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In order to solve the problem of image denoising in irradiation fields such as nuclear waste disposal hot cells，this study made corresponding improvements to the algorithm based on the idea of median filtering for radiation noise points，and finally proposed an algorithm suitable for image denoising in strong irradiation fields. The algorithm process is divided into three steps: noise recognition，noise processing and detail protection. Noise recognition starts from visual perception. If the pixel value is higher than its surrounding value and reaches the set threshold，it is marked as suspicious. By setting the maximum area threshold of radiation noise，the area larger than the threshold is excluded. The idea of median filtering is used to deal with noise，and the size of filtering window is adjusted adaptively. The protection of detail borrows from the idea of image fusion. Compared with other noise reduction algorithms，the results show that the proposed algorithm is accurate in the identification of radiated noise points，has obvious noise reduction effect，and protects the details of the picture to the greatest extent. The algorithm demonstrates good robustness under radiation environments with different dose rates，and still achieves effective denoising even under a strong irradiation field of 100 Gy/h. This can provide technical support for intelligent applications in nuclear waste disposal.

Abstract Background An increasing number of clinical studies have begun to explore combination strategies with immune checkpoint inhibitors, aiming to present new opportunities for overcoming anti-PD-1 treatment resistance in gastric cancer. Unfortunately, the exploration of certain immune checkpoint inhibitor combination strategies has yielded suboptimal results. Therefore, it is necessary to comprehensively analyze the expression patterns of immune checkpoints and identify optimal combination regimens of anti-PD-1 inhibitors with other immune checkpoint inhibitors. Methods Leveraging single-cell RNA sequencing (scRNA-seq) and multivariate linear regression interaction models, we dissected the immune checkpoint expression characteristics of CD8+ T cells in gastric cancer and the immune checkpoint expression pattern (ICEP) mediating anti-PD-1 treatment resistance. Furthermore, we employed transcription factor analysis and CellOracle to explore the transcriptional regulatory mechanisms governing CD8+ T cell differentiation fates. Finally, we utilized Nichenet and spatial transcriptomic analysis to investigate the spatial expression patterns of immune checkpoints. Results Interaction analysis indicated that, among the known immune checkpoints, co-expression of NKG2A and PD-1 might exert a more profound inhibitory effect on the proliferative capacity of CD8+ T cells. The co-expression analysis revealed differential co-expression pattern of PD-1 and NKG2A, defined as ICEP1 (CD8+ T cells co-expressing PD-1, CTLA-4, TIGIT, LAG-3 or CD38) and ICEP2 (CD8+ T cells solely expressing NKG2A or co-expressing with other immune checkpoints), reflecting the co-occurrence pattern of PD-1 and the mutual exclusivity of NKG2A. Further, these two ICEP CD8+ T cell subsets represented distinct CD8+ T cell differentiation fates governed by MSC and RUNX3. Notably, ICEP2 CD8+ T cells were associated with anti-PD-1 therapy resistance in gastric cancer. This phenomenon may be attributed to the recruitment of LGMN+ macrophages mediated by the CXCL16-CXCR6 signaling pathway. Conclusion This study unveiled two distinct ICEPs and the mutually exclusivity and co-occurrence characteristics of CD8+ T cells in gastric cancer. The ICEP2 CD8+ T cell subset, highly expressed in gastric cancer patients resistant to anti-PD-1 therapy, may be recruited by LGMN+ macrophages through CXCL16-CXCR6 axis. These findings provide evidence for NKG2A as a novel immunotherapeutic target in gastric cancer and offer new insights into combination strategies for immune checkpoint inhibitors in gastric cancer. Graphical Abstract

Abstract Background Understanding sex‐specific factors contributing to advanced‐stage diagnosis can guide interventions to reduce sex inequality in patients with urological cancers. Method We used linked primary care and cancer registry data to examine associations between symptoms and advanced‐stage in 1151 bladder cancer and 440 renal cancer patients diagnosed between January 2012 and December 2015 in England. We performed logistic regression, adjusting for sex, age, deprivation and routes to diagnosis, including interaction terms between symptoms and sex and symptoms and age. Results Female sex (OR vs. men 1.89 [1.28–2.79]; p = 0.001) and patients presenting with urinary tract infections (OR 2.22 [1.34–3.69]) and abdominal symptoms (OR 2.19 [1.30–3.70]) were associated with increased odds of advanced‐stage bladder cancer (vs. haematuria, p = 0.016 for both). Women with haematuria and men with abdominal symptoms (compared with the opposite sex with the same presenting symptom) were more likely to have advanced‐stage bladder cancer. Neither sex nor symptom associations were observed for renal cancer. Conclusion Non‐haematuria symptoms are associated with higher risk of advanced‐stage bladder cancer. Greater risk of advanced‐stage bladder cancer in women may reflect biological differences in haematuria onset and sex differences during diagnostic process. Identifying higher risk women with haematuria may reduce sex inequalities in bladder cancer outcomes.

Geological disaster occurrences in loess regions are intrinsically linked to water infiltration in loess, with the Malan loess-paleosol interlayer structure significantly influencing the infiltration patterns of soil moisture. This research was carried out to reveal the moisture migration characteristics in loess-paleosol interlayers, and to investigate the influence of the moisture migration on the microstructure of loess, providing a theoretical basis for engineering practice and scientific research in loess areas. In this study, we focused on the loess of the South Plateau in Jingyang County, Shaanxi Province, and conducted water infiltration tests using a soil column model to investigate the soil moisture transport dynamics under loess-paleosol interlayer conditions. Subsequently, we analyzed the impact of soil moisture transport on the loess microstructure under these conditions through microstructural testing, and calculation of fractal dimension and probability entropy. The findings revealed that the permeability of the paleosol layer was low, causing transient water stagnation when the wetting front reached the loess-paleosol interface. The stagnant water at the interface of loess and paleosol under the influence of the paleosol layer will lead to the interconnection of pore structure, and the pore space will increase by 4.13% on average, and the analysis of the indexes of fractal dimension and probability entropy shows that the probability entropy of the pore direction decreases by 0.029 on average, and the fractal dimension decreases by 0.076 on average, i.e., the water-blocking effect of the paleosol layer makes the pore space of the loess at the interface increase, the pores are arranged in an orderly manner, and the pore morphology is regular. The results of the study provide scientific support for the engineering construction and eco-environmental protection in loess areas.

Head and neck cancer has a significant impact on a patient’s health related quality of life (HRQOL). The head and neck specific Patient Concerns Inventory (PCI-HN) has been utilised to enhance doctor-patient dialogue in routine consultations. To date there has been no formal training for oral and maxillofacial surgery (OMFS) surgical trainees in the use of the PCI-HN in consultations. The aim of the study was to evaluate training for OMFS surgical trainees in the use of the PCI-HN, using simulated follow-up HNC consultations, in order to improve doctor-patient communication skills. Material and methods: Ten oral and maxillofacial surgical trainees completed actor simulated HNC consultations before and after training. A study-specific mark scheme was developed based on the ComOn-Coaching rating scales and used to score the doctor-patient interaction. A group debrief afterwards explored the trainee’s experiences of the training and consultations. Results: All trainees showed an improvement in doctor-patient communication scores following their training. Overall, the six participants who were Specialty registrars, year 3 (ST3) or above, scored higher, than the four Specialty registrars, year 1–2 (ST1-2). The scores were higher if fewer PCI-HN items were discussed (3–4). The most frequently avoided PCI-HN items were intimacy and relationships. The trainees considered that their training was useful for organising their consultations and for providing holistic care. Conclusion: Although training improved surgeon-patient communication, further evaluation is required with a larger number of trainees and actual consultations in clinic.

Abstract The two-phase compression process in the rotary compressor often occurs, such as defrosting and startup processes, which has a significant impact on the performance and reliability of air conditioning systems. In this paper, the CFD simulations predicting the two-phase refrigerant compression process in the compressor cylinder are conducted using the commercial software ANSYS Fluent. The dynamic mesh for the fluid domain and phase change model for the refrigerant are considered in the simulation. Effects of initial liquid volume fraction, refrigerant type and compressor type on the two-phase compression characteristics using R290 as refrigerant are carried out. Variations of the pressure, temperature, gas fraction distribution and evaporation rate in the cylinder are discussed. The results show that most liquid accumulates near the leakage gap and the bottom of the compression chamber during the two-phase compression process. The peak pressure during the two-phase compression decreases with the increase of the liquid volume fraction. The evaporation rate of R32 in the cylinder is much higher than that of R290. The maximum pressure of the reciprocating compressor is 2.26 times higher than that of the rotary compressor.

