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The Mycobacterium tuberculosis (Mtb) pathogen, the causative agent of the airborne infection tuberculosis (TB), harbors a number of mycobacterial membrane protein large (MmpL) transporters. These membrane proteins can be separated into 2 distinct subclasses, where they perform important functional roles, and thus, are considered potential drug targets to combat TB. Previously, we reported both X-ray and cryo-EM structures of the MmpL3 transporter, providing high-resolution structural information for this subclass of the MmpL proteins. Currently, there is no structural information available for the subclass associated with MmpL4 and MmpL5, transporters that play a critical role in iron homeostasis of the bacterium. Here, we report cryo-EM structures of the M. smegmatis MmpL4 and MmpL5 transporters to resolutions of 2.95 Å and 3.00 Å, respectively. These structures allow us to propose a plausible pathway for siderophore translocation via these 2 transporters, an essential step for iron acquisition that enables the survival and replication of the mycobacterium. Mycobacterium tuberculosis bacteria express several MmpL membrane protein transporters that are critical for the export of lipid components for cell wall biogenesis. These authors solve the first cryo-EM structures of the subclass I MmpL4 and MmpL5 proteins, providing insights into substrate translocation. [ABSTRACT FROM AUTHOR]

The band 3 transporter is a critical integral membrane protein of the red blood cell (RBC), as it is responsible for catalyzing the exchange of bicarbonate and chloride anions across the plasma membrane. To elucidate the structural mechanism of the band 3 transporter, detergent solubilized human ghost membrane reconstituted in nanodiscs was applied to a cryo-EM holey carbon grid to define its composition. With this approach, we identified and determined structural information of the human band 3 transporter. Here, we present 5 different cryo-EM structures of the transmembrane domain of dimeric band 3, either alone or bound with chloride or bicarbonate. Interestingly, we observed that human band 3 can form both symmetric and asymmetric dimers with a different combination of outward-facing (OF) and inward-facing (IF) states. These structures also allow us to obtain the first model of a human band 3 molecule at the IF conformation. Based on the structural data of these dimers, we propose a model of ion transport that is in favor of the elevator-type mechanism. Previous studies have solved the high-resolution structures of the dimeric band 3 transporter, but the ion transport mechanism has not yet been fully elucidated. This study solves several cryo-EM structures of band 3 in different conformations indicating that the ion transport mechanism involves the concerted movement of chloride and bicarbonate ions. [ABSTRACT FROM AUTHOR]

ESX‐3 is a secretion pathway which is essential for mycobactin‐mediated iron acquisition under iron‐limited conditions. Although present in all Mycobacterium sp., ESX‐3 remains to be elucidated in Mycobacterium abscessus. In the study reported here, impaired ESX‐3 seriously restricts the growth of M. abscesses under iron‐limited conditions; growth is salvaged by functional ESX‐3 or iron supplementation. Notably, impaired ESX‐3 does not kill M. abscesses when environmental iron is insufficient but induces persistence to bedaquiline, a diarylquinoline class antibiotic used to treat multidrug‐resistant mycobacteria. One potential mechanism contributing to persistence is the iron deficiency due to impaired ESX‐3 suppressing succinate dehydrogenase activity, which dysregulates the tricarboxylic acid cycle and inactivates bedaquiline. Experiments conducted here also demonstrate that the regulator, MtrA, can bind ESX‐3 and promote the survival of M. abscessus. As such, this study suggests that a novel pathway involving MtrA, ESX‐3, iron metabolism, and the TCA cycle contributes to bedaquiline persistence in M. abscesses growing under iron‐limited conditions. [ABSTRACT FROM AUTHOR]

In lung cancer diagnosis, folate receptor (FR)–based circulating tumor cell (CTC) has shown its ability to distinguish malignancy from benign disease to some extent. However, there are still some patients that cannot be identified by FR‐based CTC detection. And studies comparing the characteristics between true positive (TP) and false negative (FN) patients are few. Thus, the study comprehensively analyzes the clinicopathological characteristics of FN and TP patients in the current study. According to inclusion and exclusion criteria, 3420 patients are enrolled. Combining the pathological diagnosis with CTC results, patients are divided into FN and TP groups, and clinicopathological characteristics are compared between two groups. Compared with TP patients, FN patients have smaller tumor, early T stage, early pathological stage, and without lymph node metastasis. Epidermal growth factor receptor (EGFR) mutation status is different between FN and TP group. And this result is also demonstrated in lung adenocarcinoma subgroup but not in lung squamous cell carcinoma subgroup. Tumor size, T stage, pathological stage, lymph node metastasis, and EGFR mutation status may influence the accuracy of FR‐based CTC detection in lung cancer. However, further prospective studies are needed to confirm the findings. [ABSTRACT FROM AUTHOR]

