Target Treatment Research Articles

Abstract Su501: Feasibility and Implications of Electrocardiogram-based Prediction of Incessant Refractory Ventricular Fibrillation

Background: Refractory ventricular fibrillation (R-VF) patients, defined as requiring ≥ 3 shocks during resuscitation of OHCA, have relatively poor outcomes. Prior studies have predicted R-VF using the ECG, suggesting potential to guide early patient-specific treatment for R-VF. However, R-VF comprises multiple phenotypes with distinct defibrillation response profiles: Incessant VF (no shocks terminate VF), recurrent VF (all shocks terminate VF but VF recurs), or mixed VF (shocks variably terminate VF). These phenotypes may have distinct prognoses, and may also respond differently to R-VF treatments such as early antiarrhythmics, modified vasopressor dosing, alternative defibrillation strategies, or expedited invasive interventions. Early prediction of specific R-VF phenotype could potentially improve outcome through preemptive targeting of treatment to individual phenotype. Aim: We sought to predict incessant R-VF using machine learning analysis of the defibrillator ECG. Methods: We performed a retrospective study of adult VF OHCA treated by EMS from 2006–2019 in King County WA. We linked a clinical OHCA registry with defibrillator recordings to evaluate ROSC and survival to hospital discharge by VF type (non-refractory; or incessant, recurrent, or mixed R-VF prior to the third shock). To predict incessant R-VF specifically, we used a series of four 2-s ECG segments from each patient within 60s surrounding the first shock. Patients were randomized 65%/35% for training/test. A support vector machine classifier was trained to predict subsequent incessant R-VF using ECG scalograms. Algorithm performance was assessed by area under the receiver operating characteristic curve (AUC) and by sensitivity at >75% specificity. Results: Of 1111 included VF patients, median age was 62, 241 (22%) were female, 658 (59%) were refractory (≥ 3 shocks), 800 (72%) achieved ROSC, and 520 (47%) survived. The incessant R-VF phenotype accounted for 10% (N=116) and had worse ROSC and survival compared to recurrent R-VF and non-refractory patients (Table). Training and test AUCs to predict incessant R-VF were 0.77 (95% CI: 0.72–0.82, N=723) and 0.76 (95% CI: 0.66–0.82, N=388) respectively. Test sensitivity and specificity were 64% and 76%. Conclusion: Refractory VF comprises distinct phenotypes with disparate outcomes. Incessant R-VF has notably poor prognosis. Machine learning may be able to predict incessant R-VF, potentially guiding preemptive, patient-specific treatments to improve outcome.

Synthesis and evaluation of homocamptothecin antibody-drug conjugates for cancer treatment

As an emerging tumor therapeutic strategy, antibody-drug conjugates (ADCs) overcome the high toxicity of traditional small molecule chemotherapy and improve the targeting of treatment. In this study, we successfully constructed a novel ADC, Tras-16b, for the first time using homocamptothecin 16b as the payload. Tras-16b, at a dose of 3 mg/kg, exhibited comparable anti-tumor activity to Enhertu and demonstrated an enhanced safety profile in the NCI–N87 xenograft model. Notably, this is the first ADC developed based on homocamptothecin, marking a significant advancement with promising prospects for the structural modification of camptothecin ADCs.

Identification of key metabolism-related genes and pathways in spontaneous preterm birth: combining bioinformatic analysis and machine learning.