Heat-resistant Al alloys used in such as aerospace, transportation fields are attracting more and more attention in recent years. Within Al alloy families, Al–Cu–Mg alloys have shown promising heat resistance properties. This work aims to investigate the influence of Cu/Mg ratio and content on the heat resistance of Al–Cu–Mg alloys, based on alloys of Al–4.5Cu–2.5 Mg (referred to as alloy A), Al–4.0Cu–2.2 Mg (alloy B) and Al–4.5Cu–1.6 Mg (alloy C). The alloys A and B possessed approximate Cu/Mg ratio, and they also exhibited nearly identical hardness retention rate during exposure at 200 °C. After 200 h, the rate is ∼75 %, though alloy A showed higher hardness (105 vs. 102 HBW) due to higher Cu, Mg content. In contrast, alloy C with a higher Cu/Mg ratio was less heat-resistant, with hardness retention rate of ∼70.5 % after 200 h exposure. Nano-sized S′(Al2CuMg) precipitate was main strengthening phase for the three alloys. Also, micron and submicron Al2CuMg particles could be formed with increase of Cu and Mg contents, which contributed a lot to yield strength for T6 heat-treated alloys, but slight contribution after exposure at 200 °C for 200 h. The degradation of mechanical properties during heat exposure can be attributed to the transformation and coarsening of S′ precipitates. In alloys with lower Cu/Mg ratio, there was excess Mg dissolved in Al matrix, which reduced Cu solubility in α-Al, and then slowed diffusion flux of Cu element, thus inhibited coarsening of Al2CuMg phase.

AimTo explore the association of Hemoglobin-to-Red Cell Distribution Width Ratio (HRR) with the risk of three-month unfavorable outcomes in acute ischemic stroke (AIS).MethodsA secondary analysis was conducted based on a prospective cohort study. A total of 1,889 patients with AIS treated in South Korea from January 2010 to December 2016 were enrolled. Multivariable logistic regression was conducted to investigated the independent relationship between HRR and risk of three-month unfavorable outcomes in AIS. Fitted smoothing curves were used to determine non-linear correlations. The recursive method was employed to explore the turning point and build a two-piece linear regression model. In addition, a set of subgroup analyses were carried out to evaluate the relationship between HRR and risk of three-month unfavorable outcomes.ResultsMultivariate analysis in which potential confounders were adjusted for indicated that the risk of unfavorable outcomes was reduced by 10% for each unit increased of HRR [OR = 0.90, 95% CI: 0.84–0.96, p = 0.0024]. In addition, a non-linear relationship was observed between HRR and risk of three-month unfavorable outcomes, which had an inflection point of HRR was 10.57. The effect sizes and the confidence intervals on the left side of the inflection point were 0.83 (0.75, 0.91), p = 0.0001. On the right side of the inflection point, no association was found between HRR and the risk of three-month unfavorable outcomes.ConclusionThis study demonstrates a negative association between HRR and risk of three-month unfavorable outcomes. The relationship between HRR and risk of three-month unfavorable outcomes is non-linear. The correlation is negative for HRR values less than 10.57. For, HRR higher than 10.57, HRR is not associated with the risk of three-month unfavorable outcomes.

Abstract Background The duration of hospitalization, especially in the intensive care unit (ICU), for patients with diabetic ketoacidosis (DKA) is influenced by patient prognosis and treatment costs. Reducing ICU length of stay (LOS) in patients with DKA is crucial for optimising healthcare resources utilization. This study aimed to establish a nomogram prediction model to identify the risk factors influencing prolonged LOS in ICU-managed patients with DKA, which will serve as a basis for clinical treatment, healthcare safety, and quality management research. Methods In this single-centre retrospective cohort study, we performed a retrospective analysis using relevant data extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Clinical data from 669 patients with DKA requiring ICU treatment were included. Variables were selected using the Least Absolute Shrinkage and Selection Operator (LASSO) binary logistic regression model. Subsequently, the selected variables were subjected to a multifactorial logistic regression analysis to determine independent risk factors for prolonged ICU LOS in patients with DKA. A nomogram prediction model was constructed based on the identified predictors. The multivariate variables included in this nomogram prediction model were the Oxford acute severity of illness score (OASIS), Glasgow coma scale (GCS), acute kidney injury (AKI) stage, vasoactive agents, and myocardial infarction. Results The prediction model had a high predictive efficacy, with an area under the curve value of 0.870 (95% confidence interval [CI], 0.831–0.908) in the training cohort and 0.858 (95% CI, 0.799–0.916) in the validation cohort. A highly accurate predictive model was depicted in both cohorts using the Hosmer–Lemeshow (H-L) test and calibration plots. Conclusion The nomogram prediction model proposed in this study has a high clinical application value for predicting prolonged ICU LOS in patients with DKA. This model can help clinicians identify patients with DKA at risk of prolonged ICU LOS, thereby enhancing prompt intervention and improving prognosis.

Abstract Double core-holes (DCHs) show remarkable and sensitive effects for understanding electron correlations and coherence. With advanced modulation of x-ray free-electron laser (XFEL) facility, we propose the forthcoming all-attosecond XFEL pump-probe spectroscopy can decipher the hidden photon-initiated dynamics of DCHs. The benchmark case of neon is investigated, and norm-nonconserving Monte-Carlo wavefunction method simulates non-Hermitian dynamics among vast states, which shows superiority in efficiency and reliability. In our scheme, population transfer to DCHs is sequentially irradiated by pump and probe laser. By varying time delay, Stark shifts and quantum path interference of resonant lines sensitively emerge at specific interval of two pulses. These ubiquitous multi-channel effects are also observed in phase-fluctuating pulses, derived from extra phases of impulsive Raman processes by pump laser. Non-perturbation absorption/emission verifies the uniquely interchangeable role of two pules in higher intensity. Our results reveal sensitive and robust responses on pulse parameters, which show potential capacity for XFEL attosecond pulse diagnosis and further attosecond-timescale chemical analysis.

BackgroundStomolophus meleagris envenomation causes severe cutaneous symptoms known as jellyfish dermatitis. The potential molecule mechanisms and treatment efficiency of dermatitis remain elusive because of the complicated venom components. The biological activity and molecular regulation mechanism of Troxerutin (TRX) was firstly examined as a potential treatment for jellyfish dermatitis. MethodsWe examined the inhibit effects of the TRX on tentacle extract (TE) obtained from S. meleagris in vivo and in vitro using the mice paw swelling models and corresponding assays for Enzyme-Linked Immunosorbent Assay (ELISA) Analysis, cell counting kit-8 assay, flow cytometry, respectively. The mechanism of TRX on HaCaT cells probed the altered activity of relevant signaling pathways by RNA sequencing and verified by RT-qPCR, Western blot to further confirm protective effects of TRX against the inflammation and oxidative damage caused by TE. ResultsTE significantly induced the mice paw skin toxicity and accumulation of inflammatory cytokines and reactive oxygen species in vivo and vitro. Moreover, a robust increase in the phosphorylation of mitogen-activated protein kinase (MAPKs) and nuclear factor-kappa B (NF-κB) signaling pathways was observed. While, the acute cutaneous inflammation and oxidative stress induced by TE were significantly ameliorated by TRX treatment. Notablly, TRX suppressed the phosphorylation of MAPK and NF-κB by initiating the nuclear factor erythroid 2-related factor 2 signaling pathway, which result in decreasing inflammatory cytokine release. ConclusionTRX inhibits the major signaling pathway responsible for inducing inflammatory and oxidative damage of jellyfish dermatitis, offering a novel therapy in clinical applications.

Daptomycin is gaining prominence for the treatment of methicillin-resistant Staphylococcus aureus infections. However, the dosage selection for daptomycin in critically ill patients remains uncertain, especially in Chinese patients. This study aimed to establish the population pharmacokinetics of daptomycin in critically ill patients, optimize clinical administration plans, and recommend appropriate dosage for critically ill patients in China. The study included 64 critically ill patients. Blood samples were collected at the designated times. The blood daptomycin concentration was determined using validated liquid chromatography-tandem mass spectrometry. A nonlinear mixed-effects model was applied for the population pharmacokinetic analysis and Monte Carlo simulations of daptomycin. The results showed a two-compartment population pharmacokinetic model of daptomycin in critically ill adult Han Chinese patients. Monte Carlo simulations revealed that a daily dose of 400 mg of daptomycin was insufficient for the majority of critically ill adult patients to achieve the anti-infective target. For critically ill adult patients with normal renal function (creatinine clearance rate >90 mL/min), the probability of achieving the target only reached 90% when the daily dose was increased to 700 mg. For patients undergoing continuous renal replacement therapy (CRRT), 24 h administration of 500 mg met the pharmacodynamic goals and did not exceed the safety threshold in most patients. Therefore, considering its efficacy and safety, intravenous daptomycin doses are best scaled according to creatinine clearance, and an increased dose is recommended for critically ill patients with hyperrenalism. For patients receiving CRRT, medication is recommended at 24 h intervals.

