ObjectiveBoth B-cell- and T-cell-mediated immunity are crucial for the effective clearance of viral infection, but little is known about the dynamic characteristics of SARS-CoV-2-specific B-cell and T-cell responses in people living with HIV (PLWH) after a full course of inactivated SARS-CoV-2 vaccination.MethodsIn this study, fifty people living with HIV (PLWH) and thirty healthy controls (HCs) were enrolled to assess B-cell and T-cell responses at the day before the vaccination (T0), two weeks after the first dose (T1), two months after the first dose (T2), the day of the third dose (T3), one month after the third dose (T4), three months after the third dose (T5) and 12 months (T6) after the third dose.ResultsSARS-CoV-2-specific B-cell and T-cell responses were induced in people living with HIV (PLWH), and these responses lasted at least one year after the third vaccine dose. However, the peak frequencies of Spike-specific B-cell and T-cell responses in PLWH were lower than those in HIV-negative controls. In addition, the expansion of activated B cells, memory B cells and plasma cells after primary vaccination was observed, but the percentages of these cells were decreased at T6 and were comparable to those at T0. Additionally, the percentages of activated T cells, exhausted T cells and SARS-CoV-2-specific T cells with enhanced functional activity were increased following the administration of inactivated SARS-CoV-2 vaccine. In addition, PLWH had lower percentages of plasma cells, RBD-specific B cells, circulating Tfh (cTfh) cells and CD38+ cTfh cells, and the percentages of the latter two types of cells were positively correlated with the titer of neutralizing antibodies, indicating these differences may account for the weaker immune responses induced in PLWH.ConclusionThese data suggest that specific B-cell and T-cell responses could be sustained for at least one year after receiving the third vaccination. Our findings emphasize that the weak SARS-CoV-2-specific B-cell and T-cell responses induced in PLWH have implications for clinical decision-making and public health policy for PLWH with respect to SARS-CoV-2 infection.

What is already known about this topic?:Human immunodeficiency virus (HIV) low-level viremia (LLV) during antiretroviral therapy (ART) occurs frequently in Dehong Dai and Jingpo Autonomous Prefecture, Yunnan Province. What is added by this report?:Among people living with HIV who achieved virological success [viral load (VL) <1,000 copies/mL] after initiating ART in Dehong Prefecture, Southwest China, 17.6% experienced first-year LLV of 50-999 copies/mL First-year LLV emerged as an independent risk factor for subsequent viral non-suppression compared with participants maintaining first-year VL <50 copies/mL. What are the implications for public health practice?:Enhanced monitoring and interventions for early LLV occurrence during the first year of ART are essential, including adherence education and timely VL testing.

To improve the node localization accuracy of large-scale wireless sensor networks (WSNs), a node localization method for WSNs using density peak clustering to optimize the Salp Swarm Algorithm is proposed. Firstly, the block-based non-ranging WSNs node localization model is established, adaptively determines the number of WSNs subregion divisions, and the location problem is abstracted as the optimal extreme value solution problem. Secondly, the improved density peak clustering (IDPC) algorithm and the improved salp swarm algorithm (ISSA) algorithm are designed for adaptive determination of hyper-parameters by defining the disparity truncation distance judgment index and two-stage approximation computation to improve the effectiveness of IDPC clustering. The IDPC is used to cluster the spatial characteristics of bottlenose sea squirt populations, adaptively determine leader and follower groups, and redefine the individual evolutionary approach to improve the global convergence accuracy of ISSA. Finally, ISSA is employed to solve the optimal extreme value problem of node location. The simulation results show that compared with the existing node location algorithm, the localization errors of the proposed method are reduced by about 65.83

