Transient social-ecological dynamics reveal signals of decoupling in a highly disturbed Anthropocene landscape.

Understanding the transient dynamics of interlinked social-ecological systems (SES) is imperative for assessing sustainability in the Anthropocene. However, how to identify critical transitions in real-world SES remains a formidable challenge. In this study, we present an evolutionary framework to characterize these dynamics over an extended historical timeline. Our approach leverages multidecadal rates of change in socioeconomic data, paleoenvironmental, and cutting-edge sedimentary ancient DNA records from China's Yangtze River Delta, one of the most densely populated and intensively modified landscapes on Earth. Our analysis reveals two significant social-ecological transitions characterized by contrasting interactions and feedback spanning several centuries. Initially, the regional SES exhibited a loosely connected and ecologically sustainable regime. Nevertheless, starting in the 1950s, an increasingly interconnected regime emerged, ultimately resulting in the crossing of tipping points and an unprecedented acceleration in soil erosion, water eutrophication, and ecosystem degradation. Remarkably, the second transition occurring around the 2000s, featured a notable decoupling of socioeconomic development from ecoenvironmental degradation. This decoupling phenomenon signifies a more desirable reconfiguration of the regional SES, furnishing essential insights not only for the Yangtze River Basin but also for regions worldwide grappling with similar sustainability challenges. Our extensive multidecadal empirical investigation underscores the value of coevolutionary approaches in understanding and addressing social-ecological system dynamics.

Metabolomics-based study of chemical compositions in cellulase additives derived from a tobacco-origin Bacillus subtilis and their impact on tobacco sensory attributes.

To enhance the quality of tobacco leaves and optimize the smoking experience, diverse strains of functional bacteria and their associated metabolites have been used in tobacco aging. Exogenous cellulase additives are frequently employed to facilitate the degradation of cellulose and other macromolecular matrices and enhance the quality of the tobacco product. However, little is known about how microbial metabolites present in exogenous enzyme additives affect tobacco quality. In this study, crude cellulase solutions, produced by a tobacco-originating bacterium Bacillus subtilis FX-1 were employed on flue-cured tobacco. The incorporation of cellulase solutions resulted in the reduction of cellulose crystallinity in tobacco and the enhancement of the overall sensory quality of tobacco. Notably, tobacco treated with cellulase obtained from laboratory flask fermentation demonstrated superior scent and flavor attributes in comparison to tobacco treated with enzymes derived from industrial bioreactor fermentation. The targeted and untargeted metabolomic analysis revealed the presence of diverse flavor-related precursors and components in the cellulase additives, encompassing sugars, alcohols, amino acids, organic acids, and others. The majority of these metabolites exhibited significantly higher levels in the flask group compared to the bioreactor group, probably contributing to a pronounced enhancement in the sensory quality of tobacco. Our findings suggest that the utilization of metabolic products derived from B. subtilis FX-1 as additives in flue-cured tobacco holds promise as a viable approach for enhancing sensory attributes, establishing a solid theoretical foundation for the potential development of innovative tobacco aging additives.

Sd-net: a semi-supervised double-cooperative network for liver segmentation from computed tomography (CT) images.

INTRODUCTION: The automatic segmentation of the liver is a crucial step in obtaining quantitative biomarkers for accurate clinical diagnosis and computer-aided decision support systems. This task is challenging due to the frequent presence of noise and sampling artifacts in computerized tomography (CT) images, as well as the complex background, variable shapes, and blurry boundaries of the liver. Standard segmentation of medical images based on full-supervised convolutional networks demands accurate dense annotations. Such a learning framework is built on laborious manual annotation with strict requirements for expertise, leading to insufficient high-quality labels. METHODS: To overcome such limitation and exploit massive weakly labeled data, we relaxed the rigid labeling requirement and developed a semi-supervised double-cooperative network (SD- Net). SD-Net is trained to segment the complete liver volume from preoperative abdominal CT images by using limited labeled datasets and large-scale unlabeled datasets. Specifically, to enrich the diversity of unsupervised information, we construct SD-Net consisting of two collaborative network models. Within the supervised training module, we introduce an adaptive mask refinement approach. First, each of the two network models predicts the labeled dataset, after which adaptive mask refinement of the difference predictions is implemented to obtain more accurate liver segmentation results. In the unsupervised training module, a dynamic pseudo-label generation strategy is proposed. First each of the two models predicts unlabeled data and the better prediction is considered as pseudo-labeling before training. RESULTS AND DISCUSSION: Based on the experimental findings, the proposed method achieves a dice score exceeding 94%, indicating its high level of accuracy and its suitability for everyday clinical use.

