Sputum bacterial microbiota signature as a surrogate for predicting disease progression of nontuberculous mycobacterial lung disease.

OBJECTIVES: Predicting progression of nontuberculous mycobacterial lung disease (NTM-LD) remains challenging. This study evaluated whether sputum bacterial microbiome diversity can be the biomarker and provide novel insights into related phenotypes and treatment timing. METHODS: We analyzed 126 sputum microbiomes of 126 patients with newly diagnosed NTM-LD due to Mycobacterium avium complex, M. abscessus complex, and M. kansasii between May 2020 and December 2021. Patients were followed for 2 years to determine their disease progression status. We identified consistently representative genera that differentiated the progressor and nonprogressor by using six methodologies. These genera were used to construct a prediction model using random forest with 5-fold cross validation. RESULTS: Disease progression occurred in 49 (38.6%) patients. Compared with nonprogressors, α-diversity was lower in the progressors. Significant compositional differences existed in the ß-diversity between groups (p=0.001). The prediction model for NTM-LD progression constructed using seven genera (Burkholderia, Pseudomonas, Sphingomonas, Candidatus Saccharibacteria, Phocaeicola, Pelomonas, and Phascolarctobacterium) with significantly differential abundance achieved an area under curve of 0.871. CONCLUSIONS: Identification of the composition of sputum bacterial microbiome facilitates prediction of the course of NTM-LD, and maybe used to develop precision treatment involving modulating the respiratory microbiome composition to ameliorate NTM-LD.

Intestinal dual-specificity phosphatase 6 regulates the cold-induced gut microbiota remodeling to promote white adipose browning.

Gut microbiota rearrangement induced by cold temperature is crucial for browning in murine white adipose tissue. This study provides evidence that DUSP6, a host factor, plays a critical role in regulating cold-induced gut microbiota rearrangement. When exposed to cold, the downregulation of intestinal DUSP6 increased the capacity of gut microbiota to produce ursodeoxycholic acid (UDCA). The DUSP6-UDCA axis is essential for driving Lachnospiraceae expansion in the cold microbiota. In mice experiencing cold-room temperature (CR) transitions, prolonged DUSP6 inhibition via the DUSP6 inhibitor (E/Z)-BCI maintained increased cecal UDCA levels and cold-like microbiota networks. By analyzing DUSP6-regulated microbiota dynamics in cold-exposed mice, we identified Marvinbryantia as a genus whose abundance increased in response to cold exposure. When inoculated with human-origin Marvinbryantia formatexigens, germ-free recipient mice exhibited significantly enhanced browning phenotypes in white adipose tissue. Moreover, M. formatexigens secreted the methylated amino acid Nε-methyl-L-lysine, an enriched cecal metabolite in Dusp6 knockout mice that reduces adiposity and ameliorates nonalcoholic steatohepatitis in mice. Our work revealed that host-microbiota coadaptation to cold environments is essential for regulating the browning-promoting gut microbiome.

Cordyceps sinensis accelerates stem cell recruitment to human skeletal muscle after exercise.

Cordyceps sinensis is a parasitic fungus known to induce immune responses. The impact of Cordyceps supplementation on stem cell homing and expansion to human skeletal muscle after exercise remains unexplored. In this study, we examined how pre-exercise Cordyceps supplementation influences cell infiltration, CD34+ cell recruitment, and Pax7+ cell expansion in human skeletal muscle after high-intensity interval exercise (HIIE) on a cycloergometer. A randomized, double-blind, placebo-controlled crossover study was conducted with 14 young adults (age: 24 ± 0.8 years). A placebo (1 g cornstarch) and Cordyceps (1 g Cordyceps sinensis) were administered before exercise (at 120% maximal aerobic power). Multiple biopsies were taken from the vastus lateralis for muscle tissue analysis before and after HIIE. This exercise regimen doubled the VEGF mRNA in the muscle at 3 h post-exercise (P = 0.006). A significant necrotic cell infiltration (+284%, P = 0.05) was observed 3 h after HIIE and resolved within 24 h. This response was substantially attenuated by Cordyceps supplementation. Moreover, we observed increases in CD34+ cells at 24 h post-exercise, notably accelerated by Cordyceps supplementation to 3 h (+51%, P = 0.002). This earlier response contributed to a four-fold expansion in Pax7+ cell count, as demonstrated by immunofluorescence double staining (CD34+/Pax7+) (P = 0.01). In conclusion, our results provide the first human evidence demonstrating the accelerated resolution of exercise-induced muscle damage by Cordyceps supplementation. This effect is associated with earlier stem cell recruitment into the damaged sites for muscle regeneration.

