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Objective To explore the efficacy and advantages of intracranial-intracranial bypass for the treatment of complex intracranial aneurysms. Methods A total of 9 patients with complex intracranial aneurysms who underwent intracranial-intracranial bypass in Xiangya Hospital of Central South University from February 2014 to May 2020 were included, and were treated with grafts bypass or reimplantation of recipient arteries. All cases underwent CTA or DSA to detect the patent of grafts, whether aneurysms were completely clipped or resected and aneurysms recurrence occurred during the follow-up. Modified Rankin Scale (mRS) was used to evaluate the neurological prognosis at discharge and during the follow - up. Results Radial artery (RA) or great saphenous vein (GSV) was used for interposition in 4 cases, and recipient arteries were used for reimplantation in 5 cases. Of 4 cases of interposition, the cavernous sinus seoment of internal carotid artery (ICA)-GSV-ICA bypass was adopted in one case, middle cerebral artery (MCA) M2-RA-M2 bypass in one case, anterior cerebral artery (ACA) A3-GSV-A3 bypass in one case, posterior cerebral artery (PCA) P2 -RA -P2 bypass in one case. Of 5 cases of reimplantation, MCA M2 inferior trunk was reimplanted to M2 superior trunk in one case, ACA A3 was reimplanted to contralateral A3 in 2 cases, the posterior inferior cerebellar artery (PICA) was reimplanted to the anterior inferior cerebellar artery (AICA) in 2 cases. CTA in 3 d postoperatively showed all cases grafts were patent and aneurysms disappeared. After 3 months of discharge, 2 were lost to follow-up. The other 7 cases kept the patency of grafts and no new aneurysms, and were constantly followed up, with an average follow-up time of 30.71 months, and mRS score was 1 or lower. Conclusions Intracranial - intracranial bypass can be applied for complex intracranial aneurysms that are difficult for conventional surgical treatment to solve. Compared with extracranial - intracranial bypass, its grafts are shorter and its hemodynamics features are more in line with physiological conditions.

Abstract Background Hematological metastasis has been recognized as a crucial factor contributing to the high rates of metastasis and mortality observed in colorectal cancer (CRC). Notably, exosomes derived from cancer cells participate in the formation of CRC pre-metastatic niches; however, the mechanisms underlying their effects are largely unknown. While our preliminary research revealed the role of exosome-derived disintegrin and metalloproteinase 17 (ADAM17) in the early stages of CRC metastasis, the role of exosomal ADAM17 in CRC hematogenous metastasis remains unclear. Methods In the present study, we isolated and purified exosomes using ultracentrifugation and identified exosomal proteins through quantitative mass spectrometry. In vitro, co-culture assays were conducted to evaluate the impact of exosomal ADAM17 on the permeability of the blood vessel endothelium. Vascular endothelial cell resistance, the cell index, membrane protein separation, flow cytometry, and immunofluorescence were employed to investigate the mechanisms underlying exosomal ADAM17-induced vascular permeability. Additionally, a mouse model was established to elucidate the role of exosomal ADAM17 in the modulation of blood vessel permeability and pre-metastatic niche formation in vivo. Results Our clinical data indicated that ADAM17 derived from the circulating exosomes of patients with CRC could serve as a blood-based biomarker for predicting metastasis. The CRC-derived exosomal ADAM17 targeted vascular endothelial cells, thus enhancing vascular permeability by influencing vascular endothelial cadherin cell membrane localization. Moreover, exosomal ADAM17 mediated the formation of a pre-metastatic niche in nude mice by inducing vascular leakage, thereby promoting CRC metastasis. Nonetheless, ADAM17 selective inhibitors effectively reduced CRC metastasis in vivo. Conclusions Our results suggest that exosomal ADAM17 plays a pivotal role in the hematogenous metastasis of CRC. Thus, this protein may serve as a valuable blood-based biomarker and potential drug target for CRC metastasis intervention.

