunohistochemistry, qPCR and Western blot, and the correlation between miR-302b and the Wnt/β-catenin signaling pathway by Western blot. The effect of miR-302b on osteoblastogenesis was also studied in a subperiosteal tumorigenesis model of NOD/SCID nude mice. Results We found that increased miR-302b suppressed cell proliferation and induced cell apoptosis in RPMI 8226 and MM1.S cells. TargetScan online bioinformatic analysis predicted that miR-302b is able to bind to 3′UTR of DKK1 mRNA. Target binding of miR-302b to DKK1 was demonstrated by dual-luciferase reporter assay, qPCR, Western blot and immunohistochemistry, indicating that miR-302b is able to degrade DKK1 in RPMI 8226 and MM1.S cells. The model of co-culturing MM cells with preosteoblast MC3T3-E1 cells showed that miR-302b inhibits MM-induced suppression of osteoblast differentiation. Western blotting showed that miR-302b promotes the Wnt/β-catenin signaling pathway in MM cells. Micro-CT and immunohistochemistry results showed that miR-302b suppresses myeloma bone destruction in vivo. Conclusion miR-302b is able to target DKK1 and promote the Wnt/β-catenin signaling pathway in MM.

T-cell acute lymphoblastic leukemia (T-ALL), a form of T-cell malignancy, is a typically aggressive hematological malignancy with high rates of disease relapse and a poor prognosis. Current guidelines do not recommend any specific treatments for these patients, and only allogeneic stem cell transplant, which is associated with potential risks and toxicities, is a curative therapy. Recent clinical trials showed that immunotherapies, including monoclonal antibodies, checkpoint inhibitors, and CAR T therapies, are successful in treating hematologic malignancies. CAR T cells, which specifically target the B-cell surface antigen CD19, have demonstrated remarkable efficacy in the treatment of B-cell acute leukemia, and some progress has been made in the treatment of other hematologic malignancies. However, the development of CAR T-cell immunotherapy targeting T-cell malignancies appears more challenging due to the potential risks of fratricide, T-cell aplasia, immunosuppression, and product contamination. In this review, we discuss the current status of and challenges related to CAR T-cell immunotherapy for T-ALL and review potential strategies to overcome these limitations.

A pandemic designated as Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading worldwide. Up to date, there is no efficient biomarker for the timely prediction of the disease progression in patients. To analyze the inflammatory profiles of COVID-19 patients and demonstrate their implications for the illness progression of COVID-19. Retrospective analysis of 3,265 confirmed COVID-19 cases hospitalized between 10 January 2020, and 26 March 2020 in three medical centers in Wuhan, China. Patients were diagnosed as COVID-19 and hospitalized in Leishenshan Hospital, Zhongnan Hospital of Wuhan University and The Seventh Hospital of Wuhan, China. Univariable and multivariable logistic regression models were used to determine the possible risk factors for disease progression. Moreover, cutoff values, the sensitivity and specificity of inflammatory parameters for disease progression were determined by MedCalc Version 19.2.0. Age (95%CI, 1.017 to 1.048; P

Abstract Background Excessive generation of reactive oxygen species (ROS) in the presence of a defective antioxidant system can induce cellular damage and disrupt normal physiological functions. Several studies have revealed the unfavorable role of ROS in promoting the growth, proliferation, migration, and survival of leukemia cells. In this review study, we summarize the mechanisms of ROS production and its role in leukemogenesis, counteractive effects of antioxidants, and implicate the current ROS-dependent anticancer therapies in acute myeloid leukemia. Body The dysregulation of the redox system is known to play a significant role in the pathogenesis of leukemia. Leukemia cells generate high levels of ROS, which further increases the levels through extra pathways, including mitochondrial deoxyribonucleic mutation, leukemic oncogene activation, increased nicotinamide adenine phosphate hydrogen (NADPH), and cytochrome P450 activities. Aforementioned pathways once activated have shown to promote genomic instability, induce drug resistance to leukemia medical therapy, disease relapse and reduce survival period. The current standard of treatment with chemotherapy employs the pro-oxidant approach to induce apoptosis and promote tumor regression. However, this approach retains several deleterious effects on the subject resulting in degradation of the quality of life. Nevertheless, the addition of an antioxidant as an adjuvant drug to chemotherapy alleviates treatment-related toxicity, increases chemotherapeutic efficacy, and improves survival rates of a patient. Conclusion Acute myeloid leukemia remains a daunting challenge to clinicians. The desire to achieve the maximum benefit of chemotherapy but also improve patient outcomes is investigated. ROS generated through several pathways promotes leukemogenesis, drug resistance, and disease relapse. Chemotherapy, the mainstay of treatment, further upregulates ROS levels. Therefore, the addition of an antioxidant to leukemia medical therapy alleviates toxicity and improves patient outcomes.

