Assessment of spermatogenesis in camels via seminiferous tubule staging and testosterone profiling

Objective:To investigate the successive morphological stages of spermatogenesis,hormonal regulation,and testosterone profile in dromedary camel reproduction.Methods:Testicular tissue samples were obtained from 12 dromedary bull camels aged 7 to 8 at a local abattoir.The histological assessment involved tissue processing,hematoxylin and eosin(H&E)staining,and examination under a microscope.Stereological analysis,germ cell identification,and assessment of seminiferous tubules and maturation were conducted.Testosterone assay was performed by radioimmunoassay using blood samples collected at regular intervals.Results:The study revealed 12 phases of the dromedary camel's seminiferous epithelium cycle,highlighting distinct morphological characteristics and cellular processes.Acrosomal migration,maturation,cap formation,and the Golgi-mediated synthesis of proacrosomal vesicles were also explained in dimension,as were the steps of acrosome biogenesis.Spermatids and mature sperm cells were present when spermatogenesis phases were examined.An analysis of the dimensions of seminiferous tubules revealed specific measures for diameter,area,and epithelial height about luminal characteristics.Moreover,there were noticeable variations in the serum testosterone concentrations during the study period,indicating temporal dynamics.Conclusions:This study outlines the spermatogenesis process in dromedary camels across 12 stages,emphasizing cellular dynamics and acrosomal biogenesis.It also provides seminiferous tubule measurements and observes seasonal testosterone fluctuations,offering insights into reproductive regulation and potential strategies for camel breeding conservation.

Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,etc.However, the research on RomanUrdu is not up to the mark.Hence, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including J48-Decision Tree (J48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and motivations.Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation.The user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social platforms.However,a combination of multiple behaviors in profiling users has yet to be considered.This research takes a novel approach and explores user intent types based on multidimensional online behavior in information acquisition.This research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine learning.The research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data annotation.User feedback is based on online behavior and practices collected by using a survey method.The participants include both males and females from different occupation sectors and different ages.The data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their characteristics.Different techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of 1136.Feature average is computed to identify user intent type characteristics.The user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on their preferences in online content,platforms,criteria,and frequency.The study also validates the proposed template on user feedback data through Inter-Rater Agreement process using an external human rater.

Genomic profiling of colorectal cancer in large-scale Chinese patients:amplification and somatic mutations in ERBB2

Objectives:Human epidermal growth factor receptor 2(HER2)-targeted therapies have demonstrated potential benefits for metastatic colorectal cancer(mCRC)patients with HER2 amplification,but are not satisfactory in cases of HER2 mutant CRCs.Methods:Consequently,further elucidation of amplifications and somatic mutations in erythroblastic oncogene B-2(ERBB2)is imperative.Comprehensive genomic profiling was conducted on 2454 Chinese CRC cases to evaluate genomic alterations in 733 cancer-related genes,tumor mutational burden,microsatellite instability,and programmed death ligand 1(PD-L1)expression.Results:Among 2454 CRC patients,85 cases(3.46%)exhibited ERBB2 amplification,and 55 cases(2.24%)carried ERBB2 mutation.p.R678Q(28%),p.V8421(24%),and p.S310F/Y(12%)were the most prevalent of the 16 detected mutation sites.In comparison to the ERBB2 altered(alt)group,KRAS/BRAF mutations were more prevalent in ERBB2 wild-type(wt)samples(ERBB2wt vs.ERBB2alt,KRAS:50.9%vs.25.6%,p<0.05;BRAF:8.5%vs.2.3%,p<0.05).32.7%(18/55)of CRCs with ERBB2 mutation exhibited microsatellite instability high(MSI-H),while no cases with HER2 amplification displayed MSI-H.Mutant genes varied between ERBB2 copy number variation(CNV)and ERBB2 single nucleotide variant(SNV);TP53 alterations tended to co-occur with ERBB2 amplification(92.3%)as opposed to ERBB2 mutation(58.3%).KRAS and PIK3CA alterations were more prevalent in ERBB2 SNV cases(KRAS/PIK3CA:45.8%/31.2%)compared to ERBB2 amplification cases(KRAS/PIK3CA:14.1%/7.7%).Conclusion:Our study delineates the landscape of HER2 alterations in a large-scale cohort of CRC patients from China.These findings enhance our understanding of the molecular features of Chinese CRC patients and offer valuable implications for further investigation.

