Disease Monitoring Research Articles

Herd immunity and sustainable development goals: role of nurses in strengthening primary health care

Herd immunity has proven as a highly valuable public health concept for dealing with reinfection. It is the immunity developed in a population to an infectious disease through vaccination or previous infection which is contributed by the virulence of the organism, susceptibility of an individual to infection, extent of immunity developed towards the pathogen, occurrence of clinical and subclinical infection in the herd and herd structure. Herd immunity assessment is imperative for continuously monitoring the risk of epidemics. The minimum proportion of the population that needs to be immune to herd effect is called herd immunity threshold which can be achieved through adequate immunization coverage. Immunization contributes to 14 out of its 17 sustainable development goals (SDGs) and is important in reaching SDGs. Nurses play a vital role in strengthening primary health care through vaccination campaigns, addressing vaccine hesitancy, community outreach programs, monitoring and surveillance of diseases, advocacy, and policy development. Nurse practitioners and nurse-led vaccination programs help in reaching underserved communities or groups with vaccine hesitancy and lead to an upsurge in vaccination rates, patient satisfaction, and attainment of community immunity. Thus, vaccination is a powerful, cost-effective public health tool to achieve the eradication of diseases through proper coverage and development of population immunity.

Automated segmentation of retinal layers in optical coherence tomography images using Xception70 feature extraction

Optical coherence tomography (OCT) imaging plays a critical role in evaluating retinal layer thickness, serving as a pivotal diagnostic tool for numerous retinal conditions. However, challenges such as speckle noise, poor image contrast, and ambiguous retinal detachments, like drusen, often hinder accurate segmentation of retinal layers. To address these challenges and enhance diagnostic precision, we introduce the Retinal Segmentation Network, or "Ret-Seg Net," a deep neural network-based approach. Leveraging the advanced Xception70 feature extractor, Ret-Seg Net extracts and comprehends the intricate properties of retinal layers. By integrating acquired feature maps from Xception70 into the atrous spatial pyramid-pooling module, Ret-Seg Net extracts multiscale feature information. The encoder-decoder module of Ret-Seg Net achieves automated segmentation of retinal layers in OCT images by reconstructing distinct retinal layer borders. This advanced module accurately recognizes and differentiates retinal layer boundaries, providing precise and reliable segmentation. Validation of our approach using real-time images and the Duke dataset, comprising 310 volumes with 40 B-scans each, demonstrates outstanding performance. Mean intersection over union (MIoU) and sensitivity (Se) metrics achieved remarkable values of 94.52 % and 96.25 % respectively. Furthermore, our approach offers a versatile segmentation framework applicable to various tissues and cell types in clinical settings. Automating segmentation of retinal layers enhances precision in disease identification and monitoring while significantly improving labor efficiency by reducing the need for manual segmentation.

At-home wearable-based monitoring predicts clinical measures and biological biomarkers of disease severity in Friedreich’s Ataxia

BackgroundFriedreich ataxia (FRDA) results in progressive impairment in gait, upper extremity coordination, and speech. Currently, these symptoms are assessed through expert examination at clinical visits. Such in-clinic assessments are time-consuming, subjective, of limited sensitivity, and provide only a limited perspective of the daily disability of patients.MethodsIn this study, we recruited 39 FRDA patients and remotely monitored their physical activity and upper extremity function using a set of wearable sensors for 7 consecutive days. We compared the sensor-derived metrics of lower and upper extremity function as measured during activities of daily living with FRDA clinical measures (e.g., mFARS and FA-ADL) and biological biomarkers of disease severity (guanine-adenine-adenine (GAA) and frataxin (FXN) levels), using Spearman correlation analyses.ResultsThe results show significant correlations with moderate to high effect sizes between multiple sensor-derived metrics and the FRDA clinical and biological outcomes. In addition, we develop multiple machine learning-based models to predict disease severity in FRDA using demographic, biological, and sensor-derived metrics. When sensor-derived metrics are included, the model performance enhances 1.5-fold and 2-fold in terms of explained variance, R², for predicting FRDA clinical measures and biological biomarkers of disease severity, respectively.ConclusionsOur results establish the initial clinical validity of using wearable sensors in assessing disease severity and monitoring motor dysfunction in FRDA.

