Search

The Northern Extended Millimeter Array (NOEMA) formIng Cluster survEy (NICE) is a NOEMA large programme targeting 69 massive galaxy group candidates at z > 2 over six deep fields with a total area of 46 deg2. Here we report the spectroscopic confirmation of eight massive galaxy groups at redshifts 1.65 ≤ z ≤ 3.61 in the Cosmic Evolution Survey (COSMOS) field. Homogeneously selected as significant overdensities of red IRAC sources that have red Herschel colours, four groups in this sample are confirmed by CO and [CI] line detections of multiple sources with NOEMA 3 mm observations, three are confirmed with Atacama Large Millimeter Array (ALMA) observations, and one is confirmed by Ha emission from Subaru/FMOS spectroscopy. Using rich ancillary data in the far-infrared and sub-millimetre, we constructed the integrated farinfrared spectral energy distributions for the eight groups, obtaining a total infrared star formation rate (SFR) of 260-1300 M⊙ yr-1. We adopted six methods for estimating the dark matter masses of the eight groups, including stellar mass to halo mass relations, overdensity with galaxy bias, and NFW profile fitting to radial stellar mass densities. We find that the radial stellar mass densities of the eight groups are consistent with a NFW profile, supporting the idea that they are collapsed structures hosted by a single dark matter halo. The best halo mass estimates are log(Mh/M⊙) = 12.8-13.7 with a general uncertainty of 0.3 dex. Based on the halo mass estimates, we derived baryonic accretion rates (BARs) of (1-8) × 103 M⊙/yr for this sample. Together with massive groups in the literature, we find a quasi-linear correlation between the integrated SFR/BAR ratio and the theoretical halo mass limit for cold streams, Mstream/Mh, with SFR/BAR = 10-0.46±0.22 (Mstream/Mh)0.71±0.16 with a scatter of 0.40 dex. Furthermore, we compared the halo masses and the stellar masses with simulations, and find that the halo masses of all structures are consistent with those of progenitors of Mh(z = 0) > 1014 M⊙ galaxy clusters, and that the most massive central galaxies have stellar masses consistent with those of the brightest cluster galaxy progenitors in the TNG300 simulation. Above all, the results strongly suggest that these massive structures are in the process of forming massive galaxy clusters via baryonic and dark matter accretion.

Abstract Background This study aimed to analyze the epidemic characteristics and influencing factors of school influenza outbreaks in Jiangsu Province, China from 2020 to 2023,following the COVID-19 pandemic, to inform prevention and control strategies. Methods Data on influenza-like illness(ILI) outbreaks from the Chinese Influenza Surveillance Information System and national-level influenza surveillance sentinel hospitals were analyzed. The temporal distribution, school type, virus strains, and outbreak scales were examined using descriptive statistics. Results From 2020 to 2023, 1142 influenza outbreaks occurred in schools, with primary schools(ages 6 to 12) accounting for 71.80%. Most large outbreaks were caused by A(H1N1) and A(H3N2), responsible for 8.99% of total outbreaks. Outbreaks were predominantly reported in the pre-peak periods of B(Victoria) and A(H1N1) circulation, accounting for 86.31% and 92.32% of their respective total outbreaks. No concurrent influenza and COVID-19 outbreaks were observed during the study period. Conclusion Primary and secondary schools are high-risk settings for influenza outbreaks. A(H3N2) shows higher adaptability and is more likely to co-circulate with other subtypes/lineages, especially A(H1N1), leading to larger outbreaks. B(Victoria)-caused outbreaks are more frequent but smaller in scale. School influenza outbreaks are more likely to occur during the early stages of seasonal peaks, particularly for B(Victoria) and A(H1N1). This suggests that influenza outbreaks in schools may play a crucial role in seeding and accelerating the spread of the virus within the broader community.

Abstract Currently, despite the vast amounts of time and money invested in cancer treatment, cancer remains one of the primary threats to human life. The primary factor contributing to the low treatment efficacy is cancer heterogeneity. The unclear molecular mechanisms underlying tumorigenesis, coupled with the complexity of human physiology, and the inability of animal models to accurately replicate the human tumor microenvironment, pose significant hurdles in the development of novel cancer therapies. Tumor-microenvironment-on-chip (TMOC) represents a research platform that integrates three-dimensional cell culture with microfluidic systems, simulating the essential components and physiological traits of the in vivo tumor microenvironment. It offers a dynamic setting within the chip system to study tumor progression, potentially heralding a breakthrough in cancer research. In this review, we will summarize the current advancements in this platform, encompassing various types of TMOCs and their applications in different types of cancer. From our perspective, the TMOC platform necessitates enhanced integration with tissue engineering techniques and microphysiological environments before it can evolve into a more refined preclinical model for cancer research.

Abstract Gliomas are the most common primary malignant tumours of the central nervous system (CNS), which are highly aggressive, with increasing morbidity and mortality rates year after year, posing a serious threat to the quality and expected survival time of patients. The treatment of gliomas is a major challenge in the field of neuro-oncology, especially high-grade gliomas such as glioblastomas (GBMs). Despite considerable progress in recent years in the study of the molecular and cellular mechanisms of GBMs, their prognosis remains bleak. Tumour-associated macrophages (TAMs) account for up to 50% of GBMs, and they are a highly heterogeneous cell population whose role cannot be ignored. Here, we focus on reviewing the contribution of classically activated M1-phenotype TAMs and alternatively activated M2-phenotype TAMs to GBMs, and exploring the research progress in reprogramming M1 TAMs into M2 TAMs.

Abstract Methylation quantitative trait loci (meQTLs) quantify the effects of genetic variants on DNA methylation levels. However, most published studies utilize bulk methylation datasets composed of different cell types and limit our understanding of cell-type-specific methylation regulation. We propose a hierarchical Bayesian interaction (HBI) model to infer cell-type-specific meQTLs, which integrates a large-scale bulk methylation data and a small-scale cell-type-specific methylation data. Through simulations, we show that HBI enhances the estimation of cell-type-specific meQTLs. In real data analyses, we demonstrate that HBI can further improve the functional annotation of genetic variants and identify biologically relevant cell types for complex traits.

Abstract High‐dose melphalan followed by stem cell rescue is the standard consolidative therapy for transplant‐eligible patients with multiple myeloma (MM) in the United Kingdom. A melphalan dose of 200 mg/m2 (Mel200) is considered the “gold standard” for autologous stem cell transplant (ASCT) conditioning for fit patients ≤70 years old; however, with a peak diagnosis incidence at 80–89 years old in the UK dose adjustments will be inevitable to limit toxicities. In this single‐centre UK‐based retrospective analysis, data was collected from patients with plasma cell dyscrasias who underwent a first reduced‐intensity, Mel140, ASCT from 2006 to 2019, a total of 81 patients. We found that the procedure was overall safe with seven (9%) of patients requiring ITU admission and a single transplant‐related death within the initial autograft admission. The progression‐free survival (PFS) and overall survival were comparable with those previously reported in the literature with median PFS for our cohort of 31 months. Univariate analysis of our data showed an inferior PFS for patients aged ≥70 years. In conclusion, although this is a retrospective analysis, it demonstrates that dose‐reduced melphalan conditioning is safe and effective in patients deemed unfit for standard‐intensity conditioning.

