The Role of Probiotics in Managing Glucose Homeostasis in Adults with Prediabetes: A Systematic Review and Meta-Analysis.

Methods: The Preferred Reporting Items for Systematic Reviews and Analysis checklist was used. A comprehensive literature search of the PubMed, Embase, and Cochrane Library databases was conducted through August 2022 to assess the impact of probiotics on blood glucose, lipid, and inflammatory markers in adults with prediabetes. Data were pooled using a random effects model and were expressed as standardized mean differences (SMDs) and 95% confidence interval (CI). Heterogeneity was evaluated and quantified as I2. Results: Seven publications with a total of 550 patients were included in the meta-analysis. Probiotics were found to significantly reduce the levels of glycosylated hemoglobin (HbA1c) (SMD -0.44; 95% CI -0.84, -0.05; p = 0.03; I2 = 76.13%, p < 0.001) and homeostatic model assessment of insulin resistance (HOMA-IR) (SMD -0.27; 95% CI -0.45, -0.09; p < 0.001; I2 = 0.50%, p = 0.36) and improve the levels of high-density lipoprotein cholesterol (HDL) (SMD -8.94; 95% CI -14.91, -2.97; p = 0.003; I2 = 80.24%, p < 0.001), when compared to the placebo group. However, no significant difference was observed in fasting blood glucose, insulin, total cholesterol, triglycerides, low-density lipoprotein cholesterol, interleukin-6, tumor necrosis factor-α, and body mass index. Subgroup analyses showed that probiotics significantly reduced HbA1c in adults with prediabetes in Oceania, intervention duration of ≥3 months, and sample size <30. Conclusions: Collectively, our meta-analysis revealed that probiotics had a significant impact on reducing the levels of HbA1c and HOMA-IR and improving the level of HDL in adults with prediabetes, which indicated a potential role in regulating blood glucose homeostasis. However, given the limited number of studies included in this analysis and the potential for bias, further large-scale, higher-quality randomized controlled trials are needed to confirm these findings. This trial is registered with CRD42022358379.

A Genetic Algorithm-Based Ensemble Learning Framework for Drug Combination Prediction.

Combination therapy is a promising clinical treatment strategy for cancer and other complex diseases. Multiple drugs can target multiple proteins and pathways, greatly improving the therapeutic effect and slowing down drug resistance. To narrow the search space of synergistic drug combinations, many prediction models have been developed. However, drug combination datasets always have the characteristics of class imbalance. Synergistic drug combinations receive the most attention in clinical application but are in small numbers. To predict synergistic drug combinations in different cancer cell lines, in this study, we propose a genetic algorithm-based ensemble learning framework, GA-DRUG, to address the problems of class imbalance and high dimensionality of input data. The cell-line-specific gene expression profiles under drug perturbations are used to train GA-DRUG, which contains imbalanced data processing and the search of global optimal solutions. Compared to 11 state-of-the-art algorithms, GA-DRUG achieves the best performance and significantly improves the prediction performance in the minority class (Synergy). The ensemble framework can effectively correct the classification results of a single classifier. In addition, the cellular proliferation experiment performed on several previously unexplored drug combinations further confirms the predictive ability of GA-DRUG.

Thin-film lithium niobate polarization modulator without polarization diversity.

With the development of photonic integrated circuits and optical information processing on thin-film lithium niobate (TFLN), the realization of the TFLN-based polarization device is becoming more and more crucial. Here, we demonstrate a polarization modulator on the TFLN platform without polarization diversity. Without polarization manipulation elements, the device only composes a phase modulator and a two-dimensional grating coupler. The structure features small footprint and high fabrication tolerance. The device holds promise for polarization encoding telecommunication.

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning.

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.

Active mode selection by defects in lithium niobate on insulator microdisks.

Whispering gallery mode (WGM) optical microcavities are important building blocks in photonic integrated circuits. Operation of such cavities on specific lower- or higher- order transverse modes has much interest in application perspectives. Here, we demonstrate active mode selection by introducing defects in lithium niobate on insulator microdisks. A focused ion beam is applied to precisely inscribe nano slits into the perimeter of the microdisk. The transmission spectra can be significantly thinned out without severe quality factor degradation. Either fundamental or high-order transverse WGMs can be retained by properly designing the size and location of the defects. The approach may have promising applications in single-mode lasing and nonlinear optics.

