New insights into decoding the lifestyle of endophytic Fusarium lateritium Fl617 via comparing genomes.

Fungal-plant interactions have persisted for 460 million years, and almost all terrestrial plants on Earth have endophytic fungi. However, the mechanism of symbiosis between endophytic fungi and host plants has been inconclusive. In this dissertation, we used a strain of endophytic Fusarium lateritium (Fl617), which was found in the previous stage to promote disease resistance in tomato, and selected the pathogenic Fusarium oxysporum Fo4287 and endophytic Fusarium oxysporum Fo47, which are in the same host and the closest relatives of Fl617, to carry out a comparative genomics analysis of the three systems and to provide a new perspective for the elucidation of the special lifestyle of the fungal endophytes. We found that endophytic F. lateritium has a smaller genome, fewer clusters and genes associated with pathogenicity, and fewer plant cell wall degrading enzymes (PCWDEs). There were also relatively fewer secondary metabolisms and typical Fusarium spp. toxins, and a lack of the key Fusarium spp. pathogenicity factor, secreted in xylem (SIX), but the endophytic fungi may be more sophisticated in their regulation of the colonization process. It is hypothesized that the endophytic fungi may have maintained their symbiosis with plants due to the relatively homogeneous microenvironment in plants for a long period of time, considering only plant interactions and discarding the relevant pathogenicity factors, and that their endophytic evolutionary tendency may tend to be genome streamlining and to enhance the fineness of the regulation of plant interactions, thus maintaining their symbiotic status with plants.

Ultrasensitive fiber sensor with enhanced Vernier effect for simultaneous measurements of transverse load and temperature.

Based on enhanced Vernier effect, a compact fiber sensor with ultrahigh sensitivity is proposed for simultaneous transverse load (TL) and temperature measurements. A single mode fiber (SMF) is spliced with a segment of hollow-core fiber (HCF) coated with polydimethylsiloxane (PDMS), some PDMS is injected into the HCF, forming a Vernier sensor with an air cavity adjacent to a PDMS cavity. It is shown that TL and temperature changes give rise to opposite and remarkable different variations in lengths of the two cavities, thereby enhancing Vernier effect and in favor of simultaneous measurements of TL and temperature. Moreover, the limited sensitivity magnification due to the length mismatch between the two cavities is compensated for by reconstructing the Vernier envelope with a broadened free spectrum range (FSR) from output signal. As a result, the highest TL sensitivity reported so far of -2637.47 nm/N and a good condition number of 69.056 for the sensitivity coefficient matrix have been achieved.

Evolution mechanism of scratch removal based on the implementation of magnetorheological finishing.

Scratches on optical components induce laser damage and limit the increase in laser power. Magnetorheological finishing (MRF) is a highly deterministic optical manufacturing technology that can improve the surface roughness of optical components. Although MRF has exhibited significant potential for reducing subsurface damage and removing scratches, the principle and mechanism behind the scratch removal are not sufficiently understood. In this study, the theory of fluid mechanics is used to analyze the pressure, velocity, and particle trajectory distribution near a scratch. A physical model was developed for the differential removal of scratches at the bottom and surface of the optical components. The morphological evolution of the scratch was predicted during removal, and detailed experiments were performed to verify the effectiveness of the proposed model. The results indicate that scratches expand laterally rather than being completely removed. Furthermore, scratch removal efficiency is greater when the removal direction is perpendicular to the scratch rather than being parallel. This study offers an intrinsic perspective for a comprehensive understanding of the MRF technique used for scratch removal, which can be beneficial for removing scratches from aspherical optical systems.

Methodology comparison of environmental sediment fungal community analysis.

