LINC08148 promotes the caveola-mediated endocytosis of Zika virus through upregulating transcription of Src.

Long non-coding RNAs (lncRNAs) represent a new group of host factors involved in viral infection. Current study identified an intergenic lncRNA, LINC08148, as a proviral factor of Zika virus (ZIKV) and Dengue virus 2 (DENV2). Knockout (KO) or silencing of LINC08148 decreases the replication of ZIKV and DENV2. LINC08148 mainly acts at the endocytosis step of ZIKV but at a later stage of DENV2. RNA-seq analysis reveals that LINC08148 knockout downregulates the transcription levels of five endocytosis-related genes including AP2B1, CHMP4C, DNM1, FCHO1, and Src. Among them, loss of Src significantly decreases the uptake of ZIKV. Trans-complementation of Src in the LINC08148KO cells largely restores the caveola-mediated endocytosis of ZIKV, indicating that the proviral effect of LINC08148 is exerted through Src. Finally, LINC08148 upregulates the Src transcription through associating with its transcription factor SP1. This work establishes an essential role of LINC08148 in the ZIKV entry, underscoring a significance of lncRNAs in the viral infection. IMPORTANCE: Long non-coding RNAs (lncRNAs), like proteins, participate in viral infection. However, functions of most lncRNAs remain unknown. In this study, we performed a functional screen based on microarray data and identified a new proviral lncRNA, LINC08148. Then, we uncovered that LINC08148 is involved in the caveola-mediated endocytosis of ZIKV, rather than the classical clathrin-mediated endocytosis. Mechanistically, LINC08148 upregulates the transcription of Src, an initiator of caveola-mediated endocytosis, through binding to its transcription factor SP1. This study identifies a new lncRNA involved in the ZIKV infection, suggesting lncRNAs and cellular proteins are closely linked and cooperate to regulate viral infection.

Overcoming Xenoantigen Immunity to Enable Cellular Tracking and Gene Regulation with Immune-competent "NoGlow" Mice.

The ability to temporally regulate gene expression and track labeled cells makes animal models powerful biomedical tools. However, sudden expression of xenobiotic genes [e.g., GFP, luciferase (Luc), or rtTA3] can trigger inadvertent immunity that suppresses foreign protein expression or results in complete rejection of transplanted cells. Germline exposure to foreign antigens somewhat addresses these challenges; however, native fluorescence and bioluminescence abrogates the utility of reporter proteins and highly spatiotemporally restricted expression can lead to suboptimal xenoantigen tolerance. To overcome these unwanted immune responses and enable reliable cell tracking/gene regulation, we developed a novel mouse model that selectively expresses antigen-intact but nonfunctional forms of GFP and Luc, as well as rtTA3, after CRE-mediated recombination. Using tissue-specific CREs, we observed model and sex-based differences in immune tolerance to the encoded xenoantigens, illustrating the obstacles of tolerizing animals to foreign genes and validating the utility of these "NoGlow" mice to dissect mechanisms of central and peripheral tolerance. Critically, tissue unrestricted NoGlow mice possess no detectable background fluorescence or luminescence and exhibit limited adaptive immunity against encoded transgenic xenoantigens after vaccination. Moreover, we demonstrate that NoGlow mice allow tracking and tetracycline-inducible gene regulation of triple-transgenic cells expressing GFP/Luc/rtTA3, in contrast to transgene-negative immune-competent mice that eliminate these cells or prohibit metastatic seeding. Notably, this model enables de novo metastasis from orthotopically implanted, triple-transgenic tumor cells, despite high xenoantigen expression. Altogether, the NoGlow model provides a critical resource for in vivo studies across disciplines, including oncology, developmental biology, infectious disease, autoimmunity, and transplantation. SIGNIFICANCE: Multitolerant NoGlow mice enable tracking and gene manipulation of transplanted tumor cells without immune-mediated rejection, thus providing a platform to investigate novel mechanisms of adaptive immunity related to metastasis, immunotherapy, and tolerance.