Abstract Background The widespread acceptance of early surgery as a treatment for acute intertrochanteric fracture (ITF) has been accompanied by ongoing controversy due to conflicting conclusions presented in previous studies. This study aims to compare the occurrence of perioperative complications and mortality, as well as functional outcomes in older patients with ITF who underwent either early or delayed surgery. Methods A retrospective multicenter cohort study involving 7414 patients with ITF between Jan. 2017 and Dec. 2021 was conducted. After predefined participants selection inclusion and exclusion criteria, 2323 surgically treated ITF patients were included and analyzed utilizing propensity score matching (PSM) method. Their demographics, injury-related data, surgery-related data, and perioperative adverse outcomes during hospitalization were collected and compared between the early or delayed surgery groups by PSM with a 1:4 ratio. All participants received a minimum of two-year follow-up and perioperative outcomes, functional outcomes, and survival analyses were conducted and compared. Results After adjustment for potential confounders, there were no significant difference in surgery duration, intraoperative blood loss, transfusion rate, mortality rates, functional outcomes, and perioperative complications rates including severe complications, cardiac complications, pulmonary complications, and neurological complications regardless of whether the patient was treated with early or delayed surgery (all P > 0.05). Although length of hospital stay (mean, 11.5 versus 14.4 days, P

Abstract Background Children with chronic kidney disease (CKD) are at high risk of cardiovascular disease. Cardiovascular magnetic resonance (CMR) is the reference method for assessing cardiac remodeling. To our knowledge, no study has reported a comprehensive analysis of left ventricular(LV) cardiac remodeling using CMR in different stages of pediatric CKD. This prospective case-control study aimed to investigate cardiac remodeling in pediatric CKD, using CMR, and determine its relationship with risk factors. Method CMR was performed in 124 children with CKD and 50 controls. The cardiac remodeling parameters included left ventricular mass index (LVMI), LV remodeling index (LVRI), and LV wall thickness. Univariable and multivariable analyses were performed to assess the cardiac remodeling risk factors. Results Cardiac remodeling was observed in 35.5% (44/124) of children with CKD. The LVMI, LVRI, and LV wall thickness were higher in advanced stages of CKD (P

Abstract Background Respiratory infectious diseases have the highest incidence among infectious diseases worldwide. Currently, global monitoring of respiratory pathogens primarily focuses on influenza and coronaviruses. This study included influenza and other common respiratory pathogens to establish a local respiratory pathogen spectrum. We investigated and analyzed the co-infection patterns of these pathogens and explored the impact of lifting non-pharmaceutical interventions (NPIs) on the transmission of influenza and other respiratory pathogens. Additionally, we used a predictive model for infectious diseases, utilizing the commonly used An autoregressive comprehensive moving average model (ARIMA), which can effectively forecast disease incidence. Methods From June 2023 to February 2024, we collected influenza-like illness (ILI) cases weekly from the community in Xuanwu District, Nanjing, and obtained 2046 samples. We established a spectrum of respiratory pathogens in Nanjing and analysed the age distribution and clinical symptom distribution of various pathogens. We compared age, gender, symptom counts, and viral loads between individuals with co-infections and those with single infections. An autoregressive comprehensive moving average model (ARIMA) was constructed to predict the incidence of respiratory infectious diseases. Results Among 2046 samples, the total detection rate of respiratory pathogen nucleic acids was 53.37% (1092/2046), with influenza A virus 479 cases (23.41%), influenza B virus 224 cases (10.95%), and HCoV 95 cases (4.64%) being predominant. Some pathogens were statistically significant in age and number of symptoms. The positive rate of mixed infections was 6.11% (125/2046). There was no significant difference in age or number of symptoms between co-infection and simple infection. After multiple iterative analyses, an ARIMA model (0,1,4), (0,0,0) was established as the optimal model, with an R2 value of 0.930, indicating good predictive performance. Conclusions The spectrum of respiratory pathogens in Nanjing, Jiangsu Province, was complex in the past. The primary age groups of different viruses were different, causing various symptoms, and the co-infection of viruses did not correlate with the age and gender of patients. The ARIMA model estimated future incidence, which plateaued in subsequent months.

Abstract Herein, we report polyphosphonate covalent organic frameworks (COFs) constructed via P-O-P linkages. The materials are synthesized via a single-step condensation reaction of the charge-assisted hydrogen-bonded organic framework, which is constructed from phenylphosphonic acid and 5,10,15,20‐tetrakis[p‐phenylphosphonic acid]porphyrin and is formed by simply heating its hydrogen-bonded precursor without using chemical reagents. Above 210 °C, it becomes an amorphous microporous polymeric structure due to the oligomerization of P-O-P bonds, which could be shown by constant-time solid-state double-quantum 31P nuclear magnetic resonance experiments. The polyphosphonate COF exhibits good water and water vapor stability during the gas sorption measurements, and electrochemical stability in 0.5 M Na2SO4 electrolyte in water. The reported family of COFs fills a significant gap in the literature by providing stable microporous COFs suitable for use in water and electrolytes. Additionally, we provide a sustainable synthesis route for the COF synthesis. The narrow pores of the COF effectively capture CO2.

In order to solve the problem of difficult deployment of existing deep learning-based defect detection models in terminal equipment with limited computational capacity, a lightweight steel surface defect testing model LSKA-YOLOv8 was proposed based on the YOLOv8n target detection framework. The model uses KernelWarehouse Conv (KWConv) with lower computational volumes, which significantly reduces the required computational resources. By updating the traditional Feature Pyramid Network (FPN) structure to Bi-directional Feature Pyramid Network (BiFPN), enhance the capture of contextual information and reduce the number of parameters of the model. In addition, the Spatial Pyramid Pooling Fast (SPPF) module was replaced with a more accurate Receptive Field Block (RFB) module, expanding the model’s sensory field and improving characteristic representation. At the same time, the Large Separable Kernel Attention (LSKAttention) module was introduced in the detection head, effectively enhancing the understanding and capture of the target characteristics, thus significantly improving the overall detection performance. Experiments on the NEU-DET dataset showed that the average accuracy of LSKA-YOLO increased by 4.4% on the map@0.5 indicator compared to the benchmark model, while the number of parameters and calculations of the model decreased by 26.7% and 50%, respectively. Provides valuable references and practical applications for deployment of defect detection models on computing-resource-limited terminal devices.

Abstract Background Given that viral infections can increase the risk of adverse pregnancy outcomes, such as spontaneous miscarriage, preterm premature rupture of membranes, and preterm birth, the effects of COVID-19, a novel emerging coronavirus disease rapidly spreading globally, on pregnancy outcomes have garnered significant attention. Methods We conducted a review of studies related to pregnant women infected with SARS-CoV-2 over the past five years (December 2019 to April 2023), utilizing search engines such as PubMed, Web of Science, and the China National Knowledge Infrastructure (CNKI). This study was registered with PROSPERO with ID: CRD42024540849. Results A total of 218 articles were screened, with 15 studies meeting the inclusion criteria for this research, including 12 cohort studies, one cross-sectional study, one case-control study, and one case series. Six studies found that the preterm birth rate was higher in the infected group compared to the control group; five studies showed that the cesarean section rate was higher in the infected group; three studies found that the APGAR scores of newborns were higher in the control group than in the infected group; three studies indicated that the mortality rate of newborns in the infected group was higher than that in the control group. Conclusions Our retrospective review suggests that compared to pregnant women not infected with SARS-CoV-2, those diagnosed with COVID-19 are more likely to experience adverse outcomes such as preterm birth, cesarean delivery, and low birth weight in newborns.

