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Abstract Atropisomeric biaryls bearing carbonyl groups have attracted increasing attention due to their prevalence in diverse bioactive molecules and crucial role as efficient organo-catalysts or ligands in asymmetric transformations. However, their preparation often involves tedious multiple steps, and the direct synthesis via asymmetric carbonylation has scarcely been investigated. Herein, we report an efficient palladium-catalyzed enantioconvergent aminocarbonylation of racemic heterobiaryl triflates with amines via dynamic kinetic asymmetric transformation (DyKAT). This protocol features a broad substrate scope and excellent compatibility for rapid construction of axially chiral amides in good to high yields with excellent enantioselectivities. Detailed mechanistic investigations discover that the base can impede the intramolecular hydrogen bond-assisted axis rotation of the products, thus allowing for the success to achieve high enantioselectivity. Moreover, the achieved axially chiral heterobiaryl amides can be directly utilized as N,N,N-pincer ligands in copper-catalyzed enantioselective formation of C(sp3)-N and C(sp3)-P bonds.

Abstract Background Remnant cholesterol (RC) reportedly contributes to the development of diabetes mellitus. However, evidence on the relationship between maternal RC and the risk of developing gestational diabetes mellitus (GDM) during pregnancy is limited. This study aimed to assess the relationship between maternal RC and GDM risk during early pregnancy, and explore the potential pathways involved in the relationship between RC levels and GDM risk. Methods From 2018 to 2021, a prospective birth cohort study was designed and carried out in China. The associations of maternal RC and other lipid parameters with GDM risk were estimated using logistic regression models and restricted cubic splines. Subgroup analyses were performed stratified by prepregnancy body mass index (pre-BMI), maternal age and gravidity. Mediation analyses were conducted to explore the mediating effect of some related factors on the relationship between RC levels and the risk of GDM. Results A total of 33,018 pregnant women were included. The median RC level was 0.47 ± 0.20 mmol/L. The prevalence of GDM was 15.19%. As RC quartiles increased, the incidence of GDM increased substantially, reaching 19.24% for the highest quartile of RC (P 0.05) and was consistent across subgroups with different pre-BMIs, maternal ages and gravidities (all P values for interactions > 0.05). Furthermore, the correlation between RC level and GDM risk was partially mediated by pre-BMI (9.20%) and blood glucose level (-11.1%). Conclusions Higher maternal RC levels in the early stage of pregnancy was positively associated with an increased risk of developing GDM. This association was partially mediated by pre- BMI and blood glucose levels.

Abstract Slow-controlled release fertilizers are experiencing a popularity in rice cultivation due to their effectiveness in yield and quality with low environmental costs. However, the underlying mechanism by which these fertilizers regulate grain quality remains inadequately understood. This study investigated the effects of five fertilizer management practices on rice yield and quality in a two-year field experiment: CK, conventional fertilization, and four applications of slow-controlled release fertilizer (UF, urea formaldehyde; SCU, sulfur-coated urea; PCU, polymer-coated urea; BBF, controlled-release bulk blending fertilizer). In 2020 and 2021, the yields of UF and SCU groups showed significant decreases when compared to conventional fertilization, accompanied by a decline in nutritional quality. Additionally, PCU group exhibited poorer cooking and eating qualities. However, BBF group achieved increases in both yield (10.8 t hm−2 and 11.0 t hm−2) and grain quality reaching the level of CK group. The adequate nitrogen supply in PCU group during the grain-filling stage led to a greater capacity for the accumulation of proteins and amino acids in the PCU group compared to starch accumulation. Intriguingly, BBF group showed better carbon–nitrogen metabolism than that of PCU group. The optimal nitrogen supply present in BBF group suitable boosted the synthesis of amino acids involved in the glycolysis/ tricarboxylic acid cycle, thereby effectively coordinating carbon–nitrogen metabolism. The application of the new slow-controlled release fertilizer, BBF, is advantageous in regulating the carbon flow in the carbon–nitrogen metabolism to enhance rice quality.

To improve the fast and efficient distribution of fresh products with dynamic customer orders, we constructed a multi-objective vehicle routing optimization model with the objectives of minimizing the distribution costs including freshness-loss cost, cold-chain-refrigeration cost, and delay-penalty cost, and maximizing customer time satisfaction. An improved multi-objective genetic algorithm (GA)-based particle swarm optimization (MOGAPSO) algorithm was designed to quickly solve the optimal solution for the distribution routes for fresh-product orders from regular customers. Furthermore, online real-time orders of fresh products were periodically inserted into the distribution routes with local optimization solutions by applying a dynamic inserting algorithm. Finally, a case study of a fresh-product distribution company in Shenzhen, China was conducted to validate the practicality of the proposed model and algorithms. A comparison with the NSGA-Ⅱ and MOPSO algorithms showed the superiority of the proposed MOGAPSO algorithm on distribution-cost reduction and customer time-satisfaction improvement. Moreover, the dynamic inserting algorithm demonstrated a better performance on distribution-cost reduction.

Abstract Resistance to androgen receptor (AR) inhibitors, including enzalutamide (Enz), as well as bone metastasis, are major challenges for castration-resistant prostate cancer (CRPC) treatment. In this study, we identified that miR26a can restore Enz sensitivity and inhibit bone metastatic CRPC. To achieve the highest combination effect of miR26a and Enz, we developed a cancer-targeted nano-system (Bm@PT/Enz-miR26a) using bone marrow mesenchymal stem cell (BMSC) membrane and T140 peptide to co-deliver Enz and miR26a. The in vitro/in vivo results demonstrated that miR26a can reverse Enz resistance and synergistically shrink tumor growth, invasion, and metastasis (especially secondary metastasis) in both subcutaneous and bone metastatic CRPC mouse models. We also found that the EZH2/SFRP1/WNT5A axis may be involved in this role. These findings open new avenues for treating bone metastatic and Enz-resistant CRPC.

Background: The neurogenic bladder symptom score (NBSS) has been widely used to specifically measure symptoms and consequences of neurogenic bladder (NB). The cognitive interviewing (CI) is effective in assessing item clarity and identifying key issues related to the comprehension of the instrument. We aim to translate the NBSS into Chinese and use the CI approach to explore the thought processes of patients with NB in responding the Chinese Version of the NBSS, identify and modify the factors hinder the thought processes to enhance the face validity of the NBSS. Methods: The translation of the NBSS into Chinese was conducted with the guidance of the recommended frameworks. Patients with NB were recruited by purpose sampling. CI with the combination of thinking aloud and verbal probing techniques were used to explore thought processes. The interviews were transcribed and analyzed based on Tourangeau four-stage response model. Results: Two rounds of CI were carried out. The problems of comprehension, judgement and response mapping were identified in 8 items. Four items were revised based on the results of the interview. The revised items were verified and eventually integrated into the final version. Conclusion: The Chinese Version of the NBSS was easy to comprehend and use. The use of CI methodologies can increase the comprehensibility and cultural applicability of the NBSS, providing the evidence for the development of a clearer and more appropriate questionnaire.

Abstract Background Living in higher greenness level community has many benefits for pregnancy outcomes, however, few research have explored the relationship between greenness and spontaneous abortion (SAB). We aimed to analyze relationships between SAB and community greenness in Chinese pregnant women, and further assessed the modifying effects from air pollutants. Methods We studied 90 890 pregnant women from the China Birth Cohort Study from February 2018 to December 2021. We diagnosed SAB by certified obstetricians and gynecologists. The level of exposure to greenness during the first trimester was measured using the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). Particulate matter ≤ 2.5 μm (PM2.5), nitrogen dioxide (NO2) and ozone (O3) were used as proxies of ambient air pollution. Time-dependent multivariable adjusted Cox proportional hazards models, with gestational weeks as the time scale, were used to analyze the association between SAB and greenness. We additionally performed subgroup analyses stratified by age, urbanicity, research location, season of birth, temperature, humidity and air pollution levels. Results Lower SAB prevalence was related to living in greener places. A 0.1 unit increase in NDVI500m and EVI500m was significantly associated with a 12.3% (95% CI 9.9%, 15.5%) and 16.2% (95% CI 11.4%, 20.6%) lower risks of SAB, respectively. In sensitivity analysis, these relationships remained consistent. The associations were stronger among older, participants lived in the north of China and lived in places with higher PM2.5 and lower NO2 levels. Conclusions Our findings indicate significantly inverse associations between community greenness and SAB in Chinese pregnant women, especially for older and participants who live in the north of China, the PM2.5 and NO2 may modify the effects of greenness on SAB.

