In-Sensor Tactile Fusion and Logic for Accurate Intention Recognition.

Touch control intention recognition is an important direction for the future development of human-machine interactions (HMIs). However, the implementation of parallel-sensing functional modules generally requires a combination of different logical blocks and control circuits, which results in regional redundancy, redundant data, and low efficiency. Here, a location-and-pressure intelligent tactile sensor (LPI tactile sensor) unprecedentedly combined with sensing, computing, and logic is proposed, enabling efficient and ultrahigh-resolution action-intention interaction. The LPI tactile sensor eliminates the need for data transfer among the functional units through the core integration design of the layered structure. It actuates in-sensor perception through feature transmission, fusion, and differentiation, thereby revolutionizing the traditional von Neumann architecture. While greatly simplifying the data dimensionality, the LPI tactile sensor achieves outstanding resolution sensing in both location (<400 µm) and pressure (75 Pa). Synchronous feature fusion and decoding support the high-fidelity recognition of action and combinatorial logic intentions. Benefiting from location and pressure synergy, the LPI tactile sensor demonstrates robust privacy as an encrypted password device and interaction intelligence through pressure enhancement. It can recognize continuous touch actions in real time, map real intentions to target events, and promote accurate and efficient intention-driven HMIs.

Application value of indocyanine green fluorescence imaging in guiding sentinel lymph node biopsy diagnosis of gastric cancer: Meta-analysis.

BACKGROUND: Gastric cancer is a common malignant tumor of the digestive system worldwide, and its early diagnosis is crucial to improve the survival rate of patients. Indocyanine green fluorescence imaging (ICG-FI), as a new imaging technology, has shown potential application prospects in oncology surgery. The meta-analysis to study the application value of ICG-FI in the diagnosis of gastric cancer sentinel lymph node biopsy is helpful to comprehensively evaluate the clinical effect of this technology and provide more reliable guidance for clinical practice. AIM: To assess the diagnostic efficacy of optical imaging in conjunction with indocyanine green (ICG)-guided sentinel lymph node (SLN) biopsy for gastric cancer. METHODS: Electronic databases such as PubMed, Embase, Medline, Web of Science, and the Cochrane Library were searched for prospective diagnostic tests of optical imaging combined with ICG-guided SLN biopsy. Stata 12.0 software was used for analysis by combining the "bivariable mixed effect model" with the "midas" command. The true positive value, false positive value, false negative value, true negative value, and other information from the included literature were extracted. A literature quality assessment map was drawn to describe the overall quality of the included literature. A forest plot was used for heterogeneity analysis, and P < 0.01 was considered to indicate statistical significance. A funnel plot was used to assess publication bias, and P < 0.1 was considered to indicate statistical significance. The summary receiver operating characteristic (SROC) curve was used to calculate the area under the curve (AUC) to determine the diagnostic accuracy. If there was interstudy heterogeneity (I 2 > 50%), meta-regression analysis and subgroup analysis were performed. RESULTS: Optical imaging involves two methods: Near-infrared (NIR) imaging and fluorescence imaging. A combination of optical imaging and ICG-guided SLN biopsy was useful for diagnosis. The positive likelihood ratio was 30.39 (95%CI: 0.92-1.00), the sensitivity was 0.95 (95%CI: 0.82-0.99), and the specificity was 1.00 (95%CI: 0.92-1.00). The negative likelihood ratio was 0.05 (95%CI: 0.01-0.20), the diagnostic odds ratio was 225.54 (95%CI: 88.81-572.77), and the SROC AUC was 1.00 (95%CI: The crucial values were sensitivity = 0.95 (95%CI: 0.82-0.99) and specificity = 1.00 (95%CI: 0.92-1.00). The Deeks method revealed that the "diagnostic odds ratio" funnel plot of SLN biopsy for gastric cancer was significantly asymmetrical (P = 0.01), suggesting significant publication bias. Further meta-subgroup analysis revealed that, compared with fluorescence imaging, NIR imaging had greater sensitivity (0.98 vs 0.73). Compared with optical imaging immediately after ICG injection, optical imaging after 20 minutes obtained greater sensitivity (0.98 vs 0.70). Compared with that of patients with an average SLN detection number < 4, the sensitivity of patients with a SLN detection number ≥ 4 was greater (0.96 vs 0.68). Compared with hematoxylin-eosin (HE) staining, immunohistochemical (+ HE) staining showed greater sensitivity (0.99 vs 0.84). Compared with subserous injection of ICG, submucosal injection achieved greater sensitivity (0.98 vs 0.40). Compared with 5 g/L ICG, 0.5 and 0.05 g/L ICG had greater sensitivity (0.98 vs 0.83), and cT1 stage had greater sensitivity (0.96 vs 0.72) than cT2 to cT3 clinical stage. Compared with that of patients ≤ 26, the sensitivity of patients > 26 was greater (0.96 vs 0.65). Compared with the literature published before 2010, the sensitivity of the literature published after 2010 was greater (0.97 vs 0.81), and the differences were statistically significant (all P < 0.05). CONCLUSION: For the diagnosis of stomach cancer, optical imaging in conjunction with ICG-guided SLN biopsy is a therapeutically viable approach, especially for early gastric cancer. The concentration of ICG used in the SLN biopsy of gastric cancer may be too high. Moreover, NIR imaging is better than fluorescence imaging and may obtain higher sensitivity.

