Control Criteria Research Articles

Unsupervised seismic random noise attenuation by a recursive deep image prior

The presence of random noise in field data significantly reduces the precision of subsequent seismic processing steps. As a result, random noise suppression is essential to improve the quality of field data. Because most traditional algorithms characterize seismic data linearly, the denoising accuracy is still open to be improved. As an unsupervised deep-learning method, the deep image prior (DIP) algorithm can characterize seismic data nonlinearly. The DIP uses randomly generated noise as input and noisy seismic data as desired output for random noise attenuation over several rounds of training epochs. However, determining the optimal training epoch for obtaining the final denoised result of unlabeled noisy data remains a challenge. To terminate the DIP training in time and obtain the denoised result, we design an improved quality control criterion (IQCC) based on adjacent estimations of seismic signal. To further improve the denoising accuracy, a recursive strategy is developed that uses the previous desired output as the new input and the previous denoised result as the new desired output. To obtain the optimal denoised results using the suggested recursive algorithm, a convergence condition also is established. Numerous examples of synthetic prestack and poststack data demonstrate the effectiveness of the designed IQCC and our recursive strategy with a convergence condition in protecting the effective signal, especially when compared with the curvelet thresholding algorithm and the original DIP. Furthermore, the denoising accuracy is on par with that of the supervised learning algorithm, demonstrating the adaptability of our recursive DIP under the convergence condition. Its superiority is further supported by field poststack seismic data processing, which uses the local similarity for performance assessments.

PH determination as a quality standard for the elaboration of oral liquid compounding formula

ObjectivepH is a critical factor for all those medications prepared as aqueous liquid forms, because it has an impact on the solubility of the molecule, determining the stability of medications, the biological tolerability of the formulation, and the activity of the molecule. The objective of this study is to determine the optimum pH range for the oral liquid formulations more frequently prepared at the Pharmacy Unit, in order to standardize and incorporate said value into the standard protocols of action as a quality control criterion. MethodThe study was conducted in three stages. The first stage consisted in a retrospective study of the records of preparation of those oral liquid formulations prepared at least 5 times since January, 2015 to December, 2016, in our Pharmacy Unit; the main value and standard deviation of the pH values recorded for each formulation were calculated. In a second stage, there was a bibliographic search in order to understand the pH for the maximum stability of the molecule, and to confirm if this characteristic was recorded as a requirement for quality control in the procedures described in the formulation guidelines. In the third stage, it was confirmed if the pH values determined coincided with the maximum stability pH described in literature, and acceptance ranges were established. ResultsIn total, 31 formulations were reviewed (14 solutions / 17 suspensions). The maximum stability pH value was known for 19 (61.3%) of the molecules and/or oral liquid formulations evaluated; 15 (78.9%) of these were within this range, and the remaining 4 (21.1%) presented a standard deviation of ± 0.5 regarding the pH value referenced in the bibliography. The pH range for the same standard work procedure ranged between 0.32 and 1.51. An acceptance pH range of ± 0.75 was determined as quality control. ConclusionsAn optimal pH range has been determined for the 31 oral liquid formulations more widely prescribed in our hospital. This characteristic should be part of the galenic validation for these preparations, as well as of its routine quality control, in order to ensure their quality and efficacy.

Functional characterization of modules for the Silicon Tracking System of the CBM experiment

The CBM experiment is a fixed-target heavy-ion physics experiment at the future FAIR facility, designed to explore the QCD phase diagram at high baryon-net densities and moderate temperatures. To address its complex physics program, the experiment is conceived to operate at beam–target interaction rates up to 10 MHz with self-triggered front-end electronics and free-streaming readout architecture. The Silicon Tracking System (STS) of CBM is the main charged-particle tracker, capable of delivering time-stamped hits for online tracking and event building, and momentum measurement inside a superconducting dipole magnet. The functional unit of the STS is the detector module, a device assembled from a double-sided silicon microstrip sensor connected via a stack of microcables to a pair of front-end boards carrying the readout electronics. The assembly and successful operation of STS modules, produced with close-to-final components, was an important milestone achieved in recent years. The systematic study of the modules’ performance is also necessary for optimizing the assembly procedure and ensuring high production yield. This work reports a series of tests, which aim to evaluate the module’s operation and establish the basic criteria for quality control. It summarizes the procedures and results of different measurements performed with the modules, starting with noise estimation and charge amplitude calibration, resulting in the linearization of the channel’s ADC and a homogeneous threshold distribution. Those results were verified using a radioactive source. Additionally, first conclusions concerning the assembly yield in terms of number of functional channels were obtained. These studies represent a fundamental step towards the series production readiness for the final STS detector.