Vaccines targeting ESR1 activating mutations elicit anti-tumor immune responses and suppress estrogen signaling in therapy resistant ER+ breast cancer.

ER+ breast cancers (BC) are characterized by the elevated expression and signaling of estrogen receptor alpha (ESR1), which renders them sensitive to anti-endocrine therapy. While these therapies are clinically effective, prolonged treatment inevitably results in therapeutic resistance, which can occur through the emergence of gain-of-function mutations in ESR1. The central importance of ESR1 and development of mutated forms of ESR1 suggest that vaccines targeting these proteins could potentially be effective in preventing or treating endocrine resistance. To explore the potential of this approach, we developed several recombinant vaccines encoding different mutant forms of ESR1 (ESR1mut) and validated their ability to elicit ESR1-specific T cell responses. We then developed novel ESR1mut-expressing murine mammary cancer models to test the anti-tumor potential of ESR1mut vaccines. We found that these vaccines could suppress tumor growth, ESR1mut expression and estrogen signaling in vivo. To illustrate the applicability of these findings, we utilize HPLC to demonstrate the presentation of ESR1 and ESR1mut peptides on human ER+ BC cell MHC complexes. We then show the presence of human T cells reactive to ESR1mut epitopes in an ER+ BC patient. These findings support the development of ESR1mut vaccines, which we are testing in a Phase I clinical trial.

Research on landslide susceptibility prediction model based on LSTM-RF-MDBN.

The occurrence of landslide disasters causes huge economic losses and casualties. Although many achievements have been made in predicting the probability of landslide disasters, various factors such as the scale and spatial location of landslide geological disasters should still be fully considered. Further research on how to quantitatively characterize the susceptibility of landslide geological disasters is necessarily important. To this end, taking the Wenchuan earthquake as the research area and extracting eight influencing factors, including terrain information entropy (Ht), lithology, distance from rivers, distance from faults, vegetation coverage (NDVI), distance from roads, peak ground motion acceleration (PGA), and annual rainfall, a landslide susceptibility prediction model was hereby established based on LSTM-RF-MDBN, a landslide susceptibility prediction map was drawn, and the spatial distribution characteristics of landslide disasters were analyzed. The results showed that (1) LSTM had good prediction results for the eight influencing factors, with an average prediction accuracy of 85%; (2) compared with models such as DNN and LR for predicting landslide disaster points, the AUC value of RF for predicting landslide point positions reached 0.88, presenting a higher accuracy compared to other models; (3) the AUC value of the landslide susceptibility prediction model based on LSTM-RF-MDBN reached 0.965, which had a high accuracy in predicting landslide susceptibility. Overall, the research results can provide a scientific basis for selecting the best strategy for landslide disaster warning, prevention, and mitigation.

Emission characteristics of cellulosic jet biofuel blend under laminar and turbulent combustion.

Alternative biofuels have the potential to reduce greenhouse gas emissions and particulate matter due to free of aromatics compared to traditional petroleum-based aviation fuel. The potential mitigating emission of hydrothermal-condensation-hydrotreating jet biofuel (HCHJ) derived from agriculture residue was investigated. The effects of aviation biofuel components, blend ratio and equivalent ratio on emission characteristics were conducted by Premixed Pre-evaporated Bunsen burner (PPBB) for laminar combustion and ZF850 jet engine for turbulent combustion. In compositions, HCHJ had a higher concentration of cycloparaffins (mostly in C8-C10) while petroleum-based aviation fuel (RP-3) had a higher concentration of alkylbenzenes (mostly in C8-C11). In laminar combustion, HCHJ and both 50% blend HCHJ appear no unburned hydrocarbon (UHC) due to low aromatics content and no sulfur in the biofuel. Moreover, there were no significant differences in NO and NO2 concentration for HCHJ and HCHJ blends. In turbulent combustion, HCHJ blends and RP-3 were compared engine emissions at various state points. Considering all complex effects of fuel and combustion environment, HCHJ blend had a noticeable reduction in PM2.5 emissions in comparison with RP-3 due to their lower aromatics and sulfur content. As HCHJ is similar to RP-3 in C/H ratio, density and heat value and the different aromatics contents have different tendencies to generate PM2.5 at different condition, PM2.5 emission is not only related with the total aromatic content and individual aromatic structure but also the combustion environment at thrust setting and coexisting pollutants including NOx and UHC emissions. CO and NOx emission indicated that both of turbulent state and fuel type influence emissions. HCHJ blend can be benefit for PM2.5 reduction and combustion efficiency growth. PM2.5 reduction can be obtained 77.5% at 10% HCHJ blend and 9.5% at 5% HCHJ blend while combustion efficiency can be obtained 0.05% at 5% HCHJ blend and 0.36% at 10% HCHJ blend through all thrust output.

