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AbstractThis study examines feasibility of incorporating waste hydrated cement paste (WHCP) and luminescent glass (LG) as sand replacements in conventional mortars. Luminescent glass aggregates (LG) were produced by initially mixing luminescent powder with adhesive resin and subsequently adding glass pellets with size smaller than 2 cm. WHCP was produced by mixing cement and water and then cured at room temperature prior to be ground into aggregate with size smaller than 2 mm. Luminescent composite mortars (WLM) were produced by replacing 50–70% of sand by WHCP and LG in which LG replaced 40% of the sand content while WHCP replaced the remaining 10–30%. The feasibility of WLM samples were assessed by their physical and luminescent properties. As results, WLM samples met requirements for constructive mortar such as flowability, drying skrinkage and porosity. At 28d, all WLM samples achieved a strength of around 45 MPa at 28 days, satisfying the strength requirements for constructive mortar. Regarding luminescence properties, all WLM samples exhibited luminescent intensity higher than the threshold of human eyes up to 8h. Luminescent decay curves followed the trend observed in luminescent powders. As such, WLM can be utilized in building projects, particularly for the auxiliary tasks related to road and bridge structures. [ABSTRACT FROM AUTHOR]

Abstract Carbon quantum dots (CQDs) have versatile applications in luminescence, whereas identifying optimal synthesis conditions has been challenging due to numerous synthesis parameters and multiple desired outcomes, creating an enormous search space. In this study, we present a novel multi-objective optimization strategy utilizing a machine learning (ML) algorithm to intelligently guide the hydrothermal synthesis of CQDs. Our closed-loop approach learns from limited and sparse data, greatly reducing the research cycle and surpassing traditional trial-and-error methods. Moreover, it also reveals the intricate links between synthesis parameters and target properties and unifies the objective function to optimize multiple desired properties like full-color photoluminescence (PL) wavelength and high PL quantum yields (PLQY). With only 63 experiments, we achieve the synthesis of full-color fluorescent CQDs with high PLQY exceeding 60% across all colors. Our study represents a significant advancement in ML-guided CQDs synthesis, setting the stage for developing new materials with multiple desired properties.

Summary: Cardiovascular diseases (CVDs) pose a significant global health threat, responsible for a considerable portion of worldwide mortality. Flexible electronics enable continuous, noninvasive, real-time, and portable monitoring, providing an ideal platform for personalized healthcare. Nevertheless, challenges persist in sustaining stable adherence across diverse and intricate skin environments, hindering further advancement toward clinical applications. Strategies such as structural design and chemical modification can significantly enhance the environmental adaptability and monitoring performance of flexible electronics. This review delineates processing techniques, including structural design and chemical modification, to mitigate signal interference from sebaceous skin, motion artifacts from the skin in motion, and infection risks from fragile skin, thereby enabling the accurate monitoring of key cardiovascular indicators in complex physiological environments. Moreover, it delves into the potential for the strategic development and improvement of flexible electronics to ensure their alignment with complex physiological environment requirements, facilitating their transition to clinical applications.

A novel method is proposed for reconstructing high-fall scenes in complex urban environments based on prominence maximization, addressing the limitations of traditional UAV tilt photogrammetry. Initially, UAV’s initial acquisition data is used to generate a Digital Surface Model (DSM). An algorithm is designed to identify local wave peaks and calculate their saliency values, which, combined with linear interpolation, results in a smoother surface elevation model(SDSM). This provides new planning points for the camera’s position, overcoming issues like mismatching shadows in the DSM model. The method was tested in Boston, USA, covering various functional types and traffic scenarios. Results indicate that compared to traditional tilt photogrammetry, UAV tilt photogrammetry based on saliency maximization achieves higher accuracy, effectively capturing local details in the surveyed area while ensuring flight safety. Furthermore, the actual 3D model’s texture information and geometric structure are expressed with high quality.

Antimicrobial resistance is considered to be one of the biggest public health problems, and airborne transmission is an important but under-appreciated pathway for the spread of antibiotic resistance genes (ARGs) in the environment. Previous research has shown pharmaceutical factories to be a major source of ARGs and antibiotic resistant bacteria (ARB) in the surrounding receiving water and soil environments. Pharmaceutical factories are hotspots of antibiotic resistance, but the atmospheric transmission and its environmental risk remain more concerns. Here, we conducted a metagenomic investigation into the airborne microbiome and resistome in three pharmaceutical factories in China. Soil (average: 38.45%) and wastewater (average: 28.53%) were major contributors of airborne resistome. ARGs (vanR/vanS, blaOXA, and CfxA) conferring resistance to critically important clinically used antibiotics were identified in the air samples. The wastewater treatment area had significantly higher relative abundances of ARGs (average: 0.64 copies/16S rRNA). Approximately 28.2% of the detected airborne ARGs were found to be associated with plasmids, and this increased to about 50% in the wastewater treatment area. We have compiled a list of high-risk airborne ARGs found in pharmaceutical factories. Moreover, A total of 1,043 viral operational taxonomic units were identified and linked to 47 family-group taxa. Different CRISPR-Cas immune systems have been identified in bacterial hosts in response to phage infection. Similarly, higher phage abundance (average: 2451.70 PPM) was found in the air of the wastewater treatment area. Our data provide insights into the antibiotic resistance gene profiles and microbiome (bacterial and non-bacterial) in pharmaceutical factories and reveal the potential role of horizontal transfer in the spread of airborne ARGs, with implications for human and animal health.