Abstract The issue of brightness in strong ambient light conditions is one of the critical obstacles restricting the application of augmented reality (AR) and mixed reality (MR). Gallium nitride (GaN)-based micro-LEDs, renowned for their exceptional brightness and stability, are considered the foremost contenders for AR applications. Nevertheless, conventional heteroepitaxial growth micro-LED devices confront formidable challenges, including substantial wavelength shifts and efficiency droop. In this paper, we firstly demonstrated the high-quality homoepitaxial GaN-on-GaN micro-LEDs micro-display, and thoroughly analyzed the possible benefits for free-standing GaN substrate from the material-level characterization to device optoelectronic properties and micro-display application compared with sapphire substrate. The GaN-on-GaN structure exhibits a superior crystal quality with ultra-low threading dislocation densities (TDDs) of ~ 105 cm−2, which is three orders of magnitude lower than that of GaN-on-Sapphire. Through an in-depth size-dependent optoelectronic analysis of blue/green emission GaN-on-GaN/ Sapphire micro-LEDs from 100 × 100 shrink to 3 × 3 μm2, real that a lower forward voltage and series resistance, a consistent emission wavelength (1.21 nm for blue and 4.79 nm for green @ 500 A/cm2), coupled with a notable reduction in efficiency droop ratios (15.6% for blue and 28.5% for green @ 500 A/cm2) and expanded color gamut (103.57% over Rec. 2020) within GaN-on-GaN 10 μm micro-LEDs. Last but not least, the GaN-on-GaN micro-display with 3000 pixels per inch (PPI) showcased enhanced display uniformity and higher luminance in comparison to its GaN-on-Sapphire counterpart, demonstrating significant potentials for high-brightness AR/MR applications under strong ambient light.

Abstract Predicting the corrosion rate for soil-buried steel is significant for assessing the service-life performance of structures in soil environments. However, due to the large amount of variables involved, existing corrosion prediction models have limited accuracy for complex soil environment. The present study employs three machine learning (ML) algorithms, i.e., random forest, support vector regression, and multilayer perception, to predict the corrosion current density of soil-buried steel. Steel specimens were embedded in soil samples collected from different regions of the Wisconsin state. Variables including exposure time, moisture content, pH, electrical resistivity, chloride, sulfate content, and mean total organic carbon were measured through laboratory tests and were used as input variables for the model. The current density of steel was measured through polarization technique, and was employed as the output of the model. Of the various ML algorithms, the random forest (RF) model demonstrates the highest predictability (with an RMSE value of 0.01095 A/m2 and an R 2 value of 0.987). In light of the feature selection method, the electrical resistivity is identified as the most significant feature. The combination of three features (resistivity, exposure time, and mean total organic carbon) is the optimal scenario for predicting the corrosion current density of soil-buried steel.

To clarify the mechanical characteristics of tight sandstone in the Cretaceous Bashijiqike Formation of Kuqa Depression in Tarim Basin, and address field issues in deep and ultra-deep oil and gas exploration and development, triaxial compression experiments were used to quantitatively study the patterns of changes in rock mechanical properties influenced by confining pressure, fluid, and loading rate, with a preliminary analysis of their causes. The results showed that the maximum principal stress difference and elastic modulus of the sandstone samples increased significantly with confining pressure. The micro-reason was that the increase in confining pressure reduced the distance between particles inside the rock, enhancing the rock's cohesion and making particle dispersion less likely. Sandstone samples exhibited a progression from brittleness under low confining pressure to brittle-ductile transformation, and to ductile deformation under high confining pressure. Compared with dry sandstone samples, the reduction in the elastic modulus of samples soaked in pure water, 150 g/L solution, 250 g/L solution, and 350 g/L solution were 67.71%, 61.45%, 64.69%, and 57.32%, respectively, with pure water soaking causing the greatest reduction. Increasing fluid salinity could mitigate the weakening trend in rock mechanical parameters. Crystallization on crystal surfaces and changes in the electric double layer thickness were important controlling factors for these patterns. At lower loading rates, the values for maximum principal stress difference, elastic modulus, and Poisson's ratio of the sandstone samples were smaller, but they increased faster with increasing loading rates. When the loading rate reached a certain critical value (around 0.05 mm/min in this experiment), the rate of increase in rock mechanical parameters slowed down.

To enhance the development efficiency of ultra-deep fault-controlled carbonate reservoirs, large-scale rock mechanical experiments were conducted to reveal the deformation and connectivity mechanisms of high-angle to near-vertical fault surfaces. Based on the mechanical and flow coupling principles of high-pressure water injection production, geomechanical modeling was employed to clarify the current in-situ stress field and fault activity distribution patterns in fault-controlled carbonate reservoirs. Significant differences were found in fault activities in different directions and in the connectivity of fracture and cavity bodies in different parts. The development effects of different wellbore trajectories were then analyzed, and an integrated geological and engineering working method was proposed to scientifically guide the design of wellbore trajectories and the optimization of water injection schemes. The results show: ① Large-scale fractured bodies and high-angle fracture systems in strike-slip fault deformation are key factors affecting reservoir quality. High-pressure water injection can activate existing fractures on one hand, and on the other hand, it can extend and expand based on existing fractures, even generating new fractures, promoting the interconnection of fault-controlled fracture and cavity bodies in both vertical and horizontal directions; ② During the high-pressure water injection process, coupling changes between mechanics and flow occur inside the fault body, improving the seepage environment, and increasing oil and gas recovery rate through cyclic lifting; ③ According to the shape and the occurrence of the fault body, and the dynamic shear deformation connectivity of the fault surface, the best well point and well trajectory for directional wells can be selected, and the water injection scheme can be optimized; ④ In the fault-controlled oil reservoir test area of Tarim Basin, the recovery rate was increased by 5% through high-pressure water injection. This method provides a good theoretical basis and technical support for the efficient development of ultra-deep fault-controlled reservoirs.

To optimize the identification of sweet spots with natural fracture development in ultra-deep tight sandstone reservoirs of Cretaceous in the Kuqa Depression, Tarim Basin, this study systematically analyzed the differences in rock mechanical properties across various sedimentary microfacies in the BZ gas field. Utilizing data from outcrops, rock slices, imaging logging, and other sources, a method for optimizing the rock mechanics parameter model of reservoirs was proposed, which enhanced the prediction accuracy of natural fractures within 200 m around the wellbore. Key findings of the research include: (1) In the third member of the Cretaceous Bashijiqike Formation in the BZ gas field, different sedimentary microfacies and the same microfacies at different positions had differences in rock composition and rock assemblages (including debris content, matrix content, grain size sorting, sand-to-mud ratio, and sand-mudstone combinations). These variations affected the reservoir's Poisson's ratio and Young's modulus, and different microfacies had different rock mechanical parameters. (2) The extent of fracture development differed across various sedimentary microfacies of sand bodies. Fractures were most developed in the underwater distributary channel sandstones at the fan delta front, making them more prone to fracturing compared to the interdistributary bay microfacies and distributary channel microfacies on the delta plain. (3) By further establishing three-dimensional models of different microfacies based on geometric parameters derived from outcrops, it would be feasible to optimize sedimentary microfacies models and rock mechanical parameter models around the wellbore, thereby facilitating more accurate fracture prediction.

Efficient exploration and development of ultra-deep oil and gas reservoirs are key objectives in current global energy geological research. The concept of "geomechanical strata and oil and gas exploration and development" represents a cutting-edge research area internationally. Establishing an effective method for dividing geomechanical layers holds both theoretical and practical significance for the efficient exploration and economical development of ultra-deep oil and gas reservoirs. Currently, the state of in-situ stress affects the effectiveness of natural fractures, while the development and distribution of fractures impact the mechanical properties of rocks, which influence the the distribution of in-situ stress. However, the existing "rock mechanical stratigraphy theory" fails to comprehensively cover the coupling relationships among these three factors. In response, this study introduced a method for the quantitative division of geomechanical strata based on six parameters: minimum horizontal principal stress, difference in horizontal stress, elastic modulus, angle between the current dominant stress orientation and the natural fracture orientation, natural fracture density, and stress concentration factor. An analysis of well W in the Dabei area of the Kelasu structural belt, Kuqa Depression, Tarim Basin, demonstrated that the target layers at the Cretaceous Bashijiqike Formation exhibited strong vertical geomechanical heterogeneity. The geomechanical strata of the reservoir correlated well with the development sections of the gas layers. Therefore, with the results of geomechanical strata division, it is possible to guide the optimization of sweet spots in ultra-deep oil and gas reservoirs.