DNA oxidation after exercise: a systematic review and meta-analysis.

Purpose: 8-Hydroxy-2'-deoxyguanosine (8-OHdG) is a byproduct of DNA oxidation resulting from free radical attacks. Paradoxically, treatment with 8-OHdG accelerates tissue healing. The aim of this study is to quantify the 8-OHdG response after a single session of exercise in both trained and untrained adults. Methods: A systematic review and meta-analysis of exercise intervention studies measuring changes in blood 8-OHdG following resistance exercise and aerobic exercise were conducted. The literature search included Web of Science, PubMed, BASE, and Scopus, with publications up to February 2023 included. Subgroup analysis of training status was also conducted. Results: Sixteen studies involving 431 participants met the eligibility criteria. Resistance exercise showed a medium effect on increasing circulating 8-OHdG levels (SMD = 0.66, p < 0.001), which was similar for both trained and untrained participants. However, studies on aerobic exercise presented mixed results. For trained participants, a small effect of aerobic exercise on increasing circulating 8-OHdG levels was observed (SMD = 0.42; p < 0.001). In contrast, for untrained participants, a large effect of decreasing circulating 8-OHdG levels was observed, mostly after long-duration aerobic exercise (SMD = -1.16; p < 0.05). Similar to resistance exercise, high-intensity aerobic exercise (5-45 min, ≥75% VO2max) significantly increased circulating 8-OHdG levels, primarily in trained participants. Conclusion: Pooled results from the studies confirm an increase in circulating 8-OHdG levels after resistance exercise. However, further studies are needed to fully confirm the circulating 8-OHdG response to aerobic exercise. Increases in 8-OHdG after high-intensity aerobic exercise are observed only in trained individuals, implicating its role in training adaptation. Systematic Review Registration: [https://Systematicreview.gov/], identifier [CRD42022324180].

Fruits are vehicles of drug-resistant pathogenic Candida tropicalis.

IMPORTANCE: Of 123 identified isolates from the fruit surface, C. tropicalis was the most frequently found species, followed by Meyerozyma caribbica and Candida krusei. All three fluconazole-resistant C. tropicalis were non-susceptible to voriconazole and belonged to the same predominant genotype of azole-resistant C. tropicalis causing candidemia in patients in Taiwan. Our findings provide evidence that fruit should be washed before eaten not only to remove chemicals but also potential drug-resistant pathogenic microbes, especially for immunocompromised individuals. To keep precious treatment options in patients, we not only continuously implement antimicrobial stewardship in hospitals but also reducing/stopping the use of agricultural fungicide classes used in human medicine.

Cost-effective complete genome sequencing using the MinION platform for identification of recombinant enteroviruses.

IMPORTANCE: By employing a cost-effective approach for complete genome sequencing, the study has enabled the identification of novel enterovirus strains and shed light on the genetic exchange events during outbreaks. The success rate of genome sequencing and the scalability of the protocol demonstrate its practical utility for routine enterovirus surveillance. Moreover, the study's findings of recombinant strains of EVA71 and CVA2 contributing to epidemics in Malaysia and Taiwan emphasize the need for accurate detection and characterization of enteroviruses. The investigation of the whole genome and upstream ORF sequences has provided insights into the evolution and spread of enterovirus subgenogroups. These findings have important implications for the prevention, control, and surveillance of enteroviruses, ultimately contributing to the understanding and management of enterovirus-related illnesses.

