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Numerous studies have investigated the effects of stannous ions on specific microbes and their efficacy in reducing dental plaque. Nonetheless, our understanding of their impact on the oral microbiome is still a subject of ongoing exploration. Therefore, this study sought to evaluate the effects of a stannous-containing sodium fluoride dentifrice in comparison to a zinc-containing sodium fluoride dentifrice and a control group on intact, healthy oral biofilms. Utilizing the novel 2bRAD-M approach for species-resolved metagenomics, and FISH/CLSM with probes targeting periodontal and caries associated species alongside Sn2+ and Zn2+ ions, we collected and analyzed in situ biofilms from 15 generally healthy individuals with measurable dental plaque and treated the biofilms with dentifrices to elucidate variations in microbial distribution. Although significant shifts in the microbiome upon treatment were not observed, the use of a stannous-containing sodium fluoride dentifrice primarily led to an increase in health-associated commensal species and decrease in pathogenic species. Notably, FISH/CLSM analysis highlighted a marked reduction in representative species associated with periodontitis and caries following treatment with the use of a stannous-containing sodium fluoride dentifrice, as opposed to a zinc-containing sodium fluoride dentifrice and the control group. Additionally, Sn2+ specific intracellular imaging reflected the colocalization of Sn2+ ions with P. gingivalis but not with other species. In contrast, Zn2+ ions exhibited non-specific binding, thus suggesting that Sn2+ could exhibit selective binding toward pathogenic species. Altogether, our results demonstrate that stannous ions could help to maintain a healthy oral microbiome by preferentially targeting certain pathogenic bacteria to reverse dysbiosis and underscores the importance of the continual usage of such products as a preventive measure for oral diseases and the maintenance of health.

Single molten track (SMT) is the basic unit of the selective laser melting (SLM) process, of which the morphology features and microstructures have great significance on the molding quality. In this study, the effects of laser energy density (LED) on characteristics of SMT were studied with 316 L stainless steel processing by SLM. The results indicate that an optimized range of LED was between 200 and 500 J/mm3, which was the best for SLM process of 316 L leading to beautiful SMT appearance such as continuous uniform water-ridge-like surface, good contour straightness, smooth edges, little adhesive powder, and high densification. The microstructures of the SMT molten pool are mainly composed of equiaxed cellular and columnar dendrites. As the LED decreased, the cellular became smaller and disappeared, while the length and width of columnar crystals even gradually increased. The size of the cellular varies between 0.43 and 1.70 μm with the LEDs increase. The relationship between SMT characteristics and LED found in this work can be readily used to optimize SMT and control the microstructures in situ, and the laser energy density range that the work has identified will simplify most of the guess work in additive manufacturing.

Abstract Microbiome samples with low microbial biomass or severe DNA degradation remain challenging for amplicon-based or whole-metagenome sequencing approaches. Here, we introduce 2bRAD-M, a highly reduced and cost-effective strategy which only sequences ~ 1% of metagenome and can simultaneously produce species-level bacterial, archaeal, and fungal profiles. 2bRAD-M can accurately generate species-level taxonomic profiles for otherwise hard-to-sequence samples with merely 1 pg of total DNA, high host DNA contamination, or severely fragmented DNA from degraded samples. Tests of 2bRAD-M on various stool, skin, environmental, and clinical FFPE samples suggest a successful reconstruction of comprehensive, high-resolution microbial profiles.

