Sentinel lymph node biopsy versus observation in high-risk cutaneous squamous cell carcinoma in immunosuppressed and immunocompetent patients: An inverse probability of treatment weighting study.

BACKGROUND: The survival benefit of sentinel lymph node biopsy (SLNB) in immunocompetent and immunosuppressed patients with high-risk cutaneous squamous cell carcinoma (cSCC) has not been established. OBJECTIVE: To determine whether SLNB improves disease-specific survival (DSS) in high-risk cSCC. Secondary objectives were to analyse disease-free survival, nodal recurrence-free survival and overall survival (OS). METHODS: Multicentre, retrospective, observational cohort study comparing survival outcomes in immunosuppressed and immunocompetent patients treated with SLNB or watchful waiting. Inverse probability of treatment weighting was used to adjust for possible confounding effects. RESULTS: We studied 638 tumours in immunocompetent patients (SLNB n = 42, observation n = 596) and 173 tumours in immunosuppressed patients (SLNB n = 28, observation n = 145). Overall, SLNB was positive in 15.7% of tumours. SLNB was associated with a reduced risk of nodal recurrence (NR) (hazard ratio [HR], 0.05 [95% CI, 0.01-0.43]; p = 0.006), disease specific mortality (HR, 0.17 [95% CI, 0.04-0.72]; p = 0.016) and all-cause mortality (HR, 0.33 [95% CI, 0.15-0.71]; p = 0.004) only in immunocompetent patients. CONCLUSIONS: SLNB was associated with improvements in NR, DSS and OS in immunocompetent but not in immunosuppressed patients with high-risk cSCC.

Identification of novel biomarkers in the early diagnosis of malignant melanoma by untargeted liquid chromatography coupled to high-resolution mass spectrometry-based metabolomics: a pilot study.

BACKGROUND: Malignant melanoma (MM) is a highly aggressive form of skin cancer whose incidence continues to rise worldwide. If diagnosed at an early stage, it has an excellent prognosis, but mortality increases significantly at advanced stages after distant spread. Unfortunately, early detection of aggressive melanoma remains a challenge. OBJECTIVES: To identify novel blood-circulating biomarkers that may be useful in the diagnosis of MM to guide patient counselling and appropriate disease management. METHODS: In this study, 105 serum samples from 26 healthy patients and 79 with MM were analysed using an untargeted approach by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to compare the metabolomic profiles of both conditions. Resulting data were subjected to both univariate and multivariate statistical analysis to select robust biomarkers. The classification model obtained from this analysis was further validated with an independent cohort of 12 patients with stage I MM. RESULTS: We successfully identified several lipidic metabolites differentially expressed in patients with stage I MM vs. healthy controls. Three of these metabolites were used to develop a classification model, which exhibited exceptional precision (0.92) and accuracy (0.94) when validated on an independent sample. CONCLUSIONS: These results demonstrate that metabolomics using LC-HRMS is a powerful tool to identify and quantify metabolites in bodily fluids that could serve as potential early diagnostic markers for MM.

Melanoma is a type of skin cancer that can be deadly if it is not detected at an early stage. Unfortunately, the early detection of melanoma is challenging. Our team has developed a model that could be used to predict whether a person has stage I malignant melanoma based on blood serum analysis. The model was trained on data from a group of people with melanoma and it was found to be accurate in predicting melanoma at an early stage. This means that the model could be used to identify people who have skin cancer before it progresses and becomes more complicated to treat. Although the researchers recommend that further studies are conducted to validate the model in a larger population of people, this research could help with the early diagnosis of melanoma and work toward improving survival rates.

Multicenter Retrospective Andalusian Study of the Use of Sonidegib for the Treatment of Local Advanced Basal Cell Carcinoma in Real Clinical Practice.

INTRODUCTION: Locally advanced basal cell carcinoma (LA-BCC) is defined as that BCC in which there is radiological confirmation of invasion of certain neighboring structures in depth and also, usually, a BCC that is of a sufficient size and invasion (although there is no radiological demonstration of deep invasion) in which surgery and radiotherapy are not adequate, are insufficient or are contraindicated to achieve the cure of the tumor, either due to characteristics of the tumor itself or of the patient. Sonidegib is indicated for the treatment of adult patients with locally advanced basal cell carcinoma that is not amenable to curative surgery or radiotherapy. MATERIAL AND METHODS: This is a retrospective, multicenter and descriptive study in nine centers in Andalusia, Spain. Patients treated with sonidegib for >3 months for locally advanced BCC were included from 1 January 2021 to 1 January 2023. Epidemiological, efficacy and safety data were collected. RESULTS: In the present study, a total of 38 patients were included, with a median age of 76.23 years (range 40-101). Prior treatment was surgery (31.57%; n = 25), radiotherapy (15.78%; n = 6), vismodegib (31.57%; n = 12). Eleven patients had not received prior treatment. LA-BCC were located in the cephalic pole, face or scalp. There was a total response in 9/38 patients (23.7%), partial response in 25/38 patients (65.8%) and no response in 4 patients (10.52%). In 6/34 patients, the dose was reduced to 200 mg every other day until it was discontinued due to adverse effects. The main adverse effects reported were dysgeusia (n = 8), asthenia (n = 8), = 6), muscle spasms (n = 6), alopecia (n = 4) and gastrointestinal intolerance (n = 4). DISCUSSION: Sonidegib is the second iHh authorized for the treatment of adult patients with locally advanced BCC who are not amenable to curative surgery or radiotherapy, based on the results of the phase II clinical trial, BOLT. Sonidegib shows good effectiveness and an acceptable safety profile in routine clinical practice in the sample presented.