Fungi play important roles in ecosystems. Analyzing fungal communities in environments has long been a challenge due to the large difference in compositions retrieved using different methods or sequencing regions, obscuring the true abundance and species information. Our study aimed to compare and determine more accurate approach for evaluating fungal populations in river sediment. To achieve this, different primer sets in the internal transcribed spacer (ITS) (ITS5/ITS1R, ITS1F/ITS2), 18S rRNA gene (0817F/1196R) for High-throughput sequencing (HTS), metagenomic shotgun sequencing (MS) directly from environmental samples, and HTS using ITS primers for the fungal samples collected from plate cultivation were used to characterize the fungal communities. We calculated diversity index and used FungalTraits to analyze methods preferences for fungal species. The study revealed that when analyzing the fungal species directly from environmental samples, amplification and sequencing of ITS region demonstrated more accuracy than MS and 18S rRNA gene sequencing methods, but displayed significant primer preference. Over 30 % fungal species from HTS after plate cultivation were not present in HTS from the environmental samples. NMDS analysis demonstrated significant disparities in species diversity among different methods, suggesting potential complementarity between them. Over 85% species identified by HTS using ITS primers belonged to filamentous fungi, while the MS mostly identified yeast (62%). Therefore, to get more accurate fungal community information in sediment, multiple methods were recommended by using cultivation, molecular biological methods dependent on PCR techniques like ITS1F/ITS2 primer for HTS and PCR independent method such as metagenomic shotgun sequencing techniques.

Long-term and combined heavy-metal contamination forms a unique microbiome and resistome: A case study in a Yellow River tributary sediments.

Microorganisms have developed mechanisms to adapt to environmental stress, but how microbial communities adapt to long-term and combined heavy-metal contamination under natural environmental conditions remains unclear. Specifically, this study analyzed the characteristics of heavy metal composition, microbial community, and heavy metal resistance genes (MRGs) in sediments along Mang River, a tributary of the Yellow River, which has been heavily polluted by industrial production for more than 40 years. The results showed that the concentrations of Cr, Zn, Pb, Cu and As in most sediments were higher than the ambient background values. Bringing the heavy metals speciation and concentration into the risk evaluation method, two-thirds of the sediment samples were at or above the moderate risk level, and the ecological risk of combined heavy metals in the sediments decreased along the river stream. The high ecological risk of heavy metals affected the microbial community structure, metabolic pathways and MRG distribution. The formation of a HM-resistant microbiome possibly occurred through the spread of insertion sequences (ISs) carrying multiple MRGs, the types of ISs carrying MRGs outnumber those of plasmids, and the quantity of MRGs on ISs is also higher than that on plasmids. These findings could improve our understanding of the adaptation mechanism of microbial communities to long-term combined heavy metal contamination.

Nighttime color constancy using robust gray pixels.

Color constancy is a basic step for achieving stable color perception in both biological visual systems and the image signal processing (ISP) pipeline of cameras. So far, there have been numerous computational models of color constancy that focus on scenes under normal light conditions but are less concerned with nighttime scenes. Compared with daytime scenes, nighttime scenes usually suffer from relatively higher-level noise and insufficient lighting, which usually degrade the performance of color constancy methods designed for scenes under normal light. In addition, there is a lack of nighttime color constancy datasets, limiting the development of relevant methods. In this paper, based on the gray-pixel-based color constancy methods, we propose a robust gray pixel (RGP) detection method by carefully designing the computation of illuminant-invariant measures (IIMs) from a given color-biased nighttime image. In addition, to evaluate the proposed method, a new dataset that contains 513 nighttime images and corresponding ground-truth illuminants was collected. We believe this dataset is a useful supplement to the field of color constancy. Finally, experimental results show that the proposed method achieves superior performance to statistics-based methods. In addition, the proposed method was also compared with recent deep-learning methods for nighttime color constancy, and the results show the method's advantages in cross-validation among different datasets.

Influencing factors analysis of asymmetry in knee adduction moment among patients with unilateral knee osteoarthritis.