Entropy production in quasi-isentropic compression (QIC) is critically important for understanding the properties of materials under extreme conditions. However, the origin and accurate quantification of entropy in this situation remain long-standing challenges. In this work, a framework is established for the quantification of entropy production and partition, and their relation to microstructural change in QIC. Cu50Zr50 is taken as a model material, and its compression is simulated by molecular dynamics. On the basis of atomistic simulation-informed physical properties and free energy, the thermodynamic path is recovered, and the entropy production and its relation to microstructural change are successfully quantified by the proposed framework. Contrary to intuition, entropy production during QIC of metallic glasses is relatively insensitive to the strain rate γ̇ when γ̇ ranges from 7.5 × 108 to 2 × 109/s, which are values reachable in QIC experiments, with a magnitude of the order of 10−2 kB/atom per GPa. However, when γ̇ is extremely high (>2×109/s), a notable increase in entropy production rate with γ̇ is observed. The Taylor–Quinney factor is found to vary with strain but not with strain rate in the simulated regime. It is demonstrated that entropy production is dominated by the configurational part, compared with the vibrational part. In the rate-insensitive regime, the increase in configurational entropy exhibits a linear relation to the Shannon-entropic quantification of microstructural change, and a stretched exponential relation to the Taylor–Quinney factor. The quantification of entropy is expected to provide thermodynamic insights into the fundamental relation between microstructure evolution and plastic dissipation.

Candida albicans (C. albicans) is one of the most common clinical isolates of systemic fungal infection. Long-term and inappropriate use of antifungal drugs can cause fungal resistance, which poses a great challenge to the clinical treatment of fungal infections. The combination of antifungal drugs and non-antifungal drugs to overcome the problem of fungal resistance has become a research hotspot in recent years. Our previous study found that the combination of rifapentine (RFT) and fluconazole (FLC) has a significant synergistic against FLC-resistant C. albicans. The present study aimed to further verify the synergistic effect between FLC and RFT against the FLC-resistant C. albicans 100, and explore the underlying mechanism. The growth curve and spot assay test not only showed the synergistic effect of FLC and RFT on FLC-resistant C. albicans in vitro but exhibited a dose-dependent effect on RFT, indicating that RFT may play a principal role in the synergic effect of the two drugs. Flow cytometry showed that the combined use of RFT and FLC arrested cells in the G2/M phase, inhibiting the normal division and proliferation of FLC-resistant C. albicans. Transmission electron microscopy (TEM) demonstrated that FLC at a low concentration could still cause a certain degree of damage to the cell membrane in the FLC-resistant C. albicans, as represented by irregular morphologic changes and some defects observed in the cell membrane. When FLC was used in combination with RFT, the nuclear membrane was dissolved and the nucleus was condensed into a mass. Detection of the intracellular drug concentration of fungi revealed that the intracellular concentration of RFT was 31–195 fold that of RFT alone when it was concomitantly used with FLC. This indicated that FLC could significantly increase the concentration of RFT in cells, which may be due to the damage caused to the fungal cell membrane by FLC. In short, the present study revealed a synergistic mechanism in the combined use of RFT and FLC, which may provide a novel strategy for the clinical treatment of FLC-resistant C. albicans.

The electron impact excitation process is important to investigate the ionization balance, the dynamical evolution of non-equilibrium plasmas, and the physical properties of plasmas. In dense plasmas, previous theories show that the electron impact excitation cross section is generally decreased compared with that in the case of isolated atoms or ions which applies to a dilute system. Investigations show that such decrease is caused by plasma screening. In this study, we propose a mechanism which increases the electron impact excitation cross section in dense plasmas. Due to the random collisions of the scattering electrons with other free electrons and ions in the plasma, the wavefunction of the scattering electrons can no longer be described by employing a plane wave distorted only by the scattering potential. The momentum of the scattering electrons is no longer a constant but changes with their distribution in a certain range, resulting in a phenomenon of transient spatial localization. The momentum broadening of the scattering electron is proposed to quantitatively describe such a localization. A theoretical formalism is developed to consider the transient spatial localization effect in the atomic collision theory and is applied to investigate the electron impact excitation processes of 1s2 1S0 → 1s2p 1P1o and 1s2 1S0 → 1s3p 1P1o of Si12+ embedded in dense plasmas. The results show that the calculated cross sections and rate coefficients are decreased by plasma screening, whereas their quantities are significantly increased in the dense plasmas by the transient spatial localization compared with those obtained by the isolated-atom model. These research findings provide new insight into the microscopic atomic process of the electron impact excitation and macroscopic physical properties such as the electron conductive opacity and the thermal conductivity.

Abstract Background Studies exploring whether metastatic organotropism and risk in gastric cancer (GC) differ by primary anatomical site are scarce. Methods This study included 15,260 and 1623 patients diagnosed with GC from the Surveillance, Epidemiology, and End Results (SEER) registry database and the Nanfang Hospital in China, respectively. Patients were stratified according to primary site of GC, and the incidence of metastasis to different organs was used to determine the metastatic organotropism for each GC subsite. Finally, the metastatic organotropism and risk were compared among the different subsite groups. Results Liver metastasis was the most common metastasis site in cardia GC, whereas other‐site metastases were more common in the body, antrum, overlapping lesions, and unspecified GCs. Liver and other‐site metastases were also frequently observed in the fundus, pylorus, lesser curvature, and greater curvature GCs. Patients with GC with definite primary tumor sites in the SEER and validation Nanfang hospital cohorts were compared by grouping as proximal and distal GCs for further analysis. In the SEER cohort, the top three metastatic sites of proximal GC were liver (21.4%), distant lymph node (LN) (14.6%), and other‐site (mainly peritoneum, 11.9%), whereas those of distal GC were other‐site (mainly peritoneum, 19.5%), liver (11.8%), and distant LN (9.5%). The incidence of metastasis to the liver, distant LN, lung, and brain was significantly higher in patients with proximal GC than in those with distal GC in both the SEER and Nanfang cohorts (p

Objectives: To explore whether: (i) people with severe mental illness (SMI) experience worse oral health than the general population, and (ii) the risk factors for poor oral health in people with SMI. Methods: Cross-sectional data were extracted from the National Health and Nutrition Examination Survey (1999–2016), including on self-rated oral health, oral pain, tooth loss, periodontitis stage, and number of decayed, missing, and filled teeth. Candidate risk factors for poor oral health included demographic characteristics, lifestyle factors, physical health comorbidities, and dental hygiene behaviours. Ordinal logistic regression and zero-inflated negative binomial models were used to explore predictors of oral health outcomes. Results: There were 53,348 cases included in the analysis, including 718 people with SMI. In the fully adjusted model, people with SMI were more likely to suffer from tooth loss (OR 1.60, 95% CI: 1.34–1.92). In people with SMI, risk factors identified for poor oral health outcomes were older age, white ethnicity, lower income, smoking history, and diabetes. Engaging in physical activity and daily use of dental floss were associated with better oral health outcomes. Conclusions: People with SMI experience higher rates of tooth loss than the general population, and certain subgroups are particularly at risk. Performing regular physical exercise and flossing may lower the risk of poor oral health, while smoking and diabetes may increase the risk. These findings suggest opportunities for targeted prevention and early intervention strategies to mitigate adverse oral health outcomes in people with SMI.

Poly(dimethylsiloxane) (PDMS) coatings are considered to be environmentally friendly antifouling coatings. However, the presence of hydrophobic surfaces can enhance the adhesion rate of proteins, bacteria and microalgae, posing a challenge for biofouling removal. In this study, hydrophilic polymer chains were synthesised from methyl methacrylate (MMA), Poly(ethylene glycol) methyl ether methacrylate (PEG-MA) and 3-(trimethoxysilyl) propyl methacrylate (TPMA). The crosslinking reaction between TPMA and PDMS results in the formation of a silicone-based amphiphilic co-network with surface reconstruction properties. The hydrophilic and hydrophobic domains are covalently bonded by condensation reactions, while the hydrophilic polymers migrate under water to induce surface reconstruction and form hydrogen bonds with water molecules to form a dense hydrated layer. This design effectively mitigates the adhesion of proteins, bacteria, algae and other marine organisms to the coating. The antifouling performance of the coatings was evaluated by assessing their adhesion rates to proteins (BSA-FITC), bacteria (B. subtilis and P. ruthenica) and algae (P. tricornutum). The results show that the amphiphilic co-network coating (e.g., P-AM-15) exhibits excellent antifouling properties against protein, bacterial and microalgal fouling. Furthermore, an overall assessment of its antifouling performance and stability was conducted in the East China Sea from 16 May to 12 September 2023, which showed that this silicon-based amphiphilic co-network coating remained intact with almost no marine organisms adhering to it. This study provides a novel approach for the development of high-performance silicone-based antifouling coatings.

