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Jing Wang,1,* Weijian Chen,1,2,* Wenxiang Du,2 Hongjie Zhang,2 Matthias Ilmer,3 Lei Song,2 Yuan Hu,2 Xiaopeng Ma1 1Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, People’s Republic of China; 2State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei, Anhui, 230026, People’s Republic of China; 3Department of General, Visceral, and Transplantation Surgery, Ludwig-Maximilians-University (LMU), Campus Grosshadern, Munich, 81377, Germany*These authors contributed equally to this workCorrespondence: Yuan Hu; Xiaopeng Ma, Email yuanhu@ustc.edu.cn; XiaopengMa@fsyy.ustc.edu.cnIntroduction: Tamoxifen (TAM) has proven to be a therapeutic breakthrough to reduce mortality and recurrence in estrogen receptor-positive (ER+) breast cancer patients. However, the application of TAM exhibits low bioavailability, off-target toxicity, instinct and acquired TAM resistance.Methods: We utilized black phosphorus (BP) as a drug carrier and sonosensitizer, integrated with TAM and tumor-targeting ligand folic acid (FA) to construct TAM@BP-FA for synergistic endocrine and sonodynamic therapy (SDT) of breast cancer. The exfoliated BP nanosheets were modified through in situ polymerization of dopamine, followed by electrostatic adsorption of TAM and FA. The anticancer effect of TAM@BP-FA was evaluated through in vitro cytotoxicity and in vivo antitumor model. RNA-sequencing (RNA-seq), quantitative real-time PCR, Western blot analysis, flow cytometry analysis and peripheral blood mononuclear cells (PBMCs) analysis were performed for mechanism investigation.Results: TAM@BP-FA had satisfactory drug loading capacity, the TAM release behavior can be controlled through pH microenvironment and ultrasonic stimulation. An amount of hydroxyl radical (∙OH) and singlet oxygen (1O2) were as expected generated under ultrasound stimulation. TAM@BP-FA nanoplatform showed excellent internalization in both TAM-sensitive MCF7 and TAM-resistant (TMR) cells. Using TMR cells, TAM@BP-FA displayed significantly enhanced antitumor ability in comparison with TAM (7.7% vs 69.6% viability at 5μg/mL), the additional SDT further caused 15% more cell death. RNA-seq unraveled the TAM@BP-FA antitumor mechanisms including effects on cell cycle, apoptosis and cell proliferation. Further analysis showed additional SDT successfully triggering reactive oxygen species (ROS) generation and mitochondrial membrane potential (MMP) reduction. Moreover, PBMCs exposed to TAM@BP-FA induced an antitumor immune response by natural killer (NK) cell upregulation and immunosuppression macrophage reduction.Conclusion: The novel BP-based strategy not only delivers TAM specifically to tumor cells but also exhibits satisfactory antitumor effects through targeted therapy, SDT, and immune cell modulation. The nanoplatform may provide a superior synergistic strategy for breast cancer therapy.Keywords: black phosphorus, breast cancer, sonodynamic therapy, tamoxifen, PBMC, combination therapy

Protein heterogeneity in molecular expression and structures determines tumorigenesis and is the diagnostic and therapeutic cancer biomarker. Small extracellular vesicles (sEVs) are cell-released nanoscaled membrane-bound vesicles transferring bioactive molecules for intercellular communication and playing essential roles in tumor progression and metastasis. Therefore, protein heterogeneity in tumor-derived sEVs indicates the degree of malignant transformation, providing a noninvasive biomarker for cancer diagnosis and malignancy evaluation. We employ near-field infrared (nano-FTIR) spectroscopy to investigate malignancy-related protein heterogeneity in a single sEV and demonstrate the discriminability of sEV protein heterogeneity to evaluate tumor malignancy and metastasis. We found that the amide I/II adsorption ratio of the sEVs increases with tumor malignancy, the proportion of α-helix + random coil (α-helix and random coil) in sEV proteins decreases with tumor malignancy, and the proportion of β-sheet + β-turn (β-sheet and β-turn) increases with tumor malignancy. These nano-FTIR spectral signatures of the sEVs from the primary tumor tissue of breast cancer patients show high sensitivity and specificity in evaluating tumor metastasis. This study shows the advantages of nano-FTIR in single sEV characterization and demonstrates the significance of sEV protein heterogeneity in cancer diagnosis. It provides a noninvasive solution to elucidate cancer development and facilitates the exploitation of potential cancer biomarkers.