HyperFace: A Deep Fusion Model for Hyperspectral Face Recognition.

Face recognition has been well studied under visible light and infrared (IR) in both intra-spectral and cross-spectral cases. However, how to fuse different light bands for face recognition, i.e., hyperspectral face recognition, is still an open research problem, which has the advantages of richer information retention and all-weather functionality over single-band face recognition. Thus, in this research, we revisit the hyperspectral recognition problem and provide a deep learning-based approach. A new fusion model (named HyperFace) is proposed to address this problem. The proposed model features a pre-fusion scheme, a Siamese encoder with bi-scope residual dense learning, a feedback-style decoder, and a recognition-oriented composite loss function. Experiments demonstrate that our method yields a much higher recognition rate than face recognition using only visible light or IR data. Moreover, our fusion model is shown to be superior to other general-purpose image fusion methods that are either traditional or deep learning-based, including state-of-the-art methods, in terms of both image quality and recognition performance.

Bioactive fiber-reinforced hydrogel to tailor cell microenvironment for structural and functional regeneration of myotendinous junction.

Myotendinous junction (MTJ) injuries are prevalent in clinical practice, yet the treatment approaches are limited to surgical suturing and conservative therapy, exhibiting a high recurrence rate. Current research on MTJ tissue engineering is scarce and lacks in vivo evaluation of repair efficacy. Here, we developed a three-dimensional-printed bioactive fiber-reinforced hydrogel containing mesenchymal stem cells (MSCs) and Klotho for structural and functional MTJ regeneration. In a rat MTJ defect model, the bioactive fiber-reinforced hydrogel promoted the structural restoration of muscle, tendon, and muscle-tendon interface and enhanced the functional recovery of injured MTJ. In vivo proteomics and in vitro cell cultures elucidated the regenerative mechanisms of the bioactive fiber-reinforced hydrogel by modulating oxidative stress and inflammation, thus engineering an optimized microenvironment to support the survival and differentiation of transplanted MSCs and maintain the functional phenotype of resident cells within MTJ tissues, including tendon/muscle cells and macrophages. This strategy provides a promising treatment for MTJ injuries.

Research on the evolution mechanism and decoupling effect of China's carbon emissions from the perspective of green credit: based on system dynamics model and Tapio model.

