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Abstract Background High-altitude cerebral edema (HACE) is considered an end-stage acute mountain sickness (AMS) that typically occurs in people after rapid ascent to 2500 m or more. While hypoxia is a fundamental feature of the pathophysiological mechanism of HACE, emerging evidence suggests that inflammation serves as a key risk factor in the occurrence and development of this disease. However, little is known about the molecular mechanism underlying their crosstalk. Methods A mouse HACE model was established by combination treatment with hypobaric hypoxia exposure and lipopolysaccharides (LPS) stimulation. Lactylated-proteomic analysis of microglia was performed to reveal the global profile of protein lactylation. Molecular modeling was applied to evaluate the 3-D modeling structures. A combination of experimental approaches, including western blotting, quantitative real-time reverse transcriptionpolymerase chain reaction (qRT-PCR), and enzyme-linked immunosorbent assay (ELISA), confocal microscopy and RNA interference, were used to explore the underlying molecular mechanisms. Results We found that hypoxia exposure increased the lactate concentration and lactylation in mouse HACE model. Moreover, hypoxia aggravated the microglial neuroinflammatory response in a lactate-dependent manner. Global profiling of protein lactylation has shown that a large quantity of lysine-lactylated proteins are induced by hypoxia and preferentially occur in protein complexes, such as the NuRD complex, ribosome biogenesis complex, spliceosome complex, and DNA replication complex. The molecular modeling data indicated that lactylation could affect the 3-D theoretical structure and increase the solvent accessible surface area of HDAC1, MTA1 and Gatad2b, the core members of the NuRD complex. Further analysis by knockdown or selectively inhibition indicated that the NuRD complex is involved in hypoxia-mediated aggravation of inflammation. Conclusions These results revealed a comprehensive profile of protein lactylation in microglia and suggested that protein lysine lactylation plays an important role in the regulation of protein function and subsequently contributes to the neuroinflammatory response under hypoxic conditions.

Abstract Background Breast cancer patients exhibit various response patterns to neoadjuvant chemotherapy (NAC). However, it is uncertain whether diverse tumor response patterns to NAC in breast cancer patients can predict survival outcomes. We aimed to develop and validate radiomic signatures indicative of tumor shrinkage and therapeutic response for improved survival analysis. Methods This retrospective, multicohort study included three datasets. The development dataset, consisting of preoperative and early NAC DCE-MRI data from 255 patients, was used to create an imaging signature-based multitask model for predicting tumor shrinkage patterns and pathological complete response (pCR). Patients were categorized as pCR, nonpCR with concentric shrinkage (CS), or nonpCR with non-CS, with prediction performance measured by the area under the curve (AUC). The prognostic validation dataset (n = 174) was used to assess the prognostic value of the imaging signatures for overall survival (OS) and recurrence-free survival (RFS) using a multivariate Cox model. The gene expression data (genomic validation dataset, n = 112) were analyzed to determine the biological basis of the response patterns. Results The multitask learning model, utilizing 17 radiomic signatures, achieved AUCs of 0.886 for predicting tumor shrinkage and 0.760 for predicting pCR. Patients who achieved pCR had the best survival outcomes, while nonpCR patients with a CS pattern had better survival than non-CS patients did, with significant differences in OS and RFS (p = 0.00012 and p = 0.00063, respectively). Gene expression analysis highlighted the involvement of the IL-17 and estrogen signaling pathways in response variability. Conclusions Radiomic signatures effectively predict NAC response patterns in breast cancer patients and are associated with specific survival outcomes. The CS pattern in nonpCR patients indicates better survival.

BackgroundWith the continuous development of society and the economy, population aging has become an inevitable global development trend, triggering a series of social problems and having a more serious impact on the physical and mental health of middle-aged and older adults. Physical exercise is one of the key factors for improving the overall health and quality of life of individuals, but the role of square dance exercise and the quality of life of middle-aged and older adults have not yet been clarified.PurposeThis study aimed to investigate the associations between square dance exercise and the quality of life of middle-aged and older adults and its mechanism of action, including its effects on physical health and mental health, with negative emotions and attitudes towards aging as mediating variables.MethodThis study adopted a cross-sectional research method, using the Physical Activity Rating Scale (PARS-3), Depression-Anxiety-Stress Scale in Simplified Chinese (DASS-21), Attitudes toward Aging Questionnaire (AAQ), and 12-item Short Form of the Health Survey (SF-12), and launched an online survey on the QuestionStar platform from August–September 2023 for 4,636 middle and older adults aged 45–74 years. The survey results were analyzed via Pearson correlation analysis via SPSS 27.0 and structural equation modeling analysis via Mplus 8.3 to test the model fit and mediation effects.ResultsSquare dance exercise was significantly correlated with negative emotions, attitudes towards aging, and quality of life (r = −0.042–0.878, p

The advanced prostate biopsy robot system has broad application prospects in clinical practice, but due to the deformation and distortion between MR-TRUS (magnetic resonance transrectal ultrasound) images, it poses challenges in biopsy accuracy and safety. The study utilized an advanced prostate biopsy robot system based on MR-TRUS image flexible registration technology and conducted experiments on animal models. Retrospective analysis of the puncture accuracy of 12 animal experiments undergoing prostate puncture using MR-TRUS flexible registration technology from May 2022 to October 2023, and observation of intraoperative and 7-day postoperative complications. The study obtained MR-TRUS images and utilized image processing algorithms for registration to reduce image deformation and distortion. Then, precise positioning and operation are carried out through the robot system to execute the prostate biopsy program. The experimental results indicate that the advanced prostate biopsy robot system based on MR-TRUS image flexible registration technology has demonstrated good feasibility and safety in animal experiments. Image registration technology has successfully reduced image distortion and deformation, improving biopsy accuracy. The precise positioning and operation of robot systems play a crucial role in the biopsy process, reducing the occurrence of complications.

Abstract Background There was limited research data on large‐scale locally advanced non‐small cell lung cancer (LA‐NSCLC) radical radiotherapy (RT) reported in China. This study examined overall survival (OS), progression‐free survival (PFS), treatment effectiveness, and toxicity in patients with LA‐NSCLC treated with definitive RT in the pre‐durvalumab era. Methods A retrospective analysis of demographic information, clinical characteristics, treatment patterns, and clinical outcomes of 789 patients with LA‐NSCLC who underwent radical RT at our center between January 2005 and December 2015 was performed. The Kaplan–Meier method and log‐rank test were used for survival comparisons, and Cox regression was used for multivariate analysis. Results There were 328 patients with stage IIIA disease and 461 with stage IIIB disease. By the last follow‐up, there were 365 overall deaths and 576 cases of recurrence, metastasis, or death. The median survival time was 31 months. The OS rates at 1, 2, 5, and 10 years were 83.7%, 59.5%, 28.8%, and 18.9%, respectively. PFS rates at 1, 2, 5, and 10 years were 48%, 24.5%, 11.9%, and 5.5%, respectively. Rates of ≥grade 3 acute radiation pneumonitis or esophagitis were 7.6% and 1.9%, respectively. Rates of ≥grade 3 chronic radiation pneumonitis and esophagitis were 11% and 0.4%, respectively. Multivariate analysis showed that the Karnofsky Performance Status (KPS) score, smoking status, and combined chemotherapy were prognostic factors for OS (p

