Integration of a fully automated flow cytometry system with high robustness into a Screening Station.

In recent years, there has been an increasing demand for the detection of rare cells in drug discovery research, such as cells that have differentiated off-purpose or are required for immunogenicity evaluation. Since detection and quantification limits depend on the robustness of the experiment, inter-human differences in technique have a significant impact on the performance of the assay system. Here, we integrated flow cytometry into a cell experiment platform, Screening Station, to construct a robust assay system, examined each step of the flow cytometric pretreatment using Jurkat cells, and finally evaluated the overall assay performance. Cell detection rate when the experiment was performed manually was 48.8% ± 5.7% (CV=11.6%) versus 73.7%±2.0% (CV=2.8%) with the automated method. To further clarify the analytical performance of the automated method, 1-100 PD-1 expressing Jurkat cells were spiked with 1 × 105 Jurkat cells, and the lower limit of detection, linearity, and CV% were evaluated. Average detection rate was 69%, decision count was 0.985, and lower limit of detection was 4 cells (0.004%). We evaluated the CV% value of the number of detected cells per spiked cell and found our system to be highly robust, approximating a binomial distribution with a 69% recovery rate. In conclusion, we have integrated the Novocyte flow cytometry system into an automated experimental platform, Screening Station, to create a fully automated flow cytometric assay system with high robustness. Our platform can fulfill the technology needs of drug discovery for rare cell detection, which have intensified in recent years.

First registry of patients treated with foam sclerotherapy using a new automated microfoam preparation device (2021-2022).

Objectives: To present results for the use of an automated microfoam preparation system (AMPS) in the treatment of varicose veins in a real-world setting.Method: We performed a descriptive study based on a prospective database of patients treated with foam sclerotherapy between February 2021 and December 2022. Polidocanol foam was prepared using a capsule containing sterile air or a low-nitrogen mix. We recorded volume per session, percentage of sclerosing drug, number of sessions, release of thrombus entrapment, complications, and adverse events. A univariate descriptive analysis was performed using Stata V.16.Results: Over a 23-month period, 185 patients (84.9% women, 15.1% men) underwent 685 sessions. Median age was 51.6 years (range, 16-79 years). Thread veins were the condition treated in 68.9% of sessions, tributaries in 7.2%, and truncal veins in 22.6%. The average volume per session was as follows: thread veins, 8 mL; great saphenous vein (GSV), 6.9 mL; and small saphenous vein (SSV), 4.3 mL. The average drug concentration was as follows: thread veins, 0.18%; GSV, 1.49%; and SSV, 1.63%. The average number of sessions was 3.4 for thread veins, 2 for tributaries, 2.7 for the GSV, and 2.9 for the SSV. The occlusion rate at 15 months was 93.2% (41/43) for the great saphenous vein and 86% (13/15) for the small saphenous vein. We recorded a total of 21 complications (3.1% of sessions), 14 of which were minor complications (2% sessions), and 7 moderate adverse events (1% of sessions).Conclusions: This new device is highly versatile and can be used for preparing foam at all concentrations. It contributes to a high rate of occlusion in saphenous trunks, with a minimal number of sessions required for thread veins indicating that the system is a favorable option in the treatment of venous diseases. Additionally, the low frequency of residual pigmentation may be attributed to the system's ability to tailor the foam concentration to the individual case, thus supporting optimal outcomes.

Retrospective study investigating the performance of the SQA-vision analyser compared with manual semen analysis.

