Accuracy study of Angiotensin 1-7 composite index test to predict pulmonary fibrosis and guide treatment.

BACKGROUND: Pulmonary fibrosis can develop after acute respiratory distress syndrome (ARDS). The hypothesis is we are able to measure phenotypes that lie at the origin of ARDS severity and fibrosis development. The aim is an accuracy study of prognostic circulating biomarkers. METHODS: A longitudinal study followed COVID-related ARDS patients with medical imaging, pulmonary function tests and biomarker analysis, generating 444 laboratory data. Comparison to controls used non-parametrical statistics; p < 0·05 was considered significant. Cut-offs were obtained through receiver operating curve. Contingency tables revealed predictive values. Odds ratio was calculated through logistic regression. RESULTS: Angiotensin 1-7 beneath 138 pg/mL defined Angiotensin imbalance phenotype. Hyper-inflammatory phenotype showed a composite index test above 34, based on high Angiotensin 1-7, C-Reactive Protein, Ferritin and Transforming Growth Factor-ß. Analytical study showed conformity to predefined goals. Clinical performance gave a positive predictive value of 95 % (95 % confidence interval, 82 %-99 %), and a negative predictive value of 100 % (95 % confidence interval, 65 %-100 %). Those severe ARDS phenotypes represented 34 (Odds 95 % confidence interval, 3-355) times higher risk for pulmonary fibrosis development (p < 0·001). CONCLUSIONS: Angiotensin 1-7 composite index is an early and objective predictor of ARDS evolving to pulmonary fibrosis. It may guide therapeutic decisions in targeted phenotypes.

Sex-specific Prediction of Cardiogenic Shock After Acute Coronary Syndromes: The SEX-SHOCK Score.

BACKGROUND: and aims: Cardiogenic shock (CS) remains the primary cause of in-hospital death after acute coronary syndromes (ACS), with its plateauing mortality rates approaching 50%. To test novel interventions, personalized risk prediction is essential. The ORBI (Observatoire Régional Breton sur l'Infarctus) score represents the first-of-its-kind risk score to predict in-hospital CS in ACS patients undergoing percutaneous coronary intervention (PCI). However, its sex-specific performance remains unknown, and refined risk prediction strategies are warranted. METHODS: This multinational study included a total of 53 537 ACS patients without CS on admission undergoing PCI. Following sex-specific evaluation of ORBI, regression and machine-learning models were used for variable selection and risk prediction. By combining best-performing models with highest-ranked predictors, SEX-SHOCK was developed, and internally and externally validated. RESULTS: The ORBI score showed lower discriminative performance for the prediction of CS in females than males in Swiss (AUC [95% CI]: 0.78 [0.76-0.81] vs. 0.81 [0.79-0.83]; p=0.048) and French ACS patients (0.77 [0.74-0.81] vs. 0.84 [0.81-0.86]; p=0.002). The newly developed SEX-SHOCK score, now incorporating ST-segment elevation, creatinine, C-reactive protein, and left ventricular ejection fraction, outperformed ORBI in both sexes (females: 0.81 [0.78-0.83]; males: 0.83 [0.82-0.85]; p<0.001), which prevailed following internal and external validation in RICO (females: 0.82 [0.79-0.85]; males: 0.88 [0.86-0.89]; p<0.001) and SPUM-ACS (females: 0.83 [0.77-0.90], p=0.004; males: 0.83 [0.80-0.87], p=0.001). CONCLUSIONS: The ORBI score showed modest sex-specific performance. The novel SEX-SHOCK score provides superior performance in females and males across the entire spectrum of ACS, thus providing a basis for future interventional trials and contemporary ACS management.

Severity of Rolling Reconstituted High Moisture Barley on Ensiling Characteristics and In Vitro Ruminal Fermentation.

