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ObjectivesTo systematically review the effects of dezocine (DZC) on the occurrence rate and severity of opioid-induced cough (OIC).DesignSystematic review and meta-analysisData sourcesPubMed, Embase, Cochrane Library, Ovid, Web of Science as well as Chinese BioMedical Literature & Retrieval System, China National Knowledge Infrastructure, Wanfang and VIP Data were searched from 1978 to 31 December 2020.Inclusion criteriaAll randomised controlled trials (RCTs) comparing DZC with placebo on the occurrence rate and severity of OIC.Data analysisAll data were analysed by using RevMan V.5.3. Each outcome was tested for heterogeneity, and randomised-effects or fixed-effects model was used in the presence or absence of significant heterogeneity.ResultsOur search yielded 33 RCTs including 4442 patients, and 2521 patients were allocated into the DZC group and 1921 into the control group. Fentanyl was administrated in 1880 patients and sufentanil in 2562 patients during the induction of general anaesthesia. The meta-analysis demonstrated that DZC significantly reduced the occurrence rate of OIC induced by either fentanyl (8.8% vs 49.7%, OR=0.07, 95% CI 0.04 to 0.12, p<0.00001) or sufentanil (5.0% vs 41.5%, OR=0.07, 95% CI 0.04 to 0.12, p<0.00001). The meta-analysis also indicated that the occurrence rate of mild, moderate and severe OIC in the DZC group was remarkably lower than that of the control group (mild: 3.6% vs 13.6%, OR=0.19, 95% CI 0.14 to 0.25, p<0.00001; moderate: 2.0% vs 13.6%, OR=0.12, 95% CI 0.09 to 0.18, p<0.00001; severe: 1.0% vs 13.9%, OR=0.08, 95% CI 0.05 to 0.12, p<0.00001). Additionally, the current meta-analysis indicated that DZC pretreatment was not associated with increased occurrence rate of adverse effects (7.0% vs 4.2%, OR=2.34, 95% CI 0.60 to 9.14, p=0.22) except for dizziness (11.8% vs 0%, OR=8.06, 95% CI 1.40 to 46.35, p=0.02).ConclusionThis meta-analysis demonstrated that DZC significantly inhibited OIC and may be used to manage OIC. More high-quality RCTs are needed to complement the safety of DZC.PROSPERO registration numberCRD42019141255.

IntroductionCough is often observed when administrating a bolus of opioids. Opioid-induced cough (OIC) is mostly transient, benign and self-limiting, but could be associated with adverse effects. Numerous pharmacological and non-pharmacological interventions have been used to manage OIC with controversial efficacy and safety. Recent studies suggested that, pretreatment of intravenous dezocine (DZC) could completely suppress OIC during anaesthesia induction. To address this knowledge lack, we will perform a systemic review and meta-analysis to evaluate the efficacy of DZC on OIC and possible complications. We provide here a protocol that will outline the methods and analyses planned for the systematic review.MethodsPubMed, Embase, Cochrane Library, Web of Science as well as Chinese BioMedical Literature & Retrieval System (SinoMed), China National Knowledge Infrastructure, Wanfang Data and VIP Data will be searched from 1978 to 31 December 2019 to identify all randomised controlled trials comparing DZC with placebo on the incidence and severity of OIC. Primary outcomes of interest include the incidence and severity of OIC. Secondary outcomes of interest include possible complications or adverse effects of DZC. Two authors will independently extract relevant variables and outcome data. For continuous variables, treatment effects will be calculated as weighted mean difference and 95% CI. For dichotomous data, treatment effects will be calculated as OR and 95% CI. Each outcome will be tested for heterogeneity, and randomised-effects or fixed-effects model will be used in the presence or absence of significant heterogeneity. Sensitivity analyses will be done by examining the influence of statistical model and individual trial(s) on estimated treatment effects. Publication bias will be explored through visual inspection of funnel plots of the outcomes. Statistical significance will be defined as p<0.05.Ethics and disseminationThis study is a protocol of meta-analysis of previously published literatures, ethical approval was not necessary according to the Ethical Committee of Fuwai Hospital. The study will be submitted to a peer-reviewed journal and disseminated via research presentations.PROSPERO registration numberCRD42019141255.

