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Hospital-at-home care in Singapore: A qualitative exploration of health system partners’ state of readiness, and policy and implementation strategies essential to support scale-up

Rationale Many Hospital-at-Home (HaH) programs have proliferated in recent years to cope with the increasing demands of an ageing population and global hospital bed shortages. Singapore has implemented its own version, Mobile Inpatient Care at Home (MIC@Home). However, many HaH programs remain small, raising concerns about their scalability. Hence, a clear implementation strategy is needed. Objectives To address: (1) What is the readiness of Singapore’s health system partners to scale up MIC@Home? and (2) What multi-level strategies are necessary for the successful scaling of MIC@Home in Singapore?. Methods A descriptive qualitative study design was used. Through purposive sampling, 32 participants (16 HaH clinicians, 11 enabling units, and 5 regulators) were recruited and semi-structured interviews were conducted. The interviews were transcribed using Trint and thematically analysed using Atlas.ti via Braun and Clarke’s six-step inductive approach. This analysis was guided by the Health Policy and Partnership Readiness Assessment Framework. Results The key themes were: (1) perceived readiness to scale, focusing on stakeholder motivation and capacity; (2) implementation strategies, highlighting the need for training, collaborations, and operational refinements; and (3) policy strategies, addressing financial sustainability, governance, and regulation. MIC@Home is seen as a viable solution to acute bed shortages, with high readiness for scaling. Effective governance requires stakeholder buy-in, organizational alignment, partnerships, and adequate manpower. Regulatory strategies should be adjusted to sustain MIC@Home and improve patient access. For service provision, standardized guideline and data is vital to prove MIC@Home’s effectiveness and safety, while convincing clinicians and patients of its value will increase acceptability. Finally, refining governance and establishing regulations for minimum care standards will support smooth operations and long-term success. Conclusion Despite the challenges of scaling MIC@Home, the findings underscore the potential of MIC@Home to enhance healthcare delivery through identifying readiness and strategies to position MIC@Home as an alternative to traditional care.

EZH-2 expression and prognostic significance in patients with low-grade non-Hodgkin lymphoma

Health assessment of snacks and desserts in Guizhou Province: Analysis of fatty acids and sugar content

Introduction Dietary patterns, particularly the excessive consumption of snacks high in fats and sugars, remain a pivotal factor producing adverse impact on the global prevalence of obesity and chronic diseases. However, the current situation is that there is insufficient study on the nutritional value and health risks of local snacks and desserts of Guizhou Province. To fill this gap, this study aimed to analyze the fatty acid (FA) composition and sugar content of popular snacks and desserts in Guizhou Province. Methods A comprehensive nutritional evaluation was conducted on local snacks and desserts in Guizhou province, with a focus on the FA profile and five sugars (glucose, fructose, sucrose, maltose, and lactose). The study examined how cooking methods (steaming, baking, frying) and food classification (traditional vs. non-traditional) influence the nutritional profiles of these foods, which are predominantly made from rice, wheat, and cream. Results Rice-based foods, particularly those steamed using traditional methods, showed superior nutritional profiles. They had significantly lower crude fat (7.35±1.50 g/100g) and total FA (6.10±1.55 g/100g) compared to other methods. Trans fatty acid (TFA) content was minimal (0.0179±0.0137 g/100g), and atherogenic index (AI) and thrombogenic index (TI) were low at 0.19±0.07 and 0.38±0.27, respectively. Rice-based foods also had an acceptable sugar content with no lactose, suitable for lactose-intolerant individuals. Among the rice-based foods, Rice Tofu (RT) had the best performance with the lowest Crude Fat (5.98 g/100g), AI (0.04), TI (0.05), highest monounsaturated FA (MUFA) content (3.11 g/100g), polyunsaturated FA (PUFA) to saturated FA (SFA) ratio (8.48), and n-3PUFA/n-6PUFA ratio (0.25), along with acceptable sugar levels. Conclusion The nutritional value of snacks varies widely due to differences in raw materials, cooking methods, and traditional preparation techniques. Traditional steamed rice products, especially RT, offer the best nutritional profile and can be promoted as representative healthy traditional foods in Guizhou Province.

