Peripheral immune cell profiling of double-hit lymphoma by mass cytometry.

BACKGROUND: Double-hit or Triple-hit lymphoma (DHL/THL) is a subset of high-grade B cell lymphoma harboring rearrangements of MYC and BCL2 and/or BCL6, and usually associate with aggressive profile, while current therapies tend to provide poor clinical outcomes and eventually relapsed. Further explorations of DHL at cellular and molecular levels are in demand to offer guidance for clinical activity. METHODS: We collected the peripheral blood of DHL patients and diffused large B cell lymphoma (DLBCL) patients from single institute and converted them into PBMC samples. Mass cytometry was then performed to characterize these samples by 42 antibody markers with samples of healthy people as control. We divided the immune cell subtypes based on the expression profile of surface antigens, and the proportion of each cell subtype was also analyzed. By comparing the data of the DLBCL group and the healthy group, we figured out the distinguished immune cell subtypes of DHL patients according to their abundance and marker expression level. We further analyzed the heterogeneity of DHL samples by pairwise comparison based on clinical characteristics. RESULTS: We found double-positive T cells (DPT) cells were in a significantly high percentage in DHL patients, whereas the ratio of double-negative T cells (DNT) was largely reduced in patients. Besides, CD38 was uniquely expressed at a high level on some naïve B cells of DHL patients, which could be a marker for the diagnosis of DHL (distinguishing from DLBCL), or even be a drug target for the treatment of DHL. In addition, we illustrated the heterogeneity of DHL patients in terms of immune cell landscape, and highlighted TP53 as a major factor that contributes to the heterogeneity of the T cells profile. CONCLUSION: Our study demonstrated the distinct peripheral immune cell profile of DHL patients by contrast to DLBCL patients and healthy people, as well as the heterogeneity within the DHL group, which could provide valuable guidance for the diagnosis and treatment of DHL.

Discovery of mobocertinib, a potent, oral inhibitor of EGFR exon 20 insertion mutations in non-small cell lung cancer.

In the treatment of non-small cell lung cancer (NSCLC), patients harboring exon 20 insertion mutations in the epidermal growth factor receptor (EGFR) gene (EGFR) have few effective therapies because this subset of mutants is generally resistant to most currently approved EGFR inhibitors. This report describes the structure-guided design of a novel series of potent, irreversible inhibitors of EGFR exon 20 insertion mutations, including the V769_D770insASV and D770_N771insSVD mutants. Extensive structure-activity relationship (SAR) studies led to the discovery of mobocertinib (compound 21c), which inhibited growth of Ba/F3 cells expressing the ASV insertion with a half-maximal inhibitory concentration of 11 nM and with selectivity over wild-type EGFR. Daily oral administration of mobocertinib induced tumor regression in a Ba/F3 ASV xenograft mouse model at well-tolerated doses. Mobocertinib was approved in September 2021 for the treatment of adult patients with advanced NSCLC with EGFR exon 20 insertion mutations with progression on or after platinum-based chemotherapy.

Cadmium exposure impairs skeletal muscle function by altering lipid signature and inducing inflammation in C57BL/6J mice.

Cadmium (Cd) is a well-known environmental pollutant with high toxicity. Despite a variety of studies have demonstrated that Cd exposure induces multiple organ damages in humans, there is still a lack of knowledge of Cd induced skeletal muscle impairment. Exercise is a non-invasive, effective intervention to improve human health and combat diseases. In this study, we aimed to evaluate the toxic effects of Cd exposure on skeletal muscle function and explore the possibility of exercise for attenuating skeletal muscle toxicity of chronic Cd exposure. C57BL/6J mice were exposed to Cd via drinking water containing CdCl2 10 mg/dL for 8 weeks while a moderate exercise was daily induced by a motorized treadmill to mice. It was found that Cd exposure significantly reduced the ratio of gastrocnemius and body weight, decreased mouse exercise capacity, weakened muscle strength, promoted lipid accumulation and up-regulated pro-apoptotic genes in the skeletal muscle. Non-targeted lipidomics analysis indicated that Cd exposure disturbed lipid metabolism, altered lipid signatures and elevated pro-inflammatory lipid species in the skeletal muscle. Moreover, Cd exposure evoked an intense inflammatory response in the skeletal muscle by up-regulating pro-inflammatory cytokine production such as Eotaxin (CCL11), TNF-α, IL-1ß, IL-6, RANTES (CCL5) and so on. Notably, treadmill exercise effectively protected against Cd induced skeletal muscle impairment indicated by the effects of inhibiting lipid metabolism disturbance, suppressing pro-inflammatory cytokine production and preserving skeletal muscle function. These results demonstrated that environment relevant Cd exposure impairs skeletal muscle function and exercise effectively antagonizes the Cd toxicity in the skeletal muscle and preserves skeletal muscle function. This study provided the novel evidence for unraveling Cd toxicity on the skeletal muscle function and highlighted the possibility of considering exercise as a countermeasure for Cd induced skeletal muscle impairment at population level.

