Target Range Research Articles

A sensor-augmented pump with a predictive low-glucose suspend system could lead to an optimal time in target range during pregnancy in Japanese women with type 1 diabetes.

It is challenging for pregnant women with type 1 diabetes to maintain optimum glucose level to attain good neonatal outcomes. This study evaluated the efficacy of sensor-augmented insulin pump (SAP) with a predictive low-glucose suspend (PLGS) system in pregnant Japanese women with type 1 diabetes. SAP with PLGS was used in 11 of the 22 women with type 1 diabetes who delivered between 2011 and 2021 at the two medical institutions in Japan. Glucose management, insulin delivery suspension time (IST) and neonatal outcomes were retrospectively studied. In SAP with PLGS cases (n = 11), average glycated hemoglobin levels were < 6.5% throughout the pregnancy, and the time in range (TIR, 63-140mg/dl) was > 70% in the second and third trimesters. PLGS was safely used without inducing ketoacidosis. Positive correlation was observed between IST and TIR (r = 0.62, p < 0.01). Negative correlation was observed between IST and time below range (TBR) (r = - 0.40, p = 0.02), and IST and time above range (TAR) (r = - 0.45, p = 0.01). Total daily insulin dose was adequately increased without increasing hypoglycemia. There was only one heavy-for-date HFD) infant among the 11 newborns in SAP with PLGS cases. In cases without SAP (n = 11), target glycemic levels were difficult to achieve and there were 5 HFD infants among the 11 newborns. SAP with PLGS was safely and effectively used in pregnant women with type 1 diabetes to achieve target glucose levels without increasing the risk of hypoglycemia, which may have led to good neonatal outcomes. The online version contains supplementary material available at 10.1007/s13340-024-00716-7.

High-Throughput Screening of PAM-Flexible Cas9 Variants for Expanded Genome Editing in the Silkworm (Bombyx mori).

Genome editing provides novel opportunities for the precise genome engineering of diverse organisms. Significant progress has been made in the development of genome-editing tools for Bombyx mori (B. mori) in recent years. Among these, CRISPR/Cas9, which is currently the most commonly used system in lepidopteran insects, recognizes NGG protospacer adjacent motif (PAM) sequences within the target locus. However, Cas9 lacks the ability to target all gene loci in B. mori, indicating the need for Cas9 variants with a larger editing range. In this study, we developed a high-throughput screening platform to validate Cas9 variants at all possible recognizable and editable PAM sites for target sequences in B. mori. This platform enabled us to identify PAM sites that can be recognized by both xCas9 3.7 and SpCas9-NG variants in B. mori and to assess their editing efficiency. Cas9 shows PAM sites every 13 base pairs in the genome, whereas xCas9 3.7 and SpCas9-NG have an average distance of 3.4 and 3.6 base pairs, respectively, between two specific targeting sites. Combining the two Cas9 variants could significantly expand the targeting range of the genome, accelerate research on the B. mori genome, and extend the high-throughput rapid screening platform to other insects, particularly those lacking suitable NGG PAM sequences.

Systolic and diastolic blood pressure time in target range and cardiovascular outcomes in patients with hypertension and pre-frailty or frailty status.

In patients with hypertension and pre-frailty or frailty, the influence of systolic (SBP) and diastolic blood pressure (DBP) time in target range (TTR) on clinical outcomes is unclear. Thus, we conducted a post hoc analysis of the Systolic Blood Pressure Intervention Trial (SPRINT). Classifying 4208 participants into frail and non-frail groups using a frailty index, the study calculated blood pressure time in target range (BP-TTR) for the first three months using the Rosendaal method. The primary endpoint included a composite of nonfatal myocardial infarction (MI), acute coronary syndromes, stroke, acute decompensated heart failure (ADHF), and cardiovascular death. Relationships between BP-TTR and outcomes were analyzed using Kaplan-Meier curves, Cox models, and restricted cubic spline curves, with subgroup analysis for further insights. In a median follow-up of 3.17 years, primary outcomes occurred in 6.7% of participants. Kaplan-Meier analysis showed that a lower systolic blood pressure time in target range (SBP-TTR) (0%-25%) correlated with an increased cumulative incidence of the primary outcome (p<.001), nonfatal MI (P=.021), stroke (P=.004), and cardiovascular death (P=.002). A higher SBP-TTR (75%-<100%) was linked to a reduced risk of these outcomes. The restricted cubic spline (RCS) curve revealed a linear association between SBP-TTR and the primary outcome (non-linear P=.704). Similar patterns were observed for diastolic blood pressure time in target range (DBP-TTR). Subgroup analysis showed that the protective effect of higher SBP-TTR was less pronounced at low DBP-TTR levels (P for interaction=.023). In conclusion, this study highlights the importance of maintaining BP within the target range to mitigate cardiovascular risks in this population.

