Neoantigen cancer vaccines:a new star on the horizon

Immunotherapy represents a promising strategy for cancer treatment that utilizes immune cells or drugs to activate the patient's own immune system and eliminate cancer cells.One of the most exciting advances within this field is the targeting of neoantigens,which are peptides derived from non-synonymous somatic mutations that are found exclusively within cancer cells and absent in normal cells.Although neoantigen-based therapeutic vaccines have not received approval for standard cancer treatment,early clinical trials have yielded encouraging outcomes as standalone monotherapy or when combined with checkpoint inhibitors.Progress made in high-throughput sequencing and bioinformatics have greatly facilitated the precise and efficient identification of neoantigens.Consequently,personalized neoantigen-based vaccines tailored to each patient have been developed that are capable of eliciting a robust and long-lasting immune response which effectively eliminates tumors and prevents recurrences.This review provides a concise overview consolidating the latest clinical advances in neoantigen-based therapeutic vaccines,and also discusses challenges and future perspectives for this innovative approach,particularly emphasizing the potential of neoantigen-based therapeutic vaccines to enhance clinical efficacy against advanced solid tumors.

Density functional theory study of B- and Si-doped carbons and their adsorption interactions with sulfur compounds

Understanding the adsorption interactions between carbon materials and sulfur compounds has far-reaching impacts,in addition to their well-known important role in energy storage and conversion,such as lithium-ion batteries.In this paper,properties of intrinsic B or Si single-atom doped,and B-Si codoped graphene(GR)and graphdiyne(GDY)were investigated by using density functional theory-based calculations,in which the optimal doping configurations were explored for potential applications in adsorbing sulfur compounds.Results showed that both B or Si single-atom doping and B-Si codoping could substantially enhance the electron transport properties of GR and GDY,improving their surface activity.Notably,B and Si atoms displayed synergistic effects for the codoped configurations,where B-Si codoped GR/GDY exhibited much better performance in the adsorption of sulfurcontaining chemicals than single-atom doped systems.In addition,results demonstrated that,after B-Si codoping,the adsorption energy and charge transfer amounts of GDY with sulfur compounds were much larger than those of GR,indicating that B-Si codoped GDY might be a favorable material for more effectively interacting with sulfur reagents.

Design and test of a dual-axis layered rotary tillage stubble exterminator in saline-alkali land based on discrete elements

Considering the problems of poor straw mulching performance,low soil crushing rate and poor straw mulching performance of the traditional rotary tiller on saline-alkali soils,a two-axis layered rotary stubble cutter for saline-alkali soils with front-axis positive rotation of the front axle and rear-axis counter-rotation of the rear axle was developed,focusing on the kinetic properties of the straw and soil under positive and counter-rotation.In addition,the most important structural parameters and the arrangement of the front-axis stubble cutting knife and the rear-axis return knife were analyzed and determined.Hertz-Mindlin with bonding was used to create a discrete element model of the agglomerate of implement,straw and soil.The forward speed,horizontal distance and vertical distance were used as test factors,and the straw return rate and soil fragmentation rate were used as test indexes to analyze the straw-soil transport law under different operating parameters from a microscopic point of view,and then Design-Expert was used to conduct the test 1.07 km/h,horizontal distance of 569.55 mm,vertical distance of 176.59 mm.To validate the performance of the two-axis,layered rotary tiller,a field trial was conducted and the results show that the straw return ratio was(91.59±0.41)%,soil fragmentation ratio was(91.90±0.29)%and tillage depth stability was(91.52±0.46)%,which met the requirements for peanut seedbed preparation on saline-alkali land.

Ectopic recurrence following treatment of arteriovenous malformations in an adult:A case report and review of literature

BACKGROUND Digital subtraction angiography(DSA),the gold standard for the diagnosis of intracranial arteriovenous malformations(AVMs),can show clean nidus resection,leading to a perceived cure.Most cases of intracranial AVM recurrence have been reported in pediatric patients.The conventional understanding indicates that AVMs arise when abnormal blood vessels develop between the fourth and eighth weeks of embryonic development,which coincides with the typical period of blood vessel formation in the brain.As such,recurrent ectopic AVM are rare in adults.CASE SUMMARY Herein,we present the case of a 31-year-old adult with a history of an intracranial AVM originally diagnosed with a symptomatic de novo cerebellar AVM formation.Recurrence was observed five years following angiographically-confirmed excision of the initial AVM.DSA performed prior to initial AVM resection indicated no cerebellar abnormalities.Moreover,the recurrent arteries exhibited differences in arteries and draining veins.In addition to reporting this case,we analyzed six previously-reported adult patients with similar ectopic recurrent AVMs.These cases are summarized to review and explore the potential causes of ectopic AVM recurrence in adults,which increase the likelihood of acquired AVM.CONCLUSION The clinical course of the reported patients demonstrated the possibility of ectopic AVM recurrence in adults.The median time between the diagnosis of the initial AVM and the occurrence of ectopic recurrent AVM in adults was 11 years(range:5–20 years).Magnetic resonance imaging follow-up for more than 10 years may be required in adult AVM-treated patients.

