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Uric acid (UA) is an important biomarker, as a high concentration in blood can lead to gout and further renal syndrome. Although several point-of-care testing (POCT) devices have been reported to detect UA, there are some limitations such as the requirement for uricase and the complicated pretreatment of serum/plasma samples, which restricts their use at home or in undeveloped areas. In this work, we developed an approach by applying Zn2+ to precipitate proteins and cells in whole blood to avoid interference with the chromogenic reaction. We used carboxymethylcellulose (CMC) to immobilize tetramethylbenzidine (TMB) on a nitrocellulose membrane for colorimetric detection. Using the oxidization properties of H2O2, which turns TMB into oxidized tetramethylbenzidine (TMBox) in the presence of catalyst gold nanoparticles (AuNPs), we successfully constructed an enzyme-free paper-based POCT device using the reduction reaction of UA and TMBox for simple, speedy, and cheap colorimetric detection of UA, achieving a detection time of 8 min, a linear range of 0–150 μg/mL, and an LOD of 25.79 μg/mL. The UA concentration in whole blood samples was further measured and correlated well with the clinical value (R2 = 0.8212). Thus, the proposed assay has the potential for POCT diagnosis, monitoring, and prognosis of diseases related to UA. By applying Zn2+ reagent to precipitate proteins and cells in whole blood and the reduction reaction of UA, an enzyme-free paper-based POCT assay was established. [ABSTRACT FROM AUTHOR]

The International Journal of Molecular Sciences has published a special issue on molecular oncology, featuring nineteen articles written by leading experts in specific cancer research fields. The articles cover a wide range of topics, including cancer development, progression, and treatment options. Some of the areas explored include endoplasmic reticulum stress activation, immunotherapies, non-genetic determinants of cancer, environmental carcinogens, social stress, epigenetic reprogramming, drug resistance, microbiome modulation, tumor microenvironment, and the efficacy of ALK inhibitors. The issue also discusses the use of liposomes as a delivery strategy for chemotherapeutic drugs. The articles provide valuable insights into the global burden of cancer and offer potential avenues for further research and improved treatment options. The editorial expresses gratitude to the authors, reviewers, and editors for their contributions and hopes that the articles will promote further research in cancer treatment. [Extracted from the article]

Background: The diagnostic and prognostic clinical value of circulating tumor DNA (ctDNA) and cell-free DNA (cfDNA) in pancreatic malignancies are unclear. Herein, we aimed to perform a meta-analysis to evaluate ctDNA and cfDNA as potential diagnostic and prognostic biomarkers. Methods: PRISMA reporting guidelines were followed closely for conducting the current meta-analysis. The PubMed/Medline, Scopus, and Web of Science (WoS) databases were scanned in detail to identify eligible papers for the study. A quality assessment was performed in accordance with the REMARK criteria. The risk ratios (RRs) of the diagnostic accuracy of ctDNA compared to that of carbohydrate antigen 19.9 (CA 19.9) in all disease stages and the hazard ratios (HRs) of the prognostic role of ctDNA in overall survival (OS) were calculated with 95% confidence intervals (CIs). Results: A total of 18 papers were evaluated to assess the diagnostic accuracy and prognostic value of biomarkers related to pancreatic malignancies. The pooled analysis indicated that CA19.9 provides greater diagnostic accuracy across all disease stages than ctDNA or cfDNA (RR = 0.64, 95% CI: 0.50-0.82, p < 0.001). Additionally, in a secondary analysis focusing on prognosis, patients who were ctDNA-positive were found to have significantly worse OS (HR = 2.00, 95% CI: 1.51-2.66, p < 0.001). Conclusion: The findings of this meta-analysis demonstrated that CA19-9 still has greater diagnostic accuracy across all disease stages than KRAS mutations in ctDNA or cfDNA. Nonetheless, the presence of detectable levels of ctDNA was associated with worse patient outcomes regarding OS. There is a growing need for further research on this topic. [ABSTRACT FROM AUTHOR]

Background: Dementia has a major impact on individuals, their families and caregivers, and wider society. Some individuals experience a faster decline of their function and health compared to others. The objective of this systematic review was to determine prognostic factors, measurable in primary care, for poor outcome in people living with dementia. Methods: Cohort studies set in the community or primary care, and examining prognostic factors for care home admission, cognitive decline, or palliative care were included. Databases were searched from inception to 17th June 2022. Identified papers were screened, the risk of bias assessed using Quality in Prognostic Studies (QUIPS) tool, and data extracted by 2 reviewers, with disagreements resolved by consensus or a 3rd reviewer. A narrative synthesis was undertaken, informed by GRADE, taking into consideration strength of association, risk of bias and precision of evidence. Patient and Public Involvement and Engagement (PPIE) and stakeholder input was obtained to prioritise factors for further investigation. Results: Searches identified 24,283 potentially relevant titles. After screening, 46 papers were included, 21 examined care home admission investigating 94 factors, 26 investigated cognitive decline as an outcome examining 60 factors, and 1 researched palliative care assessing 13 factors. 11 prognostic factors (older age, less deprived, living alone, white race, urban residence, worse baseline cognition, taking dementia medication, depression, psychosis, wandering, and caregiver's desire for admission) were associated with an increased risk of care home admission and 4 prognostic factors (longer duration of dementia, agitation/aggression, psychosis, and hypercholesterolaemia) were associated with an increased risk of cognitive decline. PPIE and other stakeholders recommended further investigation of 22 additional potential prognostic factors. Conclusions: Identifying evidence for prognostic factors in dementia is challenging. Whilst several factors highlighted as of relevance by our stakeholder groups need further investigation, inequalities may exist in care home admission and there is evidence that several prognostic factors measurable in primary care could alert clinicians to risk of a faster progression. Registration: PROSPERO CRD42019111775. [ABSTRACT FROM AUTHOR]

Purpose: Recent papers suggested a correlation between the risk of distant metastasis (DM) and dose outside the PTV, though conclusions in different publications conflicted. This study resolves these conflicts and provides a compelling explanation of prognostic factors. Materials and methods: A dataset of 478 NSCLC patients treated with SBRT (IMRT or VMAT) was analyzed. We developed a deep learning model for DM prediction and explainable AI was used to identify the most significant prognostic factors. Subsequently, the prognostic power of the extracted features and clinical details were analyzed using conventional statistical methods. Results: Treatment technique, tumor features, and dosiomic features in a 3 cm wide ring around the PTV (PTV3cm) were identified as the strongest predictors of DM. The Hazard Ratio (HR) for Dmean,PTV3cm was significantly above 1 (p < 0.001). There was no significance of the PTV3cm dose after treatment technique stratification. However, the dose in PTV3cm was found to be a highly significant DM predictor (HR > 1, p = 0.004) when analyzing only VMAT patients with small and spherical tumors (i.e., sphericity > 0.5). Conclusions: The main reason for conflicting conclusions in previous papers was inconsistent datasets and insufficient consideration of confounding variables. No causal correlation between the risk of DM and dose outside the PTV was found. However, the mean dose to PTV3cm can be a significant predictor of DM in small spherical targets treated with VMAT, which might clinically imply considering larger PTV margins for smaller, more spherical tumors (e.g., if IGTV > 2 cm, then margin ≤ 7 mm, else margin > 7 mm). [ABSTRACT FROM AUTHOR]