Early T-cell precursor acute lymphoblastic leukemia: diagnostic pitfalls, genomic alteration, novel therapeutics, and minimal residual disease monitoring

Early precursor T-cell acute lymphoblastic leukemia (ETP-ALL) is a rare type of T-cell ALL (T-ALL) that was initially described in 2009. Since its initial description, it has been formally recognized as a distinct entity, according to the 2016 World Health Organization classification. ETP-ALL is characterized by unique immunophenotypic and genomic profiles. The diagnosis and management of ETP-ALL remain challenging. Poorer outcomes, high incidence of induction failure and relapsed/refractory disease demand novel therapies. This review emphasizes the challenges of initial diagnosis, the molecular mechanisms underlying leukemogenesis, and the available therapeutic options. Additionally, it discusses the importance of induction failure, the prognostic value of detecting minimal residual disease, and the implications of hematopoietic stem cell transplantation, along with emerging novel therapies.

A Zn‐MOF With Its Mixed‐Matrix Membranes for Convenient and Efficient Visualization Detection of 3‐Nitrotyrosine Biomarker in Aqueous Media and Practical Application in Serum

ABSTRACTInstant and accurate detection of 3‐nitrotyrosine (3‐NT) biomarker is an important but challenging task in clinical diagnosis, treatment, and monitoring of diseases. Herein, this work reported a Zn (II)–based metal–organic framework (MOF) {[Zn2(BDPT)(DIMB)]}n, denoted as Zn‐BDPT, synthesized by solvothermal method using bis(3,5‐dicarboxyphenyl)terephthalamide (H4BDPT) and 1,4‐di(1H‐imidazol‐1‐yl)butane (DIMB). Neighboring [Zn (COO)2] clusters were connected by BDPT4− units and DIMB to form a (2,4,4)‐connected three‐dimensional (3D) architecture. X‐ray powder diffraction (PXRD) and thermogravimetric (TGA) experiments indicated that Zn‐BDPT had good purity and stability. Zn‐BDPT could selectively and rapidly recognize 3‐NT in an aqueous environment. For rapid economic detection of 3‐NT in actual samples, mixed‐matrix membranes (MMMs) based on Zn‐BDPT were successfully prepared and named Zn‐BDPT@PMMA. The addition of 3‐NT under the UV lamp displayed an evident visible fluorescence quenching effect. Quantitative titration analysis of Zn‐BDPT@PMMA in real serum sample obtained the Ksv value of 1.13 × 104 M−1 and a limit of detection (LOD) of 0.17 μM. This report demonstrated that MOF‐based MMMs could be used as ideal candidate for luminescent probe in actual application.

Cardiovascular diseases risk assessment: the Italian Health Examination Survey 2023 - CUORE Project

