Disentangling the Inverse LDL-C-hemorrhagic Stroke Association in Chinese Adults with Hypertension: Findings from the Chinese Multi-Provincial Cohort Study.

Why lower low-density lipoprotein cholesterol (LDL-C) was associated with a decreased atherosclerotic cardiovascular disease (ASCVD) risk but an increased hemorrhagic stroke (HS) risk in hypertensive adults remains unclear. We examined whether the inverse LDL-C-HS association partly arises from its effect on ASCVD. We estimated separable effects of LDL-C on HS outside (i.e., separable direct effect) or only through its effect on ASCVD (i.e., separable indirect effect) in hypertensive adults from the Chinese Multi-provincial Cohort Study. We quantified such effects using numbers needed to treat (NNT) to prevent or cause an extra HS based on the restricted mean event-free time till a 25-year follow-up. LDL-C $<$ 70 mg/dL was not associated with an increased HS risk compared to LDL-C $\ge$ 70 mg/dL regarding total and separable direct effects. However, a small separable indirect effect (i.e., NNT to harm: 9722 participants) was noted and validated via a series of sensitivity analyses. Moreover, modified effects were observed, particularly in the 35-49-year age group, men, and those with SBP $\ge$ 140 mm Hg. These results suggest the inverse LDL-C-HS association in hypertensive adults is partly due to its effect on ASCVD. A better understanding of such associations would provide more enlightening into stroke prevention.

Supercritical and homogenous transmission of monkeypox in the capital of China.

Starting from May 31, 2023, the local transmission of monkeypox (Mpox) in mainland China began in Beijing. Till now, the transmission characteristics have not been explored. Based on the daily Mpox incidence data in the first 3 weeks of Beijing (from May 31 to June 21, 2023), we employed the instant-individual heterogeneity transmission model to simultaneously calculate the effective reproduction number (Re ) and the degree of heterogeneity (k) of the Beijing epidemic. We additionally simulated the monthly infection size in Beijing from July to November and compared with the reported data to project subsequent transmission dynamics. We estimated Re to be 1.68 (95% highest posterior density [HPD]: 1.12-2.41), and k to be 2.57 [95% HPD: 0.54-83.88], suggesting the transmission of Mpox in Beijing was supercritical and didn't have considerable transmission heterogeneity. We projected that Re fell in the range of 0.95-1.0 from July to November, highlighting more efforts needed to further reduce the Mpox transmissibility. Our findings revealed supercritical and homogeneous transmission of the Mpox epidemic in Beijing. Our results could serve as a reference for understanding and predicting the ongoing Mpox transmission in other regions of China and evaluating the effect of control measures.

Causal inference for time-to-event data with a cured subpopulation.

When studying the treatment effect on time-to-event outcomes, it is common that some individuals never experience failure events, which suggests that they have been cured. However, the cure status may not be observed due to censoring which makes it challenging to define treatment effects. Current methods mainly focus on estimating model parameters in various cure models, ultimately leading to a lack of causal interpretations. To address this issue, we propose 2 causal estimands, the timewise risk difference and mean survival time difference, in the always-uncured based on principal stratification as a complement to the treatment effect on cure rates. These estimands allow us to study the treatment effects on failure times in the always-uncured subpopulation. We show the identifiability using a substitutional variable for the potential cure status under ignorable treatment assignment mechanism, these 2 estimands are identifiable. We also provide estimation methods using mixture cure models. We applied our approach to an observational study that compared the leukemia-free survival rates of different transplantation types to cure acute lymphoblastic leukemia. Our proposed approach yielded insightful results that can be used to inform future treatment decisions.

Direct and indirect treatment effects in the presence of semicompeting risks.

Semicompeting risks refer to the phenomenon that the terminal event (such as death) can censor the nonterminal event (such as disease progression) but not vice versa. The treatment effect on the terminal event can be delivered either directly following the treatment or indirectly through the nonterminal event. We consider 2 strategies to decompose the total effect into a direct effect and an indirect effect under the framework of mediation analysis in completely randomized experiments by adjusting the prevalence and hazard of nonterminal events, respectively. They require slightly different assumptions on cross-world quantities to achieve identifiability. We establish asymptotic properties for the estimated counterfactual cumulative incidences and decomposed treatment effects. We illustrate the subtle difference between these 2 decompositions through simulation studies and two real-data applications in the Supplementary Materials.

