A Passive WiFi Source Localization System based on Fine-grained Power-based Trilateration

Indoor localization systems become more interesting for researchers because of the attractiveness of business cases in various application fields. A WiFi-based passive localization system can provide user location information to third-party providers of positioning services. However, indoor localization techniques are prone to multipath and Non-Line Of Sight (NLOS) propagation, which lead to significant performance degradation. To overcome these problems, we provide a passive localization system for WiFi targets with several improved algorithms for localization. Through Software Defined Radio (SDR) techniques, we extract Channel Impulse Response (CIR) information at the physical layer. CIR is later adopted to mitigate the multipath fading problem. We propose to use a Nonlinear Regression (NLR) method to relate the filtered power information to propagation distances, which significantly improves the ranging accuracy compared to the commonly used log-distance path loss model. To mitigate the influence of ranging errors, a new trilateration algorithm is designed as well by combining Weighted Centroid and Constrained Weighted Least Square (WC-CWLS) algorithms. Experiment results show that our algorithm is robust against ranging errors and outperforms the linear least square algorithm and weighted centroid algorithm.

Small Cell Carcinoma of the Urinary Bladder: A Retrospective, Multicenter Rare Cancer Network Study of 107 Patients

PURPOSE Small cell carcinomas of the bladder (SCCB) account for fewer than 1% of all urinary bladder tumors. There is no consensus regarding the optimal treatment for SCCB. METHODS AND MATERIALS Fifteen academic Rare Cancer Network medical centers contributed SCCB cases. The eligibility criteria were as follows: pure or mixed SCC; local, locoregional, and metastatic stages; and age ≥18 years. The overall survival (OS) and disease-free survival (DFS) were calculated from the date of diagnosis according to the Kaplan-Meier method. The log-rank and Wilcoxon tests were used to analyze survival as functions of clinical and therapeutic factors. RESULTS The study included 107 patients (mean [±standard deviation, SD] age, 69.6 [±10.6] years; mean follow-up time, 4.4 years) with primary bladder SCC, with 66% of these patients having pure SCC. Seventy-two percent and 12% of the patients presented with T2-4N0M0 and T2-4N1-3M0 stages, respectively, and 16% presented with synchronous metastases. The most frequent curative treatments were radical surgery and chemotherapy, sequential chemotherapy and radiation therapy, and radical surgery alone. The median (interquartile range, IQR) OS and DFS times were 12.9 months (IQR, 7-32 months) and 9 months (IQR, 5-23 months), respectively. The metastatic, T2-4N0M0, and T2-4N1-3M0 groups differed significantly (P=.001) in terms of median OS and DFS. In a multivariate analysis, impaired creatinine clearance (OS and DFS), clinical stage (OS and DFS), a Karnofsky performance status <80 (OS), and pure SCC histology (OS) were independent and significant adverse prognostic factors. In the patients with nonmetastatic disease, the type of treatment (ie radical surgery with or without adjuvant chemotherapy vs conservative treatment) did not significantly influence OS or DFS (P=.7). CONCLUSIONS The prognosis for SCCB remains poor. The finding that radical cystectomy did not influence DFS or OS in the patients with nonmetastatic disease suggests that conservative treatment is appropriate in this situation.

Older patients with low Charlson score and high-risk prostate cancer benefit from radical prostatectomy

