Hasil untuk "Therapeutics. Pharmacology"

Zhijun Wang, Ling Luo, Dinghao Pan et al.

Automated Drug Combination Extraction (DCE) from large-scale biomedical literature is crucial for advancing precision medicine and pharmacological research. However, existing relation extraction methods primarily focus on binary interactions and struggle to model variable-length n-ary drug combinations, where complex compatibility logic and distributed evidence need to be considered. To address these limitations, we propose RexDrug, an end-to-end reasoning-enhanced relation extraction framework for n-ary drug combination extraction based on large language models. RexDrug adopts a two-stage training strategy. First, a multi-agent collaborative mechanism is utilized to automatically generate high-quality expert-like reasoning traces for supervised fine-tuning. Second, reinforcement learning with a multi-dimensional reward function specifically tailored for DCE is applied to further refine reasoning quality and extraction accuracy. Extensive experiments on the DrugComb dataset show that RexDrug consistently outperforms state-of-the-art baselines for n-ary extraction. Additional evaluation on the DDI13 corpus confirms its generalizability to binary drugdrug interaction tasks. Human expert assessment and automatic reasoning metrics further indicates that RexDrug produces coherent medical reasoning while accurately identifying complex therapeutic regimens. These results establish RexDrug as a scalable and reliable solution for complex biomedical relation extraction from unstructured text. The source code and data are available at https://github.com/DUTIR-BioNLP/RexDrug

Muhammad Muneeb, David B. Ascher

Human genetics offers a promising route to therapeutic discovery, yet practical frameworks translating genotype-derived signal into ranked target and drug hypotheses remain limited, particularly when matched disease transcriptomics are unavailable. Here we present G2DR, a genotype-first prioritization framework propagating inherited variation through genetically predicted expression, multi-method gene-level testing, pathway enrichment, network context, druggability, and multi-source drug--target evidence integration. In a migraine case study with 733 UK Biobank participants under stratified five-fold cross-validation, we imputed expression across seven transcriptome-weight resources and ranked genes using a reproducibility-aware discovery score from training and validation data, followed by a balanced integrated score for target selection. Discovery-based prioritization generalized to held-out data, achieving gene-level ROC-AUC of 0.775 and PR-AUC of 0.475, while retaining enrichment for curated migraine biology. Mapping prioritized genes to compounds via Open Targets, DGIdb, and ChEMBL yielded drug sets enriched for migraine-linked compounds relative to a global background, though recovery favoured broader mechanism-linked and off-label space over migraine-specific approved therapies. Directionality filtering separated broadly recovered compounds from mechanistically compatible candidates. G2DR is a modular framework for genetics-informed hypothesis generation, not a clinically actionable recommendation system. All outputs require independent experimental, pharmacological, and clinical validation.

Yukino Shirakawa, Takafumi Nakano, Keisuke Sato et al.

Abstract Background Atovaquone (Atov), a second-line drug, is used to treat patients with Pneumocystis pneumonia (PCP) who cannot tolerate sulfamethoxazole/trimethoprim (SMX/TMP). However, the efficacy and safety of Atov are based on clinical trials conducted in patients with human immunodeficiency virus (HIV) or acquired immunodeficiency syndrome, with limited data available on HIV-uninfected individuals with PCP (non-HIV PCP). In this study, we retrospectively evaluated the clinical outcomes of switching from SMX/TMP to Atov in patients with non-HIV PCP. Methods The study included patients with non-HIV PCP who were admitted to Fukuoka University Hospital between 2016 and 2023 and initially received SMX/TMP therapy. The primary endpoint was 30-day survival rate from the date of PCP diagnosis. Secondary endpoints included factors associated with mortality and the cumulative incidence of switching from SMX/TMP to Atov. Results Of the 56 patients receiving SMX/TMP therapy for PCP, 17 were switched to Atov due to SMX/TMP-related side effects. The Kaplan–Meier estimated 30-day survival was 76.9% in the “remained on” SMX/TMP group and 82.4% in the “switched to” Atov group (log-rank test, P = 0.58). Univariable logistic regression analysis of 30-day mortality showed that switching to Atov was not associated with higher mortality compared with continued SMX/TMP therapy (odds ratio 0.71, 95% confidence interval 0.17 to 3.05). The Kaplan–Meier estimated cumulative incidence of switching from SMX/TMP to Atov during the PCP treatment period was 33.8%. Conclusion Our data suggest that switching from SMX/TMP to Atov may not be associated with worse survival. Long-term administration of SMX/TMP is often challenging due to its side effects, and in this study, more than 30% of patients were unable to tolerate its therapeutic dose. Our findings support the role of Atov as a viable second-line treatment for PCP in immunocompromised patients, such as those with non-HIV PCP.

