Injective Programmable Proanthocyanidin-Coordinated Zinc-Based Composite Hydrogel for Infected Bone Repair.

Effectively integrating infection control and osteogenesis to promote infected bone repair is challenging. Herein, injective programmable proanthocyanidin (PC)-coordinated zinc-based composite hydrogels (ipPZCHs) are developed by compositing antimicrobial and antioxidant PC-coordinated zinc oxide (ZnO) microspheres with thioether-grafted sodium alginate (TSA), followed by calcium chloride (CaCl2 ) crosslinking. Responsive to the high endogenous reactive oxygen species (ROS) microenvironment in infected bone defects, the hydrophilicity of TSA can be significantly improved, to trigger the disintegration of ipPZCHs and the fast release of PC-coordinated ZnOs. This together with the easily dissociable PC-Zn2+ coordination induced fast release of antimicrobial zinc (Zn2+ ) with/without silver (Ag+ ) ions from PC-coordinated ZnOs (for Zn2+ , > 100 times that of pure ZnO) guarantees the strong antimicrobial activity of ipPZCHs. The exogenous ROS generated by ZnO and silver nanoparticles during the antimicrobial process further speeds up the disintegration of ipPZCHs, augmenting the antimicrobial efficacy. At the same time, ROS-responsive degradation/disintegration of ipPZCHs vacates space for bone ingrowth. The concurrently released strong antioxidant PC scavenges excess ROS thus enhances the immunomodulatory (in promoting the anti-inflammatory phenotype (M2) polarization of macrophages) and osteoinductive properties of Zn2+ , thus the infected bone repair is effectively promoted via the aforementioned programmable and self-adaptive processes.

Chitosan nanofibrous scaffold with graded and controlled release of ciprofloxacin and BMP-2 nanoparticles for the conception of bone regeneration.

The repair of bone defects using grafts is commonly employed in clinical practice. However, the risk of infection poses a significant concern. Tissue engineering scaffolds with antibacterial functionalities offer a better approach for bone tissue repair. In this work, firstly, two kinds of nanoparticles were prepared using chitosan to complex with ciprofloxacin and BMP-2, respectively. The ciprofloxacin complex nanoparticles improved the dissolution efficiency of ciprofloxacin achieving a potent antibacterial effect and cumulative release reached 95 % in 7 h. For BMP-2 complexed nanoparticles, the release time points can be programmed at 80 h, 100 h or 180 h by regulating the number of coating chitosan layers. Secondly, a functional scaffold was prepared by combining the two nanoparticles with chitosan nanofibers. The microscopic nanofiber structure of the scaffold with 27.28 m2/g specific surface area promotes cell adhesion, high porosity provides space for cell growth, and facilitates drug loading and release. The multifunctional scaffold exhibits programmed release function, and has obvious antibacterial effect at the initial stage of implantation, and releases BMP-2 to promote osteogenic differentiation of mesenchymal stem cells after the antibacterial effect ends. The scaffold is expected to be applied in clinical bone repair and graft infection prevention.

Quantum-noise-limited optical neural networks operating at a few quanta per activation.

A practical limit to energy efficiency in computation is ultimately from noise, with quantum noise [1] as the fundamental floor. Analog physical neural networks [2], which hold promise for improved energy efficiency and speed compared to digital electronic neural networks, are nevertheless typically operated in a relatively high-power regime so that the signal-to-noise ratio (SNR) is large (>10). We study optical neural networks [3] operated in the limit where all layers except the last use only a single photon to cause a neuron activation. In this regime, activations are dominated by quantum noise from the fundamentally probabilistic nature of single-photon detection. We show that it is possible to perform accurate machine-learning inference in spite of the extremely high noise (signal-to-noise ratio ~ 1). We experimentally demonstrated MNIST handwritten-digit classification with a test accuracy of 98% using an optical neural network with a hidden layer operating in the single-photon regime; the optical energy used to perform the classification corresponds to 0.008 photons per multiply-accumulate (MAC) operation, which is equivalent to 0.003 attojoules of optical energy per MAC. Our experiment also used >40× fewer photons per inference than previous state-of-the-art low-optical-energy demonstrations [4, 5] to achieve the same accuracy of >90%. Our training approach, which directly models the system's stochastic behavior, might also prove useful with non-optical ultra-low-power hardware.

Insights into As accumulation in soil-groundwater-wheat-hair system of suburban farmland: Distribution, transfer and potential health risk.