BACKGROUND: The knee adduction moment(KAM) of both lower limbs in patients with unilateral knee osteoarthritis(KOA) exhibits asymmetry during walking, but the factors influencing this asymmetry remain unclear. This study aimed to explore the influencing factors of KAM asymmetry in patients with unilateral KOA. METHODS: A total of 148 patients with unilateral medial compartment KOA were selected for this retrospective study, and general data such as gender, age, and duration of disease were collected. The hip-knee-ankle (HKA) angle, degree of pain, and knee-extension muscle strength on the affected side were assessed through radiographic outcomes, the visual analog scale(VAS), and the Biodex isokinetic system. The peak KAM of both lower limbs was analyzed using a BTS motion-capture system and force platform. The asymmetry index(ASI) of KAM was calculated, and the patients were further categorized into the KAM symmetry group(ASI value ≤ 10%) and the KAM asymmetry group(ASI value>10%).Binary logistic regression analysis was employed to analyze the factors influencing the asymmetry of KAM. RESULTS: 90 patients were categorized into the KAM asymmetry group, representing 60.8% of the cohort. A significant difference in the ASI value of KAM was observed between the two groups. Correlation analysis identified nine factors, including sex, age, and BMI, that were positively correlated with the ASI value of KAM. In contrast, knee-extension muscle strength and per-capita monthly household income were negatively correlated with the ASI value of KAM. Regression analysis revealed that being female(OR = 1.752), older age(OR = 2.472), increased BMI(OR = 1.535), larger varus angle(OR = 3.965), higher VAS score(OR = 2.617), Kellgren-Lawrence(K-L) grade IV(OR = 4.474), history of knee joint trauma(OR = 5.684), and living in a rural location(OR = 1.554) increased the risk of KAM asymmetry. Conversely, increased knee-extension muscle strength(OR = 0.758) and a per-capita monthly household income of 3000 ~ 6000 yuan(OR = 0.814) decreased the risk of KAM asymmetry. CONCLUSION: Female gender, older age, increased BMI, larger varus angle, higher VAS score, K-L grade IV, history of knee joint trauma, and living in a rural location are identified as risk factors for KAM asymmetry. Conversely, increased knee-extension muscle strength and a per-capita monthly household income of 3000 ~ 6000 yuan serve as protective factors against this asymmetry.

Immediate effect of kinesiology taping on muscle strength, static balance and proprioception after eccentric muscle fatigue on ankle: a randomized cross-over trial.

BACKGROUND: Kinesiology Taping(KT) is commonly used as a physical therapy to prevent exercise-induced fatigue. This study aims to evaluate the immediate effects of KT on muscle strength, static balance, and proprioception after eccentric muscle fatigue on ankle. METHODS: Twenty healthy male university students were recruited. The experimental protocol was structured into four sessions, each separated by a one-week washout period to prevent carryover effects. Participants were randomly allocated to one of four intervention conditions in each session, ensuring no participant received the same intervention twice. These conditions were: no taping(NT),sham taping(ST),athletic taping(AT),and kinesiology taping(KT).Taping was applied immediately following an eccentric muscle fatigue protocol targeting the ankle, and assessments were conducted in the order of proprioception, muscle strength and static balance. Isometric muscle strength and proprioception were evaluated using the Biodex isokinetic system. Static balance was measured using the TecnoBody balance platform. RESULTS: KT had a significantly higher plantarflexion/dorsiflexion peak torque, dorsiflexion average peak torque, and plantarflexion/dorsiflexion average power at 60°/s compared with NT and ST in terms of isometric muscle strength (p < 0.05).Furthermore, the plantarflexion peak torque of KT was significantly greater than AT at 60°/s[p = 0.005,95% confidence interval(CI) = 3.39 to 18.20] and 180°/s[p = 0.006,95%CI(2.62,21.98)]. In terms of proprioception, KT showed a lower absolute error in 25° plantarflexion and 10° dorsiflexion compared to NT, ST and AT. For static balance with eyes-open and eyes-closed conditions, AT and KT had a lower total sway area than NT and ST (p < 0.05). Additionally, a significant difference in total sway length with eyes-open condition was observed between AT and KT[p < 0.001,95%CI(-431.81,-168.25)];total sway area and the center of pressure(COP) velocity in the mediolateral(ML) and anteroposterior(AP) directions with eyes-closed condition were significantly lower in AT compared to KT. CONCLUSION: This study suggests that KT is more effective than other taping conditions in improving muscle strength and proprioception after eccentric muscle fatigue on ankle. However, AT is more helpful in increasing static postural control ability after ankle muscle fatigue than KT. TRIAL REGISTRATION: This study was registered with www.chictr.org.cn (registration number: ChiCTR2300068278) on 13/2/2023.