During the operational process of an axial-flow compressor, the blade structure is simultaneously subjected to both aerodynamic loads and centrifugal loads, posing significant challenges to the safe and reliable operation of the blades. Considering both centrifugal loads and aerodynamic loads comprehensively, a bidirectional CFD-CSD coupling analysis method for blade structure was established. The Navier–Stokes governing equations were utilized to solve the internal flow field of the axial-flow compressor. The conservative interpolation method was utilized to couple and solve the blade’s static equilibrium equation, and the deformation, stress distribution, and prestress modal behavior of compressor blades were mainly analyzed. The research results indicate that the maximum deformation of the blades occurred at the lead edge tip, while stress predominantly concentrated approximately 33% upward from the blade root, exhibiting a radial distribution that gradually decreased. As the rotational speed increased, the maximum deformation of the blades continuously increased. Furthermore, at a constant rotational speed, the maximum deformation of the blade exhibited a trend of first increasing and then decreasing with the increase in mass flow. In contrast, the maximum stress showed a trend of first increasing, then decreasing, and finally increasing again as the rotational speed continuously increased. Centrifugal loads are the primary factor influencing blade stress and natural frequency. During operation, the blades exhibited two resonance points, approximately occurring at 62% and 98% of the design rotational speed.

Chlamydia infections commonly afflict both humans and animals, resulting in significant morbidity and imposing a substantial socioeconomic burden worldwide. As an obligate intracellular pathogen, Chlamydia interacts with other cell organelles to obtain necessary nutrients and establishes an intracellular niche for the development of a biphasic intracellular cycle. Eventually, the host cells undergo lysis or extrusion, releasing infectious elementary bodies and facilitating the spread of infection. This review provides insights into Chlamydia development and host cell responses, summarizing the latest research on the biphasic developmental cycle, nutrient acquisition, intracellular metabolism, host cell fates following Chlamydia invasion, prevalent diseases associated with Chlamydia infection, treatment options, and vaccine prevention strategies. A comprehensive understanding of these mechanisms will contribute to a deeper comprehension of the intricate equilibrium between Chlamydia within host cells and the progression of human disease.

A hybrid enhanced inverse finite element method (E-iFEM) is proposed for real-time intelligent sensing of discontinuous aerospace structures. The method can improve the flight performance of intelligent aircrafts by feeding back the structural shape information to the control system. Initially, the presented algorithm combines rigid kinematics with the classical iFEM to discretize the aerospace structures into elastic parts and rigid parts, which will effectively overcome structural complexity due to fluctuating bending stiffness and a special aerodynamic section. Subsequently, the rigid parts provide geometric constraints for the iFEM in the shape reconstruction method. Meanwhile, utilizing the Fiber Bragg grating (FBG) strain sensor to obtain real-time strain information ensures lightweight and anti-interference of the monitoring system. Next, the strain data and the geometric constraints are processed by the iFEM for monitoring the full-field elastic deformation of the aerospace structures. The whole procedure can be interpreted as a piecewise sensing technology. Overall, the effectiveness and reliability of the proposed method are validated by employing a comprehensive numerical simulation and experiment.

There are few studies on the changes of heart rate of the Asian elephant (Elephas maximus), one of the largest tropical terrestrial mammals, with its self-factors and external environment. By measuring the heart rate of 35 Asian elephants, ranging in age from 4 months to 52 years, using a non-invasive electrocardiogram sensor in their natural habitat at Wild Elephant Valley, Xishuangbanna of China, we found factors that significantly influenced the HR were season, phase of the day, age, body weight, and the interaction between some of the above factors. We also observed that Asian elephants had lower resting heart rate in the morning of hot season than the cold and mild season, and the differences were significant, but the heart rate increased to similar levels in the afternoon regardless of the season. HR also decreased with age in all seasons and phases of the day. However, there was no significant effect of sex. This study reveals the adaptability of Asian elephant to tropical environment, and provides a basic reference for heart rate of Asian elephant under various natural conditions.