Previous studies have shown that major depressive disorder (MDD) patients exhibit structural and functional impairments, but few studies have investigated changes in higher-order coupling between structure and function. Here, we systematically investigated the effect of MDD on higher-order coupling between structural connectivity (SC) and functional connectivity (FC). Each brain region was mapped into embedding vector by the node2vec algorithm. We used support vector machine (SVM) with the brain region embedding vector to distinguish MDD patients from health controls (HCs) and identify the most discriminative brain regions. Our study revealed that MDD patients had decreased higher-order coupling in connections between the most discriminative brain regions and local connections in rich-club organization and increased higher-order coupling in connections between the ventral attentional network and limbic network compared with HCs. Interestingly, transcriptome-neuroimaging association analysis demonstrated the correlations between regional rSC-FC coupling variations between MDD patients and HCs and α/β-hydrolase domain-containing 6 (ABHD6), β 1,3-N-acetylglucosaminyltransferase-9(β3GNT9), transmembrane protein 45B (TMEM45B), the correlation between regional dSC-FC coupling variations and retinoic acid early transcript 1E antisense RNA 1(RAET1E-AS1), and the correlations between regional iSC-FC coupling variations and ABHD6, β3GNT9, katanin-like 2 protein (KATNAL2). In addition, correlation analysis with neurotransmitter receptor/transporter maps found that the rSC-FC and iSC-FC coupling variations were both correlated with neuroendocrine transporter (NET) expression, and the dSC-FC coupling variations were correlated with metabotropic glutamate receptor 5 (mGluR5). Further mediation analysis explored the relationship between genes, neurotransmitter receptor/transporter and MDD related higher-order coupling variations. These findings indicate that specific genetic and molecular factors underpin the observed disparities in higher-order SC-FC coupling between MDD patients and HCs. Our study confirmed that higher-order coupling between SC and FC plays an important role in diagnosing MDD. The identification of new biological evidence for MDD etiology holds promise for the development of innovative antidepressant therapies.

Background: The most effective method for improving the prognosis of lung cancer is the application of low-dose computed tomography (LDCT) for pulmonary nodule screening in populations at high risk. Timely diagnosis and treatment of early-stage lung cancer can contribute to higher long-term survival rates. However, it remains difficult to differentiate malignant from benign pulmonary nodules measuring 8–15 mm, and avoid overtreatment on the one hand and delayed diagnosis on the other hand. In this consensus paper, we aimed to clarify the definition of “high-risk indeterminate pulmonary nodules (IPNs)” and discuss appropriate evaluation and management to facilitate timely diagnosis of lung cancer to improve lung cancer outcome. Direction for future research was discussed. Methods: A multi-disciplinary panel of doctors and IT experts from Asia, Canada and the U.S. were invited to participate. Published evidence and consensus guidelines were used to develop this consensus was clarified. Their evaluation and management were discussed. Findings: The experts believed that the prevalence of pulmonary nodules was very high, and it that was difficult to diagnose early-stage lung cancer due to the small size of the nodules, often leading to delayed diagnosis or overtreatment. To address this issue and to improve long-term outcome, the panel considered important to revise the classification of high-risk IPNs, (1) as pulmonary nodules that cannot be clearly diagnosed with non-surgical biopsy procedures, but is highly suspicious for early-stage lung cancer. The panel also recommends the most responsible should arrange imaging evaluations and follow-ups, taking new technologies into account. Artificial intelligence (AI) assessment based on the Medical Internet of Things (MIoT) can be combined with expert opinion to form a human–computer multidisciplinary team (MDT) that can fully implement the three core procedures of the MIoT, namely, comprehensive perception, reliable transmission, and intelligent processing. This will help to upgrade the non-standard diagnosis and treatment, the so-called “handicraft workshop model”, to a modern assembly-line model that meets international standards. The MIoT technology, which has the potential to realize “simplification of complex problems, digitalization of simple problems, programming of digital problems, and systematization of programming problems”, can promote the homogeneous evaluation of pulmonary nodules by enhancing both the sensitivity and the specificity of detecting early-stage lung cancer, in order to avoid delayed diagnosis and overtreatment. Conclusion: To optimize the evaluation of early-stage lung cancer, and to avoid delayed diagnosis and overtreatment, it is necessary to propose and promote the concept of “high-risk IPNs”. The application of current technologies, AI, and a human–computer MDT, will facilitate improvement in nodule evaluation, transforming the current diagnosis and treatment model, which is akin to production in handicraft workshops, into a modern assembly-line model that meets international standards, and will ultimately result in better prognosis.

Abstract Background The tumor microenvironment and intercellular communication between solid tumors and the surrounding stroma play crucial roles in cancer initiation, progression, and prognosis. Radiomics provides clinically relevant information from radiological images; however, its biological implications in uncovering tumor pathophysiology driven by cellular heterogeneity between the tumor and stroma are largely unknown. We aimed to identify radiogenomic signatures of cellular tumor-stroma heterogeneity (TSH) to improve breast cancer management and prognosis analysis. Methods This retrospective multicohort study included five datasets. Cell subpopulations were estimated using bulk gene expression data, and the relative difference in cell subpopulations between the tumor and stroma was used as a biomarker to categorize patients into good- and poor-survival groups. A radiogenomic signature-based model utilizing dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was developed to target TSH, and its clinical significance in relation to survival outcomes was independently validated. Results The final cohorts of 1330 women were included for cellular TSH biomarker identification (n = 112, mean age, 57.3 years ± 14.6) and validation (n = 886, mean age, 58.9 years ± 13.1), radiogenomic signature of TSH identification (n = 91, mean age, 55.5 years ± 11.4), and prognostic (n = 241) assessments. The cytotoxic lymphocyte biomarker differentiated patients into good- and poor-survival groups (p

Abstract Radiation‐induced dermatitis is one of the most prevalent complications in patients undergoing cancer radiotherapy and poses a significant challenge to cancer therapy. The symptoms include erythema, dry desquamation, and moist desquamation, which are frequently observed in patients with breast, head and neck, anal, and vulvar cancers. Early skin reactions typically manifest within 2–4 weeks following the initiation of radiotherapy. In severe cases, acute dermatitis can cause radiotherapy interruptions, prolong treatment time, and ultimately affect patient outcomes and quality of life. Currently, there are numerous guidelines on radiation dermatitis, including the Multinational Association of Supportive Care in Cancer (MASCC), British Columbia Cancer Agency (BCCA), Oncology Nursing Society (ONS), and UK Society of Radiographers (SCoR) guidelines. In China, dermatology experts have drafted a consensus. However, due to the differing backgrounds of experts, recommendations among guidelines vary. These guidelines were first developed by Chinese radiation oncologists. The evidence‐based guideline in this paper fully considers and adopts China's national conditions; hence, it can be easily applied in daily practice.