INTRODUCTION The aim of the study was to identify the appropriate level of Charlson comorbidity index (CCI) in older patients (>70 years) with high-risk prostate cancer (PCa) to achieve survival benefit following radical prostatectomy (RP). METHODS We retrospectively analyzed 1008 older patients (>70 years) who underwent RP with pelvic lymph node dissection for high-risk prostate cancer (preoperative prostate-specific antigen >20 ng/mL or clinical stage ≥T2c or Gleason ≥8) from 14 tertiary institutions between 1988 and 2014. The study population was further grouped into CCI < 2 and ≥2 for analysis. Survival rate for each group was estimated with Kaplan-Meier method and competitive risk Fine-Gray regression to estimate the best explanatory multivariable model. Area under the curve (AUC) and Akaike information criterion were used to identify ideal 'Cut off' for CCI. RESULTS The clinical and cancer characteristics were similar between the two groups. Comparison of the survival analysis using the Kaplan-Meier curve between two groups for non-cancer death and survival estimations for 5 and 10 years shows significant worst outcomes for patients with CCI ≥ 2. In multivariate model to decide the appropriate CCI cut-off point, we found CCI 2 has better AUC and p value in log rank test. CONCLUSION Older patients with fewer comorbidities harboring high-risk PCa appears to benefit from RP. Sicker patients are more likely to die due to non-prostate cancer-related causes and are less likely to benefit from RP.

Pasteurization of Apple Cider with UV Irradiation

In a period of increasing concern about food safety, food poisoning outbreaks where unpasterurized apple cider or apple juice was found contaminated with Escherichia coli 0157:H7 reinforces the need for using the best technologies in apple cider production. Most apple cider is sold as an unpasteurized raw product. Because of their acidity, it was believed that juice products do not usually contain microorganisms such as E. coli 0157:H7, Salmonella, and Crytosporidium. Yet all of these foodborne pathogens are capable of being transmitted in unpasteurized juices. It is known that these pathogens can survive for several weeks in a variety of acidic juices. Although heat pasteurization is probably the best method to eliminate these pathogens, it is not the most desirable method as it changes sensory properties and also is very costly for small to mid-sized apple cider processors. Pasteurization of apple cider with Ultraviolet Irradiation (UV) is a potential alternative to heat pasteurization. Germicidal W irradiation is effective in inactivating microorganisms without producing undesirable by-products and changing sensory properties. Unpasteurized raw apple cider from a small local processor was purchased for this study. The effects of physical parameters, exposure time and dosage on the W treatment efficacy were examined as well as the effects of the UV light on apple cider quality. W light with principal energy at a wavelength of 254.7 nm, was effective in reducing bacteria (E .coli, ATCC 25922) inoculated apple cider. The W dosage absorbed by the apple cider was mathematically calculated. A radiation dose of 8,777 μW-s/cm2 reduced bacteria an average of 2.20 logs and in multiple passes, the FDA mandated 5-log reduction was achieved. Sensory analysis showed there was no significant difference between the W treated and non-treated cider. Experiments with W treated apple cider indicated a significant (p < 0.01) extension of product shelf life through inhibition of yeast and mold growth. The extension of the researched performed is applicable to other fruit juice processing operations.

Traditional linkage analysis in admixed families

Currently there is no general method to study the impact of population admixture within families on the assumptions of random mating and consequently, Hardy-Weinberg equilibrium (HWE) and linkage equilibrium (LE) and on the inference obtained from traditional linkage analysis. ^ First, through simulation, the effect of admixture of two populations on the log of the odds (LOD) score was assessed, using Prostate Cancer as the typical disease model. Comparisons between simulated mixed and homogeneous families were performed. LOD scores under both models of admixture (within families and within a data set of homogeneous families) were closest to the homogeneous family scores of the population having the highest mixing proportion. Random sampling of families or ascertainment of families with disease affection status did not affect this observation, nor did the mode of inheritance (dominant/recessive) or sample size. ^ Second, after establishing the effect of admixture on the LOD score and inference for linkage, the presence of induced disequilibria by population admixture within families was studied and an adjustment procedure was developed. The adjustment did not force all disequilibria to disappear but because the families were adjusted for the population admixture, those replicates where the disequilibria exist are no longer affected by the disequilibria in terms of maximization for linkage. Furthermore, the adjustment was able to exclude uninformative families or families that had such a high departure from HWE and/or LE that their LOD scores were not reliable. ^ Together these observations imply that the presence of families of mixed population ancestry impacts linkage analysis in terms of the LOD score and the estimate of the recombination fraction. ^

Toxics Release Inventory facilities and childhood cancer: Geographic information systems based approach