Spontaneous preterm birth (sPTB) is a global disease that is a leading cause of death in neonates and children younger than 5 years of age. However, the etiology of sPTB remains poorly understood. Recent evidence has shown a strong association between metabolic disorders and sPTB. To determine the metabolic alterations in sPTB patients, we used various bioinformatics methods to analyze the abnormal changes in metabolic pathways in the preterm placenta via existing datasets. In this study, we integrated two datasets (GSE203507 and GSE174415) from the NCBI GEO database for the following analysis. We utilized the "Deseq2" R package and WGCNA for differentially expressed genes (DEGs) analysis; the identified DEGs were subsequently compared with metabolism-related genes. To identify the altered metabolism-related pathways and hub genes in sPTB patients, we performed multiple functional enrichment analysis and applied three machine learning algorithms, LASSO, SVM-RFE, and RF, with the hub genes that were verified by immunohistochemistry. Additionally, we conducted single-sample gene set enrichment analysis to assess immune infiltration in the placenta. We identified 228 sPTB-related DEGs that were enriched in pathways such as arachidonic acid and glutathione metabolism. A total of 3 metabolism-related hub genes, namely, ANPEP, CKMT1B, and PLA2G4A, were identified and validated in external datasets and experiments. A nomogram model was developed and evaluated with 3 hub genes; the model could reliably distinguish sPTB patients and term labor patients with an area under the curve (AUC) > 0.75 for both the training and validation sets. Immune infiltration analysis revealed immune dysregulation in sPTB patients. Three potential hub genes that influence the occurrence of sPTB through shadow participation in placental metabolism were identified; these results provide a new perspective for the development and targeting of treatments for sPTB.

In Vivo Optogenetic Manipulation of Transgene Expression in Retinal Neurovasculature.

The retina is prone to developing pathological neovascularization, a leading cause of blindness in humans. Because excess neovascularization does not affect the entire retina, global inhibition treatment of angiogenesis critically interferes with healthy, unaffected retinal tissue. We therefore established an in vivo photoactivated gene expression paradigm which would allow light-mediated targeting of antiangiogenic genetic treatment only to affected retinal regions. We synthesized a "caged" (i.e., reversibly inhibited) photosensitive 4-hydroxytamoxifen analog. Molecular docking analyses validated its reduced transcriptional activity. Caged 4-hydroxytamoxifen was intravitreally injected into mice harboring the inducible Cre/lox system, with CreERT2 being expressed via the Tie2 promoter in the neurovasculature. Subsequent in vivo irradiation of eyes significantly induced retinal expression of a Cre-dependent transgene in retinal blood vessels. Using GFAP-CreERT2 mice, successful photoactivation was also achieved in eyes and also in ex vivo brain slices for validation of the approach. This highlights the possibility of light-mediated gene therapies specific for the retina, a key first step in personalized medicine.

Serum metabolomics reveals the effectiveness of human placental mesenchymal stem cell therapy for Crohn's disease

Mesenchymal stem cell (MSC) therapy offers a promising cure for Crohn's disease (CD), however, its therapeutic effects vary significantly due to individual differences. Therefore, identifying easily detectable biomarkers is essential to assess the efficacy of MSC therapy. In this study, SAMP1/Yit mice were used as a model of CD, which develop spontaneous chronic ileitis, closely resembling the characteristics present in CD patients. Serum metabolic alterations during treatment were analyzed, through the application of differential 12C-/13C-dansylation labeling liquid chromatography-mass spectrometry. Based on the significant differences and time-varying trends of serum amine/phenol-containing metabolites abundance between the control group, the model group, and the treatment group, four serum biomarkers were ultimately screened for evaluating the efficacy of MSC treatment for CD, namely 4-hydroxyphenylpyruvate, 4-hydroxyphenylacetaldehyde, caffeate, and N-acetyltryptamine, whose abundances both increased in the serum of CD model mice and decreased after MSC treatment. These metabolic alterations were associated with tyrosine metabolism, which was validated by the dysregulation of related enzymes. The discovery of biomarkers may help to improve the targeting and effectiveness of treatment and provide innovative prospects for the clinical application of MSC for CD.

The pathway alteration load as a pan-cancer determinant of outcome of targeted therapies: Results from the Drug Rediscovery Protocol (DRUP).

