BACKGROUND: Dual-person inspection in IVF laboratories cannot fully avoid mix-ups or embryo transfer errors, and data transcription or entry is time-consuming and redundant, often leading to delays in completing medical records.
METHODS: This study introduced a workflow-based RFID tag witnessing and real-time information entry platform for addressing these challenges. To assess its potential in reducing mix-ups, we conducted a simulation experiment in semen preparation to analyze its error correction rate. Additionally, we evaluated its impact on work efficiency, specifically in operation and data entry. Furthermore, we compared the cycle costs between paper labels and RFID tags. Finally, we retrospectively analyzed clinical outcomes of 20,424 oocyte retrieval cycles and 15,785 frozen embryo transfer cycles, which were divided into paper label and RFID tag groups.
RESULTS: The study revealed that comparing to paper labels, RFID tag witnessing corrected 100% of tag errors, didn\'t affect gamete/embryo operations, and notably shorten the time of entering data, but the cycle cost of RFID tags was significantly higher. However, no significant differences were observed in fertilization, embryo quality, blastocyst rates, clinical pregnancy, and live birth rates between two groups.
CONCLUSIONS: RFID tag witnessing doesn\'t negatively impact gamete/embryo operation, embryo quality and pregnancy outcomes, but it potentially reduces the risk of mix-ups or errors. Despite highly increased cost, integrating RFID tag witnessing with real-time information entry can remarkably decrease the data entry time, substantially improving the work efficiency. This workflow-based management platform also enhances operational safety, ensures medical informational integrity, and boosts embryologist\'s confidence.

Microphthalmia transcription factor (MiT) family translocation renal cell carcinoma (tRCC) is a rare, aggressive, and heterogeneous subtype of kidney cancer, which is not well characterized. Since genetic alterations are always associated with carcinogenesis, and proteins are the major executors of biological features, multi-omics studies can reveal the systematic tRCC biological process comprehensively. Here, we describe the proteogenomic workflow for characterization of tRCC in detail to provide the knowledge foundation for integrated proteogenomic analysis of tRCC and other malignant tumors in the future.

BACKGROUND: This case report highlights the importance of standardized and fully digital sequential treatment in complex occlusal rehabilitation cases. To fully resolve the patient\'s dental needs, such cases often require multidisciplinary interventions including periodontal therapy, endodontic treatment, anterior esthetics, implant restoration, and prosthetic rehabilitation. A fully digital workflow (including facial scanners, intraoral scanners, jaw motion tracking systems, virtual articulators, and computer-aided design software) streamlined the complex treatment, enhancing workflow simplicity, efficiency, visibility, and precision.
METHODS: The patient presented with decreased chewing efficiency of the upper and lower prostheses, along with unsatisfactory esthetic appearance of the anterior teeth. After physical examination and radiological assessment, this complex occlusal rehabilitation case required periodontal therapy, anterior esthetic enhancement, implant restoration, and fixed prosthetic rehabilitation. Therefore, a fully digital workflow was adopted. Full-crown prostheses were placed on teeth 13, 23, and 34; a fixed bridge encompassed positions 32 to 42, and single implant crowns were placed on teeth 35 and 36. Implant-supported fixed bridges were constructed for teeth 12 to 22 and 44 to 46, anchored by implants at teeth 12, 22, 44, and 46. All definitive prostheses were fabricated from zirconia ceramics, chosen for their durability and esthetic characteristics. Finally, restorations with satisfactory esthetic and functional characteristics were seated, preserving the tooth and its supporting structures. During treatment and follow-up, the T-scan occlusal analysis system was utilized to continuously monitor and guide the adjustment of occlusal distribution across the patient\'s dental arches. After 18 months, the patient remains satisfied with the definitive restorations.
CONCLUSIONS: This report is intended to help dentists understand and implement standardized and fully digital workflows during the management of complex occlusal rehabilitation cases; it may also facilitate harmonious integration of esthetic and functional characteristics.

OBJECTIVE: To review recent advances of artificial intelligence (AI) in enhancing the efficiency and throughput of the MRI acquisition workflow in neuroimaging, including planning, sequence design, and correction of acquisition artifacts.
METHODS: A comprehensive analysis was conducted on recent AI-based methods in neuro MRI acquisition. The study focused on key technological advances, their impact on clinical practice, and potential risks associated with these methods.
RESULTS: The findings indicate that AI-based algorithms have a substantial positive impact on the MRI acquisition process, improving both efficiency and throughput. Specific algorithms were identified as particularly effective in optimizing acquisition steps, with reported improvements in workflow efficiency.
CONCLUSIONS: The review highlights the transformative potential of AI in neuro MRI acquisition, emphasizing the technological advances and clinical benefits. However, it also discusses potential risks and challenges, suggesting areas for future research to mitigate these concerns and further enhance AI integration in MRI acquisition.

