Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4.

Large language models (LLMs) are seen to have tremendous potential in advancing medical diagnosis recently, particularly in dermatological diagnosis, which is a very important task as skin and subcutaneous diseases rank high among the leading contributors to the global burden of nonfatal diseases. Here we present SkinGPT-4, which is an interactive dermatology diagnostic system based on multimodal large language models. We have aligned a pre-trained vision transformer with an LLM named Llama-2-13b-chat by collecting an extensive collection of skin disease images (comprising 52,929 publicly available and proprietary images) along with clinical concepts and doctors' notes, and designing a two-step training strategy. We have quantitatively evaluated SkinGPT-4 on 150 real-life cases with board-certified dermatologists. With SkinGPT-4, users could upload their own skin photos for diagnosis, and the system could autonomously evaluate the images, identify the characteristics and categories of the skin conditions, perform in-depth analysis, and provide interactive treatment recommendations.

Multifunctional bacterial cellulose-bentonite@polyethylenimine composite membranes for enhanced water treatment: Sustainable dyes and metal ions adsorption and antibacterial properties.

Developing multifunctional materials for water treatment remains a significant challenge. Bacterial cellulose (BC) holds immense potential as an adsorbent with high pollutant-binding capacity, hydrophilicity, and biosafety. In this study, N-acetylglucosamine was used as a carbon source to ferment BC, incorporating amide bonds in situ. Bentonite, renowned for its adsorption properties, was added to the culture medium, resulting in BC-bentonite composite membranes via a one-step fermentation process. Polyethyleneimine (PEI) was crosslinked with amide bonds on the membrane via glutaraldehyde through Schiff base reactions to enhance the performance of the composite membrane. The obtained membrane exhibited increased hydrophilicity, enhanced active adsorption sites, and enlarged specific surface area. It not only physically adsorbed contaminants through its unique structure but also effectively captured dye molecules (Congo red, Methylene blue, Malachite green) via electrostatic interactions. Additionally, it formed stable complexes with metal ions (Cd²âº, Pb²âº, Cu²âº) through coordination and effectively adsorbed their mixtures. Moreover, the composite membrane demonstrated the broad-spectrum antibacterial activity, effectively inhibiting the growth of tested bacteria. This study introduces an innovative method for fabricating composite membranes as adsorbents for complex water pollutants, showing significant potential for long-term wastewater treatment of organic dyes, heavy metal ions, and pathogens.

Various functions of detoxification enzymes against insecticides in Nilaparvata lugens selected by toxicity assays and RNAi methods.

The brown planthopper (BPH), Nilaparvata lugens is a devastating agricultural pest of rice, and they have developed resistance to many pesticides. In this study, we assessed the response of BPH nymphs to nitenpyram, imidacloprid, and etofenprox using contact and dietary bioassays, and investigated the underlying functional diversities of BPH glutathione-S-transferase (GST), carboxylesterase (CarE) and cytochrome P450 monooxygenase (P450) against these insecticides. Both contact and ingestion toxicity of nitenpyram to BPH were significantly higher than either imidacloprid or etofenprox. Under the LC50 concentration of each insecticide, they triggered a distinct response for GST, CarE, and P450 activities, and each insecticide induced at least one detoxification enzyme activity. These insecticides almost inhibited the expression of all tested GST, CarE, and P450 genes in contact bioassays but induced the transcriptional levels of these genes in dietary bioassays. Silencing of NlGSTD2 expression had the greatest effect on BPH sensitivity to nitenpyram in contact test and imidacloprid in dietary test. The sensitivities of BPH to insecticide increased the most in the contact test was etofenprox after silencing of NlCE, while the dietary test was nitenpyram. Knockdown of NlCYP408A1 resulted in BPH sensitivities to insecticide increasing the most in the contact test was nitenpyram, while the dietary test was imidacloprid. Taken together, these findings reveal that NlGSTD2, NlCE, and NlCYP408A1 play an indispensable role in the detoxification of the contact and ingestion toxicities of different types of insecticides to BPH, which is of great significance for the development of new strategies for the sucking pest control.

Based on molecular docking and real-time PCR technology, the two-component system Bae SR was investigated on the mechanism of drug resistance in CRAB.