3138 Background: Although targeted treatment (TT) has improved outcomes for many patients with cancer, the emergence of primary or secondary resistance remains a common challenge. A frequently suggested contributing mechanism to this resistance is the existence of parallel activated oncogenic signaling pathways that remain untargeted and support tumor survival. Therefore, we hypothesized that an increased number of altered oncogenic signaling pathways (Pathway Alteration Load, PAL) predicts reduced benefit of TT which targets only one altered pathway. Methods: The Drug Rediscovery Protocol (DRUP) is a prospective, pan-cancer, non-randomized clinical trial (NCT02925234) in which patients with treatment-refractory metastatic cancer with an actionable molecular profile are treated with matched approved targeted- and immunotherapies outside their registered indication. All patients treated with TT for whom clinical outcome and whole genome sequencing results of a pre-treatment biopsy were available were included. The PAL was determined by counting the number of proliferation pathways impacted by somatic driver alterations, using an established pathway classification scheme (Sanchez-Vega et al., Cell, 2018). Influence of PAL on clinical benefit rate (CBR, defined as objective response or stable disease ≥ 16 weeks according to RECIST v1.1 or RANO), progression-free survival (PFS) and overall survival (OS) was evaluated. Cox proportional-hazards models, stratified by tumor type, were used to adjust outcomes for drug, performance status, previous treatment lines, tumor mutational burden and cancer cell ploidy. Results were validated using the independent Hartwig database of metastatic cancers. Results: In all 154 patients treated with single pathway-directed TT, PAL was 0 in 3, 1 in 20, 2 in 37, 3 in 56, 4 in 31, 5 in 6 and 6 in 1 patient(s). Patients with a PAL below the median of 3 ( N= 60) demonstrated a higher CBR (41.7% vs 25.5%, odds ratio [OR] 0.48, P = 0.051), longer PFS (median 4.7 vs 2.9 months, adjusted hazard ratio [aHR] 1.70, P = 0.020) and OS (median 13.7 vs 5.6 months, aHR 3.80, P< 0.001), compared to those with PAL ≥3. Results were consistent across different PAL cut-offs and when applying PAL continuously (aHR for PFS 1.41, P = <0.001; aHR for OS 1.77, P = <0.001). In the independent Hartwig cohort, 258 patients treated with single pathway-directed TT were identified and similar results were found for CBR (54.2% vs 36.7%, OR 2.04, P = 0.009) and PFS (7.0 vs 4.2 months, aHR 1.55, P = 0.009), but not for OS (14.7 vs 8.2 months, aHR 1.37, P = 0.111). Conclusions: In our population, PAL emerged as a pan-cancer predictor of resistance to TT. Our findings provide support for more refined patient selection for TT and highlight the rationale for combinatorial treatment strategies, especially in patients with multiple affected pathways. Clinical trial information: NCT02925234 .

Treatment (Tx) inequities in patients (pts) with metastatic non-small cell lung cancer (mNSCLC) harboring actionable driver oncogenes (ADO) in the first-line (1L) setting.

e13673 Background: Targeted treatments (TT) have been approved for pts with mNSCLC harboring ADO in the 1L setting in recent years. This study aimed to understand if subpopulations of mNSCLC pts harboring ADO do not receive equitable access to guideline recommended 1L TT in US clinical settings. Methods: This retrospective study used the Flatiron Health electronic health record-derived, US nationwide, de-identified database. Pts with de novo mNSCLC (stage IVA or IVB) diagnosed between 4/1/2018-6/30/2023 were included if they were ≥18 y, had ≥2 visits after advanced diagnosis (aDx) and ≥90 days follow-up, received any biomarker testing prior to 1L Tx initiation, and harbored ADO (ALK, BRAF, EGFR, MET, NTRK, RET and/or ROS1). Results: Overall 2165 pts met study criteria: mean age was 67 y, 65% female, 11% Medicare insured, 58% commercial insured, 76% treated in the community setting with 11% Medicare and 64% commercial insured (vs 12% and 41% treated in the academic setting with Medicare and commercial insurance), and 45% had smoking history; of non-missing data, 12% had lowest socioeconomic status (SES), 26% with highest SES, 95% had non-squamous NSCLC, and 83% had ECOG performance status ≤1. The median time from aDx to testing result among the 53% non-Latinx (nL) white, 8% nL Black, 7% Latinx, 13% nL Asian, 7% nL other and 13% missing race/ethnicity was 21, 23, 24, 21, 23 and 20 days, respectively; median time from aDx to TT initiation was 38, 38, 43, 36, 47 and 37 days, respectively. Pts significantly more likely to receive 1L TT were (Table): pts of color vs white pts; Medicare vs commercial insurance at community sites; without vs with smoking history. Pts less likely to receive 1L TT were (Table): community vs academic sites; Medicare vs commercial insurance at academic sites. Consistent findings were seen in the 1817 pts with established 1L ADO (ie. ALK, EGFR or ROS1) (Table). Conclusions: When pts with mNSCLC harboring ADO had biomarker testing before Tx initiation, contrary to prior observed racial inequity in NGS testing, there was no racial inequity in receiving 1L TT. However, inequity in receiving 1L TT was observed by insurance type, smoking history and site of care. Interventions are warranted to address these contributors to 1L TT inequities. [Table: see text]

