Drug Treatment Strategies Research Articles

Trajectories of Violence Exposure and Drug Use Among Justice-Involved Male Adolescents: A Multi-Trajectory Approach

A strong link exists between exposure to violence and drug use, yet their simultaneous development is less understood. This study utilizes multi-trajectory modeling to investigate the dynamic relationship between violence exposure and drug use among justice-involved male adolescents. Using a sample from the Pathways to Desistance study ( n = 1,095), we identify five group trajectories of violence exposure and drug use; “Chronic Low” (39.2%), “Resisters” (17.6%), “Accelerators” (13.9%), “Desisters” (22.2%), and “At-risk” (7.1%). Multinomial logistic regression analysis examines individual, social, and environmental risk factors predicting trajectory group membership. Results highlight the need to address cumulative vulnerabilities shaping outcomes among high-risk adolescents. We conclude by discussing the importance of drug treatment and intervention strategies to foster positive outcomes for justice-involved youth.

Application of nanoultrasonography in early diagnosis of coronary heart disease.

Coronary heart disease (CHD) remains one of the leading causes of mortality and disability globally. In recent years, nanoultrasonography technology has demonstrated significant potential in both the diagnosis and treatment of CHD. This review summarizes the latest research advancements in nanoultrasonography within the field of coronary heart disease, focusing on its applications in early diagnosis, targeted drug delivery, imaging techniques, and treatment strategies. We explore the working principles of nanoultrasonography, its technological advantages, and the challenges faced in clinical applications. The aim is to provide guidance for future research and clinical practice in this promising area.

Pay attention to the impact of cardiopulmonary comorbidities on the management strategies of pulmonary arterial hypertension

With the increasing age of patients with pulmonary arterial hypertension (PAH) at diagnosis, multiple comorbidities are more and more common in these patients, especially cardiopulmonary diseases. This article introduces the incidence of PAH combined with cardiovascular disease and/or chronic lung disease, elaborates on the impact of cardiopulmonary comorbidities on the diagnosis, prognosis, and targeted drug treatment strategies of PAH, and proposes management recommendations for PAH patients with comorbidities, aiming to further improve the diagnosis and treatment level of pulmonary hypertension.

AGCNAF: predicting disease-gene associations using GCN and multi-head attention to fuse the similarity features

Abstract Association prediction between diseases and genes is a critical step in revealing the molecular mechanisms of diseases and developing drug treatment strategies. With the explosive growth of data in the biomedical field, how to effectively utilize these data for accurate prediction has become a hotspot and challenge in current research. To overcome the limitations of current prediction methods in dealing with complex biological network structures and feature extraction, this study proposes AGCNAF, a method that combines an unsupervised Graph Convolutional Network (GCN) and a multi-head attention mechanism. The metagraph-guided random walk strategy enables AGCNAF to capture local and high-order topological structures in the graph, while GCN is responsible for realizing deep feature extraction of these structures. By incorporating similarity features through the multi-attention mechanism, AGCNAF achieves effective integration of global and local features, which significantly improves the prediction performance. By incorporating similarity features through the multi-attention mechanism, AGCNAF achieves effective integration of global and local features, which significantly improves the prediction performance. By utilizing the machine learning binary classification model for prediction, the experimental results through five-fold cross-validation show that AGCNAF demonstrates significant advantages in prediction performance compared to existing methods, with its AUC and AUPR reaching 0.9686 and 0.9709, respectively, and the AUC up to 0.9812 under specific conditions. 
To verify the practical application value of AGCNAF, this study also conduct case studies on Alzheimer's disease, lung cancer, and breast cancer. The results further confirm the excellent performance of AGCNAF in identifying potential disease-gene associations, which opens up new possibilities for future disease-gene research.

Analysis of criteria for choosing drug treatment strategies in allergic rhinitis.

