TRPM8 overexpression suppresses hepatocellular carcinoma progression and improves survival by modulating the RTP3/STAT3 pathway.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) is a malignant tumour associated with high morbidity and mortality rates worldwide. Recently, TRPM8 was reported to play an important role in tumour progression. However, the precise role of TRPM8 in HCC remains unclear. In this study, we explored the expression levels, molecular functions and underlying mechanisms of TRPM8 in HCC. METHODS: Tissue samples were used to analyse the expression of TRPM8 to assess its diagnostic value for prognosis. Cell Counting Kit-8, EdU and colony formation assays were performed to evaluate the effects of TRPM8 on cell proliferation, whereas the Transwell assay was used to assess cell migration and invasion. The role of TRPM8 in vivo was evaluated using a mouse subcutaneous xenograft tumour model. We performed PPI network analyses to understand the possible mechanisms of TRPM8 action. RESULTS: TRPM8 expression was decreased in HCC tissues and was correlated with histological grade and poor patient prognosis. Functionally, TRPM8 repressed the proliferation and metastasis of HCC cells both in vitro and in vivo by modulating the RTP3/STAT3 signalling pathway. CONCLUSION: Our findings underscore the critical role of the TRPM8-RTP3-STAT3 axis in maintaining the malignant progression of HCC. Moreover, our study demonstrates that AD80 is involved in anti-tumour processes by upregulating the expression of TRPM8.

Development and characterization of a recombinant Senecavirus A expressing enhanced green fluorescent protein.

Introduction: Senecavirus A (SVA), belonging to the genus Senecavirus in the family Picornaviridae, is an emerging pathogen causing vesicular disease in pigs. The main clinical manifestations of SVA infection include high mortality in neonatal piglets, skin ulceration, and vesicular lesions. So far, there is no commercially available vaccines or drugs against SVA. Construction of SVA infectious clones carrying reporter genes will help understand the characteristics of SVA and promote vaccine development. Methods: In this study, we established a reverse genetics system for a local SVA isolate and used it to rescue a recombinant SVA, rSVA-eGFP, expressing the enhanced green fluorescent protein (eGFP) by inserting eGFP, GSG linker and the P2A sequence between 2A and 2B genes. Results: We found that rSVA-eGFP exhibited a high replication efficiency comparable to the parental virus, was able to express the eGFP reporter efficiently and stable in maintaining the reporter gene up to six rounds of serial passages in BHK-21 cells. In mice, rSVA-eGFP also showed similar replication kinetics and pathogenicity to the parental virus, both causing mild lung lesions. In addition, a high-throughput viral neutralization assay was developed using eGFP as a surrogate readout in a fluorescence-based direct titration (FBT) assay based on rSVA-eGFP, facilitating rapid and accurate determination of the neutralizing antibody (nAb) titers. Discussion: The successful establishment of an SVA reverse genetics system and the rescue of rSVA-eGFP would create a powerful tool for future studies of SVA replication mechanisms and pathogenicity as well as for antiviral development.

A self-powered photoelectrochemical aptasensor using 3D-carbon nitride and carbon-based metal-organic frameworks for high-sensitivity detection of tetracycline in milk and water.

Antibiotic residues have become a significant challenge in food safety, threatening both ecosystem integrity and human health. To combat this problem, we developed an innovative photo-powered, self-powered aptasensor that employs a novel carbon-doped three-dimensional graphitic carbon nitride (3D-CN) combined with a metal-organic framework composed of N-doped copper(I) oxide-carbon (Cu2O@C) skeletons. The 3D-CN serves as the photoanode, offering stable photocurrent production due to its three-dimensional open framework structure. The N-doped Cu2O@C acts as the photocathode, providing oxidation protection for the metal core and enhancing light absorption due to its metal-organic framework structure. A key feature of our work is exploiting the Fermi level difference between the n-type photoanode and p-type photocathode, which facilitates faster migration of photogenerated electrons toward the photocathode, thereby enhancing the sensor's self-powered effect. Experimental results reveal that upon aptamer loading, the sensor can linearly detect tetracycline (TC) within a range of 0.5 pmol/L to 300 nmol/L, with a detection limit as low as 0.13 pmol/L. It also demonstrates excellent selectivity, stability, and reproducibility, making it applicable to real samples such as milk and river water. Consequently, our research provides a highly efficient and sensitive method for monitoring TC in food, with significant practical implications and profound impacts on food safety.

