Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021.

A phase I study of Mirvetuximab Soravtansine and gemcitabine in patients with FRα-positive recurrent ovarian, primary peritoneal, fallopian tube, or endometrial cancer, or triple negative breast cancer.

OBJECTIVE: Platinum-resistant epithelial ovarian cancer (EOC), recurrent endometrial cancer (EC), and triple negative breast cancer (TNBC) are difficult to treat after failing standard therapies. This phase I study evaluated mirvetuximab soravtansine (MIRV) and gemcitabine in patients with recurrent FRα-positive EOC, EC, or TNBC to determine the maximum tolerated dose (MTD)/recommended phase 2 dose (RP2D) (primary endpoint). METHODS: FRα-positive patients with platinum-resistant EOC, EC, or TNBC with ≤4 prior chemotherapy regimens (2 for EC) were enrolled. FRα expression requirement varied among eligible tumors and changed during the study. RESULTS: Twenty patients were enrolled; 17 were evaluable for DLT. Half the patients received ≥3 prior chemotherapy lines. Most EOC and EC patients (78%) were medium (50-74%) or high(75-100%) FRα expressors. TNBC patients were low (25-49%) FRα expressors. The MTD/RP2D was MIRV 6 mg/kg AIBW D1 and gemcitabine 800 mg/m2 IV, D1 and D8, every 21 days (Dose Level [DL] 3), where 5/7 patients demonstrated a partial response (PR) as their best response, including 2 confirmed ovarian responses whose time-to-progression and duration of response were 7.9/5.4 and 8.0/5.7 months respectively. Most common treatment-related adverse events at MTD were anemia and neutropenia (3/7 each, 43%), diarrhea, hypophosphatemia, thrombocytopenia, and leukopenia (2/7 each, 29%). DLTs were thrombocytopenia (DL1), oral mucositis (DL4) and diarrhea (DL4). Nine of 20 patients (45%; 95% CI: 21.1-68.9%) achieved PR as their best response, with 3/20 patients or 15% (95%CI, 0-32.1%) confirmed PR. CONCLUSION: MIRV and gemcitabine demonstrate promising activity in platinum resistant EOC at RP2D, but frequent hematologic toxicities.

Artificial neural networks for the prediction of solvation energies based on experimental and computational data.

The knowledge of thermodynamic properties for novel electrolyte formulations is of fundamental interest for industrial applications as well as academic research. Herewith, we present an artificial neural networks (ANN) approach for the prediction of solvation energies and entropies for distinct ion pairs in various protic and aprotic solvents. The considered feed-forward ANN is trained either by experimental data or computational results from conceptual density functional theory calculations. The proposed concept of mapping computed values to experimental data lowers the amount of time-consuming and costly experiments and helps to overcome certain limitations. Our findings reveal high correlation coefficients between predicted and experimental values which demonstrate the validity of our approach.

The Actor-Dueling-Critic Method for Reinforcement Learning.

Model-free reinforcement learning is a powerful and efficient machine-learning paradigm which has been generally used in the robotic control domain. In the reinforcement learning setting, the value function method learns policies by maximizing the state-action value (Q value), but it suffers from inaccurate Q estimation and results in poor performance in a stochastic environment. To mitigate this issue, we present an approach based on the actor-critic framework, and in the critic branch we modify the manner of estimating Q-value by introducing the advantage function, such as dueling network, which can estimate the action-advantage value. The action-advantage value is independent of state and environment noise, we use it as a fine-tuning factor to the estimated Q value. We refer to this approach as the actor-dueling-critic (ADC) network since the frame is inspired by the dueling network. Furthermore, we redesign the dueling network part in the critic branch to make it adapt to the continuous action space. The method was tested on gym classic control environments and an obstacle avoidance environment, and we design a noise environment to test the training stability. The results indicate the ADC approach is more stable and converges faster than the DDPG method in noise environments.

Neural network emulation of the human ventricular cardiomyocyte action potential for more efficient computations in pharmacological studies.

