Failure of non-vacuum steam sterilization processes for dental handpieces

Background: Dental handpieces are used in critical and semi-critical operative interventions. Although a number of dental professional bodies recommend that dental handpieces are sterilized between patient use there is a lack of clarity and understanding of the effectiveness of different steam sterilization processes. The internal mechanisms of dental handpieces contain narrow lumens (0·8-2·3mm) which can impede the removal of air and ingress of saturated steam required to achieve sterilization conditions. Aim: To identify the extent of sterilization failure in dental handpieces using a non-vacuum process. Methods: In-vitro and in-vivo investigations were conducted on commonly used UK benchtop steam sterilizers and three different types of dental handpieces. The sterilization process was monitored inside the lumens of dental handpieces using thermometric (TM) methods (dataloggers), chemical indicators (CI) and biological indicators (BI). Findings: All three methods of assessing achievement of sterility within dental handpieces that had been exposed to non-vacuum sterilization conditions demonstrated a significant number of failures (CI=8/3,024(fails/n tests); BI=15/3,024; TM=56/56) compared to vacuum sterilization conditions (CI=2/1,944; BI=0/1,944; TM=0/36). The dental handpiece most likely to fail sterilization in the non-vacuum process was the surgical handpiece. Non-vacuum sterilizers located in general dental practice had a higher rate of sterilization failure (CI=25/1,620; BI=32/1,620; TM=56/56) with no failures in vacuum process. Conclusion: Non-vacuum downward/gravity displacement, type-N steam sterilizers are an unreliable method for sterilization of dental handpieces in general dental practice. The handpiece most likely to fail sterilization is the type most frequently used for surgical interventions

Investigating steam penetration using thermometric methods in dental handpieces with narrow internal lumens during sterilizing processes with non-vacuum or vacuum processes

Background: Dental handpieces are required to be sterilized between patient use. Vacuum steam sterilization processes with fractionated pre/post-vacuum phases or unique cycles for specified medical devices, are required for hollow instruments with internal lumens to assure successful air removal. Entrapped air will compromise achievement of required sterilization conditions. Many countries and professional organisations still advocate non-vacuum sterilization processes for these devices. Aim: To investigate non-vacuum downward/gravity displacement, type-N steam sterilization of dental handpieces, using thermometric methods to measure time to achieve sterilization temperature at different handpiece locations. Methods: Measurements at different positions within air turbines were undertaken with thermocouples and dataloggers. Two examples of commonly used UK benchtop steam sterilizers were tested; a non-vacuum benchtop sterilizer (Little Sister 3, Eschmann, UK) and a vacuum benchtop sterilizer (Lisa, W&H, Austria). Each sterilizer cycle was completed with three handpieces and each cycle in triplicate. Findings: A total of 140 measurements inside dental handpiece lumens were recorded. We demonstrate that the non-vacuum process fails (time range 0-150 seconds) to reliably achieve sterilization temperatures within the time limit specified by the International standard (15 seconds equilibration time). The measurement point at the base of the handpiece failed in all test runs (n=9) to meet the standard. No failures were detected with the vacuum steam sterilization type B process with fractionated pre-vacuum and post-vacuum phases. Conclusion: Non-vacuum downward/gravity displacement, type-N steam sterilization processes are unreliable in achieving sterilization conditions inside dental handpieces and the base of the handpiece is the site most likely to fail

Grammaticality, Acceptability, and Probability: A Probabilistic View of Linguistic Knowledge

The question of whether humans represent grammatical knowledge as a binary condition on membership in a set of well‐formed sentences, or as a probabilistic property has been the subject of debate among linguists, psychologists, and cognitive scientists for many decades. Acceptability judgments present a serious problem for both classical binary and probabilistic theories of grammaticality. These judgements are gradient in nature, and so cannot be directly accommodated in a binary formal grammar. However, it is also not possible to simply reduce acceptability to probability. The acceptability of a sentence is not the same as the likelihood of its occurrence, which is, in part, determined by factors like sentence length and lexical frequency. In this paper, we present the results of a set of large‐scale experiments using crowd‐sourced acceptability judgments that demonstrate gradience to be a pervasive feature in acceptability judgments. We then show how one can predict acceptability judgments on the basis of probability by augmenting probabilistic language models with an acceptability measure. This is a function that normalizes probability values to eliminate the confounding factors of length and lexical frequency. We describe a sequence of modeling experiments with unsupervised language models drawn from state‐of‐the‐art machine learning methods in natural language processing. Several of these models achieve very encouraging levels of accuracy in the acceptability prediction task, as measured by the correlation between the acceptability measure scores and mean human acceptability values. We consider the relevance of these results to the debate on the nature of grammatical competence, and we argue that they support the view that linguistic knowledge can be intrinsically probabilistic