Multimodal imaging for the diagnosis of oligodendroglioma associated with arteriovenous malformation:A case report

BACKGROUND The rare co-occurrence of oligodendroglioma and arteriovenous malformation(AVM)in the same intracranial location.CASE SUMMARY In a 61-year-old man presenting with progressive headaches,is described in this case study.Preoperative multimodal imaging techniques(computed tomography,magnetic resonance imaging,magnetic resonance spectroscopy,digital subtraction angiography,and computed tomography angiography)were employed to detect hemorrhage,cystic and solid lesions,and arteriovenous shunting in the right temporal lobe.The patient underwent right temporal craniotomy for lesion removal,and postoperative pathological analysis confirmed the presence of oligodendroglioma(World Health Organization grade II,not otherwise specified)and AVM.CONCLUSION The preoperative utilization of multimodal imaging examination can help clinicians reduce the likelihood of misdiagnosis or oversight of these conditions,and provides important information for subsequent treatment.This case supports the feasibility of craniotomy for the removal of glioma with AVM.

Alzheimer's disease with sleep insufficiency:a cross-sectional study on correlations among clinical characteristics,orexin,its receptors,and the bloodbrain barrier

Previous studies have shown that reduced sleep duration,sleep fragmentation,and decreased sleep quality in patients with Alzheimer's disease are related to dysfunction in orexin signaling.At the same time,blood-brain barrier disruption is considered an early biomarker of Alzheimer's disease.However,currently no report has examined how changes in orexin signaling relate to changes in the blood-brain barrier of patients who have Alzheimer's disease with sleep insufficiency.This cross-sectional study included 50 patients with Alzheimer's disease who received treatment in 2019 at Beijing Tiantan Hospital.Patients were divided into two groups:those with insufficient sleep(sleep duration≤6 hours,n=19,age 61.58±8.54 years,10 men)and those with normal sleep durations(sleep duration>6 hours,n=31,age 63.19±10.09 years,18 men).Demographic variables were collected to evaluate cognitive function,neuropsychiatric symptoms,and activities of daily living.The levels of orexin,its receptor proteins,and several blood-brain barrier factors were measured in cerebrospinal fluid.Sleep insufficiency was associated with impaired overall cognitive function that spanned multiple cognitive domains.Furthermore,levels of orexin and its receptors were upregulated in the cerebrospinal fluid,and the blood–brain barrier was destroyed.Both these events precipitated each other and accelerated the progression of Alzheimer's disease.These findings describe the clinical characteristics and potential mechanism underlying Alzheimer's disease accompanied by sleep deprivation.Inhibiting the upregulation of elements within the orexin system or preventing the breakdown of the blood-brain barrier could thus be targets for treating Alzheimer's disease.

Flash-based in-memory computing for stochastic computing in image edge detection

The“memory wall”of traditional von Neumann computing systems severely restricts the efficiency of data-intensive task execution,while in-memory computing(IMC)architecture is a promising approach to breaking the bottleneck.Although variations and instability in ultra-scaled memory cells seriously degrade the calculation accuracy in IMC architectures,stochastic computing(SC)can compensate for these shortcomings due to its low sensitivity to cell disturbances.Furthermore,massive parallel computing can be processed to improve the speed and efficiency of the system.In this paper,by designing logic functions in NOR flash arrays,SC in IMC for the image edge detection is realized,demonstrating ultra-low computational complexity and power consumption(25.5 fJ/pixel at 2-bit sequence length).More impressively,the noise immunity is 6 times higher than that of the traditional binary method,showing good tolerances to cell variation and reliability degradation when implementing massive parallel computation in the array.

