Subspace Identification of a Glucose-Insulin model Using Meal Tracer Protocol Measurements

In this study, the problem of identifying a low complexity state space model describing glucose and insulin dynamics from low sample meal tracer experiments is investigated. Triple tracer meal protocol measurements (sampled as low as 15 samples per meal) together with continuous glucose monitoring measurements, measured concurrently at a rate of 5 minutes per sample, are used. A new formulation to estimate the missing input and output measurements at such low sample rates is developed. Nuclear norm minimization is used to exploit low rankness of the stacked input and output matrix, while the {ell1} norm is used to exploit an available sparse basis for the glucose flux profiles. Simulation results, using the UVa Padova simulator, show that the technique outperforms previous methods and also demonstrate the possibility of identifying state space models from triple tracer measurements with good prediction performance under non-ideal conditions

Dysmenorrhea Among High-School Students and It\u27s Associated Factors in Kuwait

Background Although dysmenorrhea is not a life-threatening condition, it can cause a substantial burden on individuals and communities. There is no data on the prevalence of dysmenorrhea in Kuwait. This study aimed to estimate the prevalence of dysmenorrhea among female public high-school students in Kuwait and investigate factors associated with dysmenorrhea. Methods A cross-sectional study using multistage cluster sampling with probability proportional to size method was conducted on 763 twelfth grade female public high-school students (aged 16–21 years). We used face-to-face interview with a structured questionnaire to collect data on dysmenorrhea and presumed risk factors. Weight and height of the students were measured using appropriate weight and height scales in a standardized manner. The association between dysmenorrhea and potential risk factors was assessed using multiple logistic regression. Results The one-year prevalence of dysmenorrhea was found to be 85.6% (95%CI: 83.1–88.1%). Of the participants with dysmenorrhea, 26% visited a public or a private clinic for their pain and 4.1% were hospitalized for their menstrual pain. Furthermore, 58.2% of students with dysmenorrhea missed at least one school day and 13.9% missed at least one exam. Age of menarche (p-value = 0.005), regularity and flow of the menstrual period (p-value = 0.025, p-value = 0.009; respectively), and drinking coffee (p-value = 0.004) were significantly associated with dysmenorrhea in multivariable analysis. Conclusion Dysmenorrhea seems to be highly prevalent among female high-school students in Kuwait, resembling that of high-income countries. Because of the scale of the problem, utilizing school nurses to reassure and manage students with primary dysmenorrhea and referring suspected cases of secondary dysmenorrhea is recommended

Sparse Reconstruction of Glucose Fluxes Using Continuous Glucose Monitors

A new technique for estimating postprandial glucose flux profiles without the use of glucose tracers is proposed. A sparse vector space representation is first found for the space of plausible glucose flux profiles using sparse encoding. A Lasso formulation is then used to estimate the glucose fluxes that combines (1) known patient model parameters; (2) the vector space of plausible glucose flux profiles; (3) continuous glucose monitor measurements taken during the meal; (4) amount of insulin injected; (5) amount of meal carbohydrates; and (6) an estimate of the initial conditions. Three glucose fluxes are then estimated, namely; glucose rate of appearance from the intestine; endogenous glucose production from the liver; insulin dependent glucose utilization; and other important state variables. The simulation results show that the technique is capable of estimating the glucose fluxes with high accuracy, even for complex meal scenarios. The experimental results indicate that the technique is capable of reproducing the triple tracer measurements for three T1DM undergoing the triple tracer protocol while estimating the missing measurements for a certain model parameter selection

Nitrogen removal performance and bacterial community analysis of a multistage step-feeding tidal flow constructed wetland

A multistage mesocosm vertical flow constructed wetland system was designed to treat synthetic domestic wastewater with a high nitrogen (N) load. The study aim was to determine the impact of design and operational variables on N removal efficiency in such systems. A tidal flow operational strategy enhanced aeration and was coupled with a step-feeding approach to promote N removal. Over the 420-day running period N removal rates were between 70 and 77 gN/m3/d, for a step-feeding ratio range of 60:40 to 80:20. The system was able to remove 91–95% of chemical oxygen demand, 74–91% of ammonium and 66–81% of total-N. Tidal flow and step-feeding strategies significantly impacted nitrogen removal with the best performance at a step-feeding ratio of 80:20 providing a carbon to nitrogen (COD/N) ratio of 4–5. The bacterial diversity increased at each stage throughout the system with dominating phyla Proteobacteria, Firmicutes, Planctomycetes, Bacteroidetes, Chloroflexi, Verrucomicrobia and Acidobacteria. Dominant bacteria at the genus level were Thiothrix, Planctomyces, Azonexus, Pseudoxanthomonas, Hydrogenophaga, Gemmobacter and other genera suggesting that N removal was accomplished via diverse metabolic pathways, including autotrophic nitrification, heterotrophic denitrification, autotrophic denitrification, and possibly anammox. This study shows benefits of step-feeding strategies in tidal flow constructed wetlands as a cost-effective solution for minimizing external carbon input to achieve effective N removal