Barley grain sources with variable kernel sizes makes adequate and consistent processing of kernels challenging. This study evaluated how the severity of processing for reconstituted high moisture (65% on DM basis) barley (RHB) affects ensiling characteristics and in vitro ruminal fermentation. Three independent sources of light (<630 g/500 mL) and heavy (>670 g/500 mL) barley were blended to create 4 sources of variable kernel sized barley (646 g/500 mL). Reconstituted barley was rolled through a roller gap width of 1.40 (RHBF), 1.86 (RHBM), or 2.31 mm (RHBC) and ensiled for 1 or 5 mo with dry rolled barley (DRB; roller gap width 1.86 mm) used as a control. The 1-mo RHB and the DRB were further evaluated using the artificial rumen technique (RUSITEC) to investigate the effects of severity of processing for RHB on ruminal fermentation, and gas, methane, and microbial protein production. Using a randomized complete block design (n = 4), 16 fermenters from 2 RUSITEC apparatuses were used to assess the 4 sources and 4 processing treatments. The addition of water increased kernel width before rolling and resulted in increased kernel length, width, and thickness for RHB relative to dry rolled barley. Increasing processing severity for RHB linearly increased kernel width. The percentage of fine particles (<1.18 mm) was greater for DRB than RHBF, but did not differ by processing severity for RHB. Dry matter, organic matter, and starch disappearance were not different between DRB and RHBF, but linearly increased with increasing processing severity for RHB. Fermenter pH tended to be less for DRB relative to RHBF. In conclusion, the reduction in fine particles with the addition of water for RHB may prevent a decline in fermenter pH and when processed to achieve the same PI using a smaller roller gap width, yielded similar DM and OM disappearance suggesting a lesser risk for low ruminal pH without compromising digestibility.

Employing Magnetic Resonance Histology for Precision Chronic Limb-Threatening Ischemia Treatment Planning.

OBJECTIVE: Recent randomized controlled trials have demonstrated a notable prevalence of immediate technical failures (ITFs) in percutaneous vascular interventions (PVIs) for complex arterial lesions associated with chronic limb-threatening ischemia (CLTI). Current imaging modalities present inherent limitations in identifying these lesions, making it challenging to determine the most suitable candidates for PVI. We present a novel preprocedural magnetic resonance imaging (MRI) histology protocol for identifying lesions that might present a higher rate of immediate and mid-term PVI failure. METHODS: 22 patients (13 females, average age 65.8±9.72 years) scheduled for PVI were prospectively enrolled and underwent 3T MRI using ultrashort echo time and 'Steady-State Free Precession' contrasts to characterize target lesions prior to PVI. Lesions were scored as 'hard' if >50% of the lumen was occluded by hard components (calcium/dense collagen) on MRI in the hardest cross-section. Two readers evaluated MRI datasets. TASC/GLASS/WIFi scoring was performed based on intraprocedural angiograms and chart review. The relationship between MRI scoring, TASC/GLASS scoring and procedural outcomes was investigated using univariate analysis. Mid-term follow-up (revascularization and amputation rate) was recorded at 3 months and 6 months, post-intervention. RESULTS: Our cohort of 22 patients yielded 40 target lesions. 5 lesions were excluded (2 non-diagnostic image quality, 3 PVIs were ultimately diagnostic only). 6 lesions (17%) were scored as 'hard'. MRI-scored 'hard' lesions had higher proportion of ITF ('hard' vs 'soft' 83% (n/N=5/6) vs. 3% (n/N=1/29), p<.001). 'Hard' versus 'soft' MRI scoring was the only factor significantly associated with immediate PVI technical success (p < .001), as opposed to TASC/GLASS scoring. Both at 3 months and 6 months after PVI, the re-intervention rate was significantly higher among those lesions which were scored 'hard' on MRI (3-month: hard: 80% vs. soft: 16%, p =.011 6-month: hard: 80%, soft: 27%, p=.047). CONCLUSIONS: MRI histology could be a valuable tool for optimizing PVI patient selection and treatment strategies.

Stakeholder-informed positivity thresholds for disease markers and risk scores: a methodological framework and an application in obstructive lung disease.

