Hasil untuk "Pharmacy and materia medica"

Mariam Gamal Elsayed, Amal A. El kholy, Eman Mohamed Elmokadem et al.

Abstract Background Acute exacerbations of chronic obstructive pulmonary disease are critical clinical events that substantially contribute to morbidity, mortality, and healthcare utilization. Standard management with bronchodilators, systemic corticosteroids, and antibiotics remains central to acute care; however, these therapies incompletely address the complex and multifactorial pathophysiological processes that drive exacerbation severity, delayed recovery, and early readmission. Persistent oxidative stress, corticosteroid-resistant inflammation, mucus hypersecretion, systemic inflammatory activation, and metabolic dysfunction often continue despite optimal guideline-directed treatment. Main body This review synthesizes current evidence on pharmacological and non-pharmacological adjuvant therapies for acute exacerbations of chronic obstructive pulmonary disease, integrating mechanistic rationale with emerging data from experimental and clinical studies. Pharmacological adjuvants—including thiol-based antioxidants and mucolytics, non-adrenergic bronchodilators, metabolic and mitochondrial modulators, and selected precision-targeted agents—may enhance standard therapy by restoring redox balance, improving mucus clearance, modulating inflammatory signaling, and supporting systemic recovery. In parallel, non-pharmacological interventions such as early pulmonary rehabilitation, nutritional optimization, individualized oxygen titration, and non-invasive ventilation target functional impairment and systemic stress that are insufficiently addressed by pharmacotherapy alone. The review also explores the potential utility of readily available systemic inflammatory biomarkers, including the neutrophil-to-lymphocyte ratio and composite inflammation indices, for risk stratification and individualized selection of adjuvant interventions. Key limitations of the current evidence base—such as heterogeneity in study design, variability in clinical endpoints, and underrepresentation of severe exacerbations—are critically discussed. Conclusion Integrating adjuvant therapies within a biomarker- and phenotype-informed framework represents a promising strategy to accelerate recovery, reduce early readmission, and improve short- and long-term outcomes in patients with acute exacerbations of chronic obstructive pulmonary disease. Well-designed, biomarker-stratified randomized trials are needed to define the optimal selection, timing, and duration of adjuvant interventions.

Diana Shakirova, Adrià Canós Valero, Daniil Riabov et al.

Identifying the handedness of chiral molecules is of fundamental importance in chemistry, biology, pharmacy, and medicine. Nanophotonic structures allow us to control light at the nanoscale and offer powerful tools for chiral sensing, enabling the detection of small analyte volumes and low molecular concentrations by harnessing optical resonances. Most existing strategies rely on intuitive concepts such as strong local field enhancement or large local optical chirality, often achieved by engineering electric and magnetic Mie resonances in dielectric or plasmonic nanostructures. Recent insights, however, reveal that the chiroptical response of resonant systems is governed not only by local field effects, but also by less obvious mechanisms such as modal crosstalk. In this work, we present a dielectric metasurface engineered to amplify the modal crosstalk by supporting two nearly degenerate, high-quality-factor resonant states known as quasi-bound states in the continuum. Our theoretical and numerical analysis predicts a pronounced differential transmittance that exceeds the detection threshold of standard spectrometers. In particular, the differential transmittance reaches up to $10^{-2}$ for the Pasteur parameter $κ= 1\cdot10^{-4}$. These findings advance the capabilities of nanophotonic sensors for chiral detection, paving the way toward ultrasensitive identification of molecular handedness in increasingly smaller volumes and concentrations at the experimentally visible level.

Junyu Liu, Kaiqi Yan, Tianyang Wang et al.