Experiencing urban forests for mitigation of negative emotions of people exposed to seasonal PM_(2.5)in Northeast China

Experiencing urban green and blue spaces(GBSs)can be a nature-based solution to improve mental well-being and cope with negative moods for people exposed to PM2.5 pollution.In this study,a total of 1257 photos were collected to recognize their posted emotions of Sina Weibo users from 38 parks in 22 cities in Northeast China in 2021,when atmospheric PM_(2.5)and landscape metrics were evaluated for GBSs of each park.Autumn and winter had heavy atmospheric PM_(2.5)pollutions in resource-dependent cities of Liaoning.Net positive emotions(happy minus sad scores)decreased in larger green spaces.The perception of blue space countered the presentation of sadness only for a limited period over four seasons.High elevation decreased the level of happiness presented in winter.Overall,this study confirms that visiting large urban green spaces at low elevations can benefit the perception of positive sentiments for people exposed to PM_(2.5)in autumn.For planning urban forests in Northeast China,more green spaces should be constructed in cities in southern Jilin province to alleviate air PM_(2.5)pollution and gain better well-being of local people.

Application of Time Serial Model in Water Quality Predicting

Water resources are an indispensable and valuable resource for human survival and development.Water quality predicting plays an important role in the protection and development of water resources.It is difficult to predictwater quality due to its random and trend changes.Therefore,amethod of predicting water quality which combines Auto Regressive Integrated Moving Average(ARIMA)and clusteringmodelwas proposed in this paper.By taking thewater qualitymonitoring data of a certain river basin as a sample,thewater quality Total Phosphorus(TP)index was selected as the prediction object.Firstly,the sample data was cleaned,stationary analyzed,and white noise analyzed.Secondly,the appropriate parameters were selected according to the Bayesian Information Criterion(BIC)principle,and the trend component characteristics were obtained by using ARIMA to conduct water quality predicting.Thirdly,the relationship between the precipitation and the TP index in themonitoring water field was analyzed by the K-means clusteringmethod,and the random incremental characteristics of precipitation on water quality changes were calculated.Finally,by combining with the trend component characteristics and the random incremental characteristics,the water quality prediction results were calculated.Compared with the ARIMA water quality prediction method,experiments showed that the proposed method has higher accuracy,and its Mean Absolute Error(MAE),Mean Square Error(MSE),and Mean Absolute Percentage Error(MAPE)were respectively reduced by 44.6%,56.8%,and 45.8%.

A Big Data Based Dynamic Weight Approach for RFM Segmentation

Using the RFM(Recency,Frequency,Monetary value)model can provide valuable insights about customer clusterswhich is the core of customer relationship management.Due to accurate customer segment coming from dynamic weighted applications,in-depth targeted marketing may also use type of dynamic weight of R,F and M as factors.In this paper,we present our dynamic weighted RFM approach which is intended to improve the performance of customer segmentation by using the factors and variations to attain dynamic weights.Our dynamic weight approach is a kind of Custom method in essential which roots in the understanding of the data set.Firstly,Analytic Hierarchy Process is used to calculate the subjective weight,then the entropy method is applied to calculate the objective weight.Finally,we use comprehensive integration weighting method to combine the subjective and objective weight to obtain the final weight of the index to calculate the individual user value and quantify the user value difference.The experiment shows that the dynamic weight we used in RFM model is vital,affects the customer segmentation performance positively.Also,this study indicates that customer segments containing dynamic weighted RFM scores bring about stronger and more accurate association rules for the understanding of customer behavior.At last,we discuss the limitations of RFM analysis.

Enhanced E-commerce Fraud Prediction Based on a Convolutional Neural Network Model

The rapidly escalating sophistication of e-commerce fraud in recent years has led to an increasing reliance on fraud detection methods based on machine learning.However,fraud detection methods based on conventional machine learning approaches suffer from several problems,including an excessively high number of network parameters,which decreases the efficiency and increases the difficulty of training the network,while simultaneously leading to network overfitting.In addition,the sparsity of positive fraud incidents relative to the overwhelming proportion of negative incidents leads to detection failures in trained networks.The present work addresses these issues by proposing a convolutional neural network(CNN)framework for detecting ecommerce fraud,where network training is conducted using historical market transaction data.The number of network parameters reduces via the local perception field and weight sharing inherent in the CNN framework.In addition,this deep learning framework enables the use of an algorithmiclevel approach to address dataset imbalance by focusing the CNN model on minority data classes.The proposed CNN model is trained and tested using a large public e-commerce service dataset from 2018,and the test results demonstrate that the model provides higher fraud prediction accuracy than existing state-of-the-art methods.

Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data

At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the prediction of total phosphorus in water quality has good research significance.This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform.By constructing the attribute object mapping relationship,the correlation between the two indicators was analyzed and used to predict the future data.Firstly,the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers were calculated after cleaning,and the correlation between them was analyzed.Secondly,the correlation coefficients of different times and frequencies were used to predict the values for the next five days,and the data trend was predicted by python visualization.Finally,the real value was compared with the predicted value data,and the results showed that the correlation between total phosphorus and turbidity was useful in predicting the water quality.

