Clonal replacement sustains long-lived germinal centers primed by respiratory viruses.

Germinal centers (GCs) form in secondary lymphoid organs in response to infection and immunization and are the source of affinity-matured B cells. The duration of GC reactions spans a wide range, and long-lasting GCs (LLGCs) are potentially a source of highly mutated B cells. We show that rather than consisting of continuously evolving B cell clones, LLGCs elicited by influenza virus or SARS-CoV-2 infection in mice are sustained by progressive replacement of founder clones by naive-derived invader B cells that do not detectably bind viral antigens. Rare founder clones that resist replacement for long periods are enriched in clones with heavily mutated immunoglobulins, including some with very high affinity for antigen, that can be recalled by boosting. Our findings reveal underappreciated aspects of the biology of LLGCs generated by respiratory virus infection and identify clonal replacement as a potential constraint on the development of highly mutated antibodies within these structures.

HA-1-targeted T cell receptor (TCR) T cell therapy for recurrent leukemia after hematopoietic stem cell transplantation.

Relapse is the leading cause of death after allogeneic hematopoietic stem cell transplantation (HCT) for leukemia. T cells engineered by gene transfer to express T cell receptors (TCR; TCR-T) specific for hematopoietic-restricted minor histocompatibility (H) antigens may provide a potent selective anti-leukemic effect post-HCT. We conducted a phase I clinical trial employing a novel TCR-T product targeting the minor H antigen HA-1 to treat or consolidate treatment of persistent or recurrent leukemia and myeloid neoplasms. The primary objective was to evaluate the feasibility and safety of administration of HA-1 TCR-T post-HCT. CD8+ and CD4+ T cells expressing the HA-1 TCR and a CD8-co-receptor were successfully manufactured from HA-1 disparate HCT donors. One or more infusions of HA-1 TCR-T following lymphodepleting chemotherapy were administered to nine HCT recipients who had developed disease recurrence post-HCT. TCR-T cells expanded and persisted in vivo after adoptive transfer. No dose-limiting toxicities occurred. Although the study was not designed to assess efficacy, four patients achieved or maintained complete remissions following lymphodepletion and HA-1 TCR-T, with one ongoing at >2 years. Single-cell RNA sequencing of relapsing/progressive leukemia after TCR-T therapy identified upregulated molecules associated with T cell dysfunction or cancer cell survival. HA-1 TCR-T therapy appears feasible and safe and shows preliminary signals of efficacy. This clinical trial is registered at clinicaltrials.gov as NCT03326921.

Advances in next-generation sequencing and emerging technologies for hematologic malignancies.

Innovations in molecular diagnostics have often evolved through the study of hematologic malignancies. Examples include the pioneering characterization of the Philadelphia chromosome by cytogenetics in the 1970s, the implementation of polymerase chain reaction for high-sensitivity detection and monitoring of mutations and, most recently, targeted next- generation sequencing to drive the prognostic and therapeutic assessment of leukemia. Hematologists and hematopath- ologists have continued to advance in the past decade with new innovations improving the type, amount, and quality of data generated for each molecule of nucleic acid. In this review article, we touch on these new developments and discuss their implications for diagnostics in hematopoietic malignancies. We review advances in sequencing platforms and library preparation chemistry that can lead to faster turnaround times, novel sequencing techniques, the development of mobile laboratories with implications for worldwide benefits, the current status of sample types, improvements to quality and reference materials, bioinformatic pipelines, and the integration of machine learning and artificial intelligence into mol- ecular diagnostic tools for hematologic malignancies.

Ultra-deep mutational landscape in chronic lymphocytic leukemia uncovers dynamics of resistance to targeted therapies.