The objective of this study was to compare the results of semen analysis using the manual method and the SQA-Vision sperm analyser after four years of practice and with a large cohort of patients. This was a comparative study of 1130 cases collected for semen analysis between October 2019 and October 2023, which were analysed simultaneously and independently by different operators using the manual microscopic method and an SQA-V automated analyser. For each sample, sperm concentration, progressive motility, motility, normal morphology, and round cells count were performed. There was no significant difference between the SQA-V method and manual assessment for all sperm parameters (Mann-Whitney test p > 0.05). According to the parameter studied, there was a strong correlation (rho = 0.81) and a very high correlation (rho = 0.98) between manual assessment and the SQA-V method. In the analysis of sperm concentration, the sensitivity and specificity were 0.90 and 0.99, respectively. The sensitivity and specificity for the analysis of sperm progressive motility were 0.98 and 0.99, respectively, while the sensitivity and specificity for the analysis of sperm motility were 0.87 and 0.99, respectively. The sensitivity and specificity for the analysis of normal morphology were 0.88 and 0.99, respectively. Regarding the analysis of round cells, the sensitivity and specificity were 0.98 and 0.99, respectively. The results of this retrospective study indicate that the SQA-V system offers satisfactory performance for routine sperm analysis.

Optimizing carry-over in automated dissolution system dissoBOT for paracetamol and diclofenac sodium analysis.

In this work, an automated dissolution system (dissoBOT) was used for dissolution testing for the first time. Carry-over (CO) of the dissoBOT was determined for paracetamol (PA) and diclofenac sodium (DS), which are active pharmaceutical ingredients (APIs). Initially, partial method validation of the UV-VIS spectrophotometry method for PA and DS determination was performed by defining the limit of detection (LOD), the limit of quantification (LOQ), linear concentration range, accuracy, and precision. The LODs and LOQs were less than 0.01 mg/L for both APIs. The determined linear concentration ranges were from 1.00 mg/L to 30.00 mg/L for PA and from 0.50 mg/L to 3.50 mg/L for DS (the square of the correlation coefficient was greater than 0.9990, and the quality coefficient was less than 1.00 % for both APIs). The accuracy of the method was evaluated by calculating the recovery (Re) of the solutions of standards with known concentrations. The method for both APIs was deemed to be accurate (the average Re for PA and DS were 99.81 % and 101.43 %, respectively). Precision was evaluated by calculating the relative standard deviation (RSD). The method for PA and DS was deemed to be precise, as the RSD value for PA was 0.13 %, and for DS was 0.38 %. The volume (V) of the washing medium in both cleaning cycles performed by the dissoBOT system, as well as the medium dispensing V, were established, where the medium dispensing V was in accordance with the United States Pharmacopeia requirements. The CO of the dissoBOT system, using tap water as the washing medium, was determined to be less than 1.00 % for both APIs. The CO values for one cleaning cycle of the sampling station with a V of 2 mL was in the range of 1.24-1.54 %, for V of 5 mL was in the range of 0.78-0.93 %, and for V of 10 mL was in the range of 0.27-0.36 %. In addition, the CO of the dissoBOT, when employing two cleaning cycles of the sampling station (each V of 10 mL) was reduced (CO <0.20 %). Finally, the dissoBOT was successfully employed for the dissolution PA and DS tables.

Clustering analysis of HRCT parameters measured using a texture-based automated system: relationship with clinical outcomes of IPF.

PURPOSE: The extent of honeycombing and reticulation predict the clinical prognosis of IPF. Emphysema, consolidation, and ground glass opacity are visible in HRCT scans. To date, there have been few comprehensive studies that have used these parameters. We conducted automated quantitative analysis to identify predictive parameters for clinical outcomes and then grouped the subjects accordingly. METHODS: CT images were obtained while patients held their breath at full inspiration. Parameters were analyzed using an automated lung texture quantification system. Cluster analysis was conducted on 159 IPF patients and clinical profiles were compared between clusters in terms of survival. RESULTS: Kaplan-Meier analysis revealed that survival rates declined as fibrosis, reticulation, honeycombing, consolidation, and emphysema scores increased. Cox regression analysis revealed that reticulation had the most significant impact on survival rate, followed by honeycombing, consolidation, and emphysema scores. Hierarchical and K-means cluster analyses revealed 3 clusters. Cluster 1 (n = 126) with the lowest values for all parameters had the longest survival duration, and relatively-well preserved FVC and DLCO. Cluster 2 (n = 15) with high reticulation and consolidation scores had the lowest FVC and DLCO values with a predominance of female, while cluster 3 (n = 18) with high honeycombing and emphysema scores predominantly consisted of male smokers. Kaplan-Meier analysis revealed that cluster 2 had the lowest survival rate, followed by cluster 3 and cluster 1. CONCLUSION: Automated quantitative CT analysis provides valuable information for predicting clinical outcomes, and clustering based on these parameters may help identify the high-risk group for management.