Bladder cancer (BCa) is the fourth most common cancer in men and one of the most common urinary tract cancers, especially in developed countries. The aim of this paper is to comprehensively analyze the biology of bladder cancer, including its epidemiology, etiology, histological types, risk factors, clinical symptoms, and diagnostic methods. The paper presents the dominant histological types of bladder cancer, such as transitional cell carcinoma (TCC), which accounts for 90–95% of cases, squamous cell carcinoma (SCC), and adenocarcinoma, which is much rarer. Risk factors, such as smoking, occupational exposure to chemicals, schistosomiasis, and genetic factors, which significantly affect the pathogenesis of bladder cancer, are also discussed. The paper focuses on modern diagnostic methods, including blue light cystoscopy (BLC) and computed tomography urography (CTU), which show increased sensitivity and specificity in detecting early neoplastic changes. The importance of TNM classification and the role of neoadjuvant chemotherapy in improving patient prognosis are also discussed. Based on a review of the scientific literature, the paper emphasizes the need for early diagnosis and an individualized therapeutic approach, which may contribute to improving the survival and quality of life of patients with bladder cancer. The potential for prevention, including quitting smoking and limiting exposure to harmful chemicals, has also been demonstrated to significantly reduce the risk of disease. Patient education and monitoring high-risk groups are key to reducing the incidence of bladder cancer. [ABSTRACT FROM AUTHOR]

Laryngeal squamous cell carcinoma (LSCC) is a common malignancy that, despite scientific advancements, has not seen an improvement in its prognosis in the last decades. Few promising predictive markers have been found and none are relevant in clinical practice. p16ink4a, an oncosuppressor protein involved in cell cycle arrest, with a prognostic impact on other cancers, has been widely used in the head and neck region as a surrogate marker of HPV infection. Published papers and recent meta-analyses seem to minimize the biological role of HPV in the context of LSCC's cancerogenesis, and to disprove the reliability of p16ink4a as a surrogate prognostic marker in this context, while still highlighting its potential role as an independent predictor of survival. Unfortunately, the available literature, in particular during the last two decades, is often not focused on its potential role as an independent biomarker and few relevant data are found in papers mainly focused on HPV. The available data suggest that future research should focus specifically on p16ink4a, taking into account both its potential inactivation and overexpression, different patterns of staining, and immunohistochemistry cutoffs, and should focus not on its potential role as a surrogate marker but on its independent role as a predictor of survival. [ABSTRACT FROM AUTHOR]

Intermediate filaments are one of three polymeric structures that form the cytoskeleton of epithelial cells. In the epithelium, these filaments are made up of a variety of keratin proteins. Intermediate filaments complete a wide range of functions in keratinocytes, including maintaining cell structure, cell growth, cell proliferation, cell migration, and more. Given that these functions are intimately associated with the carcinogenic process, and that hyperkeratinization is a quintessential feature of oral leukoplakias, the utility of keratins in oral leukoplakia is yet to be fully explored. This scoping review aims to outline the current knowledge founded on original studies on human tissues regarding the expression and utility of keratins as diagnostic, prognostic, and predictive biomarkers in oral leukoplakias. After using a search strategy developed for several scientific databases, namely, PubMed, Scopus, Web of Science, and OVID, 42 papers met the inclusion and exclusion criteria. One more article was added when it was identified through manually searching the list of references. The included papers were published between 1989 and 2024. Keratins 1–20 were investigated in the 43 included studies, and their expression was assessed in oral leukoplakia and dysplasia cases. Only five studies investigated the prognostic role of keratins in relation to malignant transformation. No studies evaluated keratins as a diagnostic adjunct or predictive tool. Evidence supports the idea that dysplasia disrupts the terminal differentiation pathway of primary keratins. Gain of keratin 17 expression and loss of keratin 13 were significantly observed in differentiated epithelial dysplasia. Also, the keratin 19 extension into suprabasal cells has been associated with the evolving features of dysplasia. The loss of keratin1/keratin 10 has been significantly associated with high-grade dysplasia. The prognostic value of cytokeratins has shown conflicting results, and further studies are required to ascertain their role in predicting the malignant transformation of oral leukoplakia. [ABSTRACT FROM AUTHOR]

Biomedical information retrieval for diagnosis, treatment and prognosis has been studied for a long time. In particular, image recognition using deep learning has been shown to be very effective for cancers and diseases. In these fields, scaphoid fracture recognition is a hot topic because the appearance of scaphoid fractures is not easy to detect. Although there have been a number of recent studies on this topic, no studies focused their attention on surgical treatment recommendations and nonsurgical prognosis status classification. Indeed, a successful treatment recommendation will assist the doctor in selecting an effective treatment, and the prognosis status classification will help a radiologist recognize the image more efficiently. For these purposes, in this paper, we propose potential solutions through a comprehensive empirical study assessing the effectiveness of recent deep learning techniques on surgical treatment recommendation and nonsurgical prognosis status classification. In the proposed system, the scaphoid is firstly segmented from an unknown X-ray image. Next, for surgical treatment recommendation, the fractures are further filtered and recognized. According to the recognition result, the surgical treatment recommendation is generated. Finally, even without sufficient fracture information, the doctor can still make an effective decision to opt for surgery or not. Moreover, for nonsurgical patients, the current prognosis status of avascular necrosis, non-union and union can be classified. The related experimental results made using a real dataset reveal that the surgical treatment recommendation reached 80% and 86% in accuracy and AUC (Area Under the Curve), respectively, while the nonsurgical prognosis status classification reached 91% and 96%, respectively. Further, the methods using transfer learning and data augmentation can bring out obvious improvements, which, on average, reached 21.9%, 28.9% and 5.6%, 7.8% for surgical treatment recommendations and nonsurgical prognosis image classification, respectively. Based on the experimental results, the recommended methods in this paper are DenseNet169 and ResNet50 for surgical treatment recommendation and nonsurgical prognosis status classification, respectively. We believe that this paper can provide an important reference for future research on surgical treatment recommendation and nonsurgical prognosis classification for scaphoid fractures. [ABSTRACT FROM AUTHOR]