Aqueous production of secondary organic aerosol from fossil-fuel emissions in winter Beijing haze.

Secondary organic aerosol (SOA) produced by atmospheric oxidation of primary emitted precursors is a major contributor to fine particulate matter (PM2.5) air pollution worldwide. Observations during winter haze pollution episodes in urban China show that most of this SOA originates from fossil-fuel combustion but the chemical mechanisms involved are unclear. Here we report field observations in a Beijing winter haze event that reveal fast aqueous-phase conversion of fossil-fuel primary organic aerosol (POA) to SOA at high relative humidity. Analyses of aerosol mass spectra and elemental ratios indicate that ring-breaking oxidation of POA aromatic species, leading to functionalization as carbonyls and carboxylic acids, may serve as the dominant mechanism for this SOA formation. A POA origin for SOA could explain why SOA has been decreasing over the 2013-2018 period in response to POA emission controls even as emissions of volatile organic compounds (VOCs) have remained flat.

Characteristics, Influence, Prevention, and Control Measures of the Mpox Infodemic: Scoping Review of Infodemiology Studies.

BACKGROUND: The mpox pandemic has caused widespread public concern around the world. The spread of misinformation through the internet and social media could lead to an infodemic that poses challenges to mpox control. OBJECTIVE: This review aims to summarize mpox-related infodemiology studies to determine the characteristics, influence, prevention, and control measures of the mpox infodemic and propose prospects for future research. METHODS: The scoping review was conducted based on a structured 5-step methodological framework. A comprehensive search for mpox-related infodemiology studies was performed using PubMed, Web of Science, Embase, and Scopus, with searches completed by April 30, 2024. After study selection and data extraction, the main topics of the mpox infodemic were categorized and summarized in 4 aspects, including a trend analysis of online information search volume, content topics of mpox-related online posts and comments, emotional and sentiment characteristics of online content, and prevention and control measures for the mpox infodemic. RESULTS: A total of 1607 articles were retrieved from the databases according to the keywords, and 61 studies were included in the final analysis. After the World Health Organization's declaration of an mpox public health emergency of international concern in July 2022, the number of related studies began growing rapidly. Google was the most widely used search engine platform (9/61, 15%), and Twitter was the most used social media app (32/61, 52%) for researchers. Researchers from 33 countries were concerned about mpox infodemic-related topics. Among them, the top 3 countries for article publication were the United States (27 studies), India (9 studies), and the United Kingdom (7 studies). Studies of online information search trends showed that mpox-related online search volume skyrocketed at the beginning of the mpox outbreak, especially when the World Health Organization provided important declarations. There was a large amount of misinformation with negative sentiment and discriminatory and hostile content against gay, bisexual, and other men who have sex with men. Given the characteristics of the mpox infodemic, the studies provided several positive prevention and control measures, including the timely and active publishing of professional, high-quality, and easy-to-understand information online; strengthening surveillance and early warning for the infodemic based on internet data; and taking measures to protect key populations from the harm of the mpox infodemic. CONCLUSIONS: This comprehensive summary of evidence from previous mpox infodemiology studies is valuable for understanding the characteristics of the mpox infodemic and for formulating prevention and control measures. It is essential for researchers and policy makers to establish prediction and early warning approaches and targeted intervention methods for dealing with the mpox infodemic in the future.