ABMRF:An Ensemble Model for Author Profiling Based on Stylistic Features Using Roman Urdu

This study explores the area of Author Profiling(AP)and its importance in several industries,including forensics,security,marketing,and education.A key component of AP is the extraction of useful information from text,with an emphasis on the writers’ages and genders.To improve the accuracy of AP tasks,the study develops an ensemble model dubbed ABMRF that combines AdaBoostM1(ABM1)and Random Forest(RF).The work uses an extensive technique that involves textmessage dataset pretreatment,model training,and assessment.To evaluate the effectiveness of several machine learning(ML)algorithms in classifying age and gender,including Composite Hypercube on Random Projection(CHIRP),Decision Trees(J48),Na飗e Bayes(NB),K Nearest Neighbor,AdaboostM1,NB-Updatable,RF,andABMRF,they are compared.The findings demonstrate thatABMRFregularly beats the competition,with a gender classification accuracy of 71.14%and an age classification accuracy of 54.29%,respectively.Additional metrics like precision,recall,F-measure,Matthews Correlation Coefficient(MCC),and accuracy support ABMRF’s outstanding performance in age and gender profiling tasks.This study demonstrates the usefulness of ABMRF as an ensemble model for author profiling and highlights its possible uses in marketing,law enforcement,and education.The results emphasize the effectiveness of ensemble approaches in enhancing author profiling task accuracy,particularly when it comes to age and gender identification.

Identification of antimalarial targets of chloroquine by a combined deconvolution strategy of ABPP and MS-CETSA

Background: Malaria is a devastating infectious disease that disproportionally threatens hundreds of millions of people in developing countries. In the history of anti-malaria campaign, chloroquine(CQ) has played an indispensable role, however, its mechanism of action(MoA) is not fully understood.Methods: We used the principle of photo-affinity labeling and click chemistry-based functionalization in the design of a CQ probe and developed a combined deconvolution strategy of activity-based protein profiling(ABPP) and mass spectrometry-coupled cellular thermal shift assay(MS-CETSA) that identified the protein targets of CQ in an unbiased manner in this study. The interactions between CQ and these identified potential protein hits were confirmed by biophysical and enzymatic assays.Results: We developed a novel clickable, photo-affinity chloroquine analog probe(CQP) which retains the antimalarial activity in the nanomole range, and identified a total of 40 proteins that specifically interacted and photocrosslinked with CQP which was inhibited in the presence of excess CQ. Using MS-CETSA, we identified 83 candidate interacting proteins out of a total of 3375 measured parasite proteins. At the same time, we identified 8 proteins as the most potential hits which were commonly identified by both methods.Conclusions: We found that CQ could disrupt glycolysis and energy metabolism of malarial parasites through direct binding with some of the key enzymes, a new mechanism that is different from its well-known inhibitory effect of hemozoin formation. This is the first report of identifying CQ antimalarial targets by a parallel usage of labeled(ABPP)and label-free(MS-CETSA) methods.

Depth profiling of arsenian pyrite in Carlin-type ores through wet chemistry

Enrichment of As and Au at the overgrowth rims of arsenian pyrite is a distinctive feature of Carlin-type gold ores.Revealing distribution of such key elements in high resolution is of fundamental importance yet often proves challenging.In this study,repeated non-oxidative acid etching of ore samples from Shuiyindong gold deposit was applied to enable elemental depth profiling of goldbearing arsenian pyrite grains.ICP-OES and AAS were used to determine the dissolved Fe,As,and Au concentrations in each of the etching solutions,and XPS was carried out to exam the etched mineral surfaces.In contrast to conventional ion beam etching that may cause substantial sample damage,our acid etching method does not seem to significantly alter the composition and chemical state of the samples.The etched depths directly converted from the measured elemental concentrations can reproducibly reach a very high resolution of~1 nm,and can be conveniently controlled through varying the etching time.While the Fe and As depth profiles consistently reflect the surface oxidation property of arsenian pyrite,the Au profile displaying an obvious upward trend reveals the ore fluid evolution at the late stage of mineralization.Based on our experimental results,we demonstrate that our wet chemistry method is capable of effective depth profiling of gold ore and perhaps other geological samples,with advantages surpassing many instrumental techniques including negligible sample damage,nanoscale resolution as well as isotropic etching.