Preoperative risk factors for prolonged length of stay after bullectomy: A single-center retrospective study.

Objective: Prolonged length of stay (LOS) increases the economic burden on patients, therefore, optimizing LOS is a critical clinical challenge for physicians. This study aims to examine the correlation between the postoperative LOS and surgery-related adverse events after bullectomy. We defined prolonged postoperative LOS after bullectomy and analyzed the preoperative risk factors linked to prolonged LOS. Methods: In this retrospective study, we analyzed patient data from thoracoscopic bullectomy performed at our hospital between January 2018 and December 2023. The receiver operating characteristic (ROC) curve was used to identify the optimal cut-off values defining prolonged LOS after bullectomy. It was then characterized as prolonged LOS. Patients were divided into prolonged and normal LOS groups based on their postoperative duration. Further, univariate and multivariate logistic regression analyses were performed to identify preoperative risk factors associated with prolonged postoperative LOS after bullectomy. Results: Among the 152 patients analyzed, binary logistic regression revealed a significant effect of surgery-related adverse events after bullectomy on the LOS (P < 0.001). A postoperative LOS exceeding 3 days was considered prolonged. Among the 152 patients, 38.2 % (58/152) experienced a prolonged LOS out of which 20.4 % (31/152) developed surgery-related adverse events. Multivariate regression analysis revealed that preoperative risk factors associated with prolonged LOS included age ≥60 years (OR = 3.052, 95%CI 1.226-7.586, P = 0.016), current smoking status (OR = 2.754, 95%CI 1.482-6.346, P = 0.025), and ASA grade 3 (OR = 4.783, 95%CI 2.356-9.131, P = 0.003). Conclusion: In summary, the postoperative length of stay beyond 3 days after bullectomy was considered prolonged. The preoperative risk factors associated with prolonged postoperative stays after bullectomy included age (over 60), current smoking, and grade 3 ASA. Therefore, quick identification and intervention in patients with these high-risk factors may promote rapid recovery.

A dual-scale fused hypergraph convolution-based hyperedge prediction model for predicting missing reactions in genome-scale metabolic networks.

Genome-scale metabolic models (GEMs) are powerful tools for predicting cellular metabolic and physiological states. However, there are still missing reactions in GEMs due to incomplete knowledge. Recent gaps filling methods suggest directly predicting missing responses without relying on phenotypic data. However, they do not differentiate between substrates and products when constructing the prediction models, which affects the predictive performance of the models. In this paper, we propose a hyperedge prediction model that distinguishes substrates and products based on dual-scale fused hypergraph convolution, DSHCNet, for inferring the missing reactions to effectively fill gaps in the GEM. First, we model each hyperedge as a heterogeneous complete graph and then decompose it into three subgraphs at both homogeneous and heterogeneous scales. Then we design two graph convolution-based models to, respectively, extract features of the vertices in two scales, which are then fused via the attention mechanism. Finally, the features of all vertices are further pooled to generate the representative feature of the hyperedge. The strategy of graph decomposition in DSHCNet enables the vertices to engage in message passing independently at both scales, thereby enhancing the capability of information propagation and making the obtained product and substrate features more distinguishable. The experimental results show that the average recovery rate of missing reactions obtained by DSHCNet is at least 11.7% higher than that of the state-of-the-art methods, and that the gap-filled GEMs based on our DSHCNet model achieve the best prediction performance, demonstrating the superiority of our method.

DGCPPISP: a PPI site prediction model based on dynamic graph convolutional network and two-stage transfer learning.

