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Abstract Background Acute coronary syndrome (ACS) is a serious cardiovascular disease that severely affects the quality of life and longevity of patients. MicroRNAs (miRNAs) play a key role in the progression of ACS with significant clinical value. The aim of this study was to examine the clinical value of miR-223-5p in ACS and on the occurrence of major adverse cardiovascular events (MACE) after percutaneous coronary intervention (PCI). Methods The plasma expression of miR-223-5p was detected by RT-qPCR. The correlation of miR-223-5p and cTnI or Gensini score was shown by the Pearson method. Risk factors for the development of ACS were analyzed by multivariate logistic regression. The efficacy of miR-223-5p in identifying patients with ACS was shown by ROC curve. The predictive value of miR-223-5p for MACE development in ACS patients within 6 months after PCI was assessed by Kaplan-Meier curve and multivariate Cox regression. Results miR-223-5p levels were markedly elevated in ACS patients. miR-223-5p was found to be positively related to cTnI or Gensini score. miR-223-5p was a risk factor for ACS and significantly identified patients with ACS. MACE was more likely to occur after PCI in patients with high miR-223-5p levels, and miR-223-5p was an independent prognostic indicator of MACE. Conclusions miR-223-5p had diagnostic value for ACS and predicted MACE after PCI.

Abstract Purpose This study aims to elucidate the biological functions of ferroptosis-related genes in periodontitis, along with their correlation to tumor microenvironment (TME) features such as immune infiltration. It aims to provide potential diagnostic markers of ferroptosis for clinical management of periodontitis. Methods Utilizing the periodontitis-related microarray dataset GSE16134 from the Gene Expression Omnibus (GEO) and a set of 528 ferroptosis-related genes identified in prior studies, this research unveils differentially expressed ferroptosis-related genes in periodontitis. Subsequently, a protein–protein interaction network was constructed. Subtyping of periodontitis was explored, followed by validation through immune cell infiltration and gene set enrichment analyses. Two algorithms, randomForest and SVM(Support Vector Machine), were employed to reveal potential ferroptosis diagnostic markers for periodontitis. The diagnostic efficacy, immune correlation, and potential transcriptional regulatory networks of these markers were further assessed. Finally, potential targeted drugs for differentially expressed ferroptosis markers in periodontitis were predicted. Results A total of 36 ferroptosis-related genes (30 upregulated, 6 downregulated) were identified from 829 differentially expressed genes between 9 periodontitis samples and the control group. Subsequent machine learning algorithm screening highlighted 4 key genes: SLC1A5(Solute Carrier Family 1 Member 5), SLC2A14(Solute Carrier Family 1 Member 14), LURAP1L(Leucine Rich Adaptor Protein 1 Like), and HERPUD1(Homocysteine Inducible ER Protein With Ubiquitin Like Domain 1). Exploration of these 4 key genes, supported by time-correlated ROC analysis, demonstrated reliability, while immune infiltration results indicated a strong correlation between key genes and immune factors. Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted for the four key genes, revealing enrichment in GO/KEGG pathways that have a significant impact on periodontitis. Finally, the study predicted potential transcriptional regulatory networks and targeted drugs associated with these key genes in periodontitis. Conclusions The ferroptosis-related genes identified in this study, including SLC1A5, SLC2A14, LURAP1L, and HERPUD1, may serve as novel diagnostic and therapeutic targets for periodontitis. They are likely involved in the occurrence and development of periodontitis through mechanisms such as immune infiltration, cellular metabolism, and inflammatory chemotaxis, potentially linking the ferroptosis pathway to the progression of periodontitis. Targeted drugs such as flurofamide, L-733060, memantine, tetrabenazine, and WAY-213613 hold promise for potential therapeutic interventions in periodontitis associated with these ferroptosis-related genes.

In this paper, a novel casein phosphopeptide fractionation process was proposed based on the calcium chelating properties of casein phosphopeptide and different casein phosphopeptide fractions with different chelating abilities and enhanced purity were produced using different calcium ion concentrations. Three casein phosphopeptide-calcium chelate fractions (CPP1-Ca, CPP2-Ca and CPP3-Ca) were precipitated hierarchically from the trypsin digest of casein by increasing the Ca2+ addition step by step in an ethanol solution with a concentration of 55% (v/v), and PBS was used to decalcify to obtain the corresponding casein phosphopeptides (CPP1, CPP2 and CPP3). The physicochemical properties and calcium uptake characteristics of the three casein phosphopeptide-calcium chelate fractions were analyzed and compared with those of the peptide-calcium chelate fraction (CPP-Ca) obtained by the conventional calcium-ethanol precipitation method as a control. The results showed that among the three casein phosphopeptide-calcium chelate fractions, CPP3-Ca contained the highest purity and calcium chelating amount of 89.42% and 69.59 mg/g, respectively, which were significantly higher than those of the ungraded CPP-Ca of 83.77% and 55.05 mg/g. The analysis of the amino acid composition and the N/P (molar ratio) revealed that the CPP3-Ca contained a higher phosphatidylserine group, which in turn binds more Ca2+. Analysis of the calcium holding capacity of different casein phosphopeptide fractions showed that CPP3 was able to better delay and prevent the formation of calcium phosphate precipitation, and had a higher calcium holding capacity. Meanwhile, CPP3-Ca had higher calcium solubility in the simulated intestinal environment, indicating that the in vitro bioavailability of the graded casein phosphopeptide-calcium chelates was improved.

Abstract Background To investigate the role of C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) as early predictors of infectious complications after laparoscopic gastric cancer surgery. Methods Patients who underwent laparoscopic gastric cancer surgery between January 2020 and June 2022 were retrospectively enrolled. IL-6, PCT, and CRP levels were assessed before surgery and on postoperative days (PODs) 3 and 5. Differences in serum IL-6, PCT, and CRP levels between the infected and non-infected groups were compared. The diagnostic accuracy was determined using the area under the receiver operating characteristic curve (AUC). Results A total of 206 patients were enrolled, and 21 patients (10.19%) developed postoperative infections. Serum IL-6, PCT, and CRP levels in the infected group were significantly higher than those in the non-infected group on PODs 3 and 5. IL-6 with an optimal cutoff value of 84.00 pg/mL (AUC 0.84), PCT with an optimal cutoff value of 1.39 ng/mL (AUC 0.80), CRP with an optimal cutoff value of 150.00 mg/L (AUC 0.76) on POD 3 had superior diagnostic accuracy in predicting postoperative infections. Multivariate analysis identified PCT and IL-6 levels on POD 3 as independent risk factors, the AUC of the combination of IL-6 and PCT was 0.89. The Delong test showed no difference between the AUC of IL-6 alone and IL-6 combined with PCT prediction (P = 0.07, Z = 1.81). Conclusions IL-6 level on POD 3 is an excellent predictor of infectious complications following laparoscopic gastric cancer surgery. Patients with IL-6 levels lower than 84.00 pg/mL on POD 3 can ensure safe early discharge with a low probability of infection.

