Can linezolid be validly measured in endotracheal aspiration in critically ill patients? A proof-of-concept trial.

BACKGROUND: Therapeutic drug monitoring (TDM) of anti-infectives such as linezolid is routinely performed in blood of intensive care unit (ICU) patients to optimize target attainment. However, the concentration at the site of infection is considered more important for a successful therapy. Until now, bronchoalveolar lavage (BAL) is the gold standard to measure intrapulmonary concentrations of anti-infective agents. However, it is an invasive method and unsuitable for regular TDM. The aim of this proof-of-concept study was to investigate whether it is possible to reliably determine the intrapulmonary concentration of linezolid from endotracheal aspiration (ENTA). METHODS: Intubated ICU patients receiving 600 mg intravenous linezolid twice daily were examined in steady state. First, preliminary experiments were performed in six patients to investigate which patients are suitable for linezolid measurement in ENTA. In a second step, trough and peak linezolid concentrations of plasma and ENTA were determined in nine suitable patients. RESULTS: Linezolid can validly be detected in ENTA with viscous texture and > 0.5 mL volume. The mean (SD) linezolid trough concentration was 2.02 (1.27) mg/L in plasma and 1.60 (1.36) mg/L in ENTA, resulting in a median lung penetration rate of 104%. The mean (SD) peak concentration in plasma and ENTA was 10.77 (5.93) and 4.74 (2.66) mg/L. CONCLUSIONS: Linezolid can validly be determined in ENTA with an adequate texture and volume. The penetration rate is comparable to already published BAL concentrations. This method might offer a simple and non-invasive method for TDM at the site of infection "lung". Due to promising results of the feasibility study, comparison of ENTA and BAL in the same patient should be investigated in a further trial.

Investigating the activity of indigenous microbial communities from Italian depleted gas reservoirs and their possible impact on underground hydrogen storage.

H2 produced from renewable energies will play a central role in both greenhouse gas reduction and decarbonization by 2050. Nonetheless, to improve H2 diffusion and utilization as a fuel, large storage capacity systems are needed. Underground storage of natural gas in depleted reservoirs, aquifers and salt caverns is a well-established technology. However, new challenges arise when it comes to storing hydrogen due to the occurrence and activity of indigenous microbial populations in deep geological formations. In a previous study, four Italian natural gas reservoirs were characterized both from a hydro-chemical and microbiological point of view, and predictive functional analyses were carried out with the perspective of underground hydrogen storage (UHS). In the present work, formation waters from the same reservoirs were used as inoculant during batch cultivation tests to characterize microbial activity and its effects on different gas mixtures. Results evidence a predominant acidogenic/acetogenic activity, whilst methanogenic and sulfate reducing activity were only marginal for all tested inoculants. Furthermore, the microbial activation of tested samples is strongly influenced by nutrient availability. Obtained results were fitted and screened in a computational model which would allow deep insights in the study of microbial activity in the context of UHS.

An institutional experience of intraoperative neurophysiological monitoring application in robotic thyroidectomy: a retrospective case-control study.

Purpose: Intraoperative neurophysiological monitoring (IONM) has been introduced in thyroid surgery to prevent injury of the recurrent laryngeal nerve (RLN). However, its effectiveness remains controversial in robotic thyroidectomy (RT). This study aimed to compare the surgical outcome of RT in patients with and without the application of IONM. Methods: This retrospective case-control study included 100 patients who underwent total thyroidectomy via robotic bilateral axillo-breast approach in a tertiary center. A study group of 50 patients who had IONM during RT was compared to a control group of 50 patients who underwent RT with nerve visualization alone. Results: The sex ratio (4:45 vs. 7:43, P = 0.538), mean age (39.3 ± 7.1 years vs. 37.5 ± 10.4 years, P = 0.304), and body mass index (23.1 ± 2.6 kg/m2 vs. 22.2 ± 3.9 kg/m2, P = 0.215) were comparable between the IONM and control groups. Pathologic features including tumor size (0.8 cm vs. 0.9 cm, P = 0.283), extrathyroidal extension (58.0% vs. 24.0%, P = 0.316), lymph node metastasis (30% vs. 34%, P = 0.668), and number of lymph nodes (5.3 vs. 5.3, P = 0.668) showed no differences. There was no permanent RLN palsy, postoperative bleeding, and wound complications. Transient hypoparathyroidism was observed in 12 (24.0%) and 14 (28.0%), permanent hypoparathyroidism in 0 (0%) and 1 (2.0%), and transient RLN palsy was observed in 3 (6.0%) and 3 (6.0%), respectively. Conclusion: We did not demonstrate a clear advantage of IONM in RT. Controversies regarding the effectiveness of IONM is not closed.

