A Review on Commercial Oligonucleotide Drug Products.

Oligonucleotide drug products commercially approved in the US and the EU are reviewed. A total of 20 products that includes 1 aptamer, 12 antisense oligonucleotides (ASOs), 6 small interfering ribonucleic acids (siRNAs), and 1 mixture of single-stranded and double-stranded polydeoxyribonucleotides have been identified. A typical oligonucleotide formulation is composed of an oligonucleotide with buffering agent(s), pH adjusting agents, and a tonicity adjusting agent. All the products are presented as 2.1 - 200 mg/mL solutions at pH between 6 and 8.7. Majority of the products are approved for intravenous (IV) and subcutaneous (SC) routes, with two for intravitreal (IVT), two for intrathecal (IT), and one for intramuscular (IM) routes. The primary packaging includes vials and prefilled syringes (PFS). Products approved for IV and IT administration routes and requiring >1.5 mL dose volumes are supplied in vials, while those approved for SC, IM, and IVT and requiring ≤1.5 mL dose volume are supplied in PFS. Based on the compiled dataset, we propose a generalized starting point for an oligonucleotide formulation during early phase development for IV, SC, and IT administration routes. Overall, we believe this harmonized evaluation and understanding of various oligonucleotide drug product attributes will help derive platform generalizations and allows for accelerated early phase development for first-in-human studies.

Diagnostic utility of capnography in emergency department triage for screening acidemia: a pilot study.

BACKGROUND: Capnography is a quantitative and reliable method of determining the ventilatory status of patients. We describe the test characteristics of capnography obtained during Emergency Department triage for screening acidemia. RESULTS: We performed an observational, pilot study of adult patients presenting to Emergency Department (ED) triage. The primary outcome was acidemia, as determined by the basic metabolic panel and/or blood gas during the ED visit. Secondary outcomes include comparison of estimated and measured respiratory rates (RR), relationships between end-tidal CO2 (EtCO2) and venous partial pressure of CO2, admission disposition, in-hospital mortality during admission, and capnogram waveform analysis. A total of 100 adult ED encounters were included in the study and acidemia ([Formula: see text] or [Formula: see text]) was identified in 28 patients. The measured respiratory rate (20.3 ± 6.4 breaths/min) was significantly different from the estimated rate (18.4 ± 1.6 breaths/min), and its area under the receiver operating curve (c-statistic) to predict acidemia was only 0.60 (95% CI 0.51-0.75, p = 0.03). A low end-tidal CO2 (EtCO2 < 32 mmHg) had positive (LR+) and negative (LR-) likelihood ratios of 4.68 (95% CI 2.59-8.45) and 0.34 (95% CI 0.19-0.61) for acidemia, respectively-corresponding to sensitivity 71.4% (95% CI 51.3-86.8) and specificity 84.7% (95% CI 74.3-92.1). The c-statistic for EtCO2 was 0.849 (95% CI 0.76-0.94, p = 0.00). Waveform analysis further revealed characteristically abnormal capnograms that were associated with underlying pathophysiology. CONCLUSIONS: Capnography is a quantitative method of screening acidemia in patients and can be implemented feasibly in Emergency Department triage as an adjunct to vital signs. While it was shown to have only modest ability to predict acidemia, triage capnography has wide generalizability to screen other life-threatening disease processes such as sepsis or can serve as an early indicator of clinical deterioration.

Routine follow-up care for head and neck cancer after curative treatment: A 3-year experience of measuring patients' self-reported needs, preferences, quality of life and attitudes towards follow-up.

