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The neural cell adhesion molecule (NCAM) promotes neural development and regeneration. Whether NCAM mimetic peptides could synergize with bone marrow mesenchymal stem cells (BMSCs) in stroke treatment deserves investigation. We found that the NCAM mimetic peptide P2 promoted BMSC proliferation, migration, and neurotrophic factor expression, protected neurons from oxygen-glucose deprivation through ERK and PI3K/AKT activation and anti-apoptotic mechanisms in vitro. Following middle cerebral artery occlusion (MCAO) in rats, P2 alone or in combination with BMSCs inhibited neuronal apoptosis and induced the phosphorylation of ERK and AKT. P2 combined with BMSCs enhanced neurotrophic factor expression and BMSC proliferation in the ischemic boundary zone. Moreover, combined P2 and BMSC therapy induced translocation of nuclear factor erythroid 2-related factor, upregulated heme oxygenase-1 expression, reduced infarct volume, and increased functional recovery as compared to monotreatments. Treatment with LY294002 (PI3K inhibitor) and PD98059 (ERK inhibitor) decreased the neuroprotective effects of combined P2 and BMSC therapy in MCAO rats. Collectively, P2 is neuroprotective while P2 and BMSCs work synergistically to improve functional outcomes after ischemic stroke, which may be attributed to mechanisms involving enhanced BMSC proliferation and neurotrophic factor release, anti-apoptosis, and PI3K/AKT and ERK pathways activation. [ABSTRACT FROM AUTHOR]

Emotional intelligence (EI) is one's ability to monitor one's own and other's emotions and the use of emotional information to enhance thought and action. Previous behavioral studies have shown that EI is separable into trait EI and ability EI, which are known to have distinct characteristics at the behavioral level. A relevant and unanswered question is whether both forms of EI have a dissociable neural basis. Previous studies have individually explored the neural underpinnings of trait EI and ability EI, but there has been no direct comparison of the neural mechanisms underlying these two types of emotional intelligence. The present study addresses this question by using resting-state fMRI to examine the correlational pattern between the regional amplitude of low-frequency fluctuations (ALFF) of the brain and individuals' trait EI and ability EI scores. We found that trait EI scores were positively correlated with the ALFF in the bilateral superior temporal gyrus, and negatively correlated with the ALFF in the ventral medial prefrontal cortex. In contrast, ability EI scores were positively correlated with the ALFF in the insula. Taken together, these results provide preliminary evidence of dissociable neural substrates between trait EI and ability EI. [ABSTRACT FROM AUTHOR]

Bacterial species within the Acinetobacter baumannii-calcoaceticus (Acb) complex are very similar and are difficult to discriminate. Misidentification of these species in human infection may lead to severe consequences in clinical settings. Therefore, it is important to accurately discriminate these pathogens within the Acb complex. Raman spectroscopy is a simple method that has been widely studied for bacterial identification with high similarities. In this study, we combined surfaced-enhanced Raman spectroscopy (SERS) with a set of machine learning algorithms for identifying species within the Acb complex. According to the results, the support vector machine (SVM) model achieved the best prediction accuracy at 98.33% with a fivefold cross-validation rate of 96.73%. Taken together, this study confirms that the SERS-SVM method provides a convenient way to discriminate between A. baumannii, Acinetobacter pittii, and Acinetobacter nosocomialis in the Acb complex, which shows an application potential for species identification of Acinetobacter baumannii-calcoaceticus complex in clinical settings in near future. [ABSTRACT FROM AUTHOR]

Elaborated molecular architectures, especially carbocyclic, heterocyclic, endocyclic, and polycyclic molecular structures, serve as an important class of organic complexes because they are frequently occurring core structural units in a variety of biologically and pharmacologically relevant natural products, drug molecules, agrochemicals, and functional materials. A main challenge of current synthetic approaches is the development of strategically efficient and selective formation of these compounds from easy‐to‐handle starting materials. The cascade cyclizations of 1,7‐enynes have afforded an indispensable method for accessing molecular complexity and diversity, thus highlighting their potential significance in both academic and industrial communities. In the last decades, tremendous efforts have been devoted to discovering convenient routes to access sophisticated annulation derivatives, and a wide range of powerful and straightforward synthetic strategies have been reported. In this review, the latest achievements in the cascade cyclization reactions of 1,7‐enynes are summarized, which could be separated into three categories: (1) Visible‐light‐induced reactions of 1,7‐enynes; (2) Metal‐free catalyzed reactions of 1,7‐enynes; (3) Transition‐metal‐catalyzed reactions of 1,7‐enynes. [ABSTRACT FROM AUTHOR]

An H‐slot loaded metasurface (MTS) structure has been developed for the purpose of constructing a miniaturized wideband metasurface antenna (MTSA). The MTS is composed of an array of 3 × 3 rectangular small metal patches, each of which is loaded with an H‐slot. The inclusion of the H‐slot significantly lengthens the current path on the small metal patch, resulting in a small antenna size. Since the direction of the effective total current does not change, the radiation performance of the antenna is almost unaffected. To excite the MTS resonance and generate a stable radiation pattern while decreasing the backward radiation, an L‐probe with an intact ground is employed. Characteristic mode analysis (CMA) is applied to reveal the miniaturization mechanism of the MTS and guide modal excitation. The prototype is fabricated and measured within a compact radiation aperture size of 0.35λ0 × 0.29λ0 (λ0 is the free‐space wavelength at the center operating frequency). The measured −10 dB impedance bandwidth is 20.16% (5.22–6.39 GHz), with a peak gain of 6.28 dBi and a front‐to‐back ratio is larger than 20 dB. [ABSTRACT FROM AUTHOR]

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent gastrointestinal malignancies with high mortality worldwide. Emerging evidence indicates that long noncoding RNAs (lncRNAs) are involved in human cancers, including ESCC. However, the detailed mechanisms of lncRNAs in the regulation of ESCC progression remain incompletely understood. LUESCC was upregulated in ESCC tissues compared with adjacent normal tissues, which was associated with gender, deep invasion, lymph node metastasis, and poor prognosis of ESCC patients. LUESCC was mainly localized in the cytoplasm of ESCC cells. Knockdown of LUESCC inhibited cell proliferation, colony formation, migration, and invasion in vitro and suppressed tumor growth in vivo. Mechanistic investigation indicated that LUESCC functions as a ceRNA by sponging miR-6785-5p to enhance NRSN2 expression, which is critical for the malignant behaviors of ESCC. Furthermore, ASO targeting LUESCC substantially suppressed ESCC both in vitro and in vivo. Collectively, these data demonstrate that LUESCC may exerts its oncogenic role by sponging miR-6785-5p to promote NRSN2 expression in ESCC, providing a potential diagnostic marker and therapeutic target for ESCC patients. [ABSTRACT FROM AUTHOR]

