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Reconstructing flexible pathways of Aurignacian blade and bladelet production at Vogelherd
The beginning of the Upper Paleolithic represents a key period in human history. At this time, we can grasp the technological concepts that Homo sapiens used in the early Upper Paleolithic. The age of the Aurignacian in combination with the three-dimensional ivory artworks, musical instruments and personal ornaments in the Swabian Jura sites emphasize the importance of this region for understanding and defining the Upper Paleolithic. During that time blade and bladelet production became the central interest of lithic production. The study of these lithic reduction sequences is essential for understanding technological inventions and socio-economic behaviors of early anatomically modern humans in Central Europe. So far, however, the lithic technology from the Aurignacian of the Swabian Jura has only been studied in detail at the site of Geißenklösterle. In this paper, we provide an exhaustive study based on the rich lithic assemblage from Vogelherd Cave combining both the chaîne opératoire approach and attribute analysis. This work highlights the importance of carefully sorting minimal raw material units and engaging in systematic refitting. These observations allow us to reconstruct entire reduction sequences including the biographies of both cores and tools. The source and physical characteristics of lithic raw materials greatly influenced decision-making during the reduction process. As in many other Paleolithic contexts, Aurignacian knappers thoroughly exploited imported raw materials while exhausting low quality local material to a lesser degree. Comparisons with other assemblages from the region help to facilitate the characterization of the Swabian Aurignacian. This comparison allows us to separate regional adaptations from more site-specific behaviors.
Female membrane proteins regulate postmating ovulation in <i>Drosophila melanogaster</i> by ovulin-dependent and -independent pathways
Ovulation is an intricate process that is essential for reproductive success. In Drosophila melanogaster , ovulation increases after mating. This increase is initiated by the male seminal fluid protein ovulin and is executed by female pathways, including octopamine (OA) neuronal signaling. Despite OA signaling’s central role in ovulation regulation, the broader molecular landscape underlying female control of ovulation remains poorly understood. Here, using ovulin as a probe, we performed evolutionary rate covariation and AlphaFold-Multimer prediction screens to identify candidate female ovulation-regulating proteins. Ovulation assays performed on knockdowns or mutants of identified membrane-protein candidates revealed seven important female ovulation regulators: Lgr3, GabaβR1, SIFaR, mthl9, Smog, Cirl, and CG6067. Lgr3 and GabaβR1 function in an ovulin-dependent manner, while SIFaR and mthl9 regulate ovulation independently of ovulin. For proteins with known nervous system expression, we examined their requirement in OA neurons and their expression in female reproductive tract neurons. Tissue-specific knockdown revealed that Lgr3, GabaβR1, SIFaR, and CG6067 act in OA neurons to influence ovulation, highlighting OA neurons as a key signaling hub. Additionally, Lgr3, GabaβR1, SIFaR, Smog, and Cirl are expressed in OA neurons innervating the reproductive tract, suggesting a potential local function. Finally, we identified evidence of recurrent positive selection having acted on residues within Smog’s ligand binding region, which is interesting in light of ovulin’s rapid evolution. Together, these findings significantly expand our understanding of the molecular networks regulating ovulation following mating in Drosophila .
Overcoming barriers to NHS adoption of innovative IPC products: A qualitative study of SMEs in the Liverpool city region
Healthcare-associated infections (HAIs) result in prolonged hospital stays and an increased incidence of infections caused by antimicrobial-resistant bacteria. Small and Medium Enterprises (SMEs) play a crucial role in developing innovative Infection Prevention and Control (IPC) solutions, but they face substantial challenges in navigating the complex NHS procurement system. This study, carried out in the Liverpool City Region in 2022, investigated these barriers. The methodology involved qualitative data collection through an online survey and five semi-structured interviews with SMEs involved in IPC innovation. The survey targeted 114 SMEs, and the interviews were conducted remotely with management teams. Data were analysed thematically using NVivo software, allowing for the identification of key barriers and recurring themes across the dataset. Key challenges identified included high market-entry costs, navigating complex regulatory and procurement frameworks, and limited access to key NHS stakeholders. These issues were compounded by fragmented decision-making processes within NHS Trusts, making it difficult for SMEs to secure product adoption. Despite these barriers, SMEs remain committed to innovating IPC solutions, driven by the potential to improve patient care and address antimicrobial resistance. This report recommends streamlining support mechanisms for SMEs, improving access to NHS decision-makers, and advocating for policy reforms to simplify the procurement process. By facilitating collaboration between SMEs, the NHS, and other stakeholders, the adoption of innovative IPC products can be accelerated, ultimately benefiting patients and addressing the significant public health threats posed by HAIs and antimicrobial resistance.