Green credit is an important topic in the study of green finance system, but it has not been combined with China's carbon emission reduction effect and industrial carbon emissions. This study takes different industries in China as research objects to explore the relationship between green credit and industrial carbon emissions. First, the LMDI decomposition model was used to decompose the driving factors of industrial carbon emissions, and the effects of green credit efficiency and scale on carbon emissions were obtained. Secondly, on this basis, a system dynamics model was established to predict the changing trend of carbon emissions in different industries. By setting different scenarios of green credit, the development and evolution trend of carbon emission system was simulated when parameters changed, and the Tapio decoupling model was further established to analyze the decoupling effect of green credit and carbon emissions under different scenarios. Finally, the research results show that the increase in the scale of green credit can effectively inhibit carbon emissions and has the greatest effect on carbon emissions of the secondary industry. The incentive policy of green credit can effectively encourage industrial upgrading and development. With the growth of the balance of green credit, green credit and carbon emissions gradually reach the best decoupling state. This study provides empirical evidence for the objective evaluation of the implementation effect of China's green credit policy and has important reference value for the improvement and development of future policies.

Enhanced Cartilage and Subchondral Bone Repair Using Carbon Nanotube-Doped Peptide Hydrogel-Polycaprolactone Composite Scaffolds.

A carbon nanotube-doped octapeptide self-assembled hydrogel (FEK/C) and a hydrogel-based polycaprolactone PCL composite scaffold (FEK/C3-S) were developed for cartilage and subchondral bone repair. The composite scaffold demonstrated modulated microstructure, mechanical properties, and conductivity by adjusting CNT concentration. In vitro evaluations showed enhanced cell proliferation, adhesion, and migration of articular cartilage cells, osteoblasts, and bone marrow mesenchymal stem cells. The composite scaffold exhibited good biocompatibility, low haemolysis rate, and high protein absorption capacity. It also promoted osteogenesis and chondrogenesis, with increased mineralization, alkaline phosphatase (ALP) activity, and glycosaminoglycan (GAG) secretion. The composite scaffold facilitated accelerated cartilage and subchondral bone regeneration in a rabbit knee joint defect model. Histological analysis revealed improved cartilage tissue formation and increased subchondral bone density. Notably, the FEK/C3-S composite scaffold exhibited the most significant cartilage and subchondral bone formation. The FEK/C3-S composite scaffold holds great promise for cartilage and subchondral bone repair. It offers enhanced mechanical support, conductivity, and bioactivity, leading to improved tissue regeneration. These findings contribute to the advancement of regenerative strategies for challenging musculoskeletal tissue defects.

Conformal Human-Machine Integration Using Highly Bending-Insensitive, Unpixelated, and Waterproof Epidermal Electronics Toward Metaverse.

Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals, which is critical to the breakthrough development of metaverse. Interactive electronics face common dilemmas, which realize high-precision and stable touch detection but are rigid, bulky, and thick or achieve high flexibility to wear but lose precision. Here, we construct highly bending-insensitive, unpixelated, and waterproof epidermal interfaces (BUW epidermal interfaces) and demonstrate their interactive applications of conformal human-machine integration. The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection, high flexibility, rapid response time, excellent stability, and versatile "cut-and-paste" character. Regardless of whether being flat or bent, the BUW epidermal interface can be conformally attached to the human skin for real-time, comfortable, and unrestrained interactions. This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics, which offers a new technology route and may further broaden human-machine interactions toward metaverse.

Silk Fibroin and Sericin Differentially Potentiate the Paracrine and Regenerative Functions of Stem Cells Through Multiomics Analysis.

Silk fibroin (SF) and sericin (SS), the two major proteins of silk, are attractive biomaterials with great potential in tissue engineering and regenerative medicine. However, their biochemical interactions with stem cells remain unclear. In this study, multiomics are employed to obtain a global view of the cellular processes and pathways of mesenchymal stem cells (MSCs) triggered by SF and SS to discern cell-biomaterial interactions at an in-depth, high-throughput molecular level. Integrated RNA sequencing and proteomic analysis confirm that SF and SS initiate widespread but distinct cellular responses and potentiate the paracrine functions of MSCs that regulate extracellular matrix deposition, angiogenesis, and immunomodulation through differentially activating the integrin/PI3K/Akt and glycolysis signaling pathways. These paracrine signals of MSCs stimulated by SF and SS effectively improve skin regeneration by regulating the behavior of multiple resident cells (fibroblasts, endothelial cells, and macrophages) in the skin wound microenvironment. Compared to SS, SF exhibits better immunomodulatory effects in vitro and in vivo, indicating its greater potential as a carrier material of MSCs for skin regeneration. This study provides comprehensive and reliable insights into the cellular interactions with SF and SS, enabling the future development of silk-based therapeutics for tissue engineering and stem cell therapy.

