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Introduction: Colorectal cancer screening programs are effective in reducing incidence and mortality. In Europe, every FIT+ patient is referred to colonoscopy. The available data show that ~75.0% of these patients are negative. It is desirable to select patients at a greater risk of having a positive colonoscopy. Materials and Methods: 711 subjects, aged 50–74, attending the screening program of ASL-NA-3-SUD (Naples, Italy), were enrolled in a cross-sectional study to evaluate the performance of the QuantiDNA™ test and the non-inferiority of an alternative approach (AAP). This evaluation is based on FIT+ and QuantiDNA™+ patients referred to colonoscopy, compared to Standard of Care (SOC) colonoscopy following a FIT+ test alone. A non-inferiority margin (NIM) for colorectal neoplasia (CN) and advanced adenomas (AA) was set at −10% and at −3.8% for CRC. Results: The odds ratio was 1.76 (p-value = 0.009). The detection rate of AAP was 15.9% for colorectal neoplasia, 13.0% for advanced adenoma, and 3.0% for CRC. The risk difference between AAP and SOC was −5.07% (95% C.I. −9.23, −0.90) for colorectal neoplasia, −4.02% (95% C.I. −7.89, −0.16) for advanced adenomas, and −1.04% (95% C.I. −3.16, 1.07) for CRC. This data suggests that AAP is non-inferior to SOC for detecting CN, AA, and CRC. The expected decrease in colonoscopies is 33.4%. Conclusions: The QuantiDNA™ test is straightforward, non-invasive, and well-tolerated. Data from this study indicate that it is effective in the reduction of the need for colonoscopy examinations (−33.4%) and is non-inferior to SOC in the detection of significant colorectal lesions.

The development of high-performance optically transparent radio frequency (RF) radiators is limited by the intrinsic loss issue of transparent conductive films (TCFs). Instead of pursuing expensive endeavors to improve the TCFs’ electrical properties, this study introduces an innovative approach that leverages leaky-wave mode manipulation to mitigate the TCFs’ attenuating effect and maximize the RF radiation. Our finding reveals that the precise control of the mode confinement on glass-coated TCFs can create a low-attenuation window for leaky-wave propagation, where the total attenuation caused by TCF dissipation and wave leakage is effectively reduced. The observed low-attenuation leaky-wave state on lossy TCFs originates from the delicate balance between wave leakage and TCF dissipation, attained at a particular glass cladding thickness. By leveraging the substantially extended radiation aperture achieved under suppressed wave attenuation, this study develops an optically transparent antenna with an enhanced endfire realized gain exceeding 15 dBi and a radiation efficiency of 66%, which is validated to offer competitive transmission performance for advancing ubiquitous wireless communication and sensing applications.

Large-element-spacing (LES) antenna arrays present an attractive proposition with their cost-effectiveness and simplified structures. However, they often encounter the challenge of high-level grating lobes. This paper proposes a novel meta-lens methodology to effectively address the grating lobe issue in fixed-beam LES arrays. The proposed approach involves strategically positioning a meta-lens above the LES arrays at a suitable vertical distance. This setup enables precise manipulation and compensation of the near-field phase, resulting in the suppression or elimination of grating lobes without introducing additional design complexity. Comprehensive theoretical analyses, meticulous design calculations employing efficient numerical methods, rigorous field simulations, and practical experiments are conducted. The results demonstrate that our meta-lens solution achieves significant grating-lobe suppressions and substantial gain enhancements with only a marginal increase in system profile or volume. The proposed meta-lens approach is versatile and applicable to various LES antenna arrays, including sparse/thinned arrays, regardless of their size, element spacing, and configuration (uniform or non-uniform, periodic or aperiodic).