To evaluate the safety, tolerability, and efficacy of prolonged bedaquiline (Bdq) treatment in patients with multi-drug/rifampin-resistant tuberculosis (MDR/RR-TB).Methods: This prospective cohort study was performed from August 2018 to August 2021. Patients diagnosed with MDR/RR-TB who met the inclusion criteria were prospectively included. Patients were treated with individual regimens of 18– 20 months containing Bdq for six months or a prolonged course of nine or 12 months according to treatment demands, and the efficacy and safety with a different course of Bdq-containing regimens were compared and evaluated.Results: A total of 159 MDR/RR-TB patients were included in the study, including 96 cases with six months of Bdq, 50 cases with nine months of Bdq, and 13 patients with 12 months of Bdq. The treatment success rates were 89.6%, 90%, and 84.6% in Bdq at six months, nine months, and 12 months, respectively, which were not statistically different (P = 0.85). The main adverse events (AEs) were anemia, thrombocytopenia, and liver dysfunction in all patients, with no significant difference among the three groups. Patients who had fewer drugs chosen, disseminated lesions or lesions that were slowly absorbed, and severe cavities were the common reasons for prolonged use of Bdq.Conclusion: Prolonged course use of Bdq from six months to 12 months clinically proved to be safe and efficient, and patients with severe or disseminated lesions had the chance to prolong the use of Bdq for more than six months to achieve optimal treatment outcomes. [ABSTRACT FROM AUTHOR]

Background: During infection, Mycobacterium abscessus encounters numerous environmental changes and adapts to them using a variety of complex mechanisms. Non‐coding small RNAs (sRNAs) have been shown in other bacteria to be involved in post‐transcriptional regulatory pathways, including environmental stress adaptation. However, the potential role of sRNAs in the resistance to oxidative stress in M. abscessus was not clearly described. Methods: In the present study, we analyzed putative sRNAs identified by RNA‐sequencing (RNA‐seq) experiments in M. abscessus ATCC_19977 under oxidative stress, and the transcription profiles of sRNAs with differential expression were verified by quantitative reverse transcription‐PCR (qRT‐PCR). Six sRNA overexpression strains were constructed, and the differences in growth curves between these strains and the control strain were verified. An upregulated sRNA under oxidative stress was selected and named sRNA21. The survival ability of the sRNA21 overexpression strain was assessed, and computer‐based approaches were used to predict the targets and pathways regulated by sRNA21. The total ATP production and NAD+/NADH ratio of the sRNA21 overexpression strain were measured. The expression level of antioxidase‐related genes and the activity of antioxidase were tested to confirm the interaction of sRNA21 with the predicted target genes in silico. Results: In total, 14 putative sRNAs were identified under oxidative stress, and the qRT‐PCR analysis of six sRNAs showed comparable results to RNA‐seq assays. Overexpression of sRNA21 in M. abscessus increased cell growth rate and intracellular ATP level before and after peroxide exposure. The expression of genes encoding alkyl hydroperoxidase and superoxide dismutase was significantly increased, and superoxide dismutase activity was enhanced in the sRNA21 overexpression strain. Meanwhile, after sRNA21 overexpression, the intracellular NAD+/NADH ratio decreased, indicating changes in redox homeostasis. Conclusions: Our findings show that sRNA21 is an oxidative stress‐induced sRNA that increases M. abscessus survival and promotes the expression of antioxidant enzymes under oxidative stress. These findings may provide new insights into the adaptive transcriptional response of M. abscessus to oxidative stress. [ABSTRACT FROM AUTHOR]

The thermal protection performance of fire suit is vital to the safety of firefighters. Using certain physical properties of fabrics to evaluate their thermal protection performance speeds up the process. This work aims to develop a TPP value prediction model that can be easily applied. Five properties of three types of Aramid 1414 made of the same material were tested, and the relationships between the physical properties of Aramid 1414 and its thermal protection performance (TPP value) were investigated. The results showed that the TPP value of the fabric had a positive correlation with grammage and air gap, and a negative correlation with the underfill factor. A stepwise regression analysis was used to solve the collinearity issue between the independent variables. Finally, a model for predicting TPP value by air gap and underfill factor was developed. The method adopted in this work reduced the number of independent variables in the prediction model, which is conducive to the application of the model. [ABSTRACT FROM AUTHOR]