Abstract Photo‐driven nitrogen fixation is regarded as a promising sustainable strategy to generate low‐concentration NH3/NH4+. Insoluble SiW11Fe@δ‐Bi2O3 with “core–shell” structure and Z‐scheme featured heterojunction is constructed under solvothermal conditions. Chemisorption of nitrogen improves significantly due to increased oxygen vacancies on δ‐Bi2O3 as induced by insoluble SiW11Fe salt. Z‐scheme heterojunction is suggested according to energy diagram analyses and electron paramagnetic resonance spin‐trapping experiments, which can be well correlated to enhanced transient photocurrent and catalytic efficacy. [Ru(bpy)3]2+ counter ion in the composite acts as a photosensitizer, leading to improved light harvesting. These merits account for superior performance of Ru2.5SiW11Fe@δ‐Bi2O3. NH3/NH4+ production rate of 121 µmol gcat−1 h−1 is achieved under simulated sunlight irradiation in nitrogen atmosphere, but reduces on switching to air. The impact of oxygen over nitrogen reduction is investigated, and productions of both NH3/NH4+ and H2O2 are evaluated when using gas mixture feedstock with different V(N2):V(O2) ratios. The performance of nitrogen reduction depends mainly on its volume ratio in mixture feedstock, in addition to reduction capability of photocatalyst. By reducing the latter one appropriately, nitrogen reduction would be slightly favored when using air as feedstock.

Microbiomes on surfaces in kindergartens, the intermediate transfer medium for microbial exchange, can exert significant impact on the hygiene and wellbeing of young children, both individually and as a community. Here employing 2bRAD-M, a novel species-resolved metagenomics approach for low-biomass microbiomes, we surveyed over 100 samples from seven frequently contacted surfaces by children, plus individual children’s palms, in two kindergartens. Microbiome compositions, although kindergarten-specific, were grouped closely based on the type of surface within each kindergarten. Extensive microbial admixture were found among the various sampled sites, likely facilitated by contact with children’s hands. Notably, bacterial species with potential human health concerns and potentially antibiotic-resistant, although found across all sampled locations, were predominantly enriched on children’s hands instead of on the environmental sites. This first species-resolved kindergarten microbiome survey underscores the importance of good hand hygiene practices in kindergartens and provides insights into better managing hygiene levels and minimizing spread of harmful microbes in susceptible indoor environments.

The Dabei deep high-pressure condensate gas field occupies the paramount position in the Tarim Oilfield in China, the exploration and developments of which have been progressing. Since the initial development, the wax deposition and plugging in the wellbore and gathering pipeline have been the most bothering issues, resulting in the reduction or even shutdown of condensate gas well production. Therefore, the wax appearance temperature of Dabei condensate oil was studied using the capillary viscometer, differential scanning calorimetry (DSC), and polarizing microscope observation. The wax content was tested by using the DSC and crystallization separation test method. Finally, the wax appearance temperatures of degassed condensate oil and equilibrium condensate oil under different pressures were tested. Experimental results show that the wax appearance temperature measured by polarizing microscope observation was higher than that measured by the DSC and capillary viscometer, the lag of which can be recorded as the cloud point. The wax appearance temperature measured by polarizing microscope observation is of high accuracy. Secondly, the DSC method is not sufficient for measuring wax precipitation at low temperatures, showing a lower wax content than the crystallization separation test method. Thus, the wax content of Dabei condensate oil can be better measured by using the crystallization separation test method. Additionally, the wax precipitation law of equilibrium condensate oil is opposite to that of degassed condensate oil. The wax appearance temperature of equilibrium condensate oil increases as the pressure decreases. The results of wax appearance temperature of equilibrium condensate oil provide a useful and quick index to judge the potential risk of wax precipitation in the Tarim Oilfield, which can provide an efficient strategy for the development of waxy condensate gas reservoirs and the optimization of wax prevention and treatment technology.

Due to the influence of signal-to-noise ratio in the early failure stage of rolling bearings in rotating machinery, it is difficult to effectively extract feature information. Variational Mode Decomposition (VMD) has been widely used to decompose vibration signals which can reflect more fault omens. In order to improve the efficiency and accuracy, a method to optimize VMD by using the Niche Genetic Algorithm (NGA) is proposed in this paper. In this method, the optimal Shannon entropy of modal components in a VMD algorithm is taken as the optimization objective, by using the NGA to constantly update and optimize the combination of influencing parameters composed of α and K so as to minimize the local minimum entropy. According to the obtained optimization results, the optimal input parameters of the VMD algorithm were set. The method mentioned is applied to the fault extraction of a simulated signal and a measured signal of a rolling bearing. The decomposition process of the rolling-bearing fault signal was transferred to the variational frame by the NGA-VMD algorithm, and several eigenmode function components were obtained. The energy feature extracted from the modal component containing the main fault information was used as the input vector of a particle swarm optimized support vector machine (PSO-SVM) and used to identify the fault type of the rolling bearing. The analysis results of the simulation signal and measured signal show that: the NGA-VMD algorithm can decompose the vibration signal of a rolling bearing accurately and has a better robust performance and correct recognition rate than the VMD algorithm. It can highlight the local characteristics of the original sample data and reduce the interference of the parameters selected artificially in the VMD algorithm on the processing results, improving the fault-diagnosis efficiency of rolling bearings.