Abstract Background The reduction of NCDs premature mortality is pursued by the WHO; risk conditions targets are recommended as well as population-level monitoring of cardiovascular disease (CVD) risk. The Italian Ministry of Health (MoH) has strengthened prevention/health promotion and supported periodic CVD risk assessment through national health examination surveys (HESs), funded by the MoH-CCM and conducted within the CUORE Project. Methods In 2023 a new HES started including the 10-year fatal and non-fatal CVD risk assessment based on knowledge of sex, age, smoking habit, measured systolic blood pressure and fasting total and HDL serum cholesterol, and presence of diabetes (on measured fasting serum glycemia and/or treatment) and anti-hypertensive therapy. Up to now, data from random samples of residents in 7 Regions (of 20 regions) distributed in North, Centre and South of Italy, aged 35-69 years, without previous CVD, are available (585 men, 617 women). Determinations were assayed by a central lab. CUORE Project functions developed on and for the Italian adults were used. Results Mean values of the CVD risk assessment resulted 6.9% (95% CI: 6.3-7.4) in men and 2.3% (2.1-2.5) in women. For men aged 35-44 years risk was 1.6% (1.5-1.8), for 45-54 years 3.8% (3.5-4.2), for 55-64 years 10.0% (9.0-10.9), for 65-69 years 17.6% (16.4-18.9); for women was 0.5% (0.4-0.6), 1.0% (0.9-1.1), 3.3% (2.9-3.7) and 6.0% (5.5-6.6) respectively. Prevalence of CVD risk less than 5% was 57% (49-64) in men and 88% (84-93) in women, of 10-15% risk were 22% (15-28) of men and 9% (5-14) of women, of 15-20% risk were 5% (1.6-8.0) of men and 0% of women, of over 20% risk were 2% (0-3.6) of men and 0% of women. Conclusions Compared to 2008, these data showed stable mean levels of CVD risk both in men and women at any age-classes and stable prevalence of CVD risk classes. CVD risk perception represents a challenge in primary prevention especially for young age groups and women. Key messages • In the Italian general population, CVD risk assessment remained stable compared to 15 years ago. • CVD risk perception represents a challenge in primary prevention.

Long‐Term Monitoring of ApoE4 within Aqueous Humor Using Intraocular Lenses Containing Target‐Responsive Inverse Opal Hydrogel

Neurodegenerative diseases, including Alzheimer's disease (AD), pose significant challenges to global healthcare because of their irreversible postsymptomatic progression. Conventional radiographic techniques have limitations in early detection, owing to the time lapse between symptom recognition by individuals and precise inspection using medical instruments. Current research explores ophthalmic approaches to address this gap, investigating the physiological link between ocular health and brain diseases. Intraocular lenses (IOLs), widely used in cataract and refractive surgeries, provide a safe and minimally invasive platform for the continuous monitoring of neurodegenerative disease biomarkers, including those associated with AD. By integrating biomolecule‐responsive sensors with IOLs, it becomes feasible to achieve early diagnosis and long‐term, noninvasive monitoring postimplantation. Herein, a fluorescently labeled inverse opal hydrogel (FIOH) is merged with IOLs for ApoE4 detection, a key risk factor for AD. The permeability and inherent photonic properties of FIOH facilitate the cumulative enhancement of the fluorescence signal. In a simulation of the aqueous humor circulation, the detection limit for ApoE4 is determined to be 0.1 nM. Therefore, FIOH‐integrated IOLs hold promise not only for early detection but also for providing a reliable platform for the continuous, noninvasive monitoring of neurodegenerative diseases after the initial, minimally invasive implantation.

Exploring the diagnostic potential of miRNA signatures in the Fabry disease serum: A comparative study of automated and manual sample isolations.

Fabry disease, an X-linked lysosomal storage disorder caused by galactosidase α (GLA) gene mutations, exhibits diverse clinical manifestations, and poses significant diagnostic challenges. Early diagnosis and treatment are crucial for improved patient outcomes, pressing the need for reliable biomarkers. In this study, we aimed to identify miRNA candidates as potential biomarkers for Fabry disease using the KingFisher™ automated isolation method and NanoString nCounter® miRNA detection assay. Clinical serum samples were collected from both healthy subjects and Fabry disease patients. RNA extraction from the samples was performed using the KingFisher™ automated isolation method with the MagMAX mirVanaTM kit or manually using the Qiagen miRNeasy kit. The subsequent NanoString nCounter® miRNA detection assay showed consistent performance and no correlation between RNA input concentration and raw count, ensuring reliable and reproducible results. Interestingly, the detection range and highly differential miRNA between the control and disease groups were found to be distinct depending on the isolation method employed. Nevertheless, enrichment analysis of miRNA-targeting genes consistently revealed significant associations with angiogenesis pathways in both isolation methods. Additionally, our investigation into the impact of enzyme replacement therapy on miRNA expression indicated that some differential miRNAs may be sensitive to treatment. Our study provides valuable insights to identify miRNA biomarkers for Fabry disease. While different isolation methods yielded various detection ranges and highly differential miRNAs, the consistent association with angiogenesis pathways suggests their significance in disease progression. These findings lay the groundwork for further investigations and validation studies, ultimately leading to the development of non-invasive and reliable biomarkers to aid in early diagnosis and treatment monitoring for Fabry disease.