In the rapidly evolving landscape of smart transportation, the passenger volume in urban rail transit consistently demonstrates an upward trajectory. In this context, precise and scientifically grounded short-term passenger flow prediction methods are essential for optimizing operational scheduling and ensuring safety in urban rail transit. Consequently, this paper introduces Temporal Graph Attention Long Short-Term Memory (TGALSTM), a spatiotemporal integrated prediction network model that incorporates the surrounding environment of the station. Initially, the paper enhanced the Temporal Convolutional Network (TCN) model to capture temporal features more accurately. Subsequently, the paper utilizes the Graph Attention Network (GAT) network module specifically to extract the topological structure and surrounding environmental features of the station. Lastly, the prediction task is accomplished by weighted fusion of various features, inputting them into the Attention Long Short-Term Memory (LSTM) network. Experiments were conducted on two authentic datasets, revealing that the TGALSTM model outperforms the baseline model in both single-step and double-step predictions, showcasing the model’s exceptional performance and robustness. This research offers a robust method and support to enhance the operational efficiency and passenger flow management of urban rail transit systems.

Abstract Background Subclinical hypothyroidism (SCH) is linked to dyslipidaemia and adverse pregnancy outcomes. However, the impact of dyslipidaemia on the outcome of pregnancy in SCH is unclear. Methods We enrolled 36,256 pregnant women and evaluated their pregnancy outcomes. The following data was gathered during the first trimester (≤ 13+ 6 weeks of gestation): total cholesterol (TC), low-density lipoprotein (LDL-C), triglyceride (TG), high-density lipoprotein (HDL-C), free thyroxine (FT4) and thyroid-stimulating hormone (TSH) concentrations. The reference ranges for lipids were estimated to range from the 5th to the 95th percentile. Logistic regression assessed the relationships between dyslipidaemia and adverse pregnancy outcomes, including abortion, preeclampsia/eclampsia, low birth weight, foetal growth restriction, premature rupture of foetal membranes, gestational hypertension, preterm birth, macrosomia and gestational diabetes mellitus (GDM). Additionally, the best thresholds for predicting adverse pregnancy outcomes based on TSH, FT4, and lipid levels were determined using receiver operating characteristic curves. Results In the first trimester, LDL-C > 3.24 mmol/L, TG > 1.92 mmol/L, HDL-C 5.39 mmol/L were used to define dyslipidaemia. In this cohort, 952 (3.56%) patients were diagnosed with SCH, and those who had dyslipidaemia in the first trimester had higher incidences of gestational hypertension (6.59% vs. 3.25%), preeclampsia/eclampsia (7.14% vs. 3.12%), GDM (22.53% vs. 13.77%), and low birth weight (4.95% vs. 2.08%) than did those without dyslipidaemia. However, after adjusting for prepregnancy body mass index (pre-BMI), dyslipidaemia was no longer related to these risks. Furthermore, elevated TG dyslipidaemia in SCH patients was connected to an enhanced potential of gestational hypertension (odds ratio [OR]: 2.687, 95% confidence interval [CI]: 1.074 ~ 6.722), and elevated LDL-C dyslipidaemia correlated with increased preeclampsia/eclampsia risk (OR: 3.172, 95% CI: 1.204 ~ 8.355) after accounting for age, smoking status, alcohol use, pre-BMI, and levothyroxine use. Additionally, the combination of TC, TG, LDL-C, pre-BMI, and TSH exhibited enhanced predictive capabilities for gestational hypertension, preeclampsia/eclampsia, and GDM. Values of 0.767, 0.704, and 0.706 were obtained from the area under the curve. Conclusions Among pregnant women with SCH, dyslipidaemia in early pregnancy was related to elevated risks of adverse pregnancy consequences. The combined consideration of age, pre-BMI, TSH, and lipid levels in the first trimester could be beneficial for monitoring patients and implementing interventions to reduce adverse pregnancy outcomes.

Introduction: Metastatic castration-resistant prostate cancer (mCRPC) patients face challenges due to limited treatment options. About 50% of patients with mCRPC have a functional loss of phosphatase and tensin homology deleted on chromosome 10 (PTEN), leading to tumor progression, metastasis, and immune suppression. Moreover, elevated IL-23 produced by myeloid-derived suppressor cells (MDSCs) is found in CRPC patients, driving tumor progression. Therefore, a combination strategy based on PTEN restoration and IL-23 inhibition may block CRPC progression and metastasis.Methods: The antitumor effect of restoring PTEN expression combined with the IL-23 inhibitor Apilimod was studied in a mouse model of bone metastasis CRPC and mouse prostate cancer RM-1 cells. To verify the targeting ability of PTEN DNA coated with lipid nanoparticles (LNP@PTEN) in vitro and in vivo. In addition, RT-qPCR and flow cytometry were used to investigate the related mechanisms of the antitumor effect of LNP@PTEN combined with Apilimod.Results: LNPs exhibited significant tumor-targeting and tumor accumulation capabilities both in vitro and in vivo, enhancing PTEN expression and therapeutic efficacy. Additionally, the combination of LNP@PTEN with the IL-23 inhibitor Apilimod demonstrated enhanced inhibition of tumor growth, invasion, and metastasis (particularly secondary organ metastasis) compared to other groups, and extended the survival of mice to 41 days, providing a degree of bone protection. These effects may be attributed to the PTEN function restoration combined with IL-23 inhibition, which help reverse immune suppression in the tumor microenvironment by reducing MDSCs recruitment and increasing the CD8+/CD4+ T cell ratio.Discussion: In summary, these findings highlight the potential of LNPs for delivering gene therapeutic agents. And the combination of LNP@PTEN with Apilimod could achieve anti-tumor effects and improve tumor microenvironment. This combinational strategy opens new avenues for the treatment of mCRPC.

BackgroundNumerous epidemiological studies have elucidated the intricate connection between inflammation and cancer, highlighting how sustained inflammatory responses can fuel carcinogenesis by fostering proliferation, angiogenesis, and metastasis, while dampening immune responses and sensitivity to chemotherapy. Previous clinical investigations have underscored the potential of anti-inflammatory medications in either preventing or mitigating tumor formation. Here, the causal relationship between anti-inflammatory drugs and cancer was further explored through Mendelian randomization studies.MethodsEmploying Mendelian randomization, we scrutinized the causal links between three anti-inflammatory drugs—NSAIDs, Aspirin, and Anilide—and 37 types of cancer. We primarily utilized inverse variance weighting (IVW) as the primary analytical approach to delineate the causal association between these drugs and cancer types. Concurrently, sensitivity analyses were conducted to ascertain the absence of horizontal pleiotropy and heterogeneity.ResultsOur investigation revealed a discernible causal relationship between certain anti-inflammatory drugs and a subset of cancers, albeit without a pervasive impact across all cancer types. Specifically, NSAIDs exhibited a risk-reducing effect on non-small cell lung cancer (OR: 0.76, 95% CI: 0.59–0.97, p-value: 0.03) and gastric cancer (OR: 0.57, 95% CI: 0.34–0.98, p-value: 0.04). Conversely, aspirin was associated with an increased risk of oral malignant tumors (OR: 2.18, 95% CI: 1.13–4.21, p-value: 0.02). Notably, no statistically significant findings were observed for anilide drugs (p < 0.05).ConclusionWe identified several cancers with potential causal links to NSAIDs, including non-small cell lung cancer and gastric cancer. Despite our extensive analysis, we did not identify a substantial causal relationship between the use of anti-inflammatory drugs and the development of various cancers.