Recent advances in large language models (LLMs) have demonstrated notable performance in medical licensing exams. However, comprehensive evaluation of LLMs across various healthcare roles, particularly in high-stakes clinical scenarios, remains a challenge. Existing benchmarks are typically text-based, English-centric, and focus primarily on medicines, which limits their ability to assess broader healthcare knowledge and multimodal reasoning. To address these gaps, we introduce KokushiMD-10, the first multimodal benchmark constructed from ten Japanese national healthcare licensing exams. This benchmark spans multiple fields, including Medicine, Dentistry, Nursing, Pharmacy, and allied health professions. It contains over 11588 real exam questions, incorporating clinical images and expert-annotated rationales to evaluate both textual and visual reasoning. We benchmark over 30 state-of-the-art LLMs, including GPT-4o, Claude 3.5, and Gemini, across both text and image-based settings. Despite promising results, no model consistently meets passing thresholds across domains, highlighting the ongoing challenges in medical AI. KokushiMD-10 provides a comprehensive and linguistically grounded resource for evaluating and advancing reasoning-centric medical AI across multilingual and multimodal clinical tasks.

Lizzy Farrugia, Lilian M. Azzopardi, Jeremy Debattista et al.

The role of pharmacists is evolving from medicine dispensing to delivering comprehensive pharmaceutical services within multidisciplinary healthcare teams. Central to this shift is access to accurate, up-to-date medicinal product information supported by robust data integration. Leveraging artificial intelligence and semantic technologies, Knowledge Graphs (KGs) uncover hidden relationships and enable data-driven decision-making. This paper presents medicX-KG, a pharmacist-oriented knowledge graph supporting clinical and regulatory decisions. It forms the semantic layer of the broader medicX platform, powering predictive and explainable pharmacy services. medicX-KG integrates data from three sources, including, the British National Formulary (BNF), DrugBank, and the Malta Medicines Authority (MMA) that addresses Malta's regulatory landscape and combines European Medicines Agency alignment with partial UK supply dependence. The KG tackles the absence of a unified national drug repository, reducing pharmacists' reliance on fragmented sources. Its design was informed by interviews with practicing pharmacists to ensure real-world applicability. We detail the KG's construction, including data extraction, ontology design, and semantic mapping. Evaluation demonstrates that medicX-KG effectively supports queries about drug availability, interactions, adverse reactions, and therapeutic classes. Limitations, including missing detailed dosage encoding and real-time updates, are discussed alongside directions for future enhancements.

Pooja Arora, Shinu Singla, B. Radhika et al.

Background: Periodontitis and cardiovascular disease (CVD) are both chronic inflammatory conditions with growing evidence of a potential link. Objective: This study aimed to assess the relationship between periodontitis and cardiovascular disease by evaluating clinical parameters and systemic inflammatory markers. Methods: A cross-sectional observational study was conducted involving 90 patients aged 35–70 years, divided into three groups: Group A (periodontitis with CVD), Group B (periodontitis only), and Group C (CVD only). Periodontal parameters such as probing pocket depth (PPD), clinical attachment loss (CAL), plaque index (PI), and bleeding on probing (BOP) were recorded. Results: Group A showed the most severe periodontal disease (PPD: 5.2 ± 1.1 mm; CAL: 4.8 ± 0.9 mm) and the highest inflammatory marker levels (CRP: 5.8 mg/L; IL-6: 12.5 pg/mL). Significant correlations were found between CAL and CRP (r = 0.62, P = 0.001), PPD and systolic BP (r = 0.47, P = 0.003), and BOP and IL-6 (r = 0.51, P = 0.002). Group A also had poorer oral hygiene practices and a higher prevalence of CAD (80%). Conclusion: It is concluded that periodontitis is significantly associated with cardiovascular disease, primarily through systemic inflammation.

