Search

Abstract Background Computed tomography (CT) is widely in clinics and is affected by metal implants. Metal segmentation is crucial for metal artifact correction, and the common threshold method often fails to accurately segment metals. Purpose This study aims to segment metal implants in CT images using a diffusion model and further validate it with clinical artifact images and phantom images of known size. Methods A retrospective study was conducted on 100 patients who received radiation therapy without metal artifacts, and simulated artifact data were generated using publicly available mask data. The study utilized 11,280 slices for training and verification, and 2,820 slices for testing. Metal mask segmentation was performed using DiffSeg, a diffusion model incorporating conditional dynamic coding and a global frequency parser (GFParser). Conditional dynamic coding fuses the current segmentation mask and prior images at multiple scales, while GFParser helps eliminate high-frequency noise in the mask. Clinical artifact images and phantom images are also used for model validation. Results Compared with the ground truth, the accuracy of DiffSeg for metal segmentation of simulated data was 97.89% and that of DSC was 95.45%. The mask shape obtained by threshold segmentation covered the ground truth and DSCs were 82.92% and 84.19% for threshold segmentation based on 2500 HU and 3000 HU. Evaluation metrics and visualization results show that DiffSeg performs better than other classical deep learning networks, especially for clinical CT, artifact data, and phantom data. Conclusion DiffSeg efficiently and robustly segments metal masks in artifact data with conditional dynamic coding and GFParser. Future work will involve embedding the metal segmentation model in metal artifact reduction to improve the reduction effect.

Abstract Background PM2.5 can induce and aggravate the occurrence and development of cardiovascular diseases (CVDs). The objective of our study is to estimate the causal effect of PM2.5 on mortality rates associated with CVDs using the instrumental variables (IVs) method. Methods We extracted daily meteorological, PM2.5 and CVDs death data from 2016 to 2020 in Binzhou. Subsequently, we employed the general additive model (GAM), two-stage predictor substitution (2SPS), and control function (CFN) to analyze the association between PM2.5 and daily CVDs mortality. Results The 2SPS estimated the association between PM2.5 and daily CVDs mortality as 1.14% (95% CI: 1.04%, 1.14%) for every 10 µg/m3 increase in PM2.5. Meanwhile, the CFN estimated this association to be 1.05% (95% CI: 1.02%, 1.10%). The GAM estimated it as 0.85% (95% CI: 0.77%, 1.05%). PM2.5 also exhibited a statistically significant effect on the mortality rate of patients with ischaemic heart disease, myocardial infarction, or cerebrovascular accidents (P

Abstract Objective The objective of this study was to investigate the therapeutic efficacy of thalidomide across various genotype presentations of β-thalassemia so as to facilitate the early screening of thalidomide-sensitive thalassemia cases and to understand the impact of iron overload on thalidomide. Methods From our initial sample of 52 patients, we observed 48 patients with β-thalassemia for two years after administration of thalidomide. This cohort included 34 patients with transfusion-dependent thalassemia (TDT) and 14 patients with non-transfusion-dependent thalassemia (NTDT). We recorded the values of hemoglobin (Hb), fetal hemoglobin (HbF), and serum ferritin (SF) in the baseline period and at 1, 3, 6, 12, 18, and 24 months after enrollment, as well as the pre- and post-treatment blood transfusion volume in all 48 cases. According to the increase in Hb levels from baseline during the 6-month observation period, the response to thalidomide was divided into four levels: main response (MaR), minor response (MiR), slow response (SLR), and no response (NR). A decrease in serum ferritin levels compared to baseline was considered alleviation of iron overload. We calculated the overall response rate (ORR) as follows: ORR = MaR + MiR + SLR/number of observed cases. Results The ORR was 91.7% (44/48 cases), and 72.9% showed MaR (35/48 cases). Among the 34 patients with TDT, 21 patients (61.8%) were free of blood transfusion, and the remaining 13 patients still required blood transfusion, but their total blood transfusion volume reduced by 31.3% when compared to the baseline. We found a total of 33 cases with 10 combinations of advantageous genes, which included 5 cases with βCD41-42/βCD17 and 6 cases with βCD41-42/β-28. Based on the treatment outcomes among the 48 cases in the observation group, there were 33 cases in the MaR group and 15 cases in the SLR/NR group. There was a difference in HbF between the two groups at baseline (P = 0.041). There were significant differences between the two groups in Hb and HbF at the time points of 6 and 12 months, respectively (P

To evaluate the risk of acquiring syphilis from a donated kidney, we evaluated kidney transplantation pairs from West China Hospital, Sichuan, China, during 2007–2022. Donor-derived syphilis was rare. Risk may be higher if donors have active syphilis and may be reduced if recipients receive ceftriaxone.

Abstract Electrochemical uranium extraction from nuclear wastewater represents an emerging strategy for recycling uranium resources. However, in nuclear fuel production which generates the majority of uranium-containing nuclear wastewater, fluoride ion (F−) co-exists with uranyl (UO2 2+), resulting in the complex species of UO2Fx and thus decreasing extraction efficiency. Herein, we construct Tiδ+-PO4 3− ion pair extraction sites in Ti(OH)PO4 for efficient electrochemical uranium extraction in wastewater from nuclear fuel production. These sites selectively bind with UO2Fx through the combined Ti-F and multiple O-U-O bonds. In the uranium extraction, the uranium species undergo a crystalline transition from U3O7 to K3UO2F5. In real nuclear wastewater, the uranium is electrochemically extracted with a high efficiency of 99.6% and finally purified as uranium oxide powder, corresponding to an extraction capacity of 6829 mg g−1 without saturation. This work paves an efficient way for electrochemical uranium recycling in real wastewater of nuclear production.

The relationship between sarcopenia and prognosis in solid organ transplantation recipients (SOTr) remains unverified. We aimed to quantify the prevalence of pretransplant sarcopenia and its effect on patient and graft survival in SOTr. We used PubMed, EMBASE, Cochrane Library and Web of Science to search relevant studies published in English (from inception to December 31, 2021). Prospective and retrospective cohort studies that reported the prevalence of sarcopenia before transplant or the association between sarcopenia and clinical outcomes in SOTr were included. Primary outcomes were the prevalence of sarcopenia and its impact on patient and graft survival. Secondary outcomes included perioperative complications, acute rejection, length of hospital stay, length of intensive care unit stay (ICU LOS) and early readmission. Thirty-nine studies involving 5792 patients were included. Pooled prevalence of sarcopenia amongst SOTr candidates was 40 % (95 % confidence interval [CI]: 34%–47 % and I2 = 97 %). Sarcopenia was associated with increased risk of death (hazard ratio [HR] = 1.87, 95 % CI: 1.46–2.41 and I2 = 60 %), poor graft survival (HR = 1.71, 95 % CI: 1.16–2.54 and I2 = 57 %) and increased liver graft loss (HR = 1.43, 95 % CI: 1.03–1.99 and I2 = 38 %). Patients with sarcopenia demonstrated increased incidence of perioperative complications (risk ratio [RR] = 1.34, 95 % CI: 1.17–1.53 and I2 = 40 %), long ICU LOS (mean difference = 2.31 days, 95 % CI: 0.58–4.04 and I2 = 97 %) and decreased risk of acute rejection (RR = 0.61, 95 % CI: 0.42–0.89 and I2 = 0 %). In Conclusion, sarcopenia is prevalent in SOTr candidates and associated with death and graft loss. Identifying sarcopenia before transplantation and intervening may improve long-term outcomes.

