Sci Adv. 2025 Feb 28;11(9):eadr1938. doi: 10.1126/sciadv.adr1938. Epub 2025 Feb 28.

ABSTRACT

The Parkinson's disease-linked kinase, PINK1, is a short-lived protein that undergoes cleavage upon mitochondrial import leading to its proteasomal degradation. Under depolarizing conditions, it accumulates on mitochondria where it becomes activated, phosphorylating both ubiquitin and the ubiquitin E3 ligase Parkin, at Ser65. Our experiments reveal that in retinal pigment epithelial cells, only a fraction of PINK1 becomes stabilized after depolarization by electron transport chain inhibitors. Furthermore, the observed accrual of PINK1 cannot be completely accounted for without an accompanying increase in biosynthesis. We have used a ubiquitylation inhibitor TAK-243 to accumulate cleaved PINK1. Under these conditions, generation of unconjugated "free" phospho-ubiquitin serves as a proxy readout for PINK1 activity. This has enabled us to find a preconditioning phenomenon, whereby an initial depolarizing treatment leaves a residual pool of active PINK1 that remains competent to seed the activation of nascent cleaved PINK1 following a 16-hour recovery period.

PMID:40020067 | DOI:10.1126/sciadv.adr1938

Inflammopharmacology. 2025 Feb 28. doi: 10.1007/s10787-025-01682-5. Online ahead of print.

ABSTRACT

Resistant strains of Plasmodium spp. pose a great threat to healthcare. Drug repurposing is a smart, and an effective way to look for new alternatives for different ailments including malaria. Protein tyrosine kinases (PTKs) play a crucial role in growth, maturation as well as differentiation of Plasmodium and this study explores antimalarial activity of PTKs inhibitor gefitinib using in silico and experimental approaches. The drug showed considerable inhibitory activity against P. falciparum 3D7 (IC50 0.49 µg/mL) and RKL-9 (IC50 0.83 µg/mL) strains. Isobologram analysis revealed substantial synergism between gefitinib and artesunate. Gefitinib illustrated highest negative D-score towards phosphoethanolamine methyltransferase followed by PfPK5 and CDPK1. Its acute toxicity was 4 g/kg. Gefitinib (100 mg/kg) exhibited a dose-dependent curative activity against P. berghei with 91.09% chemo-suppression and the combination of gefitinib 100 mg/kg and AS 50 mg/kg exhibited complete parasite clearance with no recrudescence which was also evidenced by cytokine analysis, biochemical as well as histopathological studies. At length, gefitinib illustrated considerable antiplasmodial action by targeting phosphoethanolamine methyltransferase, PfPK5 and CDPK1. The combination of gefitinib (100 mg/kg) and AS (50 mg/kg) holds promise for malaria treatment. Further, research is being done to evaluate its pharmacokinetic properties.

PMID:40019687 | DOI:10.1007/s10787-025-01682-5

JMIR Med Inform. 2025 Feb 28;13:e67984. doi: 10.2196/67984.

ABSTRACT

BACKGROUND: The digitalization of health care has increased the demand for efficient data exchange, emphasizing semantic interoperability. SNOMED Clinical Terms (SNOMED CT), a comprehensive terminology with over 360,000 medical concepts, supports this need. However, it cannot cover all medical scenarios, particularly in complex cases. To address this, SNOMED CT allows postcoordination, where users combine precoordinated concepts with new expressions. Despite SNOMED CT's potential, the creation and validation of postcoordinated expressions (PCEs) remain challenging due to complex syntactic and semantic rules.

OBJECTIVE: This work aims to develop a tool that validates postcoordinated SNOMED CT expressions, focusing on providing users with detailed, automated correction instructions for syntactic and semantic errors. The goal is not just validation, but also offering user-friendly, actionable suggestions for improving PCEs.

