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Background: Chinese women tend to have small and dense breasts and ultrasound is a common method for breast cancer screening in China. However, its efficacy and cost comparing with mammography has not been evaluated in randomised trials. Methods: At 14 breast centres across China during 2008–2010, 13 339 high-risk women aged 30–65 years were randomised to be screened by mammography alone, ultrasound alone, or by both methods at enrolment and 1-year follow-up. Results: A total of 12 519 and 8692 women underwent the initial and second screenings, respectively. Among the 30 cancers (of which 15 were stage 0/I) detected, 5 (0.72/1000) were in the mammography group, 11 (1.51/1000) in the ultrasound group, and 14 (2.02/1000) in the combined group (P=0.12). In the combined group, ultrasound detected all the 14 cancers, whereas mammography detected 8, making ultrasound more sensitive (100 vs 57.1%, P=0.04) with a better diagnostic accuracy (0.999 vs 0.766, P=0.01). There was no difference between mammography and ultrasound in specificity (100 vs 99.9%, P=0.51) and positive predictive value (72.7 vs 70.0% P=0.87). To detect one cancer, the costs of ultrasound, mammography, and combined modality were $7876, $45 253, and $21 599, respectively. Conclusions: Ultrasound is superior to mammography for breast cancer screening in high-risk Chinese women.

As a typical sedimentary rock, coal seams are usually rich in bedding planes, which significantly affect the propagation process of hydraulic fracture (HF) network and reservoir permeability. In this study, the profile characteristics and the bedding roughness of the coal seam at depth of 2800 m from Daniudi Gas Field in China is investigated. The failure mechanism of shear-expansion effect under low pressure and dynamic shear under high pressure of coal beddings induced by the dissolution-corrosion effect of fracturing liquid is analyzed. The development process of HF network under different bedding angles, joint roughness coefficients (JRCs), stress differences, and confining pressures is numerically simulated by cohesive element method. Results show that the JRC of coal beddings has significant effects on the morphology of HF networks. When the JRC exceeds 15, a HF network structure with tensile main fractures and shear secondary cracks is developed. The shear fractures account for a considerable proportion (33-66%) multi-layer layered coal seams and should be taken seriously during reservoir reconstruction. As confining pressure increases, the total length of tensile HFs sharply decreases, while the change in the total length of shear HFs is not significant. When the confining pressure increases from 5 to 15 MPa, the length ratio of shear HFs to tensile hydraulic fractures increases from 0.36 to about 1, confirming that increasing confining pressure can promote the transformation of HF failure types from tension to shear. The ratio of secondary crack to main crack length is between 6.31 and 9.78, indicating the secondary fractures occupy an absolute proportion in the hydraulic fracture network. This study is of significance for understanding the hydraulic fracture network development in coal reservoirs., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Laser speckle contrast imaging (LSCI) is an optical technique used to assess blood flow perfusion by modeling changes in speckle intensity, but it is generally limited to qualitative analysis due to difficulties in absolute quantification. Three-dimensional convolutional neural networks (3D CNNs) enhance the quantitative performance of LSCI by excelling at extracting spatiotemporal features from speckle data. However, excessive downsampling techniques can lead to significant information loss. To address this, we propose a hybrid quantum-classical 3D CNN framework that leverages variational quantum algorithms (VQAs) to enhance the performance of classical models. The proposed framework employs variational quantum circuits (VQCs) to replace the 3D global pooling layer, enabling the model to utilize the complete 3D information extracted by the convolutional layers for feature integration, thereby enhancing velocity prediction performance. We perform cross-validation on experimental LSCI speckle data and demonstrate the superiority of the hybrid models over their classical counterparts in terms of prediction accuracy and learning stability. Furthermore, we evaluate the models on an unseen test set and observe that the hybrid models outperform the classical models with up to 14.8% improvement in mean squared error (MSE) and up to 26.1% improvement in mean absolute percentage error (MAPE) evaluation metrics. Finally, our qualitative analysis shows that the hybrid models offer substantial improvements over classical models in predicting blood flow at both low and high velocities. These results indicate that the hybrid models possess more powerful learning and generalization capabilities., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Depression frequently comorbidities with cancer, adversely affecting survivors' quality of life. Liver dysfunction is also prevalent among cancer survivors. However, the association between these two conditions remains unclear. This study aimed to explore the relationship between depression and liver function biomarkers in US cancer survivors. A cross-sectional study was conducted utilizing data from the National Health and Nutrition Examination Survey (NHANES) 2005-2020. Cancer survivors were screened and depression was assessed using the Patient Health Questionnaire-9 (PHQ-9), and 18 liver function biomarkers were included. Survey-weighted generalized linear models with multiple covariables adjusted were employed to examine the associations between depression and liver function biomarkers. A total of 4118 cancer survivors were included, representing a weighted population of 21 501 237. After adjusted with age, gender, race, marital status, education level, family income-to-poverty ratio, and number of cancer types, 8 biomarkers demonstrated positive correlations with depression in cancer survivors, included alanine aminotransferase (ALT, OR = 1.007, 95% CI: 1.000 to 1.013), alkaline phosphatase (ALP, 1.006 [1.002, 1.010]), gamma glutamyl transferase (GGT, 1.004 [1.001, 1.007]), lactate dehydrogenase (LDH, 1.004 [1.000, 1.009]), total protein (TP, 1.040 [1.009, 1.072]), globulin (GLB, 1.060 [1.030, 1.091]), total cholesterol (TC) to high-density lipoprotein cholesterol (HDL-C) ratio (1.162 [1.050, 1.286]), and low-density lipoprotein cholesterol (LDL-C) to HDL-C ratio (1.243 [1.012, 1.526]); while 4 other biomarkers exhibited negative correlations, included HDL-C (0.988 [0.980, 0.997]), total bilirubin (TBi, 0.501 [0.284, 0.883]), aspartate aminotransferase (AST) to ALT ratio (0.588 [0.351, 0.986]), albumin (ALB) to GLB ratio (0.384 [0.229, 0.642]). Following sensitivity analysis, 5 biomarkers included LDH, HDL-C, TBi, AST/ALT and LDL-C/HDL-C lost their statistical significance for the association. This study identified certain associations between 7 liver function biomarkers and depression in US cancer survivors. Further research, particularly prospective longitudinal studies, is warranted to elucidate the causal relationships and explore the potential of improving liver function for the management of depression in cancer patients., Competing Interests: Declarations Competing interests The authors declare no competing interests. Ethics approval and consent to participate All the NHANES protocols were approved by the Ethics Review Board of U.S. National Center for Health Statistics, and written informed consents were obtained from all participants of NAHNES surveys., (© 2024. The Author(s).)

