Risk factor assessment and microbiome analysis in peritoneal dialysis-related peritonitis reveal etiological characteristics

BackgroundPeritoneal dialysis-related peritonitis (PDRP) is one of the most common complications of peritoneal dialysis (PD). Understanding the risk factors and etiological characteristics is indispensable for infection prevention and improving the outcome and life quality.MethodsA total of 70 PD patients were separated into the PDRP group (n=25) and the control group (n=45). Variables, including gender, age, body mass index, primary diseases, and history of basic diseases, in the two groups were analyzed to assess the risk factors of PDRP. Metagenomic next-generation sequencing (mNGS) and microbial culture were compared in detecting pathogenic microorganisms. Gut microbiota analysis was performed in 35 PDRP patients based on mNGS data.ResultsDialysis time and times of dialysate change were the risk factors of PDRP, and times of dialysate change was the independent risk factor of PDRP (p = 0.046). mNGS produced higher sensitivity (65.79%) than microbial culture (36.84%) in identifying pathogenic microorganisms. Staphylococcus aureus and Klebsiella pneumoniae (four cases) were the most frequent pathogens causing PDRP, followed by Staphylococcus capitis (three cases). β diversity of the gut microbiota was significantly different between patients with fewer times of dialysate change (≤4) and more (>5), as well as between patients with gram-positive (G+) bacterial and gram-negative (G−) bacterial infection.ConclusionThe dialysis time and times of dialysate changes not only are risk factors for peritonitis in PD patients but also stimulate significant changes in the gut microbiome structure in PDRP patients. These findings may provide a novel viewpoint for the management of patients with PDRP

Effects of Pressure, Surfactant Concentration, and Heat Flux on Pool Boiling Using Expanding Microchanneled Surface for Two-Phase Immersion Cooling

Deionized water is replacing fluorinated liquids as the preferred choice for two-phase immersion cooling in data centers. Yet, insufficient bubble removal capability at low saturated pressure is a key challenge hindering the widespread application. To solve this issue, this study employs non-ionic surfactant (Tween 20) and asymmetric structures (expanding microchannel) to enhance the boiling performances of deionized water under sub-atmospheric pressure. The research examines the effects of pressure (8.8~38.5 kPa), surfactant concentration (0.1~0.5 mL/L), and heat flux density (10~180 W/cm2) on the boiling heat transfer characteristics and analyzes the mechanism of unusual temperature oscillations induced by surfactants. It was found that the trade-off between the sub-atmospheric pressure, surface tension coefficient, and reduced static contact angle results in pronounced intermittent boiling on the heated surface. Even with the addition of surfactants, the improvement in heat transfer requires demanding conditions. Boiling enhancement throughout all heat flux conditions was achieved when the surfactant concentration was higher than 0.2 mL/L for the expanding microchanneled surface. The heat transfer coefficient reached 6.89 W·cm−2·K−1 under 8.8 kPa, which was 45% higher than without the surfactant. Under the same heat flux and sub-atmospheric pressure, as the concentration increased from 0.1 to 0.5 mL/L, the amplitudes of temperature fluctuation of the plane surface and expanding microchanneled surface decreased from 10 K to 2 K and 18 K to 1 K, respectively. The onset of nucleate boiling and wall superheat of the expanding microchanneled surface gradually decreased with the increase in surfactant concentration, where the onset of nucleate boiling decreased by 10.54 K. When the heat flux is 160 W/cm2, the wall superheat is reduced by 12.8 K

Detecting Proximal Caries on Periapical Radiographs Using Convolutional Neural Networks with Different Training Strategies on Small Datasets

The present study aimed to evaluate the performance of convolutional neural networks (CNNs) that were trained with small datasets using different strategies in the detection of proximal caries at different levels of severity on periapical radiographs. Small datasets containing 800 periapical radiographs were randomly categorized into a training and validation dataset (n = 600) and a test dataset (n = 200). A pretrained Cifar-10Net CNN was used in the present study. Different training strategies were used to train the CNN model independently; these strategies were defined as image recognition (IR), edge extraction (EE), and image segmentation (IS). Different metrics, such as sensitivity and area under the receiver operating characteristic curve (AUC), for the trained CNN and human observers were analysed to evaluate the performance in detecting proximal caries. IR, EE, and IS recognition modes and human eyes achieved AUCs of 0.805, 0.860, 0.549, and 0.767, respectively, with the EE recognition mode having the highest values (p all p all < 0.05). The CNN trained with the EE strategy, the best performer in the present study, showed potential utility in detecting proximal caries on periapical radiographs when using small datasets

Detecting Proximal Caries on Periapical Radiographs Using Convolutional Neural Networks with Different Training Strategies on Small Datasets