Design Specifications for an Automated System to Deliver Instructions About Preprocedure Fasting.

PURPOSE: Many patients undergoing surgical and other medical procedures requiring sedation or anesthesia receive standardized "no eating or drinking after midnight" instructions. This "standardized" instruction does not change regardless of potential alterations in scheduling that result in significant delays in procedure start times. As a result, the duration of preprocedure fasting often far exceeds recommended requirements. A technological solution that automates the delivery of preprocedure fasting instructions to patients would likely improve the patient experience. The purpose of this study was to determine design specifications for the delivery of notifications to patients as part of an automated system. DESIGN: A qualitative study was conducted with 14 adult participants using the persona-scenario method. METHODS: Participants worked in groups to create realistic but fictitious personas and scenarios that described how individuals like themselves would interact with an automated preprocedure fasting instruction system. Data generated through the development of the scenarios were analyzed to first identify important themes, which were then interpreted into design specifications. FINDINGS: Seven women and seven men, aged 25 to 75, developed 9 persona-scenarios, which captured outpatient and inpatient preprocedure fasting experiences, as well as perspectives of individuals who were not comfortable with technology, or those for which English was not the primary spoken language. Most scenarios described preprocedure fasting instructions delivered by an automated bidirectional short message service system. Two major themes were identified as patient priorities, including: (1) enhancing communication between patients and healthcare providers; and (2) the importance of using simple technology so that a greater number of patients with varying degrees of comfort and capabilities would be able to use the system confidently. A corresponding set of proposed design specifications was devised. CONCLUSIONS: The results of this study provide actionable ways to operationalize patient-centered ideas in the design of an automated preprocedure fasting instruction system.

Clinical validation of automated depth camera-based measurement of the Fugl-Meyer assessment for upper extremity.

OBJECTIVE: Depth camera-based measurement has demonstrated efficacy in automated assessment of upper limb Fugl-Meyer Assessment for paralysis rehabilitation. However, there is a lack of adequately sized studies to provide clinical support. Thus, we developed an automated system utilizing depth camera and machine learning, and assessed its feasibility and validity in a clinical setting. DESIGN: Validation and feasibility study of a measurement instrument based on single cross-sectional data. SETTING: Rehabilitation unit in a general hospital. PARTICIPANTS: Ninety-five patients with hemiparesis admitted for inpatient rehabilitation unit (2021-2023). MAIN MEASURES: Scores for each item, excluding those related to reflexes, were computed utilizing machine learning models trained on participant videos and readouts from force test devices, while the remaining reflex scores were derived through regression algorithms. Concurrent criterion validity was evaluated using sensitivity, specificity, percent agreement and Cohen's Kappa coefficient for ordinal scores of individual items, as well as correlations and intraclass correlation coefficients for total scores. Video-based manual assessment was also conducted and compared to the automated tools. RESULT: The majority of patients completed the assessment without therapist intervention. The automated scoring models demonstrated superior validity compared to video-based manual assessment across most items. The total scores derived from the automated assessment exhibited a high coefficient of 0.960. However, the validity of force test items utilizing force sensing resistors was relatively low. CONCLUSION: The integration of depth camera technology and machine learning models for automated Fugl-Meyer Assessment demonstrated acceptable validity and feasibility, suggesting its potential as a valuable tool in rehabilitation assessment.

Development and validation of an automated robotic system for preparation of embryo culture dishes.