Integrating properties and conditions to predict spray performance of alternative aviation fuel by ANN model.

Alternative aviation fuel has been confirmed benefits for GHGs reduction and energy saving. Alternative fuel use should meet drop-in fuel requirement, and one of the important factors to ensure combustion completeness is to achieve spray requirement in the whole envelop of flight. Alternative fuels are characterized different fuel properties at low temperature comparison with traditional jet fuel. For understanding fuel properties and spray-related processes under different conditions, alternative aviation fuel, including Fischer Tropsch (FT), cellulose hydrotreating jet fuel (CHJ) and traditional jet fuel (RP-3), were investigated spray performance. According to empirical equation deduced from experiment data (283 K-343 K), deviations to RP-3 enhanced significantly on surface tension and viscosity at low temperature aera (243 K-273 K). As the complex and discontinuous interaction between nozzle structure and fuel properties with temperature, and thus it is difficult to obtain appropriate empirical equation or simulation results at low temperature. Moreover, non-drop-in fuel like pure FT fuel cannot comply with the same spray mechanism as drop-in fuel. The artificial neural network (ANN) approaches have been involved to solve the complex relationship of properties with spray performance. ANN-spray model coupling with ANN-mass flow can predict not only cone angle and liquid length but also SMD and velocity in liquid zone and droplet zone with above 0.99 total correlation coefficient. Coupling simulation results of mass flow and spray performance, FT and CHJ as well as blend fuels present more obvious difference to RP-3 in droplet size distribution and velocity distribution at low temperature.

Correlation analysis of regional carbon emission intensity and green industry development-A case study of Chengdu-Chongqing region.

Industrial structure markedly affects the level of carbon emissions generated in a region. It is imperative to study the industrial structure of the Chengdu-Chongqing region to obtain information to achieve regional high-quality development by promoting low-carbon development. We selected 16 cities in Chengdu-Chongqing area as the research object in this study. The total carbon emissions (CE), carbon intensity (CI) and per capita carbon emissions (PCE) were calculated for each city. The green industry development (GI) evaluation indexes were then extracted, and the comprehensive evaluation value was determined using the entropy weight-TOPSIS model (EWM-TOPSIS). The green industry development was used as the core explanatory variable to construct a system representing the dynamic relationship between green industry development and carbon intensity using the quantile regression (QR) model. The results of the study showed that: (1) the total carbon emissions of Chengdu-Chongqing region increased whereas the carbon intensity decreased from 2010 to 2020. (2) The green industry development evaluation results showed that Chengdu-Chongqing had unevenly distributed green industry development during the study period, and Chengdu and Chongqing cities had higher green industry development values than other cities. (3) The green industry development of the region had a significant negative effect on carbon intensity at low quantile and a significant positive effect on carbon intensity at high quantile. Energy supply (ES) was positively correlated with the carbon intensity of the region at 1 % level of significance, whereas urbanization rate (U) and power consumption (PEC) were negatively correlated with the carbon intensity at 1 % level of significance. We comprehensively evaluated the development of green industry and introduced it as a core explanatory variable into the quantile regression model to explore the relationship between regional carbon emission intensity and industrial development. The results provide a reference for designing strategies to promote high-quality development in the cities in the Chengdu-Chongqing region.

