Dual Channel H2O2 Photosynthesis in Pure Water over S-Scheme Heterojunction Cs3PMo12/CC Boosted by Proton and Electron Reservoirs.

Dual channel photo-driven H2O2 production in pure water on small-scale on-site setups is a promising strategy to provide low-concentrated H2O2 whenever needed. This process suffers, however, strongly from the fast recombination of photo-generated charge carriers and the sluggish oxidation process. Here, insoluble Keggin-type cesium phosphomolybdate Cs3PMo12O40 (abbreviated to Cs3PMo12) is introduced to carbonized cellulose (CC) to construct S-scheme heterojunction Cs3PMo12/CC. Dual channel H2O2 photosynthesis from both H2O oxidation and O2 reduction in pure water has been thus achieved with the production rate of 20.1 mmol L-1 gcat. -1 h-1, apparent quantum yield (AQY) of 2.1% and solar-to-chemical conversion (SCC) efficiency of 0.050%. H2O2 accumulative concentration reaches 4.9 mmol L-1. This high photocatalytic activity is guaranteed by unique features of Cs3PMo12/CC, namely, S-scheme heterojunction, electron reservoir, and proton reservoir. The former two enhance the separation of photo-generated charge carriers, while the latter speeds up the torpid oxidation process. In situ experiments reveal that H2O2 is formed via successive single-electron transfer in both channels. In real practice, exposing the reaction system under natural sunlight outdoors successfully results in 0.24 mmol L-1 H2O2. This work provides a key practical strategy for designing photocatalysts in modulating redox half-reactions in photosynthesis.

Interactions and effects of a stannous-containing sodium fluoride dentifrice on oral pathogens and the oral microbiome.

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.

Real-Time Evaluation of Helicobacter pylori Infection by Convolution Neural Network During White-Light Endoscopy: A Prospective, Multicenter Study (With Video).

INTRODUCTION: Convolutional neural network during endoscopy may facilitate evaluation of Helicobacter pylori infection without obtaining gastric biopsies. The aim of the study was to evaluate the diagnosis accuracy of a computer-aided decision support system for H. pylori infection (CADSS-HP) based on convolutional neural network under white-light endoscopy. METHODS: Archived video recordings of upper endoscopy with white-light examinations performed at Sir Run Run Shaw Hospital (January 2019-September 2020) were used to develop CADSS-HP. Patients receiving endoscopy were prospectively enrolled (August 2021-August 2022) from 3 centers to calculate the diagnostic property. Accuracy of CADSS-HP for H. pylori infection was also compared with endoscopic impression, urea breath test (URT), and histopathology. H. pylori infection was defined by positive test on histopathology and/or URT. RESULTS: Video recordings of 599 patients who received endoscopy were used to develop CADSS-HP. Subsequently, 456 patients participated in the prospective evaluation including 189 (41.4%) with H. pylori infection. With a threshold of 0.5, CADSS-HP achieved an area under the curve of 0.95 (95% confidence interval [CI], 0.93-0.97) with sensitivity and specificity of 91.5% (95% CI 86.4%-94.9%) and 88.8% (95% CI 84.2%-92.2%), respectively. CADSS-HP demonstrated higher sensitivity (91.5% vs 78.3%; mean difference = 13.2%, 95% CI 5.7%-20.7%) and accuracy (89.9% vs 83.8%, mean difference = 6.1%, 95% CI 1.6%-10.7%) compared with endoscopic diagnosis by endoscopists. Sensitivity of CADSS-HP in diagnosing H. pylori was comparable with URT (91.5% vs 95.2%; mean difference = 3.7%, 95% CI -1.8% to 9.4%), better than histopathology (91.5% vs 82.0%; mean difference = 9.5%, 95% CI 2.3%-16.8%). DISCUSSION: CADSS-HP achieved high sensitivity in the diagnosis of H. pylori infection in the real-time test, outperforming endoscopic diagnosis by endoscopists and comparable with URT. Clinicaltrials.gov ; ChiCTR2000030724.

External-Shell Oxygen Enabling the Local Environment Modulation of Unsaturated NbN3 for Efficient Electrosynthesis of Hydrogen Peroxide.