Computer models of the human ventricular cardiomyocyte action potential (AP) have reached a level of detail and maturity that has led to an increasing number of applications in the pharmaceutical sector. However, interfacing the models with experimental data can become a significant computational burden. To mitigate the computational burden, the present study introduces a neural network (NN) that emulates the AP for given maximum conductances of selected ion channels, pumps, and exchangers. Its applicability in pharmacological studies was tested on synthetic and experimental data. The NN emulator potentially enables massive speed-ups compared to regular simulations and the forward problem (find drugged AP for pharmacological parameters defined as scaling factors of control maximum conductances) on synthetic data could be solved with average root-mean-square errors (RMSE) of 0.47 mV in normal APs and of 14.5 mV in abnormal APs exhibiting early afterdepolarizations (72.5% of the emulated APs were alining with the abnormality, and the substantial majority of the remaining APs demonstrated pronounced proximity). This demonstrates not only very fast and mostly very accurate AP emulations but also the capability of accounting for discontinuities, a major advantage over existing emulation strategies. Furthermore, the inverse problem (find pharmacological parameters for control and drugged APs through optimization) on synthetic data could be solved with high accuracy shown by a maximum RMSE of 0.22 in the estimated pharmacological parameters. However, notable mismatches were observed between pharmacological parameters estimated from experimental data and distributions obtained from the Comprehensive in vitro Proarrhythmia Assay initiative. This reveals larger inaccuracies which can be attributed particularly to the fact that small tissue preparations were studied while the emulator was trained on single cardiomyocyte data. Overall, our study highlights the potential of NN emulators as powerful tool for an increased efficiency in future quantitative systems pharmacology studies.

Multi-cancer risk stratification based on national health data: a retrospective modelling and validation study.

BACKGROUND: Health care is experiencing a drive towards digitisation, and many countries are implementing national health data resources. Although a range of cancer risk models exists, the utility on a population level for risk stratification across cancer types has not been fully explored. We aimed to close this gap by evaluating pan-cancer risk models built on electronic health records across the Danish population with validation in the UK Biobank. METHODS: In this retrospective modelling and validation study, data for model development and internal validation were derived from the following Danish health registries: the Central Person Registry, the Danish National Patient Registry, the death registry, the cancer registry, and full-text medical records from secondary care records in the capital region. The development data included adults aged 16-86 years without previous malignant cancers in the time period from Jan 1, 1995, to Dec 31, 2014. The internal validation period was from Jan 1, 2015, to April 10, 2018, and the data included all adults without a previous indication of cancer aged 16-75 years on Dec 31, 2014. The external validation cohort from the UK Biobank included all adults without a previous indication of cancer aged 50-75 years. We used time-dependent Bayesian Cox hazard models built on the combined medical history of Danish individuals. A set of 1392 covariates from available clinical disease trajectories, text-mined basic health factors, and family histories were used to train predictive models of 20 major cancer types. The models were validated on cancer incidence between 2015 and 2018 across Denmark and on individuals in the UK Biobank. The primary outcomes were discrimination and calibration performance. FINDINGS: From the Danish registries, we included 6 732 553 individuals covering 60 million hospital visits, 90 million diagnoses, and a total of 193 million life-years between Jan 1, 1978, and April 10, 2018. Danish registry data covering the period from Jan 1, 2015, to April 10, 2018, were used to internally validate risk models, containing a total of 4 248 491 individuals who remained at risk of a primary malignant cancer diagnosis and 67 401 cancer cases recorded. For the external validation, we evaluated the same time period in the UK Biobank covering 377 004 individuals with 11 486 cancer cases. The predictive performance of the models on Danish data showed good discrimination (concordance index 0·81 [SD 0·08], ranging from 0·66 [95% CI 0·65-0·67] for cervix uteri cancer to 0·91 [0·90-0·92] for liver cancer). Performance was similar on the UK Biobank in a direct transfer when controlling for shifts in the age distribution (concordance index 0·66 [SD 0·08], ranging from 0·55 [95% CI 0·44-0·66] for cervix uteri cancer to 0·78 [0·77-0·79] for lung cancer). Cancer risks were associated, in addition to heritable components, with a broad range of preceding diagnoses and health factors. The best overall performance was seen for cancers of the digestive system (oesophageal, stomach, colorectal, liver, and pancreatic) but also thyroid, kidney, and uterine cancers. INTERPRETATION: Data available in national electronic health databases can be used to approximate cancer risk factors and enable risk predictions in most cancer types. Model predictions generalise between the Danish and UK health-care systems. With the emergence of multi-cancer early detection tests, electronic health record-based risk models could supplement screening efforts. FUNDING: Novo Nordisk Foundation and the Danish Innovation Foundation.

Neural network emulation of the human ventricular cardiomyocyte action potential: a tool for more efficient computation in pharmacological studies.

