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EWS fusion oncoproteins underlie several human malignancies including Desmoplastic Small Round Cell Tumor (DSRCT), an aggressive cancer driven by EWS-WT1 fusion proteins. Here we combine chromatin occupancy and 3D profiles to identify EWS-WT1-dependent gene regulation networks and target genes. We show that EWS-WT1 is a powerful chromatin activator controlling an oncogenic gene expression program that characterizes primary tumors. Similar to wild type WT1, EWS-WT1 has two isoforms that differ in their DNA binding domain and we find that they have distinct DNA binding profiles and are both required to generate viable tumors that resemble primary DSRCT. Finally, we identify candidate EWS-WT1 target genes with potential therapeutic implications, including CCND1, whose inhibition by the clinically-approved drug Palbociclib leads to marked tumor burden decrease in DSRCT PDXs in vivo. Taken together, our studies identify gene regulation programs and therapeutic vulnerabilities in DSRCT and provide a mechanistic understanding of the complex oncogenic activity of EWS-WT1.

The impact of variations in the three-dimensional structure of the genome has been recognized, but solid cancer tissue studies are limited. Here, we performed integrated deep Hi-C sequencing with matched whole-genome sequencing, whole-genome bisulfite sequencing, 5-hydroxymethylcytosine (5hmC) sequencing and RNA sequencing across a cohort of 80 biopsy samples from patients with metastatic castration-resistant prostate cancer. Dramatic differences were present in gene expression, 5-methylcytosine/5hmC methylation and in structural variation versus mutation rate between A and B (open and closed) chromatin compartments. A subset of tumors exhibited depleted regional chromatin contacts at the AR locus, linked to extrachromosomal circular DNA (ecDNA) and worse response to AR signaling inhibitors. We also identified topological subtypes associated with stark differences in methylation structure, gene expression and prognosis. Our data suggested that DNA interactions may predispose to structural variant formation, exemplified by the recurrent TMPRSS2-ERG fusion. This comprehensive integrated sequencing effort represents a unique clinical tumor resource.

BACKGROUND: Neurotrophic tyrosine receptor kinase (NTRK) gene fusions are rare oncogenic drivers prevalent in 0.3% of solid tumors. They are most common in salivary gland cancer (2.6%), thyroid cancer (1.6%), and soft-tissue sarcoma (1.5%). Currently, there are 2 US Food and Drug Administration-approved targeted therapies for NTRK gene fusions: larotrectinib, approved in 2018, and entrectinib, approved in 2019. To date, the real-world uptake of tyrosine receptor kinase inhibitor (TRKi) use for NTRK-positive solid tumors in academic cancer centers remains largely unknown. OBJECTIVE: To describe the demographics, clinical and genomic characteristics, and testing and treatment patterns of patients with NTRK-positive solid tumors treated at US academic cancer centers. METHODS: This was a retrospective chart review study conducted in academic cancer centers in the United States. All patients diagnosed with an NTRK fusion-positive (NTRK1, NTRK2, NTRK3) solid tumor (any stage) and who received cancer treatment at participating sites between January 1, 2012, and July 1, 2023, were included in this study. Patient demographics, clinical characteristics, genomic characteristics, NTRK testing data, and treatment patterns were collected from electronic medical records and analyzed using descriptive statistics as appropriate. RESULTS: In total, 6 centers contributed data for 55 patients with NTRK-positive tumors. The mean age was 49.3 (SD = 20.5) years, 51% patients were female, and the majority were White (78%). The median duration of time from cancer diagnosis to NTRK testing was 85 days (IQR = 44-978). At the time of NTRK testing, 64% of patients had stage IV disease, compared with 33% at cancer diagnosis. Prevalent cancer types in the overall cohort included head and neck (15%), thyroid (15%), brain (13%), lung (13%), and colorectal (11%). NTRK1 fusions were most common (45%), followed by NTRK3 (40%) and NTRK2 (15%). Across all lines of therapy, 51% of patients (n = 28) received a TRKi. Among TRKi-treated patients, 71% had stage IV disease at TRKi initiation. The median time from positive NTRK test to initiation of TRKi was 48 days (IQR = 9-207). TRKis were commonly given as first-line (30%) or second-line (48%) therapies. Median duration of therapy was 610 (IQR = 182-764) days for TRKi use and 207.5 (IQR = 42-539) days for all other first-line therapies. CONCLUSIONS: This study reports on contemporary real-world NTRK testing patterns and use of TRKis in solid tumors, including time between NTRK testing and initiation of TRKi therapy and duration of TRKi therapy.

PURPOSE: There is limited information on the clustering or co-occurrence of complications after spinal fusion surgery for neuromuscular disease in children. We aimed to identify the frequency and predictive factors of co-occurring perioperative complications in these children. METHODS: In this retrospective database cohort study, we identified children (ages 10-18 years) with neuromuscular scoliosis who underwent elective spinal fusion in 2012-2020 from the National Surgical Quality Improvement Program-Pediatric database. The rates of co-occurring complications within 30 days were calculated, and associated factors were identified by logistic regression analysis. Correlation between a number of complications and outcomes was assessed. RESULTS: Approximately 11% (709/6677 children with neuromuscular scoliosis undergoing spinal fusion had co-occurring complications: 7% experienced two complications and 4% experienced ≥ 3. The most common complication was bleeding/transfusion (80%), which most frequently co-occurred with pneumonia (24%) and reintubation (18%). Surgical time ≥ 400 min (odds ratio (OR) 1.49 [95% confidence interval (CI) 1.25-1.75]), fusion ≥ 13 levels (1.42 [1.13-1.79]), and pelvic fixation (OR 1.21 [1.01, 1.44]) were identified as procedural factors that independently predicted concurrent complications. Clinical risk factors for co-occurring complications included an American Society of Anesthesiologist physical status classification ≥ 3 (1.73 [1.27-2.37]), structural pulmonary/airway abnormalities (1.24 [1.01-1.52]), impaired cognitive status (1.80 [1.41-2.30]), seizure disorder (1.36 [1.12-1.67]), hematologic disorder (1.40 [1.03-1.91], preoperative nutritional support (1.34 [1.08-1.72]), and congenital malformations (1.20 [1.01-1.44]). Preoperative tracheostomy was protective against concurrent complications (0.62 [0.43-0.89]). Significant correlations were found between number of complications and length of stay, non-home discharge, readmissions, and death. CONCLUSION: Longer surgical time (≥ 400 min), fusion ≥ 13 levels and pelvic fixation are surgical risk factors independently associated with co-occurring complications, which were associated with poorer patient outcomes. Recognizing identified nonmodifiable risk factors might also be important for preoperative planning and risk stratification of children with neuromuscular scoliosis requiring spinal fusion. LEVEL OF EVIDENCE: Level IV evidence.

Aberrant expression of the E26 transformation-specific (ETS) transcription factors characterizes numerous human malignancies. Many of these proteins, including EWS:FLI1 and EWS:ERG fusions in Ewing sarcoma (EwS) and TMPRSS2:ERG in prostate cancer (PCa), drive oncogenic programs via binding to GGAA repeats. We report here that both EWS:FLI1 and ERG bind and transcriptionally activate GGAA-rich pericentromeric heterochromatin. The respective pathogen-like HSAT2 and HSAT3 RNAs, together with LINE, SINE, ERV, and other repeat transcripts, are expressed in EwS and PCa tumors, secreted in extracellular vesicles (EVs), and are highly elevated in plasma of patients with EwS with metastatic disease. High human satellite 2 and 3 (HSAT2,3) levels in EWS:FLI1- or ERG-expressing cells and tumors were associated with induction of G2/M checkpoint, mitotic spindle, and DNA damage programs. These programs were also activated in EwS EV-treated fibroblasts, coincident with accumulation of HSAT2,3 RNAs, proinflammatory responses, mitotic defects, and senescence. Mechanistically, HSAT2,3-enriched cancer EVs induced cGAS-TBK1 innate immune signaling and formation of cytosolic granules positive for double-strand RNAs, RNA-DNA, and cGAS. Hence, aberrantly expressed ETS proteins derepress pericentromeric heterochromatin, yielding pathogenic RNAs that transmit genotoxic stress and inflammation to local and distant sites. Monitoring HSAT2,3 plasma levels and preventing their dissemination may thus improve therapeutic strategies and blood-based diagnostics.