Hematologic malignancies are one of the most common malignant tumors caused by the clonal proliferation and differentiation of hematopoietic and lymphoid stem cells. The examination of bone marrow cells combined with immunodeficiency typing is of great significance to the diagnostic type, treatment and prognosis of hematologic malignancies. Super-resolution fluorescence microscopy (SRM) is a special kind of optical microscopy technology, which breaks the resolution limit and was awarded the Nobel Prize in Chemistry in 2014. With the development of SRM, many related technologies have been applied to the diagnosis and treatment of clinical diseases. It was reported that a major type of SRM technique, single molecule localization microscopy (SMLM), is more sensitive than flow cytometry (FC) in detecting cell membrane antigens’ expression, thus enabling better chances in detecting antigens on hematopoietic cells than traditional analytic tools. Furthermore, SRM may be applied to clinical pathology and may guide precision medicine and personalized medicine for clone hematopoietic cell diseases. In this paper, we mainly discuss the application of SRM in clone hematological malignancies.

PurposeThe study aimed to assess factors associated with early infection and identify patients at high risk of developing infection in multiple myeloma.MethodsThe study retrospectively analyzed patients with MM seen at two medical centers between January 2013 and June 2019. One medical center reported 745 cases, of which 540 of the cases were available for analysis and were further subdivided into training cohort and internal validation cohort. 169 cases from the other medical center served as an external validation cohort. The least absolute shrinkage and selection operator (Lasso) regression model was used for data dimension reduction, feature selection, and model building.ResultsBacteria and the respiratory tract were the most common pathogen and localization of infection, respectively. In the training cohort, PS≥2, HGB

Multiple myeloma (MM) is a hematological malignancy of plasma cell origin. Cardiac amyloidosis (CA) is a common form of heart damage caused by MM and is associated with a poor prognosis. This study was a prospective cohort study and was aimed at evaluating the clinical predictive value of extracellular volume fraction (ECV) based on cardiovascular magnetic resonance (CMR) T1 mapping for cardiac amyloidosis and cardiac dysfunction in MM patients. Fifty-one newly diagnosed MM patients in Zhongnan Hospital of Wuhan University were enrolled in the study. A total of 19 patients (19/51; 37.25%) developed CA. The basal ECV of CA group was significantly higher than that of the non-CA group (p

Abstract Background Infection is a leading cause of morbidity and death in patients with multiple myeloma (MM). The increased susceptibility to infection is complicated and multifactorial. However, no studies have explored the spectrum and risk factors of infections in newly diagnosed MM patients at the first admission. This cross-sectional study aimed to provide ideas for the assessment, prevention and treatment of infection in newly diagnosed MM patients when admitted for the first time. Methods Retrospectively, the data from electronic medical records for 161 patients newly diagnosed with MM from May 2013 to December 2018 were analysed. All the information was collected at the time of admission, and the patients had received no antineoplastic therapy previously. Independent risk factors of infection in multiple myeloma were determined by univariate and multivariate analysis. Results Newly diagnosed patients with MM were highly susceptible to viruses (43.9%), especially Epstein-Barr virus (EBV) (24.4%) and hepatitis B virus (HBV) (17.1%). Advanced stage (ISS stage III, P = 0.040), more severe anaemia (Hb 10 mg/L, P = 0.006) were independent risk factors for infection. Moreover, infections represented a major survival threat to patients with newly diagnosed MM (P = 0.033), and the existence of risk factors for infection was significantly correlated with poor prognosis (P = 0.011), especially ISS stage III (P = 0.008) and lower haemoglobin level (P = 0.039). Conclusions Newly diagnosed MM patients are highly susceptible to viruses. Advanced ISS stage, more severe anaemia and the elevation of CRP are independent risk factors of infection, which also have a strong impact on prognosis. Our results suggest that viral infection should be taken into account if antibacterial drugs are not effective, and the prevention of infection and improvement of prognosis should be paid more attention in newly diagnosed patents with advanced stage and more severe anaemia.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can cause acute respiratory distress syndrome, hypercoagulability, hypertension, and multiorgan dysfunction. Effective antivirals with safe clinical profile are urgently needed to improve the overall prognosis. In an analysis of a randomly collected cohort of 124 patients with COVID-19, we found that hypercoagulability as indicated by elevated concentrations of D-dimers was associated with disease severity. By virtual screening of a U.S. FDA approved drug library, we identified an anticoagulation agent dipyridamole (DIP) in silico, which suppressed SARS-CoV-2 replication in vitro. In a proof-of-concept trial involving 31 patients with COVID-19, DIP supplementation was associated with significantly decreased concentrations of D-dimers (P