Application of environmental DNA metabarcoding to identify fish community characteristics in subtropical river systems.

Fish are vital in river ecosystems; however, traditional investigations of fish usually cause ecological damage. Extracting DNA from aquatic environments and identifying DNA sequences offer an alternative, noninvasive approach for detecting fish species. In this study, the effects of environmental DNA (eDNA), coupled with PCR and next-generation sequencing, and electrofishing for identifying fish community composition and diversity were compared. In three subtropical rivers of southern China, fish specimens and eDNA in water were collected along the longitudinal (upstream-downstream) gradient of the rivers. Both fish population parameters, including species abundance and biomass, and eDNA OTU richness grouped 38 sampling sites into eight spatial zones with significant differences in local fish community composition. Compared with order-/family-level grouping, genus-/species-level grouping could more accurately reveal the differences between upstream zones I-III, midstream zones IV-V, and downstream zones VI-VIII. From the headwaters to the estuary, two environmental gradients significantly influenced the longitudinal distribution of the fish species, including the first gradient composed of habitat and physical water parameters and the second gradient composed of chemical water parameters. The high regression coefficient of alpha diversity between eDNA and electrofishing methods as well as the accurate identification of dominant, alien, and biomarker species in each spatial zone indicated that eDNA could characterize fish community attributes at a level similar to that of traditional approaches. Overall, our results demonstrated that eDNA metabarcoding can be used as an effective tool for revealing fish composition and diversity, which is important for using the eDNA technique in aquatic field monitoring.

Breeding phase and outcome determine space use in European rollers Coracias garrulus prior to migration.

The breeding period is a demanding and time-constrained phase for migratory bird species. Breeding outcome and duration can interact with the extent and duration of post-breeding movements, resulting in individual differences in space use ultimately influencing later stages of the annual cycle. We present space-use and home range estimates during the breeding season for 21 European rollers Coracias garrulus tracked between 2018 and 2022, in Italy and Croatia. Using high-resolution spatial GPS data coupled with regular nest-box monitoring, we analyzed differences in space use during the incubation/nestling period versus post-breeding period prior to migration, accounting for the breeding outcome (successful vs. failure). We found that adult movements were strongly reduced during the first phase, whereas increased in the post-breeding phase, especially for failed breeders. Successful breeders remained in the surroundings of the nest site, whereas unsuccessful ones tended to abandon the nest and visit distant areas (up to 500 km) for long periods (60.5 ±â€…6.2 days). Breeding outcome did not influence the departure date of autumn migration, suggesting that failed breeders used this period for exploratory movements but not for advancing the onset of migration. Such exploratory movements may be functional to prospect and inform settlement decisions in failed breeders in search of new breeding opportunities and may be particularly important in migratory species, which generally have a limited period to gather information prior to autumn migration. The study demonstrates the need to investigate seasonal movements in different populations and the potential importance of prospecting post-breeding movements for long-distance migratory species.

Nurses' practice of metabolic monitoring for patients on antipsychotics in Lesotho.