Single-atom catalysts with a tunable coordination structure have shown grand potential in flexibly altering the selectivity of oxygen reduction reaction (ORR) toward the desired pathway. However, rationally mediating the ORR pathway by modulating the local coordination number of the single-metal sites is still challenging. Herein, we prepare the Nb single-atom catalysts (SACs) with an external-shell oxygen-modulated unsaturated NbN3 site in carbon nitride and the NbN4 site anchored in nitrogen-doped carbon carriers, respectively. Compared with typical NbN4 moieties for 4e- ORR, the as-prepared NbN3 SACs exhibit excellent 2e- ORR activity in 0.1 M KOH, with the onset overpotential close to zero (9 mV) and the H2O2 selectivity above 95%, making it one of the state-of-the-art catalysts in the electrosynthesis of hydrogen peroxide. Density functional theory (DFT) theoretical calculations indicate the unsaturated Nb-N3 moieties and the adjacent oxygen groups optimize the interface bond strength of pivotal intermediates (OOH*) for producing H2O2, thus accelerating the 2e- ORR pathway. Our findings may provide a novel platform for developing SACs with high activity and tunable selectivity.

Facile and controllable preparation of carbon microsphere for electro-driven nitrogen reduction: Accommodating nitrogen doping with hierarchical porous structure.

Driven by sustainable electricity, electrochemical nitrogen fixation under ambient conditions is considered as a promising strategy to generate low-concentrated NH3/NH4+. Under the principle of doping and porous engineering, nitrogen-doped carbon microsphere with hierarchical pores (NC-HP) is fabricated via pyrolyzing polymer microsphere. Hierarchical structure with macro-, meso- and micropores is obtained by assembling melamine/phenol-formaldehyde oligomers in Pickering droplets, with the assistance of triblock copolymer Pluronic F127. The regularity of mesopores is strongly affected by melamine to phenol mass ratio. For NC-HP, nitrogen content (N-content) in the carbon matrix can reach as high as 19.1 wt%, yet trade-off effect is observed between N-content and regularity of mesopores. As consequence, NC-HP-3 with N-content of 15.6 wt% and distinct mesopores exhibits the highest catalytic performance. At -0.5 V vs. RHE, NH3/NH4+ production rate and Faradaic efficiency (FE) value reach 15.6 µg∙mgcat.-1∙h-1 and 15.5%, respectively. It shows excellent recyclability, and no degradations are observed with respect to morphology and porous structure. In this hierarchical porous structure, mesopores are expected to facilitate mass transfer for both electrolyte ions and nitrogen, and hence catalytic active sites (e.g. pyrrolic- and pyridinic-N species) in hierarchically mutually connected pores can be well utilized.

An end-to-end tracking method for polyp detectors in colonoscopy videos.

Deep learning based computer-aided diagnosis technology demonstrates an encouraging performance in aspect of polyp lesion detection on reducing the miss rate of polyps during colonoscopies. However, to date, few studies have been conducted for tracking polyps that have been detected in colonoscopy videos, which is an essential and intuitive issue in clinical intelligent video analysis task (e.g. lesion counting, lesion retrieval, report generation). In the paradigm of conventional tracking-by-detection system, detection task for lesion localization is separated from the tracking task for cropped lesions re-identification. In the multi object tracking problem, each target is supposed to be tracked by invoking a tracker after the detector, which introduces multiple inferences and leads to external resource and time consumption. To tackle these problems, we proposed a plug-in module named instance tracking head (ITH) for synchronous polyp detection and tracking, which can be simply inserted into object detection frameworks. It embeds a feature-based polyp tracking procedure into the detector frameworks to achieve multi-task model training. ITH and detection head share the model backbone for low level feature extraction, and then low level feature flows into the separate branches for task-driven model training. For feature maps from the same receptive field, the region of interest head assigns these features to the detection head and the ITH, respectively, and outputs the object category, bounding box coordinates, and instance feature embedding simultaneously for each specific polyp target. We also proposed a method based on similarity metric learning. The method makes full use of the prior boxes in the object detector to provide richer and denser instance training pairs, to improve the performance of the model evaluation on the tracking task. Compared with advanced tracking-by-detection paradigm methods, detectors with proposed ITH can obtain comparative tracking performance but approximate 30% faster speed. Optimized model based on Scaled-YOLOv4 detector with ITH illustrates good trade-off between detection (mAP 91.70%) and tracking (MOTA 92.50% and Rank-1 Acc 88.31%) task at the frame rate of 66 FPS. The proposed structure demonstrates the potential to aid clinicians in real-time detection with online tracking or offline retargeting of polyp instances during colonoscopies.