Abstract Background Programmed cell death-1 (PD-1) inhibitor was proven to be useful for the recurrent/metastatic head and neck squamous carcinoma (R/M HNSCC) patients. Though both PD-1 inhibitor alone and combination with chemotherapy showed some benefit for PFS and OS, the survival outcome was still not satisfactory. Some studies showed the possible benefit for PD-1 inhibitors combination with radiation for head and neck squamous carcinoma, however there was few studies concerned about synergy of concurrent PD-1 inhibitor combination with chemoradiotherapy for R/M HNSCC. So, we aimed to explore the potential effect and toxicity of the concurrent PD-1 inhibitor and chemoradiotherapy for R/M HNSCC. Methods We consecutively enrolled the R/M HNSCC patients treated with concurrent PD-1 inhibitor and chemoradiotherapy from August 2018 to April 2022 in Sichuan Cancer hospital. All the patients received the combination of PD-1 inhibitor and chemotherapy, and followed with synergy of concurrent PD-1 inhibitor and chemoradiotherapy, then maintenance PD-1 inhibitor. ORR and DCR was calculated by immune-related Response Evaluation Criteria in Solid Tumors (irRECIST-1.1), and Common terminology criteria for adverse events (CTCAE-4.0) was used to evaluate the toxicity.The Kaplan–Meier method was used to analyze OS and PFS. Results 40 R/M HNSCC patients were enrolled in our stuty. The median follow up time was 14 months. 22 patients had recurrent disease only, 16 patients had metastatic disease only, and 2 patients had both recurrence and metastasis disease. For the recurrent lesions, 23 patients received a median radiation dose of 64 Gy (range 50–70 Gy). 18 patients received a median dose of 45 Gy (range 30–66 Gy) for metastatic lesions. The median courses of PD-1 inhibitors and chemotherapy were 8 and 5 respectively. After the treatment, the ORR and DCR were 70.0% and 100%. The median OS was 19 months (range 6.3–31.7 months), with 1 and 2-years OS rates of 72.8% and 33.3%. The median PFS was 9 months (range 3.1–14.9 months), with 6 and 12 months PFS rates of 75.5% and 41.4% respectively. The PFS had no statistical significance in PD-L1 negative and positive group (7 vs 12 months, p = 0.059). The most common grade 3 or 4 adverse events(AE) were leucopenia (25.0%), neutropenia (17.5%), anemia (10.0%), thrombocytopenia (5.0%), hyponatremia (2.5%), and pneumonia(2.5%). No grade 5 AE was observed. Conclusions The synergy of concurrent PD-1 inhibitor treatment with chemoradiotherapy shows promise as a treatment strategy and an acceptable toxicity for the R/M HNSCC patients.

Abstract Hypoxic environments like those present at high altitudes may negatively affect brain function. Varying levels of hypoxia, whether acute or chronic, are previously shown to impair cognitive function in humans. Assessment and prevention of such cognitive impairment require detection of cognitive changes and impairment using specific cognitive function assessment tools. This paper summarizes the findings of previous research, outlines the methods for cognitive function assessment used at a high altitude, elaborates the need to develop standardized and systematic cognitive function assessment tools for high‐altitude hypoxia environments.

Study RegionUpper Colorado River Basin and Great Basin in the United StatesStudy FocusAccurate subseasonal reservoir inflow forecasts and understanding the influence of hydrometeorological forcings on these forecasts are crucial for improving water resources management. Machine learning (ML) techniques, such as long short-term memory (LSTM) networks, perform well for short-term inflow forecasts but have deficiencies in subseasonal forecasts and lack interpretability. To address these limitations, we propose an explainable ML method that integrates an encoder–decoder LSTM (ED-LSTM) network to improve long-term reservoir inflow forecasts and a gradient-based explanation method to quantify the importance of individual hydrometeorological forcings and their interactions on inflow forecasts.New Hydrological Insights for the RegionThe ED-LSTM model outperforms the standard LSTM in the 30-day inflow forecasts at all 30 reservoirs. At the 1-day lead time, ED-LSTM produces NSEs exceeding 0.75 at 29 reservoirs; at the 15-day lead time, about half of reservoirs maintain this high-accurate performance, and when forecasting 30 days ahead, ED-LSTM achieves NSEs exceeding 0.5 at most reservoirs. The variable importance identifies past inflow and temperature as crucial drivers for predicting inflow dynamics. When considering interactions between hydrometeorological forcings, precipitation contributes significantly to inflow forecasting through its interaction with temperature and historical inflow. The proposed method enhances subseasonal reservoir inflow forecasts and the understanding of the impact of hydrometeorological factors, which supports decision-making in reservoir operations.

Abstract The standard of care for patients with recurrent and metastatic nasopharyngeal carcinoma remains unclear. There is an urgent need to identify effective and low‐toxicity treatment methods for such patients. The integration of current evidence to form an optimal treatment modality for recurrent and/or metastatic nasopharyngeal is worth exploring. In recent years, several outstanding clinical trials have emerged for the comprehensive treatment of recurrent and/or metastatic nasopharyngeal carcinoma . New evidence has been added for the local treatment of patients with metastasis. Endoscopic surgery, radiomics, and other technologies help achieve precise local treatment. Novel immunotherapeutic drugs have been approved for the treatment of patients with metastasis in China. The combination of immunotherapy, chemotherapy, and targeted therapy is promising and requires confirmation. Future studies will continue to focus on individualization and precision medicine.

Abstract It is a critical quality assurance activity to effectively detect the root cause of faults causing the software crashes (i.e. crashing faults). Previous studies extracted features to characterise crash instances and built models to identify whether the residences of crashing faults locate inside the stack traces. These models all belong to supervised learning methods which require labelled crash data to be involved. In this study, the introduction of an unsupervised model, called Transfer Spectral Clustering (TSC), for the task of crashing fault residence identification under the unlabelled data scenario is proposed. Unlike traditional unsupervised methods which are applied to individual project data, TSC transfers the knowledge of auxiliary unlabelled data from the source project to assist the clustering task on the unlabelled data from the target project. TSC is an unsupervised transfer learning method, and simultaneously considers the data manifold information of the individual project and feature manifold information across projects to facilitate the clustering effect. Extensive experiments are conducted on a benchmark dataset containing seven software projects. Five indicators were chosen for performance evaluation. The results show that TSC achieves better performance than four clustering based unsupervised methods, and competitive performance compared with eight supervised cross‐project methods.

Abstract Mitophagy is an important metabolic mechanism that modulates mitochondrial quality and quantity by selectively removing damaged or unwanted mitochondria. BNIP3 (BCL2/adenovirus e1B 19 kDa protein interacting protein 3), a mitochondrial outer membrane protein, is a mitophagy receptor that mediates mitophagy under various stresses, particularly hypoxia, since BNIP3 is a hypoxia-responsive protein. However, the underlying mechanisms that regulate BNIP3 and thus mediate mitophagy under hypoxic conditions remain elusive. Here, we demonstrate that in hypoxia JNK1/2 (c-Jun N-terminal kinase 1/2) phosphorylates BNIP3 at Ser 60/Thr 66, which hampers proteasomal degradation of BNIP3 and drives mitophagy by facilitating the direct binding of BNIP3 to LC3 (microtubule-associated protein 1 light chain 3), while PP1/2A (protein phosphatase 1/2A) represses mitophagy by dephosphorylating BNIP3 and triggering its proteasomal degradation. These findings reveal the intrinsic mechanisms cells use to regulate mitophagy via the JNK1/2-BNIP3 pathway in response to hypoxia. Thus, the JNK1/2-BNIP3 signaling pathway strongly links mitophagy to hypoxia and may be a promising therapeutic target for hypoxia-related diseases.