Computer models of the human ventricular cardiomyocyte action potential (AP) have reached a level of detail and maturity that has led to an increasing number of applications in the pharmaceutical sector. However, interfacing the models with experimental data can become a significant computational burden. To mitigate the computational burden, the present study introduces a neural network (NN) that emulates the AP for given maximum conductances of selected ion channels, pumps, and exchangers. Its applicability in pharmacological studies was tested on synthetic and experimental data. The NN emulator potentially enables massive speed-ups compared to regular simulations and the forward problem (find drugged AP for pharmacological parameters defined as scaling factors of control maximum conductances) on synthetic data could be solved with average root-mean-square errors (RMSE) of 0.47mV in normal APs and of 14.5mV in abnormal APs exhibiting early afterdepolarizations (72.5% of the emulated APs were alining with the abnormality, and the substantial majority of the remaining APs demonstrated pronounced proximity). This demonstrates not only very fast and mostly very accurate AP emulations but also the capability of accounting for discontinuities, a major advantage over existing emulation strategies. Furthermore, the inverse problem (find pharmacological parameters for control and drugged APs through optimization) on synthetic data could be solved with high accuracy shown by a maximum RMSE of 0.21 in the estimated pharmacological parameters. However, notable mismatches were observed between pharmacological parameters estimated from experimental data and distributions obtained from the Comprehensive in vitro Proarrhythmia Assay initiative. This reveals larger inaccuracies which can be attributed particularly to the fact that small tissue preparations were studied while the emulator was trained on single cardiomyocyte data. Overall, our study highlights the potential of NN emulators as powerful tool for an increased efficiency in future quantitative systems pharmacology studies.

Mechanoelectric effects in healthy cardiac function and under Left Bundle Branch Block pathology.

Mechanoelectric feedback (MEF) in the heart operates through several mechanisms which serve to regulate cardiac function. Stretch activated channels (SACs) in the myocyte membrane open in response to cell lengthening, while tension generation depends on stretch, shortening velocity, and calcium concentration. How all of these mechanisms interact and their effect on cardiac output is still not fully understood. We sought to gauge the acute importance of the different MEF mechanisms on heart function. An electromechanical computer model of a dog heart was constructed, using a biventricular geometry of 500K tetrahedral elements. To describe cellular behavior, we used a detailed ionic model to which a SAC model and an active tension model, dependent on stretch and shortening velocity and with calcium sensitivity, were added. Ventricular inflow and outflow were connected to the CircAdapt model of cardiovascular circulation. Pressure-volume loops and activation times were used for model validation. Simulations showed that SACs did not affect acute mechanical response, although if their trigger level was decreased sufficiently, they could cause premature excitations. The stretch dependence of tension had a modest effect in reducing the maximum stretch, and stroke volume, while shortening velocity had a much bigger effect on both. MEF served to reduce the heterogeneity in stretch while increasing tension heterogeneity. In the context of left bundle branch block, a decreased SAC trigger level could restore cardiac output by reducing the maximal stretch when compared to cardiac resynchronization therapy. MEF is an important aspect of cardiac function and could potentially mitigate activation problems.

A lower leg surrogate study to investigate the effect of quadriceps-hamstrings activation ratio on ACL tensile force.

OBJECTIVES: Many studies have investigated the relationship between muscle activation and tensile force of the anterior cruciate ligament. These studies lacked a holistic representation of the muscle status. For instance, they were limited with respect to the peak muscle forces, number of muscles, and possible muscle activation patterns. DESIGN: This study used a knee surrogate including ten muscles with motor-controlled muscle force activation crossing the knee joint, thus providing a fully muscle-supported knee joint. METHODS: Anterior cruciate ligament tensile force is measured in different knee flexion and extension movements to evaluate ratios of quadriceps/hamstring muscle activations in low hip angle setups. RESULTS: Increasing the extension of the leg increased anterior cruciate ligament tension forces. Different quadriceps/hamstring ratios had different effects on anterior cruciate ligament tension forces during unrestricted flexion and extension movements. This was dependent on the direction of movement. Sole hamstring activation increased the anterior cruciate ligament tensile forces in extension movements compared with flexion movements. Sole quadriceps activation provoked greater anterior cruciate ligament tensile forces in flexion than in extension. This was not prominent in the test in which the other muscle groups counteracted the dominant muscle group. CONCLUSIONS: The findings from the present study demonstrate that active hamstring activation can reduce the load on the anterior cruciate ligament, and the dominant quadriceps increase anterior cruciate ligament loads for knee flexions of less than 40°. Moreover, the anterior cruciate ligament is loaded differently in flexion or extension movements with flexion movements, resulting in higher anterior cruciate ligament loads.