BACKGROUND: Proteins play a pivotal role in the diverse array of biological processes, making the precise prediction of protein-protein interaction (PPI) sites critical to numerous disciplines including biology, medicine and pharmacy. While deep learning methods have progressively been implemented for the prediction of PPI sites within proteins, the task of enhancing their predictive performance remains an arduous challenge. RESULTS: In this paper, we propose a novel PPI site prediction model (DGCPPISP) based on a dynamic graph convolutional neural network and a two-stage transfer learning strategy. Initially, we implement the transfer learning from dual perspectives, namely feature input and model training that serve to supply efficacious prior knowledge for our model. Subsequently, we construct a network designed for the second stage of training, which is built on the foundation of dynamic graph convolution. CONCLUSIONS: To evaluate its effectiveness, the performance of the DGCPPISP model is scrutinized using two benchmark datasets. The ensuing results demonstrate that DGCPPISP outshines competing methods in terms of performance. Specifically, DGCPPISP surpasses the second-best method, EGRET, by margins of 5.9%, 10.1%, and 13.3% for F1-measure, AUPRC, and MCC metrics respectively on Dset_186_72_PDB164. Similarly, on Dset_331, it eclipses the performance of the runner-up method, HN-PPISP, by 14.5%, 19.8%, and 29.9% respectively.

Association of metabolic syndrome and sarcopenia with all-cause and cardiovascular mortality: a prospective cohort study based on the NHANES.

Background: Metabolic syndrome (MetS) and sarcopenia (SP) have emerged as significant public health concerns in contemporary societies, characterized by shared pathophysiological mechanisms and interrelatedness, leading to profound health implications. In this prospective cohort study conducted within a US population, we aimed to examine the influence of MetS and SP on all-cause and cardiovascular mortality. Methods: This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) III for the years 1999-2006 and 2011-2018, and death outcomes were ascertained by linkage to National Death Index (NDI) records through December 31, 2019. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for all-cause and cardiovascular mortality. In addition, subgroup and sensitivity analyses were conducted to test the robustness of the results. Results: Over a median follow-up period of 13.3 years (95% CI: 12.8-13.8), 1714 deaths were observed. The groups characterized by MetS-/SP+, MetS+/SP-, and MetS+/SP+ exhibited higher all-cause mortality rates in comparison to the MetS-/SP- group, with the MetS+/SP+ group (HR 1.76, 95% CI: 1.37-2.25) displaying the highest all-cause mortality. Increased cardiovascular mortality was observed in the MetS+/SP- (HR 1.84, 95% CI: 1.24-2.72), and MetS+/SP+ groups (HR 2.39, 95% CI: 1.32-4.35) compared to the MetS-/SP- group, whereas it was not statistically significant in the MetS-/SP+ group. However, among males and individuals aged < 60, the presence of both MetS and SP (MetS+/SP+ group) was found to be significantly associated with a higher risk of all-cause and cardiovascular mortality. Conclusion: The coexistence of MetS and SP increased the risk of all-cause and cardiovascular mortality, particularly in males and in nonelderly populations. Individuals with either MetS or SP may require more careful management to prevent the development of other diseases and thereby reduce mortality.

The effect of intelligent management interventions in intensive care units to reduce false alarms: An integrative review.

Objective: In intensive care units (ICU), frequent false alarms from medical equipment can cause alarm fatigue among nurses, which might lead to delayed or missed responses and increased risk of adverse patient events. This review was conducted to evaluate the effectiveness of intelligent management interventions to reduce false alarms in ICU. Method: Following the framework of Whitmore and Knafl, the reviewers systematically searched six databases: PubMed, EMBASE, CINAHL, OVID, Cochrane Library, and Scopus, and studies included intelligent management of clinical alarms published in the English or Chinese language from the inception of each database to December 2022 were retrieved. The researchers used the PICOS framework to formulate the search strategy, developed keywords, screened literature, and assessed the studies' quality using the Joanna Briggs Institute-Meta-Analysis of Statistics, Assessment, and Review Instrument (JBI-MAStARI). The review was preregistered on PROSPERO (CRD42023411552). Results: Seven studies met the inclusion criteria. The results showed that different interventions for intelligent management of alarms were beneficial in reducing the number of false alarms, the duration of alarms, the response time to important alarms for nurses, and the alarm fatigue levels among nurses. Positive results were found in practice after the application of the novel alarm management approaches. Conclusion: Intelligent management intervention may be an effective way to reduce false alarms. The application of systems or tools for the intelligent management of clinical alarms is urgent in hospitals. To ensure more effective patient monitoring and less distress for nurses, more alarm management approaches combined with artificial intelligence will be needed in the future to enable accurate identification of critical alarms, ensure nurses are responding accurately to alarms, and make a real difference to alarm-ridden healthcare environments.