BackgroundThe occurrence of a range of health outcomes following myocardial infarction (MI) is unknown. Therefore, this study aimed to determine the long-term risk of major health outcomes following MI and generate sociodemographic stratified risk charts in order to inform care recommendations in the post-MI period and underpin shared decision making.Methods and findingsThis nationwide cohort study includes all individuals aged ≥18 years admitted to one of 229 National Health Service (NHS) Trusts in England between 1 January 2008 and 31 January 2017 (final follow-up 27 March 2017). We analysed 11 non-fatal health outcomes (subsequent MI and first hospitalisation for heart failure, atrial fibrillation, cerebrovascular disease, peripheral arterial disease, severe bleeding, renal failure, diabetes mellitus, dementia, depression, and cancer) and all-cause mortality. Of the 55,619,430 population of England, 34,116,257 individuals contributing to 145,912,852 hospitalisations were included (mean age 41.7 years (standard deviation [SD 26.1]); n = 14,747,198 (44.2%) male). There were 433,361 individuals with MI (mean age 67.4 years [SD 14.4)]; n = 283,742 (65.5%) male). Following MI, all-cause mortality was the most frequent event (adjusted cumulative incidence at 9 years 37.8% (95% confidence interval [CI] [37.6,37.9]), followed by heart failure (29.6%; 95% CI [29.4,29.7]), renal failure (27.2%; 95% CI [27.0,27.4]), atrial fibrillation (22.3%; 95% CI [22.2,22.5]), severe bleeding (19.0%; 95% CI [18.8,19.1]), diabetes (17.0%; 95% CI [16.9,17.1]), cancer (13.5%; 95% CI [13.3,13.6]), cerebrovascular disease (12.5%; 95% CI [12.4,12.7]), depression (8.9%; 95% CI [8.7,9.0]), dementia (7.8%; 95% CI [7.7,7.9]), subsequent MI (7.1%; 95% CI [7.0,7.2]), and peripheral arterial disease (6.5%; 95% CI [6.4,6.6]). Compared with a risk-set matched population of 2,001,310 individuals, first hospitalisation of all non-fatal health outcomes were increased after MI, except for dementia (adjusted hazard ratio [aHR] 1.01; 95% CI [0.99,1.02];p = 0.468) and cancer (aHR 0.56; 95% CI [0.56,0.57];p < 0.001). The study includes data from secondary care only-as such diagnoses made outside of secondary care may have been missed leading to the potential underestimation of the total burden of disease following MI.ConclusionsIn this study, up to a third of patients with MI developed heart failure or renal failure, 7% had another MI, and 38% died within 9 years (compared with 35% deaths among matched individuals). The incidence of all health outcomes, except dementia and cancer, was higher than expected during the normal life course without MI following adjustment for age, sex, year, and socioeconomic deprivation. Efforts targeted to prevent or limit the accrual of chronic, multisystem disease states following MI are needed and should be guided by the demographic-specific risk charts derived in this study.

With the development of artificial intelligence and breakthroughs in deep learning, large-scale foundation models (FMs), such as generative pre-trained transformer (GPT), Sora, etc., have achieved remarkable results in many fields including natural language processing and computer vision. The application of FMs in autonomous driving holds considerable promise. For example, they can contribute to enhancing scene understanding and reasoning. By pre-training on rich linguistic and visual data, FMs can understand and interpret various elements in a driving scene, and provide cognitive reasoning to give linguistic and action instructions for driving decisions and planning. Furthermore, FMs can augment data based on the understanding of driving scenarios to provide feasible scenes of those rare occurrences in the long tail distribution that are unlikely to be encountered during routine driving and data collection. The enhancement can subsequently lead to improvement in the accuracy and reliability of autonomous driving systems. Another testament to the potential of FMs’ applications lies in world models, exemplified by the DREAMER series, which showcases the ability to comprehend physical laws and dynamics. Learning from massive data under the paradigm of self-supervised learning, world models can generate unseen yet plausible driving environments, facilitating the enhancement in the prediction of road users’ behaviors and the off-line training of driving strategies. In this paper, we synthesize the applications and future trends of FMs in autonomous driving. By utilizing the powerful capabilities of FMs, we strive to tackle the potential issues stemming from the long-tail distribution in autonomous driving, consequently advancing overall safety in this domain.

Introduction Heart failure (HF) is increasingly common and associated with excess morbidity, mortality, and healthcare costs. Treatment of HF can alter the disease trajectory and reduce clinical events in HF. However, many cases of HF remain undetected until presentation with more advanced symptoms, often requiring hospitalisation. Predicting incident HF is challenging and statistical models are limited by performance and scalability in routine clinical practice. An HF prediction model implementable in nationwide electronic health records (EHRs) could enable targeted diagnostics to enable earlier identification of HF.Methods and analysis We will investigate a range of development techniques (including logistic regression and supervised machine learning methods) on routinely collected primary care EHRs to predict risk of new-onset HF over 1, 5 and 10 years prediction horizons. The Clinical Practice Research Datalink (CPRD)-GOLD dataset will be used for derivation (training and testing) and the CPRD-AURUM dataset for external validation. Both comprise large cohorts of patients, representative of the population of England in terms of age, sex and ethnicity. Primary care records are linked at patient level to secondary care and mortality data. The performance of the prediction model will be assessed by discrimination, calibration and clinical utility. We will only use variables routinely accessible in primary care.Ethics and dissemination Permissions for CPRD-GOLD and CPRD-AURUM datasets were obtained from CPRD (ref no: 21_000324). The CPRD ethical approval committee approved the study. The results will be submitted as a research paper for publication to a peer-reviewed journal and presented at peer-reviewed conferences.Trial registration details The study was registered on Clinical Trials.gov (NCT 05756127). A systematic review for the project was registered on PROSPERO (registration number: CRD42022380892).

Recent findings have suggested that solute carrier (SLC) transporters play an important role in tumor development and progression, and alterations in the expression of individual SLC genes are critical for fulfilling the heightened metabolic requirements of cancerous cells. However, the global influence of the co-expression pattern of SLC transporters on the clinical stratification and characteristics of the tumor microenvironment (TME) remains unexplored. In this study, we identified five SLC gene subtypes based on transcriptome co-expression patterns of 187 SLC transporters by consensus clustering analysis. These subtypes, which were characterized by distinct TME and biological characteristics, were successfully employed for prognostic and chemotherapy response prediction in colon cancer patients, as well as demonstrated associations with immunotherapy benefits. Then, we generated an SLC score model comprising 113 genes to quantify SLC gene co-expression patterns and validated it as an independent prognostic factor and drug response predictor in several independent colon cancer cohorts. Patients with a high SLC score possessed distinct characteristics of copy number variation, genomic mutations, DNA methylation, and indicated an SLC-S2 subtype, which was characterized by strong stromal cell infiltration, stromal pathway activation, poor prognosis, and low predicted fluorouracil and immunotherapeutic responses. Furthermore, the analysis of the Cancer Therapeutics Response Portal database revealed that inhibitors targeting PI3K catalytic subunits could serve as promising chemosensitizing agents for individuals exhibiting high SLC scores. In conclusion, the co-expression patterns of SLC transporters aided the disease classification, and the SLC score proved to be a reliable tool for distinguishing SLC gene subtypes and guiding precise treatment in patients with colon cancer.

Wastewater is a multicomponent and multiphase mixture. Gas bubbles and solid particles in the dispersed phase influence sonochemical efficiency during ultrasonic treatment of wastewater, sometimes unfavorably; however, the influencing factors and mechanisms remain unclear. In this paper, the influence of argon gas bubbles (1.2 mm) and monodisperse silica particles (0.1 mm) on sonochemical effects in an aqueous system using a horn-type reactor (20 kHz) is reported. Triiodide formation decreased with an increase in the volume fraction of either or both phases. The two phases started inhibiting sonoreactions as the total volume fraction approached 3.0–4.0 vol% compared to pure water. The effect of the gas-to-solid ratio is also considered. We propose an acoustic attenuation model, which incorporates the scattering effect of solid particles and the thermal effect of gas bubbles. The agreement between the modeling and experimental results demonstrates that the two phases are jointly responsible for sonochemical inhibition by increasing ultrasound attenuation. This enhances the understanding of sonochemistry in gas–solid–liquid systems and helps regulate gases and solids in sonochemical reactors.

