Monitoring Disease Progression Research Articles

Possible alteration in serum ferritin level in malaria infected HIV seropositive individuals in Nauth, Nnewi, Nigeria

The role of Ferritin in monitoring disease progression in immune compromised HIV individuals with an underlying active infection like malaria is a subject of growing research. Ferritin being an acute phase protein, plays important role in assessing the range of damage due to inflammation in immunosuppressed patients leaving in highly endemic malaria regions. The levels of serum ferritin in malaria infected HIV positive individuals in Nnamdi Azikiwe University teaching hospital (NAUTH), Nnewi, Anambra State, Nigeria, was assessed. Questionnaire was used to obtain the demographic details of the participants, and to rule out other inflammatory infections. 88 participants of the age group 18 - 65 years, comprising 24 with HIV infection, 22 with HIV and Malaria co-infection, 22 with Malaria infection, and a control group of 22 individuals with neither HIV nor malaria infection were randomly recruited. Ferritin level was determined using enzyme linked immunosorbent assay technique and a cross sectional prospective study design was used. A significantly high mean serum ferritin level was observed in HIV infected individuals with and/ or without malaria co-infection than in malaria positive and control group (p<0.05 respectively). Serum ferritin level was significantly higher in female participants than in male counterparts (p < 0.05). Serum ferritin level was significantly higher in individuals with CD4 count >500 than in CD4 count ≤ 500 (p < 0.05). Blood pressure was significantly higher in HIV infected and malaria positive individuals when compared with controls. The increased serum ferritin level and higher blood pressure in HIV infected participants suggests active inflammatory process, reduced immunity and hypertension which may have worsened by malaria co-infection. This may subsequently lead to vascular and endothelia damage causing disease severity.

Gold Nanoparticles: An Emerging Novel Technology for Targeted Delivery System for Site-Specific Diseases

Abstract: Gold Nanoparticles (GNPs) have emerged as a novel technology in the field of targeted delivery systems, offering promising solutions for site-specific disease treatment. These nanoparticles possess unique physicochemical properties, such as controlled size, shape, and surface chemistry, which enable precise manipulation for enhanced therapeutic efficacy. The biocompatibility and ease of functionalization of GNPs facilitate the conjugation with various biomolecules, including drugs, peptides, and nucleic acids, thereby improving their targeted delivery capabilities. Recent advancements in nanotechnology have leveraged GNPs for the treatment of a range of diseases, particularly in oncology, cardiology, and neurology. In cancer therapy, GNPs can be engineered to target tumor cells selectively, minimizing damage to healthy tissues and reducing side effects. This is achieved through the conjugation of GNPs with tumor-specific ligands, antibodies, or aptamers, which direct the nanoparticles to malignant cells, allowing for localized drug release and improved therapeutic outcomes. Moreover, GNPs exhibit remarkable potential in diagnostic imaging and photothermal therapy. Their unique optical properties, such as surface plasmon resonance, enable their use as contrast agents in imaging techniques, providing high-resolution and real-time monitoring of disease progression. In photothermal therapy, GNPs convert light energy into heat, effectively destroying targeted cells with minimal invasiveness. The development of GNP-based delivery systems also addresses significant challenges in drug resistance and bioavailability. By overcoming biological barriers and enhancing cellular uptake, GNPs improve the pharmacokinetics and pharmacodynamics of therapeutic agents. However, despite these advancements, the clinical translation of GNPs faces challenges such as potential toxicity, long-term stability, and regulatory hurdles. In conclusion, gold nanoparticles represent a cutting-edge approach in targeted delivery systems, offering significant potential for site-specific disease treatment. Continued research and innovation are essential to overcome existing challenges and fully realize the clinical applications of GNPs, ultimately revolutionizing precision medicine. Gold nanoparticles exhibit unique physicochemical and optical properties. The gold nanoparticles have advanced techniques to cure different chronic diseases. Today, gold nanoparticles are aided by photodynamic therapy and radiation therapy as drug carriers. Due to this, researchers now focus on medical sciences to treat various diseases and therapeutic applications. This review provides all the aspects of gold-based nanoparticles, methods, and their pharmacological benefits in different fields of medical sciences. We also discuss various preparation methods and their advantages in pharmaceutical formulations.