Abstract Electrocaloric refrigeration which is environmentally benign has attracted considerable attention. In distinction to ferroelectric materials, which exhibit an extremely high positive electrocaloric effect near the Curie temperature, antiferroelectric materials represented by PbZrO3 have a specific negative electrocaloric effect, i.e., electric field decreases the temperature of the materials. However, the explanation of the microscopic mechanism of the negative electrocaloric effect is still unclear, and further research is still needed to provide a theoretical basis for the negative electrocaloric effect enhancement. Herein, the antiferroelectric phase-field model has been proposed to design polar boundaries enhancing antiferroelectric negative electrocaloric performance in PbZrO3-based materials. Based on this, we have simulated the polarization response and domain switching process of the temperature and electric field-induced antiferroelectric—ferroelectric phase transition. It is shown that the temperature range tends to increase as the density of polar boundaries increases from the antiferroelectric stripe domain, polymorphic domain to the nanodomain. Among them, the peak adiabatic temperature change of antiferroelectric nanodomains can reach −13.05 K at 84 kV/cm, and a wide temperature range of about 75 K can be realized at 42 kV/cm. We expect these discoveries to spur further interest in the potential applications of antiferroelectric materials for next-generation refrigeration devices.

Abstract Background Angina is a crucial risk signal for cardiovascular disease. However, few studies have evaluated the effects of ambient air pollution exposure on angina. Objective We aimed to explore the short-term effects of air pollution on hospitalization for angina and its lag effects. Methods We collected data on air pollutant concentrations and angina hospitalizations from 2013 to 2020. Distributed lag nonlinear model (DLNM) was used to evaluate the short-term effects of air pollutants on angina hospitalization under different lag structures. Stratified analysis by sex, age and season was obtained. Results A total of 39,110 cases of angina hospitalization were included in the study. The results showed a significant positive correlation between PM2.5, SO2, NO2, and CO and angina hospitalization. Their maximum harmful effects were observed at lag0-7 (RR = 1.042; 95% CI: 1.017, 1.068), lag0-3 (RR = 1.067; 95% CI: 1.005, 1.133), lag0-6 (RR = 1.078; 95% CI: 1.041, 1.117), and lag0-6 (RR = 1.244; 95% CI: 1.109, 1.397), respectively. PM10 did not have an overall risk effect on angina hospitalization, but it did have a risk effect on women and the elderly. O3 was significantly negatively correlated with angina hospitalization, with the most pronounced effect observed at lag0-6 (RR = 0.960; 95% CI: 0.940, 0.982). Stratified analysis results showed that women and the elderly were more susceptible to pollutants, and the adverse effects of pollutants were stronger in the cold season. Conclusion Short-term exposure to PM2.5, SO2, NO2, and CO increases the risk of hospitalization for angina.

Abstract Ulcerative colitis (UC) is a persistent inflammatory condition that specifically targets the colon and rectum. Existing therapies fail to adequately address the clinical requirements of people suffering from this ailment. Despite the acknowledged potential of nanomedicines in the field of anti-inflammatory treatment, their widespread use in clinical settings is impeded by their expensive nature and the uncertainty surrounding their safety profiles. This study illustrates that two naturally occurring phytochemicals, Costunolide (COS) and Glycyrrhizic acid (GA), form carrier-free, multifunctional spherical nanoparticles (NPs) through noncovalent interactions, such as π–π stacking and hydrogen bonding. The COS-GA NPs displayed a synergistic anti-inflammatory effect, providing much more evidently improved therapeutic benefits for dextran sodium sulfate (DSS)-induced UC mice due to more effective reduction in inflammation and oxidative stress than did equal dosages of COS or GA used alone. In addition, COS-GA NPs have biocompatibility and biosafety properties unique to them. This study will serve as affirmation of the potential of COS-GA NPs as innovative natural anti-inflammatory and antioxidant activities and also such agents as drug discovery in UC, leading possibly to better outcomes in people living with this disabling condition.

Posttraumatic osteoarthritis (PTOA) patients are often diagnosed by X-ray imaging at a middle-late stage when drug interventions are less effective. Early PTOA is characterized by overexpressed matrix metalloprotease 13 (MMP13). Herein, we constructed an integrated diagnosis and treatment micelle modified with MMP13 enzyme-detachable, cyanine 5 (Cy5)-containing PEG, black hole quencher-3 (BHQ3), and cRGD ligands and loaded with siRNA silencing MMP13 (siM13), namely ERMs@siM13. ERMs@siM13 could be cleaved by MMP13 in the diseased cartilage tissues to detach the PEG shell, causing cRGD exposure. Accordingly, the ligand exposure promoted micelle uptake by the diseased chondrocytes by binding to cell surface αvβ3 integrin, increasing intracellular siM13 delivery for on-demand MMP13 downregulation. Meanwhile, the Cy5 fluorescence was restored by detaching from the BHQ3-containing micelle, precisely reflecting the diseased cartilage state. In particular, the intensity of Cy5 fluorescence generated by ERMs@siM13 that hinged on the MMP13 levels could reflect the PTOA severity, enabling the physicians to adjust the therapeutic regimen. Finally, in the murine PTOA model, ERMs@siM13 could diagnose the early-stage PTOA, perform timely interventions, and monitor the OA progression level during treatment through a real-time detection of MMP13. Therefore, ERMs@siM13 represents an appealing approach for early-stage PTOA theranostics.

This paper presents a selective review of statistical computation methods for massive data analysis. A huge amount of statistical methods for massive data computation have been rapidly developed in the past decades. In this work, we focus on three categories of statistical computation methods: (1) distributed computing, (2) subsampling methods, and (3) minibatch gradient techniques. The first class of literature is about distributed computing and focuses on the situation, where the dataset size is too huge to be comfortably handled by one single computer. In this case, a distributed computation system with multiple computers has to be utilized. The second class of literature is about subsampling methods and concerns about the situation, where the blacksample size of dataset is small enough to be placed on one single computer but too large to be easily processed by its memory as a whole. The last class of literature studies those minibatch gradient related optimization techniques, which have been extensively used for optimizing various deep learning models.

Post translational modifications (PTMs) can change the properties of a protein by covalent addition of functional groups to one or more amino acids, and influence almost all aspects of normal cell biology and pathogenesis. Lactylation is a novel identified PTM, and has been found in both histone and non-histone proteins. Since associated with the end product of glycolysis-- lactate, lactylation modification could provide a new perspective for understanding the relationship between metabolic reprogramming and epigenetic modifications. Accumulated evidences suggest that lactylation play important roles in tumor progression and links to poor prognosis in clinical studies. Histone lactylation can affect gene expression in tumor cells and immunological cells, further promoting tumor progression and immune suppression. Lactylation on non-histone proteins can also regulate tumor progression and drug resistance. In this review, we aimed to summarize the roles of lactylation in cancer progression, microenvironment interactions and immune suppression, try to identify new molecular targets for cancer therapy and provide a new direction for combined targeted therapy and immunotherapy.