Using acrylic acid advanced ester and styrene as raw materials, the long-chain polyester polymer, polyacrylic acid advanced ester-styrene pour point depressant (P-PPD), was synthesized by molecular design, and its structure was characterized by infrared spectroscopy and nuclear magnetic resonance. In addition, this study experimentally investigated the effect of P-PPD on the phase equilibrium and induction time of natural gas hydrate inhibitors in deionized water (DW) and crude oil/water (O/W) systems, respectively. Polyvinylpyrrolidone (PVP) and mono ethylene glycol (EG) were selected as representatives of kinetic hydrate inhibitor (KHIs) and thermodynamic hydrate inhibitor (THIs), respectively. The results exhibit that P-PPD played a sight role in the phase equilibrium of hydrate, while the addition of P-PPD significantly prolonged the induction time of methane hydrate both in O/W + PVP, OW + EG and O/W + PVP + EG system, indicating that the addition of as-synthesized PPD has a synergistic inhibition effect on the nucleation ability of methane hydrate and can prevent hydrate from formatting during oil and gas transport process, and thus guarantee the flow assurance. The findings of this work will provide a data reference for the hybrid use of hydrate inhibitors and pour point depressants in oil and gas transport., (© 2024. The Author(s).)

Several clinical trials have been conducted to evaluate the use of flavopiridol (FP) to treat a variety of cancers, and almost all cancer drugs were found to be associated with toxicity and side effects. It is not clear whether the use of FP will affect the female reproductive system. Granulosa cells, as the important cells that constitute the follicle, play a crucial role in determining the reproductive ability of females. In this study, we investigated whether different concentrations of FP have a toxic effect on the growth of immortalized human ovarian granulosa cells. The results showed that FP had an inhibitory effect on cell proliferation at a level of nanomole concentration. FP reduced cell proliferation and induced apoptosis by inducing mitochondrial dysfunction and oxidative stress, as well as increasing BAX/BCL2 and pCDK1 levels. These results suggest that toxicity to the reproductive system should be considered when FP is used in clinical applications., (© 2024. The Author(s).)

Digital transformation in the architecture industry encounters challenges such as data silos within design stages, between design and construction, and across the entire industry chain, including BIM and project management. This study introduces a pioneering approach for seamlessly integrating building information modeling (BIM) and product lifecycle management (PLM) within the management framework and collaborative workflows of architectural design and construction. The proposed methodology was implemented in two major projects, namely, the Wuhan Next-Generation Weather Radar Construction Project and the Hubei Center for Disease Control and Prevention Comprehensive Capacity Enhancement Project (Phase I), with the former being China's first end-to-end digitally integrated construction project. Compared with traditional projects, these implementations achieved improvements of 24.39% and 38.04%, respectively, in objective function values. The findings highlight the unique advantages of BIM-PLM integration in optimizing lifecycle management, enhancing cross-disciplinary, cross-enterprise, and cross-regional collaboration, improving project design efficiency and quality, and reducing costs and waste. This integration provides valuable insights into the digital advancement of the construction industry., (© 2024. The Author(s).)

Induced pluripotent stem cell (iPSC) technology, in combination with electrophysiological characterization via multielectrode array (MEA), has facilitated the utilization of iPSC-derived motor neurons (iPSC-MNs) as highly valuable models for underpinning pathogenic mechanisms and developing novel therapeutic interventions for motor neuron diseases (MNDs). However, the challenge of MN adherence to the MEA plate and the heterogeneity presented in iPSC-derived cultures raise concerns about the reproducibility of the findings obtained from these cellular models. We discovered that one novel factor modulating the electrophysiological activity of iPSC-MNs is the extracellular matrix (ECM) used in the coating to support in vitro growth, differentiation and maturation of iPSC-MNs. The current study showed that two coating conditions, namely, Poly-L-ornithine/Matrigel (POM) and Polyethyleneimine (PEI) strongly promoted attachment of iPSC-MNs on MEA culture dishes compared to three other coating conditions, and both facilitated the maturation of iPSC-MNs as characterized by the detection of extensive electrophysiological activities from the MEA plates. POM coating accelerated the maturation of the iPSC-MNs for up to 5 weeks, which suits modeling of neurodevelopmental disorders. However, the application of PEI resulted in more even distribution of the MNs on the culture dish and reduced variability of electrophysiological signals from the iPSC-MNs in 7-week cultures, which permitted the detection of enhanced excitability in iPSC-MNs from patients with amyotrophic lateral sclerosis (ALS). This study provides a comprehensive comparison of five coating conditions and offers POM and PEI as favorable coatings for in vitro modeling of neurodevelopmental and neurodegenerative disorders, respectively., (© 2024. The Author(s).)

Observational studies and clinical trials have suggested the relationship between the gut microbiome and respiratory diseases, but the causality between them remains unclear. Firstly, we selected eight respiratory diseases Genome-wide association study (GWAS) datasets mainly from the FinnGen collaboration as outcomes. The exposure was based on GWAS statistics about the gut microbiome, sourced from the MiBioGen consortium, including gut microbial taxa. The causal link between the gut microbiome and respiratory illnesses was then estimated using a Two-sample Mendelian randomization (MR) analysis, including the inverse-variance weighted (IVW), weighted median, MR-Egger, simple mode, and weighted mode. To ensure reliability, F-statistics and sensitivity tests were conducted. Furthermore, we performed a reverse MR analysis of the pre-Mendelian positive findings to possible reverse causality. For the 196 gut microbe taxa, the IVW analysis suggested 88 potential associations with eight clinically prevalent respiratory diseases. Among them, 30 causal associations were found in more than one MR method. Multiple statistical corrections have confirmed three causal associations: genus Holdemanella was a risk factor for chronic obstructive pulmonary disease (COPD) (P = 1.3 × 10 -4 , OR = 1.18), family FamilyXIII was a protective factor for COPD (P = 1.3 × 10 -3 , OR = 0.75), and genus Oxalobacter was a risk factor for asthma (P = 2.1 × 10 -4 , OR = 1.09). Our MR analysis results indicate that there would be a causal relationship between the gut microbiome and respiratory diseases, contributing to the gut-lung axis. This finding offers new insights into the gut microbiome's roles in respiratory diseases' clinical prevention, pathogenesis, and improvement of clinical symptoms. Further randomized controlled trials are necessary to clarify the protective effect of probiotics and fecal microbial transplantation on respiratory health., (© 2024. The Author(s).)

Prostate cancer is one of the most common cancers in men and poses a significant threat to global male health. Traditional prostate cancer assessment methods have certain limitations, necessitating the identification of new prognostic factors and treatment targets. Our study revealed that low expression of the cornichon family AMPA receptor auxiliary protein 2 (CNIH2) gene was associated with a better progression-free survival rate in prostate cancer patients. The area under the receiver operating characteristic (ROC) curve (AUC) showed that the prognostic ability of the CNIH2 gene was high at 1, 3, and 5 years. The gene was an independent prognostic factor according to multivariate analysis. Functional verification experiments showed that knocking down the CNIH2 gene could inhibit the proliferation, migration and invasion of prostate cancer cells and could also inhibit tumor growth in nude mice. Our study is the first to reveal the important role of the CNIH2 gene in prostate cancer. This discovery provides a new research direction for individualized treatment and prognostic evaluation of prostate cancer., (© 2024. The Author(s).)