Abstract Purpose We investigated the prognostic value of pretreatment patient‐reported outcomes (PROs) in patients with diffuse large B‐cell lymphoma (DLBCL) receiving obinutuzumab/rituximab plus chemotherapy in the GOYA phase III study. Methods Patients completed the European Organization for Research and Treatment of Cancer Quality of Life (EORTC QLQ‐C30) and the Functional assessment of chronic illness therapy‐Lymphoma (FACT–Lym) lymphoma subscale (LYMS) during the study. PRO scales with high prognostic value were identified through Cox regression analyses of overall survival (OS) and progression‐free survival (PFS). These scales were evaluated in terms of their additional prognostic value beyond the International Prognostic Index (IPI). A preliminary assessment was performed to evaluate whether the scales provided improved patient‐risk stratification beyond IPI. Results One thousand two hundred and fifty‐nine patients with valid pretreatment PRO scales were included in the analyses, and complete pretreatment data were available for 1239/1414 patients (87.6%). Four PRO scales with high prognostic value were identified: FACT–Lym LYMS and EORTC QLQ‐C30 physical functioning, global health status/quality of life (QoL), and fatigue. All four scales retained significant prognostic value for OS and PFS after IPI adjustment (all p

Although extensively studied, it is unknown what is the major cellular energy driving tumor metastasis after anti-cancer radiotherapy. Metabolic reprogramming is one of the fundamental hallmarks in carcinogenesis and tumor progression featured with the increased glycolysis in solid tumors. However, accumulating evidence indicates that in addition to the rudimentary glycolytic pathway, tumor cells are capable of reactivating mitochondrial OXPHOS under genotoxic stress condition to meet the increasing cellular fuel demand for repairing and surviving anti-cancer radiation. Such dynamic metabolic rewiring may play a key role in cancer therapy resistance and metastasis. Interestingly, data from our group and others have demonstrated that cancer cells can re-activate mitochondrial oxidative respiration to boost an annexing energy to meet the increasing cellular fuel demand for tumor cells surviving genotoxic anti-cancer therapy with metastatic potential.

PurposeDuring neoadjuvant chemotherapy (NACT), breast tumor morphological and vascular characteristics are usually changed. This study aimed to evaluate the tumor shrinkage pattern and response to NACT by preoperative multiparametric magnetic resonance imaging (MRI), including dynamic contrast-enhanced MRI (DCE-MRI), diffuse weighted imaging (DWI) and T2 weighted imaging (T2WI).MethodIn this retrospective analysis, female patients with unilateral unifocal primary breast cancer were included for predicting tumor pathologic/clinical response to NACT (n=216, development set, n=151 and validation set, n=65) and for discriminating the tumor concentric shrinkage (CS) pattern from the others (n=193; development set, n=135 and validation set, n=58). Radiomic features (n=102) of first-order statistical, morphological and textural features were calculated on tumors from the multiparametric MRI. Single- and multiparametric image-based features were assessed separately and were further combined to feed into a random forest-based predictive model. The predictive model was trained in the testing set and assessed on the testing dataset with an area under the curve (AUC). Molecular subtype information and radiomic features were fused to enhance the predictive performance.ResultsThe DCE-MRI-based model showed higher performance (AUCs of 0.919, 0.830 and 0.825 for tumor pathologic response, clinical response and tumor shrinkage patterns, respectively) than either the T2WI or the ADC image-based model. An increased prediction performance was achieved by a model with multiparametric MRI radiomic feature fusion.ConclusionsAll these results demonstrated that multiparametric MRI features and their information fusion could be of important clinical value for the preoperative prediction of treatment response and shrinkage pattern.

Long short-term memory (LSTM) networks have demonstrated successful applications in accurately and efficiently predicting reservoir releases from hydrometeorological drivers including reservoir storage, inflow, precipitation, and temperature. However, due to its black-box nature and lack of process-based implementation, we are unsure whether LSTM makes good predictions for the right reasons. In this work, we use an explainable machine learning (ML) method, called SHapley Additive exPlanations (SHAP), to evaluate the variable importance and variable-wise temporal importance in the LSTM model prediction. In application to 30 reservoirs over the Upper Colorado River Basin, United States, we show that LSTM can accurately predict the reservoir releases with NSE ≥ 0.69 for all the considered reservoirs despite of their diverse storage sizes, functionality, elevations, etc. Additionally, SHAP indicates that storage and inflow are more influential than precipitation and temperature. Moreover, the storage and inflow show a relatively long-term influence on the release up to 7 days and this influence decreases as the lag time increases for most reservoirs. These findings from SHAP are consistent with our physical understanding. However, in a few reservoirs, SHAP gives some temporal importances that are difficult to interpret from a hydrological point of view, probably because of its ignorance of the variable interactions. SHAP is a useful tool for black-box ML model explanations, but the hydrological processes inferred from its results should be interpreted cautiously. More investigations of SHAP and its applications in hydrological modeling is needed and will be pursued in our future study.

Acquired radioresistance is a challenge for the cure of glioblastoma. Here, the authors show that radioresistant glioblastoma boosts mitochondrial fatty acid oxidation that fuels cell proliferation and induces immunosuppression via CD47 mediated anti-phagocytosis. Inhibition of FAO by etomoxir combined with anti-CD47 antibodies sensitizes glioblastoma to radiotherapy.

Cell-cell interactions mediated by ligand-receptor complexes are critical to coordinating organismal development and functions. Majority of studies focus on the key time point, the mediator cell types or the critical genes during organismal development or diseases. However, most existing methods are specifically designed for stationary paired samples, there hasn’t been a repository to deal with inferring cell–cell communications in developmental series RNA-seq data, which usually contains multiple developmental stages. Here we present a cell–cell interaction networks inference method and its application for developmental series RNA-seq data (termed dsCellNet) from the developing and aging brain. dsCellNet is implemented as an open-access R package on GitHub. It identifies interactions according to protein localizations and reinforces them via dynamic time warping within each time point and between adjacent time points, respectively. Then, fuzzy clustering of those interactions helps us refine key time points and connections. Compared to other published methods, our methods display high accuracy and high tolerance based on both simulated data and real data. Moreover, our methods can help identify the most active cell type and genes, which may provide a powerful tool to uncover the mechanisms underlying the organismal development and disease.

Summary: During evolution, humans are acclimatized to the stresses of natural radiation and circadian rhythmicity. Radiosensitivity of mammalian cells varies in the circadian period and adaptive radioprotection can be induced by pre-exposure to low-level radiation (LDR). It is unclear, however, if clock proteins participate in signaling LDR radioprotection. Herein, we demonstrate that radiosensitivity is increased in mice with the deficient Period 2 gene (Per2def) due to impaired DNA repair and mitochondrial function in progenitor bone marrow hematopoietic stem cells and monocytes. Per2 induction and radioprotection are also identified in LDR-treated Per2wt mouse cells and in human skin (HK18) and breast (MCF-10A) epithelial cells. LDR-boosted PER2 interacts with pGSK3β(S9) which activates β-catenin and the LEF/TCF mediated gene transcription including Per2 and genes involved in DNA repair and mitochondrial functions. This study demonstrates that PER2 plays an active role in LDR adaptive radioprotection via PER2/pGSK3β/β-catenin/Per2 loop, a potential target for protecting normal cells from radiation injury.

In this paper, the co-occurring characteristics of pore gas and water in the Longmaxi Formation shales in the Sichuan Basin, South China were investigated. Water vapor and methane adsorption by the means of gravimetric methods were carried out to quantitatively determine the behavior of gas and bounding water in micro-nano pores. The impact of the shale compositions and pore structures on the occurring characteristics were discussed. Results showed that the storage capacity of bound water in different types of shales varied dramatically, and the characteristics of bound water could be described by the water vapor adsorption curve and the GAB model. There is an apaprent positive correlation between the maximum monolayer water molecule adsorption capacity and the clay mineral content in shales, indicating that clay minerals provide the main active adsorption sites for water molecules. The adsorption capacity of shale to water molecule is higher than that of methane molecule overall, and methane molecule mainly exist in pores with the form of monolayer adsorption. Bound water, adsorbed gas and free gas could be stored in different pore ranges of different shales. Pores with diameters lower than 2 nm are occupied by bounding water and adsorbed gas. For shales with TOC < 2.5%, free gas would be stored in pores with diameters larger than 5 nm approximately, while for the shales with TOC>2.5%, free gas would be stored in pores with diameters larger than 3 nm approximately. The higher the TOC content, the higher the proportion of the free-gas storage space.