Cerebral ischaemiareperfusion injury is an important pathological process in nervous system diseases during which neurons undergo oxygenglucose deprivation and reoxygenation (OGD/R) injury. No study has used epitranscriptomics to explore the characteristics and mechanism of injury. N6methyladenosine (m6A) is the most abundant epitranscriptomic RNA modification. However, little is known about m6A modifications in neurons, especially during OGD/R. m6A RNA immunoprecipitation sequencing (MeRIPseq) and RNA-sequencing data for normal and OGD/R-treated neurons were analysed by bioinformatics. MeRIP quantitative real-time polymerase chain reaction was used to determine the m6A modification levels on specific RNAs. We report the m6A modification profiles of the mRNA and circRNA transcriptomes of normal and OGD/R-treated neurons. Expression analysis revealed that the m6A levels did not affect m6A mRNA or m6A circRNA expression. We found crosstalk between m6A mRNAs and m6A circRNAs and identified three patterns of m6A circRNA production in neurons; thus, distinct OGD/R treatments induced the same genes to generate different m6A circRNAs. Additionally, m6A circRNA biogenesis during distinct OGD/R processes was found to be time specific. These results expand our understanding of m6A modifications in normal and OGD/R-treated neurons, providing a reference to explore epigenetic mechanisms and potential treatments for OGD/R-related diseases.

Abstract Nonthermal irreversible electroporation (NTIRE) is emerging as a promising tissue ablation technique. However, maintaining irreversible electroporation (IRE) electrodes against displacement during strong esophageal spasms remains an obstacle. The present study aimed to evaluate the efficacy and safety of newly designed balloon-type endoscopic IRE catheters. Six pigs were randomly allocated to each catheter group, and each pig was subjected to four ablations at alternating voltages of 1500 V and 2000 V. Esophagogastroscopy was performed during the IRE. The ability of balloon-type catheters to execute complete IRE with 40 pulses was assessed. The success rate was higher for the balloon-type catheter than that for the basket-type (12/12 [100%] vs. 2/12 [16.7%], p

Abstract Acinetobacter is present in the livestock environment, but little is known about their antibiotic resistance and pathogenic species in the farm groundwater. Here we investigated antibiotic resistance of Acinetobacter in the swine farm groundwater (JZPG) and residential groundwater (JZG) of a swine farming village, in comparison to a nearby (3.5 km) non-farming village (WTG) using metagenomic and culture-based approaches. Results showed that the abundance of antibiotic resistome in some JZG and all JZPG (~3.4 copies/16S rRNA gene) was higher than that in WTG (~0.7 copies/16S rRNA gene), indicating the influence of farming activities on both groundwater types. Acinetobacter accounted for ~95.7% of the bacteria in JZG and JZPG, but only ~8.0% in WTG. They were potential hosts of ~95.6% of the resistome in farm affected groundwater, which includes 99 ARG subtypes against 23 antibiotic classes. These ARGs were associated with diverse intrinsic and acquired resistance mechanisms, and the predominant ARGs were tetracyclines and fluoroquinolones resistance genes. Metagenomic binning analysis elucidated that non-baumannii Acinetobacter including A. oleivorans, A. beijerinckii, A. seifertii, A. bereziniae and A. modestus might pose environmental risks because of multidrug resistance, pathogenicity and massive existence in the groundwater. Antibiotic susceptibility tests showed that the isolated strains were resistant to multiple antibiotics including sulfamethoxazole (resistance ratio: 96.2%), levofloxacin (42.5%), gatifloxacin (39.0%), ciprofloxacin (32.6%), tetracycline (32.0%), doxycycline (29.0%) and ampicillin (12.0%) as well as last-resort polymyxin B (31.7%), colistin (24.1%) and tigecycline (4.1%). The findings highlight potential prevalence of groundwater-borne antibiotic-resistant pathogenic Acinetobacter in the livestock environment.

[Objective] The simulation effects and land use prediction accuracy of three land use transition models (LogReg, MLP, and SimWeight) for multi-land change analysis were compared and analyzed in order to provide a reference for land space planning, soil and water conservation, and ecological restoration in the Yunnan-Guizhou Plateau. [Methods] Three models were used to simulate land use changes for Kunming City from 2000 to 2020. Various methods such as ROC curve, AUC coefficient, and kappa coefficient were used to evaluate model performance. [Results] The simulations of change trends for most land use classes by MLP and SimWeight were better than the simulations by LogReg, especially with regard to the change analysis of unused land where the AUC values for MLP and SimWeight were greater than 0.9. The kappa values for LogReg, MLP, and SimWeight were 0.906 6, 0.904 1, and 0.925 3, respectively. The overall prediction results for the three models were similar, and SimWeight was slightly better than the two other models. [Conclusion] For LUCC modeling of Kunming City, SimWeight is recommended when the user desires higher accuracy, MLP is recommended when the user cares more about calculation speed, and LogReg is recommended when the user wants to further analyze the relationship between driving factors and land use changes.