Microglia contribute to bipolar depression through Serinc2-dependent phospholipid synthesis
Although clinical research has revealed microglia-related inflammatory and immune responses in bipolar disorder (BD) patient brains, it remains unclear how microglia contribute to the pathogenesis of BD. Here, we demonstrated that Serinc2 is associated with susceptibility to BD and showed a reduced expression in BDII patient plasma, which correlated with the disease severity. Using induced pluripotent stem cell (iPSC) models of sporadic and familial BDII patients, we found that Serinc2 expression showed deficits in iPSC-derived microglia-like cells, resulting in decreased synaptic pruning. Further, combining the microglia-specific Serinc2-deficient mouse and iPSC-microglia models, we found that microglial Serinc2 deficits functioned through attenuating the synthesis of serine-related phospholipids in the plasma membrane, thus resulting in depression-like behavioral abnormalities in the animals. Finally, we showed that the Serinc2-dependent lipid deficits diminished microglial membrane CR3 formation to interrupted synaptic pruning signals from neurons. Therefore, our results indicated that Serinc2 deficits in microglia might contribute to the pathogenesis of BD.
A phosphoramidate modification of FUDR, NUC-3373, causes DNA damage and DAMPs release from colorectal cancer cells, potentiating lymphocyte-induced cell death
Colorectal cancer (CRC) is one of the leading causes of cancer-related mortality worldwide with 5-FU still the primary chemotherapeutic of choice. With the increasing use of immunotherapies, much research is focused on the ability to make tumours more immunogenic, thereby rationalising combination with immunotherapy. Here we investigate whether NUC-3373, a phosphoramidate transformation of 5-fluorodeoxyuridine (FUDR), enhances immunogenicity in CRC cell lines and facilitates lymphocyte mediated cell death in vitro . At sub IC 50 doses NUC-3373 upregulates damage associate molecular patterns (DAMPs) in both HCT116 and SW480 cells and increases surface expression of MHCII and PD-L1. Pre-treatment with NUC-3373 and subsequent coculture with NK-92 MI natural killer cells caused an increase in LAMP1 expression (degranulation), production of IFN-γ, and NK-mediated cytotoxicity compared to vehicle controls. Cocultures with patient-derived PBMCs with heterologous CRC cells pre-treated with NUC-3373 demonstrated increased cell death compared to both vehicle controls and monocultures of CRC cells exposed to NUC-3373. Lastly, the PD-1 immune checkpoint inhibitor nivolumab showed synergistic activity when HCT116 cells were pre-treated with NUC-3373. To conclude, we show that NUC-3373 can modulate immune signaling and may therefore facilitate immune mediated tumour cell death in vitro .
Adjusting the management of the Antarctic krill fishery to meet the challenges of the 21st century
Antarctic krill ( Euphausia superba ) is the central prey species in the Southern Ocean food web, supporting the largest and fastest-growing fishery in the region, managed by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR). Climate change is threatening krill populations and their predators, while current catch limits do not take into account climate variability or krill population dynamics. In 2024, CCAMLR was unable to renew its spatial catch limits, highlighting the urgent need for improved management of the krill fishery to prevent any harm to the Southern Ocean ecosystem. To address this, we propose a management framework that integrates variability in krill recruitment and key pathways between spawning and nursery areas—a krill stock hypothesis—to inform decisions on catch limits and conservation measures. Implementing this approach will require targeted data collection, which we propose can be achieved through a multisector collaborative network that combines traditional and new technologies, including the use of fishing vessels as data collection platforms. We use case studies to demonstrate how fisheries can contribute to data collection while promoting sustainable management. A major challenge in this effort is securing long-term funding for data collection, which is critical for managing climate-sensitive populations of high commercial interest. We therefore recommend using the industry as a source of funding, research platform and data provider, alongside national research funding opportunities. Given the fundamental role of krill in the Southern Ocean ecosystem, its decline would have cascading effects on predators and essential ecosystem services.