OBJECTIVE: To evaluate and describe attitudes, quality of life (Qol), needs and preferences of patients with head and neck cancer after 3 years of follow-up care. METHODS: This is an exploratory prospective study of recurrence-free patients. Survey results were compared between 1-, 2- and 3-year post-treatment and by disease characteristics. RESULTS: A total of 116 patients were included with 46% oropharyngeal cancer, 66% early stage disease and 41% having had surgery. After 3 years, most patients reported good to excellent health (88%), however expressed uncertainty regarding recurrence (66%), multiple needs (information on prognosis 91%, long-term sequalae 72%) and wanted to continue with follow-up (96%). Few changes were observed over time, with exceptions. Patients with more advanced disease, oral cancer or who had surgery experienced declining Qol (p < 0.050). Women experienced improvements in Qol domains (pain p = 0.028, speech p = 0.009) over time. Attitudes towards communication with oncologists demonstrated improved patient comfort (p = 0.044) over the 3 years; however, patients' beliefs about their prognosis did not (71% vs. 73% vs. 77% did not believe they were cured, p = 0.581). CONCLUSION: Although patients' needs, preferences and attitudes towards follow-up did not change drastically, important needs persist. This work supports identifying individual patient needs and the challenges in addressing prognostic expectations.

Mapping of HIE CT terms to LOINC®: analysis of content-dependent coverage and coverage improvement through new term creation.

Objective: We describe and evaluate the mapping of computerized tomography (CT) terms from 40 hospitals participating in a health information exchange (HIE) to a standard terminology. Methods: Proprietary CT exam terms and corresponding exam frequency data were obtained from 40 participant HIE sites that transmitted radiology data to the HIE from January 2013 through October 2015. These terms were mapped to the Logical Observations Identifiers Names and Codes (LOINC®) terminology using the Regenstrief LOINC mapping assistant (RELMA) beginning in January 2016. Terms without initial LOINC match were submitted to LOINC as new term requests on an ongoing basis. After new LOINC terms were created, proprietary terms without an initial match were reviewed and mapped to these new LOINC terms where appropriate. Content type and token coverage were calculated for the LOINC version at the time of initial mapping (v2.54) and for the most recently released version at the time of our analysis (v2.63). Descriptive analysis was performed to assess for significant differences in content-dependent coverage between the 2 versions. Results: LOINC's content type and token coverages of HIE CT exam terms for version 2.54 were 83% and 95%, respectively. Two-hundred-fifteen new LOINC CT terms were created in the interval between the releases of version 2.54 and 2.63, and content type and token coverages, respectively, increased to 93% and 99% (P < .001). Conclusion: LOINC's content type coverage of proprietary CT terms across 40 HIE sites was 83% but improved significantly to 93% following new term creation.

Likelihood Ratios for the Emergency Physician.

The concept of likelihood ratios was introduced more than 40 years ago, yet this powerful metric has still not seen wider application or discussion in the medical decision-making process. There is concern that clinicians-in-training are still being taught an oversimplified approach to diagnostic test performance and have limited exposure to likelihood ratios. Even for those familiar with likelihood ratios, they might perceive them as mathematically cumbersome in application, if not difficult to determine for a particular disease process. This article takes a conceptual approach to likelihood ratios and applies them to two clinical settings: 1) severe intracranial injury after minor head trauma and 2) suspected pulmonary embolism with shortness of breath. Likelihood ratios are the most appropriate metric for efficient rational clinical examination and can prevent unnecessary and wasteful treatments and procedures.

Association Between Anesthesiology Volumes and Early and Late Outcomes After Cystectomy for Bladder Cancer: A Population-Based Study.