Seismic inversion is one of the fundamental techniques for solving geophysics problems. To obtain the elastic parameters or petrophysical parameters, it is necessary to establish a direct or indirect mapping that is usually nonlinear between the observed data and the inversion parameters in seismic inversion. The traditional model-based inversion method, which is calculating complex and expensive, relies on strict physics theories. Neural networks are an excellent artificial intelligence method for establishing nonlinear mapping. Theoretically, any linear and nonlinear functions can be fitted with neural networks. Compared with model-based inversion methods, the inversion efficiency and accuracy can be improved remarkably using neural networks with their powerful ability to discover and extract features from big data. By reviewing the application of fully-connected neural networks, probabilistic neural networks, convolutional neural networks, recurrent neural networks, generative neural networks, and physics-based neural networks in seismic inversion, we provide a comprehensive overview of neural network methods to seismic inversion, including the basic principles of different neural networks, types of seismic inversion, seismic datasets, and the general framework of neural networks for seismic inversion. In addition, the future trends of seismic inversion based on neural networks are also discussed, including the application of image segmentation networks and generative adversarial networks in seismic inversion. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate whether MRI-based T stage (TMRI), [18F]FDG PET/CT-based N (NPET/CT), and M stage (MPET/CT) are superior in NPC patients' prognostic stratification based on long-term survival evidences, and whether TNM staging method involving TMRI + NPET/CT + MPET/CT could improve NPC patients' prognostic stratification. Methods: From April 2007 to December 2013, 1013 consecutive untreated NPC patients with complete imaging data were enrolled. All patients' initial stages were repeated based on (1) the NCCN guideline recommended "TMRI + NMRI + MPET/CT" ("MMP") staging method; (2) the traditional "TMRI + NMRI + Mconventional work-up (CWU)" ("MMC") staging method; (3) the single-step "TPET/CT + NPET/CT + MPET/CT" ("PPP") staging method; or (4) the "TMRI + NPET/CT + MPET/CT" ("MPP") staging method recommended in present research. Survival curve, ROC curve, and net reclassification improvement (NRI) analysis were used to evaluate the prognosis predicting ability of different staging methods. Results: [18F]FDG PET/CT performed worse on T stage (NRI = − 0.174, p < 0.001) but better on N (NRI = 0.135, p = 0.004) and M stage (NRI = 0.126, p = 0.001). The patients whose N stage upgraded by [18F]FDG PET/CT had worse survival (p = 0.011). The "TMRI + NPET/CT + MPET/CT" ("MPP") method performed better on survival prediction when compared with "MMP" (NRI = 0.079, p = 0.007), "MMC" (NRI = 0.190, p < 0.001), or "PPP" method (NRI = 0.107, p < 0.001). The "TMRI + NPET/CT + MPET/CT" ("MPP") method could reclassify patients' TNM stage to a more appropriate stage. The improvement is significant in patients with more than 2.5-years follow-up according to the time-dependent NRI values. Conclusions: The MRI is superior to [18F]FDG PET/CT in T stage, and [18F]FDG PET/CT is superior to CWU in N/M stage. The "TMRI + NPET/CT + MPET/CT" ("MPP") staging method could significantly improve NPC patients' long-term prognostic stratification. Clinical relevance statement: The present research provided long-term follow-up evidence for benefits of MRI and [18F]FDG PET/CT in TNM staging for nasopharyngeal carcinoma, and proposes a new imaging procedure for TNM staging incorporating MRI-based T stage and [18F]FDG PET/CT-based N and M stage, which significantly improves long-term prognostic stratification for patients with NPC. Key Points: • The long-term follow-up evidence of a large-scale cohort was provided to evaluate the advantages of MRI, [18F]FDG PET/CT, and CWU in the TNM staging of nasopharyngeal carcinoma. • A new imaging procedure for TNM stage of nasopharyngeal carcinoma was proposed. [ABSTRACT FROM AUTHOR]

Owing to the progress of transformer-based networks, there have been significant improvements in the performance of vision models in recent years. However, there is further potential for improvement in positional embeddings that play a crucial role in distinguishing information across different positions. Based on the biological mechanisms of human visual pathways, we propose a positional embedding network that adaptively captures position information by modeling the dorsal pathway, which is responsible for spatial perception in human vision. Our proposed double-stream architecture leverages large zero-padding convolutions to learn local positional features and utilizes transformers to learn global features, effectively capturing the interaction between dorsal and ventral pathways. To evaluate the effectiveness of our method, we implemented experiments on various datasets, employing differentiated designs. Our statistical analysis demonstrates that the simple implementation significantly enhances image classification performance, and the observed trends demonstrate its biological plausibility. [ABSTRACT FROM AUTHOR]

Elaborated molecular architectures including complex carbocycles, heterocycles, and polycyclic molecular structures represent an important class of organic compounds because they are ubiquitous structural units in a broad variety of biologically and pharmacologically relevant natural products, medicinal molecules, and functional materials. A major challenge in modern synthetic methodology is the development of strategically efficient and selective construction of these compounds from readily available starting materials. Transition‐metal‐catalyzed transformations involving Heck reaction as the pivotal step have afforded a powerful approach for accessing sophisticated polycyclic skeletons from a set of easy‐to handle starting materials, thus highlighting its potential significance in streamlining the drug discovery process. Over the past few decades, significant effort has been devoted to accessing complex polycyclic derivatives in efficient and versatile routes, and a number of powerful and direct synthetic strategies have been reported. In this review, the latest advances in transition‐metal‐catalyzed transformations involving Heck reaction as the critical step are summarized, which could be divided into six categories: 1) Heck/Sonogashira tandem reaction; 2) Heck/Suzuki tandem reaction; 3) Heck/Heck tandem reaction; 4) Heck/Hiyama tandem reaction; 5) Heck/Cacchi tandem reaction; 6) Heck/C−H bond functionalization tandem reaction. [ABSTRACT FROM AUTHOR]

Radar target echoes undergo fading in the presence of specular reflection, which is adverse to radar detection. To address this problem, this paper proposes a radar detection method that uses a single transmitting antenna and three receiving antennas. The proposed method uses the maximum absolute value of the difference in the radar received signal power among the three receiving antennas as the test statistic. First, the target echo in the presence of specular reflection is analyzed. Then, selection of the required number of radar antennas and the heights at which they must be situated are discussed. Subsequently, analytical expressions of the radar detection probability and the false alarm probability are derived. Finally, simulation results are presented, which show that the proposed method improves radar detection performance in the presence of specular reflection. [ABSTRACT FROM AUTHOR]

Antibiotic tolerance has become an increasingly serious crisis that has seriously threatened global public health. However, little is known about the exogenous factors that can trigger the development of antibiotic tolerance, both in vivo and in vitro. Herein, we found that the addition of citric acid, which is used in many fields, obviously weakened the bactericidal activity of antibiotics against various bacterial pathogens. This mechanistic study shows that citric acid activated the glyoxylate cycle by inhibiting ATP production in bacteria, reduced cell respiration levels, and inhibited the bacterial tricarboxylic acid cycle (TCA cycle). In addition, citric acid reduced the oxidative stress ability of bacteria, which led to an imbalance in the bacterial oxidation–antioxidant system. These effects together induced the bacteria to produce antibiotic tolerance. Surprisingly, the addition of succinic acid and xanthine could reverse the antibiotic tolerance induced by citric acid in vitro and in animal infection models. In conclusion, these findings provide new insights into the potential risks of citric acid usage and the relationship between antibiotic tolerance and bacterial metabolism. [ABSTRACT FROM AUTHOR]

Objective(s): To examine the effect and potential mechanism of electroacupuncture (EA) pretreatment in spatial learning, memory, gut microbiota, and JNK signaling in D-galactose-induced AD-like rats. Materials and Methods: The AD-like rat model was generated by intraperitoneal injection of D-galactose. Morris water maze was used to determine spatial learning and memory ability, Real-time PCR to determine intestinal flora levels, ELISA to determine tryptophan (Trp) and 5-HT levels in the colon and hippocampal tissues, immunofluorescence to determine 5-HT levels in enterochromaffin cells (ECs), and immunoblotting to determine JNK signaling protein levels in hippocampal tissues. Results: Electroacupuncture pretreatment significantly reduced escape latency and prolonged exploration time in the target quadrant, and significantly increased the relative DNA abundance of Lactobacillus and Bifidobacterium. Meanwhile, electroacupuncture pretreatment also reduced colonic 5-HT levels and increased hippocampal 5-HT levels. Moreover, electroacupuncture pretreatment significantly inhibited hippocampal JNK pathway-related protein expression, including 5-HT6R, JNK, p-JUNK, c-JUN, and p-c-Jun. And the combination of GV20 and ST36 was more effective than single acupoints. Conclusion: Electroacupuncture pretreatment improved the learning and memory ability of D-galactose-induced AD-like model rats, changed the gut microbiota composition, and the mechanism may be related to the gut-brain axis and the JNK signaling pathway. In addition, the combination of GV20 and ST36 could further enhance the efficacy. [ABSTRACT FROM AUTHOR]