A 3D multifunctional bi-layer scaffold to regulate stem cell behaviors and promote osteochondral regeneration.

Osteochondral defect (OCD) regeneration remains a great challenge. Recently, multilayer scaffold simulating native osteochondral structures have aroused broad interest in osteochondral tissue engineering. Here, we developed a 3D multifunctional bi-layer scaffold composed of a kartogenin (KGN)-loaded GelMA hydrogel (GelMA/KGN) as an upper layer mimicking a cartilage-specific extracellular matrix and a hydroxyapatite (HA)-coated 3D printed polycaprolactone porous scaffold (PCL/HA) as a lower layer simulating subchondral bone. The bi-layer scaffolds were subsequently modified with tannic acid (TA) prime-coating and E7 peptide conjugation (PCL/HA-GelMA/KGN@TA/E7) to regulate endogenous stem cell behaviors and exert antioxidant activity for enhanced osteochondral regeneration. In vitro, the scaffolds could support cell attachment and proliferation, and enhance the chondrogenic and osteogenic differentiation capacity of bone marrow-derived mesenchymal stem cells (BMSCs) in a specific layer. Besides, the incorporation of TA/E7 significantly increased the biological activity of the bi-layer scaffolds including the pro-migratory effect, antioxidant activity, and the maintenance of cell viability against oxidative stress. In vivo, the developed bi-layer scaffolds enhanced the simultaneous regeneration of cartilage and subchondral bone when implanted into a rabbit OCD model through macroscopic, micro-CT, and histological evaluation. Taken together, these investigations demonstrated that the 3D multifunctional bi-layer scaffolds could provide a suitable microenvironment for endogenous stem cells, and promote in situ osteochondral regeneration, showing great potential for the clinical treatment of OCD.

Silk-based hydrogel incorporated with metal-organic framework nanozymes for enhanced osteochondral regeneration.

Osteochondral defects (OCD) cannot be efficiently repaired due to the unique physical architecture and the pathological microenvironment including enhanced oxidative stress and inflammation. Conventional strategies, such as the control of implant microstructure or the introduction of growth factors, have limited functions failing to manage these complex environments. Here we developed a multifunctional silk-based hydrogel incorporated with metal-organic framework nanozymes (CuTA@SF) to provide a suitable microenvironment for enhanced OCD regeneration. The incorporation of CuTA nanozymes endowed the SF hydrogel with a uniform microstructure and elevated hydrophilicity. In vitro cultivation of mesenchymal stem cells (MSCs) and chondrocytes showed that CuTA@SF hydrogel accelerated cell proliferation and enhanced cell viability, as well as had antioxidant and antibacterial properties. Under the inflammatory environment with the stimulation of IL-1ß, CuTA@SF hydrogel still possessed the potential to promote MSC osteogenesis and deposition of cartilage-specific extracellular matrix (ECM). The proteomics analysis further confirmed that CuTA@SF hydrogel promoted cell proliferation and ECM synthesis. In the full-thickness OCD model of rabbit, CuTA@SF hydrogel displayed successfully in situ OCD regeneration, as evidenced by micro-CT, histology (HE, S/O, and toluidine blue staining) and immunohistochemistry (Col I and aggrecan immunostaining). Therefore, CuTA@SF hydrogel is a promising biomaterial targeted at the regeneration of OCD.

Cell-free and cytokine-free self-assembling peptide hydrogel-polycaprolactone composite scaffolds for segmental bone defects.

