Exploring the Impact of Artificial Intelligence on Global Health and Enhancing Healthcare in Developing Nations.

BACKGROUND: Artificial intelligence (AI), which combines computer science with extensive datasets, seeks to mimic human-like intelligence. Subsets of AI are being applied in almost all fields of medicine and surgery. AIM: This review focuses on the applications of AI in healthcare settings in developing countries, designed to underscore its significance by comprehensively outlining the advancements made thus far, the shortcomings encountered in AI applications, the present status of AI integration, persistent challenges, and innovative strategies to surmount them. METHODOLOGY: Articles from PubMed, Google Scholar, and Cochrane were searched from 2000 to 2023 with keywords including AI and healthcare, focusing on multiple medical specialties. RESULTS: The increasing role of AI in diagnosis, prognosis prediction, and patient management, as well as hospital management and community healthcare, has made the overall healthcare system more efficient, especially in the high patient load setups and resource-limited areas of developing countries where patient care is often compromised. However, challenges, including low adoption rates and the absence of standardized guidelines, high installation and maintenance costs of equipment, poor transportation and connectivvity issues hinder AI's full use in healthcare. CONCLUSION: Despite these challenges, AI holds a promising future in healthcare. Adequate knowledge and expertise of healthcare professionals for the use of AI technology in healthcare is imperative in developing nations.

Unmet needs in survivorship: Increased anxiety post oesophago-gastric cancer surgery.

INTRODUCTION: Despite significant surgical advancements in the treatment of oesophago-gastric cancer (OGC), patients often experience a considerable decline in health-related quality of life postoperatively. Psychological factors, such as hypervigilance and symptom-specific anxiety, may contribute to this. This study aimed to investigate the prevalence and trend of hypervigilance and symptom-specific anxiety in OGC survivors across treatment stages. MATERIALS AND METHODS: 103 patients with either gastric or oesophageal cancer, treated with surgery (and/or neoadjuvant chemotherapy), completed a specialist measure of oesophageal hypersensitivity (Oesophageal Anxiety and Hypervigilance Scale) at five time-points: spanning from diagnostic clinics to 6 months post-hospital discharge. RESULTS: The results indicate a trend of rising symptom-specific anxiety and hypervigilance scores over time post-hospital discharge. Total scores showed variations over time; elevated at diagnosis, decreasing between pre-operative assessment and 2-4 weeks post-hospital discharge, and rising again at between 3 and 6 months post-discharge, exceeding the average score at diagnosis. The patterns for the subscale scores for symptom-specific anxiety and hypervigilance followed a similar trend, though anxiety scores consistently exceeded hypervigilance scores at previous time-points. CONCLUSION: In noting the presence and variations of symptom-specific anxiety and hypervigilance in patients with OGC, this study directs attention to the previously unexplored significant psychological distress. Although specific conclusions from the data are restricted due to the study's design, it indicates the importance of assessing and addressing these psychological factors for effective management of patients with OGC.

Proteomic-based stratification of intermediate-risk prostate cancer patients.

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

Differences in quality of life of patients undergoing total pelvic exenteration compared with standard rectal cancer surgery: a scoping review.

AIM: Rectal cancer is often treated surgically with an anterior resection (AR) or abdominoperineal excision (APE). However, for patients with locally advanced disease or local recurrence total pelvic exenteration (TPE) surgery can be performed. The magnitude of surgery varies, and little research has been done to consider how quality of life (QoL) may vary according to the extent of surgery. METHOD: A search was conducted on MEDLINE and PubMed for papers published from 2010 to 2021. Inclusion criteria consisted of observational studies comparing adult populations with rectal cancer undergoing APE, AR or TPE, reporting QoL using validated tools. Risk of bias was assessed using the Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool. Outcomes of interest were global QoL, gastrointestinal (GI) symptoms (nausea and vomiting, diarrhoea, and constipation) and pain. RESULTS: Seven studies including 1402 patients were analysed. QoL following TPE generally improves over time, back to baseline or better. AR and APE groups have similar patterns of improvement between baseline and 12 months after surgery, although scores declined in some studies at 12 months. TPE scores are lower overall, and the pattern of improvement differs, with patients tending to have worse nausea and vomiting symptoms. AR and APE patients tend to experience more lower GI symptoms. CONCLUSION: It is not possible to draw firm conclusions based on the studies analysed. However, QoL returns to baseline following TPE, APE and AR. Preoperative QoL appears to be an indication of postoperative outcomes. Further observational studies are required.