Objectives: This study focused on developing and validating a nomogram to predict the overall survival (OS) of patients with nasopharyngeal carcinoma (NPC) without distant metastasis based on their clinical characteristics, serum biomarkers, and presence of nasopharyngeal (NP) necrosis. Methods: This study included 9298 patients with NPC. Patients from January 2009 to December 2014 were randomly categorized into the training cohort and validation cohort A. Validation cohort B, whose data were collected from January 2015 to December 2017, was also included. OS was the primary endpoint of this study. Cox regression analysis was used to detect independent risk variables. Decision curve analysis, calibration curve, time-dependent receiver operating characteristic (ROC) curve, and concordance index (C-index) were used to evaluate the performance of the nomogram model. Results: A total of 267 patients developed NP necrosis after the first routine radiotherapy. After radiotherapy, patients with NP necrosis had significantly lower OS than other patients in all three cohorts (p < 0.001). Eleven factors, including NP necrosis, were involved in the nomogram, which had favorable discrimination and calibration with a C-index of 0.768 in the training cohort, 0.749 in validation cohort A, and 0.739 in validation cohort B. The nomogram exhibited a significantly larger area under the ROC curve for predicting OS than the TNM stage and Epstein-Barr virus (EBV) DNA (p < 0.001). Conclusion: Compared with the TNM system and EBV DNA, we established a nomogram model with an accurate prognostic prediction for patients with NPC, which might help with patient management in NPC. Key Points: • This study included 9298 patients with NPC, and 11 factors were involved in the final model. • The nomogram had a significantly higher C-index and area under the ROC curve than the TNM stage and EBV DNA. • We established the first nomogram model for NPC involving the occurrence of NP necrosis, which was valuable for providing individual counseling and clinical assessments. [ABSTRACT FROM AUTHOR]

Objective. Mesenchymal stem cell (MSC) therapy has been explored in Huntington disease (HD) as a potential therapeutic approach; however, a complete synthesis of these results is lacking. We conducted a meta-analysis to evaluate the effects of MSCs on HD. Method. Eligible studies published before November 2022 were screened from Embase, PubMed, Web of Science, Medline, and Cochrane in accordance with PRISMA guidelines. ClinicalTrial.gov and the World Health Organization International Clinical Trials Registry Platform were also searched for registered clinical trials. The outcomes in rodent studies evaluated included morphological changes (striatal volume and ventricular volume), motor function (rotarod test, wire hang test, grip strength test, limb-clasping test, apomorphine-induced rotation test, and neuromuscular electromyography activity), cognition (Morris water maze test), and body weight. Result. The initial search returned 362 records, of which 15 studies incorporating 346 HD rodents were eligible for meta-analysis. Larger striatal and smaller ventricular volumes were observed in MSC-treated animals compared to controls. MSCs transplanted before the occurrence of motor dysfunction rescued the motor incoordination of HD. Among different MSC sources, bone marrow mesenchymal stem cells were the most investigated cells and were effective in improving motor coordination. MSC therapy improved muscle strength, neuromuscular electromyography activity, cortex-related motor function, and striatum-related motor function, while cognition was not changed. The body weight of male HD rodents increased after MSC transplantation, while that of females was not affected. Conclusion. Meta-analysis showed a positive effect of MSCs on HD rodents overall, as reflected in morphological changes, motor coordination, muscle strength, neuromuscular electromyography activity, cortex-related motor function, and striatum-related motor function, while cognition was not changed by MSC therapy. [ABSTRACT FROM AUTHOR]

Synchronizers are the heart for vehicles. The reliability of synchronizer ring in the gearbox affects the operation of the entire systems of vehicles. In this paper, a pre-failure of synchronizer ring made of brass was investigated. Macro and micro analysis, chemical composition analysis, mechanical property test and finite element method were conducted on the synchronizer ring. The analysis results showed that the content of element in the micro area of the outer ring exceeded the standard, which caused the increases of hardness and brittleness of material. The resisting crack propagation ability of material was reduced due to the element segregation. It was concluded that the synchronizer ring was fractured due to the high hardness and brittleness of material, combined with the stress concentration. Finally, countermeasures were proposed to address similar problems. [ABSTRACT FROM AUTHOR]

The analysis of epilepsy electro-encephalography (EEG) signals is of great significance for the diagnosis of epilepsy, which is one of the common neurological diseases of all age groups. With the developments of machine learning, many data-driven models have achieved great performance in EEG signals classification. However, it is difficult to select appropriate hyperparameters for the models to file a specific task. In this paper, an evolutionary algorithm enhanced model is proposed, which optimizes the fixed weights of the reservoir layer of the echo state network (ESN) according to the specific task. As evaluating a feature extractor relies heavily on the classifiers, a new feature distribution evaluation function (FDEF) using the label information of EEG signals is defined as the fitness function, which is an objective way to evaluate the performance of a feature extractor that not only focuses on the degree of dispersion, but also considers the relation amongst triplets. The performance of the proposed method is verified on the Bonn University dataset with an accuracy of 98.16% and on the CHB-MIT dataset with the highest sensitivity of 96.14%. The proposed method outperforms the previous EEG methods, as it can automatically optimize the hyperparameters of ESN to adjust the structure and initial parameters for a specific classification task. Furthermore, the optimization direction by using FDEF as the fitness of MFO no longer relies on the performance of the classifier but on the relative separability amongst classes. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the clinical benefit of salvage allogeneic hematopoietic stem cell transplantation (allo-HSCT) in combination with enhanced myeloablative preconditioning in the treatment of refractory liver and spleen T-cell lymphomas. A retrospective analysis was performed on three patients (with refractory liver and spleen T-cell lymphomas) who have been treated with salvage allo-HSCT combined with enhanced myeloablative preconditioning. One of three patients had a liver biopsy; the other two underwent bone marrow analysis using morphology, immunology, cytogenetics, and molecular biology. All three patients were resistant to chemotherapy and with a high tumor load, so a new total body irradiation/splenic region irradiation/GEM/CLAG/ATG preconditioning regimen was conducted and followed with salvage HSCT. Two patients received haploidentical-donor hematopoietic stem cell transplants, and one received an unrelated full-donor hematopoietic stem cell transplant. The three patients survived disease-free until May 2021. Clinically, hepatosplenic T-cell lymphoma (HSTCL) is rare, with a poor prognosis and chemotherapy response. Based on the present study's encouraging clinical results, salvage allo-HSCT in conjunction with an enhanced myeloablative preconditioning regiment may be an effective and safe treatment for HSTCL. [ABSTRACT FROM AUTHOR]

Objective: We compared the clinical characteristics and survival outcomes after radical radiotherapy between nasopharyngeal carcinoma (NPC) with early and late metastases based on a relatively large cohort, which provides valuable data for the planning of clinical surveillance strategies. Methods: This was a single-center retrospective analysis of 10,566 patients who received radical radiotherapy in China from January 2000 to December 2016. Overall survival was the primary endpoint. Kaplan–Meier survival analysis and log-rank tests were applied to investigate the association between early or late metastasis and the endpoints. The prognostic value of clinicopathological features was identified using univariate and multivariate Cox proportional hazards models. Results: The cutoff value for time to metastasis was based on ROC analysis. A total of 559 (5.3%) patients developed distant metastases, 297 (53.1%) of which developed early metastatic disease, with the rest (46.9%) developing late metastatic disease. The K-M analysis showed that the patients with late metastatic foci had significantly better post-metastatic OS (P = 0.0056). Multivariate analysis indicated that age, liver metastasis, the number of metastatic foci and time to metastasis (P = 0.013) are independent prognostic factors for OS. After analyzing the impact of different treatment methods, we found that local treatment was an independent protective factor for LM, while local treatment was not associated with a survival benefit for EM disease. Conclusions: The time to metastasis after radical radiotherapy affected the prognosis of NPC patients and local treatment was an independent protective factor that could improve the survival of late metastatic NPC patients. [ABSTRACT FROM AUTHOR]

