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Scintillators that exhibit X-ray-excited luminescence have great potential in radiation detection, X-ray imaging, radiotherapy, and non-destructive testing. However, most reported scintillators are limited to inorganic or organic crystal materials, which have some obstacles in repeatability and processability. Here we present a facile strategy to achieve the X-ray-excited organic phosphorescent scintillation from amorphous copolymers through the copolymerization of the bromine-substituted chromophores and acrylic acid. These polymeric scintillators exhibit efficient X-ray responsibility and decent phosphorescent quantum yield up to 51.4% under ambient conditions. The universality of the design principle was further confirmed by a series of copolymers with multi-color radioluminescence ranging from green to orange-red. Moreover, we demonstrated their potential application in X-ray radiography. This finding not only outlines a feasible principle to develop X-ray responsive phosphorescent polymers, but also expands the potential applications of polymer materials with phosphorescence features. The authors achieved the X-ray-excited organic phosphorescent scintillation from copolymers through copolymerization of bromine-substituted chromophores and acrylic acid and demonstrated their potential application in X-ray radiography.

Dynamic luminescence behavior by external stimuli, such as light, thermal field, electricity, mechanical force, etc., endows the materials with great promise in optoelectronic applications. Upon thermal stimulus, the emission is inevitably quenched due to intensive non-radiative transition, especially for phosphorescence at high temperature. Herein, we report an abnormal thermally-stimulated phosphorescence behavior in a series of organic phosphors. As temperature changes from 198 to 343 K, the phosphorescence at around 479 nm gradually enhances for the model phosphor, of which the phosphorescent colors are tuned from yellow to cyan-blue. Furthermore, we demonstrate the potential applications of such dynamic emission for smart dyes and colorful afterglow displays. Our results would initiate the exploration of dynamic high-temperature phosphorescence for applications in smart optoelectronics. This finding not only contributes to an in-depth understanding of the thermally-stimulated phosphorescence, but also paves the way toward the development of smart materials for applications in optoelectronics. In thermally stimulated phosphorescent materials a thermal stimulus inevitably quenches the emission due to intensive non radiative transition. Here, the authors report an abnormal thermally stimulated phosphorescence behavior in organic phosphors and show enhancement of phosphorescence and change of the emission color upon temperature increase.

X-ray-induced photodynamic therapy utilizes penetrating X-rays to activate reactive oxygen species in deep tissues for cancer treatment, which combines the advantages of photodynamic therapy and radiotherapy. Conventional therapy usually requires heavy-metal-containing inorganic scintillators and organic photosensitizers to generate singlet oxygen. Here, we report a more convenient strategy for X-ray-induced photodynamic therapy based on a class of organic phosphorescence nanoscintillators, that act in a dual capacity as scintillators and photosensitizers. The resulting low dose of 0.4 Gy and negligible adverse effects demonstrate the great potential for the treatment of deep tumours. These findings provide an optional route that leverages the optical properties of purely organic scintillators for deep-tissue photodynamic therapy. Furthermore, these organic nanoscintillators offer an opportunity to expand applications in the fields of biomaterials and nanobiotechnology. Conventional X-ray-induced photodynamic therapy usually requires heavy-metal-containing inorganic scintillators and organic photosensitizers to generate singlet oxygen. Here, the authors develop an organic phosphorescent nanoscintillator for low-dose X-ray-induced photodynamic therapy of deep tumours.

Luminescent materials with narrowband emission show great potential for diverse applications in optoelectronics. Purely organic phosphors with room-temperature phosphorescence (RTP) have made significant success in rationally manipulating quantum efficiency, lifetimes, and colour gamut in the past years, but there is limited attention on the purity of the RTP colours. Herein we report a series of closed-loop molecules with narrowband phosphorescence by multiple resonance effect, which significantly improves the colour purity of RTP. Phosphors show narrowband phosphorescence with full width at half maxima (FWHM) of 30 nm after doping into a rigid benzophenone matrix under ambient conditions, of which the RTP efficiency reaches 51.8%. At 77 K, the FWHM of phosphorescence is only 11 nm. Meanwhile, the colour of narrowband RTP can be tuned from sky blue to green with the modification of methyl groups. Additionally, the potential applications in X-ray imaging and display are demonstrated. This work not only outlines a design principle for developing narrowband RTP materials but also makes a major step forward extending the potential applications of narrowband luminescent materials in optoelectronics. Luminescent materials with narrowband emissions are vital for optoelectronic applications. Here, the authors achieve room temperature phosphorescence with a FWHM of 30 nm through the multiple resonance effect and showcase its practical application in X-ray imaging.