Haojie Wang, Yuanyuan Xie

In recent years, ferroptosis, as an emerging modality of programmed cell death, has captured significant attention within the scientific community. This comprehensive review meticulously canvasses the pertinent literature of the past few years, spanning multiple facets. It delves into the intricate mechanisms underpinning ferroptosis, tracks the evolution of its inducers and inhibitors, and dissects its roles in a diverse array of diseases, as well as the resultant therapeutic implications. A profound exploration is conducted of the functional mechanisms of ferroptosis-related molecules, intracellular pathways, metabolic cascades, and signaling transduction routes. Novel ferroptosis inducers and inhibitors are introduced in detail, covering their design blueprints, synthetic methodologies, and bioactivity profiles. Moreover, an exhaustive account is provided regarding the involvement of ferroptosis in malignancies, neurodegenerative disorders, cardiovascular ailments, and other pathologies. By highlighting the pivotal status and potential therapeutic regimens of ferroptosis in various diseases, this review aspires to furnish a thorough and profound reference framework for future investigations and clinical translations in the ferroptosis domain.

Mona Aljefiri, Mona Alhabsh, Manar Alabbasi et al.

Background: Artificial intelligence (AI) and robotics have gained much attention during the last decade in the medical field, and they will probably affect the practice of the next generation of healthcare providers. Methods: This cross-sectional study used an online questionnaire to assess students’ and faculty’s prior knowledge and perceptions of AI and robotics. It was conducted at King Abdulaziz University, Jeddah. The sample of the present study includes 374 participants. Data was collected, processed, and statistically analyzed using IBM SPSS Statistics Data Editors. The level of statistical significance was assumed to be a P value >0.05, which indicates a non-significant difference. Results: Most participants were healthcare students (87%) aged 18–24 (84%). Overall, both students and faculty were moderately familiar with AI and robotics in medicine (30.7% and 31.3%, respectively). Both students and faculty wanted to incorporate AI and robotics into their medical curriculum (63.2% and 81.2%, respectively). They saw AI as already present in the field of surgery (37.4% and 45.8%, respectively) and further implemented in the same field prospectively, too (38.3% and 52.1%, respectively). Many participants believed that AI would only be integrated into healthcare and operated by a specialist (79%); however, the majority still favored the physician’s opinion over AI (63%). Conclusion: Most healthcare students and faculty recognize the significance of AI and are excited to engage. AI and robotics should be given ample consideration in the education curriculum by enhancing continual training programs for faculty to conduct AI and robotics courses.

Yizhi Zhang, Wan Li, Yihui Yang et al.

Abstract Background Glioblastoma (GBM) is the most common brain tumor with the worst prognosis. Temozolomide is the only first-line drug for GBM. Unfortunately, the resistance issue is a classic problem. Therefore, it is essential to develop new drugs to treat GBM. As an oncogene, Skp2 is involved in the pathogenesis of various cancers including GBM. In this study, we investigated the anticancer effect of AAA237 on human glioblastoma cells and its underlying mechanism. Methods CCK-8 assay was conducted to evaluate IC50 values of AAA237 at 48, and 72 h, respectively. The Cellular Thermal Shift Assay (CETSA) was employed to ascertain the status of Skp2 as an intrinsic target of AAA237 inside the cellular milieu. The EdU-DNA synthesis test, Soft-Agar assay and Matrigel assay were performed to check the suppressive effects of AAA237 on cell growth. To identify the migration and invasion ability of GBM cells, transwell assay was conducted. RT-qPCR and Western Blot were employed to verify the level of BNIP3. The mRFP-GFP-LC3 indicator system was utilized to assess alterations in autophagy flux and investigate the impact of AAA237 on the dynamic fusion process between autophagosomes and lysosomes. To investigate the effect of compound AAA237 on tumor growth in vivo, LN229 cells were injected into the brains of mice in an orthotopic model. Results AAA237 could inhibit the growth of GBM cells in vitro. AAA237 could bind to Skp2 and inhibit Skp2 expression and the degradation of p21 and p27. In a dose-dependent manner, AAA237 demonstrated the ability to inhibit colony formation, migration, and invasion of GBM cells. AAA237 treatment could upregulate BNIP3 as the hub gene and therefore induce BNIP3-dependent autophagy through the mTOR pathway whereas 3-MA can somewhat reverse this process. In vivo, the administration of AAA237 effectively suppressed the development of glioma tumors with no side effects. Conclusion Compound AAA237, a novel Skp2 inhibitor, inhibited colony formation, migration and invasion of GBM cells in a dose-dependent manner and time-dependent manner through upregulating BNIP3 as the hub gene and induced BNIP3-dependent autophagy through the mTOR pathway therefore it might be a viable therapeutic drug for the management of GBM. Graphical Abstract