Construction and application of a predictive model for optimal peripherally inserted central catheter (PICC) insertion depth in preterm infants under high-frequency ultrasound guidance based on clinical parameters
Objective This study aims to construct and validate a predictive formula based on routine clinical parameters for determining the optimal catheter placement depth (OCPD) in preterm infants undergoing peripherally inserted central catheter (PICC) insertion via the basilic vein (BV) or axillary vein (AXV). The goal is to provide a standardized reference protocol for precise PICC placement in neonatal intensive care, with the aim of enhancing procedural accuracy and reducing catheter-related complications. Methods This prospective study enrolled 105 preterm infants, who were categorized into two groups based on the puncture site: the basilic vein PICC group (BV-PICC, n = 59) and the axillary vein PICC group (AXV-PICC, n = 46). All catheter placements were performed under high-frequency ultrasound guidance to ensure accurate positioning and optimal catheter depth. The optimal catheter insertion length was recorded for each infant. Subsequently, clinical data were collected and analyzed, including gestational age, head circumference, chest circumference, maximum abdominal circumference, mid-forearm circumference, body weight, and body length. Multiple linear regression analysis was conducted to explore the relationship between optimal catheter depth and the clinical parameters of the preterm infants. Based on this analysis, a predictive formula for PICC insertion depth in preterm infants was developed using clinical parameters. Results In the BV-PICC group, birth weight and weight at the time of catheterization were identified as significant predictors. The optimal catheter placement depth (cm) was calculated using the following formula: OCPD = 8.205 + 0.005 × birth weight (g)–0.003 × weight at catheterization (g). In the AXV-PICC group, only body length at catheterization was identified as a significant predictor. The formula was: OCPD = 1.024 + 0.177 × body length at catheterization (cm). Conclusion The predictive formulas for the OCPD of PICC inserted via different pathways in preterm infants, developed under high-frequency ultrasound guidance and based on clinical parameters, demonstrated accuracy and excellent clinical applicability. These formulas provide a valuable reference for both standardized and individualized PICC placement in preterm infants, thereby facilitating evidence-based clinical decision-making and potentially reducing catheter-related complications.
Wild, scenic, and toxic: Recent degradation of an iconic Arctic watershed with permafrost thaw
The streams of Alaska’s Brooks Range lie within a vast (~14M ha) tract of protected wilderness and have long supported both resident and anadromous fish. However, dozens of historically clear streams have recently turned orange and turbid. Thawing permafrost is thought to have exposed sulfide minerals to weathering, delivering iron and other potentially toxic metals to aquatic ecosystems. Here, we report stream water metal concentrations throughout the federally designated Wild and Scenic Salmon River watershed and compare them with United States Environmental Protection Agency (EPA) chronic (4-d) exposure thresholds for toxicity to aquatic life. The main stem of the Salmon had elevated SO 4 2− concentrations and elevated SO 4 2− : Ca relative to a predisturbance baseline for most of its length, consistent with increased sulfide mineral weathering. Most of the tributaries also had elevated SO 4 2− concentrations and elevated SO 4 2− : Ca, especially those in the upper watershed. The Salmon River mainstem consistently exceeded EPA chronic exposure thresholds for total recoverable iron, total recoverable aluminum, and dissolved cadmium from its first major tributary to its mouth. Nine of ten major tributaries that we sampled exceeded EPA thresholds for at least one metal on at least one of three sampling dates. Our findings indicate that habitat quality for resident and anadromous fish has been severely degraded in the Salmon River watershed. Loss of important spawning habitat in the Salmon and many other streams in the region might help explain a recent crash in chum salmon returns, which local communities depend upon for commercial and subsistence harvest.
Analysis of transportation patterns through call detail records (CDRs)
Public transportation is essential for smart city development, especially in rapidly growing urban areas. In Riyadh, Saudi Arabia, the implementation of the metro system is expected to significantly impact the city’s transportation dynamics. This study uses Call Detail Records (CDRs) to analyze human mobility patterns and predict metro usage in 2024. This study also developed a methodology to categorize Traffic Analysis Zones (TAZs) and create metro zones, aiding in the visualization of the city’s population distribution and expected flow around the upcoming metro stations. Demographic data, including information on females and non-Saudis, was incorporated to predict metro usage more accurately. This approach identified areas with higher anticipated metro demand for the metro and potential feeder bus routes to support transportation efficiency. The insights gained from this analysis contribute to optimizing the metro system and addressing the needs of target populations, such as women and non-Saudi residents. This study demonstrates how mobile phone data can enhance transport planning in emerging urban environments.