Interindividual variability in average glucose-glycated haemoglobin relationship in type 1 diabetes and implications for clinical practice.

AIM: Glycated haemoglobin (HbA1c) can fail to reflect average glucose levels, potentially compromising management decisions. We analysed variability in the relationship between mean glucose and HbA1c in individuals with diabetes. MATERIALS AND METHODS: Three months of continuous glucose monitoring and HbA1c data were obtained from 216 individuals with type 1 diabetes. Universal red blood cell glucose transporter-1 Michaelis constant KM and individualized apparent glycation ratio (AGR) were calculated and compared across age, racial and gender groups. RESULTS: The mean age (range) was 30 years (8-72) with 94 younger than 19 years, 78 between 19 and 50 years, and 44 were >50 years. The group contained 120 women and 96 men with 106 white and 110 black individuals. The determined KM value was 464 mg/dl and AGR was (mean ± SD) 72.1 ± 7 ml/g. AGR, which correlated with red blood cell lifespan marker, was highest in those aged >50 years at 75.4 ± 6.9 ml/g, decreasing to 73.2 ± 7.8 ml/g in 19-50 years, with a further drop to 71.0 ± 5.8 ml/g in the youngest group (p <0 .05). AGR differed between white and black groups (69.9 ± 5.8 and 74.2 ± 7.1 ml/g, respectively; p < .001). In contrast, AGR values were similar in men and women (71.5 ± 7.5 and 72.5 ± 6.6 ml/g, respectively; p = .27). Interestingly, interindividual AGR variation within each group was at least four-fold higher than average for between-group variation. CONCLUSIONS: In this type 1 diabetes cohort, ethnicity and age, but not gender, alter the HbA1c-glucose relationship with even larger interindividual variations found within each group than between groups. Clinical application of personalized HbA1c-glucose relationships has the potential to optimize glycaemic care in the population with diabetes.

Real world hypoglycaemia related to glucose variability and Flash glucose scan frequency assessed from global FreeStyle Libre data.

AIM: Flash glucose monitoring provides a range of glucose metrics. In the current study, we aim to identify those that indicate that glycaemic targets can be consistently met and contrast the total (t-CV) and within-day coefficient of variation (wd-CV) to guide the assessment of glucose variability and hypoglycaemia exposure. METHODS: De-identified data from Flash readers were collected. The readers were sorted into 10 equally sized groups of scan frequency followed by quartiles of estimated A1c (eA1c). A similar grouping was performed for the total coefficient of variation (t-CV) and within-day coefficient of variation (wd-CV). In addition, analysis of the association of time below 54 mg/dl and glucose variability measured by t-CV and wd-CV was performed. RESULTS: The dataset included 1 002 946 readers. Readers sorted by 10 equal groups of scan rate and quartiles by eA1c, t-CV and wd-CV represented 25 074 readers per group. The association of lower eA1c with higher time in range and reduced time above range was clear. The correlation of eA1c quartiles and time below range was not consistent. An association between glucose variability and hypoglycaemia was found. Both wd-CV and t-CV were associated with time below range. For achieving the consensus target of <1% time below 54 mg/dl, the associated wd-CV and t-CV values were 33.5% and 39.5%, respectively. CONCLUSIONS: The type of CV reported by the different continuous glucose monitoring systems should be acknowledged. CV <36% might not be adequate to ensure low hypoglycaemia exposure. To our knowledge, the majority of continuous glucose monitoring reports the t-CV. Appropriate thresholds should be used to identify patients that would probably meet time below range targets (t-CV <40% or wd-CV <34%).

Evaluation of continuous glucose monitoring-derived person-specific HbA1c in the presence and absence of complications in type 1 diabetes.