AbstractRNA-binding proteins (RBPs) are emerging as a novel class of therapeutic targets in cancer, including in leukemia, given their important role in posttranscriptional gene regulation, and have the unexplored potential to be combined with existing therapies. The RBP insulin-like growth factor 2 messenger RNA-binding protein 3 (IGF2BP3) has been found to be a critical regulator of MLL-AF4 leukemogenesis and represents a promising therapeutic target. Here, we study the combined effects of targeting IGF2BP3 and menin-MLL interaction in MLL-AF4-driven leukemia in vitro and in vivo, using genetic inhibition with CRISPR-Cas9-mediated deletion of Igf2bp3 and pharmacologic inhibition of the menin-MLL interaction with multiple commercially available inhibitors. Depletion of Igf2bp3 sensitized MLL-AF4 leukemia to the effects of menin-MLL inhibition on cell growth and leukemic initiating cells in vitro. Mechanistically, we found that both Igf2bp3 depletion and menin-MLL inhibition led to increased differentiation in vitro and in vivo, seen in functional readouts and by gene expression analyses. IGF2BP3 knockdown had a greater effect on increasing survival and attenuating disease than pharmacologic menin-MLL inhibition with small molecule MI-503 alone and showed enhanced antileukemic effects in combination. Our work shows that IGF2BP3 is an oncogenic amplifier of MLL-AF4-mediated leukemogenesis and a potent therapeutic target, providing a paradigm for targeting leukemia at both the transcriptional and posttranscriptional level.

Machine learning (ML) applications in medical artificial intelligence (AI) systems have shifted from traditional and statistical methods to increasing application of deep learning models. This survey navigates the current landscape of multimodal ML, focusing on its profound impact on medical image analysis and clinical decision support systems. Emphasizing challenges and innovations in addressing multimodal representation, fusion, translation, alignment, and co-learning, the paper explores the transformative potential of multimodal models for clinical predictions. It also highlights the need for principled assessments and practical implementation of such models, bringing attention to the dynamics between decision support systems and healthcare providers and personnel. Despite advancements, challenges such as data biases and the scarcity of big data in many biomedical domains persist. We conclude with a discussion on principled innovation and collaborative efforts to further the mission of seamless integration of multimodal ML models into biomedical practice.

Neurotrophic receptor tyrosine kinases (NTRKs) belong to the receptor tyrosine kinase (RTK) family. NTRKs are responsible for the activation of multiple downstream signaling pathways that regulate cell growth, proliferation, differentiation, and apoptosis. NTRK-associated mutations often result in oncogenesis and lead to aberrant activation of downstream signaling pathways including MAPK, JAK/STAT, and PLCγ1. This study characterizes the NACC2-NTRK2 oncogenic fusion protein that leads to pilocytic astrocytoma and pediatric glioblastoma. This fusion joins the BTB domain (Broad-complex, Tramtrack, and Bric-a-brac) domain of NACC2 (Nucleus Accumbens-associated protein 2) with the transmembrane helix and tyrosine kinase domain of NTRK2. We focus on identifying critical domains for the biological activity of the fusion protein. Mutations were introduced in the charged pocket of the BTB domain or in the monomer core, based on a structural comparison of the NACC2 BTB domain with that of PLZF, another BTB-containing protein. Mutations were also introduced into the NTRK2-derived portion to allow comparison of two different breakpoints that have been clinically reported. We show that activation of the NTRK2 kinase domain relies on multimerization of the BTB domain in NACC2-NTRK2. Mutations which disrupt BTB-mediated multimerization significantly reduce kinase activity and downstream signaling. The ability of these mutations to abrogate biological activity suggests that BTB domain inhibition could be a potential treatment for NACC2-NTRK2-induced cancers. Removal of the transmembrane helix leads to enhanced stability of the fusion protein and increased activity of the NACC2-NTRK2 fusion, suggesting a mechanism for the oncogenicity of a distinct NACC2-NTRK2 isoform observed in pediatric glioblastoma.

T(8;21)(q22;q22), which generates the AML1-ETO fusion oncoprotein, is a common chromosomal abnormality in acute myeloid leukemia (AML) patients. Despite having favorable prognosis, 40% of patients will relapse, highlighting the need for innovative models and application of the newest technologies to study t(8;21) leukemogenesis. Currently, available AML1-ETO mouse models have limited utility for studying the pre-leukemic stage because AML1-ETO produces mild hematopoietic phenotypes and no leukemic transformation. Conversely, overexpression of a truncated variant, AML1-ETO9a (AE9a), promotes fully penetrant leukemia and is too potent for studying pre-leukemic changes. To overcome these limitations, we devised a germline-transmitted Rosa26 locus AE9a knock-in mouse model that moderately overexpressed AE9a and developed leukemia with long latency and low penetrance. We observed pre-leukemic alterations in AE9a mice, including skewing of progenitors towards granulocyte/monocyte lineages and replating of stem and progenitor cells. Next, we performed single-cell RNA sequencing to identify specific cell populations that contribute to these pre-leukemic phenotypes. We discovered a subset of common myeloid progenitors that have heightened granulocyte/monocyte bias in AE9a mice. We also observed dysregulation of key hematopoietic transcription factor target gene networks, blocking cellular differentiation. Finally, we identified Sox4 activation as a potential contributor to stem cell self-renewal during the pre-leukemic stage.

BACKGROUND: Atlantoaxial dislocation is often facilitated by interlaminar bone grafting. However, there are relatively few reports on the treatment of complex atlantoaxial dislocation with posterior atlantoaxial lateral mass interarticular release and fusion. OBJECTIVE: To explore the safety and effectiveness of atlantoaxial dislocation treated by simple posterior atlantoaxial lateral block interarticular release and fusion. METHODS: We retrospectively analyzed the clinical data of 30 patients with atlantoaxial dislocation who were treated from January 2017 to July 2021, all of whom suffered from reducible atlantoaxial dislocation. Posterior atlantoaxial lateral mass interarticular release and fusion were performed in all patients. During the surgery, patented instruments were used to release the atlantoaxial lateral mass joint, and posterior screw reduction and fixation were used with bone grafting in the lateral mass joint space. The postoperative follow-up period was 6 to 24 months, mean (13.0±5.4) months. During the follow-up period, cervical MRI was reviewed to observe the decompression of the upper cervical spine. X-ray films and CT scans were reviewed to observe the reduction of the upper cervical spine, as well as the internal fixation for looseness and breakage. CT scans were reviewed to assess interlateral block implant fusion. The Japanese Orthopaedic Association score was used to evaluate the improvement of spinal cord function. The neck disability index and the quality of life scale were used to assess the improvement of daily life function. The atlanto-anterior interspace and atlanto-planar spinal effective space were used to evaluate atlantoaxial repositioning and decompression. RESULTS AND CONCLUSION: (1) The surgery of 30 patients went smoothly, and no serious complications such as spinal nerve and vertebral artery injuries occurred during the operation. Postoperative review of cervical MRI showed that the spinal cord compression was lifted. X-ray film and CT showed that the atlanto-anterior gap was significantly reduced; the effective space of atlantoaxial spinal cord was significantly increased, and neurological dysfunctional symptoms were significantly reduced. (2) During the follow-up period, X-ray film and CT showed that the internal fixation was solid; no broken nails or rods occurred, and there was no recurrence of atlantoaxial dislocation. (3) The Japanese Orthopaedic Association scores, neck disability index, and quality of life scores were significantly improved at the last follow-up compared with the preoperative period (P < 0.05). The average improvement rate of Japanese Orthopaedic Association scores at the last follow-up was 73.1%. The average neck disability index was 8.80%. All of the patients had a continuous bone-scalp connection between atlantoaxial lateral block joints to achieve osseous fusion. (4) These findings indicate that the use of simple posterior atlantoaxial lateral block interarticular release and fusion for the treatment of atlantoaxial dislocation can significantly increase the fusion rate and shorten the fusion time. [ABSTRACT FROM AUTHOR]

This research introduces a Computer-Aided Diagnosis-system designed aimed at automated detections & classification of tomato leaf diseases, combining traditional handcrafted features with advanced deep learning techniques. The system's process encompasses preprocessing, feature extraction, feature fusion, and classification. It utilizes enhancement filters and segmentation algorithms to isolate with Regions-of-Interests (ROI) in images tomato leaves. These features based arranged in ABCD rule (Asymmetry, Borders, Colors, and Diameter) are integrated with outputs from a Convolutional Neural Network (CNN) pretrained on ImageNet. To address data imbalance, we introduced a novel evaluation method that has shown to improve classification accuracy by 15% compared to traditional methods, achieving an overall accuracy rate of 92% in field tests. By merging classical feature engineering with modern machine learning techniques under mutual information-based feature fusion, our system sets a new standard for precision in agricultural diagnostics. Specific performance metrics showcasing the effectiveness of our approach in automated detection and classifying of tomato leaf disease. [ABSTRACT FROM AUTHOR]

