Revista De Investigacion Clinica-Clinical and Translational Investigation最新文献

Unassigned: Background: Smoking remains a significant issue that increases the prevalence of multiple sclerosis (MS) and its progression to secondary progressive forms. Objectives: The goal is to identify the relationship between smoking and disease progression in MS patients who have undergone autologous hematopoietic stem cell transplantation (auto-HSCT) at the Centro de Hematología y Medicina Interna, Clínica Ruiz, Puebla, Mexico. Methods: This retrospective study involved MS patients treated with auto-HSCT, followed for 12 months. The response to transplantation was measured using the difference in Expanded Disability Status Scale (EDSS) scores before and 12 months after the transplant. A difference of -0.5 or greater indicated a good response, while a difference below 0.5 indicated a poor response. Results: The study included 419 patients, with a median age of 47 years (IQR: 40-53). The majority were non-smokers (315) compared to smokers/ex-smokers (104). In patients with PMSS, EDSS stabilization at 12 months was observed in both smokers/ex-smokers (median 6, interquartile range (IQR) = 1 vs. 6, IQR = 1, p = 0.466) and non-smokers (median 6, IQR = 1 vs. 6, IQR = 1.5, p = 0.001), although non-smokers showed a statistically significant difference. Conclusion: Smoking may negatively impact MS progression, especially in its progressive forms. (Rev Invest Clin. 2024;76(5):223-9).

Background: Osteoarthritis is a frequent rheumatic disease. Some single-nucleotide polymorphisms of the gene associated with fat mass and obesity are associated with increased body mass index and knee osteoarthritis.

Objective: The objective of this study was to analyze the association of single nucleotide polymorphism rs1477196 of the fat mass and obesity gene with primary knee osteoarthritis.

Methods: This observational and cross-sectional study included 347 Mexican participants. We performed the genotypification analysis with TaqMan® probe C_2031262_10 for rs1477196 (Thermo Fisher Scientific). Multivariate analysis included covariables such as age, type 2 diabetes, obesity, and postmenopause.

Results: Type 2 diabetes, obesity, and postmenopause were associated with primary knee osteoarthritis in female participants. We did not find an association between rs1477196 and obesity. In the codominant and dominant genetic models, rs1477196 was significantly associated with primary knee osteoarthritis only in the female group, including in the model adjusted by other covariables (odds ratio = 2.517; 1.035-6.123; p = 0.042 and odds ratio = 2.387; 1.054-5.407; p = 0.037, respectively). The interaction between rs1477196 and obesity was significantly associated with primary knee osteoarthritis in female participants (p = 0.039 and p = 0.043).

Conclusions: Our findings suggest that the rs1477196 variant of the fat and obesity mass gene may be associated with the risk of primary knee osteoarthritis in women.

Unassigned: Background: Clinical practice has advanced toward a combined diagnostic approach that involves clinical criteria and biological markers for Alzheimer's disease (AD) and other dementias. Objective: To establish the level of diagnostic agreement between an initial clinical diagnosis and cerebrospinal fluid (CSF) and [18F]-fluorodeoxyglucose (FDG)-positron emission tomography (PET) biomarkers in a cohort of patients from a memory clinic. Methods: This is a observational, retrospective, cohort study conducted at an outpatient memory clinic. Between July 2018 and September 2023, data from adults' ≥ 55 years with a mild cognitive impairment or dementia diagnosis without etiological diagnosis were obtained, complemented with the evaluation of biomarkers in CSF and [18F] FDG-PET biomarker assessment were included. Kappa coefficients (κ) were used to establish the level of agreement between CSF and [18F] FDG-PET results. Results: Seventy-seven patients had an available [18F] FDG-PET scan, and 25 (32.5%) had both biomarkers. We observed a fair-to-moderate diagnostic agreement between patients' initial and their final diagnosis in the presence of CSF (κ = 0.233, 95% confidence interval [CI]: -0.099-0.566) and [18F] FDG-PET (κ = 0.451, 95% CI: 0.277-0.625, p < 0.001) results. The Kappa value for diagnostic concordance between [18F] FDG-PET and CSF to differentiate between AD and other dementias was 0.733 (95% CI: 0.425-1.000, p < 0.005). Conclusion: This study demonstrates good agreement between the CSF and FDG-PET biomarkers to differentiate AD from other dementias. (Rev Invest Clin. 2024;76(5):230-7).