Increased prevalence of coronary atherosclerosis in cancer survivors: a matched cross-sectional study with coronary CT angiography

Abstract Background Cancer and atherosclerosis share many risk factors. Although cardiovascular disease is highly prevalent among cancer survivors, it is unknown whether coronary atherosclerosis is present at a younger age in patients with a history of cancer. Purpose The purpose of this study is to evaluate the prevalence of coronary atherosclerosis in different age groups of patients with a history of cancer compared to matched controls. Methods Consecutive patients with a history of cancer aged >30 years who underwent evaluation for coronary artery disease with coronary computed tomography angiography (CCTA) between 2010 and 2023 were included in this cross-sectional study. Patients with a history of cancer were matched 1:2 to a control population without oncological history using propensity score matching. Patients were matched on age, gender, body mass index, hypercholesterolemia, hypertension, diabetes, use of statins and smoking status. The presence of atherosclerosis in the main coronary arteries was compared between the groups. Results The study population consisted of 313 patients with an oncological history and 626 matched control patients. The median age during CCTA scan was 59.4 [50.4-67.5] years and 66.1% of the patients were female. Coronary atherosclerosis was observed in 258 (82.4%) patients with a history of cancer compared to 461 (73.6%) control patients with a risk ratio of 1.12 [95% CI: 1.04-1.20], p<0.01. Mainly younger patients with a history of cancer aged between 30-59 years had a significant increased prevalence of coronary atherosclerosis with a risk ratio of 1.18 [1.04-1.33] compared to healthy controls (p=0.02). In our study population, thoracic radiotherapy was not associated with an increased prevalence of coronary atherosclerosis. Calcified plaques were observed more frequently in patients with a history of cancer (14.4% vs. 9.3% respectively, p=0.018). Conclusion Patients with a history cancer have a higher prevalence of coronary atherosclerosis as observed on CCTA compared to matched patients without cancer. This effect was most pronounced in younger patients aged 30-59 years. There is an unmet need to define strategies for cardiovascular disease monitoring and prevention in this growing patient population of patients with a history of cancer.Presence of coronary atherosclerosisRadiotherapy and atherosclerosis

Determination of 3-hydroxyanthranilic acid in the sweat of healthy older adults

3-Hydroxyanthranillic acid (3HAA) is one of the key metabolites from the tryptophan (TRP) metabolism pathway and is associated with aging, age-associated diseases, and healthy lifespan extension. This study aims to detect 3HAA in the sweat of healthy older adults using simple, high-performance liquid chromatography (HPLC) method. Chromatographic separation using 20 mmol/L sodium acetate, 3 mmol/L zinc acetate, and 7% (v/v) acetonitrile as mobile phase is possible to simultaneous detect 3HAA, KYN, and TRP with UV and fluorescence detection, respectively, under 6 min. This method demonstrated excellent linearity with coefficient of determination (r2) greater than 0.998 for all analytes. The linear range were 0.05–6 µg/mL for TRP, 0.1–6 µg/mL for KYN and 0.2–6 µg/mL for 3HAA. Percentage recoveries from spiked in human sweat ranged from 90 ± 7–101 ± 3 for TRP, 86 ± 1–92 ± 3 for KYN, and 96 ± 1–103 ± 4 for 3HAA. The precision (%RSD) of repeatability and reproducibility is less than 3% and 6%, respectively. This method was used in a cross-sectional study with 81 participants aged 50–79 years, selected randomly from a local primary healthcare hospital’s sampling frame. A detectable amount of 3HAA was observed in all sweat samples, marking the first report of 3HAA presence in human sweat. Additionally, the results revealed that the 3HAA sweat levels increased with age analyzed in three different age groups ranging from 50–59, 60–69, and 70–79. These findings enhance our understanding of sweat profiles and their correlation with aging, potentially further improving early diagnosis, disease monitoring, and development of customized treatment programs for older adults.

