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Abstract To understand how ectotherms will respond to warming temperatures, we require information on thermal habitat quality at spatial resolutions and extents relevant to the organism. Measuring thermal habitat quality is either limited to small spatial extents, such as with ground‐based 3D operative temperature (Te) replicas, representing the temperature of the animal at equilibrium with its environment, or is based on microclimate derived from physical models that use land cover variables and downscale coarse climate data. We draw on aspects of both these approaches and test the ability of unoccupied aerial vehicle (UAV) data (optical RGB) to predict fine‐scale heterogeneity in sub‐canopy lizard (Anolis bicaorum) Te in tropical forest using random forest models. Anolis bicaorum is an endemic, critically endangered, species, facing significant threats of habitat loss and degradation, and work was conducted as part of a larger project. Our findings indicate that a model incorporating solely air temperature, measured at the centre of the 20 × 20 m plot, and ground‐based leaf area index (LAI) measurements, measured at directly above the 3D replica, predicted Te well. However, a model with air temperature and UAV‐derived canopy metrics performed slightly better with the added advantage of enabling the mapping of Te with continuous spatial extent at high spatial resolutions, across the whole of the UAV orthomosaic, allowing us to capture and map Te across the whole of the survey plot, rather than purely at 3D replica locations. Our work provides a feasible workflow to map sub‐canopy lizard Te in tropical environments at spatial scales relevant to the organism, and across continuous areas. This can be applied to other species and can represent species within the same community that have evolved a similar thermal niche. Such methods will be imperative in risk modelling of such species to anthropogenic land cover and climate change.

Abstract This post hoc analysis of the randomized, placebo‐controlled N‐MOmentum study (NCT02200770) of inebilizumab in neuromyelitis optica spectrum disorder (NMOSD) evaluated relationships between circulating B‐cell subsets and aquaporin‐4 immunoglobulin G (AQP4‐lgG) titers and attacks. Among participants receiving placebo, CD20+ and CD27+ B‐cell counts were modestly increased from the pre‐attack visit to attack; plasmablast/plasma cell gene signature was increased from baseline to the pre‐attack visit (p = 0.016) and from baseline to attack (p = 0.009). With inebilizumab treatment, B‐cell subset counts decreased and did not increase with attacks. No difference in change of AQP4‐IgG titers from baseline to time of attack was observed.

Abstract We examined how resistance exercise (RE), cycling exercise and disuse atrophy affect myosin heavy chain (MyHC) protein fragmentation. The 1boutRE study involved younger men (n = 8; 5 ± 2 years of RE experience) performing a lower body RE bout with vastus lateralis (VL) biopsies being obtained prior to and acutely following exercise. With the 10weekRT study, VL biopsies were obtained in 36 younger adults before and 24 h after their first/naïve RE bout. Participants also engaged in 10 weeks of resistance training and donated VL biopsies before and 24 h after their last RE bout. VL biopsies were also examined in an acute cycling study (n = 7) and a study involving 2 weeks of leg immobilization (n = 20). In the 1boutRE study, fragmentation of all MyHC isoforms (MyHCTotal) increased 3 h post‐RE (∼200%, P = 0.018) and returned to pre‐exercise levels by 6 h post‐RE. Interestingly, a greater magnitude increase in MyHC type IIa versus I isoform fragmentation occurred 3 h post‐RE (8.6 ± 6.3‐fold vs. 2.1 ± 0.7‐fold, P = 0.018). In 10weekRT participants, the first/naïve and last RE bouts increased MyHCTotal fragmentation 24 h post‐RE (+65% and +36%, P

Abstract Over the past five decades, a large number of wild animals have been individually identified by various observation systems and/or temporary tracking methods, providing unparalleled insights into their lives over both time and space. However, so far there is no comprehensive record of uniquely individually identified animals nor where their data and metadata are stored, for example photos, physiological and genetic samples, disease screens, information on social relationships. Databases currently do not offer unique identifiers for living, individual wild animals, similar to the permanent ID labelling for deceased museum specimens. To address this problem, we introduce two new concepts: (1) a globally unique animal ID (UAID) available to define uniquely and individually identified animals archived in any database, including metadata archived at the time of publication; and (2) the digital ‘home’ for UAIDs, the Movebank Life History Museum (MoMu), storing and linking metadata, media, communications and other files associated with animals individually identified in the wild. MoMu will ensure that metadata are available for future generations, allowing permanent linkages to information in other databases. MoMu allows researchers to collect and store photos, behavioural records, genome data and/or resightings of UAIDed animals, encompassing information not easily included in structured datasets supported by existing databases. Metadata is uploaded through the Animal Tracker app, the MoMu website, by email from registered users or through an Application Programming Interface (API) from any database. Initially, records can be stored in a temporary folder similar to a field drawer, as naturalists routinely do. Later, researchers and specialists can curate these materials for individual animals, manage the secure sharing of sensitive information and, where appropriate, publish individual life histories with DOIs. The storage of such synthesized lifetime stories of wild animals under a UAID (unique identifier or ‘animal passport’) will support basic science, conservation efforts and public participation.

Abstract The lysosomal storage diseases chronic visceral acid sphingomyelinase deficiency (ASMD) and Gaucher disease type 1 (GD1) are both macrophage storage disorders with overlapping clinical manifestations. We compared cross‐sectional data on visceral, hematological, and biochemical manifestations of untreated adult patients with chronic visceral ASMD (n = 19) and GD1 (n = 85). Spleen volume, liver volume, and bone marrow fat fraction did not significantly differ between the two disease groups (p >0.05 for all). Chitotriosidase activity was higher in GD1 (GD1: median 30 940 nmol/(mL.h), range 513–201 352, ASMD: median 1693 nmol/(mL.h), range 326–6620, p

Abstract Objective The first international consensus criteria for optic neuritis (ICON) were published in 2022. We applied these criteria to a prospective, global observational study of acute optic neuritis (ON). Methods We included 160 patients with a first‐ever acute ON suggestive of a demyelinating CNS disease from the Acute Optic Neuritis Network (ACON). We applied the 2022 ICON to all participants and subsequently adjusted the ICON by replacing a missing relative afferent pupillary defect (RAPD) or dyschromatopsia if magnetic resonance imaging pathology of the optical nerve plus optical coherence tomography abnormalities or certain biomarkers are present. Results According to the 2022 ICON, 80 (50%) patients were classified as definite ON, 12 (7%) patients were classified as possible ON, and 68 (43%) as not ON (NON). The main reasons for classification as NON were absent RAPD (52 patients, 76%) or dyschromatopsia (49 patients, 72%). Distribution of underlying ON etiologies was as follows: 78 (49%) patients had a single isolated ON, 41 (26%) patients were diagnosed with multiple sclerosis, 25 (16%) patients with myelin oligodendrocyte glycoprotein antibody‐associated disease, and 15 (9%) with neuromyelitis optica spectrum disorder. The application of the adjusted ON criteria yielded a higher proportion of patients classified as ON (126 patients, 79%). Interpretation According to the 2022 ICON, almost half of the included patients in ACON did not fulfill the requirements for classification of definite or possible ON, particularly due to missing RAPD and dyschromatopsia. Thorough RAPD examination and formal color vision testing are critical to the application of the 2022 ICON.

Abstract Background Acne is a common pilosebaceous unit chronic inflammatory disease, with a multifactorial pathogenesis. It involves several processes: increased sebum production, alteration of the follicular keratinization process and bacterial colonization by Cutibacterium acnes. Objectives To evaluate the effectiveness of reflectance confocal microscopy (RCM) in evaluating the reduction of mild to severe acne lesions in patients treated with an investigational product containing Silybum marianum fruit extract (SMFE). Methods Subjects previously examined for counting acne lesions were topically treated in the face, with an investigational product containing SMFE in monotherapy over the course of 60 days (n = 31). They were examined for counting acne lesions. Efficacy and quality of life, tolerability, and safety assessments were performed. The infundibular diameter (ID) measurement of normal and acne skin areas was analyzed using RCM. Results The RCM data statistical analysis allowed us to identify two ID patterns, 300–750 µm, with a reduction of 33.33% (p