Steroid hormones (SHs) have been widely used over the past few decades as both human and veterinary drugs to prevent or treat infectious diseases and anti-inflammatory benefits in clinical. Unfortunately, their residues in foodstuffs and environmental samples can produce adverse effects on human and animal life such as disrupting the endocrine system. For these reasons, sensitive, simple and efficient methods have been developed for the determination of these compounds in various matrices. This critical review summarized the articles published in the period from 2012 to 2019 and can be used to help researchers to understand development of the sample pretreatment protocols and analytical methods used to detect SHs. The developed extraction and purification techniques used for steroids in different samples, such as cloud point extraction, solid phase extraction based on different novel materials, microextraction methods, QuEChERS and other methods are summarized and discussed. Analytical methods used to quantify these compounds, such as different chromatography methods, electrochemical methods, as well as other methods, are illustrated and compared. We focused on the latest advances in SHs pretreatment, and the application of new technologies in SHs analysis. [ABSTRACT FROM AUTHOR]

Background: The virulent ATP-binding cassette (ABC) importers from Mycobacterium abscessus, the most common native multidrug resistant and emerging opportunistic pathogen in rapidly growing NTM, were explored by comparative genomic study, in view of the fact that the ABC importers of Mycobacterium tuberculosis, responsible for uptaking metals, anions, amino acids, peptides, sugars, and other crucial substances from the host, had been proved to be closely related with the bacillus's virulence, survival in the host macrophages, antibiotic resistance, modulation of host immune system, and so on, although detailed mechanism was unclear. Methods: For virulent ABC importers from M. abscessus predicted by orthology and phylogeny analysis of nucleotide-binding domains (NBDs) of Mycobacterium smegmatis, M. abscessus, and M. tuberculosis, the antibiotic susceptibility of overexpression transformant and knockout mutant was assayed after confirmation by in vitro experiment. Results: Three-domain importers were dominant ones in M. abscessus (60.0%), four-domain ones dominant in M. tuberculosis (87.5%), whereas both types were same in M. smegmatis (41.9%). In the phylogenetic tree, the importers of M. abscessus (53.3%) and M. tuberculosis (62.5%) were mainly distributed in clay A, whereas the clay E was exclusively composed of M. smegmatis NBDs, which hinted possible reprogramming of the transporter system during the pathogen evolution. In clay A, MAB_2178 and others were predicted virulence-associated because of high sequence similarity to M. tuberculosis virulence importers. Conclusions: The importance and complexity of antibiotics resistance mechanisms of MAB_2176-2177-2178 were pointed out by its overexpression enhancing bacterial resistance to ciprofloxacin, clarithromycin, cefoxitin, and sensitivity to amikacin, and knockout having opposite phenotypes. [ABSTRACT FROM AUTHOR]

Purpose: Although treatment planning and individualized dose application for emerging prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) are generally recommended, it is still difficult to implement in practice at the moment. In this study, we aimed to prove the concept of pretherapeutic prediction of dosimetry based on imaging and laboratory measurements before the RLT treatment. Methods: Twenty-three patients with metastatic castration-resistant prostate cancer (mCRPC) treated with 177Lu-PSMA I&T RLT were included retrospectively. They had available pre-therapy 68 Ga-PSMA-HEBD-CC PET/CT and at least 3 planar and 1 SPECT/CT imaging for dosimetry. Overall, 43 cycles of 177Lu-PSMA I&T RLT were applied. Organ-based standard uptake values (SUVs) were obtained from pre-therapy PET/CT scans. Patient dosimetry was calculated for the kidney, liver, spleen, and salivary glands using Hermes Hybrid Dosimetry 4.0 from the planar and SPECT/CT images. Machine learning methods were explored for dose prediction from organ SUVs and laboratory measurements. The uncertainty of these dose predictions was compared with the population-based dosimetry estimates. Mean absolute percentage error (MAPE) was used to assess the prediction uncertainty of estimated dosimetry. Results: An optimal machine learning method achieved a dosimetry prediction MAPE of 15.8 ± 13.2% for the kidney, 29.6% ± 13.7% for the liver, 23.8% ± 13.1% for the salivary glands, and 32.1 ± 31.4% for the spleen. In contrast, the prediction based on literature population mean has significantly larger MAPE (p < 0.01), 25.5 ± 17.3% for the kidney, 139.1% ± 111.5% for the liver, 67.0 ± 58.3% for the salivary glands, and 54.1 ± 215.3% for the spleen. Conclusion: The preliminary results confirmed the feasibility of pretherapeutic estimation of treatment dosimetry and its added value to empirical population-based estimation. The exploration of dose prediction may support the implementation of treatment planning for RLT. [ABSTRACT FROM AUTHOR]

A bis-Schiff base N,N'-ethylene-bis(3-bromosalicylaldimine) (H2L) was prepared from 3-bromosalicylaldehyde and ethane-1,2-diamine. With H2L as ligand, a new copper(II) complex [CuL] (1) and a new cobalt(III) complex [CoL(NCS) (DMF)] (2) were prepared and characterized by physico-chemical methods and single crystal X-ray analysis. X-ray analysis indicates that the Cu atom in complex 1 is in square planar coordination, and the Co atom in complex 2 is in octahedral coordination. The compounds were tested in vitro for their antibacterial activities on Bacillus subtilis, Staphylococcus aureus, Escherichia coli and Pseudomonas fluorescens. Both complexes have effective activities on the bacteria. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated the importance of the downwind development of a rainband in secondary eyewall formation (SEF) in tropical cyclones. However, the details of the transition from rainbands to a secondary eyewall are not well understood. This study examined the convection onset in the early stage of SEF in the numerically simulated Typhoon Soudelor (2015). Results show that the convection onset in the SEF region was associated with the organization of a stationary band complex (SBC), which resulted from the outward propagation of inner rainbands and downwind propagation of secondary rainbands, with convection enhanced in the downwind sector of the SBC. The outward propagation of the inner rainbands involved the mesoscale pressure perturbations-induced unbalanced boundary layer dynamics, which were responsible for the radial outflow above the boundary layer inflow and the related secondary circulation on the inward side of the rainband. In the downwind propagation, secondary rainbands evolved into stratiform precipitation in the downshear-left quadrant, where mesoscale descending inflow continuously occurred and transported low equivalent potential temperature (θe) and dry air downward and downwind, leading to a decrease in low-level θe on the outward side of the rainband. A balanced state of the cold pool dynamics was finally reached in the downwind sector of the SBC between the supergradient-induced vertical wind shear and the low-θe-induced cold pool, resulting in the convection enhancement. Our results strongly suggest that both the unbalanced dynamics and rainband processes were essential in the early stage of SEF. Significance Statement: The purpose of this study is to better understand how spiral rainbands evolve into a stationary rainband complex (SBC), and the physical processes responsible for the convection enhancement in the downwind sector of the SBC. This is important because it is this downwind convective enhancement that leads to the secondary eyewall formation (SEF). Our results provide the details of the transition from rainbands to a secondary eyewall and suggest that both the unbalanced boundary layer dynamics and rainband processes are essential in the early stage of SEF. [ABSTRACT FROM AUTHOR]

Bone marrow aspiration suggested relapse of AML, and the patient achieved I AML1/ETO i negative status after four cycles of chemotherapy (details unknown). Donor lymphocyte infusion (DLI) is the main immunotherapy given for relapse post-HSCT, and although ~60% of relapsed AML patients achieve complete remission after chemotherapy plus DLI, only ~33% achieve long-term leukemia-free survival [[8]]. Acute myeloid leukemia (AML) encompasses a clinically and genetically diverse set of blood cancers caused by abnormally rapid expansion of myeloid progenitor cells in the bone marrow and extramedullary sites leading to disrupted hematopoiesis [[1]]. To our knowledge, this is the first report of avapritinib use for treating relapsed AML post allo-HSCT, and the outcome in this patient supports further investigation of avapritinib therapy for AML. [Extracted from the article]