OBJECTIVE: A positivity threshold is often applied to markers or predicted risks to guide disease management. These rules are often decided exclusively by clinical experts despite being sensitive to the preferences of patients and general public as ultimate stakeholders. STUDY DESIGN AND SETTING: We propose an analytical framework for quantifying the net benefit of an evidence-based positivity threshold based on combining preference-sensitive (e.g., how individuals weight benefits and harms of treatment) and preference-agnostic (e.g., the magnitude of benefit and the risk of harm) parameters. We propose parsimonious choice experiments to elicit preference-sensitive parameters from stakeholders, and evidence synthesis to quantify the value of preference-agnostic parameters. We apply this framework to maintenance azithromycin therapy for chronic obstructive pulmonary disease (COPD) using a discrete choice experiment (DCE) to estimate preference weights for attribute level associated with treatment. We identify the positivity threshold on 12-month moderate or severe exacerbation risk that would maximize the net benefit of treatment in terms of severe exacerbations avoided. RESULTS: In the case study, the prevention of moderate and severe exacerbations (benefits) and the risk of hearing loss and gastrointestinal symptoms (harms) emerged as important attributes. 477 respondents completed the DCE survey. Relative to each percent risk of severe exacerbation, preference weights for each percent risk of moderate exacerbation, hearing loss, and gastrointestinal symptoms were 0.395 (95%CI 0.338-0.456), 1.180 (95%CI 1.071-1.201) and 0.253 (95%CI 0.207-0.299), respectively. The optimal threshold that maximized net benefit was to treat patients with a 12-month risk of moderate or severe exacerbations ≥12%. CONCLUSION: The proposed methodology can be applied to many contexts where the objective is to devise positivity thresholds that need to incorporate stakeholder preferences. Applying this framework to COPD pharmacotherapy resulted in a stakeholder-informed treatment threshold that was substantially lower than the implicit thresholds in contemporary guidelines.

Microgel delivery systems of functional substances for precision nutrition.

Microgels delivery system have great potential in functional substances encapsulation, protection, release, precise delivery and nutritional intervention. Microgel is a three-dimensional network structure formed by physical or chemical crosslinking of biopolymers, whose characteristics include dispersion and swelling, stable structure, small volume and high specific surface area, and is a special kind of colloid. In this chapter, the common wall materials for preparing food grade microgels, and the main preparation principles, methods, advantages and disadvantages of microgels loaded with functional substances were firstly reviewed. Then the main characteristics of microgel as delivery system, such as deformability, high encapsulation, stimulus-responsive release and targeted delivery, and its potential benefits in intervening chronic diseases were summarized. Finally, the applications of microgel delivery system for functional substance in the field of precision nutrition were discussed. This chapter will help to design of next-generation advanced targeting microgel delivery system, and realize precision nutrition intervention of food functional substances on body health.

Future development trend of food-borne delivery systems of functional substances for precision nutrition.

BACKGROUND: Precision nutrition, a personalized nutritional supplementation model, is widely acknowledged for its significant impact on human health. Nevertheless, challenges persist in the advancement of precision nutrition, including consumer dietary behaviors, nutrient absorption, and utilization. Thus, the exploration of effective strategies to enhance the efficacy of precision nutrition and maximize its potential benefits in dietary interventions and disease management is imperative. SCOPE AND APPROACH: The primary objective of this comprehensive review is to synthesize and assess the latest technical approaches and future prospects for achieving precision nutrition, while also addressing the existing constraints in this field. The role of delivery systems is pivotal in the realization of precision nutrition goals. This paper outlines the potential applications of delivery systems in precision nutrition and highlights key considerations for their design and implementation. Additionally, the review offers insights into the evolving trends in delivery systems for precision nutrition, particularly in the realms of nutritional fortification, specialized diets, and disease prevention. KEY FINDINGS AND CONCLUSIONS: By leveraging computer data collection, omics, and metabolomics analyses, this review scrutinizes the lifestyles, dietary patterns, and health statuses of diverse organisms. Subsequently, tailored nutrient supplementation programs are devised based on individual organism profiles. The utilization of delivery systems enhances the bioavailability of functional compounds and enables targeted delivery to specific body regions, thereby catering to the distinct nutritional requirements and disease prevention needs of consumers, with a particular emphasis on special populations and dietary preferences.