Longer serum phosphorus time in range associated with lower mortality risk among peritoneal dialysis patients: a multicenter retrospective cohort study

BackgroundRelationship between serum phosphorus time in range and mortality risk in peritoneal dialysis (PD) patients remains uncertain. We aimed to evaluate the association between serum phosphorus time in range and all-cause mortality in Chinese PD population.MethodsThis was a multicenter, retrospective, cohort study of 1,915 patients collected from January 2008 to October 2020 in 4 Chinese centers. Serum phosphorus time in range was estimated as the months during the first year that a patient’s serum phosphorus level was within the target range (defined as 1.13–1.78 mmol/L). The primary outcome was all-cause mortality. The secondary outcomes were cardiovascular (CV) mortality and PD withdrawal. Cox proportional hazards regression model with comprehensive adjustments was used to assess the association.ResultsThe primary outcome occurred in 249 (13.0%) PD patients over a median follow-up of 28 months. Overall, the serum phosphorus time in range was negatively associated with all-cause mortality (per 3-month increments, adjusted HR [aHR], 0.83; 95%CI: 0.75–0.92), CV mortality (per 3-month increments, aHR, 0.87; 95%CI: 0.77–0.99), and PD withdrawal (per 3-month increments, aHR, 0.89; 95%CI: 0.83–0.95). Competing-risk model showed that the relationship of serum phosphorus time in range with all-cause mortality remained stable. None of the variables including demographics, history of diabetes and CV disease, as well as several PD-related and clinical indicators modified this association.ConclusionsPD patients with longer serum phosphorus time in range in the first year was negatively associated with all-cause mortality and CV mortality. Our findings highlight the importance of maintaining serum phosphorus levels within 1.13–1.78 mmol/L for PD patients.

Research on local sound field intensity control technique in metasurface based on deep neural networks.

The use of tunable metasurface technology to realize the underwater tracking function of submarines, which is one of the hotspots and difficulties in submarine design. The structure-to-sound-field metasurface design approach is a highly iterative process based on trial and error. The process is cumbersome and inefficient. Therefore, an inverse design method was proposed based on parallel deep neural networks. The method took the global and local target sound field feature information as input and the metasurface physical structure parameters as output. The deep neural network was trained using a kernel loss function based on a radial basis kernel function, which established an inverse mapping relationship between the desired sound field to the metasurface physical structure parameters. Finally, the sound field intensity modulation at a localized target range was achieved. The results indicated that within the regulated target range, this method achieved an average prediction error of less than 5 dB for 92.9% of the sample data.

Remnant cholesterol is an independent risk factor for the incidence of chronic kidney disease in newly-diagnosed type 2 diabetes: A nationwide population-based study

AimsTo evaluate the impact of remnant cholesterol (remnant-C) on chronic kidney disease (CKD) incidence in newly-diagnosed type 2 diabetes. MethodsThis retrospective cohort study used Korean National Health Insurance Service data on 212,836 patients with newly-diagnosed type 2 diabetes between 2009 and 2014. We conducted cox regression analysis to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for developing CKD according to remnant-C tertile. ResultsDuring a median follow-up duration of 5.23 years, 6,850 CKD cases developed. In the fully adjusted model, HRs and 95 % CIs for incident CKD increased in the highest tertile of baseline remnant-C compared to the lowest (HR [95 % CI]; 1.234 [1.159–1.314]). This association was more prominent in patients with hypertension or low-income status (P for interaction < 0.05). Increased HRs in the highest tertile of remnant-C was sustained in type 2 diabetes patients within target range of conventional lipid profile such as low-density lipoprotein cholesterol (LDL-C) < 100 mg/dL and < 70 mg/dL (1.165 [1.041–1.304] and 1.308 [1.063–1.609]), high-density lipoprotein cholesterol (HDL-C) (1.243 [1.155–1.338]) and triglyceride (1.168 [1.076–1.268]), respectively. ConclusionsIn newly-diagnosed type 2 diabetes patients, higher remnant-C is independently associated with CKD incidence, even when conventional lipid values are well-controlled.