Objective Health literacy is an important social determinant of health, with limited health literacy associated with worse health outcomes. This study examined the associations between limited health literacy with patient‐reported outcomes and disease activity/damage among 267 Black women with active systemic lupus erythematosus (SLE) enrolled in the Peer Approaches to Lupus Self‐Management (PALS) program. Methods The three‐item Chew Health Literacy Screening was used to dichotomize those reporting in the “limited” range on any item with outcomes compared via generalized linear models. Baseline surveys and assessments obtained at study entry as part of the PALS study were used. Primary outcomes included disease activity and lupus damage; other secondary outcomes included patient activation, self‐efficacy, physician/patient communication, and quality of life. Results The study included 267 Black women with SLE. In covariate‐adjusted analyses, participants with limited health literacy (88 [33%]) were more likely to have lower patient activation (Patient Activation Measure P

ABSTRACT Biomarkers of kidney function, including glomerular, tubular, and fibrotic markers, have been associated with blood pressure in elderly populations and individuals with kidney and cardiovascular diseases. However, limited information is available in young adults. In this study, we compared levels of several kidney function biomarkers between normotensive and hypertensive young adults and explored the associations of these biomarkers with blood pressure within these groups. In this cross‐sectional assessment, twenty‐four‐hour (24‐h) blood pressure measurements of 1055 participants (mean age = 24.6 years) were used to classify hypertension as per the 2018 ESC/ESH guidelines. Biomarkers of kidney function included estimated glomerular filtration rate, urinary albumin, alpha‐1 microglobulin (uA1M), neutrophil gelatinase‐associated lipocalin (uNGAL), uromodulin (uUMOD), and the CKD273 classifier. All urinary biomarkers, except for the CKD273 classifier, were standardized for urinary creatinine (Cr). In the hypertensive group (61.0% White; 73.2% men), urinary albumin‐to‐creatinine ratio (uACR), uNGAL/Cr and uUMOD/Cr were lower than the normotensive group. In multiple regression analyses, 24‐h systolic blood pressure (SBP) (β = 0.14; p = 0.042), 24‐h diastolic blood pressure (DBP) (β = 0.14; p = 0.040), and 24‐h mean arterial pressure (MAP) (β = 0.16; p = 0.020) associated positively with uA1M/Cr in the hypertensive group, while 24‐h MAP positively associated with uACR (β = 0.17; p = 0.017). In exploratory factor analysis, positive associations of 24‐h DBP and 24‐h MAP with a factor pattern including tubular biomarkers were observed in the hypertensive group (24‐h DBP: β = 0.18; p = 0.026, 24‐h MAP: β = 0.17; p = 0.032). In the setting of hypertension, high perfusion pressure in the kidneys may play a role in the development of proximal tubule damage and promote early deterioration in kidney function in young adults. Trial Registration: ClinicalTrials.gov identifier: NCT03292094

Abstract Objective This study aims to compare the long‐term outcomes of Aquablation for small‐to‐moderate (30–80 cm3) prostates with the outcomes for large (80–150 cm3) prostates at 5‐year follow up. Methods The Waterjet Ablation Therapy for Endoscopic Resection of Prostate Tissue (WATER; NCT02505919) is a prospective, double‐blind, international clinical trial encompassing 116 patients, examining Aquablation versus transurethral resection of the prostate (TURP) for LUTS/BPH in prostates sized between 30 and 80 cm3. In parallel, WATER II (W‐II; NCT03123250), a prospective, multicentre, single‐arm international clinical trial, explores Aquablation outcomes in prostates ranging from 80 to 150 cm3. Baseline parameters and 60‐month outcomes were scrutinized using statistical analyses, including Students' t test, Wilcoxon tests for continuous variables, and Fisher's test for binary variables. Results There is a significant improvement in International Prostate Symptom Score (IPSS) from baseline to 60 months in both WATER (22.9 to 7.0) and WATER II (23.2 to 6.8) (P = 0.852). Urinary flow rate (Qmax) increased in both groups from baseline to 60 months (WATER: 9.4 to 17.3 cc/s; WATER II: 8.7 to 17.1 cc/s) (P = 0.933). Immediate and sustained enhancements were observed in IPSS and Qmax. At 5 years, a notable percentage of patients in both groups were BPH medication‐free (WATER: 99%; WATER II: 94%) (P = 0.0517) and free from surgical retreatment (WATER: 95%; WATER II: 97%) (P = 0.508). Conclusions The 5‐year follow‐up affirms that Aquablation therapy exhibits sustained outcomes, minimal irreversible complications, and low retreatment rates for treating LUTS/BPH, irrespective of prostate volume ranging from 30 to 150 cm3.

Abstract Objective There is a shortage of established prognostic biomarkers in bladder cancer. One candidate is tumour protein 63 (p63), a transcription factor of the p53 gene family that is expressed in the normal urothelium. Recently proposed RNA expression‐based molecular classifiers of bladder cancer identified high p63 expression as a component of a basal/squamous subtype linked to poor patient prognosis. Methods In this study, p63 protein expression was analysed by immunohistochemistry on more than 2500 urothelial bladder carcinomas in a tissue microarray format to determine its relationship with clinicopathological parameters of disease progression and patient outcome. Results Nuclear p63 staining was seen in all cells of normal urothelium and at elevated levels in pTaG2 tumours. The rate of p63 positive cases and the staining intensity was lower in pTaG3 tumours (93.2%, p

Abstract Background Neoadjuvant platinum‐based chemotherapy offers a modest survival advantage in muscle‐invasive bladder cancer (MIBC) for patients with pathologic response. B7‐H3 (CD276), an immune checkpoint overexpressed in various cancers, including urothelial‐cell carcinoma (UCC), has been associated with chemoresistance and poor oncologic outcomes. We aimed to explore if B7H3 expression on bladder biopsy samples was a predictive biomarker for pathologic response to neoadjuvant platinum‐based chemotherapy. Methods This was a retrospective cohort study among MIBC patients receiving neoadjuvant platinum‐based chemotherapy followed by radical cystectomy. All patients underwent routine preoperative biopsy of their tumour. Immunohistochemistry was used to evaluate B7‐H3 expression from pre‐operative specimens. The primary outcome of interest was pathologic complete response (pCR). Statistical analysis included Mann–Whitney U test, Fisher's exact test, Kaplan–Meier method, and Cox regression for survival analysis. Results Among 87 patients analysed, high B7‐H3 expression was found in 44.8% (n = 39) of patients. The median follow‐up periods were similar between the high and low B7‐H3 groups (high expression; 4.29 years [SD 3.04], low expression 3.94 years [SD 3.04], p = 0.60). Only 20.5% of patients with high B7‐H3 expression achieved pCR, compared to 41.7% in the low expression group (p = 0.04). Cox regression showed no significant differences in recurrence‐free or cancer‐specific survival between the high and low B7‐H3 expression groups (p > 0.05). Conclusion High B7‐H3 expression is associated with a reduced likelihood of achieving pCR in MIBC patients undergoing neoadjuvant chemotherapy. This suggests B7‐H3's potential as a predictive biomarker for chemotherapy response. Further research is needed to explore the role of B7‐H3 on platinum‐based chemotherapy response in urothelial cancer.

Patients with gastro‐intestinal stromal tumors (GISTs) undergoing tyrosine kinase inhibitor therapy are monitored with regular computed tomography (CT) scans, exposing patients to cumulative radiation. This exploratory study aimed to evaluate circulating tumor DNA (ctDNA) testing to monitor treatment response and compare changes in ctDNA levels with RECIST 1.1 and total tumor volume measurements. Between 2014 and 2021, six patients with KIT proto‐oncogene, receptor tyrosine kinase (KIT) exon‐11‐mutated GIST from whom long‐term plasma samples were collected prospectively were included in the study. ctDNA levels of relevant plasma samples were determined using the KIT exon 11 digital droplet PCR drop‐off assay. Tumor volume measurements were performed using a semi‐automated approach. In total, 94 of 130 clinically relevant ctDNA samples were analyzed. Upon successful treatment response, ctDNA became undetectable in all patients. At progressive disease, ctDNA was detectable in five out of six patients. Higher levels of ctDNA correlated with larger tumor volumes. Undetectable ctDNA at the time of progressive disease on imaging was consistent with lower tumor volumes compared to those with detectable ctDNA. In summary, ctDNA levels seem to correlate with total tumor volume at the time of progressive disease. Our exploratory study shows promise for including ctDNA testing in treatment follow‐up.

