Whole-genome analysis of Escherichia coli isolated from wild Amur tiger (Panthera tigris altaica) and North China leopard (Panthera pardus japonensis).

Background: Escherichia coli is an important intestinal flora, of which pathogenic E. coli is capable of causing many enteric and extra-intestinal diseases. Antibiotics are essential for the treatment of bacterial infections caused by pathogenic E. coli; however, with the widespread use of antibiotics, drug resistance in E. coli has become particularly serious, posing a global threat to human, animal, and environmental health. While the drug resistance and pathogenicity of E. coli carried by tigers and leopards in captivity have been studied intensively in recent years, there is an extreme lack of information on E. coli in these top predators in the wild environment. Methods: Whole genome sequencing data of 32 E. coli strains collected from the feces of wild Amur tiger (Panthera tigris altaica, n = 24) and North China leopard (Panthera pardus japonensis, n = 8) were analyzed in this article. The multi-locus sequence types, serotypes, virulence and resistance genotypes, plasmid replicon types, and core genomic SNPs phylogeny of these isolates were studied. Additionally, antimicrobial susceptibility testing (AST) was performed on these E. coli isolates. Results: Among the E. coli isolates studied, 18 different sequence types were identified, with ST939 (21.9%), ST10 (15.6%), and ST3246 (9.4%) being the most prevalent. A total of 111 virulence genes were detected, averaging about 54 virulence genes per sample. They contribute to invasion, adherence, immune evasion, efflux pump, toxin, motility, stress adaption, and other virulence-related functions of E. coli. Sixty-eight AMR genes and point mutations were identified. Among the detected resistance genes, those belonging to the efflux pump family were the most abundant. Thirty-two E. coli isolates showed the highest rate of resistance to tetracycline (14/32; 43.8%), followed by imipenem (4/32; 12.5%), ciprofloxacin (3/32; 9.4%), doxycycline (2/32; 6.3%), and norfloxacin (1/32; 3.1%). Conclusions: Our results suggest that E. coli isolates carried by wild Amur tigers and North China leopards have potential pathogenicity and drug resistance.

5G-Based Remote Virtual Bronchoscopic Navigation-Guided Transbronchial Lung Biopsy for Diagnosis of Lung Cancer: Description of 2 Cases.

INTRODUCTION: Bronchoscopic navigation combined with endobronchial ultrasound-guided transbronchial lung biopsy (EBUS-TBLB) is an important approach for the diagnosis of peripheral pulmonary lesions (PPL). The fifth-generation (5G) network, characterized by low latency and high stability, has shown promising possibilities in telemedicine for remote areas. METHODS: We present two cases of PPL in primary hospitals without navigation equipment. The EBUS-TBLB was performed with the guidance of remote augmented reality virtual bronchoscopic navigation (VBN) based on a 5G network. In practice, the 5G network could enable the matching of actual/virtual bronchoscopic images and navigation paths in real time, as well as high-speed transmission at long distances (>20 km), without any visual delay (<500 ms). CONCLUSION: Both patients were successfully diagnosed with lung cancer after accurate positioning and obtaining biopsies of target lesions. This 5G-based remote VBN-guided EBUS-TBLB appears to be safe with reliable connections in both cases and shows potential for cost-effectiveness. It would be an optimal resource for undeveloped regions and/or regions lacking endoscopists with extensive experience in navigation-related procedures.

The Novel Application of Robotic-Assisted Bronchoscopy Combined with Photodynamic Therapy for Adenoid Cystic Carcinoma of the Trachea.