Abstract The nasal cavity harbors diverse microbiota that contributes to human health and respiratory diseases. However, whether and to what extent the host genome shapes the nasal microbiome remains largely unknown. Here, by dissecting the human genome and nasal metagenome data from 1401 healthy individuals, we demonstrated that the top three host genetic principal components strongly correlated with the nasal microbiota diversity and composition. The genetic association analyses identified 63 genome-wide significant loci affecting the nasal microbial taxa and functions, of which 2 loci reached study-wide significance (p

ObjectivesThis study aimed to assess the knowledge and awareness of nicotine, nicotine replacement therapy (NRT), and electronic cigarettes (e-cigarettes) among general practitioners with a special interest (GPwSIs) in respiratory medicine.MethodsA cross-sectional study was conducted from October 2021 to February 2022. Knowledge and awareness were compared among smokers and non-smokers, as well as different age and gender groups.ResultsThe study consisted of 102 GPwSIs from 21 cities in Sichuan Province, China. Most respondents would recommend NRT for long-term use. Only a few believed that e-cigarettes are an effective means of smoking cessation and 71.6% would not recommend e-cigarettes as a substitute for cigarettes to their patients. Additionally, the majority did not regularly provide extensive help to assist patients in quitting smoking and needed smoking cessation counseling training.ConclusionGPwSIs in respiratory medicine in China could have a relatively low level of knowledge and awareness regarding nicotine, NRT, and e-cigarettes. The study highlights the need for smoking cessation training among GPwSIs to improve their knowledge and provide better assistance to patients who want to quit smoking.

Abstract Fine needle aspiration (FNA) biopsy of thyroid nodules is a safe, cost-effective, and accurate diagnostic method for detecting thyroid cancer. However, about 10% of initial FNA biopsy samples from patients are non-diagnostic and require repeated FNA, which delays the diagnosis and appropriate care. On-site evaluation of the FNA sample can be performed to filter out non-diagnostic FNA samples. Unfortunately, it involves a time-consuming staining process, and a cytopathologist has to be present at the time of FNA. To bypass the staining process and expert interpretation of FNA specimens at the clinics, we developed a deep learning-based ensemble model termed FNA-Net that allows in situ screening of adequacy of unstained thyroid FNA samples smeared on a glass slide which can decrease the non-diagnostic rate in thyroid FNA. FNA-Net combines two deep learning models, a patch-based whole slide image classifier and Faster R-CNN, to detect follicular clusters with high precision. Then, FNA-Net classifies sample slides to be non-diagnostic if the total number of detected follicular clusters is less than a predetermined threshold. With bootstrapped sampling, FNA-Net achieved a 0.81 F1 score and 0.84 AUC in the precision-recall curve for detecting the non-diagnostic slides whose follicular clusters are less than six. We expect that FNA-Net can dramatically reduce the diagnostic cost associated with FNA biopsy and improve the quality of patient care.

Objective: This paper discusses the feasibility of using mineral element fingerprinting technology of to identify tobacco producing areas, screens out the effective indicators, and constructs the discrimination model of tobacco producing areas. Methods: The contents of 20 mineral elements in tobacco leaves from 11 producing areas were simultaneously determined by ICP-MS, and the data were analyzed by variance analysis, cluster analysis, principal component analysis and discriminant analysis. Results: The contents of 16 elements were significantly different among producing areas, and principal component analysis resulted in 6 principal components, with the cumulative variance contribution of 89.253%. Using linear discriminant analysis, four elementsmineral, K, Mn, Se and Ba, were screened as the effective indicators to discriminate the geographical origin of tobacco leaves. The established discriminant model could accurately distinguish tobacco leaf samples from different tobacco producing areas. Conclusion: Significant differences were showed in the contents of mineral elements in tobacco leaves from 11 producing areas. Four elements, K, Mn, Se and Ba, are important indicators for distinguishing tobacco producing areas. Mineral element fingerprinting technology can be used for distinguishing tobacco producing areas.