An Integrated Workflow for Building Digital Twins of Cardiac Electromechanics-A Multi-Fidelity Approach for Personalising Active Mechanics.

Personalised computer models of cardiac function, referred to as cardiac digital twins, are envisioned to play an important role in clinical precision therapies of cardiovascular diseases. A major obstacle hampering clinical translation involves the significant computational costs involved in the personalisation of biophysically detailed mechanistic models that require the identification of high-dimensional parameter vectors. An important aspect to identify in electromechanics (EM) models are active mechanics parameters that govern cardiac contraction and relaxation. In this study, we present a novel, fully automated, and efficient approach for personalising biophysically detailed active mechanics models using a two-step multi-fidelity solution. In the first step, active mechanical behaviour in a given 3D EM model is represented by a purely phenomenological, low-fidelity model, which is personalised at the organ scale by calibration to clinical cavity pressure data. Then, in the second step, median traces of nodal cellular active stress, intracellular calcium concentration, and fibre stretch are generated and utilised to personalise the desired high-fidelity model at the cellular scale using a 0D model of cardiac EM. Our novel approach was tested on a cohort of seven human left ventricular (LV) EM models, created from patients treated for aortic coarctation (CoA). Goodness of fit, computational cost, and robustness of the algorithm against uncertainty in the clinical data and variations of initial guesses were evaluated. We demonstrate that our multi-fidelity approach facilitates the personalisation of a biophysically detailed active stress model within only a few (2 to 4) expensive 3D organ-scale simulations-a computational effort compatible with clinical model applications.

Dynamic Sparse Subspace Clustering for Evolving High-Dimensional Data Streams.

In an era of ubiquitous large-scale evolving data streams, data stream clustering (DSC) has received lots of attention because the scale of the data streams far exceeds the ability of expert human analysts. It has been observed that high-dimensional data are usually distributed in a union of low-dimensional subspaces. In this article, we propose a novel sparse representation-based DSC algorithm, called evolutionary dynamic sparse subspace clustering (EDSSC). It can cope with the time-varying nature of subspaces underlying the evolving data streams, such as subspace emergence, disappearance, and recurrence. The proposed EDSSC consists of two phases: 1) static learning and 2) online clustering. During the first phase, a data structure for storing the statistic summary of data streams, called EDSSC summary, is proposed which can better address the dilemma between the two conflicting goals: 1) saving more points for accuracy of subspace clustering (SC) and 2) discarding more points for the efficiency of DSC. By further proposing an algorithm to estimate the subspace number, the proposed EDSSC does not need to know the number of subspaces. In the second phase, a more suitable index, called the average sparsity concentration index (ASCI), is proposed, which dramatically promotes the clustering accuracy compared to the conventionally utilized SCI index. In addition, the subspace evolution detection model based on the Page-Hinkley test is proposed where the appearing, disappearing, and recurring subspaces can be detected and adapted. Extinct experiments on real-world data streams show that the EDSSC outperforms the state-of-the-art online SC approaches.

US-guided fine-needle aspiration of major salivary gland masses and adjacent lymph nodes: accuracy and impact on clinical decision making.

PURPOSE: To determine whether ultrasonography (US)-guided fine-needle aspiration (FNA) is an effective technique for diagnosing masses in the salivary gland and adjacent lymph nodes. MATERIALS AND METHODS: The institutional review board waived the requirement to obtain informed consent and approved this HIPAA-compliant retrospective study. Radiology records of 50 patients (28 female patients aged 25-85 years [median age, 58 years], 22 male patients aged 11-82 years [median age, 62 years]) who underwent 52 consecutive US-guided FNA procedures from 2004 to 2009 were reviewed. In 46 cases, lesions were sampled for biopsy under real-time US guidance by means of three passes with a 25-gauge needle. In six cases, two subsequent passes were performed with a 22-gauge needle after the first pass showed minimal or no aspirate. Findings from cytopathologic analysis, clinical follow-up, and surgery were evaluated and compared. RESULTS: A diagnostically adequate biopsy specimen was obtained in 48 of the 52 cases (92%). Among the 20 patients who underwent surgical intervention after diagnostic US-guided FNA findings, results of surgical-pathologic analysis helped confirm the cytologic diagnosis in 19 (95%). Twenty of the 50 patients (40%) were spared surgical intervention on the basis of findings from US-guided FNA. US-guided FNA did not result in any intra- or postprocedural complications. CONCLUSION: The diagnostic accuracy of US-guided FNA is similar to that of core needle biopsy, and there were no complications in this study. Information yielded with FNA cytology plays an integral role in clinical decision making in the management of masses in the major salivary glands and adjacent structures.