Robotic platforms have been widely used in the various fields of clinical diagnosis and therapy of diseases in the past decade. Robotic-assisted bronchoscopy (RAB) demonstrates its advantages of visibility, flexibility, and stability in comparison to conventional bronchoscopic techniques. Improving diagnostic yield and navigation yield for peripheral pulmonary lesions has been defined; however, RAB platform of treatment was not reported. In this article, we report a case of a 52-year-old woman who was diagnosed with the tracheal adenoid cystic carcinoma and recurred in the second postoperative year, leading to the involvement of the entire tracheal wall and lumen obstruction. Since the lesion was inoperable, we combined RAB and photodynamic therapy (PDT) for the patient. The potential advantages of using RAB for PDT delivery include precise light irradiation of target lesions and stable intra-operative control over the long term. This is a novel application of RAB combined with PDT for airway diseases. The case report may provide a new insight into the diagnosis and treatment of pulmonary diseases. In addition to improving the diagnostic rates, the RAB platform may also play an important role in the treatment of airway and lung disease in the future.

Distinguishing bronchoscopically observed anatomical positions of airway under by convolutional neural network.

Background: Artificial intelligence (AI) technology has been used for finding lesions via gastrointestinal endoscopy. However, there were few AI-associated studies that discuss bronchoscopy. Objectives: To use convolutional neural network (CNN) to recognize the observed anatomical positions of the airway under bronchoscopy. Design: We designed the study by comparing the imaging data of patients undergoing bronchoscopy from March 2022 to October 2022 by using EfficientNet (one of the CNNs) and U-Net. Methods: Based on the inclusion and exclusion criteria, 1527 clear images of normal anatomical positions of the airways from 200 patients were used for training, and 475 clear images from 72 patients were utilized for validation. Further, 20 bronchoscopic videos of examination procedures in another 20 patients with normal airway structures were used to extract the bronchoscopic images of normal anatomical positions to evaluate the accuracy for the model. Finally, 21 respiratory doctors were enrolled for the test of recognizing corrected anatomical positions using the validating datasets. Results: In all, 1527 bronchoscopic images of 200 patients with nine anatomical positions of the airway, including carina, right main bronchus, right upper lobe bronchus, right intermediate bronchus, right middle lobe bronchus, right lower lobe bronchus, left main bronchus, left upper lobe bronchus, and left lower lobe bronchus, were used for supervised machine learning and training, and 475 clear bronchoscopic images of 72 patients were used for validation. The mean accuracy of recognizing these 9 positions was 91% (carina: 98%, right main bronchus: 98%, right intermediate bronchus: 90%, right upper lobe bronchus: 91%, right middle lobe bronchus 92%, right lower lobe bronchus: 83%, left main bronchus: 89%, left upper bronchus: 91%, left lower bronchus: 76%). The area under the curves for these nine positions were >0.98. In addition, the accuracy of extracting the images via the video by the trained model was 94.7%. We also conducted a deep learning study to segment 10 segment bronchi in right lung, and 8 segment bronchi in Left lung. Because of the problem of radial depth, only segment bronchi distributions below right upper bronchus and right middle bronchus could be correctly recognized. The accuracy of recognizing was 84.33 ± 7.52% by doctors receiving interventional pulmonology education in our hospital over 6 months. Conclusion: Our study proved that AI technology can be used to distinguish the normal anatomical positions of the airway, and the model we trained could extract the corrected images via the video to help standardize data collection and control quality.

Exploration of Parascaris species in three different Equus populations in China.

BACKGROUND: The roundworms, Parascaris spp., are important nematode parasites of foals and were historically model organisms in the field of cell biology, leading to many important discoveries. According to karyotype, ascarids in Equus are commonly divided into Parascaris univalens (2n = 2) and Parascaris equorum (2n = 4). METHODS: Here, we performed morphological identification, karyotyping and sequencing of roundworms from three different hosts (horses, zebras and donkeys). Phylogenetic analysis was performed to study the divergence of these ascarids based on cytochrome c oxidase subunit I (COI) and internal transcribed spacer (ITS) sequences. RESULTS: Karyotyping, performed on eggs recovered from worms of three different Equus hosts in China, showed two different karyotypes (2n = 2 in P. univalens collected from horses and zebras; 2n = 6 in Parascaris sp. collected from donkeys). There are some differences in the terminal part of the spicula between P. univalens (concave) and Parascaris sp. (rounded). Additionally, it was found that the egg's chitinous layer was significantly thicker in Parascaris sp. (> 5 µm) than P. univalens (< 5 µm) (F(2537) = 1967, P < 0.01). Phylogenetic trees showed that the sequences of Parascaris from Equus hosts were divided into two distinct lineages based on sequences of the COI and ITS. CONCLUSIONS: Comparing the differences in roundworms collected from three different Equus hosts, this study describes a Parascaris species (Parascaris sp.) with six chromosomes in donkeys. It is worth noting that the thickness of the chitinous layer in the Parascaris egg may serve as a diagnostic indicator to distinguish the two roundworms (P. univalens and Parascaris sp.). The Parascaris sp. with six chromosomes in donkeys in the present study may be a species of P. trivalens described in 1934, but the possibility that it is a new Parascaris species cannot be ruled out. Both karyotyping and molecular analysis are necessary to solve the taxonomic problems in Parascaris species.