XDH genotypes through gene-gene interactions with NUDT15 affect azathioprine-induced leukopenia in Chinese patients.

Aim: To investigate whether genotypes of XDH, GMPS and MOCOS were associated with azathioprine-induced adverse drug reaction (ADR) and had the gene-gene interactions with NUDT15 rs116855232 to induce leukopenia. Methods: Patients who had taken azathioprine were recruited. Genotyping of those gene was performed. Risk factor to ADR was analyzed by logistic regression. The generalized multifactor dimensionality reduction (GMDR) was assessed based on gene-gene interactions with ADR. Results: A total of 111 patients were included in this study, all of whom were Han Chinese. XDH rs2295475 was a risk factor of myelotoxicity (p = 0.022). NUDT15 rs116855232 was a risk factor of myelotoxicity, grade ≥2 leukopenia and drug treatment termination (p-values were <0.05). Rs2295475 and rs116855232 had a gene-gene interaction. The model was associated with grade ≥2 leukopenia (OR: 17.99; 95% CI: 4.11-78.81). Conclusion: Combined testing genotype for rs2295475 and rs116855232 could improve the prediction of azathioprine-induced leukopenia.

Research on Fault Diagnosis of Rolling Bearings Based on Variational Mode Decomposition Improved by the Niche Genetic Algorithm.

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.

A Novel Central Camera Calibration Method Recording Point-to-Point Distortion for Vision-Based Human Activity Recognition.

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.

Species-Resolved Metagenomics of Kindergarten Microbiomes Reveal Microbial Admixture Within Sites and Potential Microbial Hazards.

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.

Multi-label recognition of cancer-related lesions with clinical priors on white-light endoscopy.

Deep learning-based computer-aided diagnosis techniques have demonstrated encouraging performance in endoscopic lesion identification and detection, and have reduced the rate of missed and false detections of disease during endoscopy. However, the interpretability of the model-based results has not been adequately addressed by existing methods. This phenomenon is directly manifested by a significant bias in the representation of feature localization. Good recognition models experience severe feature localization errors, particularly for lesions with subtle morphological features, and such unsatisfactory performance hinders the clinical deployment of models. To effectively alleviate this problem, we proposed a solution to optimize the localization bias in feature representations of cancer-related recognition models that is difficult to accurately label and identify in clinical practice. Optimization was performed in the training phase of the model through the proposed data augmentation method and auxiliary loss function based on clinical priors. The data augmentation method, called partial jigsaw, can "break" the spatial structure of lesion-independent image blocks and enrich the data feature space to decouple the interference of background features on the space and focus on fine-grained lesion features. The annotation-based auxiliary loss function used class activation maps for sample distribution correction and led the model to present localization representation converging on the gold standard annotation of visualization maps. The results show that with the improvement of our method, the precision of model recognition reached an average of 92.79%, an F1-score of 92.61%, and accuracy of 95.56% based on a dataset constructed from 23 hospitals. In addition, we quantified the evaluation representation of visualization feature maps. The improved model yielded significant offset correction results for visualized feature maps compared with the baseline model. The average visualization-weighted positive coverage improved from 51.85% to 83.76%. The proposed approach did not change the deployment capability and inference speed of the original model and can be incorporated into any state-of-the-art neural network. It also shows the potential to provide more accurate localization inference results and assist in clinical examinations during endoscopies.

Species-resolved sequencing of low-biomass or degraded microbiomes using 2bRAD-M.

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.

A randomized, controlled comparison of a stannous-containing dentifrice for reducing gingival bleeding and balancing the oral microbiome relative to a positive control.