Abstract Nitrate (NO3 ‒) pollution poses significant threats to water quality and global nitrogen cycles. Alkaline electrocatalytic NO3 ‒ reduction reaction (NO3RR) emerges as an attractive route for enabling NO3 ‒ removal and sustainable ammonia (NH3) synthesis. However, it suffers from insufficient proton (H+) supply in high pH conditions, restricting NO3 ‒-to-NH3 activity. Herein, we propose a halogen-mediated H+ feeding strategy to enhance the alkaline NO3RR performance. Our platform achieves near-100% NH3 Faradaic efficiency (pH = 14) with a current density of 2 A cm–2 and enables an over 99% NO3 –-to-NH3 conversion efficiency. We also convert NO3 ‒ to high-purity NH4Cl with near-unity efficiency, suggesting a practical approach to valorizing pollutants into valuable ammonia products. Theoretical simulations and in situ experiments reveal that Cl-coordination endows a shifted d-band center of Pd atoms to construct local H+-abundant environments, through arousing dangling O-H water dissociation and fast *H desorption, for *NO intermediate hydrogenation and finally effective NO3 ‒-to-NH3 conversion.

Abstract Background Chronic postsurgical pain (CPP) markedly impairs patients’ quality of life. Research has shown that chronic stress may extend incisional nociception in male mice. Dopaminergic (DAergic) neurons in the ventral tegmental area (VTA) are integral to stress-related mental disorders (including major depressive disorder, anxiety disorders, and PTSD) and pain. However, the impact of chronic social defeat stress (CSDS) on mesolimbic dopamine (DA) transmission in the development of CPP is yet to be established. It remains uncertain whether the dopamine signals in the rostral anterior cingulate cortex (rACC), which regulate pain, derive from the VTA. This study aims to explore the role of VTA-rACC dopaminergic circuits in a mouse model of CPP induced by CSDS. Methods We conducted CSDS on C57BL/6 J wild-type male mice (n = 12–16 mice/group) and DAT-cre male mice (n = 10–12 mice/group). After 10 days of CSDS, a left posterior plantar incision was made to establish a mouse model of CPP. Paw withdrawal thresholds (PWTs) were evaluated using Von-Frey fibre stimulation. The open field test (OFT) and elevated plus maze test (EPM) were used to assess pain-related negative emotions. We used immunofluorescence staining and Western Blot to analyse D1, D2, c-Fos, and TH expression. DAergic fibre projections in the VTA-rACC neural pathway were traced using retrograde tracing and immunofluorescence staining. Optogenetics and Chemogenetics were employed to manipulate DAergic neurons in the VTA and their axons in the rACC. Results The ipsilateral PWTs in male C57BL/6 J mice significantly decreased after surgery, returning to baseline after seven days. Conversely, in CSDS mice, ipsilateral PWTs remained reduced for at least 30 days post-incision. A significant reduction in TH-positive neurons expressing c-Fos in the VTA of CPP mice was observed 15 days post-incision. Activating DAergic neurons significantly improved ipsilateral PWTs and locomotor performance in the OFT and EPM in CPP mice post-incision. Additionally, D1 expression in the rACC was found to decrease in CPP mice, and this reduction counteracted the increase in PWTs caused by activating DAergic neuron axon terminals in the rACC. Conclusion CSDS results in chronicity of postsurgical nociception and anxiety-like negative emotions, with alterations in DA transmission playing a role in CPP. Specific activation of DAergic neurons mitigates nociceptive responses and anxiety-like bahaviors, possibly mediated by D1 receptors in the rACC.

Abstract Tumor metastasis severely limits the prognosis of gastric cancer patients. RNA-binding proteins (RBPs) are crucial in tumor metastasis, yet there is limited research into their involvement in gastric cancer. Here, we found that ESRP1, a RBP specific in epithelial cells, is important in regulating the metastasis of gastric cancer cells. ESRP1 is negatively correlated with distant metastasis and lymph node metastasis in gastric cancer patients. And we demonstrated that ESRP1 inhibit migration and invasion of gastric cancer in vitro and in vivo. Mechanistically, ESRP1 promotes exon 11 alternative splicing of CLSTN1 pre-mRNA. The post-splicing short CLSTN1 stabilizes the Ecadherin/β-catenin binding structure, and promotes β-catenin protein ubiquitination and degradation, thereby inhibiting the migration and invasion of gastric cancer cells. Our study highlights the role of ESRP1 in regulating metastasis of gastric cancer and extends its mechanism. These results provide a possibility for ESRP1 and CLSTN1 to become therapeutic targets for metastasis of gastric cancer.

Abstract Background Laparoscopic gastrectomy (LG) is increasingly applied in locally advanced gastric cancer (LAGC) after neoadjuvant chemotherapy (NC). However, there is no study to comprehensively evaluate the clinicopathological, prognostic, and laboratory data such as nutrition, immune, inflammation-associated indexes, and tumor markers between LG and open gastrectomy (OG) for LAGC following NC. Methods The clinicopathological, prognostic, and laboratory data of LAGC patients with clinical stage of cT2-4aN1-3M0 who underwent gastrectomy after NC were retrospectively collected. The effects of LG and OG were compared after propensity score matching (PSM). Results This study enrolled 148 cases, of which 110 cases were included after PSM. The LG group had a shorter length of incision (P

Objectives: Studies on rectal neuroendocrine tumors (R-NETs) that are 1–2 cm in size are limited, and the optimal treatment for these tumors is not well established. Methods: Data from patients with primary localized R-NETs 1–2 cm in size were retrospectively collected from 17 large-scale referral medical centers in China. Long-term prognosis, quality of life (QOL), and fecal incontinence were evaluated, and the effects of local excision (LE) or radical resection (RR) were elucidated using propensity score matching (PSM). Results: A total of 272 patients were included in this study; 233 underwent LE, and the remaining 39 underwent RR. Patients in the LE group showed lower tumor location, fewer postoperative Clavien–Dindo III–V complications, more G1 tumors, and lower tumor stage. There were no significant differences in the relapse-free survival or overall survival (OS) between the LE and RR groups after PSM. Patients in the LE group reported superior physical, role, emotional, social, and cognitive functions, global QOL, and Wexner fecal incontinence scores compared with those in the RR group (all P 1.80 (OR = 4.50, 1.46–15.89, P = 0.012), and T3–T4 (OR = 36.31, 95% CI 7.85–208.62, P 1.8 or T3/T4 tumors, RR should be considered.

Summary: Wearable devices realize health monitoring, information transmission, etc. In this study, the human-friendliness, adaptability, reliability, and economy (HARE) principle for designing human energy harvesters is first proposed and then a biomechanical energy harvester (BMEH) is proposed to recover the knee negative energy to generate electricity. The proposed BMEH is mounted on the waist of the human body and connected to the ankles by ropes for driving. Double-rotor mechanism and half-wave rectification mechanism design effectively improves energy conversion efficiency with higher power output density for more stable power output. The experimental results demonstrate that the double-rotor mechanism increases the output power of the BMEH by 70% compared to the single magnet-rotor mechanism. And the output power density of BMEH reaches 0.07 W/kg at a speed of 7 km/h. Furthermore, the BMEH demonstrates the excitation mode detection accuracy of 99.8% based on the Gate Recurrent Unit deep learning model with optimal parameters.

Abstract Visual adaptation that can autonomously adjust the response to light stimuli is a basic function of artificial visual systems for intelligent bionic robots. To improve efficiency and reduce complexity, artificial visual systems with integrated visual adaptation functions based on a single device should be developed to replace traditional approaches that require complex circuitry and algorithms. Here, we have developed a single two-terminal opto-sensor based on multilayer γ-InSe flakes, which successfully emulated the visual adaptation behaviors with a new working mechanism combining the photo-pyroelectric and photo-thermoelectric effect. The device can operate in self-powered mode and exhibit good human-eye-like adaptation behaviors, which include broadband light-sensing image adaptation (from ultraviolet to near-infrared), near-complete photosensitivity recovery (99.6%), and synergetic visual adaptation, encouraging the advancement of intelligent opto-sensors and machine vision systems.