DMMIC derivatization-assisted liquid chromatography-mass spectrometry method for metabolite profiling of the glutathione anabolic pathway in esophageal cancer tissues and cells

In this work,a new pyrylium derivatization-assisted liquid chromatography-mass spectrometry(LC-MS)method was developed for metabolite profiling of the glutathione anabolic pathway(GAP)in cancer tissues and cells.The pyrylium salt of 6,7-dimethoxy-3-methyl isochromenylium tetrafluoroborate(DMMIC)was used to label the amino group of metabolites,and a reductant of dithiothreitol(DTT)was employed to stabilize the thiol group.By combining DMMIC derivatization with LC-MS,it was feasible to quantify the 13 main metabolites on the GAP in complex biological samples,which had good linearity(R^(2)=0.99810.9999),precision(interday precision of 1.6%e19.0%and intraday precision of 1.4%e19.8%)and accuracy(83.4%-115.7%).Moreover,the recovery assessments in tissues(82.5%e107.3%)and in cells(98.1%e118.9%)with GSH-^(13)C2,^(15)N,and Cys-^(15)N demonstrated the reliability of the method in detecting tissues and cells.Following a methodological evaluation,the method was applied successfully to investigate difference in the GAP between the carcinoma and para-carcinoma tissues of esophageal squamous cell carcinoma(ESCC)and the effect of p-hydroxycinnamaldehyde(CMSP)on the GAP in KYSE150 esophageal cancer cells.The results demonstrate that the developed method provides a promising new tool to elucidate the roles of GAP in physiological and pathological processes,which can contribute to research on drugs and diseases.

Thermal integrity profiling of cast-in-situ piles in sand using fiber-optic distributed temperature sensing

Defects in cast-in-situ piles have an adverse impact on load transfer at the pile‒soil interface and pile bearing capacity. In recent years, thermal integrity profiling (TIP) has been developed to measure temperature profiles of cast-in-situ piles, enabling the detection of structural defects or anomalies at the early stage of construction. However, using this integrity testing method to evaluate potential defects in cast-in-situ piles requires a comprehensive understanding of the mechanism of hydration heat transfer from piles to surrounding soils. In this study, small-scale model tests were conducted in laboratory to investigate the performance of TIP in detecting pile integrity. Fiber-optic distributed temperature sensing (DTS) technology was used to monitor detailed temperature variations along model piles in sand. Additionally, sensors were installed in sand to measure water content and matric suction. An interpretation method against available DTS-based thermal profiles was proposed to reveal the potential defective regions. It shows that the temperature difference between normal and defective piles is more obvious in wet sand. In addition, there is a critical zone of water migration in sand due to the water absorption behavior of cement and temperature transfer-induced water migration in the early-age concrete setting. These findings could provide important insight into the improvement of the TIP testing method for field applications.

Molecular Profiling of Sugarcane Wine, a Traditional Fermented Beverage (Loungouila) from Madingou

