A mobile health app for the collection of functional outcomes after inpatient stroke rehabilitation: Pilot randomized controlled trial

BACKGROUND: Monitoring the functional status of poststroke patients after they transition home is significant for rehabilitation. Mobile health (mHealth) technologies may provide an opportunity to reach and follow patients post discharge. However, the feasibility and validity of functional assessments administered by mHealth technologies are unknown. OBJECTIVE: This study aimed to evaluate the feasibility, validity, and reliability of functional assessments administered through the videoconference function of a mobile phone-based app compared with administration through the telephone function in poststroke patients after rehabilitation hospitalization. METHODS: A randomized controlled trial was conducted in a rehabilitation hospital in Southeast China. Participants were randomly assigned to either a videoconference follow-up (n=60) or a telephone follow-up (n=60) group. We measured the functional status of participants in each group at 2-week and 3-month follow-up periods. Half the participants in each group were followed by face-to-face home visit assessments as the gold standard. Validity was assessed by comparing any score differences between videoconference follow-up and home visit assessments, as well as telephone follow-up and home visit assessments. Reliability was assessed by computing agreements between videoconference follow-up and home visit assessments, as well as telephone follow-up and home visit assessments. Feasibility was evaluated by the levels of completion, satisfaction, comfort, and confidence in the 2 groups. RESULTS: Scores obtained from the videoconference follow-up were similar to those of the home visit assessment. However, most scores collected from telephone administration were higher than those of the home visit assessment. The agreement between videoconference follow-up and home visit assessments was higher than that between telephone follow-up and home visit assessments at all follow-up periods. In the telephone follow-up group, completion rates were 95% and 82% at 2-week and 3-month follow-up points, respectively. In the videoconference follow-up group, completion rates were 95% and 80% at 2-week and 3-month follow-up points, respectively. There were no differences in the completion rates between the 2 groups at all follow-up periods (X CONCLUSIONS: The videoconference follow-up assessment of functional status demonstrates higher validity and reliability, as well as higher confidence and satisfaction perceived by patients, than the telephone assessment. The videoconference assessment provides an efficient means of assessing functional outcomes of patients after hospital discharge. This method provides a novel solution for clinical trials requiring longitudinal assessments. TRIAL REGISTRATION: chictr.org.cn: ChiCTR1900027626; http://www.chictr.org.cn/edit.aspx?pid=44831&htm=4

Prognostic value of inflammatory nutritional scores in locally advanced esophageal squamous cell carcinoma patients undergoing neoadjuvant chemoimmunotherapy: a multicenter study in China

ObjectiveThis study investigates the prognostic significance of inflammatory nutritional scores in patients with locally advanced esophageal squamous cell carcinoma (LA-ESCC) undergoing neoadjuvant chemoimmunotherapy.MethodsA total of 190 LA-ESCC patients were recruited from three medical centers across China. Pre-treatment laboratory tests were utilized to calculate inflammatory nutritional scores. LASSO regression and multivariate logistic regression analyses were conducted to pinpoint predictors of pathological response. Kaplan-Meier and Cox regression analyses were employed to assess disease-free survival (DFS) prognostic factors.ResultsThe cohort comprised 154 males (81.05%) and 36 females (18.95%), with a median age of 61.4 years. Pathological complete response (pCR) was achieved in 17.38% of patients, while 44.78% attained major pathological response (MPR). LASSO and multivariate logistic regression analyses identified that hemoglobin, albumin, lymphocyte, and platelet (HALP) (P=0.02) as an independent predictors of MPR in LA-ESCC patients receiving neoadjuvant chemoimmunotherapy. Kaplan-Meier and log-rank tests indicated that patients with low HALP, MPR, ypT1-2, ypN0 and, ypTNM I stages had prolonged DFS (P < 0.05). Furthermore, univariate and multivariate Cox regression analyses underscored HALP (P = 0.019) and ypT (P = 0.029) as independent predictive factors for DFS in ESCC.ConclusionOur study suggests that LA-ESCC patients with lower pre-treatment HALP scores exhibit improved pathological response and reduced recurrence rate. As a comprehensive index of inflammatory nutritional status, pre-treatment HALP may be a reliable prognostic marker in ESCC patients undergoing neoadjuvant chemoimmunotherapy