Unassigned: Background: Since to the prognosis of lung squamous cell carcinoma is generally poor, there is an urgent need to innovate new prognostic biomarkers and therapeutic targets to improve patient outcomes. Objectives: Our goal was to develop a novel multi-gene prognostic model linked to neutrophils for predicting lung squamous cell carcinoma prognosis. Methods: We utilized messenger RNA expression profiles and relevant clinical data of lung squamous cell carcinoma patients from the Cancer Genome Atlas database. Through K-means clustering, least absolute shrinkage and selection operator regression, and univariate/multivariate Cox regression analyses, we identified 12 neutrophil-related genes strongly related to patient survival and constructed a prognostic model. We verified the stability of the model in the Cancer Genome Atlas database and gene expression omnibus validation set, demonstrating the robust predictive performance of the model. Results: Immunoinfiltration analysis revealed remarkably elevated levels of infiltration for natural killer cells resting and monocytes in the high-risk group compared to the low-risk group, while macrophages had considerably lower infiltration in the high risk group. Most immune checkpoint genes, including programmed cell death protein 1 and cytotoxic T-lymphocyte-associated antigen 4, exhibited high expression levels in the high risk group. Tumor immune dysfunction and exclusion scores and immunophenoscore results suggested a potential inclination toward immunotherapy in the "RIC" version V2 revised high risk group. Moreover, prediction results from the CellMiner database revealed great correlations between drug sensitivity (e.g., Vinorelbine and PKI-587) and prognostic genes. Conclusion: Overall, our study established a reliable prognostic risk model that possessed significant value in predicting the overall survival of lung squamous cell carcinoma patients and may guide personalized treatment strategies. (Rev Invest Clin. 2024;76(2):116-31).

Background: Human immunodeficiency virus (HIV) drug resistance is a major cause of treatment failure in children and adolescents infected with the virus.

Objectives: The objectives of the study are to investigate HIV drug resistance (HIVDR) in patients who attended a referral care center in Argentina over a 15-year period and to compare mutational patterns between HIV-1 polsequences characterized as B or BF recombinants.

Methods: Individual resistance-associated mutations (RAMs) (to protease and reverse transcriptase inhibitors) were identified according to IAS-USA guidelines in 374 HIV-1-infected children and adolescents. HIV-1 subtype was characterized by phylogenetic and recombination analysis using MEGA5.1 and Simplot. Poisson linear regression was used to model the dynamics of the RAMs over time.

Results: The prevalence of RAMs to protease inhibitors (R2 = 0.52, p = 0.0012) and nucleoside reverse transcriptase inhibitors (R2 = 0.30, p = 0.0225) decreased over time. HIVDR to non-nucleoside reverse transcriptase inhibitors remained moderate to high, ranging between 33% and 76%. BF recombinants showed a higher frequency of thymidine analog mutation 1 RAMs profile and I54V mutation.

Conclusion: In Argentina, HIVDR observed in children and adolescents has decreased over the past 15 years, regardless of the viral subtype. (REV INVEST CLIN. 2024;76(1):29-36).

Background: Triple-negative breast cancer (TNBC) is a subtype of breast cancer (BC) that lacks receptors for targeted therapy. Deeper insight into the molecular mechanisms regulating TNBC metastasis is urgently needed. The epithelial-mesenchymal transition process facilitates the metastasis of neighboring epithelial tumor cells. Protein kinase, membrane-associated tyrosine/threonine 1 (PKMYT1), a member of the Wee family of protein kinases, is upregulated in BC, and its high expression predicts poor prognosis in BC patients. Notch signaling activation is a pathognomonic feature of TNBC. PKMYT1 has been found to induce EMT in non-small cell lung cancer by activating Notch signaling. However, whether PKMYT1 exerts effects on TNBC progression by regulating Notch signaling remains unknown.

Objectives: The objective of this study was to investigate whether PKMYT1 exerts effects on TNBC progression by regulating Notch signaling.

Methods: Fifty cases of surgically resected BC samples (tumor and adjacent non-tumor tissue samples) were collected from patients diagnosed with BC. We measured the expression of PKMYT1 in clinical samples with real-time quantitative polymerase chain reaction (RT-qPCR). For in vitro analysis, RT-qPCR and Western blotting were conducted to evaluate PKMYT1 expression in TNBC cells. Then, the viability, migration, and invasion of TNBC cells were detected by cell counting kit-8 assays, wound healing assays, and Transwell assays. The EMT event was examined by evaluating the levels of EMT-associated proteins. For in vivo analysis, xenograft models in nude mice were established to explore PKMYT1 roles. E-cadherin and Ki67 expression in xenograft models were estimated by immunohistochemistry staining. Hematoxylin and eosin staining was performed to assess tumor metastasis. The underlying mechanisms by which PKMYT1 affected the malignant phenotypes of TNBC cells were explored by Western blotting measuring the pathway-associated proteins.