292P Extended molecular profiling (EMP) and access to targeted treatment (TT) in advanced biliary tract cancer (BTC): Results from the Italian cholangiocarcinoma dataset (ANITA)

292P Extended molecular profiling (EMP) and access to targeted treatment (TT) in advanced biliary tract cancer (BTC): Results from the Italian cholangiocarcinoma dataset (ANITA)

Curcumin-Enclosed Nanoparticles for Cancer Therapy

Abstract: Cancer is the greatest cause of mortality worldwide, and it is distinguished by the unrestrained proliferation of a group of aberrant cells, the random division of cells, and the invasiveness of genetically organized cells. At present, there are various strategies for curing of cancer-based on the type & severity. In the earlier two decades, curcumin has received huge attention in pharmacological, biological, and nutraceutical research. In addition to triggering apoptosis in cancer cells, curcumin also inhibits cancer cell invasion and proliferation by stifling cellular signaling pathways. The lower water solubility of curcumin decreases the oral bioavailability, absorption into the systemic circulation, and chemical stability and finally bound the activity of curcumin as an anticancer agent. The pharmacology of curcumin, as well as its derivatives with relation to its anticancer potential, primary modes of action, & cellular target, has been summarised in this article along with a list of the numerous curcumin enclosing nanoformulations. Multiple methods of administration have been developed for curcumin to boost its specificity. Encapsulation and other formulation processing techniques have been found to enhance both the solubility and bioavailability of curcumin. The nanoparticles' size, shape, surface characteristics, and targeting ligand are all factors that nanoformulation designers must think about when working to increase the efficacy and cellular targeting of anticancer treatments.

Pericyte in retinal vascular diseases: A multifunctional regulator and potential therapeutic target.

Retinal vascular diseases (RVDs), in particular diabetic retinopathy, retinal vein occlusion, and retinopathy of prematurity, are leading contributors to blindness. The pathogenesis of RVD involves vessel dilatation, leakage, and occlusion; however, the specific underlying mechanisms remain unclear. Recent findings have indicated that pericytes (PCs), as critical members of the vascular mural cells, significantly contribute to the progression of RVDs, including detachment from microvessels, alteration of contractile and secretory properties, and excessive production of the extracellular matrix. Moreover, PCs are believed to have mesenchymal stem properties and, therefore, might contribute to regenerative therapy. Here, we review novel ideas concerning PC characteristics and functions in RVDs and discuss potential therapeutic strategies based on PCs, including the targeting of pathological signals and cell-based regenerative treatments.

