Risk factors for agitation in home-cared older adults with dementia: evidence from 640 elders in East China

BackgroundAgitation is common among older adults with dementia, negatively affecting their quality of life and their caregivers’. Since home care remains the dominant approach for older adults, this study investigates the risk factors for agitation in older adults with dementia in China.MethodsWe perform a cross-sectional study of home-cared older adults with dementia in Ningbo, China, using 2020 data. We use a self-made questionnaire to investigate the risks of agitated behavior and its related factors. We perform descriptive, univariate, and regression analyses.FindingsWe address 640 older Chinese adults; 42.8% of the sample exhibits one or more agitated behaviors. We find that basic health issues, such as activities of daily living (ADL), family support issues, such as Zarit Burden Interview (ZBI) scale and Family APGAR Questionnaire (APGAR), and behavioral awareness issues, such as fall and scald, significantly influence the occurrence of agitation behaviors (p < 0.05). Older adults with severe ADL disorder (b = 6.835, β = 0.196, p < 0.001), ZBI score of 67.00–88.0 (b = 10.212, β = 0.248, p = 0.005), severe APGAR disorder (b = 3.699, β = 0.100, p = 0.012) and a history of fall (b = 9.311, β = 0.199, P = <0.001) or scald (b = 9.288, β = 0.125, p = 0.002) are more likely to exhibit agitated behaviors.InterpretationAgitated behavior in home-cared older adults with dementia are diverse and related to mental state, family support, and behavioral awareness issues. Caregivers, often family members, should be attentive to the needs of dementia patients and take active and effective measures to improve their quality of life. They should be aware of the causes and triggers of agitated behavior and take steps to reduce its occurrence

Psychometric properties of the Chinese version of the preoperative assessment of readiness tool among surgical patients

BackgroundThe evaluation of the surgical readiness of patients plays an important role in clinical care. Preoperative readiness assessment is needed to identify the inadequacy among surgical patients, which provides guide for interventions to improve patients’ preoperative readiness. However, there is a paucity of high-level, quality tool that evaluate surgical readiness of patients in China. The purpose of this study is to translate the Preoperative Assessment of Readiness Tool (PART) into Chinese and determine the reliability and validity of the Chinese version in the population of surgical patients.MethodsUsing a standard translation-backward method, the original English version of PART was translated into Chinese. A convenient sampling of 210 surgical patients was recruited from 6 hospitals in Zhejiang Province to test the psychometric properties of this scale including internal consistency, split-half reliability, content validity, structure validity, and floor/ceiling effect.ResultsA total of 194 patients (92%) completed questionnaires. The Chinese version of PART achieved Cronbach’s alphas 0.948 and McDonald’s omega coefficient 0.947, respectively, for the full scale. The estimated odd-even split-half reliability was 0.959. The scale-level content validity index was 0.867, and the items content validity index ranged from 0.83 to 1.0.The output of confirmatory factor analysis (CFA) revealed a two-factor model (χ2 = 510.96; df = 86; p < 0.001; root mean square error approximation = 0.08) with no floor/ceiling effect.ConclusionThe Chinese version of PART demonstrated acceptable reliability and validity among surgical patients. It can be used to evaluate patients’ preoperative preparation and help health professionals provide proper preoperative support

Intrachromosomal Looping Is Required for Activation of Endogenous Pluripotency Genes during Reprogramming

SummaryGeneration of induced pluripotent stem cells (iPSCs) by defined factors is an extremely inefficient process, because there is a strong epigenetic block preventing cells from achieving pluripotency. Here we report that virally expressed factors bound to the promoters of their target genes to the same extent in both iPSCs and unreprogrammed cells (URCs). However, expression of endogenous pluripotentcy genes was observed only in iPSCs. Comparison of local chromatin structure of the OCT4 locus revealed that there was a cohesin-complex-mediated intrachromosomal loop that juxtaposes a downstream enhancer to the gene’s promoter, enabling activation of endogenous stemness genes. None of these long-range interactions were observed in URCs. Knockdown of the cohesin-complex gene SMC1 by RNAi abolished the intrachromosomal interaction and affected pluripotency. These findings highlight the importance of the SMC1-orchestrated intrachromosomal loop as a critical epigenetic barrier to the induction of pluripotency