Abstract As a non-thermal ablation method, irreversible electroporation (IRE) has been widely investigated in the treatment of prostate cancer. However, no consensus has been achieved on the optimal parameters of IRE for prostate cancer. Since high voltage is known to carry risks of muscle contraction and patient discomfort, it is crucial to identify the minimum but effective and safer applied voltage to inhibit tumor growth. In this study, the effect of different applied voltages of IRE on prostate cancer was evaluated in BALB/c nude mice. Mathematical simulation and measurement of the actual ablation area revealed a larger ablation area at a higher voltage. In in vivo experiment, except for the three different voltages applied, all groups received identical electrical conditions: pulse number, 180 (20 groups × 9 pulses/group); pulse width, 100 µs; pulse interval, 2 ms; distance between the electrodes, 5 mm; and electrode exposure length, 15 mm. Whilst the tumor volume initially decreased in the 500 V (1000 V/cm) and 700 V (1400 V/cm) groups and subsequently increased, only a transient increase followed by a continuous decrease until the sacrifice was observed in the 900 V (1800 V/cm) group. This result demonstrated a lasting effect of a higher applied voltage on tumor growth inhibition. The histological, immunohistochemical, and western blot findings all confirmed IRE-induced apoptosis in the treatment groups. Taken together, 900 V seemed to be the minimum applied voltage required to reduce tumor growth, though subsequent studies are anticipated to further narrow the voltage intervals and lower the minimum voltage required for tumor inhibition.

Aim • To investigate the overall effect of modified Buqi Yangyin Sanjie decoction combined with levothyroxine sodium tablets on thyroid function and immune function in patients after thyroid cancer surgery. Methods • A total of 104 patients with postoperative thyroid cancer were treated in Wuhan No.1 Hospital between April 2021 and April 2022. The patients were randomly divided into two groups, with 52 patients in each group: the control group, which received levothyroxine sodium tablets, and the study group, which received modified Buqi Yangyin Sanjie decoction in combination with levothyroxine sodium tablets. The thyroid hormones, immune function, and T lymphocyte subsets of both groups were compared before and after treatment, and the efficacy and adverse reactions were analyzed. Results • After treatment, evidently better clinical efficacy of the study group was found than that of the control group (P < .05). Before treatment, there was no statistically significant difference in the levels of FT4, TSH, and FT3 between the two groups (P > .05). After treatment, the levels of FT4 and FT3 in the study group were higher than those in the control group, while the levels of TSH were lower than those in the control group, with a statistically significant difference (P < .05). There was no significant difference in the levels of IgA, IgM, and IgG between the two groups before treatment (P > .05). However, after treatment, the study group had significantly higher levels of all three antibodies than the control group (P < .05). Before treatment, no statistically significant difference was seen in the levels of CD3+, CD4+, and CD8+ between the two groups (P > .05). After treatment, the levels of CD3+ and CD4+ in the study group were higher than those in the control group, while the levels of CD8+ were significantly lower than those in the control group (P < .05). During the treatment, 1 case of mild hyperhidrosis occurred in the study group, and the adverse reaction rate was 1/52. The control group had 2 cases of palpitations, 1 case of hand tremor, 3 cases of hyperhidrosis, and 1 case of weight loss, with an incidence of adverse reactions of 7/52. The incidence of adverse reactions in the study group was lower than that in the control group, with a statistically significant difference (χ² = 4.875, P = .027). Conclusion • The present study highlighted the good outcomes of modified Buqi Yangyin Sanjie decoction combined with levothyroxine sodium tablets that effectively restored thyroid function and improved immune function in postoperative thyroid cancer patients. Hence the approach is available for clinical practice. [ABSTRACT FROM AUTHOR]

Prediction of the maximum size of inclusion in a large weight of steel using data from a small volume steel sample is an important topic for steelmakers. Therefore, the probable maximum sizes (PMS) of inclusions in three steel grades were evaluated by the statistics of extreme values (SEV) and the particle size distributions (PSD) methods based on three-dimensional (3D) investigations of inclusions using the electrolytic extraction (EE) method. The effect of number of measurements and size of unit area on the PMS of inclusions were investigated. The results showed that at least 80 measurements of NMIs should be done in the SEV method, while in the PSD method the number of measurements has little influence when the number of inclusions in the observed areas was large enough. The effect of unit area size on the PMS of inclusions in the SEV method can be ignored for small-sized inclusions (less than 10 μm). The PMS of inclusions determined from the SEV method agreed with that from the PSD method by considering the 95% confidence interval. The SEV method was preferred when predicting the PMS of inclusions because of its simplicity by reducing the cost and labour involved compared to the PSD method.

In this study, we investigated the effect of photobiomodulation (PBM) using near-infrared light on the dentin and periodontal ligament in a beagle model. We utilized a specific PBM device to irradiate NIR light with a wavelength of 810 nm and an energy density of 80.22 mJ/cm2. The device’s settings were optimized for a frequency of 300 Hz and a 30% duty cycle, allowing precise and controlled light exposure. Through a comprehensive analysis involving micro-computed tomography, scanning electron microscopy, and hematoxylin and eosin staining, we demonstrated increased odontoblast activity at the pulp–dentin interface in PBM-treated samples. This increased activity may be postulated to potentially contribute to alleviating dental hypersensitivity through the differentiation of dental pulp stem cells and the promotion of vascular development within the odontoblast layer. Moreover, our observations also indicated an improvement in the strength and integrity of fibrous connective tissue within the periodontal ligament. These findings highlight the potential of PBM with specific parameters applied using NIR as a valuable treatment method for tooth tissue regeneration. It shows particular promise in the treatment of dental diseases associated with dentin and periodontal ligament damage and offers a new perspective in the management of tooth hypersensitivity and other related dental diseases.