Allergic rhinitis (AR) is the most common type of rhinitis, the treatment of which relies on relieving symptoms. Therefore, we aimed to assess the criteria that influence doctors' decision-making in the process of drug selection for the treatment of allergic rhinitis based on quantitative, qualitative, and cost analyses. We conducted a survey study with the participation of 300 allergologists. A self-developed questionnaire was presented during a computer-assisted telephone interview (CATI) according tostandard procedures. The contingency table underwent statistical analysis using the chi-square test with Cramer's V. Results were considered statistically significant at p < 0.05. Our analyses showed that doctors most often prescribe intranasal glucocorticoids and oral antihistamines to treat allergic rhinitis in patients of all ages. The most common factor that affects the decision-making related to AR treatment was the efficiency of the drug. We found a significant relationship between factors and the main workplace (X-squared = 122.81, df = 90, p-value = 0.0123, Cramer's V = 0.1787216), as well as voivodeship of the main workplace (X-squared = 440.75, df = 270, p-value = 2.378e-10, Cramer's V = 0.1954731). In our study, respondents claimed that patients are willing to pay 31-50 PLN (∼€7- €11) monthly for the treatment of mild and moderate forms of AR, while they were willing to pay 51-100 PLN (∼€11-€22) for treatment of the severe AR form. Our study confirms that the management of AR should be focused on the patient. One of the most important factors in choosing a drug is its effectiveness. Moreover, an important factor in the effective treatment of AR is the financial issue; as shown in our analysis, AR treatment costs can be a significant burden, especially for less wealthy citizens in Poland.

Deciphering the role of sphingolipid metabolism in the immune microenvironment and prognosis of esophageal cancer via single-cell sequencing and bulk data analysis

BackgroundEsophageal squamous cell carcinoma (ESCC) stands as a significant global health challenge, distinguished by its aggressive progression from the esophageal epithelium. Central to this malignancy is sphingolipid metabolism, a critical pathway that governs key cellular processes, including apoptosis and immune regulation, thereby influencing tumor behavior. The advent of single-cell and transcriptome sequencing technologies has catalyzed significant advancements in oncology research, offering unprecedented insights into the molecular underpinnings of cancer.MethodsWe explored sphingolipid metabolism-related genes in ESCC using scRNA-seq data from GEO and transcriptome data from TCGA. We assessed 97 genes in epithelial cells with AUCell, UCell, and singscore algorithms, followed by bulk RNA-seq and differential analysis to identify prognosis-related genes. Immune infiltration and potential immunotherapeutic strategies were also investigated, and tumor gene mutations and drug treatment strategies were analyzed.ResultOur study identified distinct gene expression patterns, highlighting ARSD, CTSA, DEGS1, and PPTQ's roles in later cellular stages. We identified seven independent prognostic genes and created a precise nomogram for prognosis.ConclusionThis study integrates single-cell and transcriptomic data to provide a reliable prognostic model associated with sphingolipid metabolism and to inform immunotherapy and pharmacotherapy for ESCC at the genetic level. The findings have significant implications for precision therapy in esophageal cancer.

Multidrug Combinations against SARS-CoV-2 Using GS-441524 or Ivermectin with Molnupiravir and/or Nirmatrelvir in Reconstituted Human Nasal Airway Epithelia.

Background. The emergence, global spread, and persistence of SARS-CoV-2 resulted in an unprecedented need for effective antiviral drugs. Throughout the pandemic, various drug development and treatment strategies were adopted, including repurposing of antivirals designed for other viruses along with a multitude of other drugs with varying mechanisms of action (MoAs). Furthermore, multidrug treatment against COVID-19 is an ongoing topic and merits further investigation. Method/Objectives. We assessed the efficacy of multidrug treatment against SARS-CoV-2 in reconstituted human nasal epithelia, using combinations of molnupiravir and nirmatrelvir as a baseline, adding suboptimal concentrations of either GS-441524 or ivermectin, attempting to increase overall antiviral activity while lowering the overall therapeutic dose. Results. Nirmatrelvir combined with molnupiravir, GS-441524, or ivermectin at suboptimal concentrations show increased antiviral activity compared to single treatment. No triple combinations showed improved inhibition of SARS-CoV-2 replication beyond what was observed for double treatments. Conclusions. In general, we observed that the addition of a third compound is not beneficial for antiviral activity, while various double combinations exhibit increased antiviral activity over single treatment.