OBJECTIVE: To study the development and clinical validation of the ART Pipetting Robot for the IVF Laboratory (APRIL), a liquid-handling robot customized for the precise preparation of microdroplet culture dishes in the field of in vitro fertilization (IVF). DESIGN: A prospective randomized study conducted at an academic IVF center comparing mouse and human embryo outcomes and quantitative measures of accuracy in embryo dishes prepared using APRIL compared with standard manual preparation. SETTING: Academic IVF center. SUBJECTS: The study involved the assessment of the automated culture dish preparation system, APRIL, compared with manual preparation methods in the context of IVF treatment. INTERVENTION: ART Pipetting Robot for the IVF Laboratory is an enclosed liquid-handling robot equipped with custom three-dimensional-printed adapters and designed to dispense embryo culture media and mineral oil into microdroplet culture dishes. MAIN OUTCOME MEASURES: The study evaluated the precision and consistency of APRIL in culture dish preparation by looking at droplet mass, pH of prepared media droplets, and mouse and human embryo development rates. Clinical implementation was assessed by comparing embryo development and outcomes in dishes prepared by APRIL and human embryologists. RESULTS: Compared with embryo culture dishes prepared using standard manual procedures, embryo culture dishes prepared using APRIL demonstrated a greater than 10-fold improvement in consistency (coefficient of variation, 0.46% vs. 6%-7%), maintained optimal pH levels (pH range, 7.281-7.33 vs. 7.275-7.311), and had a greater mouse embryo blastocyst rate (100% vs. 90%-91%). Human embryos cultured in dishes prepared by APRIL had a higher rate of development on days 3 (92.4% vs. 82.6%) and 5 (19.75% vs. 15.57%), and a total number of usable embryos (50.3% vs. 46.1%) compared with manually prepared dishes, although the last two outcomes did not reach statistical significance. CONCLUSION: The results suggest that the use of an automated robotic system for preparation of embryo culture dishes may improve accuracy and outcome measures while reducing the need for trained laboratory personnel to prepare the dishes manually.

Appetitively motivated tasks in the IntelliCage reveal a higher motivational cost of spatial learning in male than female mice.

The IntelliCage (IC) permits the assessment of the behavior and learning abilities of mice in a social home cage context. To overcome water deprivation as an aversive driver of learning, we developed protocols in which spatial learning is motivated appetitively by the preference of mice for sweetened over plain water. While plain water is available at all times, only correct task responses give access to sweetened water rewards. Under these conditions, C57BL/6J mice successfully mastered a corner preference task with the reversal and also learned a more difficult time-place task with reversal. However, the rate of responding to sweetened water decreased strongly with increasing task difficulty, indicating that learning challenges and reduced success in obtaining rewards decreased the motivation of the animals to seek sweetened water. While C57BL/6J mice of both sexes showed similar initial taste preferences and learned similarly well in simple learning tasks, the rate of responding to sweetened water and performance dropped more rapidly in male than in female mice in response to increasing learning challenges. Taken together, our data indicate that male mice can have a disadvantage relative to females in mastering difficult, appetitively motivated learning tasks, likely due to sex differences in value-based decision-making.

Harmonization of ANA testing challenge: quantification strategy to accurately predict end-point titers avoiding serial dilution.

Despite the advantages of automated systems for antinuclear antibody (ANA) analysis, the prediction of end-point titers avoiding serial dilutions is still in progress. The aims of this study were to set a conversion table providing discriminant ranges of fluorescence signal intensity values (FI) corresponding to the end-point titers and validate this tool in a real-life laboratory setting. Eight hundred ninety-four serum samples were analyzed for ANA using Image Navigator System. In order to classify FI into non-overlapping groups corresponding to conventional end-point titers, statistical discriminant analysis was used. Validation study was performed calculating agreement and error rates between visual readings and conversion table of 1119 routine ANA positive samples. Setting of FI ranges corresponding to the end-point titers for different staining patterns was computed. For samples showing single pattern, the overall agreement between visual readings and conversion table was 98.4% for all titers ranging from 1:160 to 1:2560, of which 68.0% had the same titer and 30.4% were within ± one titer difference. Concordance rates according to ANA patterns were as follows: (1) nuclear 98.4%, of which 67.0% had the same titer and 31.4% ± one titer; (2) cytoplasmic 100%, of which 72.7% had the same titer and 27.3% than ± one titer; (3) mitotic 66.6%, of which 33.3% had more ± one titer. Our study developed a quantification method for autoantibodies titers assessment based on just one single sample dilution instead of traditional serial dilution approach, providing significant advantages in routine laboratory in terms of reduction in hand-on time and harmonization of results.