With the widespread application of HIV-1 nucleic acid testing (NAT) in China, particularly in the diagnosis of HIV-1 infection, ensuring the accuracy of NAT results through quality control has become critically important. However, existing HIV-1 NAT quality control materials (QCMs), such as clinical plasma samples and inactivated HIV-1 cell culture supernatants, have limitations in sustainability, biosafety risks, and costs. MS2-armed RNA (MS2) does not replicate the biological characteristics of natural viruses or the complexities of the extraction and detection processes associated with authentic viral particles. To address these limitations, this study developed a novel HIV-1 NAT QCM based on HIV-1 pseudovirus (PsV). HIV-1 PsV packaged using an improved four-plasmid lentiviral vector (LV) system could be generated with a high concentration of up to 10⁹ copies/mL. The HIV-1 PsV mimics the morphology of the real virus and is capable of only single-cycle infection, thereby ensuring biosafety. The HIV-1 PsV-based QCM demonstrated excellent homogeneity, absence of matrix effects, stability for 7 days at 4°C and -20°C, and the ability to withstand up to five freeze-thaw times. We further found that HIV-1 PsV outperformed inactivated HIV-1 and MS2 in terms of short-term stability and freeze-thaw stability, respectively. Additionally, the PsV-based QCM was successfully detected by 12 commercial HIV-1 NAT quantification kits in the Chinese market and demonstrated excellent performance in an external quality assessment (EQA) involving 60 laboratories. In summary, the novel HIV-1 PsV-based QCM can serve as a safe and sustainable alternative to existing HIV-1 NAT QCMs for EQA of HIV-1 NAT laboratories.IMPORTANCEThis study proposes a novel strategy to prepare HIV-1 nucleic acid testing (NAT) quality control material (QCM) using HIV-1 pseudovirus (PsV) packaged by an improved four-plasmid lentiviral vector (LV) system. The HIV-1 PsV-based QCM can simulate authentic virus particles and better monitor the entire HIV-1 NAT process, including nucleic acid extraction, amplification, and detection. The innovative HIV-1 NAT QCM possesses several desirable characteristics: biosafety, homogeneity, stability, and the ability to be prepared at high concentrations and on a large scale, significantly reducing production costs. Compared to commonly used QCMs such as inactivated HIV-1 and MS2, the HIV-1 PsV demonstrates superior stability and better meets the requirements for transportation, storage, and quality control applications of HIV-1 NAT laboratory. Particularly, the ability of HIV-1 PsV to accommodate the insertion of large nucleic acid sequences provides a solid technical foundation for developing more advanced quality control solutions in the future.

No novel biomarkers are currently available for evaluating immune reconstitution among people living with HIV/AIDS (PLWH) receiving combined antiretroviral treatment (cART). The objective of this study was to analyze the expression patterns of interferon-stimulating genes (ISGs) in PLWH with the aim of identifying potential biomarkers for immune reconstitution. Study samples were collected from 102 PLWH, including 47 immunological non-responders (INRs) and 58 immunological responders (IRs). The expression of eight ISGs in the peripheral blood in INRs and IRs were detected by RT-qPCR. Expression differences between groups were analyzed with the Mann-Whitney U test, and a logistic regression model was developed to predict immune reconstitution. Among eight ISGs, the expression levels of IFI27 and IFI6 were significantly higher in INRs than IRs ( P =0.001 and 0.005, respectively). The model combining age, CD4 + T/CD8 + T ratio, IFI27, and IFI6 had the highest diagnostic value (AUC=0.836), with an optimal cut-off value of 0.6, sensitivity of 60.5%, and specificity of 98.1%. No significant change in the expression of IFI27 and IFI6 was observed in samples collected 3 years apart ( P =0.1232 and 0.4877, respectively), and the model score negatively correlated with ΔCD4 + T cells (r=−0.2888, P =0.0465). Enhanced expression of IFI27 and IFI6 in INRs are important characteristics that may serve as biomarkers of immune reconstitution after cART. The combination of age, CD4 + T/CD8 + T ratio, IFI27, and IFI6 was highly effective in discriminating INRs.

Since the advent of massive open online courses (MOOC), it has been the focus of educators and learners around the world, however the high dropout rate of MOOC has had a serious negative impact on its popularity and promotion. How to effectively predict students' dropout status in MOOC for early intervention has become a hot topic in MOOC research. Due to there are huge differences in the learning behaviors, study habits and learning time of different students in MOOC, i.e. the students' learning behavior data containing rich learning information, so it can be used to predict the students' dropout status. In this paper, according to the students' learning behaviour data, a feature extraction method is firstly designed, which can reflect the characteristics of weekly student learning behaviors. Then, the intelligently optimized support vector regression (SVR) model is used as the student dropout prediction (SDP) model. In this SDP model, the three parameters of SVR are not randomly selected but determined by an improved quantum particle swarm optimization (IQPSO) algorithm. Experimental results from both direct observation and statistical analysis on public data indicate that the proposed SDP model can achieve better predictive performance than various benchmark SDP models.