The Lianzigou deposit, which has an Au–Te paragenetic association, is hosted in plagioclase gneiss of the Qincanggou Formation in the Taihua Group in the Xiaoqinling region, central China. This quartz vein-type Au deposit comprises native Au and a variety of tellurides. The latter include calaverite (AuTe2), krennerite (Au3AgTe8), petzite (Au3AgTe2), hessite (Ag2Te), melonite (NiTe2), and altaite (PbTe). Four stages have been recognized in this deposit: stage I consists of K-feldspar and quartz; stage II is of milky quartz veins accompanied by coarse-grained disseminated and lumps of pyrite with weak Au mineralization; stage III is composed mainly of Au, tellurides, and sulfides; and stage IV is characterized by abundant carbonate and quartz. Based on mineral assemblage and thermodynamic data, we estimated the physicochemical conditions of the main metallogenic stages. Based on thermodynamic modelling, the physicochemical conditions of Au–Ag–Te mineral associations were estimated. The Au–Ag–Te minerals from stage III formed mainly under conditions of logƒO2 = −43.15 to −33.31, logƒH2S = ~−9.29, pH < 7, logfTe2 = −10.6 to −9.8 and logαAu+/αAg+ = −7.2 to −6.5. In contrast, the physicochemical conditions of stage II were higher, specifically pH (8.3–8.5) and logƒO2 (−34.90−31.96). In the ore-forming fluids of the Lianzigou deposit, the dominant Au species was Au(HS)2− while the dominant Te species were HTe−(aq) and Te22−(aq). Moreover, the Au–Ag–Te metal associations in the Lianzigou Au deposit were derived from mantle materials related to lithospheric thinning of the eastern North China craton in the Early Cretaceous under an extensional tectonic system.

The La’erma and Qiongmo Au–Se deposits are characterized by a paragenetic Au–Se association hosted in the siliceous formation of the Cambrian Taiyangding Group in the western Qinling Orogen, central China. The La’erma and Qiongmo Au–Se deposits, which are considered to be the Carlin gold deposits, comprise a variety of selenides, native gold, and stibnite coexisting with baryte. Four stages have been recognized: sage I comprises pyrite and quartz with minor stibnite; stage II is composed mainly of sulfides; stage III is composed mainly of selenides; and stage IV is dominated by quartz–baryte–dickite. Stages II and III are the main metallogenic stages. Based on changes in mineral assemblages, combined with fluid inclusions and thermodynamic data, we evaluated the physicochemical conditions of the main metallogenic stages. The logfS2 values of ore-forming fluids at stage II ranged between −10.44 and −14.60 with logfSe2 being less than −10.70. Comparably, during stage III, which is characterized by numerous selenides, the logfS2 and logfSe2 ranged from −7.13 to −12.20 and −13.98 to −8.82, respectively. The occurrence of baryte during the mineralization suggests a consistently oxidizing condition, which can effectively remove Au from fluids. More importantly, this study emphasizes that the oxidizing condition was only a fundamental prerequisite for the deposition of selenides, and a high ∑Se/S ratio of the fluid ultimately controlled the precipitation of selenides. In the La’erma and Qiongmo deposits, intense water–rock reactions occurred as ore-forming fluids flowed into the Se-rich siliceous formations, resulting in an increase in the ∑Se/S ratio of the fluid and in the precipitation of selenides.

In this paper, we study the dynamic meal delivery routing problem (MDRP) with time-sensitive customers. The multi-objective MDRP optimization model is developed to maximize customer satisfaction and minimize delay penalty cost and riding cost. To solve the dynamic MDRP, a novel waiting strategy is proposed to divide the dynamic problem into a series of static subproblems. This waiting strategy utilizes the decision threshold to determine rerouting points based on the number of dynamic meal orders. Meanwhile, time-sensitive priority is introduced to accelerate assignment and routing decisions for orders from customers with high time sensitivity. For each static subproblem, a hybrid AGA–ALNS algorithm that incorporates the adaptive genetic algorithm and adaptive large neighborhood search is developed to improve both the global and local search capabilities of the genetic algorithm. We validate the performance of the proposed waiting strategy and the AGA–ALNS algorithm through numerical instances. In addition, managerial insights are obtained from sensitivity analysis experiments.

Mineral assemblages containing Cu-Bi sulfosalts, Bi chalcogenides, and Ag-(Au) tellurides have been identified in the mid-Miocene Zhibula Cu skarn deposit, Gangdese Belt, southern Tibet. Different mineral assemblages from three locations in the deposit, including proximal massive garnet skarn, proximal retrogressed pyroxene-dominant skarn in contact with marble, and distal banded garnet–pyroxene skarn hosted in marble, are studied to constrain the evolution of the mineralization. Hypogene bornite contains elevated Bi (mean 6.73 wt.%) and co-exists in proximal andradite skarn with a second bornite with far lower Bi content, carrollite, Au-Ag tellurides (hessite, petzite), and wittichenite. This assemblage indicates formation at relatively high temperatures (>400 °C) and high fS2 and fTe2 during prograde-stage mineralization. Assemblages of Bi sulfosalts (wittichenite, aikinite, kupčíkite, and paděraite) and bismuth chalcogenides (e.g., tetradymite) in proximal pyroxene skarn are also indicative of formation at relatively high temperatures, but at relatively lower fTe2 and fS2 conditions. Within the reduced distal skarn (chalcopyrite–pyrrhotite-bearing) in marble, cobalt, and nickel occur as discrete minerals: cobaltite, melonite and cobaltic pentlandite. The trace ore mineral signature of the Zhibula skarn and the distributions of precious and critical trace elements such as Ag, Au, Co, Te, Se, and Bi support an evolving magmatic–hydrothermal system in which different parts of the deposit each define ore formation at distinct local physicochemical conditions. This is the first report of kupčíkite and paděraite from a Chinese location. Their compositions are comparable to other occurrences, but conspicuously, they do not form nanoscale intergrowths with one another.

Controlled-release urea (CRU) is widely reported to supply crop nitrogen (N) demand with one basal application, thus effectively replacing split applications of urea without diminishing grain yield and N use efficiency (NUE). However, its use for replacement for high-yield split applications of urea (CK) for rice is untested. In addition, the degree to which greenhouse gas (GHG) emissions in rice systems are affected when CRU is substituted for CK remains unclear. During 2017 and 2018, we sampled plant growth and gas emissions in a rice paddy field treated with three CRU types (sulfur-coated urea [SCU], polymer-coated urea [PCU], and bulk blended CRU [BBU]) applied via two methods (surface broadcasting on the soil and subsurface banding at 5 cm depth), with CK as a control. The three CRUs led to different soil NH4+-N dynamics, and the N supply pattern under BBU was more beneficial for rice seedling establishment than under SCU and PCU, resulting in grain yield and NUE comparable to those under CK. CRU type showed no significant effect on either CH4 emissions or N2O emissions, and broadcast CRUs exhibited significantly higher total GHG emissions than CK. However, banded CRUs significantly reduced the total GHG emissions in comparison with broadcast CRUs, by 9.2% averaged across the two years. Reduced CH4 emissions, particularly during the period prior to the middle drainage, contributed largely to the GHG difference. With comparably high grain yield and low total GHG emissions, banded BBU showed a low yield-scaled GHG (GHG emissions divided by grain yield) comparable to that under CK in both years. Overall, our study suggested that N management synchronized with rice demand and contributing to a high NUE tended to minimize yield-scaled GHG. Broadcast CRU can hardly substitute for CK in terms of either grain yield or GHG emissions, but banded BBU is a promising N management strategy for sustaining rice production while minimizing environmental impacts.