BTK inhibitors, Bcl-2 inhibitors, and other targeted therapies have significantly improved the outcomes of patients with chronic lymphocytic leukemia (CLL). With increased survivorship, monitoring disease and deciphering potential mechanisms of resistance to these agents are critical for devising effective treatment strategies. We used duplex sequencing, a technology that enables detection of mutations at ultra-low allelic frequencies, to identify mutations in five genes associated with drug resistance in CLL and followed their evolution in two patients who received multiple targeted therapies and ultimately developed disease progression on pirtobrutinib. In both patients we detected variants that expanded and reached significant cancer cell fractions (CCF). In patient R001, multiple known resistance mutations in both BTK and PLCG2 appeared following progression on zanubrutinib (BTK p.L528W, p.C481S; PLCG2 S707F, L845F, R665W, and D993H). In contrast, patient R002 developed multiple BTK mutations following acalabrutinib treatment, including known resistance mutations p.C481R, p.T474I and p.C481S. We found that pirtobrutinib was able to suppress, but not completely eradicate, BTK p.C481S mutations in both patients, but other resistance mutations such as mutations in PLCG2 and new BTK mutations increased while the patients were receiving pirtobrutinib. For example, BTK p.L528W in patient R001 increased in frequency more than 1,000-fold (from a CCF of 0.02% to 35%), and the CCF in p.T474I in patient R002 increased from 0.03% to 4.2% (more than 100-fold). Our data illuminate the evolutionary dynamics of resistant clones over the patients' disease course and under selective pressure from different targeted treatments.

Abnormal bone marrow findings in patients following treatment with chimeric antigen receptor-T cell therapy.

BACKGROUND: Bone marrow (BM) assessment after CAR-T cell immunotherapy infusion is not routinely performed to monitor adverse events such as cytopenias, hemophagocytic lymphohistiocytosis, or infections. Our institution has performed BM biopsies as part of CAR-T cell treatment protocols, encompassing pre- and post-treatment time points and during long-term follow-up. METHODS: We conducted a systematic retrospective review of BM abnormalities observed in samples from 259 patients following CAR-T cell immunotherapy. We correlated BM pathology findings with mortality, relapse/residual disease, and laboratory values. RESULTS: At a median of 35.5 days post-CAR-T infusion, 25.5% showed severe marrow hypocellularity, and 6.2% showed serous atrophy, and peripheral blood cytopenias corroborated these observations. Marrow features associated with reduced disease burden post-CAR-T infusion include increased lymphocytes seen in 16 patients and an increase of macrophages or granulomatous response seen in 25 patients. However, a 100-day landmark analysis also showed increased marrow histiocytes were associated with lower survival (median OS 6.0 vs. 21.4 months, p = .026), as was grade 2-3 marrow reticulin (18 patients) (median OS 12.5 vs. 24.2 months, p = .034). CONCLUSIONS: These data represent the first systematic observations of BM changes in patients receiving CAR-T cell immunotherapy.

Desmoplakin I/II immunohistochemical staining may be a helpful tool in differentiating cutaneous graft versus host disease from the erythema multiforme, Stevens-Johnson syndrome, and toxic epidermal necrolysis spectrum disorders.

Cutaneous graft versus host disease (cGVHD) has substantial clinical and histopathologic overlap with erythema multiforme (EM), Stevens-Johnson syndrome (SJS), and toxic epidermal necrolysis (TEN). This overlap can make it difficult to distinguish these disorders in patients who have received hematopoietic transplants. We sought to evaluate the utility of Dp I/II immunohistochemical stain in differentiating EM/SJS/TEN and cGVHD in a large cohort. Skin biopsy specimens from patients with cGVHD (n = 58) and EM/SJS/TEN (n = 60) were evaluated for Dp I/II expression by immunohistochemistry. We found a statistically significant difference in Dp I/II staining between cGVHD (all grades) and EM/SJS/TEN (mean scores 1.62 and 2.14, respectively; p < 0.005), as well as between Grades 2 + 3 cGVHD and EM/SJS/TEN (mean scores 2.26 and 1.62, respectively; p < 0.005), while we did not find a significant difference between Grade 4 cGVHD and EM/SJS/TEN (mean scores 1.69 and 1.62, respectively; p = 0.71). Dp I/II immunostain may be useful for differentiating EM/SJS/TEN from Grade 2 and Grade 3 cGVHD, especially in clinically ambiguous cases without extracutaneous GVHD.

Safety and Efficacy of Insulins in Critically Ill Patients Receiving Continuous Enteral Nutrition.