Abstract The skin is the largest organ in the human body. Various skin environments on its surface constitutes a complex ecosystem. One of the characteristics of the skin micro‐ecosystem is low biomass, which greatly limits a comprehensive identification of the microbial species through sequencing. In this study, deep‐shotgun sequencing (average 21.5 Gigabyte (Gb)) from 450 facial samples and publicly available skin metagenomic datasets of 2069 samples to assemble a Unified Human Skin Genome (UHSG) catalog is integrated. The UHSG encompasses 813 prokaryotic species derived from 5779 metagenome‐assembled genomes, among which 470 are novel species covering 20 phyla with 1385 novel assembled genomes. Based on the UHSG, the core functions of the skin microbiome are described and the differences in amino acid metabolism, carbohydrate metabolism, and drug resistance functions among different phyla are identified. Furthermore, analysis of secondary metabolites of the near‐complete genomes further find 1220 putative novel secondary metabolites, several of which are found in previously unknown genomes. Single nucleotide variant (SNV) reveals a possible skin protection mechanism: the negative selection process of the skin environment to conditional pathogens. UHSG offers a convenient reference database that will facilitate a more in‐depth understanding of the role of skin microorganisms in the skin.

BackgroundAccurate preoperative assessment of surgical difficulty is crucial to the success of the surgery and patient safety. This study aimed to evaluate the difficulty for endoscopic resection (ER) of gastric gastrointestinal stromal tumors (gGISTs) using multiple machine learning (ML) algorithms.MethodsFrom December 2010 to December 2022, 555 patients with gGISTs in multi-centers were retrospectively studied and assigned to a training, validation, and test cohort. A difficult case was defined as meeting one of the following criteria: an operative time ≥ 90 min, severe intraoperative bleeding, or conversion to laparoscopic resection. Five types of algorithms were employed in building models, including traditional logistic regression (LR) and automated machine learning (AutoML) analysis (gradient boost machine (GBM), deep neural net (DL), generalized linear model (GLM), and default random forest (DRF)). We assessed the performance of the models using the areas under the receiver operating characteristic curves (AUC), the calibration curve, and the decision curve analysis (DCA) based on LR, as well as feature importance, SHapley Additive exPlanation (SHAP) Plots and Local Interpretable Model Agnostic Explanation (LIME) based on AutoML.ResultsThe GBM model outperformed other models with an AUC of 0.894 in the validation and 0.791 in the test cohorts. Furthermore, the GBM model achieved the highest accuracy among these AutoML models, with 0.935 and 0.911 in the validation and test cohorts, respectively. In addition, it was found that tumor size and endoscopists’ experience were the most prominent features that significantly impacted the AutoML model’s performance in predicting the difficulty for ER of gGISTs.ConclusionThe AutoML model based on the GBM algorithm can accurately predict the difficulty for ER of gGISTs before surgery.

The vagina contains at least a billion microbial cells, dominated by lactobacilli. Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age, as well as cervical, fecal, and salivary samples from a second cohort of 632 women. Factors such as pregnancy history, delivery history, cesarean section, and breastfeeding were all more important than menstrual cycle in shaping the microbiome, and such information would be necessary before trying to interpret differences between vagino-cervical microbiome data. Greater proportion of Bifidobacterium breve was seen with older age at sexual debut. The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history. Potential markers for lack of menstrual regularity, heavy flow, dysmenorrhea, and contraceptives were also identified. Lactobacilli were rare during breastfeeding or post-menopause. Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome. Gut and salivary microbiomes, plasma vitamins, metals, amino acids, and hormones showed associations with the vagino-cervical microbiome. Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth.