Incremental Task learning (ITL) is a category of continual learning that seeks to train a single network for multiple tasks (one after another), where training data for each task is only available during the training of that task. Neural networks tend to forget older tasks when they are trained for the newer tasks; this property is often known as catastrophic forgetting. To address this issue, ITL methods use episodic memory, parameter regularization, masking and pruning, or extensible network structures. In this paper, we propose a new incremental task learning framework based on low-rank factorization. In particular, we represent the network weights for each layer as a linear combination of several rank-1 matrices. To update the network for a new task, we learn a rank-1 (or low-rank) matrix and add that to the weights of every layer. We also introduce an additional selector vector that assigns different weights to the low-rank matrices learned for the previous tasks. We show that our approach performs better than the current state-of-the-art methods in terms of accuracy and forgetting. Our method also offers better memory efficiency compared to episodic memory- and mask-based approaches. Our code will be available at https://github.com/CSIPlab/task-increment-rank-update.git

Deception detection has attracted broad interest in professional practice and academic research, and body movement is considered one of the key aspects in deception detection. Previous work has focused on certain body parts (i.e., hand, head, leg) or gestures (i.e., gaze aversion, leg unnatural movement, etc.), which were manually coded by human judges. However, manual coding of nonverbal behavior is time-consuming and painstaking to the coders, as well as possibly vulnerable to observation biases. To overcome the challenges associated with manual coding, we employed a motion capture system to collect the body movements, in which a total of 80 participants were engaged in two interviews about their holiday experiences. In interviews about their vacation experiences, participants either told the whole truth or lied completely. The results revealed distinct movement patterns across conditions. Lower body movement differentiated honest from deceptive responses, and this association was moderated by task order, whereas upper body movement showed no reliable effects once task order was taken into account. Notably, the pattern does not support a generalized “rigidity effect” (i.e., uniformly reduced movement during deception); instead, the observed movement differences were order-dependent. Exploratory analyses using machine learning approaches further delineated the temporal dynamics of deceptive movement, providing complementary insights into nonverbal markers of deception.

Estimates of potential harmful effects on ecosystems in the Canadian provinces of Alberta and Saskatchewan due to acidifying deposition were calculated, using a 1-year simulation of a high-resolution implementation of the Global Environmental Multiscale-Modelling Air-quality and Chemistry (GEM-MACH) model, and estimates of aquatic and terrestrial ecosystem critical loads. The model simulation was evaluated against two different sources of deposition data: total deposition in precipitation and total deposition to snowpack in the vicinity of the Athabasca oil sands. The model captured much of the variability of observed ions in wet deposition in precipitation (observed versus model sulfur, nitrogen and base cation R2 values of 0.90, 0.76 and 0.72, respectively), while being biased high for sulfur deposition, and low for nitrogen and base cations (slopes 2.2, 0.89 and 0.40, respectively). Aircraft-based estimates of fugitive dust emissions, shown to be a factor of 10 higher than reported to national emissions inventories (Zhang et al., 2018), were used to estimate the impact of increased levels of fugitive dust on model results. Model comparisons to open snowpack observations were shown to be biased high, but in reasonable agreement for sulfur deposition when observations were corrected to account for throughfall in needleleaf forests. The model–observation relationships for precipitation deposition data, along with the expected effects of increased (unreported) base cation emissions, were used to provide a simple observation-based correction to model deposition fields. Base cation deposition was estimated using published observations of base cation fractions in surface-collected particles (Wang et al., 2015).Both original and observation-corrected model estimates of sulfur, nitrogen, and base cation deposition were used in conjunction with critical load data created using the NEG-ECP (2001) and CLRTAP (2017) methods for calculating critical loads, using variations on the Simple Mass Balance model for terrestrial ecosystems, and the Steady State Water Chemistry and First-order Acidity Balance models for aquatic ecosystems. Potential ecosystem damage was predicted within each of the regions represented by the ecosystem critical load datasets used here, using a combination of 2011 and 2013 emissions inventories. The spatial extent of the regions in exceedance of critical loads varied between 1  ×  104 and 3.3  ×  105 km2, for the more conservative observation-corrected estimates of deposition, with the variation dependent on the ecosystem and critical load calculation methodology. The larger estimates (for aquatic ecosystems) represent a substantial fraction of the area of the provinces examined.Base cation deposition was shown to be sufficiently high in the region to have a neutralizing effect on acidifying deposition, and the use of the aircraft and precipitation observation-based corrections to base cation deposition resulted in reasonable agreement with snowpack data collected in the oil sands area. However, critical load exceedances calculated using both observations and observation-corrected deposition suggest that the neutralization effect is limited in spatial extent, decreasing rapidly with distance from emissions sources, due to the rapid deposition of emitted primary dust particles as a function of their size. We strongly recommend the use of observation-based correction of model-simulated deposition in estimating critical load exceedances, in future work.

