Boron and nitrogen co-doped carbon dots as the dual functional fluorescent probe for Fe3+ and pH detection

Carbon dots doped with boron and nitrogen atoms (B, N-CDs) were designed and prepared by hydrothermal strategy using citric acid, urea and borax as raw materials. The structure and optical properties of B, N-CDs were characterized by various characterization technologies. The results showed that the B, N-CDs exhibited good mono-dispersion, excellent fluorescence stability, and high fluorescence intensity (quantum yield up to 32 %). A dual-functional Fe3+ and pH detection platform based on B, N-CDs was constructed. The Fe3+ sensing method based on B, N-CDs fluorescence quenching showed an excellent linear relationship between 0.044–70 μM (R2 = 0.994), with a detection limit as low as 0.044 μM. Then, this detection method was successfully applied to the high-accuracy detection of Fe3+ in water samples and iron supplement tablets. The study of the quenching mechanism showed that the fluorescence of B, N-CDs was quenched by Fe3+ in two ways: static quenching and dynamic quenching. Moreover, B, N-CDs can also be used as a pH fluorescence sensor in the ranges of pH 2.0–4.8 and 5.2–7.6. The developed sensing system based on B, N-CDs has high selectivity and sensitivity for the detection of Fe3+, and a wide detection range for pH

Computer Vision and Machine Learning-Based Gait Pattern Recognition for Flat Fall Prediction

Background: Gait recognition has been applied in the prediction of the probability of elderly flat ground fall, functional evaluation during rehabilitation, and the training of patients with lower extremity motor dysfunction. Gait distinguishing between seemingly similar kinematic patterns associated with different pathological entities is a challenge for the clinician. How to realize automatic identification and judgment of abnormal gait is a significant challenge in clinical practice. The long-term goal of our study is to develop a gait recognition computer vision system using artificial intelligence (AI) and machine learning (ML) computing. This study aims to find an optimal ML algorithm using computer vision techniques and measure variables from lower limbs to classify gait patterns in healthy people. The purpose of this study is to determine the feasibility of computer vision and machine learning (ML) computing in discriminating different gait patterns associated with flat-ground falls. Methods: We used the Kinect® Motion system to capture the spatiotemporal gait data from seven healthy subjects in three walking trials, including normal gait, pelvic-obliquity-gait, and knee-hyperextension-gait walking. Four different classification methods including convolutional neural network (CNN), support vector machine (SVM), K-nearest neighbors (KNN), and long short-term memory (LSTM) neural networks were used to automatically classify three gait patterns. Overall, 750 sets of data were collected, and the dataset was divided into 80% for algorithm training and 20% for evaluation. Results: The SVM and KNN had a higher accuracy than CNN and LSTM. The SVM (94.9 ± 3.36%) had the highest accuracy in the classification of gait patterns, followed by KNN (94.0 ± 4.22%). The accuracy of CNN was 87.6 ± 7.50% and that of LSTM 83.6 ± 5.35%. Conclusions: This study revealed that the proposed AI machine learning (ML) techniques can be used to design gait biometric systems and machine vision for gait pattern recognition. Potentially, this method can be used to remotely evaluate elderly patients and help clinicians make decisions regarding disposition, follow-up, and treatment

Multiplex Plasmonic Sensor for Detection of Different Metal Ions Based on a Single Type of Gold Nanorod

In this paper, a label-free multiplex plasmonic sensor has been developed to selectively determine different metal ions including Fe³⁺, Hg²⁺, Cu²⁺, and Ag⁺ ions based on a single type of gold nanorod (GNR). Under proper conditions, these metal ions can react with GNRs, resulting in changes of nanostructure and composition. The determination of Fe³⁺, Hg²⁺, Cu²⁺, and Ag⁺ ions is therefore readily implemented due to changes of longitudinal plasmon wavelength (LPW) of nanorods. Moreover, the GNR-based assay can not only determine all four kinds of metal ions successively but also can detect which of any one or several kinds of metal ions. This assay is sensitive to detect Fe³⁺, Hg²⁺, Cu²⁺, and Ag⁺ as low as 10^–6, 10^–8, 10^–10, and 10^–8 M, respectively. Importantly, the special nanostructure and composition of the nanorods are induced by these metal ions, which allow this sensor to maintain high selectivity to determine these metal ions. This nanosensor abrogates the need for complicated chemosensors or sophisticated equipment, providing a simple and highly selective detection platform

Effect of subchronic cigarette smoke exposure and HFD on IGF-1 mRNA expression in skeletal muscles.