Degradation is an inevitable companion in the operation of solid oxide fuel cell (SOFC) systems since it directly deteriorates the reliability of the system's operation and the system's durability. Both are seen as barriers that limit the extensive commercial use of SOFC systems. Therefore, diagnosis and prognosis are valuable tools that can contribute to raising the reliability of the system operation, efficient health management, increased durability and implementation of predictive maintenance techniques. Remaining useful life (RUL) prediction has been extensively studied in many areas like batteries and proton-exchange membrane fuel cell (PEM) systems, and a range of different approaches has been proposed. On the other hand, results available in the domain of SOFC systems are still relatively limited. Moreover, methods relying on detailed process models and models of degradation turned out to have limited applicability for in-field applications. Therefore, in this paper, we propose an effective, data-driven approach to predicting RUL where the trend of the health index is modeled by an adaptive linear model, which is updated at all times during the system operation. This allows for a closed-form solution of the probability distribution of the RUL, which is the main novelty of this paper. Such a solution requires no computational load and is as such very convenient for the application in ordinary low-cost control systems. The performance of the approach is demonstrated first on the simulated case studies and then on the data obtained from a long-term experiment on a laboratory SOFC system. From the tests conducted so far, it turns out that the quality of the RUL prediction is usually rather low at the beginning of the system operation, but then gradually improves while the system is approaching the end-of-life (EOL), making it a viable tool for prognosis. [ABSTRACT FROM AUTHOR]

This document is an editorial discussing the importance of understanding neurodevelopmental and neurodegenerative disorders for improved patient care and treatment. It highlights specific disorders such as Down syndrome, neural tube defects, inherited retinal diseases, Alzheimer's disease, and fatty acid hydroxylase-associated neurodegeneration. The editorial mentions the use of model organisms like Drosophila melanogaster and Xenopus laevis to study these diseases. It provides a summary of research papers included in the topic, covering various aspects of these disorders and potential therapeutic targets. This document is a note from the publisher of an article titled "Talents in the 'Prairie Talents' Project of Inner Mongolia." The note acknowledges an error in the article but states that it does not affect the scientific conclusions. It clarifies that the claims expressed in the article are solely those of the authors and do not necessarily represent their affiliated organizations or the publisher. The document does not provide any additional information about the content of the article. [Extracted from the article]

Objective: To evaluate the efficacy and safety of cetuximab instead of cisplatin in combination with downstaging radiotherapy for papillomavirus (HPV) positive oropharyngeal squamous cell carcinoma (HPV+ OPSCC). Design: Meta-analysis and systematic evaluation. Data sources: The PubMed, Embase, Web of Science, and Cochrane library databases were searched up to June 8, 2023, as well as Clinicaltrials.gov Clinical Trials Registry, China Knowledge Network, Wanfang Data Knowledge Service Platform, and Wiprojournal.com. Eligibility criteria for selecting studies: Randomized controlled trials reporting results of standard regimens of cetuximab + radiotherapy vs cisplatin + radiotherapy in treating HPV+ OPSCC were included. The primary outcomes of interest were overall survival (OS), progression-free survival (PFS), local regional failure rate (LRF), distant metastasis rate (DM), and adverse events (AE). Data extraction and synthesis: Two reviewers independently extracted data and assessed the risk of bias of the included studies. The HR and its 95% CI were used as the effect analysis statistic for survival analysis, while the OR and its 95% CI were used as the effect analysis statistic for dichotomous variables. These statistics were extracted by the reviewers and aggregated using a fixed-effects model to synthesise the data. Results: A total of 874 relevant papers were obtained from the initial search, and five papers that met the inclusion criteria were included; a total of 1,617 patients with HPV+ OPSCC were enrolled in these studies. Meta-analysis showed that OS and PFS were significantly shorter in the cetuximab + radiotherapy group of patients with HPV+ OPSCC compared with those in the conventional cisplatin + radiotherapy group (HR = 2.10, 95% CI [1.39–3.15], P = 0.0004; HR = 1.79, 95% CI [1.40–2.29], P < 0.0001); LRF and DM were significantly increased (HR = 2.22, 95% CI [1.58–3.11], P < 0.0001; HR = 1.66, 95% CI [1.07–2.58], P = 0.02), but there was no significant difference in overall grade 3 to 4, acute and late AE overall (OR = 0.86, 95% CI [0.65–1.13], P = 0.28). Conclusions: Cisplatin + radiotherapy remains the standard treatment for HPV+ OPSCC. According to the 7th edition AJCC/UICC criteria, low-risk HPV+ OPSCC patients with a smoking history of ≤ 10 packs/year and non-pharyngeal tumors not involved in lymphatic metastasis had similar survival outcomes with cetuximab/cisplatin + radiotherapy. However, further clinical trials are necessary to determine whether cetuximab + radiotherapy can replace cisplatin + radiotherapy for degraded treatment in individuals who meet the aforementioned characteristics, particularly those with platinum drug allergies. Prospero registration number: CRD42023445619. [ABSTRACT FROM AUTHOR]

This document is an editorial from the International Journal of Molecular Sciences that discusses recent advancements in cancer treatment. The editorial highlights various innovative approaches, such as nanomedicines, combined therapy, drug repurposing, genomics, and personalized therapy, that target the hallmarks of cancer. It presents nine original research papers and three reviews that explore these advancements and their potential in addressing specific cancer mechanisms. The research papers cover topics such as inflammation control strategies for prostate cancer, prognostic indicators for colorectal cancer, immunohistochemical markers for renal cell carcinoma, immunomodulatory effects in colorectal cancer, and safer superantigen-based peptides for cancer treatment. The reviews focus on circulating tumor cells and tumor-derived materials in breast cancer research, the role of human endogenous retroviruses in cancer development and progression, and the inflammatory mechanisms driving oral squamous cell carcinoma. The document emphasizes the importance of these innovative methods in advancing cancer treatment and highlights their potential for future clinical applications. [Extracted from the article]

Stroke is one of the leading causes of long-term disabilities in motor and cognition functionality. An early and accurate prediction of rehabilitation outcomes can lead to a tailor-made treatment that can significantly improve the post-stroke quality of life of a person. This scoping review aimed to summarize studies that use Artificial Intelligence (AI) for the prediction of language and cognition rehabilitation outcomes and the need to use AI in this domain. This study followed the PRISMA-ScR guidelines for two databases, Scopus and PubMed. The results, which are measured with several metrics depending on the task, regression, or classification, present encouraging outcomes as they can predict the cognitive functionality of post-stroke patients with relative precision. Among the results of the paper are the identification of the most effective Machine Learning (ML) algorithms, and the identification of the key factors that influence rehabilitation outcomes. The majority of studies focus on aphasia and present high performance achieving up to 97% recall and 91.4% precision. The main limitations of the studies were the small subject population and the lack of an external dataset. However, effective ML algorithms along with explainability are expected to become among the most prominent solutions for precision medicine due to their ability to overcome non-linearities on data and provide insights and transparent predictions that can help healthcare professionals make more informed and accurate decisions. [ABSTRACT FROM AUTHOR]