The Conundrum of Mechanics Versus Genetics in Congenital Hydrocephalus and Its Implications for Fetal Therapy Approaches: A Scoping Review.

Recent advances in gene therapy, particularly for single-gene disorders (SGDs), have led to significant progress in developing innovative precision medicine approaches that hold promise for treating conditions such as primary hydrocephalus (CH), which is characterized by increased cerebrospinal fluid (CSF) volumes and cerebral ventricular dilation as a result of impaired brain development, often due to genetic causes. CH is a significant contributor to childhood morbidity and mortality and a driver of healthcare costs. In many cases, prenatal ultrasound can readily identify ventriculomegaly as early as 14-20 weeks of gestation, with severe cases showing poor neurodevelopmental outcomes. Postnatal surgical approaches, such as ventriculoperitoneal shunts, do not address the underlying genetic causes, have high complication rates, and result in a marginal improvement of neurocognitive deficits. Prenatal somatic cell gene therapy (PSCGT) promises a novel approach to conditions such as CH by targeting genetic mutations in utero, potentially improving long-term outcomes. To better understand the pathophysiology, genetic basis, and molecular pathomechanisms of CH, we conducted a scoping review of the literature that identified over 160 published genes linked to CH. Mutations in L1CAM, TRIM71, MPDZ, and CCDC88C play a critical role in neural stem cell development, subventricular zone architecture, and the maintenance of the neural stem cell niche, driving the development of CH. Early prenatal interventions targeting these genes could curb the development of the expected CH phenotype, improve neurodevelopmental outcomes, and possibly limit the need for surgical approaches. However, further research is needed to establish robust genotype-phenotype correlations and develop safe and effective PSCGT strategies for CH.

Lectin-glycan interactions: a comprehensive cataloguing of cancer-associated glycans for biorecognition and bio-alteration: a review.

This comprehensive review meticulously compiles data on an array of lectins and their interactions with different cancer types through specific glycans. Crucially, it establishes the link between aberrant glycosylation and cancer types. This repository of lectin-defined glycan signatures, assumes paramount importance in the realm of cancer and its dynamic nature. Cancer, known for its remarkable heterogeneity and individualized behaviour, can be better understood through these glycan signatures. The current review discusses the important lectins and their carbohydrate specificities, especially recognizing glycans of cancer origin. The review also addresses the key aspects of differentially expressed glycans on normal and cancerous cell surfaces. Specific cancer types highlighted in this review include breast cancer, colon cancer, glioblastoma, cervical cancer, lung cancer, liver cancer, and leukaemia. The glycan profiles unveiled through this review hold the key to tailor-made treatment and precise diagnostics. It opens up avenues to explore the potential of targeting glycosyltransferases and glycosidases linked with cancer advancement and metastasis. Armed with knowledge about specific glycan expressions, researchers can design targeted therapies to modulate glycan profiles, potentially hampering the advance of this relentless disease.

Multidisciplinary approaches to study anaemia with special mention on aplastic anaemia (Review).

Anaemia is a common health problem worldwide that disproportionately affects vulnerable groups, such as children and expectant mothers. It has a variety of underlying causes, some of which are genetic. A comprehensive strategy combining physical examination, laboratory testing (for example, a complete blood count), and molecular tools for accurate identification is required for diagnosis. With nearly 400 varieties of anaemia, accurate diagnosis remains a challenging task. Red blood cell abnormalities are largely caused by genetic factors, which means that a thorough understanding requires interpretation at the molecular level. As a result, precision medicine has become a key paradigm, utilising artificial intelligence (AI) techniques, such as deep learning and machine learning, to improve prognostic evaluation, treatment prediction, and diagnostic accuracy. Furthermore, exploring the immunomodulatory role of vitamin D along with biomarker­based molecular techniques offers promising avenues for insight into anaemia's pathophysiology. The intricacy of aplastic anaemia makes it particularly noteworthy as a topic deserving of concentrated molecular research. Given the complexity of anaemia, an integrated strategy integrating clinical, laboratory, molecular, and AI techniques shows a great deal of promise. Such an approach holds promise for enhancing global anaemia management options in addition to advancing our understanding of the illness.