Abstract Background Alzheimer’s disease (AD) is a progressive, degenerative, and terminal disease without cure. There is an urgent need for a new strategy to treat AD. The aim of this study was to investigate the effects of intermittent hypoxic treatment (IHT) on cognitive functions in a mouse model of AD and unravel the mechanism of action of IHT. Methods Six-month-old APPswe/PS1dE9 (APP/PS1) male mice were exposed to hypoxic environment (14.3% O2) 4 h/day for 14 days or 28 days. Cognitive functions were measured by Morris water maze test after either 14 days or 42 days of interval. Thereafter the distribution of amyloid plaque and microglial activation were determined by mouse brain immunohistochemistry, while the amyloid beta (Aβ) and inflammatory cytokines were measured by ELISA and Western Blot. Microarray was used for studying gene expressions in the hippocampus. Results IHT for 14 days or 28 days significantly improved the spatial memory ability of the 6-month-old APP/PS1 mice. The memory improvement by 14 days IHT lasted to 14 days, but not to 42 days. The level of Aβ plaques and neurofilament accumulations was reduced markedly after the IHT exposure. IHT reduced the pro-inflammatory cytokines IL-1β, IL-6 levels, and β-secretase cleavage of APP processing which implies reduced Aβ production. Microarray analysis revealed a large number of genes in the hippocampus were significantly altered which are known to be metabolism-regulated genes. Conclusions This study provides evidence of the beneficial effect of IHT on the progression of AD by alleviating memory impairment, reducing Aβ accumulation and inflammation in the brain. IHT can be developed as a novel measure to relieve the progression of AD by targeting multiple pathways in the AD pathogenesis.

The characteristics and influencing factors of pore development in organic matters of shale are of great significance for shale gas exploration and production in China. The pore development in organic matters of shale has been found to be heterogeneous with SEM observation. However, due to the lack of effective approach for micro-scale research, the influencing factors of pore development of organic matter are still controversial. Black shale samples of the Longmaxi Formation of Pingqiao area of the Sichuan Basin were selected by this study and the heterogeneity of development and distribution of pores in organic matters were analyzed in detail from two-dimensional and three-dimensional levels by the means of Ar ion polishing SEM and FIB-SEM observation. The organic matters with different pore development degrees were divided into three levels, and the area occupancy and contribution to the pores of these three levels of organic matter were studied by MAPS. In this paper, the Raman spectrum of three levels of organic matter with different pore development were obtained by SEM-Raman. The main factors affecting the heterogeneity of pore development of organic matter were discussed in view of the differences of Raman parameters. The results showed that the intensity ratio of D peak to G peak of organic matter was different, which indicated that the order degree of aromatic structure of different organic matter was significantly different, proving that the main factor affecting the pore development in organic matter could be the composition of original organic matter. This method can be used to observe the pores of organic matter in micro area and analyze the molecular structure characteristics of organic matter macerals in-situ, and further clarifies the main influencing factors of pore development of organic matter.

Introducing a coating shell between the filler and matrix is an effective way to reduce the dielectric loss of the particle/matrix dielectric composites. It found that besides the improvement in interface compatibility, there may be some other effects of the coating shell, such as the elimination of the dielectric mismatch. However, the specific mechanism is still unclear due to the absence of an effective model for the quantitative analysis of the relationship between core–shell structure and dielectric loss, hindering the progress of the dielectric composite design. Here, a phase-field model for simulating high-frequency, alternating-field polarization is employed to study the relationship between high-frequency polarization loss and the coating shell in the silicon dioxide coating boron nitride polytetrafluoroethylene-based (BN@SiO2/PTFE) composite. The results show that the dielectric mismatch makes the high-frequency polarization loss spatially localized and periodically time-variant. The reduction of polarization loss depends on the polarization loss of SiO2. To reduce the high-frequency dielectric loss of the composite, the coating shell should not only eliminate the dielectric mismatch, but its dielectric loss must also be lower than that of the core filler. Furthermore, the model provided in this work has the potential to extend the quantitative calculation of non-intrinsic polarization loss and conduction loss.

The Upper Triassic Xujiahe Formation in the Sichuan Basin is a tight sandstone reservoir with developed dissolution pores, but its formation mechanism is still unclear. In this paper, three samples, including feldspathic lithic, lithic arkose and feldspathic quartz sandstones of the Xujiahe Formation, were taken as examples. Some reaction fluid similar to the organic acid component of the formation was prepared. Five kinds of temperature and pressure conditions were applied in the corrosion simulation experiments, and four understandings were obtained. Firstly, with the increase of temperature and pressure, the concentrations of K+ and Na+ ions in the reaction solution increased, the concentrations of Ca2+ and Mg2+ ions remained stable, but the concentration of Al3+ ions decreased significantly. Secondly, the reaction produced a small amount of quartz and a large number of kaolinite and other new minerals, and the dissolution of feldspar particles and carbonate cement produced a large number of dissolution pores, the porosity was increased and the pore structure was then improved. Thirdly, with the same temperature and pressure, the dissolution rate of feldspathic lithic sandstone was relatively higher than that of feldspathic quartz sandstone. With higher temperature and pressure (e.g. 180℃, 53 MPa), the dissolution rate of sandstone samples were significantly increased. Lastly, the results of dissolution experiments provided a reference for the reconstructing of burial sequence, diagenesis as well as pore evolution of the Xujiahe Formation and the distribution of favorable reservoirs can be predicted. The rapid dissolution of feldspar under higher temperature pressure is one of the genetic mechanisms of effective reservoir of deep clastic rock.

Many efforts have been devoted to the forecasting of the capillary force generated by capillary adsorption between solids, which is fundamental and essential in the fields of micro-object manipulation and particle wetting. In this paper, an artificial neural network (ANN) model optimized by a genetic algorithm (GA-ANN) was proposed to predict the capillary force and contact diameter of the liquid bridge between two plates. The mean square error (MSE) and correlation coefficient (R2) were employed to evaluate the prediction accuracy of the GA-ANN model, theoretical solution method of the Young–Laplace equation and simulation approach based on the minimum energy method. The results showed that the values of MSE of capillary force and contact diameter using GA-ANN were 10.3 and 0.0001, respectively. The values of R2 were 0.9989 and 0.9977 for capillary force and contact diameter in regression analysis, respectively, demonstrating the accuracy of the proposed predictive model. The sensitivity analysis was conducted to investigate the influence of input parameters, including liquid volume and separation distance, on the capillary force and contact diameter. The liquid volume and separation distance played dominant roles in affecting the capillary force and contact diameter.