Bioengineered chondrocyte membrane-camouflaged anti-ferroptotic drug-loaded liposomes: A highly effective cartilage-targeted drug delivery system for osteoarthritis treatment

Osteoarthritis (OA) is a chronic degenerative joint disorder that severely impacts patients’ quality of life. Despite various drug treatment strategies, achieving effective therapeutic outcomes remains challenging due to the joint’s unique structure, which results in rapid drug clearance through synovial fluid and the dense, avascular cartilage matrix. To address this issue, we developed an innovative nanoplatform utilizing biomimetic cell membrane-coating technology. This bioengineered chondrocyte membrane-camouflaged, anti-ferroptotic, drug-loaded system enhances cartilage penetration, prolongs drug retention, and provides targeted therapy. As a nanovehicle, it targets chondrocytes through membrane fusion, allowing rapid penetration and mitigating OA progression. In vitro experiments show that this nanocarrier alleviates iron homeostasis imbalance and suppresses lipid peroxidation, helping ameliorate metabolic disorders in chondrocytes and addressing multiple pathological processes triggered by ferroptosis. In vivo results further suggest that this “Trojan Horse” strategy extends drug retention in joints and improves therapeutic efficacy. This study presents a potential universal nanoplatform comprising bioengineered chondrocyte membrane-coated liposomes for highly effective cartilage-targeted drug delivery in OA treatment.

Unveiling gut microbiota's role: Bidirectional regulation of drug transport for improved safety.

Drug safety is a paramount concern in the field of drug development, with researchers increasingly focusing on the bidirectional regulation of gut microbiota in this context. The gut microbiota plays a crucial role in maintaining drug safety. It can influence drug transport processes in the body through various mechanisms, thereby modulating their efficacy and toxicity. The main mechanisms include: (1) The gut microbiota directly interacts with drugs, altering their chemical structure to reduce toxicity and enhance efficacy, thereby impacting drug transport mechanisms, drugs can also change the structure and abundance of gut bacteria; (2) bidirectional regulation of intestinal barrier permeability by gut microbiota, promoting the absorption of nontoxic drugs and inhibiting the absorption of toxic components; (3) bidirectional regulation of the expression and activity of transport proteins by gut microbiota, selectively promoting the absorption of effective components or inhibiting the absorption of toxic components. This bidirectional regulatory role enables the gut microbiota to play a key role in maintaining drug balance in the body and reducing adverse reactions. Understanding these regulatory mechanisms sheds light on novel approaches to minimize toxic side effects, enhance drug efficacy, and ultimately improve drug safety. This review systematically examines the bidirectional regulation of gut microbiota in drug transportation from the aforementioned aspects, emphasizing their significance in ensuring drug safety. Furthermore, it offers a prospective outlook from the standpoint of enhancing therapeutic efficacy and reducing drug toxicity, underscoring the importance of further exploration in this research domain. It aims to provide more effective strategies for drug development and treatment.

Gastrointestinal Cancer Patient Derived Organoids at the Frontier of Personalized Medicine and Drug Screening.

Cancer is a leading cause of death worldwide. Around one-third of the total global cancer incidence and mortality are related to gastrointestinal (GI) cancers. Over the past few years, rapid developments have been made in patient-derived organoid (PDO) models for gastrointestinal cancers. By closely mimicking the molecular properties of their parent tumors in vitro, PDOs have emerged as powerful tools in personalized medicine and drug discovery. Here, we review the current literature on the application of PDOs of common gastrointestinal cancers in the optimization of drug treatment strategies in the clinic and their rising importance in pre-clinical drug development. We discuss the advantages and limitations of gastrointestinal cancer PDOs and outline the microfluidics-based strategies that improve the throughput of PDO models in order to extract the maximal benefits in the personalized medicine and drug discovery process.

Bayesian network analysis of drug treatment strategies for thyroid associated ophthalmopathy.

The first line treatment for moderate to severe active thyroid associated ophthalmopathy is glucocorticoid pulse therapy, but for patients with contraindications to hormone therapy or hormone resistance, it is urgent to find a suitable treatment plan. To find a reliable alternative to hormone pulse therapy for thyroid associated ophthalmopathy by comparing the efficacy with first-line treatment regimens. Search PubMed, Ovid, Web of science, Cochrane library, and Clinical Trials.gov for randomized controlled trials on the treatment of thyroid associated ophthalmopathy published as of July 7, 2024. Quality evaluation and Bayesian network analysis were conducted using RevMan 5.3 software, STATA15.0 software, and ADDIS 1.16.8 software. A total of 666 patients were included in 11 studies and 8 interventions. Network analysis showed that the three interventions of mycophenolate mofetil combined with glucocorticoids, Teprotumumab and 99Tc-MDP were superior to glucocorticoid pulse therapy in improving clinical activity scores and proptosis. The regimen of glucocorticoids combined with statins can improve the quality of life score and diplopia score of patients. Neither methotrexate combined with glucocorticoids nor rituximab alone showed additional advantages when compared with glucocorticoid pulse therapy. Mycophenolate mofetil combined with glucocorticoid therapy is very beneficial for moderate to severe active thyroid associated ophthalmopathy. Mycophenolate mofetil may be a good choice when patients have contraindications to hormone use or hormone resistance. Teprotumumab is very promising and may be able to avoid patients undergoing orbital decompression surgery. The durability and safety of its long-term efficacy need to be further observed.