OBJECTIVE: There is a relative lack of consensus regarding the optimal management of hyperglycemia in patients receiving continuous enteral nutrition (EN), with or without a diagnosis of diabetes. METHODS: This retrospective study examined 475 patients (303 with known diabetes) hospitalized in critical care setting units in 2019 in a single center who received continuous EN. Rates of hypoglycemia, hyperglycemia, and glucose levels within the target range (70-180 mg/dL) were compared between patients with and without diabetes, and among patients treated with intermediate-acting (IA) biphasic neutral protamine Hagedorn 70/30, long-acting (LA) insulin, or rapid-acting insulin only. RESULTS: Among those with type 2 diabetes mellitus, IA and LA insulin regimens were associated with a significantly higher proportion of patient-days in the target glucose range and fewer hyperglycemic days. Level 1 (<70 mg/dL) and level 2 (<54 mg/dL) hypoglycemia occurred rarely, and there were no significant differences in level 2 hypoglycemia frequency across the different insulin regimens. CONCLUSION: Administration of IA and LA insulin can be safe and effective for those receiving insulin doses for EN-related hyperglycemia.

Assessing Surface Adsorption in Cyclic Olefin Copolymer Microfluidic Devices Using Two-Dimensional Nano Liquid Chromatography-Micro Free Flow Electrophoresis Separations.

Surface interactions are a concern in microscale separations, where analyte adsorption can decrease the speed, sensitivity, and resolution otherwise achieved by miniaturization. Here, we functionally characterize the surface adsorption of hot-embossed cyclic olefin copolymer (COC) micro free-flow electrophoresis (µFFE) devices using two-dimensional nLC × µFFE separations, which introduce a 3- to 5 s plug of analyte into the device and measure temporal broadening that arises from surface interactions. COC is an attractive material for microfluidic devices, but little is known about its potential for surface adsorption in applications with continuous fluid flow and temporal measurements. Adsorption was minimal for three small molecule dyes: positively charged rhodamine 123, negatively charged fluorescein, and neutral rhodamine 110. Temporal peak widths for the three dyes ranged from 3 to 7 s and did not change significantly with increasing transit distance. Moderate adsorption was observed for Chromeo P503-labeled myoglobin and cytochrome c with temporal peak widths around 20 s. Overall, the COC surface adsorption was low compared to traditional glass devices, where peak widths are on the order of minutes. Improvements in durability, long-term performance, and ease of fabrication, combined with low overall adsorption, make the COC µFFE devices a practical choice for applications involving time-resolved continuous detection.

Hormonal profile prior to luteolysis modulates the uterine luminal transcriptome in the subsequent cycle in beef cross-bred cows†.

Sex steroid concentrations modulate endometrial function and fertility in cattle. Our objective was to compare the post-estrus luminal transcriptome of cows that were exposed to contrasting concentrations of progesterone (P4) before luteolysis that displayed estrus and ovulated spontaneously. Cross-bred beef cows received either (1) a new CIDR and GnRH (day -9; high progesterone treatment; HP4; n = 16) or (2) a previously used CIDR, PGF2α, and GnRH (low progesterone treatment; LP4; n = 24). All cows received PGF2α at CIDR removal (day -2). Ovarian ultrasonography and blood collections were performed on days -9, -2, -0.5, and 0 (day of observed estrus), and days 4, 7, and 14 for measurement of ovarian structures, P4, and estradiol (E2). Luminal epithelial cells were collected using a cytology brush on days 4, 7, and 14 for RNAseq. On day -2, CL area and concentrations of P4 were greater, while on day -0.5, concentrations of E2 were decreased in HP4. Ovarian structures and hormonal concentrations were similar on days 4, 7, or 14 (P > 0.05). There were enriched pathways in HP4 related to activation and signaling of the innate immune system at day 4, downregulation in the network involved in the extracellular matrix remodeling at day 7, and exacerbated inflammatory response as well as differentiation and activation of macrophages at day 14 (Benjamini-Hochberg P-value ≤ 0.05). In conclusion, manipulation of pre-luteolysis sex steroid concentrations altered the post-estrus luminal transcriptome even though all cows showed estrus and ovulated spontaneously.