Noninvasive Deep Learning Analysis for Smith–Magenis Syndrome Classification

Smith–Magenis syndrome (SMS) is a rare, underdiagnosed condition due to limited public awareness of genetic testing and a lengthy diagnostic process. Voice analysis can be a noninvasive tool for monitoring and detecting SMS. In this paper, the cepstral peak prominence and mel-frequency cepstral coefficients are used as disease monitoring and detection metrics. In addition, an efficient neural network, incorporating synthetic data processes, was used to detect SMS in a cohort of individuals with the disease. Three study cases were conducted with a set of 19 SMS patients and 292 controls. The three study cases employed various oversampling and undersampling techniques, including SMOTE, random oversampling, NearMiss, random undersampling, and 16 additional methods, resulting in balanced accuracies ranging from 69% to 92%. This is the first study using a neural network model to focus on a rare genetic syndrome using phonation analysis data. By using synthetic data (oversampling and undersampling) and a CNN, it was possible to detect SMS with high levels of accuracy. Voice analysis and deep learning techniques have proven to be a useful and noninvasive method. This is a finding that may help in the complex identification of this syndrome as well as other rare diseases.

Neurovascular unit, neuroinflammation and neurodegeneration markers in brain disorders.

Neurovascular unit (NVU) inflammation via activation of glial cells and neuronal damage plays a critical role in neurodegenerative diseases. Though the exact mechanism of disease pathogenesis is not understood, certain biomarkers provide valuable insight into the disease pathogenesis, severity, progression and therapeutic efficacy. These markers can be used to assess pathophysiological status of brain cells including neurons, astrocytes, microglia, oligodendrocytes, specialized microvascular endothelial cells, pericytes, NVU, and blood-brain barrier (BBB) disruption. Damage or derangements in tight junction (TJ), adherens junction (AdJ), and gap junction (GJ) components of the BBB lead to increased permeability and neuroinflammation in various brain disorders including neurodegenerative disorders. Thus, neuroinflammatory markers can be evaluated in blood, cerebrospinal fluid (CSF), or brain tissues to determine neurological disease severity, progression, and therapeutic responsiveness. Chronic inflammation is common in age-related neurodegenerative disorders including Alzheimer's disease (AD), Parkinson's disease (PD), and dementia. Neurotrauma/traumatic brain injury (TBI) also leads to acute and chronic neuroinflammatory responses. The expression of some markers may also be altered many years or even decades before the onset of neurodegenerative disorders. In this review, we discuss markers of neuroinflammation, and neurodegeneration associated with acute and chronic brain disorders, especially those associated with neurovascular pathologies. These biomarkers can be evaluated in CSF, or brain tissues. Neurofilament light (NfL), ubiquitin C-terminal hydrolase-L1 (UCHL1), glial fibrillary acidic protein (GFAP), Ionized calcium-binding adaptor molecule 1 (Iba-1), transmembrane protein 119 (TMEM119), aquaporin, endothelin-1, and platelet-derived growth factor receptor beta (PDGFRβ) are some important neuroinflammatory markers. Recent BBB-on-a-chip modeling offers promising potential for providing an in-depth understanding of brain disorders and neurotherapeutics. Integration of these markers in clinical practice could potentially enhance early diagnosis, monitor disease progression, and improve therapeutic outcomes.

Equity-centered adaptive sampling in sub-sewershed wastewater surveillance using census data.