The reciprocal interactions between microglia and T cells in Parkinson's disease: a double-edged sword.

In Parkinson's disease (PD), neurotoxic microglia, Th1 cells, and Th17 cells are overactivated. Overactivation of these immune cells exacerbates the disease process and leads to the pathological development of pro-inflammatory cytokines, chemokines, and contact-killing compounds, causing the loss of dopaminergic neurons. So far, we have mainly focused on the role of the specific class of immune cells in PD while neglecting the impact of interactions among immune cells on the disease. Therefore, this review demonstrates the reciprocal interplays between microglia and T cells and the associated subpopulations through cytokine and chemokine production that impair and/or protect the pathological process of PD. Furthermore, potential targets and models of PD neuroinflammation are highlighted to provide the new ideas/directions for future research.

Co-mutation modules capture the evolution and transmission patterns of SARS-CoV-2.

The rapid spread and huge impact of the COVID-19 pandemic caused by the emerging SARS-CoV-2 have driven large efforts for sequencing and analyzing the viral genomes. Mutation analyses have revealed that the virus keeps mutating and shows a certain degree of genetic diversity, which could result in the alteration of its infectivity and pathogenicity. Therefore, appropriate delineation of SARS-CoV-2 genetic variants enables us to understand its evolution and transmission patterns. By focusing on the nucleotides that co-substituted, we first identified 42 co-mutation modules that consist of at least two co-substituted nucleotides during the SARS-CoV-2 evolution. Then based on these co-mutation modules, we classified the SARS-CoV-2 population into 43 groups and further identified the phylogenetic relationships among groups based on the number of inconsistent co-mutation modules, which were validated with phylogenetic trees. Intuitively, we tracked tempo-spatial patterns of the 43 groups, of which 11 groups were geographic-specific. Different epidemic periods showed specific co-circulating groups, where the dominant groups existed and had multiple sub-groups of parallel evolution. Our work enables us to capture the evolution and transmission patterns of SARS-CoV-2, which can contribute to guiding the prevention and control of the COVID-19 pandemic. An interactive website for grouping SARS-CoV-2 genomes and visualizing the spatio-temporal distribution of groups is available at https://www.jianglab.tech/cmm-grouping/.

The potential of high-order features of routine blood test in predicting the prognosis of non-small cell lung cancer.

BACKGROUND: Numerous studies have demonstrated that the high-order features (HOFs) of blood test data can be used to predict the prognosis of patients with different types of cancer. Although the majority of blood HOFs can be divided into inflammatory or nutritional markers, there are still numerous that have not been classified correctly, with the same feature being named differently. It is an urgent need to reclassify the blood HOFs and comprehensively assess their potential for cancer prognosis. METHODS: Initially, a review of existing literature was conducted to identify the high-order features (HOFs) and classify them based on their calculation method. Subsequently, a cohort of patients diagnosed with non-small cell lung cancer (NSCLC) was established, and their clinical information prior to treatment was collected, including low-order features (LOFs) obtained from routine blood tests. The HOFs were then computed and their associations with clinical features were examined. Using the LOF and HOF data sets, a deep learning algorithm called DeepSurv was utilized to predict the prognostic risk values. The effectiveness of each data set's prediction was evaluated using the decision curve analysis (DCA). Finally, a prognostic model in the form of a nomogram was developed, and its accuracy was assessed using the calibration curve. RESULTS: From 1210 documents, over 160 blood HOFs were obtained, arranged into 110, and divided into three distinct categories: 76 proportional features, 6 composition features, and 28 scoring features. Correlation analysis did not reveal a strong association between blood features and clinical features; however, the risk value predicted by the DeepSurv LOF- and HOF-models is significantly linked to the stage. Results from DCA showed that the HOF model was superior to the LOF model in terms of prediction, and that the risk value predicted by the blood data model could be employed as a complementary factor to enhance the prognosis of patients. A nomograph was created with a C-index value of 0.74, which is capable of providing a reasonably accurate prediction of 1-year and 3-year overall survival for patients. CONCLUSIONS: This research initially explored the categorization and nomenclature of blood HOF, and proved its potential in lung cancer prognosis.

