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Understanding and managing locally advanced basal cell carcinoma (BCC) is crucial given its substantial prevalence and potential for local tissue destruction. While BCC typically exhibits low metastatic potential, its high incidence underscores the need for enhanced therapeutic strategies. Locally advanced BCC presents unique challenges, often necessitating aggressive interventions to prevent disfigurement and functional impairment. The emergence of hedgehog pathway inhibitors (HHIs) offers promising therapeutic avenues by targeting aberrant hedgehog signaling, a key driver in BCC pathogenesis. Thus, elucidating the pathogenesis of locally advanced BCC and exploring the role of HHIs are critical endeavors in effectively managing this prevalent carcinoma. Epidemiologically, BCC primarily affects individuals with fair skin and chronic sun exposure, with an increasing incidence noted among younger age groups. Risk factors include UV radiation exposure, familial history of skin cancer, immunosuppression, and genetic syndromes such as basal cell nevus syndrome and xeroderma pigmentosum. Pathogenetically, BCC arises from cells in the skin's epidermis, with hedgehog pathway activation being a primary genetic driver, involving mutations in PTCH1 and SMO. Resistance to hedgehog inhibitors may occur due to genetic changes, complicating treatment strategies. BCC is characterized by low immunogenicity, which hinders immune response and contributes to treatment challenges. Enhanced understanding of the epidemiology, risk factors, and pathogenesis of locally advanced BCC, along with the development of targeted therapeutic approaches such as hedgehog pathway inhibitors, is essential for effectively managing this prevalent carcinoma and improving patient outcomes.

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., (© 2024 European Academy of Dermatology and Venereology.)

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.

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.

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.

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.

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., (Copyright © 2011 Elsevier Inc. All rights reserved.)

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.

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., (© 2010 John Wiley & Sons A/S.)

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.

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., ((c) 2009 Wiley-Liss, Inc.)

We constructed a predictive model of the total deactivation rate constant (k(t)) of singlet oxygen by heterocyclic compounds that are widespread in biological systems and participate in highly relevant biologic functions related with photochemical processes, by means of quantitative structure-property relationships (QSPR). The study of the reactivity of singlet oxygen with biomolecules provides their antioxidant capability, and the determination of the rate constants allows evaluation of the efficiencies of these processes. Our optimal linear model based on 41 molecular structures, which have not been used previously in a QSPR study, consists of six variables, selected from more than thousand geometrical, topological, quantum-mechanical and electronic types of molecular descriptors. Our recently developed strategy to determine the optimal number of descriptors in model is successfully applied. As a practical application of our QSPR model we estimated the unknown k(t) of several heterocyclic compounds that are of particular interest for further experimental studies in our research group.

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.

We performed a predictive analysis based on quantitative structure-activity relationships (QSAR) of an important property of flavonoids, which is the inhibition (IC(50)) of aldose reductase (AR). The importance of AR inhibition is that it prevents cataract formation in diabetic patients. The best linear model constructed from 55 molecular structures incorporated six molecular descriptors, selected from more than a thousand geometrical, topological, quantum-mechanical, and electronic types of descriptors. As a practical application, we used the obtained QSAR model to predict the AR inhibitory effect of newly synthesized flavonoids that present 2-, 7-substitutions in the benzopyrane backbone.

Hybrid density functional calculations are performed on a series of 21 new quinoxaline derivatives, which would likely exhibit important biological activities. Optimized geometries, harmonic vibrational frequencies, and (1)H chemical shifts are reported and compared with experimental data when available. In addition, melting points of 75 derivatives are predicted resorting to the Quantitative Structure-Property Relationship (QSPR) Theory, doing the variable selection by means of the Replacement Method and using 875 theoretical descriptors obtained from Dragon 5 software. The best relationship found has seven descriptors with R=0.8818 and R(l-10%-o)=0.7705.

By means of QSAR algorithms we model the potency pIC(90) [mM] of 154 non-nucleoside reverse transcriptase inhibitors (NNRTI) of the wild-type HIV-1 virus, considered as the second generation analogues of Efavirenz. In addition, 56 inhibitors of the K-103N viral mutant form are also investigated. A pool of 1494 theoretical molecular descriptors provided mainly by the Dragon 5 software is explored by several methods of variable selection: forward stepwise regression, the replacement method, and the genetic algorithm approach. The optimal models found include up to seven parameters: R = 0.7991, R(l-20%-o) = 0.7233 for the case of wild-type, and R = 0.9261, R(l-5%-o) = 0.8802 for the K-103N mutation.

In this paper we generalize and improve a method for calculating the period of a classical oscillator and other integrals of physical interest, which was recently developed by some of the authors. We derive analytical expressions that prove to be more accurate than those commonly found in the literature, and test the convergence of the series produced by the approach.