Abstract Isolation of viable circulating tumor cells (CTC) holds the promise for improving screening, early diagnosis, and personalized treatment of lymphoma. In this study, we isolated and characterized spontaneously immortalized B‐lymphocyte (SIBC) lines from HIV‐infected patients with and without Non‐Hodgkin's Lymphoma (AIDS‐NHL). A total of 22 SIBC lines was isolated from peripheral blood mononuclear cells (PBMC) of HIV‐infected patients with (n = 40) and without (n = 77) clinically detectable NHL, but not from healthy individuals (n = 34). Of these, 8 SIBC lines named HIV‐SIBC were generated from HIV‐infected patients without AIDS‐NHL (10%, 8/77), while 14 SIBCs named AIDS‐NHL‐SIBC were from 13 of the AIDS‐NHL patients (32.5%, 13/40). Among the 14 AIDS‐NHL‐SIBCs, 12 were derived from AIDS‐NHL patients with poor prognoses (survival time less than 1 year). SIBCs displayed markers typical of memory B cells (CD3‐CD20+CD27+) with EBV infection. Moreover, AIDS‐NHL‐SIBCs were representative of CTC as evidenced by monoclonal Ig gene rearrangement, abnormal chromosomal karyotype, and the formation of xenograft tumors, while HIV‐SIBCs generated harbored some features of tumor cells, none had the capacity of xenograft tumor formation, suggesting HIV‐SIBC present the precursor of CTC. These results indicate that SIBCs is associated with poor prognosis in AIDS‐NHL patients and can be isolated from HIV‐infected patients with NHL and without NHL. This findings point to the need for further molecular characterization and functional studies of SIBCs, which may prove the value of SIBCs in the diagnosis, prognoses, and screening for NHL among HIV‐infected patients.

Background: Thrombocytosis is a common symptom in myeloproliferative neoplasms (MPN), and excessive proliferation may deteriorate into thrombosis, bleeding, myelofibrosis, and may ultimately convert to acute leukemia. This study aimed to investigate the collection efficiency of plateletpheresis (CEPP) and factors influencing its efficacy in patients with thrombocytosis.Materials and Methods: From September 2010 to December 2016, 81 patients from two institutions in China with myeloproliferative neoplasms and thrombocytosis accompanied by severe symptoms were treated with plateletpheresis by Fresenius COM. TEC machine.Results: After apheresis, the median CEPP was 20.71% (IQR: 9.99–36.69%) and median PLT reduction rate was 25.87% (IQR: 21.78–36.23%). Further analysis showed that no significant difference was observed between PLT count with 800–1,000 × 109/L and > 1,000 × 109/L. The PLT counts significantly decreased (P < 0.001) after plateletpheresis, the red blood cell (RBC), white blood cell (WBC), hemoglobin (HGB), and hematocrit (HCT) levels showed no significant differences before- or after- plateletpheresis. Multivariate analysis showed that female sex (P = 0.009) and HGB (P = 0.010) before apheresis were associated with CEPP. Female (P = 0.022), HCT (P = 0.001) and blood volume (P = 0.015) were associated with the PLT reduction rate. Furthermore, symptoms were relieved after apheresis in patients whose PLT count was 800–1,000 × 109/L accompanied with symptoms.Conclusions: It is reasonable to perform plateletpheresis when the PLT count is over 800 × 109/L and patients are complicated by clinical symptoms such as dizziness, headache, somnolence, and stupor. Plateletpheresis is effective in removing PLTs especially in females with high HGB.

Sensitive and efficient detection of drug-resistant mutations is essential in cancer precision medicine. In treating acute myeloid leukemia (AML), FLT3 gene F691L mutation shows universal resistance to all currently available FLT3 inhibitors. However, there is no particular detection method for FLT3-F691L. Commonly-used first-generation sequencing (FGS) approaches have low sensitivity, and next-generation sequencing (NGS) is time-consuming. Herein, we developed an accurate and sensitive FLT3-F691L diagnostic method by CRISPR detection. Briefly, the FLT3-691 region is amplified by recombinase polymerase amplification (RPA) and detected by L691-crRNA induced Cas12a reaction, and finally the result can be directly observed under a blue lamp or analyzed by a fluorescence reader. Confirmed by the tests on diluted plasmids and 120 AML patient samples, this method can achieve a sensitivity of 0.1% and complete the whole diagnosis process within 40 min. Potentially, this method will play an important role in point-of-care applications and guidance of AML treatment.