This study aimed to explore the role of the two-component system Bae SR in the mechanism of drug resistance in carbapenem-resistant A. baumannii (CRAB) using molecular docking and real-time polymerase chain reaction (PCR). The two-component system Bae SR of Acinetobacter baumannii was subjected to molecular docking with imipenem, meropenem, and levofloxacin. Antibacterial assays and fluorescence quantitative PCR were used to explore protein-ligand interactions and molecular biological resistance mechanisms related to CRAB. The analysis of the two-component system in A. baumannii revealed that imipenem exhibited the highest docking energy in Bae S at - 5.81 kcal/mol, while the docking energy for meropenem was - 4.92 kcal/mol. For Bae R, imipenem had a maximum docking energy of - 4.28 kcal/mol, compared with - 4.60 kcal/mol for meropenem. The highest binding energies for Bae S-levofloxacin and Bae R-levofloxacin were - 3.60 and - 3.65 kcal/mol, respectively. All imipenem-resistant strains had minimum inhibitory concentration (MIC) values of 16 µg/mL, whereas levofloxacin-resistant strains had MIC values of 8 µg/mL. The time-sterilization curve showed a significant decrease in bacterial colony numbers at 2 h under the action of 8 µg/mL imipenem, indicating antibacterial effects. In contrast, levofloxacin did not exhibit any antibacterial activity. Fluorescence quantitative PCR results revealed significantly increased relative expression levels of bae S and bae R genes in the CRAB group, which were 2 and 1.5 times higher than those in the CSAB group, respectively, with statistically significant differences. Molecular docking in this study found that the combination of Bae SR and carbapenem antibiotics (imipenem, meropenem) exhibited stronger affinity and stability compared with levofloxacin. Moreover, the overexpression of the two-component system genes in carbapenem-resistant A. baumannii enhanced its resistance to carbapenem, providing theoretical and practical insights into carbapenem resistance in respiratory tract infections caused by A. baumannii.

Development and Validation of Data-Level Innovation Data-Balancing Machine Learning Models for Predicting Optimal Implantable Collamer Lens Size and Postoperative Vault.

INTRODUCTION: There are only four sizes of implantable collamer lens (ICL) available for selection, which cannot completely fit all patients as a result of the discontinuity of ICL sizes. Sizing an optimal ICL and predicting postoperative vault are still unresolved problems. This study aimed to develop and validate innovative data-level data-balancing machine learning-based models for predicting ICL size and postoperative vault. METHODS: The patients were randomly assigned to training and internal validation sets in a 4:1 ratio. Feature selection was performed using analysis of variance (ANOVA) and Kruskal-Wallis feature importance methods. Traditional linear regression model and machine learning-based models were used. The accuracy of models was assessed using the area under the curve (AUC) and confusion matrix. RESULTS: A total of 564 patients (1127 eyes) were eligible for this study, consisting of 808 eyes in the training set, 202 eyes in the internal validation set, and 117 eyes in the external validation set. Compared with the traditional linear regression method, the machine learning model bagging tree showed the best performance for ICL size selection, with an accuracy of 84.5% (95% confidence interval (CI) 83.2-85.8%), and the AUC ranged from 0.88 to 0.99; the prediction accuracy of 12.1 mm and 13.7 mm ICL sizes was improved by 49% and 59%, respectively. The bagging tree model achieved the best accuracy [90.2%, (95% CI 88.9-91.5%)] for predicting the postoperative vault, and the AUC ranged from 0.90 to 0.94. The prediction accuracies of internal and external validation dataset for ICL sizing were 82.2% (95% CI 81.1-83.3%) and 82.1% (95% CI 81.1-83.1%), respectively. CONCLUSIONS: The innovative data-level data balancing-based machine learning model can be used to predict ICL size and postoperative vault more accurately, which can assist surgeons in choosing optimal ICL size, thus reducing risks of postoperative complications and secondary surgery.

A mitochondria-targeted far-red AIE fluorescent probe for distinguishing between mitophagy and ferroptosis in cancer cells.

A mitochondria-targeted far-red fluorescent probe LY-1 with AIE character was formulated to track cell viscosity alterations with excellent sensitivity and selectivity, which was used to discriminate between mitophagy and ferroptosis in cancer cells. Probe LY-1 is expected to be an effective vehicle for the diagnosis of mitochondrial viscosity relevant diseases.