Patrick Gallegos, Muhammad Salaar Riaz, Michael Peeters

Objective: Leadership discussion, including leadership development programs, is common. However, discussion of followership as a component of leadership seems less frequently discussed. With a focus on leadership and followership, this investigation reviewed the health-professions education literature and characterized leadership-followership within health-professions education. Methods: Using PubMed, ERIC, and Google Scholar, two investigators independently and systematically searched health-professions education literature for articles related to leadership and followership. Reports were categorized based on the articles by type, application, profession, leadership, and followership qualities. Results: Eighty-one articles were included. More than half (48/81, 59%) were theoretical, 27% (22/81) empirical, 7% (6/81) commentaries, and 6% (5/81) letters-to-the-editor). Empirical studies did not share outcomes that could be meaningfully combined quantitatively by meta-analysis; however, the vast majority (96%) of theoretical articles discussed a healthcare-related application of leadership and followership (e.g., improving patient care, improving communication, improving organizational efficiency). Thus, a qualitative review was completed. Of the 81 articles, 57% (n=46) involved multiple professions, while 43% (n=35) focused on a specific profession [Nursing (n=16), Medicine (n=7), Others (n=5) Surgery (n=3), Pharmacy (n=2), Veterinary Medicine (n=2)]. While most articles (75%) discussed leadership qualities (with top qualities of effective communication, visionary, and delegating tasks), fewer (57%) discussed followership qualities (with top qualities of being responsible, committed, and supportive). Of note, some qualities overlapped in both leadership and followership (with top qualities of effective communication, being supportive, and providing/receiving feedback). Conclusions: Leadership-Followership was described in many health-professions’ education literature. However, Pharmacy and Veterinary Medicine had substantially fewer articles published on this topic. Notably, followership did not receive nearly as much attention as leadership. Leadership has a dynamic and complex interaction with followership highlighting that an effective leader must know how to be an effective follower and vice versa. To improve leadership within healthcare teamwork, education should focus on both leadership-followership.  

Vidhya Rekha Umapathy, Bhuminathan Swamikannu, Prabhu Manickam Natarajan et al.

Background: Oral cancer is the sixth most common cancer occurring anywhere in the globe. Cancers of the mouth are caused by tobacco and alcohol overuse, and also between pre-malignancy and full-fledged malignancy. In order to avoid the onset of illness, proper cleanliness of the mouth is important. Objective: In this study we aimed to identify the potential inhibitor for Aurora kinase B as a potential therapeutic target for oral cancer from the phytocompounds from Ocimum sanctum. Methodology: Compounds from Ocimum sanctum were screened against Aurora kinase B using a structure-based virtual screening approach using Pyrx software. Based on the scoring parameters best compounds were chosen to analysis the interaction by using Discovery studio visualizer. Results: Four compounds—pedunculin, nevadensin, chrysoeriol, and genistein were selected as the most promising leads based on the scoring parameter. Conclusion: These chemicals could be potential therapeutic candidates that need to be investigated further in the laboratory.