Introduction: The accurate prognosis of reactor accidents is essential for deploying effective strategies that prevent radioactive releases. However, research in the nuclear sector is limited. This paper introduces a novel Temporal Fusion Transformer (TFT) model-based method for accident prognosis that incorporates multi-headed self-attention and gating mechanisms. Methods: Our proposed method combines multi-headed self-attention and gating mechanisms of TFT with multiple covariates to enhance prediction accuracy. Additionally, we employ quantile regression for uncertainty assessment. We apply this method to the HPR1000 reactor to predict outcomes following loss of coolant accidents (LOCAs). Results: The experimental results reveal that our proposed method outperforms existing deep learning-based prediction models in both prediction accuracy and confidence intervals. We also demonstrate increased robustness through interference experiments with varying signal-to-noise ratios and ablation studies on static covariates. Discussion: Our method contributes to the development of intelligent and reduced-staff maintenance methods for reactor systems, showcasing its ability to effectively extract and utilize features of static and historical covariates for improved predictive performance. [ABSTRACT FROM AUTHOR]

Background: Necrobiosis lipoidica (NL) is a rare granulomatous skin disorder with a predilection for females, often associated with diabetes mellitus (DM). This paper aims to comprehensively review the literature on NL, focusing on its association with DM, thyroid disorders, and the metabolic syndrome. Methods: A systematic search was conducted in English-language literature from inception to October 2023, utilizing PubMed. We identified 530 studies and selected 19 based on clinical significance, statistical support, and relevance to the paper's goals. Results: The coexistence of NL and DM is prevalent, with rates ranging from 11% to 65.71%. NL may precede DM diagnosis and a correlation between NL and increased daily insulin requirements has been observed in such patients. NL is suggested as a potential prognostic marker for DM complications; however, recent studies question this association, highlighting the need for further research. Studies in the context of NL and Thyroid Disease indicate a correlation, especially with autoimmune thyroiditis. Regarding NL and Metabolic Syndrome, the prevalence of metabolic syndrome among NL patients is notably higher than in the general population. Additionally, DM patients with ulcerated NL commonly exhibit hypertension or obesity, raising questions about the potential influence of hypertension and obesity on NL ulcerations. Conclusion: Additional research is required to untangle the complex connections between NL and various comorbidities. [ABSTRACT FROM AUTHOR]

Background: NUP98 gene fusions in acute myeloid leukemia (AML) have recently attracted much interest. Despite substantial research illuminating the roles of NUP98 fusions in the course of AML, their impacts on the outcome of patients with AML should be explored in more detail. As a result, this meta-analysis was designed to provide further light on the prognostic implications of NUP98 fusions in AML. Methods: We completed an extensive search in PubMed, Scopus, and Web of Science to identify papers evaluating the prognostic effects of NUP98 rearrangements in patients with AML until August 22, 2022. In total, 15 publications with 6142 participants fulfilled the requirements for the current meta-analysis. All the qualified studies were examined for information regarding HRs and 95% confidence interval (95%CI) for overall survival (OS) and event-free survival (EFS). In addition, we utilized Comprehensive Meta-analysis software version 2 (CMA2) for calculating pooled HRs and 95% CI. Results: Our analyses for NUP98-NSD1 indicated that this fusion could significantly impact the outcome of patients with AML (pooled HR: 2.84; 95% CI: 2.49-3.24, P=0.000). Additionally, we observed a strong correlation between NUP98-KDM5A rearrangement and poor prognosis in AML (pooled HR: 2.65; 95% CI: 2.5-2.81; P=0.000). A subgroup analysis also showed that the NUP98-NSD1 and FLT3-ITD together confer a poor prognostic effect (pooled HR: 2.60, 95% CI: 1.61-4.18; P=0.000). Conclusions: NUP98 fusions could significantly impact the outcome of patients with AML. The use of these fusions as prognostic indicators in AML seems rational. [ABSTRACT FROM AUTHOR]

Introduction: Primary Sjögren's syndrome (pSS) is an autoimmune disorder primarily affecting salivary and lacrimal glands, although about 40% of patients experience systemic complications. In this setting, the identification of patient phenotypes characterized by increased risk of extra-glandular involvement still represents an unmet need. Areas covered: The aim of this paper is to review the scientific evidence on the utility of salivary gland biopsies in pSS, emphasizing their role in defining prognosis. In latest years, research focused on disease-specific clinical, serological, or histological features able to categorize patient prognosis. Among histopathological features, focus score and ectopic germinal centers exhibit associations with glandular and extraglandular manifestations, including higher rates of lymphomagenesis. Expert Opinion: Pathological characterization of salivary glands provides information that go beyond a mere diagnostic or classification utility, providing insights for a stratification of disease severity and for predicting systemic manifestations. Thus, a salivary gland biopsy should be offered to all patients and included in routine practice, even when not strictly required for diagnostic purposes. More advanced analysis techniques of the tissue, including immunohistochemistry and 'omics' should be further explored in longitudinal studies to boost the ability to further stratify and predict disease evolution. [ABSTRACT FROM AUTHOR]

Breast cancer is the most common malignant tumor among women worldwide and remains one of the leading causes of death among women. Its incidence and mortality rates are continuously rising. In recent years, with the rapid advancement of deep learning (DL) technology, DL has demonstrated significant potential in breast cancer diagnosis, prognosis evaluation, and treatment response prediction. This paper reviews relevant research progress and applies DL models to image enhancement, segmentation, and classification based on large-scale datasets from TCGA and multiple centers. We employed foundational models such as ResNet50, Transformer, and Hover-net to investigate the performance of DL models in breast cancer diagnosis, treatment, and prognosis prediction. The results indicate that DL techniques have significantly improved diagnostic accuracy and efficiency, particularly in predicting breast cancer metastasis and clinical prognosis. Furthermore, the study emphasizes the crucial role of robust databases in developing highly generalizable models. Future research will focus on addressing challenges related to data management, model interpretability, and regulatory compliance, ultimately aiming to provide more precise clinical treatment and prognostic evaluation programs for breast cancer patients. [ABSTRACT FROM AUTHOR]

Multiple sclerosis (MS) is a devastating immune-mediated disorder of the central nervous system resulting in progressive disability accumulation. As there is no cure available yet for MS, the primary therapeutic objective is to reduce relapses and to slow down disability progression as early as possible during the disease to maintain and/or improve health-related quality of life. However, optimizing treatment for people with MS (pwMS) is complex and challenging due to the many factors involved and in particular, the high degree of clinical and subclinical heterogeneity in disease progression among pwMS. In this paper, we discuss these many different challenges complicating treatment optimization for pwMS as well as how a shift towards a more pro-active, data-driven and personalized medicine approach could potentially improve patient outcomes for pwMS. We describe how the ‘Clinical Impact through AI-assisted MS Care’ (CLAIMS) project serves as a recent example of how to realize such a shift towards personalized treatment optimization for pwMS through the development of a platform that offers a holistic view of all relevant patient data and biomarkers, and then using this data to enable AI-supported prognostic modelling. [ABSTRACT FROM AUTHOR]

