红树林沉积物聚乙烯降解菌的筛选和降解特性

【目的】探究湛江市麻章区红树林沉积物中微生物对聚乙烯(PE)塑料的降解特性,丰富红树林塑料降解菌种类。【方法】在湛江市麻章区红树林的高、中、低潮带随机选取9个样点,并采用五点采样法从红树林表层2~5 cm的沉积物中取样。将采集到的沉积物样本在以聚乙烯为唯一碳源的无机盐培养基中进行富集、分离、纯化,以筛选出能够降解PE的菌株,并通过显微形态分析、分子鉴定等方法确定其种属;通过测定生长曲线、失重率、以及分析官能团变化来验证菌株对PE塑料的降解性能。【结果与结论】从沉积物中共筛选出K1-1、K1-2和K1-3三株PE降解能力较强的菌,分别为威尼斯不动杆菌(Acinetobacter venetianus)、Pseudomonas juntendi和维德曼芽孢杆菌(Bacillus wiedmannii)。在120 d的培养周期中,这些菌株的生长曲线均呈抛物线形态。经三株菌作用后,PE表面生成羟基,并形成氨基和羟基化合物,羟基取代羰基,导致PE表观和内部结构明显改变。经120 d处理后,PE膜的失重率分别为6.42%、5.38%和5.73%,其中K1-1菌株处理后PE塑料的失重率相较于目前报道的红树林沉积物中最高降解效率菌株Bacillus gottheilii处理后塑料的失重率提升3.55%。威尼斯不动杆菌(A.venetianus)在PE塑料降解上具有一定潜力,这丰富了湛江红树林沉积物中PE降解菌的种类,为PE塑料的生物降解提供理论支持。

A comparison study on structure-function relationship of polysaccharides obtained from sea buckthorn berries using different methods:antioxidant and bile acid-binding capacity

In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.

On calculating glacial isostatic adjustment

Modeling the earth's fluid and elastic response to the melting of the glaciers of the last ice age is the most direct way to infer the earth's radial viscosity profile.Here,we compare two methods for calculating the viscoelastic response to surface loading.In one,the elastic equation of motion is converted to a viscoelastic equation using the Correspondence Principle.In the other,elastic deformation is added to the viscous flow as isostatic adjustment proceeds.The two modeling methods predict adjustment histories that are different enough to potentially impact the interpretation of the observed glacial isostatic adjustment(GIA).The differences arise from buoyancy and whether fluid displacements are subjected to hydrostatic pre-stress.The methods agree if they use the same equations and boundary conditions.The origin of the differences is determined by varying the boundary conditions and pre-stress application.

A novel histone methyltransferase gene Cg SDG40 positively regulates carotenoid biosynthesis during citrus fruit ripening

The flesh color of pummelo(Citrus maxima)fruits is highly diverse and largely depends on the level of carotenoids,which are beneficial to human health.It is vital to investigate the regulatory network of carotenoid biosynthesis to improve the carotenoid content in pummelo.However,the molecular mechanism underlying carotenoid accumulation in pummelo is not fully understood.In this study,we identified a novel histone methyltransferase gene,CgSDG40,involved in carotenoid regulation by analyzing the flesh transcriptome of typical white-fleshed pummelo,red-fleshed pummelo and extreme-colored F1 hybrids from a segregated pummelo population.Expression of CgSDG40 corresponded to flesh color change and was highly coexpressed with CgPSY1.Interestingly,CgSDG40 and CgPSY1 are located physically adjacent to each other on the chromosome in opposite directions,sharing a partially overlapping promoter region.Subcellular localization analysis indicated that CgSDG40 localizes to the nucleus.Overexpression of CgSDG40 significantly increased the total carotenoid content in citrus calli relative to that in wild type.In addition,expression of CgPSY1 was significantly activated in overexpression lines relative to wild type.Taken together,our findings reveal a novel histone methyltransferase regulator,CgSDG40,involved in the regulation of carotenoid biosynthesis in citrus and provide new strategies for molecular design breeding and genetic improvement of fruit color and nutritional quality.