Abstract Background Doxorubicin (Dox) has been recommended in clinical guidelines for the standard-of-care treatment of breast cancer. However, Dox therapy faces challenges such as hypoxia, acidosis, H2O2-rich conditions and condensed extracellular matrix in TME as well as low targeted ability. Methods We developed a nanosystem H-MnO2-Dox-Col NPs based on mesoporous manganese dioxide (H-MnO2) in which Dox was loaded in the core and collagenase (Col) was wrapped in the surface. Further the H-MnO2-Dox-Col NPs were covered by a fusion membrane (MP) of inflammation-targeted RAW264.7 cell membrane and pH-sensitive liposomes to form biomimetic MP@H-MnO2-Dox-Col for in vitro and in vivo study. Results Our results shows that MP@H-MnO2-Dox-Col can increase the Dox effect with low cardiotoxicity based on multi-functions of effective penetration in tumor tissue, alleviating hypoxia in TME, pH sensitive drug release as well as targeted delivery of Dox. Conclusions This multifunctional biomimetic nanodelivery system exhibited antitumor efficacy in vivo and in vitro, thus having potential for the treatment of breast cancer.

Aims Serum uric acid (SUA) is considered as a risk factor for gestational diabetes mellitus (GDM). However, current studies showed inconsistent results. This study aimed to explore the relationship between SUA levels and GDM risk.Methods Eligible studies were retrieved from PubMed, Web of Science, Embase, China National Knowledge Infrastructure, and Wanfang databases up to November 1, 2022. The pooled standardized mean difference (SMD) and 95% confidence interval (CI) were used to represent the difference in SUA levels between GDM women and controls. The combined odds ratios (OR) and 95% CI were applied to assess association between SUA levels and GDM risk. Subgroup analyses were conducted on study continents, design, and quality, detection time of SUA, and GDM diagnostic criteria.Results Totally 11 studies including five case-control and six cohort studies, in which 80,387 pregnant women with 9815 GDM were included. The overall meta-analysis showed that the mean SUA level in GDM group was significantly higher than in controls (SMD = 0.423, 95%CI = 0.019–0.826, p = .040, I2 = 93%). Notably, pregnant women with elevated levels of SUA had a significantly increased risk of GDM (OR = 1.670, 95%CI = 1.184–2.356, p = .0035, I2 = 95%). Furthermore, subgroup analysis performed on the detection time of SUA showed a significant difference in the association between SUA and GDM risk within different trimesters (1st trimester: OR = 3.978, 95%CI = 2.177–7.268; 1st to 2nd trimester: OR = 1.340, 95%CI = 1.078–1.667; p between subgroups

AbstractBackground The heterogeneity of oral glucose tolerance test (OGTT) patterns during pregnancy remains unclear. This study aims to identify latent OGTT patterns in pregnant women and investigate the high-risk population for late-onset gestational diabetes mellitus (GDM).Methods This study including 17,723 participants was conducted from 2018 to 2021. Latent mixture modeling was used to identify subgroups. Modified Poisson regression was performed to explore the relationship between OGTT patterns and late-onset GDM or adverse perinatal outcomes.Results Three distinct glucose patterns, high, medium, and low glucose levels (HG, MG, and LG patterns) were identified. The HG pattern represented 28.5% of the participants and 5.5% of them developed late-onset GDM. A five-fold higher risk of late-onset GDM was found in HG pattern than in LG pattern (relative risk [RR]: 5.17, 95% confidence interval [CI]: 3.38-7.92) after adjustment. Participants in HG pattern were more likely to have macrosomia, large for gestational age, preterm birth, and cesarean deliveries, with RRs of 1.59 (1.31-1.93), 1.55 (1.33-1.82), 1.30 (1.02-1.64) and 1.15 (1.08-1.23), respectively.Conclusion Three distinct OGTT patterns presented different risks of late-onset GDM and adverse perinatal outcomes, indicating that timely monitoring of glucose levels after OGTT should be performed in pregnant women with HG pattern.

AbstractBackground To quantitatively synthesize evidence from prospective observational studies regarding the mean levels of circulating adiponectin in patients with gestational diabetes mellitus (GDM) and the association between adiponectin levels and GDM risk.Methods PubMed, EMBASE and Web of Science were searched from their inception until November 8th, 2022, for nested case-control studies and cohort studies. Random-effect models were applied to the synthesized effect sizes. The difference in circulating adiponectin levels between the GDM and control groups was measured using the pooled standardized mean difference (SMD) and 95% confidence interval (CI). The relationship between circulating adiponectin levels and GDM risk was examined using the combined odds ratio (OR) and 95% CI. Subgroup analyses were performed according to the study continent, GDM risk in the study population, study design, gestational weeks of circulating adiponectin detection, GDM diagnostic criteria, and study quality. Sensitivity and cumulative analyses were performed to evaluate the stability of the meta-analysis. Publication bias was assessed by funnel plots and Egger’s test.Results The 28 studies included 13 cohort studies and 15 nested case-control studies, containing 12,256 pregnant women in total. The mean adiponectin level in GDM patients was significantly lower than in controls (SMD = −1.514, 95% CI = −2.400 to −0.628, p = .001, I2 = 99%). The risk of GDM was significantly decreased among pregnant women with increasing levels of circulating adiponectin (OR = 0.368, 95% CI = 0.271–0.500, p

The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs. Recently, Large Language Models (LLMs) have demonstrated exceptional capabilities in text understanding, generation, and knowledge inference, opening up exciting avenues for IR research. LLMs not only facilitate generative retrieval but also offer improved solutions for user understanding, model evaluation, and user-system interactions. More importantly, the synergistic relationship among IR models, LLMs, and humans forms a new technical paradigm that is more powerful for information seeking. IR models provide real-time and relevant information, LLMs contribute internal knowledge, and humans play a central role of demanders and evaluators to the reliability of information services. Nevertheless, significant challenges exist, including computational costs, credibility concerns, domain-specific limitations, and ethical considerations. To thoroughly discuss the transformative impact of LLMs on IR research, the Chinese IR community conducted a strategic workshop in April 2023, yielding valuable insights. This paper provides a summary of the workshop’s outcomes, including the rethinking of IR’s core values, the mutual enhancement of LLMs and IR, the proposal of a novel IR technical paradigm, and open challenges.

Cracks on concrete surfaces are vital factors affecting construction safety. Accurate and efficient crack detection can prevent safety-related accidents. Using drones to photograph cracks on a concrete surface and detect them through computer vision technology has the advantages of accurate target recognition, simple practical operation, and low cost. To solve this problem, an improved CenterNet concrete crack-detection model is proposed. Firstly, a channel-space attention mechanism is added to the original model to enhance the ability of the convolution neural network to pay attention to the image. Secondly, a feature selection module is introduced to scale the feature map in the downsampling stage to a uniform size and combine it in the channel dimension. In the upsampling stage, the feature selection module adaptively selects the combined features and fuses them with the output features of the upsampling. Finally, the target size loss is optimized from a Smooth L1 Loss to IoU Loss to lessen its inability to adapt to targets of different sizes. The experimental results show that the improved CenterNet model reduces the FPS by 123.7 Hz, increases the GPU memory by 62 MB, increases the FLOPs by 3.81 times per second, and increases the AP by 15.4% compared with the original model. The GPU memory occupancy remained stable during the training process and exhibited good real-time performance and robustness.

While Carbon Dioxide based Enhanced Oil Recovery (CO2 -EOR) is often regarded as one of the most economically viable methods of carbon capture, utilization and storage (CCUS), little is known about the existing CO2 supply contracts in the CO2 -EOR industry. By studying a sample of 103 CO2 sales contracts in the U.S. in the 1980s and 1990s, this paper aims to find out what drives the key terms in these contracts. In particular, a special price adjustment clause is included to peg the CO2 price to the oil price. Our analyses suggest that the probability that the pegging term is used is positively associated with the contract length. Besides, initial oil prices, volatile historical oil prices, and the net CO2 utilization also positively impacts the adoption of the price-pegging adjustment mechanism.