Zaixi Zhang, Ruofan Jin, Le Cong et al.

DNA language models have revolutionized our ability to understand and design DNA sequences--the fundamental language of life--with unprecedented precision, enabling transformative applications in therapeutics, synthetic biology, and gene editing. However, this capability also poses substantial dual-use risks, including the potential for creating pathogens, viruses, and even bioweapons. To address these biosecurity challenges, we introduce two innovative watermarking techniques to reliably track the designed DNA: DNAMark and CentralMark. DNAMark employs synonymous codon substitutions to embed watermarks in DNA sequences while preserving the original function. CentralMark further advances this by creating inheritable watermarks that transfer from DNA to translated proteins, leveraging protein embeddings to ensure detection across the central dogma. Both methods utilize semantic embeddings to generate watermark logits, enhancing robustness against natural mutations, synthesis errors, and adversarial attacks. Evaluated on our therapeutic DNA benchmark, DNAMark and CentralMark achieve F1 detection scores above 0.85 under various conditions, while maintaining over 60% sequence similarity to ground truth and degeneracy scores below 15%. A case study on the CRISPR-Cas9 system underscores CentralMark's utility in real-world settings. This work establishes a vital framework for securing DNA language models, balancing innovation with accountability to mitigate biosecurity risks.

Samuel C. T. Moorcroft, Benjamin Calmé, Charles Brooker et al.

The prompt identification of pancreatic cancer symptoms is an ongoing clinical challenge, often leading to late diagnosis and poor prognosis. Tumor 'hijacking' of the pancreatic stromal structure limits the uptake of systemic chemotherapeutics. Localized drug delivery systems (DDS) using endoluminal techniques are widely utilized, with positive early results for improved control over tumor growth. There is a need for technologies that integrate endoluminal resources and intelligent material systems to better control the spatiotemporal delivery of chemotherapeutics. We demonstrate the ultrasound (US)-triggered localized release of therapeutics through the design of solvent traceless drug-loaded vinylbenzyl-functionalized gelatin (gel4vbc) nanoparticles (NPs) integrated with an electrospun fabric. Albumin-loaded NPs encapsulated into a poly(vinyl alcohol) (PVA) coating of a poly(epsilon-caprolactone) fabric evidence tunable triggered NP delivery controlled by regulating PVA concentration (0-1 wt.%) and US intensity (0-3 W/cm2). The fixation of the NP-coated fabric to a magnetic tentacle robot (MTR) enables the automated manipulation into a phantom pancreatic duct before the US-triggered release of NP-loaded albumin and MTR retraction. Albumin release is controlled by varying the surface area of the NP-loaded MTR-coating fabric. Herein we have designed a novel DDS capable of facile integration into soft robotics and US-triggered delivery of therapeutic-loaded NPs.

Emily Sakamoto-Rablah, Jordan Bye, Arghya Modak et al.

Protein engineering enables the creation of tailor-made proteins for an array of applications. ImmTACs stand out as promising therapeutics for cancer and other treatments, while also presenting unique challenges for stability, formulation and delivery. We have shown that ImmTACs behave as Janus particles in solution, leading to self-association at low concentrations, even when the averaged protein-protein interactions suggest that the molecule should be stable. The formation of small but stable oligomers has been confirmed by static and dynamic light scattering and analytical ultracentrifugation. Modelling of the structure using Alphafold leads to a rational explanation for this behaviour, consistent with the Janus particle assembly observed for inverse patchy particles.