Background: Severe mental illness is associated with higher physical health morbidities and reduced life expectancy, with an estimated 14.3% of global deaths attributed to mental disorders. Antipsychotic medications (APs) used in treatment contribute to physical health issues, including metabolic and cardiovascular effects. Aim: The aim of this study was to assess nurses' practices regarding metabolic monitoring for patients prescribed antipsychotic medications at Mohlomi Hospital in Lesotho. Setting: The study was conducted at Mohlomi Hospital, the primary psychiatric facility in Lesotho. Methods: Using a cross-sectional design, 44 nurses from Mohlomi Hospital participated in the study. A structured questionnaire assessed nurses' metabolic monitoring practices. Results: Most of the respondents were female (n = 30, 75%), and minority were male (n = 10, 25%). The academic qualifications of respondents were distributed as follows: 40% (16) held a nursing assistant certificate and 22.5% (9) held an advanced nursing diploma, among others. The average age of all respondents was 39.05 (s.d. 8.9), with an average of 8 years of experience in psychiatry (s.d. 7.6). The overall rate of nurses' practices of metabolic monitoring for patients taking antipsychotic medications showed variability, with a mean score of 2.83 (s.d. 0.524). However, only 20% performed ECG tests, 22.5% measured blood pressure, 27.5% tested for glucose abnormalities and 17.5% conducted lipid profile testing. Conclusion: Results revealed a significant gap in the practice of metabolic monitoring among nurses with various aspects of metabolic monitoring, not being adequately monitored. Contribution: The study's findings shall inform policy and guidelines for monitoring patients on antipsychotic medications while guiding future research.

Intention to Use Mobile-Based Partograph and Its Predictors Among Obstetric Health Care Providers Working at Public Referral Hospitals in the Oromia Region of Ethiopia in 2022: Cross-Sectional Questionnaire Study.

BACKGROUND: A partograph is a pictorial representation of the relationship between cervical dilatation and the time used to diagnose prolonged and obstructed labor. However, the utilization of paper-based partograph is low and it is prone to documentation errors, which can be avoided with the use of electronic partographs. There is only limited information on the proportion of intention to use mobile-based partographs and its predictors. OBJECTIVE: The objective of this study was to determine the proportion of obstetric health care providers at public referral hospitals in Oromia, Ethiopia, in 2022 who had the intention to use mobile-based partographs and to determine the predictors of their intention to use mobile-based partographs. METHODS: We performed an institution-based cross-sectional study from June 1 to July 1, 2022. Census was conducted on 649 participants. A self-administered structured English questionnaire was used, and a 5% pretest was performed. Data were entered into EpiData version 4.6 and exported to SPSS version 25 for descriptive analysis and AMOS (analysis of moment structure; version 23) for structural and measurement model assessment. Descriptive and structural equation modeling analyses were performed. The hypotheses developed based on a modified Technology Acceptance Model were tested using path coefficients and P values <.05. RESULTS: About 65.7% (414/630; 95% CI 61.9%-69.4%) of the participants intended to use mobile-based electronic partographs, with a 97% (630/649) response rate. Perceived usefulness had a positive influence on intention to use (ß=.184; P=.02) and attitude (ß=.521; P=.002). Perceived ease of use had a positive influence on attitude (ß=.382; P=.003), perceived usefulness (ß=.503; P=.002), and intention to use (ß=.369; P=.001). Job relevance had a positive influence on perceived usefulness (ß=.408; P=.001) and intention to use (ß=.185; P=.008). Attitude positively influenced intention to use (ß=.309; P=.002). Subjective norms did not have a significant influence on perceived usefulness (ß=.020; P=.61) and intention to use (ß=-.066; P=.07). CONCLUSIONS: Two-thirds of the obstetric health care providers in our study intended to use mobile-based partographs. Perceived usefulness, perceived ease of use, job relevance, and attitude positively and significantly influenced their intention to use mobile-based electronic partographs. The development of a user-friendly mobile-based partograph that meets job and user expectations can enhance the intention to use.

E-Health & Innovation to Overcome Barriers in Neuromuscular Diseases. Report from the 3rd eNMD Congress: Pisa, Italy, 29-30 October 2021.

Neuromuscular diseases (NMDs), in their phenotypic heterogeneity, share quite invariably common issues that involve several clinical and socio-economical aspects, needing a deep critical analysis to develop better management strategies. From diagnosis to treatment and follow-up, the development of technological solutions can improve the detection of several critical aspects related to the diseases, addressing both the met and unmet needs of clinicians and patients. Among several aspects of the digital transformation of health and care, this congress expands what has been learned from previous congresses editions on applicability and usefulness of technological solutions in NMDs. In particular the focus on new solutions for remote monitoring provide valuable insights to increase disease-specific knowledge and trigger prompt decision-making. In doing that, several perspectives from different areas of expertise were shared and discussed, pointing out strengths and weaknesses on the current state of the art on topic, suggesting new research lines to advance technology in this specific clinical field.