Liver-directed therapiesfor fibrolamellar carcinoma:Asingle-center experience

Background:This article aims to present the single-institution outcomes of patients with Fibrolamellar Carcinoma(FLC)treated with liver-directed therapies(LDT).Methods:In this single-center retrospective study,all patients diagnosed with FLC who underwent LDT were identified.Between July 2012 and July 2023,six patients were identified.One patient was excluded due to bleeding.Demographic and clinical parameters were recorded.Complications within 30 days of the LDT were evaluated.Radiological treatment responses at 1,6,and 12 months were assessed per mRECIST.Results:A total offive patients,which included three females and two males,were reviewed.Three patients were treated with transarterial hepatic embolization(TAE;n=3),transarterial radioembolization(TARE;n=1),and combined TAE+radiofrequency ablation(n=1).The objective response rate at one month was 80%[CR=2(40%),PR=2(40%),and SD=1(20%)].At 12 months(n=4),two patients demonstrated CR(50%)and two demonstrated PR(50%).Overall survival from LDT atfive years was 50%.There was no 30-day mortality among this group of patients or any adverse event attributable to the LDT.Conclusion:TAE,TARE,and ablation are safe and effective therapeutic options for FLC.Based on this study and previously published case reports,ablation and TARE yielded the most favorable results.

Adaptive State-Dependent Diffusion for Derivative-Free Optimization

This paper develops and analyzes a stochastic derivative-free optimization strategy.A key feature is the state-dependent adaptive variance.We prove global convergence in probability with algebraic rate and give the quantitative results in numerical examples.A striking fact is that convergence is achieved without explicit information of the gradient and even without comparing different objective function values as in established methods such as the simplex method and simulated annealing.It can otherwise be compared to annealing with state-dependent temperature.

Bridging Time-series Image Phenotyping and Functional-Structural Plant Modeling to Predict Adventitious Root System Architecture

Root system architecture(RSA)is an important measure of how plants navigate and interact with the soil environment.However,current methods in studying RSA must make tradeoffs between precision of data and proximity to natural conditions,with root growth in germination papers providing accessibility and high data resolution.Functional-structural plant models(FSPMs)can overcome this tradeoff,though parameterization and evaluation of FSPMs are traditionally based in manual measurements and visual comparison.Here,we applied a germination paper system to study the adventitious RSA and root phenology of Populus trichocarpa stem cuttings using time-series image-based phenotyping augmented by FSPM.We found a significant correlation between timing of root initiation and thermal time at cutting collection(P value=0.0061,R2=0.875),but little correlation with RSA.We also present a use of RhizoVision[1]for automatically extracting FSPM parameters from time series images and evaluating FSPM simulations.A high accuracy of the parameterization was achieved in predicting 2D growth with a sensitivity rate of 83.5%.This accuracy was lost when predicting 3D growth with sensitivity rates of 38.5%to 48.7%,while overall accuracy varied with phenotyping methods.Despite this loss in accuracy,the new method is amenable to high throughput FSPM parameterization and bridges the gap between advances in time-series phenotyping and FSPMs.

Preventing the Immense Increase in the Life-Cycle Energy and Carbon Footprints of LLM-Powered Intelligent Chatbots

Intelligent chatbots powered by large language models(LLMs)have recently been sweeping the world,with potential for a wide variety of industrial applications.Global frontier technology companies are feverishly participating in LLM-powered chatbot design and development,providing several alternatives beyond the famous ChatGPT.However,training,fine-tuning,and updating such intelligent chatbots consume substantial amounts of electricity,resulting in significant carbon emissions.The research and development of all intelligent LLMs and software,hardware manufacturing(e.g.,graphics processing units and supercomputers),related data/operations management,and material recycling supporting chatbot services are associated with carbon emissions to varying extents.Attention should therefore be paid to the entire life-cycle energy and carbon footprints of LLM-powered intelligent chatbots in both the present and future in order to mitigate their climate change impact.In this work,we clarify and highlight the energy consumption and carbon emission implications of eight main phases throughout the life cycle of the development of such intelligent chatbots.Based on a life-cycle and interaction analysis of these phases,we propose a system-level solution with three strategic pathways to optimize the management of this industry and mitigate the related footprints.While anticipating the enormous potential of this advanced technology and its products,we make an appeal for a rethinking of the mitigation pathways and strategies of the life-cycle energy usage and carbon emissions of the LLM-powered intelligent chatbot industry and a reshaping of their energy and environmental implications at this early stage of development.