AIM: To evaluate the accuracy of a novel kinetic model at predicting HbA1c in a real-world setting and to understand and explore the role of diabetes complications in altering the glucose-HbA1c relationship and the mechanisms involved. MATERIALS AND METHODS: Deidentified HbA1c and continuous glucose monitoring values were collected from 93 individuals with type 1 diabetes. Person-specific kinetic variables were used, including red blood cell (RBC) glucose uptake and lifespan, to characterize the relationship between glucose levels and HbA1c. The resulting calculated HbA1c (cHbA1c) was compared with glucose management indicator (GMI) for prospective agreement with laboratory HbA1c. RESULTS: The cohort (42 men and 51 women) had a median age (IQR) of 61 (43, 72) years and a diabetes duration of 21 (10, 33) years. A total of 24 459 days of continuous glucose monitoring (CGM) data were available and 357 laboratory HbA1c were used to assess the average glucose-HbA1c relationship. cHbA1c had a superior correlation with laboratory HbA1c compared with GMI with a mean absolute deviation of 1.7 and 6.7 mmol/mol, r2  = 0.85 and 0.44, respectively. The fraction within 10% of absolute relative deviation from laboratory HbA1c was 93% for cHbA1c and 63% for GMI. Macrovascular disease had no effect on the model's accuracy, whereas microvascular complications resulted in a trend towards higher HbA1c, secondary to increased RBC glucose uptake. CONCLUSIONS: cHbA1c, which takes into account RBC glucose uptake and lifespan, accurately reflects laboratory HbA1c in a real-world setting and can aid in the management of individuals with diabetes.

CRNNTL: Convolutional Recurrent Neural Network and Transfer Learning for QSAR Modeling in Organic Drug and Material Discovery.

Molecular latent representations, derived from autoencoders (AEs), have been widely used for drug or material discovery over the past couple of years. In particular, a variety of machine learning methods based on latent representations have shown excellent performance on quantitative structure-activity relationship (QSAR) modeling. However, the sequence feature of them has not been considered in most cases. In addition, data scarcity is still the main obstacle for deep learning strategies, especially for bioactivity datasets. In this study, we propose the convolutional recurrent neural network and transfer learning (CRNNTL) method inspired by the applications of polyphonic sound detection and electrocardiogram classification. Our model takes advantage of both convolutional and recurrent neural networks for feature extraction, as well as the data augmentation method. According to QSAR modeling on 27 datasets, CRNNTL can outperform or compete with state-of-art methods in both drug and material properties. In addition, the performances on one isomers-based dataset indicate that its excellent performance results from the improved ability in global feature extraction when the ability of the local one is maintained. Then, the transfer learning results show that CRNNTL can overcome data scarcity when choosing relative source datasets. Finally, the high versatility of our model is shown by using different latent representations as inputs from other types of AEs.

Discovery of imidazo[1,2-a]-pyridine inhibitors of pan-PI3 kinases that are efficacious in a mouse xenograft model.

Alterations in PI3K/AKT signaling are known to be implicated with tumorigenesis. The PI3 kinases family of lipid kinases has been an attractive therapeutic target for cancer treatment. Imidazopyridine compound 1, a potent, selective, and orally available pan-PI3K inhibitor, identified by scaffold morphing of a benzothiazole hit, was further optimized in order to achieve efficacy in a PTEN-deleted A2780 ovarian cancer mouse xenograft model. With a hypothesis that a planar conformation between the core and the 6-heteroaryl ring will allow for the accommodation of larger 5'-substituents in a hydrophobic area under P-loop, SAR efforts focused on 5'-alkoxy heteroaryl rings at the 6-position of imidazopyridine and imidazopyridazine cores that have the same dihedral angle of zero degrees. 6'-Alkoxy 5'-aminopyrazines in the imidazopyridine series were identified as the most potent compounds in the A2780 cell line. Compound 14 with 1,1,1-trifluoroisopropoxy group at 6'-position demonstrated excellent potency and selectivity, good oral exposure in rats and in vivo efficacy in A2780 tumor-bearing mouse. Also, we disclose the X-ray co-crystal structure of one enantiomer of compound 14 in PI3Kα, confirming that the trifluoromethyl group fits nicely in the hydrophobic hot spot under P-loop.

FOCUS--Development of a Global Communication and Modeling Platform for Applied and Computational Medicinal Chemists.

