Advances in biomarker sciences and technology最新文献

Lean 4.0, a fusion of lean manufacturing and digital technologies, is a powerful tool for implementing Industry 4.0. Its widespread use across sectors is driven by its ability to eliminate waste, reduce errors, boost revenue, and enhance customer care and efficiency. In the healthcare sector, this fourth lean revolution is particularly beneficial, as it helps to curb wastage and enhance efficiency, leading to more effective outcomes. Lean 4.0, a globally recognized best practice for industrial organisations, has proven its worth in enhancing performance and competitiveness. Its success has led to its adoption not only in manufacturing but also in non-manufacturing sectors such as Healthcare, finance, telecommunications, construction, and logistics. Its ease of use and effectiveness make it a superior alternative to traditional medical waste management techniques. Relevant papers on Lean 4.0 for Healthcare in the current literature are identified and studied to evaluate the impact of Lean 4.0 principles in Healthcare. This review-based research studies Lean 4.0 technologies and their needs in Healthcare. It discusses sustainable support for the healthcare sphere through Lean 4.0. Paper briefs several modalities of Lean 4.0 for the healthcare domain. Finally, the paper identifies and discusses the significant applications of Lean 4.0 in Healthcare. Lean 4.0 is essential to lowering errors that lead to medical mistakes since this business deals with life-or-death situations. Healthcare institutions need to reduce their overall waste reduction. With Lean 4.0, staff members working in quality management, clinical operations, consulting, and patient experience can progress into leadership roles in the healthcare sector. Lean 4.0 technologies can reduce waste production, including employing reusable medical equipment or cutting down on packaging waste. The possible difficulty of integrating digital technologies with healthcare systems and practices is Lean 4.0's limitations for the healthcare industry. Healthcare institutions can use refillable syringes and other disposable items to reduce waste rather than disposable plastic syringes. In future, healthcare institutions may save costs and lessen their environmental effect by minimising trash by using lean 4.0 technologies.

The progress made in the field of nanotechnology has resulted in the development of nanomedicine agents, which have demonstrated their efficacy as a promising clinical tool in the fight against different types of cancers. Furthermore, Nanomedicine products possess the potential to achieve intricate targeting strategies and multifunctionality. Currently, nanoparticles possess diverse applications across various scientific disciplines and serve as a crucial component in contemporary medical practices. The specimens have undergone analysis for diverse clinical purposes, including serving as drug carriers, delivering tumor genes, and functioning as contrast compounds in imaging. Diverse nanomaterials derived from organic, inorganic, lipid, or glycan compounds, in addition to synthetic polymers, have been employed to advance and enhance novel cancer therapeutics. The present review centers on the utilization of nanoparticles in clinical settings for the purposes of cancer diagnosis and treatment, with a particular emphasis on their function as drug carriers and targeted therapy agents.

Background

Methodology

Results

Objective

To explore whether differences between male rats on the next day of mating and on the day of mating can be reflected by the urine proteome.

Methods

Urine samples were collected from male Sprague-Dawley rats on the day of mating and the next day of mating. Urine samples were analysed by the label-free quantitative proteomics technique of high-performance liquid chromatography tandem mass spectrometry (LC-MS/MS). Differential proteins of the urine proteome were analysed for protein function and biological pathways.

Results

54 differential proteins were identified by comparing the urine proteome of rats on the next day of mating with that on the day of mating, and nearly two-thirds of the differential proteins were related to spermatogenesis.

Conclusions

The urine proteome has the potential to reflect spermatogenesis without interfering with it.

Introduction

Methods

Results

Conclusion

Background

Methodology

Results

Conclusion

The current study is related to fabrication of point-of-care molecularly imprinted paper-based analytical devices, specifically related to ovarian cancer early stage detection. The task involves creating a paper coated with silver nanoparticles (AgNPs) that can be used as a transducer via surface enhanced Raman spectroscopy (SERS) to detect the threshold level of the biomarker lysophosphatidic acid (LPA) as a template molecule to diagnose ovarian cancer. MIPs are synthetic receptors designed for a targeted molecule which are prepared from polymers in the presence of target such as small molecules, proteins or cells etc. Removal of the template results in cavities which are structurally and electrostatically complementary to the template molecule. The molecularly imprinted polymer (MIP) layer was anchored on vinyl trimethoxy silane modified-paper, which served as a detector by hydrolytically modifying the paper surface with vinyl trimethoxy silane. To detect LPA in serum samples for ovarian cancer, MIP-paper based on SERS was developed. Patients with benign ovarian tumors had an LPA level of 7.73 μM whereas those with ovarian cancer have a level of 16.99 μM. A healthy person's LPA level is 2.92 μM. Consequently, the rise in LPA levels may aid in the early detection of ovarian cancer. The study refers to the use of a point of care device to diagnose ovarian cancer early, which should be simple, effective, and cost-effective. The analytical tool in the study is a sensor with high selectivity and sensitivity, quick assay times, and inexpensive costs. For LPA in serum, the binding constant of modified paper-based MIP ranges from 11.00 μM to 0.08 μM. The amalgamation of nanoparticles on 2D-paper with MIP have lead to develop sensor which can effectively select LPA in untreated real samples like serum.