Senolytic effect of high intensity interval exercise on human skeletal muscle.

p16INK4a expression is a robust biomarker of senescence for stem cells in human tissues. Here we examined the effect of exercise intensity on in vivo senescence in skeletal muscle, using a randomized counter-balanced crossover design. Biopsied vastus lateralis of 9 sedentary men (age 26.1 ± 2.5 y) were assessed before and after a single bout of moderate steady state exercise (SSE, 60% maximal aerobic power) and high intensity interval exercise (HIIE, 120% maximal aerobic power) on a cycloergometer accumulating same amount of cycling work (in kilojoule). Increases in cell infiltration (+1.2 folds), DNA strand break (+1.3 folds), and γ-H2AX+ myofibers (+1.1 folds) occurred immediately after HIIE and returned to baseline in 24 h (p < 0.05). Muscle p16Ink4a mRNA decreased 24 h after HIIE (-57%, p < 0.05). SSE had no effect on cell infiltration, p16Ink4a mRNA, and DNA strand break in muscle tissues. Senescence-lowering effect of HIIE was particularly prominent in the muscle with high pre-exercise p16INK4a expression, suggesting that exercise intensity determines the level of selection pressure to tissue stem cells at late senescent stage in human skeletal muscle. This evidence provides an explanation for the discrepancy between destructive nature of high intensity exercise and its anti-aging benefits.

Traditional chinese god image dataset: A glimpse of chinese culture.

This data article describes a dataset of images of common Chinese deities. The dataset is divided into five categories according to the types of deities, and a total of 1314 original images were captured by smart phones from Chinese temples and through Google search engine. Each category were split into training, validation and test subsets in a ratio of 70:20:10. We rotated the pictures by 30°, 60°, 90°, 120°, 150°, and 180°; and zoomed in and out to augment the images for training and validation sets. After data enhancement, the total number of images reaches 10,786. Two models, EfficientNet-B0 and MobileNetV2, are used to identify five kinds of god images. After data augmentation, the accuracy, precision, recall, specificity and F1-score of EfficientNet-B0 were 96.15%, 96.44%, 96.18%, 96.16% and 97.60%, respectively; the accuracy, precision recall, specificity and F1-score of MobileNetV2 were 92.31%, 92.89%, 92.37%, 92.33% and 95.19%, respectively. This dataset can be used as a reference for traditional Chinese god statue images, and can also be used for object detection and image classification through machine learning and deep learning methods.

Stacking Ensemble and ECA-EfficientNetV2 Convolutional Neural Networks on Classification of Multiple Chest Diseases Including COVID-19.

RATIONALE AND OBJECTIVES: Early detection and treatment of COVID-19 patients is crucial. Convolutional neural networks have been proven to accurately extract features in medical images, which accelerates time required for testing and increases the effectiveness of COVID-19 diagnosis. This study proposes two classification models for multiple chest diseases including COVID-19. MATERIALS AND METHODS: The first is Stacking-ensemble model, which stacks six pretrained models including EfficientNetV2-B0, EfficientNetV2-B1, EfficientNetV2-B2, EfficientNetV2-B3, EfficientNetV2-S and EfficientNetV2-M. The second model is self-designed model ECA-EfficientNetV2 based on ECA-Net and EfficientNetV2. Ten-fold cross validation was performed for each model on chest X-ray and CT images. One more dataset, COVID-CT dataset, was tested to verify the performance of the proposed Stacking-ensemble and ECA-EfficientNetV2 models. RESULTS: The best performance comes from the proposed ECA-EfficientNetV2 model with the highest Accuracy of 99.21%, Precision of 99.23%, Recall of 99.25%, F1-score of 99.20%, and (area under the curve) AUC of 99.51% on chest X-ray dataset; the best performance comes from the proposed ECA-EfficientNetV2 model with the highest Accuracy of 99.81%, Precision of 99.80%, Recall of 99.80%, F1-score of 99.81%, and AUC of 99.87% on chest CT dataset. The differences for five metrics between Stacking-ensemble and ECA-EfficientNetV2 models are not significant. CONCLUSION: Ensemble model achieves better performance than single pretrained models. Compared to the SOTA, Stacking-ensemble and ECA-EfficientNetV2 models proposed in this study demonstrate promising performance on classification of multiple chest diseases including COVID-19.

Distribution and Genomic Characterization of Third-Generation Cephalosporin-Resistant Escherichia coli Isolated from a Single Family and Home Environment: A 2-Year Longitudinal Study.

