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Early and accurate detection of lung cancer remains a central challenge in intelligence-based medicine, where robust imaging informatics solutions are required to interpret complex chest CT data. This study proposes a novel hybrid convolutional neural network-graph attention network (CNN-GAT) framework, optimized by the Whale Optimization Algorithm (WOA), for clinical three-class classification of lung cancer (benign, malignant, normal) from chest CT images. The proposed architecture employs a ResNet-18 backbone to extract deep spatial representations, which are subsequently modeled as a graph structure and processed by graph attention layers to capture non-linear relational dependencies among localized CT features. To enhance generalization and mitigate overfitting, WOA is used for automated hyperparameter tuning, including learning rate, batch size, hidden channel dimensions, and dropout rates. The framework is evaluated on a curated chest CT dataset and benchmarked against standard CNN and compound EfficientNet architectures. Experimental results demonstrate that the proposed intelligence-based framework substantially outperforms the baseline models, achieving a test accuracy of 98.7%, precision of 98.5%, recall of 98.9%, F1-score of 98.7%, a Matthews correlation coefficient of 0.975, and an area under the curve of 0.994. In addition, the model is highly efficient, with approximately 4.1 million trainable parameters and an average inference time of 0.035 s per CT scan, making it suitable for real-time deployment. In conclusion, integrating graph-based topological intelligence with meta-heuristic optimization on top of a lightweight CNN backbone yields a highly accurate, generalizable, and computationally efficient diagnostic framework. The proposed CNN-GAT + WOA model shows strong potential for seamless integration into clinical workflows as an automated decision-support tool for high-stakes lung cancer screening from chest CT images.
Halide-based solid electrolytes (HSEs) have garnered substantial interest for all-solid-state batteries (ASSBs) due to their wide electrochemical windows, moderate-to-high room-temperature ionic conductivity, and enhanced air stability over traditional sulfide and oxide-based SEs. This review consolidates recent advances in HSEs, focusing on the link between structure, compositions, and materials properties that influence the transport of lithium-ion (Li-ion) and post-lithium-ion (P-Li-ion) and their stability at the interface. Based on the chemistry of their central metal, HSEs are divided into five classes; key factors influencing ionic conductivity are examined. Nevertheless, despite these benefits, many challenges remain, including interfacial instability, the trade-off between ionic conductivity and electrochemical stability, mechanical challenges, and material costs. The main synthesis methods, mechanochemical, co-melting, and wet-chemical, are investigated for phase formation, scalability, and defect control. The link between synthesis, microstructure, and device-level performance metrics, including critical current density, area-specific resistance, and cycle life, is examined. The strategies, involving bilayer and dual-electrolyte design as well as interface engineering, are analyzed to reduce interfacial resistance and dendrite growth. The applications of HSE in Li-ion and P-Li-ion systems are examined. This review offers a detailed framework and delineates potential research paths to advance scalable, high-performance HSEs for next-generation ASSBs.
Twenty-one Anglo-Nubian goat kids (21.6 ± 2.9 kg) were assigned to a completely randomized design to evaluate the effects of different whole grain-based diets on performance, ingestive behavior, physiological parameters, and carcass characteristics. The experimental diets consisted of a control diet (CON), containing 10% hay and 90% concentrate, and two non-forage diets: a whole corn grain-based diet (WC) and a whole millet grain-based diet (WM), both composed of 20% commercial pellet and 80% the respective whole grain. The non-forage diets reduced dry matter intake (P = 0.002); however, crude protein intake was reduced only in the WC diet (P = 0.001). The CON diet increased fiber intake (P < 0.001) and resulted in the longest rumination time (P = 0.026), whereas the WM diet showed the highest ether extract (EE) intake (P < 0.001). The WC diet altered the feed-sorting behavior of the goat kids and consequently showed the highest DM digestibility (P = 0.042). The WC diet showed higher EE digestibility than the CON diet (P = 0.025), whereas EE digestibility in the WM diet did not differ from that in the other diets. However, the WC diet reduced average daily gain (P = 0.006), and slaughter weight (P = 0.025), without affecting carcass weight, carcass yield, or leg tissue composition (P > 0.05). Physiological parameters were not influenced by diet (P > 0.05). Overall, WM can replace WC in non-forage diets, maintaining satisfactory performance, carcass characteristics, and leg tissue composition in goat kids.