Glioblastoma is rather recalcitrant to existing therapies and effective interventions are needed. Here we report a novel microenvironment-responsive micellar system (ch-K5(s-s)R8-An) for the co-delivery of the radiosensitizer Dbait and the chemotherapeutic doxorubicin (DOX) to glioblastoma. Accordingly, the ch-K5(s-s)R8-An/(Dbait-DOX) micelles plus radiotherapy (RT) treatment resulted in a high degree of apoptosis and DNA damage, which significantly reduced cell viability and proliferation capacity of U251 cells to 64.0% and 16.3%, respectively. The angiopep-2-modified micelles exhibited substantial accumulation in brain-localized U251 glioblastoma xenografts in mice compared to angiopep-2-lacking micelles. The ch-K5(s-s)R8-An/(Dbait-DOX) + RT treatment group exhibited the smallest tumor size and most profound tumor tissue injury in orthotopic U251 tumors, leading to an increase in median survival time of U251 tumor-bearing mice from 26 days to 56 days. The ch-K5(s-s)R8-An/(Dbait-DOX) micelles can be targeted to brain-localized U251 tumor xenografts and sensitize the tumor to chemotherapy and radiotherapy, thereby overcoming the inherent therapeutic challenges associated with malignant glioblastoma.

BackgroundThere is an urgent need to find an effective and accurate method for triaging coronavirus disease 2019 (COVID-19) patients from millions or billions of people. Therefore, this study aimed to develop a novel deep-learning approach for COVID-19 triage based on chest computed tomography (CT) images, including normal, pneumonia, and COVID-19 cases.MethodsA total of 2,809 chest CT scans (1,105 COVID-19, 854 normal, and 850 non-3COVID-19 pneumonia cases) were acquired for this study and classified into the training set (n = 2,329) and test set (n = 480). A U-net-based convolutional neural network was used for lung segmentation, and a mask-weighted global average pooling (GAP) method was proposed for the deep neural network to improve the performance of COVID-19 classification between COVID-19 and normal or common pneumonia cases.ResultsThe results for lung segmentation reached a dice value of 96.5% on 30 independent CT scans. The performance of the mask-weighted GAP method achieved the COVID-19 triage with a sensitivity of 96.5% and specificity of 87.8% using the testing dataset. The mask-weighted GAP method demonstrated 0.9% and 2% improvements in sensitivity and specificity, respectively, compared with the normal GAP. In addition, fusion images between the CT images and the highlighted area from the deep learning model using the Grad-CAM method, indicating the lesion region detected using the deep learning method, were drawn and could also be confirmed by radiologists.ConclusionsThis study proposed a mask-weighted GAP-based deep learning method and obtained promising results for COVID-19 triage based on chest CT images. Furthermore, it can be considered a convenient tool to assist doctors in diagnosing COVID-19.

Hyperoside (Hyp), a kind of Chinese herbal medicine, exerts multiple therapeutic effects on many diseases. However, the role and mechanisms of Hyp in vascular pathophysiology in ischemic stroke need to be further established. The study aimed to investigate the role of (large-conductance Ca2+-activated K+) BK channels on the vasoprotection of Hyp against cerebral ischemia and reperfusion (I/R) injury in rats. The concentration gradient of Hyp was pretreated in both the middle cerebral artery occlusion and reperfusion model and oxygen-glucose deprivation/reoxygenation (OGD/R) model of primary vascular smooth muscle cells (VSMCs) in rats. A series of indicators were detected, including neurological deficit score, infarct volume, malondialdehyde (MDA), superoxide dismutase (SOD), cerebral blood flow (CBF), cell viability, membrane potential, and BK channels α- and β1-subunits expression. The results showed that Hyp significantly reduced infarct volume and ameliorated neurological dysfunction in I/R-injured rats. Besides, the effects of I/R-induced reduction of BK channels α- and β1-subunits expression were significantly reversed by Hyp in endothelial-denudated cerebral basilar arteries. Furthermore, the protective effect against I/R-induced increases of MDA and reduction of SOD as well as CBF induced by Hyp was significantly reversed by iberiotoxin (IbTX). In OGD/R-injured VSMCs, downregulated cellular viability and BK channels β1-subunits expression were remarkably reversed by Hyp. However, neither OGD/R nor Hyp affected BK channels α-subunits expression, and Hyp failed to induced hyperpolarization of VSMCs. Moreover, the protective effect against OGD/R-induced reduction of cell viability and SOD level and increases of MDA production induced by Hyp was significantly reversed by IbTX in VSMCs. The study indicates that Hyp has the therapeutic potential to improve vascular outcomes, and the mechanism is associated with suppressing oxidative stress and improving CBF through upregulating BK channels.

Recent years have witnessed a surge of interest in the field of open-domain dialogue. Thanks to the rapid development of social media, large dialogue corpus from the Internet builds up a fundamental premise for data-driven dialogue model. The breakthrough in neural network also brings new ideas to researchers in AI and NLP. A great number of new techniques and methods therefore came into being. In this paper, we review some of the most representative works in recent years and divide existing prevailing frameworks for a dialogue model into three categories. We further analyze the trend of development for open-domain dialogue and summarize the goal of an open-domain dialogue system in two aspects, informative and controllable. The methods we review in this paper are selected according to our unique perspectives and by no means complete. Rather, we hope this servery could benefit NLP community for future research in open-domain dialogue.

Second-generation androgen receptor (AR) inhibitors such as enzalutamide are the first-line treatments for castration-resistant prostate cancer (CRPC). Resistance to enzalutamide will greatly increase the difficulty of prostate cancer treatment and reduce the survival time of patients. However, drug-resistant cancer cells seem to be more sensitive to ferroptosis. Therefore, we constructed a biomimetic tumor-targeting magnetic lipid nanoparticle (t-ML) to codeliver dihomo-γ-linolenic acid (DGLA) and 2,4-dienoyl-CoA reductase 1 (DECR1) siRNA (t-ML@DGLA/siDECR1). DGLA is a dietary polyunsaturated fatty acid (PUFA), while DECR1 is overexpressed in prostate cancer and can inhibit the generation of PUFAs. The combination of DGLA and siDECR1 can efficiently induce ferroptosis by peroxidation of PUFAs, which has been verified both in vitro and in vivo. With the assistance of an external magnet, t-ML showed good tumor targeting ability and biocompatibility, and t-ML@DGLA/siDECR1 exhibited significant ferroptosis induction and tumor suppression capabilities. Moreover, in a nude mouse model of prostate cancer fed on a high-fat diet (HFD), there was no distant organ metastasis when the tumor-bearing mice were treated with t-ML@DGLA/siDECR1 and an external magnet, with upregulated PUFAs and downregulated monounsaturated fatty acids (MUFAs). Hence, this study has broadened the way of treating drug-resistant prostate cancer based on ferroptosis induction.

