Graded diagnosis of Helicobacter pylori infection using hyperspectral images of gastric juice.

Helicobacter pylori is a potential underlying cause of many diseases. Although the Carbon 13 breath test is considered the gold standard for detection, it is high cost and low public accessibility in certain areas limit its widespread use. In this study, we sought to use machine learning and deep learning algorithm models to classify and diagnose H. pylori infection status. We used hyperspectral imaging system to gather gastric juice images and then retrieved spectral feature information between 400 and 1000 nm. Two different data processing methods were employed, resulting in the establishment of one-dimensional (1D) and two-dimensional (2D) datasets. In the binary classification task, the random forest model achieved a prediction accuracy of 83.27% when learning features from 1D data, with a specificity of 84.56% and a sensitivity of 92.31%. In the ternary classification task, the ResNet model learned from 2D data and achieved a classification accuracy of 91.48%.

Color-guided deformable convolution network for intestinal metaplasia severity classification using endoscopic images.

Objective. Intestinal metaplasia (IM) is a common precancerous condition for gastric cancer, and the risk of developing gastric cancer increases as IM worsens. However, current deep learning-based methods cannot effectively model the complex geometric structure of IM lesions. To accurately diagnose the severity of IM and prevent the occurrence of gastric cancer, we revisit the deformable convolution network (DCN), propose a novel offset generation method based on color features to guide deformable convolution, named color-guided deformable convolutional network (CDCN).Approach. Specifically, we propose a combined strategy of conventional and deep learning methods for IM lesion areas localization and generating offsets. Under the guidance of offsets, the sample locations of convolutional neural network adaptively adjust to extract discriminate features in an irregular way that conforms to the IM shape.Main results. To verify the effectiveness of CDCN, comprehensive experiments are conducted on the self-constructed IM severity dataset. The experimental results show that CDCN outperforms many existing methods and the accuracy has been improved by 5.39% compared to DCN, reaching 84.17%. Significance. To the best of our knowledge, CDCN is the first method to grade the IM severity using endoscopic images, which can significantly enhance the clinical application of endoscopy, achieving more precise diagnoses.

The cure rate of 10-day bismuth-containing quadruple therapy for Helicobacter pylori eradication is equivalent to 14-day: a systematic review and meta-analysis.

Helicobacter pylori (H. pylori) infection is a major cause of duodenal ulcers, gastric ulcers, and gastric cancer. However, the optimal duration for H. pylori eradication therapy remains controversial. Most studies have mainly focused on triple therapy, and there is insufficient research on bismuth-containing quadruple therapy. The aim of this study was to compare the clinical effect of the 10-day bismuth-containing quadruple treatment regimen with the 14-day regime in eradicating H. pylori. We searched PubMed, Embase, Web of Science, and the Cochrane Library for randomized controlled trials published in English until May 2022 according to the eligibility criteria. Summary risk ratios (RRs) and 95% confidence intervals (CIs) for eradication rates, adverse effects, and compliance were calculated for included studies. Four studies, involving 1173 patients, were eligible for inclusion. The eradication rate was similar in the 10-day treatment group and the 14-day treatment group in the intention-to-treat analysis (RR 0.97, 95% CI 0.93 to 1.01). Meanwhile, the incidence of adverse effects was lower in patients who received 10 days of treatment than in those who received 14 days of treatment and patients' compliance was almost the same between two groups. Compared to the 14-day bismuth-containing quadruple regimens, 10-day regimens had similar efficacy and lower incidence of adverse effects. Therefore, the 10-day regimen is safe and well-tolerated and should be recommended for H. pylori infection.

Efficacy of bismuth for antibiotic-resistant Helicobacter pylori strains eradication: A systematic review and meta-analysis.

BACKGROUND & AIMS: Antibiotic resistance of Helicobacter pylori (H. pylori) is increasing worldwide, and bismuth quadruple therapy has been recommended as a first-line regimen in many areas. This study aimed to investigate whether bismuth would improve the eradication rate (ER) of clarithromycin-/metronidazole-/levofloxacin-resistant H. pylori strains and how much additional efficacy bismuth could achieve. METHODS: PubMed, EMBASE, Web of Science, and Cochrane Central databases for randomized controlled trials were systematically searched by two independent reviewers until 15 January 2022. Pooled ERs of clarithromycin-/metronidazole-/levofloxacin-resistant H. pylori strains were compared between bismuth-containing and non-bismuth therapies. Pooled risk ratios (RRs) with 95% confidence intervals (CIs) were calculated using a random-effects model. RESULTS: Eight studies enrolling 340 individuals were included. The RRs of pooled ERs compared between bismuth-containing and non-bismuth therapies were 1.83 for clarithromycin-resistant strains (95% CI 1.16-2.89, pooled ER: 76.9% vs. 36.6%, p = .009, I2  = 0%), 1.39 for metronidazole-resistant strains (95% CI 1.09-1.78, pooled ER: 86.8% vs. 60.9%, p = .008, I2  = 37%), 2.75 for dual clarithromycin/metronidazole-resistant strains (95% CI 1.01-7.52, pooled ER: 76.9% vs. 18.2%, p = .05, I2  = 0%), and 1.04 for levofloxacin-resistant strains (95% CI 0.56-1.93, pooled ER: 63.4% vs. 54.3%, p = .90; I2  = 60%). Bismuth significantly increased the ERs of clarithromycin-, metronidazole-, and dual-resistant strains by 40%, 26%, and 59%, respectively. Subgroup analysis of treatment duration showed that the significantly higher eradication rate for antibiotic-resistant strains in bismuth-containing therapy than non-bismuth therapy was only observed in 14-day treatment regimens and not in 7-day regimens (p = .02 and .17, respectively). CONCLUSIONS: Bismuth was most effective in improving the ERs of dual-resistant H. pylori strains, followed by clarithromycin- and metronidazole-resistant strains. Prolonged treatment duration might effectively improve the efficacy of bismuth in overcoming antibiotic resistance.

Cause analysis of PM2.5 pollution during the COVID-19 lockdown in Nanning, China.

To analyse the cause of the atmospheric PM2.5 pollution that occurred during the COVID-19 lockdown in Nanning, Guangxi, China, a single particulate aerosol mass spectrometer, aethalometer, and particulate Lidar coupled with monitoring near-surface gaseous pollutants, meteorological conditions, remote fire spot sensing by satellite and backward trajectory models were utilized during 18-24 February 2020. Three haze stages were identified: the pre-pollution period (PPP), pollution accumulation period (PAP) and pollution dissipation period (PDP). The dominant source of PM2.5 in the PPP was biomass burning (BB) (40.4%), followed by secondary inorganic sources (28.1%) and motor vehicle exhaust (11.7%). The PAP was characterized by a large abundance of secondary inorganic sources, which contributed 56.1% of the total PM2.5 concentration, followed by BB (17.4%). The absorption Ångström exponent (2.2) in the PPP was higher than that in the other two periods. Analysis of fire spots monitored by remote satellite sensing indicated that open BB in regions around Nanning City could be one of the main factors. A planetary boundary layer-relative humidity-secondary particle matter-particulate matter positive feedback mechanism was employed to elucidate the atmospheric processes in this study. This study highlights the importance of understanding the role of BB, secondary inorganic sources and meteorology in air pollution formation and calls for policies for emission control strategies.