METTL3-mediated m6A modification of SIRT1 mRNA inhibits progression of endometriosis by cellular senescence enhancing.

BACKGROUND: Endometriosis (EMs), the ectopic planting of functional endometrium outside of the uterus, is a leading cause of infertility and pelvic pain. As a fundamental mRNA modification, N6-methyladenosine (m6A) participates in various pathological processes. However, the role of m6A RNA modification in endometriosis remains unclear. The present study explores METTL3-mediated m6A modification and the mechanisms involved in endometriosis. METHODS: The dominant m6A regulators in EMs were analysed using RT‒PCR. Candidate targets and possible mechanisms of METTL3 were assessed by m6A-mRNA epitranscriptomic microarray and RNA sequencing. A primary ESCs model was employed to verify the effect of METTL3 on m6A modification of SIRT1 mRNA, and the mechanism was elucidated by RT‒PCR, Western blotting, MeRIP, and RIP assays. CCK-8 viability assays, Transwell invasion assays, EdU proliferation assays, wound healing migration assays, and senescence-associated ß-galactosidase staining were performed to illuminate the potential biological mechanism of METTL3 and SIRT1 in ESCs in vitro. An in vivo PgrCre/ + METTL3 -/- female homozygous mouse model and a nude mouse xenograft model were employed to further investigate the physiologic consequences of METTL3-mediated m6A alteration on EMs. RESULTS: Our data show that decreased METTL3 expression significantly downregulates m6A RNA methylation levels in ESCs. Silencing m6A modifications mediated by METTL3 accelerates ESCs viability, proliferation, migration, and invasion in vitro. The m6A reader protein YTHDF2 binds to m6A modifications to induce the degradation of SIRT1 mRNA. SIRT1/FOXO3a signalling pathway activation is subsequently inhibited, promoting the cellular senescence of ESCs and inhibiting the ectopic implantation of ESCs in vitro and in vivo. CONCLUSIONS: Our findings demonstrate that METTL3-mediated m6A methylation epigenetically regulates the ectopic implantation of ESCs, resulting in the progression of endometriosis. Our study establishes METTL3-YTHDF2-SIRT1/FOXO3a as a critical axis and potential mechanism in endometriosis.

Association between choriocapillaris perfusion and axial elongation in children using defocus incorporated multiple segments (DIMS) spectacle lenses.

PURPOSE: To investigate choroidal and ocular biological variables that influence axial length (AL) elongation in children wearing defocused incorporated multiple segments (DIMS) spectacle lenses. METHODS: This cohort study included 106 myopic children aged 7-14 years with a 1-year follow-up. Participants were divided into two groups according to the increase in AL in one year: rapid (>0.2 mm) and slow (≤0.2 mm) axial elongation groups. Cycloplegic autorefraction and AL were measured at baseline and after 6 and 12 months. The area of choriocapillaris flow voids (FVs) and choroidal thickness (ChT) at baseline were measured. RESULTS: Univariate linear regression analysis showed that AL elongation were significantly associated with the FVs area (standardised ß = 0.198, P < 0.05) and age (standardised ß = -0.201, P < 0.05). Multiple linear regression showed that the FVs area, age, and average K reading were associated with AL elongation. Multiple logistic regression analyses showed that greater degrees of myopia and larger FVs areas were risk factors for rapid axial elongation, while older age, large pupil diameter and steeper cornea were protective factors. In estimating axial elongation, the FVs area alone demonstrated an area under the curve (AUC) of 0.672 (95% CI, 0.569-0.775, P < 0.01), and that of FVs area and other ocular variables was 0.788 (95% CI, 0.697-0.878, P < 0.001). CONCLUSION: Larger choriocapillaris FVs area at baseline may help to predict axial elongation in myopic eyes. The association between FVs area and axial elongation should be taken into consideration in further myopic cohort studies.

The effects and underlying mechanism of extracorporeal shockwave therapy on fracture healing.