不同结构导向剂合成不同硅含量SAPO-34分子筛的酸性质

SAPO-34分子筛由于其独特的拓扑结构和适宜的酸性,在以甲醇制烯烃(MTO)和氨气选择性催化还原NO_(x)(NH_(3)-SCR)为代表的系列催化反应中显示了优良的性能,因此吸引了研究者的广泛关注。但是,在合成过程中如何通过选择有机模板和控制硅含量来得到合适酸量的SAPO-34催化剂是极具挑战的。本文中,四个系列的SAPO-34分子筛,即分别由四乙基氢氧化铵(TEAOH)、二异丙胺(DIPA)、正丁胺(nBA)和吗啉(MOR)为有机模板剂合成不同硅含量的样品,通过热重量分析(TG),结构精修和固态核磁进行了研究。TG和结构精修结果显示在TEAOH和DIPA合成的SAPO-34分子筛cha(一种复合结构单元)笼子中只有一个结构导向剂而MOR和nBA合成的SAPO-34分子筛的cha笼中有两个。采用固态核磁氢谱(^(1)H ss-NMR)探究碱性探针分子氘代乙腈(CD_(3)CN)和分子筛骨架之间主客体的相互作用,并对其酸性(酸量和酸强度)进行了系统的研究。例如,TEAOH合成的SAPO-34分子筛随着硅含量的增加酸强度增加而酸量却保持着不变。而DIPA合成的SAPO-34,与前者存在较大的差异,即随着硅含量的上升,酸量显著下降而酸强度只发生了微小的变化。该工作为SAPO-34分子筛催化剂酸性的定向调变提供了理论基础。

A Spectral Method for Convection-Diffusion Equations

In the practical problems such as nuclear waste pollution and seawater intrusion etc., many problems are reduced to solving the convection-diffusion equation, so the research of convection-diffusion equation is of great value. In this work, a spectral method is presented for solving one and two dimensional convection-diffusion equation with source term. The finite difference method is also used to solve the convection diffusion equation. The numerical experiments show that the spectral method is more efficient than other methods for solving the convection-diffusion equation.

LEO-LEO掩星大气反演技术及误差分析

本文介绍了LEO-LEO掩星大气反演算法的物理机制,基本流程及计算原理,同时模拟仿真分析了多种误差源(例如钟误差、多路径效应以及LEO卫星轨道误差等)对反演结果的影响。通过统计反演温度及湿度发现:现有的卫星钟的稳定度及LEO卫星定轨精度满足反演需求;对于多路径效应,需要抑制强振幅、低频噪音。为LEO-LEO掩星观测、数据预处理以及数据反演流程优化提供了重要的解决思路与技术。

三七总皂苷预防髋关节置换术后异位骨化的临床效果分析

目的分析三七总皂苷预防髋关节置换术后异位骨化的临床效果。方法将86例行髋关节置换术治疗患者随机分为对照组和观察组各43例。对照组术后给予吲哚美辛片预防异位骨化,观察组术后给予三七总皂苷联合吲哚美辛片预防异位骨化,比较两组的异位骨化发生率、髋关节Harris评分及不良反应。结果观察组的异位骨化发生率明显低于对照组(P<0.05)。术后6个月,观察组髋关节Harris评分明显高于对照组(P<0.05)。观察组的不良反应发生率明显低于对照组(P<0.05)。结论髋关节置换术后给予三七总皂苷预防治疗能够有效降低异位骨化发生率,改善患者的髋关节功能,具有较高的安全性及推广应用价值。

我国油茶资源研究与开发利用现状及展望

本文主要从茶油主要成分及质量评价体系、生物和非生物胁迫对油茶生长的影响及应对措施、品种选育及栽培、油茶油脂生物合成途径调控、油茶的资源化利用等方面进行了综述。植物激素是植物生长发育过程中不可缺少的物质,研究植物激素在油茶生长发育和油脂合成过程中的作用,开发安全高效的刺激剂,对油茶的丰产育种具有重要意义。生物菌肥能调节植物生长,增加作物产量。多功能生物菌肥的开发和利用,将提高油茶产量。将构建油茶遗传转化体系与多组学分析技术相结合,研究油茶油脂合成代谢途径,可以为油茶分子育种提供新思路。

On the Generic Taxonomy of Opisthotropis balteata(Cope, 1895)(Squamata: Colubridae: Natricinae): Taxonomic Revision of Two Natricine Genera