NRP1 transduces mechanical stress inhibition via LATS1/YAP in hypertrophic scars.

Hypertrophic scar (HS) is an abnormal fibrous hyperplasia of the skin caused by excessive tissue repair in response to skin burns and trauma, which restricts physical function and impairs patients' quality of life. Numerous studies have shown that pressure garment therapy (PGT) is an effective treatment for preventing hypertrophic scars. Herein, we found that mechanical stress stimulates the neuropilin 1 (NRP1) expression through screening GSE165027, GSE137210, and GSE120194 from Gene Expression Omnibus (GEO) database and bioinformatics analysis. We verified this stimulation in the human hypertrophic scar, pressure culture cell model, and rat tail-scar model. Mechanical compression increased LATS1 and pYAP enrichment, thus repressing the expression of YAP. Functionally, the knockdown of NRP1 promoted the expression of LATS1, thus decreasing the expression of YAP and inhibiting endothelial cell proliferation. Furthermore, co-immunoprecipitation analysis confirmed that NRP1 binds to YAP, and mechanical compression disrupted this binding, which resulted in the promotion of YAP relocation to nuclear. In conclusion, our results indicated that NRP1 transduces mechanical force inhibition by inhibiting YAP expression. Mechanical pressure can release YAP bound to NRP1, which explains the phenomenon that mechanical stress increases YAP in the nucleus. Strategies targeting NRP1 may promote compression therapy with optimal and comfortable pressures.

Genetic diversity, antibiotic resistance, and virulence characteristics of Staphylococcus aureus from raw milk over 10 years in Shanghai.

Staphylococcus aureus (S. aureus) is a major cause of foodborne infections and its persistence in raw milk is a multifaceted phenomenon that poses a considerable public health challenge. Our study investigated the prevalence, virulence genes, antibiotic resistance, and genetic characterization of S. aureus in raw milk in six Shanghai districts from 2013 to 2022. At 18 dairy farms, a total of 704 S. aureus strains were isolated from 1799 samples tested for drug sensitivity. The highest rates of antibiotic resistance were ampicillin (96.7 %), sulfamethoxazole (65 %), and erythromycin (21.6 %). Between 2018 and 2022, there was a significant decrease in the resistance rates of ceftiofur, ofloxacin, tilmicosin, erythromycin, clindamycin, amoxicillin-clavulanic acid, and sulfamethoxazole in comparison to the period from 2013 to 2017. There were 205 S. aureus strains chosen for whole genome sequencing (WGS), with no more than 2 strains of the same resistance phenotype from each farm per year. The prevalence of mecA-positive strains was 14.15 %, while other antibiotic resistance-associated genes were observed as follows: blaI (70.21 %), lnu(B) (5.85 %), lsa(E) (5.75 %), fexA (6.83 %), erm(C) (4.39 %), tet(L) (9.27 %), and dfrG (5.85 %). Isolates harboring the immune evasion cluster (IEC) genes (scn, chp, and sak) were predominantly categorized as sequence types (STs) 7, 188, 15, 59, and 398. The predominant cluster complexes were CC97, CC1, CC398, and CC1651. In 2017-2022, there was a transition in CC1 from the highly antibiotic-resistant ST9 strain that emerged between 2013 and 2018 to the low-resistant but highly virulent ST1 strain. Retrospective phylogenetic analysis elucidated the evolutionary history of the isolates and demonstrated that the human-animal host transition of S. aureus was linked to the genesis of MRSA CC398. The implementation of extended surveillance will aid in the development of innovative strategies to avoid the transmission of S. aureus along the dairy food chain and the occurrence of public health events.

Characterization and evaluation of the cholesterol-lowering ability of Lactiplantibacillus plantarum HJ-S2 isolated from the intestine of Mesoplodon densirostris.