The clinical efficacy of ESWT in treating bone non union has been widely recognized, but the biological mechanism of ESWT promoting bone non union healing is still unclear. ESWT can make old callus micro fracture through mechanical conduction, form subperiosteal hematoma, promote the release of bioactive factors, reactivate the fracture healing mechanism, rebalance the activities of osteoblasts and osteoclast, promote the angiogenesis of fracture site, and accelerate the healing of bone nonunion.Over recent years, great efforts have been made by both scientists and clinicians to explore the underlying mechanism behind the healing effect of ESWT on bone fractures. In this review, we introduced the growth factors during osteogenesis induced by ESWT hoping to provide new insights in the clinical use of ESWT.

Promotion of BST2 expression by the transcription factor IRF6 affects the progression of endometriosis.

Background: Endometriosis (EM) is a benign, multifactorial, immune-mediated inflammatory disease that is characterized by persistent activation of the NF-κB signaling pathway and some features of malignancies, such as proliferation and lymphangiogenesis. To date, the pathogenesis of EM is still unclear. In this study, we investigated whether BST2 plays a role in the development of EM. Methods: Bioinformatic analysis was performed with data from public databases to identify potential candidate targets for drug treatment. Experiments were conducted at the cell, tissue, and mouse EM model levels to characterize the aberrant expression patterns, molecular mechanisms, biological behaviors of endometriosis as well as treatment outcomes. Results: BST2 was significantly upregulated in ectopic endometrial tissues and cells compared with control samples. Functional studies indicated that BST2 promoted proliferation, migration, and lymphangiogenesis and inhibited apoptosis in vitro and in vivo. The transcription factor (TF) IRF6 induced high BST2 expression by directly binding the BST2 promoter. The underlying mechanism by which BST2 functions in EM was closely related to the canonical NF-κB signaling pathway. New lymphatic vessels may serve as a channel for the infiltration of immune cells into the endometriotic microenvironment; these immune cells further produce the proinflammatory cytokine IL-1ß, which in turn further activates the NF-κB pathway to promote lymphangiogenesis in endometriosis. Conclusion: Taken together, our findings provide novel insight into the mechanism by which BST2 participates in a feedback loop with the NF-κB signaling pathway and reveal a novel biomarker and potential therapeutic target for endometriosis.

Cocaine induces locomotor sensitization through a dopamine-dependent VTA-mPFC-FrA cortico-cortical pathway in male mice.

As a central part of the mammalian brain, the prefrontal cortex (PFC) has been implicated in regulating cocaine-induced behaviors including compulsive seeking and reinstatement. Although dysfunction of the PFC has been reported in animal and human users with chronic cocaine abuse, less is known about how the PFC is involved in cocaine-induced behaviors. By using two-photon Ca2+ imaging to simultaneously record tens of intact individual networking neurons in the frontal association cortex (FrA) in awake male mice, here we report that a systematic acute cocaine exposure decreased the FrA neural activity in mice, while the chemogenetic intervention blocked the cocaine-induced locomotor sensitization. The hypoactivity of FrA neurons was critically dependent on both dopamine transporters and dopamine transmission in the ventromedial PFC (vmPFC). Both dopamine D1R and D2R neurons in the vmPFC projected to and innervated FrA neurons, the manipulation of which changed the cocaine-induced hypoactivity of the FrA and locomotor sensitization. Together, this work demonstrates acute cocaine-induced hypoactivity of FrA neurons in awake mice, which defines a cortico-cortical projection bridging dopamine transmission and cocaine sensitization.

Weighted gene co-expression network analysis revealed the key pathways and hub genes of potassium regulating cotton root adaptation to salt stress.

Soil salinization is one of the main abiotic stresses affecting cotton yield and planting area. Potassium application has been proven to be an important strategy to reduce salt damage in agricultural production. However, the mechanism of potassium regulating the salt adaptability of cotton has not been fully elucidated. In the present research, the appropriate potassium application rate for alleviating salt damage of cotton based on different K+/Na+ ratios we screened, and a gene co-expression network based on weighted gene co-expression network analysis (WGCNA) using the transcriptome data sets treated with CK (0 mM NaCl), S (150 mM NaCl), and SK8 (150 mM NaCl + 9.38 mM K2SO4) was constructed. In this study, four key modules that are highly related to potassium regulation of cotton salt tolerance were identified, and the mitogen-activated protein kinase (MAPK) signaling pathway, tricarboxylic acid (TCA) cycle and glutathione metabolism pathway were identified as the key biological processes and metabolic pathways for potassium to improve cotton root salt adaptability. In addition, 21 hub genes and 120 key candidate genes were identified in this study, suggesting that they may play an important role in the enhancement of salt adaptability of cotton by potassium. The key modules, key biological pathways and hub genes discovered in this study will provide a new understanding of the molecular mechanism of potassium enhancing salinity adaptability in cotton, and lay a theoretical foundation for the improvement and innovation of high-quality cotton germplasm.