Communication of data and ideas within a medicinal chemistry project on a global as well as local level is a crucial aspect in the drug design cycle. Over a time frame of eight years, we built and optimized FOCUS, a platform to produce, visualize, and share information on various aspects of a drug discovery project such as cheminformatics, data analysis, structural information, and design. FOCUS is tightly integrated with internal services that involve-among others-data retrieval systems and in-silico models and provides easy access to automated modeling procedures such as pharmacophore searches, R-group analysis, and similarity searches. In addition, an interactive 3D editor was developed to assist users in the generation and docking of close analogues of a known lead. In this paper, we will specifically concentrate on issues we faced during development, deployment, and maintenance of the software and how we continually adapted the software in order to improve usability. We will provide usage examples to highlight the functionality as well as limitations of FOCUS at the various stages of the development process. We aim to make the discussion as independent of the software platform as possible, so that our experiences can be of more general value to the drug discovery community.

Identifying topology of distribution substation in power Internet of Things using dynamic voltage load fluctuation flow analysis.

At present, the reconfiguration, maintenance, and review of power lines play a pivotal role in maintaining the stability of electrical grid operations and ensuring the accuracy of electrical energy measurements. These essential tasks not only guarantee the uninterrupted functioning of the power system, thereby improving the reliability of the electricity supply but also facilitate precise electricity consumption measurement. In view of these considerations, this article endeavors to address the challenges posed by power line restructuring, maintenance, and inspections on the stability of power grid operations and the accuracy of energy metering. To accomplish this goal, this article introduces an enhanced methodology based on the hidden Markov model (HMM) for identifying the topology of distribution substations. This approach involves a thorough analysis of the characteristic topology structures found in low-voltage distribution network (LVDN) substations. A topology identification model is also developed for LVDN substations by leveraging time series data of electricity consumption measurements and adhering to the principles of energy conservation. The HMM is employed to streamline the dimensionality of the electricity consumption data matrix, thereby transforming the topology identification challenge of LVDN substations into a solvable convex optimization problem. Experimental results substantiate the effectiveness of the proposed model, with convergence to minimal error achieved after a mere 50 iterations for long time series data. Notably, the method attains an impressive discriminative accuracy of 0.9 while incurring only a modest increase in computational time, requiring a mere 35.1 milliseconds. By comparison, the full-day data analysis method exhibits the shortest computational time at 16.1 milliseconds but falls short of achieving the desired accuracy level of 0.9. Meanwhile, the sliding time window analysis method achieves the highest accuracy of 0.95 but at the cost of a 50-fold increase in computational time compared to the proposed method. Furthermore, the algorithm reported here excels in terms of energy efficiency (0.89) and load balancing (0.85). In summary, the proposed methodology outperforms alternative approaches across a spectrum of performance metrics. This article delivers valuable insights to the industry by fortifying the stability of power grid operations and elevating the precision of energy metering. The proposed approach serves as an effective solution to the challenges entailed by power line restructuring, maintenance, and inspections.

Variation in the relationship between fasting glucose and HbA1c: implications for the diagnosis of diabetes in different age and ethnic groups.

INTRODUCTION: Identify non-glycemic factors affecting the relationship between fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c), in order to refine diabetes diagnostic criteria. RESEARCH DESIGN AND METHODS: Relationship between FPG-HbA1c was assessed in 12 531 individuals from 2001 to 2018 US National Health and Nutrition Examination Survey. Using a recently described method, FPG and HbA1c were used to calculate apparent glycation ratio (AGR) of red blood cells for different subgroups based on age, race, and gender. RESULTS: At an FPG of 7 mmol/L, black individuals had a higher HbA1c (p<0.001, mean: 50.2 mmol/mol, 95% CI (49.8 to 50.4)) compared with white individuals (47.4 mmol/mol (47.2 to 47.5)). This corresponds to NGSP (National Glycohemoglobin Standardization Program) units of 6.7% and 6.5% for black versus white individuals, respectively. Similarly, individuals under 21 years had lower HbA1c (p<0.001, 47.9 mmol/mol (47.7 to 48.1), 6.5%) compared with those over 50 years (48.3 mmol/mol (48.2 to 48.5), 6.6%). Differences were also observed between women (p<0.001, 49.2 mmol/mol (49.1 to 49.3), 6.7%) and men (47.0 mmol/mol (46.8 to 47.1), 6.5%). Of note, the difference in HbA1c at FPG of 7 mmol/L in black females over 50 and white males under 21 years was 5 mmol/mol (0.46%). AGR differences according to race (p<0.001), age (p<0.001), and gender (p<0.001) explained altered glucose-HbA1c relationship in the analyzed groups. CONCLUSIONS: FPG-HbA1c relationship is affected by non-glycemic factors leading to incorrect diagnosis of diabetes in some individuals and ethnic groups. Assessment of AGR helps understand individual-specific relationship between glucose levels and HbA1c, which has the potential to more accurately diagnose and manage diabetes.

