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.

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.

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.

Recognition of H3K9 methylation by GLP is required for efficient establishment of H3K9 methylation, rapid target gene repression, and mouse viability.

GLP and G9a are major H3K9 dimethylases and are essential for mouse early embryonic development. GLP and G9a both harbor ankyrin repeat domains that are capable of binding H3K9 methylation. However, the functional significance of their recognition of H3K9 methylation is unknown. Here, we report that the histone methyltransferase activities of GLP and G9a are stimulated by neighboring nucleosomes that are premethylated at H3K9. These stimulation events function in cis and are dependent on the H3K9 methylation binding activities of ankyrin repeat domains of GLP and G9a. Disruption of the H3K9 methylation-binding activity of GLP in mice causes growth retardation of embryos, ossification defects of calvaria, and postnatal lethality due to starvation of the pups. In mouse embryonic stem cells (ESCs) harboring a mutant GLP that lacks H3K9me1-binding activity, critical pluripotent genes, including Oct4 and Nanog, display inefficient establishment of H3K9me2 and delayed gene silencing during differentiation. Collectively, our study reveals a new activation mechanism for GLP and G9a that plays an important role in ESC differentiation and mouse viability.

The safety and effectiveness of enhanced recovery after surgery (ERAS) in older patients undergoing orthopedic surgery: a systematic review and meta-analysis.

INTRODUCTION: To systematically review and analyze the safety and effectiveness of ERAS in older patients undergoing orthopedic surgeries. MATERIALS AND METHODS: We searched PubMed, EMBASE, CINAHL, MEDLINE (Ovid), Web of Science, the Cochrane Library, and other databases to identify all randomized controlled studies and cohorts. We used the Cochrane Risk of Bias Assessment Tool and the Newcastle‒Ottawa Scale to assess the study quality. A meta-analysis was performed using the inverse variance weighting method. RESULTS: This study included 15 studies involving a total of 2591 older patients undergoing orthopedic surgeries with 1480 in the ERAS group. The ERAS group had a lower incidence of postoperative complications than the control group (RR 0.52; 95% CI 0.42-0.65). Length of stay was 3.37 days lower in the ERAS group than in the control group (P < 0.01). And the ERAS protocol reduced the patient's postoperative VAS score (P < 0.01). Meanwhile, there was a lack of evidence of significant differences between the ERAS group and the control group in total bleeding and 30-day readmission rate. CONCLUSIONS: The implementation of the ERAS program in older patients undergoing orthopedic surgeries is safe and effective. However, there is still a lack of standardization of protocols across institutions and centers for orthopedic surgery for older patients. Identifying ERAS components that are beneficial to older patients and developing ERAS protocols that are appropriate for older adults may further improve outcomes.

Comparing the accuracy of screening tests with verification of disease status restricted to test positives.

As a fundamental component of health care, disease screening is of highly importance. Oftentimes, two screening tests for a specific disease are compared in order to determine an optimal screening policy, for example, the digital rectal examination (DRE) and serum prostate specific antigen (PSA) level for screening prostate cancer. Ideally, if a gold standard test is given to each individual being screened to establish their true disease status, the difference in accuracy measures between two tests can be evaluated. In practice, however, it is common that only individuals who test positive on at least one screening test are to receive gold standard tests, which are often invasive and cannot be applied to those with negative results on both tests due to ethical reasons. Under such circumstances, estimates of the differences in accuracy measures between two tests cannot be determined, thus the inference problem within this framework is challenging. In this article, using sensitivity and specificity as measures of test accuracy, we show that their difference between two tests is interval-identified, as bounded by estimable sharp bounds. Here, we develop the asymptotic normality for the estimators of the bounds and construct confidence intervals for the difference by utilizing the method for solving inference problem for partially identified parameters. The performance of constructed confidence intervals for the difference and their sharp bounds are evaluated via simulation studies. We also apply the proposed method to the prostate cancer example to compare the accuracy of DRE and PSA.

A novel regression method for the analysis of multireader multicase-free-response receiver operating characteristics studies.

In diagnostic radiology, the multireader multicase (MRMC) design and the free-response receiver operating characteristics (FROC) method are often used in combination. The cross-correlated data generated by the MRMC-FROC study leads to difficulties in the corresponding analysis, and the need to include covariates in the model further complicates the subsequent analysis. In this paper, we propose a regression approach based on three new measures with good interpretability. The correlation structure of the original test results is taken directly into account in the estimation procedure. The proposed method also allows the inclusion of continuous or discrete covariates. Consistent and asymptotically normal estimators are derived for the new measures. Simulation studies are conducted to evaluate the performance of the proposed approach. The simulation results show that the regression approach performs well under a wide range of scenarios. We also apply the proposed regression approach to a diagnostic study of computer-aided diagnosis in lung cancer.

Extending Hui-Walter framework to correlated outcomes with application to diagnosis tests of an eye disease among premature infants.

Diagnostic accuracy, a measure of diagnostic tests for correctly identifying patients with or without a target disease, plays an important role in evidence-based medicine. Diagnostic accuracy of a new test ideally should be evaluated by comparing to a gold standard; however, in many medical applications it may be invasive, costly, or even unethical to obtain a gold standard for particular diseases. When the accuracy of a new candidate test under evaluation is assessed by comparison to an imperfect reference test, bias is expected to occur and result in either overestimates or underestimates of its true accuracy. In addition, diagnostic test studies often involve repeated measurements of the same patient, such as the paired eyes or multiple teeth, and generally lead to correlated and clustered data. Using the conventional statistical methods to estimate diagnostic accuracy can be biased by ignoring the within-cluster correlations. Despite numerous statistical approaches have been proposed to tackle this problem, the methodology to deal with correlated and clustered data in the absence of a gold standard is limited. In this article, we propose a method based on the composite likelihood function to derive simple and intuitive closed-form solutions for estimates of diagnostic accuracy, in terms of sensitivity and specificity. Through simulation studies, we illustrate the relative advantages of the proposed method over the existing methods that simply treat an imperfect reference test as a gold standard in correlated and clustered data. Compared with the existing methods, the proposed method can reduce not only substantial bias, but also the computational burden. Moreover, to demonstrate the utility of this approach, we apply the proposed method to the study of National-Eye-Institute-funded Telemedicine Approaches to Evaluating of Acute-Phase Retinopathy of Prematurity (e-ROP), for estimating accuracies of both the ophthalmologist examination and the image evaluation.

AR Expression Correlates with Distinctive Clinicopathological and Genomic Features in Breast Cancer Regardless of ESR1 Expression Status.

Androgen receptor (AR) expression is frequently observed in breast cancer, but its association with estrogen receptor (ER) expression in breast cancer remains unclear. This study analyzed the clinicopathological and molecular features associated with AR negativity in both ER-positive and ER-negative breast cancer, trying to elucidate the molecular correlation between AR and ER. Our results showed that AR negativity was associated with different clinicopathological characteristics and molecular features in ER-positive and ER-negative breast cancer. Moreover, AR-positive breast cancer has better clinicopathological features than AR-negative breast cancer, especially in the ER-negative subtype. These results suggest that the role of AR in ER-negative breast cancer is distinctive from that in ER-positive breast cancer.