Breast carcinoma is one of the common causes of cancer-related mortality in women. Maternally expressed gene 3 (MEG3), a lncRNA located at 14q32, can be involved in carcinogenesis. In this study, we discovered that MEG3 was downregulated by CpG hypermethylation within its gene promoter. Functionally, treatment of breast cancer cells with the DNA methylation inhibitor 5-AzadC as well as silencing of DNA methyltransferase-1 (DNMT1) could decrease the abnormal hypermethylation of the MEG3 promoter, reverse MEG3 expression, inhibit cell proliferation and promote cell apoptosis. In addition, we found that MEG3 expression was negatively correlated with DNMT1. Mechanistically, MEG3 knockdown combined with 5-AzadC or sh-DNMT1 treatment restored the expression of Notch1 receptor, leading to the Notch1 pathway activation, and promoted the progression of epithelial mesenchymal transformation (EMT). Finally, the mice tumor model experiments showed that DNMT1 knockdown can increase MEG3 expression and inhibit tumor growth. Collectively, our findings uncovered that DNMT1-mediated MEG3 demethylation leads to MEG3 upregulation, which in turn inhibits the Notch1 pathway and EMT process in breast cancer.

Acupuncture and moxibustion have been accepted as add-on options for primary dysmenorrhea (PD); however, the clinical evidence is still inadequate. We searched AMED, CENTRAL, EMBASE, PubMed, Web of Science, CBM, CNKI, VIP, Wangfang database, ANZCTR, ClinicalTrials.gov, and the WHO ICTRP, from their inception to February 2021. The pooled analysis of 13 RCTs with 675 participants for VAS showed that acupuncture and moxibustion were more effective in managing PD than the control group with the MD of −1.93 (95% CI [−2.80, −1.06] and −2.67 (95% CI [−4.96, −0.38]). With the CMSS, seven studies with 487 participants showed that these modalities were more effective than the control group with the MD of −7.58 (95% CI [−10.97, −4.19]) and −3.78 (95% CI [−6.90, −0.66]). The findings indicated that acupuncture and moxibustion could relieve pain effectively and has fewer adverse events (AEs) in managing PD.

Clear cell renal cell carcinoma (ccRCC) accounts for the highest number of renal malignancies and 3% of all adult cancers. The incidence of ccRCC is increasing worldwide, and its prognosis is poor. Approximately 30% of the patients are diagnosed at a late stage and are frequently asymptomatic. Cuproptosis is a new type of cell death that is regulated by Cu ions. As cuproptosis is associated with cancer development, we hypothesized that changes in the expression of cuproptosis-related genes (CRGs) are associated with the prognosis of ccRCC, and that CRGs can serve as biomarkers for the diagnosis and prognosis of ccRCC. In the present study, we explored the correlation between CRGs and ccRCC prognosis by analyzing publicly available data. We analyzed the clinical information and RNA-sequencing data in The Cancer Genome Atlas using bioinformatics tools. Dihydrolipoamide S-succinyltransferase (DLST) was identified as a novel gene with predictive and diagnostic potential. CRGs were under-expressed in ccRCC samples, and downregulation ofDLSTwas highly associated with poor prognosis. Cox univariate and multivariate regression analyses revealed thatDLSTcould serve as an independent prognostic factor for ccRCC. Further, functional enrichment analysis indicated that low expression ofDLSTmay affect immune function. Our results strongly indicate thatDLSTplays an important role in ccRCC progression and may serve as an independent diagnostic and prognostic biomarker for ccRCC. Therefore,DLSTis a potential therapeutic target for patients with ccRCC.