Background: Kidney renal clear cell carcinoma (KIRC) is a representative histologic subtype of renal cell carcinoma (RCC). RCC exhibits a strong immunogenicity with a prominent dysfunctional immune infiltration. Complement C1q C chain (C1QC) is a polypeptide in serum complement system and is involved in tumorigenesis and the modulation of tumor microenvironment (TME). However, researches have not explored the effect of C1QC expression on prognosis and tumor immunity of KIRC.Methods: The difference in a wide variety of tumor tissues and normal tissues in terms of the C1QC expression was detected using TIMER and TCGA portal databases, and further validation of protein expression of C1QC was conducted via Human Protein Atlas. Then, the associations of C1QC expression with clinicopathological data and other genes were studied with the use of UALCAN database. Subsequently, the association of C1QC expression with prognosis was predicted by searching the Kaplan-Meier plotter database. A protein-protein interaction (PPI) network with the Metascape database was built using STRING software, such that the mechanism underlying the C1QC function can be studied in depth. The TISCH database assisted in the evaluation of C1QC expression in different cell types in KIRC at the single-cell level. Moreover, the association of C1QC and the infiltration level of tumor immune cell was assessed using TIMER platform. The TISIDB website was selected to deeply investigate the Spearman correlation between C1QC and immune-modulator expression. Lastly, how C1QC affected the cell proliferation, migration, and invasion in vitro was assessed using knockdown strategies.Results: KIRC tissues had notably upregulated C1QC level in comparison with adjacent normal tissues, with showed a positive relevance to clinicopathological features including tumor stage, grade, and nodal metastasis, and a negative relevance to clinical prognosis in KIRC. C1QC knockdown inhibited KIRC cell proliferation, migration, and invasion, as indicated by the results of the in vitro experiment. Furthermore, functional and pathway enrichment analysis demonstrated that C1QC was involved in immune system-related biological processes. According to single-cell RNA analysis, C1QC exhibited a specific upregulation in macrophages cluster. Additionally, there was an obvious association of C1QC and a wide variety of tumor-infiltrating immune cells in KIRC. Also, high C1QC expression presented inconsistent prognosis in different enriched immune cells subgroups in KIRC. Immune factors might contribute to C1QC function in KIRC.Conclusion: C1QC is qualified to predict KIRC prognosis and immune infiltration biologically. Targeting C1QC may bring new hope for the treatment of KIRC.

Summary: The oral microbiome has been implicated in a growing number of diseases; however, determinants of the oral microbiome and their roles remain elusive. Here, we investigated the oral (saliva and tongue dorsum) metagenome, the whole genome, and other omics data in a total of 4,478 individuals and demonstrated that the oral microbiome composition and its major contributing host factors significantly differed between sexes. We thus conducted a sex-stratified metagenome-genome-wide-association study (M-GWAS) and identified 11 differential genetic associations with the oral microbiome (psex-difference

Lhasa is a typical high-altitude city with strong solar radiation and high background ozone levels. With the rapid development and urbanization, the emission of volatile organic compounds (VOCs) in Tibet has been increasing annually. However, VOCs activity and the impact on air quality and human health have scarcely been investigated. We conducted online measurement of VOCs in urban Lhasa during May 2019. The mean mixing ratio (with one standard deviation) of the total VOCs was 21.5 ± 18.6 ppb. Of the total VOCs, alkanes, alkenes, and aromatic hydrocarbons accounted for 57.7%, 20.9%, and 21.4%, respectively. On the basis of VOC atmospheric reactivity, the ozone formation potential (OFP) and hydroxyl radical loss rate (LOH) were 91.7 ppb and 3.1 s−1, respectively. Alkenes accounted for the largest proportion of the OFP and LOH, followed by aromatic hydrocarbons. The results of correlation analysis on the benzene series (BTEX), and the similarity of the diurnal changes in CO, NOy, BTEX, and TVOC mixing ratios indicated that Lhasa city strongly affected by motor vehicle emissions. Source apportionments using positive matrix factorization (PMF) model further confirmed that traffic related emissions, including gasoline automobiles, diesel vehicles, and public transportation vehicles fueled with liquid natural gas contributed the most in total VOCs concentration (44.5%–50.2%), LOH (41.6%–46.8%) and OFP (47.4%–52.3%). Biomass combustion, mainly from the traditional biomass fuel in the plateau, was the second contributor to ambient VOCs (41.3%), LOH (26.4%), and OFP (29.7%), and existed a less variation in diurnal changes with a feature of regional background. Plants contributed only about 1.5% to the VOCs concentration but a relatively high (approximately 14.6%) LOH. The noncarcinogenic risk of BTEX did not exceed the hazard quotient value, but the carcinogenic risk of benzene was 4.47 × 10–6, indicating a potential risk.