The interaction of microalgae on the reinforced concrete with corrosion inhibitor is not well understood. Moreover, the inhibition role of microalgae on corrosion has been reported in recent years. In this study, the corrosion inhibition behavior of Q235 carbon steel (CS) due to the presence of Chlorella sp. and benzotriazole (BTA) in alkaline artificial seawater was investigated by means of weight loss, electrochemical measurements including open circuit potential, electrochemical impedance spectroscopy, and potentiodynamic polarization curves, and surface analysis including scanning electron microscopy, energy dispersion spectrometer, and X-ray photoelectron spectroscopy. The results of reduced corrosion rates in the algae-BTA system demonstrated that Chlorella sp. could facilitate the corrosion inhibition efficiency of BTA on the CS specimens. Moreover, polarization measurement showed the algae-BTA system had a mixed-type corrosion inhibition effect. The mechanisms of inhibition were proposed to be the precipitation of iron complexes such as Fe-BTA-EPS and Fe-BTA and iron compounds on the steel surface in the presence of the microalgae and BTA - . This study highlights the application of CS corrosion control by combining biological and chemical approaches that can be used for future research and practice, rather than purely chemical approaches., (© 2024. The Author(s).)

Against the backdrop of digitization and global warming, fintech plays a crucial role in accelerating the growth of green finance, driving innovation in the financial industry, and catalyzing the low-carbon transformation of economic activities. This paper utilizes city panel data from 2007 to 2019 to examine the direct impact of fintech on carbon emission efficiency (CEE), the transmission channels of green technological innovation and green finance, and the spatial spillover effects, using dynamic panel models, mediation effect models, and dynamic spatial Durbin models (SDM). The study finds that: (i) Fintech significantly improves CEE, and this conclusion remains robust after accounting for potential endogeneity issues and conducting robustness tests. (ii) Mechanism analysis reveals that green finance and green technological innovation are the primary channels through which fintech influences CEE. (iii) Results from the dynamic SDM model indicate that fintech has a significant positive spatial spillover effect on CEE, with the long-term spillover effect being smaller than the short-term spillover effect. (iv) Heterogeneity analysis reveals that fintech's improvement effect on CEE is mainly evident in eastern regions, emerging first-tier and first-tier cities, and non-resource-based cities. Our research provides new insights for policymakers on achieving China's dual-carbon goals through the promotion of fintech development, green finance, and green technological innovation. It also aids in the coordinated development of fintech among cities and the formulation of differentiated policies, providing a theoretical foundation and empirical support for future research., (© 2024. The Author(s).)

In this study, a feasibility of γ radiation detection using complementary metal-oxide semiconductor (CMOS) image sensors with a neural network algorithm to extract the γ rays interacted pixels has been investigated. The responses characteristics of the CMOS imaging sensor to γ-ray is studied by placed in a γ fields produced by standard 60 Co or 137 Cs isotope sources. The supported preview frame rate of the CMOS image sensor is 25 fps, establishing the functional relationship between the gray level histograms and the dose rate through the neural network, the high energy γ-ray from 60 Co and 137 Cs source radiation dose rate in µSv/h level can be detected using the CMOS imaging sensor. The results show that the proposed method can effectively identify the number of photon particles which detected by the radiation monitoring system based on CMOS image sensor, and infer that the CMOS imaging sensor with a radiation signal extraction algorithm can be used as a dose warner for radiation protection purpose., (© 2024. The Author(s).)

Cardiovascular disease (CVD) is a major chronic disease worldwide and its risk factors have long been investigating in epidemiological studies. Our study aims to develop a body composition-based risk score and integrate it into the Framingham Risk Score (FRS) to improve CVD prediction among well-functioning older adults. We included 1882 older adults from the Health, Aging and Body Composition (Health ABC) study to screen body composition variables obtained from the Dual-energy X-ray absorptiometry (DXA). Three models were developed and compared: the 4-DXA model, the refit FRS, and the refit FRS plus 4-DXA model. C-statistics were 0.62 (95% CI: 0.59, 0.65) for the refit FRS, 0.58 (95% CI: 0.55, 0.61) for the 4-DXA model, and 0.63 (95% CI: 0.60, 0.66) for the refit FRS plus 4-DXA model. Compared to the refit FRS, the refit FRS plus 4-DXA model slightly improved CVD outcome prediction as the discrimination slope, net reclassification index, and the integrated discrimination index were 0.053 (95% CI: 0.041, 0.066), 0.098 (95% CI = - 0.0033, 0.20) and 0.013 (95% CI: 0.0069-0.019). This study provides a model for more accurate risk stratification and draws more attention on DXA-based indices in the clinical setting. It also encourages further research in validating the developed risk score in more diverse population and in investigating a broader range of CVD risk factors., (© 2024. The Author(s).)

This article presents a physical model that describes the interaction between surface electron beams and plasma. The dispersion relations for beam plasma interactions were derived using perturbation method and field matching methods. The study investigates how different parameters affect radiation frequency and bandwidth. The results indicate that as electron beam velocity increases, the associated kinetic energy also rises, leading to an increase in both the maximum radiation frequency and bandwidth at high frequencies. Conversely, the radiation bandwidth at low frequencies decreases. Similarly, a higher plasma density results in a greater maximum radiation frequency, but the high-frequency bandwidth decreases, while the low-frequency bandwidth increases. Additionally, when the electron density and electron velocity of the electron beam remain constant, increasing the plasma density can increase the microwave radiation frequency However, there exists a plasma density threshold, beyond which high-frequency electromagnetic waves are no longer radiated., (© 2024. The Author(s).)

Type 2 diabetes (T2D) is a disease characterized by heterogeneously progressive loss of islet β cell insulin secretion usually occurring after the presence of insulin resistance (IR) and it is one component of metabolic syndrome (MS), and we named it metabolic dysfunction syndrome (MDS). The pathogenesis of T2D is not fully understood, with IR and β cell dysfunction playing central roles in its pathophysiology. Dyslipidemia, hyperglycemia, along with other metabolic disorders, results in IR and/or islet β cell dysfunction via some shared pathways, such as inflammation, endoplasmic reticulum stress (ERS), oxidative stress, and ectopic lipid deposition. There is currently no cure for T2D, but it can be prevented or in remission by lifestyle intervention and/or some medication. If prevention fails, holistic and personalized management should be taken as soon as possible through timely detection and diagnosis, considering target organ protection, comorbidities, treatment goals, and other factors in reality. T2D is often accompanied by other components of MDS, such as preobesity/obesity, metabolic dysfunction associated steatotic liver disease, dyslipidemia, which usually occurs before it, and they are considered as the upstream diseases of T2D. It is more appropriate to call "diabetic complications" as "MDS-related target organ damage (TOD)", since their development involves not only hyperglycemia but also other metabolic disorders of MDS, promoting an up-to-date management philosophy. In this review, we aim to summarize the underlying mechanism, screening, diagnosis, prevention, and treatment of T2D, especially regarding the personalized selection of hypoglycemic agents and holistic management based on the concept of "MDS-related TOD"., (© 2024. The Author(s).)