Wheat stripe rust poses a marked threat to global wheat production. Accurate and effective disease severity assessments are crucial for disease resistance breeding and timely management of field diseases. In this study, we propose a practical solution using mobile-based deep learning and model-assisted labeling. StripeRust-Pocket, a user-friendly mobile application developed based on deep learning models, accurately quantifies disease severity in wheat stripe rust leaf images, even under complex backgrounds. Additionally, StripeRust-Pocket facilitates image acquisition, result storage, organization, and sharing. The underlying model employed by StripeRust-Pocket, called StripeRustNet, is a balanced lightweight 2-stage model. The first stage utilizes MobileNetV2-DeepLabV3+ for leaf segmentation, followed by ResNet50-DeepLabV3+ in the second stage for lesion segmentation. Disease severity is estimated by calculating the ratio of the lesion pixel area to the leaf pixel area. StripeRustNet achieves 98.65% mean intersection over union (MIoU) for leaf segmentation and 86.08% MIoU for lesion segmentation. Validation using an additional 100 field images demonstrated a mean correlation of over 0.964 with 3 expert visual scores. To address the challenges in manual labeling, we introduce a 2-stage labeling pipeline that combines model-assisted labeling, manual correction, and spatial complementarity. We apply this pipeline to our self-collected dataset, reducing the annotation time from 20 min to 3 min per image. Our method provides an efficient and practical solution for wheat stripe rust severity assessments, empowering wheat breeders and pathologists to implement timely disease management. It also demonstrates how to address the “last mile” challenge of applying computer vision technology to plant phenomics.

IntroductionThe cold stress is one of the most important factors for affecting production throughout year, so effectively evaluating frost damage is great significant to the determination of the frost tolerance in lettuce.MethodsWe proposed a high-throughput method to estimate lettuce FDI based on remote sensing. Red-Green-Blue (RGB) and multispectral images of open-field lettuce suffered from frost damage were captured by Unmanned Aerial Vehicle platform. Pearson correlation analysis was employed to select FDI-sensitive features from RGB and multispectral images. Then the models were established for different FDI-sensitive features based on sensor types and different groups according to lettuce colors using multiple linear regression, support vector machine and neural network algorithms, respectively.Results and discussionDigital number of blue and red channels, spectral reflectance at blue, red and near-infrared bands as well as six vegetation indexes (VIs) were found to be significantly related to the FDI of all lettuce groups. The high sensitivity of four modified VIs to frost damage of all lettuce groups was confirmed. The average accuracy of models were improved by 3% to 14% through a combination of multisource features. Color of lettuce had a certain impact on the monitoring of frost damage by FDI prediction models, because the accuracy of models based on green lettuce group were generally higher. The MULTISURCE-GREEN-NN model with R2 of 0.715 and RMSE of 0.014 had the best performance, providing a high-throughput and efficient technical tool for frost damage investigation which will assist the identification of cold-resistant green lettuce germplasm and related breeding.

The cGAS/STING signaling pathway plays a pivotal role in regulating innate immunity. Emerging novel drugs aim to regulate the anti-tumor immune response by activating innate immunity. The anti-diabetic drug metformin has been reported to exhibit anti-cancer effect against various types of cancer. However, the role of metformin in regulating the cGAS/STING signaling pathway in gastric cancer remains unknown. In our study, we first used bioinformatic analysis to detect that metformin is closely related to tumor immunity in multiple tumors. Next, we validated the function of metformin in activating the cGAS/STING signaling pathway in gastric cancer cell lines. In addition, KEGG pathway enrichment analysis showed that metformin is negatively correlated with the PI3K/AKT signaling pathway in gastric cancer. We further verified that metformin activates the cGAS/STING signaling pathway by blocking AKT phosphorylation. Moreover, we found that metformin regulates the AKT signaling pathway by mediating the transcription factor SOX2. Thus, our study indicates that metformin activates the cGAS/STING signaling pathway by suppressing SOX2/AKT and has promising potential in gastric cancer immunotherapy.

Abstract The microtubule (MT) plus-end binding protein Clip170 is associated closely with breast cancer invasion and migration. In this study, Clip170 tension observed by a newly designed cpstFRET tension probe was suggested to be positive related to breast cancer aggressiveness, which could be regulated by α-tubulin detyrosination-induced MT disassembly. Clip170 phosphorylation induced by Ribosomal protein S6 kinase (RSK) could also increase its tension and promote the conversion of a discrete comet-like Clip-170 distribution into a spotty pattern during cancer metastasis. Heightened Clip170 tension was correlated with the formation of cortactin-associated filopodia and lamellipodia, and then promoted invasion and metastasis both in vitro and in vivo. Meanwhile, Clip170 tension enhanced at the leading edge in directional migration, accompanying with IQGAP1 subcellular distribution variation. Our work indicates that the malignancy and directionality during breast cancer migration depend on the magnitude and polarization of Clip170 tension, and we suggest Clip170 tension as a new potential drug target for breast cancer therapy.

Abstract Background The accuracy of lymph node ratio (LNR) as a prognostic index remains to be proven for gastric cancer patients after neoadjuvant chemotherapy (NACT). This study sought to investigate the prognostic value of LNR in locally advanced gastric cancer (LAGC) patients after NACT. Methods LAGC patients with clinical TNM stages 2–3, Her2(−), and Eastern Cooperative Oncology Group, scores 0–2 are routinely scheduled with NACT. Patients with LAGC after NACT and surgical operation between January 2012 and October 2020 were retrospectively reviewed. The correlation between LNR and survival was investigated. Results Overall, 148 patients were enrolled: 103 with low-LNR (LNR ≤ 30%) and 45 with high-LNR (LNR > 30%). Approximately, 50.5% and 24.4% patients responded to NACT at the primary site in the low-LNR and high-LNR groups, respectively. The overall survival (OS) and progression-free survival (PFS) of low-LNR group were considerably better than those of high-LNR group (3-year OS: 81.9% vs 18.5%, P < 0.001; 3-year PFS: 72.6% vs 13.5%, P < 0.001). In the low-LNR group, OS and PFS were superior in patients with tumor regression grade (TRG) 0–2 than in those with TRG 3 (3-year OS: 89.2% vs 73.2%, P = 0.086; 3-year PFS: 80.3% vs 66.5%, P = 0.036). In association with OS and PFS, the degree of tumor differentiation, TRG, and LNR were identified as predictive factors, and LNR was identified as the independent prognostic factor in univariate and multivariate analyses, respectively. Conclusions LNR is a prospective index of prognosis in patients with LAGC after NACT.