BackgroundInhalational anesthetic agents are a major source of potent greenhouse gases in the medical sector, and reducing their emissions is a readily addressable goal. Nitrous oxide (N2O) has a long environmental half-life relative to carbon dioxide combined with a low clinical potency, leading to relatively large amounts of N2O being stored in cryogenic tanks and H cylinders for use, increasing the chance of pollution through leaks. Building on previous findings, Stanford Health Care’s (SHC’s) N2O emissions were analyzed at 2 campuses and targeted for waste reduction as a precursor to system-wide reductions. ObjectiveWe aimed to determine the extent of N2O pollution at SHC and subsequently whether using E-cylinders for N2O storage and delivery at the point of care in SHC’s ambulatory surgery centers could reduce system-wide emissions. MethodsIn phase 1, total SHC (Palo Alto, California) N2O purchase data for calendar year 2022 were collected and compared (volume and cost) to total Palo Alto clinical delivery data using Epic electronic health records. In phase 2, a pilot study was conducted in the 8 operating rooms of SHC campus A (Redwood City). The central N2O pipelines were disconnected, and E-cylinders were used in each operating room. E-cylinders were weighed before and after use on a weekly basis for comparison to Epic N2O delivery data over a 5-week period. In phase 3, after successful implementation, the same methodology was applied to campus B, one of 3 facilities in Palo Alto. ResultsIn phase 1, total N2O purchased in 2022 was 8,217,449 L (33,201.8 lbs) at a total cost of US $63,298. Of this, only 780,882.2 L (9.5%) of N2O was delivered to patients, with 7,436,566.8 L (90.5%) or US $57,285 worth lost or wasted. In phase 2, the total mass of N2O use from E-cylinders was 7.4 lbs (1 lb N2O=247.5 L) or 1831.5 L at campus A. Epic data showed that the total N2O volume delivered was 1839.3 L (7.4 lbs). In phase 3, the total mass of N2O use from E-cylinders was 10.4 lbs or 2574 L at campus B (confirming reliability within error propagation margins). Epic data showed that the total N2O volume delivered was 2840.3 L (11.5 lbs). Over phases 2 and 3, total use for campuses A and B was less than the volume of 3 E-cylinders (1 E-cylinder=1590 L). ConclusionsConverting N2O delivery from centralized storage to point-of-care E-cylinders dramatically reduced waste and expense with no detriment to patient care. Our results provide strong evidence for analyzing N2O storage in health care systems that rely on centralized storage, and consideration of E-cylinder implementation to reduce emissions. The reduction in N2O waste will help meet SHC’s goal of reducing scope 1 and 2 emissions by 50% before 2030.

Abstract Background The rapid evolution, complexity, and specialization of oncology treatment makes it challenging for physicians to provide care based on the latest and best evidence. We hypothesized that physicians would use evidence-based trusted care pathways if they were easy to use and integrated into clinical workflow at the point of care. Methods Within a large integrated care delivery system, we assembled clinical experts to define and update drug treatment pathways, encoded them as flowcharts in an online library integrated with the electronic medical record, communicated expectations that clinicians would use these pathways for every eligible patient, and combined data from multiple sources to understand usage over time. Results We were able to achieve > 75% utilization of eligible protocols ordered through these pathways within two years, with > 90% of individual oncologists having consulted the pathway at least once, despite no requirements or external incentives associated with pathway usage. Feedback from users contributed to improvements and updates to the guidance. Conclusions By making our clinical decision support easily accessible and actionable, we find that we have made considerable progress toward our goal of having physicians consult the latest evidence in their treatment decisions.

BackgroundEvaluation of artificial intelligence (AI) tools in clinical trials remains the gold standard for translation into clinical settings. However, design factors associated with successful trial completion and the common reasons for trial failure are unknown. ObjectiveThis study aims to compare trial design factors of complete and incomplete clinical trials testing AI tools. We conducted a case-control study of complete (n=485) and incomplete (n=51) clinical trials that evaluated AI as an intervention of ClinicalTrials.gov. MethodsTrial design factors, including area of clinical application, intended use population, and intended role of AI, were extracted. Trials that did not evaluate AI as an intervention and active trials were excluded. The assessed trial design factors related to AI interventions included the domain of clinical application related to organ systems; intended use population for patients or health care providers; and the role of AI for different applications in patient-facing clinical workflows, such as diagnosis, screening, and treatment. In addition, we also assessed general trial design factors including study type, allocation, intervention model, masking, age, sex, funder, continent, length of time, sample size, number of enrollment sites, and study start year. The main outcome was the completion of the clinical trial. Odds ratio (OR) and 95% CI values were calculated for all trial design factors using propensity-matched, multivariable logistic regression. ResultsWe queried ClinicalTrials.gov on December 23, 2023, using AI keywords to identify complete and incomplete trials testing AI technologies as a primary intervention, yielding 485 complete and 51 incomplete trials for inclusion in this study. Our nested propensity-matched, case-control results suggest that trials conducted in Europe were significantly associated with trial completion when compared with North American trials (OR 2.85, 95% CI 1.14-7.10; P=.03), and the trial sample size was positively associated with trial completion (OR 1.00, 95% CI 1.00-1.00; P=.02). ConclusionsOur case-control study is one of the first to identify trial design factors associated with completion of AI trials and catalog study-reported reasons for AI trial failure. We observed that trial design factors positively associated with trial completion include trials conducted in Europe and sample size. Given the promising clinical use of AI tools in health care, our results suggest that future translational research should prioritize addressing the design factors of AI clinical trials associated with trial incompletion and common reasons for study failure.

