Controlled glycemic concentrations are associated with a lower risk of conditions such as cardiovascular disease and diabetes. Models commonly used to guide interventions to control the glycemic ...response to food have low efficacy, with recent clinical guidelines arguing for the use of personalized approaches.
We tested the efficacy of a predictive model of personalized postprandial glycemic response to foods that was developed with an Israeli cohort and that takes into consideration food components and specific features, including the microbiome, when applied to individuals from the Midwestern US.
We recruited 327 individuals for this study. Participants provided information regarding lifestyle, dietary habits, and health, as well as a stool sample for characterization of their gut microbiome. Participants were connected to continuous glucose monitors for 6 d, and the glycemic response to meals logged during this time was computed. The ability of a model trained using meals logged by the Israeli cohort to correctly predict glycemic responses in the Midwestern cohort was assessed and compared with that of a model trained using meals logged by both cohorts.
When trained on the Israeli cohort meals only, model performance for predicting responses of individuals in the Midwestern cohort was better (R = 0.596) than that observed for models taking into consideration the carbohydrate (R = 0.395) or calorie content of the meals alone (R = 0.336). Performance increased (R = 0.618) when the model was trained on meals from both cohorts, likely because of the observed differences in age distribution, diet, and microbiome.
We show that the modeling framework described in Zeevi et al. for an Israeli cohort is applicable to a Midwestern population, and outperforms commonly used approaches for the control of blood glucose responses. The adaptation of the model to the Midwestern cohort further enhances performance and is a promising means for designing effective nutritional interventions to control glycemic responses to foods. This trial was registered at clinicaltrials.gov as NCT02945514.
Emerging evidence suggests that postprandial glycemic responses (PPGRs) to food may be influenced by and predicted according to characteristics unique to each individual, including anthropometric and ...microbiome variables. Interindividual diversity in PPGRs to food requires a personalized approach for the maintenance of healthy glycemic levels.
To describe and predict the glycemic responses of individuals to a diverse array of foods using a model that considers the physiology and microbiome of the individual in addition to the characteristics of the foods consumed.
This cohort study using a personalized predictive model enrolled 327 individuals without diabetes from October 11, 2016, to December 13, 2017, in Minnesota and Florida to be part of a study lasting 6 days. The study measured anthropometric variables, described the gut microbial composition, and assessed blood glucose levels every 5 minutes using a continuous glucose monitor. Participants logged their food and activity information for the duration of the study. A predictive model of individualized PPGRs to a diverse array of foods was trained and applied.
Glycemic responses to food consumed over 6 days for each participant. The predictive model of personalized PPGRs considered individual features, including the microbiome, in addition to the features of the foods consumed.
Postprandial response to the same foods varied across 327 individuals (mean SD age, 45 12 years; 78.0% female). A model predicting each individual's responses to food that considers several individual factors in addition to food features had better overall performance (R = 0.62) than current standard-of-care approaches using nutritional content alone (R = 0.34 for calories and R = 0.40 for carbohydrates) to control postprandial glycemic levels.
Across the cohort of adults without diabetes who were examined, a personalized predictive model that considers unique features of the individual, such as clinical characteristics, physiological variables, and the microbiome, in addition to nutrient content was more predictive than current dietary approaches that focus only on the calorie or carbohydrate content of foods. Providing individuals with tools to manage their glycemic responses to food based on personalized predictions of their PPGRs may allow them to maintain their blood glucose levels within limits associated with good health.
HbA1c% is the most commonly used metric for assessing glycemic status, but only represents an averaged, indirect measure. Continuous Glucose Monitors (CGM) provides additional, elaborated assessment ...metrics. A recent study, Zeevi et al., 2015, Cell showed that glycemic responses to foods vary across individuals and can be predicted using a machine learning framework. Moreover, it showed that personally tailored diets based on this framework improves Postprandial Glycemic Response (PPGR) in one-week interventions. Here, we tested the ability of such framework to improve longer term measures of glycemic control. A cohort of 28 diabetic individuals, not using short term insulin, were tracked. Each participant was tested for initial HbA1c, and connected to a CGM for a period of 14 days. Then, participant's anthropometrics, lifestyle, clinical parameters, and gut microbiome composition, were fed into a machine learning algorithm built into a personalized mobile application. Using the application, participants could define meals by combining foods, and obtain instant scores indicating the predicted PPGR for each meal. Participants were instructed to limit consumption to highly scoring meals. After 4-20 months of using the application, participants were re-connected to CGM, and HbA1c% levels were measured again.