The camera is the main sensor of vison-based human activity recognition, and its high-precision calibration of distortion is an important prerequisite of the task. Current studies have shown that multi-parameter model methods achieve higher accuracy than traditional methods in the process of camera calibration. However, these methods need hundreds or even thousands of images to optimize the camera model, which limits their practical use. Here, we propose a novel point-to-point camera distortion calibration method that requires only dozens of images to get a dense distortion rectification map. We have designed an objective function based on deformation between the original images and the projection of reference images, which can eliminate the effect of distortion when optimizing camera parameters. Dense features between the original images and the projection of the reference images are calculated by digital image correlation (DIC). Experiments indicate that our method obtains a comparable result with the multi-parameter model method using a large number of pictures, and contributes a 28.5% improvement to the reprojection error over the polynomial distortion model.

Abstract Background Even though human sweat is odorless, bacterial growth and decomposition of specific odor precursors in it is believed to give rise to body odor in humans. While mechanisms of odor generation have been widely studied in adults, little is known for teenagers and pre-pubescent children who have distinct sweat composition from immature apocrine and sebaceous glands, but are arguably more susceptible to the social and psychological impact of malodor. Results We integrated information from whole microbiome analysis of multiple skin sites (underarm, neck, and head) and multiple time points (1 h and 8 h after bath), analyzing 180 samples in total to perform the largest metagenome-wide association study to date on malodor. Significant positive correlations were observed between odor intensity and the relative abundance of Staphylococcus hominis, Staphylococcus epidermidis, and Cutibacterium avidum, as well as negative correlation with Acinetobacter schindleri and Cutibacterium species. Metabolic pathway analysis highlighted the association of isovaleric and acetic acid production (sour odor) from enriched S. epidermidis (teen underarm) and S. hominis (child neck) enzymes and sulfur production from Staphylococcus species (teen underarm) with odor intensity, in good agreement with observed odor characteristics in pre-pubescent children and teenagers. Experiments with cultures on human and artificial sweat confirmed the ability of S. hominis and S. epidermidis to independently produce malodor with distinct odor characteristics. Conclusions These results showcase the power of skin metagenomics to study host-microbial co-metabolic interactions, identifying distinct pathways for odor generation from sweat in pre-pubescent children and teenagers and highlighting key enzymatic targets for intervention.

A significant portion of world population still fails to brush teeth daily. As a result, the majority of the global adult population is afflicted with chronic gingivitis, and if it is left untreated, some of them will eventually suffer from periodontitis.

With the increasing market demand for artificial hip joints, total hip joint replacement has gradually become an effective means of treating a series of hip joint diseases. In order to improve the service life of artificial hip joints, some new artificial hip joint materials, including polyetheretherketone (PEEK) and carbon fiber reinforced polyetheretherketone (CFR-PEEK), have been developed. In this paper, pin-on-plate wear tests under different cross-shear ratios and contact pressures were carried out to study the wear mechanism and worn surface topography of PEEK and CFR-PEEK. The experimental results showed that the wear of PEEK was associated with cross-shear, while CFR-PEEK was not. When the cross-shear ratio was 0.039 and contact pressure was 3.18 MPa, PEEK had poor wear resistance and its wear factor was about eight times that of ultra-high molecular weight polyethylene (UHMWPE). The wear resistance of CFR-PEEK had a significant advantage, since its wear factor was about 30% of that of PEEK. The wear factors of PEEK and CFR-PEEK increased as the contact pressure increased. The arithmetic average of the height amplitude of the surface, Sa, also increased gradually according to the topography of the worn surface. The wear mechanisms of PEEK and CFR-PEEK were scratching, plough cutting, and abrasion Since CFR-PEEK had good wear resistance and insensitivity to cross-shear motion, it is suitable for making artificial hip joints under low contact pressure condition.

