Profile Of Candidates Research Articles

Prodrugs as empowering tools in drug discovery and development: recent strategic applications of drug delivery solutions to mitigate challenges associated with lead compounds and drug candidates.

The delivery of a drug to a specific organ or tissue at an efficacious concentration is the pharmacokinetic (PK) hallmark of promoting effective pharmacological action at a target site with an acceptable safety profile. Sub-optimal pharmaceutical or ADME profiles of drug candidates, which can often be a function of inherently poor physicochemical properties, pose significant challenges to drug discovery and development teams and may contribute to high compound attrition rates. Medicinal chemists have exploited prodrugs as an informed strategy to productively enhance the profiles of new chemical entities by optimizing the physicochemical, biopharmaceutical, and pharmacokinetic properties as well as selectively delivering a molecule to the site of action as a means of addressing a range of limitations. While discovery scientists have traditionally employed prodrugs to improve solubility and membrane permeability, the growing sophistication of prodrug technologies has enabled a significant expansion of their scope and applications as an empowering tool to mitigate a broad range of drug delivery challenges. Prodrugs have emerged as successful solutions to resolve non-linear exposure, inadequate exposure to support toxicological studies, pH-dependent absorption, high pill burden, formulation challenges, lack of feasibility of developing solid and liquid dosage forms, first-pass metabolism, high dosing frequency translating to reduced patient compliance and poor site-specific drug delivery. During the period 2012-2022, the US Food and Drug Administration (FDA) approved 50 prodrugs, which amounts to 13% of approved small molecule drugs, reflecting both the importance and success of implementing prodrug approaches in the pursuit of developing safe and effective drugs to address unmet medical needs.

Barriers to Sustainable Management of Organizational Intellectual Capital

In the global economy, intellectual capital management is a strategically important resource that affects the market value of organizations. Efficient management of intellectual capital requires the use of new management methods and techniques. One of them is knowledge management, which, in particular, focuses on removing barriers to knowledge sharing. The survey was conducted among employees of the Glogow, Jawor and Trzebnica counties, and the results constitute a pilot study. The conclusions from the collected research results are surprising and imply the need to conduct research on a larger scale in the area of human capital. The collected results provide information to management staff in the field of talent management and knowledge. The results may constitute the basis for developing succession plans, succession plans and employee training. Additionally, the results can help recruiters create profiles of candidates with specific competencies. The main aim of the study was to analyse and evaluate the personnel management process in the Glogow, Jawor and Trzebnica poviats. The use of various research methods made it possible to achieve the intended research goals. The basic research tool used was a survey. Analyses of the literature, research reports, and statistical summaries were treated as a complement to the main research methods. Research and statistical data indicate that among smaller companies in Lower Silesia, there is a need for development programs related to acquiring, collecting, and sharing knowledge. The study identified a number of factors that constitute a significant barrier to the development of employees of the surveyed companies. They allowed us to verify the relationship between the factors that constitute the greatest barrier to the learning process and the impact of the company’s size on it. The relationship between the barriers to intellectual development that constitute the greatest threat to the company and the factors that make it difficult for the company to recruit employees with the highest intellectual capital were also verified.

Irish apprenticeships in financial services: negotiating gender and navigating social justice