Multimodal prehabilitation service for patients with colorectal cancer: the challenges of implementation.

Prehabilitation has been shown to improve outcomes for patients undergoing major surgery; benefits include reductions in length of hospital stay and postoperative complications. Multimodal prehabilitation programmes lead to improved patient engagement and experience. This report describes implementation of a personalised multimodal prehabilitation programme for patients awaiting colorectal cancer surgery. We aim to highlight the successes, challenges and future direction of our programme.Patients listed for colorectal cancer surgery were referred for initial prehabilitation assessment. The prehabilitation group were assessed by specialist physiotherapists, dieticians and psychologists. An individualised programme was developed for each patient, aiming to optimise preoperative functional capacity and enhance physical and psychological resilience. Clinical primary outcome measures were recorded and compared with contemporaneous controls. For those undergoing prehabilitation, a set of secondary functional, nutritional and psychological outcomes were recorded at initial assessment and on completion of the programme.61 patients were enrolled in the programme from December 2021 to October 2022. 12 patients were excluded as they received less than 14 days prehabilitation or had incomplete data. The remaining 49 patients received a median duration of 24 days prehabilitation (range 15-91 days). The results show statistically significant improvements in the following functional outcome measures after prehabilitation: Rockwood scores, maximal inspiratory pressures, International Physical Activity Questionnaire Score and Functional Assessment of Chronic Illness - Fatigue Score. There was a lower postoperative complication rate in the prehabilitation group when compared with a control group (50% vs 67%).This quality improvement project has 3 Plan-Do-Study-Act (PDSA) cycles. PDSA 1 demonstrates prehabilitation can be successfully imbedded within a colorectal surgical unit and that patients are grateful for the service. PDSA 2 provides the project's first complete data set and demonstrates functional improvements in patients undergoing prehabilitation. The third PDSA cycle is ongoing and aims to refine the prehabilitation interventions and improve clinical outcomes for patients undergoing colorectal cancer surgery.

Plasma proteomic changes in response to surgical trauma and a novel transdermal analgesic treatment in dogs.

Assessment of pain responses and inflammation during animal surgery is difficult because traditional methods, such as visual analogue scores, are not applicable while under anaesthesia. Acute phase proteins (APPs), such as C-reactive protein and haptoglobin, that are typically monitored in veterinary research, do not show a significant change until at least 2 h post-surgery and therefore, immediate pathophysiological changes are uncertain. The current study used sequential window acquisition of all theoretical mass spectra (SWATH-MS) to investigate plasma proteome changes that occur immediately following surgery in dogs and also to assess the efficacy of a novel transdermal ketoprofen (TK) formulation. Castration was chosen as surgical model in this study. The procedure was performed on twelve dogs (n = 6 in two groups) and blood samples were collected at 0 h, 1 and 2 h after surgery for proteomic analysis. Following surgery, there was a general downregulation of proteins, including complement C- 3, complement factor B, complement factor D, transthyretin, and proteins associated with lipid, cholesterol, and glucose metabolisms, reflecting the systemic response to surgical trauma. Many of these changes were diminished in the transdermal group (TD) since ketoprofen, a non-steroidal anti-inflammatory drug (NSAID), inhibits prostanoids and the associated chemotactic neutrophil migration to site of tissue injury. SIGNIFICANCE: SWATH-MS Proteomic analysis revealed significant changes in plasma proteins, predominantly involved in early acute phase and inflammatory response at 1 & 2 h after surgery in castrated dogs. Pre-operative application of transdermal ketoprofen formulation had reduced the systemic immune response, which was confirmed by negligible alteration of proteins in transdermal treated group. A key outcome of this experiment was studying the efficacy of a novel transdermal NSAID formulation in dogs.

Data-Independent Acquisition Enables Robust Quantification of 400 Proteins in Non-Depleted Canine Plasma.