Abstract Background The spread of antibiotic resistance has become one of the most urgent threats to global health, which is estimated to cause 700,000 deaths each year globally. Its surrogates, antibiotic resistance genes (ARGs), are highly transmittable between food, water, animal, and human to mitigate the efficacy of antibiotics. Accurately identifying ARGs is thus an indispensable step to understanding the ecology, and transmission of ARGs between environmental and human-associated reservoirs. Unfortunately, the previous computational methods for identifying ARGs are mostly based on sequence alignment, which cannot identify novel ARGs, and their applications are limited by currently incomplete knowledge about ARGs. Results Here, we propose an end-to-end Hierarchical Multi-task Deep learning framework for ARG annotation (HMD-ARG). Taking raw sequence encoding as input, HMD-ARG can identify, without querying against existing sequence databases, multiple ARG properties simultaneously, including if the input protein sequence is an ARG, and if so, what antibiotic family it is resistant to, what resistant mechanism the ARG takes, and if the ARG is an intrinsic one or acquired one. In addition, if the predicted antibiotic family is beta-lactamase, HMD-ARG further predicts the subclass of beta-lactamase that the ARG is resistant to. Comprehensive experiments, including cross-fold validation, third-party dataset validation in human gut microbiota, wet-experimental functional validation, and structural investigation of predicted conserved sites, demonstrate not only the superior performance of our method over the state-of-art methods, but also the effectiveness and robustness of the proposed method. Conclusions We propose a hierarchical multi-task method, HMD-ARG, which is based on deep learning and can provide detailed annotations of ARGs from three important aspects: resistant antibiotic class, resistant mechanism, and gene mobility. We believe that HMD-ARG can serve as a powerful tool to identify antibiotic resistance genes and, therefore mitigate their global threat. Our method and the constructed database are available at http://www.cbrc.kaust.edu.sa/HMDARG/ . Video abstract (MP4 50984 kb)

Previous studies demonstrate an accumulation of transferrin and transferrin receptor 1 (TfR1) in regenerating peripheral nerves. However, the expression and function of transferrin and TfR1 in the denervated skeletal muscle remain poorly understood. In this study, a mouse model of denervation was produced by complete tear of the left brachial plexus nerve. RNA-sequencing revealed that transferrin expression in the denervated skeletal muscle was upregulated, while TfR1 expression was downregulated. We also investigated the function of TfR1 during development and in adult skeletal muscles in mice with inducible deletion or loss of TfR1. The ablation of TfR1 in skeletal muscle in early development caused severe muscular atrophy and early death. In comparison, deletion of TfR1 in adult skeletal muscles did not affect survival or glucose metabolism, but caused skeletal muscle atrophy and motor functional impairment, similar to the muscular atrophy phenotype observed after denervation. These findings suggest that TfR1 plays an important role in muscle development and denervation-induced muscular atrophy. This study was approved by the Institutional Animal Care and Use Committee of Beijing Institute of Basic Medical Sciences, China (approval No. SYXK 2017-C023) on June 1, 2018.

Abstract Background Metastasis is the most devastating stage of cancer progression and often shows a preference for specific organs. Methods To reveal the mechanisms underlying organ-specific metastasis, we systematically analyzed gene expression profiles for three common metastasis sites across all available primary origins. A rank-based method was used to detect differentially expressed genes between metastatic tumor tissues and corresponding control tissues. For each metastasis site, the common differentially expressed genes across all primary origins were identified as organ-specific metastasis genes. Results Pathways enriched by these genes reveal an interplay between the molecular characteristics of the cancer cells and those of the target organ. Specifically, the neuroactive ligand-receptor interaction pathway and HIF-1 signaling pathway were found to have prominent roles in adapting to the target organ environment in brain and liver metastases, respectively. Finally, the identified organ-specific metastasis genes and pathways were validated using a primary breast tumor dataset. Survival and cluster analysis showed that organ-specific metastasis genes and pathways tended to be expressed uniquely by a subgroup of patients having metastasis to the target organ, and were associated with the clinical outcome. Conclusions Elucidating the genes and pathways underlying organ-specific metastasis may help to identify drug targets and develop treatment strategies to benefit patients.

BackgroundThe search for a method that utilizes biomarkers to identify patients with schizophrenia from healthy individuals has occupied researchers for decades. However, no single indicator can be employed to achieve the good in clinical practice. We aim to develop a comprehensive machine learning pipeline based on neurocognitive and electrophysiological combined features for distinguishing schizophrenia patients from healthy people.MethodsIn the present study, 69 patients with schizophrenia and 50 healthy controls participated. Neurocognitive (contains seven specific domains of cognition) and electrophysiological [prepulse inhibition, electroencephalography (EEG) power spectrum, detrended fluctuation analysis, and fractal dimension (FD)] features were collected, all these features were taken together to generate the identification models of schizophrenia by applying logistics, random forest, and extreme gradient boosting algorithm. The classification capabilities of these models were also evaluated.ResultsBoth the neurocognitive and electrophysiological feature sets showed a good classification effect with the highest accuracy greater than 85% and AUC greater than 90%. Specifically, the performances of the combined neurocognitive and electrophysiological feature sets achieved the highest accuracy of 93.28% and AUC of 97.91%. The extreme gradient boosting algorithm as a whole presented more stably and precisely in classification efficiency.ConclusionThe highest classification accuracy of 93.28% by combination of neurocognitive and electrophysiological features shows that both measurements are appropriate indicators to be used in discriminating schizophrenia patients and healthy individuals. Also, among three algorithms, extreme gradient boosting had better classified performances than logistics and random forest algorithms.

The emergence of tumour adaptive radioresistance can limit the success of radiation therapy and immunotherapy in breast cancer. In this study, the authors demonstrate that CD47 and HER2 are coordinating in tumor response to radiation and that co-blockage of both receptors can eliminate radiorestistant breast cancer cells.

Tumours are made up of heterogeneous subclones. Here, the authors show using breast cancer imaging and gene expression datasets that these subclones can be inferred by the deconvolution of gene expression data, mapped to MRI derived radiogenomic signatures and used to estimate prognosis.

A method for analyzing the pore connectivity of shale based on a suction experiment of tracer fluid is presented. Sodium chloraurate solution is absorbed into shale pores which have been previously evacuated, and then the solute in the pores is converted to gold by heating. After the suction experiment, the sample surface is polished and analyzed with scanning electron microscopy, in order to get the characteristics of connected pores at the nano-scale. The results of two core samples from the Wufeng-Longmaxi formations in the Sichuan Basin show the connected network in shale could be divided into three parts. The interior connectivity of pores in organic matter is related to the density of pores, and organic matter normally has low flow efficiency because of narrow throat radius. Fractures distributed at grain boundaries such as minerals, organic matter and clay sheets are advantageous pathways, and organic pores are connected by grain boundaries. The development of micro-cracks/fractures, which have high permeability, could significantly improve shale connectivity. Shale pore connectivity has great anisotropy, which means connectivity parallel to bedding is much better than that vertical to bedding.

Thin section analysis, X-ray diffraction, conventional scanning electron microscopy (SEM), high-resolution Ar+ ion polishing SEM, mercury intrusion, nitrogen adsorption, total organic carbon (TOC) content and porosity analyses were used to determine the mineral composition, microstructure and micro-pore volume of shale reservoirs from different depths in the Upper Ordovician Wufeng Formation and Lower Silurian Longmaxi Formation in southeastern Sichuan Basin. There are slight differences in the content of siliceous, clay, carbonate and other minerals in shale reservoirs of well D1 in the deep layer and well J1 in the shallow layer, and the longitudinal changes are similar. Only high-quality shale layers with a silica content greater than 40% have different thicknesses. The shale reservoirs of the Wufeng-Longmaxi formations in the deep and shallow layers are dominated by micro-pores in organic matter disseminated in the shale matrix, and the microfractures around the boundaries of silt particles or organic grains and micro-foliation seams parallel to bedding plane are also common, while and intergranular pores are not developed. The high quality shale reservoir at the bottom is structurally isotropic, and the vertical and horizontal structural anisotropy becomes stronger upwards, with thinner micro-lamina and more foliation seams. The TOC content is high at the bottom, and diminishes upwards. The porosity at the bottom shows the same changing trend, indicating a large contribution of organic pores; however, the decrease in porosity is significantly smaller than that of TOC, which is inferred to be related to the existence of more inorganic pores in the shale. The mineral composition, microstructure, TOC and porosity of the Wufeng-Longmaxi shales in the deep and shallow layers have similar changes with depth. Compared with well J1 in the shallow layer, the high-quality reservoir in well D1 in the deep layer has a larger number of micro-pores, meso-pores, macro-pores and total pore volume, which might be explained by more inorganic pores such as grain boundary pores.The shale reservoirs of the Wufeng-Longmaxi formations in the southeastern Sichuan Basin maintain a good porosity under deep burial conditions and have good storage space.

