Estimating the Complier Average Causal Effect in a Meta-Analysis of Randomized Clinical Trials With Binary Outcomes Accounting for Noncompliance: A Generalized Linear Latent and Mixed Model Approach.

Noncompliance, a common problem in randomized clinical trials (RCTs), can bias estimation of the effect of treatment receipt using a standard intention-to-treat analysis. The complier average causal effect (CACE) measures the effect of an intervention in the latent subpopulation that would comply with their assigned treatment. Although several methods have been developed to estimate the CACE in analyzing a single RCT, methods for estimating the CACE in a meta-analysis of RCTs with noncompliance await further development. This article reviews the assumptions needed to estimate the CACE in a single RCT and proposes a frequentist alternative for estimating the CACE in a meta-analysis, using a generalized linear latent and mixed model with SAS software (SAS Institute, Inc.). The method accounts for between-study heterogeneity using random effects. We implement the methods and describe an illustrative example of a meta-analysis of 10 RCTs evaluating the effect of receiving epidural analgesia in labor on cesarean delivery, where noncompliance varies dramatically between studies. Simulation studies are used to evaluate the performance of the proposed method.

Initial Solution Generation and Diversified Variable Picking in Local Search for (Weighted) Partial MaxSAT.

The (weighted) partial maximum satisfiability ((W)PMS) problem is an important generalization of the classic problem of propositional (Boolean) satisfiability with a wide range of real-world applications. In this paper, we propose an initialization and a diversification strategy to improve local search for the (W)PMS problem. Our initialization strategy is based on a novel definition of variables' structural entropy, and it aims to generate a solution that is close to a high-quality feasible one. Then, our diversification strategy picks a variable in two possible ways, depending on a parameter: continuing to pick variables with the best benefits or focusing on a clause with the greatest penalty and then selecting variables probabilistically. Based on these strategies, we developed a local search solver dubbed ImSATLike, as well as a hybrid solver ImSATLike-TT, and experimental results on (weighted) partial MaxSAT instances in recent MaxSAT Evaluations show that they outperform or have nearly the same performances as state-of-the-art local search and hybrid competitors, respectively, in general. Furthermore, we carried out experiments to confirm the individual impacts of each proposed strategy.

Evaluation of Sensitivity to Phoxim and Cypermethrin in an Endoparasitoid, Meteorus pulchricornis (Wesmael) (Hymenoptera: Braconidae), and Its Parasitization Efficiency Under Insecticide Stress.

Insecticides can have consequences for beneficial arthropods. Insect parasitoids can contact insecticides through direct exposure spray droplets or residues on crop foliage. Here, we focus on better understand the response of Meteorus pulchricornis (Wesmael), a parasitoid wasp of lepidopteran pests, and its detoxification mechanisms on stress caused by phoxim and cypermethrin. Hence, we determined the dose-mortality curves and estimating the sublethal concentrations (LC30 and LC50). Then, we applied the sublethal concentrations against adult parasitoids to assess its survival, parasitism efficacy, and also developmental and morphometric parameters of their offspring. Simultaneously, we check the activities of glutathione S-transferase (GST), acetylcholinesterase (AChE), and peroxidase (POD) after sublethal exposure of both insecticides, which has measured until 48 h after treatment. Overall, phoxim and cypermethrin exhibited acute lethal activity toward the parasitoid with LC50 values 4.608 and 8.570 mg/liter, respectively. Also, we detect that LC30 was able to trigger the enzymatic activity of GST, AChE, and POD, suggesting a potential detoxification mechanism. However, even when subjected to sublethal exposure, our results indicate strong negatives effects, in particular for phoxim, which has affected the parasitism efficacy and also the developmental and morphometric parameters of M. pulchricornis offspring. Therefore, it can be concluded that both phoxim and cypermethrin have negative impacts on M. pulchricornis and we suggest cautioning their use and the need for semifield and field assessments to confirm such an impact.

A Structural Entropy Measurement Principle of Propositional Formulas in Conjunctive Normal Form.