Purpose. To examine the association between living in proximity to Toxics Release Inventory (TRI) facilities and the incidence of childhood cancer in the State of Texas. ^ Design. This is a secondary data analysis utilizing the publicly available Toxics release inventory (TRI), maintained by the U.S. Environmental protection agency that lists the facilities that release any of the 650 TRI chemicals. Total childhood cancer cases and childhood cancer rate (age 0-14 years) by county, for the years 1995-2003 were used from the Texas cancer registry, available at the Texas department of State Health Services website. Setting: This study was limited to the children population of the State of Texas. ^ Method. Analysis was done using Stata version 9 and SPSS version 15.0. Satscan was used for geographical spatial clustering of childhood cancer cases based on county centroids using the Poisson clustering algorithm which adjusts for population density. Pictorial maps were created using MapInfo professional version 8.0. ^ Results. One hundred and twenty five counties had no TRI facilities in their region, while 129 facilities had at least one TRI facility. An increasing trend for number of facilities and total disposal was observed except for the highest category based on cancer rate quartiles. Linear regression analysis using log transformation for number of facilities and total disposal in predicting cancer rates was computed, however both these variables were not found to be significant predictors. Seven significant geographical spatial clusters of counties for high childhood cancer rates (p<0.05) were indicated. Binomial logistic regression by categorizing the cancer rate in to two groups (<=150 and >150) indicated an odds ratio of 1.58 (CI 1.127, 2.222) for the natural log of number of facilities. ^ Conclusion. We have used a unique methodology by combining GIS and spatial clustering techniques with existing statistical approaches in examining the association between living in proximity to TRI facilities and the incidence of childhood cancer in the State of Texas. Although a concrete association was not indicated, further studies are required examining specific TRI chemicals. Use of this information can enable the researchers and public to identify potential concerns, gain a better understanding of potential risks, and work with industry and government to reduce toxic chemical use, disposal or other releases and the risks associated with them. TRI data, in conjunction with other information, can be used as a starting point in evaluating exposures and risks. ^

Outcome-based adaptive randomization for binary data in clinical trials---Compare and contrast

Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing in some well known adaptive randomization procedures. The four urn models studied are Randomized Play-the-Winner (RPW), Randomized Pôlya Urn (RPU), Birth and Death Urn with Immigration (BDUI), and Drop-the-Loses Urn (DL). Two sequential estimation methods, the sequential maximum likelihood estimation (SMLE) and the doubly adaptive biased coin design (DABC), are simulated at three optimal allocation targets that minimize the expected number of failures under the assumption of constant variance of simple difference (RSIHR), relative risk (ORR), and odds ratio (OOR) respectively. Log likelihood ratio test and three Wald-type tests (simple difference, log of relative risk, log of odds ratio) are compared in different adaptive procedures. ^ Simulation results indicates that although RPW is slightly better in assigning more patients to the superior treatment, the DL method is considerably less variable and the test statistics have better normality. When compared with SMLE, DABC has slightly higher overall response rate with lower variance, but has larger bias and variance in parameter estimation. Additionally, the test statistics in SMLE have better normality and lower type I error rate, and the power of hypothesis testing is more comparable with the equal randomization. Usually, RSIHR has the highest power among the 3 optimal allocation ratios. However, the ORR allocation has better power and lower type I error rate when the log of relative risk is the test statistics. The number of expected failures in ORR is smaller than RSIHR. It is also shown that the simple difference of response rates has the worst normality among all 4 test statistics. The power of hypothesis test is always inflated when simple difference is used. On the other hand, the normality of the log likelihood ratio test statistics is robust against the change of adaptive randomization procedures. ^

Response to chemotherapy, recurrence and survival in advanced-stage ovarian, fallopian tube and primary peritoneal cancer patients with non-Ashkenazi Jewish BRCA mutations, compared to those without