The VOC emission characteristics of the typical fiber-reinforced plastics (FRPs) industry were studied for an assessment of the impact on the environment. The results showed that the VOC emissions of the typical FRP industry mainly come from grille, sheet, winding, molding, and pultrusion process links, including ketones, aldehydes, alcohols, and benzene series. The benzene series' concentration represented by styrene was much higher than that of other species. The generation potential of ozone and the SOA in the typical production process were evaluated: in terms of ozone impact, the OFP values of the winding process were the highest, accounting for 65.9% of the total contribution. For the component contribution, the OFP contribution of the benzene series represented by styrene was far more than that of other VOC species, and the styrene mainly came from the use of unsaturated resin. In terms of the SOA impact, the pultrusion process contributed the most to the generation of SOA, accounting for 63.9% of the total SOA contribution. In terms of the component contribution, the contribution of SOA mainly came from the benzene series, accounting for nearly 95% of the total contribution of VOCs. Therefore, FRP enterprises should give priority to controlling the emission of the benzene series. [ABSTRACT FROM AUTHOR]

COMplete AMMonia OXidizer (comammox) refers to microorganisms that have the function of oxidizing NH 4 + to NO 3 − alone. The discovery of comammox overturned the two-step theory of nitrification in the past century and triggered many important scientific questions about the nitrogen cycle in nature. This comprehensive review delves into the origin and discovery of comammox, providing a detailed account of its detection primers, clades metabolic variations, and environmental factors. An in-depth analysis of the ecological niche differentiation among ammonia oxidizers was also discussed. The intricate role of comammox in anammox systems and the relationship between comammox and nitrogen compound emissions are also discussed. Finally, the relationship between comammox and anammox is displayed, and the future research direction of comammox is prospected. This review reveals the metabolic characteristics and distribution patterns of comammox in ecosystems, providing new perspectives for understanding nitrogen cycling and microbial ecology. Additionally, it offers insights into the potential application value and prospects of comammox. [Display omitted] • Unraveling the mysteries of comammox: from discovery to ecological significance. • The environmental factors and influencing mechanisms were summarized. • Comammox thriving mostly in freshwater ecosystems. • Is comammox a green engineering process worth further evaluation. • Future focus: evaluating actual contribution and conducting engineering application. [ABSTRACT FROM AUTHOR]

Seismic data acquired in seismic exploration is often contaminated by random noise, and it is necessary to develop effective seismic data denoising methods in seismic signal processing. The current seismic data denoising solutions mainly include traditional model-based methods and supervised deep learning methods. However, the traditional model-based methods cannot achieve satisfactory denoising accuracy, while the supervised deep learning methods have a demand for labeled data, which is difficult to collect in field seismic exploration. To address these difficulties in seismic signal denoising, we proposed an unsupervised deep learning method USDDM (Unsupervised Seismic Denoising Diffusion Model) based on diffusion model. USDDM utilizes the forward process of a diffusion model to assimilate the noise in seismic data, and then the backward process of the diffusion model is used to gradually remove the assimilated noise. Experiments on synthetic and field data are carried out to evaluate the denoising performance of USDDM, model-based methods f-x deconvolution and curvelet, and supervised deep learning methods CAE and DnCNN are used as comparison models. The results of the simulated experiments suggest that the proposed USDDM can effectively reduce the random noise in contaminated seismic data. USDDM can achieve better denoising accuracy compared to f-x deconvolution and curvelet, and the performance between USDDM and supervised deep learning methods is very close. The effectiveness and practicality of USDDM are demonstrated. [ABSTRACT FROM AUTHOR]

Background and objective: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET.23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map.Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach.Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.Methods: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET.23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map.Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach.Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.Results: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET.23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map.Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach.Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.Conclusion: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET.23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map.Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach.Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map. [ABSTRACT FROM AUTHOR]

[Display omitted] • The Segmented modeling method proposed in this study can be used to explore the concentration range of samples for building the model with the best prediction performance. • The Virtual sample generation method based on background difference compensation is proposed, which can effectively reduce the demand of the model for samples. • The segmented model method and Virtual sample generation method can provide some reference ideas for similar applications of near-infrared spectroscopy. The determination of the o-nitrotoluene (o-MNT) content in separation process of mononitrotoluene (MNT) is of interest, since it affects the purity of m-nitrotoluene (m-MNT) and p-nitrotoluene (p-MNT). However, the analytical techniques traditionally used for its content determination are tedious and time consuming. Therefore, we explored the analysis of spectral data based on near-infrared spectroscopy (NIRS) and chemometrics, and extracted the spectral features of the o-MNT based on the interval selection algorithm. The calibration models for the o-MNT content based on samples with different concentration ranges were developed by PLS. Among them, the calibration model based on samples with 0.01–0.5 % concentration range has the best prediction performance. The calibration model was established with the determination coefficient of prediction (R2) of 0.959, root mean squared error of prediction (RMSEP) of 0.011 and ratio of standard deviation of the calibration set to standard error of prediction (RPD) of 4.899 for o-MNT. It is sufficient to meet the fast detection needs of the o-MNT content for process control in chemical industry. In addition, in order to reduce the demand of the model on samples and corresponding reference values, we explored the virtual sample generation method based on background difference compensation. The calibration model based on virtual samples was established with R2 of 0.74, RMSEP of 0.028 and RPD of 1.951. This study shows that the method based on NIRS and chemometrics has strong prediction performance for o-MNT in separation process of MNT, which is a guideline for controlling product purity of m-MNT and p-MNT. And the virtual sample generation method proposed in this study can significantly reduce the sample demand of calibration model. [ABSTRACT FROM AUTHOR]

The determination of the o-nitrotoluene (o-MNT) content in separation process of mononitrotoluene (MNT) is of interest, since it affects the purity of m-nitrotoluene (m-MNT) and p-nitrotoluene (p-MNT). In real-world applications, the calibration model inevitably requires dealing with complex extrapolation problems. Therefore, this study extracted the spectral features of the o-nitrotoluene based on the interval selection algorithm. The linear calibration method (partial least squares (PLS)) and nonlinear calibration methods (support vector machine (SVM), back propagation (BP), random forest (RF), extreme learning machine (ELM)) were used to build the calibration models based on o-nitrotoluene samples in different concentration ranges, and the prediction accuracy and robustness of the calibration model were compared. The results indicate that the effectiveness of different calibration methods is different when going from prediction accuracy to robustness. The prediction accuracy and robustness of RF models are not satisfactory. BP models, which are capable of producing very accurate results in terms of prediction accuracy, are not able to solve extrapolation problems. PLS model has more advantages in model prediction accuracy. ELM has shown the best behavior in terms of robustness of model, but is inferior to PLS in terms of prediction accuracy. [ABSTRACT FROM AUTHOR]

This article proposed a model free based finite time fault‐tolerant control (FTC) method of robot manipulators subject to unknown disturbances, input saturation, and actuator faults. First, an accuracy‐driven integral terminal sliding mode surface (ADITSMS) was constructed, and the finite‐time convergence and the parametric analysis were investigated. Second, based on the proposed ADITSMS, a double‐loop control framework which consists of the position loop and velocity loop was proposed, and the finite time command filtered algorithm was utilized to estimate the derivative of the virtual control law of the position loop, thus a novel finite‐time robust adaptive FTC was proposed. Third, to eliminate the negative effects of the faults and disturbances and implement model free control, the uncertainty and disturbance estimation is designed, and a novel adaptive algorithm is developed to suppress the estimation error whose upper bound or derivative was not required. Meanwhile, an auxiliary system is constructed to deal with the input saturation. The proposed controller possess the superiorities of model free nature and global finite time convergence property. Finally, numerical simulations and comparison studies were conducted to demonstrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

Purpose: A critical bottleneck for the credibility of artificial intelligence (AI) is replicating the results in the diversity of clinical practice. We aimed to develop an AI that can be independently applied to recover high-quality imaging from low-dose scans on different scanners and tracers. Methods: Brain [18F]FDG PET imaging of 237 patients scanned with one scanner was used for the development of AI technology. The developed algorithm was then tested on [18F]FDG PET images of 45 patients scanned with three different scanners, [18F]FET PET images of 18 patients scanned with two different scanners, as well as [18F]Florbetapir images of 10 patients. A conditional generative adversarial network (GAN) was customized for cross-scanner and cross-tracer optimization. Three nuclear medicine physicians independently assessed the utility of the results in a clinical setting. Results: The improvement achieved by AI recovery significantly correlated with the baseline image quality indicated by structural similarity index measurement (SSIM) (r = −0.71, p < 0.05) and normalized dose acquisition (r = −0.60, p < 0.05). Our cross-scanner and cross-tracer AI methodology showed utility based on both physical and clinical image assessment (p < 0.05). Conclusion: The deep learning development for extensible application on unknown scanners and tracers may improve the trustworthiness and clinical acceptability of AI-based dose reduction. [ABSTRACT FROM AUTHOR]