BACKGROUND: Current RNA-seq analysis software for RNA-seq data tends to use similar parameters across different species without considering species-specific differences. However, the suitability and accuracy of these tools may vary when analyzing data from different species, such as humans, animals, plants, fungi, and bacteria. For most laboratory researchers lacking a background in information science, determining how to construct an analysis workflow that meets their specific needs from the array of complex analytical tools available poses a significant challenge.
RESULTS: By utilizing RNA-seq data from plants, animals, and fungi, it was observed that different analytical tools demonstrate some variations in performance when applied to different species. A comprehensive experiment was conducted specifically for analyzing plant pathogenic fungal data, focusing on differential gene analysis as the ultimate goal. In this study, 288 pipelines using different tools were applied to analyze five fungal RNA-seq datasets, and the performance of their results was evaluated based on simulation. This led to the establishment of a relatively universal and superior fungal RNA-seq analysis pipeline that can serve as a reference, and certain standards for selecting analysis tools were derived for reference. Additionally, we compared various tools for alternative splicing analysis. The results based on simulated data indicated that rMATS remained the optimal choice, although consideration could be given to supplementing with tools such as SpliceWiz.
CONCLUSIONS: The experimental results demonstrate that, in comparison to the default software parameter configurations, the analysis combination results after tuning can provide more accurate biological insights. It is beneficial to carefully select suitable analysis software based on the data, rather than indiscriminately choosing tools, in order to achieve high-quality analysis results more efficiently.

Infectious diseases are a great threat to human health. Rapid and accurate detection of pathogens is important in the diagnosis and treatment of infectious diseases. Metagenomics next-generation sequencing (mNGS) is an unbiased and comprehensive approach for detecting all RNA and DNA in a sample. With the development of sequencing and bioinformatics technologies, mNGS is moving from research to clinical application, which opens a new avenue for pathogen detection. Numerous studies have revealed good potential for the clinical application of mNGS in infectious diseases, especially in difficult-to-detect, rare, and novel pathogens. However, there are several hurdles in the clinical application of mNGS, such as: (1) lack of universal workflow validation and quality assurance; (2) insensitivity to high-host background and low-biomass samples; and (3) lack of standardized instructions for mass data analysis and report interpretation. Therefore, a complete understanding of this new technology will help promote the clinical application of mNGS to infectious diseases. This review briefly introduces the history of next-generation sequencing, mainstream sequencing platforms, and mNGS workflow, and discusses the clinical applications of mNGS to infectious diseases and its advantages and disadvantages.
传染病对人类健康产生巨大威胁。快速准确地检测出病原体对于传染病的诊断和治疗非常重要。宏基因组二代测序技术（mNGS）能无差别检测样本中所有的核酸（DNA和RNA）。随着测序和生物信息学技术的发展，mNGS正从实验室研究向临床应用迈进，为病原体检测开辟了新的途径。大量研究表明，mNGS在感染性疾病的临床应用中具有良好的潜力，尤其适用于难检测、罕见和新型病原。但是，mNGS在临床应用中仍存在一些问题:（1）缺乏通用的、可验证的工作流程和质量保证；（2）对高宿主背景和低生物量的样本不敏感；（3）缺乏对海量数据分析和报告解读的标准化指导。因此，全面了解这项新技术将有助于促进mNGS在感染性疾病中的临床应用。本文简要综述了二代测序技术的发展历史、主流测序平台和mNGS工作流程，并讨论了mNGS在感染性疾病中的临床应用及该技术的优缺点。.

Low-input proteomics, which treats tens to hundreds of mammalian cells, is the gap between standard proteomics and single-cell proteomics. Low-input proteomics is widely applicable and needs special sample preparation methods to achieve deep proteome profiling. This chapter describes protocols for the preparation and application of an easy-to-use and scalable device for processing low-input samples. Protein preconcentration, impurity removal, reduction, alkylation, digestion, and desalting are fully integrated into this workflow, and the device can be directly connected to online nanoLC-MS to avoid sample transfer.

Massive microbiome sequencing data has been generated, which elucidates associations between microbes and their environmental phenotypes such as host health or ecosystem status. Outstanding bioinformatic tools are the basis to decipher the biological information hidden under microbiome data. However, most approaches placed difficulties on the accessibility to nonprofessional users. On the other side, the computing throughput has become a significant bottleneck of many analytical pipelines in processing large-scale datasets. In this study, we introduce Parallel-Meta Suite (PMS), an interactive software package for fast and comprehensive microbiome data analysis, visualization, and interpretation. It covers a wide array of functions for data preprocessing, statistics, visualization by state-of-the-art algorithms in a user-friendly graphical interface, which is accessible to diverse users. To meet the rapidly increasing computational demands, the entire procedure of PMS has been optimized by a parallel computing scheme, enabling the rapid processing of thousands of samples. PMS is compatible with multiple platforms, and an installer has been integrated for full-automatic installation.