SummaryWhile deep learning has achieved great success in solving partial differential equations (PDEs) that accurately describe engineering systems, it remains a big challenge to obtain efficient and accurate solutions for complex problems instead of traditional numerical simulation. In the field of reservoir engineering, the current mainstream machine learning methods have been successfully applied. However, these popular methods cannot directly solve the problem of 2D two-phase oil/water PDEs well, which is the core of reservoir numerical simulation. Fourier neural operator (FNO) is a recently proposed high-efficiency PDE solution architecture that overcomes the shortcomings of the above popular methods, which can handle this type of PDE problem well in our work. In this paper, a deep-learning-based model is developed to solve three categories of problems controlled by the subsurface 2D oil/water two-phase flow PDE based on the FNO. For this complex engineering equation, we consider many factors, select characteristic variables, increase the dimension channel, expand the network structure, and realize the solution of the engineering problem. The first category is to predict the distribution of saturation and pressure fields by PDE parameters. The second category is the prediction of time series. The third category is for the inverse problem. It has achieved good results on both forward and inverse problems. The network uses fast Fourier transform (FFT) to extract PDE information in Fourier space to approximate differential operators, making the network faster and with greater physics significance. The model is mesh-independent and has good generalization, which also shows superresolution. Compared to the original FNO, we improve the network structure, add physical constraints to deal with boundary conditions (BCs), and use a shape matrix to control irregular boundaries. Also, we have improved the FFT module to make the transformation smoother. Compared with advanced deep learning-based solvers at different resolutions, the results show that this model overcomes some shortcomings of popular algorithms such as physics-informed neural networks (PINNs) and fully convolutional network (FCN) and has stronger accuracy and applicability. Our work has great potential in the replacement of traditional numerical methods with neural networks for reservoir numerical simulation.

We attempted to analyze the clinical value of microRNA (miR)-590-3p in diabetic nephropathy (DN) patients and its role in high glucose (HG)-induced renal tubular epithelial cell (HK-2) injury. Serum levels of miR-590-3p were detected by quantitative real-time polymerase chain reaction (qRT-PCR). Spearman correlation coefficient analysis of the correlation between miR-590-3p and clinical indicators. The diagnostic value of miR-590-3p was analyzed by the receiver operating characteristic (ROC) curve. Then, the DN cell model induced by HG in HK-2 cells was established. Enzyme-linked immunosorbent assay (ELISA), flow cytometry, and CCK-8 assay were employed to assess cell inflammation, oxidative stress, apoptosis, and proliferation. Dual-luciferase reporter assay confirmed the target of miR-590-3p. Serum miR-590-3p was reduced in patients of DN, which was positively correlated with eGFR and negatively associated with albuminuria. Furthermore, miR-590-3p also can diagnose patients of DN from healthy subjects or patients of T2DM. Furthermore, miR-590-3p was decreased in a concentration- and time-dependent manner during HG-induction. miR-590-3p overexpression bated HG-induced inhibition effect on cell proliferation and promotion effects on apoptosis, oxidative stress, and inflammation. C-X3-C motif chemokine ligand1 (CX3CL1) is the target of miR-590-3p, whose levels were enhanced in DN patients and are negatively regulated by miR-590-3p. Our discoveries offered new insights that reduced miR-590-3p as a potential biomarker for the diagnosis of DN, and elevated miR-590-3p can alleviate renal tubular injury by HG-induced through targeting CX3XL1, which may be a novel target for improving the development of DN.

Summary Surrogate modeling has shown to be effective in improving the solving efficiency for history matching in the development of oil and gas, but the traditional surrogate models are difficult to directly deal with the high-dimensional spatial uncertain parameters, such as the permeability field. In this paper, we introduce a new deep-learning-based surrogate modeling framework, image-to-sequence regression, which can directly predict the production data from the high-dimensional spatial parameters. Specifically, a spatial-temporal convolution recurrent neural network surrogate model is proposed based on a densely connected convolutional neural network (CNN) model and a stacked multilayer long short-term memory (LSTM) model. And a surrogate-based history-matching workflow is then developed by combining the proposed surrogate model with an improved ensemble smoother data assimilation algorithm. Two case studies on a 2D and a 3D reservoir model demonstrate that the proposed surrogate model can effectively predict production data and improve the efficiency of history matching.

The typical hypoxia of tumor microenvironment seriously affects the efficacy of Starvation therapy (ST) and Photodynamic therapy (PDT). Therefore, it is of great significance to prepare a multimodal combined therapy...