Highly frequent PIK3CA amplification is associated with poor prognosis in gastric cancer

<p>Abstract</p> <p>Background</p> <p>The phosphoinositide 3-kinase (PI3K)/Akt pathway plays a fundamental role in cell proliferation and survival in human tumorigenesis, including gastric cancer. <it>PIK3CA </it>mutations and amplification are two major causes of overactivation of this pathway in human cancers. However, until this work, there was no sound investigation on the association of <it>PIK3CA </it>mutations and amplification with clinical outcome in gastric cancer, particularly the latter.</p> <p>Methods</p> <p>Using direct sequencing and real-time quantitative PCR, we examined <it>PIK3CA </it>mutations and amplification, and their association with clinicopathological characteristics and clinical outcome of gastric cancer patients.</p> <p>Results</p> <p><it>PIK3CA </it>mutations and amplification were found in 8/113 (7.1%) and 88/131 (67%) gastric cancer patients, respectively. <it>PIK3CA </it>amplification was closely associated with increased phosphorylated Akt (p-Akt) level. No relationship was found between <it>PIK3CA </it>mutations and clinicopathological characteristics and clinical outcome in gastric cancer. <it>PIK3CA </it>amplification was significantly positively associated with cancer-related death. Importantly, Kaplan-Meier survival curves revealed that the patients with <it>PIK3CA </it>amplification had significantly shorter survival times than the patients without <it>PIK3CA </it>amplification.</p> <p>Conclusions</p> <p>Our data showed that <it>PIK3CA </it>mutations were not common, but its amplification was very common in gastric cancer and may be a major mechanism in activating the PI3K/Akt pathway in gastric cancer. Importantly, Kaplan-Meier survival curves revealed that <it>PIK3CA </it>amplification was significantly positively associated with poor survival of gastric cancer patients. Collectively, the PI3K/Akt signaling pathway may be an effective therapeutic target in gastric cancer.</p

A Context-Aware Neural Embedding for Function-Level Vulnerability Detection

Exploitable vulnerabilities in software systems are major security concerns. To date, machine learning (ML) based solutions have been proposed to automate and accelerate the detection of vulnerabilities. Most ML techniques aim to isolate a unit of source code, be it a line or a function, as being vulnerable. We argue that a code segment is vulnerable if it exists in certain semantic contexts, such as the control flow and data flow; therefore, it is important for the detection to be context aware. In this paper, we evaluate the performance of mainstream word embedding techniques in the scenario of software vulnerability detection. Based on the evaluation, we propose a supervised framework leveraging pre-trained context-aware embeddings from language models (ELMo) to capture deep contextual representations, further summarized by a bidirectional long short-term memory (Bi-LSTM) layer for learning long-range code dependency. The framework takes directly a source code function as an input and produces corresponding function embeddings, which can be treated as feature sets for conventional ML classifiers. Experimental results showed that the proposed framework yielded the best performance in its downstream detection tasks. Using the feature representations generated by our framework, random forest and support vector machine outperformed four baseline systems on our data sets, demonstrating that the framework incorporated with ELMo can effectively capture the vulnerable data flow patterns and facilitate the vulnerability detection task

Scintillation Index for Spherical Wave Propagation in Anisotropic Weak Oceanic Turbulence with Aperture Averaging under the Effect of Inner Scale and Outer Scale