Automated high-throughput extraction system of sRNA and high-resolution melting quantitative PCR (HRM-qPCR) analysis for viroid detection.

A rare viroid disease, Orange Spotting (OS), has been associated with Coconut cadang-cadang viroid variant (named OS-CCCVd) in oil palm. The low concentration of OS-CCCVd in oil palm leaf tissues makes it tedious to obtain high-quality RNA. Various conventional extraction protocols are available for extracting RNA; however, the bottleneck to the methods is the acquisition of good yields of high-quality RNA suitable for use in viroid detection. Studies looking into the automation of magnetic bead extraction systems for viroid detection in oil palm are limited. In this study, we have compared four extraction methods, namely the MagMAX™ mirVana Total RNA isolation kit (Mag-A), MagMAX™ plant RNA isolation kit (Mag-B), modification of MagMAX™ mirVana Total RNA isolation kit (Mag-Mod) and the convention method (NETME buffer). The KingFisher Flex System uses a 96-well plate format for the three automated approaches. The major modification in the Mag-Mod protocol is the inclusion of lithium chloride solution and NETME buffer to the lysis buffer (which enhances RNA recovery) and the reduction in the volume of reagents used per reaction and run conditions, including time. High-quality small RNA was produced as a result of altering the buffers and reagent volume in the Mag-Mod method, which also increased sample productivity (48 samples per day) and detection sensitivity. These effects indirectly decreased the number of technical replicates in a run. Importantly, the alteration permitted the use of ground plant tissue samples with a small sample amount of 0.05- 0.1 g as opposed to the 2-4 grequired with the conventional method. The development of the modified Mag-Mod method using the 96-deep well plate with a magnetic bead system vastly increased our sample throughput, complementing the detection methods (e.g. RT-PCR and HRM-qPCR). Aside from developing an improved extraction method (Mag-Mod method), a novel HRM-qPCR assay successfully differentiated OS-CCCVd variants and identified the presence of OS-CCCVd in samples, obviating the need for Sanger Sequencing.

Research on a Magnetic Separation-Based Rapid Nucleic Acid Extraction System and Its Detection Applications.

Nucleic acid extraction represents the "first step" in molecular diagnostic experiments. The quality of this extraction serves as a fundamental prerequisite for ensuring the accuracy of nucleic acid detection. This article presents a comprehensive design scheme for a rapid automated nucleic acid extraction system based on magnetic separation. The design and implementation of the system are analyzed and investigated in-depth, focusing on the core methods, hardware control, and software control of the automated nucleic acid extraction system. Additionally, a study and evaluation were carried out concerning the nucleic acid extraction and detection aspects encompassed by the system. The results demonstrate that the temperature deviation in the lysis and elution fluids is approximately ±1 °C, the positioning accuracy of the system's movement is ±0.005 mm, the average magnetic bead recovery rate is 94.98%, and the average nucleic acid recovery rate is 91.83%. The developed automated system and manual methods are employed for sample extraction, enabling the isolation of highly pure nucleic acids from bacteria, blood, and animal tissues for RT-PCR detection. The instrument employs lysis temperatures ranging from 70-80 °C, elution temperature of 80 °C, and drying time of 5-10 min, with a total extraction time of less than 35 min for different sample types. Overall, the system yields high nucleic acid concentration and purity, exhibits stable instrument operation, good repeatability, high efficiency, and low cost. It meets the requirements of genetic-level research and is worthy of clinical promotion and usage.

Mathematical Method of Rational Placement of Gas Fire Sensors.