Nonparametric receiver operating characteristic curve analysis with an imperfect gold standard.

This article addresses the challenge of estimating receiver operating characteristic (ROC) curves and the areas under these curves (AUC) in the context of an imperfect gold standard, a common issue in diagnostic accuracy studies. We delve into the nonparametric identification and estimation of ROC curves and AUCs when the reference standard for disease status is prone to error. Our approach hinges on the known or estimable accuracy of this imperfect reference standard and the conditional independent assumption, under which we demonstrate the identifiability of ROC curves and propose a nonparametric estimation method. In cases where the accuracy of the imperfect reference standard remains unknown, we establish that while ROC curves are unidentifiable, the sign of the difference between two AUCs is identifiable. This insight leads us to develop a hypothesis-testing method for assessing the relative superiority of AUCs. Compared to the existing methods, the proposed methods are nonparametric so that they do not rely on the parametric model assumptions. In addition, they are applicable to both the ROC/AUC analysis of continuous biomarkers and the AUC analysis of ordinal biomarkers. Our theoretical results and simulation studies validate the proposed methods, which we further illustrate through application in two real-world diagnostic studies.

Drug Efficacy Estimation for Follow-on Companion Diagnostic Devices Through External Studies.

A therapeutic product is usually not suitable for all patients but for only a subpopulation. The safe and effective use of such a therapeutic product requires the co-approval of a companion diagnostic device which can be used to identify suitable patients. While the first-of-a-kind companion diagnostic device is often developed in conjunction with its intended therapeutic product and simultaneously validated through a randomized clinical trial, there remains room for the innovation of new and improved follow-on companion diagnostic devices designed for the same therapeutic product. However, conducting a new randomized trial or a bridging study for the follow on companion devices may be unethical, expensive or unpractical. Hence, there arises a need for an external study to evaluate the concordance between the FDA-approved comparator companion diagnostic device (CCD) and the subsequent follow-on companion diagnostic devices (FCD), indirectly validating the latter. In this article, we introduce a novel external study design, referred to as the targeted treatment design, as an extension of the existing concordance design. Additionally, we present corresponding statistical analysis methods. Our approach combines the CCD randomized trial data and the FCD external study data, enabling the estimation of drug efficacy within the FCD+ and FCD- subpopulations-the parameters crucial for the validation of the FCD. Theoretical results and simulation studies validate the proposed methods and we further illustrate the proposed methods through an application in a real example of non-small-cell lung cancer.

Effects of interventions on smoking cessation: A systematic review and network meta-analysis.

A network meta-analysis (NMA) including randomized controlled trials (RCTs) was conducted to evaluate the effects of different interventions on smoking cessation. Studies were collected from online databases including PubMed, EMBASE, Cochrane Library, and Web of Science based on inclusion and exclusion criteria. Eligible studies were further examined in the NMA to compare the effect of 14 interventions on smoking cessation. Thirty-four studies were examined in the NMA, including a total of 14 interventions and 28 733 participants. The results showed that health education (HE; odds ratio ([OR] = 200.29, 95% CI [1.62, 24 794.61])), other interventions (OI; OR = 29.79, 95% CI [1.07, 882.17]) and multimodal interventions (MUIs; OR = 100.16, 95% CI [2.06, 4867.24]) were better than self-help material (SHM). HE (OR = 243.31, 95% CI [1.39, 42531.33]), MUI (OR = 121.67, 95% CI [1.64, 9004.86]) and financial incentive (FI; OR = 14.09, 95% CI [1.21, 164.31]) had positive effects on smoking cessation rate than smoking cessation or quitting APP (QA). Ranking results showed that HE (83.6%) and motivation interviewing (MI; 69.6%) had better short-term effects on smoking cessation. HE and MUI provided more smoking cessation benefits than SHM and QA. FI was more effective at quitting smoking than QA. Also, HE and MI were more likely to be optimal smoking cessation interventions.

Knockdown of SETD5 Inhibits Colorectal Cancer Cell Growth and Stemness by Regulating PI3K/AKT/mTOR Pathway.