Advances in therapeutic approaches for melanoma urge the need for biomarkers that can identify patients at risk for recurrence and to guide treatment. The potential use of liquid biopsies in identifying biomarkers is increasingly being recognized. Here, we present a head‐to‐head comparison of several techniques to analyze circulating tumor cells (CTCs) and cell‐free DNA (cfDNA) in 20 patients with metastatic melanoma. In this study, we investigated whether diagnostic leukapheresis (DLA) combined with multimarker flow cytometry (FCM) increased the detection of CTCs in blood compared to the CellSearch platform. Additionally, we characterized cfDNA at the level of somatic mutations, extent of aneuploidy and genome‐wide DNA methylation. Both CTCs and cfDNA measures were compared to tumor markers and extracranial tumor burden on radiological imaging. Compared to the CellSearch method applied on peripheral blood, DLA combined with FCM increased the proportion of patients with detectable CTCs from 35% to 70% (P = 0.06). However, the median percentage of cells that could be recovered by the DLA procedure was 29%. Alternatively, cfDNA mutation and methylation analysis detected tumor load in the majority of patients (90% and 93% of samples successfully analyzed, respectively). The aneuploidy score was positive in 35% of all patients. From all tumor measurements in blood, lactate dehydrogenase (LDH) levels were significantly correlated to variant allele frequency (P = 0.004). Furthermore, the presence of CTCs in DLA was associated with tumor burden (P

Circulating tumor DNA (ctDNA) detection has multiple promising applications in oncology, but the road toward implementation in clinical practice is unclear. We aimed to support the implementation process by exploring potential future pathways of ctDNA testing. To do so, we studied four ctDNA‐testing applications in two cancer types and elicited opinions from 30 ctDNA experts in the Netherlands. Our results showed that the current available evidence differed per application and cancer type. Tumor profiling and monitoring treatment response were found most likely to be implemented in non‐small cell lung cancer (NSCLC) within 5 years. For colorectal cancer, applications of ctDNA testing were found to be at an early stage in the implementation process. Demonstrating clinical utility was found a key aspect for successful implementation, but there was no consensus regarding the evidence requirements. The next step toward implementation is to define how clinical utility of biomarkers should be evaluated. Finally, these data indicate that specific challenges for each clinical application and tumor type should be appropriately addressed in a deliberative process involving all stakeholders to ensure implementation of ctDNA testing and timely access for patients.

Several studies have demonstrated the prognostic value of circulating tumor DNA (ctDNA); however, the correlation of mean tumor molecules (MTM)/ml of plasma and mean variant allele frequency (mVAF; %) with clinical parameters is yet to be understood. In this study, we analyzed ctDNA data in a pan‐cancer cohort of 23 543 patients who had ctDNA testing performed using a personalized, tumor‐informed assay (Signatera™, mPCR‐NGS assay). For ctDNA‐positive patients, the correlation between MTM/ml and mVAF was examined. Two subanalyses were performed: (a) to establish the association of ctDNA with tumor volume and (b) to assess the correlation between ctDNA dynamics and patient outcomes. On a global cohort, a positive correlation between MTM/ml and mVAF was observed. Among 18 426 patients with longitudinal ctDNA measurements, 13.3% had discordant trajectories between MTM/ml and mVAF at subsequent time points. In metastatic patients receiving immunotherapy (N = 51), changes in ctDNA levels expressed both in MTM/ml and mVAF showed a statistically significant association with progression‐free survival; however, the correlation with MTM/ml was numerically stronger.

Abstract Angiogenesis, vital for tumor growth and metastasis, is a promising target in cancer therapy. Natural compounds offer potential as antiangiogenic agents with reduced toxicity. This review provides a comprehensive overview of natural product‐based antiangiogenic therapies, focusing on molecular mechanisms and therapeutic potential. A systematic search identified relevant articles from 2019 to 2023. Various natural compounds, including polyphenols, terpenes, alkaloids, cannabinoids, omega‐3 fatty acids, polysaccharides, proteins, and carotenoids, were investigated for their antiangiogenic properties. Challenges such as dose standardization, routes of administration, and potential side effects remain. Further studies, including in‐depth animal models and human epidemiological studies, must elucidate clinical efficacy and safety. Synergistic effects with current antiangiogenic therapies, such as bevacizumab and tyrosine kinase inhibitors, should be explored. Additionally, the potential hormone‐dependent effects of compounds like genistein highlight the need for safety evaluation. In conclusion, natural products hold promise as adjunctive therapies to conventional antineoplastic drugs in modulating angiogenesis in cancer. However, robust clinical trials are needed to validate preclinical findings and ensure safety and efficacy.

Abstract Raspberries (RBs) (Rubus idaeus) are rich in bioactive compounds with promising anticancer properties. This review provides a comprehensive analysis of the anticancer effects of RBs, highlighting their potential as natural agents in cancer prevention and therapy. Bioactive compounds in RBs induce apoptosis, arrest the cell cycle, inhibit angiogenesis, and suppress metastasis. Preclinical studies demonstrate significant anticancer effects against colon, breast, lung, prostate, and cervical cancers, with clinical studies also supporting their therapeutic potential. Although preclinical findings are encouraging, further large‐scale clinical trials are needed to confirm their efficacy and safety in humans. Optimizing formulations to enhance bioavailability and therapeutic effectiveness is crucial. This review emphasizes the potential of dietary interventions involving RBs as a complementary approach to conventional cancer therapies, paving the way for future research and clinical innovations.

Abstract Widespread fuel accumulation in various strata is increasing the risk of high‐severity, crown‐fires. Knowing the vertical forest structure is a crucial factor for fire management planning. Light detection and ranging (LiDAR) sensors have successfully retrieved the main characteristics of the vertical structure of forests. However, detecting and vertically mapping the various fuel strata that can act as ladder fuels (i.e. fuel arrangements that will bring the fire from the surface to the canopy) is challenging and limits our ability to manage the most hazardous forests. Here we show how using LiDAR data and the LadderFuelsR package, developed in the R platform, can provide an automated tool for analysing the vertical fuel structure of a forest and to calculate crown base height (CBH) at tree‐level, among other parameters. We include a suite of tools integrated into a sequential workflow for: (1) calculating the leaf area density (LAD) profiles of each segmented tree; (2) identifying gaps and the non‐continuous fuel layers present; (3) estimating the vertical distance between fuel layers; and (4) retrieving their base height and depth. Additionally, other functions recalculate previous metrics after considering vertical distances greater than certain threshold and calculates the LAD percentage comprised in each fuel layer removing fuel layers below a specified value. Moreover, it calculates tree's CBH based on three criteria: maximum LAD, and both the largest and the last vertical distance between fuel layers. Additionally, when the LAD profiles showed only one fuel layer with CBH at the minimum base height, it identifies the tree's CBH by performing a segmented linear regression. Finally, a collection of plotting functions is developed to represent all previous metrics. This tool has been tested with different LiDAR sensors and thousands of trees in several Pinus pinaster forest areas in Central Spain, and its accuracy has been evaluated using field‐based tree CBH in Pinus palustris Mills dominated forests in Florida (USA). This tool provides accurate information about the vertical structure of a forest, which can be used for prioritizing treatment areas to reduce fire hazard or identify high crown‐fire risk areas.

Abstract The rise of suspicious activities in network communication, driven by increased internet accessibility, necessitates the development of advanced intrusion detection systems (IDS). Existing IDS solutions often exhibit poor performance in detecting suspicious activity and fail to identify various attack types within packet capture (PCAP) files, which monitor network traffic. This paper proposes a deep learning‐based dual IDS model designed to address these issues. The process begins with utilizing the CSE‐CIC‐IDS2019 dataset to extract features from PCAP files. Suspicious activities are detected using the Exponential Geometric‐Gaussian Error Linear Units‐Gated Recurrent Unit (EG‐GELU‐GRU) method. Normal data undergoes further feature extraction and preprocessing through Log ZScore‐Jacosine Density‐Based Spatial Clustering of Applications with Noise (LZ‐JC‐DBSCAN). Feature selection is optimized using the Entropy Pearson R Correlation‐Red Panda optimization algorithm. Suspicious files are flagged, while load balancing is performed on normal data. Attack detection is achieved through word embedding with the Glorot Kaufman‐bidirectional encoder representations from transformers technique and classification via the EG‐GELU‐GRU model. Attacked packets are blocked, and the method is reapplied for attack‐type classification. Experimental results using Python demonstrate the model’s superior performance, achieving 98.18% accuracy and 98.73% precision, surpassing existing approaches and significantly enhancing intrusion detection capabilities.