BACKGROUND: Hospital and surgeon volume are related to postoperative complications and long-term survival after radical cystectomy. Here, we describe the relationships between these provider characteristics and anesthesiologist volumes on early and late outcomes after radical cystectomy for bladder cancer. METHODS: Records of treatment and surgical pathology reports were linked to the population-based Ontario Cancer Registry to identify all patients with radical cystectomy in Ontario during 1994 to 2008. Volume was divided into quartiles and determined on the basis of mean annual number of hospital/surgeon/anesthesiologist radical cystectomy cases during a 5-year study period. A composite anesthesiologist volume also was used and defined as major colorectal procedures in addition to radical cystectomy given the similar complexity of these cases. Logistic and Cox proportional hazards regression models were used to explore the associations between volume and outcomes while adjusting for potential patient-, disease-, and system-related confounders. The primary outcomes were postoperative readmission rates, postoperative mortality, and 5-year survival. RESULTS: The study included 3585 patients with radical cystectomy between 1994 and 2008. Median annual anesthesiologist radical cystectomy volume was 1 (maximum 8.8 cases/year); lowest volume quartile (Q1) <0.6 cases/year and highest volume quartile (Q4) >1.4 cases/year. The median annual composite anesthesiologist volume was 9 radical cystectomy and colorectal cases (Q1 [range 0.2-6.4 cases/year], Q4 [range 11.8-29.2 cases/year]); subsequent analyses used this composite volume. Anesthesiologist volume was associated with readmission rates at 30 days (P = .02, Q1 mean = 27% vs Q4 mean = 21%) and at 90 days (P = .01, Q1 mean = 39% vs Q4 mean = 31%). In multivariable analysis, including the adjustment for surgeon and hospital volume, the cohort of anesthesiologists who performed the lowest volume of cases annually (Q1) was associated with greater rates of readmission at 30 days (OR 1.36, 95% confidence interval [CI], 1.09-1.71, P = .04) and at 90 days (OR 1.36, 95% CI, 1.11-1.66, P = .03). Anesthesiologist volumes were not associated with postoperative mortality or long-term survival. CONCLUSIONS: Anesthesiologist case volume for radical cystectomy was low, reflecting the lack of subspecialization in urologic procedures in routine clinical practice. Lower volume anesthesia providers were associated with higher readmission rates after radical cystectomy. Further studies are needed to validate this finding and to identify the processes that may explain an association between provider volume and patient outcome.

Lymphoma: immune evasion strategies.

While the cellular origin of lymphoma is often characterized by chromosomal translocations and other genetic aberrations, its growth and development into a malignant neoplasm is highly dependent upon its ability to escape natural host defenses. Neoplastic cells interact with a variety of non-malignant cells in the tumor milieu to create an immunosuppressive microenvironment. The resulting functional impairment and dysregulation of tumor-associated immune cells not only allows for passive growth of the malignancy but may even provide active growth signals upon which the tumor subsequently becomes dependent. In the past decade, the success of immune checkpoint blockade and adoptive cell transfer for relapsed or refractory lymphomas has validated immunotherapy as a possible treatment cornerstone. Here, we review the mechanisms by which lymphomas have been found to evade and even reprogram the immune system, including alterations in surface molecules, recruitment of immunosuppressive subpopulations, and secretion of anti-inflammatory factors. A fundamental understanding of the immune evasion strategies utilized by lymphomas may lead to better prognostic markers and guide the development of targeted interventions that are both safer and more effective than current standards of care.

Classifying epileptic EEG signals with delay permutation entropy and Multi-Scale K-means.

Most epileptic EEG classification algorithms are supervised and require large training datasets, that hinder their use in real time applications. This chapter proposes an unsupervised Multi-Scale K-means (MSK-means) MSK-means algorithm to distinguish epileptic EEG signals and identify epileptic zones. The random initialization of the K-means algorithm can lead to wrong clusters. Based on the characteristics of EEGs, the MSK-means MSK-means algorithm initializes the coarse-scale centroid of a cluster with a suitable scale factor. In this chapter, the MSK-means algorithm is proved theoretically superior to the K-means algorithm on efficiency. In addition, three classifiers: the K-means, MSK-means MSK-means and support vector machine (SVM), are used to identify seizure and localize epileptogenic zone using delay permutation entropy features. The experimental results demonstrate that identifying seizure with the MSK-means algorithm and delay permutation entropy achieves 4. 7 % higher accuracy than that of K-means, and 0. 7 % higher accuracy than that of the SVM.

Analysis and classification of sleep stages based on difference visibility graphs from a single-channel EEG signal.

The existing sleep stages classification methods are mainly based on time or frequency features. This paper classifies the sleep stages based on graph domain features from a single-channel electroencephalogram (EEG) signal. First, each epoch (30 s) EEG signal is mapped into a visibility graph (VG) and a horizontal VG (HVG). Second, a difference VG (DVG) is obtained by subtracting the edges set of the HVG from the edges set of the VG to extract essential degree sequences and to detect the gait-related movement artifact recordings. The mean degrees (MDs) and degree distributions (DDs) P (k) on HVGs and DVGs are analyzed epoch-by-epoch from 14,963 segments of EEG signals. Then, the MDs of each DVG and HVG and seven distinguishable DD values of P (k) from each DVG are extracted. Finally, nine extracted features are forwarded to a support vector machine to classify the sleep stages into two, three, four, five, and six states. The accuracy and kappa coefficients of six-state classification are 87.5% and 0.81, respectively. It was found that the MDs of the VGs on the deep sleep stage are higher than those on the awake and light sleep stages, and the MDs of the HVGs are just the reverse.