Summary: Background: The ubiquitin regulatory X (UBX) domain-containing proteins (UBXNs) are putative adaptors for ubiquitin ligases and valosin-containing protein; however, their in vivo physiological functions remain poorly characterised. We recently showed that UBXN3B is essential for activating innate immunity to DNA viruses and controlling DNA/RNA virus infection. Herein, we investigate its role in adaptive immunity. Methods: We evaluated the antibody responses to multiple viruses and pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza in tamoxifen-inducible global and constitutive B cell-specific Ubxn3b knockout mice; quantified various immune populations, B lineage progenitors/precursors, B cell receptor (BCR) signalling and apoptosis by flow cytometry, immunoblotting and immunofluorescence microscopy. We also performed bone marrow transfer, single-cell and bulk RNA sequencing. Findings: Both global and B cell-specific Ubxn3b knockout mice present a marked reduction in small precursor B-II (>60%), immature (>70%) and mature B (>95%) cell numbers. Transfer of wildtype bone marrow to irradiated global Ubxn3b knockouts restores normal B lymphopoiesis, while reverse transplantation does not. The mature B population shrinks rapidly with apoptosis and higher pro and activated caspase-3 protein levels were observed following induction of Ubxn3b knockout. Mechanistically, Ubxn3b deficiency leads to impaired pre-BCR signalling and cell cycle arrest. Ubxn3b knockout mice are highly vulnerable to respiratory viruses, with increased viral loads and prolonged immunopathology in the lung, and reduced production of virus-specific IgM/IgG. Interpretation: UBXN3B is essential for B lymphopoiesis by maintaining constitutive pre-BCR signalling and cell survival in a cell-intrinsic manner. Funding: United States National Institutes of Health grants, R01AI132526 and R21AI155820.

Hydrogenation and fluorination is a significant method to tune the electronic properties of two-dimensional (2D) materials. This paper theoretically predicted and analyzed the effects and regulatory mechanisms of surface functionalization on the electronic properties of 2D semiconductor tetrahex Boron/Aluminium Nitride (th-BN/th-AlN). The density-functional theory (DFT) calculations were employed to study various trends of band structure, effective mass, and work function. The results show that the electronic properties of 2D th-BN/th-AlN are susceptible to the surface adsorption atom species and coverage. Interconversions between semiconductor and metal properties or indirect and direct band structures in 2D th-XN (X = B, Al) can be realized by hydrogen and fluorine surface adsorption. The band gap expands and the work function decreases after H atom is adsorbed on the surface, while the band gap first increases and then decreases and the work function expands after F is adsorbed on the surface. After functionalization, the effective mass of the hole will be reduced to even lighter than that of an electron in certain directions. The change mechanisms of electronic properties in th-BN/AlN is surface adsorbed atoms will cause sp2-hybridized atoms to turn into sp3-hybridized atoms, which leads to the polarized double bonds between adjacent atoms becoming a single σ bond. The chemical bond changing will result in the band near the Fermi level gradually disappearing.

Background: Prior research has demonstrated that programmed cell death (PCD) and mitochondria assume pivotal roles in controlling cellular metabolism and maintaining bone cell equilibrium. Nonetheless, the comprehensive elucidation of their mode of operation in osteoporosis (OP) warrants further investigation. Therefore, this study aimed at analyzing the role of genes associated with PCD (PCD-RGs) and mitochondria (mortality factor-related genes; MRGs) in OP.Methods: Differentially expressed genes (DEGs) were identified by subjecting the GSE56815 dataset obtained from the Gene Expression Omnibus database to differential expression analysis and comparing OP patients with healthy individuals. The genes of interest were ascertained through the intersection of DEGs, MRGs, and PCD-RGs; these genes were filtered using machine learning methodologies to discover potential biomarkers. The prospective biomarkers displaying uniform patterns and statistically meaningful variances were identified by evaluating their levels in the GSE56815 dataset and conducting quantitative real-time polymerase chain reaction-based assessments. Moreover, the functional mechanisms of these biomarkers were further delineated by constructing a nomogram, which conducted gene set enrichment analysis, explored immune infiltration, generated regulatory networks, predicted drug responses, and performed molecular docking analyses.Results: Eighteen candidate genes were documented contingent upon the intersection between 2,354 DEGs, 1,136 MRGs, and 1,548 PCD-RGs. The biomarkers DAP3, BIK, and ACAA2 were upregulated in OP and were linked to oxidative phosphorylation. Furthermore, the predictive ability of the nomogram designed based on the OP biomarkers exhibited a certain degree of accuracy. Correlation analysis revealed a strong positive correlation between CD56dim natural killer cells and ACAA2 and a significant negative correlation between central memory CD4+ T cells and DAP3. DAP3, BIK, and ACAA2 were regulated by multiple factors; specifically, SETDB1 and ZNF281 modulated ACAA2 and DAP3, whereas TP63 and TFAP2C governed DAP3 and BIK. Additionally, a stable binding force was observed between the drugs (estradiol, valproic acid, and CGP52608) and the biomarkers.Conclusion: This investigation evidenced that the biomarkers DAP3, BIK, and ACAA2 are associated with PCD and mitochondria in OP, potentially facilitate the diagnosis of OP in clinical settings.

IntroductionFeeding bamboo powder is a kind of fiber raw material mainly composed of insoluble dietary fiber (IDF). In this study, IDF-based rice husk meal and feeding bamboo powder were used to compare the effects of bamboo fiber on fecal microflora and the performance of lactating sows and their offspring piglets.MethodsThirty healthy crossbred gilts (Yorkshire × Landrace) at day 105 of gestation were randomly allocated into three groups: CON, TRE1 supplemented with 2% BBF1 (feeding bamboo powder), and TRE2 supplemented with 2% BBF2 (99% feeding bamboo powder +1% bamboo fiber polymer material). The reproductive performance, serum indexes, and fecal microbiota of sows and piglets were analyzed. The results showed that, compared with CON, the average feed intake of sows in TRE1 during the second week of lactation was significantly increased by 21.96% (p

Summary: Biofilm formation plays a significant role in antibiotic resistance, necessitating the search for alternative therapies against biofilm-associated infections. This study demonstrates that 20 μg/mL tryptanthrin can hinder biofilm formation above 50% in various A. baumannii strains. Tryptanthrin impacts various stages of biofilm formation, including the inhibition of surface motility and eDNA release in A. baumannii, as well as an increase in its sensitivity to H202. RT-qPCR analysis reveals that tryptanthrin significantly decreases the expression of the following genes: abaI (19.07%), abaR (33.47%), bfmR (43.41%), csuA/B (64.16%), csuE (50.20%), ompA (67.93%), and katE (72.53%), which are related to biofilm formation and quorum sensing. Furthermore, tryptanthrin is relatively safe and can reduce the virulence of A. baumannii in a Galleria mellonella infection model. Overall, our study demonstrates the potential of tryptanthrin in controlling biofilm formation and virulence of A. baumannii by disrupting different stages of biofilm formation and intercellular signaling communication.