Esophagogastroduodenoscopy (EGD) is a critical step in the diagnosis of upper gastrointestinal disorders. However, due to inexperience or high workload, there is a wide variation in EGD performance by endoscopists. Variations in performance may result in exams that do not completely cover all anatomical locations of the stomach, leading to a potential risk of missed diagnosis of gastric diseases. Numerous guidelines or expert consensus have been proposed to assess and optimize the quality of endoscopy. However, there is a lack of mature and robust methods to accurately apply to real clinical real-time video environments. In this paper, we innovatively define the problem of recognizing anatomical locations in videos as a multi-label recognition task. This can be more consistent with the model learning of image-to-label mapping relationships. We propose a combined structure of a deep learning model (GL-Net) that combines a graph convolutional network (GCN) with long short-term memory (LSTM) networks to both extract label features and correlate temporal dependencies for accurate real-time anatomical locations identification in gastroscopy videos. Our methodological evaluation dataset is based on complete videos of real clinical examinations. A total of 29,269 images from 49 videos were collected as a dataset for model training and validation. Another 1736 clinical videos were retrospectively analyzed and evaluated for the application of the proposed model. Our method achieves 97.1% mean accuracy (mAP), 95.5% mean per-class accuracy and 93.7% average overall accuracy in a multi-label classification task, and is able to process these videos in real-time at 29.9 FPS. In addition, based on our approach, we designed a system to monitor routine EGD videos in detail and perform statistical analysis of the operating habits of endoscopists, which can be a useful tool to improve the quality of clinical endoscopy.

Abstract Clavibacter michiganensis subsp. michiganensis (Cmm), which is a Gram positive bacterium, causes the bacterial canker of tomato disease. The purpose of the study was to evaluate the antibacterial activity of Polygonum orientale extracts against Cmm. In this study, firstly, effects of three extracting parameters (extractive time, extractive temperature, and solid to liquid ratio) of orthogonal experiment design L27 (313) were conducted. Secondly, survival rate was determined and inhibition zone of Cmm rescued post-stress was monitored. Finally, extracellular OD260nm value, extracellular protein content, conformational structure of membrane protein, extracellular alkaline phosphatase (AKP) activity, and ATPase activity were measured to investigate the antibacterial mechanism. Results of orthogonal experiment revealed that extractive time and extractive temperature had highly significant (P

Retrograde intrarenal surgery (RIRS) is a minimally invasive endoscopic procedure for the treatment of kidney stones. Traditionally, RIRS is usually performed by reconstructing a 3D model of the kidney from preoperative CT images in order to locate the kidney stones; then, the surgeon finds and removes the stones with experience in endoscopic video. However, due to the many branches within the kidney, it can be difficult to relocate each lesion and to ensure that all branches are searched, which may result in the misdiagnosis of some kidney stones. To avoid this situation, we propose a convolutional neural network (CNN)-based method for matching preoperative CT images and intraoperative videos for the navigation of ureteroscopic procedures. First, a pair of synthetic images and depth maps reflecting preoperative information are obtained from a 3D model of the kidney. Then, a style transfer network is introduced to transfer the ureteroscopic images to the synthetic images, which can generate the associated depth maps. Finally, the fusion and matching of depth maps of preoperative images and intraoperative video images are realized based on semantic features. Compared with the traditional CT-video matching method, our method achieved a five times improvement in time performance and a 26% improvement in the top 10 accuracy.