A New Hydrogen Sensor Based on SNS Fiber Interferometer with Pd/WO3 Coating

This paper presents a new hydrogen sensor based on a single mode–no core–single mode (SNS) fiber interferometer structure. The surface of the no core fiber (NCF) was coated by Pd/WO3 film to detect the variation of hydrogen concentration. If the hydrogen concentration changes, the refractive index of the Pd/WO3 film as well as the boundary condition for light propagating in the NCF will all be changed, which will then cause a shift into the resonant wavelength of interferometer. Therefore, the hydrogen concentration can be deduced by measuring the shift of the resonant wavelength. Experimental results demonstrated that this proposed sensor had a high detection sensitivity of 1.26857 nm/%, with good linearity and high accuracy (maximum 0.0055% hydrogen volume error). Besides, it also possessed the advantages of simple structure, low cost, good stability, and repeatability

The complete chloroplast genome of Atractylodes koreana (Nakai) Kitam and its phylogenetic analysis

Atractylodes koreana (Nakai) Kitam is a perennial herb of Asteraceae, mainly distributed in China and Korea, which is the main adulterant of traditional herbal medicine ‘Cangzhu’. In the present study, we reported the complete chloroplast (cp) genome of A. koreana with the total length of 153,232 bp, which is consisted of four regions, including one large single copy (LSC) region of 84,250 bp, one small single copy (SSC) region of 18,690 bp, and two inverted repeat regions (IRa and IRb) of 25,146 bp. The GC content of the complete cp genome is 37.7%. A total of 110 unique genes were annotated, comprising 79 protein-coding genes, 27 transfer RNA (tRNA) genes and four ribosome RNA (rRNA) genes. Moreover, nine protein-coding genes contained one intron and three protein-coding genes (clpP, ycf3, and rps12) contained two introns. The phylogenetic analysis indicated that A. koreana is a sister group of A. chinensis and A. lancea

Detection and Identification of External Intrusion Signals from 33 km Optical Fiber Sensing System Based on Deep Learning

In real-world environments, it is usually hard to achieve accurate identification and classification of external vibration signals collected by optical fiber. In this paper, we have applied deep neural networks to a 33 km optical fiber sensing system to recognize and classify the signals of the external intrusion (third-party intrusion) events. It enables the fast identification and localization of the destructive events in complex environments with large amount of monitoring data. Pipeline intrusion events intelligent identification system in this paper is mainly divided into two parts: a distributed acoustic sensing (DAS) System and a pattern recognition system (PRS). DAS was utilized to monitor external intrusion signals in the real-world environment. A Deep learning model, which is called Convolutional, Long Short-Term Memory, Fully Connected Deep Neural Networks (CLDNN), is first applied in PRS to directly input the time series of data into the network for deep learning without any preprocessing, which is simpler and better than the ways used in the previous work. After training and testing with real data, the average recognition rate of the constructed model for intrusion events can reach over 97%. Finally, 33 km blind tests were carried out to verify that the model has good recognition, classification and localization applications for external intrusion signals in the real-world environment

Evolutionary Multiobjective Optimization with Endmember Priori Strategy for Large-Scale Hyperspectral Sparse Unmixing

Mixed pixels inevitably appear in the hyperspectral image due to the low resolution of the sensor and the mixing of ground objects. Sparse unmixing, as an emerging method to solve the problem of mixed pixels, has received extensive attention in recent years due to its robustness and high efficiency. In theory, sparse unmixing is essentially a multiobjective optimization problem. The sparse endmember term and the reconstruction error term can be regarded as two objectives to optimize simultaneously, and a series of nondominated solutions can be obtained as the final solution. However, the large-scale spectral library poses a challenge due to the high-dimensional number of spectra, it is difficult to accurately extract a few active endmembers and estimate their corresponding abundance from hundreds of spectral features. In order to solve this problem, we propose an evolutionary multiobjective hyperspectral sparse unmixing algorithm with endmember priori strategy (EMSU-EP) to solve the large-scale sparse unmixing problem. The single endmember in the spectral library is used to reconstruct the hyperspectral image, respectively, and the corresponding score of each endmember can be obtained. Then the endmember scores are used as a prior knowledge to guide the generation of the initial population and the new offspring. Finally, a series of nondominated solutions are obtained by the nondominated sorting and the crowding distances calculation. Experiments on two benchmark large-scale simulated data to demonstrate the effectiveness of the proposed algorithm