Abstract Background Q fever, caused by the zoonotic pathogen Coxiella burnetii, exhibits a worldwide prevalence. In China, Q fever is not recognized as a notifiable disease, and the disease is overlooked and underestimated in clinical practice, leading to diagnostic challenges. Case presentation We present a case series of three patients diagnosed with persistent Q fever between 2022 and 2023. The average age of our three cases was 63.33 years old, consisting of two males and one female. The medical history of the individuals included previous valve replacement, aneurysm followed by aortic stent-graft placement and prosthetic hip joint replacement. At the onset of the disease, only one case exhibited acute fever, while the remaining two cases were devoid of any acute symptoms. The etiology was initially overlooked until metagenomic next-generation sequencing test identified Coxiella burnetii from the blood or biopsy samples. Delayed diagnosis was noted, with a duration ranging from three months to one year between the onset of the disease and its confirmation. The epidemiological history uncovered that none of the three cases had direct exposure to domestic animals or consumption of unpasteurized dairy products. Case 1 and 2 resided in urban areas, while Case 3 was a rural resident engaged in farming. All patients received combination therapy of doxycycline and hydroxychloroquine, and no recurrence of the disease was observed during the follow-up period. Conclusion Q fever is rarely diagnosed and reported in clinical practice in our country. We should be aware of persistent Q fever in high-risk population, even with unremarkable exposure history. Metagenomic next-generation sequencing holds great potential as a diagnostic tool for identifying rare and fastidious pathogens such as Coxiella burnetii.

During checking continuous waveform record, it was found that some stations of Tianjin such as EWZ were significantly affected by one unknown noise, and EWZ station was the most seriously affected. Long term observations had also found that this noise cannot be observed for uncertainly several days each year. This noise was all year round and did not change with day and night time, and it had been existed for many years. This noise was different from typical environmental background noise and had some fixed characteristics. This article studied the noise from several aspects such as its own characteristic, its coverage of influence, spectral characteristics, and impact on earthquake records. The research has shown that the noise was not affected by natural factors such as weather and season, and had a characteristic of amplitude decreasing as the distance increasing from EWZ station. The main frequency of this noise ranged 1～2 Hz. The impact of noise was relatively wide and it can be recorded by 12 surrounding stations, with YGZ station being the farthest and approximately 58 km away from EWZ station. Through polarization analysis, it was found that the propagation of noise had a specific directionality, so it is preliminary judged that this noise had the characteristic of fixed source noise. This noise will have an impact on seismic records, reducing the seismic phase pickup rate, and even completely submerging it in the noise. Frequency filtering can improve it.

Abstract Background Pediatric-type diffuse high-grade glioma (pHGG) is the most frequent malignant brain tumor in children and can be subclassified into multiple entities. Fusion genes activating the MET receptor tyrosine kinase often occur in infant-type hemispheric glioma (IHG) but also in other pHGG and are associated with devastating morbidity and mortality. Methods To identify new treatment options, we established and characterized two novel orthotopic mouse models harboring distinct MET fusions. These included an immunocompetent, murine allograft model and patient-derived orthotopic xenografts (PDOX) from a MET-fusion IHG patient who failed conventional therapy and targeted therapy with cabozantinib. With these models, we analyzed the efficacy and pharmacokinetic properties of three MET inhibitors, capmatinib, crizotinib and cabozantinib, alone or combined with radiotherapy. Results Capmatinib showed superior brain pharmacokinetic properties and greater in vitro and in vivo efficacy than cabozantinib or crizotinib in both models. The PDOX models recapitulated the poor efficacy of cabozantinib experienced by the patient. In contrast, capmatinib extended survival and induced long-term progression-free survival when combined with radiotherapy in two complementary mouse models. Capmatinib treatment increased radiation-induced DNA double-strand breaks and delayed their repair. Conclusions We comprehensively investigated the combination of MET inhibition and radiotherapy as a novel treatment option for MET-driven pHGG. Our seminal preclinical data package includes pharmacokinetic characterization, recapitulation of clinical outcomes, coinciding results from multiple complementing in vivo studies, and insights into molecular mechanism underlying increased efficacy. Taken together, we demonstrate the groundbreaking efficacy of capmatinib and radiation as a highly promising concept for future clinical trials.

Compared to bioactive glass 45S5, bioactive glass 1393 has shown greater potential in activating tissue cells and promoting angiogenesis for bone repair. Nevertheless, the effect of bioactive glass 1393 in the context of wound healing remains extensively unexplored, and its mechanism in wound healing remains unclear. Considering that angiogenesis is a critical stage in wound healing, we hypothesize that bioactive glass 1393 may facilitate wound healing through the stimulation of angiogenesis. To validate this hypothesis and further explore the mechanisms underlying its pro-angiogenic effects, we investigated the impact of bioactive glass 1393 on wound healing angiogenesis through both in vivo and in vitro studies. The research demonstrated that bioactive glass 1393 accelerated wound healing by promoting the formation of granulation, deposition of collagen, and angiogenesis. The results of Western blot analysis and immunofluorescence staining revealed that bioactive glass 1393 up-regulated the expression of angiogenesis-related factors. Additionally, bioactive glass 1393 inhibited the expression of ROS and P53 to promote angiogenesis. Furthermore, bioactive glass 1393 stimulated angiogenesis through the P53 signaling pathway, as evidenced by P53 activation assays. Collectively, these findings indicate that bioactive glass 1393 accelerates wound healing by promoting angiogenesis via the ROS/P53/MMP9 signaling pathway.

Pancreatic cancer (PC) is a very aggressive digestive system tumor, known for its high mortality rate, low cure rate, low survival rate and poor prognosis. In particular, pancreatic ductal adenocarcinoma (PADC), which accounts for more than 90% of PC cases, has an overall 5-year survival rate of only 5%, which is an extremely critical situation. Early detection and effective treatment of PC is extremely difficult, which leads many patients to despair. In the current medical context, targeted therapy, as an important strategy for cancer treatment, is expected. However, the problems of immune escape and drug resistance in PC have become two major obstacles that are difficult to be overcome by targeted therapy. How to break through these two difficulties has become a key issue to be solved in the field of PC therapy. In recent years, non-coding RNAs (ncRNAs) have continued to heat up in the field of cancer research. NcRNAs play a pivotal role in gene regulation, cell differentiation, development, and disease processes, and their important roles in the genesis, development, and therapeutic response of PC have been gradually revealed. More importantly, ncRNAs have many advantages as therapeutic targets, such as high specificity and low side effects, making them a new favorite in the field of PC therapy. Therefore, the aim of this paper is to provide new ideas and methods for the targeted therapy of PC by reviewing the mechanism of action of four major ncRNAs (circRNAs, lncRNAs, miRNAs, siRNAs) in both immune escape and drug resistance of PC. It is expected that an effective way to overcome immune escape and drug resistance can be found through in-depth study of ncRNA, bringing a ray of hope to PC patients.