PurposeSet within the context of International Financial Services (IFS), this research aims to considers the demographic profile of IFS apprenticeship candidates in relation to gender equality and social mobility in Ireland. This study also offers valuable insights as to the gendered nature of these “new” apprenticeships and examine whether these programmes provide opportunities for social mobility.Design/methodology/approachImplementing a quantitative approach, underpinned by a positivist stance, this study analyses Irish national apprenticeship data relating to IFS programmes (n = 1118). Non-parametric tests were applied in the analysis of the gender dimension, while to analyse social mobility, the socio-economic status and spatial profile of candidates were compiled and analysed using the Pobal HP Deprivation Index (SA).FindingsThe findings revealed more women are undertaking non-traditional apprenticeship programmes as compared with traditional craft apprenticeships. Within the IFS context, while female participation was seen to be growing, gender divergence was observed in terms of programme level, with a greater number of men, as compared with women, engaging in higher-level degree apprenticeship programmes. The findings also show that IFS apprentices are primarily from socio-economic areas that are above average. This trend indicates a distinctive candidate who is more aligned with the sectoral profile of IFS than that of traditional apprenticeship programmes. Such findings reveal that the “widening participation” aim of IFS apprenticeships is not yet fully realised with issues of gender inequality and social mobility persistent within the wider IFS sector.Originality/valueThis study provides an important dimension to both academic and practitioner literature concerning apprenticeships. To date, there has been a proliferation of publications concerning the beneficial impact of skills and vocational-led apprenticeships. However, limited attention has been directed to non-traditional apprenticeships and even less still within the setting of IFS. This research initiates the process of addressing that gap within an Irish context. This study also adds to the existing apprenticeship discourse regarding issues of gender and social mobility by examining the gendered nature of IFS apprenticeships and well as assessing whether these apprenticeships aid social mobility.

Geopolitical analysis of the new scenario in the bidding process for the host cities of the olympic games

Study Objective: To analyze the new conjuncture in the process for bidding to be the host city of the Summer or Winter Olympic Games. Methodology/Approach: Taking the 1990s as an initial reference point, this qualitative and exploratory research has been conducted, entailing the analysis and synthesis of data and information from secondary sources. The research extensively involves scrutinizing academic articles, books, news reports, and sources published on specialized websites.Originality/Relevance: The hosting of the Games and the demands imposed by the IOC have been increasingly criticized. A rise in the number of referendums with local inhabitants of bidding cities has resulted in applications being withdrawn throughout the selection process. Main Results: The results indicate that the new geopolitical scenario has significant implications for the bidding process for the Olympics. An unusual scenario ensues in the geopolitical environment of the Olympics, promoting not only changes in the profile of candidates, but also institutional changes within the IOC itself.Theoretical/methodological contributions: It can provide a better understanding of the complex relationship between politics, power, and sports events. The research can help to identify key variables that impact the selection process, which can then be further investigated through quantitative studies.Social/Management Contribution: The research can shed light on the impact of the selection process on society, including its economic, political, and social consequences. It can also inform the decision-making process of the IOC and other stakeholders involved.

Drug Repurposing for COVID-19: Current Status of Potential Therapeutics

The maneuver clinical investigation of an effective drug for coronavirus disease 2019 (COVID-19) is still ongoing and the milieu of a successful investigational drug with proven efficacy is still obscure. Drug repurposing is a method to identify new therapeutic uses for existing drugs, which include approved, delayed, withdrawn, and investigational drugs and drug candidates. Indeed, the cost of the standard drug discovery and development process amounts to more than a billion dollars, and the investigations are expected to last 10–15 years. Notably, repurposing existing approved drugs is a potential, effective, and profitable approach as it significantly reduces the cost and time of developing a new drug. Owing to the established safety, pharmacokinetic, and pharmacodynamic profiles of potential drug candidates, drug repurposing may allow scientists to skip or shorten some critical steps of the traditional drug discovery and development process. Prospectively, advanced approaches could be harnessed to conduct proof-of-concept trials that would accelerate the clinical evaluation of repurposed drugs. Drawing lessons from repurposing efforts for COVID-19 therapeutics, the present review briefly summarizes the current status of various potential drugs that have been clinically evaluated for repurposing platforms as well as that could maximize safety, efficacy, and possible therapeutic benefits, both alone or in combination, and clinical outcomes in patients with COVID-19.