Pre-estrus progesterone does not affect post-estrus luminal metabolome in cross-bred beef cows.

In brief: The concentration of progesterone through the estrous cycle modulates uterine function to affect the luminal metabolome. This paper reports that the dynamic changes in the bovine uterine luminal metabolome during diestrus are independent of the concentration of progesterone in the previous cycle. Abstract: In cattle, the concentration of sex steroids modulates uterine function, which is reflected in the composition of the luminal metabolome. Ultimately, the uterine luminal metabolome influences embryonic growth and development. Our objectives were (i) to compare the luminal metabolome 4, 7, and 14 days after estrus of cows that were exposed to greater (HP4; n = 16) vs lower (LP4; n = 24) concentrations of progesterone before displaying estrus and ovulating spontaneously and (ii) to identify changes in the luminal concentration of metabolites across these time points. Luminal epithelial cells and fluid were collected using a cytology brush, and gene expression and metabolite concentrations were assessed by RNAseq and targeted mass spectrometry, respectively. Metabolome profile was similar between treatments within each of days 4, 7, and 14 (false discovery rate (FDR): ≥ 0.1). Concentrations of 53 metabolites changed, independent of treatment, across the diestrus. Metabolites were mostly lipids (40 out 53) and the greatest concentrations were at day 14 (FDR: ≤ 0.1). On day 7, the concentration of putrescine and the gene expression of ODC1, PAOX, SLC3A2, and SAT1 increased (P ≤ 0.05). On day 14, the concentration of 3 ceramides, 4 glucosylceramides, and 12 sphingomyelins and the expression of SGMS2 were increased, in addition to the concentration of choline and 20 phosphatidylcholines. Collectively, the post-estrus concentration of luminal metabolites changed dynamically, independent of the concentration of sex steroids on the previous cycle, and the greatest magnitude changes were on day 14 when lipid metabolism was the most enriched pathway.

A methodology of phenotyping ICU patients from EHR data: High-fidelity, personalized, and interpretable phenotypes estimation.

OBJECTIVE: Computing phenotypes that provide high-fidelity, time-dependent characterizations and yield personalized interpretations is challenging, especially given the complexity of physiological and healthcare systems and clinical data quality. This paper develops a methodological pipeline to estimate unmeasured physiological parameters and produce high-fidelity, personalized phenotypes anchored to physiological mechanics from electronic health record (EHR). METHODS: A methodological phenotyping pipeline is developed that computes new phenotypes defined with unmeasurable computational biomarkers quantifying specific physiological properties in real time. Working within the inverse problem framework, this pipeline is applied to the glucose-insulin system for ICU patients using data assimilation to estimate an established mathematical physiological model with stochastic optimization. This produces physiological model parameter vectors of clinically unmeasured endocrine properties, here insulin secretion, clearance, and resistance, estimated for individual patient. These physiological parameter vectors are used as inputs to unsupervised machine learning methods to produce phenotypic labels and discrete physiological phenotypes. These phenotypes are inherently interpretable because they are based on parametric physiological descriptors. To establish potential clinical utility, the computed phenotypes are evaluated with external EHR data for consistency and reliability and with clinician face validation. RESULTS: The phenotype computation was performed on a cohort of 109 ICU patients who received no or short-acting insulin therapy, rendering continuous and discrete physiological phenotypes as specific computational biomarkers of unmeasured insulin secretion, clearance, and resistance on time windows of three days. Six, six, and five discrete phenotypes were found in the first, middle, and last three-day periods of ICU stays, respectively. Computed phenotypic labels were predictive with an average accuracy of 89%. External validation of discrete phenotypes showed coherence and consistency in clinically observable differences based on laboratory measurements and ICD 9/10 codes and clinical concordance from face validity. A particularly clinically impactful parameter, insulin secretion, had a concordance accuracy of 83%±27%. CONCLUSION: The new physiological phenotypes computed with individual patient ICU data and defined by estimates of mechanistic model parameters have high physiological fidelity, are continuous, time-specific, personalized, interpretable, and predictive. This methodology is generalizable to other clinical and physiological settings and opens the door for discovering deeper physiological information to personalize medical care.