ABSTRACT Aims/Hypothesis In diabetes haptoglobin (Hp) 2 vs Hp 1 allelic product is associated with cardiac and renal complications. Few studies report both Hp phenotype and Hp levels. In a Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial substudy we evaluated the Hp phenotype, Hp levels, and fenofibrate effects. Materials and Methods In 480 adults with type 2 diabetes (T2D) the Hp phenotype was assessed and the Hp level quantified (both using ELISAs assays) in plasma from baseline, after 6 weeks of fenofibrate, and (in n = 200) at 2 years post‐randomization to fenofibrate or placebo. Results The Hp phenotypes 1‐1, 2‐1, and 2‐2 frequencies were 15%, 49%, and 36%, respectively. Baseline Hp levels differed by phenotype (P

Abstract At least four mechanisms have been proposed to elucidate how neurons in the retrotrapezoid (RTN) region sense changes in CO2/H+ to regulate breathing (i.e., function as respiratory chemosensors). These mechanisms include: (1) intrinsic neuronal sensitivity to H+ mediated by TASK‐2 and GPR4; (2) paracrine activation of RTN neurons by CO2‐responsive astrocytes (via a purinergic mechanism); (3) enhanced excitatory synaptic input or disinhibition; and (4) CO2‐induced vascular contraction. Although blood flow can influence tissue CO2/H+ levels, there is limited understanding of how control of vascular tone in central CO2 chemosensitive regions might contribute to respiratory output. In this review, we focus on recent evidence that CO2/H+‐induced purinergic‐dependent vasoconstriction in the ventral parafacial region near RTN neurons supports respiratory chemoreception. This mechanism appears to be unique to the ventral parafacial region and opposite to other brain regions, including medullary chemosensor regions, where CO2/H+ elicits vasodilatation. We speculate that this mechanism helps to maintain CO2/H+ levels in the vicinity of RTN neurons, thereby maintaining the drive to breathe. Important next steps include determining whether disruption of CO2/H+ vascular reactivity contributes to or can be targeted to improve breathing problems in disease states, such as Parkinson's disease.

Abstract In muscle, digoxin inhibits Na+,K+‐ATPase (NKA) whereas acute exercise can increase NKA gene expression, consistent with training‐induced increased NKA content. We investigated whether oral digoxin increased NKA isoform mRNA expression (qPCR) in muscle at rest, during and post‐exercise in 10 healthy adults, who received digoxin (DIG, 0.25 mg per day) or placebo (CON) for 14 days, in a randomised, double‐blind and cross‐over design. Muscle was biopsied at rest, after cycling 20 min (10 min each at 33%, then 67% V̇O2peak), then to fatigue at 90% V̇O2peak and 3 h post‐exercise. No differences were found between DIG and CON for NKA α1–3 or β1–3 isoform mRNA. Both α1 (354%, P = 0.001) and β3 mRNA (P = 0.008) were increased 3 h post‐exercise, with α2 and β1–2 mRNA unchanged, whilst α3 mRNA declined at fatigue (−43%, P = 0.045). In resting muscle, total β mRNA (∑(β1+β2+β3)) increased in DIG (60%, P = 0.025) and also when transcripts for each isoform were normalised to CON then either summed (P = 0.030) or pooled (n = 30, P = 0.034). In contrast, total α mRNA (∑(α1+α2+α3), P = 0.348), normalised then summed (P = 0.332), or pooled transcripts (n = 30, P = 0.717) did not differ with DIG. At rest, NKA α1–2 and β1–2 protein abundances were unchanged by DIG. Post‐exercise, α1 and β1–2 proteins were unchanged, but α2 declined at 3 h (19%, P = 0.020). In conclusion, digoxin did not modify gene expression of individual NKA isoforms at rest or with exercise, indicating NKA gene expression was maintained consistent with protein abundances. However, elevated resting muscle total β mRNA with digoxin suggests a possible underlying β gene‐stimulatory effect. Highlights What is the central question of this study? Na+,K+‐ATPase (NKA) in muscle is important for Na+/K+ homeostasis. We investigated whether the NKA‐inhibitor digoxin stimulates increased NKA gene expression in muscle and exacerbates NKA gene responses to exercise in healthy adults. What is the main finding and its importance? Digoxin did not modify exercise effects on muscle NKA α1–3 and β1–3 gene transcripts, which comprised increased post‐exercise α1 and β3 mRNA and reduced α3 mRNA during exercise. However, in resting muscle, digoxin increased NKA total β isoform mRNA expression. Despite inhibitory‐digoxin or acute exercise stressors, NKA gene regulation in muscle is consistent with the maintenance of NKA protein contents.

Abstract Intelligent fault diagnosis for wind energy systems requires identifying unique characteristics to differentiate various fault types effectively, even when data discrepancy occurs due to the unpredictable and dynamic nature of its environment. This article addresses some of the challenges of fault classification in wind energy systems by proposing an integrated approach that combines deep learning features with a resampled supervisory control and data acquisition (SCADA) dataset. The methodology involves resampling the imbalanced SCADA dataset using synthetic minority oversampling technique (SMOTE) and near‐miss undersampling techniques, extracting deep learning features using deep convolutional neural network, and feeding them into an XGBoost (extreme gradient boosting) classifier with tuned parameters using adaptive elite‐particle swarm optimization (AEPSO). The effectiveness of the proposed method is demonstrated through validation conducted on a different imbalanced dataset showing superior performance metrics in terms of accuracy. Additionally, the study contributes to methodological advancements in wind turbine fault diagnosis by providing a rigorous framework for fault classification. It is confirmed that utilizing the extracted deep learning features into the resampled data can significantly affect the classification performance metrics. Furthermore, the proposed integrated approach shows significance for fault diagnosis enhancement in wind energy systems and advancing the field towards more efficient and reliable operation.

Abstract During operation, the smart grid is subject to different false data injection attacks (FDIA). If the different kinds of FDIAs and typical failures have been detected, the system operator can develop various defenses to protect the smart grid in multiple categories. Therefore, this article aims to propose a multi‐data classification detection model to differentiate the data of regular operation, faults, and FDIAs when the smart grid suffers FDIAs. Due to the unbalanced number of different kinds of samples in the dataset, Affinitive Borderlinen SMOTE is used to pre‐process the data by oversampling to improve the training accuracy. A multi‐data detection model based on the Inception network is established, and the overall structure of the network and the individual Inception modules are given. A small power system is an example of simulating a smart grid suffering from FDIAs. The designed classification detection model is simulated, validated, and compared with two‐dimensional convolutional neural networks and existing research results. The qualitative analysis of the evaluation metrics can show that the Inception network model has high accuracy and real‐time performance for detecting different data.

Abstract Regular counts of walruses (Odobenus rosmarus) across their pan‐Arctic range are necessary to determine accurate population trends and in turn understand how current rapid changes in their habitat, such as sea ice loss, are impacting them. However, surveying a region as vast and remote as the Arctic with vessels or aircraft is a formidable logistical challenge, limiting the frequency and spatial coverage of field surveys. An alternative methodology involving very high‐resolution (VHR) satellite imagery has proven to be a useful tool to detect walruses, but the feasibility of accurately counting individuals has not been addressed. Here, we compare walrus counts obtained from a VHR WorldView‐3 satellite image, with a simultaneous ground count obtained using a remotely piloted aircraft system (RPAS). We estimated the accuracy of the walrus counts depending on (1) the spatial resolution of the VHR satellite imagery, providing the same WorldView‐3 image to assessors at three different spatial resolutions (i.e., 50, 30 and 15 cm per pixel) and (2) the level of expertise of the assessors (experts vs. a mixed level of experience – representative of citizen scientists). This latter aspect of the study is important to the efficiency and outcomes of the global assessment programme because there are citizen science campaigns inviting the public to count walruses in VHR satellite imagery. There were 73 walruses in our RPAS ‘control’ image. Our results show that walruses were under‐counted in VHR satellite imagery at all spatial resolutions and across all levels of assessor expertise. Counts from the VHR satellite imagery with 30 cm spatial resolution were the most accurate and least variable across levels of expertise. This was a successful first attempt at validating VHR counts with near‐simultaneous, in situ, data but further assessments are required for walrus aggregations with different densities and configurations, on different substrates.