Monitoring mouse papillomavirus-associated cancer development using longitudinal Pap smear screening.

Papanicolaou (Pap) smear has saved millions of women's lives as a valuable early screening tool for detecting human papillomavirus (HPV) cervical precancers and cancer. However, more than 200,000 women in the United States alone remain at risk for cervical cancer due to pre-existing HPV infection-induced precancers, as there are currently no effective treatments for HPV-associated precancers and cancers other than invasive procedures including a loop electrosurgical excision procedure (LEEP) to remove abnormal tissues. In the current study, we validated the use of Pap smears to monitor disease progression in our recently established mouse papillomavirus model. To the best of our knowledge, this is the first study that provides compelling evidence of applying Pap smears from cervicovaginal swabs to monitor disease progression in mice. This HPV-relevant cytology assay will enable us to develop and test novel antiviral and anti-tumor therapies using this model to eliminate HPV-associated diseases and cancers.

Mechanical rheological model on the assessment of elasticity and viscosity in tissue inflammation: A systematic review.

Understanding the extent of inflammation is crucial for early disease detection, monitoring disease progression, and evaluating treatment responses. Over the past decade, researchers have demonstrated the need to understand the extent of inflammation through qualitative or quantitative characterization of tissue viscoelasticity using different techniques. In this scientific review, an examination of research on the association between elasticity and Viscosity in diseases, particularly as tissue inflammation progresses, is conducted. A review of utilizing mechanical rheological models to characterize quantitative viscoelastic parameters of normal and inflamed tissues is also undertaken. Based on inclusion and exclusion criteria, we identified 14 full-text studies suitable for review out of 290 articles published from January 2000 to January 2024. We used PRISMA guidelines for the systematic review. In the review, three studies demonstrated the criterion used by the researchers in identifying the best rheological model. Eleven studies showed the clinical application of the rheological model in quantifying the viscoelastic properties of normal and pathological tissue. The review quantified viscoelastic parameters for normal and pathological tissue across various soft tissues. It evaluated the effectiveness of each viscoelastic property in distinguishing between normal and pathological tissue stiffness. Furthermore, the review outlined additional viscoelastic-related parameters for researchers to consider in future stiffness classification studies.

Parotid saliva and blood biomarkers in juvenile idiopathic arthritis in relation to temporomandibular joint magnetic resonance imaging findings.

Juvenile idiopathic arthritis (JIA) often affects the temporomandibular joint (TMJ) caused by an abnormal immune system that includes overactive inflammatory processes. Salivary biomarkers may be a powerful tool that can help establishing diagnosis, prognosis and monitor disease progress. The objective was to investigate biomarkers in parotid saliva and blood plasma in relation to temporomandibular joint (TMJ) magnetic resonance imaging (MRI) findings in patients with JIA and healthy individuals. Forty-five children aged 6 to 16 years with JIA and 16 healthy age- and sex-matched controls were included. Unstimulated parotid saliva samples and venous blood were collected. Biochemical analyses were performed for the cytokine biomarkers. The participants underwent MR imaging of the TMJs, where changes in the inflammatory and the damage domains were assessed. In the JIA patients, lower concentrations of IL-6R and gp130 were found in parotid saliva than in plasma. Higher concentrations of IL-6 were found in parotid saliva than in plasma. IL-6, IL-6R and gp130 in parotid saliva explained the presence of bone marrow oedema and effusion in the JIA patients. This study suggests that the IL-6 family in parotid saliva is associated with TMJ bone marrow oedema and effusion in patients with JIA, suggesting that IL-6 has promising properties as a parotid saliva biomarker for TMJ inflammatory activity.