Two new metal-organic compounds, namely [Cu(CrO4)(4,4'-bipy)(H2O)]·n(H2O) (1) together with [Mn(Cr2O7)(bpp)2]n (2) (4,4'-bipy is 4,4'-bipyridine and bpp is 1,3-bis(4-pyridyl)propane), were hydrothermally generated, which were characterized structurally through a series of characterization techniques. Moreover, compounds 1 and 2 have 2.95 eV and 3.02 eV of narrow optical band gap values, and possess outstanding photocatalytic effects for the methylene blue degradation under irradiation of visible light. The application of above compounds in the ophthalmic local anesthesia was examined and the specific mechanism was tested. First of all, the acetylcholine content in the synaptic cleft was measured with enzyme linked immunosorbent assay (ELISA) assay after treated with the CPs. The acetylcholine receptor relative expression on nerve cells was subsequently measured via real time reverse transcription-polymerase chain reaction (RT-PCR) under the treatment of compounds. In the end, the complexes' toxicity was evaluated by Cell Counting Kit-8 (CCK-8) detection. [ABSTRACT FROM AUTHOR]

Polyuria is found in patients with spinal cord injury (SCI). However, the underlying cellular and molecular mechanism is unknown. Here, we show that mice had elevated urine for 7 days after T10 contusion. Using multi-photon confocal microscopy, we performed intra-vital imaging experiments to evaluate water reabsorption in kidney tubules by examining fluorescent intensity in the lumen of the distal tubule from live mice. The data show that SCI significantly reduced the concentrating function of kidney tubules. The reduced water reabsorption appears to be mediated by atrial natriuretic peptide (ANP) because SCI increased the expression levels of both ANP and natriuretic peptide receptor A (NPR-A) in the kidney cortex. Our patch-clamp single-channel recordings from split-open distal tubules show that SCI decreased the activity of the epithelial sodium channel (ENaC). Western blot combined with confocal microscopy data show that the levels of 70 kD γ-ENaC, which is an active isoform because of proteolytic cleavage, were significantly reduced in distal tubule principal cells. An NPR-A inhibitor (A71915) given intravenously eliminated the effects of SCI on ENaC and polyuria. These data together with previous studies suggest that SCI causes polyuria, probably by reducing ENaC activity through elevating ANP and NPR-A. Further investigation of the signal transduction pathways may provide useful information for discovering an efficient drug to treat SCI-induced polyuria. [ABSTRACT FROM AUTHOR]

[Display omitted] • Bone metastasis attenuates efficacy of immune checkpoint inhibitors in NSCLC patients. • Bone metastasis negatively affects clinical outcomes irrespective of PD-L1 expression. • Bone metastatic NSCLC patients display "cold" immune characteristics. This study aimed to assess the clinical characteristics affecting outcomes after immune checkpoint inhibitors (ICI) therapies in non-small cell lung cancer (NSCLC) patients, and the underlying mechanism in tumor immune micro-environment (TIME). A total of 144 patients treated with ICI-based strategies were retrospectively analyzed. Expression of 10 immune antibodies in tumor tissues from other 60 untreated NSCLC patients were sequentially tested using multiplexed immunofluorescence (mIF) staining method. Correlation of clinical characteristics with ICI treatment outcomes and TIME characteristics were analyzed. Multivariate logistic and cox regression indicated that BoM negatively affected disease control rate (OR = 0.32, 95%CI: 0.13–0.82, P = 0.018), progression free survival (HR = 3.44, 95% CI:1.97–6.00, P < 0.001) and overall survival (HR = 3.24, 95% CI:1.62–6.50, P = 0.001), irrespective of programmed death-ligand 1 (PD-L1) expression. BoM patients were with significantly lower PD-L1, and this heterogeneity of TIME was then confirmed in the mIF staining, where 36 (61.0%) patients were clustered into immune-subtype A, with low expression of all the detected immune markers, similar to "cold" tumors, and 23 (39.0%) in cluster B with likely "hot" tumors. More patients in immune-subtype A were non-smokers (63.9% vs. 39.1% P = 0.063), with BoM (66.7% vs. 21.7%, P = 0.001), in stage IV(88.9% vs. 65.2%, P = 0.045), and with adenocarcinoma (91.7% vs. 69.6%, P = 0.037). Multivariate logistic regression indicated that BoM was independently associated with the "cold" immune characteristics (OR = 0.19, 95% CI:0.04–0.84, P = 0.028). Combination therapy with chemotherapy /antiangiogenesis or use of bisphosphonate during ICI treatment significantly improved clinical outcomes in BoM patients. BoM displays adverse impact on clinical outcomes after ICI treatments in NSCLC patients. The "cold" characteristics of TIME may be the underlying mechanism for the attenuated efficacy of ICIs in bone metastatic NSCLC patients. [ABSTRACT FROM AUTHOR]

Non-maximum suppression (NMS) is a post-processing step in most object detection pipelines. It is a greedy algorithm based on the Intersection over Union (IoU) of the bounding boxes to reduce false positives by removing excessive repeated bounding boxes, yet the geometric distributions of bounding boxes are not fully utilized. It is found that the distributions of bounding boxes' center points correspond to the distributions of objects. Local areas with clustered distributions of center points exist objects. Local areas with sparse distributions of center points are considered as the false positives or noises of the detector. In this work, a density-based NMS (DB-NMS) is proposed, which is based on the density distributions of the bounding boxes' center points to evaluate the importance of difference anchors. The proposed DB-NMS is able to obtain better results than the original NMS on the MS-COCO 2017 dataset. Because DB-NMS does not change the network structure, it can be easily integrated into the object detection pipelines to achieve better performances. Object detection pipelines such as Faster R-CNN and RetinaNet can be integrated with the proposed DB-NMS with little degradation on the computational efficiency. [ABSTRACT FROM AUTHOR]

Background: Esophageal squamous cell carcinoma (ESCC) is a common invasive malignancy worldwide with poor clinical outcomes. Increasing amount of long non-coding RNAs (lncRNAs) have been reported to be involved in cancer development. However, lncRNAs that are functional in ESCC and the underlying molecular mechanisms remain largely unknown. Methods: Transcriptomic analysis was performed to identify dysregulated lncRNAs in ESCC tissue samples. The high expression of LINC00680 in ESCC was validated by RT-qPCR, and the oncogenic functions of LINC00680 was investigated by cell proliferation, colony formation, migration and invasion assays in ESCC cells in vitro and xenografts derived from ESCC cells in mice. RNA-seq, competitive endogenous RNA (ceRNA) network analysis, and luciferase reporter assays were carried out to identify LINC00680 target genes and the microRNAs (miRNAs) bound to LINC00680. Antisense oligonucleotides (ASOs) were used for in vivo treatment. Results: Transcriptome profiling revealed that a large number of lncRNAs was dysregulated in ESCC tissues. Notably, LINC00680 was highly expressed, and upregulation of LINC00680 was associated with large tumor size, advanced tumor stage, and poor prognosis. Functionally, knockdown of LINC00680 restrained ESCC cell proliferation, colony formation, migration, and invasion in vitro and inhibited tumor growth in vivo. Mechanistically, LINC00680 was found to act as a ceRNA by sponging miR-423-5p to regulate PAK6 (p21-activated kinase 6) expression in ESCC cells. The cell viability and motility inhibition induced by LINC00680 knockdown was significantly reversed upon PAK6 restoration and miR-423-5p inhibition. Furthermore, ASO targeting LINC00680 substantially suppressed ESCC both in vitro and in vivo. Conclusions: An oncogenic lncRNA, LINC00680, was identified in ESCC, which functions as a ceRNA by sponging miR-423-5p to promote PAK6 expression and ESCC. LINC00680/miR-423-5p/PAK6 axis may serve as promising diagnostic and prognostic biomarkers and therapeutic targets for ESCC. [ABSTRACT FROM AUTHOR]

