Clinically Applicable Pan-Origin Cancer Detection for Lymph Nodes via AI-Based Pathology.

Lymph node metastasis is one of the most common ways of tumour metastasis. The presence or absence of lymph node involvement influences the cancer's stage, therapy, and prognosis. The integration of artificial intelligence systems in the histopathological diagnosis of lymph nodes after surgery is urgent. Here, we propose a pan-origin lymph node cancer metastasis detection system. The system is trained by over 700 whole slide images and is composed of two deep learning models to locate the lymph nodes and detect cancers. It achieved a area under the receiver operating characteristic (ROC) curve (AUC) of 0.958, with a 95.2% sensitivity and 72.2% specificity, on 1,402 whole-slide images (WSIs) from 49 organs at the National Cancer Center, China. Moreover, we demonstrated that the system could perform robustly with 1,051 WSIs from 52 organs from another medical center, with a AUC of 0.925. Our research represents a step forward in a pan-origin lymph node metastasis detection system, providing accurate pathological guidance by reducing the probability of missed diagnosis in routine clinical practice.

Metabolism of Inulin via Difructose Anhydride I Pathway in Microbacterium flavum.

Difructose anhydride I (DFA-I) can be produced from inulin, with DFA-I-forming inulin fructotransferase (IFTase-I). However, the metabolism of inulin through DFA-I remains unclear. To clarify this pathway, several genes of enzymes related to this pathway in the genome of Microbacterium flavum DSM 18909 were synthesized, and the corresponding enzymes were encoded, purified, and investigated in vitro. After inulin is decomposed to DFA-I by IFTase-I, DFA-I is hydrolyzed to inulobiose by DFA-I hydrolase. Inulobiose is then hydrolyzed by ß-fructofuranosidase to form fructose. Finally, fructose enters glycolysis through fructokinase. A ß-fructofuranosidase (MfFFase1) clears the byproducts (sucrose and fructo-oligosaccharides), which might be partially hydrolyzed by fructan ß-(2,1)-fructosidase/1-exohydrolase and another fructofuranosidase (MfFFase2). Exploring the DFA-I pathway of inulin and well-studied enzymes in vitro extends our basic scientific knowledge of the energy-providing way of inulin, thereby paving the way for further investigations in vivo and offering a reference for further nutritional investigation of inulin and DFA-I in the future.

Innovative application of a novel and thermostable inulin fructotransferase from Arthrobacter sp. ISL-85 to fructan inulin in burdock root to improve nutrition.

Inulin fructotransferase converts prebiotic polysaccharide inulin to difructose anhydride III, known for its numerous beneficial physiological effects. While previous studies focused on using inulin extracts under optimal conditions, this study delves into the enzyme's behavior when dealing with more complex food materials, inulin-rich burdock root, which possesses greater nutritional value but may influence the enzymatic reaction. An inulin fructotransferase from Arthrobacter sp. ISL-85 was identified and characterized, which has the highest activity of 783 U mg-1 at pH 6.5 and 65 °C and remains stable even up to 80 °C. When applied to inulin-rich burdock root (pH 4.7) at 80 °C for 2 h, the enzyme yielded 4.1 g of difructose anhydride III, concurrently increasing fructo-oligosaccharides. This study demonstrates the potential of this enzyme as a valuable tool for efficiently processing inulin within whole food materials under high temperatures. Such an approach could pave the way for enhancing nutrition and promoting health benefits.

Innovative application of a novel di-D-fructofuranose 1,2':2,3'-dianhydride hydrolase (DFA-IIIase) from Duffyella gerundensis A4 to burdock root to improve nutrition.