Comprehensive Overview of Alzheimer's Disease: Etiological Insights and Degradation Strategies.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and affects millions of individuals globally. AD is associated with cognitive decline and memory loss that worsens with aging. A statistical report using U.S. data on AD estimates that approximately 6.9 million individuals suffer from AD, a number projected to surge to 13.8 million by 2060. Thus, there is a critical imperative to pinpoint and address AD and its hallmark tau protein aggregation early to prevent and manage its debilitating effects. Amyloid-β and tau proteins are primarily associated with the formation of plaques and neurofibril tangles in the brain. Current research efforts focus on degrading amyloid-β and tau or inhibiting their synthesis, particularly targeting APP processing and tau hyperphosphorylation, aiming to develop effective clinical interventions. However, navigating this intricate landscape requires ongoing studies and clinical trials to develop treatments that truly make a difference. Genome-wide association studies (GWASs) across various cohorts identified 40 loci and over 300 genes associated with AD. Despite this wealth of genetic data, much remains to be understood about the functions of these genes and their role in the disease process, prompting continued investigation. By delving deeper into these genetic associations, novel targets such as kinases, proteases, cytokines, and degradation pathways, offer new directions for drug discovery and therapeutic intervention in AD. This review delves into the intricate biological pathways disrupted in AD and identifies how genetic variations within these pathways could serve as potential targets for drug discovery and treatment strategies. Through a comprehensive understanding of the molecular underpinnings of AD, researchers aim to pave the way for more effective therapies that can alleviate the burden of this devastating disease.

A Mathematical Analysis of Competitive Dynamics and Aggressive Treatment in the Evolution of Drug Resistance in Malaria Parasites

Experimental evidence supports the counterintuitive notion that rapid eradication of pathogens within a host, infected with both drug-sensitive and -resistant malaria parasites, can actually accelerate the evolution of drug-resistant pathogens. This study aims to analyze the competitive dynamics between these two strains through a mathematical model and evaluate the impact of aggressive treatment on the spread of drug resistance. We conducted equilibrium, uncertainty, and sensitivity analyses to assess the model, identifying and measuring the influence of key factors on the outcome variable (the population of drug-resistant parasites). Both equilibrium and local sensitivity analyses concurred that the density of drug-resistant parasites is notably affected by genetic instability, the production rate of red blood cells, the number of merozoites, and competition factors. Conversely, there is a negative relationship between genetic instability and one of the competition coefficients. Global sensitivity analysis offers a comprehensive examination of the impact of each input parameter on the temporal propagation of drug resistance, effectively accounting for the interplay among parameters. Both local and global sensitivity analyses underscore the continuous impact of drug treatment on the progression of drug resistance over time. This paper anticipates exploring the underlying mechanisms of drug resistance and providing theoretical support for developing more effective drug treatment strategies.

On the additive artificial intelligence-based discovery of nanoparticle neurodegenerative disease drug delivery systems.