Upstrapping to determine futility: predicting future outcomes nonparametrically from past data.

BACKGROUND: Clinical trials often involve some form of interim monitoring to determine futility before planned trial completion. While many options for interim monitoring exist (e.g., alpha-spending, conditional power), nonparametric based interim monitoring methods are also needed to account for more complex trial designs and analyses. The upstrap is one recently proposed nonparametric method that may be applied for interim monitoring. METHODS: Upstrapping is motivated by the case resampling bootstrap and involves repeatedly sampling with replacement from the interim data to simulate thousands of fully enrolled trials. The p-value is calculated for each upstrapped trial and the proportion of upstrapped trials for which the p-value criteria are met is compared with a pre-specified decision threshold. To evaluate the potential utility for upstrapping as a form of interim futility monitoring, we conducted a simulation study considering different sample sizes with several different proposed calibration strategies for the upstrap. We first compared trial rejection rates across a selection of threshold combinations to validate the upstrapping method. Then, we applied upstrapping methods to simulated clinical trial data, directly comparing their performance with more traditional alpha-spending and conditional power interim monitoring methods for futility. RESULTS: The method validation demonstrated that upstrapping is much more likely to find evidence of futility in the null scenario than the alternative across a variety of simulations settings. Our three proposed approaches for calibration of the upstrap had different strengths depending on the stopping rules used. Compared to O'Brien-Fleming group sequential methods, upstrapped approaches had type I error rates that differed by at most 1.7% and expected sample size was 2-22% lower in the null scenario, while in the alternative scenario power fluctuated between 15.7% lower and 0.2% higher and expected sample size was 0-15% lower. CONCLUSIONS: In this proof-of-concept simulation study, we evaluated the potential for upstrapping as a resampling-based method for futility monitoring in clinical trials. The trade-offs in expected sample size, power, and type I error rate control indicate that the upstrap can be calibrated to implement futility monitoring with varying degrees of aggressiveness and that performance similarities can be identified relative to considered alpha-spending and conditional power futility monitoring methods.

Ambient fine particulate matter and daily mortality: a comparative analysis of observed and estimated exposure in 347 cities.

BACKGROUND: Model-estimated air pollution exposure products have been widely used in epidemiological studies to assess the health risks of particulate matter with diameters of ≤2.5 µm (PM2.5). However, few studies have assessed the disparities in health effects between model-estimated and station-observed PM2.5 exposures. METHODS: We collected daily all-cause, respiratory and cardiovascular mortality data in 347 cities across 15 countries and regions worldwide based on the Multi-City Multi-Country collaborative research network. The station-observed PM2.5 data were obtained from official monitoring stations. The model-estimated global PM2.5 product was developed using a machine-learning approach. The associations between daily exposure to PM2.5 and mortality were evaluated using a two-stage analytical approach. RESULTS: We included 15.8 million all-cause, 1.5 million respiratory and 4.5 million cardiovascular deaths from 2000 to 2018. Short-term exposure to PM2.5 was associated with a relative risk increase (RRI) of mortality from both station-observed and model-estimated exposures. Every 10-µg/m3 increase in the 2-day moving average PM2.5 was associated with overall RRIs of 0.67% (95% CI: 0.49 to 0.85), 0.68% (95% CI: -0.03 to 1.39) and 0.45% (95% CI: 0.08 to 0.82) for all-cause, respiratory, and cardiovascular mortality based on station-observed PM2.5 and RRIs of 0.87% (95% CI: 0.68 to 1.06), 0.81% (95% CI: 0.08 to 1.55) and 0.71% (95% CI: 0.32 to 1.09) based on model-estimated exposure, respectively. CONCLUSIONS: Mortality risks associated with daily PM2.5 exposure were consistent for both station-observed and model-estimated exposures, suggesting the reliability and potential applicability of the global PM2.5 product in epidemiological studies.

Redox-Modified Nanostructured Electrochemical Surfaces for Continuous Glucose Monitoring in Complex Biological Fluids.