Socio-Economic and Health Indicators’ Relation to Self-Assessed Health: A Case Study of Phai Tha Pho, Phichit Province, Thailand

Background: Self-assessed health (SAH) is used as a common method of sociology research to understand the implications of self-reported health and the link to social factors like education, income, and occupation. The paper explores the impact of socio-economic and health indicators on self-assessed health in the middle-aged to the senior population in a rural community in Thailand. Methods: Primary data were collected after conducting a randomized sampling for 100 people using direct interviews in two locations within the sub-district of Phai Tha Pho, Thailand. The target demographic was the middle-age to elderly population. A logit model was applied to the collected samples. Results: The study highlights that higher education, income, and sleep are high predictors for positive SAH while high blood sugar level has significant adverse effects on SAH. Detection of metabolic syndrome further indicates degraded overall health perception over time. Conclusion: The study demonstrated the relationship between socio-economic indicators and illnesses alongside individual SAH in rural Thailand. Accordingly, policies have been proposed that include targeted subsidies for healthy food alternatives, promoting work-rest balance at all levels, and an expansion of sub-district education up to secondary school. SAH can be performed regularly and expanded across communities including areas of low-income living due to its low implementation costs. It could also be used as a tool to support the government’s public health initiatives complementing the existing five-year direct health check-up programme. A comparative study of SAH across regions is recommended for future research.

Effects of improved amino acid balance diet on lysine mammary utilization, whole body protein turnover and muscle protein breakdown on lactating sows

Background The study objective was to test the hypothesis that low crude protein(CP)diet with crystalline amino acids(CAA)supplementation improves Lys utilization efficiency for milk production and reduces protein turnover and muscle protein breakdown.Eighteen lactating multiparous Yorkshire sows were allotted to 1 of 2 isocaloric diets(10.80 MJ/kg net energy):control(CON;19.24%CP)and reduced CP with“optimal”AA profile(OPT;14.00%CP).Sow body weight and backfat were recorded on d 1 and 21 of lactation and piglets were weighed on d 1,14,18,and 21 of lactation.Between d 14 and 18,a subset of 9 sows(CON=4,OPT=5)was infused with a mixed solution of 3-[methyl-2H3]histidine(bolus injection)and[13C]bicarbonate(priming dose)first,then a constant 2-h[13C]bicarbonate infusion followed by a 6-h primed constant[1-13C]lysine infusion.Serial blood and milk sampling were performed to determine plasma and milk Lys enrichment,Lys oxidation rate,whole body protein turnover,and muscle protein breakdown.Results Over the 21-d lactation period,compared to CON,sows fed OPT had greater litter growth rate(P<0.05).Compared to CON,sows fed OPT had greater efficiency of Lys(P<0.05),Lys mammary flux(P<0.01)and whole-body protein turnover efficiency(P<0.05).Compared to CON,sows fed OPT tended to have lower whole body protein breakdown rate(P=0.069).Muscle protein breakdown rate did not differ between OPT and CON(P=0.197).Conclusion Feeding an improved AA balance diet increased efficiency of Lys and reduced whole-body protein turnover and protein breakdown.These results imply that the lower maternal N retention observed in lactating sows fed improved AA balance diets in previous studies may be a result of greater partitioning of AA towards milk rather than greater body protein breakdown.

Digital Twins for Wastewater Treatment:A Technical Review

The digital twins concept enhances modeling and simulation through the integration of real-time data and feedback.This review elucidates the foundational elements of digital twins,covering their concept,entities,domains,and key technologies.More specifically,we investigate the transformative potential of digital twins for the wastewater treatment engineering sector.Our discussion highlights the application of digital twins to wastewater treatment plants(WWTPs)and sewage networks,hardware(i.e.,facilities and pipes,sensors for water quality and activated sludge,hydrodynamics,and power consumption),and software(i.e.,knowledge-based and data-driven models,mechanistic models,hybrid twins,control methods,and the Internet of Things).Furthermore,two cases are provided,followed by an assessment of current challenges in and perspectives on the application of digital twins in WWTPs.This review serves as an essential primer for wastewater engineers navigating the digital paradigm shift.

Dietary Lipid Intervention in the Prevention of Brain Aging

As people live longer,the burden of aging-related brain diseases,especially dementia,is increasing.Brain aging increases the risk of cognitive impairment,which manifests as a progressive loss of neuron function caused by the impairment of synaptic plasticity via disrupting lipid homeostasis.Therefore,supplemental dietary lipids have the potential to prevent brain aging.This review summarizes the important roles of dietary lipids in brain function from both structure and mechanism perspectives.Epidemiological and animal studies have provided evidence of the functions of polyunsaturated fatty acids(PUFAs)in brain health.The results of interventions indicate that phospholipids—including phosphatidylcholine,phosphatidylserine,and plasmalogen—are efficient in alleviating cognitive impairment during aging,with plasmalogen exhibiting higher efficacy than phosphatidylserine.Plasmalogen is a recognized nutrient used in clinical trials due to its special vinyl ether bonds and abundance in the postsynaptic membrane of neurons.Future research should determine the dose-dependent effects of plasmalogen in alleviating brain-aging diseases and should develop extraction and storage procedures for its clinical application.