Third-generation cephalosporin-resistant Escherichia coli (CREC), particularly strains producing extended-spectrum ß-lactamases (ESBLs), are a global concern. Our study aims to longitudinally assemble the genomic characteristics of CREC isolates from fecal samples from an index patient with recurrent CREC-related urinary tract infections and his family and swabs from his home environment 12 times between 2019 and 2021 to investigate the distribution of antibiotic resistance genes. CREC identified using the VITEK 2 were subjected to nanopore whole-genome sequencing (WGS). The WGS of 27 CREC isolates discovered in 137 specimens (1 urine, 123 feces, and 13 environmental) revealed the predominance of ST101 and ST131. Among these sequence types, blaCTX-M (44.4%, n = 12) was the predominant ESBL gene family, with blaCTX-M-14 (n = 6) being the most common. The remaining 15 (55.6%) isolates harbored blaCMY-2 genes and were clonally diverse. All E. coli isolated from the index patient's initial urine and fecal samples belonged to O25b:H4-B2-ST131 and carried blaCTX-M-14. The results of sequence analysis indicate plasmid-mediated household transmission of blaCMY-2 or blaCTX-M-55. A strong genomic similarity was discovered between fecal ESBL-producing E. coli and uropathogenic strains. Furthermore, blaCMY-2 genes were widely distributed among the CREC isolated from family members and their home environment.

Engineered multivalent DNA capsules for multiplexed detection of genotoxicants via versatile controlled release mechanisms.

Assessing the risks associated with genotoxic compounds is challenging because of their complex genotoxicity and the difficulty in the dynamic monitoring of coexisting hazards. In this paper, DNA-assembly-based multistimulus responsive capsules that can detect multiple genotoxic agents simultaneously are presented. By exploiting the sequence- and reactivity-editable properties of DNA, DNA sequences in a DNA shell are designed to exhibit multivalent susceptibility against ultraviolet B radiation, aflatoxin B1, and styrene oxide. Upon exposure to genotoxicants, the developed DNA capsules dissociate because of the production of DNA adducts or aptamer-ligand complex-activated dehybridization, which results in the release of encapsulated fluorophores for a measure of the genotoxicant level. The fluorophore release kinetics for each genotoxicant is investigated. Moreover, the destruction behaviors of the developed capsules are evaluated in binary and ternary toxin mixtures. Multiple linear regression indicates the existence of a strong relationship between the fluorescent response and the genotoxicant level; the result highlights the significance of particular genotoxicant and the antagonistic effect of interacting genotoxic substances on capsule destruction. This DNA architecture allows the monitoring of human exposure to genotoxic agents, which enables the timely adoption of remedial measures, and benefits development of an endogenous genotoxin-responsive drug delivery system.

A lightweight CNN-based network on COVID-19 detection using X-ray and CT images.

BACKGROUND AND OBJECTIVES: The traditional method of detecting COVID-19 disease mainly rely on the interpretation of computer tomography (CT) or X-ray images (X-ray) by doctors or professional researchers to identify whether it is COVID-19 disease, which is easy to cause identification mistakes. In this study, the technology of convolutional neural network is expected to be able to efficiently and accurately identify the COVID-19 disease. METHODS: This study uses and fine-tunes seven convolutional neural networks including InceptionV3, ResNet50V2, Xception, DenseNet121, MobileNetV2, EfficientNet-B0, and EfficientNetV2 on COVID-19 detection. In addition, we proposes a lightweight convolutional neural network, LightEfficientNetV2, on small number of chest X-ray and CT images. Five-fold cross-validation was used to evaluate the performance of each model. To confirm the performance of the proposed model, LightEfficientNetV2 was carried out on three different datasets (NIH Chest X-rays, SARS-CoV-2 and COVID-CT). RESULTS: On chest X-ray image dataset, the highest accuracy 96.50% was from InceptionV3 before fine-tuning; and the highest accuracy 97.73% was from EfficientNetV2 after fine-tuning. The accuracy of the LightEfficientNetV2 model proposed in this study is 98.33% on chest X-ray image. On CT images, the best transfer learning model before fine-tuning is MobileNetV2, with an accuracy of 94.46%; the best transfer learning model after fine-tuning is Xception, with an accuracy of 96.78%. The accuracy of the LightEfficientNetV2 model proposed in this study is 97.48% on CT image. CONCLUSIONS: Compared with the SOTA, LightEfficientNetV2 proposed in this study demonstrates promising performance on chest X-ray images, CT images and three different datasets.