Metastasis is the primary cause of treatment failure in nasopharyngeal carcinoma (NPC); however, the current tumour-node-metastasis staging system has limitations in predicting distant metastasis and guiding induction chemotherapy (IC) application. Here, we established a transcriptomics-based gene signature to assess the risk of distant metastasis and guide IC in locoregionally advanced NPC. Transcriptome sequencing was performed on NPC biopsy samples from 12 pairs of patients with different metastasis risks. Bioinformatics and qPCR were used to identify differentially expressed genes (DEGs), while univariate and multivariate analyses were used to select prognostic indicators for the gene signature. A signature-based nomogram was established in a training cohort (n = 191) and validated in an external cohort (n = 263). Eleven DEGs were identified between metastatic and non-metastatic NPC. Four of these (AK4, CPAMD8, DDAH1 and CRTR1) were used to create a gene signature that effectively categorised patients into low- and high-risk metastasis groups (training: 91.1 versus 70.4%, p < 0.0001, C-index = 0.752; validation: 88.4 versus 73.9%, p = 0.00057, C-index = 0.741). IC with concurrent chemoradiotherapy (CCRT) improved distant metastasis-free survival in low-risk patients (94.4 versus 85.0%, p = 0.043), whereas patients in the high-risk group did not benefit from IC (72.6 versus 74.9%, p = 0.946). Our transcriptomics-based gene signature was able to reliably predict metastasis in locoregionally advanced NPC and could be used to identify candidates that could benefit from IC + CCRT. • Transcriptomics identified 11 DEGs between metastatic and non-metastatic NPC. • A four-DEG signature categorised patients into low and high-risk metastasis groups. • IC improved distant metastasis-free survival in patients in the low-risk group. • The signature can reliably predict metastasis in locoregionally advanced NPC. • The signature could be used to identify candidates that could benefit from IC + CCRT. [ABSTRACT FROM AUTHOR]

• A total of 531 patients with local recurrence nasopharyngeal carcinoma (lrNPC) were retrospectively reviewed. • We established and validated an integrated prognostic model for lrNPC patients. • Three risk groups were derived from an RPA model that combined rT stage and EBV DNA. • Re-radiotherapy could benefit patients in the low and intermediate-risk subgroups. • No association between re-RT and survival benefit was found in the high-risk. subgroup. In this study, we aimed to establish and validate an integrated prognostic model for locally recurrent nasopharyngeal carcinoma (lrNPC) patients, and evaluate the benefit of re-radiotherapy (re-RT) in patients with different risk levels. In total, 531 patients with lrNPC were retrospectively reviewed in this study, including 271 patients from 2006 to 2012 as the training cohort and 260 patients from 2013 to 2016 as the validation cohort. Overall survival (OS) was the primary endpoint. Multivariate analysis was performed to select the significant prognostic factors (P < 0.05). A prognostic model for OS was derived by recursive partitioning analysis (RPA) combining independent predictors using the algorithm of optimized binary partition. Three independent prognostic factors (age, relapsed T [rT] stage, and Epstein-Barr virus [EBV] DNA) were identified from multivariate analysis. Five prognostic groups were derived from an RPA model that combined rT stage and EBV DNA. After further pair-wise comparisons of survival outcome in each group, three risk groups were generated. We investigated the role of re-RT in different risk groups, and found that re-RT could benefit patients in the low (P < 0.001) and intermediate-risk subgroups (P = 0.017), while no association between re-RT and survival benefit was found in the high-risk subgroup (P = 0.328). The results of risk stratification and re-RT efficacy were verified in the validation cohort. Age, rT stage and EBV DNA were identified as independent predictors for lrNPC. We established an integrated RPA-based prognostic model for OS incorporating rT stage and EBV DNA, which could guide individual treatment for lrNPC. [ABSTRACT FROM AUTHOR]

A dual‐polarized wide‐beam (DPWB) antenna is optimized by a hybrid topology optimization (HTO) method, which combines the scalar isotropic material with penalization and the level set method. The HTO method has high optimization freedom degree, strong topology‐searching ability and fast convergence speed. The initial model of the antenna is designed as a dual‐feeding square microstrip patch antenna with short‐circuit metal walls around the patch. By optimizing the metal patch on the upper side of the model, the DPWB antenna is obtained. The DPWB antenna is symmetric with respect to both ports. When fed to either port, the half‐power beamwidth of the DPWB antenna can reach 166° (−82° ~ 84°) in the E‐plane and 124° (−62° ~ 62°) in the H‐plane. The performance is verified by both simulation and measurement. The DPWB antenna is further applied to a linear phased array, reaching an E‐plane scanning angle range of 160° (−80° ~ 80°) and an H‐plane scanning angle range of 122° (−61° ~ 61°), with the gain fluctuation less than 3 dB and the sidelobe level less than −10.1 dB. [ABSTRACT FROM AUTHOR]

Background: Osteoarthritis (OA) is widely recognized as the most common chronic joint disease accompanied by progressive cartilage and subchondral bone damage. Toddalolactone (TOD), a natural compound extracted from Toddalia asiatica (L.) Lam., has been widely used in the treatment of stroke, rheumatoid arthritis, and oedema. Nevertheless, what TOD acts as in the pathogenesis and progression of OA hasn't been reported. In this investigation, we have aimed to determine how TOD affects OA in vitro and in vivo. Methods: LPS (10 µg/ml) and IL-1β (10 ng/ml) were employed to induce chondrocyte inflammation or RANKL to induce osteoclast differentiation in bone marrow derived macrophages (BMMs). The effects of TOD on chondrocyte inflammation and osteoclast differentiation were evaluated. Anterior cruciate ligament transection (ACLT) was performed to develop an OA animal model and study the effects of TOD. Results: We found that TOD inhibited the expression of inflammatory and catabolic mediators (IL-6, IL-8, TNF-α, MMP2, MMP9, and MMP13) in inflammatory chondrocytes in vitro. Furthermore, TOD was proven to inhibit RANKL-induced-osteoclastogenesis and inhibit the expression of osteoclast marker genes. Our data also confirmed that TOD suppressed the destruction of articular cartilage and osteoclastogenesis via inhibiting the activation of NF-κB and MAPK signalling pathways. In the ACLT mouse model, we found that TOD attenuated cartilage erosion and inhibited bone resorption. Conclusions: These results showed that TOD can be adopted as a potential therapeutic agent for OA. [ABSTRACT FROM AUTHOR]

[Display omitted] • Species and emission concentration of VOCs and odors related to drying mode. • VOCs with high concentration produced from indirect drying process. • Methyl mercaptan and methyl sulfide were main gases causing odor in SDN. • SO 2 was the main odor-causing gaseous pollutant identified from SDS. Emissions of odorous and volatile organic compounds (VOCs) were investigated between two sludge drying methods. A total of 37 chemical compounds were identified and quantified from the off-gases from sludge drying by indirect drying method. The total number of VOCs detected ranged from 3.45 × 10-3 to 4.53 mg/m3, which includes benzene series, volatile organic sulfur, and nitrogenous organic compounds. High emissions were found in the exhaust gas released from drying workshop that used direct drying method. Sulfur dioxide, aromatics, and chlorinated compounds were dominant. Based on the olfactory effect analysis and cancer risk assessment, the main odor-causing gaseous pollutants were methyl mercaptan and methyl sulfide (for indirect sludge drying process) and SO 2 (for direct sludge drying process), while the dominant carcinogens were benzene, carbon tetrachloride, chloroform, and methylene. This study provides new insights into the emission characteristics, olfactory effects, and cancer risks of VOCs and odorous compounds in the exhaust gas from thermal sludge drying processes. [ABSTRACT FROM AUTHOR]

