The association between clinician-based common terminology criteria for adverse events (CTCAE) and patient-reported outcomes (PRO): a systematic review

Symptomatic adverse events (AEs) are monitored by clinicians as part of all US-based clinical trials in cancer via the U.S. National Cancer Institute’s Common Terminology Criteria for Adverse Events (CTCAE) for the purposes of ensuring patient safety. Recently there has been a charge toward capturing the patient perspective for those AEs amenable to patient self-reporting via patient-reported outcomes (PRO). The aim of this review was to summarize the empirically reported association between analogous CTCAE and PRO ratings

Halogenated triazinediones behave as antagonists of PKR1: in vitro and in vivo pharmacological characterization

Different prokineticin receptor antagonists, based on the triazinedione scaffold, were synthesized by a new efficient method. Here we demonstrated that 5-benzyltriazinedionessubstituted in position para of the benzyl group with halogens provide compounds endowed with interesting selectivity for the Prokineticin receptor 1 (PKR1). BRET technology indicates that such substitutionresults in increased affinity for thePKR1.The affinity for PKR2, always in M range, was never significantly affected by the para-halogen-benzyl pharmacophores. The analog bearing a para-bromobenzyl pharmacophore (PC-25) displayed the highest affinity for PKR1 (~18 times higher than the reference PC-1 that bears apara-ethyl benzyl group) and the highest selectivity (~300 times). The other halogen substitutedanalogs (PC-7, PC-18 and PC-35), showed selectivity for PKR1 more than 100 times higher than for PKR2. Using transgenic mice lacking one of the two PKRs we demonstrated that all these compounds were able to abolish the Bv8-induced hyperalgesia in mice still expressing the PKR1 at doses lower than those necessary to abolish hyperalgesia in mice expressing only the PKR2. The dose ratio reflected the in- vitro evaluated receptor selectivity

A global review on short peptides: frontiers and perspectives

Peptides are fragments of proteins that carry out biological functions. They act as signaling entities via all domains of life and interfere with protein-protein interactions, which are indispensable in bio-processes. Short peptides include fundamental molecular information for a prelude to the symphony of life. They have aroused considerable interest due to their unique features and great promise in innovative bio-therapies. This work focusing on the current state-of-the-art short peptide-based therapeutical developments is the first global review written by researchers from all continents, as a celebration of 100 years of peptide therapeutics since the commencement of insulin therapy in the 1920s. Peptide “drugs” initially played only the role of hormone analogs to balance disorders. Nowadays, they achieve numerous biomedical tasks, can cross membranes, or reach intracellular targets. The role of peptides in bio-processes can hardly be mimicked by other chemical substances. The article is divided into independent sections, which are related to either the progress in short peptide-based theranostics or the problems posing challenge to bio-medicine. In particular, the SWOT analysis of short peptides, their relevance in therapies of diverse diseases, improvements in (bio)synthesis platforms, advanced nano-supramolecular technologies, aptamers, altered peptide ligands and in silico methodologies to overcome peptide limitations, modern smart bio-functional materials, vaccines, and drug/gene-targeted delivery systems are discussed

Evaluation of a stable Gonadotropin-Releasing Hormone analog in mice for the treatment of endocrine disorders and prostate cancer

Gonadotropin-releasing hormone (GnRH) receptor agonists have wide clinical applications including the treatment of prostate cancer and endocrine disorders. However, such agonists are characterized by poor pharmacokinetic properties, often requiring repeated administration or special formulations. Therefore, the development of novel peptide analogs with enhanced in vivo stability could potentially provide therapeutic alternatives. The pharmacological evaluation of a bioactive peptide [Des-Gly10,Tyr5(OMe),D-Leu 6,Aze-NHEt9]GnRH, analog 1, is presented herein and compared with leuprolide. Peptide stability was evaluated using mouse kidney membrane preparations, followed by a liquid chromatography-tandem mass spectrometry-based approach that afforded identification and quantification of its major metabolites. The analog was significantly more stable in vitro in comparison with leuprolide. In vitro and in vivo stability results correlated well, encouraging us to develop a clinically relevant pharmacokinetic mouse model, which facilitated efficacy measurements using testosterone as a biomarker. Analog 1, an agonist of the GnRH receptor with a binding affinity in the nanomolar range, caused testosterone release in mice that was acutely dose-dependent, an effect blocked by the GnRH receptor antagonist cetrorelix. Repeated dosing studies in mice demonstrated that analog 1 was well tolerated and had potency similar to that of leuprolide, based on plasma and testis testosterone reduction and histopathological findings. Analog 1 also shared with leuprolide similar significant antiproliferative activity on androgen-dependent prostate cancer (LNCaP) cells. On the basis of pharmacokinetic advantages, we expect that analog 1 or analogs based on this new design will be therapeutically advantageous for the treatment of cancer and endocrine disorders. Copyrigh