Intermolecular interactions, including attractive and repulsive interactions, play a vital role in manipulating functionalization of the materials from micro to macro dimensions. Despite great success in generation of ultralong organic phosphorescence (UOP) by suppressing non-radiative transitions through attractive interactions recently, there is still no consideration of repulsive interactions on UOP. Herein, we proposed a feasible approach by introducing carboxyl groups into organic phosphors, enabling formation of the intense repulsive interactions between the isolated molecules and the matrix in rigid environment. Our experimental results show a phosphor with a record lifetime and quantum efficiency up to 3.16 s and 50.0% simultaneously in film under ambient conditions. Considering the multiple functions of the flexible films, the potential applications in anti-counterfeiting, afterglow display and visual frequency indicators were demonstrated. This finding not only outlines a fundamental principle to achieve bright organic phosphorescence in film, but also expands the potential applications of UOP materials. Despite great success in generation of ultralong organic phosphorescence (UOP) by suppressing non-radiative transitions through attractive interactions, consideration of repulsive interactions on UOP remains largely unexplored. Here, the authors introduce carboxyl groups into organic phosphors, enabling formation of the intense repulsive interactions between the isolated molecules and the matrix in rigid environment.

Dengue is an arthropod-borne infectious disease caused by dengue virus (DENV) infection and transmitted by mosquitoes. Approximately 50-100 million people are infected with DENV each year, resulting in a high economic burden on both governments and individuals. Here, we conducted a systematic review and meta-analysis to summarize information regarding the epidemiology, clinical characteristics, and serotype distribution and risk factors for global dengue outbreaks occurring from 1990 to 2015. We searched the PubMed, Embase and Web of Science databases through December 2016 using the term \"dengue outbreak.\" In total, 3,853 studies were identified, of which 243 studies describing 262 dengue outbreaks met our inclusion criteria. The majority of outbreak-associated dengue cases were reported in the Western Pacific Region, particularly after the year 2010; these cases were primarily identified in China, Singapore and Malaysia. The pooled mean age of dengue-infected individuals was 30.1 years; of the included patients, 54.5% were male, 23.2% had DHF, 62.0% had secondary infections, and 1.3% died. The mean age of dengue patients reported after 2010 was older than that of patients reported before 2010 (34.0 vs. 27.2 years); however, the proportions of patients who had DHF, had secondary infections and died significantly decreased after 2010. Fever, malaise, headache, and asthenia were the most frequently reported clinical symptoms and signs among dengue patients. In addition, among the identified clinical symptoms and signs, positive tourniquet test ( = 4.86), ascites ( = 13.91) and shock ( = 308.09) were identified as the best predictors of dengue infection, DHF and mortality, respectively (both < 0.05). The main risk factors for dengue infection, DHF and mortality were living with uncovered water container ( = 1.65), suffering from hypotension ( = 6.18) and suffering from diabetes mellitus ( = 2.53), respectively (all < 0.05). The serotype distribution varied with time and across WHO regions. Overall, co-infections were reported in 47.7% of the evaluated outbreaks, and the highest pooled mortality rate (2.0%) was identified in DENV-2 dominated outbreaks. Our study emphasizes the necessity of implementing programs focused on targeted prevention, early identification, and effective treatment.

The iron and steel industry has made an important contribution to China’s economic development, and sinter accounts for 70–80% of the blast furnace feed charge. However, the average grade of domestic iron ore is low, and imported iron ore is easily affected by transportation and price. The intelligent ore blending model with an intelligent algorithm as the core is studied. It has a decisive influence on the development of China’s steel industry. This paper first analyzes the current situation of iron ore resources, the theory of sintering ore blending, and the difficulties faced by sintering ore blending. Then, the research status of the neural network algorithms, genetic algorithms, and particle swarm optimization algorithms in the intelligent ore blending model is analyzed. On the basis of the neural network algorithm, genetic algorithm and particle swarm algorithm, linear programming method, stepwise regression analysis method, and partial differential equation are adopted. It can optimize the algorithm and make the model achieve better results, but it is difficult to adapt to the current complex situation of sintering ore blending. From the sintering mechanism, sintering foundation characteristics, liquid phase formation capacity of the sinter, and the influencing factors of sinter quality were studied, it can carry out intelligent ore blending more accurately and efficiently. Finally, the research of intelligent sintering ore blending model has been prospected. On the basis of sintering mechanism research, combined with an improved intelligent algorithm. An intelligent ore blending model with raw material parameters, equipment parameters, and operating parameters as input and physical and metallurgical properties of the sinter as output is proposed.