Burdock is native to Europe and Asia and rich in many functional ingredients, including biomacromolecule polysaccharide inulin. The prebiotic fructan inulin can provide energy to organisms via several pathways. One pathway is that inulin fructotransferase (IFTase) first converts inulin to III-type difructose anhydride (DFA-III), which has many beneficial physiological functions. Then, DFA-III is hydrolyzed to inulobiose, which is a Fn-type prebiotic fructo-oligosaccharide, via difructose anhydride hydrolase (DFA-IIIase). However, there has been no study on the application of IFTase or DFA-IIIase to process burdock to increase DFA-III or inulobiose. Moreover, only five DFA-IIIases have been reported to date and all of them are from the Arthrobacter genus. Whether other microbes except for the Arthrobacter genus can utilize DFA-III through DFA-IIIase is unknown. In this work, a DFA-IIIase from Duffyella gerundensis A4 (D. gerundensis A4), abbreviated as DgDFA-IIIase, was identified and characterized in detail. DgDFA-IIIase is a bifunctional enzyme, that is, besides its hydrolytic ability to DFA-III, it has the same catalytic ability as IFTase to inulin. The enzyme was applied to the burdock root aiming at inulin and DFA-III, and inulobiose was produced with an increase in Gn-type fructo-oligosaccharide. The work verifies that microorganisms of the non-Arthrobacter genus also have the potential ability to use DFA-III by DFA-IIIase, and DFA-IIIase is feasible to increase functional substances of burdock root instead of IFTase and endo-inulinase, which paves the way for the production of functional food utilizing the polysaccharide inulin to improve nutrition and health.

Variational Quantum Algorithm Applied to Collision Avoidance of Unmanned Aerial Vehicles.

Mission planning for multiple unmanned aerial vehicles (UAVs) is a complex problem that is expected to be solved by quantum computing. With the increasing application of UAVs, the demand for efficient conflict management strategies to ensure airspace safety continues to increase. In the era of noisy intermediate-scale quantum (NISQ) devices, variational quantum algorithms (VQA) for optimizing parameterized quantum circuits with the help of classical optimizers are currently one of the most promising strategies to gain quantum advantage. In this paper, we propose a mathematical model for the UAV collision avoidance problem that maps the collision avoidance problem to a quadratic unconstrained binary optimization (QUBO) problem. The problem is formulated as an Ising Hamiltonian, then the ground state is solved using two kinds of VQAs: the variational quantum eigensolver (VQE) and the quantum approximate optimization algorithm (QAOA). We select conditional value-at-risk (CVaR) to further promote the performance of our model. Four examples are given to validate that with our method the probability of obtaining a feasible solution can exceed 90% based on appropriate parameters, and our method can enhance the efficiency of a UAVs' collision avoidance model.

Clinical-grade endometrial cancer detection system via whole-slide images using deep learning.

The accurate pathological diagnosis of endometrial cancer (EC) improves the curative effect and reduces the mortality rate. Deep learning has demonstrated expert-level performance in pathological diagnosis of a variety of organ systems using whole-slide images (WSIs). It is urgent to build the deep learning system for endometrial cancer detection using WSIs. The deep learning model was trained and validated using a dataset of 601 WSIs from PUPH. The model performance was tested on three independent datasets containing a total of 1,190 WSIs. For the retrospective test, we evaluated the model performance on 581 WSIs from PUPH. In the prospective study, 317 consecutive WSIs from PUPH were collected from April 2022 to May 2022. To further evaluate the generalizability of the model, 292 WSIs were gathered from PLAHG as part of the external test set. The predictions were thoroughly analyzed by expert pathologists. The model achieved an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of 0.928, 0.924, and 0.801, respectively, on 1,190 WSIs in classifying EC and non-EC. On the retrospective dataset from PUPH/PLAGH, the model achieved an AUC, sensitivity, and specificity of 0.948/0.971, 0.928/0.947, and 0.80/0.938, respectively. On the prospective dataset, the AUC, sensitivity, and specificity were, in order, 0.933, 0.934, and 0.837. Falsely predicted results were analyzed to further improve the pathologists' confidence in the model. The deep learning model achieved a high degree of accuracy in identifying EC using WSIs. By pre-screening the suspicious EC regions, it would serve as an assisted diagnostic tool to improve working efficiency for pathologists.

[Analysis of volatile oil components of different species of Curcumae Rhizoma based on GC-MS and chemometrics].