PURPOSE: To evaluate the effect of a stannous-containing fluoride dentifrice on gingival health and on the composition of the oral microbiome versus a positive control dentifrice over 2 weeks, in a population of healthy adults with self-reported sub-optimal oral health at baseline. METHODS: This was a randomized, controlled, double-blind clinical study. 87 subjects with self-reported sub-optimal oral health at enrollment were randomized to brush twice daily with either an experimental dentifrice (n= 43) or a marketed positive control dentifrice (n= 43), both containing stannous chloride and 0.321% sodium fluoride. All subjects used a soft, manual toothbrush that was provided. The Mazza modification of gingival papillary bleeding Index (Mazza GI) was used to assess gingivitis at baseline and at Week 2. Supragingival plaque was collected for microbiome composition analyses at baseline, Week 1, and Week 2. RESULTS: 83 subjects completed the study. Baseline means were balanced between the treatment groups (P> 0.34). At Week 2, the positive control dentifrice demonstrated a 63.8% statistically significant (P< 0.0001) reduction relative to baseline for Mazza number of gingival bleeding sites. The experimental stannous containing dentifrice provided a comparable 63.5% gingival bleeding reduction versus baseline. There was no significant (P= 0.96) difference between the two dentifrices for either Mazza GI score or number of bleeding sites measured. The microbiome composition analysis at Week 1 found that 28 gingivitis-associated bacterial genera, including Porphyromonas, Tannerella, and Fusobacterium, were significantly inhibited in both dentifrice groups when compared to baseline, while the relative abundance of genera associated with oral health, such as Rothia, Streptococcus, Haemophilus, and Lautropia, was significantly elevated after treatment. These improvements in the oral ecosystem were sustained at Week 2. CLINICAL SIGNIFICANCE: An experimental stannous-containing sodium fluoride dentifrice significantly reduced gingival bleeding comparable to a positive control, and both dentifrices promoted a shift in the oral microbiome towards those genera associated with oral health in a subject population with self-reported sub-optimal oral health at baseline.

Simultaneous Recognition of Atrophic Gastritis and Intestinal Metaplasia on White Light Endoscopic Images Based on Convolutional Neural Networks: A Multicenter Study.

INTRODUCTION: Patients with atrophic gastritis (AG) or gastric intestinal metaplasia (GIM) have elevated risk of gastric adenocarcinoma. Endoscopic screening and surveillance have been implemented in high incidence countries. The study aimed to evaluate the accuracy of a deep convolutional neural network (CNN) for simultaneous recognition of AG and GIM. METHODS: Archived endoscopic white light images with corresponding gastric biopsies were collected from 14 hospitals located in different regions of China. Corresponding images by anatomic sites containing AG, GIM, and chronic non-AG were categorized using pathology reports. The participants were randomly assigned (8:1:1) to the training cohort for developing the CNN model (TResNet), the validation cohort for fine-tuning, and the test cohort for evaluating the diagnostic accuracy. The area under the curve (AUC), sensitivity, specificity, and accuracy with 95% confidence interval (CI) were calculated. RESULTS: A total of 7,037 endoscopic images from 2,741 participants were used to develop the CNN for recognition of AG and/or GIM. The AUC for recognizing AG was 0.98 (95% CI 0.97-0.99) with sensitivity, specificity, and accuracy of 96.2% (95% CI 94.2%-97.6%), 96.4% (95% CI 94.8%-97.9%), and 96.4% (95% CI 94.4%-97.8%), respectively. The AUC for recognizing GIM was 0.99 (95% CI 0.98-1.00) with sensitivity, specificity, and accuracy of 97.9% (95% CI 96.2%-98.9%), 97.5% (95% CI 95.8%-98.6%), and 97.6% (95% CI 95.8%-98.6%), respectively. DISCUSSION: CNN using endoscopic white light images achieved high diagnostic accuracy in recognizing AG and GIM.

[Clinical study of calcium phosphate cement loaded with recombinant human bone morphogenetic protein 2 combined with calcium phosphate cement loaded with antibiotic for chronic osteomyelitis with bone defect].