Diagnosis of neoplasia in Barrett's esophagus using vital-dye enhanced fluorescence imaging.

The ability to differentiate benign metaplasia in Barrett's Esophagus (BE) from neoplasia in vivo remains difficult as both tissue types can be flat and indistinguishable with white light imaging alone. As a result, a modality that highlights glandular architecture would be useful to discriminate neoplasia from benign epithelium in the distal esophagus. VFI is a novel technique that uses an exogenous topical fluorescent contrast agent to delineate high grade dysplasia and cancer from benign epithelium. Specifically, the fluorescent images provide spatial resolution of 50 to 100 µm and a field of view up to 2.5 cm, allowing endoscopists to visualize glandular morphology. Upon excitation, classic Barrett's metaplasia appears as continuous, evenly-spaced glands and an overall homogenous morphology; in contrast, neoplastic tissue appears crowded with complete obliteration of the glandular framework. Here we provide an overview of the instrumentation and enumerate the protocol of this new technique. While VFI affords a gastroenterologist with the glandular architecture of suspicious tissue, cellular dysplasia cannot be resolved with this modality. As such, one cannot morphologically distinguish Barrett's metaplasia from BE with Low-Grade Dysplasia via this imaging modality. By trading off a decrease in resolution with a greater field of view, this imaging system can be used at the very least as a red-flag imaging device to target and biopsy suspicious lesions; yet, if the accuracy measures are promising, VFI may become the standard imaging technique for the diagnosis of neoplasia (defined as either high grade dysplasia or cancer) in the distal esophagus.

Epileptic seizure detection in EEGs signals using a fast weighted horizontal visibility algorithm.

This paper proposes a fast weighted horizontal visibility graph constructing algorithm (FWHVA) to identify seizure from EEG signals. The performance of the FWHVA is evaluated by comparing with Fast Fourier Transform (FFT) and sample entropy (SampEn) method. Two noise-robustness graph features based on the FWHVA, mean degree and mean strength, are investigated using two chaos signals and five groups of EEG signals. Experimental results show that feature extraction using the FWHVA is faster than that of SampEn and FFT. And mean strength feature associated with ictal EEG is significant higher than that of healthy and inter-ictal EEGs. In addition, an 100% classification accuracy for identifying seizure from healthy shows that the features based on the FWHVA are more promising than the frequency features based on FFT and entropy indices based on SampEn for time series classification.

Simulation study of pO2 distribution in induced tumour masses and normal tissues within a microcirculation environment.

The biological microenvironment is interrupted when tumour masses are introduced because of the strong competition for oxygen. During the period of avascular growth of tumours, capillaries that existed play a crucial role in supplying oxygen to both tumourous and healthy cells. Due to limitations of oxygen supply from capillaries, healthy cells have to compete for oxygen with tumourous cells. In this study, an improved Krogh's cylinder model which is more realistic than the previously reported assumption that oxygen is homogeneously distributed in a microenvironment, is proposed to describe the process of the oxygen diffusion from a capillary to its surrounding environment. The capillary wall permeability is also taken into account. The simulation study is conducted and the results show that when tumour masses are implanted at the upstream part of a capillary and followed by normal tissues, the whole normal tissues suffer from hypoxia. In contrast, when normal tissues are ahead of tumour masses, their pO2 is sufficient. In both situations, the pO2 in the whole normal tissues drops significantly due to the axial diffusion at the interface of normal tissues and tumourous cells. As the existence of the axial oxygen diffusion cannot supply the whole tumour masses, only these tumourous cells that are near the interface can be partially supplied, and have a small chance to survive.

Analysis of alcoholic EEG signals based on horizontal visibility graph entropy.