Examining traumatic brain injury as a risk factor for violent offending: testing for cognitive and affective mediation

PurposeWhile prior research has established that traumatic brain injury (TBI) is a risk factor for violent offending, there is little understanding of mechanisms that may underpin this relationship. This is problematic, as a better understanding of these mechanisms could facilitate more effective targeting of treatment. This study aims to address these gaps in the extant literature by examining TBI as a predictor of violent offending and test for mediation effects through cognitive constructs of dual systems imbalance and hostility among a sample of justice-involved youth (JIY).Design/methodology/approachThe Pathways to Desistance data were analyzed. The first three waves of this data set comprising the responses of 1,354 JIY were analyzed. Generalized structural equation modeling was used to test for direct and indirect effects of interest. A bootstrap resampling process was used to compute unbiased standard errors for determining the statistical significance of mediation effects.FindingsLifetime experience of TBI was associated with increased violent offending frequency at follow-up. Hostility significantly mediated this relationship, but dual systems imbalance did not. This indicated that programming focused on reducing hostility among JIY who have experienced TBI could aid in reducing violent recidivism rates.Originality/valueTo the best of the author’s knowledge, this study was the first to identify significant mediation of the relationship between TBI and violent offending through hostility.

Evaluation of Fecal Inflammatory Biomarkers to Identify Bacterial Diarrhea Episodes: Systematic Review and Protocol for the Enterics for Global Health Shigella Surveillance Study.

The measurement of fecal inflammatory biomarkers among individuals presenting to care with diarrhea could improve the identification of bacterial diarrheal episodes that would benefit from antibiotic therapy. We reviewed prior literature in this area and describe our proposed methods to evaluate 4 biomarkers in the Enterics for Global Health (EFGH) Shigella surveillance study. We systematically reviewed studies since 1970 from PubMed and Embase that assessed the diagnostic characteristics of inflammatory biomarkers to identify bacterial diarrhea episodes. We extracted sensitivity and specificity and summarized the evidence by biomarker and diarrhea etiology. In EFGH, we propose using commercial enzyme-linked immunosorbent assays to test for myeloperoxidase, calprotectin, lipocalin-2, and hemoglobin in stored whole stool samples collected within 24 hours of enrollment from participants in the Bangladesh, Kenya, Malawi, Pakistan, Peru, and The Gambia sites. We will develop clinical prediction scores that incorporate the inflammatory biomarkers and evaluate their ability to identify Shigella and other bacterial etiologies of diarrhea as determined by quantitative polymerase chain reaction (qPCR). Forty-nine studies that assessed fecal leukocytes (n = 39), red blood cells (n = 26), lactoferrin (n = 13), calprotectin (n = 8), and myeloperoxidase (n = 1) were included in the systematic review. Sensitivities were high for identifying Shigella, moderate for identifying any bacteria, and comparable across biomarkers. Specificities varied depending on the outcomes assessed. Prior studies were generally small, identified red and white blood cells by microscopy, and used insensitive gold standard diagnostics, such as conventional bacteriological culture for pathogen detection. Our evaluation of inflammatory biomarkers to distinguish diarrhea etiologies as determined by qPCR will provide an important addition to the prior literature, which was likely biased by the limited sensitivity of the gold standard diagnostics used. We will determine whether point-of-care biomarker tests could be a viable strategy to inform treatment decision making and increase appropriate targeting of antibiotic treatment to bacterial diarrhea episodes.

Distinguishing emotional distress from mental disorder in primary care: a qualitative exploration of the Four-Dimensional Symptom Questionnaire.

Primary care clinicians see people experiencing the full range of mental health problems. Determining when symptoms reflect disorder is complex. The Four-Dimensional Symptom Questionnaire (4DSQ) uniquely distinguishes general distress from depressive and anxiety disorders. It may support diagnostic conversations and targeting of treatment. To explore peoples' experiences of completing the 4DSQ and their perceptions of their resulting score profile across distress, depression, anxiety, and physical symptoms. A qualitative study was conducted in the UK with people recruited from primary care and community settings. Participants completed the 4DSQ then took part in semi-structured telephone interviews. They were interviewed about their experience of completing the 4DSQ, their perceptions of their scores across four dimensions, and the perceived utility if used with a clinician. Interviews were transcribed verbatim and data were analysed thematically. Twenty-four interviews were conducted. Most participants found the 4DSQ easy to complete and reported that scores across the four dimensions aligned well with their symptom experience. Distinct scores for distress, depression, and anxiety appeared to support improved self-understanding. Some valued the opportunity to discuss their scores and provide relevant context. Many felt the use of the 4DSQ with clinicians would be helpful and likely to support treatment decisions, although some were concerned about time-limited consultations. Distinguishing general distress from depressive and anxiety disorders aligned well with people's experience of symptoms. Use of the 4DSQ as part of mental health consultations may support targeting of treatment and personalisation of care.