Effects of COVID-19 Lockdown on Tumour Burden of Melanoma and Cutaneous Squamous Cell Carcinoma.

The aim of this study was to compare tumour burden in patients who underwent surgery for melanoma and cutaneous squamous cell carcinoma during nationwide lockdown in Spain due to COVID-19 (for the period 14 March to 13 June 2020) and during the same dates in 2019 before the COVID-19 pandemic. In addition, associations between median tumour burden (Breslow thickness for melanoma and maximum clinical diameter for cutaneous squamous cell carcinoma) and demographic, clinical, and medical factors were analysed, building a multivariate linear regression model. During the 3 months of lockdown, there was a significant decrease in skin tumours operated on (41% decrease for melanoma (n = 352 vs n = 207) and 44% decrease for cutaneous squamous cell carcinoma (n = 770 vs n = 429)) compared with the previous year. The proportion of large skin tumours operated on increased. Fear of SARS-CoV-2 infection, with respect to family member/close contact, and detection of the lesion by the patient or doctor, were related to thicker melanomas; and fear of being diagnosed with cancer, and detection of the lesion by the patient or relatives, were related to larger size cutaneous squamous cell carcinoma. In conclusion, lockdown due to COVID-19 has resulted in a reduction in treatment of skin cancer.

Metabolomic profile of cancer stem cell-derived exosomes from patients with malignant melanoma.

Malignant melanoma (MM) is the most aggressive and life-threatening form of skin cancer. It is characterized by an extraordinary metastasis capacity and chemotherapy resistance, mainly due to melanoma cancer stem cells (CSCs). To date, there are no suitable clinical diagnostic, prognostic or predictive biomarkers for this neoplasia. Therefore, there is an urgent need for new MM biomarkers that enable early diagnosis and effective disease monitoring. Exosomes represent a novel source of biomarkers since they can be easily isolated from different body fluids. In this work, a primary patient-derived MM cell line enriched in CSCs was characterized by assessing the expression of specific markers and their stem-like properties. Exosomes derived from CSCs and serums from patients with MM were characterized, and their metabolomic profile was analysed by high-resolution mass spectrometry (HRMS) following an untargeted approach and applying univariate and multivariate statistical analyses. The aim of this study was to search potential biomarkers for the diagnosis of this disease. Our results showed significant metabolomic differences in exosomes derived from MM CSCs compared with those from differentiated tumour cells and also in serum-derived exosomes from patients with MM compared to those from healthy controls. Interestingly, we identified similarities between structural lipids differentially expressed in CSC-derived exosomes and those derived from patients with MM such as the glycerophosphocholine PC 16:0/0:0. To our knowledge, this is the first metabolomic-based study aimed at characterizing exosomes derived from melanoma CSCs and patients' serum in order to identify potential biomarkers for MM diagnosis. We conclude that metabolomic characterization of CSC-derived exosomes sets an open door to the discovery of clinically useful biomarkers in this neoplasia.

Trichomycosis axillaris dermoscopy.

Trichomycosis axillaris is a common but underdiagnosed condition of the skin. The dermoscopic image of this disease is not previously described in the scientific literature. We believe that dermoscopy is a convenient and interesting diagnostic method that may aid in the diagnosis.

Fibrilación auricular paroxística en el contexto de cefalea en racimos / Paroxysmal atrial fibrillation within the context of cluster headaches

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Mathematical analysis of recent analytical approximations to the collapse of an empty spherical bubble.

We analyze the Rayleigh equation for the collapse of an empty bubble and provide an explanation for some recent analytical approximations to the model. We derive the form of the singularity at the second boundary point and discuss the convergence of the approximants. We also give a rigorous proof of the asymptotic behavior of the coefficients of the power series that are the basis for the approximate expressions.

A comparative QSAR on 1,2,5-thiadiazolidin-3-one 1,1-dioxide compounds as selective inhibitors of human serine proteinases.

Selective inhibitors of target serine proteinases have a potential therapeutic role for the treatment of various inflammatory and related diseases. We develop a comparative quantitative structure-activity relationships based analysis on compounds embodying the 1,2,5-thiadiazolidin-3-one 1,1-dioxide scaffold. By means of classical Molecular Dynamics we obtain the conformation of each lowest-energy molecular structure from which we derive more than a thousand of structural descriptors necessary for building predictive QSAR models. We resort to two different modeling approaches with the purpose of testing the consistency of our results: (a) multivariable linear regressions based on the replacement method and forward stepwise regression, and (b) the calculation of flexible descriptors with the CORAL program. All the models are properly validated by means of standard procedures. The resulting QSAR models are supposed to be of great utility for the rational search and design (including synthesis and/or in vitro biochemical studies) of new effective non-peptidyl inhibitors of serine proteinases.