A strategy combining denoising and cryo-EM single particle analysis.

In cryogenic electron microscopy (cryo-EM) single particle analysis (SPA), high-resolution three-dimensional structures of biological macromolecules are determined by iteratively aligning and averaging a large number of two-dimensional projections of molecules. Since the correlation measures are sensitive to the signal-to-noise ratio, various parameter estimation steps in SPA will be disturbed by the high-intensity noise in cryo-EM. However, denoising algorithms tend to damage high frequencies and suppress mid- and high-frequency contrast of micrographs, which exactly the precise parameter estimation relies on, therefore, limiting their application in SPA. In this study, we suggest combining a cryo-EM image processing pipeline with denoising and maximizing the signal's contribution in various parameter estimation steps. To solve the inherent flaws of denoising algorithms, we design an algorithm named MScale to correct the amplitude distortion caused by denoising and propose a new orientation determination strategy to compensate for the high-frequency loss. In the experiments on several real datasets, the denoised particles are successfully applied in the class assignment estimation and orientation determination tasks, ultimately enhancing the quality of biomacromolecule reconstruction. The case study on classification indicates that our strategy not only improves the resolution of difficult classes (up to 5 Å) but also resolves an additional class. In the case study on orientation determination, our strategy improves the resolution of the final reconstructed density map by 0.34 Å compared with conventional strategy. The code is available at https://github.com/zhanghui186/Mscale.

Tongbian decoction restores intestinal microbiota and activates 5-hydroxytryptamine signaling: implication in slow transit constipation.

Introduction: Slow transit constipation (STC) is a type of functional constipation. The detailed mechanism of STC, for which there is currently no effective treatment, is unknown as of yet. Tongbian decoction (TBD), a traditional Chinese medicinal formula, is commonly used to treat STC in clinical settings. However, the potential impact of TBD on the management of STC via modulation of the gut microbiota remains unclear. Methods: Pseudo-germ-free rats were constructed after 6 days of treatment with bacitracin, neomycin, and streptomycin (abbreviated as ABX forthwith). Based on the successful construction of pseudo-germ-free rats, the STC model (ABX + STC) was induced using loperamide hydrochloride. After successful modeling, based on the different sources of donor rat microbiota, the ABX + STC rats were randomly divided into three groups: Control → ABX + STC, STC → ABX + STC, and STC + TBD → ABX + STC for fecal microbiota transplant (FMT). Body weight, fecal water content, and charcoal power propelling rate of the rats were recorded. Intestinal microbiota was detected by 16S rRNA sequencing, and the 5-hydroxytryptamine (5-HT) signaling pathway was examined by western blots, immunofluorescence, and immunohistochemical analysis. Results: After treatment with fecal bacterial solutions derived from rats treated with Tongbian decoction (TBD), there was an increase in body weight, fecal water content, and the rate of charcoal propulsion in the rats. Additionally, activation of the 5-hydroxytryptamine (5-HT) signaling pathway was observed. The 16S rRNA sequencing results showed that the fecal bacterial solution from TBD-treated rats affected the intestinal microbiota of STC rats by increasing the proliferation of beneficial bacteria and suppressing the expansion of harmful bacteria. Conclusion: Our study showed that TBD alleviated constipation in STC rats by modulating the structure of the intestinal microbiota.