SET domain-containing 5 (SETD5), a member of protein lysine methyltransferase family, is expressed in multiple cancers, making it potential therapeutic targets. However, the role of SETD5 in colorectal cancer remains largely unknown. The expression of SETD5 in the 30 pairs colorectal cancer tissues samples and cell lines were determined by qRT-PCR. The functions of SETD5 was detected by knocked-down or overexpression in colorectal cancer cell lines SW480 and HCT116 cells. Cell proliferative activity, cell death, and stemness characteristics were assessed. BEZ235, a PI3K/AKT/mTOR pathway inhibitor, was used to perform rescue experiment to analyze whether SETD5 exerted its effects through activating PI3K/AKT/mTOR pathway. SETD5 was substantially upregulated in colorectal cancer, and correlated to metastasis and clinical stage of patients. Knockdown of SETD5 inhibited SW480 and HCT116 cell growth, as evidenced by the inhibition of cell viability and clone-forming. Moreover, Knockdown of SETD5 suppressed the capability of tumor sphere formation of SW480 and HCT116 cells, and reduced the expression of stemness-related proteins Nanog and Sox2. Further western blot analysis revealed that SETD5 knockdown inhibited the phosphorylation of proteins associated with the PI3K/AKT/mTOR pathway. In contrast, overexpression of SETD5 exerted the opposite effects. Mechanistically, by blocking PI3K/AKT/mTOR pathway with BEZ235, the effects of SETD5 overexpression on cell viability and Nanog and Sox2 protein expression were reversed. Our results substantiated that SETD5 functioned as an oncogene by promoting cell growth and stemness in colorectal cancer cells through activating the PI3K/AKT/mTOR signaling pathway.

CA19­9 is a significant prognostic factor in stage III gastric cancer patients undergoing radical gastrectomy.

BACKGROUND: Due to the great heterogeneity of gastric cancer (GC), the prognosis of patients within a stage is very different. Therefore, it is necessary to identify the high risk factors for postoperative recurrence and metastasis and take appropriate therapeutic strategies to improve the prognosis of patients. In this study, we aimed to explore the prognostic significance of preoperative and postoperative serum carcinoembryonic antigen (CEA), carbohydrate antigen 19 - 9 (CA19-9) and carbohydrate antigen 72 - 4 (CA72-4) in patients with stage I, II and III GC who underwent radical gastrectomy. METHODS: A total of 580 patients who underwent curative surgical resection and had not received neoadjuvant chemotherapy were included in this study. The relationship between clinicopathological features and recurrence was analysed. Survival analysis was performed by Kaplan-Meier curve. Univariate and multivariate Cox regression analyses were performed to determine prognostic factors in GC patients. RESULTS: Among patients with stage III GC, the recurrence free survival (RFS) and overall survival (OS) of patients with CA19-9>35 U/mL were significantly lower than those with CA19-9 ≤ 35 U/mL; CA19-9 was always a significant independent marker. CEA and CA72-4 were sometime useful to predict RFS or OS alternatively in the pre- or postoperative period. The only other independent significant factors for prognosis in our study were lymph node metastases for RFS and postoperative adjuvant chemotherapy for OS. CONCLUSION: Preoperative and postoperative CA19-9 values are independent risk factors for predicting prognosis in stage III GC after curative gastrectomy.

Development and verification of a prediction model for outcomes of elderly patients with nursing home-acquired pneumonia.

BACKGROUND: Among all infections in nursing homes, pneumonia has the highest mortality. Nurses have a 24-h relationship with patients and have a key role in identifying and preventing adverse outcomes. However, tools to engage nurses in pneumonia patient outcomes evaluation have not occurred. PURPOSE: This study aimed to develop and validate a prediction model to predict the outcome of elderly patients with nursing home-acquired pneumonia (NHAP). METHODOLOGY: A retrospective observational study was conducted with 219 elderly NHAP patients. Baseline characteristics, health history, and treatment/nursing status were collected. Variables for constructing nomograms were screened by univariate and multivariate analysis. The nomogram model was evaluated using the concordance index (C-index), decision curve analysis (DCA) curves, and receiver operating characteristic (ROC) curves. RESULTS: 9 independent risk factors were identified and assembled into the nomogram. The nomogram exhibited reasonably accurate discrimination (area under the receiver operating characteristic curve (AUC-ROC): 0.931, P < 0.05) and calibration (C-index: 0.931, 95 % CI: 0.898-0.964) in the validation cohort. DCA and clinical impact curves demonstrated that the nomogram was clinically beneficial. CONCLUSIONS: A visualization nomogram model was successfully established for predicting the outcome of the NHAP elderly patients. The model has extremely high reliability, extremely high predictive ability, and good clinical applicability.