Abstract Background Long noncoding RNA (lncRNA), urothelial carcinoma-associated 1 (UCA1) is aberrantly expressed in multiple cancers and has been verified as an oncogene. However, the underlying mechanism of UCA1 in the development of gastric cancer is not fully understood. In the present study, we aimed to identify how UCA1 promotes gastric cancer development. Methods The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) data were used to analyze UCA1 and myosin VI (MYO6) expression in gastric cancer. Western blot and quantitative real-time PCR (QPCR) were performed to test the expression level of the UCA1/miR-145/MYO6 axis in gastric cancer cell lines and tissues. The roles of the UCA1/miR-145/MYO6 axis in gastric cancer in vitro and in vivo were investigated by CCK-8 assay, flow cytometry, siRNAs, immunohistochemistry, and a mouse xenograft model. The targeted relationship among UCA1, miR-145, and MYO6 was predicted using LncBase Predicted v.2 and TargetScan online software, and then verified by luciferase activity assay and RNA immunoprecipitation. Results UCA1 expression was higher but miR-145 expression was lower in gastric cancer cell lines or tissues, compared to the adjacent normal cell line or normal tissues. Function analysis verified that UCA1 promoted cell proliferation and inhibited cell apoptosis in the gastric cancer cells in vitro and in vivo. Mechanistically, UCA1 could bind directly to miR-145, and MYO6 was found to be a downstream target gene of miR-145. miR-145 mimics or MYO6 siRNAs could partly reverse the effect of UCA1 on gastric cancer cells. Conclusions UCA1 accelerated cell proliferation and inhibited cell apoptosis through sponging miR-145 to upregulate MYO6 expression in gastric cancer, indicating that the UCA1/miR-145/MYO6 axis may serve as a potential therapeutic target for gastric cancer.

PurposeIn clinical work, accurately measuring the volume and the size of breast cancer is significant to develop a treatment plan. However, it is time-consuming, and inter- and intra-observer variations among radiologists exist. The purpose of this study was to assess the performance of a Res-UNet convolutional neural network based on automatic segmentation for size and volumetric measurement of mass enhancement breast cancer on magnetic resonance imaging (MRI).Materials and methodsA total of 1,000 female breast cancer patients who underwent preoperative 1.5-T dynamic contrast-enhanced MRI prior to treatment were selected from January 2015 to October 2021 and randomly divided into a training cohort (n = 800) and a testing cohort (n = 200). Compared with the masks named ground truth delineated manually by radiologists, the model performance on segmentation was evaluated with dice similarity coefficient (DSC) and intraclass correlation coefficient (ICC). The performance of tumor (T) stage classification was evaluated with accuracy, sensitivity, and specificity.ResultsIn the test cohort, the DSC of automatic segmentation reached 0.89. Excellent concordance (ICC > 0.95) of the maximal and minimal diameter and good concordance (ICC > 0.80) of volumetric measurement were shown between the model and the radiologists. The trained model took approximately 10–15 s to provide automatic segmentation and classified the T stage with an overall accuracy of 0.93, sensitivity of 0.94, 0.94, and 0.75, and specificity of 0.95, 0.92, and 0.99, respectively, in T1, T2, and T3.ConclusionsOur model demonstrated good performance and reliability for automatic segmentation for size and volumetric measurement of breast cancer, which can be time-saving and effective in clinical decision-making.

This experiment explored the effects of single application of seven types of slow- and controlled-release fertilizers on rice yield and various population characteristics. Based on a study of the nitrogen (N) release characteristics of these fertilizers, pot experiments were conducted in 2018 and 2019 with split fertilization (CK, urea applied split equally at basal and panicle initiation stages, respectively) as control, which assessed the effects on SPAD value, yield and yield components, dynamic changes of rice tillers and dry matter accumulation. The results showed that the N release characteristics of different types of slow- and controlled-release fertilizers were significantly different. Polymer-coated urea (PCU) showed a controlled-release mode and provided sustained release throughout the whole growth stages. Sulfur-coated urea (SCU) exhibited a slow-release mode, providing insufficient release at the middle and late stages. Urease inhibitor urea (AHA) and urea-formaldehyde (UF) yielded a rapid-release mode, with an explosive N release at the early stage and no release at the middle and late stages. These results showed that PCU delayed the peak seedling stage. Compared with CK, dry matter accumulation and SPAD showed no significant differences, and due to the continuous release of N throughout the growth stages, rice yield, spikelets per panicle, seed setting rate, and 1 000-grain weight were all increased. Owing to the lack of N supply at the late stage and the low number of spikelets, SCU led to a reduction of rice yield, which is nevertheless not statistically significant. AHA and UF were susceptible to environmental factors and had varying effects on rice yield. The results of this experiment indicated that given a fixed amount of N applied in a pot, the stronger the N supply capacity and the longer the effective duration time of the fertilizer, the higher the dry matter accumulation at the late growth stage, and the higher the rice yield.

Abstract The combination of an immuno-metabolic adjuvant and immune checkpoint inhibitors holds great promise for effective suppression of tumor growth and invasion. In this study, a pH-responsive co-delivery platform was developed for metformin (Met), a known immuno-metabolic modulator, and short interfering RNA (siRNA) targeting fibrinogen-like protein 1 mRNA (siFGL1), using a hybrid biomimetic membrane (from macrophages and cancer cells)-camouflaged poly (lactic-co-glycolic acid) nanoparticles. To improve the endo-lysosomal escape of siRNA for effective cytosolic siRNA delivery, a pH-triggered CO2 gas-generating nanoplatform was developed using the guanidine group of Met. It can react reversibly with CO2 to form Met-CO2 for the pH-dependent capture/release of CO2. The introduction of Met, a conventional anti-diabetic drug, promotes programmed death-ligand 1 (PD-L1) degradation by activating adenosine monophosphate-activated protein kinase, subsequently blocking the inhibitory signals of PD-L1. As a result, siFGL1 delivery by the camouflaged nanoparticles of the hybrid biomimetic membrane can effectively silence the FGL1 gene, promoting T-cell-mediated immune responses and enhancing antitumor immunity. We found that a combination of PD-L1/programmed death 1 signaling blockade and FGL1 gene silencing exhibited high synergistic therapeutic efficacy against breast cancer in vitro and in vivo. Additionally, Met alleviated tumor hypoxia by reducing oxygen consumption and inducing M1-type differentiation of tumor-related macrophages, which improved the tumor immunosuppressive microenvironment. Our results indicate the potential of hybrid biomimetic membrane-camouflaged nanoparticles and combined Met-FGL1 blockade in breast cancer immunotherapy.

Ammonia (NH3) volatilization from paddy fields is a major issue which leads to poor fertilizer use efficiency and is considered a severe threat to the atmosphere. The previous research studies gave importance to the use of nitrogen fertilizers to mitigate NH3 volatilization, while very little emphasis was given to the role of other fertilizers, such as phosphorus (P), for the alleviation of NH3 volatilization in rice fields. Considering P importance herein, we conducted two consecutive field experiments using an innovative, controlled-release, phosphorus-blended fertilizer (CRPBF, with levels CRP0, CRP1, and CRP2). We compared CP0 (in which no fertilizer was applied), CP1 (112.5 kg P ha−1 P of locally recommended fertilizers), and CP2: (P and K blended fertilizers) to determine the best possible way to reduce NH3 volatilization without affecting the yield and quality of rice. The results of the study suggested that the yield of rice increased significantly with the application of CRP1 (11.11 t ha−1) and CRP2 (11.99 t ha−1). The addition of CRP1 and CRP2 to the rice field also enhanced yield-related components, i.e., panicle weight, total spikelets per unit area, spikelets per panicle, and above-ground biomass. CRP0 showed a lower yield and related components when compared to CP2. The addition of CRP1 and CRP2 demonstrated lower protein contents when compared to other treatments. The CRPBF application improved starch content and taste scores, and reduced the chalkiness of the rice grain during both years. The results showed a decreasing trend in NH3 volatilization from CRPBF amendments by improving the nitrogen use efficiency traits when compared to other treatments: CRP2, CRP1, and CRP0 reduced NH3 volatilization by 45%, 35%, and 15%, respectively. The results of this study indicate that, due to the episodic nature of NH3 volatilization, CRPBFs with 50% P and 100% P can markedly reduce NH3 volatilization from paddy fields without compromising the yield and quality of the crop, and could be a promising alternative to the ordinary commercial fertilizers used in rice fields.