Virtual Design of Novel Coumarinyl-Substituted Sulfonamide Inhibitors of Carbonic Anhydrase II as Potential Drugs against Glaucoma

Background: We have carried out virtual design of coumarinyl-substituted sulfonamides (CSAM) analogs as inhibitors of human carbonic anhydrase II (hCA II) endowed with favorable predicted pharmacokinetic profiles and potential therapeutic effects against glaucoma.
 Methods: modifying in situ the x-ray structure of 2-(7-methoxy-2-oxo-2H-chromen-4-yl)-N-(4-sulfamoyl-phenyl)-acetamide (CSAM0)-hCA II complex (PDB entry 3ML2), permitted 3D models of hCA II-CSAMx complexes preparation for a TS of 14 CSAMs the experimental activities of which are available in the literature (IC50exp). Active bound conformation of the CSAM1-14 assessment led to linear correlation between computed enthalpy of hCA II-CSAMx complexes formation in gas phase (ΔΔHMM) with the IC50exp. Moreover, considering the solvation and ligand loss of entropy upon binding led to a superior QSAR model where a better linear correlation is established between calculated GFE (ΔΔGcom) and IC50exp. The successive 3D-pharmacophore (PH4) built from CSAMs active conformations helped to virtually screen CSAM populating a sulfonamides scaffolds virtual combinatorial library (VCL), focused by Lipinski’s rule-of-five to reach novel CSAMs.
 Results: Enthalpy QSAR model: pIC50exp = -0.068×ΔΔHMM + 7.722, R2 = 0.82; GFE QSAR model: pIC50exp = - 0.061× ΔΔGcom + 7.647, R2 = 0.92 and PH4 model: pIC50exp = 1.095×pIC50pre – 0.680, R2 = 0.87. The VCL of more than 1,500,625 CSAMs was lowered to 865,670 drug likely compounds by the Lipinski’s rule (except the restriction Mw ≤ 500 g/mol). The three-point PH4-based screening identified 81 novel CSAMs with predicted IC50pre reaching 78-times better than CSAM1 potency (IC50exp = 23 nM). Computed pharmacokinetic profile of the new candidates showed enhanced cell membrane permeability and high human oral absorption compared to current anti-glaucoma agents.
 Conclusions: Combination of QSAR models of the CSAMs’ affinity to the hCA II, pharmacophore model, and ADME profile guided to the sulfonamides inhibitors identification and helped to in silico screen VCL sulfonamides scaffold bearing analogs and allowed emerging of novel more potent compounds with predicted IC50 and favorable pharmacokinetic profiles.

Exploring the antimicrobial peptidome of nematodes through phylum-spanning in silico analyses highlights novel opportunities for pathogen control.

Antimicrobial Peptides (AMPs) are key constituents of the invertebrate innate immune system and provide critical protection against microbial threat. Nematodes display diverse life strategies where they are exposed to heterogenous, microbe rich, environments highlighting their need for an innate immune system. Within the Ecdysozoa, arthropod AMPs have been well characterised, however nematode-derived AMP knowledge is limited. In this study the distribution and abundance of putative AMP-encoding genes was examined in 134 nematode genomes providing the most comprehensive profile of AMP candidates within phylum Nematoda. Through genome and transcriptome analyses we reveal that phylum Nematoda is a rich source of putative AMP diversity and demonstrate (i) putative AMP group profiles that are influenced by nematode lifestyle where free-living nematodes appear to display enriched putative AMP profiles relative to parasitic species; (ii) major differences in the putative AMP profiles between nematode clades where Clade 9/V and 10/IV species possess expanded putative AMP repertoires; (iii) AMP groups with highly restricted profiles (e.g. Cecropins and Diapausins) and others [e.g. Nemapores and Glycine Rich Secreted Peptides (GRSPs)] which are more widely distributed; (iv) complexity in the distribution and abundance of CSαβ subgroup members; and (v) that putative AMPs are expressed in host-facing life stages and biofluids of key nematode parasites. These data indicate that phylum Nematoda displays diversity in putative AMPs and underscores the need for functional characterisation to reveal their role and importance to nematode biology and host-nematode-microbiome interactions.