Predictors of Preexposure Prophylaxis Eligibility among Pregnant People with Opioid Use Disorder.

We seek to evaluate risk factors for eligibility for preexposure prophylaxis (PrEP) among pregnant people with opioid use disorder (OUD). This is a single-site retrospective cohort study of pregnant people admitted for management of OUD at an urban, tertiary care center from 2013 to 2022. PrEP eligibility was defined based on (1) modified American College of Obstetricians and Gynecologists' (ACOG) 2014 criteria: diagnosis of a sexually transmitted infection (STI), engagement in transactional sex work, intravenous drug use (IVDU), or incarceration and (2) modified 2021 Centers for Disease Control (CDC) criteria: diagnosis of bacterial STI (e.g., gonorrhea or syphilis) or transactional sex work. Risk factors associated with PrEP eligibility were evaluated using chi- square or Fischer's exact tests for categorical variables and t-tests or Wilcoxon rank-sum tests for continuous variables. Multivariable regression was used to control for confounding covariates, defined as p < 0.10 on bivariate analysis. p < 0.05 was used to indicate statistical significance. A total of 132 individuals met inclusion criteria, of whom 101 (76.5%) were deemed eligible for PrEP by meeting one or more modified 2014 ACOG criteria: 42 (31.8%) were incarcerated or had one or more STIs, while 30 (22.7%) endorsed engaging in transactional sex work and 68 (58.6%) endorsed IVDU. Using modified 2021 CDC criteria, 37 (28%) met PrEP eligibility, with 12 (9.1%) diagnosed specifically with a bacterial STI and 30 (22.7%) engaging in transactional sex work. Only comorbid psychiatric illness was associated with an increased risk for PrEP eligibility based on 2014 criteria, which persisted after controlling for maternal race/ethnicity (aRR 1.52, 95% confidence interval [CI] 1.24-1.86), and 2021 criteria, which persisted after controlling for nulliparity (aRR 2.12, 95% CI 1.30-3.57). A significant number of pregnant people with OUD meet one or more criteria for PrEP, with comorbid psychiatric conditions increasing the risk of meeting criteria. · Comorbid psychiatric illness is significantly associated with high risk of PrEP eligibility.. · A large proportion of pregnant individuals with active OUD meet criteria for PrEP prescribing.. · Risk-based screening algorithms for PrEP eligibility have limitations..

Immunoblot Criteria for Diagnosis of Lyme Disease: A Comparison of CDC Criteria to Alternative Interpretive Approaches.

The current Centers for Disease Control and Prevention (CDC) interpretive criteria for serodiagnosis of Lyme disease (LD) involve a two-tiered approach, consisting of a first-tier EIA, IFA, or chemiluminescent assay, followed by confirmation of positive or equivocal results by either immunoblot or a second-tier EIA. To increase overall sensitivity, single-tier alternative immunoblot assays have been proposed, often utilizing antigens from multiple Borrelia burgdorferi strains or genospecies in a single immunoblot; including OspA and OspB in their antigen panel; requiring fewer positive bands than permitted by current CDC criteria; and reporting equivocal results. Published reports concerning alternative immunoblot assays have used relatively small numbers of LD patients and controls to evaluate novel multi-antigen assays and interpretive criteria. We compared the two most commonly used alternative immunoblot interpretive criteria (labeled A and B) to CDC criteria using data from multiple FDA-cleared IgG and IgM immunoblot test kits. These single-tier alternative interpretive criteria, applied to both IgG and IgM immunoblots, demonstrated significantly more false-positive or equivocal results in healthy controls than two-tiered CDC criteria (12.4% and 35.0% for Criteria A and B, respectively, versus 1.0% for CDC criteria). Due to limited standardization and high false-positive rates, the presently evaluated single-tier alternative immunoblot interpretive criteria appear inferior to CDC two-tiered criteria.