Aging has less effect on adipose‐derived mesenchymal stem cells (ADSCs) than on bone marrow‐derived mesenchymal stem cells (BMSCs), but whether the fact holds true in stem cells from elderly patients with osteoporotic fractures is unknown. In this study, ADSCs and BMSCs of the same donor were harvested and divided into two age groups. Group A consisted of 14 young patients (36.4 ± 11.8 years old), and group B consisted of eight elderly patients (71.4 ± 3.6 years old) with osteoporotic fractures. We found that the doubling time of ADSCs from both age groups was maintained below 70 hrs, while that of BMSCs increased significantly with the number of passage. When ADSCs and BMSCs from the same patient were compared, there was a significant increase in the doubling time of BMSCs in each individual from passages 3 to 6. On osteogenic induction, the level of matrix mineralization of ADSCs from group B was comparable to that of ADSCs from group A, whereas BMSCs from group B produced least amount of mineral deposits and had a lower expression level of osteogenic genes. The p21 gene expression and senescence‐associated β‐galactosidase activity were lower in ADSCs compared to BMSCs, which may be partly responsible for the greater proliferation and differentiation potential of ADSCs. It is concluded that the proliferation and osteogenic differentiation of ADSCs were less affected by age and multiple passage than BMSCs, suggesting that ADSCs may become a potentially effective therapeutic option for cell‐based therapy, especially in elderly patients with osteoporosis.

Articular cartilage (AC) has a very limited capacity for self-healing once damaged. Chondrocytes maintain AC homeostasis and are key cells in AC tissue engineering (ACTE). However, chondrocytes lose their function due to oxidative stress. Umbilical cord mesenchymal stem cells (UCMSCs) are investigated as an alternative cell source for ACTE. MSCs are known to regulate tissue regeneration through host cell modulation, largely via extracellular vesicle (EV)-mediated cell-to-cell communication. The purpose of this study was to verify whether UCMSC-derived EVs (UCMSC-EVs) enhance chondrocyte function. The mean particle sizes of the UCMSC-EVs were 79.8 ± 19.05 nm. Transmission electron microscopy (TEM) revealed that UCMSC-EVs exhibited a spherical morphology. The presence of CD9, CD63, and CD81 confirmed the identity of UCMSC-EVs, with α-tubulin undetected. UCMSC-EVs maintained chondrocyte survival, and increased chondrocyte proliferation after intake by chondrocytes. UCMSC-EVs upregulated mRNA levels of SOX-9, collagen type II (Col-II), and Aggrecan, while decreasing collagen type I (Col-I) levels. UCMSC-EVs reduced the oxidative stress of chondrocytes by reducing mitochondrial superoxide production and increasing protein levels of SOD-2 and Sirt-3 in chondrocytes. The 50 most abundant known microRNAs (miRNAs) derived from UCMSC-EVs were selected for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. GO analysis revealed enrichment in pathways associated with small GTPase-mediated signal transduction, GTPase regulatory activity, and mitochondrial matrix. The KEGG analysis indicated that these miRNAs may regulate chondrocyte function through the PI3K-Akt, MAPK, and cAMP signaling pathways. In summary, this study shows that UCMSC-EVs enhance chondrocyte function and may be applied to ACTE.

Rapamycin (Rap) and its derivatives, called rapalogs, are being explored in clinical trials targeting cancer and neurodegeneration. The underlying mechanisms of Rap actions, however, are not well understood. Mechanistic target of rapamycin (mTOR), a lysosome-localized protein kinase that acts as a critical regulator of cellular growth, is believed to mediate most Rap actions. Here, we identified mucolipin 1 (transient receptor potential channel mucolipin 1 [TRPML1], also known as MCOLN1), the principle Ca2+ release channel in the lysosome, as another direct target of Rap. Patch-clamping of isolated lysosomal membranes showed that micromolar concentrations of Rap and some rapalogs activated lysosomal TRPML1 directly and specifically. Pharmacological inhibition or genetic inactivation of mTOR failed to mimic the Rap effect. In vitro binding assays revealed that Rap bound directly to purified TRPML1 proteins with a micromolar affinity. In both healthy and disease human fibroblasts, Rap and rapalogs induced autophagic flux via nuclear translocation of transcription factor EB (TFEB). However, such effects were abolished in TRPML1-deficient cells or by TRPML1 inhibitors. Hence, Rap and rapalogs promote autophagy via a TRPML1-dependent mechanism. Given the demonstrated roles of TRPML1 and TFEB in cellular clearance, we propose that lysosomal TRPML1 may contribute a significant portion to the in vivo neuroprotective and anti-aging effects of Rap via an augmentation of autophagy and lysosomal biogenesis.