The antibiotic options available for Mycobacterium abscessus (M. abscessus) infection are limited and no definitive therapeutic strategies have been formulated. The recent discovery that rifabutin is active against M. abscessus has raised interest in using rifabutin to treat this intractable disease. In this study, we evaluated the in vitro activity of rifabutin against 194 M. abscessus clinical isolates collected during 2012 January to 2017 December. As expected, rifabutin demonstrated considerably lower MICs against M. abscessus, with an MIC50 of 2 μg/mL and MIC90 of 4 μg/mL, respectively. Notably, the anti‐M.abscessus activity was even stronger among clarithromycin‐insusceptible strains. In addition, M. abscessus isolates with a rough morphotype were more sensitive to rifabutin compared with those forming smooth colonies when considered as a whole or in separate subspecies. Results from synergistic experiments revealed that the in vitro activity of rifabutin was significantly enhanced by the addition of amikacin, suggesting a promising strategy for M. abscessus infection combination treatment. Finally, five and three mutation patterns in rpoB and arr, respectively, were identified among the 194 strains through whole genome sequencing. However, none of them conferred rifabutin resistance. Our study is among the first to report the susceptibility of M. abscessus to rifabutin in vitro with a large amount of clinical isolates, suggesting that rifabutin is active, both alone and in combination, against M. abscessus and is worth considering as part of a combination treatment regimen for M. abscessus infections. [ABSTRACT FROM AUTHOR]

Sepsis is a global health care issue that affects millions of people. DNA methyltransferase I (DNMT1)-mediated DNA methylation is involved in a number of human diseases by affecting many types of cellular progression events. However, the role and underlying molecular mechanism of DNMT1 in development of sepsis remain largely unknown. Lipopolysaccharide (LPS) induced lung fibrosis in the sepsis mouse model, and DNMT1 was upregulated in lung tissues of a sepsis mouse model compared with lung tissues from control mice. Then, this study demonstrated that LPS induced the production of interleukin (IL)-7 and tumor necrosis factor (TNF)-α and promoted DNMT1 expression in primary type II alveolar epithelial cells (AECII cells). Knockdown of DNMT1 inhibited IL-7 and TNF-α secretion in AECII cells exposed to LPS. Further study demonstrated that DNMT1 repressed the expression of miR-130a in AECII cells with or without LPS exposure. Next, this study demonstrated that miR-130a inhibited ZEB1 expression in AECII cells exposed to LPS. Ultimately, this study revealed the role of the DNMT1/miR-130a/ZEB1 regulatory pathway in AECII cells exposed to LPS. Overall, our data revealed that LPS induced the secretion of inflammatory factors by modulating the DNMT1/miR-130a/ZEB1 regulatory pathway in AECII cells, thus providing a novel theoretical basis that might be beneficial for establishment of diagnostic and therapeutic strategies for sepsis. [ABSTRACT FROM AUTHOR]

The purpose of the study is to assess the etiology detection ability of Metagenomic Next-Generation Sequencing (mNGS) on formalin fixation and paraffin embedding (FFPE) tissue from postoperative biopsy specimens. We prospectively enrolled specimens from patients undergone surgery biopsy due to undefinite diagnosis and pathologically indicated granulomatous lesions. FFPE tissues were tested by mNGS and histopathology. The etiology detection rate of mNGS was calculated and compared with histopathology.. Among the 69 cases eventually included, 41 (59.42%) were diagnosed with infectious granuloma. The overall fungi and mycobacteria etiology detection rates of mNGS in granuloma lesions was 87.80% (36/41). The mNGS increased the detection rate by 68.29% (28/41) compared with histopathology, the difference was statistically significant (χ2 = 28.97, P = 0.00). The detection rates of mNGS in fungal infections (12/12,100%) and in mycobacterium infections (22/27, 81.48%) were significant higher than those of histopathology (8/12, 66.67% and 0/27, 0.00%; both P = 0.00). Two (2/2.100%) cases of co-infection were detected at one time by mNGS. All mNGS-based clinical decisions were made within 2 days. The mNGS could accurately and quickly detect fungi and mycobacteria in FFPE specimens from postoperative granuloma specimens and identify the pathogens to the species level. China Clinical Trial Registry ChiCTR2000035464 [ABSTRACT FROM AUTHOR]