Optimization and validation of flow cytometry method for quantification of SARS-CoV-2 antigen-reactive human memory T cells

A proper and representative monitoring of SARS-CoV-2 herd immunity including a long-term health impact on recovered patients and vaccinated individuals is of great importance. For this, a monitoring campaign should assesses both humoral and T-cell immune arms. Upon that, analyzing antigen specific-cell activation and cellular phenotype are informative. We developed a flow cytometry method for detection of intracellular IFN-producing antigen-reactive T cells after exposure of human peripheral blood mononuclear cells (PBMC) to SARS-CoV-2 virus antigens. The method was validated according to the following characteristics: sensitivity, specificity, precision, and robustness. We used positive samples from donors recovered from COVID-19 and negative samples from donors who had no contact with COVID-19 patients and lacking antibodies to SARS-CoV-2. All samples were tested by laboratory methods. Peripheral blood mononuclear cells were isolated from donor blood by centrifugation in a Ficoll density gradient. Specific T cells were stimulated with S-protein as well as N, M, ORF3a, and ORF7a protein peptides to count IFN-producing T cells by flow cytometer. The data were statistically analyzed. The area limited by ROC-curve and false positive rate (AUC) for CD4 and CD8 cells was from 0.97 to 1.00. Precision was considered acceptable because the coefficient of variation for all PBCM did not exceed 20%. Robustness was confirmed for frozen and freshly prepared PBMC samples. The thresholds levels to recognize immune and non-immune samples were defined for CD4-positive T-cells (0.029%) and CD8-positive T-cells (0.0640.068%). Also, acceptance criteria for positive and negative controls were defined. Based on the validation, the suitability of the method Evaluation of antigen-reactive T cells that produce intracellular IFN in response to SARS-CoV-2 virus antigens by flow cytometry was confirmed. The method allows for reliable data that was used to characterize standard control samples for internal quality control of TigraTest SARS-CoV-2 kits.

Adaptive Smoothing for Visual Improvement of Image Quality via the p(x)-Laplacian Operator Effects of the p(x)-Laplacian Smoothing Operator on Digital Image Restoration: Contribution to an Adaptive Control Criterion

This article concerns the improvement of digital image quality using mathematical tools such as nonlinear partial differential operators. In this paper, to perform smoothing on digital images, we propose to use the p(x)-Laplacian operator. Its smoothing power plays a main role in the restoration process. This enables us to dynamically process certain areas of an image. We used a mathematical model of image regularisation that is described by a nonlinear diffusion Equation (this diffusion is modelled by the p(x)-Laplacian operator). We implemented the continuous model in order to observe the steps of the regularisation process to understand the effects of the different parameters of the model on an image. This will enable parameters to be used and adapted in order to provide a proposed solution.

Simplified optimization of inerter-enabled tuned mass damper for lightweight-oriented seismic response mitigation of long-span domes

Suspending tuned mass dampers (TMDs) from long-span domes has been studied to mitigate seismic responses of long-span domes. However, the strict weight limitations on the suspension mass in conventional tuned mass dampers (TMDs) hinder their widespread adoption. To address this issue, we introduce the inerter-enabled tuned mass damper (IeTMD) that consists of a suspension mass, tuning spring, and a tuned viscous mass damper (TVMD) sub-system into the seismic vibration mitigation of long-span domes. Under the assumption that long-span domes remain within the elastic range and adhere to the small deformation hypothesis, we have proposed simplified design formulae for IeTMDs, guided by the lightweight-based seismic vibration control criterion. Parametric studies are conducted to illustrate the degree to which an IeTMD can improve the performance of the long-span dome when its key parameters change within certain ranges. The effectiveness of the design strategy in exploiting the damping enhancement effect is confirmed. Time history responses of a benchmark long-span dome demonstrate that the IeTMD has high control efficiency, as bi-directional displacements, accelerations, and base shear are significantly reduced. Comparative analyses between the proposed IeTMD and conventional TMD are conducted. Results show that the IeTMD designed by the simplified design formulae can achieve the target control performance with less suspension mass. Furthermore, the frequency analysis shows that the proposed IeTMD contains a wider control frequency band than conventional TMD, illustrating the promising approach for long-span domes.