Mengge Yuan, Kan Wu, Ning Zhao

Automated drug dispensing systems (ADDSs) are increasingly in demand in today's pharmacies, primarily driven by the growing ageing population. Recognizing the practical challenges faced by pharmacies implementing ADDSs, this study aims to optimize the layout design and sequencing issues within a human-machine cooperation environment to enhance the system throughput of ADDSs. Specifically, we develop models for drug retrieval sequencing under different system layout designs, taking into account the stochastic sorting time of pharmacists. The prescription order arrival pattern follows a successive arrival mode. To assess the efficiency of ADDSs with one input/output point and two input/output points, we propose dual command retrieval sequencing models that optimize the retrieval sequence of drugs in adjacent prescription orders. Notably, our models incorporate the stochastic sorting time of pharmacists to analyze its impact on ADDS performance. Through experimental comparisons of average picking times for prescription orders under various operational conditions, we demonstrate that a system layout design incorporating two input/output points significantly enhances the efficiency of prescription order fulfilment within a human-machine cooperation environment. Furthermore, our proposed retrieval sequencing method outperforms dynamic programming, greedy, and random strategies in terms of improving prescription order-picking efficiency. By addressing the layout design and sequencing challenges, our research contributes to the field of intelligent warehousing, particularly in smart pharmacies. The findings provide valuable insights for healthcare facilities and organizations seeking to optimize ADDS performance and enhance drug dispensing efficiency.

Cyril Leven, Pauline Ménard, Isabelle Gouin-Thibault et al.

Apixaban and rivaroxaban have first-line use for many patients needing anticoagulation for venous thromboembolism (VTE). The pharmacokinetics of these drugs in non-obese subjects have been extensively studied, and, while changes in pharmacokinetics have been documented in obese patients, data remain scarce for these anticoagulants. The aim of this study was to perform an external validation of published population pharmacokinetic (PPK) models of apixaban and rivaroxaban in a cohort of obese patients with VTE. A literature search was conducted in the PubMed/MEDLINE, Scopus, and Embase databases following the PRISMA statement. External validation was performed using MonolixSuite software, using prediction-based and simulation-based diagnostics. An external validation dataset from the university hospitals of Brest and Rennes, France, included 116 apixaban pharmacokinetic samples from 69 patients and 121 rivaroxaban samples from 81 patients. Five PPK models of apixaban and 16 models of rivaroxaban were included, according to the inclusion criteria of the study. Two of the apixaban PPK models presented acceptable performances, whereas no rivaroxaban PPK model did. This study identified two published models of apixaban applicable to apixaban in obese patients with VTE. However, none of the rivaroxaban models evaluated were applicable. Dedicated studies appear necessary to elucidate rivaroxaban pharmacokinetics in this population.

Sadegh Rajabi, Maliheh Soodi, Fatemeh Jafari et al.

Background and objectives:  This study evaluated the acute and subacute toxicity of the Coriander Triphala tablet (CTT) in Wistar rats. Methods: The CTT was prepared according to the method described in our previous work. In the acute toxicity study, five female Wistar rats received 2000 mg/kg CTT and five female rats were administered distilled water as control. In the subacute test, sixty male and female rats were randomly divided into six groups. Three groups received 200, 500, and 1000 mg/kg of the tablet; the satellite group was treated with 1000 mg/kg of CTT, and controls received distilled water for 28 days. Body weights and food and water intake of rats were recorded. Toxicity signs were recorded and hematological, biochemical, and histopathological analyses were performed. Results: No remarkable toxic effect of the tablet was observed in the rats after receiving a single dose of 2000 mg/kg. This indicated that the median lethal dose (LD50) was more than 2000 mg/kg. In the subacute toxicity study, different doses of CTT didn’t change hematological parameters. However, the tablet increased the levels of cholesterol, creatinine, and aspartate aminotransferase (AST) in males and alanine aminotransferase (ALT) and AST in females at high doses. Histopathological evaluation of liver samples from both sexes showed congestion and hydropic degeneration of hepatocytes. Renal histopathology revealed varying degrees of tubular cell necrosis. Conclusion: Our data indicated the toxic effects of CTT on the liver and kidney, suggesting the need for special precautions in administration of this medication to the patients.

Mahdieh Eftekhari, Mohammad Sohrabi, Majid Balaei Kahnamoei et al.