Abstract Objective We investigated the effects of adding regions to current dissemination in space (DIS) criteria for multiple sclerosis (MS). Methods Participants underwent brain, optic nerve, and spinal cord MRI. Baseline DIS was assessed by 2017 McDonald criteria and versions including optic nerve, temporal lobe, or corpus callosum as a fifth region (requiring 2/5), a version with all regions (requiring 3/7) and optic nerve variations requiring 3/5 and 4/5 regions. Performance was evaluated against MS diagnosis (2017 McDonald criteria) during follow‐up. Results Eighty‐four participants were recruited (53F, 32.8 ± 7.1 years). 2017 McDonald DIS criteria were 87% sensitive (95% CI: 76–94), 73% specific (50–89), and 83% accurate (74–91) in identifying MS. Modified criteria with optic nerve improved sensitivity to 98% (91–100), with specificity 33% (13–59) and accuracy 84% (74–91). Criteria including temporal lobe showed sensitivity 94% (84–98), specificity 50% (28–72), and accuracy 82% (72–90); criteria including corpus callosum showed sensitivity 90% (80–96), specificity 68% (45–86), and accuracy 85% (75–91). Criteria adding all three regions (3/7 required) had sensitivity 95% (87–99), specificity 55% (32–76), and accuracy 85% (75–91). When requiring 3/5 regions (optic nerve as the fifth), sensitivity was 82% (70–91), specificity 77% (55–92), and accuracy 81% (71–89); with 4/5 regions, sensitivity was 56% (43–69), specificity 95% (77–100), and accuracy 67% (56–77). Interpretation Optic nerve inclusion increased sensitivity while lowering specificity. Increasing required regions in optic nerve criteria increased specificity and decreased sensitivity. Results suggest considering the optic nerve for DIS. An option of 3/5 or 4/5 regions preserved specificity, and criteria adding all three regions had highest accuracy.

Abstract Objective Predicting long‐term functional outcomes shortly after a stroke is challenging, even for experienced neurologists. Therefore, we aimed to evaluate multiple machine learning models and the importance of clinical/radiological parameters to develop a model that balances minimal input data with reliable predictions of long‐term functional independency. Methods Our study utilized data from the German Stroke Registry on patients with large anterior vessel occlusion who underwent endovascular treatment. We trained seven machine learning models using 30 parameters from the first day postadmission to predict a modified Ranking Scale of 0–2 at 90 days poststroke. Model performance was assessed using a 20‐fold cross‐validation and one‐sided Wilcoxon rank‐sum tests. Key features were identified through backward feature selection. Results We included 7485 individuals with a median age of 75 years and a median NIHSS score at admission of 14 in our analysis. Our Deep Neural Network model demonstrated the best performance among all models including data from 24 h postadmission. Backward feature selection identified the seven most important features to be NIHSS after 24 h, age, modified Ranking Scale after 24 h, premorbid modified Ranking Scale, intracranial hemorrhage within 24 h, intravenous thrombolysis, and NIHSS at admission. Narrowing the Deep Neural Network model's input data to these features preserved the high performance with an AUC of 0.9 (CI: 0.89–0.91). Interpretation Our Deep Neural Network model, trained on over 7000 patients, predicts 90‐day functional independence using only seven clinical/radiological features from the first day postadmission, demonstrating both high accuracy and practicality for clinical implementation on stroke units.

Abstract Objective Glial fibrillary acidic protein (GFAP) is expressed in astrocytes and may be a useful marker of non‐active progressive multiple sclerosis (MS). We evaluate serum GFAP (sGFAP) in a large cohort of MS patients to determine if it predicts progression independent of relapse activity (PIRA), future gait aid, and conversion to secondary progressive disease (SPMS). Methods Adults with clinically isolated syndrome or any subtype of MS who were listed in the Brigham MS Center Research Database and had at least one sGFAP result were included. All clinic visits following first sample were analyzed for PIRA, future gait aid, and conversion to SPMS. Future cognitive dysfunction and fatigue were evaluated as secondary outcomes. Results In total, 741 patients were included (average age: 42.3, average disease duration: 3.7 years, median EDSS: 2, and median follow‐up duration: 10.0 years). Of 643 patients (86.8%) without progressive disease at baseline, 15.9% developed SPMS. Among all 741, 50.5% had PIRA and 18.6% developed a gait aid requirement. sGFAP level predicted PIRA, future gait aid, and conversion to SPMS in univariable models (p

Abstract By applying nonlinear mixed‐effect (NLME) models, model‐integrated evidence (MIE) approaches are able to analyze bioequivalence (BE) data with pharmacokinetic end points that have sparse sampling, which is problematic for non‐compartmental analysis (NCA). However, MIE approaches may suffer from inflation of type I error due to underestimation of parameter uncertainty and to the assumption of asymptotic normality. In this study, we developed a MIE BE analysis method that is based on a pre‐defined model and consists of several steps including model fitting, uncertainty assessment, simulation, and BE determination. The presented MIE approach has several improvements compared with the previously reported model‐integrated methods: (1) treatment, sequence, and period effects are only added to absorption parameters (such as relative bioavailability and rate of absorption) instead of all PK parameters; (2) a simulation step is performed to generate confidence intervals of the pharmacokinetic metrics for BE assessment; and (3) in an effort to maintain type I error, two more advanced parameter uncertainty evaluation approaches are explored, a nonparametric (case resampling) bootstrap, and sampling importance resampling (SIR). To evaluate the developed method and compare the uncertainty assessment methods, simulation experiments were performed for BE studies using a two‐way crossover design with different amounts of information (sparse to rich designs) and levels of variability. Based on the simulation results, the method using SIR for parameter uncertainty quantification controls type I error at the nominal level of 0.05 (i.e., the significance level set for BE evaluation) even for studies with small sample size and/or sparse sampling. As expected, our MIE approach for BE assessment exhibited higher power than the NCA‐based method, especially as the data becomes sparser and/or more variable.

Abstract Population pharmacokinetic (PK) models are widely used to inform drug development by pharmaceutical companies and facilitate drug evaluation by regulatory agencies. Developing a population PK model is a multi‐step, challenging, and time‐consuming process involving iterative manual model fitting and evaluation. A tool for fully automatic model development (AMD) of common population PK models is presented here. The AMD tool is implemented in Pharmpy, a versatile open‐source library for pharmacometrics. It consists of different modules responsible for developing the different components of population PK models, including the structural model, the inter‐individual variability (IIV) model, the inter‐occasional variability (IOV) model, the residual unexplained variability (RUV) model, the covariate model, and the allometry model. The AMD tool was evaluated using 10 real PK datasets involving the structural, IIV, and RUV modules in three sequences. The different sequences yielded generally consistent structural models; however, there were variations in the results of the IIV and RUV models. The final models of the AMD tool showed lower Bayesian Information Criterion (BIC) values and similar visual predictive check plots compared with the available published models, indicating reasonable quality, in addition to reasonable run time. A similar conclusion was also drawn in a simulation study. The developed AMD tool serves as a promising tool for fast and fully automatic population PK model building with the potential to facilitate the use of modeling and simulation in drug development.

Abstract Conventional approaches for establishing bioequivalence (BE) between test and reference formulations using non‐compartmental analysis (NCA) may demonstrate low power in pharmacokinetic (PK) studies with sparse sampling. In this case, model‐integrated evidence (MIE) approaches for BE assessment have been shown to increase power, but may suffer from selection bias problems if models are built on the same data used for BE assessment. This work presents model averaging methods for BE evaluation and compares the power and type I error of these methods to conventional BE approaches for simulated studies of oral and ophthalmic formulations. Two model averaging methods were examined: bootstrap model selection and weight‐based model averaging with parameter uncertainty from three different sources, either from a sandwich covariance matrix, a bootstrap, or from sampling importance resampling (SIR). The proposed approaches increased power compared with conventional NCA‐based BE approaches, especially for the ophthalmic formulation scenarios, and were simultaneously able to adequately control type I error. In the rich sampling scenario considered for oral formulation, the weight‐based model averaging method with SIR uncertainty provided controlled type I error, that was closest to the target of 5%. In sparse‐sampling designs, especially the single sample ophthalmic scenarios, the type I error was best controlled by the bootstrap model selection method.

Abstract Background NPM1‐mutated acute myeloid leukemia (AML) is the most frequent AML subtype. As wild‐type NPM1 is known to orchestrate ribosome biogenesis, it has been hypothesized that altered translation may contribute to leukemogenesis and leukemia maintenance in NPM1‐mutated AML. However, this hypothesis has never been investigated. We reasoned that if mutant NPM1 (NPM1c) directly impacts translation in leukemic cells, loss of NPM1c would result in acute changes in the ribosome footprint. Methods Here, we performed ribosome footprint profiling (Ribo‐seq) and bulk messenger RNA (mRNA) sequencing in two NPM1‐mutated cell lines engineered to express endogenous NPM1c fused to the FKBP (F36V) degron tag (degron cells). Results and discussion Incubation of degron cells with the small compound dTAG‐13 enables highly specific degradation of NPM1c within 4 hours. As expected, RNA‐sequencing data showed early loss of homeobox gene expression following NPM1c degradation, confirming the reliability of our model. In contrast, Ribo‐seq data showed negligible changes in the ribosome footprint in both cell lines, implying that the presence of NPM1c does not influence ribosome abundance and positioning on mRNA. While it is predictable that NPM1c exerts its leukemogenic activity at multiple levels, ribosome footprint does not seem influenced by the presence of mutant NPM1.