Tumor microenvironment heterogeneity in hepatocellular carcinoma (HCC) on a spatial single-cell resolution is unclear. Here, we conducted co-detection by indexing to profile the spatial heterogeneity of 401 HCC samples with 36 biomarkers. By parsing the spatial tumor ecosystem of liver cancer, we identified spatial patterns with distinct prognosis and genomic and molecular features, and unveiled the progressive role of vimentin (VIM) high macrophages. Integration analysis with eight independent cohorts demonstrated that the spatial co-occurrence of VIM high macrophages and regulatory T cells promotes tumor progression and favors immunotherapy. Functional studies further demonstrated that VIM high macrophages enhance the immune-suppressive activity of regulatory T cells by mechanistically increasing the secretion of interleukin-1β. Our data provide deep insights into the heterogeneity of tumor microenvironment architecture and unveil the critical role of VIM high macrophages during HCC progression, which holds potential for personalized cancer prevention and drug discovery and reinforces the need to resolve spatial-informed features for cancer treatment., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

In a multicenter case-control investigation, we assessed the efficacy of the Electrooculogram Signal Analysis (EOG-SA) method, which integrates attention-related visual evocation, electrooculography, and nonlinear analysis, for distinguishing between intellectual and developmental disabilities (IDD) and typical development (TD) in children. Analyzing 127 participants (63 IDD, 64 TD), we applied nonlinear dynamics for feature extraction. Results indicated EOG-SA's capability to distinguish IDD, with higher template thresholds and Correlation Dimension values correlating with clinical severity. The template threshold proved a robust indicator, with higher values denoting severe IDD. Discriminative metrics showed areas under the curve of 0.91 (template threshold) and 0.85/0.91 (D2), with sensitivities and specificities of 77.6%/95.9% and 93.5%/71.0%, respectively. EOG-SA emerges as a promising tool, offering interpretable neural biomarkers for early and nuanced diagnosis of IDD., (© 2024. The Author(s).)

There is still room for improvement in first-line treatment of advanced small cell lung cancer (SCLC). This trial firstly investigated efficacy and safety of antiangiogenic therapy (surufatinib) (200 mg, qd, po) plus anti-PD-1 treatment (toripalimab) (240 mg, d1, ivdrip) combined with etoposide (100 mg/m², d1-d3, iv, drip) and cisplatin (25 mg/m², d1-d3, ivdrip) for advanced SCLC as first-line treatment, which has been registered on ClinicalTrials.gov under the identifier NCT04996771. The four-drug regimen was conducted q3w for 4 cycles with maintenance therapy of surufatinib and toripalimab. The primary endpoint was progression-free survival (PFS). The secondary end points included objective response rate (ORR), disease control rate (DCR), overall survival (OS) and safety. All of the 38 patients were enrolled for safety analysis, while only 35 patients were enrolled for efficacy analysis since loss of efficacy evaluation in 3 cases after treatment. After a median follow-up of 21.3 months, the ORR was 97.1% (34/35), and the DCR and the tumor shrinkage rate were both 100% (35/35). The median PFS was 6.9 months (95% CI: 4.6 m-9.2 m) and the median OS was 21.1 months (95% CI: 12.1 m-30.1 m). The 12-month, 18-month, and 24-month OS rates were 66.94%, 51.39% and 38.54%. The occurrence rate of grade ≥3 treatment-emergent adverse events (TEAEs) was 63.2% (24/38), including neutrophil count decreased (31.6%, 12/38), white blood cell count decreased (23.7%, 9/38) and platelet count decreased (10.5%, 4/38). No unexpected adverse events occurred. This novel four-drug regimen (surufatinib, toripalimab, etoposide plus cisplatin) revealed impressive therapeutic efficacy and tolerable toxicities., (© 2024. The Author(s).)

To adequately prepare for potential hazards caused by emerging and reemerging infectious diseases, the WHO has issued a list of high-priority pathogens that are likely to cause future outbreaks and for which research and development (R&D) efforts are dedicated, known as paramount R&D blueprints. Within R&D efforts, the goal is to obtain effective prophylactic and therapeutic approaches, which depends on a comprehensive knowledge of the etiology, epidemiology, and pathogenesis of these diseases. In this process, the accessibility of animal models is a priority bottleneck because it plays a key role in bridging the gap between in-depth understanding and control efforts for infectious diseases. Here, we reviewed preclinical animal models for high priority disease in terms of their ability to simulate human infections, including both natural susceptibility models, artificially engineered models, and surrogate models. In addition, we have thoroughly reviewed the current landscape of vaccines, antibodies, and small molecule drugs, particularly hopeful candidates in the advanced stages of these infectious diseases. More importantly, focusing on global trends and novel technologies, several aspects of the prevention and control of infectious disease were discussed in detail, including but not limited to gaps in currently available animal models and medical responses, better immune correlates of protection established in animal models and humans, further understanding of disease mechanisms, and the role of artificial intelligence in guiding or supplementing the development of animal models, vaccines, and drugs. Overall, this review described pioneering approaches and sophisticated techniques involved in the study of the epidemiology, pathogenesis, prevention, and clinical theatment of WHO high-priority pathogens and proposed potential directions. Technological advances in these aspects would consolidate the line of defense, thus ensuring a timely response to WHO high priority pathogens., (© 2024. The Author(s).)

Carbon emission reduction is crucial for mitigating global climate change, and green fiscal policies, through providing economic incentives and reallocating resources, are key means to achieve carbon reduction targets. This paper uses data covering 248 cities from 2003 to 2019 and applies a multi-period difference-in-differences model (DID) to thoroughly assess the impact of energy conservation and emission reduction (ECER) fiscal policies on enhancing carbon emission (CE 1 ) reduction and carbon efficiency (CE 2 ). It further analyzes the mediating role of Green Innovation (GI), exploring how it strengthens the impact of ECER policies. We find that: (1) ECER policies significantly promote the improvement of carbon reduction and CE 2 , a conclusion that remains robust after excluding the impacts of concurrent policy influences, sample selection biases, outliers, and other random factors. (2) ECER policies enhance CE 1 reduction and CE 2 in pilot cities by promoting green innovation, and this conclusion is confirmed by Sobel Z tests. (3) The effects of ECER policies on CE 1 reduction and the improvement of CE 2 are more pronounced in higher-level cities, the eastern regions and non-resource cities. This research provides policy makers with suggestions, highlighting that incentivizing green innovation through green fiscal policies is an effective path to achieving carbon reduction goals., (© 2024. The Author(s).)