The role of PET/CT in radiotherapy for nasopharyngeal carcinoma.

Radiotherapy has already been developed as the standard of care for patients with nasopharyngeal carcinoma (NPC), and precision staging, target volume delineation, prognosis prediction, and post-treatment surveillance are essential in the management of NPC. Positron emission tomography/computed tomography (PET/CT) is increasingly recognized as an imaging modality to guide precision radiotherapy in these areas. The feasibility and efficacy of 18F-FDG PET/CT have been confirmed in tumor diagnosis, treatment planning, prognosis, surveillance, and assessment. Coupled with the capability of revealing tumor metabolic information, 18F-FDG PET/CT is more accurate in identifying primary lesions and metastases of NPC than other conventional imaging methods including CT and MRI and shows the independently diagnostic and prognostic value for radiotherapy. However, 18F-FDG has limitations due to its physiological distribution in brain tissue and increasing uptake in post-radiation inflammation. Novel PET radiotracers including FAPI, NaF, CHO, and FLT are explored as alternatives with potential superiority for radiotherapy in NPC. In this review, we summarized the evolving role of PET/CT in the management of radiotherapy in NPC patients, aiming to facilitate precision radiotherapy from a molecular imaging aspect.

The genetic characteristics of Sarcoptes scabiei from Chinese serow (Capricornis milneedwardsii) and goral (Naemorhedus goral arnouxianus) compared with other mites from different hosts and geographic locations using ITS2 and cox1 sequences.

Scabies is a common parasitic disease in many mammalian species, caused by the infestation of Sarcoptes scabiei. There is no consistent conclusion on whether Sarcoptes mites from different hosts or geographic locations have apparent genetic divergence. In this study, we collected and morphologically identified S. scabiei from Chinese serow and goral, and we described the genetic diversity of S. scabiei and other mites based on phylogenetic analyses of the ITS2 and cox1 sequence fragments, including data available in GenBank. The mites isolated from Chinese serow and goral were S. scabiei, and they were morphologically similar. The phylogenetic trees and haplotype networks showed that S. scabiei from other locations worldwide did not cluster according to host divergence or geographical distribution. Additionally, the Fst values were - 0.224 to 0.136 and - 0.045 to 1 between S. scabiei from different hosts, including humans and domestic and wild animals, based on partial ITS and cox1 sequences. Worldwide S. scabiei samples formed three clusters (with H2, H5, and H12 at their centers) in the ITS and one cluster (with C9 at the center) in the cox1 haplotype phylogenetic network. The S. scabiei collected from Chinese serow and goral were morphologically similar and had the same genotype. A study on the genetic characteristics of S. scabiei from Chinese serow and goral together with other mites from different hosts and geographic locations around the world showed no obvious divergence. These findings indicated that scabies likely is a zoonotic disease and that the global prevalence of scabies is probably related to the worldwide trade of domestic animals.

A Transfer Learning-Based Classification Model for Particle Pruning in Cryo-Electron Microscopy.

The cryo-electron microscopy (cryo-EM) single-particle analysis requires tens of thousands of particle projections to reveal structural information of macromolecular complexes. However, due to the low signal-to-noise ratio and the presence of high contrast artifacts and contaminants in the micrographs, the semiautomatic and fully automatic particle picking algorithms tend to suffer from high false-positive rates, which degrades the confidence of structure determination. In this study, we introduce PickerOptimizer (PO), a transfer learning-based classification neural network for particle pruning in cryo-EM, as an additional strategy to complement the current automated particle picking algorithms. To achieve high classification performance with minimal human intervention, we adopted two key strategies: (1) utilizing the transfer learning techniques to train the convolutional neural network, where the knowledge gained from public classification datasets is applied to the field of cryo-EM. (2) Designing a multiloss strategy, a combination of multiple loss functions, to guide the optimization of the network parameters. To reduce the domain shift between cryo-EM images and natural images for pretraining, we build the first image classification dataset for cryo-EM, which contains positive and negative samples collected from EMPIAR entries. The PO is tested on 14 public experimental datasets, achieving accuracy and F1 scores above 95% in most cases. Furthermore, three case studies are provided to verify the model performance by applying PO on problematic particle selections, showing that our algorithm achieved better or comparable performance compared with other particle pruning strategies.