Objectives. Previous studies have shown a survival advantage in ovarian cancer patients with Ashkenazi-Jewish (AJ) BRCA founder mutations, compared to sporadic ovarian cancer patients. The purpose of this study was to determine if this association exists in ovarian cancer patients with non-Ashkenazi Jewish BRCA mutations. In addition, we sought to account for possible "survival bias" by minimizing any lead time that may exist between diagnosis and genetic testing. ^ Methods. Patients with stage III/IV ovarian, fallopian tube, or primary peritoneal cancer and a non-Ashkenazi Jewish BRCA1 or 2 mutation, seen for genetic testing January 1996-July 2007, were identified from genetics and institutional databases. Medical records were reviewed for clinical factors, including response to initial chemotherapy. Patients with sporadic (non-hereditary) ovarian, fallopian tube, or primary peritoneal cancer, without family history of breast or ovarian cancer, were compared to similar cases, matched by age, stage, year of diagnosis, and vital status at time interval to BRCA testing. When possible, 2 sporadic patients were matched to each BRCA patient. An additional group of unmatched, sporadic ovarian, fallopian tube and primary peritoneal cancer patients was included for a separate analysis. Progression-free (PFS) & overall survival (OS) were calculated by the Kaplan-Meier method. Multivariate Cox proportional hazards models were calculated for variables of interest. Matched pairs were treated as clusters. Stratified log rank test was used to calculate survival data for matched pairs using paired event times. Fisher's exact test, chi-square, and univariate logistic regression were also used for analysis. ^ Results. Forty five advanced-stage ovarian, fallopian tube and primary peritoneal cancer patients with non-Ashkenazi Jewish (non-AJ) BRCA mutations, 86 sporadic-matched and 414 sporadic-unmatched patients were analyzed. Compared to the sporadic-matched and sporadic-unmatched ovarian cancer patients, non-AJ BRCA mutation carriers had longer PFS (17.9 & 13.8 mos. vs. 32.0 mos., HR 1.76 [95% CI 1.13–2.75] & 2.61 [95% CI 1.70–4.00]). In relation to the sporadic- unmatched patients, non-AJ BRCA patients had greater odds of complete response to initial chemotherapy (OR 2.25 [95% CI 1.17–5.41]) and improved OS (37.6 mos. vs. 101.4 mos., HR 2.64 [95% CI 1.49–4.67]). ^ Conclusions. This study demonstrates a significant survival advantage in advanced-stage ovarian cancer patients with non-AJ BRCA mutations, confirming the previous studies in the Jewish population. Our efforts to account for "survival bias," by matching, will continue with collaborative studies. ^

Use of light intensity, temperature, and humidity to verify exposure location

Research studies on the association between exposures to air contaminants and disease frequently use worn dosimeters to measure the concentration of the contaminant of interest. But investigation of exposure determinants requires additional knowledge beyond concentration, i.e., knowledge about personal activity such as whether the exposure occurred in a building or outdoors. Current studies frequently depend upon manual activity logging to record location. This study's purpose was to evaluate the use of a worn data logger recording three environmental parameters—temperature, humidity, and light intensity—as well as time of day, to determine indoor or outdoor location, with an ultimate aim of eliminating the need to manually log location or at least providing a method to verify such logs. For this study, data collection was limited to a single geographical area (Houston, Texas metropolitan area) during a single season (winter) using a HOBO H8 four-channel data logger. Data for development of a Location Model were collected using the logger for deliberate sampling of programmed activities in outdoor, building, and vehicle locations at various times of day. The Model was developed by analyzing the distributions of environmental parameters by location and time to establish a prioritized set of cut points for assessing locations. The final Model consisted of four "processors" that varied these priorities and cut points. Data to evaluate the Model were collected by wearing the logger during "typical days" while maintaining a location log. The Model was tested by feeding the typical day data into each processor and generating assessed locations for each record. These assessed locations were then compared with true locations recorded in the manual log to determine accurate versus erroneous assessments. The utility of each processor was evaluated by calculating overall error rates across all times of day, and calculating individual error rates by time of day. Unfortunately, the error rates were large, such that there would be no benefit in using the Model. Another analysis in which assessed locations were classified as either indoor (including both building and vehicle) or outdoor yielded slightly lower error rates that still precluded any benefit of the Model's use.^