In this article, the authors, a cis-gender gay man and an Indigenous non-binary, two-spirit person, narrate their past encounters with health professionals and their experiences pursuing allied health care training as students. Taking an autoethnographic approach, the first author re-narrates how medical practitioners and students engage (or fail to engage) with the LGBTQIA+ community. They draw on gray documentation derived from an interaction with a consulting physician that highlighted a telling lack of knowledge about the LGBTQ+ community, including those with diverse sex characteristics and sexualities/manifesting as unconscious bias. This interaction provided the impetus to speak back to the experience of being reduced to a medical prognosis. The second author questions the hegemonic practices underpinning encounters with the medical model of response in tertiary education. Our remit in this paper is to question how adequately the specific needs of the LGBTQI+ population are being addressed by the medical model and to what extent aspiring clinicians understand how their actions can contribute to gender- and sexuality-based discrimination and stigmatization. [ABSTRACT FROM AUTHOR]

Background: Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is an important extra-articular manifestation of rheumatoid arthritis (RA). Identifying patients at risk of progression and death is crucial for improving RA-ILD management and outcomes. This paper explores current evidence on prognostic factors in RA-ILD. Methods: We conducted a systematic literature review to examine the impact of clinical, radiological, and histological factors on lung function decline and the survival of RA-ILD patients. We searched electronic databases, including Medline and EMBASE, from inception to date. The incidence and prognosis of predictors were qualitatively analyzed, and univariate results were combined when feasible. Following the "Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)" guidelines, our systematic literature review involved a five-step algorithm. Out of 2217 records, 48 studies were eligible. These studies reported various prognostic factors, including demographic variables, clinical risk factors, serum markers, and preexisting treatments. Results: Lung function declined over time in 1225 subjects, with significant variability in smoking history and radiological/pathological UIP patterns. Severe lung fibrosis and abnormal pulmonary function tests (PFTs) were key univariate prognostic indicators, while age at initial presentation, RA disease activity, predicted DLCO percentage, and UIP pattern were the most reliable multivariate risk factors for ILD progression. Age, male gender, disease duration, RA activity, acute phase reactants, and specific serum biomarkers (Krebs vin den Lungen 6, surfactant protein D, and interleukin 6) were significantly associated with all-cause mortality. Conclusions: RA-ILD is a severe complication of RA characterized by significant prognostic variability. Key prognostic factors include extensive fibrosis observed on imaging, a marked decline in lung function, high RA disease activity, and specific biomarkers. These factors can guide treatment strategies and improve patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Head and neck squamous cell carcinoma (HNSCC) is one of the most prevalent cancers worldwide. The identification of molecular alterations adding to the individual risk of HNSCC development and progression is one of the most important challenges in studies on cancer genetics. MicroRNAs (miRNAs), which belong to the group of important post-transcriptional regulators of human gene expression, seem to be valuable options for consideration as key modifiers of individual cancer risk, and therefore may be helpful in predicting inter-individual differences in cancer risk, response to treatment and prognosis. Methods: There have not been many studies focused on the relationship between miRNA variants and HNSCC published in PubMed within the last 15 years. We found and analyzed 30 reviews, meta-analyses and research papers and revealed 14 SNPs which have been reported as significant in the context of HNSCC susceptibility and/or prognosis. Results: These 14 SNPs were located in 13 separate miRNAs. Among them, four were the most frequently studied (miRNA-146, -196, -149 and -499) and have been shown to have the greatest impact on the course of HNSCC. However, the presented results have been conflicting. Conclusions: It must be concluded that, despite the years of studies, there are no conclusive reports demonstrating a significant role of SNPs in miRNAs in the context of the susceptibility to HNSCC or its prognosis. [ABSTRACT FROM AUTHOR]

Gliomas, the most common type of primary malignant brain tumors in adults, pose significant challenges in diagnosis and management due to their heterogeneity and potential aggressiveness. This review evaluates the utility of O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) positron emission tomography (PET), a promising imaging modality, to enhance the clinical management of gliomas. We reviewed 82 studies involving 4657 patients, focusing on the application of [18F]FET in several key areas: diagnosis, grading, identification of IDH status and presence of oligodendroglial component, guided resection or biopsy, detection of residual tumor, guided radiotherapy, detection of malignant transformation in low-grade glioma, differentiation of recurrence versus treatment-related changes and prognostic factors, and treatment response evaluation. Our findings confirm that [18F]FET helps delineate tumor tissue, improves diagnostic accuracy, and aids in therapeutic decision-making by providing crucial insights into tumor metabolism. This review underscores the need for standardized parameters and further multicentric studies to solidify the role of [18F]FET PET in routine clinical practice. By offering a comprehensive overview of current research and practical implications, this paper highlights the added value of [18F]FET PET in improving management of glioma patients from diagnosis to follow-up. [ABSTRACT FROM AUTHOR]

Tumour deposits (TDs) significantly impact colorectal cancer (CRC) prognosis. Integrating TDs into the TNM staging system can enhance individualized disease management. Keeping abreast of evolving TDs research is pivotal for clinical advancement. We comprehensively reviewed both recent and popular literature to grasp the field's essence. Subsequently, a data retrieval sourced articles on TDs in CRC for bibliometric analysis, spanning from 1 January 1935 to 30 April 2023. Bibliometrix software facilitated paper analysis and visualization. Bibliometric indicators, the trends and hotspots were determined. A total of 2147 articles were successfully retrieved. Brown G emerged as the most productive author, and the USA as the most prolific country. Central South University and Memorial Sloan Kettering Cancer Center led productivity. Bradford's law categorized 48 journals into zone 1. Keywords co‐occurrence analysis identified three main clusters: the application of TDs in TNM staging, the pathogenesis of TDs, and the assessment of TDs. The trend topic analysis highlighted research focused on refining TDs incorporation into tumour staging. TDs wield enduring medical significance, shaping ongoing research. Much literature focused on confirming TD's prognostic value and optimizing TNM integration. Additionally, it is worth highlighting that TD's enigmatic pathogenesis demands research priority, as it holds the potential to unveil concealed knowledge regarding their development. [ABSTRACT FROM AUTHOR]