As an important fishery resource and endangered species, studying the habitat of Coilia nasus (C. nasus) is highly significant. This study used fishery survey data from southern Zhejiang coastal waters from 2016 to 2020, employing a maximum entropy model (MaxEnt) to map the habitat distribution of C. nasus. Model performance was evaluated using two metrics: the area under the curve (AUC) of the receiver operating characteristic curve for the training and test sets and true skill statistics (TSS). This study aimed to predict the habitat distribution of C. nasus and explore how environmental variables influence habitat suitability. The results indicated that the models for each season had strong predictive performance, with AUC values above 0.8 and TSS values exceeding 0.6, indicating that they could accurately predict the presence of C. nasus. In the study area, C. nasus was primarily found in brackish or marine waters near bays and coastal islands. Among all environmental factors, salinity (S) and bottom temperature (BOT) had the highest correlations with habitat distribution, although these correlations varied across seasons. The findings of this study provide empirical evidence and a reference for the conservation and management of C. nasus and for the designation of its protected areas., (© 2024. The Author(s).)

The double carbon goal is a wide and profound economic and social systematic change. It is also crucial to China's sustainable development. How to promote emission reduction, the National High-Tech Industrial Development Zones(NHTDZs) policy is the key to addressing this problem. Based on urban data from 2003 to 2019 from China, this paper uses the multi-time point asymptotic difference method to explore the impact of the NHTDZs establishment on carbon emissions. The establishment of NHTDZs reduces CO2 emissions, which remains valid through robustness tests. The mechanism analysis demonstrated that the construction of NHTDZs reduces CO2 emissions by increasing innovation levels, increasing research expenditures and emphasizing human capital. Further analysis shown that geographic location, initial resource endowment, population size, and level of green finance development are difference in different cities. This provides guidance promoting the development of NHTDZs and future layout., (© 2024. The Author(s).)

Colorectal liver metastasis (CRLM) is challenging in the clinical treatment of colorectal cancer. Limited research has been conducted on how CRLM develops. RNA sequencing data were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Four machine learning algorithms were used to screen the hub CRLM-specific genes, including Least Absolute Shrinkage and Selection Operator (Lasso), Random forest, SVM-RFE, and XGboost. The model for identifying CRLM was developed using stepwise logistic regression and was validated using internal and independent datasets. The prognostic value of hub CRLM-specific genes was assessed using the Lasso-Cox method. The in vitro experiments were performed using SW620 cells. The CRLM identification model was developed based on four CRLM-specific genes (SPP1, ZG16, P2RY14, and PRKAR2B), and the model efficacy was validated using GSE41258 and three external cohorts. Five CRLM-specific prognostic hub genes, SPP1, ZG16, P2RY14, CYP2E1, and C5, were identified using the Lasso-Cox algorithm, and a risk score was constructed. The risk score was validated using the GSE39582 cohort. Three genes have both efficacy in identifying CRLM and prognostic value: ZG16, P2RY14, and SPP1. Immune infiltration and enrichment analyses demonstrated that SPP1 was associated with M2 macrophage polarization and extracellular matrix remodeling. In vitro experiments indicated that SPP1 may act as a cancer-promoting factor. The hub CRLM-specific gene SPP1 can help determine the diagnosis, prognosis, and immune infiltration of patients with CRLM., (© 2024. The Author(s).)

Diffusion Kurtosis Imaging (DKI)-derived metrics are recognized as indicators of maturation in neonates with low-grade germinal matrix and intraventricular hemorrhage (GMH-IVH). However, it is not yet known if these factors are associated with neurodevelopmental outcomes. The objective of this study was to acquire DKI-derived metrics in neonates with low-grade GMH-IVH, and to demonstrate their association with later neurodevelopmental outcomes. In this prospective study, neonates with low-grade GMH-IVH and control neonates were recruited, and DKI were performed between January 2020 and March 2021. These neonates underwent the Bayley Scales of Infant Development test at 18 months of age. Mean kurtosis (MK), radial kurtosis (RK) and gray matter values were measured. Spearman correlation analyses were conducted for the measured values and neurodevelopmental outcome scores. Forty controls (18 males, average gestational age (GA) 30 weeks ± 1.3, corrected GA at MRI scan 38 weeks ± 1) and thirty neonates with low-grade GMH-IVH (13 males, average GA 30 weeks ± 1.5, corrected GA at MRI scan 38 weeks ± 1). Neonates with low-grade GMH-IVH exhibited lower MK and RK values in the PLIC and the thalamus (P < 0.05). The MK value in the thalamus was associated with Mental Development Index (MDI) (r = 0.810, 95% CI 0.695-0.13; P < 0.001) and Psychomotor Development Index (PDI) (r = 0.852, 95% CI 0.722-0.912; P < 0.001) scores. RK value in the caudate nucleus significantly and positively correlated with MDI (r = 0.496, 95% CI 0.657-0.933; P < 0.001) and PDI (r = 0.545, 95% CI 0.712-0.942; P < 0.001) scores. The area under the curve (AUC) were used to assess diagnostic performance of MK and RK in thalamus (AUC = 0.866, 0.787) and caudate nucleus (AUC = 0.833, 0.671) for predicting neurodevelopmental outcomes. As quantitative neuroimaging markers, MK in thalamus and RK in caudate nucleus may help predict neurodevelopmental outcomes in neonates with low-grade GMH-IVH., (© 2024. The Author(s).)

Acute appendicitis is a typical surgical emergency worldwide and one of the common causes of surgical acute abdomen in the elderly. Accurately diagnosing and differentiating acute appendicitis can assist clinicians in formulating a scientific and reasonable treatment plan and providing high-quality medical services for the elderly. In this study, we validated and analyzed the different performances of various machine learning models based on the analysis of clinical data, so as to construct a simple, fast, and accurate estimation method for the diagnosis of early acute appendicitis. The dataset of this paper was obtained from the medical data of elderly patients with acute appendicitis attending the First Affiliated Hospital of Anhui University of Chinese Medicine from January 2012 to January 2022, including 196 males (60.87%) and 126 females (39.13%), including 103 (31.99%) patients with complicated appendicitis and 219 (68.01%) patients with uncomplicated appendicitis. By comparing and analyzing the prediction results of the models implemented by nine different machine learning techniques (LR, CART, RF, SVM, Bayes, KNN, NN, FDA, and GBM), we found that the GBM algorithm gave the optimal results and that sensitivity, specificity, PPV, NPV, precision, recall, F1 and brier are 0.9167, 0.9739, 0.9429, 0.9613, 0.9429, 0.9167, 0.9296, and 0.05649, respectively. The GBM model prediction results are interpreted using the SHAP technology framework. Calibration and Decision curve analysis also show that the machine learning model proposed in this paper has some clinical and economic benefits. Finally, we developed the Shiny application for complicated appendicitis diagnosis to assist clinicians in quickly and effectively recognizing patients with complicated appendicitis (CA) and uncomplicated appendicitis (UA), and to formulate a more reasonable and scientific clinical plan for acute appendicitis patient population promptly., (© 2024. The Author(s).)