Continuous glucose monitoring is valuable for people with diabetes but faces limitations due to enzyme-electrode interactions and biofouling from biological samples that reduce sensor sensitivity and the monitoring performance. We created an enzyme-based electrochemical system with a unique nanocomposite coating that incorporates the redox molecule, aminoferrocene (NH2-Fc). This coating enhances stability via electroactivity and reduces nonspecific binding, as demonstrated through cyclic voltammetry. Our approach enables real-time glucose detection via chronoamperometry with a calculated linear range of 0.5 to 20 mM and a 1 mM detection limit. Validated with plasma and saliva, this platform shows promise for robust metabolite detection in clinical and research contexts. This versatile platform can be applied to accurately monitor a wide range of metabolites in various biological matrices, improving patient outcomes.

Using Progress Feedback to Enhance Treatment Outcomes: A Narrative Review.

We face increasing demand for greater access to effective routine mental health services, including telehealth. However, treatment outcomes in routine clinical practice are only about half the size of those reported in controlled trials. Progress feedback, defined as the ongoing monitoring of patients' treatment response with standardized measures, is an evidence-based practice that continues to be under-utilized in routine care. The aim of the current review is to provide a summary of the current evidence base for the use of progress feedback, its mechanisms of action and considerations for successful implementation. We reviewed ten available meta-analyses, which report small to medium overall effect sizes. The results suggest that adding feedback to a wide range of psychological and psychiatric interventions (ranging from primary care to hospitalization and crisis care) tends to enhance the effectiveness of these interventions. The strongest evidence is for patients with common mental health problems compared to those with very severe disorders. Effect sizes for not-on-track cases, a subgroup of cases that are not progressing well, are found to be somewhat stronger, especially when clinical support tools are added to the feedback. Systematic reviews and recent studies suggest potential mechanisms of action for progress feedback include focusing the clinician's attention, altering clinician expectations, providing new information, and enhancing patient-centered communication. Promising approaches to strengthen progress feedback interventions include advanced systems with signaling technology, clinical problem-solving tools, and a broader spectrum of outcome and progress measures. An overview of methodological and implementation challenges is provided, as well as suggestions for addressing these issues in future studies. We conclude that while feedback has modest effects, it is a small and affordable intervention that can potentially improve outcomes in psychological interventions. Further research into mechanisms of action and effective implementation strategies is needed.

Comparing the compensatory reserve metric obtained from invasive arterial measurements and photoplethysmographic volume-clamp during simulated hemorrhage.

PURPOSE: The compensatory reserve metric (CRM) is a novel tool to predict cardiovascular decompensation during hemorrhage. The CRM is traditionally computed using waveforms obtained from photoplethysmographic volume-clamp (PPGVC), yet invasive arterial pressures may be uniquely available. We aimed to examine the level of agreement of CRM values computed from invasive arterial-derived waveforms and values computed from PPGVC-derived waveforms. METHODS: Sixty-nine participants underwent graded lower body negative pressure to simulate hemorrhage. Waveform measurements from a brachial arterial catheter and PPGVC finger-cuff were collected. A PPGVC brachial waveform was reconstructed from the PPGVC finger waveform. Thereafter, CRM values were computed using a deep one-dimensional convolutional neural network for each of the following source waveforms; (1) invasive arterial, (2) PPGVC brachial, and (3) PPGVC finger. Bland-Altman analyses were used to determine the level of agreement between invasive arterial CRM values and PPGVC CRM values, with results presented as the Mean Bias [95% Limits of Agreement]. RESULTS: The mean bias between invasive arterial- and PPGVC brachial CRM values at rest, an applied pressure of -45mmHg, and at tolerance was 6% [-17%, 29%], 1% [-28%, 30%], and 0% [-25%, 25%], respectively. Additionally, the mean bias between invasive arterial- and PPGVC finger CRM values at rest, applied pressure of -45mmHg, and tolerance was 2% [-22%, 26%], 8% [-19%, 35%], and 5% [-15%, 25%], respectively. CONCLUSION: There is generally good agreement between CRM values obtained from invasive arterial waveforms and values obtained from PPGVC waveforms. Invasive arterial waveforms may serve as an alternative for computation of the CRM.