METHODS: A tool was created using the Fast Healthcare Interoperability Resource (FHIR) service $validate-code and the terminology server Ontoserver to check the correctness of PCEs. When errors are detected, the tool processes the SNOMED CT Concept Model in JSON format and applies predefined error categories. For each error type, specific correction suggestions are generated and displayed to users. The key added value of the tool is in generating specific correction suggestions for each identified error, which are displayed to the users. The tool was integrated into a web application, where users can validate individual PCEs or bulk-upload files. The tool was tested with real existing PCEs, which were used as input and validated. In the event of errors, appropriate error messages were generated as output.

RESULTS: In the validation of 136 PCEs from 304 FHIR Questionnaires, 18 (13.2%) PCEs were invalid, with the most common errors being invalid attribute values. Additionally, 868 OncoTree codes were evaluated, resulting in 161 (20.9%) PCEs containing inactive concepts, which were successfully replaced with valid alternatives. A user survey reflects a favorable evaluation of the tool's functionality. Participants found the error categorization and correction suggestions to be precise, offering clear guidance for addressing issues. However, there is potential for enhancement, particularly regarding the level of detail in the error messages.

CONCLUSIONS: The validation tool significantly improves the accuracy of postcoordinated SNOMED CT expressions by not only identifying errors but also offering detailed correction instructions. This approach supports health care professionals in ensuring that their PCEs are syntactically and semantically valid, enhancing data quality and interoperability across systems.

PMID:40019788 | DOI:10.2196/67984

Eur J Clin Pharmacol. 2025 Feb 28. doi: 10.1007/s00228-025-03816-8. Online ahead of print.

ABSTRACT

PURPOSE: Although already a lot of research has been done on pharmacogenetic tests to inform the choice and/or dosing of medicines, the implementation and clinical uptake remain limited. This study assessed the implementation of pharmacogenetic (PGx) testing on a national scale by analyzing access to and volumes of reimbursed PGx.

METHODS: The use of pharmacogenetic tests was examined via a cross-sectional online survey among the Belgian laboratories, collecting data on PGx targets, testing volumes and technologies used. The focus was on reimbursed tests. Additional data were sourced from the national reimbursement database to describe uptake of testing per medication.

RESULTS: The uptake of PGx testing in Belgium varied by medication, with significant implementation for fluoropyrimidines, abacavir, and thiopurines. DPYD gene testing was the most frequently performed PGx test, due to endorsed (inter)national guidelines. Reimbursement rules shape access to PGx, with the majority of PGx tests performed in dedicated centers for human genetics (CHG). Access to HLA laboratories for HLA targets was not optimal and some laboratories without a CHG also included constitutional PGx targets in somatic oncology panels.

CONCLUSION: This nationwide study demonstrates that in a country where the prescribers have access to a relatively extensive list of reimbursable PGx tests, the implementation of PGx testing is shaped by the presence of endorsed evidence-based clinical practice guidelines, as well as organizational and logistical factors.

PMID:40019504 | DOI:10.1007/s00228-025-03816-8

Pediatr Pulmonol. 2025 Mar;60(3):e71021. doi: 10.1002/ppul.71021.

ABSTRACT

BACKGROUND: People with CF (pwCF) frequently have gastrointestinal symptoms (GI), including abdominal pain and irregular bowel movements. These are often embarrassing, difficult to report, and frequently missed. Thus, a GI Symptom Tracker was created and validated in the USA and translated and validated in Dutch. This questionnaire consists of four subscales: Eating Challenges, Stools, Adherence Challenges, and Abdominal Symptoms. The aim of this study was to investigate the relationship between GI symptoms, anxiety/depression, and health-related quality of life (HRQoL) in Dutch pwCF.

METHODS: In this prospective, cross-sectional single-center pilot study, pwCF completed the Dutch GI Symptom Tracker, GAD-7 (anxiety), PHQ-9 (depression), and CFQ-R (HRQoL) from September 2021 to June 2022. Regression analyses were used to analyze the univariable associations between GI symptoms, anxiety/depression, and HRQoL.