This study examined why artificial intelligence (AI)-based clinical decision support tools have had limited clinical translation in the emergency department (ED) and identified barriers and facilitators to their development and implementation. We conducted a qualitative study involving semi-structured interviews with researchers who have expertise developing and implementing AI clinical decision support tools for use in the ED. We used purposive and snowball sampling to identify participants. We used platform-based AI transcription and anonymized transcripts manually. Using grounded theory framework, two coders iteratively analyzed transcripts in three stages (initial, focused, and theoretical) to identify barriers, facilitators, and themes. We adhered to SRQR and COREQ guidelines. We achieved data saturation after ten interviews conducted between October 15, 2024 and March 22, 2025. Participants ranged across a variety of medical and academic professions. We identified eight themes pertaining to developing and implementing AI clinical decision support in the ED, in descending frequency: team capacity; data infrastructure; defining the clinical problem and solution; research, ethics, and regulatory approval; legal and liability; model building and performance; time; and cost. We identified "engaging multiple healthcare end-users" and "sharing resources with other departments" as the highest yield facilitators. Successful implementation of AI clinical decision support tools in the ED requires a clear clinician- and patient-defined problem, robust data infrastructure, and a diverse research team able to navigate challenges with regulatory, legal, and financial challenges over a long timeline. Anticipating barriers and leveraging facilitators early in the development process may increase the likelihood of successful implementation. RéSUMé: OBJECTIFS: Cette étude a examiné pourquoi les outils d’aide à la décision clinique basés sur l’intelligence artificielle (IA) ont eu une traduction clinique limitée dans le service des urgences et a identifié des obstacles et des facilitateurs pour leur développement et leur mise en œuvre. MéTHODES: Nous avons mené une étude qualitative impliquant des entretiens semi-structurés avec des chercheurs ayant une expertise dans le développement et la mise en œuvre d’outils d’aide à la décision clinique par IA pour utilisation au service des urgences. Nous avons utilisé l’échantillonnage ciblé et en boule de neige pour identifier les participants. Nous avons utilisé manuellement la transcription IA basée sur la plateforme et les transcriptions anonymisées. En utilisant la théorie ancrée, deux codeurs ont analysé de manière itérative des transcriptions en trois étapes (initiale, ciblée et théorique) afin d’identifier les obstacles, les facilitateurs et les thèmes. Nous avons respecté les directives SRQR et COREQ. RéSULTATS: Nous avons atteint la saturation des données après dix entretiens menés entre le 15 octobre 2024 et le 22 mars 2025. Les participants exerçaient diverses professions médicales et universitaires. Nous avons identifié huit thèmes relatifs au développement et à la mise en œuvre de l’aide à la décision clinique en IA dans le service d’urgence, par ordre décroissant de fréquence : capacité de l’équipe ; infrastructure des données ; définition du problème clinique et de la solution ; recherche, éthique et approbation réglementaire ; juridique et responsabilité ; construction de modèles et performance ; temps ; et coût. Nous avons identifié « l’engagement de plusieurs utilisateurs finaux du secteur de la santé » et « le partage des ressources avec d’autres départements » comme les facilitateurs à plus haut rendement CONCLUSION: La mise en œuvre réussie des outils d’aide à la décision clinique de l’IA dans le service d’urgence nécessite un problème clairement défini par les cliniciens et les patients, une infrastructure de données robuste et une équipe de recherche diversifiée capable de surmonter les défis réglementaires, juridiques et financiers sur une longue période. Anticiper les obstacles et mobiliser des facilitateurs dès le début du processus de développement peut accroître la probabilité d’une mise en œuvre réussie.