The satisfiability (SAT) problem is a core problem in computer science. Existing studies have shown that most industrial SAT instances can be effectively solved by modern SAT solvers while random SAT instances cannot. It is believed that the structural characteristics of different SAT formula classes are the reasons behind this difference. In this paper, we study the structural properties of propositional formulas in conjunctive normal form (CNF) by the principle of structural entropy of formulas. First, we used structural entropy to measure the complex structure of a formula and found that the difficulty solving the formula is related to the structural entropy of the formula. The smaller the compressing information of a formula, the more difficult it is to solve the formula. Secondly, we proposed a λ-approximation strategy to approximate the structural entropy of large formulas. The experimental results showed that the proposed strategy can effectively approximate the structural entropy of the original formula and that the approximation ratio is more than 92%. Finally, we analyzed the structural properties of a formula in the solution process and found that a local search solver tends to select variables in different communities to perform the next round of searches during a search and that the structural entropy of a variable affects the probability of the variable being flipped. By using these conclusions, we also proposed an initial candidate solution generation strategy for a local search for SAT, and the experimental results showed that this strategy effectively improves the performance of the solvers CCAsat and Sparrow2011 when incorporated into these two solvers.

Normative noninvasive bladder function measurements in healthy women: A systematic review and meta-analysis.

AIM: To conduct an evidence synthesis of normative reference values for bladder function parameters in women. METHODS: We conducted a systematic review and meta-analysis of studies reporting bladder function parameters obtained from noninvasive tests in healthy women. Seven databases were searched for relevant studies from inception through December 2018, with manual searching of reference lists. We included English language articles that provided quantitative data on urination frequency, voided and postvoid residual volumes, and uroflowmetry results in women without lower urinary tract symptoms. Study selection, data extraction, and quality assessment were undertaken by at least two independent reviewers. Random-effects meta-analytic models were used to derive study-level pooled mean estimates and 95% confidence intervals. RESULTS: A total of 24 studies (N = 3090 women, age range, 18-91 years) met eligibility criteria. Pooled mean estimates of bladder function parameters were: 6.6 daytime voids (95% confidence interval (95% CI), 6.2, 7.0), 0.4 nighttime voids (95% CI, 0.0, 0.8), 1577 mL for 24-hour voided volume (95% CI 1428,1725); 12 mL for postvoid residual volume (95% CI, 4, 20); and 28 mL/sec for maximum flow rate (95% CI, 27,30). Between-study heterogeneity was high for all outcomes (I2 = 61.1-99.6%), but insufficient data were available to explore reasons for this high heterogeneity (eg, differences by age). CONCLUSION: Although summary mean estimates of bladder function parameters were calculated, the wide heterogeneity across studies precludes generalization of these estimates to all healthy women. Further research is needed to determine normative reference values within specific groups, such as those defined by age.

Phylogenetic signals in pest abundance and distribution range of spider mites.

BACKGROUND: Attributes of pest species like host range are frequently reported as being evolutionarily constrained and showing phylogenetic signal. Because these attributes in turn could influence the abundance and impact of species, phylogenetic information could be useful in predicting the likely status of pests. In this study, we used regional (China) and global datasets to investigate phylogenetic patterns in occurrence patterns and host ranges of spider mites, which constitute a pest group of many cropping systems worldwide. RESULTS: We found significant phylogenetic signal in relative abundance and distribution range both at the regional and global scales. Relative abundance and range size of spider mites were positively correlated with host range, although these correlations became weaker after controlling for phylogeny. CONCLUSIONS: The results suggest that pest impacts are evolutionarily constrained. Information that is easily obtainable - including the number of known hosts and phylogenetic position of the mites - could therefore be useful in predicting future pest risk of species.

Mitochondrial variation in small brown planthoppers linked to multiple traits and probably reflecting a complex evolutionary trajectory.

While it has been proposed in several taxa that the mitochondrial genome is associated with adaptive evolution to different climatic conditions, making links between mitochondrial haplotypes and organismal phenotypes remains a challenge. Mitonuclear discordance occurs in the small brown planthopper (SBPH), Laodelphax striatellus, with one mitochondrial haplogroup (HGI) more common in the cold climate region of China relative to another form (HGII) despite strong nuclear gene flow, providing a promising model to investigate climatic adaptation of mitochondrial genomes. We hypothesized that cold adaptation through HGI may be involved, and considered mitogenome evolution, population genetic analyses, and bioassays to test this hypothesis. In contrast to our hypothesis, chill-coma recovery tests and population genetic tests of selection both pointed to HGII being involved in cold adaptation. Phylogenetic analyses revealed that HGII is nested within HGI, and has three nonsynonymous changes in ND2, ND5 and CYTB in comparison to HGI. These molecular changes likely increased mtDNA copy number, cold tolerance and fecundity of SBPH, particularly through a function-altering amino acid change involving M114T in ND2. Nuclear background also influenced fecundity and chill recovery (i.e., mitonuclear epistasis) and protein modelling indicates possible nuclear interactions for the two nonsynonymous changes in ND2 and CYTB. The high occurrence frequency of HGI in the cold climate region of China remains unexplained, but several possible reasons are discussed. Overall, our study points to a link between mtDNA variation and organismal-level evolution and suggests a possible role of mitonuclear interactions in maintaining mtDNA diversity.