RESULTS: A total of 51 pwCF were enrolled consecutively (n = 41 adults, 66% female, mean age (y) [range] = 32.7 [19-71] and n = 10 adolescents, 70% female, mean age (y) [range] = 14.2 [12-17]). Elevated levels of anxiety (scores ≥ 10 on GAD-7) were found in 17% of adults and 0% of adolescents. Elevated depression scores (≥ 10 on PHQ-9) were found in 9% of adults and 20% of adolescents. GI scales "Abdominal Symptoms" and "Stools" were significantly, positively associated with elevated symptoms of anxiety and depression. Most GI scales were associated with lower HRQoL.

CONCLUSION: This is the first study investigating the link between GI symptoms assessed by the Dutch GI Symptom Tracker and anxiety/depression and HRQoL in Dutch pwCF. More GI symptoms were associated with higher anxiety and depression scores and worse HRQoL. Additional research is needed to better understand how mental and physical health are linked in GI symptoms in CF.

PMID:40019138 | DOI:10.1002/ppul.71021

Pediatr Pulmonol. 2025 Mar;60(3):e71017. doi: 10.1002/ppul.71017.

ABSTRACT

BACKGROUND: Substance use has increased among people with CF (pwCF), yet communication about use remains understudied between pwCF and their healthcare providers.

OBJECTIVE: Investigate pwCF's perceptions regarding their healthcare team's discussions surrounding substance use, comfort level discussing such usage, and barriers encountered during these discussions.

METHODS: This cross-sectional study used a one-time electronic survey to assess communication regarding substance use between pwCF aged 13 years and older and their CF healthcare team.

RESULTS: Of 226 participants, 74% (n = 167) reported being asked about marijuana, 57% (n = 128) about CBD, 70% (n = 150) about e-cigarettes, and 88% (n = 189) about cigarettes by their CF healthcare team. Fewer providers discussed the risks and benefits of each substance: 47% (n = 107) for marijuana, 40% (n = 90) for CBD, 44% (n = 99) for e-cigarettes, and 61% (n = 138) for cigarettes. Provider knowledge was rated higher for cigarettes and e-cigarettes compared to marijuana and CBD. Most participants felt comfortable discussing substance use, though a minority expressed discomfort, mainly due to concerns about documentation in medical records and perceived lack of support.

CONCLUSION: This study highlights variability in communication between pwCF and their healthcare teams regarding substance use, particularly when it comes to marijuana and CBD. The findings suggest a need for standardized guidelines and educational resources to improve recreational substance screening and discussion in CF clinical care, especially given the changing landscape of marijuana regulations and increasing use among pwCF.

PMID:40019020 | DOI:10.1002/ppul.71017

Pediatr Pulmonol. 2025 Mar;60(3):e71019. doi: 10.1002/ppul.71019.

ABSTRACT

RATIONALE: The introduction of elexacaftor/tezacaftor/ivacaftor (ETI), a highly effective cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapy, to younger ages and the COVID-19 pandemic have significantly reduced pulmonary exacerbations requiring hospitalization among children with CF.

OBJECTIVE: To assess demographic and clinical characteristics of children and young adults with CF hospitalized for pulmonary exacerbations before and after pediatric ETI approval.

METHODS: A retrospective chart review was conducted at five United States CF Foundation-accredited care centers. Hospitalization data from children and young adults with CF in 2018 and 2022 were analyzed.

RESULTS: Hospitalizations decreased from 471 cases (241 individuals) in 2018 to 163 cases (110 individuals) in 2022. The racial distribution shifted, with more hospitalized patients identifying as people of color in 2022 (28% vs. 14%; p = 0.018). A greater proportion of hospitalized children in 2022 had two non-F508del mutations compared with children hospitalized in 2018 (38% vs. 19%) and were less likely to be infected with methicillin-resistant Staphylococcus aureus (MRSA). Comparing 2022-2018, children on CFTR modulator therapy, including ETI (76%), showed reduced infections with Pseudomonas aeruginosa and Achromobacter xylosoxidans.

CONCLUSIONS: The decline in hospitalizations for pulmonary exacerbations likely reflects the benefits of ETI therapy, as a higher proportion of children and young adults hospitalized in 2022 had two non-F508del mutations and were not eligible for ETI. A greater percentage of those hospitalized in 2022 identified as belonging to minority racial groups, highlighting ongoing health disparities in the ETI era. Additionally, there were notable changes in the microbiological characteristics between 2018 and 2022.