ObjectivesImmunotherapy plus chemotherapy has recently been applied in the neoadjuvant treatment for locally advanced gastric cancer (LAGC), while its superiority over neoadjuvant chemotherapy (NACT) alone remains to be explored. This study explored the safety and efficacy of NACT plus tislelizumab in patients with LAGC.MethodsThe data on patients with LAGC who received NACT combined with radical gastrectomy and NACT plus tislelizumab followed by radical gastrectomy was retrospectively collected. Clinicopathological characteristics of the two groups were compared.ResultsA total of 119 and 50 patients with gastric cancer treated with NACT and NACT plus tislelizumab, respectively, were enrolled. No significant difference was found between the baseline data of the two groups. The operative time (210.5 ± 70.4 min vs. 237.6 ± 68.4 min, P=0.732), intraoperative blood loss (157.8 ± 75.9 ml vs. 149.1 ± 92.5 ml, P=0.609), and number of dissected lymph nodes (24.7 ± 9.3 vs. 28.1 ± 10.3, P=0.195) was not statistically different between the two groups. In comparison to the NACT plus tislelizumab group, the R0 resection rate (100% vs. 89.9%, P=0.019) and pathologic complete response rate (26.0% vs. 3.4%, P

With the rapid development of urban transportation facilities, their construction inevitably encounters unfavorable conditions, such as rivers and lakes. When using the weir construction method to build transportation facilities in lakes, the design scheme for the pit slope excavation inside the cofferdam is related to the success or failure of the construction. In this study, the design scheme for pit excavations in lakes is discussed and analyzed using numerical simulation and on-site monitoring against the background of Jinji Lake Tunnel. The findings are as follows. (1) The greater the distance between the pit and the cofferdam, the smaller the impact of pit excavation on the cofferdam is; when the excavation depth is 10 m and the distance is more than 47 m, the deformation of the whole pile is less than 15 mm. (2) Under the condition that the platform width is kept the same, the smaller the height and width ratio is, the greater the safety factor will be, and under the condition that the height and width ratio is kept the same, the longer the platform width is, the greater the safety factor will be. (3) When the pit and cofferdam are far away from each other, different slope release design schemes have different effects on cofferdam deformation and stability. The results of this research can provide references and guidance for the design and construction of similar projects.

The coverage and throughput of data-independent acquisition (DIA)-based phosphoproteomics is limited by its dependence on experimental spectral libraries. Here the authors develop a DIA workflow based on in silico spectral libraries generated by a novel deep neural network to expand phosphoproteome coverage.

BackgroundThe role of gut microbiota in diabetes mellitus (DM) and its complications has been widely accepted. However, the alternation of gut microbiota in diabetic microvascular complications (DC) remains to be determined.MethodsPublications (till August 20th, 2022) on gut microbiota in patients with DC were retrieved from PubMed, Web of Science, Embase and Cochrane. Review Manager 5.3 was performed to estimate the standardized mean difference (SMD) and 95% confidence interval (CI) and calculate alpha diversity indices and the relative abundance of gut microbiota between patients in DC v.s. DM and DC v.s. healthy controls (HC).ResultsWe included 13 studies assessing 329 patients with DC, 232 DM patients without DC, and 241 HC. Compared to DM, patients with DC shared a significantly lower Simpson index (SMD = -0.59, 95% CI [-0.82, -0.36], p < 0.00001), but a higher ACE index (SMD = 0.42, 95% CI[0.11, 0.74], p = 0.009). Compared to HC, DC patients held a lower ACE index (SMD = -0.61, 95% CI[-1.20, -0.02], p = 0.04). The relative abundances of phylum Proteobacteria (SMD = 0.03, 95% CI[0.01, 0.04], p = 0.003, v.s. HC) and genus Klebsiella (SMD = 0.00, 95% CI[0.00, 0.00], p < 0.00001, v.s. HC) were enriched, accompanying with depleted abundances of phylum Firmicutes (SMD = -0.06, 95% CI[-0.11, -0.01], p = 0.02, v.s. HC), genera Bifidobacterium (SMD = -0.01, 95% CI[-0.02,-0.01], p < 0.0001, v.s. DM), Faecalibacterium (SMD = -0.01, 95% CI[-0.02, -0.00], p = 0.009, v.s. DM; SMD = -0.02, 95% CI[-0.02, -0.01], p < 0.00001, v.s. HC) and Lactobacillus (SMD = 0.00, 95% CI[-0.00, -0.00], p < 0.00001, v.s. HC) in DC.ConclusionsGut microbiota perturbations with the depletion of alpha diversity and certain short-chain fatty acids (SCFAs)-producing bacteria were associated with the pathology of DC. Therefore, gut microbiota might serve as a promising approach for the diagnosis and treatment of DC. Further investigations are required to study the mechanisms by which gut dysbiosis acts on the onset and progression of DC.

Coal-fired slag concrete is gradually used in underground projects such as coal mines. Due to the differences between concrete composites and rocks, the failure of coal-fired slag concrete cannot be predicted from the essence through the stress–strain curve. However, studying the deformation and failure law of concrete from the perspective of energy can be closer to the essence of concrete deformation and failure. Therefore, in this paper, with the help of RLJW-2000 testing machine, the uniaxial compression test of C15 strength grade coal-fired slag concrete is carried out, the energy evolution law in the process of deformation and failure of coal-fired slag concrete is analyzed, and the failure criterion based on energy consumption ratio is established. The results show that with the increase of slag-cement ratio, the total energy and elastic strain energy at the peak point gradually decrease. The evolution of peak energy density satisfies the exponential function relation with e as the base. The process that the elastic energy consumption ratio changes from the stable state tending to 0 to the beginning of growth, or the process that the elastic energy consumption ratio changes from negative value to 0, and then gradually increases to positive value can be used as the energy criterion for the strength failure of coal-fired slag concrete. The research results can essentially analyze the instability and failure of coal-fired slag concrete, which is of great significance to ensure the safety of coal-fired slag concrete in engineering application.

Abstract Background Identification of genomic biomarkers to predict the anticancer effects of indicated drugs is considered a promising strategy for the development of precision medicine. DNA endonuclease MUS81 plays a pivotal role in various biological processes during malignant diseases, mainly in DNA damage repair and replication fork stability. Our previous study reported that MUS81 was highly expressed and linked to tumor metastasis in gastric cancer; however, its therapeutic value has not been fully elucidated. Methods Bioinformatics analysis was used to define MUS81-related differential genes, which were further validated in clinical tissue samples. Gain or loss of function MUS81 cell models were constructed to elucidate the effect and mechanism of MUS81 on WEE1 expression. Moreover, the antitumor effect of targeting MUS81 combined with WEE1 inhibitors was verified using in vivo and in vitro assays. Thereafter, the cGAS/STING pathway was evaluated, and the therapeutic value of MUS81 for immunotherapy of gastric cancer was determined. Results In this study, MUS81 negatively correlated with the expression of cell cycle checkpoint kinase WEE1. Furthermore, we identified that MUS81 regulated the ubiquitination of WEE1 via E-3 ligase β-TRCP in an enzymatic manner. In addition, MUS81 inhibition could sensitize the anticancer effect of the WEE1 inhibitor MK1775 in gastric cancer in vitro and in vivo. Interestingly, when MUS81 was targeted, it increased the accumulation of cytosolic DNA induced by MK1775 treatment and activated the DNA sensor STING-mediated innate immunity in the gastric cancer cells. Thus, the WEE1 inhibitor MK1775 specifically enhanced the anticancer effect of immune checkpoint blockade therapy in MUS81 deficient gastric cancer cells. Conclusions Our data provide rational evidence that targeting MUS81 could elevate the expression of WEE1 by regulating its ubiquitination and could activate the innate immune response, thereby enhancing the anticancer efficacy of WEE1 inhibitor and immune checkpoint blockade combination therapy in gastric cancer cells.