<p>Male BALB/c mice were exposed to 4 cigarettes/day, 6 days/week for 7 weeks and the mRNA expression of IGF-I in the soleus (A), tibialis anterior (B) and gastrocnemius (C) skeletal muscles was measured. Mice had access to either standard laboratory chow (□) or a HFD (▪) across the 7 week experimental period. Data are shown as mean±SE and each sample was performed in duplicate (n = 8 per treatment group). Gene expression was normalized to 18S rRNA and expressed as a fold change relative to the Sham and Chow group. Data were analysed by two-way ANOVA and when statistical significance was achieved a <i>post hoc</i> Bonferroni test was performed. * P<0.05 significant <i>post hoc</i> effect of smoke exposure compared to sham animals on the same diet. † P<0.05 significant <i>post hoc</i> effect of HFD compared to chow fed animals.</p

The effect of subchronic cigarette smoke exposure and a HFD on BALF protein levels of cytokines and chemokines.

<p>MCP-1 protein concentration in BALF was below the detection sensitivity of the ELISA.</p><p>Results are expressed as mean±SE; n = 8 per group. Data were analysed by two-way ANOVA and where appropriate a <i>post hoc</i> Bonferroni test was used.</p>*<p>P<0.05 significant <i>post hoc</i> effect of smoke exposure compared to sham animals on the same diet.</p

The effect of subchronic cigarette smoke exposure and a HFD on body weight, skeletal muscle weights and circulating IGF-I and SAA protein levels.

<p>Results are expressed as mean±SE; n = 8 per group. Data were analysed by two-way ANOVA and where appropriate a <i>post hoc</i> Bonferroni test was used.</p>*<p>P<0.05 significant <i>post hoc</i> effect of smoke exposure compared to sham animals on the same diet.</p>†<p>P<0.05, significant <i>post hoc</i> effect of the HFD compared to chow fed animals.</p

Effect of subchronic cigarette smoke exposure and HFD on BALF cellularity.

<p>Male BALB/c mice were exposed to 4 cigarettes/day, 6 days/week for 7 weeks and the number of total cells (A), macrophages (B), neutrophils (C) and lymphocytes (D) were counted. Mice had access to either standard laboratory chow (□) or a HFD (▪) across the 7 week experimental period. Data are shown as mean±SE for n = 8 per treatment group. Data were analysed by two-way ANOVA and when significance was achieved a <i>post hoc</i> Bonferroni test was performed. * P<0.05 significant <i>post hoc</i> effect of smoke exposure compared to sham animals on the same diet.</p

The effect of subchronic cigarette smoke exposure and HFD on IGF-I protein level in the gastrocnemius skeletal muscle.

<p>Male BALB/c mice were exposed to 4 cigarettes/day, 6 days/week for 7 weeks and the protein level of IGF-I in the gastrocnemius skeletal muscle was determined. Mice had access to either standard laboratory chow (□) or a HFD (▪) across the 7 week experimental period. Data are shown as mean±SE and each sample was performed in duplicate (n = 8 per treatment group). Data were analysed by two-way ANOVA and when statistical significance was achieved a <i>post hoc</i> Bonferroni test was performed. * P<0.05 significant <i>post hoc</i> effect of smoke exposure compared to sham animals on the same diet.</p

The effect of subchronic cigarette smoke exposure and a HFD on lung tissue mRNA expression of cytokines and chemokines.

<p>Results are expressed as mean±SE; n = 8 per group. Data were analysed by two-way ANOVA and where appropriate a <i>post hoc</i> Bonferroni test was used.</p>*<p>P<0.05 significant <i>post hoc</i> effect of smoke exposure compared to sham animals on the same diet.</p

The effect of subchronic cigarette smoke exposure and HFD on the mRNA expression of atrogenes in skeletal muscles.

<p>Male BALB/c mice were exposed to 4 cigarettes/day, 6 days/week for 7 weeks and the mRNA expression of atrogin-1 (A-C) and MuRF1 (D-E) in the soleus, tibialis anterior, and gastrocnemius skeletal muscles was determined. Mice had access to either standard laboratory chow (□) or a HFD (▪) across the 7 week experimental period. Data are shown as mean±SE and each sample was performed in duplicate (n = 8 per treatment group). Gene expression was normalized to 18S rRNA and expressed as a fold change relative to the Sham and Chow group. Data were analysed by two-way ANOVA and when statistical significance was achieved a <i>post hoc</i> Bonferroni test was performed. * P<0.05 significant <i>post hoc</i> effect of smoke exposure compared to sham animals on the same diet. † P<0.05 significant <i>post hoc</i> effect of HFD compared to chow fed animals.</p