PMID:40018992 | DOI:10.1002/ppul.71019

Front Biosci (Landmark Ed). 2025 Jan 24;30(2):25765. doi: 10.31083/FBL25765.

ABSTRACT

BACKGROUND: A number of association studies have linked ribosomal DNA gene copy number (rDNA CN) to aging and pathology. Data from these studies are contradictory and depend on the quantitative method.

METHODS: The hybridization technique was used for rDNA quantification in human cells. We determined the rDNA CN from healthy controls (HCs) and patients with schizophrenia (SZ) or cystic fibrosis (CF) (total number of subjects N = 1124). For the first time, rDNA CN was quantified in 105 long livers (90-101 years old). In addition, we conducted a joint analysis of the data obtained in this work and previously published by our group (total, N = 3264).

RESULTS: We found increased rDNA CN in the SZ group (534 ± 108, N = 1489) and CF group (567 ± 100, N = 322) and reduced rDNA CN in patients with mild cognitive impairment (330 ± 60, N = 93) compared with the HC group (422 ± 104, N = 1360). For the SZ, CF, and HC groups, there was a decreased range of rDNA CN variation in older age subgroups compared to child subgroups. For 311 patients with SZ or CF, rDNA CN was determined two or three times, with an interval of months to several years. Only 1.2% of patients demonstrated a decrease in rDNA CN over time. We did not find significant rDNA CN variation in eight different organs of the same patient or in cells of the same fibroblast population.

CONCLUSIONS: The results suggest that rDNA CN is a relatively stable quantitative genetic trait statistically associated with some diseases, which however, can change in rare cases under conditions of chronic oxidative stress. We believe that age- and disease-related differences between the groups in mean rDNA CN and its variance are caused by the biased elimination of carriers of marginal (predominantly low) rDNA CN values.

PMID:40018927 | DOI:10.31083/FBL25765

Interdiscip Sci. 2025 Feb 28. doi: 10.1007/s12539-025-00697-4. Online ahead of print.

ABSTRACT

The discovery and development of novel pharmaceutical agents is characterized by high costs, lengthy timelines, and significant safety concerns. Traditional drug discovery involves pharmacologists manually screening drug molecules against protein targets, focusing on binding within protein cavities. However, this manual process is slow and inherently limited. Given these constraints, the use of deep learning techniques to predict drug-target interaction (DTI) affinities is both significant and promising for future applications. This paper introduces an innovative deep learning architecture designed to enhance the prediction of DTI affinities. The model ingeniously combines graph neural networks, pre-trained large-scale protein models, and attention mechanisms to improve performance. In this framework, molecular structures are represented as graphs and processed through graph neural networks and multiscale convolutional networks to facilitate feature extraction. Simultaneously, protein sequences are encoded using pre-trained ESM-2 large models and processed with bidirectional long short-term memory networks. Subsequently, the molecular and protein embeddings derived from these processes are integrated within a fusion module to compute affinity scores. Experimental results demonstrate that our proposed model outperforms existing methods on two publicly available datasets.

PMID:40019659 | DOI:10.1007/s12539-025-00697-4

Int J Legal Med. 2025 Feb 28. doi: 10.1007/s00414-025-03447-9. Online ahead of print.

ABSTRACT

Estimating the postmortem interval (PMI) is a critical yet complex task in forensic investigations, with accurate and timely determination playing a key role in case resolution and legal outcomes. Traditional methods often suffer from environmental variability and subjective biases, emphasizing the need for more reliable and objective approaches. In this study, we present a novel predictive model for PMI estimation, introduced here for the first time, that leverages pathological tissue images and artificial intelligence (AI). The model is designed to perform under three temperature conditions: 25 °C, 37 °C, and 4 °C. Using a ResNet50 neural network, patch-level images were analyzed to extract deep learning-derived features, which were integrated with machine learning algorithms for whole slide image (WSI) classification. The model achieved strong performance, with micro and macro AUC values of at least 0.949 at the patch-level and 0.800 at the WSI-level in both training and testing sets. In external validation, micro and macro AUC values at the patch-level exceeded 0.960. These results highlight the potential of AI to improve the accuracy and efficiency of PMI estimation. As AI technology continues to advance, this approach holds promise for enhancing forensic investigations and supporting more precise case resolutions.