Unlike necrosis by thermal ablation, irreversible electroporation (IRE) is known to induce apoptosis by disrupting plasma membrane integrity with electric pulses while preserving the structure of blood vessels and bile ducts in liver tissue without a heat sink effect. This study aimed to investigate thermal damage and histopathological effects in the porcine liver by high-frequency electric pulses (5 kHz) which is much higher than the widely used 1 Hz. The electric field and thermal distributions of 5 kHz electric pulses were compared with those of 1 Hz in numerical simulations. 5 kHz-IRE was applied on pigs under ultrasound imaging to guide the electrode placement. The animals underwent computed tomography (CT) examination immediately and 1 day after IRE. After CT, IRE-treated tissues were taken and analyzed histologically. CT revealed that hepatic veins were intact for 1-day post-IRE. Histopathologically, the structure of the portal vein was intact, but endothelial cells were partially removed. In addition, the hepatic artery structure from which endothelial cells were removed were not damaged, while the bile duct structure and cholangiocytes were intact. The thermal injury was observed only in the vicinity of the electrodes as simulated in silico . 5 kHz-IRE generated high heat due to its short pulse interval, but the thermal damage was limited to the tissue around the electrodes. The histopathological damage caused by 5 kHz-IRE was close to that caused by 1 Hz-IRE. If a short-time treatment is required for reasons such as anesthesia, high-frequency IRE treatment is worth considering. Our observations will contribute to a better understanding of the IRE phenomena and search for advanced therapeutic conditions.

Abstract Glycyrrhiza uralensis Fisch. is an important, perennial medicinal plant whose root microbiome is considered to play an important role in promoting accumulation of effective medicinal ingredients (liquiritin and glycrrhizic acid). Here, we report a comprehensive analysis of the microbial community structural composition and metabolite-plant-microbes association of G. uralensis Fisch. We collected both soil and rhizosphere samples of G. uralensis from different environmental conditions (cultivated and wild) and growth years (grown for one year and three years). Our data revealed higher species diversity in the wild group than in the cultivated group. The core rhizosphere microbiome of G. uralensis comprised 78 genera, including Bacillus, Pseudomonas, Rhizobium, some of which were potential plant beneficial microbes. Our results suggest that the growth of G. uralensis has a correlation with the root-associated microbiota assemblage. Integrated analysis among rhizosphere microbial taxa, plant gene expressions, and liquiritin and glycrrhizic acid accumulation showed that the liquiritin and glycrrhizic acid accumulation exhibited associations with the rhizosphere microbial composition at the genus level. The results provide valuable information to guide cultivation of G. uralensis, and potentially to harness the power of the root-associated microbiota to improve medicinal plant production.

The emergence of vaccines for coronavirus disease 2019 (COVID-19) raises risk of possible adverse events from interaction between the vaccines and facial aesthetic care. A 47-year-old female with no medical comorbidities visited our emergency room due to midface painful swelling after 3 hours following receiving the second dose of the messenger RNA BNT162b2 COVID-19 vaccine. About 14 years ago, she underwent nonsurgical augmentation on the nasojugal groove with a calcium hydroxylapatite dermal filler. We performed incision and drainage under general anesthesia on the next day. During operation, yellowish pus-like materials bulged out. After an operation, we performed a combination therapy with antibiotics and methylprednisolone. Her symptoms improved day by day after surgery, and then a complete recovery was achieved at 3 weeks after the treatment. In conclusion, providers of aesthetic procedures are to be aware of the potential risks of such vaccines for patients who already had or seek to receive dermal filler injections.

Abstract With the rapid development of high-throughput sequencing technology, approaches for assessing biological ingredients in Traditional Chinese Medicine (TCM) preparations have also advanced. Using a multi-barcode sequencing approach, all biological ingredients could be identified from TCM preparations in theory, as long as their DNA is present. The biological ingredients of several classical TCM preparations were analyzed successfully based on this approach in previous studies. However, the universality, sensitivity and reliability of this approach on a diverse set of TCM preparations remain unclear. In this study, we selected four representative TCM preparations, namely Bazhen Yimu Wan, Da Huoluo Wan, Niuhuang Jiangya Wan, and You Gui Wan, for concrete assessment of the multi-barcode sequencing approach. Based on ITS2 and trnL biomarkers, we have successfully detected the prescribed herbal materials (PHMs) in these representative TCM preparations (minimum sensitivity: 77.8%, maximum sensitivity: 100%). The results based on ITS2 have also shown higher reliability than trnL at species level, while their combination could provide higher sensitivity and reliability. The multi-barcode sequencing approach has shown good universality, sensitivity and reliability in decoding these four representative TCM preparations. In the omics big-data era, this work has undoubtedly made one step forward for applying multi-barcode sequencing approach in PHMs analysis of TCM preparation, towards better digitization and modernization of drug quality control.

