In this study, polycaprolactone (P) scaffolds are fabricated by 3D‐printing method, and subsequently a mixed solution of natural‐biocompatible chitosan (C), gelatin (G), and hydroxyapatite (H) is ...filled into the pores of P scaffolds. Freeze‐gelation method is then carried out to successfully form a cell‐compatible porous CGH matrix within P scaffold pores, obtaining a newly fabricated scaffold called CGH/P composite scaffold which has large specific surface area favorable for cell attachment and growth. The effects of slow cooling (sc) and fast cooling (fc) modes utilized in freeze process on pore structures of CGH matrix are observed via SEM. The use of fc mode creates a CGH matrix with a laminar structure which benefits nutrient permeation and cell migration. Mechanical properties tests indicate that the maximum compressive strength and Young's modulus of CGH/P‐fc scaffolds are 2–7 and 15–35 MPa, respectively. Cell compatibility tests show that on day 7, the cell numbers in the CGH/P‐fc scaffolds are about twofold of those in the P scaffolds, and the cell activities in the CGH/P‐fc scaffolds are even higher, indicating that the presence of laminar porous CGH matrix within P scaffold pores substantially enhances the migration, attachment, and growth of cells in the scaffolds. The results suggest that the fabricated CGH/P‐fc composite scaffold is highly promising for biomedical applications such as bone repair in the future.
A schematic diagram of fabricating C/P, CG/P, and CGH/P porous composite scaffolds by 3D‐printing and freeze‐gelation process.
Abstract
Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology‐related research. ...In this review, we summarize common MSI techniques, including matrix‐assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next‐generation pathology practices.
Osmoregulation is important for plant growth, development and response to environmental changes. SNF1-related protein kinase 2s (SnRK2s) are quickly activated by osmotic stress and are central ...components in osmotic stress and abscisic acid (ABA) signaling pathways; however, the upstream components required for SnRK2 activation and early osmotic stress signaling are still unknown. Here, we report a critical role for B2, B3 and B4 subfamilies of Raf-like kinases (RAFs) in early osmotic stress as well as ABA signaling in Arabidopsis thaliana. B2, B3 and B4 RAFs are quickly activated by osmotic stress and are required for phosphorylation and activation of SnRK2s. Analyses of high-order mutants of RAFs reveal critical roles of the RAFs in osmotic stress tolerance and ABA responses as well as in growth and development. Our findings uncover a kinase cascade mediating osmoregulation in higher plants.
Given a large unlabeled set of images how to efficiently and effectively group them into clusters based on extracted visual representations remains a challenging problem. To address this problem we ...propose a convolutional neural network (CNN) to jointly solve clustering and representation learning in an iterative manner. In the proposed method given an input image set we first randomly pick k samples and extract their features as initial cluster centroids using the proposed CNN with an initial model pretrained from the ImageNet dataset. Mini-batch k-means is then performed to assign cluster labels to individual input samples for a mini-batch of images randomly sampled from the input image set until all images are processed. Subsequently the proposed CNN simultaneously updates the parameters of the proposed CNN and the centroids of image clusters iteratively based on stochastic gradient descent. We also propose a feature drift compensation scheme to mitigate the drift error caused by feature mismatch in representation learning. Experimental results demonstrate the proposed method outperforms start-of-the-art clustering schemes in terms of accuracy and storage complexity on large-scale image sets containing millions of images.
Patients with advanced esophageal cancer have a poor prognosis and limited treatment options after first-line chemotherapy.
In this open-label, phase III study, we randomly assigned (1:1) 628 ...patients with advanced/metastatic squamous cell carcinoma or adenocarcinoma of the esophagus, that progressed after one prior therapy, to pembrolizumab 200 mg every 3 weeks for up to 2 years or chemotherapy (investigator's choice of paclitaxel, docetaxel, or irinotecan). Primary end points were overall survival (OS) in patients with programmed death ligand-1 (PD-L1) combined positive score (CPS) ≥ 10, in patients with squamous cell carcinoma, and in all patients (one-sided α 0.9%, 0.8%, and 0.8%, respectively).
At final analysis, conducted 16 months after the last patient was randomly assigned, OS was prolonged with pembrolizumab versus chemotherapy for patients with CPS ≥ 10 (median, 9.3
6.7 months; hazard ratio HR, 0.69 95% CI, 0.52 to 0.93;
= .0074). Estimated 12-month OS rate was 43% (95% CI, 33.5% to 52.1%) with pembrolizumab versus 20% (95% CI, 13.5% to 28.3%) with chemotherapy. Median OS was 8.2 months versus 7.1 months (HR, 0.78 95% CI, 0.63 to 0.96;
= .0095) in patients with squamous cell carcinoma and 7.1 months versus 7.1 months (HR, 0.89 95% CI, 0.75 to 1.05;
= .0560) in all patients. Grade 3-5 treatment-related adverse events occurred in 18.2% of patients with pembrolizumab versus 40.9% in those who underwent chemotherapy.
Pembrolizumab prolonged OS versus chemotherapy as second-line therapy for advanced esophageal cancer in patients with PD-L1 CPS ≥ 10, with fewer treatment-related adverse events.