Results: Significant improvements in multiple endpoints: Average HbA1c% dropped from 7.2% to 6.5% (p-value: 1.2e-8). Average %time-in-range 70,140 mg/dl increased from 69.1% to 79.6% (p-value: 0.005). Average %time-in-range 70,180 mg/dl increased from 89.6% to 94.2% (p-value: 0.002). Mean glucose levels decreased from 125.6 mg/dl to 114.6 mg/dl (p-value: 0.0002). These observations, coupled with the short-term benefits shown in recent work, imply that drugless, personalized, nutrition-based interventions, may be key to achieving significant improvements in glycemic control of type 2 diabetic patients.
Disclosure
Y. Ben Shlomo: Employee; Self; DayTwo. S. Azulay: Employee; Self; DayTwo. T. Raveh-Sadka: Employee; Self; DayTwo. Y. Cohen: Employee; Self; DayTwo. A. Hanemann: Employee; Self; DayTwo.
This work presents a new distributed Byzantine tolerant federated learning algorithm, HoldOut SGD, for Stochastic Gradient Descent (SGD) optimization. HoldOut SGD uses the well known machine learning ...technique of holdout estimation, in a distributed fashion, in order to select parameter updates that are likely to lead to models with low loss values. This makes it more effective at discarding Byzantine workers inputs than existing methods that eliminate outliers in the parameter-space of the learned model. HoldOut SGD first randomly selects a set of workers that use their private data in order to propose gradient updates. Next, a voting committee of workers is randomly selected, and each voter uses its private data as holdout data, in order to select the best proposals via a voting scheme. We propose two possible mechanisms for the coordination of workers in the distributed computation of HoldOut SGD. The first uses a truthful central server and corresponds to the typical setting of current federated learning. The second is fully distributed and requires no central server, paving the way to fully decentralized federated learning. The fully distributed version implements HoldOut SGD via ideas from the blockchain domain, and specifically the Algorand committee selection and consensus processes. We provide formal guarantees for the HoldOut SGD process in terms of its convergence to the optimal model, and its level of resilience to the fraction of Byzantine workers. Empirical evaluation shows that HoldOut SGD is Byzantine-resilient and efficiently converges to an effectual model for deep-learning tasks, as long as the total number of participating workers is large and the fraction of Byzantine workers is less than half (<1/3 for the fully distributed variant).
Recent work has highlighted the role of initialization scale in determining the structure of the solutions that gradient methods converge to. In particular, it was shown that large initialization ...leads to the neural tangent kernel regime solution, whereas small initialization leads to so called "rich regimes". However, the initialization structure is richer than the overall scale alone and involves relative magnitudes of different weights and layers in the network. Here we show that these relative scales, which we refer to as initialization shape, play an important role in determining the learned model. We develop a novel technique for deriving the inductive bias of gradient-flow and use it to obtain closed-form implicit regularizers for multiple cases of interest.
Despite remarkable progress, the immunotherapies currently used in the clinic, such as immune checkpoint blockade (ICB) therapy, still have limited efficacy against many types of solid tumors. One ...major barrier to effective treatment is the lack of a durable long-term response. Tumor-targeted superantigen (TTS) therapy may overcome this barrier to enhance therapeutic efficacy. TTS proteins, such as the clinical-stage molecule naptumomab estafenatox (NAP), increase tumor recognition and killing by both coating tumor cells with bacterial-derived superantigens (SAgs) and selectively expanding T-cell lineages that can recognize them. The present study investigated the efficacy and mechanism of action of repeated TTS (C215Fab-SEA) treatments leading to a long-term antitumor immune response as monotherapy or in combination with PD-1/PD-L1 inhibitors in murine tumor models.
We used syngeneic murine tumor models expressing the human EpCAM target (C215 antigen) to assess the efficacy and mechanism of action of repeated treatment with TTS C215Fab-SEA alone or with anti-PD-1/PD-L1 monoclonal antibodies. Tumor draining lymph nodes (TDLNs) and tumor tissues were processed and analyzed by immunophenotyping and immunohistochemistry. Isolated RNA from tumors was used to analyze gene expression and the TCR repertoire. Tumor rechallenge and T-cell transfer studies were conducted to test the long-term antitumor memory response.
TTS therapy inhibited tumor growth and achieved complete tumor rejection, leading to a T-cell-dependent long-term memory response against the tumor. The antitumor effect was derived from inflammatory responses converting the immunosuppressive TME into a proinflammatory state with an increase in T-cell infiltration, activation and high T-cell diversity. The combination of TTS with ICB therapy was significantly more effective than the monotherapies and resulted in higher tumor-free rates.
