A Comparison of Minimally Invasive Surgical Techniques and Standard Open Discectomy for Lumbar Disc Herniation: A Network Meta-analysis.

BACKGROUND: Lumbar disc herniation is a common spinal disease that causes low back pain; surgery is required when conservative treatment is ineffective. There is a growing demand for minimally invasive surgery in younger patient populations due to their fear of significant damage and a long recovery period following standard open discectomy. The development history of minimally invasive surgery is relatively short, and no gold standard has been established. OBJECTIVES: We aimed to find, via a network meta-analysis, the best treatment for low back pain in younger patient populations. STUDY DESIGN: Network meta-analysis. METHODS: The PubMed, Embase, Cochrane Library, and Web of Science databases were searched. Data quality was evaluated using RevMan 5.3 (The Nordic Cochrane Centre for The Cochrane Collaboration), while STATA 14.0 (StataCorp LLC) was used for the network meta-analysis and to merge data on the Visual Analog Scale (VAS) score, Oswestry Disability Index (ODI) score, complication, blood loss, reoperation rate, and function score. RESULTS: We included 50 randomized controlled trials, involving 7 interventions; heterogeneity and inconsistency were acceptable. Comparatively, microendoscopic discectomy and percutaneous endoscopic lumbar discectomy were the best surgical procedures from the aspects of VAS score and ODI score, while standard open discectomy was the worst one from the aspect of ODI score. Regarding complications, tubular discectomy was preferred with the fewest complications. Additionally, microendoscopic discectomy outperformed other surgical procedures in reducing blood loss and reoperation rate. LIMITATIONS: First, follow-up data were not reported in all included studies, and the follow-up time varied from several months to 8 years, which affected the results accuracy of our study to some extent. Second, there were some nonsurgical factors that also affected the self-reported outcomes, such as rehabilitation and pain management, which also brought a certain bias in our study results. CONCLUSIONS: Compared to standard open discectomy, minimally invasive surgical procedures not only achieve satisfactory efficacy, but also microendoscopic discectomy and percutaneous endoscopic lumbar discectomy can obtain a more satisfactory short-term VAS score and ODI score. Microendoscopic discectomy has significant advantages in blood loss and reoperation rate, and tubular discectomy has fewer postoperative complications.

Field-free spin-orbit torque switching in ferromagnetic trilayers at sub-ns timescales.

Current-induced spin torques enable the electrical control of the magnetization with low energy consumption. Conventional magnetic random access memory (MRAM) devices rely on spin-transfer torque (STT), this however limits MRAM applications because of the nanoseconds incubation delay and associated endurance issues. A potential alternative to STT is spin-orbit torque (SOT). However, for practical, high-speed SOT devices, it must satisfy three conditions simultaneously, i.e., field-free switching at short current pulses, short incubation delay, and low switching current. Here, we demonstrate field-free SOT switching at sub-ns timescales in a CoFeB/Ti/CoFeB ferromagnetic trilayer, which satisfies all three conditions. In this trilayer, the bottom magnetic layer or its interface generates spin currents with polarizations in both in-plane and out-of-plane components. The in-plane component reduces the incubation time, while the out-of-plane component realizes field-free switching at a low current. Our results offer a field-free SOT solution for energy-efficient scalable MRAM applications.

Field-free switching of perpendicular magnetization by two-dimensional PtTe2/WTe2 van der Waals heterostructures with high spin Hall conductivity.

The key challenge of spin-orbit torque applications lies in exploring an excellent spin source capable of generating out-of-plane spins while exhibiting high spin Hall conductivity. Here we combine PtTe2 for high spin conductivity and WTe2 for low crystal symmetry to satisfy the above requirements. The PtTe2/WTe2 bilayers exhibit a high in-plane spin Hall conductivity σs,y ≈ 2.32 × 105 × h/2e Ω-1 m-1 and out-of-plane spin Hall conductivity σs,z ≈ 0.25 × 105 × h/2e Ω-1 m-1, where h is the reduced Planck's constant and e is the value of the elementary charge. The out-of-plane spins in PtTe2/WTe2 bilayers enable the deterministic switching of perpendicular magnetization at room temperature without magnetic fields, and the power consumption is 67 times smaller than that of the Pt control case. The high out-of-plane spin Hall conductivity is attributed to the conversion from in-plane spin to out-of-plane spin, induced by the crystal asymmetry of WTe2. Our work establishes a low-power perpendicular magnetization manipulation based on wafer-scale two-dimensional van der Waals heterostructures.