Though generative adversarial networks (GANs) can hallucinate high-quality high-resolution (HR) faces from low-resolution (LR) faces, they cannot ensure identity preservation during face ...hallucination, making the HR faces difficult to recognize. To address this problem, we propose a Siamese GAN (SiGAN) to reconstruct HR faces that visually resemble their corresponding identities. On top of a Siamese network, the proposed SiGAN consists of a pair of two identical generators and one discriminator. We incorporate reconstruction error and identity label information in the loss function of SiGAN in a pairwise manner. By iteratively optimizing the loss functions of the generator pair and the discriminator of SiGAN, we not only achieve visually-pleasing face reconstruction but also ensure that the reconstructed information is useful for identity recognition. Experimental results demonstrate that SiGAN significantly outperforms existing face hallucination GANs in objective face verification performance while achieving promising visual-quality reconstruction. Moreover, for input LR faces with unseen identities that are not part of the training dataset, SiGAN can still achieve reasonable performance.
Frail older adults are predisposed to multiple comorbidities and adverse events. Recent interventional studies have shown that frailty can be improved and managed. In this study, effective ...individualized home-based exercise and nutrition interventions were developed for reducing frailty in older adults.
This study was a four-arm, single-blind, randomized controlled trial conducted between October 2015 and June 2017 at Miaoli General Hospital in Taiwan. Overall, 319 pre-frail or frail older adults were randomly assigned into one of the four study groups (control, exercise, nutrition, and exercise plus nutrition combination) and followed up during a 3-month intervention period and 3-month self-maintenance period. Improvement in frailty scores was the primary outcome. Secondary outcomes included improvements in physical performance and mental health. The measurements were performed at baseline, 1 month, 3 months, and 6 months.
At the 6-month measurement, the exercise (difference in frailty score change from baseline: - 0.23; 95% confidence interval CI: - 0.41, - 0.05; p = 0.012), nutrition (- 0.28; 95% CI: - 0.46, - 0.11; p = 0.002), and combination (- 0.34; 95% CI: - 0.52, - 0.16; p < 0.001) groups exhibited significantly greater improvements in the frailty scores than the control group. Significant improvements were also observed in several physical performance parameters in the exercise, nutrition, and combination groups, as well as in the 12-Item Short Form Health Survey mental component summary score for the nutrition group.
The designated home-based exercise and nutrition interventions can help pre-frail or frail older adults to improve their frailty score and physical performance.
Retrospectively registered at ClinicalTrials.gov (identifier: NCT03477097); registration date: March 26, 2018.
Abstract
Motivation
Cancer dependencies provide potential drug targets. Unfortunately, dependencies differ among cancers and even individuals. To this end, visible neural networks (VNNs) are ...promising due to robust performance and the interpretability required for the biomedical field.
Results
We design Biological visible neural network (BioVNN) using pathway knowledge to predict cancer dependencies. Despite having fewer parameters, BioVNN marginally outperforms traditional neural networks (NNs) and converges faster. BioVNN also outperforms an NN based on randomized pathways. More importantly, dependency predictions can be explained by correlating with the neuron output states of relevant pathways, which suggest dependency mechanisms. In feature importance analysis, BioVNN recapitulates known reaction partners and proposes new ones. Such robust and interpretable VNNs may facilitate the understanding of cancer dependency and the development of targeted therapies.
Availability and implementation
Code and data are available at https://github.com/LichtargeLab/BioVNN
Supplementary information
Supplementary data are available at Bioinformatics online.
This paper presents an adaptive control using radial-basis-function neural networks (RBFNNs) for a two-wheeled self-balancing scooter. A mechatronic system structure of the scooter driven by two dc ...motors is briefly described, and its mathematical modeling incorporating two frictions between the wheels and the motion surface is derived. By decomposing the overall system into two subsystems (yaw motion and mobile inverted pendulum), one proposes two adaptive controllers using RBFNN to achieve self-balancing and yaw control. The performance and merit of the proposed adaptive controllers are exemplified by conducting several simulations and experiments on a two-wheeled self-balancing scooter.
Background and aims
Nicotine is a highly addictive substance in tobacco products that dysregulates several neurotransmitters in the brain and impairs executive function. Non‐invasive brain ...stimulation (NIBS) methods such as repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) are promising treatments for nicotine dependence. We investigated the efficacy and acceptability of NIBS in managing smoking cessation through a systematic review and network meta‐analysis (NMA).
Methods
We conducted a systematic review to identify randomized controlled trials (RCTs) that investigated the efficacy of NIBS for smoking cessation. All pairwise meta‐analyses and NMA procedures were conducted using random‐effects and frequentist models. The co‐primary outcomes were (1) the change in number of cigarettes smoked per day (change in frequency of smoking) in patients with nicotine dependence after NIBS and (2) acceptability (the dropout rate). The effect sizes for co‐primary outcomes of change in frequency of smoking and acceptability were assessed according to standardized mean difference (SMD) and odds ratio, respectively.
Results
Twelve RCTs with 710 participants (mean age: 44.2 years, 31.2% female) were included. Compared with the sham control, 10‐Hz rTMS over the left dorsolateral prefrontal cortex (DLPFC) was associated with the largest changes in smoking frequency SMD = −1.22, 95% confidence interval (95% CI) = −1.77 to −0.66. The 2‐mA bifrontal tDCS (SMD = −0.97, 95% CI = −1.32 to −0.62) and 10‐Hz deep rTMS over the bilateral DLPFC with cue provocation (SMD = −0.77, 95% CI = −1.20 to −0.34) were associated with a significantly larger decrease in smoking frequency versus the sham. None of the investigated NIBSs was associated with dropout rates significantly different from those of the sham control groups.
Conclusion
Prefrontal non‐invasive brain stimulation interventions appear to reduce the number of cigarettes smoked with good acceptability.
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