Multi-model machine learning for automated identification of rice diseases using leaf image data
Rice, a staple meal for about half of the world’s population, is critical to global food security, especially in Asia. However, diseases have a severe impact on rice production, resulting in significant yield losses or outright crop failure. Traditional techniques of identifying rice diseases are time-consuming, labor-intensive, and rely heavily on specialist knowledge. As a result, a rapid, cost-effective, and automated method for detecting rice illnesses is critical for modernizing agricultural techniques and ensuring sustainable food production. This paper presents a novel hybrid deep-learning and machine-learning framework for automatically identifying rice plant diseases from leaf photos. We extracted deep features from rice leaf images using pre-trained CNN models—MobileNetV2, DarkNet19, and ResNet18. These features are then classified using machine learning classifiers with various kernel functions, which apply a strong 10-fold cross-validation technique to assure model reliability. Using a medium Gaussian kernel of the SVM classifier, the proposed system achieved a classification accuracy of 98.61%, specificity of 98.85%, and sensitivity of 97.25%. The framework is computationally efficient and scalable, allowing for greater dataset testing. The proposed technique provides a dependable and efficient solution for accurate identification of rice leaf diseases, reducing farmers’ reliance on manual inspection and supporting timely intervention.
Quasi-experimental controlled study protocol to reduce sedentary lifestyle in patients with type 2 diabetes
Introduction The prevalence of diabetes has increased worldwide, making it the most prevalent metabolic disorder. Physical inactivity contributes to the progression of this disease and aggravates other comorbidities, such as obesity and cardiovascular disease. Beneficial strategies aimed at promotion and healthy aging, oriented to decrease sedentary behavior, are necessary to obtain desirable metabolic effects and improve the quality of life of people with diabetes. Objective To examine, through a quasi-experimental study, the effect of decreasing sedentary time and increasing motivation to adopt an active lifestyle on different clinical, anthropometric and biochemical parameters in patients diagnosed with type 2 diabetes mellitus. Design and methodology Quasi-experimental controlled study, single-center, parallel, two-branch, with a 12-month follow-up. We plan to recruit up to a total of 169 participants, who will be assigned in a 1:1 ratio to a control group (who will receive e-mails) and an intervention group (who will receive face-to-face group and individual visits and telephone calls). The active intervention has a duration of 6 months and will be carried out by nursing professionals. The primary outcomes are sedentary time measured with the Sedentary Behavior Questionnaire (SBQ) and the use of accelerometers, and the state of motivation to change measured through the Transtheoretical Model of Physical Exercise Change Questionnaire (TMPECQ). Trial registration. ClinicalTrials.gov (NCT06893146).
Meeting the mental health needs of women in Irish prisons: A qualitative multi-stakeholder perspective to inform healthcare practice
The rate of female incarceration to prison has grown by approximately 60% since the year 2000. Mental ill-health is over-represented in the female carceral population and the experiences of women in the context of prison mental health services are largely invisible in empirical literature. The aim of this study was to highlight the under-represented narratives of women in prison and prison personnel to inform nursing practice and prison mental health service planning and delivery. A qualitative approach was used underpinned by institutional ethnography. Data were collected across two (n = 2) female prisons in the Republic of Ireland. Purposive and snow-ball sampling was used to recruit both women in prison and prison personnel to the study. One-to-one semi-structured interviews were conducted with participants. Reflexive Thematic Analysis was used to analyse the data. Ethical approval was granted by the Irish Prison Service and noted with Education & Health Sciences Research Ethics Committee at the University of Limerick. A total of twenty-five (n = 25) women in prison and twenty (n = 20) prison personnel participated in the study. Four analytic themes were identified from the data and present narratives that centre around women’s knowledge of and access to prison mental health services; women’s relationships with peers and prison officers; women’s relationships with medical doctors and medicine and organisational issues related to the provision of mental health services for women in prison. The barriers to accessing mental health services in the Irish prison context are numerous and complex. The findings from this study demonstrate the importance of approaching care with compassion and understanding and making inclusion health a priority.