Risk Assessment of the Possible Intermediate Host Role of Pigs for Coronaviruses with a Deep Learning Predictor.

Swine coronaviruses (CoVs) have been found to cause infection in humans, suggesting that Suiformes might be potential intermediate hosts in CoV transmission from their natural hosts to humans. The present study aims to establish convolutional neural network (CNN) models to predict host adaptation of swine CoVs. Decomposing of each ORF1ab and Spike sequence was performed with dinucleotide composition representation (DCR) and other traits. The relationship between CoVs from different adaptive hosts was analyzed by unsupervised learning, and CNN models based on DCR of ORF1ab and Spike were built to predict the host adaptation of swine CoVs. The rationality of the models was verified with phylogenetic analysis. Unsupervised learning showed that there is a multiple host adaptation of different swine CoVs. According to the adaptation prediction of CNN models, swine acute diarrhea syndrome CoV (SADS-CoV) and porcine epidemic diarrhea virus (PEDV) are adapted to Chiroptera, swine transmissible gastroenteritis virus (TGEV) is adapted to Carnivora, porcine hemagglutinating encephalomyelitis (PHEV) might be adapted to Primate, Rodent, and Lagomorpha, and porcine deltacoronavirus (PDCoV) might be adapted to Chiroptera, Artiodactyla, and Carnivora. In summary, the DCR trait has been confirmed to be representative for the CoV genome, and the DCR-based deep learning model works well to assess the adaptation of swine CoVs to other mammals. Suiformes might be intermediate hosts for human CoVs and other mammalian CoVs. The present study provides a novel approach to assess the risk of adaptation and transmission to humans and other mammals of swine CoVs.

Variable selection for mixed panel count data under the proportional mean model.

Mixed panel count data have attracted increasing attention in medical research based on event history studies. When such data arise, one either observes the number of event occurrences or only knows whether the event has happened or not over an observation period. In this article, we discuss variable selection in event history studies given such complex data, for which there does not seem to exist an established procedure. For the problem, we propose a penalized likelihood variable selection procedure and for the implementation, an expectation-maximization algorithm is developed with the use of the coordinate descent algorithm in the M-step. Furthermore, the oracle property of the proposed method is established, and a simulation study is performed and indicates that the proposed method works well in practical scenarios. Finally, the method is applied to identify the risk factors associated with medical non-adherence arising from the Sequenced Treatment Alternatives to Relieve Depression Study.

A preliminary screening system for diabetes based on in-car electronic nose.

Studies have found differences in the concentration of volatile organic compounds in the breath of diabetics and healthy people, prompting attention to the use of devices such as electronic noses to detect diabetes. In this study, we explored the design of a non-invasive diabetes preliminary screening system that uses a homemade electronic nose sensor array to detect respiratory gas markers. In the algorithm part, two feature extraction methods were adopted, gradient boosting method was used to select promising feature subset, and then particle swarm optimization algorithm was introduced to extract 24 most effective features, which reduces the number of sensors by 56% and saves the system cost. Respiratory samples were collected from 120 healthy subjects and 120 diabetic subjects to assess the system performance. Random forest algorithm was used to classify and predict electronic nose data, and the accuracy can reach 93.33%. Experimental results show that on the premise of ensuring accuracy, the system has low cost and small size after the number of sensors is optimized, and it is easy to install on in-car. It provides a more feasible method for the preliminary screening of diabetes on in-car and can be used as an assistant to the existing detection methods.

Calculation of high-order harmonic generation of atoms and molecules by combining time series prediction and neural networks.

High-order harmonic generation (HHG) from the interaction of ultra-intense laser pulses with atoms is an important tabletop short-wave coherent light source. Accurate quantum simulations of it present large computational difficulties due to multi-electron multidimensional effects. In this paper, the time-dependent response of hydrogen atoms is calculated using a time-series prediction scheme, the HHG spectrum is reconstructed very accurately. The accuracy of the forecasting is further improved by using a neural network scheme. This scheme is also applied to the simulation of the harmonic emission on multi-electron systems, and the applicability of the scheme is confirmed by the harmonic calculation of complex systems. This method is expected to simulate the nonlinear dynamic process of multi-electron atoms and molecules irradiated by intense laser pulses quickly and accurately.

