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Designing electrocatalysts with high-performance for both reduction and oxidation reactions faces severe challenges. Here, the uniform and ultrasmall (~3.4 nm) high-entropy alloys (HEAs) Pt 18 Ni 26 Fe 15 Co 14 Cu 27 nanoparticles are synthesized by a simple low-temperature oil phase strategy at atmospheric pressure. The Pt 18 Ni 26 Fe 15 Co 14 Cu 27 /C catalyst exhibits excellent electrocatalytic performance for hydrogen evolution reaction (HER) and methanol oxidation reaction (MOR). The catalyst shows ultrasmall overpotential of 11 mV at the current density of 10 mA cm −2 , excellent activity (10.96 A mg −1 Pt at −0.07 V vs. reversible hydrogen electrode) and stability in the alkaline medium. Furthermore, it is also the efficient catalyst (15.04 A mg −1 Pt ) ever reported for MOR in alkaline solution. Periodic DFT calculations confirm the multi-active sites for both HER and MOR on the HEA surface as the key factor for both proton and intermediate transformation. Meanwhile, the construction of HEA surfaces supplies the fast site-to-site electron transfer for both reduction and oxidation processes. The design of nanostructured catalysts plays a key role in the electrocatalytic redox reaction performances. Here, authors prepared uniform and small-sized high-entropy alloy PtNiFeCoCu nanoparticles that showed improved activities for H 2 evolution methanol oxidation reactions.

Background Cervical cancer is an important global health problem. In this study we aimed to analyze trends in cervical cancer at the global, regional, and national levels from 1990 to 2019, to inform health service decision-making. Methods Data on cervical cancer was extracted from the Global Burden of Disease study, 2019. Trends in cervical cancer burden were assessed based on estimated annual percentage change (EAPC) and age-standardized rate (ASR). Results Globally, decreasing trends were observed in incidence, death, and disability adjusted life years (DALYs) of cervical cancer from 1990 to 2019, with respective EAPCs of − 0.38 (95% confidence interval [CI]: − 0.41 to − 0.34), − 0.93 (95%CI: − 0.98 to − 0.88), and − 0.95 (95 CI%: − 1.00 to − 0.90). Meanwhile, decreasing trends were detected in most sociodemographic index (SDI) areas and geographic regions, particularly death and DALYs in Central Latin America, with respective EAPCs of − 2.61 (95% CI: − 2.76 to − 2.46) and − 2.48 (95% CI: − 2.63 to − 2.32); hhowever, a pronounced increasing trend in incidence occurred in East Asia (EAPC = 1.33; 95% CI: 1.12 to 1.55). At the national level, decreasing trends in cervical cancer were observed in most countries/territories, particularly DALYs in the Maldives (EAPC = − 5.06; 95% CI: − 5.40 to − 4.72), Whereas increasing trends were detected in Lesotho, Zimbabwe, and Bulgaria. Conclusions Slowly decreasing trends in cervical cancer were detected worldwide from 1990 to 2019. Cervical cancer remains a substantial health problem for women globally, requiring more effective prevention and control strategies.

Multi-modal (vision-language) models, such as CLIP, are replacing traditional supervised pre-training models (e.g., ImageNet-based pre-training) as the new generation of visual foundation models. These models with robust and aligned semantic representations learned from billions of internet image-text pairs and can be applied to various downstream tasks in a zero-shot manner. However, in some fine-grained domains like medical imaging and remote sensing, the performance of multi-modal foundation models often leaves much to be desired. Consequently, many researchers have begun to explore few-shot adaptation methods for these models, gradually deriving three main technical approaches: (1) prompt-based methods, (2) adapter-based methods, and (3) external knowledge-based methods. Nevertheless, this rapidly developing field has produced numerous results without a comprehensive survey to systematically organize the research progress. Therefore, in this survey, we introduce and analyze the research advancements in few-shot adaptation methods for multi-modal models, summarizing commonly used datasets and experimental setups, and comparing the results of different methods. In addition, due to the lack of reliable theoretical support for existing methods, we derive the few-shot adaptation generalization error bound for multi-modal models. The theorem reveals that the generalization error of multi-modal foundation models is constrained by three factors: domain gap, model capacity, and sample size. Based on this, we propose three possible solutions from the following aspects: (1) adaptive domain generalization, (2) adaptive model selection, and (3) adaptive knowledge utilization.Kindly check and confirm the edit made in the title.The title is correct.