First isolation of Trichuris from Chinese serow, Capricornis milneedwardsii (Cetartiodactyla: Caprinae).

Whipworms are soil-transmitted helminths that can infect a variety of animals. A Chinese serow possibly infected by whipworms was found during a wildlife disease surveillance project in Baima Snow Mountain National Nature Reserve, Yunnan, China, in 2021. As convergent evolution is common in coinhabiting parasites, a mitochondrial gene sequence (cox1) and ribosomal gene sequence (ITS1) were used to identify species similar to Trichuris from Chinese serow. The phylogenetic trees and genetic distances of ten Trichuris samples from a Chinese serow together with other Trichuris spp. that have been previously reported were analysed based on the cox1 and ITS1 sequences. The combined results of the phylogenetic tree and genetic distances based on cox1 gene showed that the whipworms in Chinese serow are T. skrjabini. However, the whipworms in the present study were divided into two apparent clades in the phylogenic trees constructed by the cox1 sequences (Clades A and B) and the ITS1 sequences (Clades C and D). In addition, the Fst and Nm values were 0.82 and 0.23 between Clade A and Clade B for the cox1 gene, and 0.30 and 0.45 between Clade C and Clade D for the ITS1 sequences; both indicators showed low gene flow among the clades. Therefore, the genetic population structure of T. skrjabini was illustrated.

Noise-Transfer2Clean: denoising cryo-EM images based on noise modeling and transfer.

MOTIVATION: Cryo-electron microscopy (cryo-EM) is a widely used technology for ultrastructure determination, which constructs the 3D structures of protein and macromolecular complex from a set of 2D micrographs. However, limited by the electron beam dose, the micrographs in cryo-EM generally suffer from the extremely low signal-to-noise ratio (SNR), which hampers the efficiency and effectiveness of downstream analysis. Especially, the noise in cryo-EM is not simple additive or multiplicative noise whose statistical characteristics are quite different from the ones in natural image, extremely shackling the performance of conventional denoising methods. RESULTS: Here, we introduce the Noise-Transfer2Clean (NT2C), a denoising deep neural network (DNN) for cryo-EM to enhance image contrast and restore specimen signal, whose main idea is to improve the denoising performance by correctly learning the noise distribution of cryo-EM images and transferring the statistical nature of noise into the denoiser. Especially, to cope with the complex noise model in cryo-EM, we design a contrast-guided noise and signal re-weighted algorithm to achieve clean-noisy data synthesis and data augmentation, making our method authentically achieve signal restoration based on noise's true properties. Our work verifies the feasibility of denoising based on mining the complex cryo-EM noise patterns directly from the noise patches. Comprehensive experimental results on simulated datasets and real datasets show that NT2C achieved a notable improvement in image denoising, especially in background noise removal, compared with the commonly used methods. Moreover, a case study on the real dataset demonstrates that NT2C can greatly alleviate the obstacles caused by the SNR to particle picking and simplify the identifying of particles. AVAILABILITYAND IMPLEMENTATION: The code is available at https://github.com/Lihongjia-ict/NoiseTransfer2Clean/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Correlation between lung cancer probability and number of pulmonary nodules in baseline computed tomography lung cancer screening: A retrospective study based on the Chinese population.