Major Depression in Comorbidity with Substance use Disorders: Patients' Features and Clinical-Neurobiological Rationale of Antidepressant Treatments.

The frequent co-occurrence of major depressive disorder (MDD) and substance use disorders (SUDs) entails significant clinical challenges. Compared to patients with MDD alone, patients with MDD and SUD often show increased anhedonia, emotional blunting, and impaired cognitive function. These symptoms lead to an inability to control cravings, more substance use, increased relapse rates, and poor adherence to the treatment. This fosters a detrimental cycle leading to more severe depressive symptoms, functional impairment, and chronicity, culminating in heightened morbidity, mortality, and healthcare resource utilization. Data on antidepressant treatment of MDD-SUD patients are inconclusive and often conflicting because of a number of confounding factors in clinical trials or difficulty in dissecting the specific contributions of pharmacological versus psychological interventions in real-world studies. The patient's unique clinical features and specific SUD and MDD subtypes must be considered when choosing treatments. Ideally, drug treatment for MDD-SUD should act on both conditions and address core symptoms such as anhedonia, craving, and cognitive dysfunction while ensuring minimal emotional blunting, absence of drug interactions, and no addictive potential. This approach aims to address unmet needs and optimize the outcomes in a clinical population often underrepresented in treatment paradigms.

Epitranscriptome: A Novel Regulatory Layer during Atherosclerosis Progression.

RNA modifications have recently gained great attention due to their extensive regulatory effects in a wide range of cellular networks and signaling pathways. In cardiovascular diseases (CVDs), several RNA changes, called "epitranscriptome" alterations, are found in all RNA molecules (tRNA, rRNA, mRNA, and ncRNAs). Unlike the epigenetic process, which influences the progression of atherosclerosis (AS), its transcriptional and post-transcriptional regulatory mechanisms are still unknown. Here, we described the main epitranscriptome signs to provide new insights into AS, including m6A, m5C, m1A, m7G, Ψ, and A-to-I editing. Moreover, we also included all current known RNA-- modifier-targeting, including small molecular inhibitors or activators, mainly designed against m6A- and m5A-related enzymes, such as METTL3, FTO, and ALKBH5. Finally, since only a few drugs, such as azacitidine and tazemetostat, targeting the DNA epigenome, have been approved by the FDA, the next challenge would be to identify molecules for targeting the RNA epitranscriptome. To date, total Panax notoginseng total saponin could reduce vascular hyperplasia via Wilms' tumor-associated protein-1 m6A-dependent. Indeed, a virtual screening allowed us to individuate a phytomolecule, the rhein, which acts as an FTO inhibitor by increasing mRNA m6A levels. In this review, we highlighted the RNA epitranscriptome pathways implicated in AS, describing their biological functions and their connections to the disease. The identification of epitranscriptome- sensitive pathways could provide novel opportunities to find predictive, diagnostic, and prognostic biomarkers for precision medicine.

Multi-Biomarker Profiling for Precision Diagnosis of Lung Cancer.