Background and objectives: Diploschistes ocellatus (Fr.) Norman is a valuable lichen possessing various biological properties which has been traditionally used by indigenous people in southwest of Iran in the treatment of different disorders. The aim of the current study was to evaluate cytotoxicity of different fractions of D. ocellatus against breast cancer cell lines through MTT assay, as well as lichenochemical analysis of the most potent fraction. Also, ducking study was performed to investigate the isolated compounds-protein interactions. Methods: In this work, aqueous, acetone, chloroform, ethyl acetate, and methanol fractions of D. ocellatus were evaluated against three breast cancer cell lines (MCF-7, T-47D, and MDA-MB-231) via MTT assay. Furthermore, docking was performed using the routine method and default parameters of the AutoDock 4.2 software. Results:  The acetone fraction depicted the most potent cytotoxicity and was candidate for lichenochemical analysis, leading to the isolation and identification of stictic acid and 2-(7'-hydroxy-3,5,6,8-tetramethyl-9-oxooxonan-2-yl) propanoic acid. Docking study of isolated compounds based on the inhibition of survivin, revealed desired interactions with that of amino acid residues. Conclusion: Based on the obtained results, D. ocellatus can be considered as a natural source of biologically active compounds and complementary studies are in high demand.

Matej Mihelčić, Pauli Miettinen

Non-negative Matrix Factorization (NMF) is an intensively used technique for obtaining parts-based, lower dimensional and non-negative representation. Researchers in biology, medicine, pharmacy and other fields often prefer NMF over other dimensionality reduction approaches (such as PCA) because the non-negativity of the approach naturally fits the characteristics of the domain problem and its results are easier to analyze and understand. Despite these advantages, obtaining exact characterization and interpretation of the NMF's latent factors can still be difficult due to their numerical nature. Rule-based approaches, such as rule mining, conceptual clustering, subgroup discovery and redescription mining, are often considered more interpretable but lack lower-dimensional representation of the data. We present a version of the NMF approach that merges rule-based descriptions with advantages of part-based representation offered by the NMF. Given the numerical input data with non-negative entries and a set of rules with high entity coverage, the approach creates the lower-dimensional non-negative representation of the input data in such a way that its factors are described by the appropriate subset of the input rules. In addition to revealing important attributes for latent factors, their interaction and value ranges, this approach allows performing focused embedding potentially using multiple overlapping target labels.

Qiyuan Chen, Raed Al Kontar, Maher Nouiehed et al.

Cost-sensitive classification is critical in applications where misclassification errors widely vary in cost. However, over-parameterization poses fundamental challenges to the cost-sensitive modeling of deep neural networks (DNNs). The ability of a DNN to fully interpolate a training dataset can render a DNN, evaluated purely on the training set, ineffective in distinguishing a cost-sensitive solution from its overall accuracy maximization counterpart. This necessitates rethinking cost-sensitive classification in DNNs. To address this challenge, this paper proposes a cost-sensitive adversarial data augmentation (CSADA) framework to make over-parameterized models cost-sensitive. The overarching idea is to generate targeted adversarial examples that push the decision boundary in cost-aware directions. These targeted adversarial samples are generated by maximizing the probability of critical misclassifications and used to train a model with more conservative decisions on costly pairs. Experiments on well-known datasets and a pharmacy medication image (PMI) dataset made publicly available show that our method can effectively minimize the overall cost and reduce critical errors, while achieving comparable performance in terms of overall accuracy.

Kapil Kumar Nagwanshi

The human footprint is having a unique set of ridges unmatched by any other human being, and therefore it can be used in different identity documents for example birth certificate, Indian biometric identification system AADHAR card, driving license, PAN card, and passport. There are many instances of the crime scene where an accused must walk around and left the footwear impressions as well as barefoot prints and therefore, it is very crucial to recovering the footprints from identifying the criminals. Footprint-based biometric is a considerably newer technique for personal identification. Fingerprints, retina, iris and face recognition are the methods most useful for attendance record of the person. This time the world is facing the problem of global terrorism. It is challenging to identify the terrorist because they are living as regular as the citizens do. Their soft target includes the industries of special interests such as defence, silicon and nanotechnology chip manufacturing units, pharmacy sectors. They pretend themselves as religious persons, so temples and other holy places, even in markets is in their targets. These are the places where one can obtain their footprints quickly. The gait itself is sufficient to predict the behaviour of the suspects. The present research is driven to identify the usefulness of footprint and gait as an alternative to personal identification.