This paper proposes a novel horizontal visibility graph entropy (HVGE) approach to evaluate EEG signals from alcoholic subjects and controlled drinkers and compare with a sample entropy (SaE) method. Firstly, HVGEs and SaEs are extracted from 1,200 recordings of biomedical signals, respectively. A statistical analysis method is employed to choose the optimal channels to identify the abnormalities in alcoholics. Five group channels are selected and forwarded to a K-Nearest Neighbour (K-NN) and a support vector machine (SVM) to conduct classification, respectively. The experimental results show that the HVGEs associated with left hemisphere, [Formula: see text]1, [Formula: see text]3 and FC5 electrodes, of alcoholics are significantly abnormal. The accuracy of classification with 10-fold cross-validation is 87.5 [Formula: see text] with about three HVGE features. By using just optimal 13-dimension HVGE features, the accuracy is 95.8 [Formula: see text]. In contrast, SaE features associated cannot identify the left hemisphere disorder for alcoholism and the maximum classification ratio based on SaE is just 95.2 [Formula: see text] even using all channel signals. These results demonstrate that the HVGE method is a promising approach for alcoholism identification by EEG signals.

Consciousness and depth of anesthesia assessment based on Bayesian analysis of EEG signals.

This study applies Bayesian techniques to analyze EEG signals for the assessment of the consciousness and depth of anesthesia (DoA). This method takes the limiting large-sample normal distribution as posterior inferences to implement the Bayesian paradigm. The maximum a posterior (MAP) is applied to denoise the wavelet coefficients based on a shrinkage function. When the anesthesia states change from awake to light, moderate, and deep anesthesia, the MAP values increase gradually. Based on these changes, a new function B(DoA) is designed to assess the DoA. The new proposed method is evaluated using anesthetized EEG recordings and BIS data from 25 patients. The Bland-Alman plot is used to verify the agreement of B(DoA) and the popular BIS index. A correlation between B(DoA) and BIS was measured using prediction probability P(K). In order to estimate the accuracy of DoA, the effect of sample n and variance τ on the maximum posterior probability is studied. The results show that the new index accurately estimates the patient's hypnotic states. Compared with the BIS index in some cases, the B(DoA) index can estimate the patient's hypnotic state in the case of poor signal quality.

Measuring and reflecting depth of anesthesia using wavelet and power spectral density.

This paper evaluates depth of anesthesia (DoA) monitoring using a new index. The proposed method preconditions raw EEG data using an adaptive threshold technique to remove spikes and low-frequency noise. We also propose an adaptive window length technique to adjust the length of the sliding window. The information pertinent to DoA is then extracted to develop a feature function using discrete wavelet transform and power spectral density. The evaluation demonstrates that the new index reflects the patient's transition from consciousness to unconsciousness with the induction of anesthesia in real time.

Clustering technique-based least square support vector machine for EEG signal classification.

This paper presents a new approach called clustering technique-based least square support vector machine (CT-LS-SVM) for the classification of EEG signals. Decision making is performed in two stages. In the first stage, clustering technique (CT) has been used to extract representative features of EEG data. In the second stage, least square support vector machine (LS-SVM) is applied to the extracted features to classify two-class EEG signals. To demonstrate the effectiveness of the proposed method, several experiments have been conducted on three publicly available benchmark databases, one for epileptic EEG data, one for mental imagery tasks EEG data and another one for motor imagery EEG data. Our proposed approach achieves an average sensitivity, specificity and classification accuracy of 94.92%, 93.44% and 94.18%, respectively, for the epileptic EEG data; 83.98%, 84.37% and 84.17% respectively, for the motor imagery EEG data; and 64.61%, 58.77% and 61.69%, respectively, for the mental imagery tasks EEG data. The performance of the CT-LS-SVM algorithm is compared in terms of classification accuracy and execution (running) time with our previous study where simple random sampling with a least square support vector machine (SRS-LS-SVM) was employed for EEG signal classification. We also compare the proposed method with other existing methods in the literature for the three databases. The experimental results show that the proposed algorithm can produce a better classification rate than the previous reported methods and takes much less execution time compared to the SRS-LS-SVM technique. The research findings in this paper indicate that the proposed approach is very efficient for classification of two-class EEG signals.

Phase II cancer clinical trials with a one-sample log-rank test and its corrections based on the Edgeworth expansion.