The significance of gut microbiota in the etiology of autoimmune hepatitis: a narrative review.

Autoimmune hepatitis (AIH) is a chronic inflammatory disease of the liver that is mediated by autoimmunity and has complex pathogenesis. Its prevalence has increased globally. Since the liver is the first organ to be exposed to harmful substances, such as gut-derived intestinal microbiota and its metabolites, gut health is closely related to liver health, and the "liver-gut axis" allows abnormalities in the gut microbiota to influence the development of liver-related diseases such as AIH. Changes in the composition of the intestinal microbiota and its resultant disruption of the intestinal barrier and microbial transport are involved in multiple ways in the disruption of immune homeostasis and inflammation, thereby influencing the development of AIH. In terms of the mechanisms involved in immune, the gut microbiota or its metabolites, which is decreased in secondary bile acids, short-chain fatty acids (SCFAs), and polyamines, and increased in lipopolysaccharide (LPS), branched-chain amino acids (BCAA), tryptophan metabolite, amino acid, and bile acid, can disrupt immune homeostasis by activating various immune cells and immune-related signaling pathways, resulting in aberrant activation of the immune system. Clarifying this mechanism has significant clinical implications for the treatment of AIH with drugs that target intestinal microbiota and related signaling pathways. Therefore, this narrative review summarizes the progress in exploring the involvement of gut microbiota in the pathogenesis of AIH, with the aim of helping to improve the precise targeting of therapeutic treatments against AIH for the benefit of clinical AIH treatment.

Optimizing IRE targeting using multi-electrode structure and biomedical multi-output generator

Purpose This paper aims to study the feasibility of proposed method to focus the electroporation ablation by mean of multi-output multi-electrode system. Design/methodology/approach The proposed method has been developed based on a previously designed electroporation system, which has the capabilities to modify the electric field distribution in real time, and to estimate the impedance distribution. Taking into consideration the features of the system and biological tissues, the problem has been addressed in three phases: modeling, control system design and simulation testing. In the first phase, a finite element analysis model has been proposed to reproduce the electric field distribution within the hepatic tissue, based on the characteristics of the electroporation system. Then, a control strategy has been proposed with the goal of ensuring complete ablation while minimizing the affected volume of healthy tissue. Finally, to check the feasibility of the proposal, several representative cases have been simulated, and the results have been compared with those obtained by a traditional system. Findings The proposed method achieves the proposed goal, as part of a complex electroporation system designed to improve the targeting, effectiveness and control of electroporation treatments and serve to demonstrate the feasibility of developing new electroporation systems capable of adapting to changes in the preplanning of the treatment in real-time. Originality/value The work presents a thorough study of control method to multi-output multi-electrode electroporation system by mean of a rigorous numerical simulation.

Hassle Costs versus Information: How Do Prescription Drug Monitoring Programs Reduce Opioid Prescribing?

We study hassle costs versus information provision in explaining how prescription drug monitoring programs (PDMPs) decrease opioid prescribing. PDMPs aim to reduce opioid prescribing through information provision but may also unintentionally affect prescribing through the hassle of required record checks. We analyze Kentucky’s landmark PDMP to disentangle these two mechanisms. Hassle costs reduce opioid prescribing across the board, including to opioid-naïve patients; however, physicians continue to prescribe opioids to patients who would benefit the most. Although information also affects prescribing, hassle costs explain the majority of the decline. Introducing a cost to prescribing high-risk medications improves the targeting of treatment. (JEL H75, I11, I12, I18, L65)

Real-world performance and clinical outcome of comprehensive genomic profiling of gastrointestinal tumors: High-volume, single-center experience.