Empowered chaotic local search-based differential evolution algorithm with entropy-based hybrid objective function for brain tumor segmentation

In neuro-oncology, the precise segmentation of brain tumors from Magnetic Resonance Images is crucial for diagnosis, treatment planning, and monitoring disease progression. Accurate segmentation helps determine the tumor’s size, location, and growth potential, which is essential for formulating effective treatment strategies. In response to this challenge, we developed a novel approach using Chaotic Local Search-Enhanced Differential Evolution (CJADE). CJADE, particularly its variant CJADE-M, which employs chaotic maps selected through a probability-based approach, has proven effective in optimizing brain tumor segmentation. Our study shows that CJADE-M outperforms traditional metaheuristic algorithms on various evaluation metrics. We further enhanced CJADE-M with an entropy-based hybrid objective function, which improved accuracy and reduced computational time in tumor segmentation compared to conventional methods like Minimum Cross-Entropy and Kapur. This makes our method suitable for real-time medical imaging analysis. Our findings indicate that CJADE-M, equipped with the hybrid objective function, achieves superior segmentation performance for both benign lobulated and malignant irregular tumors across metrics such as PSNR, FSIM, QILV, and HPSI. By providing a more accurate and efficient tool, our approach can significantly enhance the outcomes of brain tumor diagnosis and treatment, improving patient care in neuro-oncology.

Associations between Serum Metabolites and Female Cancers: a Bidirectional Two-sample Mendelian Randomization Study

Female cancers, especially breast, ovarian, cervical and endometrial cancers, constitute a major threat to women's health worldwide. In view of the complex genetic background of cancers cannot be fully explained with current genetic information, we used a bidirectional two-sample mendelian randomization approach to explore the causal associations between serum metabolites and four major female cancers—breast, ovarian, cervical and endometrial cancers. We analyzed the metabolites dataset from the Canadian Longitudinal Study of Aging and cancer datasets from the 10th round of the Finngen project. Replication analyses was performed with Cancer Association Consortium and Leo’s studies. Instrumental variables were analyzed using methods including the Wald ratio, inverse-variance weighted, MR-Egger, and weighted median. To ensure robustness, sensitivity analyses were performed using Cochrane’s Q, Egger’s intercept, MR-PRESSO, and leave-one-out methods. After meticulous analysis, we obtained levels of 3-hydroxyoleoylcarnitine, hexadecanedioate, tetradecanedioate and carnitine C14 with robust causal associations with breast cancer, levels of 5alpha-androstan-3alpha,17beta-diol monosulfate (1), androstenediol (3beta,17beta) monosulfate (1), androsterone sulfate, and 5alpha-androstan-3beta,17beta-diol disulfate causal associations with endometrial cancer. The reverse analysis showed that breast, ovarian, and endometrial cancer and survival of breast and ovarian cancer were found to have causal relationships with 8, 5, 2, 6, and 3 metabolites, respectively. These insights underscore the potential roles of specific metabolites in the etiology of female cancers, providing new biomarkers for early detection, risk stratification, and disease progression monitoring. Further research could elucidate how these metabolites influence specific pathways in cancer development, offering theoretical foundations for prevention and treatment strategies.

Value of Mac-2 Binding Protein Glycosylation Isomer (M2BPGi) in Assessing Liver Fibrosis in Metabolic Dysfunction-Associated Liver Disease: A Comprehensive Review of its Serum Biomarker Role.

Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD) is a broad condition characterized by lipid accumulation in the liver tissue, which can progress to fibrosis and cirrhosis if left untreated. Traditionally, liver biopsy is the gold standard for evaluating fibrosis. However, non-invasive biomarkers of liver fibrosis are developed to assess the fibrosis without the risk of biopsy complications. Novel serum biomarkers have emerged as a promising tool for non-invasive assessment of liver fibrosis in MAFLD patients. Several studies have shown that elevated levels of Mac-2 binding protein glycosylation isomer (M2BPGi) are associated with increased liver fibrosis severity in MAFLD patients. This suggests that M2BPGi could serve as a reliable marker for identifying individuals at higher risk of disease progression. Furthermore, the use of M2BPGi offers a non-invasive alternative to liver biopsy, which is invasive and prone to sampling errors. Overall, the usage of M2BPGi in assessing liver fibrosis in MAFLD holds great promise for improving risk stratification and monitoring disease progression in affected individuals. Further research is needed to validate its utility in clinical practice and establish standardized protocols for its implementation.