目的 通过对不同病毒载量的同一研究对象同时进行血浆HIV-1 RNA与干血斑HIV-1 DNA的基因型耐药检测并对结果进行比较,探讨HIV-1 DNA用于耐药检测的可行性和用途.方法 2021年12月采集云南省、广西壮族自治区及新疆维吾尔自治区接受ART后1年以上的HIV/AIDS患者静脉血5 mL,EDTA抗凝,分离血浆和制备成干血斑样本,分别提取病毒DNA和RNA进行pol区扩增,比较两种方法的扩增效率;并对同时扩增成功的序列利用MEGA7构建系统进化树并分析序列一致性.利用斯坦福大学HIV耐药数据库进行耐药位点分析,比较耐药性结果.结果 209例样本中,来自云南82份(39.2％),来自广西壮族自治区69份(33.0％),来自新疆维吾尔自治区58份(27.8％).105 例 VL＜20 拷贝/mL,25 例 20 拷贝/mL≤VL＜200 拷贝/mL,42 例 200 拷贝/mL≤VL＜1 000 拷贝/mL,37 例 VL≥1 000拷贝/mL.不同病毒载量的样本分类中,使用血浆中HIV-RNA pol区扩增成功率分别为12.4％、28.0％、69.0％、89.2％;使用干血斑中HIV-DNA pol区扩增成功率分别为39.0％、52.0％、59.5％、73.0％;血浆结合干血斑各组的扩增成功率为41.0％、56.0％、76.2％、89.2％.两种耐药检测方法同时扩增成功66例,耐药结果完全一致为98.5％,序列一致性99.7％.其中有58例(58/66,87.9％)配对样本耐药位点完全一致,8例配对样本耐药位点不完全一致.耐药位点不完全一致的配对样本中仅1例导致耐药结果不同,其他主要由混合碱基导致但未对耐药结果产生影响.结论 应用干血斑HIV-1 DNA进行基因型耐药检测可以弥补目前血浆HIV-1 RNA耐药检测不足,特别是对病毒载量＜1 000拷贝/mL的样本,能够提高耐药检测效率.同时二者检测结果基因序列与耐药位点的一致性很好.结合干血斑样本容易制备、保存与运输的优点,提高了在偏远欠发达地区进行耐药监测的可及性.

Gastrointestinal viruses include acute gastroenteritis virus and enterovirus. These viruses are highly contagious and human populations are generally susceptible to them, and the viruses require only tens to hundreds of virus particles to cause infection. Digital polymerase chain reaction (dPCR) has the advantages of high sensitivity, strong anti-interference and direct quantification. It has shown its uniqueness in the detection of gastrointestinal viruses, especially for samples with low viral loads, which is a beneficial supplement to the real-time PCR technology. This article reviews and looks forward to the application of digital PCR technology in gastrointestinal virus detection.

2021年6月,联合国艾滋病规划署发布了 2030年实现终结艾滋病流行的目标[1].尽早发现感染者,尽快开展抗病毒治疗,实现有效病毒抑制是全球终结艾滋病流行的重要策略[2].艾滋病检测为临床诊断、治疗效果监测、调整治疗方案、病程进展监测及地区发病率估计等防治工作提供了不可或缺的基础支撑.近年来艾滋病的血清学检测、核酸检测、耐药检测、CD4细胞检测技术不断创新发展,有效提高了艾滋病检测服务的可及性、检测结果的准确性、以及检测结果返回的及时性.本文就近年来艾滋病检测技术的进展以及对高质量检测服务的推动作用综述如下.

HIV infection is a serious challenge to global public health. Timely and accurate early diagnosis and early initiation of antiretroviral therapy can effectively resist the spread of the virus, and improve the immune function of HIV-infected patients, thereby improve patients′ outcomes and reduce patients′ hospitalization and mortality. Efficient and sensitive testing is a prerequisite for early diagnosis of HIV infection and is also a focus in the prevention and control of HIV epidemics. Serologic testing has been the most widely used HIV detection technology till now. However, it has been difficult for the traditional antibody detection technology to detect HIV acute infection in a timely and accurate manner and therefore restricted the early diagnosis of HIV infection. In recent years, a variety of new detection technologies, such as HIV antigen/antibody combined detection and biosensors, with their high sensitivity, have significantly shortened the window period for the diagnosis of HIV infection, bringing new hope for early diagnosis of HIV. This paper reviews the principle, scope of application, and application prospect of serological detection technology for HIV infection and provides a reference for the development of new HIV testing strategies.