Multi-modal sensors are the key to ensuring the robust and accurate operation of autonomous driving systems, where LiDAR and cameras are important on-board sensors. However, current fusion methods face challenges due to inconsistent multi-sensor data representations and the misalignment of dynamic scenes. Specifically, current fusion methods either explicitly correlate multi-sensor data features by calibrating parameters, ignoring the feature blurring problems caused by misalignment, or find correlated features between multi-sensor data through global attention, causing rapidly escalating computational costs. On this basis, we propose a transformer-based end-to-end multi-sensor fusion framework named the adaptive fusion transformer (AFTR). The proposed AFTR consists of the adaptive spatial cross-attention (ASCA) mechanism and the spatial temporal self-attention (STSA) mechanism. Specifically, ASCA adaptively associates and interacts with multi-sensor data features in 3D space through learnable local attention, alleviating the problem of the misalignment of geometric information and reducing computational costs, and STSA interacts with cross-temporal information using learnable offsets in deformable attention, mitigating displacements due to dynamic scenes. We show through numerous experiments that the AFTR obtains SOTA performance in the nuScenes 3D object detection task (74.9% NDS and 73.2% mAP) and demonstrates strong robustness to misalignment (only a 0.2% NDS drop with slight noise). At the same time, we demonstrate the effectiveness of the AFTR components through ablation studies. In summary, the proposed AFTR is an accurate, efficient, and robust multi-sensor data fusion framework.

The inverse finite element method (iFEM) based on fiber grating sensors has been demonstrated as a shape sensing method for health monitoring of large and complex engineering structures. However, the existing optimization algorithms cause the local optima and low computational efficiency for high-dimensional strain sensor layout optimization problems of complex antenna truss models. This paper proposes the improved adaptive large-scale cooperative coevolution (IALSCC) algorithm to obtain the strain sensors deployment on iFEM, and the method includes the initialization strategy, adaptive region partitioning strategy, and gbest selection and particle updating strategies, enhancing the reconstruction accuracy of iFEM for antenna truss structure and algorithm efficiency. The strain sensors optimization deployment on the antenna truss model for different postures is achieved, and the numerical results show that the optimization algorithm IALSCC proposed in this paper can well handle the high-dimensional sensor layout optimization problem.

Irreversible electroporation (IRE) is a recognized ablation technique that induces apoptosis via potent electric fields. Nonetheless, the heterogeneity of biological tissues often results in inconsistent treatment outcomes, leaving residual viable cells and leading to potential relapse. To address this, previous strategies incorporated chemical enhancers to IRE, but these faced limitations such as limited tissue diffusion and hyperpigmentation. In this study, we explore the synergistic application of near-infrared (NIR) irradiation with IRE. Using an in vivo rat gastric tissue model, we pre-irradiated samples with NIR at 3 J/cm2 prior to IRE. The combined treatment, termed NIRE, produced a change in tissue impedance of 13.5 Ohm compared to IRE alone, indicating NIR’s potential in modulating tissue electrical properties. Subsequent histopathological and molecular assessments revealed a 1.12-fold increase in apoptosis for NIRE over IRE. Notably, the apoptosis-related proteins BCL and p21 exhibited a 1.24-fold and 1.29-fold overexpression following NIRE treatment, respectively, emphasizing NIRE’s enhanced apoptotic activation. In essence, our findings underscore the augmented therapeutic efficacy of IRE when complemented with NIR, presenting a promising avenue for bolstering treatment outcomes in tissue ablation.

The incidence of Chlamydia trachomatis respiratory infection is increasing, and its pathogenesis is still unclear. Pyroptosis, as a mode of inflammatory cell death, plays a vital role in the occurrence and development of Chlamydia trachomatis respiratory infection. In this study, the potential pyroptosis-related genes involved in Chlamydia trachomatis respiratory infection were identified by constructing a mouse model of C. muridarum infection combined with bioinformatics analysis. Through in-depth analysis of the RNA sequencing data, 13 differentially expressed pyroptosis-related genes were screened, including 1 downregulated gene and 12 upregulated genes. Gene ontology (GO) analysis showed that these genes mainly regulate inflammatory responses and produce IL-1β. Protein–protein interaction network analysis identified eight hub genes of interest: Tnf, Tlr2, Il1b, Nlrp3, Tlr9, Mefv, Zbp1 and Tnfaip3. Through quantitative real-time PCR (qPCR) analysis, we found that the expression of these genes in the lungs of C. muridarum-infected mice was significantly reduced, consistent with the bioinformatics results. At the same time, we detected elevated levels of caspase-3, gasdermin D and gasdermin E proteins in the lungs of C. muridarum-infected mice, demonstrating that Chlamydia trachomatis infection does induce pyroptosis. We then predicted nine miRNAs targeting these hub genes and constructed a key competitive endogenous RNA (ceRNA) network. In summary, we identified six key pyroptosis-related genes involved in Chlamydia trachomatis respiratory infection and constructed a ceRNA network associated with these genes. These findings will improve understanding of the molecular mechanisms underlying pyroptosis in Chlamydia trachomatis respiratory infections.