Health risks caused by arsenic (As) contamination in soils and its migration in environmental media have attracted much attention. In this study, suburban farmland of KF city in the ecotone of the Yellow River and Huaihe River Basin was taken as the research area. A series of samples including topsoils (246), profile soils (280), matched wheat grains (22 groups), groundwater (26) and human hair (355) were collected. As distribution and transfer in soil-groundwater-wheat-hair (SGWH) system in typical sites were explored, and comprehensive health risk of As in SGWH system was assessed based on US EPA model and local exposure parameters. The results showed that spatial distribution of total As presented a significant high value area, and higher As contents (in the range of 0.45-29.86 mg kg-1) and bioavailability was mainly in topsoils, which indicated that anthropogenic sources have led to As enrichment in studied area. Also, it was found that the As contents in 95 % of wheat grain samples were higher than that in the control soils, and 9 % groundwater samples were above national Class I standards. Especially, average As content in hair in typical sites was obviously influenced by that in soil, wheat and groundwater. Moreover, As migration curve along soil → wheat (groundwater) → hair appeared an irregular 'V' shape, and transfer coefficients of Tf water/soil (10-5), Tf wheat/soil (10-3), Tf hair/soil (10-2), Tf hair/wheat (101) and Tf hair/water (104) presented an obvious increasing trend of magnitude, implying that human body has a higher As enrichment risk. Furthermore, comprehensive health risks for children and adults in typical sites were significant, while wheat is the main risk medium. In general, arsenic accumulation in human hair is good consistent with EPA health risk model, and their combination can better evaluate environmental exposure risk of As.

An optical neural network using less than 1 photon per multiplication.

Deep learning has become a widespread tool in both science and industry. However, continued progress is hampered by the rapid growth in energy costs of ever-larger deep neural networks. Optical neural networks provide a potential means to solve the energy-cost problem faced by deep learning. Here, we experimentally demonstrate an optical neural network based on optical dot products that achieves 99% accuracy on handwritten-digit classification using ~3.1 detected photons per weight multiplication and ~90% accuracy using ~0.66 photons (~2.5 × 10-19 J of optical energy) per weight multiplication. The fundamental principle enabling our sub-photon-per-multiplication demonstration-noise reduction from the accumulation of scalar multiplications in dot-product sums-is applicable to many different optical-neural-network architectures. Our work shows that optical neural networks can achieve accurate results using extremely low optical energies.

Environmental factors and interactions among microorganisms drive microbial community succession during fermentation of Nongxiangxing daqu.

Nongxiangxing daqu (daqu), which is produced by the open fermentation of wheat, is the fermentation starter of baijiu. This work reports the occurrence and driving factors of microbial community succession (MCS), which determines daqu quality, during daqu fermentation. The co-occurrence networks of the 2 stages of the MCS showed that module 2 of stage P1 contained Mucoromycota and Actinobacteriota and was affected by temperature, humidity, CO2, and moisture; module 8 of stage P2 contained Mucoromycota and Saccharomycetes and was influenced by acidity and moisture. Twenty-two genera were thebiomarkers of the MCS. The MCS was driven by temperature, humidity, CO2, O2, acidity,moisture and interactions between the biomarkes and Lactobacillales, Saccharomycetales, and Acetobacter. The main driving factors of the bacterial community succession were acidity, moisture, and temperature, and that of the fungal community succession was moisture. These results guide the control of MCS during daqu fermentation.

[The role and research progress of IL-17 in the pathogenesis of osteoarthritis].

Osteoarthritis (OA) is one of the most common chronic diseases with complex and varied pathogenic factors. Inflammatory response of diseased joint aggravates the degeneration of cartilage and the destruction of subchondral bone. Interleukin 17 (IL-17) is a multifunctional pro-inflammatory cytokine, which plays a significant role in the inflammation of synovium, the degeneration of cartilage, and the destruction of subchondral bone. This article has reviewed the role of IL-17 in the pathophysiological pathogenesis of OA on the levels of molecules, cells, and tissues, and the progress of targeted therapy based on IL-17 for OA.

MCSM-Wri: A Small-Scale Motion RecognitionMethod Using WiFi Based on Multi-ScaleConvolutional Neural Network.