Ab initio calculations have an essential role in our fundamental understanding of quantum many-body systems across many subfields, from strongly correlated fermions 1-3 to quantum chemistry 4-6 and from atomic and molecular systems 7-9 to nuclear physics 10-14 . One of the primary challenges is to perform accurate calculations for systems where the interactions may be complicated and difficult for the chosen computational method to handle. Here we address the problem by introducing an approach called wavefunction matching. Wavefunction matching transforms the interaction between particles so that the wavefunctions up to some finite range match that of an easily computable interaction. This allows for calculations of systems that would otherwise be impossible owing to problems such as Monte Carlo sign cancellations. We apply the method to lattice Monte Carlo simulations 15,16 of light nuclei, medium-mass nuclei, neutron matter and nuclear matter. We use high-fidelity chiral effective field theory interactions 17,18 and find good agreement with empirical data. These results are accompanied by insights on the nuclear interactions that may help to resolve long-standing challenges in accurately reproducing nuclear binding energies, charge radii and nuclear-matter saturation in ab initio calculations 19,20 ., (© 2024. The Author(s).)

Accurate prediction of the remaining useful life (RUL) of lithium-ion batteries is advantageous for maintaining the stability of electrical systems. In this paper, an interpretable online method which can reflect capacity regeneration is proposed to accurately estimate the RUL. Firstly, four health indicators (HIs) are extracted from the charging and discharging process for online prediction. Then, the HIs model is trained using support vector regression to obtain future features. And the capacity model of Gaussian process regression (GPR) is trained and analyzed by Shapley additive explanation (SHAP). Meanwhile, the state space for capacity prediction is constructed with the addition of Gaussian non-white noise to simulate the capacity regeneration. And the modified predicted HIs and noise are obtained by unscented Kalman filter. Finally, according to SHAP explainer, the predicted HIs acting as the baseline and the modified HIs containing information on capacity regeneration are chosen to predict RUL. In addition, the bounds of confidence intervals (CIs) are calculated separately to reflect the regenerated capacity. The experimental results demonstrate that the proposed online method can achieve high accuracy and effectively capture the capacity regeneration. The absolute error of failure RUL is below 5 and the minimum confidence interval is only 2., (© 2024. The Author(s).)

Railway transportation has experienced significant growth worldwide, offering numerous benefits to society. Most railway accidents are caused by wheelset faults so it's significant to monitor wheelset conditions. Therefore, we need to collect wheelset images, repaint them, extract laser stripe centerlines, construct 3D contour, and measure their geometric parameters to judge the wheelset's conditions. Deep learning can fulfill the tasks satisfyingly because it's adaptable, robust, and generalize compared with traditional methods. To train the deep learning models effectively, we need rich and high-quality wheelset datasets. So far, there are no applicable public train wheelset datasets available, which greatly hinders the research on train wheelsets. Thus we construct a publicly available Wheelset Laser Image Dataset (WLI-Set). WLI-Set consists of four sub-datasets, Original, Inpainting, Segmentation, and Centerline. The dataset contains abundant annotated multiline laser stripe images that can facilitate the research on train wheelsets effectively., (© 2024. The Author(s).)

Systemic therapy is typically the primary treatment choice for hepatocellular carcinoma (HCC) patients with extrahepatic metastases. Some patients may achieve partial response (PR) or complete response (CR) with systemic treatment, leading to the possibility of their primary tumor becoming resectable. This study aimed to investigate whether these patients could achieve longer survival through surgical resection of their primary tumor. We retrospectively collected data from 150 HCC patients with extrahepatic metastases treated at 15 different centers from January 1st, 2015, to November 30th, 2022. We evaluated their overall survival (OS) and progress-free survival (PFS) and analyzed risk factors impacting both OS and PFS were analyzed. Patients who received surgical treatment had longer OS compared to those who did not (median OS 16.5 months vs. 11.3 months). However, there was no significant difference in progression-free survival between the two groups. Portal vein invasion (P = 0.025) was identified as a risk factor for poor prognosis in patients, while effective first-line treatment (P = 0.039) and surgical treatment (P = 0.005) were protective factors. No factors showed statistical significance in the analysis of PFS. Effective first-line treatment (P = 0.027) and surgical treatment (P = 0.006) were both independent protective factors for prolonging patient prognosis, while portal vein invasion was an independent risk factor (P = 0.044). HCC patients with extrahepatic metastases who achieve PR/CR with conversion therapy may experience longer OS through surgical treatment. This study is the first to analyze the clinical outcomes of patients receiving surgical treatment for HCC with extrahepatic metastases., (© 2024. The Author(s).)

Macroautophagy is a process that cells engulf cytosolic materials by autophagosomes and deliver them to lysosomes for degradation. The biogenesis of autophagosomes requires ATG2 as a lipid transfer protein to transport lipids from existing membranes to phagophores. It is generally believed that endoplasmic reticulum is the main source for lipid supply of the forming autophagosomes; whether ATG2 can transfer lipids from other organelles to phagophores remains elusive. In this study, we identified a new ATG2A-binding protein, ANKFY1. Depletion of this endosome-localized protein led to the impaired autophagosome growth and the reduced autophagy flux, which largely phenocopied ATG2A/B depletion. A pool of ANKFY1 co-localized with ATG2A between endosomes and phagophores and depletion of UVRAG, ANKFY1 or ATG2A/B led to reduction of PI3P distribution on phagophores. Purified recombinant ANKFY1 bound to PI3P on membrane through its FYVE domain and enhanced ATG2A-mediated lipid transfer between PI3P-containing liposomes. Therefore, we propose that ANKFY1 recruits ATG2A to PI3P-enriched endosomes and promotes ATG2A-mediated lipid transfer from endosomes to phagophores. This finding implicates a new lipid source for ATG2A-mediated phagophore expansion, where endosomes donate PI3P and other lipids to phagophores via lipid transfer., (© 2024. The Author(s).)

With the development of cloud computing, users are more inclined to outsource complex computing tasks to cloud servers with strong computing capacity, and the cloud returns the final calculation results. However, the cloud is not completely trustworthy, which may leak the data of user and even return incorrect calculations on purpose. Therefore, it is important to verify the results of computing tasks without revealing the privacy of the users. Among all the computing tasks, the polynomial calculation is widely used in information security, linear algebra, signal processing and other fields. Most existing polynomial-based verifiable computation schemes require that the input of the polynomial function must come from a single data source, which means that the data must be signed by a single user. However, the input of the polynomial may come from multiple users in the practical application. In order to solve this problem, the researchers have proposed some schemes for multi-source outsourced data, but these schemes have the common problem of low efficiency. To improve the efficiency, this paper proposes an efficient polynomial-based verifiable computation scheme on multi-source outsourced data. We optimize the polynomials using Horner's method to increase the speed of verification, in which the addition gate and the multiplication gate can be interleaved to represent the polynomial function. In order to adapt to this structure, we design the corresponding homomorphic verification tag, so that the input of the polynomial can come from multiple data sources. We prove the correctness and rationality of the scheme, and carry out numerical analysis and evaluation research to verify the efficiency of the scheme. The experimental indicate that data contributors can sign 1000 new data in merely 2 s, while the verification of a delegated polynomial function with a power of 100 requires only 18 ms. These results confirm that the proposed scheme is better than the existing scheme., (© 2024. The Author(s).)