Improved MRI Brain Tumor Segmentation Method Based on UNet++

Brain tumors are one of the most common tumors with high mortality. Accurate detection and quantitative evaluation of brain tumors are necessary for patient treatment. A reliable and effective method for automatic segmentation of brain tumors by magnetic resonance imaging (MRI) plays a crucial role in patient treatment. In recent years, the Unet++ network structure has shown better performance in image segmentation. However, it is deficient in small-scale feature extraction and segmentation accuracy. In this study, the AC-ResUnet++ network was proposed to address the problems of Unet++ network mentioned above, which combined residual module, convolutional block attention module (CBAM) and Atrous spatial pyramidal pooling (ASPP). The residual module can solve the problem of gradient explosion in the deep network, CBAM can focus on local feature information and enhance the feature learning ability of the network for the target range, and ASPP module can generate different receptive fields and obtain multi-scale contextual feature information. The BraTS 2018 and BraTS 2019 datasets were used to test the proposed network. The Dice similarity coefficient of AC-ResUnet++ in whole tumor, tumor core and enhanced tumor are 0.8521, 0.8696 and 0.7868, respectively. Compared with Unet++ network, the Dice similarity coefficient increased by 1.22%, 5.08% and 2.03% on the baselines. The comprehensive results demonstrate that AC-ResUnet++ performs more effectively in improving the segmentation accuracy of brain tumor.

Abstract 2345: Docking and molecular dynamic simulations of mithramycin against Sp1, Sp3, and survivin

Abstract Purpose: Therapeutic targeting of transcription factors, Specificity protein (Sp)1 and Sp3 and their downstream effectors, such as survivin, are studied in various cancers. Due to role in in poorer cancer prognoses in several cancers their downregulation has been investigated as an effective treatment approach. Mithramycin (Mit) showed innate anti-cancer properties by targeting Sp proteins through GC/GT DNA binding interference. Recent studies have given new insights into further mechanisms of action of Mit, however in-depth binding and mechanistic studies are lacking. Our objective is to investigate Mit’s specific binding interactions with Sp1, Sp3, and survivin. Methods: Protein structures and sequences for Sp1, Sp3, and survivin (ID: P08047, Q02447, and O153392, respectively) were retrieved from UniProtKB database. Experimental predicted structures for Sp1 and Sp3 were obtained from AlphaFold. Sequence lengths of Sp1 and Sp3 were 785 and 781 amino acids (aa), domain regions of Sp1 (619-785) and Sp3 (461-781) were note. Survivin structure was obtained from PDB and was comprised of 142 aa. Co-crystallized compounds were removed during analyses using BIOVIA Discovery Studio 4.5 Visualizer. Prediction of binding sites and docking were performed using CASTp, GHECOM, DEPTH tools, glide, and AutoDock 4.2 software. Energy minimization and Molecular dynamics simulations were performed in the Schrödinger suite. Results: Binding sites were identified for Sp1, Sp3, and survivin. Simulated docking demonstrated multiple binding complexes and varying binding energies. The most efficient binding was seen with Sp1 and Sp3. RMSF and RMSD simulations revealed stabilization of Sp1-, Sp3-, and survivin-Mit complexes. This shows Mithramycin can potentially inhibit all three proteins, with slightly more stability with Sp1 and Sp3. Radius of gyration (rGyr), H-bond analysis, and solvent accessible surface area (SASA) support docking findings with Mit-protein complexes remaining stable in the binding pocket, forming new H-bonds, and altering hydrophilic and hydrophobic interaction areas. Conclusion: Our findings warrant further in vitro testing of the ability of Mit to interact with a wider range of oncogenic targets. While we only tested the ability of Mit to interact with Sp1, Sp3 and survivin, similar model can be used to evaluate the interaction with other critical proteins associated with cancer and to further elucidate mechanisms of action. These finding are crucial to understanding base mechanistic abilities and can be useful to test additional agents for their ability to interact with Sp1 or survivin. Citation Format: Christoffer Briggs Lambring, Santosh K. Behera, Riyaz Basha. Docking and molecular dynamic simulations of mithramycin against Sp1, Sp3, and survivin [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2345.