These new results indicate that TTSs not only can turn a "cold" tumor into a "hot" tumor but also can enable epitope spreading and memory response, which makes TTSs ideal candidates for combination with ICB agents and other anticancer agents.
Objective
Prenatal exome sequencing (ES) is currently indicated for fetal malformations. Some neurocognitive genetic disorders may not have a prenatal phenotype. We assessed the prevalence of ...prenatally detectable phenotypes among patients with neurocognitive syndromes diagnosed postnatally by ES.
Methods
The medical files of a cohort of 138 patients diagnosed postnatally with a neurocognitive disorder using ES were reviewed for prenatal sonographic data. The Online Mendelian Inheritance in Man (OMIM) database was searched for prenatally detectable phenotypes for all genes identified.
Results
Prenatal imaging data were available for 122 cases. Of these, 29 (23.75%) had fetal structural abnormalities and another 29 had other ultrasound abnormalities (fetal growth restriction, polyhydramnios, elevated nuchal translucency). In 30 patients, structural aberrations that were not diagnosed prenatally were detected at birth; in 21 (17.2%), the abnormalities could theoretically be detected prenatally by third‐trimester/targeted scans. According to OMIM, 55.9% of the diagnosed genes were not associated with structural anomalies.
Conclusions
Most patients (52.5%) with postnatally diagnosed neurocognitive disorders did not have prenatal sonographic findings indicating prenatal ES should be considered. The prevalence of specific prenatal phenotypes such as fetal growth restriction and polyhydramnios in our cohort suggests that additional prenatal findings should be assessed as possible indications for prenatal ES.
Key points
What's already known about this topic?
Prenatal exome sequencing (ES) is currently indicated for fetal malformations.
Some neurocognitive genetic disorders may not have prenatal phenotypes.
What does this study add?
We assessed the prevalence of prenatally detectable phenotypes among 138 patients with neurocognitive syndromes diagnosed postnatally by ES.
Fetal structural abnormalities were present in 23.75%.
Other ultrasound abnormalities (such as fetal growth restriction, polyhydramnios) were reported in 23.75%.
Most patients diagnosed with neurocognitive disorders did not have an indication for prenatal ES.
Biofilms are surface or interface-associated communities of bacterial cells, embedded in a self-secreted extracellular matrix (ECM). Cells in biofilms are 100-1000 times more resistant to antibiotic ...treatment relative to planktonic cells due to various reasons, including the ECM acting as a diffusion barrier to antibiotic molecules, the presence of persister cells that divide slowly and are less susceptible to cell-wall targeting drugs, and the activation of efflux pumps in response to antibiotic stress. In this study we tested the effect of two titanium(iv) complexes that have been previously reported as potent and non-toxic anticancer chemotherapeutic agents on
cells in culture and in biofilm forming conditions. The Ti(iv) complexes tested, a hexacoordinate diaminobis(phenolato)-bis(alkoxo) complex (phenolaTi) and a bis(isopropoxo) complex of a diaminobis(phenolato) "salan"-type ligand (salanTi), did not affect the growth rate of cells in shaken cultures, however they did affect biofilm formation. Surprisingly, while phenolaTi inhibited biofilm formation, the presence of salanTi induced the formation of more mechanically robust biofilms. Optical microscopy images of biofilm samples in the absence and presence of Ti(iv) complexes suggest that Ti(iv) complexes affect cell-cell and/or cell-matrix adhesion, and that these are interfered with phenolaTi and enhanced by salanTi. Our results highlight the possible effect of Ti(iv) complexes on bacterial biofilms, which is gaining interest in light of the emerging relations between bacteria and cancerous tumors.
The cultivation of monosex populations is common in animal husbandry. However, preselecting the desired gender remains a major biotechnological and ethical challenge. To achieve an efficient ...biotechnology for all-female aquaculture in the economically important prawn (Macrobrachium rosenbergii), we achieved - for the first time - WW males using androgenic gland cells transplantation which caused full sex-reversal of WW females to functional males. Crossing the WW males with WW females yielded all-female progeny lacking the Z chromosome. We now have the ability to manipulate - by non-genomic means - all possible genotype combinations (ZZ, WZ and WW) to retain either male or female phenotypes and hence to produce monosex populations of either gender. This calls for a study of the genomic basis underlying this striking sexual plasticity, questioning the content of the W and Z chromosomes. Here, we report on the sequencing of a high-quality genome exhibiting distinguishable paternal and maternal sequences. This assembly covers ~ 87.5% of the genome and yielded a remarkable N50 value of ~ 20 × 10
bp. Genomic sex markers were used to initiate the identification and validation of parts of the W and Z chromosomes for the first time in arthropods.
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