Animals integrate knowledge about how the state of the environment evolves to choose actions that maximise reward. Such goal-directed behaviour - or model-based (MB) reinforcement learning (RL) - can flexibly adapt choice to changes, being thus distinct from simpler habitual - or model-free (MF) RL - strategies. Previous inactivation and neuroimaging work implicates prefrontal cortex (PFC) and the caudate striatal region in MB-RL; however, details are scarce about its implementation at the single-neuron level. Here, we recorded from two PFC regions - the dorsal anterior cingulate cortex (ACC) and dorsolateral PFC (DLPFC), and two striatal regions, caudate and putamen - while two rhesus macaques performed a sequential decision-making (two-step) task in which MB-RL involves knowledge about the statistics of reward and state transitions. All four regions, but particularly the ACC, encoded the rewards received and tracked the probabilistic state transitions that occurred. However, ACC (and to a lesser extent caudate) encoded the key variables of the task - namely the interaction between reward, transition, and choice - which underlies MB decision-making. ACC and caudate neurons also encoded MB-derived estimates of choice values. Moreover, caudate value estimates of the choice options flipped when a rare transition occurred, demonstrating value update based on structural knowledge of the task. The striatal regions were unique (relative to PFC) in encoding the current and previous rewards with opposing polarities, reminiscent of dopaminergic neurons, and indicative of an MF prediction error. Our findings provide a deeper understanding of selective and temporally dissociable neural mechanisms underlying goal-directed behaviour.
Achieving efficient diagnosis and precise drug delivery for the treatment of endocrine diseases represents a significant challenge in the global biomedical field. With the continuously rising incidence of endocrine diseases worldwide, the demand for early diagnosis and targeted therapy has become increasingly urgent. This review systematically analyzes the synthetic strategies and structural characteristics of zeolitic imidazolate frameworks (ZIFs) with a focused examination of their application progress in the diagnosis and treatment of endocrine diseases. The results demonstrate that ZIF materials exhibit remarkable advantages in high-sensitivity biosensors, multimodal imaging-guided diagnosis, and theranostic integration, attributed to their high specific surface area, tunable pore structures, favorable biocompatibility, and pH-responsive degradability. Furthermore, ZIF-based nanoplatforms have shown promising synergistic effects in tumor-targeted therapy, drug-gene co-delivery, and the treatment of autoimmune endocrine diseases. Comprehensive comparative analysis reveals that, compared with other MOF materials, ZIF materials possess distinctive advantages in achieving stimulus-responsive controlled release and biosensing detection; however, critical issues regarding long-term biosafety, in vivo metabolic mechanisms, and scalable preparation remain to be addressed. This review explicitly identifies that ZIF-based nanoplatforms, particularly through their stimulus-responsive drug delivery and high-sensitivity biosensing capabilities, have achieved significant and unique accomplishments in developing intelligent diagnostic and therapeutic strategies for endocrine diseases, which is highly consistent with the scope of this journal focusing on applied biomaterials.
This report presents a 6-year antigen-based surveillance of pediatric viral gastroenteritis in Turkey, revealing substantial epidemiological shifts during and after the coronavirus disease 2019 (COVID-19) pandemic. Adenovirus circulation was strongly affected by COVID-19-related public health restrictions, showing a marked decline during restriction periods. However, rotavirus exhibited a relative increase in 2021 despite ongoing restrictions, followed by a more pronounced rise after the relaxation of measures, aligning with the "immunity debt" hypothesis associated with altered early-life viral exposure. These findings illustrate how pandemic-related interventions reshaped the circulation of enteric viruses and underscore the value of routine rapid antigen testing for detecting post-pandemic resurgences, which is underexplored in the literature. In der vorliegenden Arbeit wird eine 6 Jahre dauernde antigenbasierte Beobachtungsstudie zur pädiatrischen viralen Gastroenteritis in der Türkei vorgestellt, mit dem Ergebnis wesentlicher epidemiologischer Verschiebungen während und nach der COVID-19-Pandemie. Die Verbreitung von Adenoviren war durch Gesundheitsvorschriften aufgrund von COVID-19 stark eingeschränkt – mit einer deutlichen Abnahme während der Phasen mit geltenden Restriktionen. Rotaviren wiesen jedoch im Jahr 2021 trotz weiterhin geltender Restriktionen einen relativen Anstieg auf, mit einem anschließenden deutlicheren Anstieg nach Lockerung der Maßnahmen – in Einklang mit der Hypothese der „Immunitätsschuld“ in Zusammenhang mit veränderter Virusexposition in einem frühen Lebensabschnitt. Diese Ergebnisse zeigen, wie pandemiebezogene Maßnahmen die Verbreitung von Darmviren neu gestalten und unterstreichen den Wert der routinemäßigen schnellen Antigentestung zur Erkennung des postpandemischen Wiederauftretens, das in der Literatur noch zu wenig erforscht ist.