Abstract Objective The objective of this study was to measure and describe the national patient experience of radical cystectomy (RC) pathways in the UK using the validated Cystectomy‐Pathway Assessment Tool (C‐PAT). Patients and Methods A cohort of 1081 patients who underwent RC for bladder cancer, between 1 January 2021 and 31 July 2022 at 33 UK cystectomy centres, returned completed C‐PAT responses. SPSS was employed for data summary statistics, including median, interquartile range, Mann Whitney U test or Chi‐square test with a 95% confidence interval to assess statistical significance between potentially associated variables. Open‐text responses in the C‐PAT tool were analysed and coded using NVivo software. Results In this cohort, the greatest perceived delay in the RC pathway, reported by 19% of patients (n = 208), was at the GP consultation to first hospital referral stage with suspected bladder cancer. Around 10% of patients perceived delays at each of the other stages in their pathway. Cancer nurse specialist (CNS) contact was strongly associated with an improved patient experience (p

Abstract The majority of available climate data in global digital archives consist of data only from the 1940s or 1950s onwards, and many of these series have gaps and/or are available for only a subset of the variables which were actually observed. However, there exist billions of historical weather observations from the 1700s, 1800s, and early 1900s that are still in hard‐copy form and are at risk of being lost forever due to deterioration. An assessment of changes in climate extremes in several IPCC regions was not possible in IPCC AR6 WGI owing, in many cases, to the lack of available data. One such region is Africa, where the climate impact research and the ability to predict climate change impacts are hindered by the paucity of access to consistent good‐quality historical observational data. The aim of this innovative project was to use classroom‐based participatory learning to help transcribe some of the many meteorological observations from Africa that are thus far unavailable to researchers. This project transcribed quickly and effectively station series by enrolling the help of second‐year undergraduate students at Maynooth University in Ireland. The newly digitized African data will increase the temporal and spatial coverage of data in this important data‐sparse region. Students gained new skills while helping the global scientific community unearth new insight into past African climate. The project managed to transcribe 79 months of data at Andapa in Madagascar and 56 months of data for Macenta in Guinea. The digitized data will be openly and freely shared with the scientific and wider community via the Pangaea data repository, the C3S Climate Data Store, and the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Information (NCEI) data centre in the US. The project model has the potential for a broader roll‐out to other educational contexts and there is no shortage of data to be rescued. This paper provides details of the project, and all supporting information such as project guidelines and templates to enable other organizations to instigate similar programs.

Abstract High‐quality randomized trial evidence is lacking on whether low‐dose aspirin exerts significant effects on blood pressure (BP) in older adults. The authors assessed longitudinal BP changes in participants enrolled in ASPirin in Reducing Events in the Elderly (ASPREE), a randomized, placebo‐controlled trial of 100 mg daily aspirin in 19 114 community‐dwelling Australian and U.S. adults without cardiovascular disease (CVD), dementia, or independence‐limiting physical disability. Participants’ BP was recorded at baseline and annual study visits, and managed by their usual care provider. BP trajectories for aspirin versus placebo during 4.7 years of follow‐up were examined for systolic and diastolic BP separately, using linear mixed models to account for between and within‐individual variability in BP. Analyses by subgroups were also explored with inclusion of interaction terms in the models. The difference in mean change in systolic BP between aspirin and placebo during study follow‐up was −0.03 mm Hg (95% confidence interval [CI]: −0.13, 0.07; p = .541) (aspirin minus placebo), while the mean difference for change in diastolic BP was −0.05 mm Hg (95% CI: –0.11, 0.01; p = .094). These small, non‐significant differences in BP change between the aspirin and placebo groups were consistent across baseline levels of BP and antihypertensive treatment status (treated/untreated). Likewise, subgroups of age, sex, chronic kidney disease, diabetes, and frailty revealed no interaction effect between the subgroup, aspirin treatment, and time. Interval‐censored Cox proportional hazards regression showed no difference in rates of incident treated hypertension between aspirin and placebo‐treated participants. The authors conclude that daily low‐dose aspirin does not significantly affect BP in older adults when managed by usual care.

Immune checkpoint blockade has emerged as a potent new tool in the war on cancer. However, only a subset of cancer patients benefit from this therapeutic modality, sparking a search for combination therapies to increase the fraction of responding patients. We argue here that inhibition of protein phosphatase 2A (PP2A) is a promising approach to increase responses to immune checkpoint blockade and other therapies that rely on the presence of tumor‐reactive T cells. Inhibition of PP2A increases neoantigen expression on tumor cells, activates the cGAS/STING pathway, suppresses regulatory T cells, and increases cytotoxic T cell activation. In preclinical models, inhibition of PP2A synergizes with immune checkpoint blockade and emerging evidence indicates that patients who have tumors with mutations in PP2A respond better to immune checkpoint blockade. Therefore, inhibition of PP2A activity may be an effective way to sensitize cancer cells to immune checkpoint blockade and cell‐based therapies using tumor‐reactive T cells.

Interferon regulatory factor 4 (IRF4) was initially identified as a key controller in lymphocyte differentiation and function, and subsequently as a dependency factor and therapy target in lymphocyte‐derived cancers. In melanocytes, IRF4 takes part in pigmentation. Although genetic studies have implicated IRF4 in melanoma, how IRF4 functions in melanoma cells has remained largely elusive. Here, we confirmed prevalent IRF4 expression in melanoma and showed that high expression is linked to dependency in cells and mortality in patients. Analysis of genes activated by IRF4 uncovered, as a novel target category, epigenetic silencing factors involved in DNA methylation (DNMT1, DNMT3B, UHRF1) and histone H3K27 methylation (EZH2). Consequently, we show that IRF4 controls the expression of tumour suppressor genes known to be silenced by these epigenetic modifications, for instance cyclin‐dependent kinase inhibitors CDKN1A and CDKN1B, the PI3–AKT pathway regulator PTEN, and primary cilium components. Furthermore, IRF4 modulates activity of key downstream oncogenic pathways, such as WNT/β‐catenin and AKT, impacting cell proliferation and survival. Accordingly, IRF4 modifies the effectiveness of pertinent epigenetic drugs on melanoma cells, a finding that encourages further studies towards therapeutic targeting of IRF4 in melanoma.

Abstract Objective To characterize the experience of people with epilepsy and aligned healthcare workers (HCWs) during the first 18 months of the COVID‐19 pandemic and compare experiences in high‐income countries (HICs) with non‐HICs. Methods Separate surveys for people with epilepsy and HCWs were distributed online in April 2020. Responses were collected to September 2021. Data were collected for COVID‐19 infections, the effect of COVID‐related restrictions, access to specialist help for epilepsy (people with epilepsy), and the impact of the pandemic on work productivity (HCWs). The frequency of responses for non‐HICs and HICs were compared using non‐parametric Chi‐square tests. Results Two thousand one hundred and five individuals with epilepsy from 53 countries and 392 HCWs from 26 countries provided data. The same proportion of people with epilepsy in non‐HICs and HICs reported COVID‐19 infection (7%). Those in HICs were more likely to report that COVID‐19 measures had affected their health (32% vs. 23%; p

Abstract Fenfluramine (FFA), an antiseizure medication (ASM) with serotonergic and sigma‐1 receptor activity, is used to manage patients with developmental and epileptic encephalopathies (DEEs). It is approved in the US for treating seizures associated with Dravet syndrome (DS) and Lennox–Gastaut syndrome (LGS) in patients ≥2 years old and as add‐on therapy for seizures associated with DS and LGS in the EU, UK, and Japan in similarly aged patients. Consensus guidelines for treatment of DS have recommended FFA to be an early‐line ASM, and it has also shown efficacy in managing seizures associated with LGS. DS and LGS are DEEs associated with a range of seizure types, developmental impairments, and multiple comorbidities. Here we provide case vignettes describing 4 patients (3 DS and 1 LGS) aged 4–29 years old in whom up to 14 ASMs had previously failed, to illustrate real‐world practice issues encountered by neurologists. This review provides guidance on the use of FFA in the context of ASM polytherapy and drug–drug interactions (DDIs), behavioral issues, dose titration, and adverse events. Along with data from the clinical trial program, these case vignettes emphasize the low risk of DDIs, a generally well‐tolerated safety profile, and other seizure and nonseizure benefits (eg, improved cognition and sleep) associated with the use of FFA in DS or LGS. Plain Language Summary Fenfluramine is used to treat seizures in individuals with Dravet syndrome and Lennox–Gastaut syndrome, but there are a range of issues that clinicians may face when treating patients. This review highlights four patients from the authors’ everyday clinical work and offers guidance and practical considerations by neurologists with expertise in managing these complex conditions related to drug interactions, dosing, and side effects associated with fenfluramine.