Due to the development of aviation hydraulic systems towards high pressure and high flow, the frequency range of pressure pulsation becomes wider, and the amplitude of pulsation increases. This puts higher requirements on the attenuation characteristics of the pressure pulsation attenuator. To reduce the damage caused by pressure pulsation to the pipeline, a Helmholtz-type pulsation attenuator (HTPA) is designed, which works through the Helmholtz resonant chamber. The theoretical model of HTPA is established by the method of lumped parameter method and distribution parametric method. The insertion loss is adopted to evaluate its attenuation characteristics. The internal pressure dynamic characteristics and attenuation effect of the HTPA are analyzed by simulation and experimentation. The results show that the pulsation attenuation rate δ was 40% after the installation of the attenuator. In the frequency range of 0–1000 Hz, the maximum insertion loss is 19 dB, which verifies the validity and correctness of the theoretical model.

The existence of the physiological tremor of the human hand significantly affects the application of tele-operation systems in performing high-precision tasks, such as tele-surgery, and currently, the process of effectively eliminating the physiological tremor has been an important yet challenging research topic in the tele-operation robot field. Some scholars propose using deep learning algorithms to solve this problem, but a large number of hyperparameters lead to a slow training speed. Later, the support-vector-machine-based methods have been applied to solve the problem, thereby effectively canceling tremors. However, these methods may lose the prediction accuracy, because learning energy cannot be accurately assigned. Therefore, in this paper, we propose a broad-learning-system-based tremor filter, which integrates a series of incremental learning algorithms to achieve fast remodeling and reach the desired performance. Note that the broad-learning-system-based filter has a fast learning rate while ensuring the accuracy due to its simple and novel network structure. Unlike other algorithms, it uses incremental learning algorithms to constantly update network parameters during training, and it stops learning when the error converges to zero. By focusing on the control performance of the slave robot, a sliding mode control approach has been used to improve the performance of closed-loop systems. In simulation experiments, the results demonstrated the feasibility of our proposed method.

Marbling characteristics are important traits for the genetic improvement of pork quality. Accurate marbling segmentation is the prerequisite for the quantification of these traits. However, the marbling targets are small and thin with dissimilar sizes and shapes and scattered in pork, complicating the segmentation task. Here, we proposed a deep learning-based pipeline, a shallow context encoder network (Marbling-Net) with the usage of patch-based training strategy and image up-sampling to accurately segment marbling regions from images of pork longissimus dorsi (LD) collected by smartphones. A total of 173 images of pork LD were acquired from different pigs and released as a pixel-wise annotation marbling dataset, the pork marbling dataset 2023 (PMD2023). The proposed pipeline achieved an IoU of 76.8%, a precision of 87.8%, a recall of 86.0%, and an F1-score of 86.9% on PMD2023, outperforming the state-of-art counterparts. The marbling ratios in 100 images of pork LD are highly correlated with marbling scores and intramuscular fat content measured by the spectrometer method (R2 = 0.884 and 0.733, respectively), demonstrating the reliability of our method. The trained model could be deployed in mobile platforms to accurately quantify pork marbling characteristics, benefiting the pork quality breeding and meat industry.

Beam splitters are widely applied in various optical systems as a common beam-splitting device. The conventional stereoscopic and flat-type beam splitters greatly limit the packaging and integration of optical systems due to their large size and restricted emitting direction. Recently, beam-splitting devices made of various transmissive or reflective metasurfaces have shown the potential to overcome these challenges. However, in optical systems such as machine vision, these single-ended beam splitters increase the design complexity of the signal feedback link due to the limitation of the beam-splitting path direction. Here, we proposed and numerically simulated a transflective all-dielectric metasurface beam splitter by applying incompletely transmissive structural designs to the metasurface and using the transmission phase modulation mechanism. It can realize the beam separation for arbitrarily polarized incident light on the same side of the normal at both transmissive and reflective ends with a single-layer unit cell arrangement structure and has a similar emergence angle. The results reveal that at 1550 nm, the angular tolerance bandwidth is about 32°, the total splitting efficiency is over 90%, and the splitting ratio is approximately 1:1. After comparison and verification of simulation results, this transflective metasurface beam splitter is hopeful to be applied in new compact optical systems that require real-time signal feedback, such as coaxial light sources and photoelectric sensing.

Phosphorus-based materials are considered to be reliable anode materials for potassium ion batteries (PIBs) due to their high theoretical capacity but suffer from inferior cycling stability and an unstable Solid Electrolyte Interface (SEI) layer. Herein, optimized ball-milled parameters and concentrated electrolytes are introduced to enhance the electrochemical performance of Sn4P3/C anodes. Consequently, the electrodes synthesized under optimized ball milling parameters could deliver a reversible capacity of 307.8 mA h g−1 in diluted Potassium hexafluorophosphate (KPF6) electrolyte. Moreover, compared with diluted bis(fluorosulfonyl)imide (KFSI) electrolyte, a robust inorganic KF-rich SEI layer can be formed on the electrode’s surface by employing concentrated KFSI electrolyte and provides more rapid K ion conduction rates. Meanwhile, a large proportion of the FSI− anions participated in the K+ solvation shell when the KFSI concentration increased. As a result, high specific capacities (225.1 mA h g−1 at 50 mA g−1 after 200 cycles) and excellent Coulombic efficiency (97.24% at 500 mA g−1 after 200 cycles) can be achieved. This work may deepen our understanding of synthetic optimization in electrode material design and the role of concentrated electrolyte in tunning the solvation structure, and also offer an insightful clue to the design of high-capacity phosphorus-based anodes.

On-chip arbitrary-elliptical-polarization converter plays a key role in optical information processing. However, the traditional method of manually adjusting parameters for designing devices is limited in function. In this letter, on-chip ultra-small arbitrary-elliptical-polarization converters are realized through optimization algorithms based on genetic algorithm (GA) combined with finite element method (FEM). The converters can realize the function of arbitrary ellipticity angle conversion of full polarization states. The size of the core device is only 1 µm × 1 µm, which is very conducive to high-density integration. The difference between the ideal output ellipticity angle and the actual output ellipticity angle of each device is no more than 2 degrees. In addition, it is proved that the use of optimization algorithms can easily design arbitrary-elliptical-polarization converters with different materials, different structures and different wavelengths, and the design of three-dimensional arbitrary-elliptical-polarization converters is also verified by using the optimization algorithm. This work provides an efficient design method for arbitrary polarization state conversion, showing its significance in improving the information capacity in optical communication.

MUS81 is a critical endonuclease involved in heterodimer formation with Eme1/Mms4 and an important DNA damage repair regulatory molecule. Our previous study suggested that MUS81 was overexpressed and its high expression was positively correlated with gastric cancer metastasis. However, the therapeutic potential of targeting MUS81 in gastric cancer requires further exploration. Therefore, in this study, the Cancer Genome Atlas (TCGA) data were analyzed and showed that MUS81 is a key regulator of cell cycle distribution and DNA damage repair in gastric cancer. In vitro and in vivo, MUS81 knockdown significantly enhanced the anticancer effect of the PARP inhibitor talazoparib. Mechanistically, MUS81 inhibition impaired the activation of the ATR/CHK1 cell cycle signaling pathway and promoted gastric cancer cells with talazoparib-induced DNA damage to continue mitosis. Moreover, addition of the bromodomain-containing protein 4 inhibitor AZD5153 increased the anticancer effect of talazoparib via MUS81 inhibition in gastric cancer cells, and this combination effect was largely impaired when MUS81 was knocked down. In conclusion, these data suggested that MUS81 regulated ATR/CHK1 activation, a key signaling pathway in the G2M checkpoint, and targeting MUS81 enhanced the antitumor efficacy of talazoparib. Therefore, AZD5153 combined with talazoparib may represent a promising therapeutic strategy for patients with MUS81 proficient gastric cancer.