AbstractJoining copper with stainless steel (SS) is essential due to their complementary properties. Copper’s excellent thermal conductivity and SS’s robustness and high mechanical strength create joints that manage heat effectively and maintain structural integrity. This combination is particularly beneficial in heat exchangers, fusion reactors, electronics, batteries, chemical processing, and nuclear engineering, where efficient heat management and corrosion resistance are critical. However, the heterogeneous nature of these materials presents challenges such as differing melting points and thermal expansion coefficients. Deep understanding of metallurgical processes is needed to overcome these issues. Successfully joining copper and SS via well-established fusion welding processes can lead to innovative industrial solutions, enhancing performance, reliability, and durability across various applications. This article reviews fusion welding techniques for joining copper to SS, highlighting the need for precise parametric optimization. It identifies research gaps and emphasizes innovative welding methods to enhance joint quality, supporting advanced, reliable structural component development. [ABSTRACT FROM AUTHOR]

Man‐made ceramics generally undergo harsh manufacturing conditions (e.g., high‐temperature sintering). In contrast, mineral structures with superior mechanical strength are generated in organisms under mild biocompatible conditions. Herein, it is reported that ceramic objects can be directly produced and strengthened by drying purely inorganic gels (PIGs), mimicking the biological tactic of fabricating continuous monoliths from hydrated amorphous precursors. The overall process is easy and biocompatible in that solutions of common iron and molybdate salts are mixed to generate a PIG, consisting of 80 wt% liquid water and amorphous mineral nanoparticles (hydrated iron molybdate: FeMo2H7O11), which, upon drying under mild temperature, turns into a residual stress‐strengthened ceramic block that displays a high mechanical performance (with a hardness/elastic modulus of 1.7/17.5 GPa). Analogous to the well‐known Prince Rupert's drop reinforced by residual stress upon quenching, the uneven volume shrinkage from the outside inwards during dehydration builds up residual stress that enables amorphous mineral fusion (with the assistance of hydration water) and strengthening. Furthermore, a dramatic bandgap reduction is achieved in the dried objects due to local structural changes of the Fe atoms under residual stress. This PIG‐dehydration approach holds promise for green ceramic manufacturing and offers insights into biomineralization puzzles. [ABSTRACT FROM AUTHOR]

Background: The earliest manifestation of alcohol‐associated liver disease (ALD) is steatosis characterized by deposition of fat in specialized organelles called lipid droplets (LDs). While alcohol administration causes a rise in LD numbers in the hepatocytes, little is known regarding their characteristics that allow their accumulation and size to increase. The aim of the present study is to gain insights into underlying pathophysiological mechanisms by investigating the ethanol‐induced changes in hepatic LD proteome as a function of LD size. Methods: Adult male Wistar rats (180–200 g BW) were fed with ethanol liquid diet for 6 weeks. At sacrifice, large‐, medium‐, and small‐sized hepatic LD subpopulations (LD1, LD2, and LD3, respectively) were isolated and subjected to morphological and proteomic analyses. Results: Morphological analysis of LD1‐LD3 fractions of ethanol‐fed rats clearly demonstrated that LD1 contained larger LDs compared with LD2 and LD3 fractions. Our preliminary results from principal component analysis showed that the proteome of different‐sized hepatic LD fractions was distinctly different. Proteomic data analysis identified over 2000 proteins in each LD fraction with significant alterations in protein abundance among the three LD fractions. Among the altered proteins, several were related to fat metabolism, including synthesis, incorporation of fatty acid, and lipolysis. Ingenuity pathway analysis revealed increased fatty acid synthesis, fatty acid incorporation, LD fusion, and reduced lipolysis in LD1 compared to LD3. Overall, the proteomic findings indicate that the increased level of protein that facilitates fusion of LDs combined with an increased association of negative regulators of lipolysis dictates the generation of large‐sized LDs during the development of alcohol‐associated hepatic steatosis. Conclusion: Several significantly altered proteins were identified in different‐sized LDs isolated from livers of ethanol‐fed rats. Ethanol‐induced increases in specific proteins that hinder LD lipid metabolism led to the accumulation and persistence of large‐sized LDs in the liver. [ABSTRACT FROM AUTHOR]

Objectives: Whether gemination or fusion, double teeth are rare worldwide, including Africa based on few published data. New cases from the continent are tallied, and anomalies potentially associated with double teeth are identified. These findings should interest a range of dental researchers. Methods: The presence of double teeth was recorded in 97 modern and premodern North and sub‐Saharan African samples (5631 inds.). They and coexistent anomalies are described relative to published examples. Prevalence was estimated as possible, using a Poisson model for 95% confidence intervals (CI). Results: Three maxillary double teeth were identified: a primary left lateral incisor in a Nubian child (1938–1756 BC), permanent left central incisor in an adult Egyptian (3650–3500 BC), and permanent right central incisor in a modern (19th century) adult from Guinea. Each co‐occurs, respectively, with a talon cusp, peg lateral incisor and, in the latter individual, second premolar crown variation with rotation, and third molar dens evaginatus. Double tooth prevalence is 0.048% (CI 0.001%–0.270%), with regional variation, in premodern, and 0.000% in modern North Africans. It is 0.000% for premodern and 0.048% for modern sub‐Saharan Africans (0.008%–1.714%). Conclusions: The double incisors are comparable to other global examples, indicative of common developmental processes during odontogenesis. Prevalence is lower than published modern rates, to suggest some exceptionality in Africans as reported earlier for other dental variants. Finally, though circumstantial, double teeth and accompanying anomalies may share an etiology. Continuing research overall, and in Africa specifically, will promote an improved understanding of double teeth formation and expression. [ABSTRACT FROM AUTHOR]

The evolution of traffic monitoring systems provides rich traffic data from multiple sensors. Fuzing the data has the potential to enhance the quality of travel time estimation. It also provides better spatial-temporal coverage in traffic observations. However, each sensor's unique data collection process results in fusion challenges with respect to the coverage and data quality differences between various sources. These factors determine the degree of confidence that should be considered when fuzing different types of data. To this end, this paper proposes an adaptive weight-based fusion technique (ABAFT) that considers data spatial coverage and quality or confidence as the factors constructing the weight. The proposed ABAFT was tested using different scenarios on synthetic GPS and Bluetooth MAC Scanners data from an urban arterial corridor. The results show that the ABAFT can increase the travel time estimation accuracy by over 10%, and reliability by over 8% compared to the single sensor estimators. It also outperforms the simple average and standard-error-based fusion by around 4%. ABAFT is easy to be implemented on multiple sources of information available to transport agencies for a single point of truth. [ABSTRACT FROM AUTHOR]

The objective of this research endeavor is to identify an effective model for the classification of multiple viral respiratory diseases, encompassing COVID-19. The feature extraction phase from medical images constitutes a formidable challenge in achieving optimal disease classification outcomes. In this work, a selection of the best models among several popular transfer learning (TL) models is realized. The concatenation of the best models for better features extraction is used; the deep learning (DL) methods for deep features extraction and deep data reduction were applied for an optimal classification. This paper includes two studies, the first was applied to binary classification (COVID-19/Normal) and the second is concerned with multi-classification (COVID-19/Normal/VPneumonia). The validation of the proposed approaches is made on a big datasets: (i) binary classification 4800 COVID-19 and 4803 Normal images for the two cases Chest X-Ray (CXR) and Computed Tomography (CT) scans, and (ii) multi-class classification 3931 COVID-19, 3931 Normal, and 4273 Viral Pneumonia (VP) images for CXR. This study hypothesized that the proposed approach might be able to extract specific graphical features of COVID-19 and provide a clinical diagnosis ahead of the pathogenic test. Experimental results achieved in binary classification a high: Val_accuracy = 99.87% and 98.41%, Test_accuracy = 100% and 99.21%, Test_time = 0.002 s and 0.008 s per image for CT scans and CXR images, respectively, and in multi-classification: Val_accuracy = 97.48%, Test_accuracy = 92.96% with Test_time = 0.006 s per image for CXR images. [ABSTRACT FROM AUTHOR]