Exploring explainable AI features in the vocal biomarkers of lung disease

This review delves into the burgeoning field of explainable artificial intelligence (XAI) in the detection and analysis of lung diseases through vocal biomarkers. Lung diseases, often elusive in their early stages, pose a significant public health challenge. Recent advancements in AI have ushered in innovative methods for early detection, yet the black-box nature of many AI models limits their clinical applicability. XAI emerges as a pivotal tool, enhancing transparency and interpretability in AI-driven diagnostics. This review synthesizes current research on the application of XAI in analyzing vocal biomarkers for lung diseases, highlighting how these techniques elucidate the connections between specific vocal features and lung pathology. We critically examine the methodologies employed, the types of lung diseases studied, and the performance of various XAI models. The potential for XAI to aid in early detection, monitor disease progression, and personalize treatment strategies in pulmonary medicine is emphasized. Furthermore, this review identifies current challenges, including data heterogeneity and model generalizability, and proposes future directions for research. By offering a comprehensive analysis of explainable AI features in the context of lung disease detection, this review aims to bridge the gap between advanced computational approaches and clinical practice, paving the way for more transparent, reliable, and effective diagnostic tools.

The predictive role of the platelet-to-lymphocyte ratio for the risk of non-alcoholic fatty liver disease and cirrhosis: a nationwide cross-sectional study.

The associations between platelet-to-lymphocyte ratio (PLR) and non-alcoholic fatty liver disease (NAFLD) and cirrhosis are unclear, andthere are still no effective means for diagnosing or monitoring disease progression. Data from the National Health and Nutrition Examination Surveys were collected for analysis. Logistic regression and restricted cubic splines were used to evaluate the associations between PLR and NAFLD and cirrhosis in different populations. The Area Under Curve Receiver Operating Characteristic (AUCROC) was used to distinguish the models. Threshold analysis was performed by constructing a two-piecewise linear regression. Correlation analysis was performed separately on either side of the inflection point. A total of 5724 adults were included. Logistic regression analysis revealed that the PLR was associated with NAFLD and cirrhosis (AUCROC of NAFLD: 0.803; AUCROC of cirrhosis: 0.851). The AUCROC of the PLR for predicting NAFLD incidence was 0.762 in the diabetic population and 0.804 in the nondiabetic population. High PLR predicted cirrhosis in the diabetic population, with an AUCROC of 0.824, whereas a high PLR was not associated with cirrhosis in the nondiabetic population. The restricted cubic spline revealed a negative linear correlation between the PLR and NAFLD incidence. The inflection point of the PLR for NAFLD was 180.74.A PLR ≤180.74 was statistically significant (odds ratio=0.997, 95% confidence interval=0.995-0.999). In the NAFLD population, the PLR was negatively correlated with cirrhosis at a PLR ≤130.5 (odds ratio=0.987, 95% confidence interval=0.977-0.996) and positively correlated with cirrhosis at a PLR > 130.5 (odds ratio=1.006, 95% confidence interval=1.001-1.012). The PLR and NAFLD were negatively correlated in the U.S. population. The PLR had a U-shaped relationship with cirrhosis in the NAFLD population. The PLR has potential value in monitoring NAFLD patient progression to cirrhosis.

Nuclear imaging techniques for cardiac amyloidosis.