Purinergic P2X receptor 7 (P2X7R) inhibition induced cytotoxicity in glioblastoma
Glioblastoma is the most common and aggressive form of primary brain cancer with a median survival of 15 months from diagnosis. The purinergic receptor P2X7 (P2X7R) is a regulator of several cell signalling pathways, and its expression is upregulated in glioblastoma. This study examined the expression and function of P2X7R in a human glioblastoma cell line, U251. We used a pharmacological antagonist of P2X7R, AZ10606120, to inhibit receptor function and delineate downstream consequences of receptor inhibition. Using RNA sequencing we demonstrated that P2X7R was expressed in the U251 cell line, harbouring both Y155H (Tyr to His) and E496A (Glu to Ala) single nucleotide polymorphism (SNP) mutations. The receptors functionality – namely its pore and channel conductance states were intact. Inhibition of P2X7R with small molecule antagonist AZ10606120, for 72 hours significantly decreased U251 cell number (p < 0.0001), and significantly increased tumour cell death, as evidenced by increased LDH release (p < 0.001). This reduction in tumour cell number was concentration-dependent, modelled by a least squares linear regression (R2 = 0.8221, IC50 = 17µM). The primary mode of cell death induced by AZ10606120 was shown to not be apoptosis, demonstrated through no significant changes in annexin V or cleaved caspase 3 staining in AZ10606120 treated cell versus control cells. Multiplex mRNA analysis demonstrated changes in genes associated with both apoptosis and pyroptosis, whilst a decrease in receptor-interacting serine/threonine-protein kinase 1 (RIPK1) expression along with an increase in TNFR1-associated death domain protein (TRADD) expression suggests potential involvement of the TRADD mediated RIPK1-independent necroptosis pathway. Collectively, this study describes several key characteristics of AZ10606120s acting as an anti-tumour small molecule pharmaceutical and highlights the potential of P2X7R inhibition as a novel therapeutic target in glioblastoma.
3D cryoimaging of cell-mediated cholesterol crystal clearance in human atherosclerotic lesions
We applied micro-computed tomography, high-resolution cryo-scanning electron microscopy (SEM) combined with cathodoluminescence, and cryo-focused ion beam Milling-SEM to perform three-dimensional imaging of human atherosclerotic tissues with tens of nanometers resolution, under hydrated, near-native conditions with minimal sample processing. The same technology was applied to cultured macrophages exposed to cholesterol crystals, and the observations made on the macrophages were compared to those made on the pathological tissue. We observed that cholesterol crystal digestion and, eventually, cholesterol crystal clearance occurs in the advanced human plaques through cellular processing. Our findings suggest that cholesterol crystal disassembly occurs through the esterification of crystalline cholesterol to cholesteryl-ester in isolated volumes, whereby the ester aggregates into intra- and extracellular pools. The hypothesis is supported by the close similarity of the processes imaged in the human tissue and in the macrophages and is in agreement with earlier biochemical studies performed on cultured macrophages.
Teeth outside the jaw: Evolution and development of the toothed head clasper in chimaeras
Chimaeras ( Holocephali ) are an understudied group of mostly deep-ocean cartilaginous fishes ( Chondrichthyes ) with unique characteristics that distinguish them from their distant relatives, sharks, skates, and rays. Unlike sharks, chimaeras lack scales and do not have serially replacing rows of serrated teeth crowned with enameloid. Instead, they possess a fused dentition of dentine tooth plates. Additionally, male chimaeras develop an articulated cartilaginous facial appendage, the tenaculum, which is covered in an arcade of tooth-like structures. These extraoral teeth remain poorly understood, and their evolutionary origin is unclear. We investigate the development of the tenaculum and its teeth throughout the ontogeny of the Spotted Ratfish, Hydrolagus colliei , to assess homology and convergence between this novel craniofacial feature and oral jaws. Our study aims to 1) describe the development of the tenaculum, 2) assess tenaculum tooth development in comparison to oral teeth and denticles, and 3) characterize the genes and tissues responsible for tenaculum tooth emergence. We found that juvenile male chimaeras develop a full tenaculum before tooth development is complete and that only mature males possess a fully toothed tenaculum. These extraoral teeth emerge from within the tenaculum rather than from the surrounding epithelium. We integrate our developmental data with fossil evidence of the tenacular dentition from the Carboniferous holocephalan Helodus simplex . Our findings show that the tenaculum is closely associated with the upper jaw and that tenacular dentition resembles separate shark-like oral tooth whorls more than modified dermal denticles.
