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Background To estimate crude mortality, excess mortality, and standardized mortality rates (SMR) among people living with HIV (PLHIV) initiating highly active antiretroviral therapy (HAART) in Luzhou, China 2006–2020, and assess associated factors. Methods PLHIV initiating HAART in the HIV/AIDS Comprehensive Response Information Management System (CRIMS) in Luzhou, China 2006–2020 were included in the retrospective cohort study. The crude mortality, excess mortality, and SMR were estimated. Multivariable Poisson regression model was used for analyzing risk factors associated with excess mortality rates. Results The median age among 11,468 PLHIV initiating HAART was 54.5 years (IQR:43.1–65.2). The excess mortality rate decreased from 1.8 deaths/100 person-years (95% confidence interval [CI]:1.4–2.4) in 2006–2011 to 0.8 deaths/100 person-years (95%CI:0.7–0.9) in 2016–2020. SMR decreased from 5.4 deaths/100 person-years (95%CI:4.3–6.8) to 1.7 deaths/100 person-years (95%CI:1.5–1.8). Males had greater excess mortality with the eHR of 1.6 (95%CI:1.2–2.1) than females. PLHIV with CD4 counts ≥ 500 cells/μL had the eHR of 0.3 (95%CI:0.2–0.5) in comparison to those with CD4 counts Conclusions The excess mortality and SMR among PLHIV initiating HAART in Luzhou, China decreased substantially from 2006 to 2020, but the mortality rate among PLHIV was still higher than general population. PLHIV who were male, with baseline CD4 counts less than 200 cells/μL, WHO clinical stages III/IV, time from diagnosis to HAART initiation ≥ 12 months, initial HAART regimens unchanged, and virological failure had a greater risk of excess deaths. Early and efficient HAART would be significant in reducing excess mortality among PLHIV.

BackgroundOsteosarcoma is the most common primary malignant bone tumor. The existing treatment regimens remained essentially unchanged over the past 30 years; hence the prognosis has plateaued at a poor level. Precise and personalized therapy is yet to be exploited.MethodsOne discovery cohort (n=98) and two validation cohorts (n=53 & n=48) were collected from public data sources. We performed a non-negative matrix factorization (NMF) method on the discovery cohort to stratify osteosarcoma. Survival analysis and transcriptomic profiling characterized each subtype. Then, a drug target was screened based on subtypes’ features and hazard ratios. We also used specific siRNAs and added a cholesterol pathway inhibitor to osteosarcoma cell lines (U2OS and Saos-2) to verify the target. Moreover, PermFIT and ProMS, two support vector machine (SVM) tools, and the least absolute shrinkage and selection operator (LASSO) method, were employed to establish predictive models.ResultsWe herein divided osteosarcoma patients into four subtypes (S-I ~ S-IV). Patients of S- I were found probable to live longer. S-II was characterized by the highest immune infiltration. Cancer cells proliferated most in S-III. Notably, S-IV held the most unfavorable outcome and active cholesterol metabolism. SQLE, a rate-limiting enzyme for cholesterol biosynthesis, was identified as a potential drug target for S-IV patients. This finding was further validated in two external independent osteosarcoma cohorts. The function of SQLE to promote proliferation and migration was confirmed by cell phenotypic assays after the specific gene knockdown or addition of terbinafine, an inhibitor of SQLE. We further employed two machine learning tools based on SVM algorithms to develop a subtype diagnostic model and used the LASSO method to establish a 4-gene model for predicting prognosis. These two models were also verified in a validation cohort.ConclusionThe molecular classification enhanced our understanding of osteosarcoma; the novel predicting models served as robust prognostic biomarkers; the therapeutic target SQLE opened a new way for treatment. Our results served as valuable hints for future biological studies and clinical trials of osteosarcoma.