Role of Long Noncoding RNAs in Smoking-Induced Lung Cancer: An In Silico Study.

The prevalence of lung cancer induced by cigarette smoking has increased over time. Long noncoding (lnc) RNAs, regulatory factors that play a role in human diseases, are commonly dysregulated in lung cancer. Cigarette smoking is closely related to changes in lncRNA expression, which can affect lung cancer. Herein, we assess the mechanism of lung cancer initiation induced by smoking. To calculate the impact of smoking on the survival of patients with lung cancer, we extracted data from The Cancer Genome Atlas and Gene Expression Omnibus databases and identified the differentially expressed genes in the lung cancer tissue compared to the normal lung tissue. Genes positively and negatively associated with smoking were identified. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Cytoscape analyses were performed to determine the function of the genes and the effects of smoking on the immune microenvironment. lncRNAs corresponding to smoking-associated genes were identified, and a smoking-related lncRNA model was constructed using univariate and multivariate Cox analyses. This model was used to assess the survival of and potential risk in patients who smoked. During screening, 562 differentially expressed genes were identified, and we elucidated that smoking affected the survival of patients 4.5 years after the diagnosis of lung cancer. Furthermore, genes negatively associated with smoking were closely associated with immunity. Twelve immune cell types were also found to infiltrate differentially in smokers and nonsmokers. Thus, the smoking-associated lncRNA model is a good predictor of survival and risk in smokers and may be used as an independent prognostic factor for lung cancer.

Enhanced Energy Density at a Low Electric Field in PVDF-Based Heterojunctions Sandwiched with High Ion-Polarized BTO Films.

Inorganic/organic dielectric composites with outstanding energy storage properties at a low electric field possess the advantages of low operating voltage and small probability of failure. Composites filled with two-dimensional inorganic nanosheets have attracted much attention owing to their fewer interfacial defects caused by the agglomeration of fillers. Continuous oxide films with a preferred orientation can play a significant role in enhancing energy storage. The challenge is to prepare large-sized, freestanding, single-crystal, ferroelectric oxide films and to combine them with polymers. In this work, a well-developed water-dissolvent process was used to transfer millimeter-sized (100)-oriented BaTiO3 (BTO) films. Poly(vinylidene fluoride) (PVDF)-based heterojunctions sandwiched with the single-crystal films were synthesized via the transferring process and an optimized hot-pressing technique. By virtue of high ion displacement polarization and inhibited conductive path formation of single-crystal BTO films, the energy storage density and efficiency of BTO/PVDF heterojunctions reach 1.56 J cm-3 and 71.2% at a low electric field of 120 MV m-1, which are much higher than those of pure PVDF and BTO nanoparticles/PVDF composite films, respectively. A finite-element simulation was employed to further confirm the experimental results. This work provides an effective approach to enhance energy storage properties in various polymer-based composites and opens the door to advanced dielectric capacitors.

Curative efficacy of surgical procedures for older patients with femoral neck fracture: a network meta-analysis and systematic review.

BACKGROUND: Femoral neck fractures have a higher incidence in older people with poor prognosis, inducing serious social problems. Common treatment methods include total hip arthroplasty, bipolar hemiarthroplasty, double-screw fixation, multiple-screw fixation, and dynamic hip system. METHODS: We searched through four electronic databases, including PubMed, Web of Science, Cochrane Library, and Embase databases, for articles regarding femoral neck fractures, bone screw, and hip prosthesis published up to February 11, 2020. All included articles were used for quality evaluation and data extraction. Extracted data were expressed as odds ratios or weighted mean differences, with 95% confidence intervals. We conducted a network meta-analysis for Harris hip score, complications, 1-year mortality rate, reoperation rate, intraoperative blood loss, and duration of operation using STATA version 16.0 software. RESULTS: Twenty-two randomized controlled trials and nine cohort studies included in this study involved 3861 patients. Total hip arthroplasty significantly improved the postoperative function of patients with femoral neck fractures. The surface under the cumulative ranking curve value of the Harris hip score for more than 1 year after total hip arthroplasty was 98.2. CONCLUSIONS: This meta-analysis indicated no significant difference in mortality among different treatment groups. Total hip arthroplasty can provide satisfactory outcomes in hip joint function, and double-screw fixation results in the lowest intraoperative risk. In general, total hip arthroplasty results in a lower incidence of adverse events and is especially recommended for patients with femoral neck fractures. This article has been retrospectively registered on the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) on November 27, 2020. Registration number: INPLASY2020110123.