A Bayesian hierarchical model estimating CACE in meta-analysis of randomized clinical trials with noncompliance.

Noncompliance to assigned treatment is a common challenge in analysis and interpretation of randomized clinical trials. The complier average causal effect (CACE) approach provides a useful tool for addressing noncompliance, where CACE is defined as the average difference in potential outcomes for the response in the subpopulation of subjects who comply with their assigned treatments. In this article, we present a Bayesian hierarchical model to estimate the CACE in a meta-analysis of randomized clinical trials where compliance may be heterogeneous between studies. Between-study heterogeneity is taken into account with study-specific random effects. The results are illustrated by a re-analysis of a meta-analysis comparing the effect of epidural analgesia in labor versus no or other analgesia in labor on the outcome cesarean section, where noncompliance varied between studies. Finally, we present simulations evaluating the performance of the proposed approach and illustrate the importance of including appropriate random effects and the impact of over- and under-fitting.

Incidence of Facultative Bacterial Endosymbionts in Spider Mites Associated with Local Environments and Host Plants.

Spider mites are frequently associated with multiple endosymbionts whose infection patterns often exhibit spatial and temporal variation. However, the association between endosymbiont prevalence and environmental factors remains unclear. Here, we surveyed endosymbionts in natural populations of the spider mite, Tetranychus truncatus, in China, screening 935 spider mites from 21 localities and 12 host plant species. Three facultative endosymbiont lineages, Wolbachia, Cardinium, and Spiroplasma, were detected at different infection frequencies (52.5%, 26.3%, and 8.6%, respectively). Multiple endosymbiont infections were observed in most local populations, and the incidence of individuals with the Wolbachia-Spiroplasma coinfection was higher than expected from the frequency of each infection within a population. Endosymbiont infection frequencies exhibited associations with environmental factors: Wolbachia infection rates increased at localities with higher annual mean temperatures, while Cardinium and Spiroplasma infection rates increased at localities from higher altitudes. Wolbachia was more common in mites from Lycopersicon esculentum and Glycine max compared to those from Zea mays This study highlights that host-endosymbiont interactions may be associated with environmental factors, including climate and other geographically linked factors, as well as the host's food plant.IMPORTANCE The aim of this study was to examine the incidence of endosymbiont distribution and the infection patterns in spider mites. The main findings are that multiple endosymbiont infections were more common than expected and that endosymbiont infection frequencies were associated with environmental factors. This work highlights that host-endosymbiont interactions need to be studied within an environmental and geographic context.

Occupation and lower urinary tract symptoms in women: A rapid review and meta-analysis from the PLUS research consortium.

AIMS: Chronic, infrequent voiding may be a risk factor for lower urinary tract symptoms (LUTS) in women. To inform this hypothesis, we conducted a rapid literature review and meta-analysis of LUTS by occupation as an indirect measure of infrequent voiding behaviors. METHODS: Two independent medical librarians searched Pubmed.gov studies (1990-2017) on adult women for occupations, industries, and workplace environment and LUTS outcomes: overactive bladder (OAB), urinary incontinence (UI), urinary tract infections (UTIs), and individual voiding and storage LUTS. Two authors reviewed full text articles meeting content criteria. Among studies with similar UI definitions, we estimated the prevalence of monthly UI using a random effects meta-analysis model. RESULTS: Of 1078 unique citations identified, 113 underwent full article review and 33 met inclusion criteria. Twenty-six of these studies examined specific occupation groups, including nurses/midwives (n = 6 studies), healthcare workers/support staff (n = 6), military personnel (n = 3), teachers (n = 3), and other groups (n = 7), whereas eight compared findings across broad occupation groups. UI was reported in 30 studies (23% using validated measures), OAB in 6 (50% validated), and UTIs in 2 (non-validated). In pooled models, the degree of heterogeneity was too high (I2 = 96.9-99.2%) among the studies to perform valid prevalence estimates for LUTS. CONCLUSIONS: Current literature limits the ability to evaluate LUTS by occupation types. Future studies should characterize voiding frequency and toilet access in a consistent manner by occupation and explore its relation to LUTS development.