Software Defect Prediction (SDP) is an important method to analyze software quality and reduce development cost. Data from software life cycle has been widely used to predict the defect prone of software modules, and although many machine learning-based SDP models have been proposed, their predictive performance is not always satisfactory. Traditional machine learning-based classifiers usually assume that all samples have the same contribution to the training of SDP, which is not true. In fact, different training samples have different effects on the performance of the SDP model, the performance of machine learning-based SDP models is heavily dependent on the quality of training samples. For the above shortcoming of traditional machine learning-based classifiers, the contributions of this paper are as follows: (1) Inspired by the clustering algorithm, a method to calculate the contribution of each training sample to the SDP model is proposed, which not only considers the relationship between the contributions of the training samples to the SDP model, and also analyzes the influence of the distance between the sample and the category boundary on the performance of the SDP model, so it is different from the existing calculation method of sample contribution. (2) A Sample Selection (SS) method is proposed to improve the performance of the SDP model. It first calculates the contribution of each training sample based on several nearest neighbors of the sample and the label information of these neighbors, and then implements SS according to Hoeffding probability inequality and the contribution of each sample. To confirm the validity of the proposed SDP model, some experimental results are given. Both direct observations and statistical tests of the experimental results show that the SS method is very effective for improving the predictive performance of the SDP model.

目的 评估将HIV-1RNA定量检测作为补充试验在HIV感染辅助诊断中的应用.方法 应用云南省德宏州2014-2019年所有HIV抗体确证试验(WB)结果为不确定的样本,回顾性分析这些样本的HIV-1RNA定量检测和随访结果.结果 在47例WB不确定的样本中,21例HIV-1 RNA定量结果≥5 000拷贝/mL,经随访均确认为HIV阳性;4例HIV-1RNA定量结果＜5 000拷贝/mL,1例已接受ART,1例失访,其余2例定量检测结果分别为2 100拷贝/mL和1 500拷贝/mL,且经随访均确认为HIV阳性.22例HIV-1 RNA定量报告未检出(TND),经随访均确认为HIV阴性.当阳性诊断阈值设定为5 000拷贝/mL,HIV-1RNA定量检测作为补充实验的灵敏度为87.5％,特异度为100.0％,诊断效率为93.4％;当阳性诊断阈值设定为1 000拷贝/mL,HIV-1RNA定量检测作为补充实验的灵敏度为95.8％,特异度为100.0％,诊断效率为97.8％.结论 HIV-1 RNA定量检测作为WB不确定样本的补充试验可以及时确认HIV感染.若降低阳性诊断阈值至1 000拷贝/mL,可提高HIV感染的诊断灵敏度和诊断效率.

Objective:To determine the baseline HIV viral load and demographic characteristics of newly diagnosed HIV cases from 2015 to 2017 in Dehong prefecture and provide a scientific basis for improving HIV prevention and treatment.Methods:All newly reported HIV-infected cases from 2015 to 2017 in Dehong prefecture were included in this study. Viral load, CD 4+ T cell counts and the demographic characteristics were collected and retrospectively analyzed. Results:From 2015 to 2017, a total of 1 157 newly diagnosed HIV cases were reported in Dehong prefecture, of which 1 057 cases were tested for viral load; 64.9% were males, 59.5% aged between 25 and 49, 51.9% were married, 48.2% were Han ethnicity, 48.2% had middle school (or beyond) training and 85% were heterosexual. The median pre-treatment viral load of newly diagnosed HIV-infected individuals was 8 200 (IQR: 1 900-44 000) copies/ml. The proportion of cases with viral load between 10 3-10 5copies/ml was the highest, accounted for 65.7% (694/1 057). There were 5.2% (55/1 057) whose viral load was below the detecting limit and 24 had CD 4+ T cell counts over 500 cells/μl. Conclusions:Baseline viral load levels before treatment vary among HIV-infected individuals. In view of the impact of viral load at baseline on the effectiveness of diagnosis and treatment, it is necessary to perform viral load testing before treatment, and the result can assist in the formulation of a more personalized and effective treatment regimen.