Kinematics and stability of high-mass protostellar disk candidates at sub-arcsecond resolution

Context. The fragmentation mode of high-mass molecular clumps and the accretion processes that form the most massive stars (M ≳ 8 M⊙) are still not well understood. A growing number of case studies have found massive young stellar objects (MYSOs) to harbour disk-like structures, painting a picture that the formation of high-mass stars may proceed through disk accretion, similar to that of lower-mass stars. However, the properties of such structures have yet to be uniformly and systematically characterised. Aims. The aim of this work is to uniformly study the kinematic properties of a large sample of MYSOs and characterise the stability of possible circumstellar disks against gravitational fragmentation. Methods. We have undertaken a large observational programme (CORE) making use of interferometric observations from the Northern Extended Millimetre Array (NOEMA) for a sample of 20 luminous (L > 104 L⊙) protostellar objects in the 1.37 mm wavelength regime in both continuum and spectral line emission, reaching 0.4″ resolution (800 au at 2 kpc). Results. We present the gas kinematics of the full sample and detect dense gas emission surrounding 15 regions within the CORE sample. Using the dense gas tracer CH3CN, we find velocity gradients across 13 cores perpendicular to the directions of bipolar molecular outflows, making them excellent disk candidates. The extent of the CH3CN emission tracing the disk candidates varies from 1800 to 8500 au. Analysing the free-fall to rotational timescales, we find that the sources are rotationally supported. The rotation profiles of some disk candidates are well described by differential rotation while for others the profiles are poorly resolved. Fitting the velocity profiles with a Keplerian model, we find protostellar masses in the range of ~ 10–25 M⊙. Modelling the level population of CH3CN (12K–11K) K = 0–6 lines, we present temperature maps and find median temperature in the range 70–210 K with a diversity in distributions. Radial profiles of the specific angular momentum (j) for the best disk candidates span a range of 1–2 orders of magnitude, on average ~10−3 km s−1 pc, and they follow j ∝ r1.7, which is consistent with a poorly resolved rotating and infalling envelope-disk model. Studying the Toomre stability of the disk candidates, we find almost all (11 out of 13) disk candidates to be prone to fragmentation due to gravitational instabilities at the scales probed by our observations, as a result of their high disk to stellar mass ratio. In particular, disks with masses greater than ~ 10–20% of the mass of their host (proto)stars are Toomre unstable, and more luminous YSOs tend to have disks that are more massive compared to their host star and hence more prone to fragmentation. Conclusions. In this work, we show that most disk structures around high-mass YSOs are prone to disk fragmentation early in their formation due to their high disk to stellar mass ratio. This impacts the accretion evolution of high-mass protostars which will have significant implications for the formation of the most massive stars.

The role of sexism in holding politicians accountable for sexual misconduct

Experimental research on the impact of the #MeToo movement on the evaluation of politicians has focused on how the impact is conditioned by partisan motivation. Beyond partisanship, gender identity and sexist attitudes may also act as a barrier to the success of #MeToo in challenging sexual misconduct in politics. In a conjoint experiment, we examine the extent to which sexism and gender identities (feminine/masculine identity and self-identified gender) condition how individuals respond to politicians accused of sexual misconduct. Respondents were shown two profiles of fictional British male candidates accused of sexual misconduct where the characteristics of the candidate and the scandal were (the number of allegations made, whether they apologized for the misconduct, their partisanship, and their stance on Brexit). We find that in general, more severe misconduct has a more negative impact on evaluations but that respondents who expressed attitudes consistent with hostile sexism were less likely to punish politicians for multiple offenses and less likely to reward a recognition of wrongdoing. Categorical gender identity, whether the respondent was a man or a woman, did not condition the electoral consequences of the scandal and a feminine and masculine identities moderated the impact of the political stance of the candidate. We conclude by discussing the importance of measuring gender attitudes, especially sexism and non-categorical measures of gender identity, in future studies on the political consequences of #MeToo.