Urban green infrastructure (GI) addresses human social development issues and challenges through urban green space ecosystem services. However, the ecosystem service functions of suburban cropland, especially regulating services and cultural services, have been seriously underestimated. The distribution of green spaces and suburban cropland varies in different regions of China, as well as their potential development methods. This article examines the potential of integrating suburban cropland into urban green infrastructure, offering a perspective on nature-based solutions in China. We divided the suburban cropland in China into three parts: peri‑suburban, mid-suburban, and outer-suburban by the concept of 15-minute living circle based on different travel modes of people. Based on statistical yearbook data, satellite remote sensing images and the fragstats 4.2 programme, a quantitative analysis was conducted on the spatial distribution, landscape pattern and social development of suburban farmland and green space in four cities. Then, the potential for improving the exposure level of suburban cropland after incorporating suburban cropland into urban green infrastructure was quantified and compared. Finally, we explored the potential development of the three kinds of suburban cropland as green infrastructure based on the concept of NbS. We found the spatial pattern of cropland and green space in the mid-suburban is greatly affected by regional geographical conditions, the green exposure level, i.e., green space availability indicators, in Beijing, Shanghai, Guangzhou, and Xi'an increased by 83 %, 300 %, 24 %, and 612 %, respectively, after incorporating suburban cropland into urban green infrastructure. The potential development models for suburban cropland should be based on NbS and China's national conditions: peri‑suburban cropland should be fully utilized for cultural and social functions, the mid-suburban cropland should focus on multifunctional utilization of cropland, and the outer-suburban is prioritized for ecological functions. Our study provides scientific insights for deep exploration of the functions of suburban cropland in China.

Nature-based Solutions (NbS) is a concept aims to address challenges related to human well-being, including human health, socio-economic development, and ecological security on both national and global scales. This concept was proposed against the backdrop of global climate change, ecological crises affecting humanity, and threats to sustainable development and it has been increasingly recognized and applied internationally over the past decade. The principle of NbS is reciprocity between humans and ecosystems, which is completely in line with the goals, systems, practices, and concepts guiding China's construction of ecological civilization. This paper clarifies concepts, evaluation criteria, and comprehensive benefits related to NbS, to trace the connection between NbS and both traditional and contemporary ecological civilization principles in China. By drawing valuable experience from NbS practices in China, it will focus on proposing policy and implementation suggestions to address challenges currently faced in NbS applications in China. This research will promote the research and practice of nature-based solutions in China. Meanwhile, provide novel perspectives and technologies for urban ecological design as well as sustainable development.

Abstract Background Off-targeted distribution of chemotherapeutic drugs causes severe side effects, further leading to poor prognosis and patient compliance. Ligand/receptor-mediated targeted drug delivery can improve drug accumulation in the tumor but it always attenuated by protein corona barriers. Results To address these problems, a radically different strategy is proposed that can leave the off-targeted drugs inactive but activate the tumor-distributed drugs for cancer-targeting therapy in a tumor microenvironment-independent manner. The feasibility and effectiveness of this strategy is demonstrated by developing an ultrasound (US)-activated prodrug-loaded liposome (CPBSN38L) comprising the sonosensitizer chlorin e6 (Ce6)-modified lipids and the prodrug of pinacol boronic ester-conjugated SN38 (PBSN38). Once CPBSN38L is accumulated in the tumor and internalized into the cancer cells, under US irradiation, the sonosensitizer Ce6 rapidly induces extensive production of intracellular reactive oxygen species (ROS), thereby initiating a cascade amplified ROS-responsive activation of PBSN38 to release the active SN38 for inducing cell apoptosis. If some of the injected CPBSN38L is distributed into normal tissues, the inactive PBSN38 exerts no pharmacological activity on normal cells. CPBSN38L exhibited strong anticancer activity in multiple murine tumor models of colon adenocarcinoma and hepatocellular carcinoma with no chemotherapy-induced side effects, compared with the standard first-line anticancer drugs irinotecan and topotecan. Conclusions This study established a side-effect-evitable, universal, and feasible strategy for cancer-targeting therapy. Graphical Abstract

Due to the potential for high energy harvesting capacity, subwavelength scale semiconductor nanostructured arrays are used to address the issue of single-junction thin-film solar cells' limited solar energy harvesting. Along with numerical simulations, an effective and efficient algorithm is crucial to maximizing the optical field modulation and energy trapping capacity of nanostructures. Based on the effective medium theory and the leaky mode resonance, an analytical feedback algorithm is suggested in this study to determine the precise the dimensions of vertically aligned InP stepped nanocylinders (SNCs) for maximum solar energy absorption. For both square and hexagonally arranged two-segment or three-segment InP SNC arrays, the ideal geometrical dimensions were quantitatively estimated for maximum energy harvesting. Densities of short-circuit current Jscs under the AM 1.5G spectrum's illumination as the measurement standard, they were computed for each SNC array. The maximal Jsc of 32.85 mA/cm2 was obtained with square three-segment InP SNC arrays. The optimized SNC arrays for the maximum light absorption are also validated and examined using thorough finite-difference time-domain computational simulations. The algorithm estimated maximum Jsc had tolerances of under 1.8% for all scenarios, which, when compared to simulations, shows that this analytical method offers a practical and efficient means to direct the design of high-performance InP SNC arrays solar cells.

Underground space creation and energy extraction, which induce unloading on rock fractures, commonly occur in various rock engineering projects, and rock engineering projects are subjected to high temperatures with increasing depth. Fluid flow behavior of rock fractures is a critical issue in many subsurface rock engineering projects. Previous studies have extensively considered permeability evolution in rock fractures under loading phase, whereas changes in fracture permeability under unloading phase have not been fully understood. To examine the unloading-induced changes in fracture permeability under different temperatures, we performed water flow-through tests on fractured rock samples subjected to decreasing confining pressures and different temperatures. The experimental results show that the permeability of fracture increases with unloading of confining pressure but decreases with loading-unloading cycles. Temperature may affect fracture permeability when it is higher than a certain threshold. An empirical model of fracture hydraulic aperture including two material parameters of initial normal stiffness and maximum normal closure can well describe the permeability changes in rough rock fracture subjected to loading-unloading cycles and heating. A coupled thermo-mechanical model considering asperity damage is finally used to understand the influences of stress paths and temperatures on fracture permeability.

Summary: The stop signal is produced in response to negative experiences at the food source and inhibits honey bee (Apis mellifera) waggle dancing. Here, we present a protocol for measuring the effects of an inhibitory signal associated with danger on honey bee dopamine levels. We describe steps for observing honey bee colonies, training them with artificial nectar, and simulating hornet attacks. We then detail procedures for recording waggle dancing and stop signals and measuring brain dopamine levels during different treatments.For complete details on the use and execution of this protocol, please refer to Dong et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Currently, there are plenty of histochemical methods to classify pig muscle fibers, which confused the naming and classification of muscle fibers. This study aims to analyze the difference and correlation of 6 different histochemical methods and select the most suitable method for muscle fiber classification at the molecular and histomological levels by in-situ RT-PCR and enzyme histochemical methods. Muscle fiber samples, including psoas (PM), semitendinosus (SM) and trapezius muscle (TM), were collected from Large Spotted (LS), Lantang (LT) and Landrace (LR) pigs at their market-ages (LS at 150 d, LT at 210 d, and LR at 150 d). 6 kinds of histochemical methods combining actomyosin adenosine triphosphatase (AM-ATPase) with succinate dehydrogenase (SDH) enzyme were conducted to differentiate fiber types. 2 types of fibers (I and II) were differentiated by acid 2-fibre (2-AC) or alkaline 2-fibre classification(2-AL), 3 types of fibers (βR, αR and αW) by 3-AC or 3-AL, and 4 types of fibers (I, IIa, IIx and IIb) by 4-AC, or 4-AL. Results showed that AC and AL muscle-fiber classification were consistent in reflecting the characteristics of muscle fibers(P > 0.05), but the color of each muscle fiber type was just opposite. AC methods may be superior to AL methods because of their clear staining background, the sensitivity to staining condition. But there were breed differences and tissue specificity in the optimal preincubation condition. The optimal acid preincubation condition for classifying muscle fibers was pH4.30 for LT, while pH 4.35 for the LS and LR pigs. Meanwhile the optimal acid preincubation condition was pH4.35 for PM, while pH4.40 for TM or SM. For further selection from 2, 3, 4-AC, in-situ RT-PCR was applied to detect the mRNA distribution of myosin heavy chain I (MyHC-I). By combining in-situ PCR with enzyme histochemistry methods, MyHC-I gene and its product – Type I fibrocytes were directly located in cells at both molecular level and morphological level. Compared with the cross-sectional area (CSA) of different muscle fibers (i.e. I, II, βR, αR, αW, IIa, IIx and IIb) identified by enzyme histochemistry, it was found that the CSAs with stronger mRNA expression signal of MyHC-Ⅰ were closer to those of the Type I muscle fiber measured by 4-AC enzyme histochemistry (P > 0.05). Therefore, 4-AC may be considered as the most proper muscle typing method to study muscle fiber typing as well as meat quality. And the combination of in-situ RT-PCR and histochemistry may help better understand porcine muscle fiber characteristics and meat quality in pigs.