Background: The proportion of elderly people living with HIV (PLHIV) is increasing in China. To advance targeted interventions and substantially improve their quality of life, we investigate indicators of loneliness and sexual behavior among elderly PLHIV in 10 districts/counties in China during the COVID-19 pandemic. Methods: The demographic information and laboratory test results of the potential respondents were initially collected from the China Information System for Disease Control and Prevention. A two-stage stratified cluster sampling was used. The questionnaire survey was individually provided to all PLHIV aged +60. Results: We recruited 1017 valid respondents with a median age of 66 years (interquartile range of 63–71), of which 776 (76.3%) were male. Overall, 341 respondents (33.5%) lived alone, and 304 (29.9%) felt lonely. A total of 726 respondents (71.4%) informed others of their HIV diagnosis. Among the 726 respondents, children were the most common group with whom the older people shared their HIV infection status, accounting for 82.9%. Approximately 20% of the older PLHIV engaged in sexual behavior in the last year, and 70% reported not using condoms. A significantly greater risk of loneliness was found among the females (AOR = 1.542, CI: 1.084, 2.193), those who suffered discrimination from informed people (AOR = 4.719, CI: 2.986, 7.459), were diagnosed

Objective Reducing the prevalence of treatment failure among people living with HIV (PLHIV) on highly active antiretroviral therapy (HAART) is crucial for improving individual health and reducing disease burden. This study aimed to assess existing evidence on treatment failure and its associated factors among PLHIV in mainland China. Methods We conducted a comprehensive search of PubMed, Web of Science, Cochrane Library, WanFang, China National Knowledge Infrastructure, and SinoMed databases. Relevant studies on treatment failure among PLHIV in mainland China until September 2022 were searched, including cross-sectional, case-control, and cohort studies. The primary outcome was treatment failure, and secondary outcomes were the potential influencing factors of treatment failure. We performed a meta-analysis to pool each outcome of interest, including meta-regression, subgroup, publication bias, and sensitivity analyses. Results A total of 81 studies were deemed eligible and included in the final meta-analysis. The pooled treatment failure prevalence among PLHIV in mainland China was 14.40% (95% confidence interval [CI]:12.30–16.63), of which the virological and immunological failure prevalence was 10.53% (95%CI:8.51–12.74) and 18.75% (95%CI:15.44–22.06), respectively. The treatment failure prevalence before and after 2016 was 18.96% (95%CI:13.84–24.67) and 13.19% (95%CI:10.91–15.64). Factors associated with treatment failure included good treatment adherence (odds ratio [OR] = 0.36, 95%CI:0.26–0.51), baseline CD4 counts>200 cells/μL (OR = 0.39, 95%CI:0.21–0.75), HAART regimens containing Tenofovir Disoproxil Fumarate (TDF) (OR = 0.70, 95%CI:0.54–0.92), WHO clinical stage III/IV (OR = 2.02, 95%CI:1.14–3.59) and age≥40 years (OR = 1.56, 95%CI:1.23–1.97). Conclusion The prevalence of treatment failure among PLHIV receiving HAART in mainland China was low and tended to decline. Poor adherence, low baseline CD4 count, HAART regimens without TDF, advanced clinical stage, and old age were contributing factors for treatment failure. Relevant intervention programs are needed with increasing treatment adherence through behavioral intervention or precise intervention targeting older adults.