Debiasing the Conversion Rate Prediction Model in the Presence of Delayed Implicit Feedback.

The recommender system (RS) has been widely adopted in many applications, including online advertisements. Predicting the conversion rate (CVR) can help in evaluating the effects of advertisements on users and capturing users' features, playing an important role in RS. In real-world scenarios, implicit rather than explicit feedback data are more abundant. Thus, directly training the RS with collected data may lead to suboptimal performance due to selection bias inherited from the nature of implicit feedback. Methods such as reweighting have been proposed to tackle selection bias; however, these methods omit delayed feedback, which often occurs due to limited observation times. We propose a novel likelihood approach combining the assumed parametric model for delayed feedback and the reweighting method to address selection bias. Specifically, the proposed methods minimize the likelihood-based loss using the multi-task learning method. The proposed methods are evaluated on the real-world Coat and Yahoo datasets. The proposed methods improve the AUC by 5.7% on Coat and 3.7% on Yahoo compared with the best baseline models. The proposed methods successfully debias the CVR prediction model in the presence of delayed implicit feedback.

Catalytic Enantioselective Synthesis of Planar Chiral Pillar[5]arenes via Asymmetric Sonogashira Coupling.

As a novel type of macrocycles with attractive planar chirality, pillar[5]arenes have gained increasing research interest over the past decades, enabling their widespread applications in diverse fields such as porous materials, molecular machines, and chiral luminescence materials. However, the catalytic methodology towards the enantioselective synthesis of planar chiral pillar[5]arenes remains elusive. Here we report a novel method for the enantioselective synthesis of planar chiral pillar[5]arenes via asymmetric Sonogashira coupling, giving access to a wide range of highly functionalized planar chiral pillar[5]arenes, including both homo- and hetero-rimmed ones, with excellent enantioselectivities. Attractively, the resultant planar chiral pillar[5]arenes show great potential for widespread use in many areas such as chiral luminescent materials. This work not only enables the successful synthesis of planar chiral pillar[5]arenes with abundant structural and functional diversity as key building blocks for practical applications but also enriches the asymmetric cross-coupling methodologies in organic synthetic chemistry.

Single-Cell DNA Sequencing Reveals Punctuated and Gradual Clonal Evolution in Hepatocellular Carcinoma.

BACKGROUND & AIMS: Copy number alterations (CNAs), elicited by genome instability, are a major source of intratumor heterogeneity. How CNAs evolve in hepatocellular carcinoma (HCC) remains unknown. METHODS: We performed single-cell DNA sequencing (scDNA-seq) on 1275 cells isolated from 10 patients with HCC, ploidy-resolved scDNA-seq on 356 cells from 1 additional patient, and single-cell RNA sequencing on 27,344 cells from 3 additional patients. Three statistical fitting models were compared to investigate the CNA accumulation pattern. RESULTS: Cells in the tumor were categorized into the following 3 subpopulations: euploid, pseudoeuploid, and aneuploid. Our scDNA-seq analysis revealed that CNA accumulation followed a dual-phase copy number evolution model, that is, a punctuated phase followed by a gradual phase. Patients who exhibited prolonged gradual phase showed higher intratumor heterogeneity and worse disease-free survival. Integrating bulk RNA sequencing of 17 patients with HCC, published datasets of 1196 liver tumors, and immunohistochemical staining of 202 HCC tumors, we found that high expression of CAD, a gene involved in pyrimidine synthesis, was correlated with rapid tumorigenesis and reduced survival. The dual-phase copy number evolution model was validated by our single-cell RNA sequencing data and published scDNA-seq datasets of other cancer types. Furthermore, ploidy-resolved scDNA-seq revealed the common clonal origin of diploid- and polyploid-aneuploid cells, suggesting that polyploid tumor cells were generated by whole genome doubling of diploid tumor cells. CONCLUSIONS: Our work revealed a novel dual-phase copy number evolution model, showed HCC with longer gradual phase was more severe, identified CAD as a promising biomarker for early recurrence of HCC, and supported the diploid origin of polyploid HCC.