Abstract 78: Superior resolution of intracellular markers with CyTOF reveals greater functional diversity of human T cells

Abstract Measuring functional signatures of immune cells in a comprehensive manner, spanning the inflammatory (Th1/Th17) and immunosuppressive (Th2/Treg) lineages, would provide key insights into several facets of cancer research and therapy. Determining mechanisms underlying success/failure of checkpoint blockade, defining immunosuppressive activity of the tumor-resident cell subsets, and identifying immunological biomarkers that predict clinical outcomes, could all be achievable if detection of cytokines spanning many lineages among individual cells was in reach. To achieve this goal, powerful cytometric research tools are required. Cell phenotyping panels are expanding and often now include measurement of intracellular markers of functional potential, such as cytokines, phosphorylation events, and transcription factors. Many of these readouts, including cytokines of the Th2/Treg lineages (IL-5, IL-10, and IL-13), have been notoriously difficult to detect in human cells using fluorescence-based cytometry. Large panels with multiplex intracellular markers are subject to challenges with autofluorescence and spillover spread, thus limiting fluorochrome capacity and reducing resolving power for rare subsets even with full spectrum flow cytometers. For such applications, mass cytometry may overcome such limitations and enable better signal resolution. To address this, we evaluated three small (13-plex) panels using a full spectrum flow cytometer and the CyTOF XT™ mass cytometer. Each panel was comprised of surface and intracellular analytes (cytokines, phospho-epitopes, or transcription factors) and designed to minimize potential impact of spectral overlap on the resolution of spectral flow data. PBMCs were stimulated, split, and stained with either fluorochrome- (Cytek® Aurora) or metal-conjugated antibodies (CyTOF XT). Data sets were analyzed by PhenoGraph clustering and visualized with opt-SNE to determine cellular functional diversity. Overall, data collected on the CyTOF XT demonstrated superior resolution for many intracellular readouts, including cytokines IL-5, IL-10, and IL-13. Also, when better signal/noise enabled accurate clustering, a higher number of immune cell clusters possessing distinct functional signatures resulted from mass cytometry datasets as compared with fluorescent counterparts. In summary, the CyTOF XT mass cytometry platform offers superior signal resolution compared to spectral flow for a range of intracellular targets. Use of mass cytometry translates to the identification of more diverse functional subsets and thus a clearer understanding of the immune signatures present in a sample in the context of unbiased analysis. Our findings indicate that the CyTOF XT platform could serve as a catalyst for seminal discoveries in immune profiling to drive therapeutic design and advanced disease monitoring in cancer. Citation Format: Erika L. Smith-Mahoney, Michael J. Cohen, Anna C. Belkina, Thirumahal Selvanantham, David King, Christina Loh, Amedeo J. Cappione, Jennifer E. Snyder-Cappione. Superior resolution of intracellular markers with CyTOF reveals greater functional diversity of human T cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 78.

Abstract 14: Identification of tumor-reactive T cell receptors through functional single cell interaction analyses for personalized T cell therapy

Abstract Innovative immunotherapy approaches such as adoptive transfer of chimeric antigen receptor (CAR) T cells or tumor infiltrating lymphocytes (TILs) have shown great success in the treatment of solid tumors and hematological malignancies. Although treatment of multiple myeloma with CAR T cells can induce deep responses, relapses frequently occur due to antigen escape and limited CAR T cell persistence. TCR-engineered T cells may show prolonged persistence in vivo and could mediate sustained antitumor effects. A further benefit of TCR transgenic T cells is the ability to target intracellular antigens that are inaccessible to CAR T cells, expanding the range of potential targets for immunotherapy. In our project, we propose to identify T cell receptors (TCRs) specifically targeting autologous myeloma cells. Tumor-reactive T cells were identified using the Bruker Cellular Analysis Lightning® platform, allowing simultaneous functional analysis of up to 1500 individual T cell/target cell interactions on a chip. Reactive T cells were identified upon detection of secreted cytokines (IFNγ, TNFα, IL2) and measurement of 4-1BB (CD137) surface expression. Tumor-reactive T cells showing various cytokine secretion patterns and 4-1BB expression profiles were detected in each myeloma patient (on average 11.9 T cells out of 1243 cells tested per assay run). Individual tumor-reactive T cells have been isolated and their TCRs were sequenced. TCR sequences of tumor-reactive T cells were mapped to single-cell RNA sequencing data of T cells from the same patiens to reveal a gene expression signature of myeloma-reactive T cells. TCR genes of reactive T cells were cloned and overexpressed in autologous T cells for functional validation and analysis of tumor derived neoepitope specificity. In summary, we present a pipeline allowing identification of myeloma-recognizing T cells and recovery of bona fide tumor-reactive TCRs eligible for patient-individualized T cell therapy. Citation Format: Tim Robin Wagner, Niklas Kehl, Simon Steiger, Michael Kilian, Bruno Schönfelder, Tamara Boschert, Katharina Lindner, Patrick Schmidt, Karsten Rippe, Hartmut Goldschmidt, Marc-Steffen Raab, Michael Platten, Mirco Friedrich, Stefan B. Eichmüller. Identification of tumor-reactive T cell receptors through functional single cell interaction analyses for personalized T cell therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 14.