Background: Appropriate physical activity (PA) and good sleep are beneficial to maternal and fetal health. This paper sought to explore the associations of PA and sleep quality among healthy women at the first and second trimesters of pregnancy on mental health and pregnancy outcomes. Methods: Totally 268 healthy pregnant women were retrospectively analyzed as study subjects, 134 each in the first trimester (FT) and second trimester (ST). Their baseline clinical data were obtained respectively at two stages of pregnancy. The PA/sleep quality of subjects were assessed through the Pregnancy Physical Activity Questionnaire-Chinese version (PPAQ-C)/Pittsburgh Sleep Quality Index (PSQI) scale. The mental health was assessed via the Hospital Anxiety and Depression Scale (HADS). The correlations of PA and sleep quality with mental health were analyzed using Spearman correlation analysis. Pregnancy outcomes of all subjects, associations of moderate intensity (MI) PA and sleep quality with adverse pregnancy outcomes, and independent influencing factors for adverse outcomes were analyzed. Results: Pregnant women in the ST group exhibited higher levels of MI, worse sleep quality, and lower levels of anxiety and depression than those in the FT group. Anxiety and depression were negatively correlated with MI but positively linked with PSQI scores at the first and second trimesters. MI ≥ 7.5 MET-h/week and good sleep quality were associated with a reduced incidence of adverse pregnancy outcomes. Conclusion: MI ≥ 7.5 MET-h/week and good sleep quality at the first and second trimesters of pregnancy benefit mental health and markedly reduce the occurrence of adverse pregnancy outcomes. [ABSTRACT FROM AUTHOR]

Obesity-related ciliopathies, as a group of ciliopathies including Alström Syndrome and Bardet–Biedl Syndrome, exhibit distinct genetic and phenotypic variability. The understanding of these diseases is highly significant for understanding the functions of primary cilia in the human body, particularly regarding the relationship between obesity and primary cilia. The diagnosis of these diseases primarily relies on clinical presentation and genetic testing. However, there is a significant lack of research on biomarkers to elucidate the variability in clinical manifestations, disease progression, prognosis, and treatment responses. Through an extensive literature review, the paper focuses on obesity-related ciliopathies, reviewing the advancements in the field and highlighting the potential roles of biomarkers in the clinical presentation, diagnosis, and prognosis of these diseases. [ABSTRACT FROM AUTHOR]

Background: Solid pseudopapillary neoplasms of the pancreas with hepatic metastases are infrequent and difficult to diagnose, and treatment is uncertain. Methods: A retrospective analysis of clinical data from patients with pancreatic solid pseudopapillary neoplasm (SPN) hepatic metastases who underwent surgery at the First Hospital of Jilin University from January 2005 to December 2021 was conducted. A total of 287 patients with SPN were included in the study, of which 8 (3%) developed liver metastases, all of whom were treated surgically and recovered well after surgery. The clinical presentation, imaging features, surgical treatment, histopathological examination, and postoperative follow-up data (mean 70 months; range 28-138 months) of the patients were recorded and analyzed. Clinical response strategies can be derived by reviewing previous studies on hepatic metastases of SPNs. Results: For resectable hepatic metastases from pancreatic solid pseudopapillary neoplasms, early surgery with total resection of the primary tumor and metastasis has shown great efficiency and is associated with patient good prognosis. In patients presenting unresectable hepatic metastases, aggressive tumor reduction surgery resulted in the alleviation of clinical symptoms and reduction of tumor burden while potentially achieving long-term survival. Conclusion: For hepatic metastases of SPNs, a preoperative liver tissue biopsy is beneficial for a definitive diagnosis. Surgery demonstrates excellent therapeutic efficacy and is considered the preferred curative treatment approach. This paper presents clinical experiences with SPN-related hepatic metastases at the Affiliated Hospital of Jilin University, which can be used to guide patient counseling in clinical practice. [ABSTRACT FROM AUTHOR]

Simple Summary: Proteomics can be very useful in identifying proteins, which helps find potential markers for diseases. Managing endometrial cancer can be difficult and finding reliable markers can contribute to an early diagnosis, to manage its evolution, and even predict the response to treatment. This paper reviews the current research on the proteins involved in endometrial cancer. Most studies used tissue, serum, and plasma samples and found potential diagnostic and prognostic markers. Eight studies were examined closely, with three showing strong similarities, sharing forty-five proteins. This review also identified the 10 most commonly reported proteins in these studies. While proteomics shows promise in finding diagnostic and prognostic markers for endometrial cancer, there is still a need for more research on new therapeutic targets. Proteomics can be a robust tool in protein identification and regulation, allowing the discovery of potential biomarkers. In clinical practice, the management of endometrial cancer can be challenging. Thus, identifying promising markers could be beneficial, helping both in diagnosis and prognostic stratification, even predicting the response to therapy. Therefore, this manuscript systematically reviews the existing evidence of the proteomic profile of human endometrial cancer. The literature search was conducted via Medline (through PubMed) and the Web of Science. The inclusion criteria were clinical, in vitro, and in vivo original studies reporting proteomic analysis using all types of samples to map the human endometrial cancer proteome. A total of 55 publications were included in this review. Most of the articles carried out a proteomic analysis on endometrial tissue, serum and plasma samples, which enabled the identification of several potential diagnostic and prognostic biomarkers. In addition, eight articles were analyzed regarding the identified proteins, where three studies showed a strong correlation, sharing forty-five proteins. This analysis also allowed the identification of the 10 most frequently reported proteins in these studies: EGFR, PGRMC1, CSE1L, MYDGF, STMN1, CASP3 ANXA2, YBX1, ANXA1, and MYH11. Proteomics-based approaches pointed out potential diagnostic and prognostic candidates for endometrial cancer. However, there is a lack of studies exploring novel therapeutic targets. [ABSTRACT FROM AUTHOR]

Helicobacter pylori (H. pylori) is a harmful bacterium that is difficult to conveniently diagnose and effectively eradicate. Chronic H. pylori infection increases the risk of gastrointestinal diseases, even cancers. Despite the known findings, more underlying mechanisms are to be deeply explored to facilitate the development of novel prevention and treatment strategies of H. pylori infection. Long noncoding RNAs (lncRNAs) are RNAs with more than 200 nucleotides. They may be implicated in cell proliferation, inflammation and many other signaling pathways of gastrointestinal cancer progression. The dynamic expression of lncRNAs indicates their potential to be diagnostic or prognostic biomarkers. In this paper, we comprehensively summarize the processes of H. pylori infection and the treatment methods, review the known findings of lncRNA classification and functional mechanisms, elucidate the roles of lncRNAs in H. pylori-related gastrointestinal cancer, and discuss the clinical perspectives of lncRNAs. [ABSTRACT FROM AUTHOR]