The modified Lapidus procedure has emerged as a versatile solution for various pedal pathologies, particularly hallux abducto valgus. There have been numerous modifications over time regarding fixation techniques, joint preparation methods, graft utilization, and weightbearing protocols. However, concerns persist regarding prolonged nonweightbearing postoperatively, prompting the need for alternative approaches. This retrospective descriptive cohort analysis assessed the outcomes of 40 feet from 34 patients who underwent the modified Lapidus procedure with a medial plating system, aimed to evaluate immediate weightbearing outcomes on union rate, fixation-related complications, and functional outcomes. Among the 40 feet, findings showed a 95% (38/40) union rate within 6 months, with 2.5% (1/40) experiencing delayed union and 2.5% (1/40) facing fixation-related complications. There is a single case of malunion in the cohort. Additionally, statistically significant improvements were observed across all domains of the Manchester-Oxford Foot Questionnaire at p <.001. These findings suggest immediate weightbearing as a potential alternative to traditional nonweightbearing protocols. However, the study's retrospective nature and lack of a comparative group warrant cautious interpretation. Further research is essential to validate these findings and refine postoperative care protocols. By challenging conventional practices, this study underscores the complexity of optimizing patient outcomes in modified Lapidus procedure management. Tailored approaches and prospective investigations are imperative for establishing definitive guidelines and enhancing surgical techniques in this domain. [ABSTRACT FROM AUTHOR]

Ankle arthrodesis is an effective surgical intervention for end-stage arthritis or severe ankle joint deformity. Both internal (IF) and external fixation (EF) techniques are valid options, but there is controversy regarding the most effective technique. This study compares the safety and efficacy of EF and IF fixation techniques for ankle arthrodesis. A systematic review and meta-analysis was conducted according to the Preferred reporting items for systematic reviews and meta-analyses (PRISMA) Guidelines. A literature search of electronic databases, including MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials (CENTRAL), was performed to identify all studies directly comparing the two techniques. Both fixed and random effects models of analysis were used depending on heterogeneity. Odds of union in the EF and IF groups were comparable (OR = 0.60, CI 0.36-1.02, p =.06) however, EF was associated with greater odds of deep hardware infections (OR = 3.67, 1.97-6.83, p <.05) and amputations (OR = 3.17, CI 1.06-9.54, p =.04). Odds of revision surgery and superficial wound complications were similar between groups. EF techniques had significantly longer operation times (MD = 31.23, CI-25.11-37.34, p <.05) and intraoperative blood loss (MD = 44.1, CI 28.77-59.43, p <.05). No significant difference was noted in pain and functionality scores. IF and EF techniques have reasonable union rates with similar postoperative outcomes. [ABSTRACT FROM AUTHOR]

Background: Scaphoid excision and 4-bone fusion (4BF) is a surgical procedure to treat scapholunate advanced collapse. Some surgeons align the lunate over the capitates, whereas others leave the capitate in its uncovered native position. The capitolunate angle may affect long-term outcomes. This study examined whether postsurgical outcomes differed based on these differences in positioning. Methods: A retrospective analysis was performed for patients that underwent a 4BF between 2006 and 2020. Wrist range of motion; pain (0-10); and Disabilities of the Arm, Shoulder, and Hand (DASH) scores were recorded. The width of the capitate, the width of the lunate contacting the capitate, and the capitolunate angle were measured. Pearson correlations and t tests were performed. For t tests of capitolunate uncovering, patients were divided into 2 groups: patients with 0% capitate uncovering and patients with >0% uncovering. For capitolunate angle, the 2 groups were patients with a capitolunate angle of ≤10° and patients with a capitolunate angle of >10°. Results: There was a significant correlation between capitate coverage and wrist extension, but no correlation for flexion, pain, or DASH scores. Group 1 (0% uncovering) had increased wrist extension and decreased pain compared with group 2 (>0% uncovering). There were no significant correlations or differences in the analyses of capitolunate angle's impact on outcomes. Conclusions: In patients undergoing 4BF, those who had the lunate aligned to completely cover the capitate head had improved wrist extension and pain compared with patients where the capitate head was left partially uncovered. Capitolunate angle was not predictive of postsurgical outcomes. [ABSTRACT FROM AUTHOR]

Background: Scapho-lunate advanced collapse (SLAC) and scaphoid nonunion advanced collapse (SNAC) of the wrist are the most common types of wrist arthritis. We compared the union rate and complication profile of patients with SLAC and SNAC wrist undergoing 4 corner arthrodesis with partially threaded or fully threaded headless compression screws. Methods: A single-center retrospective review was conducted to identify all patients treated for SLAC and SNAC with 4 corner fusion using headless compression screws from 2016 to 2021. A total of 33 patients undergoing surgery on 35 wrists were identified and included in the study. Demographics, comorbidities, complication profile, and radiographs were collected and compared between groups. Results: One hundred percent (16/16) of partially threaded and 84.2% (16/19) of fully threaded screws demonstrated union by minimum 10-week follow-up. The total complication rate (avascular necrosis of lunate, screw loosening, etc.) was 31.4%; 52.6% of wrists implanted with fully threaded screws experienced complications compared with a 6.3% complication rate with partially threaded screws. The difference was statistically significant between the 2 groups (P =.004). Conclusions: Four corner arthrodesis using antegrade compression screws is an effective, reproducible method to achieve fusion in the wrist. The use of fully threaded screws was associated with more complications than with partially threaded screws, although union rate was not significantly different. Future studies with larger sample sizes would be useful to fully elucidate differences between these 2 constructs. [ABSTRACT FROM AUTHOR]

CREB gene family (ATF1, CREB1, CREM) fusions with either EWSR1 or FUS gene partners drive the pathogenesis of a wide range of neoplasms, including various soft tissue tumors, intracranial myxoid mesenchymal tumors (IMMTs), hyalinizing clear cell carcinoma (HCCC), and rare mesotheliomas. Recently, a SMARCA2::CREM fusion was reported in one case each of IMMT and HCCC. In this study, we expand the clinicopathologic and molecular spectrum of these neoplasms by describing three additional cases with SMARCA2::CREM and one with a novel SMARCA4::CREM fusion, highlighting the recurrent potential of additional CREB gene fusion partners beyond FET family members. To evaluate if these fusions define a new pathologic entity, we performed a comprehensive genomic and methylation analysis and compared the results to other related tumors. Tumors occurred in children and young adults (median age 20 years) and spanned a broad anatomic distribution, including soft tissue, intracranial, head and neck, and prostatic urethra. Microscopically, the tumors shared an undifferentiated round to epithelioid cell phenotype and a hyalinized fibrous stroma. Immunohistochemically, a polyphenotypic profile was observed, with variable expression of SOX10, desmin, and/or epithelial markers. No targetable genomic alterations were found using panel‐based DNA sequencing. By DNA methylation and transcriptomic analyses, tumors grouped closely to FET::CREB entities, but not with SMARCA4/SMARCB1‐deficient tumors. High expression of CREM by immunohistochemistry was also documented in these tumors. Patients experienced local recurrence (n = 2), locoregional lymph node metastases (n = 2), and an isolated visceral metastasis (n = 1). Overall, our study suggests that SMARCA2/4::CREM fusions define a distinct group of neoplasms with round cell to epithelioid histology, a variable immunoprofile, and a definite risk of malignancy. Larger studies are needed to further explore the pathogenetic relationship with the FET::CREB family of tumors. © 2024 The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) disorder is caused by the imbalance of inhibitory dopamine and excitatory acetylcholine neurotransmitters, which causes hindrance in locomotion. Freezing of gait (FOG), tremors, and bradykinesia are the most debilitating and disconcerting symptoms of Parkinson's Disease (PD). FOG episodes occur due to neurological control disorder and motorized impairments, which sternly hinder voluntary movement and forward locomotion. The computational intelligence techniques can effectively predict PD from the sensor data. To detect the FOG episodes often experienced by PD patients, this paper utilizes a 5G spectrum that operates at 4.8 GHz. The main idea of the proposed system is to extract the wireless channel characteristics information (containing amplitude variances) that can be integrated into a 5G communication system. This system collects data through wireless devices such as dipole antennas, network interface cards, and RF signal generators. Five human activities were performed: fast walking, slow walking, sitting on a chair, FOG episodes, and voluntary stopping. We proposed a novel deep dual self-attention and Bi-LSTM fusion architecture for PD prediction to train the collected dataset. Two architectures have been proposed, namely Deep Dual Attention Neural Network (D2ANN) and BiLSTM Neural Network (BNN), for the classification of PD using Chanel State Information (CSI) data. After that, the most prominent information is extracted using self-attention activation. A newly informed weighted fusion approach is proposed, and tree growth optimization is employed for the best feature selection. Finally, the selected features are classified using a multilayer full SoftMax neural network. The experimental process was conducted on FOG wireless sensor network data and obtained the highest accuracy of 98.66%. Compared to the results with state-of-the-art techniques, the proposed framework shows improved accuracy, recall, and precision rates. [ABSTRACT FROM AUTHOR]