In this study, ten strains of lactic acid bacteria were isolated from the intestine of Blainville's beaked whale (Mesoplodon densirostris),and their cholesterol-lowering activities in vitro and in vivo were investigated. The among these strains, HJ-S2 strain, which identified as Lactiplantibacillus plantarum, showed a high in vitro cholesterol-lowering rate (48.82%). Strain HJ-S2 was resistant to acid and bile salts, with a gastrointestinal survival rate of more than 80%, but was sensitive to antibiotics. Strain HJ-S2 was found to be able to adhere to HT-29 cells in an adhesion test. The number of cell adhesion was 132.52. In addition, we also performed the cholesterol-lowering activities in vivo using high-fat diet feed mouse models. Our results indicated that HJ-S2 reduced total cholesterol (TC), total glycerol (TG), and low-density lipoprotein cholesterol (LDLC) levels while increasing the high-density lipoprotein cholesterol (HDLC) level. It also alleviated the lipid accumulation in high-fat diet feed mouse liver and pancreas. Hence, HJ-S2 demonstrated appropriate cholesterol-lowering ability and has the potential to be used as a probiotic in functional foods.

Characterization of lacustrine harmful algal blooms using multiple biomarkers: Historical processes, driving synergy, and ecological shifts.

Harmful algal blooms (HABs) producing toxic metabolites are increasingly threatening environmental and human health worldwide. Unfortunately, long-term process and mechanism triggering HABs remain largely unclear due to the scarcity of temporal monitoring. Retrospective analysis of sedimentary biomarkers using up-to-date chromatography and mass spectrometry techniques provide a potential means to reconstruct the past occurrence of HABs. By combining aliphatic hydrocarbons, photosynthetic pigments, and cyanotoxins, we quantified herein century-long changes in abundance, composition, and variability of phototrophs, particularly toxigenic algal blooms, in China's third largest freshwater Lake Taihu. Our multi-proxy limnological reconstruction revealed an abrupt ecological shift in the 1980s characterized by elevated primary production, Microcystis-dominated cyanobacterial blooms, and exponential microcystin production, in response to nutrient enrichment, climate change, and trophic cascades. The empirical results from ordination analysis and generalized additive models support climate warming and eutrophication synergy through nutrient recycling and their feedback through buoyant cyanobacterial proliferation, which sustain bloom-forming potential and further promote the occurrence of increasingly-toxic cyanotoxins (e.g., microcystin-LR) in Lake Taihu. Moreover, temporal variability of the lake ecosystem quantified using variance and rate of change metrics rose continuously after state change, indicating increased ecological vulnerability and declined resilience following blooms and warming. With the persistent legacy effects of lake eutrophication, nutrient reduction efforts mitigating toxic HABs probably be overwhelmed by climate change effects, emphasizing the need for more aggressive and integrated environmental strategies.

One global disseminated 193 kb high-risk hybrid plasmid harboring tet(X4), mcr or blaNDM threatening public health.

In Shanghai, the prevalence of tet(X4) and tet(X4)-carrying plasmid from food-producing -animal Enterobacteriales has not been intensively investigated. Here, five tet(X4)-positive swine-origin E. coli strains were characterized among 652 food-producing-animal E. coli isolates in Shanghai during 2018-2021 using long-term surveillance among poultry, swine and cattle, antimicrobial susceptibility testing, and tet(X4)-specific PCR. A combination of short- and long-read sequencing technologies demonstrated that the five strains with 4 STs carried a nearly identical 193 kb tet(X4)-bearing plasmid (p193k-tetX4) belonging to the same IncFIA(HI1)/IncHI1A/IncHIB plasmid family (p193k). Surprisingly, 34 of the 151 global tet(X4)-positive plasmids was the p193k members and exclusively pandemic in China. Other p193k members harboring many critically important ARGs (mcr or blaNDM) with particular genetic environment are widespread throughout human-animal-environmental sources, with 33.77 % human origin. Significantly, phylogenetic analysis of 203 p193k-tetX4 sequences revealed that human- and animal-origin plasmids clustered within the same phylogenetic subgroups. The largest lineage (173/203) comprised 161 E. coli, 6 Klebsiella, 3 Enterobacter, 2 Citrobacter, and 1 Leclercia spp. from animals (n = 143), humans (n = 18), and the environment (n = 9). Intriguingly, the earliest 2015 E. coli strain YA_GR3 from Malaysian river water and 2016 S. enterica Chinese clinical strain GX1006 in another lineage demonstrated that p193k-tetX4 have been widely spread from S. enterica or E. coli to other Enterobacterales. Furthermore, 180 E. coli p193k-tetX4 strains were widespread cross-sectorial transmission among food animals, pets, migratory birds, human and ecosystems. Our findings proved the extensive transmission of the high-risk p193k harboring crucial ARGs across multiple interfaces and species. Therefore, one-health-based systemic surveillance of these similar high-risk plasmids across numerous sources and bacterial species is extremely essential.