In the long-term unattended condition, the continuous operation of bridge safety monitoring micro-system (BSMMS) in mountain areas has the issue of insufficient energy supply. Therefore, a photovoltaic-thermoelectric hybrid power generation system (PV-TEG) is proposed to power the temperature, wind speed, and tilt sensors of BSMMS. The power generation performance and characteristics of PV and TEG are experimentally investigated to find the operation mode to match the bridge monitoring. In addition, the intermittent operation mode of BSMMS is optimized to achieve longer running times. The experimental results show that the output voltage and power generation of the PV-TEG can meet the energy consumption demands of all sensors. TEG power generation is linear with bridge temperature, which can trigger TEG to support the temperature sensor operation. The energy storage battery supports the BSMMS to run for 8.99 days in the mode of running 5 min every 5-min intervals. Optimizing the operation time and interval of the BSMMS to run once in half an hour, it can run continuously for up to 17.97–22.46 days. This work provides a reference for the design of an unattended self-powered energy supply system for a multi-parameter integrated bridge safety monitoring system.

Infections caused by Pseudomonas aeruginosa biofilm significantly endanger human health worldwide. Biofilms are closely associated with antibiotic resistance because biofilms significantly undermine the efficacy of antibiotics. A novel ultrasound-launched targeted nanoparticle was developed to universally destroy biofilm, target bacteria, deliver antibiotics, and efficiently kill bacteria via ultrasonic cavitation and antibacterial sonodynamic therapy. The nanoparticle consisted of poly (lactic-co-glycolic acid) loading ciprofloxacin and perfluoropentane with a bacteria-targeted antibody installed on the nanoparticle for binding to specific bacteria. The nanoparticle exhibited a sensitive response to ultrasound and the rapid liquid-gas phase transition of perfluoropentane resulted in a cavitation effect that destroyed the extracellular polymeric substances of the biofilm and allowed deep penetration of the antibiotics. In addition, ciprofloxacin induced additional reactive oxygen species production under ultrasound stimulation, leading to an enhanced bactericidal effect and potent anti-infective activity in vivo. This study presents an effective strategy to tackle the extracellular polymeric substance barriers for overcoming antibiotic resistance and removing a biofilm.

ObjectiveTo observe the efficacy and safety of pelvic floor magnetic stimulation (PFMS) combined with mirabegron in female patients with refractory overactive bladder (OAB) symptoms.Patients and methodsA total of 160 female patients with refractory OAB symptoms were prospectively randomized into two groups. Eighty cases in the combination group accepted PFMS and mirabegron therapy and 80 cases as control only accepted mirabegron therapy (The clinical trial registry number: ChiCTR2200070171). The lower urinary tract symptoms, OAB questionnaire (OAB-q) health-related quality of life (HRQol), symptom bother score and OABSS between two groups were compared at the 1st, 2nd and 4th week ends.ResultsAll of 160 patients were randomly assigned to two groups, of which 80 patients were included in the combination group and 80 in the mirabegron group. The incidences of LUTS, including urgency, frequent urination, and incontinence episodes, in the 2nd week and the 4th week after combination treatment were significantly lower than those in the mirabegron group (p 0.05). With respect to secondary variables, the OAB-q HRQol score in the combination group was statistically superior in comparison with that in the mirabegron group between the 2nd week and the 4th week (p

Climate change and urbanization have led to an increase in extreme weather and urban heat islands. Green space can help regulate the thermal environment, but previous studies have focused on two-dimensional (2D) indicators, neglecting the intrinsic three-dimensional (3D) characteristics of green space. Therefore, we developed a set of 3D landscape indices to define green space configurations, including characteristic, shape, and compactness, based on landscape ecology and the law of universal gravity, and quantify its benefits for the thermal environment. We collected high-resolution LiDAR point cloud data from Siming Mountain, China, to calculate both 2D and 3D green space landscape patterns and investigate their effects on land surface temperature (LST) using correlation analysis and spatial statistical methods. Our study revealed: (1) All the selected green space landscape indices had a significant negative effect on LST, with a non-linear enhancement when 2D or 3D indices interacted. (2) The 3D compactness index (VCI) could be the most reliable and concise index to explain LST spatial distribution. Adjusting the VCI allowed us to reduce the LST of the study area by up to 3.71 °C in summer and 2.14 °C in winter. However, an overly compact 3D green space above the threshold could lead to higher LST in summer. (3) Terrain had a weaker effect on LST in winter than in summer, and it showed a stronger interaction with the 3D form of green space than with the 2D form. We concluded that the 3D compact form of green space can be utilized as the key factor in maximizing its cooling effect, by taking into account both terrain factors and seasonal variations. Our study can shed light on the scientific planning of green space aiming at optimizing the thermal environment for more sustainable forest and urban habitats.

Rapid urbanization leads to a discrepancy between building operational energy consumption carbon emissions (BECCE) and urban sustainable development. Urban greenspace, which modifies local microclimates and thus BECCE, plays a critical part in reducing BECCE. To improve our scientific understanding and further explore the ecological effect of urban greenspace landscape pattern on BECCE, this study proposed an innovative method for modeling the accessibility to greenspace ecological effect to reduce BECCE. Accessibility was calculated using source–sink landscape theory as the theoretical basis and an improved potential model as the numerical basis. The normalized compactness index was adopted to measure the overall resistance to the ecological process and consider compact urban morphology. A case study of 67 office buildings in China demonstrated the applicability and implications of the model. The study found that i) total area and landscape shape index of greenspace, which represent source accessibility, are both significantly negatively correlated with BECCE; ii) landscape shape index of greenspace, which represents source accessibility and reflects greenspace landscape complexity, figures prominently in building carbon reductions and improves model predictions. The newly developed model can be used to identify optimal arrangements of urban green infrastructure to reduce BECCE under current conditions of intense urban land use, make projections of carbon emissions, and support decision makers in implementing nature-based solutions to achieve carbon emission peak and carbon neutrality goals.