Development of rat duodenal monolayer model with effective barrier function from rat organoids for ADME assay

The in-depth analysis of the ADME profiles of drug candidates using in vitro models is essential for drug development since a drug’s exposure in humans depends on its ADME properties. In contrast to efforts in developing human in vitro absorption models, only a limited number of studies have explored models using rats, the most frequently used species in in vivo DMPK studies. In this study, we developed a monolayer model with an effective barrier function for ADME assays using rat duodenal organoids as a cell source. At first, we developed rat duodenal organoids according to a previous report, but they were not able to generate a confluent monolayer. Therefore, we modified organoid culture protocols and developed cyst-enriched organoids; these strongly promoted the formation of a confluent monolayer. Furthermore, adding valproic acid to the culture accelerated the differentiation of the monolayer, which possessed an effective barrier function and apicobasal cell polarity. Drug transporter P-gp function as well as CYP3A activity and nuclear receptor function were confirmed in the model. We expect our novel monolayer model to be a useful tool for elucidating drug absorption processes in detail, enabling the development of highly absorbable drugs.

Preclinical evaluation of general toxicity and safety pharmacology of a receptor-binding domain-based COVID-19 subunit vaccine in various animal models.

The coronavirus disease 2019 pandemic has resulted in the introduction of several naïve methods of vaccine development, which have been used to prepare novel viral vectors and mRNA-based vaccines. However, reluctance to receive vaccines owing to the uncertainty regarding their safety is prevalent. Therefore, rigorous safety evaluation of vaccines through preclinical toxicity studies is critical to determine the safety profiles of vaccine candidates. This study aimed to evaluate the toxicity profile of HuVac-19, a subunit vaccine of SARS-CoV-2 utilizing the receptor-binding domain as an antigen, in rats, rabbits, and dogs using single- and repeat-dose study designs. Repeat-dose toxicity studies in rats and rabbits showed transient changes in hematological and serum biochemical parameters in the adjuvant and/or vaccine groups; however, these changes were reversed or potentially reversible after the recovery period. Moreover, temporary reversible changes in absolute and relative organ weights were observed in the prostate of rats and the thymus of rabbits. Gross examination of the injection sites in rats and rabbits treated with the adjuvant- and HuVac-19 showed discoloration and foci, whereas histopathological examination showed granulomatous inflammation, inflammatory cell infiltration, and myofiber degeneration/necrosis. This inflammatory response was local, unassociated with other toxicological changes, and resolved. In a pharmacological safety study, no toxicological or physiological changes associated with HuVac-19 administration were observed. In conclusion, HuVac-19 was not associated with any major systemic adverse effects in the general toxicity and safety pharmacology evaluation, demonstrating that HuVac-19 is a vaccine candidate with sufficient capacity to be used in human clinical trials.

A Study on the Profiles of Arabic Translation-Translator Candidates in Turkish Higher Education

Translation, an ancient activity, has only been acknowledged as an independent discipline since the 1970s. Translation Studies was introduced as a program in Turkish higher education in the 1980s, with English translation and interpreting programs being the first to emerge. It was not until 2011 that the first program for training Arabic translators and interpreters was established at Kırıkkale University. Subsequently, the same program was introduced in nine other universities. In this study, we explore the profiles of prospective Arabic translators and interpreters in ten Turkish universities offering undergraduate-level programs for Arabic translation and interpreting, focusing on various aspects such as gender, geographical location, educational background, high school type, academic ranking, foreign language test scores, program preferences, and post-graduation plans. Our findings indicate that female students show a greater inclination towards the program, with one-third of the students choosing the program in their city. Arabic translator-interpreter candidates mostly originate from the Central Anatolian Region, with one-third being recent graduates and another third being experienced ones. More than half of the students who enrolled in the program graduated from Imam-Hatip High School, and top-performing students are less inclined to select this program. On average, a language test score of forty-six is required for admission to the program. Finally, we found that students who completed the program often preferred programs related to Arabic language teaching and literature.

Network neighborhood operates as a drug repositioning method for cancer treatment.