Identification and Analysis of Potential Immune-Related Biomarkers in Endometriosis.

Background: Endometriosis is an inflammatory gynecological disease leading to deep pelvic pain, dyspareunia, and infertility. The pathophysiology of endometriosis is complex and depends on a variety of biological processes and pathways. Therefore, there is an urgent need to identify reliable biomarkers for early detection and accurate diagnosis to predict clinical outcomes and aid in the early intervention of endometriosis. We screened transcription factor- (TF-) immune-related gene (IRG) regulatory networks as potential biomarkers to reveal new molecular subgroups for the early diagnosis of endometriosis. Methods: To explore potential therapeutic targets for endometriosis, the Gene Expression Omnibus (GEO), Immunology Database and Analysis Portal (ImmPort), and TF databases were used to obtain data related to the recognition of differentially expressed genes (DEGs), differentially expressed IRGs (DEIRGs), and differentially expressed TFs (DETFs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the DETFs and DEIRGs. Then, DETFs and DEIRGs were further validated in the external datasets of GSE51981 and GSE1230103. Then, we used quantitative real-time polymerase chain reaction (qRT-PCR) to verify the hub genes. Simultaneously, the Pearson correlation analysis and protein-protein interaction (PPI) analyses were used to indicate the potential mechanisms of TF-IRGs at the molecular level and obtain hub IRGs. Finally, the receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic value of the hub IRGs. Results: We screened a total of 94 DETFs and 121 DEIRGs in endometriosis. Most downregulated DETFs showed decreased expression in the endometria of moderate/severe endometriosis patients. The top-ranked upregulated DEIRGs were upregulated in the endometra of infertile women. Functional analysis showed that DETFs and DEIRGs may be involved in the biological behaviors and pathways of endometriosis. The TF-IRG PPI network was successfully constructed. Compared with the control group, high C3, VCAM1, ITGB2, and C3AR1 expression had statistical significance in endometriosis among the hub DEIRGs. They also showed higher sensitivity and specificity by ROC analysis for the diagnosis of endometriosis. Finally, compared with controls, C3 and VCAM1 were highly expressed in endometriosis tissue samples. In addition, they also showed high specificity and sensitivity for diagnosing endometriosis. Conclusion: Overall, we discovered the TF-IRG regulatory network and analyzed 4 hub IRGs that were closely related to endometriosis, which contributes to the diagnosis of endometriosis. Additionally, we verified that DETFs or DEIRGs were associated with the clinicopathological features of endometriosis, and external datasets also confirmed the hub IRGs. Finally, C3 and VCAM1 were highly expressed in endometriosis tissue samples compared with controls and may be potential biomarkers of endometriosis, which are helpful for the early diagnosis of endometriosis.

Potassium ameliorates cotton (Gossypium hirsutum L.) fiber length by regulating osmotic and K+ /Na+ homeostasis under salt stress.