ABSTRACT A quantitative and objective indicator for skin health via the microbiome is of great interest for personalized skin care, but differences among skin sites and across human populations can make this goal challenging. A three-city (two Chinese and one American) comparison of skin microbiota from atopic dermatitis (AD) and healthy pediatric cohorts revealed that, although city has the greatest effect size (the skin microbiome can predict the originated city with near 100% accuracy), a microbial index of skin health (MiSH) based on 25 bacterial genera can diagnose AD with 83 to ∼95% accuracy within each city and 86.4% accuracy across cities (area under the concentration-time curve [AUC], 0.90). Moreover, nonlesional skin sites across the bodies of AD-active children (which include shank, arm, popliteal fossa, elbow, antecubital fossa, knee, neck, and axilla) harbor a distinct but lesional state-like microbiome that features relative enrichment of Staphylococcus aureus over healthy individuals, confirming the extension of microbiome dysbiosis across body surface in AD patients. Intriguingly, pretreatment MiSH classifies children with identical AD clinical symptoms into two host types with distinct microbial diversity and treatment effects of corticosteroid therapy. These findings suggest that MiSH has the potential to diagnose AD, assess risk-prone state of skin, and predict treatment response in children across human populations. IMPORTANCE MiSH, which is based on the skin microbiome, can quantitatively assess pediatric skin health across cohorts from distinct countries over large geographic distances. Moreover, the index can identify a risk-prone skin state and compare treatment effect in children, suggesting applications in diagnosis and patient stratification.

Computer-aided polyp detection in gastric gastroscopy has been the subject of research over the past few decades. However, despite significant advances, automatic polyp detection in real time is still an unsolved problem. In this paper, we report on a convolutional neural network (CNN) for polyp detection that is constructed based on Single Shot MultiBox Detector (SSD) architecture and which we call SSD for Gastric Polyps (SSD-GPNet). To take full advantages of feature maps' information from the feature pyramid and to acquire higher accuracy, we re-use information that is abandoned by Max-Pooling layers. In other words, we reuse the lost data from the pooling layers and concatenate that data as extra feature maps to contribute to classification and detection. Meanwhile, in the feature pyramid, we concatenate feature maps of the lower layers and feature maps that are deconvolved from upper layers to make explicit relationships between layers and to effectively increase the number of channels. The results show that our enhanced SSD for gastric polyp detection can realize real-time polyp detection with 50 frames per second (FPS) and can improve the mean average precision (mAP) from 88.5% to 90.4%, with only a little loss in time-performance. And the further experiment shows that SSD-GPNet has excellent performance in improving polyp detection recalls over 10% (p = 0.00053), especially in small polyp detection. This can help endoscopic physicians more easily find missed polyps and decrease the gastric polyp miss rate. It may be applicable in daily clinical practice to reduce the burden on physicians.

Gastric precancerous diseases (GPD) may deteriorate into early gastric cancer if misdiagnosed, so it is important to help doctors recognize GPD accurately and quickly. In this paper, we realize the classification of 3-class GPD, namely, polyp, erosion, and ulcer using convolutional neural networks (CNN) with a concise model called the Gastric Precancerous Disease Network (GPDNet). GPDNet introduces fire modules from SqueezeNet to reduce the model size and parameters about 10 times while improving speed for quick classification. To maintain classification accuracy with fewer parameters, we propose an innovative method called iterative reinforced learning (IRL). After training GPDNet from scratch, we apply IRL to fine-tune the parameters whose values are close to 0, and then we take the modified model as a pretrained model for the next training. The result shows that IRL can improve the accuracy about 9% after 6 iterations. The final classification accuracy of our GPDNet was 88.90%, which is promising for clinical GPD recognition.

Image registration is a key component of computer assistance in image guided surgery, and it is a challenging topic in endoscopic environments. In this study, we present a method for image registration named Homographic Patch Feature Transform (HPFT) to match gastroscopic images. HPFT can be used for tracking lesions and augmenting reality applications during gastroscopy. Furthermore, an overall evaluation scheme is proposed to validate the precision, robustness and uniformity of the registration results, which provides a standard for rejection of false matching pairs from corresponding results. Finally, HPFT is applied for processing in vivo gastroscopic data. The experimental results show that HPFT has stable performance in gastroscopic applications.