A number of studies reported that traditional fermented beverages possessed pharmaceutical biomolecules involved in biocatalysis for good therapeutic effects on various pathology including tumor, diabetes, inflammation, and obesity. This dimension of understanding is the prerogative of the biomolecular profile found in these fermented foods and beverages. The current work aimed to study the postfermentation molecular profile of the Congolese fermented beverage (Lougwila). The determination of pH, the acidity titratable, the distillation of sugar cane, the determination of total polyphenols and flavonoids and the matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) have been used. As results, the fermenting sugar cane juice at room temperature for a period of seven days, leading to a decrease of the pH value to 4.25 ± 0.10 and increase in titratable acidity and alcohol content of at least 6.421 g/L (w/v) and 7% respectively. The polyphenol concentration of Loungouila increase from 14.9 to 20.5 mg Eq AG/g Ms after 10 days of fermentation. The flavonoid concentration varies from 1.70 to 5.22 mg Eq Cat/g Ms. among 46 isolates of Bacillus species, 55% (25/45) were able to show a very interesting clear zones in terms of cellulolytic activity with the percentage ranging from 37.3% to 83.9%, and 41.3% of amylolytic activity for the percentage ranging from 52.02% to 75%. 65.21% (30/46) of the isolates tested were found to be positive by the caseinolytic test with zones of inhibition ranging in diameter from 1.10 ± 0.09 to 3.25 ± 0.07 cm. In addition to the determination of biomolecule profile, 34.78% (16/46) of Bacillus isolates were able to produce biosurfactants with percentages ranging from 14% to 100%. Proteomic profiling of Loungouila has been investigated by using MALDI-TOF Technique. Short sequences showed 100% identity and were associated with AprE, SubC, amyE, NprE, CelA, lytF, Mut, and ykfC proteins. The National Center for Biotechnology Information (NCBI) allowed to associate short sequences to Bacillus species.

点阵激光联合重组牛碱性细胞生长因子治疗皮脂腺增生62例疗效观察

目的观察Profile铒激光治疗皮脂腺增生的效果。方法对62例皮脂腺增生患者采用Profile超级平台铒激光模式进行治疗,并对资料进行回顾性分析。结果62例患者痊愈49例,显效11例,无效2例,总有效率为96.77%。术后瘢痕发生率为6.45%,3~6个月渐平复。暂时性色素改变1~3个月后均自行消退.随访6个月后治疗区未见复发。结论Profile铒激光治疗皮脂腺增生总体疗效较好,安全有效,不良反应小,值得临床推广应用。

俯仰式播种单体仿形性能检测试验台设计与试验

为解决播种单体仿形机构性能难以检测的问题,设计了俯仰式播种单体仿形性能检测试验台。阐述了试验台组成结构与工作原理,对其高速传动系统、液压升降系统、监控系统以及关键部件参数进行设计。应用ANSYS软件对台架整体和关键部件进行静力学分析和模态分析,验证结构设计的合理性。为检验俯仰式播种单体仿形性能检测试验台的实际检测效果,以德邦大为1205型牵引式免耕精量播种机播种单体为研究对象,先以液压杆伸出量与传送带速度为试验因素,以监控系统误差为评价指标进行试验。试验得出,在液压杆伸出量为0~200 mm范围内,监控系统角度传感器最大误差为0.69 mm;在传送带速度8~19 km/范围内,光电编码器最大误差为0.18 km/h。确认监控系统准确性后,再以单体速度为试验因素,采集速度8、10、12 km/h下地块的起伏数据为目标曲线,以地形起伏模拟曲线的绝对误差平均值为指标进行单因素试验,试验得出,所设计的试验台可有效模拟田间地面的起伏频率与起伏量,绝对误差平均值为1.86 mm,满足播种单体仿形性能检测需求。

电子舌和气相色谱-离子迁移谱技术分析炖煮时间对松茸鸡汤风味的影响

以雅江鲜松茸为试验材料,采用电子舌和气相色谱-离子迁移谱技术,使用主成分、正交偏最小二乘法判别分析,结合相对气味活度值分析炖煮时间对松茸鸡汤风味的影响。结果表明:鲜松茸对鸡汤滋味贡献很大,电子舌鲜味强度值从2.1提高到8.0。采用GC-IMS方法共检出45种化合物,加入松茸后醛类含量从47.88%下降到21.13%,由ROAV值(128.08)确认3-甲基-1-丁醇是松茸鸡汤的关键化合物。其中,伞花烃、3-辛醇、正辛醇是松茸鸡汤的特征化合物,使松茸鸡汤呈现独特的汽油味、苔藓清香、坚果香味、蘑菇气味和金属气味。炖煮5 min后,鸡汤中松茸特征风味最明显,达到最佳食用效果。研究结果为雅江松茸鸡汤风味特征研究提供参考。