Background: Non-Hodgkin lymphoma is a common hematologic malignancy. This article aimed to estimate the trends of non-Hodgkin lymphoma (NHL) globally from 1990 to 2019. Methods: Data on the NHL burden were explored from the Global Burden of Disease study 2019. The trends of NHL burden were estimated using age-standardized rate (ASR) and estimated annual percentage change (EAPC). Results: The ASR of NHL incidence showed an increasing trend worldwide from 1990 to 2019, with an EAPC of.56 [95% CI: 0.45–0.66]. Meanwhile, increasing trends were observed in both sexes and in most geographic regions, particularly East Asia (EAPC = 3.57, 95% CI: 3.29–3.86). The most pronounced increasing trends were seen in Georgia (EAPC = 4.7, 95% CI: 4.20–5.21), followed by Belarus and Uzbekistan. However, death and disability-adjusted life years (DALYs) caused by NHL showed decreasing trends globally, in which the respective EAPCs were −0.09 (95% CI: −0.17 to −0.02) and −0.28 (95% CI: −0.35 to −0.22). Decreasing trends were mainly seen in high and high-middle sociodemographic index (SDI) areas. At the national level, the largest increasing trends of death and DALYs were observed in Georgia, in which the respective EAPCs were 4.54 (95% CI: 4.01–5.07) and 4.97 (95% CI: 4.42–5.52). Conclusions: Decreasing trends of death and DALYs caused by NHL were observed worldwide from 1990 to 2019, but NHL remains a substantial challenge globally. The findings would inform the strategies for reducing the burden of NHL.

Background In China, significant delays in accessing medical care for patients with head and neck cancer (HNC) are a critical public health concern. Patients often experience a long delay from the onset of symptoms to receiving treatment, which affects prognosis. This study aimed to explore the entire experience of delayed medical treatment for HNC patients through patient journey maps, identify the key obstacles at each stage, and provide a basis for formulating targeted intervention measures. Methods Using a descriptive qualitative approach, this study systematically explored the lived experiences of 14 patients diagnosed with HNC through semi-structured in-depth interviews. Thematic content analysis was conducted to systematically analyze the data and construct a detailed patient journey map, revealing critical barriers to timely care and emotional challenges faced by this population. Results Based on the timeline of diagnosis and treatment, the findings were organized into four overarching themes: assessment delay period, diagnostic delay period, treatment delay period, and cross-cutting drivers across delay stages. A total of 19 sub-themes were identified, structured across five dimensions: behavior, thinking, emotion, pain points, and contact points. Specifically, five sub-themes were related to the assessment delay period, five to the diagnostic delay period, five to the treatment delay period, and four were cross-cutting drivers that influenced multiple stages. Conclusions The healthcare journey for patients with HNC is often complex, characterized by significant delays in seeking medical care. To address these challenges, we recommend three key strategies: promoting grassroots health education, developing digital warning tools, and establishing professional medical platforms. These efforts aim to improve the efficient use of medical resources, provide patients with treatment decision-making support, and deliver social support—ultimately better addressing their health needs.

Epidemiological studies have demonstrated inconsistent associations between tea consumption and mortality of all cancers, CVD and all causes. To obtain quantitative overall estimates, we conducted a dose–response meta-analysis of prospective cohort studies. A literature search in PubMed and Embase up to April 2015 was conducted for all relevant papers published. Random-effects models were used to calculate pooled relative risks (RR) with 95 % CI. In eighteen prospective studies, there were 12 221, 11 306 and 55 528 deaths from all cancers, CVD and all causes, respectively. For all cancer mortality, the summary RR for the highest v. lowest category of green tea and black tea consumption were 1·06 (95 % CI 0·98, 1·15) and 0·79 (95 % CI 0·65, 0·97), respectively. For CVD mortality, the summary RR for the highest v. lowest category of green tea and black tea consumption were 0·67 (95 % CI 0·46, 0·96) and 0·88 (95 % CI 0·77, 1·01), respectively. For all-cause mortality, the summary RR for the highest v. lowest category of green tea and black tea consumption were 0·80 (95 % CI 0·68, 0·93) and 0·90 (95 % CI 0·83, 0·98), respectively. The dose–response analysis indicated that one cup per d increment of green tea consumption was associated with 5 % lower risk of CVD mortality and with 4 % lower risk of all-cause mortality. Green tea consumption was significantly inversely associated with CVD and all-cause mortality, whereas black tea consumption was significantly inversely associated with all cancer and all-cause mortality.

Laryngeal cancer is the second most common type of primary epithelial malignant tumor in the head and neck region, and the development of therapies that are more precise, efficient, and safe is necessary to preserve patient speech and swallowing functions as much as possible. Multi-modal imaging-guided photothermal therapy (PTT) can precisely delineate tumors, monitor the real-time accumulation of photothermal agents at the tumor site, accurately select the optimal region for irradiation, and predict the best time for laser treatment. Compared with exogeneous photothermal agents, endogenous melanin materials have better biosafety in vivo, in terms of native biocompatibility and biodegradability, as well as good near-infrared (NIR) absorbance. An NIR-II dye can be attached to melanin via a facile method, and applying a melanin-dye-based nanoprobe could be an excellent choice for the elimination of superficial laryngeal cancer while avoiding total laryngectomy. In this work, a promising nanoprobe was constructed using a facile EDC/NHS strategy involving an NIR-II dye and melanin nanoparticles. The nanoprobe exhibited good water solubility, dispersibility, strong NIR-II fluorescence and photoacoustic (PA) signals, and higher photothermal performance. Cellular studies showed that the nanoprobe had low toxicity, excellent biocompatibility, and significantly enhanced imaging properties. After the nanoprobe was intravenously injected into Hep-2 laryngeal xenografts, superior dual-modal images were obtained at various time points, which revealed that the optimal photothermal treatment time was 8 h. Subsequently, PTT was carried out in vivo, and laryngeal tumors were completely eliminated after laser irradiation without any obvious side effects. These results indicate the immense potential of nanoprobes for the NIR-II fluorescence/PA imaging-guided photothermal therapy of laryngeal cancer.