Abstract Objective Stroke is a rare but fatal complication of advanced cancer with Trousseau syndrome, especially as initial symptoms. Here, we report the clinical characteristics, treatment, and prognosis of patients with non-small cell lung cancer (NSCLC) who initially presenting with acute multiple cerebral infarction. Methods The clinical characteristics, imaging, treatment, and oncological outcomes of 10 patients diagnosed with Trousseau syndrome and NSCLC between 2015 and 2021 at Guangdong Sanjiu Brain Hospital were retrospectively collected and analyzed. The clinical course of two typical cases were presented. Results All 10 patients with pathologically confirmed lung adenocarcinoma initially presented with neurological symptoms, including hemiplegic paralysis (7 patients, 70%), dizziness (5 patients, 50%), and unclear speech (3 patients, 30%). The median age was 63.5 years. Eight and two cases were stage III and IV, respectively, at the initial diagnosis. Five patients underwent driver gene testing, revealing three patients with EGFR-sensitive mutations, one patient with ALK fusion, and one patient with wild-type EGFR. All 10 patients received antiplatelet therapy, and six patients subsequently received anti-cancer treatment. The median overall survival of the patients was 8.5 months (95% confidence interval) and 1-year survival rate was 57.1%. Patients who received antitumor treatment, especially those harboring driver gene mutations and received tyrosine kinase inhibitors, had better neurological symptom recovery and superior oncological prognosis (median overall survival, not reached versus 7.4 months, p = 0.038). Conclusion Trousseau syndrome, presenting as multiple cerebral infarctions, is a rare complication of lung adenocarcinoma. Both antiplatelet and antitumor treatment are recommended to achieve better neurological recovery and oncological prognosis in these patients.

BackgroundPublic places are frequently polluted by cigarette smoking, and there is a lack of accurate, real-time, and intelligent monitoring technology to identify smoking behavior. It is necessary to develop a tool to identify cigarette smoking behavior in public places for more efficient control of cigarette smoking and better indoor air quality. ObjectiveTo construct a model for recognizing cigarette smoking behavior based on real-time indoor concentrations of PM2.5 in public places. MethodsReal-time indoor PM2.5 concentrations were measured for at least 7 continuous days in 10 arbitrarily selected places (6 public service providers and and 4 office or other places) from Oct. to Nov. 2022 in Pudong New Area, Shanghai. Indoor nicotine concentrations were monitored with passive samplers simultaneously. Outdoor PM2.5 concentration data were obtained from three municipal environmental monitoring stations which were nearest to each monitoring point during the same period. Mann-Whitney U test was used to compare indoor and outdoor means of PM2.5 concentrations, and Spearman rank correlation was used to analyze indoor PM2.5 and nicotine concentrations. An interactive plot and a random forest model was applied to examine the association between video observation validated indoor smoking behavior and real-time indoor PM2.5 concentrations in an Internet cafe. ResultsThe average indoor PM2.5 concentration in the places providing public services [(97.5±149.3) µg·m−3] was significantly higher than that in office and other places [(19.8±12.2) µg·m−3] (P=0.011). The indoor/outdoor ratio (I/O ratio) of PM2.5 concentration in the public service providers ranged from 1.1 to 19.0. Furthermore, the indoor PM2.5 concentrations in the 10 public places were significantly correlated with the nicotine concentrations (rs=0.969, P

Providing accurate crop yield estimations at large spatial scales and understanding yield losses under extreme climate stress is an urgent challenge for sustaining global food security. While the data-driven deep learning approach has shown great capacity in predicting yield patterns, its capacity to detect and attribute the impacts of climatic extremes on yields remains unknown. In this study, we developed a deep neural network based multi-task learning framework to estimate variations of maize yield at the county level over the US Corn Belt from 2006 to 2018, with a special focus on the extreme yield loss in 2012. We found that our deep learning model hindcasted the yield variations with good accuracy for 2006-2018 (R2 = 0.81) and well reproduced the extreme yield anomalies in 2012 (R2 = 0.79). Further attribution analysis indicated that extreme heat stress was the major cause for yield loss, contributing to 72.5% of the yield loss, followed by anomalies of vapor pressure deficit (17.6%) and precipitation (10.8%). Our deep learning model was also able to estimate the accumulated impact of climatic factors on maize yield and identify that the silking phase was the most critical stage shaping the yield response to extreme climate stress in 2012. Our results provide a new framework of spatio-temporal deep learning to assess and attribute the crop yield response to climate variations in the data rich era.

When asynchronous motors, especially double-fed asynchronous motors in large capacity pump storage are the main loads in the high voltage direct current (HVDC) receiving end power grid, the increase of the equivalent slip of asynchronous motor load may cause transient voltage instability. In order to recover the voltage rapidly in the grid, the emergency reactive power support needs to be quick and accurate. A method for transient voltage stability emergency control by temporarily reducing DC current is proposed, the inverter station is used as emergency reactive power source for the HVDC receiving end power grid. In detail, firstly, aiming at the quantitative calculation of DC current, a nonlinear optimization model with the optimization variable of DC current and the objective of minimizing energy transmission reduction of HVDC is established. Further, in order to achieve fast solution and meet the accuracy requirements, global orthogonal collocation (GOC) is incorporated into the optimization model to transform the differential equations of both objective function and constraints into algebraic equations, thus the optimization is transformed into a nonlinear programming (NLP) problem, by which the emergency control strategy, in specific, the optimal DC current control scheme is obtained. Finally, the modified IEEE 14 benchmark is used to verify the effectiveness and superiority of the proposed strategy.

Gas-fired units provide great flexibility to accommodate the intermittent nature of renewable energy sources and are also considered to be an ideal substitute for retiring coal-fired generations. However, the increasing deployment of gas-fired units deepens interdependency between electric power and natural gas, calling for efficient modeling of the heterogeneous energy flow in the integrated electricity–gas systems (IEGS). Plenty of research works show the necessity of considering gas flow transients in the IEGS, which can be described by a set of partial differential equations (PDEs). To ensure a tractable optimization, the PDEs are often discretized using the finite/infinite difference method, which may result in a large computational scale for achieving good precision. To this end, this paper proposes an efficient model for capturing gas flow transients in the IEGS, which can be taken as the operational constraints in the optimal energy flow model for IEGS coordinated planning, scheduling, and control. For improving the computational efficiency, the PDE-based transient gas flow model is discretized using a space–time orthogonal collocation (OC) method, which provides high-quality results using fewer spatial–temporal discrete points than differential methods. Further, aiming at the difficulty in the determination of the number of space–time collocation points, an adaptive strategy is proposed and embedded in the proposed model utilizing the local fitting errors of state variables related to pipelines. Case studies show the superiority in computational accuracy and efficiency of the proposed model over the existing models based on Wendorff difference and global OC. And an illustrative case based on the modified IEGS benchmark system composed of the IEEE 118-bus power system and the Belgian 20-node gas network exhibits the application value of the proposed model in the optimization and control of the IEGS.

Sn-doped Ga2O3 thin films and metal–semiconductor–metal (MSM) ultraviolet detectors were prepared using the co-sputtering method to enhance their photoelectric performance. The results revealed that Sn doping can effectively change the optical and electrical properties of thin films, greatly improving the photoelectric responsiveness of the devices. Through microstructure testing results, all of the thin film structures were determined to be monoclinic beta phase gallium oxide. At a DC power of 30 W, the thickness of the Sn-doped thin film was 430 nm, the surface roughness of the thin film was 4.94 nm, and the carrier concentration, resistivity, and mobility reached 9.72 × 1018 cm−3, 1.60 × 10−4 Ω·cm, and 45.05 cm3/Vs, respectively. The optical results show that Sn doping clearly decreases the transmission of thin films and that the bandgap can decrease to 3.91 eV. Under 30 W DC power, the photo dark current ratio of the detector can reach 101, time responses of tr = 31 s and tf = 22.83 s were obtained, and the spectral responsivity reached 19.25 A/W.