Outer membrane vesicles (OMVs) are extracellular structures, ranging in size from 10 to 300 nm, produced by Gram-negative bacteria. They can be incorporated into the outer membrane of a recipient's cells, which may enable the transfer of substances with lytic properties. Due to the scarce information regarding the OMVs produced by Proteus mirabilis, the aim of this study was to test the blebbing abilities of the clinical P. mirabilis O77 and O78 strains and to determine the blebs' interactions with bacterial cells, including their possible bactericidal activities. The production of OMVs was visualised by Transmission electron microscopy (TEM). The presence of OMVs in the obtained samples as well as the phenomenon of OMV fusion to recipient cells were confirmed by Enzyme-Linked ImmunoSorbent Assay (ELISA) and Western blotting assays. The bacteriolytic activity of the OMVs was examined against P. mirabilis clinical strains and reference Staphylococcus aureus and Escherichia coli strains. It was shown that each of the two tested P. mirabilis strains could produce OMVs which were able to fuse into the cells of the other strain. The lytic properties of the O78 OMVs against another P. mirabilis O78 strain were also demonstrated. This promising result may help in the future to better understand the mechanisms of the pathogenesis and to treat the infections caused by P. mirabilis. [ABSTRACT FROM AUTHOR]

With the acceleration of global population aging, the elderly have an increasing demand for home care and nursing institutions, and the significance of health prevention and management of the elderly has become increasingly prominent. In this context, we propose a biometric recognition method for multi-modal biomedical signals. This article focuses on three key signals that can be picked up by wearable devices: ECG, PPG, and breath (RESP). The RESP signal is introduced into the existing two-mode signal identification for multi-mode identification. Firstly, the features of the signal in the time–frequency domain are extracted. To represent deep features in a low-dimensional feature space and expedite authentication tasks, PCA and LDA are employed for dimensionality reduction. MCCA is used for feature fusion, and SVM is used for identification. The accuracy and performance of the system were evaluated using both public data sets and self-collected data sets, with an accuracy of more than 99.5%. The experimental data fully show that this method significantly improves the accuracy of identity recognition. In the future, combined with the signal monitoring function of wearable devices, it can quickly identify individual elderly people with abnormal conditions, provide safer and more efficient medical services for the elderly, and relieve the pressure on medical resources. [ABSTRACT FROM AUTHOR]

Multimodal sentiment analysis models can determine users' sentiments by utilizing rich information from various sources (e.g., textual, visual, and audio). However, there are two key challenges when deploying the model in real-world environments: (1) the limitations of relying on the performance of automatic speech recognition (ASR) models can lead to errors in recognizing sentiment words, which may mislead the sentiment analysis of the textual modality, and (2) variations in information density across modalities complicate the development of a high-quality fusion framework. To address these challenges, this paper proposes a novel Multimodal Sentiment Word Optimization Module and a heterogeneous hierarchical fusion (MSWOHHF) framework. Specifically, the proposed Multimodal Sentiment Word Optimization Module optimizes the sentiment words extracted from the textual modality by the ASR model, thereby reducing sentiment word recognition errors. In the multimodal fusion phase, a heterogeneous hierarchical fusion network architecture is introduced, which first utilizes a Transformer Aggregation Module to fuse the visual and audio modalities, enhancing the high-level semantic features of each modality. A Cross-Attention Fusion Module then integrates the textual modality with the audiovisual fusion. Next, a Feature-Based Attention Fusion Module is proposed that enables fusion by dynamically tuning the weights of both the combined and unimodal representations. It then predicts sentiment polarity using a nonlinear neural network. Finally, the experimental results on the MOSI-SpeechBrain, MOSI-IBM, and MOSI-iFlytek datasets show that the MSWOHHF outperforms several baselines, demonstrating better performance. [ABSTRACT FROM AUTHOR]

Successful upscaling of tungsten fiber‐reinforced tungsten composites (Wf/W) on industrial level could represent an important milestone for future nuclear fusion reactors. The primary objective of these materials is to enhance the durability and operational lifespans of critical components. Developing mature manufacturing approaches remains a challenge, highlighting the need for innovative solutions. This study evaluates the feasibility of merging chemical vapor deposition (CVD) with spark plasma sintering (SPS) for producing such composites. This analysis indicates that combining CVD‐W sealed tungsten fabrics with SPS requires additional manufacturing steps or the utilization of tungsten powders for effective sintering. The process is currently only suitable for simple textile structures utilizing single filaments, mitigating one of the main advantages of CVD. Configurations such as radially braided yarns are currently less compatible to the high stress levels during SPS. A key outcome of this work is the introduction of a thin secondary CVD‐W interface into the composite design, substantially improving the stability of the yttria‐interface and effectively shielding the W‐fibers from potential matrix interactions. This innovation reduces issues such as carbon embrittlement and allows the potential integration of tungsten fibers into different matrix materials such as ceramics, broadening the potential application range of tungsten fiber‐reinforcements. [ABSTRACT FROM AUTHOR]

The Spherical Tokamak for Energy Production (STEP) programme hypothesizes that a compact machine offers a route to reduced capital cost that directly tackles the barrier to entry of this potentially transformative technology. History has shown that with an unsolved, complex and highly interdependent design challenge, there is a need to balance exploration of the problem with progress. Almost all complex systems arise from the evolutionary improvement of simpler systems which is an approach the programme has adopted by working through a virtual natural selection of design families towards a single concept consistent with the initiating hypothesis. Issues are uncovered and solved more rapidly this way because the effort is focused on an end. In this current phase, STEP has had to be an agile fast-moving programme to work with what emerges as well as what was planned, to sit with uncertainty and to embrace self-organizing principles. The complex decision-making and compromises in emerging trades have led to a concept respectful of the tight aspect ratio hypothesis which carefully balances cost, performance and deliverability. It remains a high-risk and high-reward programme, but the character of the challenge is better understood building confidence and enhancing capability to advance the evolving design further. This article is part of the theme issue 'Delivering Fusion Energy – The Spherical Tokamak for Energy Production (STEP)'. [ABSTRACT FROM AUTHOR]

The Spherical Tokamak for Energy Production (STEP) prototype powerplant (SPP) will be a first-of-a-kind powerplant—its prime objective is to export electrical power, to the national power transmission system ('grid'), above 100 MWe. As part of a wider issue, addressing the STEP concept design, this article seeks to explore how electrical power will be generated from a spherical tokamak heat source. Accordingly, the following key functions of the SPP power infrastructure are reviewed. Cooling the tokamak: cooling the tokamak while extracting useful thermal energy. Generating power: conversion of thermal energy to electrical energy (power generation). Managing energy: management of the site-wide distribution, storage and energy export. In each of these areas, the design scope, challenges and solution spaces have been discussed. This has shaped the design of the SPP power infrastructure, which in turn has ensured a powerplant design focused on operability and performance. Furthermore, it has been demonstrated that the SPP will achieve its prime objective in generating net power, which is enabled by a unique power infrastructure. Confidence in the ability to generate net power will be refined as the design matures. Finally, this article recommends key opportunities that STEP could use to improve power generation and reduce the parasitic load of the SPP. This article is part of the theme issue 'Delivering Fusion Energy – The Spherical Tokamak for Energy Production (STEP)'. [ABSTRACT FROM AUTHOR]