Psychometric evaluation of the Spanish version of the therapeutic communication scale in nursing students
Background Therapeutic communication is a core component of person-centered nursing care. Despite its clinical relevance, few validated instruments exist in Spanish that objectively assess this competence in undergraduate nursing students. Objective This study aimed to adapt and validate the Spanish version of the Therapeutic Communication Scale in Nursing Students (TCS-NS), originally developed by Han et al. (2024), and to examine its psychometric properties in a Spanish-speaking context. Methods A psychometric study was conducted in two phases: (1) translation and cross-cultural adaptation following international guidelines, including expert panel review and pilot testing; and (2) psychometric evaluation with a sample of 468 nursing students. Construct validity was assessed using confirmatory factor analysis (CFA), and reliability was examined via Cronbach’s alpha, McDonald’s omega, composite reliability, and test-retest stability (ICC). Results The CFA supported the two-factor structure of the TCS-NS and indicated good model fit (CFI = .963; TLI = .954; RMSEA = .053; SRMR = .044). Internal consistency was adequate for the total scale (α = .880; ω = .884), and composite reliability was high (.936). The intraclass correlation coefficient for the total score was.696 (95% CI:.605–.766). Conclusions The Spanish version of the TCS-NS is a valid and reliable instrument for assessing therapeutic communication skills in nursing students. Its use may contribute to the objective evaluation of communication competence in educational interventions and research.
Isolation, characterization, and pathogenicity of a Vibrio parahaemolyticus strain causing translucent post-larvae disease in Penaeus vannamei outside China
Translucent post-larvae disease (TPD) has emerged as a severe threat to shrimp aquaculture, causing substantial economic losses. The causative agent, Vibrio parahaemolyticus, has been primarily identified in China, but this study provides the first confirmed report of its presence in shrimp populations outside China. This research characterizes V. parahaemolyticus strain AG1 (VpTPD AG1), isolated from diseased Penaeus vannamei, through biochemical, molecular, and pathogenic analyses. PCR screening of VpTPD AG1 detected vhvp-1 and vhvp-2, genes previously linked to TPD virulence, while pirA/pirB genes associated with acute hepatopancreatic necrosis disease (AHPND) were absent. Experimental immersion challenges demonstrated high virulence and dose-dependent pathogenicity, with an LC50 of 8.51 × 102 CFU/mL at 96 hours in 15-day-old post-larvae (PL15) of Penaeus vannamei shrimp. Larger post-larvae (PL30) exhibited reduced susceptibility, suggesting a size-dependent resistance mechanism. Histopathological analysis confirmed the degeneration of the hepatopancreas, including tubular necrosis, epithelial cell sloughing, and bacterial invasion, consistent with previously reported TPD pathology. Additionally, hemocytic enteritis, a characteristic histopathological feature associated with infection with VpTPD AG1 strain, was marked by mucosal epithelium loss, intense inflammation, and a thick hemocyte layer in the intestine. Antibiotic susceptibility testing of VpTPD AG1 strain revealed resistance to β-lactams but sensitivity to multiple other antimicrobial classes. These findings highlight the expanding geographical distribution of VpTPD, its distinct pathological features compared to AHPND, and further highlight the urgent need to enhance surveillance and implement effective biosecurity measures to prevent its global dissemination.