Is It Time to Move Beyond TIR to TITR? Real-World Data from Over 20,000 Users of Continuous Glucose Monitoring in Patients with Type 1 and Type 2 Diabetes.

The growing use of continuous glucose monitoring (CGM) has been supported by expert consensus and clinical guidelines on glycemic management in diabetes with time in range (TIR 70-180 mg/dL) representing a key CGM-derived glucose metric. Time in tight range (TITR) has also been proposed for clinical use, spanning largely normal glucose levels of 70-140 mg/dL. However, keeping such narrow glucose ranges can be challenging, and understanding the factors modulating TITR can help achieve these tight glycemic targets. Our real-life study aimed to evaluate the relationship between average glucose (AG) and TIR/TITR in a large cohort (n = 22,006) of CGM users, divided into four groups: self-identified as having type 1 diabetes (T1D) treated with insulin using multiple daily injections (MDI) or pumps; type 2 diabetes (T2D) on MDI or insulin pumps; T2D on basal insulin only; and T2D not on insulin treatment. The T2D groups, regardless of treatment type, displayed the highest TIR and TITR values, associated with lowest glycemic variability measured as glucose coefficient of variation (CV; 23-30%). The T1D group showed the lowest TIR and TITR, associated with the highest CVs (36-38%). Overall, higher CV was associated with lower TIR and TITR for AG values below 180 and 140 mg/dL, respectively, with the reverse holding true for AG values above these thresholds. The discordance between AG and TIR/TITR was less pronounced in T2D compared with T1D, attributed to lower CV in the former group. It was also observed that TITR has advantages over TIR for assessing glycemia status and progress toward more stringent A1C, particularly when approaching normal glucose levels. The data detail how CV affects the AG relationship with TIR/TITR, which has implications for CGM interpretation. In many instances TITR, rather than TIR, may be preferable to employ once AG falls below 140 mg/dL and near-normal glucose levels are required clinically.

Time in Range, Time in Tight Range, and Average Glucose Relationships Are Modulated by Glycemic Variability: Identification of a Glucose Distribution Model Connecting Glycemic Parameters Using Real-World Data.

Background: Time in range (TIR), time in tight range (TITR), and average glucose (AG) are used to adjust glycemic therapies in diabetes. However, TIR/TITR and AG can show a disconnect, which may create management difficulties. We aimed to understand the factors influencing the relationships between these glycemic markers. Materials and Methods: Real-world glucose data were collected from self-identified diabetes type 1 and type 2 diabetes (T1D and T2D) individuals using flash continuous glucose monitoring (FCGM). The effects of glycemic variability, assessed as glucose coefficient of variation (CV), on the relationship between AG and TIR/TITR were investigated together with the best-fit glucose distribution model that addresses these relationships. Results: Of 29,164 FCGM users (16,367 T1D, 11,061 T2D, and 1736 others), 38,259 glucose readings/individual were available. Comparing low and high CV tertiles, TIR at AG of 150 mg/dL varied from 80% ± 5.6% to 62% ± 6.8%, respectively (P < 0.001), while TITR at AG of 130 mg/dL varied from 65% ± 7.5% to 49% ± 7.0%, respectively (P < 0.001). In contrast, higher CV was associated with increased TIR and TITR at AG levels outside the upper limit of these ranges. Gamma distribution was superior to six other models at explaining AG and TIR/TITR interactions and demonstrated nonlinear interplay between these metrics. Conclusions: The gamma model accurately predicts interactions between CGM-derived glycemic metrics and reveals that glycemic variability can significantly influence the relationship between AG and TIR with opposing effects according to AG levels. Our findings potentially help with clinical diabetes management, particularly when AG and TIR appear mismatched.