As an essential branch of artificial intelligence, recommendation systems have gradually penetrated people’s daily lives. It is the active recommendation of goods or services of potential interest to users based on their preferences. Many recommendation methods have been proposed in both industry and academia. However, there are some limitations of previous recommendation methods: (1) Most of them do not consider the cross-correlation between data. (2) Many treat the recommendation process as a one-time act and do not consider the continuity of the recommendation system. To overcome these limitations, we propose a recommendation framework based on deep reinforcement learning techniques, known as DDRCN: a deep deterministic policy gradient recommendation framework incorporating deep cross networks. We use a Deep network and a Cross network to fit the cross relationships between the data, to obtain a representation of the user interaction data. The Actor-Critic network is designed to simulate the continuous interaction behavior of users through a greedy strategy. A deep deterministic policy gradient network is also used to train the recommendation model. Finally, we conduct experiments with two publicly available datasets and find that our proposed recommendation framework outperforms the baseline approach in the recall and ranking phases of recommendations.

Perinatal exposure to heat and air pollution has been shown to affect the risk of preterm birth (PTB). However, limited evidence exists regarding their joint effects, particularly in heavily polluted regions like China. This study utilized data from the ongoing China Birth Cohort Study, including 103 040 birth records up to December 2020, and hourly measurements of air pollution (PM _2.5 , NO _2 , and O _3 ) and temperature. We assessed the nonlinear associations between air pollution and temperature extereme exposures and PTB by employing generalized additive models with restricted cubic slines. Air pollution and temperature thresholds (corresponding to minimum PTB risks) were determined by the lowest Akaike Information Criterion. We found that maternal exposures to PM _2.5 , NO _2 , O _3 , and both low and high temperature during the third trimester of pregnancy were independently associated with increased risk of PTB. The adjusted risk ratios for PTB of PM _2.5 , O _3 , NO _2 , and temperature at the 95th percentile against thresholds were 1.32 (95% CI: 1.23, 1.42), 1.33 (95% CI: 1.18, 1.50), 1.44 (95% CI: 1.33, 1.56) and 1.70 (95% CI: 1.56, 1.85), respectively. Positive additive interactions [relative excess risk due to interaction (RERI) > 0] of PM _2.5 –high temperature (HT), O _3 –HT, O _3 –low temperature (LT) are identified, but the interactive effects of PM _2.5 and LT were negative (RERI < 0). These observed independent effects of air pollution and temperature, along with their potential joint effects, have important implications for future studies and the development of public health policies aimed at improving perinatal health outcomes.

Over the past decade, the dose of nanoparticles given to solid tumors has remained at a median of 0.7% of the injected dose. Most nanoparticles are trapped in a mononuclear phagocyte system (MPS), of which 85% are Kupffer cells. In our study, threshold doses of bovine serum albumin (BSA) nanoparticles were investigated for the uptake of Kupffer cells in vitro and in vivo. The antitumor effect and safety of albumin-bound paclitaxel (ABP) were improved by using threshold doses of BSA nanoparticles. We found a threshold dose of 20,000 nanoparticles per macrophage uptake in vitro and a saturation dose of 0.3 trillion nanoparticles in tumor-bearing mice. In vivo efficacy and safety evaluations demonstrated that the threshold doses of blank BSA nanoparticles could significantly improve the efficacy and safety of ABP against tumors compared with ABP alone. In this study, the delivery efficiency of ABP was improved by using blank nanoparticles to saturate Kupffer cells, which provided a new approach to studying the Kupffer cell saturation threshold and thus a new scheme for improving the curative effect of ABP.

Background: Several studies have reported conflicting results on the association between maternal exposure to folic acid (FA) and/or multivitamin (MV) supplements and the risk of birth defects (BDs), especially for different subtypes of BDs. The present study aimed to identify the association between maternal exposure to FA or/and MV and BDs in offspring. Methods: In the Chinese Birth Cohort Study initiated from 20 November 2017, 120,652 pregnant women completed follow-up until 20 August 2021. The participants were classified into four groups: without exposure to FA and MV, exposure to only FA, exposure to only MV, and exposure to FA and MV. Birth defects were coded by the International Classification of Diseases (ICD)-10. In order to explore the structural relationship between maternal FA or MV supplements and BDs, directed acyclic graphs were drawn. Then, an inverse probability treatment weighting was utilized to reduce the systematic differences in the baseline characteristics among the different groups. Lastly, a two-level mixed-effect log binomial regression analysis was used to estimate the relative risk (RR) value of the different subtypes of BDs under different exposures to FA and/or MV. Results: Compared with the maternal group without exposure to FA and MV, the RR values of nervous system defects, face, ear, and neck defects, limb defects, and CHDs in the maternal group with only FA supplementation were less than 1.0, but they were not statistically significant. The RR values of genitourinary defects, abnormal chromosomes, and oral clefts were more than 1.0, and they were also not statistically significant. However, the risk of genitourinary defects (RR: 3.22, 95% CI: 1.42–7.29) and chromosomal abnormalities (RR: 2.57, 95% CI: 1.16–5.73) in the maternal group with only MV supplementation increased more than those in the maternal group without exposure to FA and MV. In addition, the RR values of all subtypes of BDs in the maternal group with exposure to FA and MV were closer to 1.0 than those in maternal group with exposure to only MV, but they were not statistically significant. Conclusions: It was indicated that the simultaneous supplementation of FA and MV in early pregnancy may have an interaction for the prevention of BDs and may have inconsistent effects for different subtypes of BDs. At the same time, excessive FA supplementation in pregnant women may increase the risk of BDs in their offspring. Although the mechanism is not clear, this evidence reminded us that more trade-offs are necessary for formulating strategies for the prevention of BDs with FA and/or MV supplementation in early pregnancy.

Immune checkpoint blockade has been proven to have great therapeutic potential and has revolutionized the treatment of tumors. However, various limitations remain, including the low response rate of exhausted T cells and mutual regulation of multiple immunosuppressive cell types that compromise the effect of single-target therapy. Nano-delivery systems can be used to regulate the tumor immune microenvironment in favor of immunotherapy. In this study, we constructed a polypeptide-based micellar system that encapsulates an aryl hydrocarbon receptor (AhR) inhibitor (CH223191) conjugated to T cell activator anti-CD28. The inhibition of AhR activation downregulates the fraction of immunosuppressive cells and effectively inhibits tumor cell metastasis. In addition, the combination with co-stimulatory antibodies improves T-cell activation and synergistically enhances the antitumor effect of AhR inhibitors. The micellar system developed in this study represents a novel and effective tumor immunotherapy approach.

An integrated hog futures price forecasting model based on whale optimization algorithm (WOA), LightGBM, and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is proposed to overcome the limitations of a single machine learning model with low prediction accuracy and insufficient model stability. The simulation process begins with a grey correlation analysis of the hog futures price index system in order to identify influencing factors; after that, the WOA-LightGBM model is developed, and the WOA algorithm is used to optimize the LightGBM model parameters; and, finally, the residual sequence is decomposed and corrected by using the CEEMDAN method to build a combined WOA-LightGBM-CEEMDAN model. Furthermore, it is used for comparison experiments to check the validity of the model by using data from CSI 300 stock index futures. Based on all experimental results, the proposed combined model shows the highest prediction accuracy, surpassing the comparative model. The model proposed in this study is accurate enough to meet the forecasting accuracy requirements and provides an effective method for forecasting future prices.

To address the difficulty of low prediction accuracy, insufficient model stability, and certain lag associated with a single machine learning model in the prediction of house price, this paper proposes a multimodel fusion house price prediction model based on stacking integrated learning. Firstly, web search data affecting house prices were collected by web crawler technology, and Spearman correlation analysis was performed on the attribute set to reduce its complexity and establish a prediction index system for four first-tier cities in China. Secondly, with the goal of improving accuracy, diversity, and generalization ability, the types of base learners as well as metalearners are determined, and the parameters of the base learners are optimized using the grey wolf optimization algorithm to produce the GWO-stacking model, and the experimental results from four datasets demonstrate that the model has high prediction accuracy. Finally, to solve the issue of unintelligible black boxes in machine learning models, we have used the state-of-the-art interpretation method SHAP combined with the LightGBM algorithm to interpret the model, and the result can be used as a basis for real estate policy planning and adjustment and even guide the demand of home buyers, thus improving the efficiency and effectiveness of government policy making.