The single prefrontal configuration has historically been used as an important diagnostic character for many natricine taxa. For example, the genus Trimerodytes Cope, 1895 was long been regarded as a junior synonym of Opisthotropis Günther, 1872 for their similar prefrontal configurations and the type species, T. balteatus Cope, 1895, has been assigned to the genus Opisthotropis. However, as the number and arrangement of prefrontal vary frequently both at species and generic level, it is questionable whether the synonymization of Trimerodytes reflects their evolutionary relationships. On the basis of recently collected specimens of O. balteata, the generic status of the species was assessed using both molecular and morphological data. Opisthotropis was recovered as polyphyletic with reference to O. balteata, because O. balteata is nested within the genus Sinonatrix Rossman and Eberle, 1977 and is the sister species of the type species of Sinonatrix. Consequently, we herein resurrect the long-overlooked synonym Trimerodytes from Opisthotropis and synonymize the junior generic nomen Sinonatrix with Trimerodytes. In addition, based on morphological similarities between the monotypic genus Paratapinophis Angel, 1929 and Trimerodytes, we doubt about the validity of Paratapinophis. Following taxonomic changes in this work, the taxonomic account of the genus Trimerodytes, updated descriptions of its type species, and diagnostic key to Trimerodytes species are provided.

Efficacy of a Chinese herbal formula on hepatitis B e antigenpositive chronic hepatitis B patients

BACKGROUND No guideline recommends antiviral therapy for hepatitis B e antigen(HBeAg)-positive chronic hepatitis B patients with persistently normal alanine aminotransferase levels and a high hepatitis B virus(HBV)DNA viral load.AIM To evaluate the feasibility and safety of a Chinese herbal formula as a therapeutic option for chronic HBV infection.METHODS In total,395 patients(30–65 years old)with confirmed HBeAg-positive chronic hepatitis B infection and persistently normal alanine aminotransferase were randomized to receive either Chinese herbal formula or placebo for 96 wk.Endpoints to evaluate therapeutic efficacy included:(1)HBV DNA levels decreased to less than 4 log10 IU/mL at weeks 48 and 96;and(2)HBeAg clearance and seroconversion rates at weeks 48 and 96.RESULTS HBV DNA levels≤4 log10 IU/mL were 10.05%at week 48 and 18.59%at week 96 in the treatment group.The HBeAg clearance and conversion rates were 8.54%and 8.04%at week 48 and 16.08%and 14.57%at week 96,respectively.However,HBV DNA levels≤4 log10 IU/mL were 2.55%and 2.55%at weeks 48 and 96,respectively,and the HBeAg clearance rates were 3.06%and 5.61%at weeks 48 and 96,respectively,in the control group.The quantitative hepatitis B surface antigen and HBeAg levels at baseline and changes during the treatment period as well as the alanine aminotransferase elevation at weeks 12 and 24 were strong predictors of HBeAg clearance.CONCLUSION High rates of HBV DNA reduction,HBeAg clearance and seroconversion could be achieved with Chinese herbal formula treatments,and the treatments were relatively safe for HBeAg-positive chronic hepatitis B-infected patients with persistently normal alanine aminotransferase.The ability of the compound to modulate host immune function probably contributed to this effect.

A new species of the Southeast Asian genus Opisthotropis (Serpentes Colubridae： Natricinae) from western Hunan, China

A new species of natricine snake of the Southeast Asian genus Opisthotropis GUnther, 1872 is described from western Hunan Province of China based on both mitochondrial DNA and morphological data. The new species is morphologically most similar and genetically most closely related to O. cheni Zhao, 1999 and O. latouchfi （Boulenger, 1899）, but possesses considerable genetic divergence （p- distance 5.1%-16.7%） and can be differentiated from all other congeners by a combination of the following morphological characters： （1） body size large （total length 514-586 mm） and strongly built; （2） dorsal scale rows 17 throughout, feebly keeled anteriorly and moderately keeled posteriorly; （3） ventral scales 147-152, subcaudal scales 54-62; （4） preocular absent, Ioreal elongated and touching orbit; （5） supralabials 8-9, fifth and sixth entering obit; （6） anterior temporals short, length 1.74-2.04 times longer than width; （7） maxillary teeth subequal, 28-30; （8） dorsal surface of head with distinct irregular yellow stripes and markings edged with ochre; （9） body with clear black and yellow longitudinal streaks, partly fused to several lighter patches or thicker stripes anteriorly; and （10） venter pale yellow, with asymmetric blackish speckles along outer margin. We present an updated diagnostic key to all members of the genus Opisthotropis, and recommendations on the ecological study for the group are provided.