The Biological Role of Lncrna SNHG6 in Non-Small Cell Lung Cancer Cells Via Targeting P21.

Objective: To investigate the influence of long non-coding ribonucleic acid (lncRNA) small nucleolar RNA host gene 6 (SNHG6) on proliferation and apoptosis of non-small cell lung cancer (NSCLC) cells and to provide a theoretical basis for the clinical treatment of NSCLC. Methods: This study included 25 samples of NSCLC and 20 normal tissues as the experimental group. Fluorescence quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to detect lncRNA SNHG6 and p21. The relationship between lncRNA SNHG6 and p21 in NSCLC tissues was analyzed statistically. Colony formation assay and flow cytometry were used to determine the cell cycle distribution and cell apoptosis. Methyl thiazolyl tetrazolium (MTT) assay was used to determine cell proliferation, and Western blotting (WB) was used to measure the protein expression of p21. Results: The expression level of SNHG6 [(1.98 ± 0.23) vs. (4.46 ± 0.52)] (P < .01) was significantly higher, but p21 expression [(1.02 ± 0.23) vs. (0.33 ± 0.15)] (P < .01) was lower in the 25 cases of NSCLC tissues than in the control group. The expression of SNHG6 was negatively correlated with p21 (r2 = 0.2173, P = .0188). Transfection of SNHG6 small interfering RNA (siRNA) (si-SNHG6) in HCC827 and H1975 cells significantly reduced the level of SNHG6. The viability of BEAS-2B cells transfected with pcDNA-SNHG6 had a more robust proliferative and colony-forming capacity than normal cells (P < .01). Up-regulation of SNHG6 promoted the formation of the malignant phenotype and proliferative capacity of BEAS-2B cells. Proliferation, colony-forming capacity, and G1 phase of the cell cycle in HCC827 and H1975 cells were significantly repressed via influencing the apoptosis and p21 expression after the knockdown of SNHG6 (P < .01). Conclusion: Silencing lncRNA SNHG6 represses the proliferation and facilitates the apoptosis of NSCLC cells through regulating p21.

Developing pre-service teachers' computational thinking: a systematic literature review.

Recently, computational thinking (CT) has gained importance in education systems worldwide, specifically the CT training of pre-service teachers. This study conducted a systematic literature analysis (2011-2021) of 38 works on pre-service teachers' CT based on Web of Science, Science Direct, and Google Scholar databases. The results were as follows: (1) Six training methods were found, (2) CT training effectively improved pre-service teachers' CT, (3) A positive relationship was found between pre-service teachers' CT ability and the five factors affecting the ability, (4) A mode of training to improve CT ability of pre-service teachers and the relationship between CT ability and teaching methods were considered. This study suggested ideas for designing training modules of CT ability and a reference for realizing the best training effect. Finally, future research trends and a general model of training were presented as references for researchers, instructors, and policy makers to promote the CT of pre-service teachers.

Attractive Electron Delocalization Behavior of FeCoMoPB Amorphous Nanoplates for Highly Efficient Alkaline Water Oxidation.