Objectives Despite the significant improvement in survival rates due to antiretroviral therapy, opportunistic infections continue to pose a major health risk for individuals living with HIV. As a key anatomical intersection of the upper respiratory and digestive tracts, the pharyngeal microbiome during HIV infection remains poorly characterized. This study aimed to compare the composition of bacterial and fungal communities in the pharynx between HIV-infected individuals and healthy controls, and to investigate their association with host immune status. Methods Throat swab samples were collected from 70 HIV-infected individuals—stratified into severe, moderate, and no/mild immunosuppression groups based on CD4⁺ T-cell counts—and 18 healthy controls. Microbial composition was assessed using 16S rRNA and internal transcribed spacer (ITS) amplicon sequencing. Results Bacterial alpha diversity was significantly reduced in the severe immunosuppression group (CD4⁺ T cells < 200/µL) compared to other groups, whereas fungal alpha diversity did not differ significantly across groups. Beta-diversity analysis revealed a distinct bacterial community structure in the severe immunosuppression group. Fungal communities, however, differed significantly between all HIV-infected individuals and healthy controls. At the genus level, the severe immunosuppression group exhibited a decrease in commensal bacteria such as Prevotella and an increase in Halomonas . Additionally, Candida was significantly enriched in the severe immunosuppression group, while Exophiala levels were elevated across all HIV-infected groups. Conclusions The pharyngeal microbiome of HIV infected individuals undergoes significant changes, with bacterial community disorder associated with immune suppression, while the fungal community changes are more closely related to the HIV infection status of the individuals. The enrichment of Candida in individuals with severe immune suppression is more appropriately interpreted as a manifestation of fungal dysbiosis associated with advanced immunosuppression and a potential indicator of increased susceptibility to oropharyngeal candidiasis, rather than as a diagnostic biomarker of overt disease. Clinical register number Not applicable.

Among damage imaging methods based on Lamb waves, the Minimum Variance Distortionless Response (MVDR) method adaptively calculates channel weights to suppress interference signals, improving imaging resolution and the signal-to-noise ratio (SNR). However, the MVDR method involves matrix inversion, which introduces a high computational burden to the implementation process and makes real-time damage detection challenging. We propose constructing a Convolutional-Neural-Network (CNN)-based network architecture based on the Delay-and-Sum (DAS) beamforming method. This architecture replaces the MVDR’s adaptive weight calculation by establishing a nonlinear mapping from multi-channel data to weighting factors, enabling efficient high-resolution Lamb wave damage imaging with an enhanced SNR. To verify the effectiveness and imaging performance of the CNN-based method, damage in an aluminum plate is imaged using both simulation and experimental methods. The imaging results are compared and analyzed against those of the DAS and MVDR methods. The results show that the proposed CNN-based adaptive Lamb wave beamforming method, which combines the advantages of a high resolution and signal-to-noise ratio, as well as rapid imaging, can provide reference and support for real-time Lamb-wave-based Structural Health Monitoring (SHM).

Androgenetic alopecia (AGA) is characterized by perifollicular micro-inflammation, although its precise trigger remains elusive. Given that the hair follicle harbors a distinct microbiota which may modulate local immune responses, this study aimed to comprehensively profile the bacterial and fungal microbiome within the deep hair follicles of AGA patients versus healthy controls, and to evaluate the influence of disease severity, age, sex, and geographical environment. We recruited 96 subjects (72 AGA patients and 24 healthy controls), collecting a total of 192 plucked hair follicle samples from the vertex and occipital scalp. Bacterial 16S rRNA (V3-V4) and fungal ITS regions were sequenced using the Illumina HiSeq platform. Bioinformatics pipelines were employed to analyze α- and β-diversity, as well as taxonomic composition, across multiple stratifications: disease stage, scalp region, age, sex, and geographical location. Bacterial community structure showed relative stability between groups. In contrast, fungal communities were markedly dysbiotic in AGA. A key finding was the significant depletion of the commensal yeast in AGA follicles compared to controls ( < 0.01). Conversely, opportunistic taxa such as and were enriched in advanced disease stages. Notably, microbial α-diversity increased with both disease severity and age, indicating a disruption of the follicular niche (\"niche collapse\"). Male AGA patients exhibited distinct fungal shifts compared to females, and geographical location significantly shaped the follicular microbiome in patients but not in healthy controls. Androgenetic alopecia involves fungal dysbiosis with loss of commensal Malassezia and gain of opportunistic microbes. Driven by host and environmental factors, this reframes AGA as an ecological imbalance, opening avenues for microbiome-targeted therapies.