Neurodegenerative diseases are characterized by slowly progressing neuronal cell death. Conventional drug treatment strategies often fail because of poor solubility, low bioavailability, and the inability of the drugs to effectively cross the blood-brain barrier. Therefore, the development of new neurodegenerative disease drugs (NDDs) requires immediate attention. Nanoparticle (NP) systems are of increasing interest for transporting NDDs to the central nervous system. However, discovering effective nanoparticle neuronal disease drug delivery systems (N2D3Ss) is challenging because of the vast number of combinations of NP and NDD compounds, as well as the various assays involved. Artificial intelligence/machine learning (AI/ML) algorithms have the potential to accelerate this process by predicting the most promising NDD and NP candidates for assaying. Nevertheless, the relatively limited amount of reported data on N2D3S activity compared to assayed NDDs makes AI/ML analysis challenging. In this work, the IFPTML technique, which combines information fusion (IF), perturbation theory (PT), and machine learning (ML), was employed to address this challenge. Initially, we conducted the fusion into a unified dataset comprising 4403 NDD assays from ChEMBL and 260 NP cytotoxicity assays from journal articles. Through a resampling process, three new working datasets were generated, each containing 500,000 cases. We utilized linear discriminant analysis (LDA) along with artificial neural network (ANN) algorithms, such as multilayer perceptron (MLP) and deep learning networks (DLN), to construct linear and non-linear IFPTML models. The IFPTML-LDA models exhibited sensitivity (Sn) and specificity (Sp) values in the range of 70% to 73% (>375,000 training cases) and 70% to 80% (>125,000 validation cases), respectively. In contrast, the IFPTML-MLP and IFPTML-DLN achieved Sn and Sp values in the range of 85% to 86% for both training and validation series. Additionally, IFPTML-ANN models showed an area under the receiver operating curve (AUROC) of approximately 0.93 to 0.95. These results indicate that the IFPTML models could serve as valuable tools in the design of drug delivery systems for neurosciences.

A prognostic model for hepatocellular carcinoma patients based on polyunsaturated fatty acid-related genes.

Polyunsaturated fatty acids (PUFAs) have attracted increasing attention for their role in liver cancer development. The objective of this study is to develop a prognosis prediction model for patients with liver cancer based on PUFA-related metabolic gene characteristics. Transcriptome data and clinical data were obtained from public databases, while gene sets related to PUFAs were acquired from the gene set enrichment analysis (GSEA) database. Univariate Cox analysis was conducted on the training set, followed by LASSO logistic regression and multivariate Cox analysis on genes with p < .05. Subsequently, the stepwise Akaike information criterion method was employed to construct the model. The high- and low-risk groups were divided based on the median score, and the model's survival prediction ability, diagnostic efficiency, and risk score distribution of clinical features were validated. The above procedures were also validated in the validation set. Immune infiltration levels were evaluated using four algorithms, and the immunotherapeutic potential of different groups was explored. Significant enrichment pathways among different groups were selected based on the GSEA algorithm, and mutation analyses were conducted. Nomogram prognostic models were constructed by incorporating clinical factors and risk scores using univariate and multivariate Cox regression analysis, validated through calibration curves and clinical decision curves. Additionally, sensitivity analysis of drugs was performed to screen potential targeted drugs. We constructed a prognostic model comprising eight genes (PLA2G12A, CYP2C8, ABCCI, CD74, CCR7, P2RY4, P2RY6, and YY1). Validation across multiple datasets indicated the model's favorable prognostic prediction ability and diagnostic efficiency, with poorer grading and staging observed in the high-risk group. Variations in mutation status and pathway enrichment were noted among different groups. Incorporating Stage, Grade, T.Stage, and RiskScore into the nomogram prognostic model demonstrated good accuracy and clinical decision benefits. Multiple immune analyses suggested greater benefits from immunotherapy in the low-risk group. We predicted multiple targeted drugs, providing a basis for drug development. Our study's multifactorial prognostic model across multiple datasets demonstrates good applicability, offering a reliable tool for personalized therapy. Immunological and mutation-related analyses provide theoretical foundations for further research. Drug predictions offer important insights for future drug development and treatment strategies. Overall, this study provides comprehensive insights into tumor prognosis assessment and personalized treatment planning.

Targeted lung therapy with rosmarinic acid encapsulated in PLGA microspheres for radiation-induced pulmonary fibrosis

Radiation-induced pulmonary fibrosis (RIPF) is a frequent complication among individuals affected by nuclear accidents and patients undergoing chest radiation therapy for tumors. However, the availability of effective drugs for prevention and treatment of RIPF remains limited. Rosmarinic acid (RA), which displays inhibitory properties against RIPF, suffers from poor targeting in previous drug studies. To overcome this issue and achieve optimal therapeutic effects, continuous administration over several days is usually employed. In this study, we developed PLGA microspheres with an average size of 17 μm and drug loading efficiency of 24.97 % (±0.97 %), loaded with RA (RA/PLGAMS) using the membrane emulsification method. By controlling the size of microspheres in the pulmonary capillaries, we achieved lung targeting of microspheres, and based on the release of drugs as PLGA degrades, the residence time of drugs in the body is prolonged. And it was confirmed by in vivo imaging and SEM imaging that PLGAMS could exist in the lungs for at least 7 days. Our results demonstrated successful targeting of the lungs in a mouse model and sustained release of RA encapsulated in the PLGA microspheres. Notably, under the same administration conditions, the therapeutic efficacy of PLGA-encapsulated RA surpassed that of ordinary RA. We observed decreased expression of inflammatory factors, reduced M2 macrophage polarization, and weakened epithelial mesenchymal transformation following our treatment, which might explain the radiation damage alleviating effect of RA. After treatment, it was shown that the deep inspiratory capacity of the mice improved by 57.8 %, and WB showed a decrease of 52.4 % and 28.3 % in the expression of epithelial mesenchymal transition related proteins (TGF-β1 and α-SMA). In summary, PLGA microspheres offer a promising drug delivery system and treatment strategy for radiation-induced pulmonary fibrosis.