The drug 5-fluorouracil (5-Fu) is the critical composition of colorectal cancer (CRC) treatments. Prognostic and predictive molecular biomarkers for CRC patients (CRCpts) treated with 5-Fu-based chemotherapy can provide assistance for tailoring treatment approach. Here, we established a molecular biomarker of 5-Fu resistance derived from colorectal cancer organoids (CRCOs) for predicting the survival of CRCpts. Forty-one CRCO cultures were generated from 50 CRC tumor tissues after surgery (82%). The following experiments revealed a great diversity in drug sensitivity for 10 μM 5-Fu treatment tested by using organoid size change. Fourteen cases (34.1%) were 5-Fu sensitive and the other 27 (65.9%) were resistant. Then, differentially expressed genes (DEGs) associated with 5-Fu resistance were outputted by transcriptome sequencing. In particular, DEGs were generated in two comparison groups: 1) 5-Fu sensitive and resistant untreated CRCOs; 2) CRCOs before 5-Fu treatment and surviving CRCOs after 5-Fu treatment. Some molecules and most of the pathways that have been reported to be involved in 5-Fu resistance were identified in the current research. By using DEGs correlated with 5-Fu resistance and survival of CRCpts, the gene signature and drug-resistant score model (DRSM) containing five molecules were established in The Cancer Genome Atlas (TCGA)-CRC cohort by least absolute shrinkage and selection operator (LASSO) regression analysis and 5-fold cross-validation. Multivariate analysis revealed that drug-resistant score (DRS) was an independent prognostic factor for overall survival (OS) in CRCpts in TCGA-CRC cohort (P < 0.001). Further validation results from four Gene Expression Omnibus (GEO) cohorts elucidated that the DRSM based on five genes related to 5-Fu chemosensitivity and developed from patient-derived organoids can predict survival of CRCpts. Meanwhile, our model could predict the survival of CRCpts in different subgroups. Besides, the difference of molecular pathways, tumor mutational burden (TMB), immune response-related pathways, immune score, stromal score, and immune cell proportion were dissected between DRS-high and DRS-low patients in TCGA-CRC cohort.

Slag waste can be effectively used to produce coal–fired slag concrete (CSC), which has economic and environmental benefits. However, CSC used in engineering construction will eventually be subjected to damage. The purpose of this study is to investigate the mechanical characteristics and damage evolution behaviour of CSC specimens under a uniaxial compressive load using acoustic emission (AE) monitoring technology. Through uniaxial compression testing and AE monitoring, the stress–strain curve and AE characteristics of CSC specimens are obtained. Subsequently, a damage evolution model of the CSC specimens under a uniaxial compression load is constructed, and the damage evolution characteristics of the concrete are analysed. The results indicate that an increase in the ratio of the coal–fired slag mass to the cement mass results in a gradual reduction in the compressive strength of the CSC. Moreover, the maximum value of the cumulative energy count and cumulative ringing count of the AEs gradually increases while the damage degree gradually decreases. The damage evolution process for CSC can be divided into three stages: the initial damage formation stage, accelerated damage growth stage, and damage failure stage. The damage model, based on the AE cumulative ringing count, reasonably reflects the damage evolution process of the CSC specimens. The results of this study provide a reference for theoretical research and the engineering application of CSC.

This study analyzed the characteristics of 133 Haemophilus parasuis isolates in southern China. These isolates belonged to eleven serovars (1, 2, 4-10, 13 and 15) with 12.0% of them being characterised as non-typable. A relatively high level in resistance was encountered for trimethoprim + sulfamethoxazole (89.9%), tetracycline (75.3%), amoxicillin (69.1%), streptomycin (63.6%), carbenicillin (60.2%), kanamycin (46.6%) and ampicillin (45.6%). A total of 60% of the isolates were negative for group 1 virulence-associated autotransporters (vtaA). All group 1 vtaA negative isolates fell into polyacrylamide gel electrophoresis (PAGE) type I, while all group 1 vtaA positive isolates were classified as PAGE type II. The results of Multi-locus sequence typing (MLST) indicated a high degree of variation, 45 isolates in the study were assigned into 31 sequence types with 28 of these being new (not found in the MLST database). Antimicrobial resistance was observed in every serovar, there was no statistically significant correlation between the antimicrobial resistance and the serovars. The isolates allocated to clade 2 (based on MLST target sequences) showed the molecular characteristics of highly pathogenic strains in whole-cell protein profiling, vtaA groups 1, superoxide dismutase (sodA) sequence and MLST.

While master-slave teleoperated robotic systems have extensive applications in practice, the physiological tremors can easily affect the control accuracy and even destroy the stability of the closed-loop control systems during operation. Hence, the development of some effective approaches for counteracting physiological tremors is of both theoretical and practical importance. In this paper, a broad learning network-based filter integrating a deep learning network and modified incremental learning algorithms is proposed to reconstruct and compensate for tremor signals. To strengthen the recognition of correlations between different moments, the lateral connectivity structure is adopted to obtain multi-scale feature maps. Each feature window is obtained from multi-scale feature maps generated by the convolutional neural network, which has an advantage that makes the feature nodes fuse the feature information of long time series and short time series by the lateral connection. The broad learning network is a unique construction, which only needs to obtain the input and the output to conveniently calculate the connection weights by the pseudo-inverse without involving backpropagation. It is known that the relation between the data X and the label Y can be represented as XW=Y, and the solution W can be obtained by the pseudo-inverse W=X+Y. In addition, to guarantee the ill-posed problem, a ridge regression algorithm is used for the pseudo-inverse calculation. The effectiveness of our raised network architecture is illustrated by comparative simulation and experiment results.

The layered GaS has attracted much attention in the field of photodetection recently because of its considerable responsivity (∼A/W) caused by the high quantum yields, while its slow response speed (∼ms) due to the low carrier mobility limits its practical applications. Here, by separating a few-layered GaS (∼15 nm) with its substrate to prepare a device with the typical suspended architecture, we trade off its responsivity with speed for the first time. A responsivity of ∼ 103 A/W and a switch time of ∼ μs are achieved simultaneously in a wide UV–vis range (300–628 nm), which exceeds that of the most current 2D material-based photodetectors. The excellent mechanical stiffness of layered GaS avoids the interface scattering and trap caused by the contacting with substrate or its own deformation. This is beneficial to the significant improvement of carrier mobility and fully activating the intrinsic properties of GaS. Combined with the comparative experiments and band theory analysis, this assertion is confirmed and the photoconductance effect is determined to play a dominant role. These results show a promising strategy for improving the performance of GaS photodetector, especially providing references for its future integrated devices.