Exploring the efficacy and beneficial population of preimplantation genetic testing for aneuploidy start from the oocyte retrieval cycle: a real-world study.

BACKGROUND: Preimplantation genetic testing for aneuploidy (PGT-A) is widely used as an embryo selection technique in in vitro fertilization (IVF), but its effectiveness and potential beneficiary populations are unclear. METHODS: This retrospective cohort study included patients who underwent their first oocyte retrieval cycles at CITIC-Xiangya between January 2016 and November 2019, and the associated fresh and thawed embryo transfer cycles up to November 30, 2020. PGT-A (PGT-A group) and intracytoplasmic sperm injection (ICSI)/IVF (non-PGT-A group) cycles were included. The numbers of oocytes and embryos obtained were unrestricted. In total, 60,580 patients were enrolled, and baseline data were matched between groups using 1:3 propensity score matching. Sensitivity analyses, including propensity score stratification and traditional multivariate logistic regression, were performed on the original unmatched cohort to check the robustness of the overall results. Analyses were stratified by age, body mass index, ovarian reserve/responsiveness, and potential indications to explore benefits in subgroups. The primary outcome was cumulative live birth rate (CLBR). The other outcomes included live birth rate (LBR), pregnancy loss rate, clinical pregnancy rate, pregnancy complications, low birth weight rate, and neonatal malformation rate. RESULTS: In total, 4195 PGT-A users were matched with 10,140 non-PGT-A users. A significant reduction in CLBR was observed in women using PGT-A (27.5% vs. 31.1%; odds ratio (OR) = 0.84, 95% confidence interval (CI) 0.78-0.91; P < 0.001). However, women using PGT-A had higher first-transfer pregnancy (63.9% vs. 46.9%; OR = 2.01, 95% CI 1.81-2.23; P < 0.001) and LBR (52.6% vs. 34.2%, OR = 2.13, 95% CI 1.92-2.36; P < 0.001) rates and lower rates of early miscarriage (12.8% vs. 20.2%; OR = 0.58, 95% CI 0.48-0.70; P < 0.001), preterm birth (8.6% vs 17.3%; P < 0.001), and low birth weight (4.9% vs. 19.3%; P < 0.001). Moreover, subgroup analyses revealed that women aged ≥ 38 years, diagnosed with recurrent pregnancy loss or intrauterine adhesions benefited from PGT-A, with a significant increase in first-transfer LBR without a decrease in CLBR. CONCLUSION: PGT-A does not increase and decrease CLBR per oocyte retrieval cycle; nonetheless, it is effective in infertile populations with specific indications. PGT-A reduces complications associated with multiple gestations.

Machine Learning-Enhanced Biomass Pressure Sensor with Embedded Wrinkle Structures Created by Surface Buckling.

Flexible piezoresistive sensors are core components of many wearable devices to detect deformation and motion. However, it is still a challenge to conveniently prepare high-precision sensors using natural materials and identify similar short vibration signals. In this study, inspired by microstructures of human skins, biomass flexible piezoresistive sensors were prepared by assembling two wrinkled surfaces of konjac glucomannan and k-carrageenan composite hydrogel. The wrinkle structures were conveniently created by hardness gradient-induced surface buckling and coated with MXene sheets to capture weak pressure signals. The sensor was applied to detect various slight body movements, and a machine learning method was used to enhance the identification of similar and short throat vibration signals. The results showed that the sensor exhibited a high sensitivity of 5.1 kPa-1 under low pressure (50 Pa), a fast response time (104 ms), and high stability over 100 cycles. The XGBoost machine learning model accurately distinguished short voice vibrations similar to those of individual English letters. Moreover, experiments and numerical simulations were carried out to reveal the mechanism of the wrinkle structure preparation and the excellent sensing performance. This biomass sensor preparation and the machine learning method will promote the optimization and application of wearable devices.