Introduction Atrial fibrillation (AF) is a major public health issue and there is rationale for the early diagnosis of AF before the first complication occurs. Previous AF screening research is limited by low yields of new cases and strokes prevented in the screened populations. For AF screening to be clinically and cost-effective, the efficiency of identification of newly diagnosed AF needs to be improved and the intervention offered may have to extend beyond oral anticoagulation for stroke prophylaxis. Previous prediction models for incident AF have been limited by their data sources and methodologies.Methods and analysis We will investigate the application of random forest and multivariable logistic regression to predict incident AF within a 6-month prediction horizon, that is, a time-window consistent with conducting investigation for AF. The Clinical Practice Research Datalink (CPRD)-GOLD dataset will be used for derivation, and the Clalit Health Services (CHS) dataset will be used for international external geographical validation. Analyses will include metrics of prediction performance and clinical utility. We will create Kaplan-Meier plots for individuals identified as higher and lower predicted risk of AF and derive the cumulative incidence rate for non-AF cardio-renal-metabolic diseases and death over the longer term to establish how predicted AF risk is associated with a range of new non-AF disease states.Ethics and dissemination Permission for CPRD-GOLD was obtained from CPRD (ref no: 19_076). The CPRD ethical approval committee approved the study. CHS Helsinki committee approval 21-0169 and data usage committee approval 901. The results will be submitted as a research paper for publication to a peer-reviewed journal and presented at peer-reviewed conferences.Trial registration number A systematic review to guide the overall project was registered on PROSPERO (registration number CRD42021245093). The study was registered on ClinicalTrials.gov (NCT05837364).

Abstract Background Lung cancer is the most common cancer‐related death worldwide. In 2022, the number of daily deaths of lung cancer was estimated to reach around 350 in the United States. Lung adenocarcinoma is the main subtype of lung cancer and patients with malignant pleural effusion (MPE) suffer from poor prognosis. Microbiota and its metabolites are associated with cancer progression. However, the effect of pleural microbiota on pleural metabolic profile of MPE in lung adenocarcinoma patients remains largely unknown. Methods Pleural effusion samples collected from lung adenocarcinoma patients with MPE (n = 14) and tuberculosis pleurisy patients with benign pleural effusion (BPE group, n = 10) were subjected to microbiome (16S rRNA gene sequencing) and metabolome (liquid chromatography tandem mass spectrometry [LC‐MS/MS]) analyses. The datasets were analyzed individually and integrated for combined analysis using various bioinformatic approaches. Results The metabolic profile of MPE in lung adenocarcinoma patients were clearly distinguished from BPE with 121 differential metabolites across six significantly enriched pathways identified. Glycerophospholipids, fatty and carboxylic acids, and derivatives were the most common differential metabolites. Sequencing of microbial data revealed nine significantly enriched genera (i.e., Staphylococcus, Streptococcus, Lactobacillus) and 26 enriched ASVs (i.e., species Lactobacillus_delbrueckii) in MPE. Integrated analysis correlated MPE‐associated microbes with metabolites, such as phosphatidylcholine and metabolites involved in the citrate cycle pathway. Conclusion Our results provide substantial evidence of a novel interplay between the pleural microbiota and metabolome, which was drastically perturbed in MPE in lung adenocarcinoma patients. Microbe‐associated metabolites can be used for further therapeutic explorations.

Abstract China's agricultural civilization had left numerous traditional villages (TVs) containing rich historical information and cultural landscape. Exploration the spatial agglomeration characteristics of TVs and their influencing factors is essential for the sustainable development, utilization, and protection of TVs in China. However, previous studies lacked a comprehensive analysis of the spatial distribution of TVs and their driving factors, especially at the national scale. To fill this gap, this study analyzed the spatial agglomeration characteristics and influencing factors of five batches of TVs in China during 2012–2019. The results show that TVs in China were mainly located east of the Hu Line, that is, in the southern and eastern regions of China. The spatial distribution of TVs had significant clustering characteristics, and the gravity center was mainly distributed in central China, and the compactness of the spatial distribution of TVs increased from the first to the fifth batches. The TVs were mainly located at low elevations, northern slope aspect, warm and humid areas. Ferralisol and cultivated vegetation were the main soil and vegetation types in most TVs. TVs tended to be more numerous in the vicinity of low economic development levels, low population density, and rivers. In addition, TVs had a significant correlation with intangible cultural heritage. The results of this study could provide scientific guidance for heritage protection and sustainable development of TVs.

Objective: implementing appropriate pharmacological and non-pharmacological interventions to alleviate pain related to routine dental procedures in paediatric patients could enhance children’s ability to manage dental care. The aim of this review was to investigate the effectiveness of and provide recommendations for interventions that can be used to reduce intra-operative and post-operative pain associated with routine paediatric dental procedures. Methods: A systematic review of randomised controlled clinical trials (RCT) was conducted. Multiple electronic databases were systematically searched. The Cochrane risk-of-bias tool for RCTs was used to evaluate the quality of the included studies. A meta-analysis was performed to determine the effectiveness of the interventions using the Cohen’s d standardised mean differences (SMD) and 95% confidence intervals (CIs) for continuous outcomes. The GRADE tool was used to assess the certainty of evidence to make recommendations. Results: The review included forty-five RCTs comprising 3093 children. Thirty-seven RCTs were included in the meta-analysis, which showed the effectiveness of behavioural interventions (SMD = −0.50, 95% CI −0.83 to −0.18), mechanoreceptor and thermal receptor stimulation (SMD = −1.38, 95% CI −2.02 to −0.73) for intra-operative pain, and pre-emptive oral analgesics (SMD = −0.77, 95% CI −1.21 to −0.33) for reducing post-operative pain in children receiving routine dental care. Conclusion: The GRADE results for these interventions were strong recommendation (IB) for their use, based on moderate evidence and their benefits far outweighing the harm, and they can be delivered readily with minimal training to reduce the pain experience of paediatric patients.

Hydrogeology is a crucial branch of Earth science dedicated to deciphering the complex interactions between groundwater and the lithosphere, hydrosphere, atmosphere, and biosphere [...]

The purpose of this research is to solve the complex long-distance and high-lift water supply engineering accident water hammer protection problem. Taking the Zhaojinzhuang water supply project as an example, based on the method of characteristics (MOC), the water hammer of the pumping station under the combined action of a water hammer relief valve, hydraulic-control butterfly valve, air vessel, air valve, and other water hammer protection measures is numerically simulated and calculated, and the effectiveness of the range method is analyzed, to ensure a waterproof hammer in pump stop accidents. The results show that the main factors affecting the effect of water hammer protection under the two-stage valve-closing parameters of the hydraulic-control butterfly valve are the fast-closing angle and the slow-closing time. The arrangement of the air vessel behind the pump can effectively increase the minimum water hammer pressure in the climbing section, and with the increase of the volume of the air vessel, the pump reverse speed and the maximum positive pressure increase slightly, but the overall water hammer protection effect is better. With the increase of the moment of inertia of the motor, the maximum positive pressure and minimum negative pressure of the pipeline still do not meet the requirements of the specification, and the modification cost is relatively large. The combination of the one-stage hydraulic-control butterfly valve, the air valve, the air vessel, and the water hammer relief valve can effectively reduce the volume of the air vessel. Under the optimal method, the maximum positive pressure head is 236.61 m, and the minimum negative pressure head is −3.18 m. Compared with the original method, the maximum positive pressure head is increased by 1.18%, the minimum negative pressure head is reduced by 95.78%, the maximum reverse speed of the pump is reduced by 100%, and the maximum reverse flow of the pump is reduced by 70.27%, meeting the requirements of water hammer protection. This is a safe and economical protection method.

Abstract The Yangtze River Basin (YRB) is the birthplace of Chinese civilization and is rich in traditional village resources. Studying their spatial distribution characteristics and influencing factors can guide the protection, inheritance, and development of traditional villages in YRB. This study takes 5 batches of 3346 traditional villages in YRB since 2012 as the research object. Using the nearest neighbor index, kernel density analysis, standard deviation ellipse, and Geodetector model, we analyzed the spatial distribution characteristics of traditional villages in YRB and detected their influencing factors. The results show that the distribution of traditional villages in YRB exhibited a spatial pattern of cohesive clusters, forming a high-density area and development center in the junction zone between Guizhou and Hunan provinces and southeast of Anhui Province, and secondary-density areas in Northeast Yunnan Province and east Jiangxi Province. The results of the Geodetector show that the formation of the spatial distribution pattern of traditional villages in YRB is affected by the combined effects of natural and socio-economic factors, among which elevation and NDVI were the main factors, and the interaction of multiple factors showed an enhanced trend. The findings of this study can provide scientific decision-making support for the development and protection of traditional villages in YRB.