Background: Screening for lung cancer with LDCT detects a large number of nodules. However, it is unclear whether nodule number influences lung cancer probability. This study aimed to acquire deeply insight into the distribution characteristics of nodule number in the Chinese population and to reveal the association between the nodule number and the probability of lung cancer (LC). Methods: 10,167 asymptomatic participants who underwent LDCT LC screening were collected. Noncalcified nodules larger than 4 mm were included. The nodule number per participant was determined. We defined five categories according to the number of nodules (based on nodule type and size): one, two, three, four, and more than four nodules. We stratified the nodules as groups A, B, and C and participants as Amax, Bmax, and Cmax groups, and explored the association between nodule number and the probability of LC on nodule and participant levels. Results: 97 participants were confirmed to have LC. The probabilities of LC were 49/1719, 22/689, 11/327, 6/166, and 9/175 in participants with one, two, three, four, and more than four nodules (p>0.05), respectively. In the Bmax group, the probability of LC was significantly higher in participants with one nodule than those with >4 nodules (p<0.05), and the probability of LC showed a negative linear trend with increasing nodule numbers (p<0.05). Based on the nodule-level analyses, in Group B, LC probability was significantly higher when participants had a solitary nodule than when they had >4 nodules (p<0.05). Conclusion: LC probability does not significantly change with the number of nodules. However, when stratified by the nodule size, the effect of nodule number on LC probability was nodule-size dependent, and greater attention and active follow-up are required for solitary nodules especially SNs/solid component of PSNs measuring 6-15 mm or NSNs measuring 8-15 mm. Assessing the nodule number in conjunction with nodule size in baseline LDCT LC screening is considered beneficial.

DETECTOR: structural information guided artifact detection for super-resolution fluorescence microscopy image.

Super-resolution fluorescence microscopy, with a spatial resolution beyond the diffraction limit of light, has become an indispensable tool to observe subcellular structures at a nanoscale level. To verify that the super-resolution images reflect the underlying structures of samples, the development of robust and reliable artifact detection methods has received widespread attention. However, the existing artifact detection methods are prone to report false alert artifacts because it relies on absolute intensity mismatch between the wide-field image and resolution rescaled super-resolution image. To solve this problem, we proposed DETECTOR, a structural information-guided artifact detection method for super-resolution images. It detects artifacts by computing the structural dissimilarity between the wide-field image and the resolution rescaled super-resolution image. To focus on structural similarity, we introduce a weight mask to weaken the influence of strong autofluorescence background and proposed a structural similarity index for super-resolution images, named MASK-SSIM. Simulations and experimental results demonstrated that compared with the state-of-the-art methods, DETECTOR has advantages in detecting structural artifacts in super-resolution images. It is especially suitable for wide-field images with strong autofluorescence background and super-resolution images of single molecule localization microscopy (SMLM). DETECTOR has extreme sensitivity to the weak signal region. Moreover, DETECTOR can guide data collection and parameter tuning during image reconstruction.

Live-SIMBA: an ImageJ plug-in for the universal and accelerated single molecule-guided Bayesian localization super resolution microscopy (SIMBA) method.

Live-cell super-resolution fluorescence microscopy techniques allow biologists to observe subcellular structures, interactions and dynamics at the nanoscale level. Among of them, single molecule-guided Bayesian localization super resolution microscopy (SIMBA) and its derivatives produce an appropriate 50 nm spatial resolution and a 0.1-2s temporal resolution in living cells with simple off-the-shelf total internal reflection fluorescence (TIRF) equipment. However, SIMBA and its derivatives are limited by the requirement for dual-channel dataset or single-channel dataset with special design, the time-consuming calculation for extended field of view and the lack of real-time visualization tool. Here, we propose a universal and accelerated SIMBA ImageJ plug-in, Live-SIMBA, for time-series analysis in living cells. Live-SIMBA circumvents the requirement of dual-channel dataset using intensity-based sampling algorithm and improves the computing speed using multi-core parallel computing technique. Live-SIMBA also better resolves the weak signals inside the specimens with adjustable background estimation and distance-threshold filter. With improved fidelity on reconstructed structures, greatly accelerated computation, and real-time visualization, Live-SIMBA demonstrates its extended capabilities in live-cell super-resolution imaging.

Super-resolution nanoscopy by coherent control on nanoparticle emission.