Overexpression of OsPIN9 Impairs Chilling Tolerance via Disturbing ROS Homeostasis in Rice.

The auxin efflux transporter PIN-FORMED (PIN) family is one of the major protein families that facilitates polar auxin transport in plants. Here, we report that overexpression of OsPIN9 leads to altered plant architecture and chilling tolerance in rice. The expression profile analysis indicated that OsPIN9 was gradually suppressed by chilling stress. The shoot height and adventitious root number of OsPIN9-overexpressing (OE) plants were significantly reduced at the seedling stage. The roots of OE plants were more tolerant to N-1-naphthylphthalamic acid (NPA) treatment than WT plants, indicating the disturbance of auxin homeostasis in OE lines. The chilling tolerance assay showed that the survival rate of OE plants was markedly lower than that of wild-type (WT) plants. Consistently, more dead cells, increased electrolyte leakage, and increased malondialdehyde (MDA) content were observed in OE plants compared to those in WT plants under chilling conditions. Notably, OE plants accumulated more hydrogen peroxide (H2O2) and less superoxide anion radicals (O2-) than WT plants under chilling conditions. In contrast, catalase (CAT) and superoxide dismutase (SOD) activities in OE lines decreased significantly compared to those in WT plants at the early chilling stage, implying that the impaired chilling tolerance of transgenic plants is probably attributed to the sharp induction of H2O2 and the delayed induction of antioxidant enzyme activities at this stage. In addition, several OsRboh genes, which play a crucial role in ROS production under abiotic stress, showed an obvious increase after chilling stress in OE plants compared to that in WT plants, which probably at least in part contributes to the production of ROS under chilling stress in OE plants. Together, our results reveal that OsPIN9 plays a vital role in regulating plant architecture and, more importantly, is involved in regulating rice chilling tolerance by influencing auxin and ROS homeostasis.

An AQI decomposition ensemble model based on SSA-LSTM using improved AMSSA-VMD decomposition reconstruction technique.

Air quality index (AQI) is a key index for monitoring air pollution and can be used as guide for ensuring good public health. Accurate AQI prediction allows timely control and management of air pollution. In this study, a new integrated learning model was constructed to predict AQI. A smart reverse learning approach based on AMSSA was utilized to increase the diversity of populations, and an improved AMSSA (IAMSSA) was established. The optimum parameters with penalty factor α and mode number K of VMD were obtained using IAMSSA. The IAMSSA-VMD was used to decompose nonlinear and non-stationary AQI information series into several regular and smooth sub-sequences. The Sparrow Search Algorithm (SSA) was used to determine the optimum LSTM parameters. The results showed that: (1) IAMSSA exhibits faster convergence and higher accuracy and stability using simulation experiments compared with seven conventional optimization algorithms in 12 test functions. (2) IAMSSA-VMD was used to decompose the original air quality data results in multiple uncoupled intrinsic mode function (IMF) components and one residual (RES). An SSA-LSTM model was built for each IMF and one RES component, which effectively extracted the predicted values. (3) LSTM, SSA-LSTM, VMD-LSTM, VMD-SSA-LSTM, AMSSA-VMD-SSA-LSTM, and IAMSSA-VMD-SSA-LSTM models were used for prediction of AQI based on data from three cities (Chengdu, Guangzhou, and Shenyang). IAMSSA-VMD-SSA-LSTM exhibited the optimal prediction performance with MAE, RMSE, MAPE, and R2 of 3.692, 4.909, 6.241, and 0.981, respectively. (4) Generalization outcomes revealed that the IAMSSA-VMD-SSA-LSTM model had optimal generalization ability. In summary, the decomposition ensemble model proposed in this study has higher prediction accuracy, improved fitting effect and generalization ability compared with other models. These properties indicate the superiority of the decomposition ensemble model and provides a theoretical and technical basis for prediction of air pollution and ecosystem restoration.