Computational drug repositioning approaches are important, as they cost less compared to the traditional drug development processes. This study proposes a novel network-based drug repositioning approach, which computes similarities between disease-causing genes and drug-affected genes in a network topology to suggest candidate drugs with highest similarity scores. This new method aims to identify better treatment options by integrating systems biology approaches. It uses a protein-protein interaction network that is the main topology to compute a similarity score between candidate drugs and disease-causing genes. The disease-causing genes were mapped on this network structure. Transcriptome profiles of drug candidates were taken from the LINCS project and mapped individually on the network structure. The similarity of these two networks was calculated by different network neighborhood metrics, including Adamic-Adar, PageRank and neighborhood scoring. The proposed approach identifies the best candidates by choosing the drugs with significant similarity scores. The method was experimented on melanoma, colorectal, and prostate cancers. Several candidate drugs were predicted by applying AUC values of 0.6 or higher. Some of the predictions were approved by clinical phase trials or other in-vivo studies found in literature. The proposed drug repositioning approach would suggest better treatment options with integration of functional information between genes and transcriptome level effects of drug perturbations and diseases.

Molecular Representations in Machine-Learning-Based Prediction of PK Parameters for Insulin Analogs.

Therapeutic peptides and proteins derived from either endogenous hormones, such as insulin, or de novo design via display technologies occupy a distinct pharmaceutical space in between small molecules and large proteins such as antibodies. Optimizing the pharmacokinetic (PK) profile of drug candidates is of high importance when it comes to prioritizing lead candidates, and machine-learning models can provide a relevant tool to accelerate the drug design process. Predicting PK parameters of proteins remains difficult due to the complex factors that influence PK properties; furthermore, the data sets are small compared to the variety of compounds in the protein space. This study describes a novel combination of molecular descriptors for proteins such as insulin analogs, where many contained chemical modifications, e.g., attached small molecules for protraction of the half-life. The underlying data set consisted of 640 structural diverse insulin analogs, of which around half had attached small molecules. Other analogs were conjugated to peptides, amino acid extensions, or fragment crystallizable regions. The PK parameters clearance (CL), half-life (T1/2), and mean residence time (MRT) could be predicted by using classical machine-learning models such as Random Forest (RF) and Artificial Neural Networks (ANN) with root-mean-square errors of CL of 0.60 and 0.68 (log units) and average fold errors of 2.5 and 2.9 for RF and ANN, respectively. Both random and temporal data splittings were employed to evaluate ideal and prospective model performance with the best models, regardless of data splitting, achieving a minimum of 70% of predictions within a twofold error. The tested molecular representations include (1) global physiochemical descriptors combined with descriptors encoding the amino acid composition of the insulin analogs, (2) physiochemical descriptors of the attached small molecule, (3) protein language model (evolutionary scale modeling) embedding of the amino acid sequence of the molecules, and (4) a natural language processing inspired embedding (mol2vec) of the attached small molecule. Encoding the attached small molecule via (2) or (4) significantly improved the predictions, while the benefit of using the protein language model-based encoding (3) depended on the used machine-learning model. The most important molecular descriptors were identified as descriptors related to the molecular size of both the protein and protraction part using Shapley additive explanations values. Overall, the results show that combining representations of proteins and small molecules was key for PK predictions of insulin analogs.

Epidemiological Profile and Complications of Patients on the Waiting List for Liver Transplantation

Objective: To identify the epidemiological profile of candidates for liver transplantation and the complications that occurred up to the sixth month of admission to the waiting list. Method: Descriptive-exploratory study conducted in a liver transplant program located in a city in the interior of the state of São Paulo. Candidates aged ≥ 18 of both genders who entered the waiting list between January 1, 2018, and February 28, 2019, made up the study sample, totaling 51 patients. Data analysis was performed using descriptive statistics. Results: The average age of the participants was 52.7 years, most male (60.8%) with incomplete primary education (58.8%). Arterial hypertension was the most frequent comorbidity (51.4%). Most participants had blood type O (58.8%). The average Body Mass Index was 28.8 Kg/m²(overweight). Alcoholic cirrhosis was the most frequent indication for transplantation (31.4%). The average MELD score when joining the waiting list and six months later was 17.9 points. Class B of the Child-Pugh score had the highest frequency at the patient’s admission and the first follow-up. Ascites were the most frequent complication (56.9%), followed by portal hypertension (52.9%) and hepatic encephalopathy (33.3%). At the end of the study, 29 patients remained on the waiting list (56.9%), ten patients were transplanted (19.6%), and 12 died (23.5%).Conclusion: As for the epidemiological profile, the study’s results were in line with other studies, that is, participants with a predominance of male biological sex, most frequent age group of 50 to 59 years and low level of education. Concerning the identified complications, ascites were the most frequent. Among participants who did not remain on the waiting list, the number of deaths was more significant than the number of transplants performed, evidence that differs from other studies.