All-photonic kinase inhibitors: light-controlled release-and-report inhibition.

Light-responsive molecular tools targeting kinases affords one the opportunity to study the underlying cellular function of selected kinases. In efforts to externally control lymphocyte-specific protein tyrosine kinase (LCK) activity, the development of release-and-report LCK inhibitors is described, in which (i) the release of the active kinase inhibitor can be controlled externally with light; and (ii) fluorescence is employed to report both the release and binding of the active kinase inhibitor. This introduces an unprecedented all-photonic method for users to both control and monitor real-time inhibitory activity. A functional cellular assay demonstrated light-mediated LCK inhibition in natural killer cells. The use of coumarin-derived caging groups resulted in rapid cellular uptake and non-specific intracellular localisation, while a BODIPY-derived caging group predominately localised in the cellular membrane. This concept of release-and-report inhibitors has the potential to be extended to other biorelevant targets where both spatiotemporal control in a cellular setting and a reporting mechanism would be beneficial.

Transport dynamics of rare earth elements in weathering crust soils.

In modern industries, rare earth elements (REEs) are considered as essential metals and invaluable natural resources. Ion-adsorption deposits (IADs) are repositories of REE in the weathering crust soils, in which REEs are adsorbed on clay minerals. In the last few decades, the mining of REEs from IADs has caused substantial environmental damage owing to the overuse of leaching agents for the desorption and transport of REEs in weathering crust soils. These environmental issues have sparked extensive research interest in modeling REE transport dynamics in weathering crust soils. Nevertheless, because current models treat REE adsorption and transport independently, they do not accurately describe REE transport dynamics. Therefore, in this study, a unified workflow that synergizes adsorption and transport dynamics is proposed to predict REE transport. The adsorption of REEs on IADs was found to follow the Freundlich isotherm with the coefficient of determination exceeding 0.9826. The adsorption capacities of La3+, Sm3+, Er3+, and Y3+ reach 1.3127, 1.4423, 1.5793, and 1.1061 mg g-1 at 300 ppm, respectively. For the breakthrough curve, an advection-dispersion-adsorption-equation (ADAE) model was developed and utilized to accurately and reliably predict REE transport dynamics in soil columns. It was found the saturation time of REEs in soils is 39.22, 44.15, 50.64, and 32.17 h, respectively at 2 mL min-1 and decreased with the increase of flow velocity. The upper and lower limits of REE transport are ADAE-Freundlich and ADAE-Toth. More importantly, the model was applied to simulate REEs transport in field-scale weathering crusts over 100 years and predict REE accumulation in the highly weathered layered, which is found in natural weathering crusts. The qualitative prediction of REE transport dynamics in weathering crusts may help fundamentally lower the usage of leaching agents and mitigate concomitant the environmental impacts of mining.

Personalized Glycated Hemoglobin in Diabetes Management: Closing the Gap with Glucose Management Indicator.

Glycated hemoglobin (HbA1c) has played a central role in the management of diabetes since the end of the landmark Diabetes Control and Complications Trial 30 years ago. However, it is known to be subject to distortions related to altered red blood cell (RBC) properties, including changes in cellular lifespan. On occasion, the distortion of HbA1c is associated with a clinical pathological condition affecting RBCs, however, the more frequent scenario is related to interindividual RBC variations that alter HbA1c-average glucose relationship. Clinically, these variations can potentially lead to over- or underestimating glucose exposure of the individual to the extent that may put the person at excess risk of over- or undertreatment. Furthermore, the variable association between HbA1c and glucose levels across different groups of people may become an unintentional driver of inequitable health care delivery, outcomes, and incentives. The subclinical effects within the normal expected physiological range of RBCs can be large enough to alter clinical interpretation of HbA1c and addressing this will help with individualized care and decision making. This review describes a new glycemic measure, personalized HbA1c (pA1c), that may address the clinical inaccuracies of HbA1c by taking into account interindividual variability in RBC glucose uptake and lifespan. Therefore, pA1c represents a more sophisticated understanding of glucose-HbA1c relationship at an individual level. Future use of pA1c, after adequate clinical validation, has the potential to refine glycemic management and the diagnostic criteria in diabetes.

Real-life 24-week changes in glycemic parameters among European users of flash glucose monitoring with type 1 and 2 diabetes and different levels of glycemic control.