Sub-city, or sub-sewershed, wastewater monitoring for infectious diseases offers a data-driven strategy to inform local public health response and complements city-wide data from centralized wastewater treatment plants. Developing strategies for equitable representation of diverse populations in sub-city wastewater sampling frameworks is complicated by misalignment between demographic data and sampling zones. We address this challenge by: (1) developing a geospatial analysis tool that probabilistically assigns demographic data for subgroups aggregated by race and age from census blocks to sub-city sampling zones; (2) evaluating representativeness of subgroup populations for COVID-19 wastewater-based disease surveillance in Davis, California; and (3) demonstrating scenario planning that prioritizes vulnerable populations. We monitored SARS-CoV-2 in wastewater as a proxy for COVID-19 incidence in Davis (November 2021-September 2022). Daily city-wide sampling and thrice-weekly sub-city sampling from 16 maintenance holes covered nearly the entire city population. Sub-city wastewater data, aggregated as a population-weighted mean, correlated strongly with centralized treatment plant data (Spearman's correlation 0.909). Probabilistic assignment of demographic data can inform decisions when adapting sampling locations to prioritize vulnerable groups. We considered four scenarios that reduced the number of sampling zones from baseline by 25% and 50%, chosen randomly or to prioritize coverage of >65-year-old populations. Prioritizing representation increased coverage of >65-year-olds from 51.1% to 67.2% when removing half the zones, while increasing coverage of Black or African American populations from 67.5% to 76.7%. Downscaling had little effect on correlations between sub-city and centralized data (Spearman's correlations ranged from 0.875 to 0.917), with strongest correlations observed when prioritizing coverage of >65-year-old populations.

Soluble B-cell maturation antigen levels for disease monitoring in oligo- and non-secretory relapsed multiple myeloma

Soluble B-cell maturation antigen (sBCMA) is overexpressed on multiple myeloma (MM) cells. We investigated whether sBCMA levels correlated with other myeloma tumor volume indicators and its utility in monitoring oligo-secretory/non-secretory (O-S/Non-S) MM. In 115 patients with newly diagnosed MM, sBCMA was compared with M-protein levels, bone marrow plasma cells (BMPCs), circulating tumor cells (CTCs), and total diffusion volume (tDV; estimated by whole-body diffusion-weighted magnetic resonance imaging) at diagnosis. sBCMA levels increased significantly with International Staging System stage, chromosome 1q21 gain/amplification and CTC levels. sBCMA also correlated strongly with %BMPC (r = 0.65), moderately with tDV (r = 0.55) and paraprotein levels (involved immunoglobulin in IgG and IgA subtypes, r = 0.44 and 0.4; involved free light-chain levels in light-chain-only MM, r = 0.61, all P < 0.05). Longitudinal changes in sBCMA were consistent with disease status in both 17 O-S/Non-S and other secretory MM cases. Furthermore, sBCMA levels increased as early as 6 months pre-relapse in almost all O-S/Non-S relapsed patients. Thus, sBCMA correlates strongly with total tumor volume in MM, as assessed using different modalities. We suggest that sBCMA is useful, not only for monitoring responses in patients with O-S/Non-S MM but also for early relapse detection and prediction.

Glycomics as prognostic biomarkers of hepatocellular carcinoma: A systematic review.

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies, which is associated with a low 5-year survival rate. The importance of effective disease monitoring and prognostic evaluation is undeniable. For the present study, a systematic review was performed using extensive searches in Medline, Embase, Web of Science and Scopus up to December 29, 2023. The aim of the present study was to examine whether N-glycomics could predict the risk of developing HCC in adults with chronic liver disease and, if HCC was present, predict overall survival. As a secondary outcome, the prediction capability of HCC recurrence was assessed. After deduplication, 3,904 studies were identified, of which 30 were included. Overall, the median size of the study cohort was 144 patients, with a median follow-up time of 63.6 months. Three studies explored N-glycomics in whole serum, whereas the rest focused on individual glycoproteins, with Mac-2 binding protein glycosylation isomer (M2BPGi) being the most commonly studied. Most articles investigated baseline M2BPGi values as predictors for the development of HCC and demonstrated a median area under the curve of 0.83 with a cut-off index value of 1.8. In conclusion, it was revaled that N-glycan changes exhibit added value in determining patient prognosis in terms of survival, monitoring HCC development and recurrence.