Background: The outbreak of COVID-19 attracted the attention of the whole world. Our study aimed to explore the predictors for the survival of patients with COVID-19 by machine learning.Methods: We conducted a retrospective analysis and used the idea of machine learning to train the data of COVID-19 patients in Leishenshan Hospital through the logical regression algorithm provided by scikit-learn.Results: Of 2010 patients, 42 deaths were recorded until March 29, 2020. The mortality rate was 2.09%. There were 6,812 records after data features combination and data arrangement, 3,025 records with high-quality after deleting incomplete data by manual checking, and 5,738 records after data balancing finally by the method of Borderline-1 Smote. The results of 10 times of data training by logistic regression model showed that albumin, saturation of pulse oxygen at admission, alanine aminotransferase, and percentage of neutrophils were possibly associated with the survival of patients. The results of 10 times of data training including age, sex, and height beyond the laboratory measurements showed that percentage of neutrophils, saturation of pulse oxygen at admission, alanine aminotransferase, sex, and albumin were possibly associated with the survival of patients. The rates of precision, recall, and f1-score of the two training models were all higher than 0.9 and relatively stable.Conclusions: We demonstrated that percentage of neutrophils, saturation of pulse oxygen at admission, alanine aminotransferase, sex, and albumin were possibly associated with the survival of patients with COVID-19.

Objective: Early identification of coronavirus disease 2019 (COVID-19) patients with worse outcomes may benefit clinical management of patients. We aimed to quantify pneumonia findings on CT at admission to predict progression to critical illness in COVID-19 patients.Methods: This retrospective study included laboratory-confirmed adult patients with COVID-19. All patients underwent a thin-section chest computed tomography (CT) scans showing evidence of pneumonia. CT images with severe moving artifacts were excluded from analysis. Patients' clinical and laboratory data were collected from medical records. Three quantitative CT features of pneumonia lesions were automatically calculated using a care.ai Intelligent Multi-disciplinary Imaging Diagnosis Platform Intelligent Evaluation System of Chest CT for COVID-19, denoting the percentage of pneumonia volume (PPV), ground-glass opacity volume (PGV), and consolidation volume (PCV). According to Chinese COVID-19 guidelines (trial version 7), patients were divided into noncritical and critical groups. Critical illness was defined as a composite of admission to the intensive care unit, respiratory failure requiring mechanical ventilation, shock, or death. The performance of PPV, PGV, and PCV in discrimination of critical illness was assessed. The correlations between PPV and laboratory variables were assessed by Pearson correlation analysis.Results: A total of 140 patients were included, with mean age of 58.6 years, and 85 (60.7%) were male. Thirty-two (22.9%) patients were critical. Using a cutoff value of 22.6%, the PPV had the highest performance in predicting critical illness, with an area under the curve of 0.868, sensitivity of 81.3%, and specificity of 80.6%. The PPV had moderately positive correlation with neutrophil (%) (r = 0.535, p < 0.001), erythrocyte sedimentation rate (r = 0.567, p < 0.001), d-Dimer (r = 0.444, p < 0.001), high-sensitivity C-reactive protein (r = 0.495, p < 0.001), aspartate aminotransferase (r = 0.410, p < 0.001), lactate dehydrogenase (r = 0.644, p < 0.001), and urea nitrogen (r = 0.439, p < 0.001), whereas the PPV had moderately negative correlation with lymphocyte (%) (r = −0.535, p < 0.001).Conclusions: Pneumonia volume quantified on initial CT can non-invasively predict the progression to critical illness in advance, which serve as a prognostic marker of COVID-19.

Natural killer (NK) cells are prominent cytotoxic and cytokine-producing components of the innate immune system representing crucial effector cells in cancer immunotherapy. Presently, various NK cell-based immunotherapies have contributed to the substantial improvement in the reconstitution of NK cells against advanced-staged and high-risk AML. Various NK cell sources, including haploidentical NK cells, adaptive NK cells, umbilical cord blood NK cells, stem cell-derived NK cells, chimeric antigen receptor NK cells, cytokine-induced memory-like NK cells, and NK cell lines have been identified. Devising innovative approaches to improve the generation of therapeutic NK cells from the aforementioned sources is likely to enhance NK cell expansion and activation, stimulate ex vivo and in vivo persistence of NK cells and improve conventional treatment response of myeloid leukemia. The tumor-promoting properties of the tumor microenvironment and downmodulation of NK cellular metabolic activity in solid tumors and hematological malignancies constitute a significant impediment in enhancing the anti-tumor effects of NK cells. In this review, we discuss the current NK cell sources, highlight ongoing interventions in enhancing NK cell function, and outline novel strategies to circumvent immunosuppressive factors in the tumor microenvironment to improve the efficacy of NK cell-based immunotherapy and expand their future success in treating myeloid leukemia.