Prevalence of Intracranial Atherosclerotic Stenosis Using High-Resolution Magnetic Resonance Angiography in the General Population: The Atherosclerosis Risk in Communities Study.

BACKGROUND AND PURPOSE: Intracranial atherosclerotic stenosis (ICAS) is a common cause of stroke, but little is known about its epidemiology. We studied the prevalence of ICAS and its association with vascular risk factors using high-resolution magnetic resonance angiography in a US cardiovascular cohort. METHODS: The Atherosclerosis Risk in Communities (ARIC) study recruited participants from 4 US communities from 1987 to 1989. Using stratified sampling, we selected 1980 participants from visit 5 (2011-2013) for high-resolution 3T-magnetic resonance angiography. All images were analyzed in a centralized laboratory, and ICAS was graded as: no stenosis, <50% stenosis, 50% to 69% stenosis, 70% to 99% stenosis, and complete occlusion. We calculated per-vessel and per-person prevalence of ICAS (weighted for n=6538 visit 5 participants) and also estimated the US prevalence. We used multivariable logistic regression to identify variables independently associated with ICAS. RESULTS: Subjects who had an adequate magnetic resonance angiography (n=1765) were aged 67 to 90 years, 41% were men, 70% were white, and 29% were black. ICAS was prevalent in 31% of participants and 9% had ICAS ≥50%. Estimated US prevalence of ICAS ≥50% for 65 to 90 years old was 8% for whites and 12% for blacks. Older age, black race, higher systolic blood pressure, and higher low-density lipoprotein cholesterol levels were associated with increased odds of ICAS, whereas higher levels of high-density lipoprotein cholesterol and use of cholesterol-lowering medications were associated with decreased odds of ICAS. Body mass index and smoking were not associated with ICAS. CONCLUSIONS: The prevalence of ICAS in older adults is high, and it could be a target for primary prevention of stroke and dementia in this population.

A Bayesian approach to estimating causal vaccine effects on binary post-infection outcomes.

To estimate causal effects of vaccine on post-infection outcomes, Hudgens and Halloran (2006) defined a post-infection causal vaccine efficacy estimand VEI based on the principal stratification framework. They also derived closed forms for the maximum likelihood estimators of the causal estimand under some assumptions. Extending their research, we propose a Bayesian approach to estimating the causal vaccine effects on binary post-infection outcomes. The identifiability of the causal vaccine effect VEI is discussed under different assumptions on selection bias. The performance of the proposed Bayesian method is compared with the maximum likelihood method through simulation studies and two case studies - a clinical trial of a rotavirus vaccine candidate and a field study of pertussis vaccination. For both case studies, the Bayesian approach provided similar inference as the frequentist analysis. However, simulation studies with small sample sizes suggest that the Bayesian approach provides smaller bias and shorter confidence interval length.

Data completeness as an unmeasured confounder in dialysis facility performance comparison with 1-year follow-up
.

;Aims: Standardized mortality and hospitalization ratios (SMRs, SHRs) are used to measure dialysis facility performance in the US, with adjustment for demographics and comorbid conditions derived from the end-stage renal disease (ESRD) Medical Evidence (ME) Report. Sensitivities are low for ME-based comorbidity, and levels of under-reporting may differ among facilities. We aimed to assess the effect of data inaccuracy on performance comparison. METHODS: Using the United States Renal Data System ESRD database, we included patients who initiated hemodialysis July 1 - December 31 in each of the years 2006 - 2010, had Medicare as primary payer, were aged ≥ 66 years, and had no prior transplant. Patients were followed from dialysis initiation to the earliest of death, transplant, modality change, or 1 year. SMRs and SHRs were calculated for for-profit/non-profit and rural/urban facilities for ME-based and claims-based comorbidity, separately. Cox models were used for expected number of deaths and piecewise Poison models for expected number of hospitalizations. Comorbidity agreement was measured by κ-statistic. Testing of differences between ME-based and claims-based SMRs/SHRs was performed by bootstrap. RESULTS: In all, 73,950 incident hemodialysis patients were included. κ-values for comorbidity agreement were low, < 0.5, except for diabetes (0.77). Percentages of claims-based comorbidity were similar for for-profit and non-profit facilities; ME-based comorbidity was lower for for-profit facilities. Differences between ME-based and claims-based SMRs/SHRs were statistically significant. Compared with ME-based SMRs/SHRs, claims-based ratios decreased 0.9/0.6% for for-profit and 1/0.7% for urban facilities and increased 3.4/2.8% for non-profit and 5.9/4.1% for rural facilities. CONCLUSIONS: Comorbidity data source may affect performance evaluation. The impact is larger for smaller groups.
.