Abstract 8: Deep Immunomics pipeline for discovery and validation of novel cancer-specific T cell receptors

Abstract Background: T cell receptor-engineered T cell (TCR-T) therapy has been studied as a high potential approach for cancer treatment. Beyond cell-surface tumor antigens, TCR-Ts can recognize HLA-presented intracellular epitopes which allows them to address a wide range of cancer-specific targets. Existing TCR-T therapies focus on a limited number of epitopes, many of which are restricted to HLA allele HLA-A*02:01. Identification of novel anti-tumor TCRs covering a broad range of HLA alleles is necessary to address unmet clinical needs. Natural T cells undergo thymic selection and present a favorable safety profile for mining such anti-tumor TCRs for therapeutic development. However, discovery of natural anti-tumor TCRs has been challenging due to i) the absence of high-throughput methods for identifying tumor-reactive TCRs in limited quantity human samples and ii) lack of sensitivity in detecting low frequency, naturally occurring tumor-reactive T cells. Methods: We developed TargetScape® as a part of our Deep Immunomics platform for efficient discovery of natural tumor-specific TCRs in healthy donors and cancer patients. Cells from blood and tissue samples were stained with metal-barcoded peptide-MHC tetramers, containing 500+ tumor-specific antigens, alongside metal-conjugated antibodies, allowing rapid identification and high dimensional phenotypic analysis of CD8+ T cells at the millions of cells scale. Single-cell sequencing revealed paired TCR sequences. Selected TCRs were introduced into luminescent Jurkat reporter cells for validation screening with peptide-pulsed targets and the relevant HLA restriction. TCRs of interest were further integrated into primary T cells and evaluated for their effector function. Results: We utilize our sensitive, high-throughput TargetScape® platform to detect and characterize putative cancer-specific TCRs from blood and tissue samples in frequencies as low as ~0.003% of total CD8+ cells. We have functionally validated over 100 TargetScape® derived TCRs with luminescent Jurkat reporters. Validated TCRs cover high prevalence HLA alleles and target a broad range of cancer antigen classes, including tumor associated antigens (TAA), Human endogenous retroviruses (HERVs), shared splice variants, and frameshift mutations. Several natural TCRs demonstrate recognition of low concentrations of peptide, indicating high functional avidity. Further evaluations of specificity and activity of TCRs of interest transduced into primary T cells are currently in progress. Conclusions: Our Deep Immunomics platform allows us to identify and confirm activity of novel, naturally-derived TCR candidates against therapeutically relevant cancer antigens presented on six common HLA alleles. These findings validate our discovery workflow leading to a portfolio of potential clinically relevant candidates that are currently under preclinical development. Citation Format: Hannah Fields, Juliana Velez Lujan, Kan Xing Wu, Natalie Epstein, Nazihah Beevi, Florence Chioh, Nicholas Tan, Neeraja Kulkarni, Noella Mukobo, Srikanthi R, Yovita Purwanti, Evan Newell, Alessandra Nardin, Michael Fehlings, Katja Fink, Daniel MacLeod. Deep Immunomics pipeline for discovery and validation of novel cancer-specific T cell receptors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 8.