Cardiac amyloidosis is a condition marked by the misfolding of precursor proteins into insoluble amyloid fibrils, leading to restrictive cardiomyopathy and heart failure symptoms. This review discusses advancements in nuclear imaging techniques that enhance the diagnosis and guide the management of cardiac amyloidosis, addressing the critical need for early and accurate detection in clinical practice. Recent studies and guidelines emphasizes the pivotal role of nuclear imaging techniques in diagnosing cardiac amyloidosis. Cardiac scintigraphy, using bone-avid tracers like 99mTc-PYP, 99mTc-DPD, and 99mTc-HMDP, is instrumental in distinguishing between transthyretin amyloidosis and light chain amyloidosis. PET, with tracers such as 11C-Pittsburgh Compound B (11C-PiB) and 18F-Florbetapir, offers significant potential in measuring amyloid burden and monitoring disease progression, providing detailed insights into the myocardial involvement. The advancements in nuclear imaging techniques significantly impact the management of cardiac amyloidosis. These methods allow for a more accurate diagnosis, detailed assessment of disease extent, and better differentiation between amyloidosis types, which are crucial for tailoring treatment approaches. The integration of these techniques into clinical practice is essential for improving patient outcomes and advancing research in cardiac amyloidosis.

Value of Mac-2 Binding Protein Glycosylation Isomer (M2BPGi) in Assessing Liver Fibrosis in Metabolic Dysfunction-Associated Liver Disease: A Comprehensive Review of its Serum Biomarker Role.

Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD) is a broad condition characterized by lipid accumulation in the liver tissue, which can progress to fibrosis and cirrhosis if left untreated. Traditionally, liver biopsy is the gold standard for evaluating fibrosis. However, non-invasive biomarkers of liver fibrosis are developed to assess the fibrosis without the risk of biopsy complications. Novel serum biomarkers have emerged as a promising tool for non-invasive assessment of liver fibrosis in MAFLD patients. Several studies have shown that elevated levels of Mac-2 binding protein glycosylation isomer (M2BPGi) are associated with increased liver fibrosis severity in MAFLD patients. This suggests that M2BPGi could serve as a reliable marker for identifying individuals at higher risk of disease progression. Furthermore, the use of M2BPGi offers a non-invasive alternative to liver biopsy, which is invasive and prone to sampling errors. Overall, the usage of M2BPGi in assessing liver fibrosis in MAFLD holds great promise for improving risk stratification and monitoring disease progression in affected individuals. Further research is needed to validate its utility in clinical practice and establish standardized protocols for its implementation.

Clinical significance of circulating tumor cells in colorectal cancer with peritoneal metastases: a prospective cohort study using a novel method for monitoring treatment response, and assessing minimal residual disease.

The treatment for patients with colorectal cancer with metastases to the peritoneum is complex and may involve both surgery and chemotherapy. Circulating tumor cells (CTCs) have been poorly investigated in peritoneal metastatic colorectal cancer. The aim of the study is to examine the role of circulating tumor cells (CTCs) as a biomarker for monitoring disease progression, treatment response and residual disease using CellMate® - a new promising in vitro diagnostic platform technology. We prospectively followed clinical outcomes of 46 patients treated with cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) for colorectal cancer with peritoneal metastases and examined whether CTCs were present the week of surgery. The CTC measurements were made with the CellMate® technology, which is a platform technology to detect CTCs based on the difference in biomechanical properties compared to blood resident cells. The study was registered online (ClinicalTrials.gov). CTCs were detected in 17 (37%) patients. The presence of CTCs was associated with shorter recurrence-free survival and overall survival after CRS and HIPEC. Both recurrence free survival (HR 4.00, 95%CI 1.15-13.9; P=0.029) and overall survival (HR 5.91; 95% CI 1.18-29.7; P=0.03) were significantly worse if CTCs were detected after neoadjuvant treatment. In the subgroup of patients with CTCs detected, adjuvant therapy tended to improve the prognosis while in CTC negative patients it did not. Pending a prospective multi-center trial to validate these findings, CTCs may in the future be used as a dynamic personalized biomarker for prognostication, predicting response to therapy, and for monitoring disease progression in colorectal cancer with metastases to the peritoneum.