Therapeutic options for treating Mycobacterium abscessus infections are extremely limited; quinolones are important. The in vitro anti- M. abscessus activities of nine quinolones, emphasizing sitafloxacin, were investigated. Antimicrobial susceptibility testing was performed on 10 non-tuberculous mycobacterium reference strains and 194 clinical, M. abscessus isolates. The activity of sitafloxacin against intracellular M. abscessus residing within macrophages was also evaluated. A checkerboard assay was conducted to determine synergy between sitafloxacin and 10 clinically important antibiotics. Among the nine quinolones tested, sitafloxacin exhibited the greatest anti- M. abscessus activity with MIC50 and MIC90 of 1 and 2 mg/L, respectively. Sitafloxacin exerted a bacteriostatic effect on M. abscessus and inhibited the intracellular growth of M. abscessus at concentrations equivalent to clarithromycin. No antagonism between sitafloxacin and 10 clinically important anti- M. abscessus antibiotics was evident. In summary, sitafloxacin exhibited a significant advantage relative to other quinolones in inhibiting the growth of M. abscessus in vitro , suggesting the potential inclusion of sitafloxacin in new strategies to treat M. abscessus infections. [ABSTRACT FROM AUTHOR]

With the development of smart grid information physical systems, some of the data processing functions gradually approach the edge layer of end-users. To better realize the energy theft detection function at the edge, we proposed an energy theft detection method based on the power consumption information acquisition system of power enterprises. The method involves the following steps. In the centralized data center, K-means is used to decompose a large amount of data into small data and then input and train neural network parameters to realize feature extraction. We design a neural network named DWMCNN, which can extract features from the day, week, and month and can extract more accurate features. In the edge data center, the random forest (RF) algorithm is used to classify the extracted features. The experimental results show that the clustering method accords with the idea of edge computing-distributed processing and improves the operation speed and that the feature extractor has good convergence performance. In addition, compared with the methods based on various classifiers, this method has higher accuracy and lower computational complexity, which is suitable for the deployment of edge data centers. [ABSTRACT FROM AUTHOR]

Smart healthcare has undergone new opportunities and challenges with the arrival of the Industry 4.0 era. The intelligent imaging diagnosis system is a staple part of smart healthcare, helping doctors make clinical decisions. Nevertheless, intelligent diagnosis analysis is still confronted with the issue that it is challenging to extract effective features from the limited and high-dimensional data, particularly in resting-state data of amnesic mild cognitive impairment (aMCI). Furthermore, the intelligent imaging diagnosis system for aMCI is conductive to make timely predicting groups that may convert to Alzheimer's disease (AD). To improve the system's detection performance and reduce its data redundancy, we first develop an adaptive structure feature generation strategy (ASFGS) based on the Laplacian matrix and sparse autoencoder to obtain the structural features of brain functional network (BFN). Concurrently, we present a multiscale local feature detection strategy (MLFDS) to overcome the low utilization of local features of BFN. And finally, multiscale features, including structural features and multiscale local features, are fused by concatenation method to further improve the detection performance of aMCI system. Support vector machine based on radial basis function (RBF-SVM) for small data learning is adopted to evaluate the effectiveness of the proposed features. Besides, we employ leave-one-out cross-validation strategy to avoid the overfitting problem of classifier training process. The experiment results elucidate that the accuracy (ACC) and the area under the curve (AUC) in this work provide 86.57% and 86.36%, respectively, which outperforms the traditional methods and offers new insights for accuracy requirements of the aMCI system. [ABSTRACT FROM AUTHOR]

In recent years, a more robust facial feature can be learned by convolutional neural networks once introducing margins into loss functions. Those methods set a margin for each class manually to squeeze the intra‐class variations within each class equally. However, the internal feature distributions of different persons in the real world are highly unbalanced, and the distance between different identities is not uniform either. As a result, applying the same margin on all classes might not lead to higher inter‐class differences. To address this problem, this paper proposes an adaptive margin based on feature distribution to squeeze the feature interior spaces of different classes. Simultaneously, because the inter‐class margin can adequately represent the distribution of different classes in the feature space, this paper proposes a novel diversity regularization method. The regularization weights of each class are dynamically set depending on their margins. This method proposed in this paper is intuitively interpretable and can be easily applied to other classification scenarios. Experiments on current existing benchmarks have demonstrated the superiority of our method over state‐of‐the‐art competitors. [ABSTRACT FROM AUTHOR]