Ziyang Yu, Wenbing Huang, Yang Liu

Molecular Dynamics (MD) is crucial in various fields such as materials science, chemistry, and pharmacology to name a few. Conventional MD software struggles with the balance between time cost and prediction accuracy, which restricts its wider application. Recently, data-driven approaches based on deep generative models have been devised for time-coarsened dynamics, which aim at learning dynamics of diverse molecular systems over a long timestep, enjoying both universality and efficiency. Nevertheless, most current methods are designed solely to learn from the data distribution regardless of the underlying Boltzmann distribution, and the physics priors such as energies and forces are constantly overlooked. In this work, we propose a conditional generative model called Force-guided Bridge Matching (FBM), which learns full-atom time-coarsened dynamics and targets the Boltzmann-constrained distribution. With the guidance of our delicately-designed intermediate force field, FBM leverages favourable physics priors into the generation process, giving rise to enhanced simulations. Experiments on two datasets consisting of peptides verify our superiority in terms of comprehensive metrics and demonstrate transferability to unseen systems.

Fuyao Liu, Xiaodan Lu, Lei Zhang et al.

We previously synthesized the xanthine oxidoreductase (XOR) inhibitor WN1703. In addition to showing XOR inhibitory effects, WN1703 also showed anti-inflammatory effects in a rat hyperuricemia model. Here, we studied WN1703's anti-inflammatory effects on gout and explored the underlying mechanisms. Tohoku Hospital Pediatrics-1 (THP-1) cells were stimulated by lipopolysaccharide/interferon-γ/monosodium urate (MSU). The levels of inflammatory cytokines in the supernatant and protein expression in THP-1 cells were detected using enzyme-linked immunosorbent assay (ELISA) kits and western blotting, respectively, to verify the inhibitory effects of WN1703 and its mechanism. Potassium oxonate, hypoxanthine, and MSU were administered to establish a hyperuricemia rat model complicated by acute gouty arthritis. At 1–24 h after MSU injection, the degree of ankle swelling was recorded to compare the anti-inflammatory effects at each time point. The potential mechanism was further explored using immunohistochemistry and ELISA. WN1703 significantly downregulated expression of nucleotide-binding oligomerization domain-like receptor thermal protein domain associated protein 3 (NLRP3), apoptosis-associated speck-like protein containing a CARD (ASC), caspase-1, toll-like receptor-4 (TLR4), myeloid differentiation primary response protein 88 (MyD88), nuclear factor-kappa B (NF-κB), and relevant cytokine levels in THP-1 cells. Identical doses of WN1703 and febuxostat had comparable effects on these proteins and cytokines. In the gout rats, the same dose of WN1703 and febuxostat showed equivalent inhibitory effects on NLRP3, ASC, and NF-κB; however, WN1703 showed weaker impacts on alleviating ankle swelling than febuxostat showed. In conclusion, WN1703 showed significant anti-inflammatory effects in hyperuricemic rats with acute gout. Such effects were related to the inhibition of the NLRP3/ASC/Caspase-1 and TLR4/MyD88/NF-κB signaling pathways, thereby downregulating inflammation-related protein expression and decreasing inflammatory cytokine secretion.

Inarah Fajriaty, Siti Nani Nurbaeti, Hariyanto IH et al.

Malnutrition is characterized by slow growth and excessive loss of body fat. The fats needed during the growth period of toddlers are essential fatty acids, which are important for the human body and cannot be made in the body but must come from food. specifically omega-3, which is beneficial for children's growth and brain intelligence. The plant that contains this content is the tengkawang fruit. The aim of this study was to examine the effect of tengkawang fruit on motor behavior and organ indices in malnourished male white rats (Rattus norvegicus L.) of the Wistar strain. Research methods include making low-protein animal feed, making test preparations, and grouping animals. Mice were divided into 5 groups, namely positive control, negative control, normal control, and two dose groups; then behavioral observations and organ index observations were observed. The organs observed were the spleen, heart, lungs, liver, and kidneys. The results of behavioral observations in the tengkawang fruit extract group showed that the platform observation increased again after being given the test preparation like the normal group, and the same as motor activity, there was an increase back to normal conditions, especially in the tengkawang fruit extract group at a dose of 100 mg/kgBB, where there was an increase exceeding the normal group by 40%. Observation of organ indices did not show a significant increase (p 0.05) in the lymph organs, heart, lungs, liver, and kidneys compared to the normal group. Giving tengkawang fruit extract at a dose of 100 mg/kgBB and a dose of 300 mg/kgBB can make the behavior and organ index of malnourished mice return to normal. However, it did not show a significant increase (p 0.05) between the two dose groups and the negative control group, so it is recommended that further research be carried out using an inert solvent with tengkawang tungul extract.