An Assessment Framework for Human Health Risk from Heavy Metals in Coal Chemical Industry Soils in Northwest China

Coal chemical industry (CCI) sites are characterized by complex environmental media, combined heavy metal pollution, and diverse exposure routes. However, existing human health risk assessment (HHRA) methods have multiple drawbacks, such as their small scope of application, limited assessment factors, and insufficient case applications. After 128 soil samples were collected, the contents of Be, V, Ni, Cu, Zn, As, Cd and Hg in the soils were analyzed based on general risk assessment guideline of China. Then, risk levels were calculated based on oral ingestion, skin contact and inhalation as the main exposure routes to compare and screen priority heavy metals. Furthermore, control values were identified through a contribution rate calculation model when CR &gt; 10−6 or HQ &gt; 1. As reference values, risk thresholds were proposed for heavy metals, and then a soil HHRA framework for the CCI site was constructed. Under the three exposure routes, the total CR was As &gt; 10−6, and the total HQ was 1 &gt; As &gt; Cd; the HHRs related to As and V via the oral ingestion, dermal contact, and inhalation pathways were 76.67%, 13.13%, and 10.18% and 1.66%, 0, and 98.34%, respectively. The risk control value of As was 1.59 mg/kg and that of V was 25.1 mg/kg. Based on these results, the threshold values for priority heavy metals should be based on comprehensive considerations of the elemental background of a specific area, the contaminant criteria in different areas, the regional industrial development plan, and the most important control criterion, as well as the control value. Through the development of an HHRA framework and case verification, the authors of this article aim to guide CCI managers in screening priority heavy metals, formulating protection measures, developing improved operational procedures and improving the HHRA system for polluted CCI sites.

Bactabolize is a tool for high-throughput generation of bacterial strain-specific metabolic models.

Metabolic capacity can vary substantially within a bacterial species, leading to ecological niche separation, as well as differences in virulence and antimicrobial susceptibility. Genome-scale metabolic models are useful tools for studying the metabolic potential of individuals, and with the rapid expansion of genomic sequencing there is a wealth of data that can be leveraged for comparative analysis. However, there exist few tools to construct strain-specific metabolic models at scale. Here, we describe Bactabolize, a reference-based tool which rapidly produces strain-specific metabolic models and growth phenotype predictions. We describe a pan reference model for the priority antimicrobial-resistant pathogen, Klebsiella pneumoniae, and a quality control framework for using draft genome assemblies as input for Bactabolize. The Bactabolize-derived model for K. pneumoniae reference strain KPPR1 performed comparatively or better than currently available automated approaches CarveMe and gapseq across 507 substrate and 2317 knockout mutant growth predictions. Novel draft genomes passing our systematically defined quality control criteria resulted in models with a high degree of completeness (≥99% genes and reactions captured compared to models derived from matched complete genomes) and high accuracy (mean 0.97, n=10). We anticipate the tools and framework described herein will facilitate large-scale metabolic modelling analyses that broaden our understanding of diversity within bacterial species and inform novel control strategies for priority pathogens.

Bactabolize is a tool for high-throughput generation of bacterial strain-specific metabolic models

Metabolic capacity can vary substantially within a bacterial species, leading to ecological niche separation, as well as differences in virulence and antimicrobial susceptibility. Genome-scale metabolic models are useful tools for studying the metabolic potential of individuals, and with the rapid expansion of genomic sequencing there is a wealth of data that can be leveraged for comparative analysis. However, there exist few tools to construct strain-specific metabolic models at scale. Here, we describe Bactabolize, a reference-based tool which rapidly produces strain-specific metabolic models and growth phenotype predictions. We describe a pan reference model for the priority antimicrobial-resistant pathogen, Klebsiella pneumoniae, and a quality control framework for using draft genome assemblies as input for Bactabolize. The Bactabolize-derived model for K. pneumoniae reference strain KPPR1 performed comparatively or better than currently available automated approaches CarveMe and gapseq across 507 substrate and 2317 knockout mutant growth predictions. Novel draft genomes passing our systematically defined quality control criteria resulted in models with a high degree of completeness (≥99% genes and reactions captured compared to models derived from matched complete genomes) and high accuracy (mean 0.97, n=10). We anticipate the tools and framework described herein will facilitate large-scale metabolic modelling analyses that broaden our understanding of diversity within bacterial species and inform novel control strategies for priority pathogens.