727 Background: In order to identify targetable mutations, the Comprehensive Genomic Profiling (CGP) is an important tool. Technologies like extensive genomic NGS panels analyze multiple genes and biomarkers in a single assay. With multi-omics analysis, clinicians could increase the possibility to provide a tailored therapy. In literature, evidence about clinical applicability and performance of NGS are mainly derived from clinical trials and real-world experiences are lacking. Methods: On these bases, we performed a retrospective analysis of CGP data from a cohort comprising 1450 patients (pts) with a diagnosis of gastrointestinal tumor. The primary objective was to estimate adequacy and quality of CGP. As secondary objective, we identified mutations with an available but not already standard of care targeted treatment (TT), defined as gain, and we collected clinical data in those pts. The genomic analysis was performed using the FoundationOne CDx panel. Clinical impact of treated vs not-treated pts with TT was evaluated using 1:1 propensity score matching, according to tumor type, treatment line and gain gene mutation. Survival outcomes were estimated with Kaplan-Meier method and compared with Hazard Ratio (HR), univariate Cox regression. Results: In our population, 1310/1450 samples (90.3%) were adequate for NGS analysis. Failure rates were higher in biopsy samples compared to resections (p < 0.0001); the first cause was insufficient tumor DNA (p = 0.0020) especially for hepato-biliary-pancreatic neoplasms. Low-quality reports observed in 252/1310 (19.2%) were mainly due to inadequate DNA quality or extraction, regardless samples type. Gain molecular alterations were identified in 355/1450 pts (24.5%), corresponding to 28.1% of cases with informative reports and metastatic disease. Among them, based on the presence of gain alteration, 15.2% of pts received TT. Overall survival did not significantly differ in pts with and without gain mutations (HR 1.10, 95% CI: 0.93-1.30). An exploratory analysis of 17 matched treated vs untreated pts showed better overall survival (HR 0.26, 95% CI: 0.08-0.79) for the treated ones. More than 50% of pts with gain mutation did not received TT due to drug unavailability (lack of trials, expanded access programs or off-label use) or decreasing of general conditions (38.1%). Conclusions: The selection of appropriate samples and a bidirectional pathologist-clinician collaboration is crucial to enhance the feasibility of CGP. In our wide population, a relevant proportion of metastatic gastrointestinal pts presented a druggable gene alteration with a potential improvement of outcomes in case of availability of TT. Moreover, the time of testing is important to do not lose the right window of opportunity, especially in the metastatic setting.

Population-level, patient-reported outcomes: a case study regarding a public health intervention that involves patients with life-limiting illnesses.

Dying and death are public health concerns, but little is known about public health interventions that target populations living with life-limiting illnesses. This gap makes it difficult to identify best-practice public health interventions for this population and to achieve public health objectives. The study aimed to describe a public health intervention that intends to improve population-level outcomes using point-of-care and patient-reported outcomes. A case study approach, informed by the Organization for Economic Co-operation and Development's (OECD) Best-Practice Public Health Framework, was used to describe coverage, effectiveness, and equity using mixed methods. Data from 2012 to 2022 were analyzed. Over the 10-year period, the number of deaths recorded in the programme (n = 16,358 to 32,421, +98.2%) as well as the percentage of the population that might benefit from palliative care increased (14.8% to 25.1%). The median age of those admitted for care (74 to 77 years) and the proportion of services participating in the programme located in outer regional and remote areas of Australia increased (2012: 59; 2022: 94; +5.4%). The access by patients that experience the greatest socioeconomic disadvantage decreased (2012: 18.2% n = 4,918; 2022: 15.9% n = 9,525). Improvements in relation to moderate distress related to pain were identified (2012: 63% n = 8,751, 2022: 69% n = 13,700), and one in five instances of severe distress related to pain did not improve (2012: 20% n = 781; 2022: 19% n = 635). Population-level, patient-reported outcome data are useful and necessary in addressing public health objectives in populations with life-limiting illnesses. Our application of the OECD's Best-Practice Public Health Framework has helped to identify and describe a national intervention that may be transferred to other settings to address health promotion objectives. This may help improve the targeting of treatments to improve pain and issues related to equity.