The response rate has been frequently used as the primary endpoint of phase II cancer clinical trials. It may not be an appropriate endpoint when a new treatment is not expected to produce any tumour shrinkage. When a large database for a historical control is available, the direct comparison of survival curves between a new treatment and the historical control may be made in phase II cancer clinical trials. In this paper, a one-sample log-rank test is introduced for the design and analysis of phase II cancer clinical trials with time-to-event endpoints. Corrections to the one-sample log-rank test are also derived based on the Edgeworth expansion. Simulations showed that the original one-sample log-rank test may be preferred if strictly controlling for type I error is important or when the sample size of a phase II trial is as large as 50, and a corrected one-sample log-rank test is used if the sample size of a phase II trial is small. A data set from a clinical trial conducted by the NCIC Clinical Trials Group is used to illustrate the proposed procedures.

Isolating surface-enhanced Raman scattering hot spots using multiphoton lithography.

We present a method for improving femtomole-level trace detection (10(9) molecules) using large-area surface-enhanced Raman scattering (SERS) substrates. Using multiphoton-induced exposure of a commercial photoresist, we physically limit the available molecular adsorption sites to only the electromagnetic "hot spots" on the substrate. This process prevents molecules from adsorbing to sites of weak SERS enhancement, while permitting adsorption to sites of extraordinary SERS enhancement. For a randomly adsorbed submonolayer of benzenethiol molecules the average Raman scattering cross section of the processed sample is 27 times larger than that of an unprocessed SERS substrate.

N5-CAIR mutase: role of a CO2 binding site and substrate movement in catalysis.

N5-Carboxyaminoimidazole ribonucleotide mutase (N5-CAIR mutase or PurE) from Escherichia coli catalyzes the reversible interconversion of N5-CAIR to carboxyaminoimidazole ribonucleotide (CAIR) with direct CO2 transfer. Site-directed mutagenesis, a pH-rate profile, DFT calculations, and X-ray crystallography together provide new insight into the mechanism of this unusual transformation. These studies suggest that a conserved, protonated histidine (His45) plays an essential role in catalysis. The importance of proton transfers is supported by DFT calculations on CAIR and N5-CAIR analogues in which the ribose 5'-phosphate is replaced with a methyl group. The calculations suggest that the nonaromatic tautomer of CAIR (isoCAIR) is only 3.1 kcal/mol higher in energy than its aromatic counterpart, implicating this species as a potential intermediate in the PurE-catalyzed reaction. A structure of wild-type PurE cocrystallized with 4-nitroaminoimidazole ribonucleotide (NO2-AIR, a CAIR analogue) and structures of H45N and H45Q PurEs soaked with CAIR have been determined and provide the first insight into the binding of an intact PurE substrate. A comparison of 19 available structures of PurE and PurE mutants in apo and nucleotide-bound forms reveals a common, buried carboxylate or CO2 binding site for CAIR and N5-CAIR in a hydrophobic pocket in which the carboxylate or CO2 interacts with backbone amides. This work has led to a mechanistic proposal in which the carboxylate orients the substrate for proton transfer from His45 to N5-CAIR to form an enzyme-bound aminoimidazole ribonucleotide (AIR) and CO2 intermediate. Subsequent movement of the aminoimidazole moiety of AIR reorients it for addition of CO2 at C4 to generate isoCAIR. His45 is now in a position to remove a C4 proton to produce CAIR.

Alternating optokinetic nystagmus (OKN) induced by intermittent display of stationary gratings.

In this paper, we report a novel optokinetic nystagmus (OKN), which was evoked by stationary gratings presented intermittently. OKN eye movements were accurately measured by the electromagnetic scleral search-coil technique. For the luminance stimuli, alternating OKN was elicited when the interstimulus interval (ISI) ranged from 33 to 83 ms duration and the ISI luminance approximated to the mean luminance of the stimulus grating; for chromatic (red/green) stimuli, the OKN could be evoked in non-isoluminant condition and vanished in the isoluminant condition. It is a plausible explanation that the present OKN, intermittent display-of-gratings-induced OKN (IDG-OKN), might be related to the temporal impulse response of the luminance channel in vision.