Potassium (K) application can alleviate cotton salt stress, but the regulatory mechanisms affecting cotton fiber elongation and ion homeostasis are still unclear. A two-year field experiment was conducted to explore the effects of K on the osmolyte contents (soluble sugar, K+ content, and malate) and related enzyme activities during the fiber elongation of two cotton cultivars with contrasting salt sensitivity (CCRI-79; salt tolerant cultivar, and Simian 3; salt-sensitive cultivar). Three K application treatments (0, 150, and 300 kg K2 O ha-1 ) were applied at three soil salinity levels (low salinity, EC = 1.73 ± 0.05 dS m-1 ; medium salinity, EC = 6.32 ± 0.10 dS m-1 ; high salinity, EC = 10.84 ± 0.24 dS m-1 ). K application improved fiber length and alleviated salt stress by increasing the maximum velocity of fiber elongation (Vmax ). The increase rate of K on fiber length decreased with elevating salt stress, and the increase rate of K on Vmax of CCRI-79 was greater than that of Simian3. K application can increase the enzyme activities (phosphoenolpyruvate carboxylase, PEPC, E.C. 4.1.1.31; pyrophosphatase, PPase, E.C. 3.6.1.1; and plasma membrane H+ -ATPase, PM H+ -ATPase, E.C. 3.6.3.14) as well as the content of osmolytes associated with the enzymes mentioned above. K increased the osmolyte contents under salt stress, and the increase in the K+ content of the fibers was much higher than that of soluble sugar and malate. The results of this study indicated K fertilizer application rates regulate the metabolism of osmolytes in cotton fiber development under salt stress, K+ is more critical to fiber elongation.

Biometric factors and orthokeratology lens parameters can influence the treatment zone diameter on corneal topography in Corneal Refractive Therapy lens wearers.

PURPOSE: To investigate the relationship between patients' baseline biometric factors or lens parameters and the diameter of the treatment zone in young myopic children undergoing Corneal Refractive Therapy. METHODS: The data of patients undergoing Corneal Refractive Therapy lens treatment within two years were retrospectively reviewed. Baseline clinical data, including sex, age, refractive power, corneal topography readings, ocular optical biometric measurements, and Corneal Refractive Therapy lens parameters, were subjected to Pearson, Spearman, and partial correlation analyses to identify the potential factors that may influence treatment zone diameter on corneal topography. Logistic and linear regression analyses were used to predict the treatment zone size. RESULTS: The Right eyes of 309 patients were included in this study. The spherical refraction, flat keratometric reading, Reverse Zone Depth 2, Landing Zone Angle 1, and lens diameter were independent factors of treatment zone diameter. In the multivariate analyses, Landing Zone Angle 1 was positively correlated, while Reverse Zone Depth 2 and lens diameter were negatively correlated with the size of the treatment area. The accuracy of logistic regression in predicting the treatment zone size was 71.5%. CONCLUSION: Adjustments to Corneal Refractive Therapy lens parameters may influence the treatment zone diameter on corneal topography. A higher Reverse Zone Depth 2, smaller Landing Zone Angle 1, and larger lens diameter can lead to a smaller treatment zone for Corneal Refractive Therapy lens treatment.

Hydroxyethyl methyl cellulose controls the diffusion behavior of pico-liter scale ink droplets on silk to improve inkjet printing performance.

In this study, a simple and effective coating method to improve printing quality and material utilization rate was proposed. The flow behavior of pico-liter scale ink droplets on the silk fabric surfaces which treated separately with Sodium alginate (SA), Hydroxyethyl cellulose (HEC) and Hydroxyethyl methyl cellulose (HEMC) was observed and measured. Indeed, based on the direct empirical results, the optimal pretreatment process on the fabrics, aiming to increase the ink utilization rate and further improve the surface printing clarity, has been obtained in the experiments. Studies on rheological property, surface activity, scanning electron microscope (SEM) and contact angle have shown that HEMC can form the densest and smoothest film on silk fabrics, where the most hydrophobic surface arises. X-ray photoelectron spectroscopy (XPS) results indicate that the surface of the fabric is covered with films of different properties formed by the treatment solution, and confirmed that the films formed by HEMC were more hydrophobic. The spreading motion of ink droplets revealed that although the hydrophobicity of HEC and HEMC effectively restrain the flow of ink droplet along the fiber, and the length and width of one-ink droplet deposition are minimum in HEMC treated fabric. Similarly, the findings on color performance suggest that HEMC has absolutely comparative advantage over HEC in improving the color effect of printing, with dye utilization rate of three different colors increasing by 68.7 %-80.0 %.

Collaborative Knowledge Distillation via Multiknowledge Transfer.