Investigating the anticancer and anti-angiogenic effects of graphene oxide nanoparticles containing 6-gingerol modified with chitosan and folate

Abstract Objective The use of nanocarriers to improve the targeting of treatment plays a key role in the treatment of many diseases, including cancer. This study was carried out to synthesize graphene oxide (GO) containing 6-gingerol (Ging) modified with chitosan (CS)-folic acid (FA) nanoparticles (Ging-GO-CS-FA) to improve the anti-cancer effects of Ging. Methods After the synthesis of nanoparticles, the average size, surface charge, and dispersion index (DPI) of nanoparticles were analyzed by the dynamic light scattering (DLS) method. Field emission scanning electron microscope (FESEM) and Fourier transform infrared spectroscopy (FTIR) were utilized to assess the morphology and functional groups of synthesized nanoparticles, respectively. The 2,5-diphenyl-2H-tetrazolium bromide (MTT) method was performed to assess the toxicity effect of nanoparticles on different types of cancer cells. The antioxidant power of nanoparticles was evaluated by ABTS and DPPH methods. In addition, the chorioallantoic membrane (CAM) test was conducted to investigate the anti-angiogenic effects of nanoparticles. Finally, the real-time quantitative PCR (qPCR) method was carried out to detect the changes in the expression of angiogenic and antioxidant genes in cancer cells. Results The nanoparticles have an average size of 73.21 nm, a DPI of 0.27, and a surface charge of 29.5. The encapsulation rate of Ging in nanoparticles was reported to be 81.7%. According to the MTT test, the most sensitive cell line to the Ging-GO-CS-FA nanoparticles was reported to be gastric cancer cells (IC50 ~ 27). The results of the antioxidant test showed the high antioxidant power of nanoparticles in the laboratory environment by inhibiting ABTS and DPPH free radicals. The pro-oxidant power of Ging-GO-CS-FA against cancer cells was confirmed by reducing the amount of the superoxide dismutase (SOD) gene in the treated cells. The decreasing effects of Ging-GO-CS-FA on angiogenesis were observed by reducing the average length, the number of blood vessels, average height, and weight of treated embryos. In addition, the decrease in the expression of VEGF and VEGF-R genes confirmed the anti-angiogenic of Ging-GO-CS-FA. Conclusions These results show the promising effect of Ging-GO-CS-FA on gastric cancer cells by inhibiting angiogenesis and increasing the level of oxidants.

ADHD as a Predictor of Quicker Time to Violent Recidivism and a Moderator of the Exposure to Violence-Violent Recidivism Relationship.

Research on the role that attention-deficit hyperactivity disorder (ADHD) plays as a moderator of the relationship between exposure to violence and violent recidivism is limited. The Pathways to Desistance data were analyzed to examine these relationships. Survival analysis was used to examine ADHD as a risk factor predicting time to violent recidivism. Cox-proportional hazard modeling was used to assess the impact of ADHD on violent recidivism risk and examine ADHD as a moderator of the relationship between exposure to violence and violent recidivism. Results indicated that ADHD predicted quicker time to recidivism. The effect of witnessed violence was significantly weaker for participants with ADHD at baseline than those without ADHD at baseline. The direct effect of ADHD diagnosis at baseline on violent recidivism risk was only significant when the hypothesized interaction terms were included in the model. These findings suggest that individuals with ADHD may be less vulnerable to the impact of witnessing violence on their own risk for perpetrating violence. Effective targeting of treatment should be understood within this context.