The present study aimed to evaluate the performance of convolutional neural networks (CNNs) that were trained with small datasets using different strategies in the detection of proximal caries at different levels of severity on periapical radiographs. Small datasets containing 800 periapical radiographs were randomly categorized into a training and validation dataset (n = 600) and a test dataset (n = 200). A pretrained Cifar-10Net CNN was used in the present study. Different training strategies were used to train the CNN model independently; these strategies were defined as image recognition (IR), edge extraction (EE), and image segmentation (IS). Different metrics, such as sensitivity and area under the receiver operating characteristic curve (AUC), for the trained CNN and human observers were analysed to evaluate the performance in detecting proximal caries. IR, EE, and IS recognition modes and human eyes achieved AUCs of 0.805, 0.860, 0.549, and 0.767, respectively, with the EE recognition mode having the highest values (p all &lt; 0.05). The EE recognition mode was significantly more sensitive in detecting both enamel and dentin caries than human eyes (p all &lt; 0.05). The CNN trained with the EE strategy, the best performer in the present study, showed potential utility in detecting proximal caries on periapical radiographs when using small datasets.</jats:p

Case report: Application of metagenomic next-generation sequencing in the diagnosis of visceral leishmaniasis and its treatment evaluation

Visceral leishmaniasis is a vector-borne infection by the Leishmania spp., a parasite. Although the overall incidence of visceral leishmaniasis is low, the disease still occurs frequently in some high-risk areas. In our study, two patients were admitted to the hospital with an unprovoked and recurrent high fever, and the condition was not improved after antibiotics administration. Meanwhile, bone marrow aspiration smears failed to find out any pathogen. Finally, Leishmania-specific nucleic acid sequences were successfully detected in the peripheral blood of two patients through metagenomic next-generation sequencing (mNGS), which was further confirmed by bone marrow smear microscopy and antibody tests. After targeted treatment for visceral leishmaniasis in the patients, mNGS reported a decrease in the reads number of Leishmania sequence. The results indicate the feasibility of mNGS in detecting Leishmania spp. in peripheral blood samples. Its therapeutic effect evaluation may be achieved through a comparative analysis of the number of reads before and after the treatment.</jats:p

Epidemiological and clinical characteristics of psittacosis among cases with complicated or atypical pulmonary infection using metagenomic next-generation sequencing: a multi-center observational study in China

Abstract Background Chlamydia psittaci (C. psittaci) causes parrot fever in humans. Development of metagenomic next-generation sequencing (mNGS) enables the identification of C. psittaci. Methods This study aimed to determine the epidemiological and clinical characteristics of parrot fever cases in China. A multi-center observational study was conducted in 44 tertiary and secondary hospitals across 14 provinces and municipalities between April 2019 and October 2021. Results A total of 4545 patients with complicated or atypical pulmonary infection were included in the study, among which the prevalence of C. psittaci was determined to be 2.1% using mNGS. The prevalence of C. psittaci was further determined across demographic groups and types of specimens. It was significantly higher in patients with senior age (2.6% in those > 50 years), winter-spring (3.6%; particularly in December, January, and February), and southwestern (3.4%) and central and southern China (2.7%) (each P  0.05). Conclusion Parrot fever remains low in patients with complicated or atypical pulmonary infection. It is likely to occur in winter-spring and southwestern region in China. BALF may be the optimal specimen in the application of mNGS. Co-infection of multiple microorganisms should be further considered

Image_2_Case report: Application of metagenomic next-generation sequencing in the diagnosis of visceral leishmaniasis and its treatment evaluation.JPEG

Visceral leishmaniasis is a vector-borne infection by the Leishmania spp., a parasite. Although the overall incidence of visceral leishmaniasis is low, the disease still occurs frequently in some high-risk areas. In our study, two patients were admitted to the hospital with an unprovoked and recurrent high fever, and the condition was not improved after antibiotics administration. Meanwhile, bone marrow aspiration smears failed to find out any pathogen. Finally, Leishmania-specific nucleic acid sequences were successfully detected in the peripheral blood of two patients through metagenomic next-generation sequencing (mNGS), which was further confirmed by bone marrow smear microscopy and antibody tests. After targeted treatment for visceral leishmaniasis in the patients, mNGS reported a decrease in the reads number of Leishmania sequence. The results indicate the feasibility of mNGS in detecting Leishmania spp. in peripheral blood samples. Its therapeutic effect evaluation may be achieved through a comparative analysis of the number of reads before and after the treatment.</p

Image_1_Case report: Application of metagenomic next-generation sequencing in the diagnosis of visceral leishmaniasis and its treatment evaluation.JPEG

Visceral leishmaniasis is a vector-borne infection by the Leishmania spp., a parasite. Although the overall incidence of visceral leishmaniasis is low, the disease still occurs frequently in some high-risk areas. In our study, two patients were admitted to the hospital with an unprovoked and recurrent high fever, and the condition was not improved after antibiotics administration. Meanwhile, bone marrow aspiration smears failed to find out any pathogen. Finally, Leishmania-specific nucleic acid sequences were successfully detected in the peripheral blood of two patients through metagenomic next-generation sequencing (mNGS), which was further confirmed by bone marrow smear microscopy and antibody tests. After targeted treatment for visceral leishmaniasis in the patients, mNGS reported a decrease in the reads number of Leishmania sequence. The results indicate the feasibility of mNGS in detecting Leishmania spp. in peripheral blood samples. Its therapeutic effect evaluation may be achieved through a comparative analysis of the number of reads before and after the treatment.</p