Topical antimitotic treatments for plantar warts are more beneficial: A Bayesian network meta-analysis of randomized controlled trials.

BACKGROUND: Plantar warts are common infectious cutaneous growths causing severe physiological and psychological discomforts in patients and heaving global financial burdens. However, paucity of clear-cut guidelines for plantar warts, selecting appropriate treatments for plantar warts remains challenging. The objective of the study is to evaluate the efficacy and safety of common treatments for plantar warts. METHODS: PubMed, EMbase, and The Cochrane Library were searched from inception to March 1, 2023 for randomized controlled trials (RCTs) of plantar warts. The primary outcome (complete response) and secondary outcome (recurrence and pain) were extracted and combined using Bayesian network meta-analysis (NMA) with random-effect and fixed-effect models. RESULTS: Totally, 33 RCTs were included in the systematic review and quantitative NMA. In NMA of complete response, topical application of 1% cantharidin, 20% podophylotoxin, 30% salicylic acid (CPS), microneedles plus bleomycin (MNB), and intralesional bleomycin injection (INB) were the only three treatments significantly superior to no treatment (NT) and CPS was of the highest possibility to be the top-ranked treatment (SUCRA = 0.9363). However, traditional warts treatments, salicylic acid (SA) and cryotherapy were not superior to NT. CONCLUSIONS: The NMA has produced evidence for using CPS, MNB, and INB, which are all topical antimitotic treatments, to improve the management of plantar warts. The classic treatment modalities for plantar warts, including SA and cryotherapy, may play a less important role in the clinical practice of plantar warts.

Dual-plasmonic Au@Cu7S4 yolk@shell nanocrystals for photocatalytic hydrogen production across visible to near infrared spectral region.

Near infrared energy remains untapped toward the maneuvering of entire solar spectrum harvesting for fulfilling the nuts and bolts of solar hydrogen production. We report the use of Au@Cu7S4 yolk@shell nanocrystals as dual-plasmonic photocatalysts to achieve remarkable hydrogen production under visible and near infrared illumination. Ultrafast spectroscopic data reveal the prevalence of long-lived charge separation states for Au@Cu7S4 under both visible and near infrared excitation. Combined with the advantageous features of yolk@shell nanostructures, Au@Cu7S4 achieves a peak quantum yield of 9.4% at 500 nm and a record-breaking quantum yield of 7.3% at 2200 nm for hydrogen production in the absence of additional co-catalysts. The design of a sustainable visible- and near infrared-responsive photocatalytic system is expected to inspire further widespread applications in solar fuel generation. In this work, the feasibility of exploiting the localized surface plasmon resonance property of self-doped, nonstoichiometric semiconductor nanocrystals for the realization of wide-spectrum-driven photocatalysis is highlighted.

Developing a theory-driven framework for a web-based intervention to improve transition in childhood cancer survivors: a protocol of realist synthesis.

BACKGROUNDS AND PURPOSE: Childhood cancer survivors (CCSs) who transition through adolescence and enter young adulthood may suffer psychological, cognitive, social, fertility, and sexual issues and concerns. There is an urgent need for comprehensive intervention strategies to improve the transition of CCSs. Web-based technologies are gaining momentum as a new mechanism to provide healthcare and education for adolescents. However, previous frameworks have been limited in their effectiveness in explaining web-based interventions.This realist synthesis aims to synthesise current evidence on transition of CCSs to develop a framework for web-based interventions. The framework can foster understanding of the integrity of web-based intervention implementation chain, examine which mechanistic factors will be triggered by web-based interventions, note and examine the flows, blockages and points of contention in the implementation, to refine web-based interventions. METHOD AND ANALYSIS: A realist synthesis that adheres to the Realist and Meta-narrative Evidence Syntheses-Evolving Standard will be used. Studies will be identified through PubMed, Web of Science, EMBASE, PsycINFO, CINAHL, Ovid and Cochrane Library from the period of January 2005 to May 2023. We will also search the reference lists provided in relevant studies and reviews. Articles will be screened based on two principles: (1) Relevance: does the research address the initial programme theory? (2) Rigour: whether a particular inference drawn by the original researcher has sufficient weight to make a methodologically credible contribution to the test of the initial programme theory. No restrictions regarding the design or language of publication will be considered. ETHICS AND DISSEMINATION: As a review, ethical approval is not required. The results from this study will be presented at international conferences and disseminated through peer-reviewed publications. Patients and the public will be involved in the dissemination plans.