Mass spectrometry-based plasma proteomics offers a major advance for biomarker discovery in the veterinary field, which has traditionally been limited to quantification of a small number of proteins using biochemical assays. The development of foundational data and tools related to sequential window acquisition of all theoretical mass spectra (SWATH)-mass spectrometry has allowed for quantitative profiling of a significant number of plasma proteins in humans and several animal species. Enabling SWATH in dogs enhances human biomedical research as a model species, and significantly improves diagnostic and disease monitoring capability. In this study, a comprehensive peptide spectral library specific to canine plasma proteome was developed and evaluated using SWATH for protein quantification in non-depleted dog plasma. Specifically, plasma samples were subjected to various orthogonal fractionation and digestion techniques, and peptide fragmentation data corresponding to over 420 proteins was collected. Subsequently, a SWATH-based assay was introduced that leveraged the developed resource and that enabled reproducible quantification of 400 proteins in non-depleted plasma samples corresponding to various disease conditions. The ability to profile the abundance of such a significant number of plasma proteins using a single method in dogs has the potential to accelerate biomarker discovery studies in this species.

Leveraging homologies for cross-species plasma proteomics in ungulates using data-independent acquisition.

The collection of blood plasma is minimally invasive, and the fluid is a rich source of proteins for biomarker studies in both humans and animals. Plasma protein analysis by mass spectrometry (MS) can be challenging, though modern data acquisition strategies, such as sequential window acquisition of all theoretical fragment ion spectra (SWATH), enable reproducible quantitation of hundreds of proteins in non-depleted plasma from humans and laboratory model animals. Although there is strong potential to enhance veterinary and translational research, SWATH-based plasma proteomics in non-laboratory animals is virtually non-existent. One limitation to date is the lack of comprehensively annotated genomes to aid protein identification. The current study established plasma peptide spectral repositories for sheep and cattle that enabled quantification of over 200 proteins in non-depleted plasma using SWATH approach. Moreover, bioinformatics pipeline was developed to leverage inter-species homologies to enhance the depth of baseline libraries and plasma protein quantification in bovids. Finally, the practical utility of using bovid libraries for SWATH data extraction in taxonomically related non-domestic ungulate species (giraffe) has been demonstrated. SIGNIFICANCE: Ability to quickly generate comprehensive spectral libraries is limiting the applicability of data-independent acquisition, such as SWATH, to study proteomes of non-laboratory animals. We describe an approach to obtain relatively shallow foundational plasma repositories from domestic ruminants and employ homology searches to increase the depth of data, which we subsequently extend to unsequenced ungulates using SWATH method. When applied to cross-species proteomics, the number of proteins quantified by our approach far exceeds what is traditionally used in plasma protein tests.

Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins.

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

PIONEER: Pipeline for Generating High-Quality Spectral Libraries for DIA-MS Data.

Data-independent-acquisition mass spectrometry (DIA-MS) is a state-of-the-art proteomic technique for high-throughput identification and quantification of peptides and proteins. Interpretation of DIA-MS data relies on the use of a spectral library, which is optimally created from data acquired from the same samples in data-dependent acquisition (DDA) mode. As DIA-MS quantification relies on the spectral libraries, having a high-quality, non-redundant, and comprehensive spectral library is essential. This article describes the major steps for creating a high-quality spectral library using a combination of multiple complementary search engines. We discuss appropriate strategies to control the false discovery rate for the final spectral library as a result of merging multiple searches. © 2021 The Authors Current Protocols © 2021 Wiley Periodicals LLC. Basic Protocol 1: Searching DDA-MS files with multiple search engines Basic Protocol 2: Merging results from multiple search engines Basic Protocol 3: Creating spectral libraries from merged results Alternate Protocol: Using CLI for automating tasks Support Protocol: Creating concatenated FASTA files.

Mass spectrometry-based protein identification in proteomics-a review.

Statistically, accurate protein identification is a fundamental cornerstone of proteomics and underpins the understanding and application of this technology across all elements of medicine and biology. Proteomics, as a branch of biochemistry, has in recent years played a pivotal role in extending and developing the science of accurately identifying the biology and interactions of groups of proteins or proteomes. Proteomics has primarily used mass spectrometry (MS)-based techniques for identifying proteins, although other techniques including affinity-based identifications still play significant roles. Here, we outline the basics of MS to understand how data are generated and parameters used to inform computational tools used in protein identification. We then outline a comprehensive analysis of the bioinformatics and computational methodologies used in protein identification in proteomics including discussing the most current communally acceptable metrics to validate any identification.

iSwathX 2.0 for Processing DDA Spectral Libraries for DIA Data Analysis.