Abstract Background To investigate the application effect of artificial intelligence (AI)-based fundus screening system in real-world clinical environment. Methods A total of 637 color fundus images were included in the analysis of the application of the AI-based fundus screening system in the clinical environment and 20,355 images were analyzed in the population screening. Results The AI-based fundus screening system demonstrated superior diagnostic effectiveness for diabetic retinopathy (DR), retinal vein occlusion (RVO) and pathological myopia (PM) according to gold standard referral. The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of three fundus abnormalities were greater (all > 80%) than those for age-related macular degeneration (ARMD), referable glaucoma and other abnormalities. The percentages of different diagnostic conditions were similar in both the clinical environment and the population screening. Conclusions In a real-world setting, our AI-based fundus screening system could detect 7 conditions, with better performance for DR, RVO and PM. Testing in the clinical environment and through population screening demonstrated the clinical utility of our AI-based fundus screening system in the early detection of ocular fundus abnormalities and the prevention of blindness.

Abstract Aims Prognosis for ST‐segment elevation myocardial infarction (STEMI) is worse when heart failure is present on admission. Understanding clinical practice in different health systems can identify areas for quality improvement initiatives to improve outcomes. In the absence of international comparison studies, we aimed to compare treatments and in‐hospital outcomes of patients admitted with ST elevation myocardial infarction (STEMI) by heart failure status in two healthcare‐wide cohorts. Methods and results We used two nationwide databases to capture admissions with STEMI in the United Kingdom (Myocardial ischemia National Audit Project, MINAP) and Japan (Japanese Registry of All Cardiac and Vascular Diseases‐Diagnostic Procedure Combination, JROAD‐DPC) between 2012 and 2017. Participants were stratified using the HF Killip classification into three groups; Killip 1: no congestive heart failure, Killip 2–3: congestive heart failure, Killip 4: cardiogenic shock. We calculated crude rate and case mix standardized risk ratios (CSRR) for use of treatments and in‐hospital death. Patients were younger in the United Kingdom (65.4 [13.6] vs. 69.1 [13.0] years) and more likely to have co‐morbidities in the United Kingdom except for diabetes and hypertension. Japan had a higher percentage of heart failure and cardiogenic shock patients among STEMI during admission than that in the United Kingdom. Primary percutaneous coronary intervention (pPCI) rates were lower in the United Kingdom compared with Japan, especially for patients presenting with Killip 2–3 class heart failure (pPCI use in patients with Killip 1, 2–3, 4: Japan, 86.2%, 81.7%, 78.7%; United Kingdom, 79.6%, 58.2% and 79.9%). In contrast, beta‐blocker use was consistently lower in Japan than in the United Kingdom (61.4% vs. 90.2%) across Killip classifications and length of hospital stay longer (17.0 [9.7] vs. 5.0 [7.4] days). The crude rate of in‐hospital mortality increased with increasing Killip class group. Both the crude rate and CSRR was higher in the United Kingdom compared with Japan for Killip 2–3 (15.8% vs. 6.4%, CSRR 1.80 95% CI 1.73–1.87, P

Despite the connection of secretory cells to distinct mucus‐containing colon cancer histological subtypes and the interaction of secretory cells with immune cells in the pathogenesis of intestinal inflammatory diseases, whether the secretory cell signatures are associated with tumor microenvironment (TME) heterogeneity and can aid in colon cancer patient classification have not been investigated. Here, by performing the principal component analysis and consensus clustering analysis, we identified four distinct expression patterns based on secretory cell signatures which were significantly associated with different clinical behaviors, TME landscape, pathway activation, genomic mutations, and DNA methylation characteristics. Subsequently, a ‘SCS score’ model was constructed. The high SCS score indicated a pattern of ‘secretory cell subtype 2’, which was characterized by stromal infiltration and activation, and predicted poor prognosis and low sensitivity to fluorouracil‐based chemotherapy and immunotherapy, but high sensitivity to PI3K catalytic subunit inhibitors. In conclusion, our study comprehensively uncovered the tumor heterogeneity related to secretory cell signature expression patterns. Moreover, the SCS score can supplement routine histopathological assessments to guide personalized therapeutic strategies in colon cancer patients.

Carpal tunnel syndrome (CTS) is a common peripheral neuropathy of the hand, mainly manifesting as sensory disturbances, motor dysfunctions, and pain in the fingers and hand. The pathogenesis of the disease is associated with fibrosis of the transverse carpal ligament in the carpal tunnel, which compresses median nerve. In our case, we demonstrate an ultrasound-guided needle knife technique to treat CTS. We guided the patient to a supine position on the examination table. The skin of the wrist area was sterilized for the procedure. After the skin was dry, we positioned sterile drapes, located the median nerve and compression, and marked the compression point. Local anesthesia was administered. An ultrasound-guided needle knife was inserted. The needle knife was advanced under ultrasound guidance. The carpal ligament was incised. A gradual release of pressure on the median nerve was observed on the ultrasound monitor. After treatment, the patient’s finger sensation and motor function can significantly improve, and pain symptoms are markedly reduced, this case demonstrates that small needle-knife treatment can serve as a safe and effective minimally invasive therapeutic method.

Introduction Atrial fibrillation (AF) is associated with a fivefold increased risk of stroke. Oral anticoagulation reduces the risk of stroke, but AF is elusive. A machine learning algorithm (Future Innovations in Novel Detection of Atrial Fibrillation (FIND-AF)) developed to predict incident AF within 6 months using data in primary care electronic health records (EHRs) could be used to guide AF screening. The objectives of the FIND-AF pilot study are to determine yields of AF during ECG monitoring across AF risk estimates and establish rates of recruitment and protocol adherence in a remote AF screening pathway.Methods and analysis The FIND-AF Pilot is an interventional, non-randomised, single-arm, open-label study that will recruit 1955 participants aged 30 years or older, without a history of AF and eligible for oral anticoagulation, identified as higher risk and lower risk by the FIND-AF risk score from their primary care EHRs, to a period of remote ECG monitoring with a Zenicor-ECG device. The primary outcome is AF diagnosis during ECG monitoring, and secondary outcomes include recruitment rates, withdrawal rates, adherence to ECG monitoring and prescription of oral anticoagulation to participants diagnosed with AF during ECG monitoring.Ethics and dissemination The study has ethical approval (the North West—Greater Manchester South Research Ethics Committee reference 23/NW/0180). Findings will be announced at relevant conferences and published in peer-reviewed journals in line with the Funder’s open access policy.Trial registration number NCT05898165.

Objective Risk-guided atrial fibrillation (AF) screening may be an opportunity to prevent adverse events in addition to stroke. We compared events rates for new diagnoses of cardio-renal-metabolic diseases and death in individuals identified at higher versus lower-predicted AF risk.Methods From the UK Clinical Practice Research Datalink-GOLD dataset, 2 January 1998–30 November 2018, we identified individuals aged ≥30 years without known AF. The risk of AF was estimated using the FIND-AF (Future Innovations in Novel Detection of Atrial Fibrillation) risk score. We calculated cumulative incidence rates and fit Fine and Gray’s models at 1, 5 and 10 years for nine diseases and death adjusting for competing risks.Results Of 416 228 individuals in the cohort, 82 942 were identified as higher risk for AF. Higher-predicted risk, compared with lower-predicted risk, was associated with incident chronic kidney disease (cumulative incidence per 1000 persons at 10 years 245.2; HR 6.85, 95% CI 6.70 to 7.00; median time to event 5.44 years), heart failure (124.7; 12.54, 12.08 to 13.01; 4.06), diabetes mellitus (123.3; 2.05, 2.00 to 2.10; 3.45), stroke/transient ischaemic attack (118.9; 8.07, 7.80 to 8.34; 4.27), myocardial infarction (69.6; 5.02, 4.82 to 5.22; 4.32), peripheral vascular disease (44.6; 6.62, 6.28 to 6.98; 4.28), valvular heart disease (37.8; 6.49, 6.14 to 6.85; 4.54), aortic stenosis (18.7; 9.98, 9.16 to 10.87; 4.41) and death from any cause (273.9; 10.45, 10.23 to 10.68; 4.75). The higher-risk group constituted 74% of deaths from cardiovascular or cerebrovascular causes (8582 of 11 676).Conclusions Individuals identified for risk-guided AF screening are at risk of new diseases across the cardio-renal-metabolic spectrum and death, and may benefit from interventions beyond ECG monitoring.