Development and usability of a Mobile Interactive Application (VCPW) for Vascular Crisis Prewarning after Skin Flap Transplantation.

Background: In microsurgical tissue transfer, skin flap transplantation is frequently used to heal the surface of a wound. Effective microcirculation surveillance of the skin flap is crucial. However, with traditional monitoring methods-that is, clinical observation-vascular crisis can still occur, thereby impairing postoperative recovery. A smartphone application is required to assist health care professionals in the standardized collection of flap perfusion parameters for flap management. Methods: The Vascular Crisis Prewarning Application was created using a design science research methodology that prioritizes users and problems. The system usability scale was used to assess the application's usability among medical practitioners. The application was used at the clinic from December 2020 to September 2022. The unplanned return to the operating room, time to diagnose vascular crisis, and flap survival rate were compared with and without the application. Results: The application consisted of 5 modules: patient addition and basic information entry, flap labeling, flap observation, crisis warning, and case archiving. The average rating for the application's usability among medical practitioners was 97.95 score (SD 2.36). With the application, the time to detect vascular crisis reduced from 26.71 to 16.26 h (P < 0.001), the unplanned return to the operation room increased from 8.18% to 10.24% (P = 0.587), and the flap survival rate went from 94.55% to 99.21% (P = 0.083). Conclusions: An easy-to-use flap perfusion monitoring and prewarning application for medical practitioners was produced using a user-centered development method. The application provided a more standardized and accurate platform for data collection in flap management and reduced the time to detect vascular crisis. Larger cohort studies are required in the future to better assess the full potential of the application.

Extraocular muscle volume index at the orbital apex with optic neuritis: a combined parameter for diagnosis of dysthyroid optic neuropathy.

OBJECTIVES: To evaluate the diagnostic performance of the extraocular muscle volume index at the orbital apex (AMI) and the signal intensity ratio (SIR) of the optic nerve in dysthyroid optic neuropathy (DON). METHODS: Clinical data and magnetic resonance imaging were collected retrospectively from 63 Graves' ophthalmopathy patients, including 24 patients with DON and 39 without DON. The volume of these structures was obtained by reconstructing their orbital fat and extraocular muscles. The SIR of the optic nerve and axial length of eyeball were also measured. The posterior 3/5 of the retrobulbar space volume was used as the orbital apex to compare parameters in patients with or without DON. Area under the receiver operating characteristic curve (AUC) analysis was used to select the morphological and inflammatory parameters with the highest diagnostic value. A logistic regression was performed to identify the risk factors of DON. RESULTS: One hundred twenty-six orbits (35 with DON and 91 without DON) were analyzed. Most of the parameters in DON patients were significantly higher than in non-DON patients. However, the SIR 3 mm behind the eyeball of the optic nerve and AMI had the highest diagnostic value in these parameters and are independent risk factors of DON by stepwise multivariate logistic regression analysis. Combining AMI and SIR had a higher diagnostic value than a single index. CONCLUSIONS: Combining AMI with SIR 3 mm behind the eyeball's orbital nerve can be a potential parameter for diagnosing DON. CLINICAL RELEVANCE STATEMENT: The present study provided a quantitative index based on morphological and signal changes to assess the DON, allowing clinicians and radiologists to monitor DON patients timely. KEY POINTS: The extraocular muscle volume index at the orbital apex (AMI) has excellent diagnostic performance for dysthyroid optic neuropathy. A signal intensity ratio (SIR) of 3 mm behind the eyeball has a higher AUC compared to other slices. Combining AMI and SIR has a higher diagnostic value than a single index.

High-speed scanless entire bandwidth mid-infrared chemical imaging.