Neurofeedback and biofeedback with 37 migraineurs: a clinical outcome study

<p>Abstract</p> <p>Background</p> <p>Traditional peripheral biofeedback has grade A evidence for effectively treating migraines. Two newer forms of neurobiofeedback, EEG biofeedback and hemoencephalography biofeedback were combined with thermal handwarming biofeedback to treat 37 migraineurs in a clinical outpatient setting.</p> <p>Methods</p> <p>37 migraine patients underwent an average of 40 neurofeedback sessions combined with thermal biofeedback in an outpatient biofeedback clinic. All patients were on at least one type of medication for migraine; preventive, abortive or rescue. Patients kept daily headache diaries a minimum of two weeks prior to treatment and throughout treatment showing symptom frequency, severity, duration and medications used. Treatments were conducted an average of three times weekly over an average span of 6 months. Headache diaries were examined after treatment and a formal interview was conducted. After an average of 14.5 months following treatment, a formal interview was conducted in order to ascertain duration of treatment effects.</p> <p>Results</p> <p>Of the 37 migraine patients treated, 26 patients or 70% experienced at least a 50% reduction in the frequency of their headaches which was sustained on average 14.5 months after treatments were discontinued.</p> <p>Conclusions</p> <p>All combined neuro and biofeedback interventions were effective in reducing the frequency of migraines with clients using medication resulting in a more favorable outcome (70% experiencing at least a 50% reduction in headaches) than just medications alone (50% experience a 50% reduction) and that the effect size of our study involving three different types of biofeedback for migraine (1.09) was more robust than effect size of combined studies on thermal biofeedback alone for migraine (.5). These non-invasive interventions may show promise for treating treatment-refractory migraine and for preventing the progression from episodic to chronic migraine.</p

Fighting with the Sparsity of Synonymy Dictionaries

Graph-based synset induction methods, such as MaxMax and Watset, induce synsets by performing a global clustering of a synonymy graph. However, such methods are sensitive to the structure of the input synonymy graph: sparseness of the input dictionary can substantially reduce the quality of the extracted synsets. In this paper, we propose two different approaches designed to alleviate the incompleteness of the input dictionaries. The first one performs a pre-processing of the graph by adding missing edges, while the second one performs a post-processing by merging similar synset clusters. We evaluate these approaches on two datasets for the Russian language and discuss their impact on the performance of synset induction methods. Finally, we perform an extensive error analysis of each approach and discuss prominent alternative methods for coping with the problem of the sparsity of the synonymy dictionaries.Comment: In Proceedings of the 6th Conference on Analysis of Images, Social Networks, and Texts (AIST'2017): Springer Lecture Notes in Computer Science (LNCS

Bayesian Inference Semantics: A Modelling System and A Test Suite

We present BIS, a Bayesian Inference Seman- tics, for probabilistic reasoning in natural lan- guage. The current system is based on the framework of Bernardy et al. (2018), but de- parts from it in important respects. BIS makes use of Bayesian learning for inferring a hy- pothesis from premises. This involves estimat- ing the probability of the hypothesis, given the data supplied by the premises of an argument. It uses a syntactic parser to generate typed syn- tactic structures that serve as input to a model generation system. Sentences are interpreted compositionally to probabilistic programs, and the corresponding truth values are estimated using sampling methods. BIS successfully deals with various probabilistic semantic phe- nomena, including frequency adverbs, gener- alised quantifiers, generics, and vague predi- cates. It performs well on a number of interest- ing probabilistic reasoning tasks. It also sus- tains most classically valid inferences (instan- tiation, de Morgan’s laws, etc.). To test BIS we have built an experimental test suite with examples of a range of probabilistic and clas- sical inference patterns