Minimum Distribution Support Vector Clustering.

Support vector clustering (SVC) is a boundary-based algorithm, which has several advantages over other clustering methods, including identifying clusters of arbitrary shapes and numbers. Leveraged by the high generalization ability of the large margin distribution machine (LDM) and the optimal margin distribution clustering (ODMC), we propose a new clustering method: minimum distribution for support vector clustering (MDSVC), for improving the robustness of boundary point recognition, which characterizes the optimal hypersphere by the first-order and second-order statistics and tries to minimize the mean and variance simultaneously. In addition, we further prove, theoretically, that our algorithm can obtain better generalization performance. Some instructive insights for adjusting the number of support vector points are gained. For the optimization problem of MDSVC, we propose a double coordinate descent algorithm for small and medium samples. The experimental results on both artificial and real datasets indicate that our MDSVC has a significant improvement in generalization performance compared to SVC.

A comparison of analgesic techniques for total knee arthroplasty: A network meta-analysis.

STUDY OBJECTIVE: There is no established analgesic method for postoperative total knee arthroplasty. We comprehensively compared the analgesic methods for postoperative total knee arthroplasty. DESIGN: A network meta-analysis of randomised controlled trials was used to compare 18 interventions, which were ranked by six outcome indices, to select the best modality. SETTING: Postoperative recovery room and inpatient ward. PATIENTS: 98 randomised controlled trials involving 7452 patients (ASA I-III) were included in the final analysis. INTERVENTIONS: Studies that included the use of at least one of the following 12 nerve block(fascia iliaca compartment block (FIB), FNB, cFNB, single femoral nerve block (sFNB), adductor canal block (ACB), sciatic nerve block (SNB), obturator nerve block (ONB), continuous posterior lumbar plexus block (PSOAS), FNB + SNB, ACB + LIA, FNB + LIA, PCA + FNB). MEASUREMENTS: Pain intensity was compared using Visual Analogue Scale (VAS). Also, postoperative complications, function score, hospital length of stay, morphine consumption and patient satisfaction were measured. MAIN RESULTS: For visual analogue scale scores, continuous femoral nerve block (FNB) and FNB + sciatic nerve block (SNB) were the the most effective interventions. For reducing postoperative complications, fascia iliaca compartment block, FNB, SNB, and obturator nerve block showed the best results. For reducing postoperative morphine consumption, adductor canal block (ACB) + local infiltration analgesia (LIA) and FNB + SNB were preferred. For function scores (range of motion, Timed-Up-and-Go test), ACB and LIA were optimal choices. For reducing hospital length of stay and patient satisfaction, ACB + LIA and FNB + LIA were best, respectively. CONCLUSIONS: Peripheral nerve block, especially FNB and ACB, is a better option than other analgesic methods, and its combination with other methods can be beneficial. Peripheral nerve block is a safe and effective postoperative analgesia method. However, our findings can only provide objective evidence. Clinicians should choose the treatment course based on the individual patient's condition and clinical situation.

Regression Analysis of Case-cohort Studies in the Presence of Dependent Interval Censoring.

The case-cohort design is widely used as a means of reducing the cost in large cohort studies, especially when the disease rate is low and covariate measurements may be expensive, and has been discussed by many authors. In this paper, we discuss regression analysis of case-cohort studies that produce interval-censored failure time with dependent censoring, a situation for which there does not seem to exist an established approach. For inference, a sieve inverse probability weighting estimation procedure is developed with the use of Bernstein polynomials to approximate the unknown baseline cumulative hazard functions. The proposed estimators are shown to be consistent and the asymptotic normality of the resulting regression parameter estimators are established. A simulation study is conducted to assess the finite sample properties of the proposed approach and indicates that it works well in practical situations. The proposed method is applied to an HIV/AIDS case-cohort study that motivated this investigation.