The three-dimension (3D) inversion of magnetic data is an effective method of recovering underground magnetic susceptibility distributions using magnetic anomaly data. The conventional regularization inversion method has good data fitting; however, its inversion model has the problem of a poor model-fitting ability due to a low depth resolution. The 3D inversion method based on deep learning can effectively improve the model-fitting accuracy, but it is difficult to guarantee the data-fitting accuracy of the inversion results. The loss function of traditional deep learning 3D inversion methods usually adopts the metric of the absolute mean squared error (MSE). In order to improve the accuracy of the data fitting, we added a forward-fitting constraint term (FFit) on the basis of the MSE. Meanwhile, in order to further improve the accuracy of the model fitting, we added the Dice coefficient to the loss function. Finally, we proposed a multi-constraint deep learning 3D inversion method based on UNet++. Compared with the traditional single-constraint deep learning method, the multi-constraint deep learning method has better data-fitting and model-fitting effects. Then, we designed corresponding test models and evaluation metrics to test the effectiveness and feasibility of the method, and applied it to the actual aeromagnetic data of a test area in Suqian City, Jiangsu Province.

With the wide application of laser weapons, the requirements of laser protection technology are becoming more and more strict. Therefore, it is important to find ideal optical limiting (OL) materials to protect human eyes and detectors. In this work, the nonlinear optical responses of gold nanoparticles/porous carbon (Au NPs/PC) nanocomposites prepared by the reduction method were studied using the nanosecond Z-scan technique. Compared with porous carbon, the Au NPs/PC nanocomposites show a lower damage threshold, a bigger optical limiting index and a wider absorption spectrum. The interaction between gold nanoparticles and porous carbon enhances the nonlinear scattering effect of suspended bubbles. These results indicate that Au NPs composites have potential applications in the protection of human eyes and detectors.

Timely and accurate estimation of Above-Ground-Biomass (AGB) in cotton is essential for precise production monitoring. The study was conducted in Shaya County, Aksu Region, Xinjiang, China. It employed an unmanned aerial vehicle (UAV) as a low-altitude monitoring platform to capture multispectral images of the cotton canopy. Subsequently, spectral features and textural features were extracted, and feature selection was conducted using Pearson’s correlation (P), Principal Component Analysis (PCA), Multivariate Stepwise Regression (MSR), and the ReliefF algorithm (RfF), combined with the machine learning algorithm to construct an estimation model of cotton AGB. The results indicate a high consistency between the mean (MEA) and the corresponding spectral bands in textural features with the AGB correlation. Moreover, spectral and textural feature fusion proved to be more stable than models utilizing single spectral features or textural features alone. Both the RfF algorithm and ANN model demonstrated optimization effects on features, and their combination effectively reduced the data redundancy while improving the model performance. The RfF-ANN-AGB model constructed based on the spectral and textural features fusion worked better, and using the features SIPI2, RESR, G_COR, and RE_DIS, exhibited the best performance, achieving a test sets R2 of 0.86, RMSE of 0.23 kg·m−2, MAE of 0.16 kg·m−2, and nRMSE of 0.39. The findings offer a comprehensive modeling strategy for the precise and rapid estimation of cotton AGB.

As urbanization in China progresses, urban spatial development is transitioning from rapid expansion to more intensive and compact growth. This study examined the role of physical geography and environmental factors in shaping the urban spatial development in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Based on the current natural conditions, we selected evaluation indices from topography, hydrogeology, climatic conditions, and natural disasters. These indices were used to create a carrying capacity and suitability evaluation system for development land under natural constraints. Finally, the spatial development potential of the city was finalized by taking into account the current state of the built-up area of the city. Meanwhile, we employed the Optimal Parameters-based Geographical Detector and assessed the impact of 14 natural factors on the spatial development of urban built-up areas. In 2020, the GBA had 52,168.77 km2 of land suitable for construction, of which 34,241.13 km2 was highly suitable (61.29%) and 17,927.64 km2 was moderately suitable (32.09%). At the Bay Area level, 90.15% of the development potential remains untapped; at the city level, Zhaoqing City has the highest potential at 99.56%, while Macao has the lowest at 26.83%. Key factors influencing urban development include silty sand content, annual average relative humidity, and cumulative temperature above 0 °C, with varying impacts across different urban scales. At the Bay Area level, the silty sand content, annual average relative humidity, and cumulative temperature above 0 °C are the main influencing factors on the spatial development of urban built-up areas; at the city level, the main factors are annual average relative humidity and cumulative active temperature above 0 °C. This study reveals the important influence of natural environmental factors on urban spatial development, which is conducive to promoting sustainable development of land resources in GBA.

A method was developed to identify and trace the geographic sources of Erigeron breviscapus using high-resolution mass spectrometry and chemometrics. The representative samples were collected from the geographic area of Honghe Dengzhanhua and other areas in Yunnan province and Guizhou province. The data points could be determined well using the PCA and PLS-DA diagram. A total of 46 characteristic compounds were identified from Honghe Dengzhanhua and within Guizhou province, but 37 compounds were different from Honghe Dengzhanhua and other counties in Yunnan province. Two biomarkers were found from three regions. Their structures were inferred as 8-amino-7-oxononanoic acid and 8-hydroxyquinoline, and they had the same molecular composition. This may suggest that a possible synthesis pathway can be proven in the future.

Green roofs are generally acknowledged as environmentally sustainable roof systems with several environmental, economic, and social benefits, as well as an effective and practical strategy for mitigating the negative consequences of urbanization. In this paper, we used CiteSpace and VOSviewer bibliometric software for visual analysis, citation analysis, co-authorship network, co-citation analysis, and keyword analysis for descriptive statistics on 3986 articles on “green roofs” published in the Web of Science core database since 2000. Descriptive statistics were used for citation analysis, co-authorship network, co-citation analysis, and keyword analysis. According to a review of green roofing-related research literature, (1) Through analysis from three dimensions of country, institution, and author, it was found that China, the United States, and Italy ranked among the top three countries in terms of green roof publication volume; All but three of the top 10 institutions in terms of publications are from China and all are from developed countries; A large-scale collaborative network has not yet formed among authors. (2) Through keyword clustering analysis, it was found that “green roof,” “performance,” and “UHI” were the three keywords with the highest frequency. The research direction of this theme mainly includes five primary themes: rainwater management, urban biodiversity, building energy efficiency, alleviating urban heat islands and improving air quality, sustainable development, and public health. Through keyword hot words, it is found that the frequency of occurrence is relatively high, mainly involving energy conservation, alleviating urban heat islands, biodiversity, and sustainable development. The research on sustainable development, its impact on urban microclimate, and air quality remains a hot topic through keyword highlighting. (3) Co-citation analysis was used to identify the most influential journals, highly cited publications, and authors. (4) Three potential study objectives have been identified: synergistic development with other green infrastructures from an urban planning standpoint, localized research on green roofs, and photovoltaic green roofs.

ObjectiveThe aim of this study was to evaluate the efficacy of the pedicle screw-U rod system in treating double-level lumbar spondylolysis with or without spondylolisthesis.MethodsA retrospective study was conducted. Twenty-six patients were included in this study and followed up at 3, 6, and 12 months. Patients without spondylolisthesis were treated with double U-shaped rods (group I), and patients with spondylolisthesis were treated with a lengthened U-shaped rod (group II). Japanese Orthopedic Association (JOA) scores, Oswestry disability index (ODI) scores, disc range of motion (ROM), intervertebral space height of fixed levels and adjacent levels, and grading the degeneration of adjacent segmental intervertebral discs were evaluated preoperatively and postoperatively.ResultsJOA and ODI scores improved significantly at 3 months both in groups I and II. The average bone grafting healing time was 6.1 ± 3.1 months for group I and 6 ± 2.8 months for group II. The intervertebral space heights of L4/L5 and L5/S1 were improved significantly at the final follow-up (p 0.05). No significant changes of intervertebral space height (L3/L4) and grading of intervertebral disc degeneration were noted before and after surgery (p = 0.141 and 0.484, respectively).ConclusionsThe pedicle screw-U rod system provided advantages of being easy in repairing symptomatic double-level lumbar spondylolysis. This technique improved disabilities of patients, preserved the lumbar spine ROM, and delayed the degeneration of adjacent segments.