Hongtai Jing, Zhengtao Gao, Sheng Xu et al.

In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, particularly viral infections. However, their development has been hindered by limited structural information and labor-intensive engineering processes. Fortunately, significant advancements in deep learning methods have facilitated the precise prediction of protein structure and function by leveraging co-evolution information from homologous proteins. Despite these advances, predicting the conformation of antibodies remains challenging due to their unique evolution and the high flexibility of their antigen-binding regions. Here, to address this challenge, we present the Bio-inspired Antibody Language Model (BALM). This model is trained on a vast dataset comprising 336 million 40% non-redundant unlabeled antibody sequences, capturing both unique and conserved properties specific to antibodies. Notably, BALM showcases exceptional performance across four antigen-binding prediction tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM, capable of swiftly predicting full atomic antibody structures from individual sequences. Remarkably, BALMFold outperforms those well-established methods like AlphaFold2, IgFold, ESMFold, and OmegaFold in the antibody benchmark, demonstrating significant potential to advance innovative engineering and streamline therapeutic antibody development by reducing the need for unnecessary trials.

Vincent Blay, Felix Grases

Kidney stone disease poses a major burden to patients and healthcare systems around the world. The formation of kidney stones may occur over months or years, but many patients are diagnosed at a late stage, suffer excruciating pain, and require surgical intervention to physically remove the stones. The prevalence of kidney stones has increased during recent decades to over 10% in many developed countries, suggesting a link with environmental and behavioral factors. Recurrence rates are also high. In terms of their impact and scale, kidney stones are an ongoing pandemic. The causes and mechanisms of kidney stone formation are diverse and often unknown, resulting in varied compositions and different anatomical locations being affected. A better understanding of these processes could enable earlier diagnoses through more sensitive and scalable biomarkers, as well as more effective preventives and therapeutics.

Hangyu Pan, Kexin Hu, Qiao Wu et al.

Abstract Background Lipid‐lowering therapy is of utmost importance in both primary and secondary prevention of atherosclerotic cardio vascular disease (ASCVD). However, the presence of residual risk allows cardiovascular events to occur even when low‐density lipoprotein cholesterol (LDL‐C) levels are very low. A large number of clinical studies have provided evidence confirming the association between elevated plasma Lp(a) and the development of ASCVD. Clinical studies have also suggested that reducing Lp(a) may help decrease the occurrence of cardiovascular events. Main Lp(a) consists of LDL‐like particles, apo(a) and OxPL. The level of Lp(a) in thehuman body is predominantly determined by genetics, with external factorshaving minimal impact. Additionally, Lp(a) levels have been found to vary among different ethnicities. There is a notable correlation between elevated levels of Lp(a) and coronary artery disease (CAD), which is independent of other lipoproteins. Furthermore, there exists a linear relationship between Lp(a) levels and the risk of developing ASCVD. It is now wildly believed that Lp(a) primarily contributes to the development of cardiovascular events through pro‐inflammation, pro‐thrombosis and pro‐atherosclerosis. From the perspective of Lp(a) influencing inflammation, it primarily promotes the release of inflammatoryfactors. This, in turn, increases levels of vascular inflammation and facilitates the recruitment of monocytes‐macrophages. Moreover, it also affects the function of endothelial cells during the development process of atherosclerosis. All these aspects complement each other and contribute to the progression of at herosclerosis. Currently, the lipid‐lowering treatment used inclinical practice can partially reduce the levels of Lp(a), but its impact on inflammation is not significant. Conclusion Lp(a) is an independent risk factor for CAD, as it promotes inflammation in the body and accelerates theprogression of atherosclerosis. Further research on effective methods to reduce Lp(a) levels can provide new insights for the treatment of atherosclerosis.