The Class Φ2/EF2 amplifier is an attractive topology for high-voltage and high-frequency power conversion because of the high efficiency, reduced device voltage stress, simplicity of gate driving, and load-independent ZVS operation. Due to many degrees of freedom for tuning, previous studies can only solve the single-ended Φ2 circuit using numerical methods. This work focuses on improving the design and operating characteristics of a push–pull Φ2 amplifier with a T network connected between the switch nodes, or a PPT Φ2 amplifier. The PPT Φ2 amplifier has less circulating energy and achieves higher cutoff frequency ƒT than other Φ2/EF2 circuits. We, then, present a series-stacked input configuration to reduce the switch voltage stress and improve the efficiency and power density. A compact 6.78-MHz, 100-V, 300-W prototype converter is demonstrated that uses low-cost Si devices and achieves 96% peak total efficiency and maintains above 94.5% drain efficiency across a wide range of voltage and power. Together with the advances in wide-bandgap semiconductors and magnetic materials, the PPT Φ2 circuit opens more possibilities for the state-of-the-art performance of solid-state RF amplifiers in high-frequency, high-power applications, including wireless charging for electric vehicles, plasma RF drives, and nuclear magnetic resonance spectroscopy. [ABSTRACT FROM AUTHOR]

Background: Smooth and rough colony morphotypes of Mycobacterium abscessus are associated with virulence, but some isolates form both smooth and rough colonies, impeding successful morphotype identification. Reportedly, smooth/rough morphotypes are also related to the glycopeptidolipid (GPL) genotype. However, the accuracy of GPL genotyping to discriminate morphotypes and the relationship between GPL genotype and clinical characteristics of M abscessus lung disease have not been verified.Methods: A retrospective analysis of colony morphology, GPL genotype, and clinical data from 182 patients with M abscessus lung disease was conducted.Results: Of 194 clinical isolates, 126 (65.0%), 15 (7.7%), and 53 (27.3%) exhibited rough, smooth, and mixed colony morphotypes, respectively. Glycopeptidolipid genotyping indicated that 86.7% (13 of 15) of smooth isolates belonged to the GPL-wild type (WT) group, whereas 98.4% (124 of 126) of rough isolates belonged to the GPL-mutant type (MUT) group. Therefore, GPL genotyping accurately distinguished between smooth and rough morphotypes. Mixed colony morphotypes were also divided into GPL-WT (18.9%) and GPL-MUT (81.1%) groups. Further analysis revealed that patients infected with the GPL-MUT group presented with significantly worse baseline clinical characteristics and exacerbated episodes of lung disease.Conclusions: Glycopeptidolipid genotyping accurately distinguishes smooth and rough colony morphotypes. Patients infected with the GPL-MUT genotype exhibit worse clinical characteristics and are at a higher risk of exacerbated lung disease. [ABSTRACT FROM AUTHOR]

Recent methods for 2D facial landmark localization perform well on close‐to‐frontal faces, but 2D landmarks are insufficient to represent 3D structure of a facial shape. For applications that require better accuracy, such as facial motion capture and 3D shape recovery, 3DA‐2D (2D Projections of 3D Facial Annotations) is preferred. Inferring the 3D structure from a single image is an ill‐posed problem whose accuracy and robustness are not always guaranteed. This paper aims to solve accurate 2D facial landmark localization and the transformation between 2D and 3DA‐2D landmarks. One way to increase the accuracy is to input more precisely annotated facial images. The traditional cascaded regressions cannot effectively handle large or noisy training data sets. In this paper, we propose a Mini‐Batch Cascaded Regressions (MBCR) method that can iteratively train a robust model from a large data set. Benefiting from the incremental learning strategy and a small learning rate, MBCR is robust to noise in training data. We also propose a new Cross‐Dimension Annotations Conversion (CDAC) method to map facial landmarks from 2D to 3DA‐2D coordinates and vice versa. The experimental results showed that CDAC combined with MBCR outperforms the‐state‐of‐the‐art methods in 3DA‐2D facial landmark localization. Moreover, CDAC can run efficiently at up to 110 fps on a 3.4 GHz‐CPU workstation. Thus, CDAC provides a solution to transform existing 2D alignment methods into 3DA‐2D ones without slowing down the speed. Training and testing code as well as the data set can be downloaded from https://github.com/SWJTU‐3DVision/CDAC. [ABSTRACT FROM AUTHOR]