Knowledge distillation (KD), as an efficient and effective model compression technique, has received considerable attention in deep learning. The key to its success is about transferring knowledge from a large teacher network to a small student network. However, most existing KD methods consider only one type of knowledge learned from either instance features or relations via a specific distillation strategy, failing to explore the idea of transferring different types of knowledge with different distillation strategies. Moreover, the widely used offline distillation also suffers from a limited learning capacity due to the fixed large-to-small teacher-student architecture. In this article, we devise a collaborative KD via multiknowledge transfer (CKD-MKT) that prompts both self-learning and collaborative learning in a unified framework. Specifically, CKD-MKT utilizes a multiple knowledge transfer framework that assembles self and online distillation strategies to effectively: 1) fuse different kinds of knowledge, which allows multiple students to learn knowledge from both individual instances and instance relations, and 2) guide each other by learning from themselves using collaborative and self-learning. Experiments and ablation studies on six image datasets demonstrate that the proposed CKD-MKT significantly outperforms recent state-of-the-art methods for KD.

Proteomic insights into SARS-CoV-2 infection mechanisms, diagnosis, therapies and prognostic monitoring methods.

At the end of 2019, the COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection, seriously damaged world public health security. Several protein markers associated with virus infection have been extensively explored to combat the ever-increasing challenge posed by SARS-CoV-2. The proteomics of COVID-19 deepened our understanding of viral particles and their mechanisms of host invasion, providing us with information on protein changes in host tissues, cells and body fluids following infection in COVID-19 patients. In this review, we summarize the proteomic studies of SARS-CoV-2 infection and review the current understanding of COVID-19 in terms of the quantitative and qualitative proteomics of viral particles and host entry factors from the perspective of protein pathological changes in the organism following host infection.

The 22-Item Benefit Finding Scale: Validation and Application among Patients with Cervical Cancer in Ethnic Minority Areas of Southwestern China.

Recently, the Benefit Finding Scale (BFS) has been translated and culturally adapted for use in China. However, further validation of the instrument is required before it can be used in the management of patients with cervical cancer in China. In this study, we conducted the questionnaire survey and examined its properties. This methodological study was conducted at a tumor hospital located in southwestern China. Patients with cervical cancer who had been reexamined in the outpatient department of the hospital and hospitalized from June to August 2019 were selected. The item analysis, exploratory factor analysis (EFA), and reliability analysis were tested. The relationships between benefit finding and sociodemographic and disease-related variables were analyzed by ANOVA and regression models. A total of 247 patients were assessed (mean age: 48.0 ± 13.3 years). Educational level, self-perceived disease severity, and physical exercise were the predictors of benefit finding. The correlation coefficient between 22 items and their dimensions was the best. EFA analysis supported a five-factor model for structure validity. All Cronbach's alpha for the Chinese version of the BFS (BFS-C) was greater than 0.80. The results demonstrated the good reliability and validity of BFS-C. It appears to be a useful scale to assess experience of benefit finding among patients with cervical cancer in China.

A randomized controlled trial of WeChat-based cognitive behavioral therapy intervention to improve cancer-related symptoms in gynecological cancer survivors: study protocol.

BACKGROUND: Gynecological malignant patients often have significant psychological and physical problems. The feasibility and generalizability of traditional intervention method is low due to the high time and labor cost, large number of gynecological malignant tumor patients in China, as well as shortage of health professionals. Therefore, it is necessary to design an alternative, innovative, and easily accessible intervention method. This study aims to evaluate the effect of WeChat-based intervention on anxiety, depression and disease-related symptoms of patients with gynecological malignant tumors during rehabilitation. METHODS: A single-blinded, randomized, controlled, parallel-group pre-test and repeated post-test design will be conducted. A total of 76 participants will be randomly divided into the intervention group and control group. Anxiety and depression, disease-related symptoms, coping ability, benefit finding and quality of life will be measured at baseline and repeated immediately after the intervention (test 1), 3 months (test 2) and 6 months (test 3) after the intervention. DISCUSSION: As the first randomized controlled trial with rigorous research design for patients with gynecological malignant tumors in the rehabilitation stage in China, this study will provide evidences for the effectiveness of the WeChat platform during intervention of patients with gynecological malignant tumors in the rehabilitation stage. The results are helpful to further explore the effect of WeChat-based intervention on improving patients' anxiety and depression, disease-related symptoms, and quality of life. TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR2100053450, Registered 21 November 2021, http://www.chictr.org.cn/searchproj.aspx.