An alternative biomimetic tool – Dual hydrophilic/reversed-phase interaction mode

During the early stages of drug discovery, it becomes increasingly important to acquire a basic physico-chemical and pharmacokinetic profile of drug candidates using efficient and cost-effective laboratory and computational models. In this study, the possibility of applying the dual hydrophilic interaction liquid chromatography/reversed-phase mode (HILIC/RP) as a alternative biomimetic tool for the preliminary profiling of imidazoline and piperazine-related compounds was investigated. Their retention behaviour on the mixed-mode HILIC/RP column was described as a dependence of the logarithm of the retention factor (logk) in relation to the volume fraction of the water component in the mobile phase (φ). The retention was quantified by integration of HILIC (logkH), RP (logkR) and the total HILIC/RP (logkA) area under the logk = f(φ) curve. The biomimetic capabilities of HILIC/RP mode were observed through physico-chemical and pharmacokinetic interpretation of chromatographic behaviour. The physico-chemical characteristics of the HILIC/RP mode were defined based on linear solvation energy relationships, genetic algorithm-multiple linear regression and Boruta-XGBoost predictive modeling. The created models showed reliable predictive performances for defining the logkA, logkR, and logkH values. The mixed-mode logkA, logkR, and logkH parameters correlate well with physico-chemical (e.g., lipophilicity indices) and basic pharmacokinetic properties of the examined compounds. The models created have confirmed that the simultaneous contribution of both HILIC/RP mechanisms can be used to accurately evaluate the key properties of newly synthesized imidazoline and piperazine-related compounds while reducing costs and selecting suitable candidates in the early stages of drug development and discovery.

Associations between the stanford integrated psychosocial assessment for transplant and one-year lung transplant medical and psychosocial outcomes.

The Stanford Integrated Psychosocial Assessment for Transplant (SIPAT) is a standardized measure of the psychosocial risk profile of solid organ transplant candidates. While studies have found associations between this measure and transplant outcomes, to date this has not been examined in lung transplant recipients. We examined relations between pre-transplant SIPAT scores and 1-year lung transplant medical and psychosocial outcomes in a sample of 45 lung transplant recipients. The SIPAT was significantly associated with 6-minute walk test (χ2(1) = 6.47, p = .010), number of readmissions (χ2(1) = 6.47, p = .011), and mental health services utilization (χ2(1) = 18.15, p < .001). It was not a significantly associated with the presence of organ rejection or mortality (ps > 0.10). Results suggest that the SIPAT can help identify patients who are at an elevated risk for transplant complications and thus would benefit from services to mitigate risk factors and improve outcomes.

Impact of mini-driver genes in the prognosis and tumor features of colorectal cancer samples: a novel perspective to support current biomarkers.

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths, and its development is associated with the gains and/or losses of genetic material, which leads to the emergence of main driver genes with higher mutational frequency. In addition, there are other genes with mutations that have weak tumor-promoting effects, known as mini-drivers, which could aggravate the development of oncogenesis when they occur together. The aim of our work was to use computer analysis to explore the survival impact, frequency, and incidence of mutations of possible mini-driver genes to be used for the prognosis of CRC. We retrieved data from three sources of CRC samples using the cBioPortal platform and analyzed the mutational frequency to exclude genes with driver features and those mutated in less than 5% of the original cohort. We also observed that the mutational profile of these mini-driver candidates is associated with variations in the expression levels. The candidate genes obtained were subjected to Kaplan-Meier curve analysis, making a comparison between mutated and wild-type samples for each gene using a p-value threshold of 0.01. After gene filtering by mutational frequency, we obtained 159 genes of which 60 were associated with a high accumulation of total somatic mutations with Log2 (fold change) > 2 and p values < 10-5. In addition, these genes were enriched to oncogenic pathways such as epithelium-mesenchymal transition, hsa-miR-218-5p downregulation, and extracellular matrix organization. Our analysis identified five genes with possible implications as mini-drivers: DOCK3, FN1, PAPPA2, DNAH11, and FBN2. Furthermore, we evaluated a combined classification where CRC patients with at least one mutation in any of these genes were separated from the main cohort obtaining a p-value < 0.001 in the evaluation of CRC prognosis. Our study suggests that the identification and incorporation of mini-driver genes in addition to known driver genes could enhance the accuracy of prognostic biomarkers for CRC.