A synthetic light-inducible photorespiratory bypass enhances photosynthesis to improve rice growth and grain yield.

Bioengineering of photorespiratory bypasses is an effective strategy for improving plant productivity by modulating photosynthesis. In previous work, two photorespiratory bypasses, the GOC and GCGT bypasses, increased photosynthetic rates but decreased seed-setting rate in rice (Oryza sativa), probably owing to excess photosynthate accumulation in the stem. To solve this bottleneck, we successfully developed a new synthetic photorespiratory bypass (called the GMA bypass) in rice chloroplasts by introducing Oryza sativa glycolate oxidase 1 (OsGLO1), Cucurbita maxima malate synthase (CmMS), and Oryza sativa ascorbate peroxidase7 (OsAPX7) into the rice genome using a high-efficiency transgene stacking system. Unlike the GOC and GCGT bypass genes driven by constitutive promoters, OsGLO1 in GMA plants was driven by a light-inducible Rubisco small subunit promoter (pRbcS); its expression dynamically changed in response to light, producing a more moderate increase in photosynthate. Photosynthetic rates were significantly increased in GMA plants, and grain yields were significantly improved under greenhouse and field conditions. Transgenic GMA rice showed no reduction in seed-setting rate under either test condition, unlike previous photorespiratory-bypass rice, probably reflecting proper modulation of the photorespiratory bypass. Together, these results imply that appropriate engineering of the GMA bypass can enhance rice growth and grain yield without affecting seed-setting rate.

Dural Arteriovenous Fistulas Presenting as Symmetric Lesions in the Internal Capsule on Imaging Studies: A Case Report and Literature Review.

BACKGROUND: Dural arteriovenous fistulas (DAVFs) leading to oedema, primarily in the internal capsule, are extremely rare and, to our knowledge, have never been reported. We reported a case of DAVFs with oedema in bilateral internal capsule oedema and reviewed the literature. METHODS: The report describes a unique imaging presentation of cases of DAVFs as symmetric lesions, mainly in the bilateral internal capsule. It also reviews the literature for symmetric lesions in the internal capsule and central grey matter caused by DAVFs to further characterize this rare entity and differential diagnosis through imaging features. RESULTS: In cases of symmetric oedema caused by DAVFs, the most common artery involved in arterial supply was the middle meningeal artery (13/24; 54%). The main vein involved in the drainage was the Galen vein (18/29; 62%). Most cases were treated with transarterial embolization (23/29; 79%), and the probability of effective treatment or complete cure is 100%. On imaging, the vasogenic oedema signal caused by DAVFs is a symmetrical lesion of the bilateral internal capsule, that is, DWI MRI shows a high signal in the unrestricted diffusion area on the apparent diffusion coefficient map. CONCLUSIONS: MR has good diagnostic value in abnormal basal ganglia symmetric signals caused by DAVFs, and can quickly identify DAVFs early.

Biomechanics of Topspin Forehand Loop in Table Tennis: An Application of OpenSim Musculoskeletal Modelling.

Topspin is one of the most attacking strokes in table tennis, and topspin forehand loop is an effective way to score. The aim of this study was to investigate the kinematics of the lower extremities in topspin forehand loop between different levels via OpenSim Musculoskeletal Modelling. Ten elite athletes (NL1) and ten medium athletes (NL2) performed the topspin forehand loop without muscle and joint injuries. An eight-camera Vicon motion capture system was used to measure the kinematics data. During the topspin forehand loop, the forward phase (FP) and the entire phase (EP) of the NL1 were significantly shorter than that of the NL2. In the sagittal plane, NL1 significantly had greater hip and ankle flexion and extension at range of motion (ROM) but less hip flexion and knee flexion at FP and less ankle flexion at BP than NL2. In the frontal plane, NL1 displayed less ROM in the hip joint and significantly less hip abduction ROM at the backward phase (BP). In the transverse plane, NL1 had a significantly greater ROM in the hip joint and displayed significantly less hip ROM at the BP. The level differences presented in this study could help table tennis athletes to improve performance and coaches to develop technical training.