Advances in the replacement and enhanced replacement method in QSAR and QSPR theories.

The selection of an optimal set of molecular descriptors from a much greater pool of such regression variables is a crucial step in the development of QSAR and QSPR models. The aim of this work is to further improve this important selection process. For this reason three different alternatives for the initial steps of our recently developed enhanced replacement method (ERM) and replacement method (RM) are proposed. These approaches had previously proven to yield near optimal results with a much smaller number of linear regressions than the full search. The algorithms were tested on four different experimental data sets, formed by collections of 116, 200, 78, and 100 experimental records from different compounds and 1268, 1338, 1187, and 1306 molecular descriptors, respectively. The comparisons showed that one of the new alternatives further improves the ERM, which has shown to be superior to genetic algorithms for the selection of an optimal set of molecular descriptors from a much greater pool. The new proposed alternative also improves the simpler and the lower computational demand algorithm RM.

Predictive QSPR study of the dissociation constants of diverse pharmaceutical compounds.

The objective of the article was to perform a predictive analysis, based on quantitative structure-property relationships, of the dissociation constants (pK(a)) of different medicinal compounds (e.g., salicylic acid, salbutamol, lidocaine). Given the importance of this property in medicinal chemistry, it is of interest to develop theoretical methods for its prediction. The descriptors selection from a pool containing more than a thousand geometrical, topological, quantum-mechanical, and electronic types of descriptors was performed using the enhanced replacement method. Genetic algorithm and the replacement method (RM) techniques were used as reference points. A new methodology for the selection of the optimal number of descriptors to include in a model was presented and successfully used, showing that the best model should contain four descriptors. The best quantitative structure-property relationships linear model constructed using 62 molecular structures not previously used in this type of quantitative structure-property study showed good predictive attributes. The root mean squared error of the 26 molecules test set was 0.5600. The analysis of the quantitative structure-property relationships model suggests that the dissociation constants depend significantly on the number of acceptor atoms for H-bonds and on the number of carboxylic acids present in the molecules.

Replacement method and enhanced replacement method versus the genetic algorithm approach for the selection of molecular descriptors in QSPR/QSAR theories.

We compare three methods for the selection of optimal subsets of molecular descriptors from a much greater pool of such regression variables. On the one hand is our enhanced replacement method (ERM) and on the other is the simpler replacement method (RM) and the genetic algorithm (GA). These methods avoid the impracticable full search for optimal variables in large sets of molecular descriptors. Present results for 10 different experimental databases suggest that the ERM is clearly preferable to the GA that is slightly better than the RM. However, the latter approach requires the smallest amount of linear regressions and, consequently, the lowest computation time.

A perturbative view of protein structural variation.

It was recently found that the lowest-energy collective normal modes dominate the evolutionary divergence of protein structures. This was attributed to a presumed functional importance of such motions, i.e., to natural selection. In contrast to this selectionist explanation, we proposed that the observed behavior could be just the expected physical response of proteins to random mutations. This proposal was based on the success of a linearly forced elastic network model (LFENM) of mutational effects on structure to account for the observed pattern of structural divergence. Here, to further test the mutational explanation and the LFENM, we analyze the structural differences observed not only in homologous (globin-like) proteins but also in unselected experimentally engineered myoglobin mutants and in wild-type variants subject to other perturbations such as ligand-binding and pH changes. We show that the lowest normal modes dominate structural change in all the cases considered and that the LFENM reproduces this behavior quantitatively. The collective nature of the lowest normal modes results in global conformational changes that depend little on the exact nature or location of the perturbation. Significantly, the evolutionarily conserved structural core matches the regions observed to be more robust with respect to mutations, so that the core would be more conserved even under unselected random mutations. In a word, the observed patterns of structural variation can be seen as the natural response of proteins to perturbations and can be adequately modeled using the LFENM, which serves as a common framework to relate a priori different phenomena.

New hybrid genetic based Support Vector Regression as QSAR approach for analyzing flavonoids-GABA(A) complexes.

Several studies were conducted in past years which used the evolutionary process of Genetic Algorithms for optimizing the Support Vector Regression parameter values although, however, few of them were devoted to the simultaneously optimization of the type of kernel function involved in the established model. The present work introduces a new hybrid genetic-based Support Vector Regression approach, whose statistical quality and predictive capability is afterward analyzed and compared to other standard chemometric techniques, such as Partial Least Squares, Back-Propagation Artificial Neural Networks, and Support Vector Machines based on Cross-Validation. For this purpose, we employ a data set of experimentally determined binding affinity constants toward the benzodiazepine binding site of the GABA (A) receptor complex on 78 flavonoid ligands.

On nonadiabatic calculation of dipole moments.

We show that a recent non-Born-Oppenheimer calculation of dipole moments exhibits obscure points and is not consistent with the well known Hellmann-Feynman theorem.