Lisinopril is a dipeptide containing an L-Proline group and an L-Lysine residue. It is an antiarrhythmic medication belonging to the family of angiotensin-converting enzyme (ACE) inhibitors . It effectively treats arterial hypertension (first-line treatment), heart failure, and heart attacks; it also prevents kidney problems in people with diabetes mellitus. The main purpose of this work consisted of the dosage of Lisinopril as a single active substance from pharmaceutical tablets. A new method for the quantitative analysis of Lisinopril using visible spectrophotometry (VIS) was found, optimized, and applied in laboratory practice. This method was based on the diazotization of the free primary amino group -NH₂ of Lisinopril in cold conditions for 25 minutes at 1-5 degrees Celsius, in the presence of sodium nitrite 5 % and hydrochloric acid 10%-15%, followed by the quantitative coupling of the obtained diazonium salt with alpha-naphthol from an alkalized 0.2 % alcoholic solution. An intense orange azo dye with a reddish shade was dosed at the wavelength corresponding to the absorption maximum, λ = 489 nm, in relation to double-distilled water, which was used as a blank. The amount of pure Lisinopril found per tablet was 19.60 mg / coated tablet .This value was very close to the official reference value of 20 mg pure Lisinopril/tablet. The average percentage deviation was only 2.00% compared to the officially declared content of the active substance; this fell perfectly within the normal limits of the average percentage deviation allowed by the Romanian Pharmacopoeias 10th Edition and European Pharmacopoeias (± 7.5%). The method proposed to be applied for the visible spectrophotometric analysis of Lisinopril from pharmaceutical tablets presented a very good linearity over the entire chosen concentration range of 0.41 μg/mL - 12.24 μg/mL. The linear regression coefficient was R² = 0.999085, which fit perfectly within the normal range of values, R² ≥ 0.9990. The proposed method was then statistically validated.

The use of alkaline microbial proteases makes the industry more eco-sustainable, both in terms of reducing the consumption of chemical products and in terms of lowering effluent treatment costs.

A proteolytic Bacillus strain isolated from a tannery alkaline bath was used to produce extracellular proteases by submerged fermentation in bioreactor and the produced proteolytic broth was applied in leather tanning and protein stain removal.

The tanning process application consisted of using fermentation broth with 780 LVU (Löhlein–Volhard Unit) proteolytic activity on half-skin tanning, and the other half-skin was tanned using a commercial enzymatic bate (OROPON) with same proteolytic activity and tanning conditions.

The physical properties of the hide tanned using proteolytic broth and the hide tanned with commercial bate were assessed in terms of bursting load (kg) and bursting elongation (mm) for hides with two different leather thicknesses (2.4 mm and 1.6 mm). The hide tanned with the produced broth showed better physical tests of bursting (with elongation till 6.8 mm before bursting) than the one tanned with commercial proteases (elongation only till 6.3 mm) for same bursting load of 19 kg and 1.6 mm leather thickness. The thicker leather (2.4 mm) showed the same bursting elongation of 10 mm for a higher load (54 Kg) for the hide tanned with bulk proteases than commercial proteases.

Protein stain removal from cotton fabric (squares of cotton fabric with 4 cm sides with the centre stained with egg, blood, soya sauce and English sauce) was tested using the produced proteolytic broth and compared with the use of water (blank), or a commercial detergent, under the same agitation at room temperature. The proteolytic broth showed better blood and egg stain removal than water or the detergent.

Produced proteases can be used in protein residue and effluent treatments. Applications showed potential for use in the bioeconomy and for green chemistry.

Near-infrared (NIR) photothermal therapy (PTT) of solid tumors utilizes localized heat to induce the immunogenic death of tumor cells. The combination of PTT with checkpoint inhibitor therapy can further amplify the immune response and improve the therapeutic outcome in what is known as photothermal immunotherapy. Here, we introduce a triple therapy, where photothermal immunotherapy is further amplified by the pharmacological silencing of tumor-infiltrating sensory neurons, an approach that was recently shown to affect tumor immunosurveillance as a standalone treatment .

For our model, B16F10-OVA melanoma cells were injected subcutaneously in mice. Once the tumors reached approximately 200 mm³, they were treated by NIR laser irradiation, with a local silencing of nociceptors using an lidocaine derivative (QX-314), and immunotherapy alone (aPDL1) or in combination.