AbstractRNA localization is involved in multiple biological processes. Recent advances in subcellular fractionation-based sequencing approaches uncovered localization pattern on a global scale. Most of existing methods adopt relative localization ratios (such as ratios of separately normalized transcripts per millions of different subcellular fractions without considering the difference in total RNA abundances in different fractions), however, absolute ratios may yield different results on the preference to different cellular compartment. Experimentally, adding external Spike-in RNAs to different fractionation can be used to obtain absolute ratios. In addition, a spike-in independent computational approach based on multiple linear regression model can also be used. However, currently, no custom tool is available. To solve this problem, we developed a method called subcellular fraction abundance estimator to correctly estimate relative RNA abundances of different subcellular fractionations. The ratios estimated by our method were consistent with existing reports. By applying the estimated ratios for different fractions, we explored the RNA localization pattern in cell lines and also predicted RBP motifs that were associated with different localization patterns. In addition, we showed that different isoforms of same genes could exhibit distinct localization patterns. To conclude, we believed our tool will facilitate future subcellular fractionation-related sequencing study to explore the function of RNA localization in various biological problems.

Estimation of crop biophysical and biochemical characteristics is the key element for crop growth monitoring with remote sensing. With the application of unmanned aerial vehicles (UAV) as a remote sensing platform worldwide, it has become important to develop general estimation models, which can interpret remote sensing data of crops by different sensors and in different agroclimatic regions into comprehensible agronomy parameters. Leaf chlorophyll content (LCC), which can be measured as a soil plant analysis development (SPAD) value using a SPAD-502 Chlorophyll Meter, is one of the important parameters that are closely related to plant production. This study compared the estimation of rice (Oryza sativa L.) LCC in two different regions (Ningxia and Shanghai) using UAV-based spectral images. For Ningxia, images of rice plots with different nitrogen and biochar application rates were acquired by a 125-band hyperspectral camera from 2016 to 2017, and a total of 180 samples of rice LCC were recorded. For Shanghai, images of rice plots with different nitrogen application rates, straw returning, and crop rotation systems were acquired by a 5-band multispectral camera from 2017 to 2018, and a total of 228 samples of rice LCC were recorded. The spectral features of LCC in each study area were analyzed and the results showed that the rice LCC in both regions had significant correlations with the reflectance at the green, red, and red-edge bands and 8 vegetation indices such as the normalized difference vegetation index (NDVI). The estimation models of LCC were built using the partial least squares regression (PLSR), support vector regression (SVR), and artificial neural network (ANN) methods. The PLSR models tended to be more stable and accurate than the SVR and ANN models when applied in different regions with R2 values higher than 0.7 through different validations. The results demonstrated that the rice canopy LCC in different regions, cultivars, and different types of sensor-based data shared similar spectral features and could be estimated by general models. The general models can be implied to a wider geographic extent to accurately quantify rice LCC, which is helpful for growth assessment and production forecasts.

The stomatal index of the leaf is the ratio of the number of stomata to the total number of stomata and epidermal cells. Comparing with the stomatal density, the stomatal index is relatively constant in environmental conditions and the age of the leaf and, therefore, of diagnostic characteristics for a given genotype or species. Traditional assessment methods involve manual counting of the number of stomata and epidermal cells in microphotographs, which is labor-intensive and time-consuming. Although several automatic measurement algorithms of stomatal density have been proposed, no stomatal index pipelines are currently available. The main aim of this research is to develop an automated stomatal index measurement pipeline. The proposed method employed Faster regions with convolutional neural networks (R-CNN) and U-Net and image-processing techniques to count stomata and epidermal cells, and subsequently calculate the stomatal index. To improve the labeling speed, a semi-automatic strategy was employed for epidermal cell annotation in each micrograph. Benchmarking the pipeline on 1,000 microscopic images of leaf epidermis in the wheat dataset (Triticum aestivum L.), the average counting accuracies of 98.03 and 95.03% for stomata and epidermal cells, respectively, and the final measurement accuracy of the stomatal index of 95.35% was achieved. R2 values between automatic and manual measurement of stomata, epidermal cells, and stomatal index were 0.995, 0.983, and 0.895, respectively. The average running time (ART) for the entire pipeline could be as short as 0.32 s per microphotograph. The proposed pipeline also achieved a good transferability on the other families of the plant using transfer learning, with the mean counting accuracies of 94.36 and 91.13% for stomata and epidermal cells and the stomatal index accuracy of 89.38% in seven families of the plant. The pipeline is an automatic, rapid, and accurate tool for the stomatal index measurement, enabling high-throughput phenotyping, and facilitating further understanding of the stomatal and epidermal development for the plant physiology community. To the best of our knowledge, this is the first deep learning-based microphotograph analysis pipeline for stomatal index assessment.

Purpose: Studies on early recurrence in gastrointestinal neuroendocrine carcinoma (NEC) and mixed adenoneuroendocrine carcinoma (MANEC) are lacking and risk factors related to early recurrence are not clear. We evaluated risk factors for early recurrence in such patients and developed a predictive scoring model.Methods: Patients undergoing curative surgery for GI-NEC or MANEC between January 2010 and January 2019 were included. Early recurrence was defined as recurrence within 12 months after surgery. Risk factors for early recurrence were identified using logistic regression.Results: Of the 80 included patients, 27 developed early recurrence and 53 had no early recurrence. Independent risk factors associated with early recurrence included tumor location in the midgut/hindgut [odds ratio (OR) = 5.077, 95% confidence interval (CI) 1.058–24.352, p = 0.042], alkaline phosphatase (ALP) >80 (OR = 5.331, 95% CI 1.557–18.258, p = 0.008), and lymph node ratio (LNR) >0.25 (OR = 6.578, 95% CI 1.971–21.951, p = 0.002). Risk scores were assigned to tumor location (foregut, 0; midgut/hindgut, 1), ALP (≤80, 0; >80, 1), and LNR (≤0.25, 0; >0.25, 1). Patients with a high risk (score 2–3) for early recurrence had significantly shorter disease-free survival and overall survival than those with low- (score 0) and intermediate risks (score 1) (both p < 0.001). The novel scoring model had superior predictive efficiency for early recurrence over TNM staging (area under the curve 0.795 vs. 0.614, p = 0.003).Conclusion: Tumor location, preoperative ALP, and LNR were independent factors associated with early recurrence after curative surgery for GI-NEC or MANEC. The risk scoring model developed based on these three factors shows superior predictive efficiency.

Increasing attention is being paid to the clean and efficient mining and utilization of coal resources. Lignite is a major component of coal; however, its high moisture and volatile contents and low calorific value cause it to have low mining and utilization efficiencies. During the dehydration, upgrading and in-situ heat injection or underground coal gasification of lignite, its pore structure plays an important role in the pyrolysis and product transfer processes. Therefore, it is necessary to systematically study the high-temperature pore structure of lignite. The evolution of pore fissures in gas-pyrolyzed lignite was studied by nuclear magnetic resonance combined with a gas heating reactor and test device. We found that the total connectivity, porosity and permeability of lignite increased between temperatures of 25 °C and 250 °C, then decreased at 350 °C and increased again at 450 °C. At 450 °C, the porosity, effective porosity and permeability of lignite were 18.32%, 30.22% and 856.98 md, respectively. The evolution in the pore structure parameters of lignite with temperature was observed to determine the changes in seepage channels that occur during the processes of lignite mining and utilization.