The rational design of high-performance and cost-effective electrocatalysts to overcome the kinetically sluggish water oxidation reaction is a grand challenge in water electrolysis. Transitional metals with incompletely filled d orbitals are expected to have intrinsic electronic interaction to promote the reaction kinetics, however, the construction of multiple active sites is still a bottleneck problem. Here, inspired by an amorphous alloy design strategy with chemical tunability, a noble-metal-free FeCoMoPB amorphous nanoplate for superior alkaline water oxidation is developed. The achieved overpotentials at current densities of 10, 100, and 500 mA cm-2 are 239, 281, and 331 mV, respectively, while retaining a reliable stability of 48 h, outperforming most currently available electrocatalysts. Experimental and theoretical results reveal that the chemical complexity of the amorphous nanoplate leads to the formation of multiple active sites that is able to greatly lower the free energy of the rate-determining step during the water oxidation reaction. Moreover, the Mo element would result in an electron delocalization behavior to promote electron redistribution at its surrounding regions for readily donating and taking electrons. This amorphous alloy design strategy is expected to stimulate the development of more efficient electrocatalysts that is applicable in energy devices, such as metal-air batteries, fuel cells, and water electrolysis.

Dynamic 3D radiomics analysis using artificial intelligence to assess the stage of COVID-19 on CT images.

OBJECTIVE: To develop a dynamic 3D radiomics analysis method using artificial intelligence technique for automatically assessing four disease stages (i.e., early, progressive, peak, and absorption stages) of COVID-19 patients on CT images. METHODS: The dynamic 3D radiomics analysis method was composed of three AI algorithms (the lung segmentation, lesion segmentation, and stage-assessing AI algorithms) that were trained and tested on 313,767 CT images from 520 COVID-19 patients. This proposed method used 3D lung lesion that was segmented by the lung and lesion segmentation algorithms to extract radiomics features, and then combined with clinical metadata to assess the possible stage of COVID-19 patients using stage-assessing algorithm. Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were used to evaluate diagnostic performance. RESULTS: Of 520 patients, 66 patients (mean age, 57 years ± 15 [standard deviation]; 35 women), including 203 CT scans, were tested. The dynamic 3D radiomics analysis method used 30 features, including 27 radiomics features and 3 clinical features to assess the possible disease stage of COVID-19 with an accuracy of 90%. For the prediction of each stage, the AUC of stage 1 was 0.965 (95% CI: 0.934, 0.997), AUC of stage 2 was 0.958 (95% CI: 0.931, 0.984), AUC of stage 3 was 0.998 (95% CI: 0.994, 1.000), and AUC of stage 4 was 0.975 (95% CI: 0.956, 0.994). CONCLUSION: With high diagnostic performance, the dynamic 3D radiomics analysis using artificial intelligence could represent a potential tool for helping hospitals make appropriate resource allocations and follow-up of treatment response. KEY POINTS: • The AI segmentation algorithms were able to accurately segment the lung and lesion of COVID-19 patients of different stages. • The dynamic 3D radiomics analysis method successfully extracted the radiomics features from the 3D lung lesion. • The stage-assessing AI algorithm combining with clinical metadata was able to assess the four stages with an accuracy of 90%, a macro-average AUC of 0.975.

Microwave ablation treatment for medically inoperable stage I non-small cell lung cancers: long-term results.

OBJECTIVES: In the present study, we aim to show the results of microwave ablation (MWA) for medically inoperable stage I non-small cell lung cancers (NSCLCs) with long-term follow-up. METHODS: From Feb 2011 to Mar 2016, patients with histologically proven clinical stage I NSCLC were treated with CT-guided MWA and retrospectively analyzed. The primary end point was overall survival (OS). Secondary end points included disease-free survival (DFS), cancer-specific survival (CSS), and complications. RESULTS: A total of 105 patients with 105 lesions underwent MWA. The mean age was 70.7 years (range: 40-86 years), and the mean diameter of all lesions was 2.40 cm (range: 0.9-4.0 cm). Adenocarcinoma was the most common histological type (77, 73.3%), followed by squamous cell carcinomas (21, 20%) and undefined NSCLC (7, 6.7%). With a median follow-up of 54.8 months, the median DFS was 36.0 months, and 1-, 3-, and 5-year DFS rates were 89.5%, 49.4%, and 42.7%, respectively. The median CSS and OS were 89.8 and 64.2 months, respectively. The OS rate was 99% at 1 year, 75.6% at 3 years, and 54.1% at 5 years, while the CSS rates were 99%, 78.9%, and 60.9%, respectively. Patients with stage IB lesions had significant shorter DFS (22.3 months vs. undefined, HR: 11.5, 95%CI: 5.85-22.40) and OS (37.3 vs. 89.8 months, HR: 8.64, 95% CI: 4.49-16.60) than IA disease. CONCLUSION: MWA is a safe, effective, and potentially curative therapy for medically inoperable stage I NSCLC patients. KEY POINTS: • In this multicenter retrospective study which included 105 patients, we found the median overall survival (OS) was 64.2 months. The OS rate was 99% at 1 year, 75.6% at 3 years, and 54.1% at 5 years. • Procedures were technically successful and well tolerated in all patients. Most MWA complications were mild or moderate.