Super-resolution nanoscopy based on wide-field microscopic imaging provided high efficiency but limited resolution. Here, we demonstrate a general strategy to push its resolution down to ~50 nm, which is close to the range of single molecular localization microscopy, without sacrificing the wide-field imaging advantage. It is done by actively and simultaneously modulating the characteristic emission of each individual emitter at high density. This method is based on the principle of excited state coherent control on single-particle two-photon fluorescence. In addition, the modulation efficiently suppresses the noise for imaging. The capability of the method is verified both in simulation and in experiments on ZnCdS quantum dot-labeled films and COS7 cells. The principle of coherent control is generally applicable to single-multiphoton imaging and various probes.

Ultrasonographic optic nerve sheath diameter correlation with ICP and accuracy as a tool for noninvasive surrogate ICP measurement in patients with decompressive craniotomy.

OBJECTIVE: Increased intracranial pressure (ICP) results in enlarged optic nerve sheath diameter (ONSD). In this study the authors aimed to assess the association of ONSD and ICP in severe traumatic brain injury (TBI) after decompressive craniotomy (DC). METHODS: ONSDs were measured by ocular ultrasonography in 40 healthy control adults. ICPs were monitored invasively with a microsensor at 6 hours and 24 hours after DC operation in 35 TBI patients. ONSDs were measured at the same time in these patients. Patients were assigned to 3 groups according to ICP levels, including normal (ICP ≤ 13 mm Hg), mildly elevated (ICP = 14-22 mm Hg), and severely elevated (ICP > 22 mm Hg) groups. ONSDs were compared between healthy control adults and TBI cases with DC. Then, the association of ONSD with ICP was analyzed using Pearson's correlation coefficient, linear regression analysis, and receiver operator characteristic curves. RESULTS: Seventy ICP measurements were obtained among 35 TBI patients after DC, including 25, 27, and 18 measurements in the normal, mildly elevated, and severely elevated ICP groups, respectively. Mean ONSDs were 4.09 ± 0.38 mm in the control group and 4.92 ± 0.37, 5.77 ± 0.41, and 6.52 ± 0.44 mm in the normal, mildly elevated, and severely elevated ICP groups, respectively (p < 0.001). A significant linear correlation was found between ONSD and ICP (r = 0.771, p < 0.0001). Enlarged ONSD was a robust predictor of elevated ICP. With an ONSD cutoff of 5.48 mm (ICP > 13 mm Hg), sensitivity and specificity were 91.1% and 88.0%, respectively; a cutoff of 5.83 mm (ICP > 22 mm Hg) yielded sensitivity and specificity of 94.4% and 81.0%, respectively. CONCLUSIONS: Ultrasonographic ONSD is strongly correlated with invasive ICP measurements and may serve as a sensitive and noninvasive method for detecting elevated ICP in TBI patients after DC.

Let-7a inhibits proliferation and promotes apoptosis of human asthmatic airway smooth muscle cells.

The present study aimed to examine the changes of let-7a expression in asthmatic airway smooth muscle cells (ASMCs) and to analyze its effect on the proliferation and apoptosis of ASMCs, as well as the potential mechanism of action. Let-7a expression levels in ASMCs from asthmatic and non-asthmatic subjects were detected using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis. Furthermore, let-7a mimics were transfected in vitro into ASMCs isolated from asthmatic patients, and the effect of let-7a on ASMC proliferation was examined using a Cell Counting Kit-8. In addition, the influence of let-7a on ASMC apoptosis was detected using flow cytometry and a caspase-3/7 activity assay. Target genes of let-7a were predicted using bioinformatics software, and the direct regulatory effect of let-7a on the potential target gene signal transducer and activator of transcription 3 (STAT3) was verified through a dual-luciferase reporter gene assay combined with RT-qPCR and western blot analysis. The results demonstrated that let-7a expression was significantly lower in ASMCs of asthmatic subjects compared with that in ASMCs of normal subjects. Furthermore, upregulation of let-7a expression in asthmatic ASMCs markedly inhibited cell proliferation and promoted cell apoptosis. The results of the dual-luciferase reporter gene assay indicated that let-7a selectively binds with the 3'-untranslated region of the STAT3 mRNA. In addition, let-7a mimics evidently reduced the mRNA and protein expression levels of STAT3 in asthmatic ASMCs. In conclusion, the present study demonstrates that let-7a expression is downregulated in ASMCs from asthmatic patients. Furthermore, let-7a suppresses the proliferation and promotes apoptosis of human asthmatic ASMCs, which may, at least partially, be associated with the downregulation of STAT3 expression.