Smart education is a new education model using modern information technology,and smart behavior analysis is the core component.In the complex classroom scenarios,traditional action recognition algorithms are seriously deficient in accuracy and timeliness.A graph convolutional method based on separation and attention mechanism (DSA-GCN) is proposed to solve the above problems.First,in order to solve the challenge that traditional algorithms are inherently inadequate in aggregating information in the channel domain,multidimensional channel mapping is performed by point-wise convolution,combining the ability of ST-GC to preserve the original spatio-temporal information with the separation ability of depth-separable convolution in spatial and channel feature learning to enhance model feature learning and abstract expressivity.Second,a multi-dimensional fused attention mechanism is used to enhance the model dynamic sensitivity in the spatial convolution domain using self-attention and channel attention mechanisms,and to enhance the key frame discrimination in the temporal convolution domain using temporal and channel attention fusion method.Experiment results show that DSA-GCN achieves better accuracy and effectiveness performance on NTU RGB+D and N-UCLA datasets,and prove the improvement of the ability to aggregate channel information.

The air temperature is a vital measuring variable widely applied in science and engineering as it is considered one vital part of the lives of plants and animals. From the point of view of time series analysis and data-driven modeling, changes in daily 24h air temperature can be described as one time-series data. Compared to relatively complicated models, simple, efficient and of even better performance are advantages of data-driven-based concise modeling methods, especially for embedded applications which usually have limited resources such as low RAM and low processing power. This study takes the perspective of data-driven modeling and time-series analysis to present one succinct and efficient solution based on discrete cosine transform (DCT)-extended modeling for the hourly air temperature forecast (HTF) in engineering and embedded applications. Characteristics of the DCT lie in optimal de-correlation and energy compaction. Orienting upon extended-DCT modeling, one concise least-squares (LS)-extended DCT predictive algorithm for the HTF is introduced. Then one Mbed-based embedded system design utilizing the proposed LS-extended DCT predictive algorithm as well as theoretical analyses and fast computation of arbitrary length DCT is presented. Verification results indicate the suitability of the proposed predictive algorithm. Only the temperature data without other parameters being straightly employed in forecast modeling is one major advantage of the proposed data-driven DCT-based HTF method, which benefits it to be suitable for engineering and embedded applications. [ABSTRACT FROM AUTHOR]

Objective To explore the efficacy and advantages of intracranial-intracranial bypass for the treatment of complex intracranial aneurysms. Methods A total of 9 patients with complex intracranial aneurysms who underwent intracranial-intracranial bypass in Xiangya Hospital of Central South University from February 2014 to May 2020 were included, and were treated with grafts bypass or reimplantation of recipient arteries. All cases underwent CTA or DSA to detect the patent of grafts, whether aneurysms were completely clipped or resected and aneurysms recurrence occurred during the follow-up. Modified Rankin Scale (mRS) was used to evaluate the neurological prognosis at discharge and during the follow - up. Results Radial artery (RA) or great saphenous vein (GSV) was used for interposition in 4 cases, and recipient arteries were used for reimplantation in 5 cases. Of 4 cases of interposition, the cavernous sinus seoment of internal carotid artery (ICA)-GSV-ICA bypass was adopted in one case, middle cerebral artery (MCA) M2-RA-M2 bypass in one case, anterior cerebral artery (ACA) A3-GSV-A3 bypass in one case, posterior cerebral artery (PCA) P2 - RA - P2 bypass in one case. Of 5 cases of reimplantation, MCA M2 inferior trunk was reimplanted to M2 superior trunk in one case, ACA A3 was reimplanted to contralateral A3 in 2 cases, the posterior inferior cerebellar artery (PICA) was reimplanted to the anterior inferior cerebellar artery (AICA) in 2 cases. CTA in 3 d postoperatively showed all cases grafts were patent and aneurysms disappeared. After 3 months of discharge, 2 were lost to follow-up. The other 7 cases kept the patency of grafts and no new aneurysms, and were constantly followed up, with an average follow-up time of 30.71 months, and mRS score was 1 or lower. Conclusions Intracranial-intracranial bypass can be applied for complex intracranial aneurysms that are difficult for conventional surgical treatment to solve. Compared with extracranial - intracranial bypass, its grafts are shorter and its hemodynamics features are more in line with physiological conditions. [ABSTRACT FROM AUTHOR]

NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.