Summary: Background: Knowledge of post-myocardial infarction (MI) disease risk to date is limited—yet the number of survivors of MI has increased dramatically in recent decades. We investigated temporally ordered sequences of all conditions following MI in nationwide electronic health record data through the application of process mining. Methods: We conducted a national retrospective cohort study of all hospitalisations (145,670,448 episodes; 34,083,204 individuals) admitted to NHS hospitals in England (1st January 2008–31st January 2017, final follow-up 27th March 2017). Through process mining, we identified trajectories of all major disease diagnoses following MI and compared their relative risk (RR) and all-cause mortality hazard ratios (HR) to a risk-set matched non-MI control cohort using Cox proportional hazards and flexible parametric survival models. Findings: Among a total of 375,669 MI patients (130,758 females; 34.8%) and 1,878,345 matched non-MI patients (653,790 females; 34.8%), we identified 28,799 unique disease trajectories. The accrual of multiple circulatory diagnoses was more common amongst MI patients (RR 4.32, 95% CI 3.96–4.72) and conferred an increased risk of death (HR 1.32, 1.13–1.53) compared with matched controls. Trajectories featuring neuro-psychiatric diagnoses (including anxiety and depression) following circulatory disorders were markedly more common and had increased mortality post MI (HR ranging from 1.11 to 1.73) compared with non-MI individuals. Interpretation: These results provide an opportunity for early intervention targets for survivors of MI—such as increased focus on the psychological and behavioural pathways—to mitigate ongoing adverse disease trajectories, multimorbidity, and premature mortality. Funding: British Heart Foundation; Alan Turing Institute.

Summary: Background: Whether the accuracy of the phenotype ascribed to patients in electronic health records (EHRs) is associated with variation in prognosis and care provision is unknown. We investigated this for heart failure (HF, characterised as HF with preserved ejection fraction [HFpEF], HF with reduced ejection fraction [HFrEF] and unspecified HF). Methods: We included individuals aged 16 years and older with a new diagnosis of HF between January 2, 1998 and February 28, 2022 from linked primary and secondary care records in the Clinical Practice Research Datalink in England. We investigated the provision of guideline-recommended diagnostic investigations and pharmacological treatments. The primary outcome was a composite of HF hospitalisation or all-cause death, and secondary outcomes were time to HF hospitalisation, all-cause death and death from cardiovascular causes. We used Kaplan–Meier curves and log rank tests to compare survival across HF phenotypes and adjusted for potential confounders in Cox proportional hazards regression analyses. Findings: Of a cohort of 95,262 individuals, 1271 (1.3%) were recorded as having HFpEF, 10,793 (11.3%) as HFrEF and 83,198 (87.3%) as unspecified HF. Individuals recorded as unspecified HF were older with a higher prevalence of dementia. Unspecified HF, compared to patients with a recorded HF phenotype, were less likely to receive specialist assessment, echocardiography or natriuretic peptide testing in the peri-diagnostic period, or receive angiotensin-converting enzyme inhibitors, beta blockers or mineralocorticoid receptor antagonists up to 12 months after diagnosis (risk ratios compared to HFrEF, 0.64, 95% CI 0.63–0.64; 0.59, 0.58–0.60; 0.57, 0.55–0.59; respectively) and had significantly worse outcomes (adjusted hazard ratios compared to HFrEF, HF hospitalisation and death 1.66, 95% CI 1.59–1.74; all-cause mortality 2.00, 1.90–2.10; cardiovascular death 1.77, 1.65–1.90). Interpretation: Our findings suggested that absence of specification of HF phenotype in routine EHRs is inversely associated with clinical investigations, treatments and survival, representing an actionable target to mitigate prognostic and health resource burden. Funding: Japan Research Foundation for Healthy Aging and British Heart Foundation.

In today’s leaf disease detection, the accuracy of recognition has never been of such importance as it is now. In this aspect, leaf disease recognition method based on machine learning relies heavily on the size of the region of interest and the dispersion of lesions. Professional instrument for leaf disease detection remains a challenging task in accuracy and convenience. A new lightweight model based on advanced residual network and attention mechanism for extracting more accurate region of interest and the lesion, SE-VRNet, was proposed. The proposed SE-VRNet incorporated deep variant residual network (VRNet) and a squeeze-and-excitation (SE) module with attention mechanism, in order to solve the problem that the feature extraction was difficult due to the dispersed location of the leaf disease. The accuracy of top-1 and top-3 obtained by the model SE-VRNet on NewData is 99.73% and 99.98%, respectively, and the accuracy of top-1 and top-3 obtained by the model on SelfData is 95.71% and 99.89%, respectively. The experimental results on the datasets of PlantVillage, OriData, NewData and SelfData were better than other state-of-the-art methods, demonstrating the effectiveness and feasibility of the proposed SE-VRNet in identifying leaf diseases with mobile devices.

Abstract Dry eye disease (DED) is a common disease associated with disorder of tear secretion. Research on risk factors for DED, such as depression, arthritis, thyroid disease, stroke and diabetes, is important to facilitate its diagnosis and prognosis. We created a dataset on risk factors for DED (DrDED) with public access that can provide up-to-date and validated data acquired from systematically searched and screened, high-quality studies. The established DrDED contained 119 studies published between 2000 and 2022. The range of the study sample size was from 43 to 4,871,504. The study types were, as follows: cross-sectional (n = 92), retrospective cohort (n = 9), prospective cohort (n = 10), and case-control (n = 8) studies. Data from eligible studies were collected and presented for the present study, including the publication information, study characteristics, definition and prevalence of the disease, and risk factors for DED, together with the strength of association. With the publication of new relevant studies, the DrDED will be updated, and the data will be made accessible to the users. Design Type(s) Dataset creation objective Measurement Type(s) Patient outcome • scientific publication • risk factors • dry eye disease Technology Type(s) Digital curation • documenting • meta-analysis Factor Type(s) Depression • arthritis • thyroid disease • stroke disease • diabetes Sample Characteristic(s) Homo sapiens • dry eye disease • global

AbstractDicer is an RNaseIII in microRNA processing that modulates multiple biological processes including tumorigenesis. We have shown that Dicer could inhibit the growth of hepatocellular carcinoma (HCC) previously [Zhang L, Wang C, Liu S, Zhao Y, et al. Oncol Lett 2016;11:3961-3966]. Here, we evaluated the relationships between Dicer and reactive oxygen species (ROS) as well as their modulation for HCC. We found Dicer expression was positively associated with ROS generation in HCC tissue at borderline statistical levels (p = .065); functional analysis showed Dicer could both induce the ROS generation (p

The No.4 tailings pond of the Dexing Copper Mine is the second largest in Asia. The tailing pond is a dangerous source of man-made debris flow with high potential energy. In view of the lack of effective and low-cost global safety monitoring means in this region, in this paper, the time-series InSAR technology is innovatively introduced to monitor the deformation of tailings dam and significant key findings are obtained. First, the surface deformation information of the tailings pond and its surrounding areas was extracted by using SBAS-InSAR technology and Sentinel-1A data. Second, the cause of deformation is explored by analyzing the deformation rate, deformation accumulation, and three typical deformation rate profiles of the representative observation points on the dam body. Finally, the power function model is used to predict the typical deformation observation points. The results of this paper indicated that: (1) the surface deformation of the tailings dam can be categorized into two directions: the upper portion of the dam moving away from the satellite along the Line of Sight (LOS) at a rate of −40 mm/yr, whereas the bottom portion approaching the satellite along the LOS at a rate of 8 mm/yr; (2) the deformation of the dam body is mainly affected by the inventory deposits and the construction materials of the dam body; (3) according to the current trend, deformation of two typical observation points in the LOS direction will reach the cumulative deformation of 80 mm and −360 mm respectively. The research results can provide data support for safety management of No.4 tailings dam in the Dexing Copper Mine, and provide a method reference for monitoring other similar tailings dams.