Faecal Microbial Transplantation (FMT), have been shown to be successfully managed along with a variety of gastrointestinal disorders, including Clostridioides difficile infection (CDI), inflammatory bowel disease (IBD), and irritable bowel syndrome (IBS). FMT is a medical procedure that involves a donor transferring healthy gut bacteria to the recipient. The effectiveness of FMT is thought to be due to the ability of the healthy gut to restore balance to the recipient's microbiome, which is the community of microorganisms that inhabit the gastrointestinal tract. One of the key advantages of FMT is that it is a relatively simple and low-cost treatment option, compared to other therapies that may be more invasive or require long-term medication use. However, FMT is not without its limitations, including the potential for the transfer of infectious agents from the donor to the recipient and the potential for negative side effects in some patients. In this research, we discuss the current state of the evidence on FMT, including its potential benefits and risks, as well as future directions for research in this area.

Cognitive computing represents a groundbreaking development in healthcare, encompassing technological platforms that emulate the human brain's functionality. While cloud computing offers on-demand internet access to computing resources and services, cognitive computing focuses on modelling human mental processes to tackle complicated issues. Cognitive computing enhances human decision-making by integrating reasoning, machine learning, speech, natural language processing (NLP), and human-computer interaction. In the healthcare sector, it facilitates the analysis of clinical and genetic data to forecast diseases, tailor therapies, and elevate drug development. Additionally, it combines data analysis with adaptive page displays to tailor content based on the audience. Relevant papers in cognitive computing for healthcare were identified and studied. This paper aims to undertake an extensive scopic review of the pertinent literature from various sources, including articles and documents from numerous journals and conference proceedings. It delves into the need for cognitive computing in healthcare, elucidates supportive technologies, and expounds on its features within the healthcare domain. Furthermore, it identifies and discusses the substantial applications of cognitive computing in healthcare. These systems utilise computer models to replicate human cognitive processes, streamlining administrative tasks through artificial intelligence and cognitive computing. As a result, healthcare administrators can allocate more of their valuable time to patient care. Cognitive computing enhances outcomes and practitioner productivity and improves treatment decisions. The self-learning system of cognitive computing relies on real-time patient data, medical transcripts, and other pertinent information. These technologies can reduce the administrative burden on healthcare workers by automating tasks such as invoicing, claims processing, and appointment scheduling. This technology is poised to become increasingly indispensable in precision medicine.

Background

The prognosis for glioma patients remains grim despite aggressive treatment approaches. Current molecular profiles have limitations in predicting glioma recurrence, highlighting the need for new and improved prognostic biomarkers. We investigated whether the growth kinetics of patient-derived glioma cultures (PDGCs) can offer valuable prognostic insights to predict tumor recurrence. Additionally, we examined the expression of glial-mesenchymal transition (GMT) markers in PDGCs to assess their potential as additional prognostic biomarkers.

Methods

130 patients diagnosed with primary glioma via MRI scans were prospectively enrolled. Surgical tumor tissues were collected from all participants and used to establish patient-derived glioma cultures (PDGCs). The growth kinetics and colony-forming ability of the respective PDGCs were calculated to derive proliferation index (PI) for each patient. Progression-free survival (PFS) and overall survival (OS) served as the primary outcome measures.

Results

We established short-term glioma cultures in 98 clinical samples, regardless of the CNS WHO tumor grade, IDH1/2 mutation and 19/19q codeletion status and maintained active cell proliferation for at least 10–12 passages. However, we observed two distinct growth kinetic patterns among PDGCs. Based on their proliferation index (PI), we categorized patients into either high proliferation index (HPI) or low proliferation index (LPI) group. Furthermore, we noted a differential expression profile of GMT markers between HPI and LPI patients. The proliferation index (PI) exhibited a significant correlation with progression-free survival (PFS), while the expression of GMT marker vimentin was associated with overall survival (OS).

Conclusion

The PDGC-derived Proliferation Index (PI) can serve as a predictive tool for tumor recurrence, independent of clinical or tumor-related factors. Moreover, reduced vimentin expression is a positive indicator for glioma patients' overall survival status.