Stabilization of interdomain interactions in G protein α subunits as a determinant of Gαi subtype signaling specificity

Highly homologous members of the Gαi family, Gαi1-3, have distinct tissue distributions and physiological functions, yet their biochemical and functional properties are very similar. We recently identified PDZ-RhoGEF (PRG) as a novel Gαi1 effector that is poorly activated by Gαi2. In a proteomic proximity labeling screen we observed a strong preference for Gαi1 relative to Gαi2 with respect to engagement of a broad range of potential targets. We investigated the mechanistic basis for this selectivity using PRG as a representative target. Substitution of either the helical domain (HD) from Gαi1 into Gαi2 or substitution of a single amino acid, A230 in Gαi2 with the corresponding D in Gαi1, largely rescues PRG activation and interactions with other potential Gαi targets. Molecular dynamics simulations combined with Bayesian network models revealed that in the GTP bound state, separation at the HD-Ras-like domain (RLD) interface is more pronounced in Gαi2 than Gαi1. Mutation of A230 to D in Gαi2 stabilizes HD-RLD interactions via ionic interactions with R145 in the HD which in turn modify the conformation of Switch III. These data support a model where D229 in Gαi1 interacts with R144 and stabilizes a network of interactions between HD and RLD to promote protein target recognition. The corresponding A230 in Gαi2 is unable to stabilize this network leading to an overall lower efficacy with respect to target interactions. This study reveals distinct mechanistic properties that could underly differential biological and physiological consequences of activation of Gαi1 or Gαi2 by GPCRs.

Colabind: A Cloud-Based Approach for Prediction of Binding Sites Using Coarse-Grained Simulations with Molecular Probes.

Binding site prediction is a crucial step in understanding protein-ligand and protein-protein interactions (PPIs) with broad implications in drug discovery and bioinformatics. This study introduces Colabind, a robust, versatile, and user-friendly cloud-based approach that employs coarse-grained molecular dynamics simulations in the presence of molecular probes, mimicking fragments of drug-like compounds. Our method has demonstrated high effectiveness when validated across a diverse range of biological targets spanning various protein classes, successfully identifying orthosteric binding sites, as well as known druggable allosteric or PPI sites, in both experimentally determined and AI-predicted protein structures, consistently placing them among the top-ranked sites. Furthermore, we suggest that careful inspection of the identified regions with a high affinity for specific probes can provide valuable insights for the development of pharmacophore hypotheses. The approach is available at https://github.com/porekhov/CG_probeMD.

Integrating essence of “time” for blood pressure control in nephrology care

Controlling blood pressure (BP) is essential in the management of patients with chronic kidney disease. Reflecting the intrinsic variability of BP, several parameters of BP over time have been shown to predict adverse outcomes. Systolic BP time in target range has been recently proposed as a new promising parameter. Park etal. confirmed its prognostic value in patients with chronic kidney disease. We review the potential clinical usefulness and challenges of this parameter in nephrology care.

Use of the Guardian Connect glycemic monitoring system in patients after total duodenopancreatectomy in the early postoperative period on intravenous insulin therapy

BACKGROUND: Among different subtypes of pancreatogenic diabetes mellitus the biggest difficulties of glycemic control arise in patients after total duodenopancreatectomy (TDPE), first of all due to the presence of absolute insulin insufficiency.AIM: Estimating safety and cost-effectiveness Guardian Connect CGM system in early postoperative period in hospitalized patients after TDPE on continuous intravenous insulin therapy (CIVIT).MATERIALS AND METHODS: Glucose measurement results of 26 patients in early postoperative period after TDPE were analyzed. In 12 of them, we used Guardian Connect CGM system. In this group 43 cycles (1 cycle — 6 days, 258 days total) of CGM and 971 glucometer measurements used for CGM calibration were analyzed; in other 14 patients in whom only glucometer was used we analyzed 2496 glycemic values.Cost-effectiveness was calculated over 6 days for CGM and only glucometer use (including cost of CGM, glucometers, disposable materials, clinic wage-costs to medical staff for time required for glucose control).RESULTS: Glucose levels of group #1 were in the target range 5.6 to 10.0 mmol/L (66.7 vs 61.2%, p=0.003) and the range 4.3–11.6 mmol/L (85.2% vs 82.2%, p=0.038) more than in comparison with group #2.The frequency of hypoglycemic episodes (&lt;3.9 mmol/L) was statistically significantly lower in the CGM group (6 vs 54, p&lt;0.001, RO 8.463 [3.579; 20.015], RR 1.746 [1.551; 1.966]).Cost analysis of glucose control using Guardian Connect CGM system for one cycle (6 days) and cost of glucose control using glucose meter for the same period showed that using Guardian Connect CGM system in patients after TDPE on intravenous insulin therapy reduced clinic costs by 21.7% in ICU and by 25.7% in the hospital department.CONCLUSION: Guardian Connect CGM have demonstrated its safety and cost-effectiveness during glucose control in patients in early postoperative period after TDPE on CIVIT.

