Background: Insulin resistance is a common etiology of metabolic syndrome, but receiver operating characteristic (ROC) curve analysis shows a weak association in Koreans. Using a machine learning (ML) approach, we aimed to generate the best model for predicting insulin resistance in Korean adults aged > 40 of the Ansan/Ansung cohort using a machine learning (ML) approach. Methods: The demographic, anthropometric, biochemical, genetic, nutrient, and lifestyle variables of 8842 participants were included. The polygenetic risk scores (PRS) generated by a genome-wide association study were added to represent the genetic impact of insulin resistance. They were divided randomly into the training (n = 7037) and test (n = 1769) sets. Potentially important features were selected in the highest area under the curve (AUC) of the ROC curve from 99 features using seven different ML algorithms. The AUC target was ≥0.85 for the best prediction of insulin resistance with the lowest number of features. Results: The cutoff of insulin resistance defined with HOMA-IR was 2.31 using logistic regression before conducting ML. XGBoost and logistic regression algorithms generated the highest AUC (0.86) of the prediction models using 99 features, while the random forest algorithm generated a model with 0.82 AUC. These models showed high accuracy and k-fold values (>0.85). The prediction model containing 15 features had the highest AUC of the ROC curve in XGBoost and random forest algorithms. PRS was one of 15 features. The final prediction models for insulin resistance were generated with the same nine features in the XGBoost (AUC = 0.86), random forest (AUC = 0.84), and artificial neural network (AUC = 0.86) algorithms. The model included the fasting serum glucose, ALT, total bilirubin, HDL concentrations, waist circumference, body fat, pulse, season to enroll in the study, and gender. Conclusion: The liver function, regular pulse checking, and seasonal variation in addition to metabolic syndrome components should be considered to predict insulin resistance in Koreans aged over 40 years.

We present a simple synthetic approach for the preparation of monodisperse thermosensitive gelatin microspheres in a microfluidic system. Based on the mechanism of shear force-driven break-off, aqueous droplets of a gelatin solution were continuously produced in an immiscible continuous fluid. Under cooling conditions, the gelatin droplets solidified into hydrogel microspheres, which resulted from the aggregation or crystallization of collagen folds. The produced gelatin microspheres possess a high monodispersity and fast response to environmental temperature. In addition, the size of the prepared microspheres can be manipulated by altering the flow rate of the continuous phase or aqueous phase, and the physical strength of the gelatin microspheres can be controlled by simply changing the gelatin concentration. Furthermore, this approach enables the preparation of monodisperse microspheres with the ability to exhibit different thermosensitivities and encapsulate colloidal particles under mild conditions, which demonstrate sequential release of the desired encapsulants according to the responsive temperature.

BACKGROUND: Generation of monodisperse hydrogel microspheres is needed to make exquisite microenvironments, provide effective delivery system, and obtain reliable results. In this work, we present a simple microfluidic approach for the preparation of monodisperse pectin hydrogel microspheres because of efficient collection and shape of hydrogel.RESULTS: Based on the mechanism of in situ gelation and efficient collection, aqueous droplets of pectin polysaccharides are continuously generated in an immiscible continuous phase dissolving divalent metal ions, such as calcium. Under in situ gelation conditions, calcium ions are diffused into the interface between the continuous phase and the aqueous droplets, which triggers gelation of the pectin polysaccharides. The settling collection method, which involves dropping consecutive hydrogels from the outlet hole, is able to maintain the shape of the soft pectin hydrogels. Thus, pectin microspheres produced show high monodispersity (a coefficient of variation of 3.5%). In addition, the stiffness of the pectin hydrogels produced can be manipulated by a simple change of the concentration of pectin in the aqueous phase. The control of the mechanical properties can also be confirmed by measurement of the deformation of the pectin hydrogels using the micropipette aspiration method. Furthermore, the versatility of this approach enables the preparation of monodisperse pectin hydrogels with the capability to encapsulate or release nanoparticles on demand under mild conditions. The pectin microspheres are freely manipulated by the control of magnetic fields. CONCLUSION:We believe that the in situ microfluidic synthesis method combined with settling collection provides an efficient approach for the preparation of soft, monodisperse hydrogel microspheres.

Red blood cell membrane (RBCM) was coated onto the enzymatic glucose sensor. The permeability of RBCM was optimized by controlling the thickness. Intriguingly, the sensor was highly accurate, despite the existence of various interfering molecules.

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Vitamin D deficiency is prevalent in many developed countries, and several studies suggest that vitamin D plays an essential role in brain function. A recent study showed that vitamin D deficiency was closely associated with daytime sleepiness and shorter sleep time. The relationshipbetween vitamin D levels and calcium levels is well established, and calcium level regulates slow-wave sleep generation. It is conceivable that the sleep disturbance in vitamin D deficiency may be due to an altered calcium level. Nonetheless, calcium levels, sleep disturbances, and activity rhythms have not been investigated directly. Therefore, we hypothesized that calcium and vitamin D levels might be important in regulating sleep and activity rhythm, and we analyzed the correlation with calcium levels by actigraphy analysis. Interestingly, a negative correlation was found between calcium level and sleep latency, total sleep time, use of sleep medicine, and daytime dysfunction among shift workers. In contrast, non-shift workers showed a negative correlation between the calcium level and the circadian phase. These findings suggest that low serum calcium levels may disrupt sleep–wake control and rest–activity rhythm, even if they are within the normal range.

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The number of chronic renal disease patients has shown a significant increase in recent decades over the globe. Hemodialysis is the most commonly used treatment for renal replacement therapy (RRT) and dominates the global dialysis market. As one of the most water-consuming treatments in medical procedures, hemodialysis has room for improvement in reducing wastewater effluent. In this study, we investigated the technological feasibility of introducing the forward osmosis (FO) process for spent dialysate reuse. A 30 LMH of average water flux has been achieved using a commercial TFC membrane with high water permeability and salt removal. The water flux increased up to 23% with increasing flowrate from 100 mL/min to 500 mL/min. During 1 h spent dialysate treatment, the active layer facing feed solution (AL-FS) mode showed relatively higher flux stability with a 4–6 LMH of water flux reduction while the water flux decreased significantly at the active layer facing draw solution (AL-DS) mode with a 10–12 LMH reduction. In the pressure-assisted forward osmosis (PAFO) condition, high reverse salt flux was observed due to membrane deformation. During the membrane filtration process, scaling occurred due to the influence of polyvalent ions remaining on the membrane surface. Membrane fouling exacerbated the flux and was mainly caused by organic substances such as urea and creatinine. The results of this experiment provide an important basis for future research as a preliminary experiment for the introduction of the FO technique to hemodialysis.