PMID:40019556 | DOI:10.1007/s00414-025-03447-9

Eur Arch Otorhinolaryngol. 2025 Feb 17. doi: 10.1007/s00405-025-09272-5. Online ahead of print.

ABSTRACT

PURPOSE: This study aims to perform a bibliometric analysis of scientific research on the use of artificial intelligence (AI) in the field of Otorhinolaryngology (ORL), with a specific focus on identifying emerging AI trend topics within this discipline.

METHODS: A total of 498 articles on AI in ORL, published between 1982 and 2024, were retrieved from the Web of Science database. Various bibliometric techniques, including trend keyword analysis and factor analysis, were applied to analyze the data.

RESULTS: The most prolific journal was the European Archives of Oto-Rhino-Laryngology (n = 67). The USA (n = 200) and China (n = 61) were the most productive countries in AI-related ORL research. The most productive institutions were Harvard University / Harvard Medical School (n = 71). The leading authors in this field were Lechien JR. (n = 18) and Rameau A. (n = 17). The most frequently used keywords in the AI research were cochlear implant, head and neck cancer, magnetic resonance imaging (MRI), hearing loss, patient education, diagnosis, radiomics, surgery, hearing aids, laryngology ve otitis media. Recent trends in otorhinolaryngology research reflect a dynamic focus, progressing from hearing-related technologies such as hearing aids and cochlear implants in earlier years, to diagnostic innovations like audiometry, psychoacoustics, and narrow band imaging. The emphasis has recently shifted toward advanced applications of MRI, radiomics, and computed tomography (CT) for conditions such as head and neck cancer, chronic rhinosinusitis, laryngology, and otitis media. Additionally, increasing attention has been given to patient education, quality of life, and prognosis, underscoring a holistic approach to diagnosis, surgery, and treatment in otorhinolaryngology.

CONCLUSION: AI has significantly impacted the field of ORL, especially in diagnostic imaging and therapeutic planning. With advancements in MRI and CT-based technologies, AI has proven to enhance disease detection and management. The future of AI in ORL suggests a promising path toward improving clinical decision-making, patient care, and healthcare efficiency.

PMID:40019544 | DOI:10.1007/s00405-025-09272-5

ACS Appl Mater Interfaces. 2025 Feb 28. doi: 10.1021/acsami.4c17680. Online ahead of print.

ABSTRACT

The continuous global effort to predict material properties through artificial intelligence has predominantly focused on utilizing material stoichiometry or structures in deep learning models. This study aims to predict material properties using electrochemical impedance data, along with frequency and time parameters, that can be obtained during processing stages. The target material, silica aerogel, is widely recognized for its lightweight structure and excellent insulating properties, which are attributed to its large surface area and pore size. However, production is often delayed due to the prolonged aging process. Real-time prediction of material properties during processing can significantly enhance process optimization and monitoring. In this study, we developed a system to predict the physical properties of silica aerogel, specifically pore diameter, pore volume, and surface area. This system integrates a 3 × 3 array Pd/Au sensor, which exhibits high sensitivity to varying pH levels during aerogel synthesis and is capable of acquiring a large data set (impedance, frequency, time) in real-time. The collected data is then processed through a deep neural network algorithm. Because the system is trained with data obtained during the processing stage, it enables real-time predictions of the critical properties of silica aerogel, thus facilitating process optimization and monitoring. The final performance evaluation demonstrated an optimal alignment between true and predicted values for silica aerogel properties, with a mean absolute percentage error of approximately 0.9%. This approach holds great promise for significantly improving the efficiency and effectiveness of silica aerogel production by providing accurate real-time predictions.

