AKT overactivation can suppress DNA repair via p70S6 kinase-dependent downregulation of MRE11

Deregulated AKT kinase activity due to PTEN deficiency in cancer cells contributes to oncogenesis by incompletely understood mechanisms. Here, we show that PTEN deletion in HCT116 and DLD1 colon carcinoma cells leads to suppression of CHK1 and CHK2 activation in response to irradiation, impaired G2 checkpoint proficiency and radiosensitization. These defects are associated with reduced expression of MRE11, RAD50 and NBS1, components of the apical MRE11/RAD50/NBS1 (MRN) DNA damage response complex. Consistent with reduced MRN complex function, PTEN-deficient cells fail to resect DNA double-strand breaks efficiently after irradiation and show greatly diminished proficiency for DNA repair via the error-free homologous recombination (HR) repair pathway. MRE11 is highly unstable in PTEN-deficient cells but stability can be significantly restored by inhibiting mTORC1 or p70S6 kinase (p70S6K), downstream kinases whose activities are stimulated by AKT, or by mutating a residue in MRE11 that we show is phosphorylated by p70S6K in vitro. In primary human fibroblasts, activated AKT suppresses MRN complex expression to escalate RAS-induced DNA damage and thereby reinforce oncogene-induced senescence. Taken together, our data demonstrate that deregulation of the PI3K-AKT/ mTORC1/ p70S6K pathways, an event frequently observed in cancer, exert profound effects on genome stability via MRE11 with potential implications for tumour initiation and therapy

Results of carpal tunnel release

We evaluated, by means of a prospective study, the results of carpal tunnel release both clinically and electrophysiologically in 188 patients with a carpal tunnel syndrome. A questionnaire was completed by patient and surgeon pre- and post-operatively (6 and 12 months after operation), when physical examination, electromyography and nerve conduction tests were also performed. Full pre- and post-operative results were available for 136 patients and 82% of the patients were satisfied with the results of the operation. Symptoms caused by median nerve compression showed the greatest improvement and no fixed patterns with regard to unsatisfactory results were found. If pain persisted in the wrist, many patients considered the operation to have been unsuccessful. Electrophysiological improvement occurred in all patients and at 12 months follow-up, median nerve conduction was normal in 21% of cases. Thus distal sensory latency remained abnormal in 79% of the patients, emphasizing the need for caution when recurrence of carpal tunnel syndrome is diagnosed in such cases.\u

Learning in stochastic scheduling

We consider a scheduling problem in which two classes of independent jobs have to be processed non-preemptively by a single machine. The processing times of the jobs are assumed to be exponentially distributed with parameters depending on the class of each job. The objective is to minimize the sum of expected completion times. We adopt a bayesian framework in which both job class parameters are assumed to be unknown. However, by processing jobs from the corresponding class, the scheduler can gradually learn about the value of these parameters, thereby enhancing the decision making in the future.for the traditional stochastic scheduling variant, in which the parameters are known, the policy that always processes a job with shortest expected processing time (sept) is an optimal policy. In this paper, we show that in the bayesian framework the performance of sept is at most a factor 2 away from the performance of an optimal policy. Furthermore, we introduce a second policy learning-sept (l-sept), which is an adaptive variant of sept. We show that l-sept is no worse than sept and empirically outperforms sept. However, both policies have the same worst-case performance, that is, the bound of 2 is tight for both policies

Stochastic online scheduling on parallel machines

We consider a non-preemptive, stochastic parallel machine scheduling model with the goal to minimize the weighted completion times of jobs. In contrast to the classical stochastic model where jobs with their processing time distributions are known beforehand, we assume that jobs appear one by one, and every job must be assigned to a machine online. We propose a simple online scheduling policy for that model, and prove a performance guarantee that matches the currently best known performance guarantee for stochastic parallel machine scheduling. For the more general model with job release dates we derive an analogous result, and for NBUE distributed processing times we even improve upon the previously best known performance guarantee for stochastic parallel machine scheduling. Moreover, we derive some lower bounds on approximation

Average case and smoothed competitive analysis for the multi-level feedback algorithm

In this paper we introduce the notion of smoothed competitive analysis of online algorithms. Smoothed analysis has been proposed by Spielman and Teng to explain the behaviour of algorithms that work well in practice while performing very poorly from a worst case analysis point of view. We apply this notion to analyze the Multi-Level Feedback (MLF) algorithm to minimize the total flow time on a sequence of jobs released over time when the processing time of a job is only known at time of completion. The initial processing times are integers in the range $[1,2^K]$. We use a partial bit randomization model, i.e., the initial processing times are smoothed by changing the $k$ least significant bits under a quite general class of probability distributions. We show that MLF admits a smoothed competitive ratio of O((2^k/psigma)^3 + (2^k/psigma)^2 2^{K-k}}), where $sigma$ denotes the standard deviation of the distribution. In particular, we obtain a competitive ratio of $O(2^{K-k})$ if $sigma = Theta(2^k)$. We also prove an $Omega(2^{K-k})$ lower bound for any deterministic algorithm that is run on processing times smoothed according to the partial bit randomization model. For various other smoothing models, including the additive symmetric smoothing one, which is a variant of the model used by Spielman and Teng, we give a higher lower bound of $Omega(2^K)$. A direct consequence of our result is also the first average case analysis of MLF. We show a constant expected ratio of the total flow time of MLF to the optimum under several distributions including the uniform one

The diagnostic accuracy of headache measurement instruments: A systematic review and meta-analysis focusing on headaches associated with musculoskeletal symptoms

Aim: To systematically review the available literature on the diagnostic accuracy of questionnaires and measurement instruments for headaches associated with musculoskeletal symptoms. Design: Articles were eligible for inclusion when the diagnostic accuracy (sensitivity/specificity) was established for measurement instruments for headaches associated with musculoskeletal symptoms in an adult population. The databases searched were PubMed (1966–2018), Cochrane (1898–2018) and Cinahl (1988–2018). Methodological quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2) and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist for criterion validity. When possible, a meta-analysis was performed. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) recommendations were applied to establish the level of evidence per measurement instrument. Results: From 3450 articles identified, 31 articles were included in this review. Eleven measurement instruments for migraine were identified, of which the ID-Migraine is recommended with a moderate level of evidence and a pooled sensitivity of 0.87 (95% CI: 0.85–0.89) and specificity of 0.75 (95% CI: 0.72–0.78). Six measurement instruments examined both migraine and tension-type headache and only the Headache Screening Questionnaire – Dutch version has a moderate level of evidence with a sensitivity of 0.69 (95% CI 0.55–0.80) and specificity of 0.90 (95% CI 0.77–0.96) for migraine, and a sensitivity of 0.36 (95% CI 0.21–0.54) and specificity of 0.86 (95% CI 0.74–0.92) for tension-type headache. For cervicogenic headache, only the cervical flexion rotation test was identified and had a very low level of evidence with a pooled sensitivity of 0.83 (95% CI 0.72–0.94) and specificity of 0.82 (95% CI 0.73–0.91). Discussion: The current review is the first to establish an overview of the diagnostic accuracy of measurement instruments for headaches associated with musculoskeletal factors. However, as most measurement instruments were validated in one study, pooling was not always possible. Risk of bias was a serious problem for most studies, decreasing the level of evidence. More research is needed to enhance the level of evidence for existing measurement instruments for multiple headaches