We employed mathematical modeling to predict heat distribution and necrotic tissue in mice bearing melanoma tumors. Our model utilized experimentally defined parameters, such as tissue optical properties, tumor size, laser beam size and power, and irradiation time. The model was experimentally validated using data on tumor temperature increases. We found that the tumor size is a key determinant of temperature increase, which underscores the need for personalized treatment conditions . We determined optimal treatment conditions (808 nm, 0.3 W/cm², 3 min) for mice bearing 200 mm³ tumors.

Laser treatment was subsequently applied either alone (Laser+) or in combination with immunotherapy (aPDL1+) and neuronal silencing (QX-314+). When compared to control groups, the triple therapy (Laser+, QX-314+, and aPDL1+) significantly decreases tumor progression (p=0.0003) and increases survival time. Specifically, it resulted in complete ablation in 42% of the treated mice. Tumor re-growth was observed in only 16% of rechallenged mice, suggesting an immune memory effect.

Our results indicated that triple treatment can lead to a significant reduction in tumor growth and could complete tumor ablation in a significant fraction of the treated mice.

Introduction: Genetic variation significantly influences individual responses to beta-blockers, a class of medications commonly used to manage cardiovascular conditions such as hypertension and heart failure. Understanding these genetic differences is crucial for optimizing treatment efficacy and minimizing adverse effects.

Methods: We conducted a systematic review using three online databases: PubMed, Scopus, and Web of Science. The search strategy included terms such as "genetic polymorphisms," "beta-blockers," "ADRB1," "ADRB2," and "CYP2D6." After removing duplicates, we screened 921 titles and abstracts for relevance. Full-text articles of 111 studies were assessed for eligibility based on the inclusion criteria, which required studies to report on genetic polymorphisms affecting beta-blocker response in human subjects. A quality assessment was performed using a modified Cochrane RoB1 tool, evaluating aspects such as study design, sample size, and statistical analysis.

Results: Out of the 111 full-text articles assessed, 95 studies met the inclusion criteria and were included in the final analysis. Of these, 16 studies were excluded due to poor quality or insufficient data. The 95 included studies provided comprehensive baseline data on the pharmacogenomics of beta-blockers. Key findings indicated that polymorphisms in the ADRB1 gene, particularly the Ser49Gly and Arg389Gly variants, significantly affected the therapeutic response to beta-blockers in hypertensive patients. Variants in the ADRB2 gene, such as Gly16Arg and Gln27Glu, were associated with differential responses in heart failure patients. Furthermore, CYP2D6 polymorphisms influenced the metabolism of beta-blockers, affecting drug plasma levels and clinical outcomes.

Conclusions: Our findings underscore the importance of genetic testing in the personalized prescription of beta-blockers. Genetic variations in ADRB1, ADRB2, and CYP2D6 genes were particularly influential, affecting drug efficacy and safety profiles. Incorporating pharmacogenomic data into clinical guidelines can enhance therapeutic outcomes for patients receiving beta-blockers by tailoring treatments based on individual genetic profiles.

Several alkaloids, terpenoids, limonoids, steroids, lignans and flavaglines have been isolated from the genus Aglaia. A significant number of them have not been tested for any biological activities, while those already screened for activities may have limited phenotypic targets, are under-utilized or may require validation. This study exploited the SuperPred tool for prospective and retrospective drug target fishing for novel bioactivities of drug-like molecules derived from Aglaia species. A total of 291 secondary metabolites were obtained from a review of the literature. The simplified molecular input line entry system (SMILES) canonical strings were subjected to drug-likeness prediction using the SwissADME tool. The anatomical therapeutic chemical class and potential targets of the compounds were deconvoluted by SuperPred logistic regression machine learning models, based on Morgan fingerprints with a length of 2048 and with a probability and model accuracy cut-off of ≥90%. Of the 291 secondary metabolites, 25 displayed the most favourable pharmacokinetic, physicochemical and toxicological properties. The 25 drug-like compounds comprised a lignan (lariciresinol acetate), a triterpenoid (17,24-epoxy-20α,25-dihydroxy-21-norbaccharan-3-one), three flavaglines (pyrimidinone, dihydropyrimidinone and rocagloic acid) and steroids ((E)-aglawone, 2β,3β,4α-trihydroxypregnan-16-one and androst-1,4-dien-3,17-dione), five sesquiterpenoids and twelve alkaloids. The compounds were found to interact with many targets, such as the NF-κB p105 subunit, cannabinoid CB2 receptor, MAP kinase ERK2, hypoxia-inducible factor 1α, G-protein coupled receptor 55, tyrosyl-DNA phosphodiesterase 1, p53-binding protein Mdm-2, cathepsin D, COX-1 and arachidonate 12-lipoxygenase. The target fishing of the secondary metabolites provided insights into the potential novel activities, polypharmacology and possible unintended off-target binding of Aglaia molecules.