Following the Goldilocks principle, mitochondria size must be "just right." Mitochondria balance division and fusion to avoid becoming too big or too small. Defects in this balance produce dysfunctional mitochondria in human diseases. Mitochondrial safeguard (MitoSafe) is a defense mechanism that protects mitochondria against extreme enlarging by suppressing fusion in mammalian cells. In MitoSafe, hyperfused mitochondria elicit flickering—short pulses of mitochondrial depolarization. Flickering activates an inner membrane protease, Oma1, which in turn proteolytically inactivates a mitochondrial fusion protein, Opa1. The mechanisms underlying flickering are unknown. Using a live-imaging screen, we identified Slc25a3 (a mitochondrial carrier transporting phosphate and copper) as necessary for flickering and Opa1 cleavage. Remarkably, copper, but not phosphate, is critical for flickering. Furthermore, we found that two copper-containing mitochondrial enzymes, superoxide dismutase 1 and cytochrome c oxidase, regulate flickering. Our data identify an unforeseen mechanism linking copper, redox homeostasis, and membrane flickering in mitochondrial defense against deleterious fusion. [Display omitted] • Flickering prevents harmful extreme mitochondrial fusion by inducing Opa1 cleavage • Mitochondrial copper, transported by Slc25a3, regulates flickering • Copper-containing SOD1 suppresses flickering • Copper-containing cytochrome c oxidase promotes flickering Murata et al. report that mitochondrial copper, transported by Slc25a3, regulates the balance between mitochondrial fusion and division by suppressing fusion when mitochondria become hyperfused. This function of copper is mediated by two copper-containing enzymes: superoxide dismutase 1 and cytochrome c oxidase. [ABSTRACT FROM AUTHOR]

Cranial suture closure has long been understood as an indicator of human development and is closely associated with the aging process. Due to this correlation, it has been widely used in forensic and archaeological contexts to estimate the age of unidentified or skeletonized individuals. Several cadaverbased studies have demonstrated the usefulness of the lambdoid suture in age estimation; however, it is not a technique that is commonly applied in routine forensic practice. Age estimation plays a crucial role in developing the biological profile that forensic anthropologists use to help identify unknown deceased individuals. This study aims to examine the pattern of cranial vault suture closure and its relationship to age, thereby contributing to more accurate age determination in forensic investigations. [ABSTRACT FROM AUTHOR]

To compare the 2-year reoperation rates for adjacent segment disease between patients with pelvic incidence–lumbar lordosis (PI-LL) mismatch postoperatively and patients with normal PI-LL measurements. Patients undergoing elective 1- to 2-level lumbar fusion for degenerative conditions between 2016 and 2018 were retrospectively reviewed. Spinopelvic radiographic parameters immediately postoperation were measured, and PI-LL mismatch was determined using the age-adjusted thresholds defined in Lafage et al. After propensity score matching, early reoperation rates were compared between the PI-LL mismatch and normal PI-LL cohorts. Early reoperation was defined as symptomatic adjacent segment disease (ASD) requiring reoperation within 2 years of the index surgery. A total of 219 patients were identified. The average age was 59 years of age, with 59.8% female. The PI-LL mismatch cohort (n = 148) was younger (57.5 vs. 63.5 years, P < 0.001) and had a higher proportion of Black patients (31.8% vs. 11.3%, P = 0.001) than the normal PI-LL cohort, respectively. A total of 100 patients in the PI-LL mismatch cohort were propensity score matched to 66 patients in the normal PI-LL cohort, resulting in no difference in age (P = 0.177), sex (P = 0.302), race (P = 0.727), or body mass index (P = 0.892). Using these matched cohorts, the rate of early reoperation for ASD was 8.0% in the PI-LL mismatch cohort and 9.1% in the normal PI-LL cohort (P = 0.805), with a mean time to reoperation of 1.28 and 1.33 years, respectively. After propensity score matching, PI-LL mismatch was not associated with early reoperation for ASD in patients undergoing 1- to 2-level lumbar fusions for degenerative conditions. [ABSTRACT FROM AUTHOR]

Purpose: To compare the outcomes of decompression alone and fusion for L4-5 DLS in different age cohorts (< 70 years, ≥ 70 years). Methods: This retrospective cohort study included patients who underwent minimally invasive decompression or fusion for L4-5 DLS and had a minimum of 1-year follow-up. Outcome measures were: (1) patient-reported outcome measures (PROMs) (Oswestry Disability Index, ODI; Visual Analog Scale back and leg, VAS; 12-Item Short Form Survey Physical Component Score, SF-12 PCS), (2) minimal clinically important difference (MCID), (3) patient acceptable symptom state (PASS), (4) response on the global rating change (GRC) scale, and (5) complication rates. The decompression and fusion groups were compared for outcomes separately in the < 70-year and ≥ 70-year age cohorts. Results: 233 patients were included, out of which 52% were < 70 years. Patients < 70 years showed non-significant improvement in SF-12 PCS and significantly lower MCID achievement rates for VAS back after decompression compared to fusion. Analysis of the ≥ 70-year age cohort showed no significant differences between the decompression and fusion groups in the improvement in PROMs, MCID/PASS achievement rates, and responses on GRC. Patients ≥ 70 years undergoing fusion had significantly higher in-hospital complication rates. When analyzed irrespective of the surgery type, both < 70-year and ≥ 70-year age cohorts showed significant improvement in PROMs with no significant difference. Conclusions: Patients < 70 years undergoing decompression alone did not show significant improvement in physical function and had significantly less MCID achievement rate for back pain compared to fusion. Patients ≥ 70 years showed no difference in outcomes between decompression alone and fusion. [ABSTRACT FROM AUTHOR]

Background: Receptor tyrosine kinase (RTK) fusions of RET, NTRK1/3, and ALK are enriched among pediatric thyroid cancer patients with metastatic and persistent disease, and their oncoproteins represent attractive drug targets. Methods: We performed RNA-sequencing in a papillary thyroid cancer (PTC) lacking other frequent driver alterations. Results: We report a novel RTK fusion, TG-insulin-like growth factor 1 receptor gene (IGF1R), in a 17-year-old female patient with angioinvasive follicular variant PTC. The in-frame fusion protein preserves the cholinesterase‐like domain of TG with dimerization properties and the transmembrane and kinase domain of IGF1R. The tumor sample shows increased IGF1R mRNA expression and tyrosine kinase phosphorylation, augmentation of Mitogen activated protein kinase (MAPK) transcriptional output genes, and decreased NIS levels. Conclusions: We reveal a novel targetable kinase fusion oncogene in thyroid cancer which is not incorporated in different thyroid-specific sequencing panels. The integration of IGF1R fusion screening in the next versions of thyroid-specific targeted next-generation sequencing panels may be beneficial to thyroid cancer patients. [ABSTRACT FROM AUTHOR]

Background: The rearranged during transfection (RET) proto-oncogene fusion is common in papillary thyroid cancer (PTC), varying across ethnic groups. However, comprehensive comparisons of RET fusion types are limited. This study aims to identify predominant RET fusions and analyze their clinicopathological characteristics in a cohort of Chinese thyroid cancer cases. Methods: This single-center retrospective cohort study analyzed thyroid cancer data, utilizing next-generation sequencing on formalin-fixed, paraffin-embedded tissue samples. Detailed clinicopathological data of thyroid cancer cases with RET fusions were collected. Results: Among 2300 thyroid cancer cases, RET fusions were exclusively found in PTC or differentiated high-grade thyroid carcinoma (DHGTC) cases (2234 cases), absent in other types (66 cases). Of the 2234 PTC or DHGTC cases, 113 (5.06%) exhibited RET fusions, including 100 primary cases. Coiled-coil domain containing 6 (CCDC6)-RET fusions predominated (78.0%, 78/100), with nuclear receptor coactivator 4 (NCOA4)-RET fusions representing 22.0% (22/100). NCOA4-RET fusions were more prevalent in patients aged 45 years and older (54.5% vs. 28.2%, p = 0.021) and DHGTC cases (p < 0.05) and associated with higher rates of lymph node metastases (90.9% vs. 67.9%, p = 0.032). CCDC6-RET fusion exhibited a higher prevalence of Hashimoto's thyroiditis (HT) (67.9% vs. 22.7%, p < 0.001) and elevated thyroglobulin antibody levels (14.11 [1.86–174.32] IU/mL vs. 2.01 [1.14–15.41] IU/mL, p = 0.018). Moreover, CCDC6-RET fusion predominantly occurred in classical PTC (56.4%, 44/78) and infiltrative follicular PTC (17.9%, 14/78), whereas NCOA4-RET fusion was more frequent in classical PTC (36.4%, 8/22), solid PTC (27.3%, 6/22), and DHGTC (27.3%, 6/22). RET fusions with compound mutations were associated with older age (≥45 years) and bilateral thyroid involvement. Follow-up data showed a higher recurrence rate in the RET fusion group compared with the BRAFV600E mutation group (5.0% vs. 0.0%, p = 0.018). Although the NCOA4-RET group showed a numerically higher recurrence rate compared with CCDC6-RET (9.1% vs. 3.8%), this difference was not statistically significant (p = 0.559). Conclusions:RET fusions are specific to PTC or DHGTC cases among Chinese thyroid cancer cases. CCDC6-RET and NCOA4-RET fusions exhibited distinct clinicopathological features, with NCOA4-RET being more aggressive. [ABSTRACT FROM AUTHOR]