We aim to develop machine learning (ML) models for predicting the complexity and mortality of polytrauma patients using clinical features, including physician diagnoses and physiological data. We conducted a retrospective analysis of a cohort comprising 756 polytrauma patients admitted to the intensive care unit (ICU) at Pizhou People's Hospital Trauma Center, Jiangsu, China between 2020 and 2022. Clinical parameters encompassed demographics, vital signs, laboratory values, clinical scores and physician diagnoses. The two primary outcomes considered were mortality and complexity. We developed ML models to predict polytrauma mortality or complexity using four ML algorithms, including Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN) and eXtreme Gradient Boosting (XGBoost). We assessed the models' performance and compared the optimal ML model against three existing trauma evaluation scores, including Injury Severity Score (ISS), Trauma Index (TI) and Glasgow Coma Scale (GCS). In addition, we identified several important clinical predictors that made contributions to the prognostic models. The XGBoost-based polytrauma mortality prediction model demonstrated a predictive ability with an accuracy of 90% and an F-score of 88%, outperforming SVM, RF and ANN models. In comparison to conventional scoring systems, the XGBoost model had substantial improvements in predicting the mortality of polytrauma patients. External validation yielded strong stability and generalization with an accuracy of up to 91% and an AUC of 82%. To predict polytrauma complexity, the XGBoost model maintained its performance over other models and scoring systems with good calibration and discrimination abilities. Feature importance analysis highlighted several clinical predictors of polytrauma complexity and mortality, such as Intracranial hematoma (ICH). Leveraging ML algorithms in polytrauma care can enhance the prognostic estimation of polytrauma patients. This approach may have potential value in the management of polytrauma patients., (© 2024. The Author(s).)

Molecular profiling guides precision treatment of breast cancer; however, Asian patients are underrepresented in publicly available large-scale studies. We established a comprehensive multiomics cohort of 773 Chinese patients with breast cancer and systematically analyzed their genomic, transcriptomic, proteomic, metabolomic, radiomic and digital pathology characteristics. Here we show that compared to breast cancers in white individuals, Asian individuals had more targetable AKT1 mutations. Integrated analysis revealed a higher proportion of HER2-enriched subtype and correspondingly more frequent ERBB2 amplification and higher HER2 protein abundance in the Chinese HR + HER2 + cohort, stressing anti-HER2 therapy for these individuals. Furthermore, comprehensive metabolomic and proteomic analyses revealed ferroptosis as a potential therapeutic target for basal-like tumors. The integration of clinical, transcriptomic, metabolomic, radiomic and pathological features allowed for efficient stratification of patients into groups with varying recurrence risks. Our study provides a public resource and new insights into the biology and ancestry specificity of breast cancer in the Asian population, offering potential for further precision treatment approaches., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

This retrospective cohort study explored the relationship between monocular and interocular optical coherence tomography (OCT) parameters and stereopsis in 56 patients undergoing pars plana vitrectomy (PPV) for unilateral idiopathic epiretinal membrane (IERM). IERM impairs visual functions, with symptoms ranging from asymptomatic to severe impairment. Despite established surgical interventions, including PPV with membrane peeling, the impact on advanced three-dimensional visual functions such as stereopsis remains inadequately investigated. All subjects were assessed for stereopsis, visual acuity, and metamorphopsia, alongside spectral domain OCT parameters. These visual functions significantly improved 3-month postoperatively. Central retinal thickness at the fovea, parafovea, and perifovea (CFT, CRT-3 mm, and CRT-6 mm), ectopic inner foveal layer thickness, and retinal layer thickness notably decreased 1 week to 3 months after surgery. The interocular difference in OCT parameters between bilateral eyes was included as a parameter. Baseline CRT-3 mm difference and inner nuclear layer (INL) thickness were independently correlated with postoperative stereopsis on the Titmus Stereo Test, while baseline CRT-6 mm difference and INL thickness were independently related to stereopsis on the TNO stereotest. This study highlights the substantial enhancement in stereopsis post-IERM surgery, with both interocular and monocular OCT parameters independently influencing postoperative stereopsis. These findings underscore the importance of retinal microstructures in assessing and predicting stereopsis in IERM patients after vitrectomy., (© 2024. The Author(s).)

Based on panel data from 210 prefecture-level cities in China from 2003 to 2021, this study employs the Time-Varying Differences-in-Differences (Time-Varying DID) approach to systematically examine the impact of smart city construction on pollution emissions and its underlying mechanisms. Additionally, the Propensity Score Matching-Differences-in-Differences method is employed for further validation. The research findings indicate that Smart City Construction (SCC) significantly reduces urban Volume of Sewage Discharge (VSD), sulfur dioxide emissions (SO 2 ), and Emissions of Fumes and Dust (EFD), thereby mitigating pollution emissions (PE) and enhancing environmental quality. Mechanism analysis reveals that SCC achieves these effects through scale effects, structural effects, and technological effects. City heterogeneity analysis shows that provincial capital cities exhibit a stronger suppression effect on pollution emissions compared to non-provincial capital cities. Moreover, cities with lower levels of education attainment demonstrate a stronger ability to curb pollution emissions, while larger cities exhibit a more pronounced impact on mitigating pollution emissions. The marginal contributions of this study mainly consist of three aspects: Firstly, it enriches the literature on environmental impact factors by assessing, for the first time, the influence of SCC on PE. Secondly, a comprehensive approach is employed, integrating VSD, EFD, SO 2 data, and economic and pollution data at the city level. Time-Varying DID is used to evaluate the policy effects of SCC. Finally, the study analyzes the impact mechanisms of SCC policy on environmental emissions from various perspectives., (© 2024. The Author(s).)

In an era where digital technology is reshaping business landscapes, understanding the factors that drive corporate digital transformation is essential. In this paper we explore these influencing factors, focusing on Chinese A-share listed companies from 2007 to 2021. Our approach involved a comprehensive analysis of multiple variables through regression techniques to determine their impact on digital transformation. The findings reveal the drive for reform in the digital transformation endeavours of enterprises. Notably, companies with higher gearing, overhead, and accounts receivable ratios exhibit a stronger inclination towards digital transformation. Conversely, enterprises in monopolistic industries and those at the inception stage of their life cycle show less propensity for such transformation. The findings of this research not only shed light on the strategic decisions behind digital transformation in response to financial and competitive challenges but also provide actionable insights for policymakers and business strategists. This study underscores the importance of contextualizing digital transformation efforts within the unique framework of industry characteristics and company development phases., (© 2024. The Author(s).)