Tumor-Derived Extracellular Vesicles as Liquid Biopsy for Diagnosis and Prognosis of Solid Tumors: Their Clinical Utility and Reliability as Tumor Biomarkers.

Early cancer detection and accurate monitoring are crucial to ensure increased patient survival. Recent research has focused on developing non-invasive biomarkers to diagnose cancer early and monitor disease progression at low cost and risk. Extracellular vesicles (EVs), nanosized particles secreted into extracellular spaces by most cell types, are gaining immense popularity as novel biomarker candidates for liquid cancer biopsy, as they can transport bioactive cargo to distant sites and facilitate intercellular communications. A literature search was conducted to discuss the current approaches for EV isolation and the advances in using EV-associated proteins, miRNA, mRNA, DNA, and lipids as liquid biopsies. We discussed the advantages and challenges of using these vesicles in clinical applications. Moreover, recent advancements in machine learning as a novel tool for tumor marker discovery are also highlighted.

Imaging the optic nerve with optical coherence tomography.

Optical coherence tomography (OCT) is a non-invasive imaging technology, which may be used to generate in vivo quantitative and qualitative measures of retinal structure. In terms of quantitative metrics, peripapillary retinal nerve fiber layer (pRNFL) thickness provides an indirect evaluation of axonal integrity within the optic nerve. Ganglion layer measures derived from macular scans indirectly reflect retinal ganglion cell status. Notably, ganglion layer indices are platform dependent and may include macular ganglion cell inner plexiform layer (mGCIPL), ganglion cell layer (GCL), and ganglion cell complex (GCC) analyses of thickness or volume. Interpreted together, pRNFL thickness and ganglion layer values can be used to diagnose optic neuropathies, monitor disease progression, and gauge response to therapeutic interventions for neuro-ophthalmic conditions. Qualitative assessments of the optic nerve head, using cross-sectional transverse axial, en face, and circular OCT imaging, may help distinguish papilledema from pseudopapilloedema, and identify outer retinal pathology. Innovations in OCT protocols and approaches including enhanced depth imaging (EDI), swept source (SS) techniques, and angiography (OCTA) may offer future insights regarding the potential pathogenesis of different optic neuropathies. Finally, recent developments in artificial intelligence (AI) utilizing OCT images may overcome longstanding challenges, which have plagued non-vision specialists who often struggle to perform reliable ophthalmoscopy. In this review, we aim to discuss the benefits and pitfalls of OCT, consider the practical applications of this technology in the assessment of optic neuropathies, and highlight scientific discoveries in the realm of optic nerve imaging that will ultimately change how neuro-ophthalmologists care for patients.

Retinal thickness and microvascular alterations observed by optical coherence tomography in antineutrophil cytoplasmic antibody-associated vasculitis: a cross-sectional study.