The OSCAR-MP Consensus Criteria for Quality Assessment of Retinal Optical Coherence Tomography Angiography.

Optical coherence tomography angiography (OCTA) is a noninvasive high-resolution imaging technique for assessing the retinal vasculature and is increasingly used in various ophthalmologic, neuro-ophthalmologic, and neurologic diseases. To date, there are no validated consensus criteria for quality control (QC) of OCTA. Our study aimed to develop criteria for OCTA quality assessment. To establish criteria through (1) extensive literature review on OCTA artifacts and image quality to generate standardized and easy-to-apply OCTA QC criteria, (2) application of OCTA QC criteria to evaluate interrater agreement, (3) identification of reasons for interrater disagreement, revision of OCTA QC criteria, development of OCTA QC scoring guide and training set, and (4) validation of QC criteria in an international, interdisciplinary multicenter study. We identified 7 major aspects that affect OCTA quality: (O) obvious problems, (S) signal strength, (C) centration, (A) algorithm failure, (R) retinal pathology, (M) motion artifacts, and (P) projection artifacts. Seven independent raters applied the OSCAR-MP criteria to a set of 40 OCTA scans from people with MS, Sjogren syndrome, and uveitis and healthy individuals. The interrater kappa was substantial (κ 0.67). Projection artifacts were the main reason for interrater disagreement. Because artifacts can affect only parts of OCTA images, we agreed that prior definition of a specific region of interest (ROI) is crucial for subsequent OCTA quality assessment. To enhance artifact recognition and interrater agreement on reduced image quality, we designed a scoring guide and OCTA training set. Using these educational tools, 23 raters from 14 different centers reached an almost perfect agreement (κ 0.92) for the rejection of poor-quality OCTA images using the OSCAR-MP criteria. We propose a 3-step approach for standardized quality control: (1) To define a specific ROI, (2) to assess the occurrence of OCTA artifacts according to the OSCAR-MP criteria, and (3) to evaluate OCTA quality based on the occurrence of different artifacts within the ROI. OSCAR-MP OCTA QC criteria achieved high interrater agreement in an international multicenter study and is a promising QC protocol for application in the context of future clinical trials and studies.

Digital Control and Management of Water Supply Infrastructure Using Embedded Systems and Machine Learning

Water supply infrastructure operational efficiency has a direct impact on the quantity of portable water available to end users. It is commonplace to find water supply infrastructure in a declining operational state in rural and some urban centers in developing countries. Maintenance issues result in unabated wastage and shortage of supply to users. This work proposes a cost-effective solution to the problem of water distribution losses using a Microcontroller-based digital control method and Machine Learning (ML) to forecast and manage portable water production and system maintenance. A fundamental concept of hydrostatic pressure equilibrium was used for the detection and control of leakages from pipeline segments. The results obtained from the analysis of collated data show a linear direct relationship between water distribution loss and production quantity; an inverse relationship between Mean Time Between Failure (MTBF) and yearly failure rates, which are the key problem factors affecting water supply efficiency and availability. Results from the prototype system test show water supply efficiency of 99% as distribution loss was reduced to 1% due to Line Control Unit (LCU) installed on the prototype pipeline. Hydrostatic pressure equilibrium being used as the logic criteria for leak detection and control indeed proved potent for significant efficiency improvement in the water supply infrastructure.

QFD-Driven Rotational Moulding Optimization and Quality Control to Reduce Defects and Increase Efficiency in LLDPE Fuel Tank Production

The present study utilized a House of Quality (HoQ) methodology to develop a fuel tank manufactured using the rotational moulding process, employing LLDPE material. In order to methodically tackle this issue, three House of Quality (HoQ) charts were created, outlining consumer demands, functional necessities, and production control parameters. The results of the study emphasize the critical significance of identifying and adapting essential customer requirements, functional prerequisites, and production control parameters throughout the design and production phases of rotational moulded fuel tanks. The inquiry findings emphasized that the major customer requirements were on the provision of a fuel tank that possesses qualities of strength, longevity, reliability, and cost-effectiveness, while also ensuring a prolonged lifespan and an aesthetically pleasing external appearance. Furthermore, it was determined that the material qualities and tank design are the most crucial functional requirements. In addition, the precise regulation of oven temperature and the automation of the moulding process have been identified as crucial control criteria in guaranteeing the quality and functionality of the fuel tanks.

