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Brain tumors remain among the most fatal diseases of the central nervous system, and early diagnosis is vital for improving patient survival outcomes. However, conventional diagnostic approaches relying on manual interpretation of MRI scans by radiologists often suffer from subjectivity, inefficiency, and a high rate of missed diagnoses. To overcome these limitations, this study introduces a systematically optimized deep learning framework designed to achieve real-time performance while preserving high detection accuracy. Specifically, we propose the A2C2f-Mona module, which enhances local and medium-range feature perception through multi-scale depthwise convolution and residual connections; design the C2PSA-DyT module, which replaces conventional normalization layers with element-wise normalization to enhance training stability and feature distribution consistency; and introduce the CGAFusion module, which integrates high- and low-level features via a channel attention mechanism, effectively improving the detection of tumors with blurred boundaries and small volumes. Experimental evaluations demonstrate that the proposed approach surpasses YOLOv12n across all performance metrics, achieving a precision of 93.8%, recall of 88.0%, and mAP@0.5 of 94.0%. Notably, the recall for pituitary tumors shows the greatest improvement, while the recognition accuracy for gliomas is also significantly enhanced. Overall, the proposed method achieves simultaneous gains in detection accuracy and stability, underscoring its substantial potential for advancing intelligent diagnosis in medical imaging.

Olfaction feedback systems could be utilized to stimulate human emotion, increase alertness, provide clinical therapy, and establish immersive virtual environments. Currently, the reported olfaction feedback technologies still face a host of formidable challenges, including human perceivable delay in odor manipulation, unwieldy dimensions, and limited number of odor supplies. Herein, we report a general strategy to solve these problems, which associates with a wearable, high-performance olfactory interface based on miniaturized odor generators (OGs) with advanced artificial intelligence (AI) algorithms. The OGs serve as the core technology of the intelligent olfactory interface, which exhibit milestone advances in millisecond-level response time, milliwatt-scale power consumption, and the miniaturized size. Empowered by robust AI algorithms, the olfactory interface shows its great potentials in latency-free mixed reality (MR) and fast olfaction enhancement, thereby establishing a bridge between electronics and users for broad applications ranging from entertainment, to education, to medical treatment, and to human machine interfaces. Liu et al. developed AI-driven, wearable olfactory interfaces with odor generators for realizing latency-free mixed-reality and fast olfaction recovery. This technology enables personalized olfactory feedback and enhanced virtual environments for various applications including education, and clinical treatment.

Chronic wound healing is a complex and long-standing problem, that has been a major and critical clinical concern around the world for years. Recent advances in digital wound dressings open new possibilities for solving the problem. Here, we report a battery-free, fully permeable, skin-adhesive, stretchable electronic wound bandage (iSAFE) for intelligent wound management. This electronic bandage exhibits superior properties in multiple features and can be conformally adhered to the skin wound. In addition, the iSAFE can accurately assess the wound conditions in-situ and thus adaptively perform localized drug release. The results from both in vitro and in vivo studies on animals prove the validity of wound monitoring, wound healing boosting and intelligent closed-loop wound management. Clinical trials on patients across age 18 to 95 with various types of wounds are performed. These results all indicate the unique and universality of the reported technology for wound monitoring and management. Electronic wound bandages have to balance conformability and wound healing properties. Here, the authors develop a smart patch (iSAFE) using biomaterials with bioelectronics to facilitate permeability with waterproofing. This achieves intelligent wound management with real-time wound monitoring and active therapy.