MicroRNAs as Biomarkers in Spinal Muscular Atrophy

Spinal muscular atrophy (SMA) is a severe neurodegenerative disease caused by the loss of the survival motor neuron (SMN) protein, leading to degeneration of anterior motor neurons and resulting in progressive muscle weakness and atrophy. Given that SMA has a single, well-defined genetic cause, gene-targeted therapies have been developed, aiming to increase SMN production in SMA patients. The SMN protein is likely involved in the synthesis of microRNAs (miRNAs), and dysregulated miRNA expression is increasingly associated with the pathophysiology of SMA. Currently, there is a lack of reliable biomarkers to monitor SMA; therefore, the search for novel SMA biomarkers, including miRNAs, is crucial as reliable tools are needed to track disease progression, predict the response to therapy and understand the different clinical outcomes of available treatments. In this review, we compile data on miRNAs associated with SMA pathogenesis and their potential use as biomarkers. Based on current knowledge, the most frequently deregulated miRNAs between SMA patients and controls, as well as pre- and post-treatment in SMA patients, include miR-1-3p, miR-133a-3p, miR-133b, and miR-206. These findings offer promising possibilities for improving patient classification and monitoring disease progression and response to treatment. Additionally, these findings provide insights into the broader molecular mechanisms and networks of SMA that could inform the development of future therapeutic strategies.

Contemporary Concise Review 2023: Interstitial lung disease.

In this review, we have discussed several important developments in 2023 in Interstitial Lung Disease (ILD). The association of pollution with genetic predispositions increased the risk of Idiopathic Pulmonary Fibrosis (IPF). An interesting comorbidity of malnutrition was not adequately recognized in ILD. Novel genes have been identified in IPF involving predominantly short telomere length and surfactant protein production leading to alveolar epithelial cell dysfunction. Genetics also predicted progression in IPF. Crosstalk between vascular endothelial cells and fibroblasts in IPF mediated by bone morphogenic protein signalling may be important for remodelling of the lung. A novel modality for monitoring of disease included the 4-min gait speed. New treatment modalities include inhaled pirfenidone, efzofitimod, for sarcoidosis, and earlier use of immunosuppression in connective tissue disease-ILD.

Phrenic Nerve Sonography Alterations in Patients with ALS: Insight with Clinical and Neurophysiological Findings.

Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder, and although the diagnosis is primarily based on clinical criteria, ENMG, as the "gold standard", does not always show detectable changes. Therefore, our study suggests that alterations in echogenicity and heterogeneity of the phrenic nerve (PN) may serve as potential additional diagnostic tools for ALS. Methods: Our study included 32 patients in the ALS group and 64 individuals in the control group. Each participant underwent an interview and completed questionnaires to collect clinical and demographic data, including age, gender, height, body mass index (BMI), hip and waist circumference, duration of illness, ALS-FRS-R score, comorbidities, and medication use. Ultrasound examinations of the PN were performed by two authors using a high-resolution "Philips EPIQ 7" ultrasound machine equipped with a linear 4-18 MHz transducer. The ALS group participants underwent PN sonography and conduction examinations, arterial blood gas (ABG) analysis, respiratory function tests (RFT), and electroneuromyography (ENMG). Results: The study demonstrated that the phrenic nerve is significantly smaller on both sides in patients with ALS compared to the control group (p < 0.01). Changes in the homogeneity and echogenicity of the PN were also observed on both sides. On the right side, 43.8% of the nerves showed heterogeneity, 40.6% were isoechoic, and 21.9% were hyperechoic. On the left side, 59.4% of the nerves exhibited heterogeneity, 34.4% were isoechoic, and 28.1% were hyperechoic. Moreover, sonography on both sides showed significant correlation with ALS-FRS-R, COMPASS-31, and ENMG results. Conclusions: Our study highlights the importance of phrenic nerve ultrasound as a promising supplementary diagnostic tool for ALS. The significant differences in phrenic nerve size, echogenicity, and homogeneity between patients with ALS and the control group demonstrate that ultrasound imaging can detect morphological changes in the phrenic nerve. Incorporating phrenic nerve ultrasound into routine diagnostic protocols could improve early detection, enhance disease monitoring, and offer a more comprehensive understanding of the neurodegenerative processes in ALS.