Abstract Homologous recombination (HR) and nucleotide excision repair (NER) are the two most frequently disabled DNA repair pathways in cancer. HR-deficient breast, ovarian, pancreatic and prostate cancers respond well to platinum chemotherapy and PARP inhibitors. However, the frequency of HR deficiency in gastric and esophageal adenocarcinoma (GEA) still lacks diagnostic and functional validation. Using whole exome and genome sequencing data, we found that a significant subset of GEA, but very few colorectal adenocarcinomas, show evidence of HR deficiency by mutational signature analysis (HRD score). High HRD gastric cancer cell lines demonstrated functional HR deficiency by RAD51 foci assay and increased sensitivity to platinum chemotherapy and PARP inhibitors. Of clinical relevance, analysis of three different GEA patient cohorts demonstrated that platinum treated HR deficient cancers had better outcomes. A gastric cancer cell line with strong sensitivity to cisplatin showed HR proficiency but exhibited NER deficiency by two photoproduct repair assays. Single-cell RNA-sequencing revealed that, in addition to inducing apoptosis, cisplatin treatment triggered ferroptosis in a NER-deficient gastric cancer, validated by intracellular GSH assay. Overall, our study provides preclinical evidence that a subset of GEAs harbor genomic features of HR and NER deficiency and may therefore benefit from platinum chemotherapy and PARP inhibitors.

Abstract Aberrant stem cell-like activity and impaired differentiation are central to the development of colorectal cancer (CRC). To identify functional mediators of these key cellular programs, we engineer a dual endogenous reporter system by genome-editing the SOX9 and KRT20 loci of human CRC cell lines to express fluorescent reporters, broadcasting aberrant stem cell-like and differentiation activity, respectively. By applying a CRISPR screen targeting 78 epigenetic regulators with 542 sgRNAs to this platform, we identify factors that contribute to stem cell-like activity and differentiation in CRC. Perturbation single cell RNA sequencing (Perturb-seq) of validated hits nominate SMARCB1 of the BAF complex (also known as SWI/SNF) as a negative regulator of differentiation across an array of neoplastic colon models. SMARCB1 is a dependency and required for in vivo growth of human CRC models. These studies highlight the utility of biologically designed endogenous reporter platforms to uncover regulators with therapeutic potential.

Abstract Introduction Characterizing the landscape of clinical trials including brachytherapy can provide an overview of the current status and research trends which may guide further areas of investigation. Method We queried 449,849 clinical trials from the ClinicalTrials.gov registry using brachytherapy-related keywords from 1980 to 2023, yielding 245 multi-arm and 201 single-arm, brachytherapy trials. Multi-arm and single-arm brachytherapy trials were compared using 12 trial protocol elements. Results The number of trials including brachytherapy has increased over time, with over 60% of trials registered in 2010 onwards. The majority of clinical trials were Phase 2 or 3, evaluated both safety and efficacy, and were funded by academic sponsors. The most common tumor sites evaluated in brachytherapy clinical trials include prostate, cervix, liver, endometrium, and breast. Conclusion There remains continued interest in clinical trials including brachytherapy focused on evaluation of novel delivery systems, treatment planning, and new indications. More brachytherapy clinical trials are needed to define the optimal clinical utilization and advance prospective research in this field.