Real-time prediction of organ failures in patients with acute pancreatitis using longitudinal irregular data.

It is extremely important to identify patients with acute pancreatitis who are at high risk for developing persistent organ failures early in the course of the disease. Due to the irregularity of longitudinal data and the poor interpretability of complex models, many models used to identify acute pancreatitis patients with a high risk of organ failure tended to rely on simple statistical models and limited their application to the early stages of patient admission. With the success of recurrent neural networks in modeling longitudinal medical data and the development of interpretable algorithms, these problems can be well addressed. In this study, we developed a novel model named Multi-task and Time-aware Gated Recurrent Unit RNN (MT-GRU) to directly predict organ failure in patients with acute pancreatitis based on irregular medical EMR data. Our proposed end-to-end multi-task model achieved significantly better performance compared to two-stage models. In addition, our model not only provided an accurate early warning of organ failure for patients throughout their hospital stay, but also demonstrated individual and population-level important variables, allowing physicians to understand the scientific basis of the model for decision-making. By providing early warning of the risk of organ failure, our proposed model is expected to assist physicians in improving outcomes for patients with acute pancreatitis.

Markedly boosted peroxymonosulfate- and periodate-based Fenton-like activities of iron clusters on sulfur/nitrogen codoped carbon: Key roles of a sulfur dopant and compared activation mechanisms.

Highly dispersed iron nanoclusters on carbon (FeNC@C) hold great promise for wastewater purification in Fenton-like reactions. The microenvironment engineering of central Fe atom is promising to boost the activation capacity of FeNC@C, which is however remains a challenge. This study developed a self-sacrificed templating strategy to S, N-codoped carbon supported Fe nanoclusters (FeNC@SNC) activator and find the key role of sulfur heteroatoms in regulating the electron structure of Fe sites and final activation property. Investigations revealed that the FeNC@SNC composite exhibited unusual bifunctional activity in both peroxymonosulfate (PMS)- and periodate (PI)-based Fenton-like reactions. We also offered insights into the differences between the degradation of organics by the FeNC@SNC/PMS and FeNC@SNC/PI systems. Specifically, under identical conditions, the FeNC@SNC/PMS system delivered a higher oxidation capability and stronger resistance to nontarget matrix constituents, but showed more severe Fe leaching than the FeNC@SNC/PI system. Furthermore, while mediated electron-transfer process was identified as the major route for pollutant decomposition in both systems, the high-valent Fe-oxo species [Fe (IV)] was the auxiliary reactive species found only in the FeNC@SNC/PMS system. Based on these findings, our results provide profound insights into the design of active and durable Fe-based activators toward highly efficient Fenton-like reactions.

Clostridium autoethanogenum protein inclusion in the diet for broiler: Enhancement of growth performance, lipid metabolism, and gut microbiota.

This study aimed to investigate the effects of dietary supplementation of the new single-cell protein Clostridium autoethanogenum protein (CAP) on growth performance, plasma biochemical indexes, liver histology, lipid metabolism, and gut microbiota in Cobb broilers. According to the randomized block experimental design, 960 Cobb broilers (1d old) were divided into six treatments with eight replicates of 20 birds each. Six isonitrogenous and isoenergetic diets were formulated with different contents of CAP (0, 1, 2, 3, 4, and 5%) to replace soybean meal (SBM). The results showed that the addition of CAP did not influence liver health when it exceeded 2%. The protein metabolism markers and feed conversion rate increased (P < 0.05), significantly improving the growth performance. When the content of CAP was greater than 4%, it could promote lipolysis without affecting lipogenesis, decreasing the abdominal fat rate. There was no significant difference in MDA between these groups (P = 0.948). The increase of SOD and GSH-Px indicated the enhancement of antioxidant response. Alpha diversity did not significantly differ between groups (P > 0.05). Inclusion of 4% or less CAP led to the increase in beneficial microbiota, the concentration of short-chain fatty acids (SCFAs) such as acetic acid, propionic acid, and butyric acid (P < 0.05), and the concentration of primary bile acids such as cholic acid and goose deoxycholic acid (P < 0.05). While the concentration of secondary bile acids such as taurocholic acid and taurine goose deoxycholic acid was decreased (P < 0.05). These results illustrated that the CAP had a high potential for application in poultry nutrition. In terms of improving growth performance and antioxidant capacity and reducing fat deposition rate, 4% CAP content is recommended.