Since the labeled wild facial expression database is relatively rare, the existing Facial Expression Recognition (FER) models based on machine learning can only be trained with a relatively limited number of samples and whether the trained FER model can have satisfactory recognition performance is a challenge. In this paper, the facial expression database from the Laboratory Environment (LE) is used as the source domain, and the facial expression database from the wild is used as the target domain. Based on these two different databases, a hybrid improved unsupervised Cross-Domain Adaptation (CDA) approach is proposed, which can not only match the data distribution between different databases, but also maximize the correlation of data between different databases, and also maximize data separability on the source database. In the proposed CDA approach, the objective functions of the two improved techniques and those of traditional CDA are to achieve the simultaneous optimization of the three objective functions. After that, the proposed CDA approach was used for Cross-domain FER (CFER) task. To confirm the effectiveness of the proposed CFER model, some experiments are implemented on four cross-database pairs. The comparison and analysis of experimental results show that, compared with other existing CFER models, the proposed CFER model can realize the reuse of LE facial expression data and achieve better recognition performance for wild facial expression data.

实验室检测是艾滋病临床诊断、病程进展监测、抗病毒治疗启动、治疗效果监测、耐药性检测及调整治疗方案等诊疗工作不可或缺的技术支撑.为满足不断增加的艾滋病诊断和治疗相关的防治需求,全国艾滋病实验室网络不断发展壮大.特别是实施"四免一关怀"政策以来,实验室网络建设快速持续发展,检测技术和检测策略也适时进行完善、更新,为艾滋病诊断和治疗提供了有力的技术支持和质量保证,助力我国艾滋病防治工作取得显著成效.

艾滋病是世界范围内流行的以经性传播为主的重大慢性传染病,对人类健康构成严重威胁.2020年全球有150万HIV新发感染和68万艾滋病相关死亡,存活HIV感染者中有16％未被检测发现,27％未接受抗病毒治疗,34％未得到有效病毒抑制[1].2020年我国尚有约20％的HIV感染者不知道自己的感染状况,高于全球平均水平(根据中国疾病预防控制中心性病艾滋病预防控制中心2020年疫情估计结果).尽早发现感染者、尽快开展抗病毒治疗,实现有效病毒抑制是全球终结艾滋病流行的重要策略.HIV检测不仅是这一策略的重要前提,也是有效干预易感染HIV危险行为人群的重要环节.为促进主动检测和早检测,最大限度发现感染者,有效遏制HIV传播,早日实现终结艾滋病流行的目标,专家就进一步扩大艾滋病检测促进早检测达成以下共识.

HIV的核酸检测在早期诊断、监测抗病毒治疗效果以及HIV感染婴儿的诊断中具有重要作用,但现有的HIV核酸检测方法操作复杂、耗时长且成本高.发展简便的HIV核酸检测方法成为近年来的研究热点,其中焦磷酸化激活性聚合反应(PAP)具有较高的特异性,且无需反转录酶处理即可实现RNA的扩增;重组酶聚合酶扩增(RPA)利用人体温度即可催化反应;环等温扩增(LAMP)对设备要求简单,灵敏度和特异性都较高,结果肉眼可见;螺旋酶依赖的扩增(HDA)和链置换扩增反应(SDA)的机制简单,可以一步完成反应.这些HIV核酸检测方法操作简便并可快速获得检测结果,适于在资源有限地区进行,未来可应用于HIV感染的早期检测.