Extension of k-ratio methods to rank-based analyses

An extension of k-ratio multiple comparison methods to rank-based analyses is described. The new method is analogous to the Duncan-Godbold approximate k-ratio procedure for unequal sample sizes or correlated means. The close parallel of the new methods to the Duncan-Godbold approach is shown by demonstrating that they are based upon different parameterizations as starting points.^ A semi-parametric basis for the new methods is shown by starting from the Cox proportional hazards model, using Wald statistics. From there the log-rank and Gehan-Breslow-Wilcoxon methods may be seen as score statistic based methods.^ Simulations and analysis of a published data set are used to show the performance of the new methods. ^

REGULATION OF TOXIN SYNTHESIS BY CLOSTRIDIUM DIFFICILE

Clostridium difficile is the leading definable cause of nosocomial diarrhea worldwide due to its virulence, multi-drug resistance, spore-forming ability, and environmental persistence. The incidence of C. difficile infection (CDI) has been increasing exponentially in the last decade. Virulent strains of C. difficile produce either toxin A and/or toxin B, which are essential for the pathogenesis of this bacterium. Current methods for diagnosing CDI are mostly qualitative tests that detect the bacterium, the toxins, or the toxin genes. These methods do not differentiate virulent C. difficile strains that produce active toxins from non-virulent strains that do not produce toxins or produce inactive toxins. Based on the knowledge that C. difficile toxins A and B cleave a substrate that is stereochemically similar to the native substrate of the toxins, uridine diphosphoglucose, a quantitative, cost-efficient assay, the Cdifftox activity assay, was developed to measure C. difficile toxin activity. The concept behind the activity assay was modified to develop a novel, rapid, sensitive, and specific assay for C. difficile toxins in the form of a selective and differential agar plate culture medium, the Cdifftox Plate assay (CDPA). This assay combines in a single step the specific identification of C. difficile strains and the detection of active toxin(s). The CDPA was determined to be extremely accurate (99.8% effective) at detecting toxin-producing strains based on the analysis of 528 C. difficile isolates selected from 50 tissue culture cytotoxicity assay-positive clinical stool samples. This new assay advances and improves the culture methodology in that only C. difficile strains will grow on this medium and virulent strains producing active toxins can be differentiated from non-virulent strains. This new method reduces the time and effort required to isolate and confirm toxin-producing C. difficile strains and provides a clinical isolate for antibiotic susceptibility testing and strain typing. The Cdifftox activity assay was used to screen for inhibitors of toxin activity. Physiological levels of the common human conjugated bile salt, taurocholate, was found to inhibit toxin A and B in vitro activities. When co-incubated ex vivo with purified toxin B, taurocholate protected Caco-2 colonic epithelial cells from the damaging effects of the toxin. Furthermore, using a caspase-3 detection assay, taurocholate reduced the extent of toxin B-induced Caco-2 cell apoptosis. These results suggest that bile salts can be effective in protecting the gut epithelium from C. difficile toxin damage, thus, the delivery of physiologic amounts of taurocholate to the colon, where it is normally in low concentration, could be useful in CDI treatment. These findings may help to explain why bile rich small intestine is spared damage in CDI, while the bile salt poor colon is vulnerable in CDI. Toxin synthesis in C. difficile occurs during the stationary phase, but little is known about the regulation of these toxins. It was hypothesized that C. difficile toxin synthesis is regulated by a quorum sensing mechanism. Two lines of evidence supported this hypothesis. First, a small (KDa), diffusible, heat-stable toxin-inducing activity accumulates in the medium of high-density C. difficile cells. This conditioned medium when incubated with low-density log-phase cells causes them to produce toxin early (2-4 hrs instead of 12-16 hrs) and at elevated levels when compared with cells grown in fresh medium. These data suggested that C. difficile cells extracellularly release an inducing molecule during growth that is able to activate toxin synthesis prematurely and demonstrates for the first time that toxin synthesis in C. difficile is regulated by quorum signaling. Second, this toxin-inducing activity was partially purified from high-density stationary-phase culture supernatant fluid by HPLC and confirmed to induce early toxin synthesis, even in C. difficile virulent strains that over-produce the toxins. Mass spectrometry analysis of the purified toxin-inducing fraction from HPLC revealed a cyclic compound with a mass of 655.8 Da. It is anticipated that identification of this toxin-inducing compound will advance our understanding of the mechanism involved in the quorum-dependent regulation of C. difficile toxin synthesis. This finding should lead to the development of even more sensitive tests to diagnose CDI and may lead to the discovery of promising novel therapeutic targets that could be harnessed for the treatment C. difficile infections.