AIM: To evaluate real-life changes of glycemic parameters among flash glucose monitoring (FLASH) users who do not meet glycemic targets. METHODS: De-identified data were obtained between 2014 and 2021 from patients using FLASH uninterrupted for a 24-week period. Glycemic parameters during first and last sensor use were examined in four identifiable groups: type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM) on basal-bolus insulin, T2DM on basal insulin, and T2DM without insulin treatment. Within each group, subgroup analyses were performed in persons with initial suboptimal glycemic regulation (time in range (TIR; 3.9-10 mmol/L) < 70%, time above range (TAR; >10 mmol/L) > 25%, or time below range (TBR; <3.9 mmol/L) > 4%). RESULTS: Data were obtained from 1,909 persons with T1DM and 1,813 persons with T2DM (1,499 basal-bolus insulin, 189 basal insulin, and 125 non-insulin users). In most of the performed analyses, both overall and in the various subgroups, significant improvements were observed in virtually all predefined primary (TIR) and secondary endpoints (eHbA1c, TAR, TBR and glucose variability). CONCLUSIONS: 24-weeks FLASH use in real life by persons with T1DM and T2DM with suboptimal glycemic regulation is associated with improvement of glycemic parameters, irrespective of pre-use regulation or treatment modality.

Disparity of Gut Microbiota Composition Among Elite Athletes and Young Adults With Different Physical Activity Independent of Dietary Status: A Matching Study.

Objective: This study aimed to investigate the disparity of gut microbiota among elite athletes and young adults with different physical activity independent of dietary status. Methods: In Hangzhou, China, an age and sex matching study was conducted between April and May 2021. A total of 66 Chinese young adults were recruited in this study and divided into an elite athlete group, physically active group, and physically inactive group. Fecal samples were collected to assess gut microbiota composition. Dietary status was measured using a food-frequency questionnaire. Comparisons in gut microbiota and blood biomarkers among three groups were analyzed by using the analysis of covariance. Results: The findings depicted a tendency to form clusters for beta diversity among three groups, while no significant difference was observed in both alpha and beta diversity. In the multiple analysis model, by adjusting dietary status, a significantly higher abundance of Clostridiaceae (p = 0.029) and Megamonas_rupellensis (p = 0.087) was observed in elite athletes compared to that in general young adults. Furthermore, inflammation-related bacteria such as Bilophila (p = 0.011) and Faecalicoccus (p = 0.050) were enriched in physically inactive young adults compared to two other groups. Pearson's correlation analysis showed a positive association between Bilophila and circulating white body cell count (r = 0.332, p = 0.006) and its subtypes including neutrophils (r = 0.273, p = 0.027), and lymphocytes (r = 0.327, p = 0.007). Megamonas_rupellensis has been shown associated positively with serum lymphocytes levels (r = 0.268, p = 0.03). Although no significant differences were observed, the elite athletes tended to have lower levels of blood biomarkers of immunity within a normal range, which may reflect a better immune function. Conclusion: This matching study indicated that physically inactive young adults are more likely to have a lower immune function and a higher abundance of pro-inflammatory gut bacteria than elite athletes and physically active young adults. Dietary status should be considered as an important factor that may affect the association of physical activity with immune function and gut microbiota.

Altered pathways and targeted therapy in double hit lymphoma.

High-grade B-cell lymphoma with translocations involving MYC and BCL2 or BCL6, usually referred to as double hit lymphoma (DHL), is an aggressive hematological malignance with distinct genetic features and poor clinical prognosis. Current standard chemoimmunotherapy fails to confer satisfying outcomes and few targeted therapeutics are available for the treatment against DHL. Recently, the delineating of the genetic landscape in tumors has provided insight into both biology and targeted therapies. Therefore, it is essential to understand the altered signaling pathways of DHL to develop treatment strategies with better clinical benefits. Herein, we summarized the genetic alterations in the two DHL subtypes (DHL-BCL2 and DHL-BCL6). We further elucidate their implications on cellular processes, including anti-apoptosis, epigenetic regulations, B-cell receptor signaling, and immune escape. Ongoing and potential therapeutic strategies and targeted drugs steered by these alterations were reviewed accordingly. Based on these findings, we also discuss the therapeutic vulnerabilities that coincide with these genetic changes. We believe that the understanding of the DHL studies will provide insight into this disease and capacitate the finding of more effective treatment strategies.