Microplastics and phthalates are prevalent and emerging pollutants that pose a potential impact on human health. Previous studies suggest that both microplastics and phthalates can adversely affect the reproductive systems of humans and mammals. However, the combined impact of these pollutants on the female reproductive system remains unclear. Here we show the impacts of exposure to polystyrene microplastics (PS-MPs) and di-2-ethylhexyl phthalate (DEHP) on female Sprague-Dawley rats’ reproductive systems. We find that co-exposure to PS-MPs and DEHP results in a marked increase in cystic and atretic follicles, oxidative stress, fibrosis, and dysregulation of serum sex hormone homeostasis in the ovaries of the rats. Proteomic analysis identified differentially expressed proteins that were predominantly enriched in signaling pathways related to fatty acid metabolism and tight junctions, regulated by transforming growth factor β1 (TGF-β1). We further confirm that co-exposure to DEHP and PS-MPs activates the TGF-β1/Smad3 signaling pathway, and inhibiting this pathway alleviates oxidative stress, hormonal dysregulation, and ovarian fibrosis. These results indicate that exposure to the combination of microplastics and phthalates leads to a significant increase in atretic follicles and may increase the risk of polycystic ovary syndrome (PCOS). Our study provides new insights into the reproductive toxicity effects of microplastics and DEHP exposure on female mammals, highlighting the potential link between environmental pollutants and the occurrence of PCOS. These findings highlight the need for comprehensive assessments of the reproductive health risks posed by microplastic pollution to women and contribute to the scientific basis for evaluating such risks.

Pancreatic cancer remains one of the most lethal malignancies, with conventional treatment options providing limited efficacy. Recent advancements in immunotherapy have offered new hope, yet the unique tumor microenvironment (TME) of pancreatic cancer poses significant challenges to its successful application. This review explores the transformative impact of single-cell technology on the understanding and treatment of pancreatic cancer. By enabling high-resolution analysis of cellular heterogeneity within the TME, single-cell approaches have elucidated the complex interplay between various immune and tumor cell populations. These insights have led to the identification of predictive biomarkers and the development of innovative, personalized immunotherapeutic strategies. The review discusses the role of single-cell technology in dissecting the intricate immune landscape of pancreatic cancer, highlighting the discovery of T cell exhaustion profiles and macrophage polarization states that influence treatment response. Moreover, it outlines the potential of single-cell data in guiding the selection of immunotherapy drugs and optimizing treatment plans. The review also addresses the challenges and prospects of translating these single-cell-based innovations into clinical practice, emphasizing the need for interdisciplinary research and the integration of artificial intelligence to overcome current limitations. Ultimately, the review underscores the promise of single-cell technology in driving therapeutic strategy innovation and improving patient outcomes in the battle against pancreatic cancer.

Parkinson’s disease (PD) is a neurodegenerative disease characterized by the gradual loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc), abnormal accumulation of α-synuclein (α-syn), and activation of microglia leading to neuroinflammation. Disturbances in circadian rhythm play a significant role in PD, with most non-motor symptoms associated with disruptions in circadian rhythm. These disturbances can be observed years before motor symptoms appear and are marked by the emergence of non-motor symptoms related to PD, such as rapid eye movement sleep behavior disorder (RBD), restless leg syndrome (RLS), excessive daytime sleepiness (EDS), depression and anxiety, changes in blood pressure, gastrointestinal dysfunction, and urinary problems. Circadian rhythm disruption precedes the onset of motor symptoms and contributes to the progression of PD. In brief, this article outlines the role of circadian rhythm disruption in triggering PD at cellular and molecular levels, as well as its clinical manifestations. It also explores how circadian rhythm research can contribute to preventing the onset and progression of PD from current and future perspectives.

Autoimmune rheumatic diseases (ARD) present a significant global health challenge characterized by a rising prevalence. These highly heterogeneous diseases involve complex pathophysiological mechanisms, leading to variable treatment efficacies across individuals. This variability underscores the need for personalized and precise treatment strategies. Traditionally, clinical practices have depended on empirical treatment selection, which often results in delays in effective disease management and can cause irreversible damage to multiple organs. Such delays significantly affect patient quality of life and prognosis. Artificial intelligence (AI) has recently emerged as a transformative tool in rheumatology, offering new insights and methodologies. Current research explores AI’s capabilities in diagnosing diseases, stratifying risks, assessing prognoses, and predicting treatment responses in ARD. These developments in AI offer the potential for more precise and targeted treatment strategies, fostering optimism for enhanced patient outcomes. This paper critically reviews the latest AI advancements for predicting treatment responses in ARD, highlights the current state of the art, identifies ongoing challenges, and proposes directions for future research. By capitalizing on AI’s capabilities, researchers and clinicians are poised to develop more personalized and effective interventions, improving care and outcomes for patients with ARD.

ObjectiveHIV drug resistance (HIVDR) has become a threat to the elimination of the AIDS epidemic due to the global scale-up of antiretroviral therapy (ART) for HIV-infected individuals. This study aims to investigate the epidemiological dynamics and molecular characterization of HIV pretreatment drug resistance (PDR) and acquired drug resistance (ADR) in Hangzhou, a developed region in China.MethodsAn epidemiological survey combined with a molecular transmission network and Bayesian analysis was conducted. A total of 3,596 individuals with newly confirmed HIV infections (from 2020 to 2023) and 164 individuals with ART failure (from 2021 to 2023) were included. The molecular transmission network was used to identify key drug-resistant transmission clusters, while the Bayesian analysis was utilized to trace the origins and spread of these clusters.ResultsThe overall prevalence of PDR was found to be 8.4% (303/3596). Among these cases, PDR to non-nucleoside reverse transcriptase inhibitors (NNRTIs) accounted for 4.7% (170/3596), significantly higher than the resistance observed for protease inhibitors (PIs; 2.8%, p

In patients with rheumatoid arthritis (RA), intestinal flora imbalance and butyrate metabolism disorders precede clinical arthritis and are associated with the pathogenesis of RA. This imbalance can alter the immunology and intestinal permeability of the intestinal mucosa, leading to damage to the intestinal barrier. In this context, bacteria and their metabolites can enter the bloodstream and reach the distant target tissues of the host, resulting in local inflammation and aggravating arthritis. Additionally, arthritis is also exacerbated by bone destruction and immune tolerance due to disturbed differentiation of osteoclasts and adaptive immune cells. Of note, butyrate is a metabolite of intestinal flora, which not only locally inhibits intestinal immunity and targets zonulin and tight junction proteins to alleviate intestinal barrier-mediated arthritis but also inhibits osteoclasts and autoantibodies and balances the immune responses of T and B lymphocytes throughout the body to repress bone erosion and inflammation. Therefore, butyrate is a key intermediate linking intestinal flora to the host. As a result, restoring the butyrate-producing capacity of intestinal flora and using exogenous butyrate are potential therapeutic strategies for RA in the future.

All‐inorganic perovskite CsPbBr3 (CPB) nanocrystals (NCs) are not widely applied in aqueous environments due to their readily decomposable nature. Therefore, the aqueous‐phase preparation of CPB NCs has been a considerable challenge. In this work, a feasible method is proposed for preparing aqueous‐phase core–shell CPB nanorods (NRs) encapsulated with polydopamine (PDA) by employing a multifunctional additive cesium trifluoroacetate (Cs‐TFA). Highly luminescent TFA‐CPB NRs are obtained via a chemical transformation of Cs4PbBr6 NCs in water. Subsequently, PDA constitutes a robust shell on the surface of TFA‐CPB NRs through the covalent oxidative polymerization, which effectively reduces the original dynamic properties of surface ligands, retards the decomposition of ligands and inhibits the leakage of Pb2+ ions. The results demonstrate that the fluorescence intensity of TFA‐CPB@PDA NRs maintains 49.3% of the initial intensity after 136 days. Meanwhile, the NRs exhibit low cytotoxicity, and the cell viability remains at 80% when the concentration of the NRs is 200 μg mL−1. The reliable preparation of aqueous‐phase core–shell perovskite NRs (PNRs) will facilitate their development in many fields, such as materials science, biology, medicine, and their applications in aqueous environments.