OBJECTIVE: To compare the effectiveness of calcium phosphate cement (CPC) loaded with recombinant human bone morphogenetic protein 2 (rhBMP-2) combined with CPC loaded with antibiotic versus CPC loaded with antibiotic alone in one stage for chronic osteomyelitis with bone defect. METHODS: A single-blind prospective randomized controlled clinical trial was conducted. Between April 2018 and April 2019, 80 patients of chronic osteomyelitis with bone defect in accordance with the random number table were randomly divided into two groups, 40 in the trial group (CPC loaded with rhBMP-2 combined with CPC loaded with antibiotic) and 40 in the control group (CPC loaded with antibiotic). There was no significant difference in gender, age, disease duration, lesion, and preoperative white blood cells (WBC) count, platelet count, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) between the two groups ( P>0.05). All patients were implanted the corresponding CPC and external fixator after lesion clearance in the two groups. The postoperative WBC count, platelet count, ESR, CRP, hospital stay, cure rate of osteomyelitis, repaired bone defect volume, the time of external fixator removal, and the time of full weight-bearing of the affected limb were compared between the two groups. RESULTS: All patients were followed up 12-24 months, with an average of 18.4 months. There was no significant difference in WBC count, platelet count, ESR, and CRP between the two groups at 4 weeks after operation ( P>0.05). There were significant differences in WBC count, platelet count, and CRP in the two groups between 1 week before operation and 4 weeks after operation ( P<0.05). And the ESR showed no significant difference between pre- and post-operation in the two groups ( P>0.05). In the trial group, the anaphylactic exudate occurred in 1 patient with tibial osteomyelitis and the incision healed after oral administration of loratadine. The incisions of other patients healed by first intention in the two groups. One case of distal tibial osteomyelitis recurred in each group, and 1 case of humeral osteomyelitis recurred in the control group. The cure rates of osteomyelitis were 97.5% (39/40) in the trial group and 95% (38/40) in the control group, showing no significant difference between the two groups ( χ 2 =0.000, P=1.000). There was no significant difference in the repaired bone defect volume and hospital stay between the two groups ( P>0.05). X-ray film and CT showed that the bone defects were repaired in the two groups. The time of external fixator removal and the time of full weight-bearing of the affected limb were significantly shorter in the trial group than in the control group ( P<0.05). CONCLUSION: Application of CPC loaded with rhBMP-2 and antibiotic in one stage is effective for the chronic osteomyelitis with bone defect, which can accelerate the bone regeneration in situ to repair bone defect, reduce the trauma, shorten the course of treatment, and obtain good function of the affected limb.

Longitudinal Multi-omics and Microbiome Meta-analysis Identify an Asymptomatic Gingival State That Links Gingivitis, Periodontitis, and Aging.

Most adults experience episodes of gingivitis, which can progress to the irreversible, chronic state of periodontitis, yet roles of plaque in gingivitis onset and progression to periodontitis remain elusive. Here, we longitudinally profiled the plaque metagenome, the plaque metabolome, and salivary cytokines in 40 adults who transited from naturally occurring gingivitis (NG) to healthy gingivae (baseline) and then to experimental gingivitis (EG). During EG, rapid and consistent alterations in plaque microbiota, metabolites, and salivary cytokines emerged as early as 24 to 72 h after oral-hygiene pause, defining an asymptomatic suboptimal health (SoH) stage of the gingivae. SoH features a swift, full activation of 11 salivary cytokines but a steep synergetic decrease of plaque-derived betaine and Rothia spp., suggesting an anti-gum inflammation mechanism by health-promoting symbionts. Global, cross-cohort meta-analysis revealed, at SoH, a greatly elevated microbiome-based periodontitis index driven by its convergence of both taxonomical and functional profiles toward the periodontitis microbiome. Finally, post-SoH gingivitis development accelerates oral microbiota aging by over 1 year within 28 days, with Rothia spp. depletion and Porphyromonas gingivalis elevation as hallmarks. Thus, the microbiome-defined, transient gum SoH stage is a crucial link among gingivitis, periodontitis, and aging.IMPORTANCE 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. Here, we identified periodontitis-like microbiome dysbiosis in an asymptomatic SoH stage as early as 24 to 72 h after oral-hygiene pause. SoH features a swift, full activation of multiple salivary cytokines but a steep synergetic decrease of plaque-derived betaine and Rothia spp. The microbial ecology during early gingivitis is highly similar to that in periodontitis under both taxonomical and functional contexts. Unexpectedly, exposures to gingivitis can accelerate over 10-fold the normal rate of oral microbiota aging. Our findings underscore the importance of intervening at the SoH stage of gingivitis via proper oral-hygiene practices on a daily basis, so as to maintain a periodontitis-preventive plaque and ensure the healthy aging of the oral ecosystem.