Brain protective effect of dexmedetomidine vs propofol for sedation during prolonged mechanical ventilation in non-brain injured patients.

Dexmedetomidine and propofol are two sedatives used for long-term sedation. It remains unclear whether dexmedetomidine provides superior cerebral protection for patients undergoing long-term mechanical ventilation. To compare the neuroprotective effects of dexmedetomidine and propofol for sedation during prolonged mechanical ventilation in patients without brain injury. Patients who underwent mechanical ventilation for > 72 h were randomly assigned to receive sedation with dexmedetomidine or propofol. The Richmond Agitation and Sedation Scale (RASS) was used to evaluate sedation effects, with a target range of -3 to 0. The primary outcomes were serum levels of S100-β and neuron-specific enolase (NSE) every 24 h. The secondary outcomes were remifentanil dosage, the proportion of patients requiring rescue sedation, and the time and frequency of RASS scores within the target range. A total of 52 and 63 patients were allocated to the dexmedetomidine group and propofol group, respectively. Baseline data were comparable between groups. No significant differences were identified between groups within the median duration of study drug infusion [52.0 (IQR: 36.0-73.5) h vs 53.0 (IQR: 37.0-72.0) h, P = 0.958], the median dose of remifentanil [4.5 (IQR: 4.0-5.0) μg/kg/h vs 4.6 (IQR: 4.0-5.0) μg/kg/h, P = 0.395], the median percentage of time in the target RASS range without rescue sedation [85.6% (IQR: 65.8%-96.6%) vs 86.7% (IQR: 72.3%-95.3), P = 0.592], and the median frequency within the target RASS range without rescue sedation [72.2% (60.8%-91.7%) vs 73.3% (60.0%-100.0%), P = 0.880]. The proportion of patients in the dexmedetomidine group who required rescue sedation was higher than in the propofol group with statistical significance (69.2% vs 50.8%, P = 0.045). Serum S100-β and NSE levels in the propofol group were higher than in the dexmedetomidine group with statistical significance during the first six and five days of mechanical ventilation, respectively (all P < 0.05). Dexmedetomidine demonstrated stronger protective effects on the brain compared to propofol for long-term mechanical ventilation in patients without brain injury.

A delicate balance: the challenges of hypoparathyroidism.

A 38-yr-old woman with chronic non-surgical hypoparathyroidism, managed elsewhere, presented to our practice with symptomatic hypocalcemia. At the age of 17, she began to suffer from muscle cramps, paresthesia, and ongoing diffuse pain. It took years before she was correctly diagnosed with hypoparathyroidism. Her symptoms were severe enough that she required emergency room visits several times a year. After she was properly diagnosed and started on calcium and calcitriol therapy, she continued to experience frequent episodes of severe hypocalcemia. She saw multiple healthcare providers who each introduced a new regimen. In addition, poor communication led to her discontinuing her medications altogether. As a result, her calcium levels remained consistently low, and she lost confidence in her prospect for better health. At the time of her visit to our clinic, she had discontinued calcitriol, was taking a large amount of oral calcium daily all at once, and had hypocalcemia. We addressed her concerns, and the challenges she faces with adherence to her medication regimen. We provided her with detailed information about the disease and the reasoning behind her treatment plan. Treatment was initiated with calcium carbonate 600mg 3 times daily and calcitriol 0.5 mcg once daily. One week after treatment initiation, her test results showed improvement in her albumin-adjusted calcium, phosphorus, and 24-h urine calcium which were all within target range.

Performance of Eight Infliximab Population Pharmacokinetic Models in a Cohort of Dutch Children with Inflammatory Bowel Disease.