Ensuring fire safety is an important condition for the successful operation of industrial enterprises. It is necessary to detect the threat of fire before the ignition. An indicator of danger is the appearance of gas, which occurs as a result of unauthorized heating of the equipment. Gas sensors make it possible to detect the appearance of gases characteristic for the decomposition of materials at the stage of smouldering and pyrolysis, which cause a change in the composition of the atmosphere. This paper presents a mathematical method for the rational placement of gas analyzers in the premises of potentially hazardous industries. The rational placement of gas sensors ensures safety, taking into account economic feasibility. For the first time, an analysis of the accumulation of gas flow from the source to the ceiling, and then to the location of the sensors, was used to select the location of gas sensors. Depending on the permissible values of the gas volume, the placement and number of gas sensors are selected. The calculation of the conditions for the rational placement of gas sensors is carried out according to the most common indicators, such as carbon monoxide and hydrogen at different sizes and heights of premises.

Evaluation of VITEK® 2 AST cards (AST-N376 and AST-N397) for susceptibility testing of challenging Gram negatives.

Due to the increasing diffusion of MDR/XDR Gram-negatives it is necessary to offer reliable antibiotic susceptibility testing (AST), which also include new drugs. Here we evaluated the performances of the VITEK®2 AST-N376 and the AST-N397 cards. A collection of 180 clinical Gram-negative bacteria, producing relevant resistance mechanisms, were tested using VITEK 2 and MERLIN, in parallel. Discrepancies between the 2 systems were solved by the reference broth microdilution method. The workflow timing of the VITEK®2 system was also assessed. Overall, the VITEK®2 cards proved to be reliable in determining AST for the molecules evaluated, even if compliance with ISO acceptance criteria for accuracy assessment was not reached for some combinations and showed a short hands-on time for panels preparation. In conclusion, VITEK®2 is a valid system that ensures accurate results for AST of the molecules evaluated in this study and speeds up the workflow in the laboratory of diagnostic microbiology.

Initial validation of an intelligent video surveillance system for automatic detection of dairy cattle lameness.

Introduction: Lameness is a major welfare challenge facing the dairy industry worldwide. Monitoring herd lameness prevalence, and early detection and therapeutic intervention are important aspects of lameness control in dairy herds. The objective of this study was to evaluate the performance of a commercially available video surveillance system for automatic detection of dairy cattle lameness (CattleEye Ltd). Methods: This was achieved by first measuring mobility score agreement between CattleEye and two veterinarians (Assessor 1 and Assessor 2), and second, by investigating the ability of the CattleEye system to detect cows with potentially painful foot lesions. We analysed 6,040 mobility scores collected from three dairy farms. Inter-rate agreement was estimated by calculating percentage agreement (PA), Cohen's kappa (κ) and Gwet's agreement coefficient (AC). Data regarding the presence of foot lesions were also available for a subset of this dataset. The ability of the system to predict the presence of potentially painful foot lesions was tested against that of Assessor 1 by calculating measures of accuracy, using lesion records during the foot trimming sessions as reference. Results: In general, inter-rater agreement between CattleEye and either human assessor was strong and similar to that between the human assessors, with PA and AC being consistently above 80% and 0.80, respectively. Kappa agreement between CattleEye and the human scorers was in line with previous studies (investigating agreement between human assessors) and within the fair to moderate agreement range. The system was more sensitive than Assessor 1 in identifying cows with potentially painful lesions, with 0.52 sensitivity and 0.81 specificity compared to the Assessor's 0.29 and 0.89 respectively. Discussion: This pilot study showed that the CattleEye system achieved scores comparable to that of two experienced veterinarians and was more sensitive than a trained veterinarian in detecting painful foot lesions.