Caring for Older People during and beyond the COVID-19 Pandemic: Experiences of Residential Health Care Workers.

Older people and health care workers in residential care homes are particularly vulnerable to the adverse impacts of the COVID-19 pandemic. As COVID-19 has been spreading around the world for more than two years, the nature of care delivery has been substantially transformed. This study aims at understanding the long-term and ongoing impacts of COVID-19 on the delivery of care in residential care homes. It investigates how the delivery of care has been transformed by the COVID-19 pandemic and how health care workers adapted to these changes from the perspectives of frontline health care workers. Semi-structured interviews were conducted from February to December 2021 with a purposive sample of 30 health care workers from six residential care homes in Hong Kong. Thematic analysis identified three themes, including (1) enhancing infection prevention and control measures; (2) maintaining the psychosocial wellbeing of residents; and (3) developing resilience. Discussions and implications were drawn from these findings.

Prognostic and immunological role of cuproptosis-related protein FDX1 in pan-cancer.

Background: Cancer is the second cause of death worldwide. Copperoptosis is a new mode of regulated cell death and is strongly associated with metabolic pathways. FDX1 is a key gene that promotes copperoptosis, and its impact on tumor pathogenesis and tumor immune response is indistinct and needs further exploration. Methods: Data was mined from the Cancer Genome Atlas database, the Broad Institute Cancer Cell Line Encyclopedia database, and the International Cancer Genome Consortium. Survival analyses included the Kaplan-Meier method for calculating the cumulative incidence of survival events and the log-rank method for comparing survival curves between groups. Immune cell infiltration levels were calculated using the Spearman correlation test and correlated with FDX1 expression to assess significance. More correlation analyses between FDX1 expression and mutational markers, such as tumor mutational burden (TMB) and microsatellite instability (MSI), were also examined via Spearman assay to explore the relation between FDX1 expression and the sensitivity of common antitumor drugs. Results: FDX1 expression was downregulated in most kinds of cancers, and this high expression indicated better overall survival and death-specific survival. For several cancer types, FDX1 expression had a positive correlation with immune cell infiltration, and FDX1 also had a positive correlation with TMB and MSI in some cancer types, linking its expression to the assessment of possible treatment responses. Conclusion: The correlations between FDX1 expression and cancer in varioustissues, including clear links to cancer survival and prognosis, make FDX1 aninteresting biomarker and potential therapeutic target for cancer surveillance and futureresearch.

Dynamic antimicrobial resistant patterns of Escherichia coli from healthy poultry and swine over 10 years in Chongming Island, Shanghai.

BACKGROUND: Antimicrobial resistance (AMR) is one of the greatest threats to animal and public health. Here, we conducted a dynamic surveillance of Escherichia coli on Chongming Island in Shanghai during 2009-2021 to identify the characteristics and trends of Chongming's AMR pandemic. METHODS: Rectal (cloaca) swabs from four poultry and nine swine farms (Chongming Island, 2009-2021) were collected for E. coli strains acquisition. The micro-broth dilution method was used to test antimicrobial susceptibility of E. coli isolates against 10 antimicrobial classes including 15 antimicrobials. Utilizing generalized linear mixed models (GLMMs) and co-occurrence analyses, we further explored the multiple-drug-resistance (MDR) combinations and dynamic patterns of E. coli over 10 years in two food animals. RESULTS: Total of 863 MDR isolates were found among 945 collected E. coli isolates, 337 from poultry and 608 from swine. Both isolates exhibited high resistant rates (> 70%) to tetracyclines, phenicols, sulfonamides, penicillins, and aminoglycosides (only in swine). The resistant rates of swine isolates to penicillins, aminoglycosides, tetracyclines, phenicols, and polymyxins were significantly higher than those of poultry isolates, whereas resistance to fluoroquinolones was reversed. Resistance to polymyxins decreased similarly in swine (42.4% in 2009 to 0.0% in 2021) and poultry isolates (from 16.5% to 0.0%). However, resistance to other seven antimicrobial classes (excluding carbapenems and penicillins) declined dramatically in swine isolates, particularly fluoroquinolones (from 80.5% to 14.4%), and tendencies of resistance to the seven classes showed markedly divergent patterns in poultry isolates. Using Poisson GLMMs, the AMR carriage since 2016 was significantly lower than that of 2009 (odds ratio < 1), indicating a decline in the risk of MDR emergence. Furthermore, despite the highly diverse MDR profiles, co-occurrence analysis identified two prominent MDR clusters of penicillins-phenicols-fluoroquinolones in poultry and aminoglycosides-tetracyclines-sulfonamides-phenicols in swine. CONCLUSIONS: Our study uncovered vastly distinct AMR patterns and dynamic tendencies of poultry and swine E. coli isolates from Chongming. Meanwhile, Chongming's AMR status has ameliorated, as indicated by the decline in antimicrobials prevalence (particularly in swine), lower likelihood of MDR emergence and low carbapenem-, cephalosporin-, and polymyxin resistance. Importantly, this surveillance results are the vital basis for future policy development in Chongming and Shanghai.