Regulation of forkhead box O transcription factor by insulin signaling pathway controls the reproductive diapause of the lady beetle, Coccinella septempunctata.

In biological control programs, knowledge about diapause regulation in natural enemy insects provides important insight for improving long-term storage, transportation, and field adoption of these biological control agents. As a natural predator of agricultural pests, the lady beetle Coccinella septempunctata has been commercially mass-cultured and widely employed in pest management. In some insects, insulin signaling, in conjunction with the downstream transcription factor Forkhead box O (FoxO), are master regulators of multiple physiological processes involved in diapause, but it is unclear whether insulin signaling and FoxO affect the diapause of C. septempunctata. In this study, we use a combination of approaches to demonstrate that insulin signaling and FoxO mediate the diapause response in C. septempunctata. In diapausing beetles, application of exogenous insulin and knocking down expression of CsFoxo with RNA interference (RNAi) both rescued beetles from developmental arrest. In non-diapausing beetles, knocking down expression of the insulin receptor (CsInR) with RNA interference (RNAi) arrested ovarian development and decreased juvenile hormone (JH) content to levels comparable to the diapause state. Taken together, these results suggest that a shutdown of insulin signaling prompts the activation of the downstream FoxO gene, leading to the diapause phenotype.

A task scheduling algorithm with deadline constraints for distributed clouds in smart cities.

Computing technologies and 5G are helpful for the development of smart cities. Cloud computing has become an essential smart city technology. With artificial intelligence technologies, it can be used to integrate data from various devices, such as sensors and cameras, over the network in a smart city for management of the infrastructure and processing of Internet of Things (IoT) data. Cloud computing platforms provide services to users. Task scheduling in the cloud environment is an important technology to shorten computing time and reduce user cost, and thus has many important applications. Recently, a hierarchical distributed cloud service network model for the smart city has been proposed where distributed (micro) clouds, and core clouds are considered to achieve a better network architecture. Task scheduling in the model has attracted many researchers. In this article, we study a task scheduling problem with deadline constraints in the distributed cloud model and aim to reduce the communication network's data load and provide low-latency services from the cloud server in the local area, hence promoting the efficiency of cloud computing services for local users. To solve the task scheduling problem efficiently, we present an efficient local search algorithm to solve the problem. In the algorithm, a greedy search strategy is proposed to improve the current solutions iteratively. Moreover, randomized methods are used in selecting tasks and virtual machines for reassigning tasks. We carried out extensive computational experiments to evaluate the performance of our algorithm and compared experimental results with Swarm-based approaches, such as GA and PSO. The comparative results show that the proposed local search algorithm performs better than the comparative algorithms on the task scheduling problem.

Improving temporal smoothness and snapshot quality in dynamic network community discovery using NOME algorithm.

The goal of dynamic community discovery is to quickly and accurately mine the network structure for individuals with similar attributes for classification. Correct classification can effectively help us screen out more desired results, and it also reveals the laws of dynamic network changes. We propose a dynamic community discovery algorithm, NOME, based on node occupancy assignment and multi-objective evolutionary clustering. NOME adopts the multi-objective evolutionary algorithm MOEA/D framework based on decomposition, which can simultaneously decompose the two objective functions of modularization and normalized mutual information into multiple single-objective problems. In this algorithm, we use a Physarum-based network model to initialize populations, and each population represents a group of community-divided solutions. The evolution of the population uses the crossover and mutation operations of the genome matrix. To make the population in the evolution process closer to a better community division result, we develop a new strategy for node occupancy assignment and cooperate with mutation operators, aiming at the boundary nodes in the connection between the community and the connection between communities, by calculating the comparison node. The occupancy rate of the community with the neighbor node, the node is assigned to the community with the highest occupancy rate, and the authenticity of the community division is improved. In addition, to select high-quality final solutions from candidate solutions, we use a rationalized selection strategy from the external population size to obtain better time costs through smaller snapshot quality loss. Finally, comparative experiments with other representative dynamic community detection algorithms on synthetic and real datasets show that our proposed method has a better balance between snapshot quality and time cost.