Population aging is a global trend, and the highest proportion of elderly people in the workforce per unit of population is found in agricultural areas. However, few systematic studies have been conducted on farmer falls in the field of agricultural machinery. This study focuses on the application of classification methods for monitoring devices to detect fall/nonfall movements of farmworkers, where agricultural biomechanical factors are considered in detecting activities of daily living. In this study, we recorded and analyzed original acquisition datasets of signals obtained from two accelerometers and one gyroscope for 40 healthy individuals who performed various falls and activities of daily living (ADLs). Spatial characteristics were used to train the machine-learning classifiers to distinguish between fall and non-fall events. Supervised machine learning experiments evaluated the effectiveness of the proposed approach: the k-nearest neighbors (kNN) and support vector machine (SVM) algorithms achieved roc auc-scores of 0.999 in distinguishing falls and ADLs (binary-class classification). Moreover, an artificial neural network (ANN) classifier showed the highest performance in terms of classification roc auc-scores of 1.0. The evaluation metric demonstrated the highest performance in the analysis and evaluation of the signal obtained from the S2 acceleration sensor with a measurement range of ±16 g. The proposed SVM classifier evaluations showed a 0.988 roc auc-score for sensor tests in multi-class classification, along with the highest performance in terms of the F1-score and Matthews Correlation Coefficient (MCC) over 84% in the multi-class classification model for distinguishing each of ADLs and Fall using ±16 g acceleration sensor.

Vision-based object detection is an essential component of autonomous driving. Because vehicles typically have limited on-board computing resources, a small-sized detection model is required. Simultaneously, high object detection accuracy and real-time inference detection speeds are required to ensure safety while driving. In this paper, an anchor-free lightweight object detector for autonomous driving called ALODAD is proposed. ALODAD incorporates an attention scheme into the lightweight neural network GhostNet and builds an anchor-free detection framework to achieve lower computational costs and provide parameters with high detection accuracy. Specifically, the lightweight backbone neural network integrates a convolutional block attention model that analyzes the valuable features from traffic scene images to generate an accurate bounding box, and then constructs feature pyramids for multi-scale object detection. The proposed method adds an intersection over union (IoU) branch to the decoupled detector to rank the vast number of candidate detections accurately. To increase the data diversity, data augmentation was used during training. Extensive experiments based on benchmarks demonstrate that the proposed method offers improved performance compared to the baseline. The proposed method can achieve an increased detection accuracy while meeting the real-time requirements of autonomous driving. The proposed method was compared with the YOLOv5 and RetinaNet models and 98.7% and 94.5% were obtained for the average precision metrics AP50 and AP75, respectively, on the BCTSDB dataset.

Antimicrobial resistance is recognized as one of the greatest public health concerns. It is becoming an increasingly threat during the COVID-19 pandemic due to increasing usage of antimicrobials, such as antibiotics and disinfectants, in healthcare facilities or public spaces. To explore the characteristics of airborne antibiotic resistome in public transport systems, we assessed distribution and health risks of airborne antibiotic resistome and microbiome in railway stations before and after the pandemic outbreak by culture-independent and culture-dependent metagenomic analysis. Results showed that the diversity of airborne antibiotic resistance genes (ARGs) decreased following the pandemic, while the relative abundance of core ARGs increased. A total of 159 horizontally acquired ARGs, predominantly confering resistance to macrolides and aminoglycosides, were identified in the airborne bacteria and dust samples. Meanwhile, the abundance of horizontally acquired ARGs hosted by pathogens increased during the pandemic. A bloom of clinically important antibiotic (tigecycline and meropenem) resistant bacteria was found following the pandemic outbreak. 251 high-quality metagenome-assembled genomes (MAGs) were recovered from 27 metagenomes, and 86 genera and 125 species were classified. Relative abundance of ARG-carrying MAGs, taxonomically assigned to genus of Bacillus, Pseudomonas, Acinetobacter, and Staphylococcus, was found increased during the pandemic. Bayesian source tracking estimated that human skin and anthropogenic activities were presumptive resistome sources for the public transit air. Moreover, risk assessment based on resistome and microbiome data revealed elevated airborne health risks during the pandemic.