Segmental bone defects over the self-healing threshold are a major challenge for orthopedics. Despite the advancements in clinical practice, traditional tissue engineering methods are limited by the addition of heterogeneous cells and cytokines, leading to carcinoma or other adverse effects. Here, we present a cell-free and cytokine-free strategy using an ECM-mimetic self-assembling peptide hydrogel (SAPH)- polycaprolactone (PCL) composite scaffold. The hydrophilic SAPH endows the rigid PCL scaffold with excellent biocompatibility and preference for osteogenesis induction. The autologous cells around the bone defect site immediately grew, proliferated, and secreted ECM and cytokines after contacting the implanted SAPH-PCL composite scaffold, and the bone repair of rabbit ulnar segmental bone defect was achieved in just six months. Quantitative proteomic analysis reveals that the SAPH-PCL composite scaffold accelerates osteoblastogenesis, osteoclastogenesis, and angiogenesis with moderate immune responses and negligible effects on pathological fibrosis. These findings have important implications for the potential clinical applications of the SAPH-PCL composite scaffold in patients with segmental bone defects and identify the mechanisms of action for accelerated segmental bone defect repair.

GMLM-CNN: A Hybrid Solution to SWIR-VIS Face Verification with Limited Imagery.

Cross-spectral face verification between short-wave infrared (SWIR) and visible light (VIS) face images poses a challenge, which is motivated by various real-world applications such as surveillance at night time or in harsh environments. This paper proposes a hybrid solution that takes advantage of both traditional feature engineering and modern deep learning techniques to overcome the issue of limited imagery as encountered in the SWIR band. Firstly, the paper revisits the theory of measurement levels. Then, two new operators are introduced which act at the nominal and interval levels of measurement and are named the Nominal Measurement Descriptor (NMD) and the Interval Measurement Descriptor (IMD), respectively. A composite operator Gabor Multiple-Level Measurement (GMLM) is further proposed which fuses multiple levels of measurement. Finally, the fused features of GMLM are passed through a succinct and efficient neural network based on PCA. The network selects informative features and also performs the recognition task. The overall framework is named GMLM-CNN. It is compared to both traditional hand-crafted operators as well as recent deep learning-based models that are state-of-the-art, in terms of cross-spectral verification performance. Experiments are conducted on a dataset which comprises frontal VIS and SWIR faces acquired at varying standoffs. Experimental results demonstrate that, in the presence of limited data, the proposed hybrid method GMLM-CNN outperforms all the other methods.

Three-dimensional-printed polycaprolactone scaffolds with interconnected hollow-pipe structures for enhanced bone regeneration.

Three-dimensional (3D)-printed scaffolds are widely used in tissue engineering to help regenerate critical-sized bone defects. However, conventional scaffolds possess relatively simple porous structures that limit the delivery of oxygen and nutrients to cells, leading to insufficient bone regeneration. Accordingly, in the present study, perfusable and permeable polycaprolactone scaffolds with highly interconnected hollow-pipe structures that mimic natural micro-vascular networks are prepared by an indirect one-pot 3D-printing method. In vitro experiments demonstrate that hollow-pipe-structured (HPS) scaffolds promote cell attachment, proliferation, osteogenesis and angiogenesis compared to the normal non-hollow-pipe-structured scaffolds. Furthermore, in vivo studies reveal that HPS scaffolds enhance bone regeneration and vascularization in rabbit bone defects, as observed at 8 and 12 weeks, respectively. Thus, the fabricated HPS scaffolds are promising candidates for the repair of critical-sized bone defects.

Multifunctional polyphenol-based silk hydrogel alleviates oxidative stress and enhances endogenous regeneration of osteochondral defects.