Numerical Simulation of Vibrational Sum Frequency Generation Intensity for Non-Centrosymmetric Domains Interspersed in an Amorphous Matrix: A Case Study for Cellulose in Plant Cell Wall.

Vibrational sum frequency generation (SFG) spectroscopy can specifically probe molecular species non-centrosymmetrically arranged in a centrosymmetric or isotropic medium. This capability has been extensively utilized to detect and study molecular species present at the two-dimensional (2D) interface at which the centrosymmetry or isotropy of bulk phases is naturally broken. The same principle has been demonstrated to be very effective for the selective detection of non-centrosymmetric crystalline nanodomains interspersed in three-dimensional (3D) amorphous phases. However, the full spectral interpretation of SFG features has been difficult due to the complexity associated with the theoretical calculation of SFG responses of such 3D systems. This paper describes a numerical method to predict the relative SFG intensities of non-centrosymmetric nanodomains in 3D systems as functions of their size and concentration as well as their assembly patterns, i.e., the distributions of tilt, azimuth, and rotation angles with respect to the lab coordinate. We applied the developed method to predict changes in the CH and OH stretch modes characteristic to crystalline cellulose microfibrils distributed with various orders, which are relevant to plant cell wall structures. The same algorithm can also be applied to any SFG-active nanodomains interspersed in 3D amorphous matrices.

The Diagnostic Value of Ultrasound-Based Deep Learning in Differentiating Parotid Gland Tumors.

Objectives: Evidence suggests that about 80% of all salivary gland tumors involve the parotid glands, with approximately 20% of parotid gland tumors (PGTs) being malignant. Discriminating benign and malignant parotid gland lesions preoperatively is vital for selecting the appropriate treatment strategy. This study explored the diagnostic performance of deep learning system for discriminating benign and malignant PGTs in ultrasonography images and compared it with radiologists. Methods. A total of 251 consecutive patients with surgical resection and proven parotid gland malignant or benign tumors who underwent preoperative ultrasound examinations were enrolled in this study between January 2014 and November 2020. Next, we compared the diagnostic accuracy of deep learning methods (ViT-B\16, EfficientNetB3, DenseNet121, and ResNet50) and radiologists in parotid gland tumor. In addition, the area under the curve (AUC), specificity, sensitivity, positive predictive value, and negative predictive value were calculated. Results: Among the 251 patients, 176/251 were the training set, whereas 75/251 were the validation set. Results showed that 74/251 patients had malignant tumor. Deep learning models achieved good performance in differentiating benign from malignant tumors, with the diagnostic accuracy and AUCs of ViT-B\16, EfficientNetB3, DenseNet121, and ResNet50 model being 81% and 0.81, 80% and 0.82, 77% and 0.81, and 79% and 0.80, respectively. On the other hand, the diagnostic accuracy and AUCs of radiologists were 77%-81% and 0.68-0.75, respectively. It was evident that the diagnostic accuracy of deep learning methods was higher than that of inexperienced radiologists, but there was no significant difference between deep learning methods and experienced radiologists. Conclusions: This study shows that the deep learning system can be used for diagnosing parotid tumors. The findings also suggest that the deep learning system may improve the diagnosis performance of inexperienced radiologists.

Diagnosis System of Microscopic Hyperspectral Image of Hepatobiliary Tumors Based on Convolutional Neural Network.