Chlamydia trachomatis is one of the most common bacterial sexually transmitted infections worldwide and has been associated with adverse reproductive health outcomes. However, evidence on its burden, clinical presentation, and associated factors among women with spontaneous abortion in Uganda remains limited. This study determined the prevalence of C. trachomatis infection, described its clinical presentation, and identified associated factors among women presenting with spontaneous abortion at Jinja Regional Referral Hospital. A hospital-based cross-sectional study was conducted among 209 women with spontaneous abortion at Jinja Regional Referral Hospital. High cervical swab specimens were collected and tested for C. trachomatis using polymerase chain reaction. Logistic regression analysis was used to identify factors associated with infection. Among the 209 women enrolled, the majority were aged 20-29 years (66.5%), married (84.7%), and unemployed (80.9%). The prevalence of laboratory-confirmed C. trachomatis infection was 18.7% (39/209; 95% CI: 13.6%-24.7%). Among infected women, pelvic pain was the most frequently reported symptom (58.9%), followed by per vaginal discharge (33.3%), while 7.7% were asymptomatic. Factors independently associated with C. trachomatis infection included age 20-29 years (aOR = 5.04, 95% CI: 1.34-18.94), previous abortion (aOR = 3.48, 95% CI: 1.22-9.91), per vaginal discharge (aOR = 6.34, 95% CI: 1.68-23.85), and pelvic pain (aOR = 6.57, 95% CI: 2.63-16.41). HIV-positive status was also associated with higher odds of infection (aOR = 2.76, 95% CI: 1.05-7.28), although the estimate was imprecise. Nearly one in five women presenting with spontaneous abortion had laboratory-confirmed C. trachomatis infection. The findings suggest that women with reproductive risk factors and suggestive clinical symptoms may benefit from targeted testing and timely management. Strengthening access to diagnostic screening within reproductive health services may improve detection of otherwise unrecognized infections and support better reproductive health outcomes.
A family of 2D tetrathiafulvalene tetracarboxylate (TTFTC)-based lanthanide (LnIII = Dy III, Er III, and Yb III) metal-organic frameworks (MOFs) is reported as a robust platform for mixed proton-electron conduction. Electronic transport arises from partially oxidized, π-stacked TTFTC columns with a fixed hole population imposed by framework stoichiometry, leading to narrow-band semiconducting behavior. The charge distribution within the π-stacks is preserved over a wide humidity range, resulting in only minor, compound-dependent variations in electronic conductivity. In parallel, proton transport is promoted by dense hydrogen-bond networks formed by coordinated water molecules anchored to rigid Ln6 cluster walls, enabling an efficient proton conduction that remains operative across a broad range of humidity and temperature conditions (Ea < 0.4 eV at RH 80%), consistent with a dominant Grotthuss-type mechanism. Among the series, Er6TTFTC5 displays the highest room-temperature single-crystal electronic conductivity reported to date for a TTF-based MOF (1.0 × 10-2 S cm-1, 4-probe), together with a proton conductivity of 3.7 × 10-3 S cm-1 under humid conditions (80 °C, 80% RH). To enable direct comparison, both electronic and proton conductivities were evaluated under identical conditions, and an effective ambipolar conductivity (σamb) was derived from the independently measured contributions. The resulting values rank among the highest reported for structurally defined proton-electron mixed conductors (2.3 × 10-3, 7.2 × 10-4, and 5.9 × 10-4 S cm-1 at 80% RH and 80 °C for Er6TTFTC5, Yb6TTFTC5, and Dy6TTFTC5). Subtle variations across the lanthanide series are attributed to differences in framework rigidity and intermolecular interactions, which modulate transport properties without altering the underlying, structurally encoded conduction pathways.