Multi-biomarker analysis can enhance the accuracy of the single-biomarker analysis by reducing the errors caused by genetic and environmental differences. For this reason, multi-biomarker analysis shows higher accuracy in early and precision diagnosis. However, conventional analysis methods have limitations for multi-biomarker analysis because of their long pre-processing times, inconsistent results, and large sample requirements. To solve these, a fast and accurate precision diagnostic method is introduced for lung cancer by multi-biomarker profiling using a single drop of blood. For this, surface-enhanced Raman spectroscopic immunoassay (SERSIA) is employed for the accurate, quick, and reliable quantification of biomarkers. Then, it is checked the statistical relation of the multi-biomarkers to differentiate between healthy controls and lung cancer patients. This approach has proven effective; with 20 µL of blood serum, lung cancer is diagnosed with 92% accuracy. It also accurately identifies the type and stage of cancer with 87% and 85%, respectively. These results show the importance of multi-biomarker analysis in overcoming the challenges posed by single-biomarker diagnostics. Furthermore, it markedly improves multi-biomarker-based analysis methods, illustrating its important impact on clinical diagnostics.

Climate Change Projections for Stroke Incidence in Taiwan: Impact of 2 °C and 4 °C Global Warming Level.

OBJECTIVES: This study aimed to establish the exposure-lag-response effect between daily maximum temperature and stroke-related emergency department visits and to project heat-induced stroke impacts under global warming levels (GWL) of 2 °C and 4 °C. METHODS: Stroke-related emergency department visits in Taiwan from 2001 to 2020 were identified using the National Health Insurance Research Database (NHIRD). The study population consisted of 1,100,074 initial stroke cases matched with 2,200,148 non-stroke controls. We employed Distributed Lag Nonlinear Models (DLNM) in a case-crossover study to investigate the association between temperature and stroke. Generalized Estimating Equations (GEE) models with a Poisson function were used to correlate high-temperature exposure with annual stroke incidence rates. Projections were made under two global warming scenarios, GWL 2.0 °C and 4.0 °C, using Coupled General Circulation Model (GCMs). Baseline data from 1995 to 2014 were transformed for spatial distribution at the township level. Geographic Information System (GIS) spatial analysis was performed using Quantum GIS 3.2.0 software. RESULTS: DLNM exposure-lag-response effect revealed that daily maximum temperature exceeding 34 °C significantly increased the risk of stroke-related emergency department visits, particularly for ischemic stroke. Under the 2 °C GWL scenario, the frequency of days with temperatures surpassing 34 °C is projected to rise substantially by the median year of 2042, with a further increase to 92.6 ± 18.0 days/year by 2065 under the 4 °C GWL scenario. Ischemic stroke showed the highest increase in temperature-related incidence rates, notably rising from 7.80% under the GWL 2 °C to 36.06% under the GWL 4 °C. Specifically, the annual temperature-related incidence rate for ischemic stroke is expected to increase significantly by 2065. Regions such as Taichung, Hsinchu, Yilan, and Taitung demonstrated pronounced changes in heat-related ischemic stroke incidence under the GWL 4 °C. CONCLUSIONS: The findings emphasize the importance of addressing temperature-related stroke risks, particularly in regions projected to experience significant temperature increases. Effective mitigation strategies are crucial to reduce the impact of rising temperatures on stroke incidence and safeguard public health.

Accuracy and clinical fit of milled versus rapid prototyped orthognathic surgical splints.

Three-dimensional (3D) printing has slowly become an integral part of orthognathic surgery. However, there is a lack of studies evaluating accuracy of orthognathic surgical splints fabricated from subtractive milling versus additive 3D printing. The primary aim of this in vitro study was to compare the differences in trueness between milled and 3D-printed splints, while the secondary aim was to compare the differences in clinical fit of these splints. A sample of eight patients was selected, and STL files of the final orthognathic surgical splint were used to fabricate three splints for each of the eight cases. The first splint was fabricated by subtractive milling (SM), whereas the second and third splints were 3D printed with Digital Light Processing (DLP) and Laser Stereolithography (SLA), respectively. Paired superimposition of scans was performed using a reference model. The clinical fit of the splints to the printed models was also assessed. The mean root mean square (RMS) deviations for the SM, SLA, and DLP were 0.11 ± 0.02, 0.16 ± 0.02 and 0.14 ± 0.02 respectively. The post-hoc analysis showed that the SM splints had the highest accuracy (p<0.01). However, DLP splints showed the best clinical fit, followed by SM and SLA. In conclusion, splints fabricated by SM were more accurate than those fabricated by 3D printing, although this difference may not be clinically significant. The site, rather than the magnitude of the errors, may have a greater effect on the clinical usability of splints. In general, SM and DLP splints demonstrated a good clinical fit and were suitable for the fabrication of surgical splints.