environmental perception technology based onWiFi, and some state-of-the-art techniques haveemerged. The wide application of small-scale motion recognition has aroused people's concern.Handwritten letter is a kind of small scale motion, and the recognition for small-scale motion basedon WiFi has two characteristics. Small-scale action has little impact on WiFi signals changes inthe environment. The writing trajectories of certain uppercase letters are the same as the writingtrajectories of their corresponding lowercase letters, but they are different in size. These characteristicsbring challenges to small-scale motion recognition. The system for recognizing small-scale motion inmultiple classes with high accuracy urgently needs to be studied. Therefore, we propose MCSM-Wri,a device-free handwritten letter recognition system using WiFi, which leverages channel stateinformation (CSI) values extracted from WiFi packets to recognize handwritten letters, includinguppercase letters and lowercase letters. Firstly, we conducted data preproccessing to provide moreabundant information for recognition. Secondly, we proposed a ten-layers convolutional neuralnetwork (CNN) to solve the problem of the poor recognition due to small impact of small-scaleactions on environmental changes, and it also can solve the problem of identifying actions with thesame trajectory and different sizes by virtue of its multi-scale characteristics. Finally, we collected6240 instances for 52 kinds of handwritten letters from 6 volunteers. There are 3120 instances fromthe lab and 3120 instances are from the utility room. Using 10-fold cross-validation, the accuracyof MCSM-Wri is 95.31%, 96.68%, and 97.70% for the lab, the utility room, and the lab+utility room,respectively. Compared with Wi-Wri and SignFi, we increased the accuracy from 8.96% to 18.13% forrecognizing handwritten letters.

[Impact of cigarette smoking on sperm quality and seminal plasma ROS in preconception males].

OBJECTIVE: To investigate the influence of cigarette smoking on sperm quality and ROS in the seminal plasma of preconception males in Chongqing so as to provide some guidance for preconception couples. METHODS: Totally, 368 preconception males were enrolled in this study, including 196 smokers and 172 non-smokers, and the former divided into mild smokers (n = 88, ≤9 cigarettes per day for ≤5 years) and moderate to heavy smokers (n = 108, ≥10 cigarettes per day for ≥5 years or ≤9 cigarettes per day for ≥10 years). All the subjects underwent physical examination, medical history interview, health questionnaire investigation, and determination of semen parameters, ROS in the seminal plasma and sperm DNA fragmentation index (DFI). RESULTS: Among the 368 preconception males, 53.26% had a history of cigarette smoking, of whom 29.35% were moderate to heavy smokers. Only 55.4% of the subjects were found with normal sperm morphology and 52.6% with normal sperm progressive motility. Compared with the non-smokers, the moderate to heavy smokers showed significantly decreased semen volume (ï¼»3.33 ± 1.20ï¼½ vs ï¼»2.78 ± 1.08ï¼½ ml, P < 0.05), sperm concentration (ï¼»88.19 ± 70.33ï¼½ vs ï¼»75.16 ± 60.13ï¼½ × 106/ml, P < 0.05), and percentages of progressively motile sperm (PMS, ï¼»36.58 ± 13.90ï¼½ % vs ï¼»32.18 ± 15.24ï¼½ %, P < 0.05) and morphologically normal sperm (MNS, ï¼»3.85 ± 1.93ï¼½ % vs ï¼»3.52 ± 1.58ï¼½ %, P < 0.05), but increased sperm DFI (ï¼»10.45 ± 8.53ï¼½ % vs ï¼»14.53 ± 12.85ï¼½ %, P < 0.05) and ROS in the seminal plasma (ï¼»12.20 ± 8.10ï¼½ vs ï¼»24.10 ± 18.50ï¼½ nmol/mg prot, P < 0.05). Cigarette smoking was correlated positively with the ROS level in the seminal plasma (r = 0.235, P < 0.05), while the ROS level of the smokers negatively with the total sperm count (r = －136, P < 0.05), PMS (r = －0.381, P < 0.01) and MNS (r = －0.218, P < 0.01), but positively with sperm DFI in the preconception males (r = 0.387, P < 0.01). CONCLUSIONS: Cigarette smoking can increase the ROS level in the seminal plasma, decrease the total sperm count and sperm progressive motility, and induce sperm malformation and sperm DNA fragmentation in preconception males.

Deactivation by HCl of CeO2-MoO3/TiO2 catalyst for selective catalytic reduction of NO with NH3.

The effect of HCl on a CeO2-MoO3/TiO2 catalyst for the selective catalytic reduction of NO with NH3 was investigated with BET, XRD, NH3-TPD, H2-TPR, XPS and catalytic activity measurements. The results showed that HCl had an inhibiting effect on the activity of the CeO2-MoO3/TiO2 catalyst. The deactivation by HCl of the CeO2-MoO3/TiO2 catalyst could be attributed to pore blockage, weakened interaction among ceria, molybdenum and titania, reduction in surface acidity and degradation of redox ability. The Ce3+/Ce4+ redox cycle was damaged because unreactive Ce3+ in the form of CeCl3 lost the ability to be converted to active Ce4+ in the SCR reaction. In addition, a decrease in the amount of chemisorbed oxygen and the concentrations of surface Ce and Mo was also responsible for the deactivation by HCl of the CeO2-MoO3/TiO2 catalyst.