Abstract Precipitation exhibits a pronounced seasonal cycle, of which the phase and amplitude are closely associated with water resource management. While previous studies suggested an emerged delaying phase in the past decades, whether the amplified amplitude has emerged is controversial. Using multiple observational data sets and climate simulations, here we show that the amplification of precipitation annual cycle has emerged in most global land areas since the 1980s, especially in the tropics. These amplifications are mainly driven by anthropogenic emissions, and will be further intensified by 17.6% in the future (2081–2100) under high emission scenario (Shared Socioeconomic Pathways, SSP585), and limited to 7.2% under SSP126 scenario, relative to the historical period (1982–2014). Precipitation seasonality will be amplified by 4.2% for each 1°C of global warming, which is seen in all emission scenarios. The mitigation of lower emissions is helpful for alleviating the amplification of precipitation seasonality in a warming world.

Abstract Shannon entropy is a core concept in machine learning and information theory, particularly in decision tree modeling. To date, no studies have extensively and quantitatively applied Shannon entropy in a systematic way to quantify the entropy of clinical situations using diagnostic variables (true and false positives and negatives, respectively). Decision tree representations of medical decision-making tools can be generated using diagnostic variables found in literature and entropy removal can be calculated for these tools. This concept of clinical entropy removal has significant potential for further use to bring forth healthcare innovation, such as quantifying the impact of clinical guidelines and value of care and applications to Emergency Medicine scenarios where diagnostic accuracy in a limited time window is paramount. This analysis was done for 623 diagnostic tools and provided unique insights into their utility. For studies that provided detailed data on medical decision-making algorithms, bootstrapped datasets were generated from source data to perform comprehensive machine learning analysis on these algorithms and their constituent steps, which revealed a novel and thorough evaluation of medical diagnostic algorithms.

Abstract Scientific research is driven by allocation of funding to different research projects based in part on the predicted scientific impact of the work. Data-driven algorithms can inform decision-making of scarce funding resources by identifying likely high-impact studies using bibliometrics. Compared to standardized citation-based metrics alone, we utilize a machine learning pipeline that analyzes high-dimensional relationships among a range of bibliometric features to improve the accuracy of predicting high-impact research. Random forest classification models were trained using 28 bibliometric features calculated from a dataset of 1,485,958 publications in medicine to retrospectively predict whether a publication would become high-impact. For each random forest model, the balanced accuracy score was above 0.95 and the area under the receiver operating characteristic curve was above 0.99. The high performance of high impact research prediction using our proposed models show that machine learning technologies are promising algorithms that can support funding decision-making for medical research.

Abstract The phylum Apicomplexa comprises important eukaryotic parasites that invade host tissues and cells using a unique mechanism of gliding motility. Gliding is powered by actomyosin motors that translocate host-attached surface adhesins along the parasite cell body. Actin filaments (F-actin) generated by Formin1 play a central role in this critical parasitic activity. However, their subcellular origin, path and ultrastructural arrangement are poorly understood. Here we used cryo-electron tomography to image motile Cryptosporidium parvum sporozoites and reveal the cellular architecture of F-actin at nanometer-scale resolution. We demonstrate that F-actin nucleates at the apically positioned preconoidal rings and is channeled into the pellicular space between the parasite plasma membrane and the inner membrane complex in a conoid extrusion-dependent manner. Within the pellicular space, filaments on the inner membrane complex surface appear to guide the apico-basal flux of F-actin. F-actin concordantly accumulates at the basal end of the parasite. Finally, analyzing a Formin1-depleted Toxoplasma gondii mutant pinpoints the upper preconoidal ring as the conserved nucleation hub for F-actin in Cryptosporidium and Toxoplasma. Together, we provide an ultrastructural model for the life cycle of F-actin for apicomplexan gliding motility.