The volatile oil of Curcumae Rhizoma has many active components,which are the key to the quality of Curcumae Rhizoma. Exploring the difference between volatile oil of different kinds of Curcumae Rhizoma facilitates the quality control and rational application of resources. In this study,GC-MS was applied to realize online qualitative and semi-quantitative analysis of the chemical composition spectrum of volatile oil from Curcuma wenyujin( CW),C. phaeocaulis( CP),and C. kwangsiensis( CK). Forty components were identified and their fingerprints were compared and evaluated. Hierarchical cluster analysis( HCA),principal component analysis( PCA),and orthogonal partial least squares discrimination analysis( OPLS-DA) were adopted to analyze the overall and outlier data. The results showed that the whole data could be divided into three kinds according to each analysis mode,and the volatile components of Curcumae Rhizoma vary greatly among species. PCA explored the difference between outliers and the mean value of the group and found that some volatile oils from CW may be greatly affected by the origin. By OPLS-DA,the samples from Zhejiang were able to gather,but those from Guizhou remained isolated,indicating the influence of growing environment on Curcumae Rhizoma metabolites. Based on VIP results combined with the heat map,characteristic volatile oil components of Curcumae Rhizoma from different varieties were screened out: curdione and linalool for CW; 2-undecanone for CP; humulene,γ-selinene,and zederone for CK. The GCMS method established in this study describes Curcumae Rhizoma samples comprehensively and accurately,and the characteristic components screened based on chemometrics can be used to distinguish Curcumae Rhizoma from different varieties and give them unique pharmacodynamic significance,which is fast,convenient,stable,and reliable and supports the rational application of Curcu-mae Rhizoma resources. It is found that the region of origin has great influence on CW,which is worthy of further study.

Potential of a Quorum Quenching Bacteria Isolate Ochrobactrum intermedium D-2 Against Soft Rot Pathogen Pectobacterium carotovorum subsp. carotovorum.

Quorum quenching (QQ) is a promising strategy for preventing and controlling quorum sensing (QS)-mediated bacterial infections. It interferes with QS by the inhibition of signal synthesis, the detection of enzyme-catalyzed degradation, and the modification of signals. N-Acyl homoserine lactones (AHLs) represent a family of widely conserved QS signals involved in the regulation of virulence factor production in many Gram-negative bacterial pathogens. In this study, AHL-degrading bacterial strains were isolated, and the most efficient one was evaluated for its potential against QS-mediated pathogens. Results showed that an AHL-degrading bacteria Ochrobactrum intermedium D-2 effectively attenuated maceration produced by the pathogen Pectobacterium carotovorum subsp. carotovorum (Pcc) on radish and potato slices. Strain D-2 exhibited a superior AHL degradation activity and efficiently degraded various AHLs, including N-hexanoyl-L-homoserine lactone (C6HSL), N-(3-oxohexanoyl)-L-homoserine lactone (3OC6HSL), N-(3-oxooctanoyl)-L-homoserine lactone (3OC8HSL), and N-(3-oxododecanoyl)-L-homoserine lactone (3OC12HSL). Analysis of the degradation products of AHL by gas chromatography-mass spectrometry led to the identification of N-cyclohexyl-propanamide and propanamide as the main intermediate products, suggesting that AHL was degraded by hydrolysis. Annotation and analysis of the whole genome sequence of strain D-2 revealed the presence of an AHL-lactonase, termed AidF. Moreover, the application of strain D-2 was able to substantially reduce the disease severity caused by Pcc on host plants. These results reveal the biochemical basis of a highly efficient AHL-degrading bacterial isolate and present the potential to attenuate Pcc virulence through QQ.

Comparison of Hospital Anxiety and Depression Scale (HADS) and Zung Self-Rating Anxiety/Depression Scale (SAS/SDS) in Evaluating Anxiety and Depression in Patients with Psoriatic Arthritis.