Falls pose a significant threat to human safety, making rapid and accurate detection and response essential. Time Exploration Network (TExNet), an attention-enhanced network tailored for identifying falls accurately and rapidly, is proposed in this paper. Unlike existing studies that rely on simulated environments, TExNet addresses the gap between simulated and real scenarios by integrating multi-branch timing and classification characteristics. It features a two-branch adaptive fusion framework, leveraging Convoluational Neural Network (CNN) and Transformer architectures to capture both local and global dependencies effectively. Additionally, dual-branch adaptive fusion framework incorporates dilated convolution and time series positional decomposition to enhance temporal correlation understanding. To handle data distribution variations, it employs an Invariant Risk Minimization (IRM) inspired loss function, penalizing misclassification of positive examples. This reduces model reliance on specific environments and improves action understanding. Moreover, a data self-conditioning module enhances data diversity and tackles imbalance issues. The model is deployed using a fine-tuning strategy based on a pre-trained framework combined with few-shot learning for downstream tasks. Experimental results show that the fine-tuned model achieves a recall of 92.16%, indicating its strong ability to rapidly adapt to new data distributions. Extensive experiments also validate the superiority of TExNet compared with existing approaches.
Among US teenagers, 79% of HIV infections are attributable to male-to-male sexual contact; yet, few interventions have been shown to effectively reduce sexual risk among gay and bisexual adolescents (GBA). Parent communication about sex is associated with adolescent sexual risk, and interventions to improve parent communication have been shown to successfully reduce sexual risk among heterosexual samples. However, no interventions designed specifically for parents of GBA have been tested in clinical trials. Parents and Adolescent Talking About Healthy Sexuality (PATHS) is a web-based intervention we created for parents of GBA that aims to improve parent communication about sexuality and HIV and increase parent behaviors supportive of GBA sexual health. This trial aims to test whether delivering PATHS to parents of GBA ages 14-19 years will improve GBA sexual health outcomes in the 6 months following intervention delivery. Secondary aims are to test whether the intervention's effects are sustained at 12 months after the intervention and to examine whether effects are mediated through specific parent behaviors. In total, 350 parents of GBA will be recruited online via social media advertising and randomized to receive either PATHS or an active control. PATHS is fully automated, self-paced, and can be completed in a single session lasting under an hour. The active control is an education entertainment film created to provide general support and guidance to parents of GBA. Both parents and their GBA sons will complete online assessments every 3 months over a 1-year period. Primary outcomes will be evaluated at 6 months after the intervention, and then, the control arm will crossover and receive PATHS, and dyads will be followed for another 6 months. Primary outcomes include both adolescent sexual preparedness (eg, condom skills) as well as HIV-related sexual risk behavior (ie, condomless anal or vaginal sex that is not protected by pre-exposure prophylaxis). The study was funded in March 2022, and we completed enrollment of 393 parent-GBA dyads in September 2025. We project that all participants will have completed study activities by November 2026, with data analysis and results of the trial forthcoming in the first quarter of 2027. If proven efficacious, PATHS will be among the first HIV prevention interventions shown to reduce sexual risk for GBA. Moreover, as other adolescent-focused interventions emerge, PATHS' unique focus on parents will offer a complementary, additional means for reaching GBA who do not engage with other intervention options. ClinicalTrials.gov NCT05852600; https://clinicaltrials.gov/study/NCT05852600. PRR1-10.2196/81316.