The effect of thoracolumbosacral orthosis on scoliosis progression and chest deformity in children with type 1 spinal muscular atrophy: A randomized controlled trial
Background Type 1 spinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disease characterized by severe muscle weakness, which results in progressive spinal and chest deformities. This study aims to evaluate the effect of thoracolumbosacral orthosis (TLSO) use along with pulmonary care (PC), individualized pulmonary rehabilitation (IPR), and individualized trunk exercises (ITE) in children with Type 1 SMA. Methods The study enrolled 24 children with Type 1 SMA aged 2–6 years, with a scoliosis angle of 20°–40°. Participants were randomly assigned into two groups using a stratified randomization method: Group 1 (PC, IPR, ITE) and Group 2 (PC, IPR, ITE & TLSO). All participants underwent an 8-week treatment program. Pre- and post-treatment assessments included scoliosis progression measured by the Cobb angle, chest deformity evaluated through the basal upper-lower chest wall ratio and the Supine Angle of Trunk Rotation Test (SATR), and motor function levels assessed using the Children’s Hospital of Philadelphia Infant Test of Neuromuscular Disorders (CHOP INTEND). Results Significant improvements were observed in Cobb angle, bell-shaped chest deformity, and motor function in both groups (p < 0.05). Group 2 demonstrated greater improvements in effect size (ES) across all evaluation parameters. Compared to Group 1, Group 2 showed superior improvement in Cobb angle (ES = 3.98), basal upper-lower chest wall ratio (ES = 5.00), SATRL (lower) (ES = 2.55), SATRU (upper) (ES = 1.64), and CHOP INTEND (ES = 1.23) (p < 0.05). Conclusions This study is the first to demonstrate that the combination of PC, IPR, ITE, and TLSO yields superior clinical outcomes in children with Type 1 SMA. The findings support current recommendations for TLSO use in patients with a Cobb angle >20°, and emphasize the potential benefits of early, proactive orthotic intervention when integrated with mobilization, trunk, and pulmonary exercise programs in managing scoliosis in this population. However, limitations such as the small sample size and short follow-up period underscore the need for larger and longer-term studies to confirm these findings. Trial Registiration: NCT05878418
Automated detection and prediction of suicidal behavior from clinical notes using deep learning
Background Deep learning approaches have tremendous potential to improve the predictive power of traditional suicide prediction models to detect and predict intentional self-harm (ISH). Existing research is limited by a general lack of consistent performance and replicability across sites. We aimed to validate a deep learning approach used in previous research to detect and predict ISH using clinical note text and evaluate its generalizability to other academic medical centers. Methods We extracted clinical notes from electronic health records (EHRs) of 1,538 patients with International Classification of Diseases codes for ISH and 3,012 matched controls without ISH codes. We evaluated the performance of two traditional bag-of-words models (i.e., Naïve Bayes, Random Forest) and two convolutional neural network (CNN) models including randomly initialized (CNNr) and pre-trained Word2Vec initialized (CNNw) weights to detect ISH within 24 hours of and predict ISH from clinical notes 1–6 months before the first ISH event. Results In detecting concurrent ISH, both CNN models outperformed bag-of-words models with AUCs of.99 and F1 scores of 0.94. In predicting future ISH, the CNN models outperformed Naïve Bayes models with AUCs of 0.81–0.82 and F1 scores of 0.61−.64. Conclusions We demonstrated that leveraging EHRs with a well-defined set of ISH ICD codes to train deep learning models to detect and predict ISH using clinical note text is feasible and replicable at more than one institution. Future work will examine this approach across multiple sites under less controlled settings using both structured and unstructured EHR data.
Design optimization of high-sensitivity PCF-SPR biosensor using machine learning and explainable AI
Photonic crystal fiber based surface plasmon resonance (PCF-SPR) biosensors are sophisticated optical sensing platforms that enable precise detection of minute refractive index (RI) variations for various applications. This study introduces a highly sensitive, low-loss, and simply designed PCF-SPR biosensor for label-free analyte detection, operating across a broad RI range of 1.31 to 1.42. In addition to conventional methods, machine learning (ML) regression techniques were integrated to predict key optical properties, while explainable AI (XAI) methods, particularly Shapley Additive exPlanations (SHAP), were used to analyze model outputs and identify the most influential design parameters. This hybrid approach significantly accelerates sensor optimization, reduces computational costs, and improves design efficiency compared to conventional methods. The proposed biosensor achieves impressive performance metrics, including a maximum wavelength sensitivity of 125,000 nm/RIU, amplitude sensitivity of −1422.34 RIU ⁻ ¹, resolution of 8 × 10 ⁻ ⁷ RIU, and a figure of merit (FOM) of 2112.15. ML models demonstrated high predictive accuracy for effective index, confinement loss, and amplitude sensitivity. SHAP analysis revealed that wavelength, analyte refractive index, gold thickness, and pitch are the most critical factors influencing sensor performance. The combination of a simple yet efficient design and advanced ML-driven optimization makes this biosensor a promising candidate for high-precision medical diagnostics, particularly cancer cell detection, and chemical sensing applications.