The 3D genome of plasma cells in multiple myeloma

Alpinetin protects against iron overload related osteoarthritis via NRF2/HO-1 pathway

Context Alpinetin(APT) is a natural product with anti-inflammatory and antioxidant effects. Iron overload has been recognized in recent years as a new way to exacerbate osteoarthritis. Objective This study evaluated the effects of ATP on iron overload related osteoarthritis. Materials and methods C57BL/6J mice were randomly allocated to five groups as follows (n = 10 mice each): (1) sham; (2) destabilized medial meniscus(DMM); (3) DMM + ID; (4) DMM + ID + APT-L (50 mg/kg APT gavage daily); (5) DMM + ID + APT-H (100 mg/kg APT gavage daily). The chondrocytes treated by FAC (100μM) were used as an in vitro model of iron overload and the effect of APT was observed. Flow cytometry, fluorescence microscopy, Western blot, qRT-PCR and micro-CT were used to detect the mechanism of action of the APT. Result Our studies showed that APT improved the viability of chondrocytes induced by iron overload. APT can reduce apoptosis of chondrocytes (19.41 ± 2.12% vs. 9.82 ± 1.74%). Furthermore, APT was found significantly attenuated ROS accumulation (2.04 ± 0.31 vs. 1.44 ± 0.15-fold) of chondrocytes through upregulating antioxidant genes NRF2 (1.18 ± 0.13 vs. 1.55 ± 0.17-fold) and HO-1 (1.27 ± 0.15 vs. 1.77 ± 0.20-fold). In vivo experiments revealed that APT attenuated cartilage damage (OARSI score 5.75 ± 1.32 vs. 3.75 ± 0.96) and subchondral bone proliferation in iron overload osteoarthritis mice. Conclusions Our results show that APT can attenuate iron overload-induced cartilage damage in vivo and in vitro via the NRF2/HO-1 pathway. We demonstrated for the first time that APT has promising applications in iron overload diseases.

Survival outcomes in secondary and primary acute lymphoblastic leukemia: a systematic review and meta-analysis

Viral acute respiratory illnesses in elite athletes: A 12-month controlled follow-up study

Background Viral acute respiratory illnesses (ARIs) are the most common acute illnesses in elite athletes. However, the occurrence, aetiology, and clinical manifestations of viral ARIs in athletes remain unclear. Methods Twenty-four elite cross-country skiers and 22 elite orienteers were followed for 12 months. Thirty-two normally exercising, healthy young adults were recruited as controls. Occurrences of ARI symptoms were collected weekly with a digital questionnaire. Nasal swabs for respiratory viruses were collected at the onset of symptoms and once monthly when asymptomatic. Results A significantly higher incidence density (per person per year) of ARI during the 12-month follow-up period was detected in the skiers compared to the controls (mean (SD) 3.39 (2.13) vs. 2.11 (1.98), respectively, p = 0.037) whereas the differences between the skiers and orienteers (mean (SD) 2.39 (1.07)) and between the orienteers and controls did not reach statistical significance (p = 0.053 and 0.506, respectively). The COVID-19 pandemic prevention measures and lockdown dramatically eliminated the occurrence of ARIs in all study groups. ARI episodes were shorter and milder in the orienteers (not studied in the skiers) compared to the controls (p = 0.001 and p = 0.001). A combination of international flights and participation in a competition was associated with a significant risk of an ARI episode in the skiers (p = 0.048). Rhinoviruses (54.1%) and seasonal coronaviruses (21.6%) were the most common viruses detected in all study groups. Conclusion The incidence of ARIs was higher among the skiers compared to the orienteers and the controls. However, ARI episodes were shorter and milder in the orienteers compared to the controls.