Addressing immortal time bias in precision medicine: Practical guidance and methods development.

OBJECTIVE: To compare theoretical strengths and limitations of common immortal time adjustment methods, propose a new approach using multiple imputation (MI), and provide practical guidance for using MI in precision medicine evaluations centered on a real-world case study. STUDY SETTING AND DESIGN: Methods comparison, guidance, and real-world case study based on previous literature. We compared landmark analysis, time-distribution matching, time-dependent analysis, and our proposed MI application. Guidance for MI spanned (1) selecting the imputation method; (2) specifying and applying the imputation model; and (3) conducting comparative analysis and pooling estimates. Our case study used a matched cohort design to evaluate overall survival benefits of whole-genome and transcriptome analysis, a precision medicine technology, compared to usual care for advanced cancers, and applied both time-distribution matching and MI. Bootstrap simulation characterized imputation sensitivity to varying data missingness and sample sizes. DATA SOURCES AND ANALYTIC SAMPLE: Case study used population-based administrative data and single-arm precision medicine program data from British Columbia, Canada for the study period 2012 to 2015. PRINCIPAL FINDINGS: While each method described can reduce immortal time bias, MI offers theoretical advantages. Compared to alternative approaches, MI minimizes information loss and better characterizes statistical uncertainty about the true length of the immortal time period, avoiding false precision. Additionally, MI explicitly considers the impacts of patient characteristics on immortal time distributions, with inclusion criteria and follow-up period definitions that do not inadvertently risk biasing evaluations. In the real-world case study, survival analysis results did not substantively differ across MI and time distribution matching, but standard errors based on MI were higher for all point estimates. Mean imputed immortal time was stable across simulations. CONCLUSIONS: Precision medicine evaluations must employ immortal time adjustment methods for unbiased, decision-grade real-world evidence generation. MI is a promising solution to the challenge of immortal time bias.

Human-derived monoclonal autoantibodies as interrogators of cellular proteotypes in the brain.

A major aim of neuroscience is to identify and model the functional properties of neural cells whose dysfunction underlie neuropsychiatric illness. In this article, we propose that human-derived monoclonal autoantibodies (HD-mAbs) are well positioned to selectively target and manipulate neural subpopulations as defined by their protein expression; that is, cellular proteotypes. Recent technical advances allow for efficient cloning of autoantibodies from neuropsychiatric patients. These HD-mAbs can be introduced into animal models to gain biological and pathobiological insights about neural proteotypes of interest. Protein engineering can be used to modify, enhance, silence, or confer new functional properties to native HD-mAbs, thereby enhancing their versatility. Finally, we discuss the challenges and limitations confronting HD-mAbs as experimental research tools for neuroscience.

Comprehensive genomic profiling in multiple cancer types: A comparative analysis of the National Biobank Consortium of Taiwan and clinical practice cohorts.