Pancreatic cancer (PC) is a highly aggressive and lethal malignancy characterized by a complex tumor microenvironment (TME) and immunosuppressive features that limit the efficacy of existing treatments. This paper reviews the potential of combining ultrasound with macrophage exhaustion in the treatment of pancreatic cancer. Macrophages, particularly tumor-associated macrophages (TAMs), are crucial in pancreatic cancer progression and immune escape. Prolonged exposure to the immunosuppressive TME leads to macrophage exhaustion, reducing their anti-tumor ability and instead promoting tumor growth. The CSF1/CSF1R signaling pathway is key in macrophage recruitment and functional regulation, making it an effective target for combating macrophage exhaustion. Ultrasound technology not only plays a significant role in diagnosis and staging but also enhances therapeutic efficacy by guiding radiofrequency ablation (RFA) and percutaneous alcohol injection (PEI) in combination with immunomodulators. Additionally, ultrasound imaging can monitor the number and functional status of TAMs in real-time, providing a basis for optimizing treatment strategies. Future studies should further investigate the combined use of ultrasound and immunomodulators to refine treatment regimens, address challenges such as individual variability and long-term effects, and offer new hope for pancreatic cancer patients.

Magnetic and ferroelectric oxide thin films have long been studied for their applications in electronics, optics, and sensors. The properties of these oxide thin films are highly dependent on the film growth quality and conditions. To maximize the film quality, epitaxial oxide thin films are frequently grown on single‐crystal oxide substrates such as strontium titanate (SrTiO3) and lanthanum aluminate (LaAlO3) to satisfy lattice matching and minimize defect formation. However, these single‐crystal oxide substrates cannot readily be used in practical applications due to their high cost, limited availability, and small wafer sizes. One leading solution to this challenge is film transfer. In this demonstration, a material from a new class of multiferroic oxides is selected, namely bismuth‐based layered oxides, for the transfer. A water‐soluble sacrificial layer of Sr3Al2O6 is inserted between the oxide substrate and the film, enabling the release of the film from the original substrate onto a polymer support layer. The films are transferred onto new substrates of silicon and lithium niobate (LiNbO3) and the polymer layer is removed. These substrates allow for the future design of electronic and optical devices as well as sensors using this new group of multiferroic layered oxide films.

This study investigates leakage mechanisms in vertical GaN-on-GaN Schottky barrier diodes (SBDs) and demonstrates effective mitigation strategies. The fabricated devices exhibit low reverse leakage current (1 × 10−5 A/cm2 at −200 V) and a high Ion/Ioff ratio (∼1010), surpassing the performance of GaN SBDs on foreign substrates. We elucidate dominant leakage mechanisms—thermionic emission, Poole–Frenkel emission, and variable-range hopping—and their evolution with temperature and bias. Optimized fabrication processes, including defect etching and a novel dual-layer passivation technique, achieve over a 1000-fold reduction in leakage current.

Cardiomyopathies, encompassing hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM), constitute a diverse spectrum of heart muscle diseases that often culminating in heart failure (HF). The inherent molecular heterogeneity of these conditions has implications for prognosis and therapeutic strategies.Publicly available microarray and RNA sequencing (RNA-seq) data sets of HCM (n = 106 from GSE36961) and DCM (n = 18 from GSE135055 and 166 from GSE141910) patients were employed for our analysis. The Non-negative Matrix Factorization (NMF) algorithm was applied to explore the molecular stratification within HCM and DCM, and enrichment analysis was performed to delineate their biological characteristics. By integrating bulk and single-nucleus RNA-seq (snRNA-seq) data, we identified a potential biomarker for HCM progression and cardiac fibrosis, which was subsequently validated using mendelian randomization and in vitro.Our application of NMF identified two distinct molecular clusters. Particularly, a profibrotic, heart failure with reduced ejection fraction (HFrEF)-resembling Cluster 1 emerged, characterized by diminished expression of CORIN and a high degree of fibroblast activation. This cluster also exhibited lower left ventricular ejection fraction (LVEF) and worse prognostic outcomes, establishing the significance of this molecular subclassification. We further found that overexpression of CORIN could mitigate TGFβ1-induced expression of col1a1 and α-SMA in neonatal rat cardiac fibroblasts.Our results indicated the heterogeneity of HCM population, and further evidenced the participation of corin in the progression of HCM, DCM and HFrEF. Nevertheless, our study is constrained by the lack of corresponding clinical data and experimental validation of the identified subtypes. Therefore, further studies are warranted to elucidate the downstream pathways of corin and to validate these findings in independent patient cohorts.

Lung cancer is one of the most common malignant tumours worldwide and its high mortality rate makes it a leading cause of cancer-related deaths. To address this daunting challenge, we need a comprehensive understanding of the pathogenesis and progression of lung cancer in order to adopt more effective therapeutic strategies. In this regard, integrating multi-omics data of the lung provides a highly promising avenue. Multi-omics approaches such as genomics, transcriptomics, proteomics, and metabolomics have become key tools in the study of lung cancer. The application of these methods not only helps to resolve the immunotherapeutic mechanisms of lung cancer, but also provides a theoretical basis for the development of personalised treatment plans. By integrating multi-omics, we have gained a more comprehensive understanding of the process of lung cancer development and progression, and discovered potential immunotherapy targets. This review summarises the studies on multi-omics and immunology in lung cancer, and explores the application of these studies in early diagnosis, treatment selection and prognostic assessment of lung cancer, with the aim of providing more personalised and effective treatment options for lung cancer patients.

Summary: Patients with diabetes often experience fragile fractures despite normal or higher bone mineral density (BMD), a phenomenon termed the diabetic bone paradox (DBP). The pathogenesis and therapeutics opinions for diabetic bone disease (DBD) are not fully explored. In this study, we utilize two preclinical diabetic models, the leptin receptor-deficient db/db mice (DB) mouse model and the streptozotocin-induced diabetes (STZ) mouse model. These models demonstrate higher BMD and lower mechanical strength, mirroring clinical observations in diabetic patients. Advanced glycation end products (AGEs) accumulate in diabetic bones, causing higher non-enzymatic crosslinking within collagen fibrils. This inhibits intrafibrillar mineralization and leads to disordered mineral deposition on collagen fibrils, ultimately reducing bone strength. Guanidines, inhibiting AGE formation, significantly improve the microstructure and biomechanical strength of diabetic bone and enhance bone fracture healing. Therefore, targeting AGEs may offer a strategy to regulate bone mineralization and microstructure, potentially preventing the onset of DBD.

ObjectiveThis study aimed to explore the relationship between smoking status and the interval to brain metastasis in patients with non-small cell lung cancer (NSCLC) and its impact on survival time after brain metastasis.MethodsData were collected from patients with NSCLC with brain metastases who were treated at our centre between January 2005 and December 2017. Clinical indices such as clinicopathological features and smoking status were recorded, and patients were followed up until 1 September 2022. Based on our inclusion and exclusion criteria, 461 patients were analysed and matched using 1:1 propensity score matching. Three balanced groups were formed: non-smoking (n = 113), smoking cessation (n = 113), and smoking (n = 113). The interval to brain metastasis and overall survival were compared between the groups.ResultsThere was a statistically significant difference in the interval to brain metastasis between the non-smoking and smoking cessation groups (p = 0.001), as well as between the non-smoking and smoking groups (p < 0.001). However, the difference between the smoking cessation and smoking groups was not statistically significant (p = 0.106). Multivariate and univariate analyses identified smoking status, clinical stage, lung cancer surgery, chemotherapy, and chest radiotherapy as independent predictors of the interval to brain metastasis. Additionally, the multivariate analysis showed that smoking status, driver gene mutations, and chest radiotherapy independently influenced survival after brain metastasis.ConclusionSmoking status in patients with NSCLC affects the interval to brain metastasis and survival after brain metastasis.