In osteochondral defects, oxidative stress caused by elevated levels of reactive oxygen species (ROS) can disrupt the normal endogenous repair process. In this study, a multifunctional hydrogel composed of silk fibroin (SF) and tannic acid (TA), the FDA-approved ingredients, was developed to alleviate oxidative stress and enhance osteochondral regeneration. In this proposed hydrogel, SF first interacts with TA to form a hydrogen-bonded supramolecular structure, which is subsequently enzymatically crosslinked to form a stable hydrogel. Furthermore, TA had multiple phenolic hydroxyl groups that formed interactions with the therapeutic molecule E7 peptide for controlled drug delivery. In vitro investigations showed that SF-TA and SF-TA-E7 hydrogels exhibited a multitude of biological effects including scavenging of ROS, maintaining cell viability, and promoting the proliferation of bone marrow mesenchymal stem cells (BMSCs) against oxidative stress. The proteomic analysis indicated that SF-TA and SF-TA-E7 hydrogels suppressed oxidative stress, which in turn improved cell proliferation in multiple proliferation and apoptosis-related pathways. In rabbit osteochondral defect model, SF-TA and SF-TA-E7 hydrogels promoted enhanced regeneration of both cartilage and subchondral bone as compared to hydrogel without TA incorporation. These findings indicated that the multifunctional SF-TA hydrogel provided a microenvironment suitable for the endogenous regeneration of osteochondral defects.

A Magnified Adaptive Feature Pyramid Network for automatic microaneurysms detection.

Diabetic retinopathy (DR), as an important complication of diabetes, is the primary cause of blindness in adults. Automatic DR detection poses a challenge which is crucial for early DR screening. Currently, the vast majority of DR is diagnosed through fundus images, where the microaneurysm (MA) has been widely used as the most distinguishable marker. Research works on automatic DR detection have traditionally utilized manually designed operators, while a few recent researchers have explored deep learning techniques for this topic. But due to issues such as the extremely small size of microaneurysms, low resolution of fundus pictures, and insufficient imaging depth, the DR detection problem is quite challenging and remains unsolved. To address these issues, this research proposes a new deep learning model (Magnified Adaptive Feature Pyramid Network, MAFP-Net) for DR detection, which conducts super-resolution on low quality fundus images and integrates an improved feature pyramid structure while utilizing a standard two-stage detection network as the backbone. Our proposed detection model needs no pre-segmented patches to train the CNN network. When tested on the E-ophtha-MA dataset, the sensitivity value of our method reached as high as 83.5% at false positives per image (FPI) of 8 and the F1 value achieved 0.676, exceeding all those of the state-of-the-art algorithms as well as the human performance of experienced physicians. Similar results were achieved on another public dataset of IDRiD.

Study on optimization of inspection mechanism of concrete beam bridge.

China is shifting from the stage of large-scale bridge construction to the stage of equal emphasis on the construction and maintenance of bridges. The problems of low efficiency and high cost in bridge inspection are becoming more and more prominent, which threaten people's life safety. In this paper, the deterioration state prediction model of concrete beam bridge under Boosting DT C5.0 was established as the basis, and optimization suggestions were put forward in terms of bridge inspection standards and processes, which aims to perfect the bridge inspection mechanism, realize the fine management of the bridge and prolong the service life of the bridge. Research shows that: first, the bridge inspection standard with a single index should be improved into the bridge inspection standard with multiple indexes, so as to scientifically determine the bridges that need to be inspected and optimize the allocation of maintenance resources. Second, the bridge deterioration state prediction model is used to add a screening mechanism for the bridge in the inspection plan, which can effectively reduce the workload of bridge inspection and enhance the inspection efficiency. Third, the deterioration phenomenon of coexistence between adjacent traffic assets should be fully considered and the linkage inspection mechanism of adjacent traffic assets should be established to improve the effect of bridge inspection.

Balancing Heterogeneous Image Quality for Improved Cross-Spectral Face Recognition.