Prognostic value of ALDH1 and Nestin in advanced cancer: a systematic meta-analysis with trial sequential analysis.

BACKGROUND: Novel prognostic markers and therapeutic targets for advanced cancer are urgently needed. This report with trial sequential analysis (TSA) was first conducted to provide robust estimates of the correlation between aldehyde dehydrogenase 1 (ALDH1) and Nestin and clinical outcomes of advanced cancer patients. METHODS: Hazard ratios (HRs) with 95% confidence intervals (CIs) were summarized for overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), cancer-specific survival (CSS), relapse/recurrence-free survival (RFS), and metastasis-free survival (MFS) from multivariable analysis. TSA was performed to control for random errors. RESULTS: A total of 20 studies with 2050 patients (ALDH1: 15 studies with 1557 patients and Nestin: 5 studies with 493 patients) were identified. ALDH1 (HR = 2.28, p < 0.001) and Nestin (HR = 2.39, p < 0.001) were associated with a worse OS, as confirmed by TSA. Nestin positivity was linked to a poor PFS (HR = 2.08, p < 0.001), but ALDH1 was not linked to DFS, RFS, MFS, or PFS, and TSA showed that more studies were needed. Subgroup analysis by tumor type indicated that ALDH1 positivity may be associated with shorter OS in breast, head and neck cancers, but there was no association with colorectal cancer. Subgroup analysis by study source showed that ALDH1 positivity was correlated with a worse OS for Japanese (HR = 1.94, p = 0.002) and European patients (HR = 4.15, p < 0.001), but there was no association for Chinese patients. Subgroup analysis by survival rate showed that ALDH1 positivity correlated with poor OS at ⩾ 5 years (HR = 2.33, p < 0.001) or 10 years (HR = 1.76, p = 0.038). CONCLUSIONS: ALDH1 may be more valuable as an effective therapeutic target than Nestin for improving the long-term survival rate of advanced cancer. Additional prospective clinical trials are needed across different cancer types.

Prognostic Value of CD44 and Its Isoforms in Advanced Cancer: A Systematic Meta-Analysis With Trial Sequential Analysis.

Objective: Cancer stem cell marker CD44 and its variant isoforms (CD44v) may be correlated with tumor growth, metastasis, and chemo-radiotherapy resistance. However, the prognostic power of CD44 and CD44v in advanced cancer remains controversial. Therefore, the purpose of our study was to generalize the prognostic significance of these cancer stem cell markers in advanced cancer patients. Methods: Hazard ratios (HRs) with 95% confidence intervals (95% CIs) were calculated from multivariable analysis to assess the associations among CD44, CD44v6, and CD44v9 positivity and overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), cancer-specific survival (CSS), and recurrence-free survival (RFS). Trial sequential analysis (TSA) was also conducted. Results: We included 15 articles that reported on 1,201 patients with advanced cancer (CD44: nine studies with 796 cases, CD44v6: three studies with 143 cases, and CD44v9: three studies with 262 cases). CD44 expression was slightly linked to worse OS (HR = 2.03, P = 0.027), but there was no correlation between CD44 expression and DFS, RFS, or PFS. Stratified analysis showed that CD44 expression was not correlated with OS at ≥5 years or OS in patients receiving adjuvant therapy. CD44v6 expression was not associated with OS. CD44v9 expression was closely associated with poor 5-years CSS in patients treated with chemo/radiotherapy (HR = 3.62, P < 0.001). However, TSA suggested that additional trials were needed to confirm these conclusions. Conclusions: CD44 or CD44v9 might be novel therapeutic targets for improving the treatment of advanced cancer patients. Additional prospective clinical trials are strongly needed across different cancer types.