Due to the advantages of high transmission rate, lower power consumption, high security, etc., underwater wireless optical communication (UWOC) has been widely studied and considered as a potential technique for underwater communication. However, its performance is severely degraded by oceanic turbulence due to refractive index fluctuations, which is caused by the change of inhomogeneous ocean environment. Within our derived spatial power spectrum model under anisotropic oceanic turbulence, we conducted a detailed investigation for a spherical wave propagating in weak anisotropic turbulence in this paper. Based on the derived oceanic spectrum, we proposed a scintillation index model for spherical wave in anisotropic oceanic turbulence considering the aperture averaging effect at non-zero inner scale and limited outer scale. Besides, we analyze the aperture averaging scintillation index under the influence of channel parameters such as inner and outer scales. Simulation results reveal that the scintillation index increases with the increase of the outer scale, while the inner scale induces an opposite trend on the scintillation index. Moreover, the inner scale exhibits a larger impact than the outer scale on the UWOC system over weak oceanic turbulence

Scintillation Index for Spherical Wave Propagation in Anisotropic Weak Oceanic Turbulence with Aperture Averaging under the Effect of Inner Scale and Outer Scale

Due to the advantages of high transmission rate, lower power consumption, high security, etc., underwater wireless optical communication (UWOC) has been widely studied and considered as a potential technique for underwater communication. However, its performance is severely degraded by oceanic turbulence due to refractive index fluctuations, which is caused by the change of inhomogeneous ocean environment. Within our derived spatial power spectrum model under anisotropic oceanic turbulence, we conducted a detailed investigation for a spherical wave propagating in weak anisotropic turbulence in this paper. Based on the derived oceanic spectrum, we proposed a scintillation index model for spherical wave in anisotropic oceanic turbulence considering the aperture averaging effect at non-zero inner scale and limited outer scale. Besides, we analyze the aperture averaging scintillation index under the influence of channel parameters such as inner and outer scales. Simulation results reveal that the scintillation index increases with the increase of the outer scale, while the inner scale induces an opposite trend on the scintillation index. Moreover, the inner scale exhibits a larger impact than the outer scale on the UWOC system over weak oceanic turbulence

Infrared and Visible Image Fusion Method Based on a Principal Component Analysis Network and Image Pyramid

The aim of infrared (IR) and visible image fusion is to generate a more informative image for human observation or some other computer vision tasks. The activity-level measurement and weight assignment are two key parts in image fusion. In this paper, we propose a novel IR and visible fusion method based on the principal component analysis network (PCANet) and an image pyramid. Firstly, we use the lightweight deep learning network, a PCANet, to obtain the activity-level measurement and weight assignment of IR and visible images. The activity-level measurement obtained by the PCANet has a stronger representation ability for focusing on IR target perception and visible detail description. Secondly, the weights and the source images are decomposed into multiple scales by the image pyramid, and the weighted-average fusion rule is applied at each scale. Finally, the fused image is obtained by reconstruction. The effectiveness of the proposed algorithm was verified by two datasets with more than eighty pairs of test images in total. Compared with nineteen representative methods, the experimental results demonstrate that the proposed method can achieve the state-of-the-art results in both visual quality and objective evaluation metrics

A Content Distribution System based on Sparse Linear Network Coding

Abstract — With network coding, intermediate nodes between source and destination node(s) encode the incoming packets into new ones and forward them to their outgoing links. The original content is decoded at the destination node(s). Recent theoretical results show that network coding is beneficial for peer-to-peer(P2P) content distribution. To evaluate the benefit of network coding, we implement a P2P content distribution system based on the sparse linear network coding method. In our system, we use the Chord protocol to construct the system topology. We determine the proper encoding density so as to reach a high probability of generating independent encoded blocks, and to reduce the computational complexity of encoding packets at each peer. To improve the system performance, we use the encoding interval to reduce the probability of transmitting linear dependent packets and dependency test to avoid accepting linear dependent packets possibly from cyclic topology. Lastly, we carry out extensive experiments to show in terms of average downloading time at peers, total distribution time and system throughput, the system with network coding slightly outperforms a BitTorrent-like non-coding system using the local-rarest-first chunk selection policy. I