BACKGROUND: This study aimed to compare the Hospital Anxiety and Depression Scale (HADS) and the Zung Self-Rating Anxiety/Depression Scale (SAS/SDS) in evaluating anxiety and depression in psoriatic arthritis (PsA) patients. METHODS: A total of 70 PsA patients were enrolled. Demographic and clinical characteristics were collected after enrollment. HADS-A and SAS were used to evaluate the anxiety of PsA patients, while HADS-D and SDS were used to evaluate the depression of PsA patients. RESULTS: Similar results were observed in detecting the rate of anxiety by HADS-A and SAS (27.1 vs. 21.4%, p = 0.424), and there was no difference in classifying the severity of anxiety by HADS-A and SAS (p = 0.347). The Spearman test also disclosed that HADS-A score was positively associated with SAS score (p <0.001). The rates of depression were similar by HADS-D and SDS (27.1 vs. 40.0%; p = 0.108). However, different results were observed in grading the severity of anxiety by HADS-D and SDS (p = 0.009), and no correlation was observed between HADS-D and SDS scores (p = 0.138). The consumption of time for HADS assessment was shorter than that for SAS/SDS assessment (p < 0.001). In addition, a positive correlation of HADS-A score with patients' global assessment (PGA) (p = 0.022) and fatigue scores (p = 0.028) was discovered, and HADS-D score was positively associated with PGA score (p = 0.019). SAS or SDS score presented less correlation with clinical features of PsA patients, which illuminated that only SAS score was positively associated with duration of psoriasis (p = 0.030). CONCLUSION: HADS seems to be a better option for anxiety and depression assessment than SAS/SDS in PsA patients.

Effects of maximum residue limit of triflumezopyrim exposure on fitness of the red imported fire ant Solenopsis invicta.

The impact of exposure to free feeding concentrations of triflumezopyrim to the red imported fire ant, Solenopsis invicta, in maximum residue tolerances for 56 days was investigated to understand whether triflumezopyrim, a novel neonicotinoid, poses unacceptable risks to the environment. Our results demonstrated that neither 0.5 µg/ml nor 0.2 µg/ml triflumezopyrim have a significant impact on the growth of the S. invicta colony and their food consumption (sugar water and locusts) during the length of treatment. While both 0.5 µg/ml and 0.2 µg/ml triflumezopyrim improved the grasping ability of S. invicta, and 0.5 µg/ml not 0.2 µg/ml triflumezopyrim increased their rate of locomotion. In addition, although 0.5 µg/ml and 0.2 µg/ml triflumezopyrim increased their individual aggressiveness index, the probability of the survival of S. invicta was not impacted by triflumezopyrim treatments in aggressive group encounters. This study suggests that triflumezopyrim did not have a negative impact on the fitness of S. invicta at 0.5 µg/ml and 0.2 µg/ml exposures.

Cupriavidus sp. HN-2, a Novel Quorum Quenching Bacterial Isolate, is a Potent Biocontrol Agent Against Xanthomonas campestris pv. campestris.

Diffusible signal factor (DSF) represents a family of widely conserved quorum sensing (QS) signals involved in the regulation of virulence factor production in many Gram-negative bacterial pathogens. Quorum quenching, which disrupts QS either by degradation of QS signals or interference of signal generation or perception, is a promising strategy for prevention and control of QS-mediated bacterial infections. In this study, a novel DSF-degrading strain, HN-2, was isolated from contaminated soil and identified as Cupriavidus sp. The isolate exhibited superior DSF degradation activity and completely degraded 2 mmol·L-1 of DSF within 24 h. Analysis of the degradation products of DSF by gas chromatography-mass spectrometry led to the identification of trans-2-decenoic acid methyl ester as the main intermediate product, suggesting that DSF could be degraded by oxidation and hydroxylation. Moreover, this study presents for the first time, evidence that Cupriavidus sp. can reduce the black rot disease caused by Xanthomonas campestris pv. campestris (Xcc). Application of the HN-2 strain as a biocontrol agent could substantially reduce the disease severity. These findings reveal the biochemical basis of a highly efficient DSF-degrading bacterial isolate and present a useful agent for controlling infectious diseases caused by DSF-dependent bacterial pathogens.

Entanglement monogamy in three qutrit systems.

By introducing an arbitrary-dimensional multipartite entanglement measure, which is defined in terms of the reduced density matrices corresponding to all possible two partitions of the entire system, we prove that multipartite entanglement cannot be freely shared among the parties in both n-qubit systems and three-qutrit systems. Furthermore, our result implies that the satisfaction of the entanglement monogamy is related to the number of particles in the quantum system. As an application of three-qutrit monogamy inequality, we give a condition for the separability of a class of two-qutrit mixed states in a 3 ⊗ 3 system.