BACKGROUND: In emergency departments (EDs), triage nurses are under tremendous daily pressure to rapidly assess the acuity level of patients and log the collected information into computers. With self-service technologies, patients could complete data entry on their own, allowing nurses to focus on higher-order tasks. Kiosks are a popular working example of such self-service technologies; however, placing a sufficient number of unwieldy and fixed machines demands a spatial change in the greeting area and affects pretriage flow. Mobile technologies could offer a solution to these issues.
OBJECTIVE: The aim of this study was to investigate the use of mobile technologies to improve pretriage flow in EDs.
METHODS: The proposed stack of mobile technologies includes patient-carried smartphones and QR technology. The web address of the self-registration app is encoded into a QR code, which was posted directly outside the walk-in entrance to be seen by every ambulatory arrival. Registration is initiated immediately after patients or their proxies scan the code using their smartphones. Patients could complete data entry at any site on the way to the triage area. Upon completion, the result is saved locally on smartphones. At the triage area, the result is automatically decoded by a portable code reader and then loaded into the triage computer. This system was implemented in three busy metropolitan EDs in Shanghai, China. Both kiosks and smartphones were evaluated randomly while being used to direct pretriage patient flow. Data were collected during a 20-day period in each center. Timeliness and usability of medical students simulating ED arrivals were assessed with the After-Scenario Questionnaire. Usability was assessed by triage nurses with the Net Promoter Score (NPS). Observations made during system implementation were subject to qualitative thematic analysis.
RESULTS: Overall, 5928 of 8575 patients performed self-registration on kiosks, and 7330 of 8532 patients checked in on their smartphones. Referring effort was significantly reduced (43.7% vs 8.8%; P<.001) and mean pretriage waiting times were significantly reduced (4.4, SD 1.7 vs 2.9, SD 1.0 minutes; P<.001) with the use of smartphones compared to kiosks. There was a significant difference in mean usability scores for \"ease of task completion\" (4.4, SD 1.5 vs 6.7, SD 0.7; P<.001), \"satisfaction with completion time\" (4.5, SD 1.4 vs 6.8, SD 0.6; P<.001), and \"satisfaction with support\" (4.9, SD 1.9 vs 6.6, SD 1.2; P<.001). Triage nurses provided a higher NPS after implementation of mobile self-registration compared to the use of kiosks (13.3% vs 93.3%; P<.001). A modified queueing model was identified and qualitative findings were grouped by sequential steps.
CONCLUSIONS: This study suggests patient-carried smartphones as a useful tool for ED self-registration. With increased usability and a tailored queueing model, the proposed system is expected to minimize pretriage waiting for patients in the ED.

The development and optimization of Antibody-Drug Conjugates (ADCs) hinge on enhanced analytical and bioanalytical characterization, particularly in assessing critical quality attributes (CQAs). The ADC\'s potency is largely determined by the average number of drugs attached to the monoclonal antibody (mAb), known as the drug-to-antibody ratio (DAR). Furthermore, the drug load distribution (DLD) influences the therapeutic window of the ADC, defining the range of dosages effective in treating diseases without causing toxic effects. Among CQAs, DAR and DLD are vital; their control is essential for ensuring manufacturing consistency and product quality. Typically, hydrophobic interaction chromatography (HIC) or reversed-phase liquid chromatography (RPLC) with UV detector have been used to quantitate DAR and DLD in quality control (QC) environment. Recently, Native size-exclusion chromatography-mass spectrometry (nSEC-MS) proves the potential as a platformable quantitative method for characterizing DAR and DLD across various cysteine-linked ADCs in research or early preclinical development. In this work, we established and assessed a streamlined nSEC-MS workflow with a benchtop LC-MS platform, to quantitatively monitor DAR and DLD of different chemotype and drug load level cysteine-linked ADCs. Moreover, to deploy this workflow in QC environment, complete method validation was conducted in three independent laboratories, adhering to the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q2(R1) guidelines. The results met the predefined analytical target profile (ATP) and performance criteria, encompassing specificity/selectivity, accuracy, precision, linearity, range, quantification/detection limit, and robustness. Finally, the method validation design offers a reference for other nSEC-MS methods that are potentially used to determine the DAR and DLD on cysteine-linker ADCs. To the best of our knowledge, this study is the first reported systematic validation of the nSEC-MS method for detecting DAR and DLD. The results indicated that the co-validated nSEC-MS workflow is suitable for DAR and DLD routine analysis in ADC quality control, release, and stability testing.