Ecological Factors Associated with the Distribution of Bemisia tabaci Cryptic Species and Their Facultative Endosymbionts.

The sweetpotato whitefly, Bemisia tabaci species complex, comprises at least 44 morphologically indistinguishable cryptic species, whose endosymbiont infection patterns often varied at the spatial and temporal dimension. However, the effects of ecological factors (e.g., climatic or geographical factors) on the distribution of whitefly and the infection frequencies of their endosymbionts have not been fully elucidated. We, here, analyzed the associations between ecological factors and the distribution of whitefly and their three facultative endosymbionts (Candidatus Cardinium hertigii, Candidatus Hamiltonella defensa, and Rickettsia sp.) by screening 665 individuals collected from 29 geographical localities across China. The study identified eight B. tabaci species via mitochondrial cytochrome oxidase I (mtCOI) gene sequence alignment: two invasive species, MED (66.9%) and MEAM1 (12.2%), and six native cryptic species (20.9%), which differed in distribution patterns, ecological niches, and high suitability areas. The infection frequencies of the three endosymbionts in different cryptic species were distinct and multiple infections were relatively common in B. tabaci MED populations. Furthermore, the annual mean temperature positively affected Cardinium sp. and Rickettsia sp. infection frequencies in B. tabaci MED but negatively affected the quantitative distribution of B. tabaci MED, which indicates that Cardinium sp. and Rickettsia sp. maybe play a crucial role in the thermotolerance of B. tabaci MED, although the host whitefly per se exhibits no resistance to high temperature. Our findings revealed the complex effects of ecological factors on the expansion of the invasive whitefly.

Can carbon emission trading improve carbon emission performance? Evidence from a quasi-natural experiment in China.

Carbon emission trading policies play a key role in reducing carbon emissions through market-based mechanisms. In the context of China's carbon neutrality goals and carbon peaking targets, it is important to predict and evaluate the effectiveness of such policies. The combined impact of carbon trading policies on carbon emission reduction and economic output has not been well investigated in previous studies. In this study, the impact of carbon emission trading policies on regional carbon emission performance was assessed through mechanism analysis and empirical tests. The mechanism analysis showed that carbon emission intensity reduction relied on three mediating effects: technological innovation incentives, industrial structure optimization, and energy substitution. For the empirical test, the multi-time difference-in-differences (DID) method was adopted to study the impact using panel data from 30 provinces in China between 2005 and 2019. Moreover, the specific impact mechanism was further tested using mediating effects. The results showed that China's carbon trading policy has significantly affected the carbon emission performance of the pilot regions, and factors such as GDP per capita, urbanization level, and capital-labor ratio have notably contributed to the reduction of carbon emission intensity. The proportions of the three mediating effects in the total effect were estimated to be 60.98%, 23.17%, and 10.14%, respectively. This study provides an empirical approach to the study of the impact of carbon trading policy on carbon emission reduction and economic output and can serve as a reference for addressing climate change and alleviating conflicts between the environment and economic growth in similar regions.

Statistical modeling: Assessing the anatomic variability of knee joint space width.

Population-based knee joint space width (JSW) assessments are promising for the prevention and early diagnosis of osteoarthritis. This study aimed to establish the statistical shape and alignment model (SSAM) of knee joints for assessing anatomic variation in knee JSW in the healthy Chinese male population. CT scans of asymptomatic knee joints of healthy male participants (n = 107) were collected for manual segmentation to create mesh samples. The as-scanned positional error was reduced by a standard processing flow of deformable mesh registration. Principal component analysis (PCA) was performed to create a tibiofemoral SSAM that was trained on all mesh samples. The anatomic variability of the JSW in the healthy Chinese male population was then assessed using the SSAM with regression analysis and 3D analysis by color-coded mapping. Almost all PCA modes had a linear influence on the anatomic variation of the medial and lateral JSW. The JSW variability within the SSAM was mainly explained by mode 1 (45.1 % of variation), demonstrating that this mode had the greatest influence on JSW variation. 3D assessment of the JSW showed that the minimum medial JSW varied from 2.76 to 3.23 mm, and its site shifted a short distance on the medial tibial plateau. The root-mean-square fitting and generalization errors of the SSAM were below 1 mm. This study will benefit the design and optimization of prosthetic devices, and may be applicable to the prevention and early diagnosis of osteoarthritis.