Abstract Objective Epileptic seizures occurring in late adulthood often remain of unknown origin. Sporadic cerebral amyloid angiopathy (CAA) is a cerebral small vessel disease characterized by intracerebral hemorrhage, microhemorrhage and superficial siderosis, occurring mostly in elderly. This observational case–control study aimed to assess the occurrence of CAA in patients experiencing their first seizure in late adulthood. Methods We enrolled consecutive patients aged ≥55 years presenting with late‐onset seizures (LOS) to the emergency departments or outpatient clinics of two Italian centers, from April 2021 to October 2022. Two age‐matched control subjects with neurological symptoms other than epileptic seizure were recruited for each enrolled case. All participants underwent brain MRI (1.5 Tesla) including blood‐sensitive sequences and were assessed for probable CAA diagnosis according to Boston criteria 2.0. Chi‐squared test was performed to evaluate group differences. Univariate logistic regression analysis tested the association between clinical variables and CAA. Results We included 65 patients with LOS (27 females; mean age 72.2 ± 8.9 years) and 130 controls (49 females; mean age 70.3 ± 8.9 years). Diagnosis of probable CAA was achieved in 10.8% (7/65) of LOS patients and 2.3% (3/130) controls, with a statistically significant difference (p = 0.011). The OR for CAA in the LOS group was 5.2 as compared to the control group (95% CI = 1.3–20.6, p = 0.02). Significance The frequency of CAA is significatively higher in patients with LOS as compared to other neurological diseases, suggesting that a portion of LOS of unknown or vascular origin are associated with CAA. Plain Language Summary Late‐onset seizures (LOS) are very frequent in the elderly and often have no clear cause. Cerebral amyloid angiopathy (CAA) is a condition where amyloid proteins build up in the blood vessels of the brain, causing them to become weak and prone to bleeding. In this study, we explored the occurrence of CAA in people with LOS. We found that people with LOS were more likely to have a diagnosis of CAA than controls (i.e., people with other neurological diseases).

Abstract Objective The objective of this study is to report the results of the genetic analysis in a large and well‐characterized population with pediatric‐onset epilepsies and to identify those who could benefit from precision medicine treatments. Methods In this retrospective observational study, we consecutively recruited patients with pediatric‐onset epilepsy observed at a tertiary neurological center over a time span of 7 years, collecting clinical and laboratory findings. Following in‐depth diagnostic process to exclude possible structural and metabolic causes of the disease, patients with a suspected genetically determined etiology underwent next‐generation sequencing (NGS) screening with panels for the analysis of target genes causative of epilepsy. Results We detected likely pathogenic or pathogenic variants (classes IV and V) in 24% of the 562 patients who underwent genetic investigations. By the evaluation of patients' data, we observed that some features (onset of epilepsy before one year old, presence of neurological deficits, psychomotor delay/cognitive disability, and malformative aspects at brain MRI) were significantly associated with class IV or V variants. Moreover, statistical analysis showed that the diagnostic yield resulted higher for patients affected by Progressive Myoclonic Epilepsy (PME) and with early onset developmental and epileptic encephalopathies (DEE), compared with focal epilepsies, genetic generalized epilepsies, DEE with onset at/after 1 y.o., and unclassified epileptic syndromes. According to the results of the genetic screening, up to 33% of patients carrying class IV or V variants resulted potentially eligible for precision medicine treatments. Significance The large‐scale application of NGS multigene panels of analysis is a useful tool for the molecular diagnosis of patients with pediatric‐onset epilepsies, allowing the identification of those who could benefit from a personalized therapeutic approach. Plain Language Summary The analysis of patients with pediatric‐onset epilepsy using advanced technologies for the screening of all the implicated genes allows the identification of the cause of diseases in an ever‐increasing number of cases. Understanding the pathogenic mechanisms could, in some cases, guide the selection and optimization of appropriate treatment approaches for patients.

Abstract Invasive alien species are considered a major contributor to biodiversity loss. Yet, many are favoured for particular ecosystem services that they provide. This is often so in urban environments experiencing rapid environmental and social change and land transformation. Public support is viewed as critical for invasive alien species prevention and management. Furthermore, it is assumed that local citizens are more likely to be willing and ready to engage if they are informed about the costs and benefits associated with invasive alien species. However, the use of, and attitudes towards, invasive alien species in urban areas is poorly understood, especially regarding urban gardens under private ownership and control. This lack of understanding is likely to compromise potential management interventions. Here, we report on a survey of 240 people across 12 small towns in the Eastern Cape province of South Africa to determine their knowledge and perceptions regarding woody invasive alien plants (IAPs), their willingness to engage in control and how these vary in relation to respondent attributes. The findings indicated that respondents have low levels of knowledge about woody IAPs despite 84% of them having at least one woody IAP species in their garden. Nineteen different woody IAPs were noted across the sample of 240 households. A wide range of ecosystem services and disservices from woody IAPs were mentioned. Because of the benefits provided, or the effort required to remove them, only 56% of respondents were willing to have the woody IAPs removed from their gardens, with most considering it the responsibility of government agencies to do so. There was a positive association between the levels of education, income, and the impression that woody IAPs pose a problem and being aware of the term, but not willingness to remove them. Synthesis and implications. These results reveal the complex relationship that urban citizens have with IAPs in garden settings, and for authorities to consider appropriate and targeted awareness campaigns if control strategies are to be successful. Read the free Plain Language Summary for this article on the Journal blog.

Abstract Social connections among individuals are essential components of social‐ecological systems (SESs), enabling people to take actions to more effectively adapt or transform in response to widespread social‐ecological change. Although scholars have associated social connections and cognitions with adaptive capacity, measuring actors' social networks may further clarify pathways for bolstering resilience‐enhancing actions. We asked how social networks and socio‐cognitions, as components of adaptive capacity, and SES regime shift severity affect individual landscape management behaviours using a quantitative analysis of ego network survey data from livestock producers and landcover data on regime shift severity (i.e. juniper encroachment) in the North American Great Plains. Producers who experienced severe regime shifts or perceived high risks from such shifts were not more likely to engage in transformative behaviour like prescribed burning. Instead, we found that social network characteristics explained significant variance in transformative behaviours. Policy implications: Our results indicate that social networks enable behaviours that have the potential to transform SESs, suggesting possible leverage points for enabling capacity and coordination toward sustainability. Particularly where private lands dominate and cultural practices condition regime shifts, clarifying how social connections promote resilience may provide much needed insight to bolster adaptive capacities in the face of global change. Read the free Plain Language Summary for this article on the Journal blog.

Abstract Understanding and addressing biodiversity declines across the globe will require interdisciplinary practices that embrace multiple worldviews and weave knowledge systems. Here, we used a Two‐Eyed Seeing approach to weave Anishinaabe ecological knowledge with peer‐reviewed Western scientific literature to provide a comprehensive understanding of the drivers of a declining moose (mooz; Alces alces) population in Ontario, Canada. We interviewed 66 participants from three Anishinabek communities on the causes of moose decline and conducted a literature review of 52 Western‐science studies that focused on factors that affect moose in Ontario. Our study revealed that there was agreement among knowledge systems on the importance of climate change and disease and parasites in explaining moose population decline in Ontario. Unique perspectives were provided on the mechanisms describing climatic impacts on calf recruitment, with an emphasis on spring onset and green‐up by Western science, and winter onset and timing of the rut by Anishinaabe knowledge. Western science also focused on the effects of habitat disturbance and predation on moose, and Anishinaabe knowledge emphasised harvest pressure. Other factors identified by both knowledge systems included the impacts of roads and railways. Distinctive information offered by Anishinaabe knowledge holders included the displacement of moose from areas in response to the range expansion of white‐tailed deer (waawaashkeshi; Odocoileus virginianus) and the negative effects of contaminants introduced into the environment by mining and forestry activity. Overall, weaving knowledge systems offered a nuanced and wholistic understanding of factors affecting moose and provided different perspectives to explain interacting and cumulative effects. Our study showcases the value in weaving knowledge systems to improve understanding of ecological problems and find wholistic strategies for conservation. Read the free Plain Language Summary for this article on the Journal blog.