Applying AI Models for Stock Investment Decisions

In the realm of finance and economics, the search for reliable stock predictions remains a focal point for researchers [1]. Contrary to common belief, stock market prices are not merely random guesses, but rather powerful tools that allow people to decide where to put their money, proving to be a significant aspect of finance. In this paper, by applying machine learning techniques, we propose to predict stock prices based on trends from previous years’ stock data using learning models, such as Linear Regression, MLP Regressor, Decision Tree Regressor and Random Forest Regressor. To enhance the model’s decision-making capabilities, the model was programmed to decide whether to sell or buy stocks using the predictions from the linear model. If the model anticipates an increase in stock prices, it suggests buying more stocks. On the contrary, if the model predicts a downturn, it suggests selling stocks in order to benefit the investor and enhance profitability. If the investor began with no stocks and $20,000, through the use of our model, the investor was able to make 161.3% profit. In another scenario where the investor holds 200 stocks and $10,000, the investor was able to make a 546.3% profit. Ultimately, the model results in profitable outcomes.

Automated knowledge graphs for complex systems (AutoGraCS): Applications to management of bridge networks

With the ability to harness the power of big data,the digital twin(DT)technology has been increasingly applied to the modeling and management of structures and infrastructure systems,such as buildings,bridges,and power distribution systems.Supporting these applications,an important family of methods are based on graphs.For DT applications in modeling and managing smart cities,large-scale knowledge graphs(KGs)are necessary to represent the complex interdependencies and model the urban infrastructure as a system of systems.To this end,this paper develops a conceptual framework:Automated knowledge Graphs for Complex Systems(AutoGraCS).In contrast to existing KGs developed for DTs,AutoGraCS can support KGs to account for interdependencies and statistical correlations across complex systems.The established KGs from AutoGraCS can then be easily turned into Bayesian networks for probabilistic modeling,Bayesian analysis,and adaptive decision supports.Besides,AutoGraCS provides flexibility in support of users’need to implement the ontology and rules when constructing the KG.With the user-defined ontology and rules,AutoGraCS can automatically generate a KG to represent a complex system consisting of multiple systems.The bridge network in Miami-Dade County,FL is used as an illustrative example to generate a KG that integrates multiple layers of data from the bridge network,traffic monitoring facilities,and flood water watch stations.

海南地区电离层闪烁监测及初步统计分析

为开展赤道区的电离层闪烁形态特性及相关物理过程的研究，空间中心海南台站建立了一套 GPS电离层闪烁监测系统．该系统是利用 Plessey GPS Builder-2 系统开发的，对软件的源码进行了修改，使其能以高采样率(50/s)同时并行记录11个通道 GPS 信号强度数据．对2003年7—12月间 L-波段电离层闪烁事件的初步统计分析结果表明，电离层闪烁主要发生在日落后到午夜附近，其中9—11月较7—8月闪烁发生和结束的时间明显提前；电离层闪烁发生的频率和强度在9—11月较其他月份明显增强，其中10月达到最大；电离层闪烁的逐日变化具有很强的随机性，闪烁的发生在秋分附近9月底到10月中旬的磁静日期间达到最大；太阳和地磁活动的增强通常会抑制电离层闪烁的发生，这种情形在秋分附近尤为明显．

水杉孑遗居群AFLP遗传变异的空间分布

本研究采用空间自相关分析方法对水杉 (Metasequoiaglyptostroboides)孑遗居群AFLP遗传变异的空间结构进行了研究 ,以探讨水杉孑遗居群遗传变异的分布特征及其形成机制。根据 6对AFLP选择性引物扩增的 46个多态性位点 ,选择了其表型频率在 2 5 %～ 75 %的 2 7个AFLP标记 ,运用等样本频率方法和等地理距离间隔方法分别对 3 9株和 3 7株原生母树进行了空间自相关系数Moran’sI值计算。结果表明 :水杉孑遗居群缺乏空间结构 ,绝大多数AFLP位点变异为随机分布的空间模式 ,但也有少数位点存在显著性随机相关 ,在 4～ 8km地理距离间隔显示负相关 ,说明该间隔可能是水杉孑遗居群的部分基因交流的有效屏障。水杉原生母树分布存在 12～ 2 8km的明显距离间隔空挡 ,说明人类从迁入该区域起就影响着水杉孑遗居群的原始生境 ,导致其生境片断化、景观破碎 ,进而形成岛屿状分布格局 ,并引起了水杉残留居群的随机遗传漂变。根据本研究结果 ,结合水杉孑遗居群较低的遗传多样性 ,分析探讨了水杉孑遗居群濒危的机理 ,并提出了相应的保育策略 。