Crossing the digital divide: The workload of manual data entry for integration between mobile health applications and eHealth infrastructure.

Background: Many digital health interventions (DHIs), including mobile health (mHealth) apps, aim to improve both client outcomes and efficiency like electronic medical record systems (EMRS). Although interoperability is the gold standard, it is also complex and costly, requiring technical expertise, stakeholder permissions, and sustained funding. Manual data linkage processes are commonly used to "integrate" across systems and allow for assessment of DHI impact, a best practice, before further investment. For mHealth, the manual data linkage workload, including related monitoring and evaluation (M&E) activities, remains poorly understood. Methodology: As a baseline study for an open-source app to mirror EMRS and reduce healthcare worker (HCW) workload while improving care in the Nurse-led Community-based Antiretroviral therapy Program (NCAP) in Lilongwe, Malawi, we conducted a time-motion study observing HCWs completing data management activities, including routine M&E and manual data linkage of individual-level app data to EMRS. Data management tasks should reduce or end with successful app implementation and EMRS integration. Data was analysed in Excel. Results: We observed 69:53:00 of HCWs performing routine NCAP service delivery tasks: 39:52:00 (57%) was spent completing M&E data related tasks of which 15:57:00 (23%) was spent on manual data linkage workload, alone. Conclusion: Understanding the workload to ensure quality M&E data, including to complete manual data linkage of mHealth apps to EMRS, provides stakeholders with inputs to drive DHI innovations and integration decision making. Quantifying potential mHealth benefits on more efficient, high-quality M&E data may trigger new innovations to reduce workloads and strengthen evidence to spur continuous improvement.

Application of in vitro bioassays to monitor pharmaceuticals in water: A synthesis of chronological analysis, mode of action, and practical insights.

Pharmaceutical compounds in wastewater have emerged as a significant concern for the aquatic environment. The use of in vitro bioassays represents a sustainable and cost-effective approach for assessing the potential toxicological risks of these biologically active compounds in wastewater and aligns with ethical considerations in research. It facilitates high-throughput analysis, captures mixture effects, integrates impacts of both known and unknown chemicals, and reduces reliance on animal testing. The core aim of the current review was to explore the practical application of in vitro bioassays in evaluating the environmental impacts of pharmaceuticals in wastewater. This comprehensive review strives to achieve several key objectives. First, it provides a summary categorisation of pharmaceuticals based on their mode of action, providing a structured framework for understanding their ecological significance. Second, a chronological analysis of pharmaceutical research aims to document their prevalence and trends over time, shedding light on evolving environmental challenges. Third, the review critically analyses existing bioassay applications in wastewater, while also examining bioassay coverage of representative compounds within major pharmaceutical classes. Finally, it explores the potential for developing innovative bioassays tailored for water quality monitoring of pharmaceuticals, paving the way for more robust environmental monitoring and risk assessment. Overall, adopting effect-based methods for pharmaceutical monitoring in water holds significant promise. It encompasses a broad spectrum of biological impacts, promotes standardized protocols, and supports a bioassay test battery approach indicative of different endpoints, thereby enhancing the effectiveness of environmental risk assessment.

Prescription drug monitoring programs and prescription pain medication misuse among U.S. high school students-2019.

BACKGROUND: Prescription drug monitoring programs (PDMPs) are state-level databases that track and inform prescribing practices to reduce prescription drug diversion and misuse. To our knowledge, only three studies have examined the impact of PDMPs on opioid-related outcomes among adolescents, and none have focused on prescription pain medication misuse among adolescents. METHODS: This study leveraged data from the 2019 National Youth Risk Behavior Survey (YRBS) to explore the associations between five categories of PDMP dimensions and the prevalence of self-reported prescription pain medication misuse. Demographic factors' associations with self-reported prescription pain medication misuse were also examined. RESULTS: In 2019, none of the PDMP dimensions were associated with self-reported prescription pain medication misuse among U.S. high school students, adjusting for gender, grade, race/ethnicity, and sexual orientation. CONCLUSIONS: None of the five PDMP dimensions were associated with lower prescription pain medication misuse, however further research is needed, especially as new YRBS data become available.