Maria Grazia Ferraro, Marialuisa Piccolo, Gabriella Misso et al.

Countless expectations converge in the multidisciplinary endeavour for the search and development of effective and safe drugs in fighting cancer. Although they still embody a minority of the pharmacological agents currently in clinical use, metal-based complexes have great yet unexplored potential, which probably hides forthcoming anticancer drugs. Following the historical success of cisplatin and congeners, but also taking advantage of conventional chemotherapy limitations that emerged with applications in the clinic, the design and development of non-platinum metal-based chemotherapeutics, either as drugs or prodrugs, represents a rapidly evolving field wherein candidate compounds can be fine-tuned to access interactions with druggable biological targets. Moving in this direction, over the last few decades platinum family metals, e.g., ruthenium and palladium, have been largely proposed. Indeed, transition metals and molecular platforms where they originate are endowed with unique chemical and biological features based on, but not limited to, redox activity and coordination geometries, as well as ligand selection (including their inherent reactivity and bioactivity). Herein, current applications and progress in metal-based chemoth are reviewed. Converging on the recent literature, new attractive chemotherapeutics based on transition metals other than platinum—and their bioactivity and mechanisms of action—are examined and discussed. A special focus is committed to anticancer agents based on ruthenium, palladium, rhodium, and iridium, but also to gold derivatives, for which more experimental data are nowadays available. Next to platinum-based agents, ruthenium-based candidate drugs were the first to reach the stage of clinical evaluation in humans, opening new scenarios for the development of alternative chemotherapeutic options to treat cancer.

Ambra Di Piano, Andrea Bulgarelli, Valentina Fioretti et al.

The Cherenkov Telescope Array (CTA) will be the next generation ground-based observatory for very-high-energy (VHE) gamma-ray astronomy, with the deployment of tens of highly sensitive and fast-reacting Cherenkov telescopes. It will cover a wide energy range (20 GeV - 300 TeV) with unprecedented sensitivity. To maximize the scientific return, the observatory will be provided with an online software system that will perform the first analysis of scientific data in real-time. This study investigates the precision and accuracy of available science tools and analysis techniques for the short-term detection of gamma-ray sources, in terms of sky localization, detection significance and, if significant detection is achieved, a first estimation of the integral photon flux. The scope is to evaluate the feasibility of the algorithms' implementation in the real-time analysis of CTA. In this contribution we present a general overview of the methods and some of the results for the test case of the short-term detection of a gamma-ray burst afterglow, as the VHE counterpart of a gravitational wave event.

Elena Lietta, Alessandro Pieri, Elisa Innocenti et al.

Chromatography is a widely used separation process for purification of biopharmaceuticals that is able to obtain high purities and concentrations. The phenomena that occur during separation, mass transfer and adsorption are quite complex. To better understand these phenomena and their mechanisms, multi-component adsorption isotherms must be investigated. High-throughput methodologies are a very powerful tool to determine adsorption isotherms and they waste very small amounts of sample and chemicals, but the quantification of component concentrations is a real bottleneck in multi-component isotherm determination. The behavior of bovine serum albumin, <i>Corynebacterium diphtheriae</i> CRM₁₉₇ protein and lysozyme, selected as model proteins in binary mixtures with hydrophobic resin, is investigated here. In this work we propose a new method for determining multi-component adsorption isotherms using high-throughput experiments with filter plates, by exploiting microfluidic capillary electrophoresis. The precision and accuracy of the microfluidic capillary electrophoresis platform were evaluated in order to assess the procedure; they were both found to be high and the procedure is thus reliable in determining adsorption isotherms for binary mixtures. Multi-component adsorption isotherms were determined with a totally high-throughput procedure that turned out to be a very fast and powerful tool. The same procedure can be applied to every kind of high-throughput screening.