Hepatobiliary tumor is one of the common tumors and cancers in medicine, which seriously affects people's lives, so how to accurately diagnose it is a very serious problem. This article mainly studies a diagnostic method of microscopic images of liver and gallbladder tumors. Under this research direction, this article proposes to use convolutional neural network to learn and use hyperspectral images to diagnose it. It is found that the addition of the convolutional neural network can greatly improve the actual map classification and the accuracy of the map, and effectively improve the success rate of the treatment. At the same time, the article designs related experiments to compare its feature extraction performance and classification situation. The experimental results in this article show that the improved diagnostic method based on convolutional neural network has an accuracy rate of 85%-90%, which is as high as 6%-8% compared with the traditional accuracy rate, and thus it effectively improves the clinical problem of hepatobiliary tumor treatment.

A multimodal fusion method for Alzheimer's disease based on DCT convolutional sparse representation.

Introduction: The medical information contained in magnetic resonance imaging (MRI) and positron emission tomography (PET) has driven the development of intelligent diagnosis of Alzheimer's disease (AD) and multimodal medical imaging. To solve the problems of severe energy loss, low contrast of fused images and spatial inconsistency in the traditional multimodal medical image fusion methods based on sparse representation. A multimodal fusion algorithm for Alzheimer' s disease based on the discrete cosine transform (DCT) convolutional sparse representation is proposed. Methods: The algorithm first performs a multi-scale DCT decomposition of the source medical images and uses the sub-images of different scales as training images, respectively. Different sparse coefficients are obtained by optimally solving the sub-dictionaries at different scales using alternating directional multiplication method (ADMM). Secondly, the coefficients of high-frequency and low-frequency subimages are inverse DCTed using an improved L1 parametric rule combined with improved spatial frequency novel sum-modified SF (NMSF) to obtain the final fused images. Results and discussion: Through extensive experimental results, we show that our proposed method has good performance in contrast enhancement, texture and contour information retention.

Metal-organic framework-derived magnetic carbon for efficient decontamination of organic pollutants via periodate activation: Surface atomic structure and mechanistic considerations.

Practical implementation of periodate-based advanced oxidation processes for environmental remediation largely relies on the development of cost-effective and high-performance activators. Surface atomic engineering toward these activators is desirable but it remains challenging to realize improved activation properties. Here, a surface atomic engineering strategy used to obtain a novel hybrid activator, namely cobalt-coordinated nitrogen-doped graphitic carbon nanosheet-enwrapped cobalt nanoparticles (denoted as Co@NC-rGO), from a sandwich-architectured metal-organic framework/graphene oxide composite is reported. This activator exhibits prominent periodate activation properties toward pollutant degradation, surpassing previously reported transition-metal-based activators. Importantly, the activator shows good stability, magnetic reusability, and the potential for application in a complex water matrix. Density functional theory modeling implies that the strong activation capability of Co@NC-rGO is related to its surface atomic structure for which the embedded cobalt nanoparticles with abundant interfacial Co-N coordinations display modified electronic configurations on the active centers and benefit periodate adsorption. Quenching experiments and electrochemical measurements showed that the system could oxidize organics through a dominant nonradical pathway. Additionally, a lower concentration of cobalt leaching was observed for the Co@NC-rGO/periodate system than for its Co@NC-rGO/persulfate counterpart. Our work provides a pathway toward engineering surface atomic structures in hybrid activators for efficient periodate activation.

Mutations in the Pectin Methyltransferase QUASIMODO2 Influence Cellulose Biosynthesis and Wall Integrity in Arabidopsis.

Pectins are abundant in the cell walls of dicotyledonous plants, but how they interact with other wall polymers and influence wall integrity and cell growth has remained mysterious. Here, we verified that QUASIMODO2 (QUA2) is a pectin methyltransferase and determined that QUA2 is required for normal pectin biosynthesis. To gain further insight into how pectin affects wall assembly and integrity maintenance, we investigated cellulose biosynthesis, cellulose organization, cortical microtubules, and wall integrity signaling in two mutant alleles of Arabidopsis (Arabidopsis thaliana) QUA2, qua2 and tsd2 In both mutants, crystalline cellulose content is reduced, cellulose synthase particles move more slowly, and cellulose organization is aberrant. NMR analysis shows higher mobility of cellulose and matrix polysaccharides in the mutants. Microtubules in mutant hypocotyls have aberrant organization and depolymerize more readily upon treatment with oryzalin or external force. The expression of genes related to wall integrity, wall biosynthesis, and microtubule stability is dysregulated in both mutants. These data provide insights into how homogalacturonan is methylesterified upon its synthesis, the mechanisms by which pectin functionally interacts with cellulose, and how these interactions are translated into intracellular regulation to maintain the structural integrity of the cell wall during plant growth and development.