In order to investigate the damage characteristics of structural components under axial compression, thin-walled columns are chosen as a more straightforward construct due to the complex structural properties of composite materials, diverse fiber laying angles, and varied geometries associated with thin-walled columns. Despite the limitations imposed by labor-intensive testing procedures, high costs, and the poor repeatability inherent in experimental research methods, there remains an insufficient exploration of axial compressive damage in columns composed of aluminum and fiber-reinforced polymers. This article utilizes the finite element technique to quantitatively analyze the crushing processes of four materials: aluminum, carbon fiber-reinforced aluminum, carbon fiber-reinforced polymer, and glass fiber-reinforced polymer. It examines the effects of varying fibers and matrix materials on their mechanical attributes. The study also evaluates the impact of different cross-sectional designs on the mechanical behavior of the columns., (© 2024. The Author(s).)

Despite epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI) have shown remarkable efficacy in patients with EGFR-mutant non-small cell lung cancer (NSCLC), acquired resistance inevitably develops, limiting clinical efficacy. We found that TET2 was poly-ubiquitinated by E3 ligase CUL7 FBXW11 and degraded in EGFR-TKI resistant NSCLC cells. Genetic perturbation of TET2 rendered parental cells more tolerant to TKI treatment. TET2 was stabilized by MEK1 phosphorylation at Ser 1107, while MEK1 inactivation promoted its proteasome degradation by enhancing the recruitment of CUL7 FBXW11 . Loss of TET2 resulted in the upregulation of TNF/NF-κB signaling that confers the EGFR-TKI resistance. Genetic or pharmacological inhibition of NF-κB attenuate the TKI resistance both in vitro and in vivo. Our findings exemplified how a cell growth controlling kinase MEK1 leveraged the epigenetic homeostasis by regulating TET2, and demonstrated an alternative path of non-mutational acquired EGFR-TKI resistance modulated by TET2 deficiency. Therefore, combined strategy exploiting EGFR-TKI and inhibitors of TET2/NF-κB axis holds therapeutic potential for treating NSCLC patients who suffered from this resistance., (© 2024. The Author(s).)

Solid-state Li-S batteries (SSLSBs) are made of low-cost and abundant materials free of supply chain concerns. Owing to their high theoretical energy densities, they are highly desirable for electric vehicles 1-3 . However, the development of SSLSBs has been historically plagued by the insulating nature of sulfur 4,5 and the poor interfacial contacts induced by its large volume change during cycling 6,7 , impeding charge transfer among different solid components. Here we report an S 9.3 I molecular crystal with I 2 inserted in the crystalline sulfur structure, which shows a semiconductor-level electrical conductivity (approximately 5.9 × 10 -7  S cm -1 ) at 25 °C; an 11-order-of-magnitude increase over sulfur itself. Iodine introduces new states into the band gap of sulfur and promotes the formation of reactive polysulfides during electrochemical cycling. Further, the material features a low melting point of around 65 °C, which enables repairing of damaged interfaces due to cycling by periodical remelting of the cathode material. As a result, an Li-S 9.3 I battery demonstrates 400 stable cycles with a specific capacity retention of 87%. The design of this conductive, low-melting-point sulfur iodide material represents a substantial advancement in the chemistry of sulfur materials, and opens the door to the practical realization of SSLSBs., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment. However, irrigant selection or irrigation procedures are far from clear. The vapor lock effect in the apical region has yet to be solved, impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes. Additionally, ambiguous clinical indications for root canal medication and non-standardized dressing protocols must be clarified. Inappropriate intracanal medication may present side effects and jeopardize the therapeutic outcomes. Indeed, clinicians have been aware of these concerns for years. Based on the current evidence of studies, this article reviews the properties of various irrigants and intracanal medicaments and elucidates their effectiveness and interactions. The evolution of different kinetic irrigation methods, their effects, limitations, the paradigm shift, current indications, and effective operational procedures regarding intracanal medication are also discussed. This expert consensus aims to establish the clinical operation guidelines for root canal irrigation and a position statement on intracanal medication, thus facilitating a better understanding of infection control, standardizing clinical practice, and ultimately improving the success of endodontic therapy., (© 2024. The Author(s).)

The bone marrow adjusts blood cell production to meet physiological demands in response to insults. The spatial organization of normal and stress responses are unknown owing to the lack of methods to visualize most steps of blood production. Here we develop strategies to image multipotent haematopoiesis, erythropoiesis and lymphopoiesis in mice. We combine these with imaging of myelopoiesis 1 to define the anatomy of normal and stress haematopoiesis. In the steady state, across the skeleton, single stem cells and multipotent progenitors distribute through the marrow enriched near megakaryocytes. Lineage-committed progenitors are recruited to blood vessels, where they contribute to lineage-specific microanatomical structures composed of progenitors and immature cells, which function as the production sites for each major blood lineage. This overall anatomy is resilient to insults, as it was maintained after haemorrhage, systemic bacterial infection and granulocyte colony-stimulating factor (G-CSF) treatment, and during ageing. Production sites enable haematopoietic plasticity as they differentially and selectively modulate their numbers and output in response to insults. We found that stress responses are variable across the skeleton: the tibia and the sternum respond in opposite ways to G-CSF, and the skull does not increase erythropoiesis after haemorrhage. Our studies enable in situ analyses of haematopoiesis, define the anatomy of normal and stress responses, identify discrete microanatomical production sites that confer plasticity to haematopoiesis, and uncover unprecedented heterogeneity of stress responses across the skeleton., (© 2024. The Author(s).)

Over half of hepatocellular carcinoma (HCC) cases diagnosed worldwide are in China 1-3 . However, whole-genome analysis of hepatitis B virus (HBV)-associated HCC in Chinese individuals is limited 4-8 , with current analyses of HCC mainly from non-HBV-enriched populations 9,10 . Here we initiated the Chinese Liver Cancer Atlas (CLCA) project and performed deep whole-genome sequencing (average depth, 120×) of 494 HCC tumours. We identified 6 coding and 28 non-coding previously undescribed driver candidates. Five previously undescribed mutational signatures were found, including aristolochic-acid-associated indel and doublet base signatures, and a single-base-substitution signature that we termed SBS&#95;H8. Pentanucleotide context analysis and experimental validation confirmed that SBS&#95;H8 was distinct to the aristolochic-acid-associated SBS22. Notably, HBV integrations could take the form of extrachromosomal circular DNA, resulting in elevated copy numbers and gene expression. Our high-depth data also enabled us to characterize subclonal clustered alterations, including chromothripsis, chromoplexy and kataegis, suggesting that these catastrophic events could also occur in late stages of hepatocarcinogenesis. Pathway analysis of all classes of alterations further linked non-coding mutations to dysregulation of liver metabolism. Finally, we performed in vitro and in vivo assays to show that fibrinogen alpha chain (FGA), determined as both a candidate coding and non-coding driver, regulates HCC progression and metastasis. Our CLCA study depicts a detailed genomic landscape and evolutionary history of HCC in Chinese individuals, providing important clinical implications., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)