The landscape of different molecular modules in an immune microenvironment during tuberculosis infection.

Tuberculosis is a chronic inflammatory disease caused by Mycobacterium tuberculosis. When tuberculosis invades the human body, innate immunity is the first line of defense. However, how the innate immune microenvironment responds remains unclear. In this research, we studied the function of each type of cell and explained the principle of an immune microenvironment. Based on the differences in the innate immune microenvironment, we modularized the analysis of the response of five immune cells and two structural cells. The results showed that in the innate immune stress response, the genes CXCL3, PTGS2 and TNFAIP6 regulated by the nuclear factor kappa B(NK-KB) pathway played a crucial role in fighting against tuberculosis. Based on the active pathway algorithm, each immune cell showed metabolic heterogeneity. Besides, after tuberculosis infection, structural cells showed a chemotactic immunity effect based on the co-expression immunoregulatory module.

Gene expression barcode values reveal a potential link between Parkinson's disease and gastric cancer.

Gastric cancer is a disease that develops from the lining of the stomach, whereas Parkinson's disease is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. Although these two diseases seem to be distinct from each other, increasing evidence suggests that they might be linked. To explore the linkage between these two diseases, differentially expressed genes between the diseased people and their normal controls were identified using the barcode algorithm. This algorithm transforms actual gene expression values into barcode values comprised of 1's (expressed genes) and 0's (silenced genes). Once the overlapped differentially expressed genes were identified, their biological relevance was investigated. Thus, using the gene expression profiles and bioinformatics methods, we demonstrate that Parkinson's disease and gastric cancer are indeed linked. This research may serve as a pilot study, and it will stimulate more research to investigate the relationship between gastric cancer and Parkinson's disease from the perspective of gene profiles and their functions.

Photovoltaic modulation of ferromagnetism within a FM metal/P-N junction Si heterostructure.

Obtaining small, fast, and energy-efficient spintronic devices requires a new way of manipulating spin states in an effective manner. Here, a prototype photovoltaic spintronic device with a p-n junction Si wafer is proposed which generates photo-induced electrons and changes the ferromagnetism by interfacial charge doping. A ferromagnetic resonance field change of 48.965 mT and 11.306 mT is achieved in Co and CoFeB thin films under sunlight illumination, respectively. The transient reflection (TR) analysis and the first principles calculation reveal the photovoltaic electrons that are doped into the magnetic layer and alter its Fermi level, correspondingly. This finding provides a new method of magnetism modulation and demonstrates a solar-driven spintronic device with abundant energy supply, which may further expand the landscape of spintronics research.

Photovoltaic Control of Ferromagnetism for Flexible Spintronics.

The demand for low-power flexible spintronics for sensing, communicating, and data processing applications boosts an intense search for novel ways of controlling magnetism. In this work, a photovoltaic controllable flexible spintronic device within a Kapton/Ta/Co/(PC71BM/PTB7-Th)/Pt heterostructure was demonstrated, and the magnetic anisotropy change of this flexible heterostructure as a function of the external light radiation and strain was quantitatively determined. 150 mW/cm2 white light illumination induced 489 Oe out-of-plane ferromagnetic resonance field modulation, which was attributed to the photogenerated electron doping in the cobalt film. The chemical contamination effect and the interfacial oxidation effect during the photovoltaic doping process were eliminated. Moreover, it was found that the working function of the thin-film electrodes were different from the bulk values via an ultraviolet photoelectron spectroscopy test. Our results on flexible photovoltaic spintronics systems will invigorate the research toward the development of solar-driven energy-efficient spintronics.

Platelet-rich plasma versus hyaluronic acid in the treatment of knee osteoarthritis: A meta-analysis.