Background One striking feature of the large KRAB domain-containing zinc finger protein (KZFP) family is its rapid evolution, leading to hundreds of member genes with various origination time in a certain mammalian genome. However, a comprehensive genome-wide and across-taxa analysis of the structural and expressional features of KZFPs with different origination time is lacking. This type of analysis will provide valuable clues about the functional characteristics of this special family. Results In this study, we found several conserved paradoxical phenomena about this issue. 1) Ordinary young domains/proteins tend to be disordered, but most of KRAB domains are completely structured in 64 representative species across the superclass of Sarcopterygii and most of KZFPs are also highly structured, indicating their rigid and unique structural and functional characteristics; as exceptions, old-zinc-finger-containing KZFPs have relatively disordered KRAB domains and linker regions, contributing to diverse interacting partners and functions. 2) In general, young or highly structured proteins tend to be spatiotemporal specific and have low abundance. However, by integrated analysis of 29 RNA-seq datasets, including 725 samples across early embryonic development, embryonic stem cell differentiation, embryonic and adult organs, tissues in 7 mammals, we found that KZFPs tend to express ubiquitously with medium abundance regardless of evolutionary age and structural disorder degree, indicating the wide functional requirements of KZFPs in various states. 3) Clustering and correlation analysis reveal that there are differential expression patterns across different spatiotemporal states, suggesting the specific-high-expression KZFPs may play important roles in the corresponding states. In particular, part of young-zinc-finger-containing KZFPs are highly expressed in early embryonic development and ESCs differentiation into endoderm or mesoderm. Co-expression analysis revealed that young-zinc-finger-containing KZFPs are significantly enriched in five co-expression modules. Among them, one module, including 13 young-zinc-finger-containing KZFPs, showed an ‘early-high and late-low’ expression pattern. Further functional analysis revealed that they may function in early embryonic development and ESC differentiation via participating in cell cycle related processes. Conclusions This study shows the conserved and special structural, expressional features of KZFPs, providing new clues about their functional characteristics and potential causes of their rapid evolution.

Tumorigenesis and the subsequent development and metastasis of tumors are continuous evolutionary processes that are a result of several molecular evolutionary events. During these processes, the tumor cells gradually gain advantages of survival and proliferation and promote tumor heterogeneity. An in-depth understanding of the mechanism underlying the molecular evolution of tumor cells will help us understand the intrinsic mechanism of tumorigenesis, tumor development, and metastasis. This in turn will aid in the development of targeted treatment strategies for blocking tumor development and metastasis as well as improve the therapeutic effects of these strategies. This review systematically summarizes the molecular evolutionary events, such as gene mutation, gene copy number variation, the generation of de novo genes, and chromosome abnormality, during the process of tumorigenesis, tumor development, and metastasis as well as their relationship with tumor development. This review summarizes the main theoretical models of molecular evolution in tumor cells and discusses future research trends and prospects. Furthermore, it provides valuable reference information for additional in-depth theoretical and applied research in this field in the future.

With the rapid progress of the Internet of Things (IoT) technology, human behavior recognition has become an important research topic in the field of ubiquitous computing and has obtained quite a number of research achievements. Accurate human behavior recognition can enhance the quality of human-computer interaction and facilitate the development of various sensing applications. With the popularity of smartphones and the improved performance of sensors such as speakers and microphones built in smartphones, the behavior recognition technique based on ultrasound signal of the smartphone has gained more attention and achieved several research results. In this paper, we first review the common behavior recognition techniques including light, video, sound, and frequency radio and outline their main characteristics. Then, we introduce the fundamental principle of human behavior recognition based on ultrasound signals. Specifically, these systems treat speakers and microphones embedded in smartphones as the transceiver and leverage the received signal changes caused by human movement including phase differences, frequency shift, and time of flight (ToF) to recognize human behavior. Next, we investigate the state-of-the-art studies and applications and analyze the signal processing techniques such as data collection, signal preprocessing, feature description, and behavior recognition approach. Afterward, according to the purpose of these applications, we classify them into five groups and compare them in detail including hand gesture recognition, activity recognition, hand trajectory tracking, vital sign monitoring, and lip reading. Finally, we conclude by discussing the limitations, challenges, and open issues involved in behavior recognition based on ultrasound signal of smartphone.