In large-scale environments, scale drift is a crucial problem of monocular visual simultaneous localization and mapping (SLAM). A common solution is to utilize the camera height, which can be obtained using the reconstructed 3D ground points (3DGPs) from two successive frames, as prior knowledge. Increasing the number of 3DGPs by using more proceeding frames can be a natural extension of this solution to estimate a more precise camera height. However, merely employing multiple frames based on conventional methods is hard to be directly applicable in a real-world scenario because the vehicle motion and inaccurate feature matching inevitably cause large uncertainty and noisy 3DGPs. In this study, we propose an elaborate method to collect confident 3DGPs from multiple frames for robust scale estimation. First, we gather 3DGP candidates that can be seen in more than a predefined number of frames. To verify the 3DGP candidates, we filter out the 3D points at the exterior of the road region obtained by the deep-learning-based road segmentation model. In addition, we formulate an optimization problem constrained by a simple but effective geometric assumption that the normal vector of the ground plane lies in the null space of a movement vector of the camera center, and provide a closed-form solution. ORB-SLAM with the proposed scale estimation method achieves the average translation error with 1.19% on the KITTI dataset, which outperforms the state-of-the-art conventional monocular visual SLAM methods in road driving scenarios.

The clinical benefit of cancer immunotherapy, including tumour vaccines, is influenced by immunosuppressive factors in the tumour microenvironment. Among these factors, cancer-associated fibroblasts (CAFs) and their products, such as fibroblast activation protein-α (FAPα), greatly affect tumourigenesis, development, metastasis and treatment tolerance, which make them promising immunotherapy targets for cancer patients. Our previous study reported that a whole cell tumour vaccine (WCTV) expressing FAPα inhibited tumour growth by simultaneously attacking cancer cells and CAFs. This study aimed to improve WCTVs with xenoantigens to end immune tolerance and to further activate the adaptive immune system. In the present study, we designed a WCTV by transducing a vector encoding human FAPα (hFAPα) into murine tumour cells and evaluated its efficacy in multiple solid tumour models. Immunotherapy with this WCTV effectively delayed tumour growth and prevented recurrence. The anti-tumour responses were clearly linked to antigen-specific cytotoxic T cells, whereas CD4(+) T lymphocytes also played a role. Humoural immune responses were activated because the adoptive transfer of immunoglobulins induced abscopal anti-tumour effects, and autoantibodies against FAPα were specifically detected in the sera of immunized mice. Moreover, an increased number of apoptotic tumour cells along with a reduced number of CAFs within the tumours suggest that xenogeneic FAPα-based WCTV has the potential to drive T cell and antibody responses against cancer cells and CAFs. This finding could offer an advanced strategy to treat multiple solid tumours with individualized cancer immunotherapy techniques.

Pore connectivity is crucial for shale gas production. However, the three-dimensional (3D) characteristics and distribution of pore networks and, more fundamentally, the underlying role of different pore types on pore connectivity in shales are inadequately understood. By comparing the 3D pore connectivity derived from direct microstructural imaging of pores filled with Wood’s metal at a pressure corresponding to the finest accessible pore throat in the resolution ranges that may be achieved by X-ray micro-CT and SEM, it is possible to evaluate pore connectivity of different types of shales. The pore connectivity of three shales including a mixed mudstone, siliceous shale, and argillaceous shale from the Silurian Longmaxi Formations is investigated via combined broad ion beam (BIB) polishing, and SEM and X-ray micro-CT imaging after Wood’s metal injection at a pressure up to 380 MPa. The three shales show significant differences in pore connectivity. The mixed mudstone shows excellent pore connectivity in the matrix; the siliceous shale shows an overall poor connectivity with only a small amount of OM (organic matter) pores immediately adjacent to microfractures displaying interconnectivity, while the pores in the argillaceous shale, dominated by plate-like clay pores, are largely not interconnected.

Depression has become one of the severe mental disorders threatening global human health. In this study, we first used the proteomics approach to obtain the differentially expressed proteins in the liver between naive control and chronic social defeat stress (CSDS) induced depressed mice. We have identified the upregulation of iron binding protein transferrin (TF) in the liver, the peripheral blood, and the brain in CSDS-exposed mice. Furthermore, bioinformatics analysis of the Gene Expression Omnibus (GEO) database from various mouse models of depression revealed the significantly upregulated transcripts of TF and its receptor TfR1 in multiple brain regions in depressed mice. We also used the recombinant TF administration via the tail vein to detect its permeability through the blood-brain barrier (BBB). We demonstrated the permeability of peripheral TF into the brain through the BBB. Together, these results identified the elevated expression of TF and its receptor TfR1 in both peripheral liver and the central brain in CSDS-induced depressed mice, and peripheral administration of TF can be transported into the brain through the BBB. Therefore, our data provide a compelling information for understanding the potential role and mechanisms of the cross-talk between the liver and the brain in stress-induced depression.

We investigated, via a phase-field model simulation, the effects of a matrix’s properties and a filler’s characters on the polytetrafluoroethylene (PTFE) crystal growth process in composites under various supercooling degrees. The results show that the supercooling degree has a deciding influence on the crystal growth process. The intrinsic properties of PTFE polymer, such as anisotropic strength and phase transition latent heat, affect the growth rate, orientation, and interfacial integrity of the crystal trunk and the branching of the PTFE crystal growth process. The factors of the PTFE crystallization process, such as anisotropic strength and phase translation interface thickness, affect the uniformity and crystallization degree of the PTFE crystal. In the composites, the biphasic interface induces the crystal growth direction via the polymer chain segment migration rate, of which the degree depends on the shapes of the filler and the PTFE crystal nucleus. According to the results, choosing the low molecular weight PTFE and mixture filler with various particle sizes and surface curvatures as the raw materials of PTFE-based composites improves the crystallization of the PTFE matrix.

Abstract Background Heterogeneity is a common finding within tumours. We evaluated the imaging features of tumours based on the decomposition of tumoural dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data to identify their prognostic value for breast cancer survival and to explore their biological importance. Methods Imaging features (n = 14), such as texture, histogram distribution and morphological features, were extracted to determine their associations with recurrence-free survival (RFS) in patients in the training cohort (n = 61) from The Cancer Imaging Archive (TCIA). The prognostic value of the features was evaluated in an independent dataset of 173 patients (i.e. the reproducibility cohort) from the TCIA I-SPY 1 TRIAL dataset. Radiogenomic analysis was performed in an additional cohort, the radiogenomic cohort (n = 87), using DCE-MRI from TCGA-BRCA and corresponding gene expression data from The Cancer Genome Atlas (TCGA). The MRI tumour area was decomposed by convex analysis of mixtures (CAM), resulting in 3 components that represent plasma input, fast-flow kinetics and slow-flow kinetics. The prognostic MRI features were associated with the gene expression module in which the pathway was analysed. Furthermore, a multigene signature for each prognostic imaging feature was built, and the prognostic value for RFS and overall survival (OS) was confirmed in an additional cohort from TCGA. Results Three image features (i.e. the maximum probability from the precontrast MR series, the median value from the second postcontrast series and the overall tumour volume) were independently correlated with RFS (p values of 0.0018, 0.0036 and 0.0032, respectively). The maximum probability feature from the fast-flow kinetics subregion was also significantly associated with RFS and OS in the reproducibility cohort. Additionally, this feature had a high correlation with the gene expression module (r = 0.59), and the pathway analysis showed that Ras signalling, a breast cancer-related pathway, was significantly enriched (corrected p value = 0.0044). Gene signatures (n = 43) associated with the maximum probability feature were assessed for associations with RFS (p = 0.035) and OS (p = 0.027) in an independent dataset containing 1010 gene expression samples. Among the 43 gene signatures, Ras signalling was also significantly enriched. Conclusions Dynamic pattern deconvolution revealed that tumour heterogeneity was associated with poor survival and cancer-related pathways in breast cancer.