Skin cancer prognosis has greatly improved recently due to the introduction of immune checkpoint inhibitors (ICIs). However, many patients with advanced skin cancer still experience immunotherapy resistance and disease progression during ICI treatment, thus calling for novel therapeutics which address this treatment gap. Talimogene laherparepvec (T-VEC) has gained popularity in recent years as a viable treatment option for patients with skin cancer. In preclinical studies, T-VEC demonstrated both a direct anti-tumor effect in injected lesions as well as a systemic immune-mediated effect in non-injected lesions, which could pose additional benefits when combined with ICI therapy. Following promising results from the OPTiM trial, the Food and Drug Administration (FDA) approved the usage of T-VEC as a single agent in advanced melanoma. However, the MASTERKEY-265 trial demonstrated that adding T-VEC to pembrolizumab did not offer additional clinical benefit in patients with melanoma. Nevertheless, the promising efficacy of T-VEC and its approval by the FDA helped oncolytic viruses (OVs) gain wide attention in cancer therapy, and extensive research has been undertaken to evaluate the usage of OVs in other tumors such as sarcomas and breast cancers. Here, we provide a review of clinical results from 2022 to 2024 that investigate the efficacy and safety of OVs as a monotherapy or in combination with other therapies in skin malignancies. Furthermore, we delineate the current limitations in OV utilization and outline future directions to enhance clinical outcomes for patients with skin malignancies receiving OV-based therapies.

Precision medicine is an emergent medical paradigm that uses information technology to inform the use of targeted therapies and treatments. One of the first steps of precision medicine involves acquiring the patient’s informed consent to protect their rights to autonomous medical decision-making. In pediatrics, there exists mixed recommendations and guidelines of consent-related practices designed to safeguard pediatric patient interests while protecting their autonomy. Here, we provide a high-level, clinical primer of (1) ethical informed consent frameworks widely used in clinical practice and (2) promising modern adaptations to improve informed consent practices in pediatric precision medicine. Given the rapid scientific advances and adoption of precision medicine, we highlight the dual need to both consider the clinical implementation of consent in pediatric precision medicine workflows as well as build rapport with pediatric patients and their substitute decision-makers working alongside interdisciplinary health teams.

Summary: Here, we present a protocol for generating gene-specific split-GAL4 drivers from coding intronic Minos-mediated integration cassette/CRISPR-mediated integration cassette (MiMIC/CRIMIC) lines in Drosophila. We describe steps for four rounds of in vivo genetic crosses, PCR genotyping, and fluorescence imaging to ensure correct orientation of split-GAL4 integration before establishing stable fly stocks. This protocol offers a cost-effective alternative to traditional microinjection techniques for converting coding intronic MiMIC/CRIMIC lines into gene-specific split-GAL4 lines that are adaptable for fly researchers working on different tissues.For complete details on the use and execution of this protocol, please refer to Chen et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract Healthcare resources are published annually in repositories such as the AHA Annual Survey DatabaseTM. However, these data repositories are created via manual surveying techniques which are cumbersome in collection and not updated as frequently as website information of the respective hospital systems represented. Also, this resource is not widely available to patients in an easy-to-use format. Network analysis techniques have the potential to create topological maps which serve to aid in pathfinding for patients in their search for healthcare services. This study explores the topological structure of forty United States academic health center websites. Network analysis is utilized to analyze and visualize 48,686 webpages. Several elements of network structure are examined including basic network properties, and centrality measures distributions. The Louvain community detection algorithm is used to examine the extent to which these techniques allow identification of healthcare resources within networks. The results indicate that websites with related healthcare services tend to form observable clusters useful in mapping key resources within a hospital system.

Abstract Rationale and objectives The purpose of this study is to summarize a survey of radiology chief residents focused on 3D printing in radiology. Materials and methods An online survey was distributed to chief residents in North American radiology residencies by subgroups of the Association of University Radiologists. The survey included a subset of questions focused on the clinical use of 3D printing and perceptions of the role of 3D printing and radiology. Respondents were asked to define the role of 3D printing at their institution and asked about the potential role of clinical 3D printing in radiology and radiology residencies. Results 152 individual responses from 90 programs were provided, with a 46% overall program response rate (n = 90/194 radiology residencies). Most programs had 3D printing at their institution (60%; n = 54/90 programs). Among the institutions that perform 3D printing, 33% (n = 18/54) have structured opportunities for resident contribution. Most residents (60%; n = 91/152 respondents) feel they would benefit from 3D printing exposure or educational material. 56% of residents (n = 84/151) believed clinical 3D printing should be centered in radiology departments. 22% of residents (n = 34/151) believed it would increase communication and improve relationships between radiology and surgery colleagues. A minority (5%; 7/151) believe 3D printing is too costly, time-consuming, or outside a radiologist’s scope of practice. Conclusions A majority of surveyed chief residents in accredited radiology residencies believe they would benefit from exposure to 3D printing in residency. 3D printing education and integration would be a valuable addition to current radiology residency program curricula.