BACKGROUND: This retrospective study analyzed tumor tissue profiling data to assess the potential of comprehensive genomic profiling (CGP) for patient care across diverse solid tumors. MATERIAL AND METHODS: Patients with newly diagnosed or recurrent stage IIIB or IV lung adenocarcinoma with a null immunophenotype and esophageal, gastric, pancreatic, or bile duct cancer between January 2020 and July 2023 at two medical centers in Taiwan were included. One cohort was a part of the National Biobank Consortium of Taiwan project, whereas the other consisted of patients undergoing routine clinical practice. Tumor samples were subjected to CGP using FoundationOne®CDx, with therapeutic implications determined using OncoKB classification. RESULTS: FoundationOne®CDx testing of 574 patients was successful in 456 (79.4%) patients. Clinically actionable genomic alterations were detected in 21.1% (96/456) of the patients, including 17.5%, 2.9%, and 0.7% of patients with evidence levels 1, 2, and 3, respectively. Lung adenocarcinoma accounted for the largest proportion of samples with at least one actionable gene alteration (63.2%), followed by bile duct (26.9%), gastric (17.6%), esophageal (4.0%), and pancreatic (3.1%) cancers. Based on CGP results, 43 patients (9.4%) received matched targeted therapy. The median overall survival of patients who received matched therapy or not was 26.1 months (95% confidence interval (CI), 16.7-35.5 months) and 10.6 months (95% CI, 8.1-13.1 months; hazard ratio, 0.28, 95% CI, 0.14-0.55, p < 0.001), respectively. CONCLUSIONS: This study provides comprehensive insights into the genomic profiles of diverse cancers in Taiwan, highlighting the crucial role of CGP in identifying actionable genomic alterations and guiding effective therapeutic strategies in real-world practice.

Cellular responses following ex vivo lung exposure to the nerve agent VX - Potential for additional treatment targets?

Following inhalation exposure to organophosphorus nerve agents, symptoms rapidly develop and severe respiratory symptoms, such as bronchorrhea and bronchoconstriction are the leading causes of lethality. Nerve agent-induced lung injury is little investigated and the standard treatment for symptomatic relief targets the enzyme acetylcholinesterase and muscarinic acetylcholine and GABAergic receptors. In the present study, cellular responses in lung tissue during the acute (40 min) and extended phase (24 h) following severe exposure to the nerve agent VX have been investigated using an ex vivo rat precision-cut lung slice model including electrostimulation to induce a cholinergic response. Changes in protein amount, cell viability, together with, inflammatory and oxidative stress markers have been determined in both the lung tissue and incubation medium. During the acute phase, VX caused significantly increased airway contraction and decreased airway relaxation. Five micromolar of VX did not affect the sample protein levels and cell viability in lung tissue. Among seven markers of cellular responses investigated in the lung tissue, increased levels of heme oxygenase-1 and matrix metalloproteinase-9 together with decreased levels of glutathione in the incubation medium were observed in the acute phase following VX-exposure compared to electrostimulation only. No difference in cellular response was observed following VX-exposure for 24 h compared to the air control. In comparison, LPS-exposure resulted in time-dependent changes in all markers of inflammation and oxidative response. In conclusion, the present study demonstrated VX-specific patterns of oxidative responses in the lung, as well as, signs of inflammatory response and remodelling of extracellular matrix. These potential mechanisms of tissue injury should be further investigated for their potential as additional therapeutic targets during the acute phase of intoxication.

Initial dosage optimization of olanzapine in patients with bipolar disorder based on model-informed precision dosing: a study from the real world.

Objectives: Olanzapine is used for treating bipolar disorder (BPD); however, the optimal initial dosing regimen is unclear. The present study aimed to investigate the optimal olanzapine initial dosage in patients with BPD via model-informed precision dosing (MIPD) based on a real-world study. Methods: Thirty-nine patients with BPD from the real-world study were collected to construct the MIPD model. Results: Weight, combined used quetiapine influenced olanzapine clearances in patients with BPD, where the clearance rates were 0.152:1 in patients with or without quetiapine under the same weight. We simulated olanzapine doses once a day or twice a day, of which twice a day was optimal. Without quetiapine, for twice-a-day olanzapine doses, 0.80, 0.70, and 0.60 mg/kg/day were suitable for 40- to 56-kg BPD patients, 56- to 74-kg BPD patients, and 74- to 100-kg BPD patients, respectively. With quetiapine, for twice-a-day olanzapine doses, 0.05 mg/kg/day was suitable for 40- to 100-kg BPD patients. Conclusion: This study was the first to investigate the optimal olanzapine initial dosage in patients with BPD via MIPD based on a real-world study, providing clinical reference for the precision medication of olanzapine in BPD patients.