Abstract Cancer‐associated cachexia is a multifactorial wasting disorder characterized by anorexia, unintentional weight loss (skeletal muscle mass with or without loss of fat mass), progressive functional impairment, and poor prognosis. This systematic literature review (SLR) examined the relationship between cachexia and survival in patients with colorectal or pancreatic cancer in recent literature. The SLR was conducted following PRISMA guidelines. Embase® and PubMed were searched to identify articles published in English between 1 January 2016 and 10 October 2021 reporting survival in adults with cancer and cachexia or at risk of cachexia, defined by international consensus (IC) diagnostic criteria or a broader definition of any weight loss. Included publications were studies in ≥100 patients with colorectal or pancreatic cancer. Thirteen publications in patients with colorectal cancer and 13 with pancreatic cancer met eligibility criteria. Included studies were observational and primarily from Europe and the United States. Eleven studies (42%) reported cachexia using IC criteria and 15 (58%) reported any weight loss. An association between survival and cachexia or weight loss was assessed across studies using multivariate (n = 23) or univariate (n = 3) analyses and within each study across multiple weight loss categories. Cachexia/weight loss was associated with a statistically significantly poorer survival in at least one weight loss category in 16 of 23 studies that used multivariate analyses and in 1 of 3 studies (33%) that used univariate analyses. Of the 17 studies demonstrating a significant association, 9 were in patients with colorectal cancer and 8 were in patients with pancreatic cancer. Cachexia or weight loss was associated with significantly poorer survival in patients with colorectal or pancreatic cancer in nearly two‐thirds of the studies. The classification of weight loss varied across and within studies (multiple categories were evaluated) and may have contributed to variability. Nonetheless, awareness of cachexia and routine assessment of weight change in clinical practice in patients with colorectal or pancreatic cancer could help inform prognosis and influence early disease management strategies.

Abstract Background Preclinical rheumatoid arthritis (Pre‐RA) is defined as the early stage before the development of clinical RA. While cachexia is a well‐known and potentially modifiable complication of RA, it is not known if such an association exists also in the Pre‐RA stage. To investigate such issue, we aimed to compare the longitudinal alterations in the muscle composition and adiposity of participants with Pre‐RA with the matched controls. Methods In this observational cohort study, the Osteoarthritis Initiative (OAI) participants were categorized into Pre‐RA and propensity score (PS)‐matched control groups. Pre‐RA was retrospectively defined as the absence of RA from baseline to year‐2, with progression to physician‐diagnosed clinical RA between years 3–8 of the follow‐up period. Using a validated deep learning algorithm, we measured MRI biomarkers of thigh muscles and adiposity at baseline and year‐2 follow‐ups of the cohort. The outcomes were the differences between Pre‐RA and control groups in the 2‐year rate of change for thigh muscle composition [cross‐sectional area (CSA) and intramuscular adipose tissue (Intra‐MAT)] and adiposity [intermuscular adipose tissue (Inter‐MAT) and subcutaneous adipose tissue (SAT)]. Linear mixed‐effect regression models were used for comparison. Results After 1:3 PS‐matching of the groups for confounding variables (demographics, risk factors, co‐morbidities, and knee osteoarthritis status), 408 thighs (102 Pre‐RA and 306 control) of 322 participants were included (age mean ± SD: 61.7 ± 8.9 years; female/male: 1.8). Over a 2‐year period, Pre‐RA was associated with a larger decrease in total thigh muscle CSA [estimate, 95% confidence interval (CI): −180.13 mm2/2‐year, −252.80 to −107.47, P‐value

Abstract Background Cachexia, a syndrome with high prevalence in non‐small cell lung cancer patients, impairs quality of life and reduces tolerance and responsiveness to cancer therapy resulting in decreased survival. Optimal nutritional care is pivotal in the treatment of cachexia and a recommended cornerstone of multimodal therapy. Here, we investigated the therapeutic effect of an intervention diet consisting of a specific combination of high protein, leucine, fish oil, vitamin D, galacto‐oligosaccharides, and fructo‐oligosaccharides on the development and progression of cachexia in an orthotopic lung cancer mouse model. Methods Eleven‐week‐old male 129S2/Sv mice were orthotopically implanted with 344P lung epithelial tumour cells or vehicle (control). Seven days post‐implantation tumour‐bearing (TB) mice were allocated to either intervention‐ or isocaloric control diet. Cachexia was defined as 5 days of consecutive body weight loss, after which mice were euthanized for tissue analyses. Results TB mice developed cachexia accompanied by significant loss of skeletal muscle mass and epididymal fat mass compared with sham operated mice. The cachectic endpoint was significantly delayed (46.0 ± 15.2 vs. 34.7 ± 11.4 days), and the amount (−1.57 ± 0.62 vs. −2.13 ± 0.57 g) and progression (−0.26 ± 0.14 vs. −0.39 ± 0.11 g/day) of body weight loss were significantly reduced by the intervention compared with control diet. Moreover, systemic inflammation (pentraxin‐2 plasma levels) and alterations in molecular markers for proteolysis and protein synthesis, indicative of muscle atrophy signalling in TB‐mice, were suppressed in skeletal muscle by the intervention diet. Conclusions Together, these data demonstrate the potential of this multinutrient intervention, targeting multiple components of cachexia, as integral part of lung cancer management.

ABSTRACT Aims/Introduction The FreeStyle Libre (FSL) intermittently scanned continuous glucose monitoring (isCGM) system continually measures interstitial glucose levels and provides the data to users in numerical and graphical formats that guide users in their daily diabetes self‐management. Although numerous studies have demonstrated the glycemic benefits of FSL in pediatric and adult populations, few studies have characterized FSL use specifically by Japanese adults with type 1 or 2 diabetes. We utilized established CGM metrics to assess glycemic control in a large cohort of Japanese adults with type 1 and 2 diabetes. Materials and Methods A total of 3,463 anonymized FSL users provided categorization into one of four therapy groups of interest: type 1 diabetes (n = 1,768), type 2 diabetes‐multiple daily injections (MDI) (n = 612), type 2 diabetes‐basal (BOI) (n = 343), and type 2 diabetes‐non‐insulin (NIT) (n = 740). Established CGM metrics were used to assess glycemic control. Results All study groups showed relatively good glycemic control. Type 1 diabetes users showed the highest glucose variability (SD, 61 mg/dL; and %CV, 40%), above the established target level (%CV ≤ 36%). type 2 diabetes‐MDI and type 2 diabetes‐BOI users had similar levels of glucose variability (both within target). Type 2 diabetes‐NIT users had the highest mean % time in range (TIR) (84.3%) and largest percentage of users that met the target of %TIR > 70% (87.4%). In contrast, type 1 diabetes users had the lowest mean %TIR (62.6%) and the lowest percentage meeting the established %TIR target (30.5%). Conclusions By utilizing CGM devices in daily diabetes care, both healthcare professionals and patients can monitor glycemic excursions and gain insights into their historical glucose control patterns.

Abstract Historically, most insect chronoecological research has used direct observations, cameras or infrared beam‐based monitors to quantify movement across timed intervals. Although some alternative DIY systems are cheaper than the current standard locomotor activity monitor, these options remain complicated to build and/or computationally intensive. We developed the imaging Locomotor Activity Monitor (iLAM), an affordable (~$75 USD/unit) system for activity quantification. The iLAM utilizes a Raspberry Pi Zero W computer and night‐vision camera inside a flight cage to photograph a population of insects at user‐defined intervals. Open‐source, modular R‐scripts process the images and output a file containing the number, size, coordinate location and timestamp of all movements (blobs) identified between consecutive images. Output can be analysed directly or converted into the standard TriKinetics DAM format. We demonstrated the flexibility and power of the iLAM system by comparing diel and circadian activity of different insect species (fireflies: Photinus marginellus, P. greeni, P. obscurellus), ecotypes (moths: Ostrinia nubilalis) and sexes (moths: O. nubilalis). Data captured by only six iLAMs ($450) identified that peak activity of O. nubilalis females (AZT: 19.2 h) occurs significantly earlier than males (22.0 h). Additionally, male moths from a univoltine population exhibited a significantly shorter endogenous period length (AZT: 21.3 h) than males from a bivoltine genetic background (22.7 h). The iLAM will serve as a valuable tool for researchers seeking to measure locomotor activity across diverse species, sexes and populations in constant and changing environments.