The prevalence of polypharmacy and hyper-polypharmacy among middle-aged vs. older patients in Saudi Arabia: a cross-sectional study

IntroductionPolypharmacy, the use of multiple medications, is a growing concern among middle-aged and older patients, posing potential risks and challenges in healthcare management.AimThis study aimed to identify the prevalence of polypharmacy and hyper-polypharmacy among populations of middle-aged vs. older patients and identify its associated common comorbidities and prescribed medications in Qatif Central Hospital (QCH), Saudi Arabia.MethodsPatients aged 40 years or older who presented to an outpatient medical care clinic at QCH, Saudi Arabia, between 1 January and 31 December 2021 were included, and their comorbidities, prescribed medications, and recent clinical laboratory test results were collected. The Charlson comorbidity index (CCI) score was calculated to predict the risk of mortality. Logistic regression was used to compute the association between the prevalence of polypharmacy and patient characteristics. The results were presented as odds ratios (ORs) and 95% confidence intervals (95% CIs).ResultsA total of 14,081 patients were included; 31% of the cohort comprised older patients, and 66% of the cohort was identified with polypharmacy. The majority of the polymedicated patients were presented to an internal medicine care unit (34%). The prevalence of polypharmacy was positively associated with CCI (OR = 3.4, 95% CI 3.3–3.6), having a disease related to the musculoskeletal system (MSD) (OR = 4.2, 95% CI 3.8–4.7), and alimentary tract and metabolism (ATM) (OR = 3.8, 95% CI 3.4–4.2). Conversely, the prevalence of polypharmacy was negatively associated with age (OR = 0.9, 95% CI 0.89–0.91) and patients with cardiovascular diseases (OR = 0.6, 95% CI 0.5–0.7).ConclusionPolypharmacy is still an ongoing concern. Patients, particularly those with diseases related to MSD or ATM, should be considered for reviewing prescriptions by pharmacists to reduce the risk of adverse drug reactions and future consequences of polypharmacy

Effect of biochar modified with magnetite nanoparticles and HNO\u3csub\u3e3\u3c/sub\u3e for efficient removal of Cr(VI) from contaminated water: A batch and column scale study

© 2020 Elsevier Ltd Chromium (Cr) poses serious consequences on human and animal health due to its potential carcinogenicity. The present study aims at preparing a novel biochar derived from Chenopodium quinoa crop residues (QBC), its activation with magnetite nanoparticles (QBC/MNPs) and strong acid HNO3 (QBC/Acid) to evaluate their batch and column scale potential to remove Cr (VI) from polluted water. The QBC, QBC/MNPs and QBC/Acid were characterized with SEM, FTIR, EDX, XRD as well as point of zero charge (PZC) to get an insight into their adsorption mechanism. The impact of different process parameters including dose of the adsorbent (1–4 g/L), contact time (0–180 min), initial concentration of Cr (25–200 mg/L) as well as solution pH (2–8) was evaluated on the Cr (VI) removal from contaminated water. The results revealed that QBC/MNPs proved more effective (73.35–93.62-%) for the Cr (VI) removal with 77.35 mg/g adsorption capacity as compared with QBC/Acid (55.85–79.8%) and QBC (48.85–75.28-%) when Cr concentration was changed from 200 to 25 mg/L. The isothermal experimental results follow the Freundlich adsorption model rather than Langmuir, Temkin and Dubinin-Radushkevich adsorption isotherm models. While kinetic adsorption results were well demonstrated by pseudo second order kinetic model. Column scale experiments conducted at steady state exhibited excellent retention of Cr (VI) by QBC, QBC/MNPs and QBC/Acid at 50 and 100 mg Cr/L. The results showed that this novel biochar (QBC) and its modified forms (QBC/Acid and QBC/MNPs) are applicable with excellent reusability and stability under acidic conditions for the practical treatment of Cr (VI) contaminated water