MsQuality: an interoperable open-source package for the calculation of standardized quality metrics of mass spectrometry data.

Multiple factors can impact accuracy and reproducibility of mass spectrometry data. There is a need to integrate quality assessment and control into data analytic workflows. The MsQuality package calculates 43 low-level quality metrics based on the controlled mzQC vocabulary defined by the HUPO-PSI on a single mass spectrometry-based measurement of a sample. It helps to identify low-quality measurements and track data quality. Its use of community-standard quality metrics facilitates comparability of quality assessment and control (QA/QC) criteria across datasets. The R package MsQuality is available through Bioconductor at https://bioconductor.org/packages/MsQuality.

Fixed/preassigned-time output synchronization for T–S fuzzy complex networks via quantized control

This article is devoted to the analysis of fixed-time (FXT) and preassigned-time (PAT) output synchronization for T–S fuzzy complex networks (CNs). Firstly, to improve transmission efficiency of information, a kind of pure power-law control strategy with logarithmic quantization is designed and the power-law terms have only one free parameter. Then, by applying FXT stability theorem as well as inequality skills, some compact criteria are obtained to achieve FXT output synchronization of T–S fuzzy CNs, and the restriction on the output matrix with positive definite and diagonal form is removed. Furthermore, the PAT output synchronization of T–S fuzzy CNs is further explored by developing a quantized control scheme with power-law form. Three numerical examples in the end are given to attest the proposed control design and criteria.

Functional Response of Biomechanical Prostheses. Controllability Criteria of their Inner Variables

Functional Response of Biomechanical Prostheses. Controllability Criteria of their Inner Variables

Use of Electronic Clinical Data to Track Incidence and Mortality for SARS-CoV-2–Associated Sepsis

Efforts to quantify the burden of SARS-CoV-2-associated sepsis have been limited by inconsistent definitions and underrecognition of viral sepsis. To describe the incidence and outcomes of SARS-CoV-2-associated sepsis vs presumed bacterial sepsis using objective electronic clinical criteria. This retrospective cohort study included adults hospitalized at 5 Massachusetts hospitals between March 2020 and November 2022. SARS-CoV-2-associated sepsis was defined as a positive SARS-CoV-2 polymerase chain reaction test and concurrent organ dysfunction (ie, oxygen support above simple nasal cannula, vasopressors, elevated lactate level, rise in creatine or bilirubin level, and/or decline in platelets). Presumed bacterial sepsis was defined by modified US Centers for Disease Control and Prevention adult sepsis event criteria (ie, blood culture order, sustained treatment with antibiotics, and organ dysfunction using identical thresholds as for SARS-CoV-2-associated sepsis). Trends in the quarterly incidence (ie, proportion of hospitalizations) and in-hospital mortality for SARS-CoV-2-associated and presumed bacterial sepsis were assessed using negative binomial and logistic regression models. This study included 431 017 hospital encounters from 261 595 individuals (mean [SD] age 57.9 [19.8] years, 241 131 (55.9%) females, 286 397 [66.5%] from academic hospital site). Of these encounters, 23 276 (5.4%) were from SARS-CoV-2, 6558 (1.5%) had SARS-CoV-2-associated sepsis, and 30 604 patients (7.1%) had presumed bacterial sepsis without SARS-CoV-2 infection. Crude in-hospital mortality for SARS-CoV-2-associated sepsis declined from 490 of 1469 (33.4%) in the first quarter to 67 of 450 (14.9%) in the last (adjusted odds ratio [aOR], 0.88 [95% CI, 0.85-0.90] per quarter). Crude mortality for presumed bacterial sepsis was 4451 of 30 604 patients (14.5%) and stable across quarters (aOR, 1.00 [95% CI, 0.99-1.01]). Medical record reviews of 200 SARS-CoV-2-positive hospitalizations confirmed electronic health record (EHR)-based SARS-CoV-2-associated sepsis criteria performed well relative to sepsis-3 criteria (90.6% [95% CI, 80.7%-96.5%] sensitivity; 91.2% [95% CI, 85.1%-95.4%] specificity). In this retrospective cohort study of hospitalized adults, SARS-CoV-2 accounted for approximately 1 in 6 cases of sepsis during the first 33 months of the COVID-19 pandemic. In-hospital mortality rates for SARS-CoV-2-associated sepsis were high but declined over time and ultimately were similar to presumed bacterial sepsis. These findings highlight the high burden of SARS-CoV-2-associated sepsis and demonstrate the utility of EHR-based algorithms to conduct surveillance for viral and bacterial sepsis.