Circulating Extracellular Matrix Products as Indicators of Disease Burden and Predictors of Disease Course in Ulcerative Colitis.

Ulcerative colitis (UC) is characterized by recurrent inflammation and challenging disease monitoring, with invasive endoscopy as the primary diagnostic tool despite the inadequacy of standard noninvasive biomarkers. This study evaluates serum extracellular matrix (ECM) fragments, which reflect the remodeling of mucosa and submucosa, as potential indicators of disease burden and treatment efficacy. We aim to determine whether serum ECM levels correlate with the extent and severity and predict treatment response. We conducted a prospective study comparing serum ECM formation (PRO-C3, PRO-C7, PRO-C11, PRO-C22), turnover (PRO-C4), and degradation markers (C1M, C3M, C4M, C7M) at Weeks 0, 12, and 24 in 49 UC patients and 50 healthy controls measured by enzyme-linked immunosorbent assay. ECM biomarkers, notably PRO-C11, differentiated UC patients from controls (area under the curve [AUC] 0.77), and PRO-C3 predicted endoscopic treatment response vs nonresponse (AUC 0.74). C7M separated moderate from severe disease in endoscopy (AUC 0.74) as well as mild from severe disease (AUC 0.84), as did the ratio C7M/PRO-C7 (AUC 0.82). Combining new and conventional markers, including hemoglobin, C-reactive protein, PRO-C3, and PRO-C22, achieved a combined AUC of 0.84 for predicting 24-week endoscopic response, adding index endoscopic activity increased the AUC to 0.92 compared to an AUC of 0.84 for endoscopy alone. Soluble ECM fragments reflect endoscopic disease severity and extent and are also predictive of therapeutic efficacy. They may as well reflect degenerative aspects of UC and may as such be future therapeutic targets aimed at prevention of intestinal damage.

Advancing personalized oncology: a systematic review on the integration of artificial intelligence in monitoring neoadjuvant treatment for breast cancer patients.

Despite suffering from the same disease, each patient exhibits a distinct microbiological profile and variable reactivity to prescribed treatments. Most doctors typically use a standardized treatment approach for all patients suffering from a specific disease. Consequently, the challenge lies in the effectiveness of this standardized treatment and in adapting it to each individual patient. Personalized medicine is an emerging field in which doctors use diagnostic tests to identify the most effective medical treatments for each patient. Prognosis, disease monitoring, and treatment planning rely on manual, error-prone methods. Artificial intelligence (AI) uses predictive techniques capable of automating prognostic and monitoring processes, thus reducing the error rate associated with conventional methods. This paper conducts an analysis of current literature, encompassing the period from January 2015 to 2023, based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). In assessing 25 pertinent studies concerning predicting neoadjuvant treatment (NAT) response in breast cancer (BC) patients, the studies explored various imaging modalities (Magnetic Resonance Imaging, Ultrasound, etc.), evaluating results based on accuracy, sensitivity, and area under the curve. Additionally, the technologies employed, such as machine learning (ML), deep learning (DL), statistics, and hybrid models, were scrutinized. The presentation of datasets used for predicting complete pathological response (PCR) was also considered. This paper seeks to unveil crucial insights into the application of AI techniques in personalized oncology, particularly in the monitoring and prediction of responses to NAT for BC patients. Finally, the authors suggest avenues for future research into AI-based monitoring systems.