Globally extensive use of antibiotics has accelerated antimicrobial resistance (AMR) in the environment. As one of the biggest antibiotic consumers, livestock farms are hotspots in AMR prevalence, especially those in the atmosphere can transmit over long distances and pose inhalation risks to the public. Here, we collected total suspended particulates in swine farms and ambient air of an intensive swine farming area. Bacterial communities and antibiotic resistomes were analyzed using amplicon and metagenomic sequencing approaches. AMR risks and inhalation exposure to potential human-pathogenic antibiotic-resistant bacteria (HPARB) were subsequently estimated with comparison to the reported hospital samples. The results show that swine farms shaped the airborne bacterial community by increasing abundances, reducing diversities and shifting compositions. Swine feces contributed 77% of bacteria to swine farm air, and about 35% to ambient air. Airborne antibiotic resistomes in swine farms mainly conferred resistance to tetracyclines, aminoglycosides and lincosamides, and over 48% were originated from swine feces. Distinct to the hospital air, Firmicutes were dominant bacteria in swine farming environments with conditional pathogens including Clostridium, Streptococcus and Aerococcus being major hosts of antibiotic resistance genes (ARGs). Therein, genomes of S. alactolyticus carrying (transposase/recombinase-associated) ARGs and virulence factor genes were retrieved from the metagenomes of all swine feces and swine farm air samples, but they were not detected in any hospital air samples. This suggests the indication of S. alactolyticus in swine farming environments with potential hazards to human health. Swine farm air faced higher AMR risks than hospital air and swine feces. The inhalation intake of HPARB by a swine farm worker was about three orders of magnitude higher than a person who works in the hospital. Consequently, this study depicted atmospheric transmission of bacteria and antibiotic resistomes from swine feces to the environment.

Background Colony-stimulating factor 1 receptor (CSF1R), a classic tyrosine kinase receptor, has been identified as a proto-oncogene in multiple cancers. The CSF1/CSF1R axis is essential for the survival and differentiation of M2-phenotype tumor-associated macrophages (M2 TAMs). However, we found here that the CSF1R expression was abnormally down-regulated in colorectal cancer (CRC), and its biological functions and underlying mechanisms have become elusive in CRC progression.Methods The expression of class III receptor tyrosine kinases in CRC and normal intestinal mucosa was accessed using The Cancer Genome Atlas and Gene Expression Omnibus datasets and was further validated by our tested cohort. CSF1R was reconstructed in CRC cells to identify its biological functions in vitro and in vivo. We compared CSF1R expression and methylation differences between CRC cells and macrophages. Furthermore, a co-culture system was used to mimic a competitive mechanism between CSF1R-overexpressed CRC cells and M2-like macrophages. We utilized a CSF1R inhibitor PLX3397 to ablate M2 TAMs and evaluated its efficacy on CRC treatment in animal models.Results We found here that the CSF1R is silenced in CRC, and the reintroduced expression of the receptor in CRC cells can be cleaved by caspases and constrain tumor growth in vitro and in vivo, functioning as a tumor suppressor gene. We further identified CSF1R as a novel dependence receptor, which has the potential to act as either a tumor suppressor gene or an oncogene, depending on its activated state. In CRC tumors, CSF1R expression is enriched in TAMs, and its expression is associated with poor prognosis in patients ith CRC. In a co-culture system, CRC cells expressing CSF1R compete with M2-like macrophages for CSF1R ligands, resulting in a decrease in CSF1R activation and cell proliferation in macrophages. Blocking CSF1R by PLX3397 could deplete M2 TAMs and augments CD8+ T cell infiltration, effectively inhibiting tumor growth and metastasis and improving responses to chemotherapy and immunotherapy.Conclusion Our findings revealed that CSF1R is a novel identified dependence receptor silenced in CRC. The silence abalienates its ligands to stimulate CSF1R expressed on M2 TAMs, which is an appealing therapeutic target for M2 TAM depletion and CRC treatment.

Abstract DNA‐based biological ingredient identification and downstream pharmacology network analysis are commonly used in research for Traditional Chinese Medicine preparations (TCM formulas). Advancements in bioinformatics tools and the accumulation of related data have become driving forces for progress in this field. However, a lack of a platform integrating biological ingredient identification and downstream pharmacology network analysis hinders the deep understanding of TCM. In this study, we developed the TCM‐Suite platform composed of two sub‐databases, Holmes‐Suite and Watson‐Suite, for TCM biological ingredient identification and network pharmacology investigation, respectively, both are among the most complete: In the Holmes‐Suite, we collected and processed six types of marker gene sequences, accounting for 1,251,548 marker gene sequences. In the Watson‐Suite, we curated and integrated a massive number of entries from more than 10 public databases. Importantly, we developed a comprehensive pipeline to integrate TCM biological ingredient identification and downstream network pharmacology research, allowing users to simultaneously identify components of a TCM formula and analyze its potential pharmacology mechanism. Furthermore, we designed search engines and a user‐friendly platform to better search and visualize these rich resources. TCM‐Suite is a comprehensive and holistic platform for TCM‐based drug discovery and repurposing. TCM‐Suite website: http://TCM-Suite.AImicrobiome.cn.