CleanSeqU algorithm for decontamination of catheterized urine 16S rRNA sequencing data

“Stay committed on the frontlines”: sustainability of the activism of social workers in Guiyang, China

Social work has played an increasingly important role in social governance, service provision and driving for social change in China. Despite of the advancement of social work at the macro level in the country, substantial challenges remain to the sustainability of activism of social workers under the current social and economic context in China. Yet the fundamental reasons that underpin social workers’ persistence in activism haven’t been well investigated. By following the sustained commitment theory, the researchers investigated how and why frontline social workers sustain their activism over time. Qualitative research was conducted with 15 frontline social workers from local organizations in Guiyang, Guizhou Province, China. The findings highlight the role of “creativity” in maintaining activism of social workers in a way that both challenge and advance the sustained commitment theory. Instead of being confined to a fixed set of creative actions described by the theory, this study stresses the creativity of social workers in addressing challenges and generating feasible strategies in specific contexts. An essential prerequisite “confidence” for creativity in sustaining activism in social work was introduced. This study contributes to a deeper understanding of sustained activism in social work through the lens of social workers and the enhancement of the professional support for social workers in China.

Association between estimated glucose disposal rate and the risk of MAFLD in American adults: a cross-sectional study

Overlapping point cloud registration algorithm based on KNN and the channel attention mechanism

With the advancement of sensor technologies such as LiDAR and depth cameras, the significance of three-dimensional point cloud data in autonomous driving and environment sensing continues to increase.Point cloud registration stands as a fundamental task in constructing high-precision environmental models, with particular significance in overlapping regions where the accuracy of feature extraction and matching directly impacts registration quality. Despite advancements in deep learning approaches, existing methods continue to demonstrate limitations in extracting comprehensive features within these overlapping areas. This study introduces an innovative point cloud registration framework that synergistically combines the K-nearest neighbor (KNN) algorithm with a channel attention mechanism (CAM) to significantly enhance feature extraction and matching capabilities in overlapping regions. Additionally, by designing an effectiveness scoring network, the proposed method improves registration accuracy and enhances system robustness in complex scenarios. Comprehensive evaluations on the ModelNet40 dataset reveal that our approach achieves markedly superior performance metrics, demonstrating significantly lower root mean square error (RMSE) and mean absolute error (MAE) compared to established methods including iterative closest point (ICP), Robust & Efficient Point Cloud Registration using PointNet (PointNetLK), Go-ICP, fast global registration (FGR), deep closest point (DCP), self-supervised learning for a partial-to-partial registration (PRNet), and Iterative Distance-Aware Similarity Matrix Convolution (IDAM). This performance advantage is consistently maintained across various challenging conditions, including unseen shapes, novel categories, and noisy environments. Furthermore, additional experiments on the Stanford dataset validate the applicability and robustness of the proposed method for high-precision 3D shape registration tasks.

Eco-friendly bioactives from Nyctanthes arbor-tristis (L.) for targeted control of Aedes aegypti and Culex quinquefasciatus with reduced impact on Toxorhynchites splendens

MSD: Multi-stage deception for data privacy protection

With the exponential growth of electronically transmitted and stored data, ensuring data privacy and security has become a fundamental challenge for organizations and enterprises. Traditional encryption methods have limitations, such as vulnerability to advanced attacks and high computational complexity, that lead to the exploration of complementary strategies like deception techniques for enhanced protection. These methods aim to mislead unauthorized users by presenting protected data as if it were authentic, but the attack resilience is still insufficient. Multi-stage deception (MSD) methods leverage multiple deception strategies, such as complement, swapping, and stack reversal, to improve data protection levels and resistance against decryption attempts. Combining these techniques addresses gaps in single-stage approaches and offers a more robust defense. The proposed MSD method incorporates a classification of encryption and deception techniques and introduces a novel evaluation approach targeting critical performance factors. A tailored pseudocode algorithm is designed to optimize deception for various attribute types, validated through simulations. Simulation results reveal that the MSD method achieves a 100% value change in the first stage and 92% in the second stage, with an overall accuracy exceeding 95%. These findings demonstrate the method’s effectiveness in elevating data protection levels while maintaining low computational complexity. The study highlights the potential of multi-stage deception as a powerful tool for safeguarding sensitive information, achieving superior performance in data security. By offering a scalable and adaptable framework, the MSD method addresses emerging challenges in data protection while setting the stage for further advancements.