Abstract Growing evidence has indicated that circular RNAs (circRNAs) play crucial roles in multiple biological processes. However, alterations in circRNA profiles during bladder cancer progression and the clinical significance thereof remain unclear. Therefore, high‐throughput RNA sequencing was conducted to identify circRNA and mRNA profiles in five pairs of bladder cancer tissues and adjacent noncancerous tissues. A total of 87 differentially expressed circRNAs and 2756 mRNAs were detected in above bladder cancer samples compared with paired noncancerous samples. Functional enrichment analyses, circRNA‐microRNA‐mRNA, and protein‐protein interaction networks revealed that these dysregulated circRNAs were potentially involved in carcinogenesis and evolution of bladder cancer. Subsequently, the differential expression of eight circRNAs was detected by real‐time qPCR. Hsa_circ_0003141 and hsa_circ_0008039 were significantly upregulated as well as hsa_circ_0026782, hsa_circ_0077837, hsa_circ_0004826, and hsa_circ_0001946 were significantly downregulated among validation of 70 matched bladder cancer tissues (≥75%). Moreover, hsa_circ_0077837 and hsa_circ_0004826 were also verified as markedly downregulated in four bladder cancer cells (100%). Naturally, hsa_circ_0077837 and hsa_circ_0004826 were also demonstrated using RNase‐R+ resistance experiments. In addition, Fisherʹs exact test, Kaplan‐Meier plots, Cox regression analyses, and receiver operating characteristic curve was performed to assess their clinical value. Downregulation of hsa_circ_0077837 and hsa_circ_0004826 all was significantly correlated with worse clinicopathological features and poor prognosis of bladder cancer patients. The area under the receiver operating characteristic curve of them was 0.775 (P

Abstract Cell membrane- covered drug-delivery nanoplatforms have been garnering attention because of their enhanced bio-interfacing capabilities that originate from source cells. In this top-down technique, nanoparticles (NPs) are covered by various membrane coatings, including membranes from specialized cells or hybrid membranes that combine the capacities of different types of cell membranes. Here, hybrid membrane-coated doxorubicin (Dox)-loaded poly(lactic-co-glycolic acid) (PLGA) NPs (DPLGA@[RAW-4T1] NPs) were fabricated by fusing membrane components derived from RAW264.7(RAW) and 4T1 cells (4T1). These NPs were used to treat lung metastases originating from breast cancer. This study indicates that the coupling of NPs with a hybrid membrane derived from macrophage and cancer cells has several advantages, such as the tendency to accumulate at sites of inflammation, ability to target specific metastasis, homogenous tumor targeting abilities in vitro, and markedly enhanced multi-target capability in a lung metastasis model in vivo. The DPLGA@[RAW-4T1] NPs exhibited excellent chemotherapeutic potential with approximately 88.9% anti-metastasis efficacy following treatment of breast cancer-derived lung metastases. These NPs were robust and displayed the multi-targeting abilities of hybrid membranes. This study provides a promising biomimetic nanoplatform for effective treatment of breast cancer metastasis.

Abstract Exosomes (Exo) hold great promise as endogenous nanocarriers that can deliver biological information between cells. However, Exo are limited in terms of their abilities to target specific recipient cell types. We developed a strategy to isolate Exo exhibiting increased binding to integrin αvβ3. Binding occurred through a modified version of a disintegrin and metalloproteinase 15 (A15) expressed on exosomal membranes (A15-Exo), which facilitated co-delivery of therapeutic quantities of doxorubicin (Dox) and cholesterol-modified miRNA 159 (Cho-miR159) to triple-negative breast cancer (TNBC) cells, both in vitro and in vivo. The targeted A15-Exo were derived from continuous protein kinase C activation in monocyte-derived macrophages. These cell-derived Exo displayed targeting properties and had a 2.97-fold higher production yield. In vitro, A15-Exo co-loaded with Dox and Cho-miR159 induced synergistic therapeutic effects in MDA-MB-231 cells. In vivo, miR159 and Dox delivery in a vesicular system effectively silenced the TCF-7 gene and exhibited improved anticancer effects, without adverse effects. Therefore, our data demonstrate the synergistic efficacy of co-delivering miR159 and Dox by targeted Exo for TNBC therapy.

Abstract Background Macrophages with tumor-tropic migratory properties can serve as a cellular carrier to enhance the efficacy of anti neoplastic agents. However, limited drug loading (DL) and insufficient drug release at the tumor site remain the main obstacles in developing macrophage-based delivery systems. In this study, we constructed a biomimetic delivery system (BDS) by loading doxorubicin (DOX)-loaded reduced graphene oxide (rGO) into a mouse macrophage-like cell line (RAW264.7), hoping that the newly constructed BDS could perfectly combine the tumor-tropic ability of macrophages and the photothermal property of rGO. Results At the same DOX concentration, the macrophages could absorb more DOX/PEG-BPEI-rGO than free DOX. The tumor-tropic capacity of RAW264.7 cells towards RM-1 mouse prostate cancer cells did not undergo significant change after drug loading in vitro and in vivo. PEG-BPEI-rGO encapsulated in the macrophages could effectively convert the absorbed near-infrared light into heat energy, causing rapid release of DOX. The BDS showed excellent anti-tumor efficacy in vivo. Conclusions The BDS that we developed in this study had the following characteristic features: active targeting of tumor cells, stimuli-release triggered by near-infrared laser (NIR), and effective combination of chemotherapy and photothermotherapy. Using the photothermal effect produced by PEG-BPEI-rGO and DOX released from the macrophages upon NIR irradiation, MAs-DOX/PEG-BPEI-rGO exhibited a significant inhibitory effect on tumor growth.

Atherosclerosis is a chronic, progressive disease which eventually leads to coronary heart disease (CHD), ischemic stroke and other atherosclerotic cardiovascular disease (ASCVD). Numerous studies have demonstrated an atherogenic role of oxidized low-density lipoprotein (ox-LDL) in the progression of ASCVD. This article briefly reviews the atherogenic mechanism of ox-LDL, the methods of measuring ox-LDL in the circulation, effect of medical therapy and life-style modification on ox-LDL level, and the association between circulating ox-LDL and atherosclerosis, including clinical ASCVD events and subclinical atherosclerosis, in observational studies. Keywords: Oxidized low density lipoprotein, Atherosclerosis, Cardiovascular disease, Subclinical atherosclerosis, Review

Cells of Microcystis are associated with heterotrophic bacteria and organized in colonies in natural environment, which are basic elements in the mass occurrence of cyanobacterial species. Analyzing these colonies by using metagenomics is helpful to understand species composition and relationship. Meanwhile, the difference in population abundance among Microcystis colonies could be used to recover genome bins from metagenome assemblies. Herein, we designed a pipeline to obtain high-quality genomes of mutualistic bacteria from single natural Microcystis colonies. Single colonies were lysed, and then amplified by using multiple displacement amplification to overcome the DNA quantity limit. A two-step assembly was performed after sequencing and scaffolds were grouped into putative bins based on their differential-coverage among species. We analyzed six natural colonies of three prevailing Microcystis species from Lake Taihu. Clustering results proved that colonies of the same species were similar in the microbial community composition. Eight putative population genome bins with wide bacterial diversity and different GC content were identified based on coverage difference among colonies. At the phylum level, proteobacteria was the most abundant besides cyanobacteria. Six of the population bins were further refined into nearly complete genomes (completeness > 90%).