Li-Fraumeni syndrome (LFS) is associated with pathogenic germline TP53 variants and predisposes patients to cancer; understanding the evolution and drivers of LFS-related tumours remains crucial. Here, the authors analyse 22 LFS tumours using whole-genome sequencing and reconstruct the evolution and timing of somatic driver alterations.

FACS-based sorting of regenerating retinal ganglion cells, following optic nerve transection in the rat, reveals a regulatory role of Na + /K + -ATPase in axon regeneration that is mediated by DNA methylation.

Abstract Background ROS1 tyrosine kinase inhibitors (TKIs) have demonstrated significant clinical benefit for ROS1+ NSCLC patients. However, TKI resistance inevitably develops through ROS1 kinase domain (KD) modification or another kinase driving bypass signaling. While multiple TKIs have been designed to target ROS1 KD mutations, less is known about bypass signaling in TKI‐resistant ROS1+ lung cancers. Methods Utilizing a primary, patient‐derived TPM3‐ROS1 cell line (CUTO28), we derived an entrectinib‐resistant line (CUTO28‐ER). We evaluated proliferation and signaling responses to TKIs, and utilized RNA sequencing, whole exome sequencing, and fluorescence in situ hybridization to detect transcriptional, mutational, and copy number alterations, respectively. We substantiated in vitro findings using a CD74‐ROS1 NSCLC patient's tumor samples. Last, we analyzed circulating tumor DNA (ctDNA) from ROS1+ NSCLC patients in the STARTRK‐2 entrectinib trial to determine the prevalence of MET amplification. Results CUTO28‐ER cells did not exhibit ROS1 KD mutations. MET TKIs inhibited proliferation and downstream signaling and MET transcription was elevated in CUTO28‐ER cells. CUTO28‐ER cells displayed extrachromosomal (ecDNA) MET amplification without MET activating mutations, exon 14 skipping, or fusions. The CD74‐ROS1 patient samples illustrated MET amplification while receiving ROS1 TKI. Finally, two of 105 (1.9%) entrectinib‐resistant ROS1+ NSCLC STARTRK‐2 patients with ctDNA analysis at enrollment and disease progression displayed MET amplification. Conclusions Treatment with ROS1‐selective inhibitors may lead to MET‐mediated resistance. The discovery of ecDNA MET amplification is noteworthy, as ecDNA is associated with more aggressive cancers. Following progression on ROS1‐selective inhibitors, MET gene testing and treatments targeting MET should be explored to overcome MET‐driven resistance.

This paper explains some design and architecture decisions around the GEODNET network and the GeoDAO decentralized autonomous organization, which aims to create and operate a truly decentralized public GNSS reference sensing network. This paper covers the motivation of the network, the capabilities of current and future reference stations, the blockchain and GEOD token mechanics, and how the network powers applications ranging from climate change monitoring to real-time centimeter-accurate positioning.

Interoperability is a property of software quality that is related to the cooperation between software systems for exchanging information. However, this concept is not well explained or understood. A theory would be useful to explain interoperability in terms of its essential elements and propositions. Theoretical contributions of interoperability are intended to formalize this concept by using common frameworks, models, and meta-models. However, tentative contributions developed in the past have failed to propose a theory of interoperability due to four reasons: (1) a disunified vocabulary is used, (2) the essential elements for describing interoperability are not well identified, (3) only a single level of interoperability is assessed, and (4) interoperability principles are not well formalized. This paper tentatively proposes an axiomatic theory of interoperability as a complementary approach to the existing knowledge. The proposed theory seeks to better formalize the concepts of interoperability and suggest actions aimed at establishing interoperability. After a brief review of related works and the state of the art, a set of axioms and propositions is presented. This theory is evaluated by a group of experts, and an example is presented to illustrate its use. Conclusions and future works are outlined at the end of the paper.