Introduction: This study aimed to investigate the anti-inflammatory effect of methanol extract of Alstonia boonei stem bark in a lipopolysaccharide (LPS)-induced model of inflammation.

Methodology: Twenty Wistar albino rats were divided into five groups (n=4). Group 1 served as the normal control, while groups 2-5 were induced with 10 mg/kg b.wt of LPS dissolved in normal saline. Thirty minutes after lipopolysaccharide (LPS) induction, group 3 (standard control) and groups 4 and 5 (Alstonia boonei groups) were treated with the standard drug (50 mg/kg of ibuprofen) and 250 mg/kg and 500 mg/kg (AB₂₅₀ and AB₅₀₀) of the Alstonia boonei extract, respectively. Blood was collected from the animals six hours post-treatment for biochemical analysis.

Results: The acute toxicity study demonstrated a high safety profile of the extract, with an LD₅₀ exceeding 5000 mg/kg body weight in mice. Phytochemical analysis of the Alstonia boonei methanol extract revealed the presence of diverse bioactive compounds, including pomiferin, quercetin, ellagic acid, rutin, coumarin, stilbenes, catechol, and gallic acid, amongst others. The in vivo results showed that the untreated group had a significantly higher (p < 0.05) increase in Interleukin-6 (IL-6), Nuclear factor kappa B-p65 (NFKB-p65), and Interleukin 1 beta (IL-1β) activities in the untreated group compared to the normal control group. In the treatment groups, both doses of the extract (AB₂₅₀ and AB₅₀₀) caused significant reductions in IL-6 and IL-1β levels but not NFKB-p65.

Conclusion: This result highlights the rich bioactive store of A. boonei stem bark and its potential to modulate inflammatory responses in vivo.

In a world marked by perpetual change and constant evolution, the pursuit of optimizing human performance transcends traditional boundaries. Central to this relentless quest is the precise assessment of cognitive workload—an essential element in unlocking and enhancing human potential. Neuro-Fusion represents a pioneering approach poised to revolutionize cognitive workload classification. This innovative methodology seamlessly integrates advanced neural network models with EEG (electroencephalogram) data, merging the capabilities of LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Unit) models into a unified, adaptive framework designed for accurate cognitive workload assessment. At the core of our research lies the real-time application of the Neuro-Fusion model in cognitive workload assessment, powered by EEG data from the STEW dataset. Rigorous EEG data preprocessing facilitated feature extraction, channeling these processed data into the innovative LSTM-GRU hybrid architecture, giving rise to the formidable Neuro-Fusion model. The Neuro-Fusion model achieved remarkable cognitive workload classification accuracy, boasting an impressive 96%. This precision underscores the substantial potential of our approach in providing dependable cognitive assessments, especially in scenarios demanding precision. The implications of our research extend across diverse practical applications. Neuro-Fusion promises to offer invaluable insights into cognitive workloads, facilitating more informed decision-making and enhanced human performance optimization. Its practical implications span various sectors, promising efficiency, productivity, and safety improvements. Neuro-Fusion, merging neural networks with EEG data, revolutionizes cognitive workload assessment, with implications for diverse sectors.