Behavioral abnormalities in C57BL/6 mice with chronic ulcerative colitis induced by DSS.

BACKGROUND: Clinical epidemiological studies have found that some patients with ulcerative colitis (UC) are prone to mental disorders. DSS-induced acute and chronic UC models are often used to evaluate the efficacy of anti-UC drugs. However, whether DSS has an effect on mouse behavior has not been reported. METHODS: Acute and chronic UC models were induced by 3% DSS and 1.5% DSS, respectively. The bloody stool, the changes in the colon length, and histopathological changes in the colon were used to evaluate the success of the animal model. The behavior of mice was evaluated by open field experiment, tail suspension experiment and Sucrose preference test. RESULTS: The weight of mice in 3% DSS group decreased significantly, the DAI score increased significantly, the colon length of mice was significantly shortened, and the structure of colonic crypts was abnormal, which showed inflammatory cell infiltration and shrinkage of crypts. Compared with the control group, the immobility time of 3%DSS group mice in the tail suspension test and forced swimming test had no effect, the number of running and grooming times was significantly reduced, and there was no significant difference in the number of standing times. No abnormality was observed in HE staining of the hippocampus. However, in 1.5% DSS-induced chronic UC model, behavioral and hippocampal abnormalities were observed not only UC symptoms. CONCLUSIONS: The acute UC model induced by 3% DSS has certain influence on the behavior of mice, but the mental state of mice is normal, which may be the abnormal behavior caused by UC symptoms; However, the chronic UC model induced by 1.5% DSS has a significant effect on the behavior of mice, and the mice have mental disorders, which are caused by mental disorders.

The potential GHGs reduction of co-processing aviation biofuel in life cycle.

The challenge of drop-in jet biofuel should couple the reduction of GHGs emission in whole life cycle with economic competitiveness and achieving performance without reducing performance of engine and aircraft. Co-processing was recognized a promising solution due to availability of existing refining infrastructure and facilities. Based on the LCA approach, the quantitative LCA assessment model (AF-3E) has been established for discovering potential GHGs reduction by co-processing. Typical representatives of oily feedstock, including used cooking oil, soybean, rapeseed, peanut, corn oil, Xanthoceras sorbifolia, jatropha and algae, were compared co-processing with HEFA-SPK blend on GHGs and energy consumption in the whole life. Computational framework is integrated into 3 sub-models and 4 modules, which include feedstocks model, fuel model, flight model and electricity module, hydrogen module, methanol module, hexane module. In flight model, the emissions were investigated at LTO condition and cruise condition and transfer to six types of typical aircraft widely used by similarity criterion. Co-processing achieve less energy consumption and GHGs emission than HEFA-SPK blend, which is attributed to less energy consumption in fuel stage. Used cooking oil conducts 8.17% GHGs reduction in 5% bio-feedstock co-processing and 6.39% in 5% HEFA-SPK jet biofuel blend compared with petroleum-based jet fuel. By sensitivity analysis, the vital factors on GHGs have been extracted in whole life cycle. The purpose of this paper is to discover the advantages and vital factors of co-processing. The results would enhance the interests in both LCA and co-processing for sustainable aviation biofuel.

A Non-Invasive Deep Photoablation Technique to Inhibit DCIS Progression and Induce Antitumor Immunity.