Digital Health and Shared Decision-Making in Diabetes Care - A Survey Initiative in Patients and Clinicians.

OBJECTIVE: To assess the landscape of digital health resources in the United States, better understand the impact of the digital health on shared decision-making, and identify potential barriers and opportunities for progress in the care of persons with diabetes. METHODS: The study consisted of two phases: A qualitative phase in which one-on-one interviews were conducted virtually with 34 physicians (endocrinologists {Endos}: n = 15; primary care physicians {PCPs}: n = 19) between February 11, 2021 and February 18, 2021, and a quantitative phase in which two online, email-based surveys in the English language were conducted between April 16, 2021 and May 17, 2021: one with healthcare professionals (HCP) (n = 403: n = 200 Endos and n = 203 PCPs), and one with persons with diabetes (n = 517: patients with type 1 diabetes, n = 257; patients with type 2 diabetes, n = 260). RESULTS: Diabetes digital health tools were found to be helpful in shared decision-making, but leading barriers include cost, coverage, and lack of time by healthcare professionals. Among diabetes digital health tools, continuous glucose monitoring (CGM) systems were used most commonly and viewed as most effective in improving quality of life and facilitating shared decision-making. Strategies for increasing use of diabetes digital health resources included lower cost, integration into electronic health records, and increased simplicity of tools. CONCLUSION: This study revealed that both Endos and PCPs feel that diabetes digital health tools have an overall positive impact. Integration with telemedicine and simpler, lower cost tools with increased patient access can further facilitate shared decision-making and improved diabetes care and quality of life.

American Association of Clinical Endocrinology Consensus Statement: Comprehensive Type 2 Diabetes Management Algorithm - 2023 Update.

OBJECTIVE: This consensus statement provides (1) visual guidance in concise graphic algorithms to assist with clinical decision-making of health care professionals in the management of persons with type 2 diabetes mellitus to improve patient care and (2) a summary of details to support the visual guidance found in each algorithm. METHODS: The American Association of Clinical Endocrinology (AACE) selected a task force of medical experts who updated the 2020 AACE Comprehensive Type 2 Diabetes Management Algorithm based on the 2022 AACE Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan and consensus of task force authors. RESULTS: This algorithm for management of persons with type 2 diabetes includes 11 distinct sections: (1) Principles for the Management of Type 2 Diabetes; (2) Complications-Centric Model for the Care of Persons with Overweight/Obesity; (3) Prediabetes Algorithm; (4) Atherosclerotic Cardiovascular Disease Risk Reduction Algorithm: Dyslipidemia; (5) Atherosclerotic Cardiovascular Disease Risk Reduction Algorithm: Hypertension; (6) Complications-Centric Algorithm for Glycemic Control; (7) Glucose-Centric Algorithm for Glycemic Control; (8) Algorithm for Adding/Intensifying Insulin; (9) Profiles of Antihyperglycemic Medications; (10) Profiles of Weight-Loss Medications (new); and (11) Vaccine Recommendations for Persons with Diabetes Mellitus (new), which summarizes recommendations from the Advisory Committee on Immunization Practices of the U.S. Centers for Disease Control and Prevention. CONCLUSIONS: Aligning with the 2022 AACE diabetes guideline update, this 2023 diabetes algorithm update emphasizes lifestyle modification and treatment of overweight/obesity as key pillars in the management of prediabetes and diabetes mellitus and highlights the importance of appropriate management of atherosclerotic risk factors of dyslipidemia and hypertension. One notable new theme is an emphasis on a complication-centric approach, beyond glucose levels, to frame decisions regarding first-line pharmacologic choices for the treatment of persons with diabetes. The algorithm also includes access/cost of medications as factors related to health equity to consider in clinical decision-making.

Pre- and perinatal exposures associated with molar incisor hypomineralization: Birth cohort, Brazil.