BACKGROUND: This meta-analysis focuses on the controversial efficacy and safety of platelet-rich plasma (PRP) as compared with hyaluronic acid (HA) in the clinical treatment of knee osteoarthritis. We have attempted to provide an evidence-based medicine protocol for the conservative treatment of knee osteoarthritis. In addition, we included the latest relevant literature in this meta-analysis, and a staging study was conducted to compare the therapeutic effects of PRP and HA for knee osteoarthritis over different time periods. METHODS: An online computer search with "platelet-rich plasma" and "knee osteoarthritis" as search terms was conducted in the PubMed, EMBASE, and Cochrane Library databases. We conducted a quality assessment of the retrieved literature and extracted the following indicators: visual analog scale (VAS) score, subjective International Knee Documentation Committee (IKDC) score, Western Ontario and McMaster Universities (WOMAC) score, Knee Injury and Osteoarthritis Outcome Score (KOOS), and adverse events. RevMan5.3 software was used to determine the effect sizes, and indicators were compared across studies at three different time points from the administration of treatment. RESULTS: A total of 14 randomized controlled trials (RCTs) involving 1350 patients were included. Long-term VAS, IKDC, WOMAC-Pain, WOMAC-Stiffness, WOMAC-Physical Function, and WOMAC-Total scores at each time point were higher in the PRP group than in the HA group. There were no significant differences in the remaining indicators between the two groups. CONCLUSION: Compared with HA, PRP offers obvious advantages in the conservative treatment of knee osteoarthritis. Treatment with PRP can reduce long-term pain and improve knee joint function with no additional risks. Therefore, PRP can be widely used for the conservative treatment of knee osteoarthritis.

Efficacy and safety of erlotinib combined with bevacizumab in the treatment of non-small cell lung cancer: A systematic review and meta-analysis.

BACKGROUND: Non-small cell lung cancer (NSCLC) has a poor prognosis despite conventional treatments of surgery, radiotherapy, and chemotherapy. Small-molecule tyrosine kinase inhibitors acting on epidermal growth factor receptor (EGFR) have shown high efficacy and low toxicity for NSCLC. In particular, combining erlotinib with the VEGF antibody bevacizumab has therapeutic value in NSCLC, but the drugs' separate effects as monotherapy and any adverse outcomes of combination therapy remain unclear. OBJECTIVES: To determine the efficacy and safety of erlotinib and bevacizumab for NSCLC, we conducted a meta-analysis and systematic review of randomized controlled trials. DATA SOURCES: PubMed, Embase, Web of Science, and Cochrane databases were searched using keywords and manual review. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTIONS: We reviewed randomized controlled trials on the use of erlotinib combined with bevacizumab in adult patients with NSCLC, including data on outcome measures of overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and adverse events. STUDY APPRAISAL AND SYNTHESIS METHODS: After quality assessment, datasets were evaluated for heterogeneity. In the event of significant heterogeneity, a random-effects model was used to assess the overall outcome measures as a result of treatments. Subgroup analysis was conducted to evaluate the source of heterogeneity on PFS. RESULTS: Compared with erlotinib or bevacizumab alone, the combined treatment did not significantly prolong OS (95% confidence interval [CI] = 0.84-1.11; P = .62) or increase the ORR (95% CI = 0.91-1.20; P = .52), but significantly improved PFS (95% CI = 0.58-0.73; P < .001). This improvement was especially notable in patients with the following characteristics: Eastern Cooperative Oncology Group Performance Status score of 0 or 1, female, no smoking history, adenocarcinoma, and EGFR Exon19 deletion or Exon21 Leu858Arg mutation. Combination therapy significantly increased incidence of grade 1-2 hypertension (20.3% vs 6.3%, 95% CI 1.73-5.88; P < .01) and severe diarrhea (10% vs 3.2%, 95% CI 1.36-6.60; P = .01). LIMITATIONS: The low number of available randomized controlled trials could influence interpretation. CONCLUSIONS: Compared with erlotinib or bevacizumab monotherapy, their combination effectively prolongs PFS but increases incidence of adverse events in NSCLC patients.

Nonparametric tests for stratified additive hazards model based on current status data.

Stratified regression models are commonly employed when study subjects may come from possibly different strata such as different medical centers, and for the situation, one common question of interest is to test the existence of the stratum effect. To address this, there exists some literature on the testing of the stratum effects under the framework of the proportional hazards model when one observes right-censored data or interval-censored data. In this paper, we consider the situation under the additive hazards model when one faces current status data, for which there does not seem to exist an established test procedure. The asymptotic distributions of the proposed test procedure are provided. Also a simulation study is performed to evaluate the performance of the proposed method and indicates that it works well for practical situations. The approach is applied to a set of real current status data from a tumorigenicity study.