Combining helium, carbon or oxygen beams with minibeam radiation therapy (MBRT) may benefit the treatment of radioresistant tumours while better protecting healthy tissues from radiation toxicities. In this study, the biomolecular response of glioma cell lines to HeMBRT, CMBRT and OMBRT was evaluated using synchrotron-based Fourier transform infrared microspectroscopy (SR-FTIRM). F98 (rat glioma) and U-87 MG (human glioma) cell lines were subjected to conventional broad beam RT (BB) or MBRT at the Heidelberg Ion-Beam Therapy Centre (Germany). Biomolecular effects were assessed with SR-FTIRM at the MIRAS beamline of the ALBA Synchrotron (Spain). Principal component analysis (PCA) uncovered the spectral alterations due to the different irradiation modalities. In F98 cells, IR signatures in the 1254-1225 cm-1 spectral region, mainly related to DNA and RNA geometries, were altered by both BB and MBRT modalities and the two ion species. Alterations of IR signatures in the 1097-1074 cm-1 spectral region, associated with the phosphodiester backbone of nucleic acids, and IR signatures associated with C-O vibrational modes in the 1110-1097 cm-1 (mainly due to nucleic acids), 1182-1163 cm-1 (mainly due to phospholipids), 1135-1110 cm-1 and 1071-1040 cm-1 (mainly due to carbohydrates) spectral regions, were generally enhanced by CMBRT; OBB and OMBRT also resulted in dose-dependent modifications of these spectral bands, suggesting nucleic acid modifications or oxidative damage. CMBRT, OBB and OMBRT also induced changes in IR signatures of the Amide I band associated with α-helical and β-sheet protein secondary structures, which might result from protein oxidation or cell death mechanisms. In U-87 MG cells, specific IR signatures in the Phosphate II band (i.e. 1173 cm-1, 1150 cm-1, 1080 cm-1, 1065 cm-1 and 1025 cm-1), primarily associated with C-O signals present in phospholipids, carbohydrates and the phosphodiester backbone of nucleic acids, were greatly affected by helium-, carbon- and oxygen-ion RT, in both conventional and spatially fractionated modes. Biomolecular changes in the C-H vibrational modes of lipids for both cell lines were consistent with free radical attacks. Cell viability results revealed cell line-dependent sensitivities to treatment, with findings consistent with the modifications observed in the SR-FTIRM analysis.
This study estimated FRAX®-based intervention thresholds for initiating osteoporosis treatment in Chinese postmenopausal women, using real-world data from the largest nationally representative osteoporosis survey in China and a validated Markov microsimulation model. Denosumab became cost-effective at a 10-year major osteoporotic fracture probability of 7%, and zoledronate at 12%, whereas alendronate and teriparatide did not reach cost-effectiveness at any FRAX probability evaluated. To determine drug-specific FRAX® thresholds for cost-effective initiation of osteoporosis treatment (alendronate, zoledronate, denosumab, teriparatide) in Chinese postmenopausal women using real-world data. A validated Markov microsimulation model was used to simulate lifetime costs and quality-adjusted life years (QALYs) of no treatment versus alendronate, zoledronate, denosumab, and teriparatide treatment. Baseline patient characteristics and risk factor distribution were sampled from the largest national osteoporosis survey in mainland China. The analysis was conducted from the societal perspective, applying a willingness-to-pay threshold of USD 13,000 per QALY gained (equivalent to one times China's GDP per capita). Denosumab was cost-effective at a 10-year major osteoporotic fracture probability of 7% and zoledronate at 12%; neither alendronate nor teriparatide became cost-effective. For denosumab, the cost-effective threshold of 10-year major osteoporotic fracture probability increased with age from 51 to 65 years and then declined in older women, ranging from 5 to 12%. For zoledronate treatment, the cost-effective thresholds of a 10-year major osteoporotic fracture probability were 8% at 51-55 years, 12% at 71-75 years, and 8.5% at 76-80 years. For Chinese postmenopausal women, denosumab was the most cost-effective treatment, while zoledronate also reached favorable thresholds in selected age groups. Implementing drug-specific FRAX®-guided thresholds may optimize treatment decisions for osteoporosis and support efficient healthcare resource use.
An initial comparison of 16S rRNA gene sequences between Alkalispirochaeta alkalica Z-7491T and other members of the genus Alkalispirochaeta revealed ≥99.4% sequence similarity, suggesting their close relatedness and the possibility that some members are in fact the same species. The genus Alkalispirochaeta includes five species with validly published names. A. alkalica Z-7491T (=ATCC 700262T=DSM 8900T) and Alkalispirochaeta sphaeroplastigenens JC133T (=KCTC 15220T=NBRC 109056T) were both isolated from alkaline lakes (Lake Magadi in Kenya and Lonar Lake in India), respectively. The present study used whole-genome data to clarify the taxonomic assignment of these two closely related Alkalispirochaeta species. A. alkalica Z-7491T and A. sphaeroplastigenens JC133T share similar phenotypic and chemotaxonomic characteristics. They are Gram-stain-negative, motile, helical-shaped bacteria that require sodium for growth and grow optimally under alkaliphilic and mesophilic conditions, and their main cellular fatty acid is C18 : 1 ω7c. Overall genomic relatedness indices analyses indicated average nucleotide identity and digital DNA-DNA hybridization values >95.0% and >70.0%, respectively. These values exceed thresholds currently accepted for bacterial species delineation. Further, these taxa cluster together within the genus Alkalispirochaeta in both the 16S rRNA gene phylogenetic tree and the core-genome phylogenomic tree. Based on the combined evidence and the earliest validly published names, priority is given to Alkalispirochaeta alkalica (Zhilina et al. 1996) Sravanthi et al. 2016. Alkalispirochaeta sphaeroplastigenens (Vishnuvardhan Reddy et al. 2013) Sravanthi et al. 2016 is proposed to be a later heterotypic synonym of Alkalispirochaeta alkalica (Zhilina et al. 1996) Sravanthi et al. 2016.