İnsan immün yetmezlik virüsü ile enfekte hastalarda sifiliz ko-enfeksiyonunun değerlendirilmesi ve rapid plasma reagin (RRP) titresinin sifiliz evresine göre takibi

Aim: Syphilis co-infection in HIV-infected patients is associated by a delayed serological response. The aim of this study is to obtain current data on the frequency of HIV/syphilis co-infection, the monitoring of rapid plasma reagin (RPR) titer after treatment, and factors affecting the serologic response. Methods: Serological tests for syphilis of HIV patients followed between January 2015 and March 2023 were evaluated retrospectively. Demografic data (age, sex), level of HIV RNA, RPR, Treponema pallidum haemagglutination test (TPHA), and syphilis stage were obtained from hospital electronic database. Serological response was defined according to Centers for Disease Control and Prevention (CDC) criteria. Results: Syphilis co-infection was detected in 36.2% of the patients, all of them were male. Distribution of syphilis stage was primary 2.9%, secondary 9.7%, latent 80.6%, and neurosyphilis 6.8%, respectively. All patients with primary, secondary, and neurosyphilis had ≥4-fold decrease in RPR titer within 12 months after treatment, while two patients with latent syphilis didn’t have a decrease in titer within 12-24 months. Overall serologic response was 95.8%. Comparing the time to a 4-fold decrease in the RPR titer in terms of syphilis stage, there was no statistically significant difference. Patients with initial RPR titer &amp;gt;1: 32 achieved faster serologic response than those with initial RPR titer ≤1: 32. Conclusion: HIV/syphilis coinfection rate was notably high. It is promising that most patients had a serologic response within the time-frame defined by the CDC. It should be considered that treatment response may take longer in patients with an initial RPR titer ≤32. Further prospective studies are needed to understand the factors associated with serologic response in HIV/syphilis co-infected patients.

Fully automated production of [11C]PiB for clinical use on Trasis-AllinOne synthesizer module

Pittsburgh compound B ([11C]PiB) was the first broadly applied radiotracer with specificity for amyloid-β (Aβ) peptide aggregates in the brain and has since been established as the gold standard for positron emission tomography (PET) employed for clinical in vivo imaging of Aβ plaques, used for imaging applications of Alzheimer's disease (AD), related dementia, and other tauopathies. The use of [11C]PiB for routine PET studies is dependent on the production capabilities of each radiochemistry laboratory, subsequently a continuous effort is made to develop suitable and sustainable methods on a variety of auto synthesis platforms.Here we report a fully automated, multi-step radio synthesis, purification, and reformulation of [11C]PiB for PET imaging using the Trasis AllinOne synthesis unit, a commonly used commercial radiochemistry module. We performed three validation runs to evaluate the reproducibility and to verify that the acceptable criteria were met for the release of clinical-grade [11C]PiB using a Trasis AllinOne auto radiosynthesis unit. Solid phase supported radiolabeling was performed through the capture of precursor (6-OH-BTA-0) on a C18 solid phase extraction (SPE) cartridge and subsequent flushing of gaseous [11C]Methyl triflate(MeOTf) through the Sep-Pak for carbon-11 (11C) N-methylation. Starting with 92.5 GBq [11C]CO2, [11C]PiB synthesis was completed in approximately 25 min after cyclotron end of bombardment with an injectable dose >7.0 GBq at end of the synthesis. The radiopharmaceutical product met all quality control criteria and specifications for use in human studies.