Base de datos automatizada para el control de la literatura docente

Introducción: Actualmente se impone la automatización de los datos, lo que contribuye a ganar tiempo, mejorar el rendimiento y la escalabilidad de los procesos. Objetivo: crear una base de datos automatizada (BDA) para el control de la literatura docente, en la Filial de Ciencias Médicas de Nuevitas. Métodos: Se realizó un estudio de innovación tecnológica, en el período comprendido desde octubre de 2021 hasta enero de 2022; para la recolección de datos se utilizó una encuesta, que permitió el diagnóstico de la necesidad de crear el producto terminado e identificar criterios que aportaron información primaria. Como herramienta de diseño se utilizó el gestor de base de datos Microsoft Access. Se trabajó en dos etapas: la primera donde se hizo un estudio de los documentos concernientes a la literatura docente existentes en el almacén y la segunda en la cual se trabajó en el diseño lógico y físico de la BDA. Resultados: La factibilidad del producto fue valorada de adecuada por parte de los especialistas. Conclusiones: Se recomienda la validación del producto para determinar su confiabilidad, así como la utilización del producto terminado en otras instituciones de la educación médica superior.

Introduction: Currently, the need for data automation is an imposition that contributes to reducing time, as well as improving performance and process scalability. Objective: to create an automated database (BDA) for the control of teaching literature in the Nuevitas Medical Sciences Branch. Methods: A study of technological innovation was carried out from October 2021 to January 2022. The information was obtained by means of a survey, which allowed the diagnosis of the need to create the finished product and identify criteria that provided primary information. Microsoft Access database manager was used as design tool. The work was carried out in two stages: a first stage related to the study of the documents concerning the teaching literature existing in the warehouse; the second stage that involved the logical and physical design of the BDA. Results: The feasibility of the computer product was assessed as adequate by the specialists. Conclusions: The validation of the product is recommended to determine its reliability, as well as its use in other institutions of higher medical education.

Diagnostic Performance of BD Phoenix CPO Detect Panels for Detection and Classification of Carbapenemase-Producing Gram-Negative Bacteria.

BD Phoenix CPO Detect panels can identify and classify carbapenemase-producing organisms (CPOs) simultaneously with antimicrobial susceptibility testing (AST) for Gram-negative bacteria. Detection and classification of carbapenemase producers were performed using the BD Phoenix CPO Detect panels NMIC/ID-441 for Enterobacterales, NMIC/ID-442 for nonfermenting bacteria, and NMIC-440 for both. The results were compared with those obtained using comparator methods. A total of 133 strains (32 Klebsiella pneumoniae, 37 Enterobacter cloacae complex, 33 Pseudomonas aeruginosa, and 31 Acinetobacter baumannii complex strains), including 60 carbapenemase producers (54 imipenemases [IMPs] and 6 OXA type), were analyzed. Using panels NMIC-440 and NMIC/ID-441 or NMIC/ID-442, all 54 IMP producers were accurately identified as CPOs (positive percent agreement [PPA], 100.0%; 54/54). Among the 54 IMP producers identified as CPOs using panels NMIC-440 and NMIC/ID-441, 12 and 14 Enterobacterales were not resistant to carbapenem, respectively. Among all 54 IMP producers, 48 (88.9%; 48/54) were correctly classified as Ambler class B using panel NMIC-440. Using panels NMIC-440 and NMIC/ID-442, all four OXA-23-like carbapenemase-producing A. baumannii complex strains (100.0%, 4/4) were correctly identified as CPOs, and three (75.0%, 3/4) were precisely classified as class D using panel NMIC-440. Both carbapenemase producers harboring the blaISAba1-OXA-51-like gene were incorrectly identified as non-CPOs using panels NMIC-440 and NMIC/ID-442. For detecting carbapenemase producers, the overall PPA and negative percent agreement (NPA) between panel NMIC-440 and the comparator methods were 96.7% (58/60) and 71.2% (52/73), respectively, and the PPA and NPA between panels NMIC/ID-441 or NMIC/ID-442 and the comparator methods were 96.7% (58/60) and 74.0% (54/73), respectively. BD Phoenix CPO Detect panels can successfully screen carbapenemase producers, particularly IMP producers, regardless of the presence of carbapenem resistance and can be beneficial in routine AST workflows. IMPORTANCE Simple and efficient screening methods of detecting carbapenemase producers are required. BD Phoenix CPO Detect panels effectively screened carbapenemase producers, particularly IMP producers, with a high overall PPA. As the panels enable automatic screening for carbapenemase producers simultaneously with AST, the workflow from AST to confirmatory testing for carbapenemase production can be shortened. In addition, because carbapenem resistance varies among carbapenemase producers, the BD Phoenix CPO Detect panels, which can screen carbapenemase producers regardless of carbapenem susceptibility, can contribute to the accurate detection of carbapenemase producers. Our results report that these panels can help streamline the AST workflow before confirmatory testing for carbapenemase production in routine microbiological tests.