The relationship between cardiac oxidative stress, inflammatory cytokine response, cardiac pump function, and prognosis post-myocardial infarction

This study delves into the potential connections between cardiac oxidative stress, inflammatory cytokine response, cardiac pump function, and prognosis in individuals following myocardial infarction. A total of 276 patients were categorized into two groups: the control group (n = 130) and the observation group (n = 146), based on the drug intervention strategies. The control group received standard drug treatment, while the observation group received early drug intervention targeting antioxidant and anti-inflammatory treatment in addition to standard treatment. Serum levels of inflammatory factors, including tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-9 (IL-6), were assessed using enzyme-linked immuno sorbent assay (ELISA) kits. The Forkhead Box Protein A2 (FOX2) reagent was used to determine the overall oxidation level. Left Ventricular End-Diastolic Diameter (LVEDD), Left Ventricular Ejection Fraction (LVEF), and End-Systolic Diameter (ESD) were measured using Doppler ultrasound. The observation group exhibited significantly reduced serum levels of TNF-α, IL-1β, and IL-6 compared to the control group (P < 0.05). Moreover, the observation group exerted lower total oxidation levels, OSI, EDD, and ESD compared to the control group (P < 0.05), while the LVEF and TAS levels in the observation group were higher than those in the control group (P < 0.05). Remarkably, the observation group experienced a significant reduction in the incidences of reinfarction, heart failure, arrhythmia, and abnormal valve function compared to the control group (P < 0.05). Decreased cardiac pump function and a more unfavorable prognosis were associated with elevated levels of cardiac oxidative stress and inflammatory factors (P < 0.05). Timely intervention with appropriate medications have a crucial effect in decreasing inflammatory marker levels, mitigating oxidative pressure, and enhancing cardiac pumping capacity and overall prognosis.

Retention of triple therapy with methotrexate, sulfasalazine, and hydroxychloroquine compared to combination methotrexate and leflunomide in rheumatoid arthritis

ObjectiveThere are various combination conventional synthetic disease-modifying-antirheumatic drug (csDMARD) treatment strategies used in rheumatoid arthritis (RA). A commonly used csDMARD combination is triple therapy with methotrexate (MTX), sulfasalazine (SSZ) and hydroxychloroquine (HCQ). Another approach is double therapy with MTX and leflunomide (LEF). We compared the real-world retention of these two treatment combinations. MethodsPatients with RA from the Ontario Best Practices Research Initiative (OBRI) who received triple or double therapy on or after OBRI enrolment were included. Retention rates were compared between these two groups. We also analyzed which medication in the combination was discontinued and the reasons for treatment discontinuation. Disease activity was assessed at baseline, 6 and 12 months after treatment initiation as well as at time of discontinuation. Risk factors for treatment discontinuation were also examined. ResultsSix hundred and ninety-two patients were included (258 triple and 434 double therapy). There were 175 (67.8%) discontinuations in the triple therapy group and 287 (66.1%) discontinuations in patients on double therapy. The median survival for triple therapy was longer (15.1 months; 95% CI: 11.2–21.2) compared to double therapy (9.6 months; 95%CI: 7.03–12.2). However, this was not statistically significant. Disease activity at 6 and 12 months, measured by 28-joint count Disease Activity Score based on erythrocyte sedimentation rate (DAS28-ESR) was lower with triple therapy (mean DAS28 at 6 months 3.4 vs. 3.9, P<0.0001 and at 12 months 3.2 vs. 3.5, P=0.0005). ConclusionPatients on triple therapy remained on treatment longer than patients on double therapy. However, this difference was not statistically significant.