Abstract The oral microbiota contains billions of microbial cells, which could contribute to diseases in many body sites. Challenged by eating, drinking, and dental hygiene on a daily basis, the oral microbiota is regarded as highly dynamic. Here, we report significant human genomic associations with the oral metagenome from more than 1915 individuals, for both the tongue dorsum (n = 2017) and saliva (n = 1915). We identified five genetic loci associated with oral microbiota at study-wide significance (p

Background: Infections of Staphylococcus aureus (S. aureus) often result in osteomyelitis, which is the acute or chronic infections of the bone marrow or bones. TNF-α is long recognized as a key factor contributing to the pathogenesis of osteomyelitis, but little is known about the underlying molecular mechanism. Methods: Expression levels of TNF-α, and several candidate genes, including endothelial nitric oxide synthase (eNOS), known to be downregulated by TNF-α were analysed in MC3T3-E1 cells with S. aureus infection and osteomyelitis patient blood. MicroRNA(miR)-129-5p was predicted and experimentally verified to target eNOS. Alizarin red sulfate (ARS) and alkaline phosphatase (ALP) staining assays were conducted on MC3T3-E1 cells with S. aureus infection to assess the role of TNF-α/miR-129-5p/eNOS on mineralization defect. Results: TNF-α and miR-129-5p were upregulated while eNOS was downregulated in MC3T3-E1 cells with S. aureus infection and osteomyelitis patients, showing inversely correlated expression profiles. MiR-129-5p directly binds to the 3′-UTR of eNOS mRNA to suppress eNOS expression in MC3T3-E1 cells. TNF-α blocker inhibited miR-129-5p and elevated eNOS expression, likely contributing to rescued mineralization defect in S. aureus-infected MC3T3-E1 cells. During S. aureus infection, upregulated TNF-α increases endogenous miR-129-5p expression, which in turn inhibits eNOS, contributing to osteomyelitis. Conclusion: Our study thereby proposes a novel signalling cascade involving TNF-α/miR-129-5p/eNOS in the pathogenesis of osteomyelitis, which may also serve as therapeutic targets.

ABSTRACT Little is unknown about the regulatory mechanisms underlying the pathogenesis of osteomyelitis induced by Staphylococcus aureus. Hypoxia-inducible factor-1α (HIF-1α) and transforming growth factor β1 (TGF-β1) were both upregulated in S. aureus-infected MC3T3-E1 cells and osteomyelitis patients. HIF-1α directly targets the hypoxia-responsive elements (HREs) of TGF-β1 mRNA to induce its expression. Silencing HIF-1α and TGF-β1, as well as treatment of hypoxia inhibitor IDF-11774, consistently elevated OPN and RUNX2 expression and alizarin Red S (ARS) and alkaline phosphatase (ALP) staining levels in MC3T3-E1 cells with S. aureus infection. S. aureus infection increased HIF-1α expression and serum TGF-β1 concentration in a mouse model of osteomyelitis. Hypoxia inhibitor IDF-11774 treatment reduced serum levels of interleukin (IL)-6, IL-1β, and C-reactive protein. Upon S. aureus infection, hypoxia was activated to trigger TGF-β1 upregulation through direct targeting of HRE on TGF-β1 mRNA by HIF-1α, eventually leading to osteomyelitis symptoms in terms of osteogenesis and mineralization deficiencies as well as elevated inflammation. This study hereby suggests a novel signaling cascade involving hypoxia/HIF-1α/TGF-β1 in osteomyelitis pathogenesis, which could potentially serve as a target for therapeutic measures. IMPORTANCE The pathogenesis of osteomyelitis induced by Staphylococcus aureus remains unclear. To develop therapeutic approaches for osteomyelitis, it is important to understand the molecular mechanisms of its pathogenesis. Our results suggests that hypoxia/HIF-1α/TGF-β1 signaling is involved in osteomyelitis pathogenesis. Thus, these findings highlight the potential of this signaling components as therapeutic targets for the treatment of osteomyelitis.