PMID:40019213 | DOI:10.1021/acsami.4c17680

Am J Primatol. 2025 Mar;87(3):e70013. doi: 10.1002/ajp.70013.

ABSTRACT

Facial gestures are a crucial component of primate multimodal communication. However, current methodologies for extracting facial data from video recordings are labor-intensive and prone to human subjectivity. Although automatic tools for this task are still in their infancy, deep learning techniques are revolutionizing animal behavior research. This study explores the distinctiveness of facial gestures in cotton-top tamarins, quantified using markerless pose estimation algorithms. From footage of captive individuals, we extracted and manually labeled frames to develop a model that can recognize a custom set of landmarks positioned on the face of the target species. The trained model predicted landmark positions and subsequently transformed them into distance matrices representing landmarks' spatial distributions within each frame. We employed three competitive machine learning classifiers to assess the ability to automatically discriminate facial configurations that cooccur with vocal emissions and are associated with different behavioral contexts. Initial analysis showed correct classification rates exceeding 80%, suggesting that voiced facial configurations are highly distinctive from unvoiced ones. Our findings also demonstrated varying context specificity of facial gestures, with the highest classification accuracy observed during yawning, social activity, and resting. This study highlights the potential of markerless pose estimation for advancing the study of primate multimodal communication, even in challenging species such as cotton-top tamarins. The ability to automatically distinguish facial gestures in different behavioral contexts represents a critical step in developing automated tools for extracting behavioral cues from raw video data.

PMID:40019116 | DOI:10.1002/ajp.70013

Am J Primatol. 2025 Mar;87(3):e70013. doi: 10.1002/ajp.70013.

ABSTRACT

Facial gestures are a crucial component of primate multimodal communication. However, current methodologies for extracting facial data from video recordings are labor-intensive and prone to human subjectivity. Although automatic tools for this task are still in their infancy, deep learning techniques are revolutionizing animal behavior research. This study explores the distinctiveness of facial gestures in cotton-top tamarins, quantified using markerless pose estimation algorithms. From footage of captive individuals, we extracted and manually labeled frames to develop a model that can recognize a custom set of landmarks positioned on the face of the target species. The trained model predicted landmark positions and subsequently transformed them into distance matrices representing landmarks' spatial distributions within each frame. We employed three competitive machine learning classifiers to assess the ability to automatically discriminate facial configurations that cooccur with vocal emissions and are associated with different behavioral contexts. Initial analysis showed correct classification rates exceeding 80%, suggesting that voiced facial configurations are highly distinctive from unvoiced ones. Our findings also demonstrated varying context specificity of facial gestures, with the highest classification accuracy observed during yawning, social activity, and resting. This study highlights the potential of markerless pose estimation for advancing the study of primate multimodal communication, even in challenging species such as cotton-top tamarins. The ability to automatically distinguish facial gestures in different behavioral contexts represents a critical step in developing automated tools for extracting behavioral cues from raw video data.

PMID:40019116 | DOI:10.1002/ajp.70013

Am J Physiol Cell Physiol. 2025 Feb 28. doi: 10.1152/ajpcell.00308.2024. Online ahead of print.

ABSTRACT

Skeletal muscle microtissues are engineered to develop therapies for restoring muscle function in patients. However, optimal electrical field stimulation (EFS) parameters to evaluate the function of muscle microtissues remain unestablished. This study reports a protocol to optimize EFS parameters for eliciting contractile force of muscle microtissues cultured in micropost platforms. Muscle microtissues were produced across an opposing pair of microposts in polydimethylsiloxane and polymethyl methacrylate culture platforms using primary, immortalized, and induced pluripotent stem cell-derived myoblasts. In response to EFS between needle electrodes, contraction deflects microposts proportional to developed force. At 5 V, pulse durations used for native muscle (0.1-1 ms) failed to elicit contraction of microtissues; durations reported for engineered muscle (5-10 ms) failed to elicit peak force. Instead, pulse durations of 20-80 ms were required to elicit peak twitch force across microtissues derived from 5 myoblast lines. Similarly, while peak tetanic force occurs at 20-50 Hz for native human muscles, it varied across microtissues depending on the cell line type, ranging from 7-60 Hz. A new parameter, the dynamic oscillation of force, captured trends during rhythmic contractions, while quantifying the duration-at-peak force provides an extended kinetics parameter. Our findings indicate that muscle microtissues have cell line type-specific contractile properties, yet all contract and relax more slowly than native muscle, implicating underdeveloped excitation-contraction coupling. Failure to optimize EFS parameters can mask the functional potential of muscle microtissues by underestimating force production. Optimizing and reporting EFS parameters and metrics is necessary to leverage muscle microtissues for advancing skeletal muscle therapies.