丹参酮ⅡA介导p38MAPK信号转导诱导人肝癌细胞凋亡

目的:研究丹参酮ⅡA诱导人肝癌细胞凋亡和凋亡相关基因表达的p38MAPK信号转导通路,揭示其抗肝癌的部分机制.方法:4、8、16mg/L丹参酮ⅡA分别作用人肝癌SMMC-7721细胞48h后,免疫荧光染色观察细胞凋亡情况;琼脂糖凝胶电泳观察凋亡细胞特征性DNA条带;流式细胞仪法(Flow cytometry,FCM)检测细胞凋亡和细胞周期;荧光定量PCR检测Fas和Caspase-3基因mRNA的表达水平;并比较阻断p38MAPK信号通路后丹参酮ⅡA对肝癌细胞凋亡和Fas和Caspase-3基因mRNA的表达.结果:丹参酮ⅡA作用48h后,荧光显微镜下观察到经Hoechst染色的典型凋亡细胞.琼脂糖凝胶电泳可见凋亡细胞DNA呈规律性的梯状条带.4、8、16mg/L浓度丹参酮ⅡA作用人肝癌细胞后的细胞凋亡率分别为12.83%±1.51%,17.86%±2.70%和29.24%±7.58%,与对照组6.30%±2.08%比较均有显著性差异(P<0.01);阻断p38MAPK信号通路后,凋亡率和G0/G1期细胞比例明显降低(P<0.01).8mg/L丹参酮ⅡA作用人肝癌细胞48h后FasmRNA和Caspase-3mRNA的表达明显上升;阻断p38MAPK信号通路后,丹参酮ⅡA作用人肝癌细胞的FasmRNA和Caspase-3mRNA的表达明显下降.结论:丹参酮ⅡA能诱导人肝癌细胞株SMMC-7721凋亡,阻滞肝癌细胞于G0/G1期.通过p38MAPK信号转导通路上调Fas、Caspase-3mRNA的表达可能是其诱导肝癌细胞凋亡的重要机制.

西藏高原上地幔的精细结构与构造——地震层析成像给出的启示

利用布置在亚东—格尔木的 1 6 4个流动地震台站记录的 92 6个远震事件的 2 4 2 4 1条射线 ,进行远震P波层析成像处理 ,高分辨率的西藏高原上地幔的速度结构图 ,显示了印度巨厚地幔岩石圈在向高原之下推进的过程中 ,在高喜马拉雅之下拆分成上、下两层 ,这是发生的第一次拆沉 .下层从高喜马拉雅以下约以 2 2°的角度向高原北部插入到 35 0km深 ;而其上层则向北伸展直到雁石坪 ,并构成了高原薄的地幔岩石圈 .在雁石坪北 (33.7°N) ,当其与亚洲大陆岩石圈地幔相遇后发生断离并下沉 .再次证实了五道梁 (35 .2 7°N)深部低速体的存在 ,本区内地壳内低速物质可能与上述运动有联系 。

海底天然气渗漏系统水合物成藏过程及控制因素

在海底天然气渗漏系统沉淀水合物的动力学基础上,建立了水合物沉淀与分解的化学动力学模型。应用该模型分析了美国墨西哥湾布什山天然气渗漏系统水合物的成藏过程,探讨了水合物沉淀、稳定性影响因素。在渗漏通量为每年400kg·m-2的单个通道中,约需425a才能导致水合物稳定带沉积层约30%孔隙完全被水合物充填,渗漏通道被堵塞,沉淀的水合物在剖面上从稳定带底部向海底趋于富C3+C4。在渗漏通道天然气流量由弱到强再到弱的演化过程中,渗漏速度增大过程中形成的水合物在渗漏速度减小过程中将分解,总量约10%的水合物将被分解。如果分解产生的天然气可快速迁移出渗漏系统,海底温度的升高可引起约40%的水合物在20d内分解,并导致海底渗漏速度的急剧增大。