The association of chemical composition particularly the heavy metals with the oxidative potential of ambient PM2.5 in a megacity (Guangzhou) of southern China.

Atmospheric fine particulate matters (PM2.5) can cause adverse health effects through the generation of reactive oxygen species (ROS), which is normally characterized by the oxidative potential (OP). However, the particulate components that are mainly responsible for the ROS-induced OP remain controversial and warrant further investigation, especially in megacities where high exposure exists and particulate composition is complex. In this study, we measured the OP of PM2.5 using the dithiothreitol (DTT) assay with and without chelation of metals in a megacity in southern China, Guangzhou, in January and April. We explored the correlations between OP and various chemical components in PM2.5, including water-soluble ions, organic carbon (OC), elemental carbon (EC), and metal elements. There are strong correlations between OPDTTv (volume-normalized) and concentrations of PM2.5, OC, and EC, while the correlations between OPDTTm (mass-normalized) and mass-normalized water-soluble ions, OC, EC or metal elements are weak. The OP values with chelation were reduced by ∼90%, indicating that water-soluble heavy metals were the major contributors to OP of PM2.5 in Guangzhou. On the other hand, correlations between OPDTTm and OC improved significantly after the chelation of heavy metals, implying that OC explains the variance of OPDTTm although its contribution to OP is much smaller than that of heavy metals. We postulate that there might be synergetic effects between water-soluble heavy metals (which contribute most to OP) and OC (which explains the variance of OP) in ROS generation by PM2.5. The findings of the current study provide a better understanding on the critical components in PM2.5 and potential synergism that might be responsible for health effects in urban areas.

Global regulatory factor VeA upregulates the production of antitumor substances in endophytic Fusarium solani.

A number of studies have demonstrated that endophytic fungi have the potential to produce antitumor active substances with novel structures and significant activities. In our previous studies, we isolated a Fusarium strain from the stem of the medicinal plant Nothapodytes pittosporoides (Oliv.). In this study, we identified this strain as Fusarium solani and found that its crude extract has significant antitumor activity against human alveolar adenocarcinoma cells (A549). We overexpressed the global regulatory factor VeA in F. solani (VeAOE), resulting in a significant increase in antitumor activity. The MTT assay results showed that the inhibition rate of the VeAOE mutant extract on A549 cancer cells was significantly higher than that of the WT extract, as the IC50 decreased from 369.22 to 285.89 µg/mL, and the apoptosis ratio was significantly increased by approximately 4.86-fold. In VeAOE, accumulation of alkaloids, terpenoids, carboxylic acid derivatives, phenols and flavonoid metabolites with potential antitumor activity was significantly increased compared with WT based on metabolomic analysis. Additionally, transcriptome analysis found that the expression patterns of 48 genes related to antitumor activity were significantly changed in VeAOE, mainly involving glycosyl hydrolases, the Zn(2)-Cys(6) class, cytochrome P450 monooxygenase, 3-isopropylmalate dehydratase, and polyketide synthases. These results suggested that VeA mediated the antitumor activity of the metabolites in F. solani HB1-J1 by regulating multiple metabolic pathways.