Effect of hydrogel rectal spacer on seminal vesicle inter-fraction motion during prostate stereotactic body radiotherapy

A non-genotoxic stem cell therapy boosts lymphopoiesis and averts age-related blood diseases in mice

Abstract Hematopoietic stem cell (HSC) transplantation offers a cure for a variety of blood disorders, predominantly affecting the elderly; however, its application, especially in this demographic, is limited by treatment toxicity. In response, we employ a murine transplantation model based on low-intensity conditioning protocols using antibody-mediated HSC depletion. While aging presents a significant barrier to effective HSC engraftment, optimizing HSC doses and non-genotoxic targeting methods greatly enhance the long-term multilineage activity of the transplanted cells. We demonstrate that young HSCs, once effectively engrafted in aged hosts, improve hematopoietic output and ameliorate age-compromised lymphopoiesis. This culminated in a strategy that robustly mitigates disease progression in a genetic model of myelodysplastic syndrome. These results suggest that non-genotoxic HSC transplantation could fundamentally change the clinical management of age-associated hematological disorders, offering a prophylactic tool to delay or even prevent their onset in elderly patients.

A hybrid PSO-FFNN approach for optimized seismic design and accurate structural response prediction in steel moment-resisting frames

The first steel is the most prevalent material used in building. Steel’s intrinsic hardness and durability make it appropriate for different uses, but its greater adaptability makes it ideal for seismic design. The brittle fracture occurred in welded moment connections of steel structures, which were originally thought to be ductile for resistance to earthquakes. The research aims to optimize structural parameters in steel structure seismic design. This paper presents an effective technique for the best seismic design of steel structures, which consists of two computational methodologies. First, particle swarm optimization (PSO) was presented to accurately define the structural characteristics in the seismic design of steel constructions, then a feed-forward neural network (FFNN) to determine unconventional seismic design methodologies for steel frameworks, precisely forecast the structural responses, and improve seismic resistance and dependability under dynamic conditions by using high-tech components and technological advancements. This study presents designing a realistic storey steel moment-resisting frame (MRF) structure and maximum weight under full seismic loading. The outcome demonstrates the reduction in generations that was accomplished during the optimization procedure. Although the PSO method in the paper converges in lower generations, the process indeed requires a significant amount of computing power. The FFNN approach involves the suggestion of a neural network model that works well to predict the necessary structural reactions during optimization. The proposed model considerably minimizes the total computation time. Study aims to improve the seismic analysis of steel using PSO along with forecasting structural responses using a network of feed-forward neural networks (FFNN) to enhance accuracy and reduce the computation time (2.4 min). The proposed FFNN model is more accurate than earlier methods, with the lowest MAPE values in S_IO (3.0661), S_LS (3.562), and S_CP (3.9252). Moreover, it reveals the highest predictive precision with the lowest RRMSE values of 0.0231 (S_IO), 0.0281 (S_LS), and 0.0314 (S_CP). Moreover, the FFNN model has a competitive run time of 2.4 minutes while possessing good goodness-of-fit, with 1.0096, 1.0995, and 0.9925 of R2 for S_IO, S_LS, and S_CP, respectively. As compared to WCFBP-RB, the proposed PSO+FFNN model has better prediction for S_IO, where the predicted value of 0.7879 is almost identical to the actual value of 0.8000. As compared to WCFBP-RB, the model predicts 1.4085 for S_LS, while the actual value is 1.4388. For S_CP, PSO+FFNN predicts 1.8621, which is more precise than WCFBP-RB and almost equals the actual figure of 1.9000.