A heuristic model-based approach for compensating wind effects in ski jumping.

Wind influences the jump length in ski jumping, which raises questions about the fairness. To counteract the wind problem, the International Ski Federation has introduced a wind compensation system in 2009: time-averaged wind velocity components tangential to the landing slope are obtained from several sites along the landing slope, and these data are used in a linear statistical model for estimating the jump length effect of wind. This is considered in the total score of the ski jump. However, it has been shown that the jump length effect estimates can be inaccurate and misleading. The present article introduces an alternative mathematical wind compensation approach that is based on an accurate mechanistic model of the flight phase. This estimates the jump length effect as difference between the jump length of the real ski jump at the given wind condition and the computed jump length of the simulated ski jump at calm wind. Inputs for the computer simulation are the initial flight velocity and aerodynamic coefficients of the real ski jump that can be obtained from kinematic and wind velocity data collected during the flight. The initial flight velocity is readily available from the kinematic data and inverse dynamics can be used to compute the aerodynamic coefficients. The accuracy of the estimated jump length effect of the mechanistic model-based approach depends only on the measurement errors in the kinematic and wind velocity data, but not on inaccuracies of an approach that is based on a linear statistical model.

Validation Is Not Verification: Precise Terminology and Scientific Methods in Bioprocess Modeling.

Advanced statistical approaches and new modeling procedures for biopharmaceutical development and manufacturing have received increasing attention. With this forum article, we would like to highlight the need for a consistent terminology and the necessity for appropriate model validation strategies.

Generic and specific recurrent neural network models: Applications for large and small scale biopharmaceutical upstream processes.

The calculation of temporally varying upstream process outcomes is a challenging task. Over the last years, several parametric, semi-parametric as well as non-parametric approaches were developed to provide reliable estimates for key process parameters. We present generic and product-specific recurrent neural network (RNN) models for the computation and study of growth and metabolite-related upstream process parameters as well as their temporal evolution. Our approach can be used for the control and study of single product-specific large-scale manufacturing runs as well as generic small-scale evaluations for combined processes and products at development stage. The computational results for the product titer as well as various major upstream outcomes in addition to relevant process parameters show a high degree of accuracy when compared to experimental data and, accordingly, a reasonable predictive capability of the RNN models. The calculated values for the root-mean squared errors of prediction are significantly smaller than the experimental standard deviation for the considered process run ensembles, which highlights the broad applicability of our approach. As a specific benefit for platform processes, the generic RNN model is also used to simulate process outcomes for different temperatures in good agreement with experimental results. The high level of accuracy and the straightforward usage of the approach without sophisticated parameterization and recalibration procedures highlight the benefits of the RNN models, which can be regarded as promising alternatives to existing parametric and semi-parametric methods.

Genetic TPH2 variants and the susceptibility for migraine: association of a TPH2 haplotype with migraine without aura.

The serotonergic system plays a major role in the etiology of migraine. The rate-limiting enzyme in serotonin homeostasis and availability is tryptophan hydroxylase (TPH). The TPH2 isoform is responsible for the cerebral serotonin biosynthesis. To investigate the role of genetic variation in TPH2 in the pathogenesis of migraine eight haplotype tagging SNPs covering the whole TPH2 gene where chosen using Haploview and genotyped in 503 migraineurs and 515 healthy controls. Association analysis was performed on a single SNP and haplotype basis using χ² and logistic regression analysis. Single SNP analysis revealed a weak association with migraine, which did not remain after correction for multiple testing. Haplotype analyses revealed association of a haplotype with migraine without aura. Stratification by aura and triptan response did not reveal a positive association with the investigated polymorphisms. These results suggest a possible influence of genetic variation in TPH2 in the pathogenesis of migraine.

Interaction of Inhibitor of DNA binding 3 (Id3) with Gut-enriched Krüppel-like factor (GKLF) and p53 regulates proliferation of vascular smooth muscle cells.