Effect of nonstationarities on detrended fluctuation analysis

Detrended fluctuation analysis (DFA) is a scaling analysis method used to quantify long-range power-law correlations in signals. Many physical and biological signals are ``noisy'', heterogeneous and exhibit different types of nonstationarities, which can affect the correlation properties of these signals. We systematically study the effects of three types of nonstationarities often encountered in real data. Specifically, we consider nonstationary sequences formed in three ways: (i) stitching together segments of data obtained from discontinuous experimental recordings, or removing some noisy and unreliable parts from continuous recordings and stitching together the remaining parts -- a ``cutting'' procedure commonly used in preparing data prior to signal analysis; (ii) adding to a signal with known correlations a tunable concentration of random outliers or spikes with different amplitude, and (iii) generating a signal comprised of segments with different properties -- e.g. different standard deviations or different correlation exponents. We compare the difference between the scaling results obtained for stationary correlated signals and correlated signals with these three types of nonstationarities.Comment: 17 pages, 10 figures, corrected some typos, added one referenc

Effect of Trends on Detrended Fluctuation Analysis

Detrended fluctuation analysis (DFA) is a scaling analysis method used to estimate long-range power-law correlation exponents in noisy signals. Many noisy signals in real systems display trends, so that the scaling results obtained from the DFA method become difficult to analyze. We systematically study the effects of three types of trends -- linear, periodic, and power-law trends, and offer examples where these trends are likely to occur in real data. We compare the difference between the scaling results for artificially generated correlated noise and correlated noise with a trend, and study how trends lead to the appearance of crossovers in the scaling behavior. We find that crossovers result from the competition between the scaling of the noise and the ``apparent'' scaling of the trend. We study how the characteristics of these crossovers depend on (i) the slope of the linear trend; (ii) the amplitude and period of the periodic trend; (iii) the amplitude and power of the power-law trend and (iv) the length as well as the correlation properties of the noise. Surprisingly, we find that the crossovers in the scaling of noisy signals with trends also follow scaling laws -- i.e. long-range power-law dependence of the position of the crossover on the parameters of the trends. We show that the DFA result of noise with a trend can be exactly determined by the superposition of the separate results of the DFA on the noise and on the trend, assuming that the noise and the trend are not correlated. If this superposition rule is not followed, this is an indication that the noise and the superimposed trend are not independent, so that removing the trend could lead to changes in the correlation properties of the noise.Comment: 20 pages, 16 figure

Discovery of a new generation of angiotensin receptor blocking drugs:Receptor mechanisms and in silico binding to enzymes relevant to SARS-CoV-2

The discovery and facile synthesis of a new class of sartan-like arterial antihypertensive drugs (angiotensin receptor blockers [ARBs]), subsequently referred to as “bisartans” is reported. In vivo results and complementary molecular modelling presented in this communication indicate bisartans may be beneficial for the treatment of not only heart disease, diabetes, renal dysfunction, and related illnesses, but possibly COVID-19. Bisartans are novel bis-alkylated imidazole sartan derivatives bearing dual symmetric anionic biphenyl tetrazole moieties. In silico docking and molecular dynamics studies revealed bisartans exhibited higher binding affinities for the ACE2/spike protein complex (PDB 6LZG) compared to all other known sartans. They also underwent stable docking to the Zn2+ domain of the ACE2 catalytic site as well as the critical interfacial region between ACE2 and the SARS-CoV-2 receptor binding domain. Additionally, semi-stable docking of bisartans at the arginine-rich furin-cleavage site of the SARS-CoV-2 spike protein (residues 681–686) required for virus entry into host cells, suggest bisartans may inhibit furin action thereby retarding viral entry into host cells. Bisartan tetrazole groups surpass nitrile, the pharmacophoric “warhead” of PF-07321332, in its ability to disrupt the cysteine charge relay system of 3CLpro. However, despite the apparent targeting of multifunctional sites, bisartans do not inhibit SARS-CoV-2 infection in bioassays as effectively as PF-07321332 (Paxlovid)

Influence of the initial chemical conditions on the rational design of silica particles

The influence of the water content in the initial composition on the size of silica particles produced using the Stöber process is well known. We have shown that there are three morphological regimes defined by compositional boundaries. At low water levels (below stoichiometric ratio of water:tetraethoxysilane), very high surface area and aggregated structures are formed; at high water content (>40 wt%) similar structures are also seen. Between these two boundary conditions, discrete particles are formed whose size are dictated by the water content. Within the compositional regime that enables the classical Stöber silica, the structural evolution shows a more rapid attainment of final particle size than the rate of formation of silica supporting the monomer addition hypothesis. The clearer understanding of the role of the initial composition on the output of this synthesis method will be of considerable use for the establishment of reliable reproducible silica production for future industrial adoption