We describe a 13-year-old boy with piso-hamate coalition confirmed by X-ray. Computed tomography (CT) and magnetic resonance imaging (MRI) revealed type 1 coalition according to the classification of DeVilliers Minnaar. Piso-hamate coalition is rare, and suspicions should be raised in instances of chronic ulnar-sided wrist pain, particularly in individuals with a history of elevated hand usage, especially amongst athletes engaging in intensive hand grip activities. Surgical resection of the synchondrosis site between the pisiform and the hamate is an efficacious intervention that can mitigate pain. Level of Evidence: Level V (Therapeutic) [ABSTRACT FROM AUTHOR]

The Transformer has become pivotal for the integrated analysis of multi-source remote-sensing (RS) data in Earth observation, particularly in applications such as the fusion classification of hyperspectral images (HSI) and Light Detection and Ranging (LiDAR) data. However, Transformers are often employed as effective feature extractors by adopting similar processing blocks for different modalities from multi-source sensors, overlooking differences in imaging principles and data characteristics. Moreover, in the feature extraction process across different sensor data, there is a lack of necessary cross-modal information interaction, leading to insufficient utilization of complementary information between different sensors and resulting in suboptimal fusion outcomes. In this paper, we propose an interactive Transformer and CNN network for the fusion classification of HSI and LiDAR data. Specifically, a heterogeneous three-branch network architecture is designed for HSI and LiDAR data, where Transformers and CNNs encapsulate global contextual spatial and spectral information for HSI and capture geometric elevation patterns for LiDAR data, respectively. Elevation-Spatial Interaction (ESI) and Spectral-Spatial Interaction (SSI) modules are then introduced for multi-stage feature interaction. ESI enables the CNN-Transformer network to focus on essential local elevation details while simultaneously modelling global contextual spatial information. SSI facilitates the Transformer-Transformer network to cyclically intertwine spectral and spatial information for long-range spectral-spatial feature fusion. Finally, the interacted elevation, spatial, and spectral features undergo the Gated Fusion module to achieve hierarchical fusion adaptively, resulting in an elevation-spatial-spectral representation. Experiments conducted on three benchmark HSI-LiDAR datasets demonstrate the effectiveness of our proposed approach. [ABSTRACT FROM AUTHOR]

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Tungsten (W) and tungsten alloys are being considered as leading candidates for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for the design of magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield, and low long-term disposal radioactive footprint. Despite these relevant features, there is a lack of understanding of how the structural and mechanical properties of W-based alloys are affected by the temperature in fusion power plants. In this work, we present a study on the thermo-mechanical properties of five W-based plasma-facing materials. First-principles density functional theory (DFT) calculations are combined with the quasi-harmonic approximation (QHA) theory to investigate the electronic, structural, mechanical, and thermal properties of these W-based alloys as a function of temperature. The coefficient of thermal expansion, temperature-dependent elastic constants, and several elastic parameters, including bulk and Young's modulus, are calculated. Our work advances the understanding of the structural and thermo-mechanical behavior of W-based materials, thus providing insights into the design and selection of candidate plasma-facing materials in fusion energy devices. [ABSTRACT FROM AUTHOR]

In radar signal processing, the pursuit of precise prediction algorithms motivates the exploration of innovative methodologies. This study introduces a pioneering fusion of learning vector quantization (LVQ)- Kalman, merging LVQ with the advanced Kalman filter. The primary aim is to enhance adaptability and robustness, vital in weather monitoring and military surveillance. LVQ, known for its efficacy in pattern recognition and prediction, adjusts prototype vectors iteratively based on input data, ideal for radar signal intricacies. Various LVQ types are incorporated, tailored meticulously for specific radar applications. The Kalman filter, originally for aerospace, excels in tracking and predicting dynamic systems, seamlessly integrated to address uncertainties in radar data. By combining LVQ's pattern recognition with the Kalman filter's adaptability, the fusion aims to create a versatile system navigating radar data intricacies. Applications range from airborne target tracking to weather analysis and military surveillance. The integrated approach offers adaptability and robustness, vital for realworld implementations, particularly in tsunami detection. Future research may explore deep learning to further enhance adaptability. This fusion technique presents significant potential for advancing radar signal processing, promising accurate and adaptive systems, especially in critical applications like tsunami detection. [ABSTRACT FROM AUTHOR]

In social learning the way in which agents represent their beliefs motivates and constrains both how they learn individually from the environment and socially from one another. Assuming that agents can only hold beliefs drawn from a finite set of possible belief states, in this paper we investigate the effect that varying the number of those belief states has on the efficacy of social learning. To this end we propose an evidence tokens model for social learning, in which agents transfer tokens between competing hypotheses on the basis both of evidence that they receive directly and of information received from their peers. Using agent-based simulations and difference equations we show that this model is effective in social learning for boundedly rational agents and scales well to the case where there are multiple hypotheses under consideration. We show that varying the number of belief states (as determined by the number of evidence tokens available) has a clear effect both on accuracy and on the time taken for the agent population to reach agreement about which hypothesis is true, so that the optimal belief granularity in social learning is strongly influenced by macro properties of the whole population governing the way that agents interact with each other and the environment. [ABSTRACT FROM AUTHOR]

Breast cancer is a leading cause of female mortality and despite advancements in personalized therapeutics, metastatic disease largely remains incurable due to drug resistance. The estrogen receptor (ER, ESR1) is expressed in two-thirds of all breast cancer, and under endocrine stress, somatic ESR1 mutations arise in approximately 30% of cases that result in endocrine resistance. We and others reported ESR1 fusions as a mechanism of ER-mediated endocrine resistance. ER fusions, which retain the activation function 1- and DNA-binding domains, harbor ESR1 exons 1 to 6 fused to an in-frame gene partner resulting in loss of the ER ligand-binding domain (LBD). We demonstrate that in a no-special type (invasive ductal carcinoma [IDC]-NST) and an invasive lobular carcinoma (ILC) cell line, ER fusions exhibit robust hyperactivation of canonical ER signaling pathways independent of estradiol or antiendocrine therapies. We employ cell line models stably overexpressing ER fusions with concurrent endogenous ER knockdown to minimize endogenous ER influence. Cell lines exhibited shared transcriptomic enrichment in pathways known to be drivers of metastatic disease, notably MYC signaling. Cells expressing the 3′ fusion partners SOX9 and YAP1 consistently demonstrated enhanced growth and cell survival. ILC cells expressing the DAB2 fusion led to enhanced growth, survival, and migration, phenotypes not appreciated in the IDC-NST DAB2 model. Herein, we report that cell line activity is subtype-, fusion-, and assay-specific, suggesting that LBD loss, the fusion partner, and the cellular landscape all influence fusion activities. Therefore, it will be critical to assess fusion frequency in the context of the clinicopathology. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is classified as a neurological, progressive illness brought on by cell death in the posterior midbrain. Early PD detection will assist doctors in reducing the disease's consequences. A collection of skilled models that may be applied to regression as well as classification is known as artificial intelligence (AI). PD can be detected using a variety of dataset formats, including text, speech, and picture datasets. For the purpose of classifying Parkinson's disease, this study suggests merging deep with machine learning recognition approaches. The three primary components of the suggested approach are designed to enhance the accuracy of Parkinson's disease early diagnosis. These sections cover the topics of categorising, combining, and separating. Convolutional Neural Networks (CNN) as well as attention procedures are used to create feature extractors. The related motion signals are fed to a combination of convolutional neural network and long-short-memory model for feature extraction. Besides, for the classification of patients from non-suffers of Parkinson's disease, Random Forest, Logistic Regression, Support Vector Machine, Extreme Boot Classifier, and voting classifier were used. Our result shows that for the PD handwriting and related motion datasets, using the proposed CNN with an attention and voting classifier yields 99.95% accuracy, 99.99% precision, 99.98% sensitivity, and 99.95% F1-score. Based on these results, it is warranted to conclude that the proposed methodology of feature extraction from photos of handwriting and relating motor symptoms, fusing of those features, and following it with a voting classifier yields excellent results for PD classification. [ABSTRACT FROM AUTHOR]