As an autoimmune disease, antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) often affects multiple organs, including the ocular system. This study aims to investigate differences in retinal thickness (RT) and retinal superficial vascular density (SVD) between patients with AAV and healthy controls (HCs) using optical coherence tomography angiography (OCTA). Currently, these differences are not clear. A total of 16 AAV individuals (32 eyes) and 16 HCs (32 eyes) were recruited to this cross-sectional study conducted in the First Affiliated Hospital of Nanchang University from June 2023 to September 2023. The study protocol conformed with the tenets of the Declaration of Helsinki (as revised in 2013). Each image observed by OCTA was divided into 9 regions using the Early Treatment Diabetic Retinopathy Study (ETDRS) subzones as a guide. In the full layer, the RT of AAV patients was found to be significantly reduced in the inner superior (IS, P<0.001), outer superior (OS, P=0.003), inner temporal (IT, P=0.003), and outer temporal (OT, P<0.001) regions; inner RT was significantly lower in the IS (P=0.006), OS (P<0.001), inner nasal (IN, P=0.005), outer nasal (ON, P<0.001), and center (C, P=0.01) regions than that in HCs. Outer RT of AAV patients showed a reduction in the IS (P<0.001), as well as IT (P=0.008), and OT (P<0.001) regions. No statistically significant differences were seen in the different subregions in other different layers (P>0.05). Only the inner inferior (II) and outer inferior (OI) regions of SVD in AAV patients did not differ significantly from controls. All other regions showed a reduction in SVD. The details are as follows: IS (P<0.001), OS (P<0.001), IT (P=0.005), OT (P<0.001), IN (P<0.001), ON (P<0.001), and C (P=0.003). According to receiver operating characteristic (ROC) curve analysis, the full IS region [area under the curve (AUC): 0.8892, 95% confidence interval (CI): 0.8041-0.9742, P<0.001] had the highest diagnostic value for AAV-induced reduction in RT. The IS (AUC: 0.9121, 95% CI: 0.8322-0.9920, P<0.001) region was also the most sensitive to changes in SVD of AAV individuals. In addition, we found that SVD in the IN region (r=-0.4224, 95% CI: -0.6779 to -0.0757, P=0.02) as well as mean visual acuity (r=-0.3922, 95% CI: -0.6579 to -0.0397, P=0.03) of AAV patients were negatively correlated with disease duration. However, we did not find an association between SVD and RT in this study. The findings from OCTA indicated a reduction in RT and SVD among patients with AAV. OCTA allows for the evaluation of AAV-related ocular lesions and holds promise for monitoring of disease progression through regular evaluations.

Biotechnology in rheumatology and immunology for researchers: An overview

Biotechnology has revolutionized the fields of rheumatology and immunology, providing innovative solutions for understanding and treating autoimmune diseases. Traditionally, these fields relied on basic immunological techniques and limited therapeutic options. However, advancements in biotechnology have introduced novel diagnostic tools, targeted therapies, and personalized medicine approaches, significantly improving patient outcomes. The aim of this overview is to provide researchers with a comprehensive understanding of the current biotechnological advancements in rheumatology and immunology, highlighting their impact on disease diagnosis, management, and treatment. The primary objective is to explore the various biotechnological innovations that have transformed rheumatology and immunology. This includes the development of biologics, biomarkers, and genetic tools that have enabled precise diagnosis and tailored treatments. Additionally, the overview seeks to examine the ongoing research and future directions in these fields, emphasizing the potential for further breakthroughs. Biotechnology has significantly advanced the fields of rheumatology and immunology, offering new hope for patients with autoimmune diseases. The introduction of biologics has been a game-changer, allowing for targeted therapies that have improved disease management and patient quality of life. Biomarker discovery has enhanced diagnostic accuracy and enabled the monitoring of disease progression. Genetic and genomic tools have paved the way for personalized medicine, tailoring treatments to individual patient profiles. As research continues to evolve, the integration of biotechnology in these fields promises to bring even more innovative solutions, ultimately transforming the landscape of autoimmune disease treatment and management. Researchers must stay abreast of these developments to continue driving progress and improving patient outcomes.

Optimizing management of chronic pulmonary hypertension in preterm infants: strategies for a complex population.

Pulmonary hypertension (PH) is commonly observed in premature infants with bronchopulmonary dysplasia (BPD) and is associated with poor outcomes and increased mortality. This review explores the management of this intricate condition of the pulmonary vasculature, which exhibits heterogeneous effects and may involve both arterial and postcapillary components. Current management of BPD-PH should focus on optimizing ventilatory support, which involves treatment of underlying lung disease, transitioning to a chronic phase ventilation strategy and evaluation of the airway. Data on management is limited to observational studies. Diuretics are considered a part of the initial management, particularly in infants with right ventricular dilation. In many cases, pulmonary vasodilator therapy is required to induce pulmonary arterial vasodilation, reduce right ventricular strain, and prevent coronary ischemia and heart failure. Echocardiography plays a pivotal role in guiding treatment decisions and monitoring disease progression. BPD-PH confers a heightened risk of mortality and long-term cardio-respiratory adverse outcomes. Echocardiography has been advocated for screening, while catheterization allows for confirmation in select more complex cases. Successful management of BPD-PH requires a multidisciplinary approach, focusing on optimizing BPD treatment and addressing underlying pathologies.