A simulation study using the hybrid statistic and the meta-analysis t-test for data with matched and unmatched subjects in the interim analysis of clinical trials

An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^

Age -period -cohort analysis: An extension of Cox's lifetable regression with time -dependent covariates

It is well known that an identification problem exists in the analysis of age-period-cohort data because of the relationship among the three factors (date of birth + age at death = date of death). There are numerous suggestions about how to analyze the data. No one solution has been satisfactory. The purpose of this study is to provide another analytic method by extending the Cox's lifetable regression model with time-dependent covariates. The new approach contains the following features: (1) It is based on the conditional maximum likelihood procedure using a proportional hazard function described by Cox (1972), treating the age factor as the underlying hazard to estimate the parameters for the cohort and period factors. (2) The model is flexible so that both the cohort and period factors can be treated as dummy or continuous variables, and the parameter estimations can be obtained for numerous combinations of variables as in a regression analysis. (3) The model is applicable even when the time period is unequally spaced.^ Two specific models are considered to illustrate the new approach and applied to the U.S. prostate cancer data. We find that there are significant differences between all cohorts and there is a significant period effect for both whites and nonwhites. The underlying hazard increases exponentially with age indicating that old people have much higher risk than young people. A log transformation of relative risk shows that the prostate cancer risk declined in recent cohorts for both models. However, prostate cancer risk declined 5 cohorts (25 years) earlier for whites than for nonwhites under the period factor model (0 0 0 1 1 1 1). These latter results are similar to the previous study by Holford (1983).^ The new approach offers a general method to analyze the age-period-cohort data without using any arbitrary constraint in the model. ^

Description of sampling sites in Northern Russia

The youngest ice marginal zone between the White Sea and the Ural mountains is the W-E trending belt of moraines called the Varsh-Indiga-Markhida-Harbei-Halmer-Sopkay, here called the Markhida line. Glacial elements show that it was deposited by the Kara Ice Sheet, and in the west, by the Barents Ice Sheet. The Markhida moraine overlies Eemian marine sediments, and is therefore of Weichselian age. Distal to the moraine are Eemian marine sediments and three Palaeolithic sites with many C-14 dates in the range 16-37 ka not covered by till, proving that it represents the maximum ice sheet extension during the Weichselian. The Late Weichselian ice limit of M. G. Grosswald is about 400 km (near the Urals more than 700 km) too far south. Shorelines of ice dammed Lake Komi, probably dammed by the ice sheet ending at the Markhida line, predate 37 ka. We conclude that the Markhida line is of Middle/Early Weichselian age, implying that no ice sheet reached this part of Northern Russia during the Late Weichselian. This age is supported by a series of C-14 and OSL dates inside the Markhida line all of >45 ka. Two moraine loops protrude south of the Markhida line; the Laya-Adzva and Rogavaya moraines. These moraines are covered by Lake Komi sediments, and many C-14 dates on mammoth bones inside the moraines are 26-37 ka. The morphology indicates that the moraines are of Weichselian age, but a Saalian age cannot be excluded. No post-glacial emerged marine shorelines are found along the Barents Sea coast north of the Markhida line.