Risk assessment is essential for planning esophagectomy in patients with esophageal or gastro-esophageal junction (GEJ) cancers. However, previous reports using only preoperative variables (preoperative risk models) have poorly predicted postoperative anastomotic leakage. This study aimed to develop a novel risk model for anastomotic leakage using a combination of preoperative, intraoperative, and postoperative variables (perioperative risk model). Clinical data of 20,113 patients with esophageal or GEJ cancer who underwent esophagectomy followed by reconstruction between 2016 and 2019 were retrieved from the National Clinical Database (NCD), a Japanese web-based nationwide registry. Preoperative and perioperative risk models for anastomotic leakage were developed using only preoperative variable and a combination of preoperative, intraoperative, and postoperative variables within 72 h, respectively. The performance of the perioperative risk model was validated using NCD data of 5,147 esophagectomies registered in 2020. In the overall population, 11,360 (45.0%) patients were aged ≥ 75 years, and 81.3% were male. Preoperative variables were comparable between the development and external validation cohorts. Anastomotic leakage was observed in 13.7% and 14.4% of the development and validation cohorts, respectively, and in 13.9% of all patients. The optimism-corrected C-statistics was higher in the perioperative risk model (0.610; 95% CI, 0.599-0.621) than in the preoperative risk model (0.565; 95% CI, 0.554-0.577). In the validation analysis, the C-statistics was 0.602 (95% CI, 0.580-0.623) for predicting anastomotic leakage. Postoperative risk assessment using perioperative variables, including operative factors and early postoperative events, may help surgeons predict anastomotic leakage and improve patient management after esophagectomy.
Research and theory suggest that neuroendocrine functioning, such as diurnal cortisol rhythms, plays an important role in emotional development and expression, but that this functioning can be impacted under conditions of elevated stress. Although mindfulness-based interventions show promise for improving emotional functioning, their effects on cortisol regulation in children remain unclear despite a solid theoretical foundation. This study provides preliminary data from a sample of children (n = 57; mean age = 10 years) on changes in diurnal cortisol rhythms associated with exposure to the Pure Power curriculum which is designed to teach youth yoga techniques, mindfulness, and emotion regulation. A non-randomized comparison design examined outcomes and diurnal cortisol levels among participants from schools that completed the intervention (n = 27) and from students in comparison schools (n = 30) assessed at three time points approximately one year apart. Modeling of diurnal patterns indicated that youth in the intervention schools demonstrated a relative change in their cortisol levels at Time 2 towards a diurnal rhythm associated with less stress. The data provide initial evidence for an association between exposure to a yoga and mindfulness curriculum and neuroendocrine function. The conclusions are limited by the non-randomized design and small sample. Replication with randomized designs and larger samples is needed.