PMID:40019026 | DOI:10.1152/ajpcell.00308.2024

Clin Exp Rheumatol. 2025 Feb;43(2):309-315. doi: 10.55563/clinexprheumatol/dyjcsn. Epub 2025 Feb 26.

ABSTRACT

OBJECTIVES: This paper aims to provide insight into the challenges and opportunities of conducting an investigator-led, international, multicentre clinical trial for Inclusion Body Myositis (IBM), a rare inflammatory myopathy.

METHODS: An international, multicentre, randomised, controlled trial of a repurposed drug (sirolimus) was initiated based on promising results from a mono-centric pilot study. The progress of the trial was analysed to identify key challenges encountered and solutions developed.

RESULTS: This large, collaborative study has presented a mosaic of challenges and opportunities, many ubiquitous with investigator-led trials. Key challenges have included securing adequate funding, coordinating manufacture of placebo, negotiating international contracts, managing limited study budgets and delays linked to the COVID-19 pandemic. Alongside these challenges, the study team have found opportunities for creative and effective solutions, including the flexibility of building study databases, optimising digital data capture and harnessing patient involvement.

CONCLUSIONS: Instrumental to the progress of the trial has been the collaboration between site teams, patient partnership and adaptability.

PMID:40018747 | DOI:10.55563/clinexprheumatol/dyjcsn

In Silico Pharmacol. 2025 Feb 25;13(1):35. doi: 10.1007/s40203-025-00314-8. eCollection 2025.

ABSTRACT

The primary objective of this study is to harness computer-aided drug repurposing (CADR) techniques to identify existing FDA-approved drugs that can potentially disrupt the assembly of the Hepatitis B Virus (HBV) core protein (HBcAg), an essential process in the virus's life cycle. By targeting this critical step, our study aims to expand the repertoire of therapeutic options for managing chronic Hepatitis B infection, a major global health challenge. Utilizing a combination of computational methods, including the CavityPlus server for ability to analyze druggable protein cavities and extract pharmacophore features and LigandScout for pharmacophore-based virtual screening of a vast library of FDA-approved drugs was conducted. Molecular dynamic simulation (MDS) was employed to evaluate the stability of HBcAg, complexed with Heteroaryldihydropyrimidine (HAP) and statins exhibiting particularly strong binding energies and conformational compatibility. Our approach focused on identifying pharmacophore features that align with known HBcAg inhibitors. The study identified several promising candidates, including Ciclopirox olamine, Voriconazole, Enasidenib, and statins, demonstrating potential interactions with HBc protein residues. Molecular docking further validated these interactions. The significance of these findings lies in their potential to offer new, effective therapeutic strategies for HBV treatment, particularly as alternatives to current therapies that often suffer from issues of viral resistance and adverse side effects. MDS analysis verified the robustness of HAP and statins by showing a high level of binding energies and compatibility with HBcAg. Our results provide a foundation for further experimental validation and underscore the utility of computer-aided drug repurposing as a rapid, cost-effective approach to drug discovery in antiviral research. This study contributes to our understanding of HBV biology and opens avenues for developing novel anti-HBV therapies based on repurposed drugs. The highlighted compound may also enhance the challenges of drug resistance when used as a combination therapy.

PMID:40018383 | PMC:PMC11861453 | DOI:10.1007/s40203-025-00314-8

Clin Exp Rheumatol. 2025 Feb;43(2):309-315. doi: 10.55563/clinexprheumatol/dyjcsn. Epub 2025 Feb 26.