Umbilical cord mesenchymal stem cells (UC-MSCs) are a class of multifunctional stem cells isolated and cultured from umbilical cord. They possessed the characteristics of highly self-renewal, multi-directional differentiation potential and low immunogenicity. Its application in the field of tissue engineering and gene therapy has achieved a series of results. Recent studies have confirmed their characteristics of inhibiting tumor cell proliferation and migration to nest of cancer. The ability of UC-MSCs to support hematopoietic microenvironment and suppress immune system suggests that they can improve engraftment after hematopoietic stem cell transplantation, which shows great potential in treatment of hematologic diseases. This review will focus on the latest advances in biological characteristics and mechanism of UC-MSCs in treatment of hematological diseases.

The coronavirus disease 2019 (COVID-19) is widely spread and remains a global pandemic. Limited evidence on the systematic evaluation of the impact of treatment regimens on antibody responses exists. Our study aimed to analyze the role of antibody response on prognosis and determine factors influencing the IgG antibodies’ seroconversion. A total of 1,111 patients with mild to moderate COVID-19 symptoms admitted to Leishenshan Hospital in Wuhan were retrospectively analyzed. A serologic SARS-CoV-2 IgM/IgG antibody test was performed on all the patients 21 days after the onset of symptoms. Patient clinical characteristics were compared. In the study, 42 patients progressed to critical illness, with 6 mortalities reported while 1,069 patients reported mild to moderate disease. Advanced age (P = 0.028), gasping (P

Breast cancer is one of the most common types of cancer and is the leading cause of cancer-related death. Diagnosis of breast cancer is based on the evaluation of pathology slides. In the era of digital pathology, these slides can be converted into digital whole slide images (WSIs) for further analysis. However, due to their sheer size, digital WSIs diagnoses are time consuming and challenging. In this study, we present a lightweight architecture that consists of a bilinear structure and MobileNet-V3 network, bilinear MobileNet-V3 (BM-Net), to analyze breast cancer WSIs. We utilized the WSI dataset from the ICIAR2018 Grand Challenge on Breast Cancer Histology Images (BACH) competition, which contains four classes: normal, benign, in situ carcinoma, and invasive carcinoma. We adopted data augmentation techniques to increase diversity and utilized focal loss to remove class imbalance. We achieved high performance, with 0.88 accuracy in patch classification and an average 0.71 score, which surpassed state-of-the-art models. Our BM-Net shows great potential in detecting cancer in WSIs and is a promising clinical tool.

Blood cell analysis is essential for the diagnosis and identification of hematological malignancies. The use of digital microscopy systems has been extended in clinical laboratories. Super-resolution microscopy (SRM) has attracted wide attention in the medical field due to its nanoscale spatial resolution and high sensitivity. It is considered to be a potential method of blood cell analysis that may have more advantages than traditional approaches such as conventional optical microscopy and hematology analyzers in certain examination projects. In this review, we firstly summarize several common blood cell analysis technologies in the clinic, and analyze the advantages and disadvantages of these technologies. Then, we focus on the basic principles and characteristics of three representative SRM techniques, as well as the latest advances in these techniques for blood cell analysis. Finally, we discuss the developmental trend and possible research directions of SRM, and provide some discussions on further development of technologies for blood cell analysis.

Chromosome karyotype analysis is of great clinical importance in the diagnosis and treatment of diseases. Since manual analysis is highly time and effort consuming, computer-assisted automatic chromosome karyotype analysis based on images is routinely used to improve the efficiency and accuracy of the analysis. However, the strip-shaped chromosomes easily overlap each other when imaged, significantly affecting the accuracy of the subsequent analysis and hindering the development of chromosome analysis instruments. In this paper, we present an adversarial, multiscale feature learning framework to improve the accuracy and adaptability of overlapping chromosome segmentation. We first adopt the nested U-shaped network with dense skip connections as the generator to explore the optimal representation of the chromosome images by exploiting multiscale features. Then we use the conditional generative adversarial network (cGAN) to generate images similar to the original ones; the training stability of the network is enhanced by applying the least-square GAN objective. Finally, we replace the common cross-entropy loss with the advanced Lovász-Softmax loss to improve the model’s optimization and accelerate the model’s convergence. Comparing with the established algorithms, the performance of our framework is proven superior by using public datasets in eight evaluation criteria, showing its great potential in overlapping chromosome segmentation.