Three-body bound, virtual and resonant states in the dtμ− and ddμ− systems were found by solving homogeneous Faddeev equations on the real and complex energy planes. The formalism of searching is conducted for the scattering matrix poles on both physical and nonphysical energy sheets with an analytical continuation of the corresponding Lippmann–Schwinger equations for t-matrix. Some benchmark tests have been done with model and realistic two-body potentials to verify the analytical continuation procedure. Direct calculations revealed five resonant states in the dtμ− and ddμ− systems, as well as two virtual states in the dtμ− system in the strong coupling mode. The key influence of short-range dt and dd interactions was found on the appearance of dtμ− and ddμ− bound states in the energy range of 1–20keV, which disappeared when such interactions were turned off. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate biopsy-related complications and detection rates of any PCa and clinically significant PCa (csPCa, intended as grade group ≥ 2) between MRI-targeted TP fusion biopsies (TPBx) and TR ones (TRBx). Methods: We performed a multicentric study on 4841 patients who underwent fusion biopsy between 2016 and 2023. A case–control matching was performed to find comparable cohorts of 646 TPBx and 646 TRBx. Mean T test and Pearson chi-square tests were used to compare continuous and categorical variables. Results: Baseline characteristics were comparable between the cohorts, except for target location with a higher rate of anterior lesions in TPBx group. Complications were rare and no difference was found between the groups, with similar rates of infections after TRBx and TPBx (N = 5 (0.8%) vs N = 2 (0.3%), p 0.45). All patients in TRBx and 90.1% in TPBx group received antibiotic prophylaxis. A higher csPCa detection rate was found in TPBx over the group (50.5% vs 36.2%, p < 0.001). On average, positive targeted cores were increased in TPBx group, for any PCa (1.6 vs 1.4, p 0.04) and csPCa (1.0 vs 0.8, p 0.02). Among the limitations of study, we acknowledge the retrospective design and the possible under-reporting of complications. Conclusions: MRI-targeted fusion TPBx achieves a significantly higher csPCa detection than TRBx, with a diagnostic advantage for apical and anterior lesions. No significant differences were found in terms of complications that were rare in both groups, considering a widespread adoption of antibiotic prophylaxis. [ABSTRACT FROM AUTHOR]

Nitrogen is a key nutrient for crop growth. Excessive or insufficient nitrogen affects crop growth, yield, and quality. Additionally, excessive nitrogen fertilizer can cause soil and water pollution. Applying panicle fertilizer during the late jointing stage can promote rice panicle growth. Therefore, accurately and timely monitoring of nitrogen status in rice fields during the late jointing stage and timely optimizing fertilization strategies is crucial for ensuring rice yield and environmental protection. This paper integrates multimodal data from unmanned aerial vehicle (UAV) remote sensing and ground observations to construct inversion models for leaf nitrogen content (LNC) and plant nitrogen content (PNC) of rice at the late jointing stage. The research was conducted at the Shapu Experimental Base of the Agricultural Science Research Institute in Zhaoqing City, Guangdong Province, with two field experiments carried out during the late rice seasons of 2021 and 2022. Each of Experiment 1 (2021) and Experiment 2 (2022) included 30 experimental plots, designed with 5 nitrogen fertilizer gradients, 2 planting densities, and 3 replications. Phosphorus and potassium fertilizers were applied uniformly across all plots. UAVs equipped with multispectral and RGB cameras were used to acquire remote sensing images of rice canopies during the late jointing stage. Vegetation indices (VIs) and texture feature values (TFVs) were extracted from the multispectral images, with TFVs derived using the gray level co-occurrence matrix (GLCM) method. Texture indices (TIs) were then constructed by combining TFVs. RGB images were used to generate digital surface models (DSM) for bare ground (pre-transplant) and rice fields (late jointing stage). These DSMs, combined with ground reference methods, were used to construct crop surface models (CSM) to derive estimated canopy heights (ECH) for each plot. Manually collected data included measured canopy height (MCH) and field nitrogen management data (FN) used as ground observations. For each experimental plot, three representative rice plants were selected as samples. After removing the roots, the leaves and stems were separated and dried at 85℃ to a constant weight, which was recorded as the aboveground biomass of the leaves and stems. The true values of leaf nitrogen content and stem nitrogen content were obtained using the Kjeldahl method. Combining these values with the dry weight data, the true values of plant nitrogen content were calculated. The maximal information coefficient (MIC) was used as an evaluation metric for feature assessment and selection. Random forest regression algorithms were employed to construct inversion models for rice LNC and PNC, respectively, using the coefficient of determination (R2), root mean squared error (RMSE), and mean absolute error (MAE) as model evaluation metrics. The analysis and experimental results indicate: TIs constructed using combinations of TFVs significantly enhanced the correlation between texture information and LNC and PNC. When the UAV flight height was 100 m, the Ratio Texture Index constructed using a 9×9 sliding window size in the GLCM method showed the best performance, improving the MIC value by 11.48% compared to the best TFV. For conventional machine-transplanted rice planting density, the correlation between TIs and LNC and PNC was best when the GLCM sliding window size was set to 9×9 or 11×11 at a UAV flight height of 100 m. The ECH derived from the CSM showed a high correlation with the manual MCH in the field. Including canopy height (MCH or ECH) as an input feature in the random forest regression model significantly improved the inversion accuracy of rice nitrogen content. The ECH extracted from the CSM showed high estimation accuracy (R² = 0.77, RMSE = 3.4 cm, MAE = 2.8 cm). The inclusion of canopy height (MCH or ECH) in the model construction improved the inversion accuracy for PNC more significantly compared to LNC. Integrating UAV remote sensing and ground observation multimodal data, the random forest regression algorithm significantly improved the inversion accuracy of rice LNC and PNC at the late jointing stage. Considering both inversion accuracy and operational convenience, it is recommended to use a feature combination of VI+TI+ECH+FN in field production. Compared to using VI alone, this feature combination improved R² by 6.73%, and reduced RMSE and MAE by 13.62% and 14.68%, respectively, for LNC inversion. For PNC inversion, R2 was improved by 12.53%, and RMSE and MAE were reduced by 22.09% and 19.80%, respectively. The results demonstrate that constructing random forest regression models by integrating UAV remote sensing and ground observation multimodal data can accurately detect rice LNC and PNC, providing a scientific basis for rice field management and fertilization decision-making. [ABSTRACT FROM AUTHOR]

An accurate estimation of evapotranspiration (ET) is critical to understanding the water cycle in watersheds and promoting the sustainable utilization of water resources. Although there are various ET products in the Yellow River Basin, various ET products have many uncertainties due to input data, parameterization schemes, and scale conversion, resulting in significant uncertainties in regional ET data products. To reduce the uncertainty of a single product and obtain more accurate ET data, more accurate ET data can be obtained by fusing different ET data. Addressing this challenge, by calculating the uncertainty of three ET data products, namely global land surface satellite (GLASS) ET, Penman–Monteith–Leuning (PML)-V2 ET, and reliability-affordable averaging (REA) ET, the weight of each product is obtained to drive the Bayesian three-cornered Hat (BTCH) algorithm to obtain higher quality fused ET data, which are then validated at the site and basin scales, and the accuracy has significantly improved compared to a single input product. On a daily scale, the fused data's root mean square error (RMSE) is 0.78 mm/day and 1.14 mm/day. The mean absolute error (MAE) is 0.53 mm/day and 0.84 mm/day, respectively, which has a lower RMSE and MAE than the model input data; the correlation coefficients (R) are 0.9 and 0.83, respectively. At the basin scale, the RMSE and MAE of the annual average ET of the fused data are 11.77 mm/year and 14.95 mm/year, respectively, and the correlation coefficient is 0.84. The results show that the BTCH ET fusion data are better than single-input product data. An analysis of the fused ET data on a spatiotemporal scale shows that from 2001 to 2017, the ET increased in 85.64% of the area of the Yellow River Basin. Fluctuations in ET were greater in the middle reaches of the Yellow River than in the upstream and downstream regions. The BTCH algorithm has indispensable reference value for regional ET estimation research, and the ET data after BTCH algorithm fusion have higher data quality than the original input data. The fused ET data can inform the development of management strategies for water resources in the YRB and provide a deeper understanding of the regional water supply and demand balance mechanism. [ABSTRACT FROM AUTHOR]