Third molar surgery, commonly known as wisdom tooth surgery, is a dental procedure frequently performed to remove these teeth located at the back end of the mouth. Often, third molars do not find enough space to erupt properly, resulting in partial or complete impaction. This condition can cause pain, infection, cysts, tooth decay, and damage to adjacent teeth. The decision to remove third molars is based on a clinical and radiographic evaluation, considering factors such as angulation, depth of impaction and the presence of symptoms. The surgical procedure varies in complexity from simple extraction to more complex procedures that require opening the gum tissue and removing some of the surrounding bone. Local anesthesia is commonly used, but in some cases general anesthesia or sedation may be used. The post-operative period may include swelling, pain and bleeding, managed with pain relievers and antibiotics. Possible complications include infection, nerve damage, and the formation of dry socket. However, with proper planning and surgical technique, most third molar extractions occur without significant problems. Collaboration between dentists, oral surgeons and patients is crucial for the success of the procedure and for rapid recovery, because often, non-cooperation of patients leads to very severe failures and discomfort.

Background: Cobalt (Co) is increasingly used in green technology development. Recently, our group detected Co in the scalp hair of 73 out of 97 monitored adolescents born and residing in Alcalá de Henares (Spain), suggesting some exposure. We studied Co presence in young children, owing to their greater susceptibility.

Methods: Co was analysed by ICP-MS, after the appropriate removal of exogenous contamination, in scalp hair from 120 children (6 to 9 years old; 70 females) who met strict inclusion criteria.

Results: Data were processed using the NADA statistical package owing to the level of censored values (26.05%; LoD=0.0034 µg/g), which was similar to the percentage observed in adolescents’ hair (24.73%). Co levels were slightly higher in children’s hair [data presented as medians and ranges, in µg/g: 0.0062 (0.0036-0.0437) vs. 0.0036 (0.0016-0.0817)], suggesting a minor dependency of detoxification on young age. This effect was also reported in an study carried out with individuals living in the city of Madrid and in a village in the NE; thus, significantly higher levels of Co were detected in children’s hair (aged 6-10 years) versus the hair of teenagers aged 11-15 years (0.0172 vs. 0.0141 µg/g). Similarly to what was observed in the adolescent cohort, Co presence in children’s hair was sex-dependent; it was significantly higher in female participants [p-value=0.00087; median and range, in µg/g: 0.0074 (0.0037-0.0437) vs. 0.0047 (0.0036-0.0157)], which is also in agreement with what was observed in individuals living in Madrid.

Conclusions: The results suggest some exposure to Co, which would be mostly from dietary sources, as little Co has been detected in the environment of Alcalá de Henares. Tentative reference values for Co, i.e., the 95% confidence interval of the 95th population percentile (CI-PP95), are proposed for girls (0.0199-0.0356) and boys (0.0083-0.0144), as age and sex have been shown to affect the levels of Co in human hair. These ranges could be used to detect exposure to Co in children living in the same city.

Introduction. This scientific contribution aims to describe a new methodology to improve diagnosis and treatment planning in daily orthodontic practice.

Methods. The proposed methodology is described by reporting a series of cases that were assessed before treatment according to the standardized digital workflow reported below. Cephalometric analyses of the included cases were performed using the “WebCeph” platform (Software Version: 1.5.0, Assemble Circle Corp., Republic of Korea), and the buccolingual inclinations of the upper incisors were assessed. Using individualized templates, the ideal position and inclination of the upper incisors were determined on the cephalometric tracing, and linear and angular differences of the incisors were measured and compared to pre-treatment values. A virtual set-up of the case was generated with a 3Shape Ortho System 2022 (3Shape, Copenhagen K, Denmark). As the first step of the virtual set-up, the positions and inclinations of the upper incisors were adjusted according to the cephalometric differences previously evaluated. Subsequently, the final set-up was defined according to the planned position of the central incisors.

Results. For the first time in the orthodontic literature, this new method describes the following workflow: planning the position of the upper incisors with respect to the cranial base structures, transferring this position to the virtual set-up, and obtaining a set-up that realistically shows the real orthodontic movements in the anteroposterior direction. This method clearly and immediately defines the ideal anchorage management, thereby facilitating the ideal biomechanical case management.

Conclusions. This article outlines an original method that combines patient data derived from cephalometric analysis with data obtained from study model analysis. This combination is used to identify the ideal position and buccolingual inclination of the upper incisors on cephalometric tracing and to transfer this position to an ideal orthodontic virtual set-up.