Mid-infrared spectroscopy probes molecular vibrations to identify chemical species and functional groups. Therefore, mid-infrared hyperspectral imaging is one of the most powerful and promising candidates for chemical imaging using optical methods. Yet high-speed and entire bandwidth mid-infrared hyperspectral imaging has not been realized. Here we report a mid-infrared hyperspectral chemical imaging technique that uses chirped pulse upconversion of sub-cycle pulses at the image plane. This technique offers a lateral resolution of 15 µm, and the field of view is adjustable between 800 µm × 600 µm to 12 mm × 9 mm. The hyperspectral imaging produces a 640 × 480 pixel image in 8 s, which covers a spectral range of 640-3015 cm-1, comprising 1069 wavelength points and offering a wavenumber resolution of 2.6-3.7 cm-1. For discrete frequency mid-infrared imaging, the measurement speed reaches a frame rate of 5 kHz, the repetition rate of the laser. As a demonstration, we effectively identified and mapped different components in a microfluidic device, plant cell, and mouse embryo section. The great capacity and latent force of this technique in chemical imaging promise to be applied to many fields such as chemical analysis, biology, and medicine.

TRPM7 mediates endoplasmic reticulum stress and ferroptosis in sepsis-induced myocardial injury.

Transient receptor potential melastatin 7 (TRPM7), a non-selective cation channel, was significantly upregulated in the blood of patients with sepsis. This study focuses on the preliminary exploration of the probable regulatory mechanism of TRPM7 in sepsis-induced myocardial injury (SIMI). HL-1 cardiac muscle cell line was treated with lipopolysaccharide (LPS) to mimic SIMI in vitro, and TRPM7 level was assessed. The impacts of TRPM7 knockdown on cellular inflammation response, oxidative stress, apoptosis, endoplasmic reticulum (ER) stress, and ferroptosis were identified. In order to explore the mechanism, ER stress agonist tunicamycin (TM) or ferroptosis inducer erastin was applied to treat HL-1 cells. The influences of TM and erastin on the aforementioned aspects were evaluated. TRPM7 was elevated in response to LPS stimulation, and its knockdown reduced the secretion of inflammatory factors and oxidative stress degree. Moreover, TRPM7 knockdown significantly suppressed cell apoptosis, ER stress, and ferroptosis. TM and erastin reversed the functions of TRPM7 knockdown, indicating ER stress and ferroptosis mediated in the regulation of TRPM7. This research proposes the possibility of TRPM7 as a marker or target for SIMI, and provides theoretical support for follow-up research.

Bilingual Bidirectional Stretchable Self-Healing Neuristors with Proprioception.

The coexistence and interaction of excitatory and inhibitory neurotransmitters at biological synapses enable bilingual communication, serving as a physiological foundation for organism adaptation, internal stability, and regulation of behavior and emotions in mammals. Neuromorphic electronics are expected to emulate the bilingual functions of the biological nervous system for artificial neurorobotics and neurorehabilitation. Here, we have proposed a bilingual bidirectional artificial neuristor array, which utilizes ion migration and electrostatic coupling properties between intrinsically stretchable and self-healing poly(urea-urethane) elastomer and carbon nanotube electrodes, realized by van der Waals integration. The neuristor exhibits depression or potentiation behaviors in response to the same stimulus in different operational phases and achieves a four-quadrant information-processing capability. These properties make it possible to simulate complex neuromorphic processes, which involve bilingual bidirectional responses, such as withdrawal or addiction responses, and array-based automated refresh. Furthermore, the neuristor array is a self-healing neuromorphic electronic device that can function effectively even under 50% mechanical strain and can recover operation voluntarily within 2 h after experiencing mechanical injury. Additionally, the bilingual bidirectional stretchable self-healing neuristor can emulate coordinated neural signal transmission from the motor cortex to muscles and integrate proprioception through strain modulation, similar to the biological muscle spindle. The properties, structure, operation mechanisms, and neurologically integrated functions of the proposed neuristor signify an advancement in neuromorphic electronics for next-generation neurorehabilitation and neurorobotics.

Pro- and eukaryotic keystone taxa as potential bio-indicators for the water quality of subtropical Lake Dongqian.