Monitoring real-time transmission heterogeneity from incidence data.

The transmission heterogeneity of an epidemic is associated with a complex mixture of host, pathogen and environmental factors. And it may indicate superspreading events to reduce the efficiency of population-level control measures and to sustain the epidemic over a larger scale and a longer duration. Methods have been proposed to identify significant transmission heterogeneity in historic epidemics based on several data sources, such as contact history, viral genomes and spatial information, which may not be available, and more importantly ignore the temporal trend of transmission heterogeneity. Here we attempted to establish a convenient method to estimate real-time heterogeneity over an epidemic. Within the branching process framework, we introduced an instant-individualheterogenous infectiousness model to jointly characterize the variation in infectiousness both between individuals and among different times. With this model, we could simultaneously estimate the transmission heterogeneity and the reproduction number from incidence time series. We validated the model with data of both simulated and real outbreaks. Our estimates of the overall and real-time heterogeneities of the six epidemics were consistent with those presented in the literature. Additionally, our model is robust to the ubiquitous bias of under-reporting and misspecification of serial interval. By analyzing recent data from South Africa, we found evidence that the Omicron might be of more significant transmission heterogeneity than Delta. Our model based on incidence data was proved to be reliable in estimating the real-time transmission heterogeneity.

Improving efficiency of inference in clinical trials with external control data.

Suppose we are interested in the effect of a treatment in a clinical trial. The efficiency of inference may be limited due to small sample size. However, external control data are often available from historical studies. Motivated by an application to Helicobacter pylori infection, we show how to borrow strength from such data to improve efficiency of inference in the clinical trial. Under an exchangeability assumption about the potential outcome mean, we show that the semiparametric efficiency bound for estimating the average treatment effect can be reduced by incorporating both the clinical trial data and external controls. We then derive a doubly robust and locally efficient estimator. The improvement in efficiency is prominent especially when the external control data set has a large sample size and small variability. Our method allows for a relaxed overlap assumption, and we illustrate with the case where the clinical trial only contains a treated group. We also develop doubly robust and locally efficient approaches that extrapolate the causal effect in the clinical trial to the external population and the overall population. Our results also offer a meaningful implication for trial design and data collection. We evaluate the finite-sample performance of the proposed estimators via simulation. In the Helicobacter pylori infection application, our approach shows that the combination treatment has potential efficacy advantages over the triple therapy.

Defining estimands in clinical trials: A unified procedure.

The ICH E9 (R1) addendum proposes five strategies to define estimands by addressing intercurrent events. However, mathematical forms of these targeted quantities are lacking, which might lead to discordance between statisticians who estimate these quantities and clinicians, drug sponsors, and regulators who interpret them. To improve the concordance, we provide a unified four-step procedure for constructing the mathematical estimands. We apply the procedure for each strategy to derive the mathematical estimands and compare the five strategies in practical interpretations, data collection, and analytical methods. Finally, we show that the procedure can help ease tasks of defining estimands in settings with multiple types of intercurrent events using two real clinical trials.

Quantile partially linear additive model for data with dropouts and an application to modeling cognitive decline.

The National Alzheimer's Coordinating Center Uniform Data Set includes test results from a battery of cognitive exams. Motivated by the need to model the cognitive ability of low-performing patients we create a composite score from ten tests and propose to model this score using a partially linear quantile regression model for longitudinal studies with non-ignorable dropouts. Quantile regression allows for modeling non-central tendencies. The partially linear model accommodates nonlinear relationships between some of the covariates and cognitive ability. The data set includes patients that leave the study prior to the conclusion. Ignoring such dropouts will result in biased estimates if the probability of dropout depends on the response. To handle this challenge, we propose a weighted quantile regression estimator where the weights are inversely proportional to the estimated probability a subject remains in the study. We prove that this weighted estimator is a consistent and efficient estimator of both linear and nonlinear effects.