Cell swelling and membrane blebbing are characteristic of pyroptosis. In the present study, we explored the role of intracellular tension activity in the deformation of pyroptotic astrocytes. Protein nanoparticle-induced osmotic pressure (PN-OP) was found to be involved in cell swelling and membrane blebbing in pyroptotic astrocytes, and was associated closely with inflammasome production and cytoskeleton depolymerization. However, accumulation of protein nanoparticles seemed not to be absolutely required for pyroptotic permeabilization in response to cytoskeleton depolymerization. Gasdermin D activation was observed to be involved in modification of typical pyroptotic features through inflammasome-induced OP upregulation and calcium increment. Blockage of nonselective ion pores can inhibit permeabilization, but not inflammasome production and ion influx in pyroptotic astrocytes. The results suggested that the inflammasomes, as protein nanoparticles, are involved in PN-OP upregulation and control the typical features of pyroptotic astrocytes.

Improving the stability of lead iodide (PbI2), especially photostability, is in crucial demand for the realization of application‐level optoelectronic devices. In this regard, deposition of organic polymers on PbI2 as a protective layer is a common strategy to improve its stability, but polymers with low thermal conductivity generally cannot produce the desired effect. Herein, a novel strategy is proposed for improving the photostability of PbI2 at different excitation wavelengths, including 320, 405, and 532 nm, via constructing type‐I heterostructure with ZnO with high thermal conductivity. In addition, due to the type‐I band alignment between PbI2 and ZnO, the photogenerated carriers in ZnO can be transferred to PbI2, resulting in a nearly eightfold photoluminescence enhancement of PbI2 under 320 nm laser excitation. The ZnO as a protective layer forming type‐I heterostructure is evidenced as a feasible strategy for enhancing the photostability and photoluminescence of PbI2, facilitating the development of practical applications.

Abstract ZnO nanowires play a very important role in optoelectronic devices due to the wide bandgap and high exciton binding energy. However, for one-dimensional nanowire, due to the large surface to volume ratio, surface traps and surface adsorbed species acts as an alternate pathway for the de-excitation of carriers. Ar plasma treatment is a useful method to enhance the optical property of ZnO nanowires. It is necessary to study the optical properties of ZnO nanowires treated by plasma with different energies. Here, we used laser spectroscopy to investigate the plasma treatments with various energies on ZnO nanowires. Significantly improved emission has been observed for low and moderate Ar plasma treatments, which can be ascribed to the surface cleaning effects and increased neutral donor-bound excitons. It is worth mentioning that about 60-folds enhancements of the emission at room temperature can be achieved under 200 W Ar plasma treatment. When the plasma energy exceeds the threshold, high-ion beam energy will cause irreparable damage to the ZnO nanowires. Thanks to the enhanced optical performance, random lasing is observed under optical pumping at room temperature. And the stability has been improved dramatically. By using this simple method, the optical property and stability of ZnO nanowires can be effectively enhanced. These results will play an important role in the development of low dimensional ZnO-based optoelectronic devices.

By establishing the mathematical model of helicopter transmission system running time and flight time, engine working time, the time ratio relation between running time and flight time is deduced, that is, conversion coefficient. Using Minitab software to complete the data calculation, the running time of the transmission system is converted into the corresponding flight time. Compared with the traditional way which only considers the flight time in the air, the real and accurate time between overhaul can be obtained and the reliability can be improved. At the same time, the maintenance time scale of the transmission system and other parts of the helicopter can be ensured. This method is successfully applied to a certain type of helicopter, and some reference for the maintenance of similar aviation products can be provided.

To study the nucleation and recrystallization behavior of deformation bands, shear bands and grain boundaries during the recrystallization process, a heat treatment test was carried out on Cr-Ti-B low-carbon steel after warm rolling and cold rolling. The results show that recrystallization occurs preferentially in shear bands and grain boundaries. The γ deformation texture can be enhanced and the Goss texture can be weakened during the warm rolling and subsequent cold rolling process. Recrystallization of the deformation bands was observed, but the nucleation time of recrystallization in the deformation band is much slower than that in the shear band and grain boundary.

Abstract Background B7 homolog 1 (B7-H1) overexpression on tumor cells is an important mechanism of immune evasion in gastric cancer (GC). Elucidation of the regulation of B7-H1 expression is urgently required to guide B7-H1-targeted cancer therapy. Interferon gamma (IFN-γ) is thought to be the main driving force behind B7-H1 expression, and epigenetic factors including histone acetylation are recently linked to the process. Here, we investigated the potential role of histone deacetylase (HDAC) in IFN-γ-induced B7-H1 expression in GC. The effect of Vorinostat (SAHA), a small molecular inhibitor of HDAC, on tumor growth and B7-H1 expression in a mouse GC model was also evaluated. Results RNA-seq data from The Cancer Genome Atlas revealed that expression of B7-H1, HDAC1–3, 6–8, and 10 and SIRT1, 3, 5, and 6 was higher, and expression of HDAC5 and SIRT4 was lower in GC compared to that in normal gastric tissues; that HDAC3 and HDAC1 expression level significantly correlated with B7-H1 in GC with a respective r value of 0.42 (p

Traditional seed and fruit phenotyping are mainly accomplished by manual measurement or extraction of morphological properties from two-dimensional images. These methods are not only in low-throughput but also unable to collect their three-dimensional (3D) characteristics and internal morphology. X-ray computed tomography (CT) scanning, which provides a convenient means of non-destructively recording the external and internal 3D structures of seeds and fruits, offers a potential to overcome these limitations. However, the current CT equipment cannot be adopted to scan seeds and fruits with high throughput. And there is no specialized software for automatic extraction of phenotypes from CT images. Here, we introduced a high-throughput image acquisition approach by mounting a specially designed seed-fruit container onto the scanning bed. The corresponding 3D image analysis software, 3DPheno-Seed&Fruit, was created for automatic segmentation and rapid quantification of eight morphological phenotypes of internal and external compartments of seeds and fruits. 3DPheno-Seed&Fruit is a graphical user interface design and user-friendly software with an excellent phenotype result visualization function. We described the software in detail and benchmarked it based upon CT image analyses in seeds of soybean, wheat, peanut, pine nut, pistachio nut and dwarf Russian almond fruit. R2 values between the extracted and manual measurements of seed length, width, thickness, and radius ranged from 0.80 to 0.96 for soybean and wheat. High correlations were found between the 2D (length, width, thickness, and radius) and 3D (volume and surface area) phenotypes for soybean. Overall, our methods provide robust and novel tools for phenotyping the morphological seed and fruit traits of various plant species, which could benefit crop breeding and functional genomics.

The sweet cherry (Prunus avium) is one of the most economically important fruit species in the world. However, there is a limited amount of genetic information available for this species, which hinders breeding efforts at a molecular level. We were able to describe a high-quality reference genome assembly and annotation of the diploid sweet cherry (2n = 2x = 16) cv. Tieton using linked-read sequencing technology. We generated over 750 million clean reads, representing 112.63 GB of raw sequencing data. The Supernova assembler produced a more highly-ordered and continuous genome sequence than the current P. avium draft genome, with a contig N50 of 63.65 KB and a scaffold N50 of 2.48 MB. The final scaffold assembly was 280.33 MB in length, representing 82.12% of the estimated Tieton genome. Eight chromosome-scale pseudomolecules were constructed, completing a 214 MB sequence of the final scaffold assembly. De novo, homology-based, and RNA-seq methods were used together to predict 30,975 protein-coding loci. 98.39% of core eukaryotic genes and 97.43% of single copy orthologues were identified in the embryo plant, indicating the completeness of the assembly. Linked-read sequencing technology was effective in constructing a high-quality reference genome of the sweet cherry, which will benefit the molecular breeding and cultivar identification in this species.