Objective:To investigate the differences in virological and immunological indicators of HIV-1 infected individuals with different degrees of immunosuppression, analyze the correlation between the sample/cutoff ratio (S/CO), viral load (VL), Western blot (WB) band type and immune status of HIV-1 infected individuals.Methods:A total of 639 HIV-1 antibodies positive and treatment-naive samples from Henan, Beijing and Yunnan during the period of 2017-2019 were divided into three groups: no immunosuppression (CD4≥500 cells/μl), mild immunosuppressive (350cells/μl≤CD4<500cells/μl), moderate immunosuppression (200 cells/μl≤CD4<350 cells/μl), severe immunosuppression (CD4<200 cells/μl). Chi-square test was used to compare S/CO, WB band type among different immunosuppression groups, analyze the relationship between various indicators and immune status.Results:In each immunosuppressive group, S/CO>20 had the highest occurrence rate (>37%), and showed a decreasing trend with the enhancement of immunity ( P<0.05), the occurrence rate of 119%), the occurrence rate of 078%), while the occurrence rates of p55 (<40%) and p39 (<3%) were the lowest, the differences of the occurrence rates of gp41 and p51 among different immunosuppression groups were statistically significant ( P<0.05). The area under the curve determined by S/CO value combined with viral load for no, mild, moderate and severe immunosuppression groups were respectively 0.651 (95% CI: 0.600-0.702; P<0.05), 0.587 (95% CI: 0.540-0.635; P<0.05), 0.605 (95% CI: 0.560~0.650; P<0.05), 0.647 (95% CI: 0.586-0.708; P<0.05). Conclusions:The S/CO value viral load was the best for the determination of non-immunosuppressive status; The absence of gp41 and p51, S/CO>20 suggest that the patient may be in non or severe immunosuppressed state, respectively.

Currently, the high dropout rate of massive open online course (MOOC) has seriously affected its popularity and promotion. How to effectively predict the dropout status of students in MOOC so as to intervene as early as possible has become a hot topic. As we know, different students in MOOC have big differences in learning behaviors, learning habits, and learning time, etc. This leads to different student samples having different effects on the prediction performance of the machine learning-based dropout prediction model (DPM). This is because the performance of machine learning-based classifiers heavily depends on the quality of training samples. To solve this problem, in this paper, a new DPM based on machine learning is proposed. Since the traditional neighborhood concept has nothing to do with the label of the sample, a new neighborhood definition, i.e., the max neighborhood, is first given. It is not only related to the distance between samples, but also related to the labels of the samples. Then, the calculation and realization algorithm of the initial weight of each student sample is studied based on the definition of the max neighborhood, which is different from the commonly methods of randomly selecting initial values. Next, the optimization method of the initial weight of the student sample is further studied using the intelligent optimization method. Finally, the classifiers trained by the weighted training samples are used as DPM. Experimental results of direct observation and statistical testing on public data sets indicate that the training sample weighting and intelligent optimization technology can significantly improve the predictive performance of DPM.

目的 分析免疫学和病毒学指标作为预测1型艾滋病病毒(HIV-1)新发感染标志的可行性.方法 对2017-2018年浙江省、北京市、云南省三个现场的HIV抗体初筛、确证阳性样本1 382份,进行新发感染、CD4+T淋巴细胞(简称CD4细胞)计数和病毒载量检测,采用Logistic回归模型比较新发感染和既往感染两组样本之间各项指标的差异,分析可能作为预测HIV-1新发感染标志的因素.结果 新发感染样本中蛋白印迹试验(WB)条带gp120、p55、p51、gp41、p31、p17的阳性检出率显著低于既往感染者(P＜0.05),多因素二元Logistic回归分析结果显示,p55、gp41、p31条带缺失被判定为新发感染的可能性比较高,尤其是p31条带的缺失[比值比(OR)=6.640,95％可信区间(CI):4.271～10.321];S/CO值＞10(OR=2.052,95％CI:1.138～3.700)被判定为新发感染的可能性是1＜S/CO≤3的2.052倍,病毒载量≥100 000copies/mL(OR=3.272,95％CI:1.254～8.537)被判定为新发感染的可能性是病毒载量＜1 000copies/mL的3.272倍,CD4细胞≥500个/μL(OR=2.575,95％ CI: 1.204～5.509)被判定为新发感染的可能性是CD4细胞＜200个/μL的2.575倍,S/CO联合病毒载量和CD4细胞计数,受试者工作特征曲线下面积达0.643(95％CI:0.588～0.699;P＜0.05),敏感度和特异度分别为50.0％和73.2％.结论 抗体确证结果WB带型p55、gp,41、p31可以作为HIV-1新发感染预测指标.抗体初筛结果S/CO值,CD4细胞计数和病毒载量具有预测HIV-1新发感染的可能性.