Gomaa Mostafa-Hedeab, Amany Behairy, Yasmina M. Abd-Elhakim et al.

This study assessed the possible protective role of green synthesized zinc oxide nanoparticles using <i>Moringa olifera</i> leaf extract (MO-ZNPs) in acrylamide (ACR)-induced reproductive dysfunctions in male rats. ACR (20 mg/kg b.wt/day) and/or MO-ZNPs (10 mg/kg b.wt/day) were given orally by gastric gavage for 60 days. Then, sperm parameters; testicular enzymes; oxidative stress markers; reproductive hormones including testosterone, luteinizing hormone (LH)-estradiol, and follicle-stimulating hormone (FSH) concentration; testis histology; steroidogenesis-related gene expression; and apoptotic markers were examined. The findings revealed that MO-ZNPs significantly ameliorated the ACR-induced decline in the gonadosomatic index and altered the pituitary–gonadal axis, reflected by decreased serum testosterone and FSH with increased estradiol and LH, and sperm analysis disruption. Furthermore, a notable restoration of the tissue content of antioxidants (catalase and reduced glutathione) but depletion of malondialdehyde was evident in MO-ZNPs+ACR-treated rats compared to ACR-exposed ones. In addition, MO-ZNPs oral dosing markedly rescued the histopathological changes and apoptotic caspase-3 reactions in the testis resulting from ACR exposure. Furthermore, in MO-ZNPs+ACR-treated rats, ACR-induced downregulation of testicular steroidogenesis genes and proliferating cell nuclear antigen (PCNA) immune-expression were reversed. Conclusively, MO-ZNPs protected male rats from ACR-induced reproductive toxicity by suppressing oxidative injury and apoptosis while boosting steroidogenesis and sex hormones.

Richard F. Ittenbach, J. William Gaynor, Jenny M. Dorich et al.

Abstract The purpose of this study was to establish the technical merit, feasibility, and generalizability of a new measure of understanding of informed consent for use with clinical research participants. A total of 109 teens/young adults at a large, pediatric medical center completed the consenting process of a hypothetical biobanking study. Data were analyzed using a combination of classical and modern theory analytic methods to produce a final set of 19 items referred to as the uConsent scale. A requirement of the scale was that each item mapped directly onto one or more of the Basic Elements of Informed Consent from the 2018 Final Rule. Descriptive statistics were computed for each item as well as the scale as a whole. Partial credit (Rasch) logistic modeling was then used to generate difficulty/endorsability estimates for each item. The final, 19‐item uConsent scale was derived using inferential methods to yield a set of items that ranged across difficulty levels (−3.02 to 3.10 logits) with a range of point‐measure correlations (0.12 to 0.50), within‐range item‐ and model‐fit statistics, varying item types mapped to both Bloom's Taxonomy of Learning and required regulatory components of the 2018 Final Rule. Median coverage rate for the uConsent scale was 95% for the 25 randomly selected studies from ClinicalTrials.gov. The uConsent scale may be used as an effective measure of informed consent when measuring and documenting participant understanding in clinical research studies today.

Steven Sachio, Cleo Kontoravdi, Maria M. Papathanasiou

Process development is typically associated with lengthy wet-lab experiments for the identification of good candidate setups and operating conditions. In this paper, we present the key features of a model-based approach for the identification and assessment of process design space (DSp), integrating the analysis of process performance and flexibility. The presented approach comprises three main steps: (1) model development & problem formulation, (2) DSp identification, and (3) DSp analysis. We demonstrate how such an approach can be used for the identification of acceptable operating spaces that enable the assessment of different operating points and quantification of process flexibility. The above steps are demonstrated on Protein A chromatographic purification of antibody-based therapeutics used in biopharmaceutical manufacturing.