Matching infrared (IR) facial probes against a gallery of visible light faces remains a challenge, especially when combined with cross-distance due to deteriorated quality of the IR data. In this paper, we study the scenario where visible light faces are acquired at a short standoff, while IR faces are long-range data. To address the issue of quality imbalance between the heterogeneous imagery, we propose to compensate it by upgrading the lower-quality IR faces. Specifically, this is realized through cascaded face enhancement that combines an existing denoising algorithm (BM3D) with a new deep-learning-based deblurring model we propose (named SVDFace). Different IR bands, short-wave infrared (SWIR) and near-infrared (NIR), as well as different standoffs, are involved in the experiments. Results show that, in all cases, our proposed approach for quality balancing yields improved recognition performance, which is especially effective when involving SWIR images at a longer standoff. Our approach outperforms another easy and straightforward downgrading approach. The cascaded face enhancement structure is also shown to be beneficial and necessary. Finally, inspired by the singular value decomposition (SVD) theory, the proposed deblurring model of SVDFace is succinct, efficient and interpretable in structure. It is proven to be advantageous over traditional deblurring algorithms as well as state-of-the-art deep-learning-based deblurring algorithms.

Study of the Risk and Preventive Factors for Progress of Mild Cognitive Impairment to Dementia.

OBJECTIVE: To evaluate the risk factors for progress of mild cognitive impairment to dementia. METHODS: This study was based on the epidemiological survey in 2011 (No. PKJ2010-Y26) and contained 441 MCI individuals. Cognitive function was measured by the Mini-Mental Status Examination, clinical dementia rating, and montreal cognitive assessment. The association between demographic characteristics and MCI outcomes were evaluated using single-and multifactor ordered logistic regression analysis models. RESULTS: Of the 441 MCI, 77 progressed to dementia (MCIp: 17.5%, 95% CI: 14.4%-21.6%), 356 remained stable (MCIs: 80.7%, 95% CI: 77.0%-88.4%), and 8 reverted to normal cognition (MCIr: 1.8%, 95% CI: 0.6%-3.0%) at follow-up in 2017. Univariate ordinal regression analysis showed that diabetes (P = .052), marriage (P = .028), worker (P = .069), and manager (P = .075) may be the risk factor for the status of MCI. Multiple ordinal regression results showed that diabetes (P = .049) and marriage (P = .04) significantly affected the cognitive function changes in the MCI patients. CONCLUSION: Nondiabetics and being married may prevent the progression from MCI to dementia.

Inhibition of basal cell carcinoma cells by cold atmospheric plasma­activated solution and differential gene expression analysis.

Basal cell carcinoma is a common skin tumor. Cold atmospheric plasma (CAP) has attracted increasing attention for its antitumor effects. The aim of the present study was to investigate the effects and related mechanisms of two CAP­activated solutions on the TE354T basal cell carcinoma and HaCat keratinocyte cell lines. Plasma­activated solution (PAS) was prepared by CAP irradiation of DMEM and PBS. TE354T cells were treated with PAS in vitro and the effect on cell viability was evaluated by an MTT assay. The apoptosis rate was detected by Annexin V/propidium iodide staining. Furthermore, western blotting and RNA­sequencing were performed. The present results demonstrated that PAS induced apoptotic signaling in basal cell carcinoma cells, and that this effect was associated with the activation of the MAPK signaling pathway. Therefore, the present study demonstrated that PAS may serve as a novel treatment for basal cell carcinoma.

Bactericidal efficacy of cold atmospheric plasma treatment against multidrug-resistant Pseudomonas aeruginosa.

Aim: The global of spread multidrug-resistant Pseudomonas aeruginosa has become a public health threat. Cold atmospheric plasma (CAP) is reported to have bactericidal efficacy; however, its effects on clinical super multidrug-resistant P. aeruginosa are unclear. The aim of this study was to investigate the bactericidal efficacy of CAP on a strain of super multidrug-resistant P. aeruginosa. Materials & methods: The effects of CAP treatments were evaluated using assays for the detection of growth, viability, metabolism, virulence factors and reactive oxygen species (ROS) levels. Results: Both CAP treatments dose-dependently inhibited cell viability and metabolic activity, and decreased the expression of several virulence factors. CAP treatment induced a significant increase in intracellular ROS levels, and ROS scavengers inhibited this effect. Conclusion: CAP treatment is a promising option for the clinical inhibition of multidrug-resistant P. aeruginosa, and the development of CAP technologies might be the key to solving the long-standing problem of drug-resistant bacteria.