OBJECTIVE: To analyze prenatal and perinatal stressors associated with molar incisor hypomineralization (MIH) in adolescents. METHODS: Prospective cohort study collected prenatal (socioeconomic status, maternal age, number of prenatal visits, smoking, obesity during pregnancy, abortion history, gestational hypertension) and perinatal stressors (type of delivery, gestational age, birth weight, intensive care unit-ICU at birth). The outcome was MIH at 18-19 years follow-up (n = 590). MIH was defined according to the Ghanim criteria - Model I. We performed a sensitivity analysis, including opacities demarcated in index tooth, incisive or molars, Model II. Through structural equation modeling, we analyzed direct and mediating pathways between multiple stressors with outcomes. RESULTS: MIH was observed in 15.25% (n = 90), and opacities demarcated in any index tooth were observed in 22.8% of adolescents (n = 135). In Model I, no stressor explained MIH significantly, although we watched high standardized coefficients (SC) for low birth weight (SC = 0.223, p = 0.147), lower gestational age (SC = 0.351; p = 0.254), and ICU admission (SC = 0.447, p = 0.254). In Model II, advanced maternal age (SC = 0.148; p < 0.05) and not undergoing prenatal care (SC = 0.384, p < 0.03) explained opacities demarcated in incisors or molars. CONCLUSION: Advanced maternal age and not undergoing prenatal care were associated with MIH lesion-like in incisors or molars.

Precursors of insulin resistance underlying periodontitis in adolescents aged 17-18 years.

OBJECTIVE: To investigate the association between insulin resistance markers and periodontitis in adolescents, analyzing confounder variables and the adiposity as a mediator. METHODS: This is population-based study is representative of adolescents aged 17-18 years from public schools in São Luís, Brazil (n = 405). Insulin resistance was assessed using the Model of Assessment of the Homeostasis of the Insulin Resistance Index (HOMA-IR) and its percussor triglycerides/HDL-cholesterol ratio (TG/HDL-c). The outcome was Initial Periodontitis, a latent variable estimated by the common variance shared among bleeding on probing, probing depth ≥ 4 mm, and clinical attachment loss ≥ 4 mm. The association between insulin resistance and Initial Periodontitis was modeled via pathways triggered by socioeconomic status, smoking, alcohol, and Adiposity, using structural equation modeling. RESULTS: Higher TG/HDL-c was directly associated with higher Initial Periodontitis (standardized coefficient [SC] = 0.130, p < 0.001). HOMA-IR was not associated with periodontal outcome (SC = 0.023, p = 0.075), but it was with Adiposity (SC = 0.495, p < 0.001). Higher TG/HDL-c was associated with Adiposity (SC = 0.202, p < 0.001). CONCLUSION: The insulin resistance markers were associated with early signs of periodontal breakdown among adolescents, suggesting a possible relationship between diabetes and periodontitis commences early in life.

The Utility of Assessing Alexithymia, in Addition to Coping, in the Context of Posttraumatic Stress.

ABSTRACT: The distinction between alexithymia and coping in relation to posttraumatic stress has not been fully explored. The present study examined the extent to which alexithymia explained unique variance in posttraumatic stress, beyond the variance explained by coping, in a sample of trauma-exposed adults ( N = 706; M age = 19.41 years, SD = 1.5; 77.1% female). Then, we explored the effect of race on these associations, comparing participants who identified as Black ( n = 275) to those who identified as White ( n = 337). Avoidant-emotional coping showed stronger correlations (compared with problem-focused and active-emotional coping) with total alexithymia, difficulty identifying feelings, and difficulty describing feelings. In regression analyses, we found alexithymia explained unique variance in posttraumatic stress severity beyond the effect of coping. Results did not differ by racial identity. These findings suggest that despite some overlap between alexithymia and coping, each shows unique relations with posttraumatic stress.

bsAS, an antisense long non-coding RNA, essential for correct wing development through regulation of blistered/DSRF isoform usage.