Osteo-NeT: An Automated System for Predicting Knee Osteoarthritis from X-ray Images Using Transfer-Learning-Based Neural Networks Approach.

Knee osteoarthritis is a challenging problem affecting many adults around the world. There are currently no medications that cure knee osteoarthritis. The only way to control the progression of knee osteoarthritis is early detection. Currently, X-ray imaging is a central technique used for the prediction of osteoarthritis. However, the manual X-ray technique is prone to errors due to the lack of expertise of radiologists. Recent studies have described the use of automated systems based on machine learning for the effective prediction of osteoarthritis from X-ray images. However, most of these techniques still need to achieve higher predictive accuracy to detect osteoarthritis at an early stage. This paper suggests a method with higher predictive accuracy that can be employed in the real world for the early detection of knee osteoarthritis. In this paper, we suggest the use of transfer learning models based on sequential convolutional neural networks (CNNs), Visual Geometry Group 16 (VGG-16), and Residual Neural Network 50 (ResNet-50) for the early detection of osteoarthritis from knee X-ray images. In our analysis, we found that all the suggested models achieved a higher level of predictive accuracy, greater than 90%, in detecting osteoarthritis. However, the best-performing model was the pretrained VGG-16 model, which achieved a training accuracy of 99% and a testing accuracy of 92%.

Screening Station, a novel laboratory automation system for physiologically relevant cell-based assays.

Due to their physiological relevance, cell-based assays using human-induced pluripotent stem cell (iPSC)-derived cells are a promising in vitro pharmacological evaluation system for drug candidates. However, cell-based assays involve complex processes such as long-term culture, real-time and continuous observation of living cells, and detection of many cellular events. Automating multi-sample processing through these assays will enhance reproducibility by limiting human error and reduce researchers' valuable time spent conducting these experiments. Furthermore, this integration enables continuous tracking of morphological changes, which is not possible with the use of stand-alone devices. This report describes a new laboratory automation system called the Screening Station, which uses novel automation control and scheduling software called Green Button Go to integrate various devices. To integrate the above-mentioned processes, we established three workflows in Green Button Go: 1) For long-term cell culture, culture plates and medium containers are transported from the automatic CO2 incubator and cool incubator, respectively, and the cell culture medium in the microplates is exchanged daily using the Biomek i7 workstation; 2) For time-lapse live-cell imaging, culture plates are automatically transferred between the CQ1 confocal quantitative image cytometer and the SCALE48W automatic CO2 incubator; 3) For immunofluorescence imaging assays, in addition to the above-mentioned devices, the 405LS microplate washer allows for formalin-fixation and immunostaining of cells. By scheduling various combinations of the three workflows, we successfully automated the culture and medium exchange processes for iPSCs derived from patients with facioscapulohumeral muscular dystrophy, confirmation of their differentiation status by live-cell imaging, and confirmation of the presence of differentiation markers by immunostaining. In addition, deep learning analysis enabled us to quantify the degree of iPSC differentiation from live-cell imaging data. Further, the results of the fully automated experiments could be accessed via the intranet, enabling experiments and analysis to be conducted remotely once the necessary reagents and labware were prepared. We expect that the ability to perform clinically and physiologically relevant cell-based assays from remote locations using the Screening Station will facilitate global research collaboration and accelerate the discovery of new drug candidates.