It was of great significance to study the damage evolution mechanism of geomaterial/soil interfaces in landfill seepage control systems to evaluate the slope instability of landfill sites with high dam and large storage capacity. In this paper, the interfacial shear behaviors of geomaterial/soil were studied by drawing test. At the same time, the interface meso-test was used to analyze the change characteristics of geomaterial/soil interfaces during the drawing process. The results showed that under the synergistic action of the interface friction of geotextile/geomembrane and the reinforced shear band at the interface of geotextile/soil, the shear strength and interface stability of the composite geomaterial/soil interface not only increased but also improved. In order to describe the shear deformation and softening characteristics of the geomaterial/soil interfaces, a constitutive model of the interface was established based on the statistical damage theory to study the damage evolution mechanism of the interface under the action of drawing. The fitting results showed that the fitting correlation between the interface constitutive model established in this paper and the shear strength–drawing displacement curves obtained from the tests was greater than 0.97, which indicated that the constitutive model could better describe the shear deformation characteristics of the interface.

Breast tumor morphological and vascular characteristics can be changed during neoadjuvant chemotherapy (NACT). The early changes in tumor heterogeneity can be quantitatively modeled by longitudinal dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is useful in predicting responses to NACT in breast cancer. In this retrospective analysis, 114 female patients with unilateral unifocal primary breast cancer who received NACT were included in a development (n = 61) dataset and a testing dataset (n = 53). DCE-MRI was performed for each patient before and after treatment (two cycles of NACT) to generate baseline and early follow-up images, respectively. Feature-level changes (delta) of the entire tumor were evaluated by calculating the relative net feature change (deltaRAD) between baseline and follow-up images. The voxel-level change inside the tumor was evaluated, which yielded a Jacobian map by registering the follow-up image to the baseline image. Clinical information and the radiomic features were fused to enhance the predictive performance. The area under the curve (AUC) values were assessed to evaluate the prediction performance. Predictive models using radiomics based on pre- and post-treatment images, Jacobian maps and deltaRAD showed AUC values of 0.568, 0.767, 0.630 and 0.726, respectively. When features from these images were fused, the predictive model generated an AUC value of 0.771. After adding the molecular subtype information in the fused model, the performance was increased to an AUC of 0.809 (sensitivity of 0.826 and specificity of 0.800), which is significantly higher than that of the baseline imaging- and Jacobian map-based predictive models (p = 0.028 and 0.019, respectively). The level of tumor heterogeneity reduction (evaluated by texture feature) is higher in the NACT responders than in the nonresponders. The results suggested that changes in DCE-MRI features that reflect a reduction in tumor heterogeneity following NACT could provide early prediction of breast tumor response. The prediction was improved when the molecular subtype information was combined into the model.

To effectively address excessive SO42-, Cr(VI), total chromium and F- in the groundwater of acidic mining areas, a facultative anaerobic bacterium, Citrobacter, with sulfate-reducing properties, tolerance to hexavalent chromium and the ability to reduce Cr(VI) to Cr(III) was isolated and domesticated. Based on microbial immobilization technology, a nano-ZrO2 polyacrylamide hybrid material was prepared as an embedding agent to form nano-ZrO2 polyacrylamide Citrobacter (ZPC) particles. ZPC was microscopically characterized, and the removal performance and mechanism of ZPC for SO42-, Cr(VI), total chromium and F- in groundwater were analyzed. The results of single-factor tests showed that the optimal reaction conditions included a reaction temperature of 35°C, Citrobacter dosage of 35% (volume ratio) in the particles and hybrid material dosage of 300 mL; under these conditions, the removal rates of SO42-, Cr(VI), total chromium and F- were 70.5%, 100%, 100% and 93.3%, respectively, and the pH value increased from 4.6 to 8.07. On this basis, the effects of the reaction layer type, influent hydraulic load and influent concentration on the removal efficiency of polluted groundwater were studied through dynamic experiments. The experimental results showed that ZPC particles were better than Citrobacter as a reaction layer; the optimal influent hydraulic load was 3.0 m3/(m2·d); the selectivity of ZPC particles to anions and anionic groups was different; and the order of adsorption selectivity was F- > Cr(VI) > SO42-.

In this work, a triple-porosity, two-phase flow model was established to fill the knowledge gap of previous models focusing on gas production characteristics while ignoring the impacts of water injection. The proposed model considers the water flow in the fracture systems and clay minerals and the gas flow in the organic matter, inorganic pore, and fracture systems. The proposed model is solved using a finite element approach with COMSOL Multiphysics (Version 5.6) and verified with field data. Then, the evolutions of the intrinsic and relative permeabilities during water injection and gas production are examined. Furthermore, the impacts of water injection time and pressure are investigated. Good verification results are obtained; the goodness-of-fit value is 0.92, indicating that the proposed model can replicate both the water stimulation and the gas production stages. The relative gas permeability declines during water injection but recovers in the gas depletion stage. Furthermore, the intrinsic permeability increases during the water injection stage but decreases during the gas production stage. A higher water injection pressure and longer injection time would enlarge the intrinsic permeability, thus improving flow capacity. However, it would reduce gas relative permeability, thereby hindering gas flow. The shale gas production characteristic is controlled by the two abovementioned competing mechanisms. There exists a perfect combination of water injection pressure and injection time for achieving the maximum profitability of a shale gas well. This work can give a better understanding of the two-phase flow process in shale reservoirs and shed light on the field application of hydraulic fracturing.

The importance of hypoxia in the pathophysiology of inflammatory bowel disease (IBD) is increasingly being realized; also, hypoxia seems to be an important accelerator of brain inflammation, as has been reported by our group and others. IBD is a chronic intestinal disorder that leads to the development of inflammation, which is related to brain dysfunction. However, no studies have reported whether hypoxia is associated with IBD-induced neuroinflammation. Therefore, the objective of the present study was to determine whether hypoxia augments cerebral inflammation in a DSS-induced colitis mouse model. The mouse model was developed using 3% DSS for five days combined with exposure to hypoxic conditions (6,000 m) for two days. Mice were randomly divided into four groups: control group, DSS group, hypoxia group, and DSS plus hypoxia group. The results demonstrated that DSS combined with hypoxia resulted in up-regulation of colonic and plasmatic proinflammatory cytokines. Meanwhile, DSS plus hypoxia increased expression of Iba1, which is a marker of activated microglia, accompanied by increased expression of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) in the brain. Moreover, the expression of tight junction proteins, such as zonula occludens-1 (ZO-1), occludin, and claudin-5, was markedly downregulated. The current study provides new insight into how hypoxia exposure induces excessive inflammatory responses andpathophysiological consequences in the brain in a DSS-induced colitis model.