Rapid and Routine Molecular Typing Using Multiplex Polymerase Chain Reaction and MinION Sequencer.

Molecular typing is an essential tool that has been extensively applied in laboratories as well as in clinical settings. Next-generation sequencing technologies promise high-throughput and cost-effective molecular applications; however, the accessibility of these technologies is limited due to the high capital cost. Oxford Nanopore Technologies (ONT) offers a MinION device with the advantages of real-time data analysis, rapid library preparation, and low cost per test. However, the advantages of the MinION device are often overshadowed by its lower raw accuracy. Herein, we present a concise multilocus sequence typing protocol of Staphylococcus aureus using multiplex polymerase chain reaction and Rapid Barcoding Kit for barcoding and MinION device for sequencing. Moreover, to clarify the effects of carryover DNA on tasks that require high sequence accuracy, we used the MinION flow cell in successive runs of washing and reusing. Our results revealed that the MinION flow cell could achieve accurate typing of a total of 467 samples with 3,269 kilobase-long genes within a total of 5 runs. This thus demonstrates the effectiveness of a portable nanopore MinION sequencer in providing accurate, rapid, and routine molecular typing.

High-Integrity Sequencing of Spike Gene for SARS-CoV-2 Variant Determination.

For tiling of the SARS-CoV-2 genome, the ARTIC Network provided a V4 protocol using 99 pairs of primers for amplicon production and is currently the widely used amplicon-based approach. However, this technique has regions of low sequence coverage and is labour-, time-, and cost-intensive. Moreover, it requires 14 pairs of primers in two separate PCRs to obtain spike gene sequences. To overcome these disadvantages, we proposed a single PCR to efficiently detect spike gene mutations. We proposed a bioinformatic protocol that can process FASTQ reads into spike gene consensus sequences to accurately call spike protein variants from sequenced samples or to fairly express the cases of missing amplicons. We evaluated the in silico detection rate of primer sets that yield amplicon sizes of 400, 1200, and 2500 bp for spike gene sequencing of SARS-CoV-2 to be 59.49, 76.19, and 92.20%, respectively. The in silico detection rate of our proposed single PCR primers was 97.07%. We demonstrated the robustness of our analytical protocol against 3000 Oxford Nanopore sequencing runs of distinct datasets, thus ensuring high-integrity sequencing of spike genes for variant SARS-CoV-2 determination. Our protocol works well with the data yielded from versatile primer designs, making it easy to determine spike protein variants.

Image dataset on the Chinese medicinal blossoms for classification through convolutional neural network.

Tree blossoms have been widely used on the prevention and treatment of a variety of diseases in traditional Chinese medicine for thousand years [1,2]. The growth of flowers is not only for their ornamental value, but also for nutritional, medicinal, cooking, cosmetic and aromatic properties. They are a rich source of many compounds, which play an important role in various metabolic processes of the human body [3]. Edible flowers can promote the global demand for more attractive and delicious food, and can improve the nutritional content of gourmet food [4]. Flowers are beneficial for anti-anxiety, anti-cancer, anti-inflammatory, antioxidant, diuretic and immune-modulator, etc. It is very important to identify edible flowers correctly, because only a few are edible [5]. The shapes or colors of different flowers may be very similar. Visual evaluation is one of the classification methods, but it is error-prone and time-consuming [6]. Flowers are divided into flowers from herbaceous plants (flower) and flower trees (blossom). Now there is a public herbaceous flower dataset [7], but lack of dataset for Chinese medicinal blossoms. This article presents and establishes the dataset for twelve most commonly and economically valuable blossoms used in traditional Chinese medicine. The dataset provide a collection of blossom images on traditional Chinese herbs help Chinese pharmacist to classify the categories of Chinese herbs. In addition, the dataset can serve as a resource for researchers who use different algorithms of machine learning or deep learning for image segmentation and image classification.

Identification of a gut microbiota member that ameliorates DSS-induced colitis in intestinal barrier enhanced Dusp6-deficient mice.