Skin benefits of moisturising body wash formulas for children with atopic dermatitis: A randomised controlled clinical study in China.

BACKGROUND: It acknowledged that skin care is an important part of atopic dermatitis therapy. However, clinical evidences are limited for the best bathing practices, especially the skin health performance of cleansing products on children's atopic dermatitis skin. METHODS: A randomised controlled clinical study was conducted in China among 4- to 18-year-old children with mild-to-moderate atopic dermatitis to evaluate the skin health effect of three cleansing systems (a mild synthetic bar, an ultra-mild body wash with lipids, and an ultra-mild body wash with lipids and zinc pyrithione) by measuring SCORing of Atopic Dermatitis (SCORAD), consumption of topical corticosteroid and the characteristics of microbiome. RESULTS: Increased Staphylococcus aureus abundance and decreased microbial diversity were observed in atopic dermatitis lesion sites compared with healthy control sites. After 4 weeks of treatment, all three treatments showed clinically important improvement from baseline in SCORAD. Four-week corticosteroid consumption was significantly lower for the two body wash groups than the bar group. A significant decrease in S. aureus abundance and increase in microbial diversity were observed in the lesion sites for the two body wash formulas, while the microbial diversity was statistically insignificant for the mild cleansing bar group. However, there were no incremental benefits provided by the body wash formulas based on the assessment of SCORAD. CONCLUSIONS: These results demonstrated the safety and efficacy of using the investigational body wash formulas with lipids in reducing the needs for corticosteroid and improving the healthy composition of skin microbiome vs. the mild synthetic bar soap.

High Accuracy of Convolutional Neural Network for Evaluation of Helicobacter pylori Infection Based on Endoscopic Images: Preliminary Experience.

OBJECTIVES: Application of artificial intelligence in gastrointestinal endoscopy is increasing. The aim of the study was to examine the accuracy of convolutional neural network (CNN) using endoscopic images for evaluating Helicobacter pylori (H. pylori) infection. METHODS: Patients who received upper endoscopy and gastric biopsies at Sir Run Run Shaw Hospital (January 2015-June 2015) were retrospectively searched. A novel Computer-Aided Decision Support System that incorporates CNN model (ResNet-50) based on endoscopic gastric images was developed to evaluate for H. pylori infection. Diagnostic accuracy was evaluated in an independent validation cohort. H. pylori infection was defined by the presence of H. pylori on immunohistochemistry testing on gastric biopsies and/or a positive 13C-urea breath test. RESULTS: Of 1,959 patients, 1,507 (77%) including 847 (56%) with H. pylori infection (11,729 gastric images) were assigned to the derivation cohort, and 452 (23%) including 310 (69%) with H. pylori infection (3,755 images) were assigned to the validation cohort. The area under the curve for a single gastric image was 0.93 (95% confidence interval [CI] 0.92-0.94) with sensitivity, specificity, and accuracy of 81.4% (95% CI 79.8%-82.9%), 90.1% (95% CI 88.4%-91.7%), and 84.5% (95% CI 83.3%-85.7%), respectively, using an optimal cutoff value of 0.3. Area under the curve for multiple gastric images (8.3 ± 3.3) per patient was 0.97 (95% CI 0.96-0.99) with sensitivity, specificity, and accuracy of 91.6% (95% CI 88.0%-94.4%), 98.6% (95% CI 95.0%-99.8%), and 93.8% (95% CI 91.2%-95.8%), respectively, using an optimal cutoff value of 0.4. DISCUSSION: In this pilot study, CNN using multiple archived gastric images achieved high diagnostic accuracy for the evaluation of H. pylori infection.

A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children.

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.