The intersection of ecology and exposure science with health concerns has led to a gradual infiltration of these disciplines. Exposure to (urban) natural ecosystems, defined as ecological exposure, has proven to be substantially beneficial to health, providing more effective and preventive measures than dealing with downstream consequences of the disease. Besides, the eco-environment & health field have shifted its paradigm from focusing on negative environmental exposure to exploring the positive health benefits of ecological exposure. However, a unified framework that integrates the nexus of natural ecosystem, ecological exposure, and health is still lacking. To address these challenges, here, we propose a new framework (discipline), exposure ecology (EE), and reviewed relevant studies. We suggest that the domain and scope of EE include subject-reality, object-reality, subject-virtual, and object-virtual dimensions and that all previous studies can be covered within this coordinate frame. We analyze the trends and shortcomings of each domain and explain the pathways of ecological exposure to health, including reduction, restoration, promotion capacity, and potential harm. Furthermore, we discuss the theoretical basis for the formation of the theoretical framework of EE, as well as the EE-derived hypotheses, implications, and connections to other related fields. In short, the EE-driven holistic critical review enhances our understanding of this frontier topic substantially, and it can serve as a unified framework for understanding the nexus of natural ecosystems, ecological exposure, and health and realizing the Sustainable Development Goals (SDGs).

A large-scale series of cyclic triaxial tests were conducted to explore the evolution of the dynamic resilient modulus of silty clay for the heavy-haul railway subgrade. A novel loading sequence for measuring the dynamic resilient modulus was established, which characterized the dynamic stress state of the subgrade induced by the heavy-haul train load. In the experimental investigation, the deviatoric stresses, confining stress, initial moisture content, and compaction degree were considered as variables, and the effects of the aforementioned variables were evaluated quantitatively. The experimental results showed that the dynamic resilient modulus was negatively related to deviatoric stresses and initial moisture content, where the average decreased rates were 14.65% and 27.79% with the increase in deviatoric stresses from 60 kPa to 150 kPa and increase in the initial moisture content from 9.8% to 15.8%, respectively. Furthermore, the dynamic resilient modulus was positively related to confining stress and compaction degree, where the average increased rates were 23.25% and 27.48% with the increase in confining stress from 20 kPa to 60 kPa and increase in compaction degree from 0.91 to 0.95. To provide a better application, the two high-accuracy predicted methods were established through the empirical model and artificial neural network approach including the aforementioned variables. This study can provide useful guidelines for the effective and safe design of the heavy-haul railway subgrade filled with silty clay.

Background The study aims to explore diagnostic value of albumin/fibrinogen ratio (AFR) and C-reactive protein (CRP)/albumin (ALB)/globulin (GLO) ratio (CAGR) for periprosthetic joint infection (PJI). Methods A retrospective analysis was conducted on clinical data collected from 190 patients who had joint replacement surgery in Qilu Hospital of Shandong University (Qingdao), from January 2017 to December 2022. Based on the occurrence of PJI after surgery, patients were divided as an infection group (10 cases) and non-infection group (180 cases). Diagnostic indicators were analyzed, univariate and multivariate logistic regression analyses were further performed to identify factors related to PJI. Sensitivity and specificity of AFR and CAGR, both individually and in combination, were calculated using ROC curves, and their diagnostic performance was compared based on the area under the curve (AUC). Results Levels of CRP, ESR, FIB, GLO, and CAGR were significantly higher in the infection group than in non-infection group (P < 0.05). Levels of ALB and AFR were significantly lower in infection group (P < 0.05). Multivariate logistic regression analysis reviewed that CRP (OR = 3.324), ESR (OR = 2.118), FIB (OR = 3.142), ALB (OR = 0.449), GLO (OR = 1.985), AFR (OR = 0.587), and CAGR (OR = 2.469) were factors influencing PJI (P < 0.05). The AUC for AFR and CAGR in diagnosing PJI were 0.739 and 0.780, while AUC for their combined detection was 0.858. Conclusion Abnormal levels of AFR and CAGR are associated with PJI, and their combined use has certain diagnostic value for PJI.

ABSTRACTMagnitude and diversity of gut microbiota and metabolic systems are critical in shaping human health and diseases, but it remains largely unclear how complex metabolites may selectively regulate gut microbiota and determine health and diseases. Here, we show that failures or compromised effects of anti-TNF-α therapy in inflammatory bowel diseases (IBD) patients were correlated with intestinal dysbacteriosis with more pro-inflammatory bacteria, extensive unresolved inflammation, failed mucosal repairment, and aberrant lipid metabolism, particularly lower levels of palmitoleic acid (POA). Dietary POA repaired gut mucosal barriers, reduced inflammatory cell infiltrations and expressions of TNF-α and IL-6, and improved efficacy of anti-TNF-α therapy in both acute and chronic IBD mouse models. Ex vivo treatment with POA in cultured inflamed colon tissues derived from Crohn’s disease (CD) patients reduced pro-inflammatory signaling/cytokines and conferred appreciable tissue repairment. Mechanistically, POA significantly upregulated the transcriptional signatures of cell division and biosynthetic process of Akkermansia muciniphila, selectively increased the growth and abundance of Akkermansia muciniphila in gut microbiota, and further reprogrammed the composition and structures of gut microbiota. Oral transfer of such POA-reprogrammed, but not control, gut microbiota induced better protection against colitis in anti-TNF-α mAb-treated recipient mice, and co-administration of POA with Akkermansia muciniphila showed significant synergistic protections against colitis in mice. Collectively, this work not only reveals the critical importance of POA as a polyfunctional molecular force to shape the magnitude and diversity of gut microbiota and therefore promote the intestinal homeostasis, but also implicates a new potential therapeutic strategy against intestinal or abenteric inflammatory diseases.

Abstract Thalamo-cortical networks are central to seizures, yet it is unclear how these circuits initiate seizures. We test whether a facial region of the thalamus, the ventral posteromedial nucleus (VPM), is a source of generalized, convulsive motor seizures and if convergent VPM input drives the behavior. To address this question, we devise an in vivo optogenetic mouse model to elicit convulsive motor seizures by driving these inputs and perform single-unit recordings during awake, convulsive seizures to define the local activity of thalamic neurons before, during, and after seizure onset. We find dynamic activity with biphasic properties, raising the possibility that heterogenous activity promotes seizures. Virus tracing identifies cerebellar and cerebral cortical afferents as robust contributors to the seizures. Of these inputs, only microinfusion of lidocaine into the cerebellar nuclei blocks seizure initiation. Our data reveal the VPM as a source of generalized convulsive seizures, with cerebellar input providing critical signals.