In summary, this case suggests that T-ALL patients with I BRCA 1/2 i mutation or other "BRCAness" phenotype may benefit from PARPi treatment. Although I BRCA i mutations in hematological tumors are uncommon, identification of the BRCAness phenotype may allow more leukemia patients to benefit from PARPi treatment [[15]]. Here, we report the use of PARPi olaparib combined with chemotherapy for the successful treatment of a T-ALL patient carrying a I BRCA1 i mutation who experienced a salvage treatment failure after the recurrence of umbilical cord blood transplantation (UCBT). [Extracted from the article]

In recent years, transformers have become a significant tool in computer vision, revolutionizing fundamental tasks. This paper focuses on the mapping strategy employed during patch embedding, explicitly addressing the transition from a two-dimensional (2D) to a one-dimensional (1D) representation. Existing methods typically divide images into tokens and perform sequential mapping in a top-to-bottom, left-to-right manner. However, these approaches suffer from a notable loss of local information due to the inherent discontinuity in the mapping process. To address these limitations, we propose a novel solution called Geometric-Fractals-based Position Encoding for Vision Transformer (GFPE-ViT). Our method capitalizes on the self-similarity and periodicity observed in fractal curves to enhance the proximity of local information. By integrating the fractalized order into the position encoding, considering the fractal periodicity, we effectively improve the simplicity and efficacy of the mapping strategy. Extensive experimental evaluations highlight the superiority of our approach over existing methods. GFPE-ViT achieves higher accuracy and faster convergence, underscoring its effectiveness in enhancing the mapping strategy for image patching tasks. Results show that GFPE-ViT performs 0.38% higher than the vanilla ViT in terms of top-1 accuracy on CIFAR-100 after pre-training with ImageNet-21k and achieves a 50% reduction in convergence time compared to vanilla ViT on small-scale datasets. By leveraging the self-similarity and periodicity in fractal curves, our proposed method opens new avenues for improving local information proximity in computer vision tasks. [ABSTRACT FROM AUTHOR]

[Display omitted] • Pirfenidone alleviated pancreatic fibrosis and inflammation in a murine model. • Pirfenidone suppressed ECM production in PSCs via TGF-β/Smad pathway. • Pirfenidone inhibited PSCs activation and proliferation via Wnt/β-catenin pathway. • Pirfenidone reduced pro-inflammatory cytokine expression via JAK1/STAT3 pathway. • Pirfenidone restrained the M1 polarization of macrophages via STAT3-related pathway. In the realm of fibroinflammatory conditions, chronic pancreatitis (CP) stands out as a particularly challenging ailment, lacking a dedicated, approved treatment. The potential of Pirfenidone (PFD), a drug originally used for treating idiopathic pulmonary fibrosis (IPF), in addressing CP's fibrotic aspects has sparked new interest. This investigation focused on the role of PFD in diminishing fibrosis and immune response in CP, using a mouse model induced by caerulein. The research extended to in vitro studies examining the influence of PFD on pancreatic stellate cells' (PSCs) behavior and the polarization of macrophages into M1 and M2 types. Advanced techniques like RNA sequencing and comprehensive data analyses were employed to decode the molecular interactions of PFD with PSCs. Supplementary experiments using techniques such as quantitative real-time PCR, western blotting, and immunofluorescence were also implemented. Results showed a notable reduction in pancreatic damage in PFD-treated mice, manifested through decreased acinar cell atrophy, lower collagen deposition, and a reduction in macrophage presence. Further investigation revealed PFD's capacity to hinder PSCs' migration, growth, and activation, alongside a reduction in the production and secretion of extracellular matrix proteins. This effect is primarily achieved by interfering with signaling pathways such as TGF-β/Smad, Wnt/β-catenin, and JAK/STAT. Additionally, PFD selectively hampers M1 macrophage polarization through the STAT3 pathway, without impacting M2 polarization. These outcomes highlight PFD's dual mechanism in moderating PSC activity and M1 macrophage polarization, positioning it as a promising candidate for CP therapy. [ABSTRACT FROM AUTHOR]

Understanding the sexual dimorphism in diseases is essential to investigate the pathogenesis of some chronic diseases (e.g., autoimmune diseases, etc). The gut microbiota has been found to show a notable impact on the pathology of several chronic diseases in recent years. Intriguingly, the composition of the gut microbiota varies between sexes. Here, we reviewed 'facts and fiction' regarding sexual dimorphism in chronic diseases and sexual dimorphism in the gut microbiota respectively. The association and causative relationship between them aiming to elucidate the pathological mechanisms of sexual dimorphism in chronic diseases were further explored. The development of gender-special food products based on the sexual dimorphism in the gut microbiota were recommended, which would be beneficial to facilitating the personalized treatment. • This review firstly focused on the underlying sexual dimorphism in gut microbiota and chronic diseases. • This review would increase the understanding of sexual dimorphism in chronic diseases. • This review provides a new perspective to study the mechanism of sexual dimorphism in chronic diseases. [ABSTRACT FROM AUTHOR]

Background: Cognitive deficit is mainly clinical characteristic of Alzheimer's disease (AD). Recent reports showed adiponectin and its analogues could reverse cognitive impairments, lower amyloid-β protein (Aβ) deposition, and exert anti-inflammatory effects in different APP/PS1 AD model mice mainly exhibiting amyloid plaque pathology. However, the potential in vivo electrophysiological mechanism of adiponectin protecting against cognitive deficits in AD and the neuroprotective effects of adiponectin on 3xTg-AD mice including both plaque and tangle pathology are still unclear.Objective: To observe the effects of adiponectin treatment on cognitive deficits in 3xTg-AD mice, investigate its potential in vivo electrophysiological mechanism, and testify its anti-inflammatory effects.Methods: Barnes maze test, Morris water maze test, and fear conditioning test were used to evaluate the memory-ameliorating effects of adiponectin on 3xTg-AD mice. In vivo hippocampal electrophysiological recording was used to observe the change of basic synaptic transmission, long-term potentiation, and long-term depression. Immunohistochemistry staining and western blot were used to observe the activation of microglia and astroglia, and the expression levels of proinflammatory factors and anti-inflammtory factor IL-10.Results: Adiponectin treatment could alleviate spatial memory and conditioned fear memory deficits observed in 3xTg-AD mice, improve in vivo LTP depression and LTD facilitation, inhibit overactivation of microglia and astroglia, decrease the expression of proinflammatory factors NF- κB and IL-1β, and increase the expression level of IL-10 in the hippocampus of 3xTg-AD mice.Conclusion: Adiponectin could ameliorate cognitive deficits in 3xTg-AD mice through improving in vivo synaptic plasticity impairments and alleviating neuroinflammation in the hippocampus of 3xTg-AD mice. [ABSTRACT FROM AUTHOR]

Objective: Ketamine is an anesthetic that induces neurotoxicity when administered at high doses. In this work, we explored the protective effects of lipoxin A4 methyl ester (LXA4 ME) against ketamine-induced neurotoxicity and the underlying protective mechanism in pheochromocytoma (PC12) cells. Methods: PC12 cells were treated with 50 μM of ketamine and different LXA4 ME concentrations of LXA4 ME (5–50 nM) for 24 h, and their viability, apoptosis, and oxidative status were assessed. Results: Quantitative real-time polymerase chain reaction experiments showed that ketamine downregulated miR-22 expression and upregulated Bcl-2-associated athanogene 5 (BAG5) in PC12 cells in a concentration-dependent manner. LXA4 ME induced the opposite effects, thus attenuating ketamine-induced neurotoxicity. Further in vitro assays showed that miR-22 directly targeted BAG5, thus promoting cell viability by suppressing cell apoptosis and oxidative stress. Under expression miR-22 or upregulation of BAG5 antagonized the effects of LXA4 ME. Conclusion: LXA4 ME can protect PC12 cells from ketamine-induced neurotoxicity by activating the miR-22/BAG5 signaling pathway. Thus, LXA4 ME can be used as a protective drug against ketamine-induced neural damage. [ABSTRACT FROM AUTHOR]