Efficacy of infliximab in children with inflammatory bowel disease can be enhanced when serum concentrations are measured and further dosing is adjusted to achieve and maintain a target concentration. Use of a population pharmacokinetic model may help to predict an individual's infliximab dose requirement. The aim of this study was to evaluate the predictive performance of available infliximab population pharmacokinetic models in an independent cohort of Dutch children with inflammatory bowel disease. In this retrospective study, we used data of 70 children with inflammatory bowel disease (443 infliximab concentrations) to evaluate eight models that focused on infliximab pharmacokinetic models in individuals with inflammatory bowel disease, preferably aged ≤ 18 years. Predictive performance was evaluated with prior predictions (based solely on patient-specific covariates) and posterior predictions (based on covariates and infliximab trough concentrations). Model accuracy and precision were calculated with relative bias and relative root mean square error and we determined the classification accuracy at the trough concentration target of ≥ 5 mg/L. The population pharmacokinetic model by Fasanmade was identified to be most appropriate for the total dataset (relative bias before/after therapeutic drug monitoring: -20.7%/11.2% and relative root mean square error before/after therapeutic drug monitoring: 84.1%/51.6%), although differences between models were small and several were deemed suitable for clinical use. For the Fasanmade model, sensitivity and specificity for maximum posterior predictions for the next infliximab trough concentration to be ≥ 5 mg/L were respectively 83.5% and 80% with an area under the receiver operating characteristic curve of 0.870. In our paediatric cohort, various models provided acceptable predictive performance, with the Fasanmade model deemed most suitable for clinical use. Model-informed precision dosing can therefore be expected to help to maintain infliximab trough concentrations in the target range.

Repurposing CRISPR-Cas13 systems for robust mRNA trans-splicing

Type VI CRISPR enzymes have been developed as programmable RNA-guided Cas proteins for eukaryotic RNA editing. Notably, Cas13 has been utilized for site-targeted single base edits, demethylation, RNA cleavage or knockdown and alternative splicing. However, the ability to edit large stretches of mRNA transcripts remains a significant challenge. Here, we demonstrate that CRISPR-Cas13 systems can be repurposed to assist trans-splicing of exogenous RNA fragments into an endogenous pre-mRNA transcript, a method termed CRISPR Assisted mRNA Fragment Trans-splicing (CRAFT). Using split reporter-based assays, we evaluate orthogonal Cas13 systems, optimize guide RNA length and screen for optimal trans-splicing site(s) across a range of intronic targets. We achieve markedly improved editing of large 5’ and 3’ segments in different endogenous mRNAs across various mammalian cell types compared to other spliceosome-mediated trans-splicing methods. CRAFT can serve as a versatile platform for attachment of protein tags, studying the impact of multiple mutations/single nucleotide polymorphisms, modification of untranslated regions (UTRs) or replacing large segments of mRNA transcripts.

Assessing the impact of type 2 diabetes on mortality and life expectancy according to the number of risk factor targets achieved: an observational study

BackgroundType 2 diabetes (T2D) is associated with an increased risk of premature death. Whether multifactorial risk factor modification could attenuate T2D-related excess risk of death is unclear. We aimed to examine the association of risk factor target achievement with mortality and life expectancy among patients with T2D, compared with individuals without diabetes.MethodsIn this longitudinal cohort study, we included 316 995 participants (14 162 with T2D and 302 833 without T2D) free from cardiovascular disease (CVD) or cancer at baseline between 2006 and 2010 from the UK Biobank. Participants with T2D were categorised according to the number of risk factors within target range (non-smoking, being physically active, healthy diet, guideline-recommended levels of glycated haemoglobin, body mass index, blood pressure, and total cholesterol). Survival models were applied to calculate hazard ratios (HRs) for mortality and predict life expectancy differences.ResultsOver a median follow-up of 13.8 (IQR 13.1–14.4) years, deaths occurred among 2105 (14.9%) participants with T2D and 18 505 (6.1%) participants without T2D. Compared with participants without T2D (death rate per 1000 person-years 4.51 [95% CI 4.44 to 4.57]), the risk of all-cause mortality among those with T2D decreased stepwise with an increasing number of risk factors within target range (0–1 risk factor target achieved: absolute rate difference per 1000 person-years 7.34 [4.91 to 9.78], HR 2.70 [2.25 to 3.25]; 6–7 risk factors target achieved: absolute rate difference per 1000 person-years 0.68 [-0.62 to 1.99], HR 1.16 [0.93 to 1.43]). A similar pattern was observed for CVD and cancer mortality. The association between risk factors target achievement and all-cause mortality was more prominent among participants younger than 60 years than those 60 years or older (P for interaction = 0.012). At age 50 years, participants with T2D who had 0–1 and 6–7 risk factors within target range had an average 7.67 (95% CI 6.15 to 9.19) and 0.99 (-0.59 to 2.56) reduced years of life expectancy, respectively, compared with those without T2D.ConclusionsIndividuals with T2D who achieved multiple risk factor targets had no significant excess mortality risk or reduction in life expectancy than those without diabetes. Early interventions aiming to promote risk factor modification could translate into improved long-term survival for patients with T2D.