胜利油田GF84区块CCUS气窜封堵技术及其应用

胜利油田GF84区块为低渗透油藏,采出程度较低,CO_(2)驱是提高该区块采收率的有效措施之一。在前期开发中注采井之间已形成明显的气窜通道,现阶段亟需进行气窜封堵,提高CO_(2)驱波及系数,实现均衡驱替。通过分析GF84区块气窜特征与开发矛盾,将气窜类型划分为“裂缝型气窜”和“基质型气窜”,并制定了“裂缝封堵”和“基质调剖”的治理策略。在明确气窜特征的基础上,通过室内实验研发了硅盐树脂堵剂、CO_(2)气溶性发泡剂和高温冻胶堵剂,并形成了“硅盐树脂裂缝封堵+CO_(2)气溶性发泡剂、高温冻胶基质调剖”化学封堵分级调控技术。结果表明,该技术在GF84区块成功应用4口井,其中硅盐树脂裂缝封堵2口井,CO_(2)气溶性发泡剂基质调剖2口井,措施有效率100%,有效期在0.5 a以上。研究成果可为低渗透油田CO_(2)驱开发提供技术支撑。

空空导弹海洋大气自然环境试验研究

针对空空导弹随航母服役需求和海洋大气自然环境适应性风险,结合相关标准和研制经验,对空空导弹海洋大气自然环境试验方案设计流程、方法及要点进行了研究。提出了一套空空导弹海洋大气自然环境试验方案,可用于指导新研型号科学有效地开展自然环境试验,为回答空空导弹海洋大气自然环境适应性指标提供了支撑。空空导弹应系统策划海洋大气自然环境试验,以尽早暴露问题,实现产品设计改进,为上舰环境适应性的提高奠定基础。同时,还应大力开展自然加速环境试验技术和动态自然环境试验技术研究工作。

基于校园行为特征的学生就业画像

基于校园行为数据分析学生就业与校园行为之间的关联性是大数据背景下高校就业管理与指导工作的重点。文章以高校本科学生为研究对象,对学生基本信息和校园行为数据进行特征提取和学生标签体系的构建,通过关联规则挖掘学生就业与校园行为之间的关联,探析不同毕业去向学生的行为特征。研究发现:国内读研类学生有4种典型学生群体画像,出国出境类大学生有3种典型学生群体画像,直接就业类大学生有4种典型学生群体画像,不同的学生群体在行为规律性、消费水平和学业水平等方面存在显著区别。文章建议:提供大学生职业生涯规划指导,加强对学生心理状况的关注,开展同学结对帮扶活动。

黄芪多糖对乳腺癌细胞抑制作用机制研究

目的 考察黄芪多糖对乳腺癌细胞的抑制作用并预测参与的通路,对关键通路进行验证,并对涉及的免疫通路进行富集分析。方法 采用CCK-8法检测不同浓度黄芪多糖(0、0.5、1.0、2.0、4.0、8.0 mg/mL)对乳腺癌MDA-MB-231细胞增殖的抑制作用;对黄芪多糖给药组和对照组进行基因表达谱测定,筛选差异表达基因,应用R语言clusterProfiler包将筛选出的差异表达基因进行京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)分析。采用Western blot法检测黄芪多糖处理后乳腺癌MDA-MB-231细胞Wnt信号通路Wnt1和β-catenin蛋白的表达;应用ImmPort数据库免疫相关基因集与差异表达基因取交集,进行免疫相关通路分析;考察不同组别程序性细胞死亡配体1(programmed cell death ligand 1,PD-L1)的表达水平。结果 黄芪多糖以浓度依赖性方式抑制乳腺癌细胞增殖作用,与对照组相比,黄芪多糖给药组共筛选出363个差异表达基因,主要富集在Wnt信号通路、ECM受体相互作用、乳腺癌等;Western blot分析进一步证实黄芪多糖能够浓度依赖性抑制Wnt信号通路中Wnt1和β-catenin蛋白的表达。与ImmPort数据库免疫基因集进行交集后获取到42个差异表达的免疫基因,KEGG通路富集结果提示,通路主要富集在抗原提呈、炎症反应和TNF信号通路,提示黄芪多糖可能主要通过增加抗原提呈作用介导其发挥乳腺癌免疫调节作用。黄芪多糖能适度降低PD-L1的表达水平,但差异无统计学意义。结论 黄芪多糖以浓度依赖性方式抑制乳腺癌细胞增殖,主要通过Wnt信号通路发挥其抑制作用,此外免疫调节方面可能通过增加抗原提呈作用介导乳腺癌免疫调节作用。