Ductal carcinoma in situ (DCIS) of the breast is often managed by lumpectomy and radiation or mastectomy, despite its indolent features. Effective non-invasive treatment strategies could reduce the morbidity of DCIS treatment. We have exploited the high heat shock protein 90 (HSP90) activity in premalignant and malignant breast disease to non-invasively detect and selectively ablate tumors using photodynamic therapy (PDT). PDT with the HSP90-targeting photosensitizer, HS201, can not only ablate invasive breast cancers (BCs) while sparing non-tumor tissue, but also induce antitumor immunity. We hypothesized that HS201-PDT would both non-invasively ablate DCIS and prevent progression to invasive BC. We tested in vitro selective uptake and photosensitivity of HS201 in DCIS cell lines compared to the non-selective parental verteporfin, and assessed in vivo antitumor efficacy in mammary fat pad and intraductal implantation models. Selective uptake of HS201 enabled treatment of intraductal lesions while minimizing toxicity to non-tumor tissue. The in vivo activity of HS201-PDT was also tested in female MMTV-neu mice prior to the development of spontaneous invasive BC. Mice aged 5 months were administered HS201, and their mammary glands were exposed to laser light. HS201-PDT delayed the emergence of invasive BC, significantly prolonged disease-free survival (DFS) (p = 0.0328) and tended to improve overall survival compared to the no-treatment control (p = 0.0872). Systemic administration of anti-PD-L1 was combined with HS201-PDT and was tested in a more aggressive spontaneous tumor model, HER2delta16 transgenic mice. A single PDT dose combined with anti-PD-L1 improved DFS compared to the no-treatment control, which was significantly improved with repetitive HS201-PDT given with anti-PD-L1 (p = 0.0319). In conclusion, a non-invasive, skin- and tissue-sparing PDT strategy in combination with anti-PD-L1 antibodies effectively prevented malignant progression of DCIS to invasive BC. This non-invasive treatment strategy of DCIS may be safe and effective, while providing an option to reduce the morbidity of current conventional treatment for patients with DCIS. Clinical testing of HS201 is currently underway.

Chlorogenic Acid Relieves the Lupus Erythematosus-like Skin Lesions and Arthritis in MRL/lpr Mice.

Chlorogenic acid (CGA) is a phenylpropyl substance synthesized through the shikimic acid pathway. In addition to its anti-tumor, anti-inflammatory, and antioxidant abilities, CGA also has immunomodulatory effects. The aim of the present study is to investigate the therapeutic effects of CGA on the skin damage and arthritis caused by systemic lupus erythematosus (SLE) in an MRL/lpr mouse model. In the SLE model, female MRL/lpr mice at the age of 10 weeks old were treated with CGA daily or cyclophosphamide (CTX) weekly via intraperitoneal injection for three months. After treatment, CGA can significantly alleviate the skin and mucous membrane damage caused by SLE and has a certain improvement effect on arthritis. CGA could inhibit dsDNA expression to a certain extent but has no obvious regulation on ANA concentration. The ELISA and BioMAP results indicated that CGA might play an anti-inflammatory role by down-regulating the interleukin (IL)-17 level. In conclusion, our study demonstrates that CGA can alleviate multiorgan damage in MRL/lpr mice by reducing IL-17.

Low temperature and freezing pretreatment for konjac glucomannan powder to improve gel strength.

Konjac glucomannan (KGM) gel has attracted widespread interest in the field of food. However, the low texture properties of gel limit its further application. In this study, the effect of KGM powder under different processing times (8 h, 12 h, 24 h and 48 h) and temperatures (4 °C, -18 °C, -80 °C) on the texture properties of gels were investigated. According to result of texture profile analysis (TPA) and puncture test, the gel prepared by pretreatment showed good texture characteristics. The gel prepared by freezing KGM powder at -18 °C for 8 h has the best gel strength in the sample, which is 1.6 times that of native KGM. The molecular weight of KGM decreased significantly after pretreatment (from 12.30 × 105 Da to 0.29 × 105 Da). In addition, low temperature and freezing treatment can influence the rheological behavior and regulate water composite in gel. According to experimental result, it can be attributed to that low temperature and the growth of ice crystal can make structures denser, promote KGM molecular chain entangled and increase the number of hydrogen bond. This study provides a convenient and effective method for improving the gel properties.