BackgroundColorectal cancer (CRC) poses a global health threat, with the oral microbiome increasingly implicated in its pathogenesis. This study leverages Mendelian Randomization (MR) to explore causal links between oral microbiota and CRC using data from the China National GeneBank and Biobank Japan. By integrating multi-omics approaches, we aim to uncover mechanisms by which the microbiome influences cellular metabolism and cancer development.MethodsWe analyzed microbiome profiles from 2017 tongue and 1915 saliva samples, and GWAS data for 6692 CRC cases and 27178 controls. Significant bacterial taxa were identified via MR analysis. Single-cell RNA sequencing and enrichment analyses elucidated underlying pathways, and drug predictions identified potential therapeutics.ResultsMR identified 19 bacterial taxa significantly associated with CRC. Protective effects were observed in taxa like RUG343 and Streptococcus_umgs_2425, while HOT-345_umgs_976 and W5053_sp000467935_mgs_712 increased CRC risk. Single-cell RNA sequencing revealed key pathways, including JAK-STAT signaling and tyrosine metabolism. Drug prediction highlighted potential therapeutics like Menadione Sodium Bisulfite and Raloxifene.ConclusionThis study establishes the critical role of the oral microbiome in colorectal cancer development, identifying specific microbial taxa linked to CRC risk. Single-cell RNA sequencing and drug prediction analyses further elucidate key pathways and potential therapeutics, providing novel insights and personalized treatment strategies for CRC.

Abstract BackgroundDrug users are a high-risk group for HIV infection and are prominent HIV carriers. Given the emergence of new drugs, we explored current drug-using behaviors, HIV infections, and the correlation between drug-using behaviors and HIV infection risk among drug users from 2014 to 2021. ObjectiveWe aimed to identify the prevalence of HIV infection risk among drug users and explore drug use behaviors based on the updated data, which could provide evidence for the precision of HIV prevention strategies among drug users. MethodsData were collected from sentinel surveillance of drug users in rehabilitation centers and communities in Hangzhou (2014‐2021), including sociodemographic characteristics, HIV awareness, drug use, risky sexual behaviors, and HIV infection status. Multivariate logistic regression was used to identify the factors influencing HIV infection and risky sexual behaviors among drug users. ResultsIn total, 5623 drug users (male: n=4734, 84.19%; age: mean 38.38, SD 9.94 years) were included. New drugs dominated among the participants (n=3674, 65.34%). The main mode of drug use was noninjection (n=4756, 84.58%). Overall, for 27.45% (n=1544) of injected drugs in the last month before the investigation, the average daily injection frequency was 3.10 (SD 8.24). Meanwhile, 3.43% of participants shared needles. The incidence of sexual behaviors after drug use was 33.13% (n=1863), with 35.75% (n=666) of them using a condom in the last time. Overall, 116 participants tested positive for HIV antibodies (infection rate=2.06%). New drug users exhibited more postuse sexual behaviors than traditional drug users (odds ratio [OR] 7.771, 95% CI 6.126‐9.856; PPPPPPP ConclusionsNew drug types and noninjection were the main patterns in last 7 years. Using new types of drugs, rather than traditional drugs, was associated with an increased risk of HIV infection. Injection drug use was a risk factor for HIV infection. HIV awareness among drug users was high, but the incidence of risky sexual behaviors remained high. Therefore, it is important to promote the behavioral transformation of high-risk populations from cognition to attitude, and then to taking protective measures.

Harmonics are an important cause of voltage distortion, and voltage reduction and voltage distortion are the main causes of commutation failure. But most of the current research studies on commutation failure are based on the drop in fundamental voltage after a fault, and there are few reports on the impact of voltage distortion on commutation failure. Aiming to solve the above problem, this article first analyzes the generation and transmission characteristics of harmonics in AC and DC systems, as well as the coupling degree of harmonics in DC systems. Then, starting from the mechanism of the commutation process, a commutation failure analysis method based on the harmonic voltage time area is proposed. This method can quantitatively analyze the impact of different harmonics on commutation failure. On this basis, the harmonic criteria for causing commutation failure are established, and the harmonic characteristics of AC voltage when harmonics cause subsequent commutation failure are quantitatively analyzed. Finally, a preventive controller is proposed to suppress commutation failure caused by different harmonics, where the above analysis is verified by the simulations.

BackgroundTryptophan Metabolism-associated Genes (TMGs), such as ECHS1 and ALDH2, are crucial in cancer progression through immunosuppressive mechanisms, particularly in Gastric Cancer (GC). This study explores their effects on the Tumor Microenvironment (TME). Additionally, it examines their potential as novel immunotherapy targets.MethodsWe utilized single-cell and bulk transcriptomic technologies to analyze the heterogeneity of GC. Non-negative Matrix Factorization (NMF) clustering identified key TMGs, and extensive RNA-seq analyses were performed to pinpoint prognostic genes and potential immunotherapy targets. Furthermore, through PCR analyses we found that ECHS1 and ALDH2 gene expression plays a regulatory role in the migration, invasion and inflammatory factor in AGS and SNU-1 cell lines. The interference effect of si-ECHS1 and ad-ALDH2 was validated using cell scratch assay in AGS and SNU-1 cell line.ResultsWe observed a statistically significant correlation between ECHS1 and ALDH2 expression and increased TME heterogeneity. Our findings also revealed that ECHS1 down-regulation and ALDH2 up-regulation contribute to reduced TME heterogeneity, decreased inflammation, and inhibited AGS and SNU-1 tumor cells migration and proliferation. GSVA enrichment analysis highlighted the NF-kappa B(NF-κB) signaling pathway as specifically regulated by TMGs. Furthermore,ECHS1 and ALDH2 modulated CD8+ and CD4+ T cell activities, impacting GC progression. In vitro experiments further solidified our conclusions by showcasing the inhibitory effects of Si-ECHS1 and ad-ALDH2 on the invasive and proliferative capabilities of AGS and SNU-1 cells. Moreover, Si-ECHS1 and ad-ALDH2 gene expression effectively reduced the expression of inflammatory factors IL-10,IL-7,CXCL8 and IL-6, leading to a remarkable alleviation of chronic inflammation and the heterogeneous nature of the TME.ConclusionThis research highlights the importance of ECHS1 and ALDH2 in GC progression and immune modulation, suggesting that targeted therapies focusing on these genes offer promising avenues for personalized immunotherapy in GC. These findings hold potential for improving patient survival and quality of life. Future studies on the NF-κB signaling pathway’s role in this context are warranted to further elucidate the mechanisms underlying TMG-mediated immune modulation in GC.

Nitrogen oxides (NOx) are common pollutants emitted from stationary sources, such as industrial boilers and power plants, with significant adverse impacts on the environment and biosphere. The abatement of NOx from anthropic industrial processes requires reliable and sensitive monitoring systems. To address this challenge, we report a sensitive, robust, and compact quantum cascade laser (QCL)-based sensor to measure NO and NO2 emissions from industrial exhausts. This sensor uses two quantum cascade lasers, which take advantage of the intense absorption spectra of NO at 1929 cm−1 and NO2 at 1599 cm−1. A high-temperature multipass cell is designed to withstand harsh environments, which increases the light path length. The NOx concentrations are directly determined from the wavelength modulation spectroscopic model without the need for calibration. We conducted several laboratory experiments to evaluate the sensor's performance, with a focus on accuracy, sensitivity and selectivity. In the end, we showcased the field deployment of our sensor by continuously measuring NOx concentrations in a 2.8-MW gas-fired industrial boiler.