With the rapid development of Internet of Things, hand gesture recognition has drawn wide attention in the field of ubiquitous computing because it provides us with simple and natural human-computer interaction mode. Among these various implementations, hand gesture recognition using ultrasonic signals of smartphone has become a hot research topic due to its various advantages. In this paper, we consider the smartphone as an active sonar sensing system to identify hand movements. Specifically, the speakers emit ultrasonic signal and the microphone on the same phone receives the changed echo affected by hand movements. This paper investigates the state-of-the-art hand gesture applications and presents a comprehensive survey on the characteristics of studies using the active sonar sensing system. Firstly, we review the existing research of hand gesture recognition based on acoustic signals. After that, we introduce the characteristics of ultrasonic signal and describe the fundamental principle of hand gesture recognition. Then, we focus on the typical methods used in these studies and present a detailed analysis on signal generation, feature extraction, preprocessing, and recognition methods. Next, we investigate the state-of-the-art ultrasonic-based applications of hand gesture recognition using smartphone and analyze them in detail from dynamic gesture recognition and hand tracking. Afterwards, we make a discussion about these systems from signal acquisition, signal processing, and performance evaluation to obtain some insight into development of the ultrasonic hand gesture recognition system. Finally, we conclude by discussing the challenges, insight, and open issues involved in hand gesture recognition based on ultrasonic signal of the smartphone.

Recent years have witnessed increasing research interest in human behavior recognition as it provides attractive applications in various sensing scenarios. Among these encouraging implementations, device-free behavior recognition based on WiFi channel state information (CSI) has attracted significant attention due to the popularity of WiFi devices and abundant channel characteristics from CSI. Meanwhile, the CSI signal provides us with additional benefits because it can propagate through a wall. This through-the-wall and device-free scheme not only enables us to identify specific human actions but also to infer person activities by collecting the data from different rooms. This paper presents a survey on the state-of-art progresses in device-free through-the-wall human behavior recognition based on CSI. Specifically, this paper first introduces the basic concept of CSI and describes the signal variation caused by human behavior. Then, it illustrates that different human behaviors can cause signal transformation. Therefore, the unique map relationship between action and signal variation can be leveraged to recognize human behavior. Next, it provides the general architecture of through-the-wall behavior recognition and highlights its core characteristic. It investigates the state-of-art applications in various scenarios and analyzes specific design schemes and implementations. Afterward, it discusses the various across wall applications and makes a detailed comparison between non-through-the-wall and through-the-wall applications. Meanwhile, it analyzes many factors that affect recognition accuracy and emphasizes performance differences under across wall scenarios. Finally, this paper concludes by summarizing the issues and challenges faced and providing insights into the possible solution and future research trend.

Recently, device-free human behavior recognition has become a hot research topic and has achieved significant progress in the field of ubiquitous computing. Among various implementation, behavior recognition based on WiFi CSI (channel state information) has drawn wide attention due to its major advantages. This paper investigates more than 100 latest CSI based behavior recognition applications within the last 6 years and presents a comprehensive survey from every aspect of human behavior recognition. Firstly, this paper reviews general behavior recognition applications using the WiFi signal and presents the basic concept of CSI and the fundamental principle of CSI-based behavior recognition. This paper analyzes the key components and core characteristics of the system architecture of human behavior recognition using CSI. Afterward, we divide the sensing procedures into many steps and summarize the typical studies from these steps, including base signal selection, signal preprocessing, and identification approaches. Next, based on the recognition technique, we classify the applications into three groups, including pattern-based, model-based, and deep learning-based approach. In every group, we categorize the state-of-the-art applications into three groups, including coarse-grained specific behavior recognition, fine-grained specific behavior recognition, and activity inference. It elaborates the typical behavior recognition applications from five aspects, including experimental equipment, experimental scenario, behavior, classifier, and system performance. Then, this paper presents comprehensive discussions about representative applications from the implementation view and outlines the major consideration when developing a recognition system. Finally, this article concludes by analyzing the open issues of CSI-based behavior recognition applications and pointing out future research directions.