Abstract Continuous monitoring for immunosuppressive status, infection and complications are a must for kidney transplantation (KTx) recipients. Traditional monitoring including blood sampling and kidney biopsy, which caused tremendous medical cost and trauma. Therefore, a cheaper and less invasive approach was urgently needed. We thought that a breath test has the potential to become a feasible tool for KTx monitoring. A prospective-specimen collection, retrospective-blinded assessment strategy was used in this study. Exhaled breath samples from 175 KTx recipients were collected in West China Hospital and tested by online ultraviolet photoionization time-of-flight mass spectrometry (UVP-TOF–MS). The classification models based on breath test performed well in classifying normal and abnormal values of creatinine, estimated glomerular filtration rate (eGFR), blood urea nitrogen (BUN) and tacrolimus, with AUC values of 0.889, 0.850, 0.849 and 0.889, respectively. Regression analysis also demonstrated the predictive ability of breath test for clinical creatinine, eGFR, BUN, tacrolimus level, as the predicted values obtained from the regression model correlated well with the clinical true values (p

Abstract Brain metastasis (BM) is an important cause of mortality for cancer patients. Many patients were diagnosed with brain metastases at their first visit who have not received any treatment while a subset of patients did not have distant metastases at the first visit and brain metastases were detected during the course of systemic therapies. The difference in their genomic characterization is unclear. 96 lung adenocarcinoma patients were enrolled in our study. 53 patients (55%) had synchronous metastatic brain tumors. 43 (45%) patients had metachronous brain metastases. We performed 168 panel-targeted gene sequencing cerebrospinal fluid (CSF) and plasma samples from patients to identify genomic features of synchronous brain metastases (SBM) and metachronous brain metastases (MBM). In conclusion, CSF liquid biopsies have a priority in detecting gene alteration. A comprehensive comparison of molecular profiling between SBM and MBM revealed the most frequently altered genes in both groups were EGFR and TP53, but with different exon point mutations. RTK-RAS and TP53 pathways were the most affected pathways.

Abstract There is a growing recognition that responding to climate change necessitates urban adaptation. We sketch a transdisciplinary research effort, arguing that actionable research on urban adaptation needs to recognize the nature of cities as social networks embedded in physical space. Given the pace, scale and socioeconomic outcomes of urbanization in the Global South, the specificities and history of its cities must be central to the study of how well-known agglomeration effects can facilitate adaptation. The proposed effort calls for the co-creation of knowledge involving scientists and stakeholders, especially those historically excluded from the design and implementation of urban development policies.

Abstract Physical reservoirs holding intrinsic nonlinearity, high dimensionality, and memory effects have attracted considerable interest regarding solving complex tasks efficiently. Particularly, spintronic and strain-mediated electronic physical reservoirs are appealing due to their high speed, multi-parameter fusion and low power consumption. Here, we experimentally realize a skyrmion-enhanced strain-mediated physical reservoir in a multiferroic heterostructure of Pt/Co/Gd multilayers on (001)-oriented 0.7PbMg1/3Nb2/3O3−0.3PbTiO3 (PMN-PT). The enhancement is coming from the fusion of magnetic skyrmions and electro resistivity tuned by strain simultaneously. The functionality of the strain-mediated RC system is successfully achieved via a sequential waveform classification task with the recognition rate of 99.3% for the last waveform, and a Mackey-Glass time series prediction task with normalized root mean square error (NRMSE) of 0.2 for a 20-step prediction. Our work lays the foundations for low-power neuromorphic computing systems with magneto-electro-ferroelastic tunability, representing a further step towards developing future strain-mediated spintronic applications.

Cotton Verticillium wilt is a common fungal disease during the growth of cotton, leading to the yellowing of leaves, stem dryness, and root rot, severely affecting the yield and quality of cotton. Current monitoring methods for Verticillium wilt mainly rely on manual inspection and field investigation, which are inefficient and costly, and the methods of applying pesticides in cotton fields are singular, with issues of low pesticide efficiency and uneven application. This study aims to combine UAV remote sensing monitoring of cotton Verticillium wilt with the precision spraying characteristics of agricultural drones, to provide a methodological reference for monitoring and precision application of pesticides for cotton diseases. Taking the cotton fields of Shihezi City, Xinjiang as the research subject, high-resolution multispectral images were collected using drones. Simultaneously, 150 sets of field samples with varying degrees of Verticillium wilt were collected through ground data collection, utilizing data analysis methods such as partial least squares regression (PLSR) and neural network models; additionally, a cotton Verticillium wilt monitoring model based on drone remote sensing images was constructed. The results showed that the estimation accuracy R2 of the PLSR and BP neural network models based on EVI, RENDVI, SAVI, MSAVI, and RDVI vegetation indices were 0.778 and 0.817, respectively, with RMSE of 0.126 and 0.117, respectively. Based on this, an analysis of the condition of the areas to be treated was performed, combining the operational parameters of agricultural drones, resulting in a prescription map for spraying against cotton Verticillium wilt.

With the wide application of intense lasers, the protection of human eyes and detectors from laser damage is becoming more and more strict. In this paper, we study the nonlinear optical limiting (OL) properties of porous carbon with a super large specific surface area (2.9 × 103 m2/g) using the nanosecond Z-scan technique. Compared to the traditional OL material C60, the porous carbon material shows an excellent broadband limiting effect, and the limiting thresholds correspond to 0.11 J/cm2 for 532 nm and 0.25 J/cm2 for 1064 nm pulses, respectively. The nonlinear scattering experiments showed that the OL behavior was mainly attributed to the nonlinear scattering effect, which is caused by the rapid growth and expansion of bubbles in the dispersion induced by laser irradiation, and the scattered light distribution is consistent with the results of Mie’s scattering. These results suggest that porous carbon materials are expected to be applied to the field of laser protection in the future to further protect the human eye and precision optical instruments.

The measurement process of ground shock wave overpressure is influenced by complex field conditions, leading to notable errors in peak measurements. This study introduces a novel pressure measurement model that utilizes the Rankine−Hugoniot relation and an equilateral ternary array. The research delves into examining the influence of three key parameters (array size, shock wave incidence angle, and velocity) on the precision of pressure measurement through detailed simulations. The accuracy is compared with that of a dual-sensor array under the same conditions. Static explosion tests were conducted using bare charges of 0.3 kg and 3 kg TNT to verify the numerical simulation results. The findings indicate that the equilateral ternary array shock wave pressure measurement method demonstrates a strong anti-interference capability. It effectively reduces the peak overpressure error measured directly by the shock wave pressure sensor from 17.73% to 1.25% in the test environment. Furthermore, this method allows for velocity-based measurement of shock wave overpressure peaks in all propagation direction, with a maximum measurement error of 3.59% for shock wave overpressure peaks ≤ 9.08 MPa.

Abstract Insults to the developing cerebellum can cause motor, language, and social deficits. Here, we investigate whether developmental insults to different cerebellar neurons constrain the ability to acquire cerebellar-dependent behaviors. We perturb cerebellar cortical or nuclei neuron function by eliminating glutamatergic neurotransmission during development, and then we measure motor and social behaviors in early postnatal and adult mice. Altering cortical and nuclei neurons impacts postnatal motor control and social vocalizations. Normalizing neurotransmission in cortical neurons but not nuclei neurons restores social behaviors while the motor deficits remain impaired in adults. In contrast, manipulating only a subset of nuclei neurons leaves social behaviors intact but leads to early motor deficits that are restored by adulthood. Our data uncover that glutamatergic neurotransmission from cerebellar cortical and nuclei neurons differentially control the acquisition of motor and social behaviors, and that the brain can compensate for some but not all perturbations to the developing cerebellum.

Abstract The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose experiment, under construction in southeast China, that is designed to determine the neutrino mass ordering and precisely measure neutrino oscillation parameters. Monte Carlo simulation plays an important role for JUNO detector design, detector commissioning, offline data processing, and physics processing. The JUNO experiment has the world’s largest liquid scintillator detector instrumented with many thousands of PMTs. The broad energy range of interest, long lifetime, and the large scale present data processing challenges across all areas. This paper describes the JUNO simulation software, highlighting the challenges of JUNO simulation and solutions to meet these challenges, including such issues as support for time-correlated analysis, event mixing, event correlation and handling the simulation of many millions of optical photons.