Natural Antisense Transcripts (NATs) are long non-coding RNAs (lncRNAs) that overlap coding genes in the opposite strand. NATs roles have been related to gene regulation through different mechanisms, including post-transcriptional RNA processing. With the aim to identify NATs with potential regulatory function during fly development, we generated RNA-Seq data in Drosophila developing tissues and found bsAS, one of the most highly expressed lncRNAs in the fly wing. bsAS is antisense to bs/DSRF, a gene involved in wing development and neural processes. bsAS plays a crucial role in the tissue specific regulation of the expression of the bs/DSRF isoforms. This regulation is essential for the correct determination of cell fate during Drosophila development, as bsAS knockouts show highly aberrant phenotypes. Regulation of bs isoform usage by bsAS is mediated by specific physical interactions between the promoters of these two genes, which suggests a regulatory mechanism involving the collision of RNA polymerases transcribing in opposite directions. Evolutionary analysis suggests that bsAS NAT emerged simultaneously to the long-short isoform structure of bs, preceding the emergence of wings in insects.

A simple modeling framework for prediction in the human glucose-insulin system.

Forecasting blood glucose (BG) levels with routinely collected data is useful for glycemic management. BG dynamics are nonlinear, complex, and nonstationary, which can be represented by nonlinear models. However, the sparsity of routinely collected data creates parameter identifiability issues when high-fidelity complex models are used, thereby resulting in inaccurate forecasts. One can use models with reduced physiological fidelity for robust and accurate parameter estimation and forecasting with sparse data. For this purpose, we approximate the nonlinear dynamics of BG regulation by a linear stochastic differential equation: we develop a linear stochastic model, which can be specialized to different settings: type 2 diabetes mellitus (T2DM) and intensive care unit (ICU), with different choices of appropriate model functions. The model includes deterministic terms quantifying glucose removal from the bloodstream through the glycemic regulation system and representing the effect of nutrition and externally delivered insulin. The stochastic term encapsulates the BG oscillations. The model output is in the form of an expected value accompanied by a band around this value. The model parameters are estimated patient-specifically, leading to personalized models. The forecasts consist of values for BG mean and variation, quantifying possible high and low BG levels. Such predictions have potential use for glycemic management as part of control systems. We present experimental results on parameter estimation and forecasting in T2DM and ICU settings. We compare the model's predictive capability with two different nonlinear models built for T2DM and ICU contexts to have a sense of the level of prediction achieved by this model.

Mycosynthesis of silver nanoparticles using psychrotrophic strains of Tulasnella albida Bourdot & Galzin from the South Orkney Islands (Antarctica).

This study is the first report on mycosynthesis of silver nanoparticles (NPs) using psychrotrophic Antarctic filamentous fungi, and the first report regarding Tulasnella (Basidiomycota). In this work, the ability to synthesize silver NPs from cell free filtrates of strains of Tulasnella albida isolated from Antarctica was assessed. All fungal filtrates were capable of synthesizing silver NPs with the addition of AgNO3. UV-vis spectroscopy, TEM and SEM microscopy analyses were performed to characterize the synthesized NPs. ATR-FTIR and Micro Raman spectroscopy analyses were conducted to find functional groups responsible for the reduction of AgNO3 and to detect the presence of silver oxide on the AgNPs. Theoretical calculations of optical absorption based on core-shell Ag-Ag2O were used to characterize the experimental absorption spectra of silver NPs colloids. Spherically shaped silver NPs, typically 2-3nm in diameter, were obtained. The largest ones showed a capping shell around them, which could be associated with the formation of small silver NPs. Functional groups corresponding to amides and alcohols were detected, confirming the presence of proteins as possible intermediates in the synthesis of AgNPs. On the other hand, the Micro Raman analysis confirms the presence of silver oxide on the surface of the AgNPs. This work presents a simple procedure for the synthesis of silver NPs using a psychrotrophic organism that could be interesting for the industry.

Chromatin dynamics in regeneration epithelia: Lessons from Drosophila imaginal discs.

During the process of regeneration, a switch in the transcription program occurs in cells that contribute to the reconstruction of the missing tissue. Early signals released upon damage are integrated into the chromatin of responding cells to change its activity and function. Changes in chromatin dynamics result in transcriptional reprogramming, this is the coordinated regulation of expression of a specific subset of genes required for the regeneration process. Here we summarize changes in gene expression and chromatin dynamics that occurs during the process of regeneration of Drosophila imaginal discs.