Electron correlation and relativistic effects on the electronic properties of a plutonium and americium mixed oxide (PuAmO4): from single-particle approximation to dynamical mean-field theory.

First-principles calculations were performed on a plutonium and americium mixed oxide (PuAmO4), aiming at revealing the effects of electron correlation, Pu/Am 5f-conduction electrons' hybridization, and relativity on its electronic properties. The many-body calculation suggests that the spin-orbit-coupling (SOC)-splitting of j = 5/2 and j = 7/2 manifolds are both in the weakly and moderately correlated states, respectively, implying that the jj coupling scheme is more appropriate for Pu/Am 5f electrons. The density of states, 5f occupation numbers, and Green's functions all suggest that both Pu and Am 5f electrons exhibit the coexistence of the localized and delocalized states. The admixture of 5fn atomic configurations, Pu/Am 5f-conduction electrons' hybridization, and dual characteristics of 5f electrons yield average occupation numbers of 5f electrons n5f = 4.78 and 5.86 for Pu and Am ions, respectively. Within the DFT+DMFT calculation, the weighted-summation-derived occupation numbers in terms of 5f4/5f5/5f6 and 5f5/5f6 configurations for Pu and Am 5f electrons, respectively, are in reasonable agreement with those of other DFT-based calculations.

A propensity score matched comparison of blood pressure lowering in essential hypertension patients treated with antihypertensive Chinese herbal Medicine: comparing the real-world registry data vs. randomized controlled trial.

BACKGROUND: Randomized controlled trials have demonstrated that Songling Xuemaikang capsule (SXC) is effective in blood pressure (BP) lowering for essential hypertension. However, the effectiveness of SXC in real-world clinical practice remains unknown. We aimed to investigate whether the BP-lowering effectiveness of SXC in the real-world practice setting is comparable to the efficacy of the intervention in a randomized controlled trial. METHODS: We included 1325 patients treated with SXC monotherapy from a real-world registry and 300 from the SXC-BP trial. A propensity score matching (PSM) approach was used to select participants from the two cohorts. The primary outcome was a change in the office of BP from baseline to 8 weeks. RESULTS: After PSM, there were 552 patients for the comparative analysis. Clinically meaningful BP reductions were observed both in the real world and in the RCT cohorts after 8-week SXC treatment. The 8-week systolic/diastolic BP was 129.50/81.33 mm Hg vs. 134.97/84.14 mm Hg in the real-world population and the RCT population, respectively. The changes in systolic BP (15.82 ± 10.71 vs. 10.48 ± 10.24; P < .001), and diastolic BP (10.01 ± 7.73 vs. 7.75 ± 8.14; P = .001) from baseline to 8 weeks were significantly greater in the real-world population. CONCLUSION: The current comparison demonstrated that SXC monotherapy is at least as effective in real-world settings as within the randomized controlled trial for BP lowering in patients with grade 1 hypertension.

CISD2 Promotes Proliferation of Colorectal Cancer Cells by Inhibiting Autophagy in a Wnt/ß-Catenin-Signaling-Dependent Pathway.

The aim of this study is to investigate the role of CDGSH iron-sulfur domain 2 (CISD2) in colorectal cancer (CRC). The purpose of this study was to investigate the role of CDGSH iron-sulfur domain 2 (CISD2) in colorectal cancer (CRC) progression. The expression of CISD2 in CRC cell lines was measured by western blotting. Functional assays including MTT assays and colony formation assays were performed to explore the role of CISD2 in regulating tumor growth. Flow cytometry analysis was used to examine the percentage of apoptotic CRC cells. Expression of apoptosis-related gene, autophagy-related markers, and the protein included in Wnt/ß-Catenin signaling was also determined by western blotting. The in vivo role of CISD2 was also examined in a xenograft model. CISD2 expression was significantly increased in CRC cells. CISD2 promoted the CRC cell proliferation and inhibited the apoptosis and autophagy of CRC cells. Moreover, knockdown of CISD2 inhibited the activation of Wnt/ß-Catenin-signaling pathway. Knockdown of CISD2 inhibited the tumor growth in nude mice. CISD2 promoted colorectal cancer development by inhibiting CRC cell apoptosis and autophagy depending on activating Wnt/ß-Catenin-signaling pathway.