换热翅片几何量数字化测量技术研究及在智能制造中的应用

为解决换热翅片开窗角度的数字化测量问题,研究了面向换热器智能制造产线的翅片几何量参数测量装置。该装置采用激光轮廓传感器进行非接触测量,对获取的多组原始轮廓数据进行数据剔除和取均值预处理,将处理后的数据逐点求导以识别兴趣测量区域,在各兴趣测量区域采用定长逐点步进的方式进行最小二乘拟合运算,选取最优拟合线段进行夹角计算,可自动实现对翅片8个开窗角度及3个长度参数的测量,设计了基于JSON的数据交互格式实现与制造执行系统的数据对接。实验结果表明:装置角度测量最大允许误差(MPE)为±0.5°,具备数字化测量及数据交互能力,测量精度满足企业质控需求。

基于高分辨一维距离像及其特征的空间目标识别效果分析

目标高分辨一维距离像(High Resolution Range Profile,HRRP)中包含了丰富的目标尺寸、结构等目标特征,是进行空间目标身份识别的有效途径。但由于卫星宽带雷达实测数据获取难度大,前期相关研究多集中于基于HRRP的目标识别算法,结论也多是基于仿真数据和少量类别(几类)的前提下得到的,与工程应用实际情况有较大差距,工程指导意义有限。为解决这一问题,基于地基雷达获取的30类卫星目标的大量一维距离像实测数据,从识别正确率的角度对目标HRRP及其特征(组合)的可分性和在空间目标个体识别中的应用效果进行了量化分析,分析结果可为后续基于HRRP的空间目标个体识别技术研究和工程应用提供可靠依据。

Th1/Th2细胞因子谱在不同感染程度病人水平变化及其对脓毒症病人预后的评估价值

目的:探讨外周血1型或2型辅助型T淋巴细胞(Th1/Th2)细胞因子谱对不同感染程度病人的临床应用及其对脓毒症病人短期预后的评估价值。方法:选取78例脓毒症病人(脓毒症组),64例局部感染病人(普通感染组)以及42例非感染病人(非感染组),收集3组病人的临床资料,比较入科后各组病人细胞因子浓度,使用Spearman等级相关分析其与感染严重程度的关系;依据随访结果,将脓毒症病人分成存活组(31例)和死亡组(47例),比较2组Th1/Th2细胞因子谱的差异,采用logistic回归分析筛选影响脓毒症病人预后的独立危险因素,对脓毒症病人28 d生存率进行亚组分析,并绘制Kaplan-Meier生存曲线,分析病人28 d累积生存情况。结果:随着感染严重程度的增加,IL-4水平逐渐降低,IL-6、IL-8及IL-10水平逐渐升高;普通感染组和脓毒症组病人IL-5水平低于非感染组(P<0.05~P<0.01)。Spearman等级相关分析显示,IL-4与感染严重程度呈负相关(P<0.01);IL-6、IL-8、IL-10与感染严重程度呈显著正相关(P<0.01)。随访28 d,脓毒症病人死亡率60.26%。死亡组病人IL-5、IL-6、IL-8、IL-10浓度均大于存活组(P<0.05~P<0.01);logistic回归分析显示,IL-5和IL-8是脓毒症病人28 d死亡的独立危险因素(P<0.05);根据最佳截断值对IL-5、IL-8进行亚分组,结果提示IL-5、IL-8升高,增加了脓毒症病人28 d死亡的风险。Kaplan-Meier生存分析进一步证实了IL-5≥0.55 pg/mL组病人的28 d累积生存率明显低于IL-5<0.55 pg/mL组病人(P<0.05);IL-8≥54.61 pg/mL组病人的28 d累积生存率明显低于IL-8<54.61 pg/mL组病人(P<0.01)。结论:Th1/Th2细胞因子谱与感染严重程度呈现出显著的相关关系,且IL-5及IL-8对脓毒症病人28 d生存情况具有良好的预测价值。