Additional file 1: Figure S1. The schematic diagram of the domain architecture of KZFP and the key amino acids in zinc finger binding to DNA. Figure S2. The SDR values of KRAB domains with different gene age grades in 7 mammals. Figure S3. The expression pattern of KZFP genes with different zinc finger divergence time grades. Figure S4. The expression pattern of KZFP genes in 7 mammals. Figure S5. The highly expressed KZFP genes in human. Figure S6. The expressional and functional characteristics of the co-expression modules containing old-zinc-finger-containing KZFPs. Figure S7. The PPIs of young- or old-zinc-finger-containing KZFPs. Figure S8. The SDR values and interactors of ZKSCAN3, ZNF287 and ZNF90. Figure S9. The WGCNA parameter for early development dataset (A) and brain development dataset (B).

One striking feature of the large KRAB-containing zinc finger protein (KZFP) family is its rapid expansion and divergence since its formation about 400 million years ago. However, the evolutionary characteristics of KRAB domains, C2H2 zinc fingers and the full protein of KZFPs have not been fully analyzed. As for the drivers of the rapid evolution, it’s partly due to their coevolution with transposable elements (TEs). But their diverse functions besides inhibiting TEs suggest other reasons exist. Here we address these two issues by the systematic analysis of the divergence time and diversification pattern of KZFPs at three aspects and the functional analysis of the potential target genes besides TEs. We found that old-zinc-finger-containing KZFPs tend to have varied and disordered KRAB domains, indicating there are two ways of the evolution of KZFPs, including the variation of KRAB domains and the diversification of zinc fingers. Among them, the divergence of zinc fingers mainly contributes to the rapid evolution of KZFPs. Thus, we mainly focused on the functional requirements of the evolution of zinc fingers. Different from the classical regulation pattern of this family, we found and experimentally confirmed that KZFPs tend to bind to non-TE regions and can positively regulate target genes. Although most young genes tend to be with a low expression level, young-zinc-finger-containing KZFPs tend to be highly expressed in early embryonic development or early mesoderm differentiation, indicating their particular evolutionarily novel functional roles in these two processes. We further validated a young KZFP, ZNF611, can bind to non-TE region of STK38 gene and positively regulates its expression in ESCs. The emergence of new sequence in STK38 promoter may drive the evolution of zinc fingers in ZNF611. Finally, we proposed a ‘two-way evolution model’ of KZFP family.

Phasor measurement units (PMUs) have been widely and successfully used in power transmission grids. PMU technologies could be exploited in distribution grids to manage the impact of distributed generation and the electrification of the transportation sector. However, distribution grids are quite different from transmission ones resulting in more stringent accuracy requirements for the distribution PMUs (D-PMUs)). Currently, no standards for D-PMUs are available. However, there are numerous requirements proposed for D-PMUs that need further understanding and assessment. In this paper, a comparison between the IEEE Std C37.118 that is applicable to T-PMUs and requirements for D-PMUs is documented. A classification based on accuracy is proposed. Finally, the factors influencing the accuracy of D-PMUs are discussed in detail.

Quantitative analysis of Cr-adsorption from a gas phase on CeO 2 , pure and doped BaCeO 3 was performed in combination with surface techniques and electrochemical impedance spectroscopy. The Cr-adsorption on BaCeO 3 is 3 times higher than on CeO 2 and it increases by 12–25% on In doping in Ba(Ce 1−x In x )O 3 (x = 0.1–0.3) in the temperature range of 600–700 °C. These perovskites adsorb chromium with the formation of a multi-phase surface layer containing BaCr 6+ O 4 and cerium oxide. Coexistence of small fractions of Cr 3+ and Cr 5+ cations in the surface layer was identified by X-ray photoelectron spectroscopy. The thickness of the surface layer and its morphology vary with temperature, affecting the conductivity of Ce containing perovskites below 700 °C. BaCrO 4 exhibits under air noticeably larger anisotropic thermal expansion than BaCeO 3 . The results indicate that high tolerance to Cr-gaseous species should be considered as an important criterion for further development of materials for proton-conducting SOFCs.