Effective four-wave mixing in the lithium niobate on insulator microdisk by cascading quadratic processes.

Whispering-gallery-mode resonators can dramatically enhance the light-matter interaction, benefitting nonlinear optics in many ways. Here, we demonstrate effective four-wave mixing (FWM) in a lithium niobate on insulator (LNOI) microdisk via cascaded quadratic nonlinear processes of second-harmonic generation and difference-frequency generation (i.e., cSHG/DFG) in the telecommunication band. The effective FWM process can be used as an optical parametric amplifier and can mimic an effectively strong Kerr nonlinearity. This shows the great promise of an integrated LNOI platform for nonlinear frequency conversion.

Enhancement of surface plasmon polariton excitation via feedback-based wavefront shaping.

Surface plasmon polariton (SPP) is an electromagnetic excitation with efficient spatial confinement and high local field intensity at a metal/dielectric interface, which has been widely applied in many fields such as nanophotonics, imaging, biosensing, nonlinear optics, and so on. However, the destructive interference, which arises from wavevector mismatching between the spatial components of incident light and SPP, limits the effective excitation of SPP. Here, we experimentally demonstrate the enhancement of SPP excitation via a feedback-based wavefront shaping method in the Kreschmann configuration. After optimizing the phase profile of the incident laser beam, the intensity is enhanced by a factor of 1.58 times even at the resonance angle of the fundamental mode Gaussian beam. Besides, the influences of different conditions for the enhancement of SPP excitation are also analyzed. This work provides a flexible and convenient method to further enhance the SPP excitation, and it may have the application of further enhancement of the interaction between SPP and other physical processes.

A possible pathogenetic factor of sickle-cell disease based on fluorescent analysis via an optofluidic resonator.

Waveguide based optofluidic resonator features high precision and high sensitivity in real-time fluorescent analysis. We present a novel optofluidic resonator following the hollow-core metal-cladding waveguide structure, which is then used to record the real-time binding process of Fe2+ and Fe3+ with protoporphyrin IX (PpIX) in PBS solution, respectively. The central fluorescent wavelength of compound with Fe2+ is in good accordance with that of the normal hemoglobin, whilst the peaks of the Fe3+ compound match the hemoglobin specimen from sickle-cell disease (SCD) patients. Similar statement holds when we monitor the real-time oxidation processes of these products by injecting oxygen into the optofluidic chip. These observations lead to the speculation that the SCD is caused by replacing the Fe2+ in hemoglobin with Fe3+, which may be insightful in the discovery of new clinical routes to cure this disease.

A clinical trial of acupuncture about time-varying treatment and points selection in primary dysmenorrhea.

OBJECTIVE: To observe the clinical therapeutic effects of acupuncture at single point Shiqizhui (EX-B8) and multi-points in time-varying treatment for primary dysmenorrhea. METHODS: 600 patients with primary dysmenorrhea were randomly assigned to the single point group (n=200) including group A (treating before the menstruation, n=100) and group B (immediately treating as soon as pain occurrence, n=100), the multi-points group (n=200) including group C (treating before the menstruation, n=100) and group D (immediately treating as soon as pain occurrence, n=100), or the control group, group E (n=200, no treatment). The therapeutic effects were analyzed after treatment for three menstrual cycles and interviewed for three follow-up periods. RESULTS: Acupuncture could effectively relieve menstrual pain for primary dysmenorrhea compared with the control group (P<0.05, P<0.01). Immediate pain relief occurred following acupuncture within 5 min in group B (P<0.01) and group D (P<0.01), and the two groups obviously relieved menstrual pain for VAS scores. Both group A and group C obviously relieved menstrual pain (P<0.01), and group C was better than group A (P<0.05). Compared with group D, Group C was much better for CMSS scores in cycle 1. CONCLUSION: Treating before the menstruation is better than immediately treating as soon as pain occurrence at the improvement in symptoms of dysmenorrheal at multi-points. And single point is better than multi-points when immediately treating as soon as pain occurrence. The present trial suggest Shiqizhui (EX-B8) should be chosen as a convenient point.