Background: The newest clinical evidence that the relationship between the peritoneal cancer index (PCI) and the postoperative prognosis of advanced ovarian cancer patients remains controversial, and there are no large-sample and multicenter studies to clarify this matter. Therefore, in this paper, we used meta-analysis to systematically assess the postoperative prognostic value of PCI in subjects with advanced ovarian cancer to provide individualized treatment plans and thus improve the prognosis of patients. Methods: Literature on the correlation between PCI and the postoperative prognosis in subjects with advanced OC undergoing cytoreductive surgery (CRS) was searched in the Cochrane Library, Pubmed, Embase, and Web of Science from the database inception to April 20, 2023. The search was updated on February 28, 2024. We only included late-stage (FIGO stage: III-IV) patients who did not undergo neoadjuvant chemotherapy (NACT) or hyperthermic intraperitoneal chemotherapy (HIPEC). Afterwards, literature screening and data extraction were conducted using Endnote20 software. The literature quality was assessed using the Newcastle-Ottawa Scale (NOS). Lastly, statistical analysis was performed with STATA 15.0 software. Results: Five studies with 774 patients were included. The result indicated that patients with high PCI had a worse prognosis than those with low PCI. The combined hazard ratio was 2.79 [95%CI: (2.04, 3.82), p<0.001] for overall survival (OS) in patients with high PCI. Further subgroup analysis by the FIGO staging revealed that in stage III [HR: 2.61, 95%CI: (2.00, 3.40), p<0.001] and stage III-IV patients [HR: 2.69, 95%CI: (1.66, 4.36), p<0.001], a high PCI score was significantly associated with a worse prognosis. The PCI score had a greater impact on the OS of patients with higher stages. The combined hazard ratio was 1.89 [95%CI: (1.51, 2.36), p<0.001] for progression-free survival (PFS) in patients with high PCI. Conclusion: PCI may be used as a postoperative prognosis indicator in patients with advanced OC on primary debulking surgery. High PCI indicates a worse prognosis. However, further research is warranted to confirm these findings. [ABSTRACT FROM AUTHOR]

Background: The course of COVID-19 is associated with severe dysbalance of the immune system, causing both leukocytosis and lymphopenia. Immune cell monitoring may be a powerful tool to prognosticate disease outcome. However, SARS-CoV-2 positive subjects are isolated upon initial diagnosis, thus barring standard immune monitoring using fresh blood. This dilemma may be solved by epigenetic immune cell counting. Methods: In this study, we used epigenetic immune cell counting by qPCR as an alternative way of quantitative immune monitoring for venous blood, capillary blood dried on filter paper (dried blood spots, DBS) and nasopharyngeal swabs, potentially allowing a home-based monitoring approach. Results: Epigenetic immune cell counting in venous blood showed equivalence with dried blood spots and with flow cytometrically determined cell counts of venous blood in healthy subjects. In venous blood, we detected relative lymphopenia, neutrophilia, and a decreased lymphocyte-to-neutrophil ratio for COVID-19 patients (n =103) when compared with healthy donors (n = 113). Along with reported sex-related differences in survival we observed dramatically lower regulatory T cell counts in male patients. In nasopharyngeal swabs, T and B cell counts were significantly lower in patients compared to healthy subjects, mirroring the lymphopenia in blood. Naïve B cell frequency was lower in severely ill patients than in patients with milder stages. Conclusions: Overall, the analysis of immune cell counts is a strong predictor of clinical disease course and the use of epigenetic immune cell counting by qPCR may provide a tool that can be used even for home-isolated patients. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) holds immense promise for transforming ophthalmic care through automated screening, precision diagnostics, and optimized treatment planning. This paper reviews recent advances and challenges in applying AI techniques such as machine learning and deep learning to major eye diseases. In diabetic retinopathy, AI algorithms analyze retinal images to accurately identify lesions, which helps clinicians in ophthalmology practice. Systems like IDx- DR (IDx Technologies Inc, USA) are FDA-approved for autonomous detection of referable diabetic retinopathy. For glaucoma, deep learning models assess optic nerve head morphology in fundus photographs to detect damage. In age-related macular degeneration, AI can quantify drusen and diagnose disease severity from both color fundus and optical coherence tomography images. AI has also been used in screening for retinopathy of prematurity, keratoconus, and dry eye disease. Beyond screening, AI can aid treatment decisions by forecasting disease progression and anti-VEGF response. However, potential limitations such as the quality and diversity of training data, lack of rigorous clinical validation, and challenges in regulatory approval and clinician trust must be addressed for the widespread adoption of AI. Two other significant hurdles include the integration of AI into existing clinical workflows and ensuring transparency in AI decisionmaking processes. With continued research to address these limitations, AI promises to enable earlier diagnosis, optimized resource allocation, personalized treatment, and improved patient outcomes. Besides, synergistic human-AI systems could set a new standard for evidence-based, precise ophthalmic care. [ABSTRACT FROM AUTHOR]

Diagnosis and management of oral pigmented lesions can be challenging in clinical practice owing to their variable aetiology and different prognoses that range from benign, physiological conditions to systemic disorders, localised mucosal abnormalities and ultimately life-threatening malignant neoplasms such as malignant melanoma. In this paper, Peter Thomson outlines a pragmatic, clinically based approach to assessment, diagnosis and management of pigmented lesions of the oral cavity. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Data relating to the prognosis of nasopalatine nerve severance during surgical exposure and bonding or extraction of palatally impacted teeth are limited. The aim of this evaluation of clinical care was to determine the effect of partially or completely severing the nasopalatine nerve during dental surgical procedures in children. METHODS: Outcomes data from one month following surgery were compared for cases where the nerve was not damaged, partially severed or completely severed. RESULTS: None of the 28 children who had the nasopalatine bundle partially or completely severed had any long-term paraesthesia in the anterior palate region. CONCLUSIONS: This paper provides evidence and reassurance regarding the prognosis following nasopalatine nerve severance in paediatric patients, for both clinicians and patients/parents. Postoperative healing in dental surgical cases where the nasopalatine nerve is severed in children can be uneventful. Informed consent and discussion of the associated risks is still needed preoperatively, however. [ABSTRACT FROM AUTHOR]

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Surgery is the primary treatment of choice for tumours, and improves prognosis, prolongs survival and is potentially curative. Previous studies have described the effects of anaesthesia and changes in the neuroendocrine, circulatory and sympathetic nervous systems on postoperative cancer progression. There is growing evidence that intraoperative blood loss is an independent prognostic factor for tumour recurrence, postoperative inflammation is a predictor of cancer prognosis, and immunosuppressive status correlates with the degree of surgical damage. This paper outlines the potential mechanisms by which blood loss, surgical trauma and postoperative immunosuppressive status contribute to tumour growth and recurrence by reducing intraoperative haemorrhage and perioperative immunotherapy, thereby reducing tumour growth and recurrence, and improving long-term prognosis. [ABSTRACT FROM AUTHOR]

Mutated or unmutated immunoglobulin heavy chain (IGHV) gene is an important prognostic factor in chronic lymphocytic leukemia (CLL). However, a small fraction of patients with CLL are classified as borderline (BL)-IGHV. Few data are available on this subgroup of CLL. In this paper, we retrospectively report and analyze data from 21 patients with BL-IGHV CLL, showing the heterogeneity of this subgroup of CLL and paving the way for more research focusing on this entity to optimize the management and treatment of patients with Borderline- IGHV CLL. [ABSTRACT FROM AUTHOR]