Sustainable Development Goals (SDGs) serve as a reference point in the global policy-making process, with their quantitative evaluation at various scales integrating spatial planning still under exploration. Major Function Oriented Zone (MFOZ) planning in China emerges as an innovative strategy, focusing on ecosystem services to achieve sustainable development. This study takes MFOZ planning as an example, and assesses SDG implementation within the MFOZ framework, focusing on 288 cities. Then, this study analyzes the zoning types of SDG realization status through cluster analysis. Based on this, we explore the influencing factors of the SDGs from the perspective of socioeconomic and environmental characteristics, and ecosystem services, and propose target strategies. The research found that there are four zoning types according to the SDG realization status, including mixed-oriented with high consumption and output (24.3%), non-agriculture-oriented with low consumption and high output (12.5%), agriculture-oriented with low consumption and output (55.9%), and agriculture-oriented with high consumption and output (7.3%) cities. Most cities do not demonstrate high efficiency in resource consumption output, and the realization status of SDGs urgently needs to improve. Socio-economic development during urbanization challenges SDGs, while the traditional environmental measures have limited effects. Ecosystem services could help improve SDGs, including GDP growth rate, and reduce water resource development intensity and carbon emissions. Focusing solely on numerical values of SDGs, such as water efficiency, may harm ecosystem services and go against sustainable development. This research underscores the necessity of adapting SDG strategies to the unique contexts of cities and has practical significance for enabling more targeted and effective strategies for SDG implementation, integrating spatial planning, and aligning local efforts with global sustainability aspirations.

The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections. The SARS-CoV-2 pandemic highlighted our need for methods that allow rapid viral surveillance. Here, authors report a wireless, battery-free and wearable self-diagnosis platform that can continuously capture viral particles, diagnose infection status and evaluate symptom severity via breath and blow.

Pectolinarin and linarin are two major flavone O-glycosides of Cirsium japonicum, which has been used for thousands of years in traditional Chinese medicine. Pharmacological research on pectolinarin and linarin is meaningful and necessary. Here, a process for the purification of pectolinarin and linarin from C. japonicum was established using macroporous resin enrichment followed by prep-HPLC separation. The results show the purity of pectolinarin and linarin reached 97.39% and 96.65%, respectively. The in vitro bioactivities result shows the ORAC values of pectolinarin and linarin are 4543 and 1441 µmol TE/g, respectively, meanwhile their inhibition rate of BSA-MGO-derived AGEs is 63.58% and 19.31% at 2 mg/mL, which is 56.03% and 30.73% in the BSA-fructose system, respectively. The COX-2 inhibition rate at 50 µg/mL of linarin and pectolinarin reached 55.35% and 40.40%, respectively. Furthermore, the in vivo bioassay combining of histopathologic evaluation and biochemical analysis of liver glutamic oxaloacetic transaminase, serum creatinine and TNF-α show pectolinarin can alleviate lipopolysaccharide (LPS)-induced acute liver and kidney injury in mice. Metabolomics analysis shows that pectolinarin attenuates LPS-challenged liver and kidney stress through regulating the arachidonic acid metabolism and glutathione synthesis pathways. Collectively, our work presents a solid process for pectolinarin and linarin purification and has discovered a promising natural therapeutic agent—pectolinarin.

Background and objectiveTetanus is associated with very high mortality, but there is currently no consensus on the mortality and risk factors for hospitalised adult patients with tetanus. Therefore, we conducted this systematic review and meta-analysis to explore the mortality and associated risk factors in hospitalised adult patients with tetanus.DesignSystematic review and meta-analysis.Data sourcesPubMed, Web of Science, The Cochrane Library and Embase, covering the period from 1 January 2000 to 5 February 2024.Eligibility criteriaObservational studies with a focus on the mortality and associated risk factors in hospitalised adult patients with tetanus.Data extraction and synthesisTwo researchers independently reviewed the studies and extracted the data. The pooled effect sizes for mortality and the total number of hospitalised patients with tetanus were calculated, along with the overall pooled mortality and corresponding 95% CI. Risk factors for mortality were determined using relative risk (RR) and 95% CI. The I2 statistic was calculated to describe heterogeneity between studies. Additionally, subgroup and meta-regression analyses were carried out to further explore potential sources of heterogeneity. All statistical analyses were conducted via StataSE V.15.0.ResultsA total of 22 studies were included, comprising 1618 hospitalised adult patients with tetanus. The overall mortality among hospitalised adult patients with tetanus was 32.0% (95% CI: 27.1% to 37.0%). Six risk factors associated with mortality in these patients were identified, including age ≥40 years (RR=1.89, 95% CI: 1.37 to 2.61), incubation period <7 days (RR=2.10, 95% CI: 1.47 to 3.00), onset period <2 days (RR=2.06, 95% CI: 1.30 to 3.29), Ablett classification ≥III (RR=3.40, 95% CI: 1.91 to 6.05), presence of autonomic dysfunction (RR=4.84, 95% CI: 2.36 to 9.94) and the need for mechanical ventilation (RR=2.46, 95% CI: 1.48 to 4.09).ConclusionThe study findings have important implications for clinical practice and public health policy. The high mortality underscored the urgent need to strengthen tetanus prevention strategies, particularly by increasing vaccination coverage and enhancing wound care education in adults aged ≥40 years. The six identified mortality risk factors provided a framework for early risk stratification and targeted interventions in hospitalised patients with tetanus. Meanwhile, more well-designed, large-scale studies are needed for further validation and exploration.PROSPERO registration numberCRD42024533554.