Aging-related metabolic dysregulation and vascular vulnerability contribute substantially to stroke susceptibility, yet subtype-specific metabolic signatures remain incompletely characterized. Employing a nested case-control design within the Taizhou Longitudinal Study, we quantified 296 lipoprotein parameters and 54 metabolites in 1208 stroke-control pairs using nuclear magnetic resonance. Logistic regression estimated subtype-specific associations, and machine learning constructed prediction models for ischemic stroke (IS) and intracerebral hemorrhage (ICH). Distinct metabolic profiles were observed across stroke subtypes. Triglyceride-enriched lipoproteins and several low-molecular-weight metabolites were positively associated with both IS and ICH, whereas apolipoprotein A-related components showed inverse associations, with generally stronger effects observed for IS than for ICH. Age-stratified and interaction analyses revealed age-dependent heterogeneity, especially among histidine and lipoprotein composition measures. To further characterize systemic metabolic vulnerability, we constructed a weighted metabolic risk score (MRS), which was associated with age and statistically accounted for part of the age-stroke association (average causal mediation effects: 0.020 for IS; 0.025 for ICH). MRSs were also positively correlated with age and inflammatory markers, particularly for IS (both P < 0.001). Metabolite-based models improved risk discrimination beyond traditional risk factors for both IS and ICH. These findings identify subtype-specific metabolic signatures of stroke and suggest that circulating metabolomic profiles reflect age-associated metabolic alterations relevant to stroke susceptibility beyond traditional cardiometabolic risk factors.
Approximately three decades ago, in response to the growing demand for rapid and sensitive analysis of small-volume samples, monolithic column technology emerged contemporaneously with other key concepts in analytical chemistry, such as the micro-total analysis system (µTAS) and lab-on-a-chip technology. These innovations attracted considerable attention as paradigm-shifting tools in the field. In the post-genomic era in particular, where miniaturization and high-throughput workflows became critical, monoliths-characterized by their continuous porous structure, high permeability, and low back pressure-were recognized as next-generation separation media, especially in omics-driven research. However, subsequent advances in liquid chromatography-most notably the development of core-shell particle packing materials and the widespread adoption of ultra-high-performance liquid chromatography (UHPLC)-gradually diminished the relative advantages of monolithic columns in standard high-throughput HPLC applications. Despite this shift, their intrinsic features, including ease of fabrication, outstanding flow properties, and flexible moldability into diverse formats, have continued to generate new value. In recent years, applications of monoliths have expanded beyond analytical separations into diverse fields, including biopharmaceutical purification (e.g., antibody drugs), solid-phase extraction, immobilized catalytic systems, and integration into micro- and nanoscale devices. This review provides a comprehensive overview of the three-decade evolution of monolithic column technology, highlighting its historical context, current applications, and emerging roles in both analytical and preparative sciences within the broader context of evolving analytical technologies.
Intimate partner violence (IPV) affects 36% to 50% across all backgrounds, yet only 30% of graduate programs offer IPV training. This interprofessional simulation aimed to improve Doctor of Nursing Practice-Family Nurse Practitioner (DNP-FNP) students' knowledge, attitudes, and skills in IPV identification and management while promoting collaboration with police, social workers, and advocates. Twenty-two DNP-FNP students completed pre- and postintervention Physician Readiness to Manage Intimate Partner Violence Surveys (PREMIS). The four-station high-fidelity simulation included patient interview, physical examination (revealing moulage bruise), assessment, and reporting, followed by debriefing and Danger Assessment training and reflective assignments. Students reported high satisfaction (4.7 to 4.8 on a 5-point scale). Perceived preparation and knowledge improved greatly (p = .0000); actual knowledge increased from 78.4% to 82.8%. The simulation greatly enhanced readiness to address IPV, supporting expansion to more than 275 participants and potential improvements in identification, interprofessional collaboration, and victim outcomes.
Left ventricular thrombus (LVT) in ischemic heart failure carries embolic risk; tools to anticipate persistence are limited. We studied 190 consecutive patients with imaging-confirmed LVT managed with guideline-concordant anticoagulation and serial echocardiography. The primary outcome was 6-month non-regression; 1-year MACE was secondary. We combined classical statistics with explainable machine learning. CatBoost yielded the best discrimination for non-regression (CV-AUC 0.76; test accuracy 0.79). SHAP highlighted left atrial diameter, pulmonary artery pressure, platelet count, and LV end-diastolic diameter as leading predictors. For 1-year outcomes, thrombus size and CHA2DS2-VA were independently associated with MACE (logistic AUC 0.71), whereas "regression vs persistence" alone was not. Baseline remodeling and coagulability markers, captured by an interpretable ML model, stratify early risk of LVT persistence and complement clinical decision-making for imaging follow-up and anticoagulation intensity.