Results: PKMYT1 was upregulated in BC tissues and cells, and its knockdown prevented cell proliferation, migration, invasion, and EMT event in TNBC. Mechanistically, Notch signaling was inactivated by PKMYT1 depletion, and Notch activation abolished the PKMYT1 silencing-induced inhibition in the malignant phenotypes of TNBC cells. For in vivo analysis, PKMYT1 knockdown inhibited tumorigenesis and metastasis of TNBC.

Conclusion: PKMYT1 promotes EMT, proliferation, migration, and invasion of TNBC cells and facilitates tumor growth and metastasis by activating Notch signaling.

The development of hemodialysis (HD) membranes has substantially advanced in the last decade. This has resulted in the manufacturing of medium cut-off membranes (MCO) whose internal architecture is based on greater pore size and a smaller diameter, thus promoting the clearance of particles of greater size as well as retrofiltration. Multiple studies have proven their efficacy in the clearance of uremic mid-sized molecules such as β2-microglobulin, free light chains, and some interleukins; this clearance is far superior with MCO membranes when compared with high-flux HD, and similar to that obtained with online hemodiafiltration. This review summarizes the results of the most relevant clinical studies of this membrane in terms of uremic toxin clearance, as well as the features of some clinical outcomes such as quality of life and hospitalizations.

Membranes and sorbents play a crucial role in extracorporeal blood purification therapies, which aim to remove harmful molecules and toxins from the blood. Over the years, advancements in hemodialysis (HD) membranes and sorbents have significantly enhanced their safety and effectiveness. This review article will summarize the latest breakthroughs in the development and clinical application of HD membranes and sorbents. We will commence with a concise examination of the mechanisms involved in solute transport across membranes and sorbents. Subsequently, we will explore the evolutionary path of HD membranes, from early cellophane membranes to high-flux membranes, including the development of high-cutoff membranes and the emergence of medium- cutoff membranes. We will discuss each type of HD membrane's advantages and limitations, highlighting the most promising advancements in novel biomaterials and biocompatibility, technologies, research in membrane performance, and their clinical applications. Furthermore, we will delve into the evolution and progress of sorbent technology, tracing its historical development, outlining its key characteristics, examining the mechanism involved in the adsorption process, and exploring its clinical application. This review aims to underscore the growth and future landscape of HD membranes and sorbents in extracorporeal blood purification techniques.

Artificial intelligence (AI) generative models driven by the integration of AI and natural language processing technologies, such as OpenAI's chatbot generative pre-trained transformer large language model (LLM), are receiving much public attention and have the potential to transform personalized medicine. Dialysis patients are highly dependent on technology and their treatment generates a challenging large volume of data that has to be analyzed for knowledge extraction. We argue that, by integrating the data acquired from hemodialysis treatments with the powerful conversational capabilities of LLMs, nephrologists could personalize treatments adapted to patients' lifestyles and preferences. We also argue that this new conversational AI integrated with a personalized patient-computer interface will enhance patients' engagement and self-care by providing them with a more personalized experience. However, generative AI models require continuous and accurate updates of data, and expert supervision and must address potential biases and limitations. Dialysis patients can also benefit from other new emerging technologies such as Digital Twins with which patients' care can also be addressed from a personalized medicine perspective. In this paper, we will revise LLMs potential strengths in terms of their contribution to personalized medicine, and, in particular, their potential impact, and limitations in nephrology. Nephrologists' collaboration with AI academia and companies, to develop algorithms and models that are more transparent, understandable, and trustworthy, will be crucial for the next generation of dialysis patients. The combination of technology, patient-specific data, and AI should contribute to create a more personalized and interactive dialysis process, improving patients' quality of life.

Home hemodialysis (HD) and automated peritoneal dialysis (APD) have advantages over HD in hospitals or HD centers. Home therapies are generally less expensive and give patients greater mobility and freedom for work, school, family, and recreational activities. Technological advances have made it possible to complement APD with devices for remote monitoring (RM) of the patient. With them, objective information generated in the APD device is collected and sent to repositories "in the cloud" for analysis or at the time decided by the health team. With APD+RM, it is possible to monitor therapeutic compliance, effective dialysis time, ultrafiltration volumes, inflow and outflow patterns of dialysis fluid, and patient actions to respond to alarms that indicate deviations from the parameters set by the nephrologist. The results of APD+RM show good acceptance by the patient, nephrologists, and nurses, treatment adherence has improved, hospitalizations and technique failure have decreased, and some aspects of quality of life have improved. However, there is a lack of controlled clinical trials that reliably demonstrate lower mortality and comorbidity due to specific causes.