Strengthening the gut epithelial barrier is a potential strategy for management of gut microbiota-associated illnesses. Here, we demonstrate that dual-specificity phosphatase 6 (Dusp6) knockout enhances baseline colon barrier integrity and ameliorates dextran sulfate sodium (DSS)-induced colonic injury. DUSP6 mutation in Caco-2 cells enhances the epithelial feature and increases mitochondrial oxygen consumption, accompanied by altered glucose metabolism and decreased glycolysis. We find that Dusp6-knockout mice are more resistant to DSS-induced dysbiosis, and the cohousing and fecal microbiota transplantation experiments show that the gut/fecal microbiota derived from Dusp6-knockout mice also confers protection against colitis. Further culturomics and mono-colonialization experiments show that one gut microbiota member in the genus Duncaniella confers host protection from DSS-induced injury. We identify Dusp6 deficiency as beneficial for shaping the gut microbiota eubiosis necessary to protect against gut barrier-related diseases.

Comparative Pan-Genome Analysis of Oral Veillonella Species.

The genus Veillonella is a common and abundant member of the oral microbiome. It includes eight species, V. atypica, V. denticariosi, V. dispar, V. infantium, V. nakazawae, V. parvula, V. rogosae and V. tobetusensis. They possess important metabolic pathways that utilize lactate as an energy source. However, the overall metabolome of these species has not been studied. To further understand the metabolic framework of Veillonella in the human oral microbiome, we conducted a comparative pan-genome analysis of the eight species of oral Veillonella. Analysis of the oral Veillonella pan-genome revealed features based on KEGG pathway information to adapt to the oral environment. We found that the fructose metabolic pathway was conserved in all oral Veillonella species, and oral Veillonella have conserved pathways that utilize carbohydrates other than lactate as an energy source. This discovery may help to better understand the metabolic network among oral microbiomes and will provide guidance for the design of future in silico and in vitro studies.

Susceptibility of Elizabethkingia spp. to commonly tested and novel antibiotics and concordance between broth microdilution and automated testing methods.

OBJECTIVES: We aimed to determine susceptibilities of Elizabethkingia spp. to 25 commonly tested and 8 novel antibiotics, and to compare the performance of different susceptibility testing methods. METHODS: Clinical isolates of Elizabethkingia spp., Chryseobacterium spp. and Flavobacterium spp. collected during 2002-18 (n = 210) in a nationwide surveillance programme in Taiwan were speciated by 16S rRNA sequencing. MICs were determined by broth microdilution. The broth microdilution results of 18 common antibiotics were compared with those obtained by the VITEK 2 automated system. RESULTS: Among the Elizabethkingia spp. identified (n = 108), Elizabethkingia anophelis was the most prevalent (n = 90), followed by Elizabethkingia meningoseptica (n = 7) and Elizabethkingia miricola cluster [E. miricola (n = 6), Elizabethkingia bruuniana (n = 3) and Elizabethkingia ursingii (n = 2)]. Most isolates were recovered from respiratory or blood specimens from hospitalized, elderly patients. PFGE showed two major and several minor E. anophelis clones. All isolates were resistant to nearly all the tested ß-lactams. Doxycycline, minocycline and trimethoprim/sulfamethoxazole inhibited >90% of Elizabethkingia spp. Rifampin inhibited E. meningoseptica (100%) and E. anophelis (81.1%). Fluoroquinolones and tigecycline were active against E. meningoseptica and E. miricola cluster isolates. Novel antibiotics, including imipenem/relebactam, meropenem/vaborbactam, ceftazidime/avibactam, cefepime/zidebactam, delafloxacin, eravacycline and omadacycline were ineffective but lascufloxacin inhibited half of Elizabethkingia spp. The very major discrepancy rates of VITEK 2 were >1.5% for ciprofloxacin, moxifloxacin and vancomycin. Major discrepancy rates were >3% for amikacin, tigecycline, piperacillin/tazobactam and trimethoprim/sulfamethoxazole. CONCLUSIONS: MDR, absence of standard interpretation criteria and poor intermethod concordance necessitate working guidelines to facilitate future research of emerging Elizabethkingia spp.