Multimodal Speech Biomarkers for Remote Monitoring of ALS Disease Progression.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that severely impacts affected persons' speech and motor functions, yet early detection and tracking of disease progression remain challenging. The current gold standard for monitoring ALS progression, the ALS functional rating scale - revised (ALSFRS-R), is based on subjective ratings of symptom severity, and may not capture subtle but clinically meaningful changes due to a lack of granularity. Multimodal speech measures which can be automatically collected from patients in a remote fashion allow us to bridge this gap because they are continuous-valued and therefore, potentially more granular at capturing disease progression. Here we investigate the responsiveness and sensitivity of multimodal speech measures in persons with ALS (pALS) collected via a remote patient monitoring platform in an effort to quantify how long it takes to detect a clinically-meaningful change associated with disease progression. We recorded audio and video from 278 participants and automatically extracted multimodal speech biomarkers (acoustic, orofacial, linguistic) from the data. We find that the timing alignment of pALS speech relative to a canonical elicitation of the same prompt and the number of words used to describe a picture are the most responsive measures at detecting such change in both pALS with bulbar (n = 36) and non-bulbar onset (n = 107). Interestingly, the responsiveness of these measures is stable even at small sample sizes. We further found that certain speech measures are sensitive enough to track bulbar decline even when there is no patient-reported clinical change, i.e. the ALSFRS-R speech score remains unchanged at 3 out of a total possible score of 4. The findings of this study have the potential to facilitate improved, accelerated and cost-effective clinical trials and care.

Pulmonary function test-related prognostic models in non-small cell lung cancer patients receiving neoadjuvant chemoimmunotherapy.

This study aimed to establish a comprehensive clinical prognostic risk model based on pulmonary function tests. This model was intended to guide the evaluation and predictive management of patients with resectable stage I-III non-small cell lung cancer (NSCLC) receiving neoadjuvant chemoimmunotherapy. Clinical pathological characteristics and prognostic survival data for 175 patients were collected. Univariate and multivariate Cox regression analyses, and least absolute shrinkage and selection operator (LASSO) regression analysis were employed to identify variables and construct corresponding models. These variables were integrated to develop a ridge regression model. The models' discrimination and calibration were evaluated, and the optimal model was chosen following internal validation. Comparative analyses between the risk scores or groups of the optimal model and clinical factors were conducted to explore the potential clinical application value. Univariate regression analysis identified smoking, complete pathologic response (CPR), and major pathologic response (MPR) as protective factors. Conversely, T staging, D-dimer/white blood cell ratio (DWBCR), D-dimer/fibrinogen ratio (DFR), and D-dimer/minute ventilation volume actual ratio (DMVAR) emerged as risk factors. Evaluation of the models confirmed their capability to accurately predict patient prognosis, exhibiting ideal discrimination and calibration, with the ridge regression model being optimal. Survival analysis demonstrated that the disease-free survival (DFS) in the high-risk group (HRG) was significantly shorter than in the low-risk group (LRG) (P=2.57×10-13). The time-dependent receiver operating characteristic (ROC) curve indicated that the area under the curve (AUC) values at 1 year, 2 years, and 3 years were 0.74, 0.81, and 0.79, respectively. Clinical correlation analysis revealed that men with lung squamous cell carcinoma or comorbid chronic obstructive pulmonary disease (COPD) were predominantly in the LRG, suggesting a better prognosis and potentially identifying a beneficiary population for this treatment combination. The prognostic model developed in this study effectively predicts the prognosis of patients with NSCLC receiving neoadjuvant chemoimmunotherapy. It offers valuable predictive insights for clinicians, aiding in developing treatment plans and monitoring disease progression.