The iSwathX web application processes and normalizes mass spectrometry-based proteomics spectral libraries generated in the data-dependent acquisition (DDA) approach. These libraries are stored in various proteomics repositories such as PeptideAtlas and NIST, or are user-generated and provide reference data for data-independent acquisition (DIA) targeted data extraction and analysis. iSwathX 2.0 can efficiently normalize DDA data from different instruments, gathered at different instances, and make it compatible with specific DIA experiments. Novel functions for parallel processing of DDA libraries and DIA report files, along with various data visualizations, are available in iSwathX 2.0. The step-by-step protocols provided here describe how the libraries are uploaded, processed, visualized, and downloaded using various modules of the application. They also provide detailed guidelines on the use of DIA report files for data analysis and visualization. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Processing, combining, and visualizing two DDA libraries Basic Protocol 2: Parallel processing and combination of multiple DDA libraries Basic Protocol 3: Downstream processing, comparison, and visualization of DIA report files.

Bioinformatics approaches for improving seminal plasma proteome analysis.

Reproduction efficiency of male animals is one of the key factors influencing the sustainability of livestock. Mass spectrometry (MS) based proteomics has become an important tool for studying seminal plasma proteomes. In this review, we summarize bioinformatics analysis strategies for current proteomics approaches, for identifying novel biomarkers of reproductive robustness.

iSwathX: an interactive web-based application for extension of DIA peptide reference libraries.

Summary: Large-scale peptide mass spectrometry (MS)/MS reference libraries are essential for the comprehensive analysis of data-independent acquisition (DIA) MS datasets, providing a comprehensive set of spectra for identification and quantification of proteins. We have developed a novel web-based R-package (iSwathX) for combining reference libraries that is compatible with different DIA analysis software. This open-source web GUI automates the process of normalization and combination of spectral libraries and provides a user-friendly method for performing library format conversions, analysis and visualizations, with no need for programing familiarity. Availability and implementation: iSwathX is freely accessible at https://biolinfo.shinyapps.io/iSwathX with the R-package and Shiny source code available from GitHub (https://github.com/znoor/iSwathX). Supplementary information: Supplementary data are available at Bioinformatics online.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools.

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics Simulation Assays.

Histone deacetylases (HDAC) are metal-dependent enzymes and considered as important targets for cell functioning. Particularly, higher expression of class I HDACs is common in the onset of multiple malignancies which results in deregulation of many target genes involved in cell growth, differentiation and survival. Although substantial attempts have been made to control the irregular functioning of HDACs by employing various inhibitors with high sensitivity towards transformed cells, limited success has been achieved in epigenetic cancer therapy. Here in this study, we used ligand-based pharmacophore and 2-dimensional quantitative structure activity relationship (QSAR) modeling approaches for targeting class I HDAC isoforms. Pharmacophore models were generated by taking into account the known IC50 values and experimental energy scores with extensive validations. The QSAR model having an external R2 value of 0.93 was employed for virtual screening of compound libraries. 10 potential lead compounds (C1-C10) were short-listed having strong binding affinities for HDACs, out of which 2 compounds (C8 and C9) were able to interact with all members of class I HDACs. The potential binding modes of HDAC2 and HDAC8 to C8 were explored through molecular dynamics simulations. Overall, bioactivity and ligand efficiency (binding energy/non-hydrogen atoms) profiles suggested that proposed hits may be more effective inhibitors for cancer therapy.

Autistic adolescents show atypical activation of the brain's mentalizing system even without a prior history of mentalizing problems.

Some autistic children pass classic Theory of Mind (ToM) tasks that others fail, but the significance of this finding is at present unclear. We identified two such groups of primary school age (labelled ToM+ and ToM-) and a matched comparison group of typically developing children (TD). Five years later we tested these participants again on a ToM test battery appropriate for adolescents and conducted an fMRI study with a story based ToM task. We also assessed autistic core symptoms at these two time points. At both times the ToM- group showed more severe social communication impairments than the ToM+ group, and while showing an improvement in mentalizing performance, they continued to show a significant impairment compared to the NT group. Two independent ROI analyses of the BOLD signal showed activation of the mentalizing network including medial prefrontal cortex, posterior cingulate and lateral temporal cortices. Strikingly, both ToM+ and ToM- groups showed very similar patterns of heightened activation in comparison with the NT group. No differences in other brain regions were apparent. Thus, autistic adolescents who do not have a history of mentalizing problems according to our ToM battery showed the same atypical neurophysiological response during mentalizing as children who did have such a history. This finding indicates that heterogeneity at the behavioural level may nevertheless map onto a similar phenotype at the neuro-cognitive level.