Aquaporin-4 antibodies (AQP4-Abs) are a diagnostic marker for patients with a demyelinating disease called neuromyelitis optica spectrum disorder (NMOSD). Anti-Argonaute antibodies (AGO-Abs) present as potential biomarkers of the overlap syndrome between NMOSD and other autoimmune diseases. In this paper, we present the case of an adult woman with numbness, tingling, and burning sensations in her arms and subsequent bilateral internuclear ophthalmoplegia. Brain–cervical–thoracic magnetic resonance imaging (MRI) showed T2 hyperintensities in the dorsal brainstem and around the midbrain aqueduct and longitudinally transverse myelitis with homogeneous enhancement on gadolinium-enhanced MRI. The contemporaneous detection of AQP4- and AGO-Abs led to a definite diagnosis of overlap syndrome of NMOSD with AGO-Abs. The patient was treated with immunosuppressive agents, including corticosteroids and immunoglobulins, and achieved remission. This case highlights a novel phenotype of NMOSD with AGO-Abs overlap syndrome, which presents with relapsing brainstem syndrome and longitudinally extensive myelitis with acute severe neurological involvement. The promising prognosis of the disease could serve as a distinct clinical profile. Broad screening for antibodies against central nervous system autoimmune antigens is recommended in suspected patients with limited or atypical clinical manifestations. [ABSTRACT FROM AUTHOR]

Maintenance planning is crucial for efficient operation of wind turbines, particularly in harsh conditions where degradation of critical components, such as bearings, can lead to costly downtimes and safety threats. In this context, prognostics of degradation play a vital role, enabling timely interventions to prevent failures and optimize maintenance schedules. Learning systems-based vibration analysis of bearings stands out as one of the primary methods for assessing wind turbine health. However, data complexity and challenging conditions pose significant challenges to accurate degradation assessment. This paper proposes a novel approach, Uncertainty Bayesian-Optimized Extreme Recurrent EXpansion (UBO-EREX), which combines Extreme Learning Machines (ELM), a lightweight neural network, with Recurrent Expansion algorithms, a recently advanced representation learning technique. The UBO-EREX algorithm leverages Bayesian optimization to optimize its parameters, targeting uncertainty as an objective function to be minimized. We conducted a comprehensive study comparing UBO-EREX with basic ELM and a set of time-series adaptive deep learners, all optimized using Bayesian optimization with prediction errors as the main objective. Our results demonstrate the superior performance of UBO-EREX in terms of approximation and generalization. Specifically, UBO-EREX shows improvements of approximately 5.1460 ± 2.1338% in the coefficient of determination of generalization over deep learners and 5.7056% over ELM, respectively. Moreover, the objective search time is significantly reduced with UBO-EREX with 99.7884 ± 0.2404% over deep learners, highlighting its effectiveness in real-time degradation assessment of wind turbine bearings. Overall, our findings underscore the significance of incorporating uncertainty-aware UBO-EREX in predictive maintenance strategies for wind turbines, offering enhanced accuracy, efficiency, and robustness in degradation assessment. [ABSTRACT FROM AUTHOR]

Background: Spinal cord compression is a formidable complication of advanced cancer, and clinicians of copious specialities often have to encounter significant complex challenges in terms of diagnosis, management, and prognosis. Metastatic lesions from cancer are a common cause of spinal cord compression, affecting a substantial portion of oncology patients, and only in the US has the percentage risen to 10%. Acute metastasis-correlated spinal cord compression poses a considerable clinical challenge, necessitating timely diagnosis and intervention to prevent neurological deficits. Clinical presentation is often non-specific, emphasizing the importance of thorough evaluation and appropriate differential diagnosis. Diagnostic workup involves various imaging modalities and laboratory studies to confirm the diagnosis and assess the extent of compression. Treatment strategies focus on pain management and preserving spinal cord function without significantly increasing patient life expectancy, while multidisciplinary approaches are often required for optimal outcomes. Prognosis depends on several factors, highlighting the importance of early intervention. We provide an up-to-date overview of acute spinal cord compression in metastases, accentuating the importance of comprehensive management strategies. Objectives: This paper extensively explores the pathophysiology, clinical presentation, diagnostic strategies, treatment modalities, and prognosis associated with spinal cord metastases. Materials and Methods: A systematic literature review was conducted in accordance with the PRISMA guidelines. Conclusions: We aim to help healthcare professionals make informed clinical decisions when treating patients with spinal cord metastases by synthesizing current evidence and clinical insights. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths globally and the sixth most common cancer worldwide. Evidence shows that growth differentiation factor 15 (GDF15) contributes to hepatocarcinogenesis through various mechanisms. This paper reviews the latest insights into the role of GDF15 in the development of HCC, its role in the immune microenvironment of HCC, and its molecular mechanisms in metabolic dysfunction associated steatohepatitis (MASH) and metabolic associated fatty liver disease (MAFLD)-related HCC. Additionally, as a serum biomarker for HCC, diagnostic and prognostic value of GDF15 for HCC is summarized. The article elaborates on the immunological effects of GDF15, elucidating its effects on hepatic stellate cells (HSCs), liver fibrosis, as well as its role in HCC metastasis and tumor angiogenesis, and its interactions with anticancer drugs. Based on the impact of GDF15 on the immune response in HCC, future research should identify its signaling pathways, affected immune cells, and tumor microenvironment interactions. Clinical studies correlating GDF15 levels with patient outcomes can aid personalized treatment. Additionally, exploring GDF15-targeted therapies with immunotherapies could improve anti-tumor responses and patient outcomes. [ABSTRACT FROM AUTHOR]

Diabetic retinopathy (DR) is a major complication of diabetes mellitus and is a leading cause of vision loss globally. A prompt and accurate diagnosis is crucial for ensuring favorable visual outcomes, highlighting the need for increased access to medical care. The recent remarkable advancements in artificial intelligence (AI) have raised high expectations for its role in disease diagnosis and prognosis prediction across various medical fields. In addition to achieving high precision comparable to that of ophthalmologists, AI-based diagnosis of DR has the potential to improve medical accessibility, especially through telemedicine. In this review paper, we aim to examine the current role of AI in the diagnosis of DR and explore future directions. [ABSTRACT FROM AUTHOR]

Apart from providing user-friendly applications that support digitized healthcare routines, the use of wearable devices has proven to increase the independence of patients in a healthcare setting. By applying machine learning techniques to real health-related data, important conclusions can be drawn for unsolved issues related to disease prognosis. In this paper, various machine learning techniques are examined and analyzed for the provision of personalized care to COVID-19 patients with mild symptoms based on individual characteristics and the comorbidities they have, while the connection between the stimuli and predictive results are utilized for the evaluation of the system's transparency. The results, jointly analyzing wearable and electronic health record data for the prediction of a daily dyspnea grade and the duration of fever, are promising in terms of evaluation metrics even in a specified stratum of patients. The interpretability scheme provides useful insight concerning factors that greatly influenced the results. Moreover, it is demonstrated that the use of wearable devices for remote monitoring through cloud platforms is feasible while providing awareness of a patient's condition, leading to the early detection of undesired changes and reduced visits for patient screening. [ABSTRACT FROM AUTHOR]