Abstract 3711: Procedure establishment of EGFR mutation test with circulating tumor cells of lung cancer by in vitro assay

Abstract Introduction: Non-small cell lung cancer (NSCLC) is the most common subtype, accounting for approximately 80% of lung cancer. The treatment for NSCLC has significantly improved since the introduction of targeted therapies. Epidermal growth factor receptor (EGFR) mutations are the most frequently found genetic alterations in NSCLC, and deletion of exon 19 is a representative example. Searching for this mutation may provide important clues to the use of EGFR tyrosine kinase inhibitors in NSCLC. So, the detection of EGFR mutation is important step in cancer diagnosis and determining the drug treatment strategy, but the detection of mutation with tissues has limitations such as clinical challenge to poorly accessible tumor tissues before and after treatment. The aim of this study was to explore the feasibility and utility of implementation of EGFR molecular testing from circulating tumor cells (CTC) in NSCLC. Here, we developed and optimized the procedure of mutated EGFR detection in CTC after isolation with CytoGen’s Smart BiopsyTM CTC isolator by cobas® EGFR Mutation Test. This EGFR mutation test in CTC showed the potential to overcome the limitations of tissue biopsy with high sensitivity and specificity in an in vitro assay. Method: PC-9 cells were used the positive control of EGFR mutation (EGFR exon 19 deletion). Limit of detection (LOD) was performed with PC-9 cells (200 cells to 5 cells, 6 points) spiked into blood sample (5mL, healthy donor) to mimic CTC in the blood of lung cancer patient. CTC were isolated from spiked samples using CytoGen’s Smart BiopsyTM CTC isolator, subsequently cobas® EGFR Mutation Test was carried out to detect of EGFR mutation. Results: In in vitro experiments of recovery test using cell lines spiked into blood from healthy donor, the recovery rate of CytoGen’s Smart Biopsy TM CTC isolator showed over 80%. As a result of LOD test, EGFR exon19 deletion mutation of PC-9 cells was clearly detected even in the smallest number of cells were spiked into blood (5 cells in 5mL blood) and was not detected at all in the negative controls. The result suggested that CytoGen’s Smart Biopsy TM CTC isolator can isolate CTC with high recovery rate and apply the test of oncogenic mutations including EGFR mutation in CTC. Conclusions: Confirmation of EGFR mutation is important step in the diagnosis and selection of optimal drug for cancer patients. However, tissue biopsy has several limitations such as difficulties to get tissue samples and inaccurate information due to invasive method and tumor heterogeneity. Detection of EGFR mutation in CTC might overcome and make up for limitations of tissue biopsy. In this study, we optimized the EGFR mutation detection procedure of intact live CTC isolated by CytoGen’s Smart BiopsyTM CTC isolator. Citation Format: Jihyun Lee, Hoin Kang, Min Hyung Kim, Jubi Lee, Hyoyong Kim, Soee Kim, Hae Ung Lee, Hai-Chon Lee, Jung Won Kim. Procedure establishment of EGFR mutation test with circulating tumor cells of lung cancer by in vitro assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3711.

Drug resistance and therapeutic advances in Treponema pallidum: A review

Treponema pallidum, a common pathogen in sexually transmitted diseases, has emerged as a significant public health threat in recent decades, showing a gradual increase in global prevalence. Antibiotics have been the primary method to treat Treponema pallidum infections. However, high-dose antibiotic use in clinical trials has raised concerns and unveiled a series of issues. This paper employs a literature review approach to summarize and compare scientific studies conducted in various countries and regions regarding Treponema pallidum in recent years. It aims to introduce and summarize the drug resistance of Treponema pallidum and the current progress in treatment. Studies indicate widespread resistance of Treponema pallidum to macrolides, while no resistance has been found to first-line drugs like benzathine penicillin and other alternative medications. Presently, benzathine penicillin remains pivotal in syphilis treatment. Alternatives such as ceftriaxone, second-generation tetracyclines, amoxicillin, and adjunctive immunomodulators, after clinical trials, have been used in early or late-stage syphilis treatment and prevention. The concept and research direction of syphilis vaccines are emerging and are poised to be a crucial approach in curtailing Treponema pallidum transmission. Diversified drug treatment strategies and the development of syphilis vaccines hold significant implications in safeguarding public health and ensuring global health security.