Background Current intensity-modulated radiation therapy (IMRT) treatment planning is still a manual and time/resource consuming task, knowledge-based planning methods with appropriate predictions have been shown to enhance the plan quality consistency and improve planning efficiency. This study aims to develop a novel prediction framework to simultaneously predict dose distribution and fluence for nasopharyngeal carcinoma treated with IMRT, the predicted dose information and fluence can be used as the dose objectives and initial solution for an automatic IMRT plan optimization scheme, respectively. Methods We proposed a shared encoder network to simultaneously generate dose distribution and fluence maps. The same inputs (three-dimensional contours and CT images) were used for both dose distribution and fluence prediction. The model was trained with datasets of 340 nasopharyngeal carcinoma patients (260 cases for training, 40 cases for validation, 40 cases for testing) treated with nine-beam IMRT. The predicted fluence was then imported back to treatment planning system to generate the final deliverable plan. Predicted fluence accuracy was quantitatively evaluated within projected planning target volumes in beams-eye-view with 5 mm margin. The comparison between predicted doses, predicted fluence generated doses and ground truth doses were also conducted inside patient body. Results The proposed network successfully predicted similar dose distribution and fluence maps compared with ground truth. The quantitative evaluation showed that the pixel-based mean absolute error between predicted fluence and ground truth fluence was 0.53% ± 0.13%. The structural similarity index also showed high fluence similarity with values of 0.96 ± 0.02. Meanwhile, the difference in the clinical dose indices for most structures between predicted dose, predicted fluence generated dose and ground truth dose were less than 1 Gy. As a comparison, the predicted dose achieved better target dose coverage and dose hot spot than predicted fluence generated dose compared with ground truth dose. Conclusion We proposed an approach to predict 3D dose distribution and fluence maps simultaneously for nasopharyngeal carcinoma patients. Hence, the proposed method can be potentially integrated in a fast automatic plan generation scheme by using predicted dose as dose objectives and predicted fluence as a warm start.

Background Quality of care in colonoscopy is closely related to colonoscopy participants and the nursing workforce in endoscopy-related settings. However, limited data are available on the evaluations and recommendations regarding quality indicators for nursing care by these two groups. Therefore, the aim of this study was to explore the standards and requirements of quality of care in colonoscopy from the perspectives of patients and nurses. Method With a descriptive qualitative study, semi-structured interviews were conducted between November 2021 and January 2022 with colonoscopy participants ( P  = 11) and nursing workforce ( N  = 7) in the endoscopy unit in a tertiary hospital. The interviews were analyzed using a thematic analysis. Results Nine major themes emerged according to the structure, process, and outcome care quality model: workforce structure, quality requirements, unit facilities, nursing tools, nursing quality control systems, dynamic assessment and intervention, pre-examination care, strengthening education, and colonoscopy outcomes. Conclusion The indicator of quality of colonoscopy care should be used to assess and improve current practices to ensure a more direct and sustained impact of colonoscopy care. This study highlights the importance of nurse managers valuing the opinions and reflections of people involved in colonoscopy to improve the quality of colonoscopy care.

Regulating bulk polymeric carbon nitride (PCN) into nanostructured PCN has long been proven effective in enhancing its photocatalytic activity. However, simplifying the synthesis of nanostructured PCN remains a considerable challenge and has drawn widespread attention. This work reported the one-step green and sustainable synthesis of nanostructured PCN in the direct thermal polymerization of the guanidine thiocyanate precursor via the judicious introduction of hot water vapor’s dual function as gas-bubble templates along with a green etching reagent. By optimizing the temperature of the water vapor and polymerization reaction time, the as-prepared nanostructured PCN exhibited a highly boosted visible-light-driven photocatalytic hydrogen evolution activity. The highest H2 evolution rate achieved was 4.81mmol∙g−1∙h−1, which is over four times larger than that of the bulk PCN (1.19 mmol∙g−1∙h−1) prepared only by thermal polymerization of the guanidine thiocyanate precursor without the assistance of bifunctional hot water vapor. The enhanced photocatalytic activity might be attributed to the enlarged BET specific surface area, increased active site quantity, and highly accelerated photo-excited charge-carrier transfer and separation. Moreover, the sustainability of this environmentally friendly hot water vapor dual-function mediated method was also shown to be versatile in preparing other nanostructured PCN photocatalysts derived from other precursors such as dicyandiamide and melamine. This work is expected to provide a novel pathway for exploring the rational design of nanostructured PCN for highly efficient solar energy conversion.