Atom economic closed-loop recycling of thermoset polyurethane foams

KDTMD: Knowledge distillation for transportation mode detection based on KAN

With the progress in sensor technology and the spread of mobile devices, transportation mode detection (TMD) is gaining importance for health and urban traffic improvements. As mobile devices become more lightweight, they require more efficient, low-power models to handle limited resources effectively. Despite extensive research on TMD, challenges remain in capturing non-stationary temporal dynamics and nonlinear fitting capabilities. Additionally, many existing models exhibit high space complexity, making lightweight deployment on devices with limited computing and memory resources difficult. To address these issues, we propose a novel deep TMD model based on discrete wavelet transform (DWT) and knowledge distillation (KD), called KDTMD. This model consists of two main modules, i.e., DWT and KD. For the DWT module, since non-stationary time variations and event distribution shifts complicate sensor time series analysis, we use the DWT modules to disentangle the sensor time series into two parts: a low-frequency part that indicates the trend and a high-frequency part that captures events. The separated trend data is less influenced by event distribution shifts, effectively mitigating the impact of non-stationary time variations. For the KD module, it includes the teacher model and student model. Specifically, for teacher model, to address the nonlinearities and interpretability, we incorporate T-KAN, which is composed of multiple layers of linear KAN that employ learnable B-spline functions to achieve a richer feature representation with fewer parameters. For student model, we develop the S-CNN, which is trained efficiently by T-KAN through KD. The KDTMD model achieves 97.27% accuracy and 97.29% F1-Score on the SHL dataset, and 96.56% accuracy and 96.72% F1-Score on the HTC dataset. Additionally, the parameters of the KDTMD model are only about 10% of the smallest baseline.

Vulnerability of power distribution networks to local temperature changes induced by global climate change

Abstract Global climate change (GCC) triggers a chain effect, converting temperature pattern changes into variations in blackout risk for power distribution grids (DGs). This occurs through GCC’s impacts on electricity supply, demand, and infrastructure, which shift the DG’s safe-operation boundary and power flow. This study presents a model integration framework to assess the associated blackout risk, showing that GCC raises blackout risks during peak hours by 4–6%, depending on Gross Domestic Product growth. Kirchhoff’s laws amplify these effects, creating nonlinear risk trajectories. Analysis of the chain effect suggests adaptation strategies, including reshaping grid topology and pairing temperature-sensitive users with robust buses. Index-based analysis reveals that over 20% of the U.S. requires at least a 10% DG capacity increase before 2050, with six states exceeding 20%. Europe faces a more moderate impact. These findings highlight the need for policymakers to prioritize peak-load management and address nonlinear risks across regions.

Complications of image-guided liver biopsies: Results of a nationwide database analysis

Background and aims Liver biopsy is the gold standard for evaluating liver diseases, the diagnosis of liver fibrosis or liver cirrhosis and malignancy. However, it is susceptible to complications, and safety data on liver biopsies remain scarce. The following study examined the complication rates following percutaneous liver biopsies. Methods We performed a study using data collected by the German interventional radiology society (DeGIR) from 2018 to 2021 of elective percutaneous liver biopsies. Clinical and hematological parameters, technical features and adverse events were retrospectively examined. Results From 2018 to 2021, a total of 12117 percutaneous liver biopsies were performed in 194 participating centers in Germany. Complications occurred in 235 biopsies (1.9%), of which 195 (1.6%) were major adverse events. Minor complications in the form of procedural hypotension and pain occurred in 7 and 33 cases (0.06% and 0.3%, respectively). Major complications such as bleeding, organ injury and pneumothorax were observed in 166, 3 and 26 cases (1.4%, 0.02% and 0.2%). Three subjects (0.02%) died as a result of massive intraperitoneal bleeding. Major and bleeding complications were significantly more frequently observed in patients with thrombocytopenia (p < 0.001) as well as in patients undergoing computed tomography (CT)-guided procedure compared to ultrasound-guided one (p < 0.001). Moreover, general and bleeding complication rates significantly differed by the liver segment biopsied (p < 0.001). In contrast, the type of needle size used (p = 0.323), internationalized ratio (INR) (p = 0.09), aPTT (p = 0.98), gender (p = 0.83), age (p = 0.08) and the number of biopsies (p = 0.91) performed did not impact the frequency of major adverse events. By multivariate logistic regression analysis, platelet count, the imaging modality used (CT vs. ultrasound-guided) and the liver segment biopsied were identified as independent risk factors of post-biopsy bleeding (p < 0.001 each). Conclusion Percutaneous liver biopsies are safe with rare procedural morbidity. Our data confirm previous data by showing that post-procedural bleeding was not associated with INR and aPTT in patients undergoing invasive procedures. However, measurement of platelet count is indicated to identify patients with increased procedural bleeding risk. Moreover, our findings suggest that patients with liver cirrhosis as well as patients with complex findings and difficult localizations could benefit from intensified monitoring post-procedural.