The microbial community plays an important role in the biogeochemical cycles in water aquatic ecosystems, and it is regulated by environmental variables. However, the relationships between microbial keystone taxa and water variables, which play a pivotal role in aquatic ecosystems, has not been clarified in detail. We analyzed the seasonal variation in microbial communities and co-occurrence network in the representative areas taking Lake Dongqian as an example. Both pro- and eukaryotic community compositions were more affected by seasons than by sites, and the prokaryotes were more strongly impacted by seasons than the eukaryotes. Total nitrogen, pH, temperature, chemical oxygen demand, dissolved oxygen and chlorophyll a significantly affected the prokaryotic community, while the eukaryotic community was significantly influenced by total nitrogen, ammonia, pH, temperature and dissolved oxygen. The eukaryotic network was more complex than that of prokaryotes, whereas the number of eukaryotic keystone taxa was less than that of prokaryotes. The prokaryotic keystone taxa belonged mainly to Alphaproteobacteria, Betaproteobacteria, Actinobacteria and Bacteroidetes. It is noteworthy that some of the keystone taxa involved in nitrogen cycling are significantly related to total nitrogen, ammonia, temperature and chlorophyll a, including Polaromonas, Albidiferax, SM1A02 and Leptolyngbya so on. And the eukaryotic keystone taxa were found in Ascomycota, Choanoflagellida and Heterophryidae. The mutualistic pattern between pro- and eukaryotes was more evident than the competitive pattern. Therefore, it suggests that keystone taxa could be as bio-indicators of aquatic ecosystems.

Stepwise rapid electrolytic synthesis of graphene oxide for efficient adsorption of organic pollutants.

Graphene oxide (GO) has been widely used in energy devices, biomedicine, environmental protection, composite materials and other fields. Hummers' method is currently one of the most powerful strategies for the preparation of GO. However, many deficiencies, including severe environmental pollution, operation safety issues and low oxidation efficiency are major obstacles for the large-scale green synthesis of GO. Here, we report a stepwise electrochemical method for the fast preparation of GO using spontaneous persulfate intercalation followed by anodic electrolytic oxidation. Such a step-by-step process not only avoids uneven intercalation and insufficient oxidation in traditional one-pot methods, but also largely shortens the overall duration by two orders of magnitude. In particular, the oxygen content of the obtained GO is as high as 33.7 at%, almost double that from Hummers' method (17.4 at%). The abundant surface functional groups render this GO an excellent adsorption platform for methylene blue with an adsorption capacity of 358 mg g-1, 1.8-fold higher than conventional GO.

Artificial Intelligence-Based Psoriasis Severity Assessment: Real-world Study and Application.

BACKGROUND: Psoriasis is one of the most frequent inflammatory skin conditions and could be treated via tele-dermatology, provided that the current lack of reliable tools for objective severity assessments is overcome. Psoriasis Area and Severity Index (PASI) has a prominent level of subjectivity and is rarely used in real practice, although it is the most widely accepted metric for measuring psoriasis severity currently. OBJECTIVE: This study aimed to develop an image-artificial intelligence (AI)-based validated system for severity assessment with the explicit intention of facilitating long-term management of patients with psoriasis. METHODS: A deep learning system was trained to estimate the PASI score by using 14,096 images from 2367 patients with psoriasis. We used 1962 patients from January 2015 to April 2021 to train the model and the other 405 patients from May 2021 to July 2021 to validate it. A multiview feature enhancement block was designed to combine vision features from different perspectives to better simulate the visual diagnostic method in clinical practice. A classification header along with a regression header was simultaneously applied to generate PASI scores, and an extra cross-teacher header after these 2 headers was designed to revise their output. The mean average error (MAE) was used as the metric to evaluate the accuracy of the predicted PASI score. By making the model minimize the MAE value, the model becomes closer to the target value. Then, the proposed model was compared with 43 experienced dermatologists. Finally, the proposed model was deployed into an app named SkinTeller on the WeChat platform. RESULTS: The proposed image-AI-based PASI-estimating model outperformed the average performance of 43 experienced dermatologists with a 33.2% performance gain in the overall PASI score. The model achieved the smallest MAE of 2.05 at 3 input images by the ablation experiment. In other words, for the task of psoriasis severity assessment, the severity score predicted by our model was close to the PASI score diagnosed by experienced dermatologists. The SkinTeller app has been used 3369 times for PASI scoring in 1497 patients from 18 hospitals, and its excellent performance was confirmed by a feedback survey of 43 dermatologist users. CONCLUSIONS: An image-AI-based psoriasis severity assessment model has been proposed to automatically calculate PASI scores in an efficient, objective, and accurate manner. The SkinTeller app may be a promising alternative for dermatologists' accurate assessment in the real world and chronic disease self-management in patients with psoriasis.