This editorial introduces the Special Issue titled “Water Resources and Sustainable Development,” underscoring the critical need for sustainable management of water resources in light of increasing demand, climate change impacts, and pollution. The issue delves into the intricate relationship between water availability, quality, utilization, and the socioeconomic determinants shaping these aspects, highlighting the necessity for novel, balanced strategies that cater to societal, economic, and environmental requirements. The research within this Special Issue is segmented into four key areas: understanding hydrochemical properties and water quality; evaluating anthropogenic effects on water resources; strategizing water resource management; and applying technological innovations in water resource management. Collectively, these studies broaden our comprehension of water resources and sustainable development, stressing the importance of continuous research in this sphere. As we look ahead, this editorial accentuates the importance of ongoing exploration and innovation in these pivotal areas, focusing on understanding climate change implications, mitigating human-induced impacts, refining water management strategies, and harnessing technological advancements. Its overarching aim is to propel worldwide initiatives towards achieving comprehensive water security and sustainability.

The development of catalysts for low-temperature methane combustion is crucial in addressing the greenhouse effect. An effective industrial catalyst strategy involves optimizing noble metal utilization and boosting metal–metal interaction. Here, the PdNi-H catalyst was synthesized using the self-assembly method, achieving the high dispersion and close proximity of Pd and Ni atoms compared to the counterparts prepared by the impregnation method, as confirmed by EDS mapping. The XRD and TEM results revealed Pd2+ and Ni2+ doping within the CeO2 lattice, causing distortions and forming Pd-O-Ce or Ni-O-Ce structures. These structures promoted oxygen vacancy formation in CeO2, and this was further confirmed by the Raman and XPS results. Consequently, the PdNi-H catalyst demonstrated an excellent redox ability and catalytic activity, achieving lower ignition and complete methane burning temperatures at 282 and 387 °C, respectively. The highly dispersed PdNi species played a pivotal role in activating methane for enhanced redox ability. Additionally, the narrow size distribution range contributed to more vacancies on the surface of CeO2, as confirmed by the XPS results, thereby facilitating the activation of gas phase oxygen to form oxygen species (O2−). This collaborative catalytic approach presents a promising strategy for developing efficient and stable methane combustion catalysts at low temperatures.

Background: Understanding predictors of pain associated with paediatric dental procedures could play an important role in preventing loss of cooperation, which often leads to the procedure having to be performed under general anaesthesia. Aim: We aimed to identify predictors of intra-operative and post-operative pain associated with routine dental procedures in children. Materials and Methods: A systematic review of observational studies was performed using electronic searches on MEDLINE, EMBASE, PsycINFO, Global Health via OVID, PubMed, Scopus, and SciELO. The NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was used to evaluate the quality of the included studies, which were meta-analysed to estimate the impact of dental procedures and anxiety on children’s pain perception. A meta-regression analysis was also performed to determine the relative effect of predictors on children’s pain perception measured as mean differences on a visual analogue scale (VAS). Results: The search identified 532 articles; 53 were retrieved for full-text screening; 6 studies were included in the review; and 4 were eligible for the meta-analysis. The meta-analysis showed the types of procedures that predicted intra-operative pain, with dental extractions being the most painful (Mean VAS Difference [MD] 46.51 mm, 95% confidence interval [CI] 40.40 to 52.62 mm). The meta-regression showed that pain scores for dental extractions were significantly higher than polishing (the least painful procedure (reference category)) by VAS MD = 23.80 mm (95% CI 5.13–42.46 mm, p-value = 0.012). It also showed that highly anxious children reported significantly higher pain scores during dental procedures by a 12.31 mm MD VAS score (95% CI 5.23–19.40 mm, p-value = 0.001) compared to those with low anxiety levels. Conclusions: This systematic review demonstrates that the strongest predictors of intra-operative pain associated with paediatric dental procedures are dental extractions followed by drilling. Children with high anxiety also reported more pain for similar procedures. Tailoring interventions to reduce pain associated with paediatric dental procedures should be a priority for future research, as reducing pain can impact compliance and could reduce the need for general anaesthesia in dental treatment.

Liupao tea as a type of dark tea can relieve irritable bowel syndrome by regulating gut microbiota, but the mechanism has not been fully explained. An ultra-high performance liquid chromatography along with quadrupole time of flight tandem mass spectrometry was used to analyze the phytochemicals in Liupao tea. Then, we explored the effects of Liupao tea against IBS. From the results of chemical analysis, we identified catechins, polyphenols, amino acids, caffeine, polysaccharides and other components in Liupao tea. The open-field test, gastrointestinal function-related indexes, histochemical assays, measurements of cytokine and aquaporin 3 (AQP3), and determination of serum metabolites were utilized to monitor the physiological consequences of Liupao tea administration in rats with irritable bowel syndrome. The results showed that Liupao tea had a significant protective effect on irritable bowel syndrome. Liupao tea increased locomotive velocity while reducing interleukin-6, interleukin-1β, and tumor necrosis factor-α levels, as well as gastrointestinal injury. Moreover, Liupao tea increased the AQP3 levels of renal tissues but reduced the AQP3 levels of gastrointestinal tissues. Liupao tea reduced the Firmicutes/Bacteroides ratio and significantly reconstructed the microbial pattern. Liupao tea relieved irritable bowel syndrome by repairing gastrointestinal dysfunction, regulating the secretion of pro-inflammatory cytokines, modulating water metabolism, and restoring microbial homeostasis.

Abstract Background Calcified nodule (CN) is a type of potentially vulnerable plaque. Its formation mechanism remains unknown. This study was to assess serum marker and computed tomography angiography (CTA) characteristics of CN validated by intravascular ultrasound (IVUS). Methods Patients who underwent coronary CTA followed by invasive coronary angiography and IVUS were retrospectively analyzed. Serum levels of alkaline phosphatase (ALP), gamma-glutamyltransferase, and calcium were collected. Results IVUS detected 128 de novo calcified lesions in 79 patients with coronary artery disease (CAD). CNs were identified in 11.4% (9/79) of patients and 9.4% (12/128) of lesions. Compared with patients with non-nodular calcified plaques, CN patients had higher serum level of ALP (82.00 vs 65.00 U/L, P = 0.022) and total plaque volume (673.00 vs 467.50 mm3, P = 0.021). Multivariable analyses revealed that serum ALP level and total plaque volume were independently associated with the prevalence of CN in CAD patients with calcified plaques. At lesion level, the CN group had a higher frequency of moderate to heavy calcification on angiography (75.00% vs 40.52%, P = 0.017). In terms of CTA characteristics, plaques with CN had a more severe diameter stenosis (79.00% vs 63.00%, P = 0.007), higher plaque burden (85.40% vs 77.05%, P = 0.005), total plaque density (398.00 vs 283.50 HU, P = 0.008), but lower lipid percentage (14.65% vs 19.75%, P = 0.010) and fiber percentage (17.90% vs 25.65%, P = 0.011). Mean plaque burden is an independent predictor of the prevalence of CN in calcified plaques (odds ratio = 1.102, 95% confidence interval: 1.025–1.185, P = 0.009). The AUC is 0.753 (95% confidence interval: 0.615–0.890, P = 0.004). When using 84.85% as the best cutoff value, the diagnostic sensitivity and specificity of mean plaque burden for predicting the presence of CN within calcified plaques were 66.7% and 80.2%, respectively. Conclusions CN had different CTA imaging features from non-nodular coronary calcification. The presence of a CN was associated with a higher serum ALP level and plaque burden.

Introduction: Multiple organ failure is the commonest cause of death in septic patients. Objectives: This study was undertaken in an attempt to elucidate the functional importance of DNA-dependent protein kinase catalytic subunit (DNA-PKcs) on mitochondrial dysfunction associated with the development and progression of sepsis-related multiple organ dysfunction syndrome (MODS). Methods: Cardiomyocyte-specific DNA-PKcs knockout (DNA-PKcsCKO) mice, liver-specific DNA-PKcs knockout (DNA-PKcsLKO) mice, and kidney tubular cell-specific DNA-PKcs knockout (DNA-PKcsTKO) mice were used to generate an LPS-induced sepsis model. Echocardiography, serum biochemistry, and tissue microscopy were used to analyze organ damage and morphological changes induced by sepsis. Mitochondrial function and dynamics were determined by qPCR, western blotting, ELISA, and mt-Keima and immunofluorescence assays following siRNA-mediated DNA-PKCs knockdown in cardiomyocytes, hepatocytes, and kidney tubular cells. Results: DNA-PKcs deletion attenuated sepsis-mediated myocardial damage through improving mitochondrial metabolism. Loss of DNA-PKcs protected the liver against sepsis through inhibition of mitochondrial oxidative damage and apoptosis. DNA-PKcs deficiency sustained kidney function upon LPS stress through normalization of mitochondrial fission/fusion events, mitophagy, and biogenesis. Conclusion: We conclude that strategies targeting DNA-PKcs expression or activity may be valuable therapeutic options to prevent or reduce mitochondrial dysfunction and organ damage associated with sepsis-induced MODS.