Identity and virtuality: The influence of personal profiles on social media on job search

This study explores the relationship between digital identity and employability, analysing how human resources departments review the digital profiles of potential candidates on social media platforms. The study created a questionnaire of 17 closed questions using variables, such as, basic demographic data and procedures of the recruitment process (analysis of social networks, use of Big Data and importance of the digital image of candidates). The study concluded that the information future candidates show on social media platforms is very important, even decisive, in recruitment. The study confirms the hypothesis that one’s digital identity on social media networks can negatively influence employment opportunities and even be a reason for the rejection of a candidate. Recruitment experts actively review candidates' presence on social media networks, both professional (LinkedIn) and personal platforms such as Facebook and Instagram.

Different resistance exercise loading paradigms similarly affect methylation status and mRNA expression patterns of myostatin-related genes in skeletal muscle

Although several resistance exercise studies have used bioinformatics platforms to identify the biological relevance of gene expression changes, these platforms seldom provide in-depth information on genes that have been mechanistically linked to skeletal muscle hypertrophy. Thus, we sought to perform a secondary analysis on a muscle transcriptomic dataset we previously collected involving two different bouts of resistance exercise. Previously trained college-aged males (n=11, training experience: 4±3 years) performed two resistance exercise bouts separated by one week. The higher-load bout (80fail) consisted of 4 sets of back squats and 4 sets of leg extensions to failure using 80% of their estimated one-repetition maximum. The lower-load bout (30fail) consisted of this same paradigm using 30% of their one-repetition maximum. Vastus lateralis muscle biopsies were collected before (PRE), 3 hours (3h), and 6 hours (6h) after each exercise bout, and bouts were separated by a one-week washout. Muscle mRNA was analyzed for genome-wide mRNA expression patterns using the Clariom S mRNA array. Based on an extensive literature search performed by us and others, the mRNA expression profile of gene candidates mechanistically associated with skeletal muscle hypertrophy (58 genes) was interrogated between 30fail and 80fail training. Select targets were further interrogated for associated protein expression and phospho-signaling events. Although none of the 58 skeletal muscle hypertrophy-associated gene targets demonstrated significant bout✕time point interactions, ~57% showed a significant time-only effect from PRE to 3h (15↑ and 18↓, p&lt;0.01) and ~26% showed significant time-only effect from PRE to 6h (8↑ and 9↓, p&lt;0.01). Genes related to myostatin signaling (9 genes) and mTORC1 signaling (9 genes) were well represented on the gene list. Compared to mTORC1 signaling mRNAs, a greater percentage of myostatin signaling-related mRNAs were dynamically altered post-exercise (i.e., significant time-only effects). There were increases in phospho (Thr389)/pan p70S6K (p=0.001; PRE to 3h) and follistatin protein levels (p=0.021; PRE to 6h) regardless of bout. No significant time effects or interactions were observed for phospho (Ser2448)/pan mTOR, phospho (Thr389)/pan AKT, phospho (Ser235/236)/pan rpS6, or myostatin protein levels. The data have multiple implications. First, performing lighter load and heavier load resistance exercise to failure elicits similar alterations in the mRNA responses of genes mechanistically associated with skeletal muscle hypertrophy and mTORC1 signaling. Second, acute resistance exercise predominantly affects the myostatin signaling pathway via transcriptional mechanisms and genes involved with mTORC1 signaling are less affected in this regard. This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.