Outcomes and Adverse Events in Patients with Cancer after Diagnosis of Immunotherapy-Associated Diabetes Mellitus: A Retrospective Cohort Study.

Immune checkpoint inhibitor (CPI)-induced diabetes mellitus (CPI-DM) is a rare immune-related adverse event (irAE). Patients and providers fear that continuing CPIs puts patients at risk for additional irAEs and thus may discontinue therapy. Currently, there are little data to inform this decision. Therefore, this study aims to elucidate whether discontinuing CPIs after diagnosis of CPI-DM impacts the development of future irAEs and cancer outcomes such as progression and death. Patients who developed CPI-DM during cancer treatment at UCSF from 1 July 2015 to 5 July 2023 were analyzed for cancer outcomes and irAE development. Fisher's exact tests, Student t-tests, Kaplan-Meier methods, and Cox regression were used as appropriate. Of the 43 patients with CPI-DM, 20 (47%) resumed CPIs within 90 days of the irAE, 4 (9%) patients restarted after 90 days, and 19 (44%) patients never restarted. Subsequent irAEs were diagnosed in 9 of 24 (38%) who resumed CPIs and 3 of 19 (16%) who discontinued CPIs (p = 0.17). There was no significant difference in death (p = 0.74) or cancer progression (p = 0.55) between these two groups. While our single-institution study did not show worse cancer outcomes after discontinuing CPIs, many variables can impact outcomes, which our study was not adequately powered to evaluate. A nuanced approach is needed to decide whether to continue CPI treatment after a severe irAE like CPI-DM.

Extracellular Vesicles for Childhood Cancer Liquid Biopsy.

Liquid biopsy involves the utilization of minimally invasive or noninvasive techniques to detect biomarkers in biofluids for disease diagnosis, monitoring, or guiding treatments. This approach is promising for the early diagnosis of childhood cancer, especially for brain tumors, where tissue biopsies are more challenging and cause late detection. Extracellular vesicles offer several characteristics that make them ideal resources for childhood cancer liquid biopsy. Extracellular vesicles are nanosized particles, primarily secreted by all cell types into body fluids such as blood and urine, and contain molecular cargos, i.e., lipids, proteins, and nucleic acids of original cells. Notably, the lipid bilayer-enclosed structure of extracellular vesicles protects their cargos from enzymatic degradation in the extracellular milieu. Proteins and nucleic acids of extracellular vesicles represent genetic alterations and molecular profiles of childhood cancer, thus serving as promising resources for precision medicine in cancer diagnosis, treatment monitoring, and prognosis prediction. This review evaluates the recent progress of extracellular vesicles as a liquid biopsy platform for various types of childhood cancer, discusses the mechanistic roles of molecular cargos in carcinogenesis and metastasis, and provides perspectives on extracellular vesicle-guided therapeutic intervention. Extracellular vesicle-based liquid biopsy for childhood cancer may ultimately contribute to improving patient outcomes.

Biominerals and Bioinspired Materials in Biosensing: Recent Advancements and Applications.

Inspired by nature's remarkable ability to form intricate minerals, researchers have unlocked transformative strategies for creating next-generation biosensors with exceptional sensitivity, selectivity, and biocompatibility. By mimicking how organisms orchestrate mineral growth, biomimetic and bioinspired materials are significantly impacting biosensor design. Engineered bioinspired materials offer distinct advantages over their natural counterparts, boasting superior tunability, precise controllability, and the ability to integrate specific functionalities for enhanced sensing capabilities. This remarkable versatility enables the construction of various biosensing platforms, including optical sensors, electrochemical sensors, magnetic biosensors, and nucleic acid detection platforms, for diverse applications. Additionally, bioinspired materials facilitate the development of smartphone-assisted biosensing platforms, offering user-friendly and portable diagnostic tools for point-of-care applications. This review comprehensively explores the utilization of naturally occurring and engineered biominerals and materials for diverse biosensing applications. We highlight the fabrication and design strategies that tailor their functionalities to address specific biosensing needs. This in-depth exploration underscores the transformative potential of biominerals and materials in revolutionizing biosensing, paving the way for advancements in healthcare, environmental monitoring, and other critical fields.