Warm Mix Asphalt (WMA) technology can effectively reduce carbon emissions and energy consumption during road project construction. However, it may have a negative impact on the binding properties of asphalt mixtures. In order to effectively evaluate the adhesion performance of asphalt binders and aggregates under the combined influence of WMA and traditional polymer-modified asphalt, this paper provides a comprehensive evaluation at the micro and macro levels. The adhesion between three different modified asphalts (warm mix crumb rubber/ Styrene-Butadiene-Styrene (SBS) composite modified asphalt, warm mix crumb rubber asphalt, and warm mix SBS modified asphalt) and two different aggregates (limestone and granite) under both virgin and short-term aging conditions were analyzed. Regardless of the type of modified asphalt, the results showed that limestone aggregates have better adhesion properties with asphalt binders. In addition, the short-term thermal oxidation aging behavior is conducive to enhancing the asphalt-aggregate adhesion characteristics. Furthermore, WMA additives, crumb rubber, and SBS compound modification can improve the adhesion performance between asphalt and aggregate.

The molecular mechanisms underlying the establishment of the monopolar growth of fission yeast spores have been less characterized. Here, we report that the Cdc42 GTPase-activating protein (GAP) Rga6 is required for promoting monopolar growth during spore germination. The absence of Rga6 increases the number of spores that grow in a bipolar fashion. Rga6 decorates the non-growing cortical region, binds phosphatidylinositol 4,5-bisphosphate, and colocalizes with the phosphatidylinositol 4,5-bisphosphate-binding protein Opy1. Overexpression of Opy1 diminishes the cortical localization of Rga6. The characteristic localization of Rga6 on the cell cortex depends on the C-terminal PBR region of Rga6. Moreover, engineered chimera composed of the Rga6 C-terminal PBR region fused to the GAP domain of Rga3 or Rga4 are sufficient to rescue the spore growth phenotype caused by the absence of Rga6. Hence, our work establishes a paradigm in which the lipid composition of the plasma membrane directs polarized cell growth by specifying the cortical localization of a GAP protein.

As a major public health problem, insomnia has garnered much attention. Acupuncture, with dialectical acupoint selection (DAS), has been proved to be effective for insomnia, but there is no evidence of evidence-based medicine to prove the efficacy of Lingguibafa acupoint selection (LAS) for insomnia. This study is to evaluate the clinical efficacy of acupuncture with LAS in patient with insomnia.The PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, Weipu Database for Chinese Technical Periodicals, Chinese Biomedical Database, and Wanfang Database were systematically searched from the inception dates to December 18, 2021. Randomized controlled trials of acupuncture with LAS versus acupuncture with DAS or acupuncture with LAS plus DAS versus acupuncture with DAS in patient with insomnia were included. Two review authors independently performed the data extraction and assessed study quality. A meta-analysis was performed using random-effects models to calculate relative risk and weighted mean difference for categorical and continuous variables, respectively. The primary efficacy outcome was improvement on Pittsburgh Sleep Quality Index (PSQI). Secondary outcomes included insomnia severity index, Epworth sleepiness scale, Hamilton anxiety scale, Hamilton Depression Scale (HAMD), and total effective rate.A total of 7 trials with 468 patients fulfilled the selection criteria. The pooled results indicated that acupuncture with LAS plus DAS could reduce PSQI score by 2.08 (1.60 after excluding heterogeneity) compared to acupuncture with DAS. Acupuncture with LAS plus DAS had high reliability in sleep quality, sleep latency, sleep time and daytime function, but showed no significant effect on sleep disorder and hypnotic drug. For total effective rate, acupuncture with LAS plus DAS or acupuncture with LAS was better than acupuncture with DAS, but the conclusion was less credible.Acupuncture with LAS is significantly associated with improvements in several sleep parameters, primarily evident on the PSQI score. Nevertheless, considering the poor methodological quality, trials employing appropriate randomization concealment and blinding based on a larger sample size are needed in the future.

The purpose of the study was to assess the efficacy of electroacupuncture on dry eye (DE).Eighty-four DE patients were randomly assigned to receive electroacupuncture (EAG) three times a week or 0.1% sodium hyaluronate artificial tears (ATG) four times per day for 4 weeks. The primary outcomes were non-invasive tear film breakup time (NIBUT) and tear meniscus height (TMH). The secondary outcomes included the ocular surface disease index (OSDI), Schirmer I test (SIT), corneal sodium fluorescein staining (CFS) score, corneal topography descriptors surface asymmetry index (SAI) and surface regularity index (SRI), corneal sensitivity, 36-item Short-form Health Survey (SF-36) score and Hospital Anxiety and Depression Scale (HADS) score. All outcomes were assessed at Week 0 (baseline), Week 4 (after-treatment) and Week 8 (follow-up).Between-group comparisons showed significant differences in the changes in NIBUT (Week 4, p = 0.003; Week 8, p = 0.008), TMH (Week 4, p = 0.014; Week 8, p = 0.009), OSDI (Week 4, p = 0.029; Week 8, p = 0.022), CFS score (Week 8, p = 0.036) and SF-36 role-physical score (Week 4, p = 0.010), favouring EAG. Mean changes in SIT, SAI, SRI, corneal sensitivity and HADS scores were statistically equal between the two groups (all p 0.05). Treatment with electroacupuncture was well-tolerated and showed minimal adverse events.Compared with artificial tears, electroacupuncture shows superior efficacy in improving tear film stability and symptoms of DE.