Enhanced proliferation of vascular smooth muscle cells (VSMCs) is one of the key features of the pathogenesis of atherosclerosis. The helix-loop-helix protein Inhibitor of DNA binding 3 (Id3) contributes to regulation of VSMC proliferation in a redox-sensitive manner. We investigated the role of Id3 and its interaction with other redox-sensitive genes, the transcription factor Gut-enriched Krüppel-like factor (GKLF, KLF4) and the tumor suppressor gene p53 in the regulation of VSMC proliferation. Cultured rat aortic VSMCs were transfected with Id3 sense and antisense constructs. Overexpression of Id3 significantly enhanced VSMC proliferation. Id3 antisense transfection inhibited VSMC proliferation induced by the physiological stimuli insulin and platelet-derived growth factor (PDGF). Because p53 is essential for the regulation of proliferation processes, the effect of Id3 on p53 expression was investigated. Id3 overexpression led to decreased p53 protein expression. Co-transfection of p53 sense constructs inhibited the enhanced VSMC mitogenicity induced by Id3 sense transfection. GKLF overexpression, which causes growth arrest in VSMCs, reduced Id3 promoter activity and led to decreased Id3 expression. Id3-induced VSMC proliferation was abolished by GKLF sense co-transfection. Finally, strong Id3 expression was found in the neointima of human coronary artery atherosclerotic plaques but not in healthy coronary arteries. These findings reveal a relevant interaction of GKLF, Id3, and p53 for VSMC proliferation which might constitute a general mechanism of growth control in vascular cells.

Non-alcoholic steatohepatitis induces non-fibrosis-related portal hypertension associated with splanchnic vasodilation and signs of a hyperdynamic circulation in vitro and in vivo in a rat model.

INTRODUCTION: Steatosis, without fibrosis, may lead to changes in liver blood flow, which are poorly understood, and to date have not been correlated to portal pressure and related haemodynamics. AIMS: To study the temporal relation between progressive steatosis, portal pressure, systemic haemodynamics, vascular responsiveness, mesenteric and portal blood flow in methionine-choline-deficient diet (MCDD)-fed rats. METHODS: Male Wistar rats fed the MCDD were examined at week (w) 0-1-2-3-4-5-6-7-8, respectively, including systemic haemodynamics and portal pressure. At w0-4-8, in vivo blood flow was measured in the portal vein and the superior mesenteric artery. Dose-response curves to phenylephrine (PE) were established in abdominal aortic rings. RESULTS: Histology showed 100% steatosis from w3 on. Fibrosis was absent. Significant inflammation was nearly absent upon w4. Portal pressure slightly increased at w2, reached a maximum at w4 [9.4 +/- 0.3 vs 2.9 +/- 0.6 mmHg at w0 (P=0.003)] and remained stable upon w8. Mean arterial blood pressure (MABP) decreased from w2 on [98.7 +/- 5.7 mmHg on w4 compared with 123.8 +/- 1.8 on w0 (P=0.002)]. Portal flow increased from 1.85 +/- 0.11 to 3.07 +/- 0.44 ml/min/100 g on w0 and w8 respectively (P=0.039). Mesenteric artery flow increased from 3.40 +/- 0.26 to 4.56 +/- 0.30 ml/min/100 g on w0 and w8 respectively (P=0.043). Vascular responsiveness to PE gradually decreased from 138 +/- 3% on w0 to 110 +/- 5% on w4 (P=0.013). CONCLUSION: Steatohepatitis induces significant portal hypertension (PHT) in the absence of fibrosis, associated with an increase in mesenteric arterial and portal venous flow, arterial hyporesponsiveness to vasoconstrictors and a decrease in MABP, indicating the presence of splanchnic vasodilation and hyperdynamic circulation. These alterations resemble those seen in cirrhotic PHT.

Long-term results of the threaded Weill cup in primary total hip arthroplasty: a 15-20-year follow-up study.

Uncemented, threaded acetabular components with smooth surface treatment were widely used in continental Europe in the 1970s and 1980s for primary total hip arthroplasty (THA). Previously published studies showed high failure rates in the mid-term. In a consecutive series of 116 patients, 127 threaded cups with smooth surface treatment (Weill cup; Zimmer, Winterthur, Switzerland) were implanted in combination with one type of uncemented stem. Patients were followed up clinically and radiographically. Mean time of follow-up was 17 years (range 15-20). At the time of follow-up, the acetabular component had been revised or was awaiting revision in 30 hips (24%). Two hips were revised for infection and 23 for aseptic loosening. Four polyethylene liners were exchanged because of excessive wear. One hip was awaiting revision. The survival rate for all acetabular revisions including one hip awaiting revision was 75% (95%CI: 65-85%) at 17 years. These results support the view that smooth, threaded acetabular components do not provide satisfactory long-term fixation and should be abandoned. It is important to closely monitor patients with these components as the failure rate remains high in the long-term.