ABSTRACT

OBJECTIVES: This paper aims to provide insight into the challenges and opportunities of conducting an investigator-led, international, multicentre clinical trial for Inclusion Body Myositis (IBM), a rare inflammatory myopathy.

METHODS: An international, multicentre, randomised, controlled trial of a repurposed drug (sirolimus) was initiated based on promising results from a mono-centric pilot study. The progress of the trial was analysed to identify key challenges encountered and solutions developed.

RESULTS: This large, collaborative study has presented a mosaic of challenges and opportunities, many ubiquitous with investigator-led trials. Key challenges have included securing adequate funding, coordinating manufacture of placebo, negotiating international contracts, managing limited study budgets and delays linked to the COVID-19 pandemic. Alongside these challenges, the study team have found opportunities for creative and effective solutions, including the flexibility of building study databases, optimising digital data capture and harnessing patient involvement.

CONCLUSIONS: Instrumental to the progress of the trial has been the collaboration between site teams, patient partnership and adaptability.

PMID:40018747 | DOI:10.55563/clinexprheumatol/dyjcsn

Pharmacogenomics. 2025 Feb 28:1-12. doi: 10.1080/14622416.2025.2470613. Online ahead of print.

ABSTRACT

Posttransplantation diabetes mellitus (PTDM) is a form of diabetes developed after solid organ or stem cell transplantation. This condition shares physiopathological traits with type 2 diabetes, including insulin resistance and β-cells dysfunction and its prevalence varies significantly based on the diagnostic criteria used. Immunosuppressive drugs directly contribute to PTDM risk through intricate impacts on glucose regulation, insulin secretion, and inflammation. In addition, modifiable and non-modifiable environmental risk factors are associated with the onset of this condition. This review aims to provide a comprehensive overview of the multifactorial nature of PTDM in order to highlight candidate genes and variants for pharmacogenetic research. An extensive literature search was conducted to identify studies on pharmacological and genetic factors influencing PTDM development. This review stresses the importance of understanding these interactions for improving PTDM management and underscores the need for further research to refine preventive approaches, ultimately enhancing patient outcomes post-transplantation.

PMID:40017426 | DOI:10.1080/14622416.2025.2470613

Pediatr Emerg Care. 2025 Feb 28. doi: 10.1097/PEC.0000000000003360. Online ahead of print.

ABSTRACT

OBJECTIVES: This study aims to evaluate patient characteristics associated with bronchodilator (BD) use at various stages of bronchiolitis illness and evaluate corresponding patient outcomes in the emergency department (ED).

METHODS: This retrospective, cross-sectional study involves secondary data analysis from a sample of 932 children ages 3 to 24 months who received a diagnosis of bronchiolitis during an ED visit (1057 cases). Predictor variables included demographics, past medical history, family history, physical findings, medication use, and disposition. Outcomes included BD use for bronchiolitis symptoms in the pre-ED and ED settings, and associated care outcomes in the ED. Predictors of BD use in the ED with statistical significance were incorporated in a predictive multivariable logistic regression model with a training-validation split of 70% to 30%.

RESULTS: Children with prior BD use were significantly more likely than children without such history to receive BD treatment during their current bronchiolitis illness before the ED [odds ratio (OR): 23.7, 95% CI: 14.4-39], in the ED (OR: 2.6, 95% CI: 1.76-3.77), and as a prescription upon discharge from the ED (OR: 3.7, 95% CI: 2.49-5.58). In multivariable regression analyses, older age, parental asthma history, and wheezes and retractions on ED physical examination were significantly associated with BD use in the ED (P<0.05). The area under the curve for the validation model with these variables was 0.826 (95% CI: 0.794-0.858).

CONCLUSIONS: Prior BD use was associated with subsequent use during the current illness, during ED care, and subsequent prescription, forming a cyclical pattern. A perceived bronchospastic phenotype of bronchiolitis may influence clinical practice in ED settings.

PMID:40016874 | DOI:10.1097/PEC.0000000000003360