Chemotherapy has become a popular combination strategy to improve the response rate of immunotherapy since certain chemotherapeutic drugs kill tumor cells by an immunogenic cell death (ICD) pathway, which activates antitumor immune responses. Unfortunately, the synergistic effect of chemoimmunotherapy can be impaired due to the toxicities of chemotherapeutic agent-induced lymphatic depletion and immunosuppression. In this study, we present an approach to improve immunotherapy by using tumor RNA nanoparticles (RNA-NPs) where RNA is directly extracted from chemotherapy-treated cancer cells and then condensed by protamine via electrostatic interactions to form complexes. Such RNA-NPs can be effectively taken up by dendritic cells (DCs) in the draining lymph nodes after subcutaneous injection. Compared with noninduced tumor RNA nanoparticles (N-RNA-NPs), chemotherapy-induced tumor RNA nanoparticles (C-RNA-NPs) can significantly promote DC maturation and stimulate a stronger immune response against established CT-26 colon carcinoma. Besides, C-RNA-NPs can improve the efficacy of immune checkpoint blockade (ICB) therapy by facilitating the infiltration of intratumoral T cells and increasing the ratio of CD8

The objective of infill well placement optimization is to determine the optimal well locations that maximize the net present value (NPV). The most common method of well infilling in oil field is based on the engineer’s knowledge, which is risky. Additionally, numerous optimization techniques have been proposed to address the issues. However, locating the global optimum in a large-scale practical reservoir model is computationally expensive, even more so in the realistic extra-low permeability reservoir, where fractures are generated and underground conditions are complex. Thus, both determining well locations solely through human experience and obtaining them through traditional optimization methods have disadvantages in actual engineering applications. In this paper, we propose an infill well optimization strategy based on the divide-and-conquer principle that divides the large-scale realistic reservoir model into several types of small-scale conceptual models using human knowledge and then uses the surrogate-assisted evolutionary algorithm to obtain the infill well laws for this reservoir. The diamond inversed nine-spot well patterns are studied and summarized to provide the optimal infill well placement laws for extra-low permeability reservoirs. Additionally, the laws are implemented in W-77 actual reservoir and the oil recovery has an equivalent increase of 2.205%. The results demonstrate the proposed method’s strong engineering potential and application value, as it combines the benefits of human experience and evolutionary algorithms to determine the optimal infill well placement in a realistic extra-low permeability reservoir development scenario.

Inflammation is the phenotypic form of various diseases. Recent development in molecular imaging provides new insights into the diagnostic and therapeutic evaluation of different inflammatory diseases as well as diseases involving inflammation such as cancer. While conventional imaging techniques used in the clinical setting provide only indirect measures of inflammation such as increased perfusion and altered endothelial permeability, optical imaging is able to report molecular information on diseased tissue and cells. Optical imaging is a quick, noninvasive, nonionizing, and easy-to-use diagnostic technology which has been successfully applied for preclinical research. Further development of optical imaging technology such as optoacoustic imaging overcomes the limitations of mere fluorescence imaging, thereby enabling pilot clinical applications in humans. By means of endogenous and exogenous contrast agents, sites of inflammation can be accurately visualized in vivo. This allows for early disease detection and specific disease characterization, enabling more rapid and targeted therapeutic interventions. In this review, we summarize currently available optical imaging techniques used to detect inflammation, including optical coherence tomography (OCT), bioluminescence, fluorescence, optoacoustics, and Raman spectroscopy. We discuss advantages and disadvantages of the different in vivo imaging applications with a special focus on targeting inflammation including immune cell tracking.