GPR35 as a Novel Therapeutic Target

G protein-coupled receptors (GPCRs) remain the best studied class of cell surface receptors and the most tractable family of proteins for novel small molecule drug discovery. Despite this, a considerable number of GPCRs remain poorly characterized and in a significant number of cases, endogenous ligand(s) that activate them remain undefined or are of questionable physiological relevance. GPR35 was initially discovered over a decade ago but has remained an “orphan” receptor. Recent publications have highlighted novel ligands, both endogenously produced and synthetic, which demonstrate significant potency at this receptor. Furthermore, evidence is accumulating which highlights potential roles for GPR35 in disease and therefore, efforts to characterize GPR35 more fully and develop it as a novel therapeutic target in conditions that range from diabetes and hypertension to asthma are increasing. Recently identified ligands have shown marked species selective properties, indicating major challenges for future drug development. As we begin to understand these issues, the continuing efforts to identify novel agonist and antagonist ligands for GPR35 will help to decipher its true physiological relevance; translating multiple assay systems in vitro, to animal disease systems in vivo and finally to man

Reducing the risk of iatrogenic Creutzfeldt–Jakob disease by improving the cleaning of neurosurgical instruments

Background: In all, there have been 178 variant Creutzfeldt–Jakob disease (vCJD) patients diagnosed in the UK, with an estimated maximum 1:2000 carriage rate based on archived appendix and tonsil tissue, implying that infection may be rare but carriage relatively frequent. Previous workers have identified that maintenance of surgical instruments in a humid atmosphere after use and prior to cleaning assists cleaning efficacy. Recently the Department of Health/Advisory Committee on Dangerous Pathogens UK have recommended a surgical instrument cleanliness threshold post cleaning of &lt;5 μg protein per instrument side. Aim: To quantify cleanliness of neurosurgical instruments and to investigate cost-effective measures for improved cleaning. Methods: Two instrument protein quantification methods were used: one based on the International Standard (15883 series) using sodium dodecyl sulphate elution and ortho-phthalaldehyde reaction, and a second in-situ protein fluorescence detection system (ProReveal) providing results per instrument side. In-vitro investigation of the efficacy of some commercial and in-house pre-clean wetting agents was undertaken using artificial test soil and stainless steel discs under standard conditions. In-vivo evaluation of best-performing in-vitro agents was undertaken on craniotomy sets. Findings: ProReveal technology demonstrated that 163 out of 187 (87%) neurosurgical instruments had &lt;5 μg residual protein per instrument side. The use of proprietary National Health Service plastic bags and sterile water-soaked wound pads were equivalent in efficacy to commercial pre-cleaning wetting products and significantly less expensive. Conclusion: Although we demonstrate low in-situ protein levels on neurosurgical instruments and the beneficial effects of keeping instruments moist, other cleaning critical-control points such as instrument loading patterns should also be monitored

The influence of lubricating oil on the efficacy of steam sterilization processes used to decontaminate dental handpieces

Dental handpieces pose a risk of cross infection due to contamination with patient material. Cleaning and sterilization of dental handpieces is challenging, due to a complex design. A further limiting, factor influencing achievement of sterilization conditions, is the presence of oil used to lubricate internal components. If moisture is absent then the process takes place in “dry heat” conditions and the time and temperature of exposure must be significantly increased (e.g. 160 °C for 2 h). Lubricating oils can be hydrophobic in nature and therefore, if present, prevent moisture in steam from reaching surfaces and thereby affect microbial kill (sterility). The aim of this study was to investigate the effect of handpiece oil in dental handpieces on the inactivation of Geobacillus stearothermophilus spores during steam sterilization. Handpieces were inoculated with a spore solution dried onto stainless steel wires, which were then placed into spray channels, followed by inoculation of handpiece oil (W&#38;H, Austria). In order to investigate kill rates of different sterilization cycle profiles a Biological Indicator Evaluation Resistometer (BIER vessel) was used. Three different sterilization processes were investigated (two vacuum and one non-vacuum process). Spores were recovered by sonication of wires in phosphate buffer saline (PBS), filtration and plating on Tryptone Soy Agar (TSA). Recovered spores were expressed as colony forming units (cfu). Spores were recovered in only one type of process (with one pre-vacuum pulse) from 4 out of 12 processed handpieces. In conclusion this study suggests that it would be prudent to validate sterilization cycles with equipment and conditions that are likely to be encountered in clinical practice. Making assumptions that all bacteria are killed during sterilization processes, despite the overkill of three minutes at 134 °C in terms of integrated lethality, is not necessarily correct