Concrete-filled steel tubes (CFSTs) are widely used in high-rise buildings and bridges, owing to their confinement effect on concrete. The confinement effect can enhance the compressive strength and ductility of the components. During the construction of high-rise buildings or bridges, CFST columns may be subject to an unforeseen preload known as a passive preload, which might impact a structure’s mechanical behavior. Additionally, a deliberate preload called an active preload is applied to a CFST column before application as a design strategy to improve the performance of the CFST. However, only a few studies have evaluated the effects of the two types of preloads on CFST performance. In this study, the eccentric compressive performances of passive and active preloading systems in a circular short CFST column were investigated using finite element numerical simulations. Four representative preloaded CFST columns were compared by analyzing their mechanical behaviors with two-stage loading (preloading and service loading). The influences of the eccentric ratio, concrete compressive strength, steel yield strength, and steel thickness on the load-bearing capacity ratio and M-P curves of the four preloaded CFST columns were evaluated. It was found that in comparison to passive preloaded CFSTs, the overall performance of the active column was satisfactory.

The nutritional composition of bamboo shoots varies significantly across regions, yet the precise environmental drivers and underlying molecular mechanisms remain poorly understood. In particular, the influence of soil properties and climatic factors on key metabolic pathways regulating bamboo shoot quality has not been systematically examined. In this study, we investigate the environmental determinants of nutrient accumulation in Lei bamboo ( Phyllostachys violascens ) shoots by integrating environmental analysis, nutritional profiling, and transcriptomics. We identified soil organic matter, total porosity, and longitude as the primary factors influencing bamboo shoot nutrition, with higher soil organic matter correlating with enhanced nutrient content. Transcriptome analysis revealed that environmental conditions regulate key metabolic pathways, including starch metabolism ( e.g. , BGLU , SPS ) and flavonoid biosynthesis ( e.g. , PAL , 4CL ), ultimately shaping bamboo shoot quality. Based on these findings, we developed a predictive model linking environmental factors, gene expression, and nutritional traits, providing a foundation for precision cultivation strategies. This study provides novel insights into plant-environment interactions governing bamboo shoot nutrition and offers actionable strategies for region-specific cultivation, aligning with consumer demand for healthier bamboo-based products.

This paper proposes a reflective fiber mercury ion sensor based on the surface plasmon resonance (SPR) principle and chitosan (CS)/polyacrylic acid (PAA) multilayer sensitive film. By optimizing the coating parameters of the gold film, the refractive index (RI) sensitivity of the reflective SPR sensor is demonstrated to be 2110.33 nm/RIU. Then, a multi-layer CS/PAA film is fixed on the surface of the gold film as a mercury ion sensitive film to form a reflective SPR fiber mercury ion sensor. Experimental results demonstrate that the sensor can be used to detect different concentrations of mercury ions with a high sensitivity of 0.5586 nm/μM and good specificity and repeatability. Therefore, the reflective SPR fiber mercury ion sensor shows great promise for future applications of environmental monitoring and drinking water safety.