Can Artificial Intelligence Chatbots Improve Mental Health?: A Scoping Review.

BACKGROUND AND OBJECTIVES: Mental health disorders, including anxiety and depression, are the leading causes of global health-related burden and have increased dramatically since the 1990s. Delivering mental healthcare using artificial intelligence chatbots may be one option for closing the gaps in mental healthcare access. The overall aim of this scoping review was to describe the use, efficacy, and advantages/disadvantages of using an artificial intelligence chatbot for mental healthcare (stress, anxiety, depression). METHODS: PubMed, PsycINFO, CINAHL, and Web of Science databases were searched. When possible, Medical Subject Headings terms were searched in combination with keywords. Two independent reviewers reviewed a total of 5768 abstracts. RESULTS: Fifty-four articles were chosen for further review, with 10 articles included in the final analysis. Regarding quality assessment, the overall quality of the evidence was lower than expected. Overall, most studies showed positive trends in improving anxiety, stress, and depression. DISCUSSION: Overall, using an artificial intelligence chatbot for mental health has some promising effects. However, many studies were done using rudimentary versions of artificial intelligence chatbots. In addition, lack of guardrails and privacy issues were identified. More research is needed to determine the effectiveness of artificial intelligence chatbots and to describe undesirable effects.

Emerging trends and hotspots in cervical intraepithelial neoplasia research from 2013 to 2023: A bibliometric analysis.

Background: Cervical intraepithelial neoplasia (CIN) encompasses a range of cervical lesions that are closely linked to cervical invasive carcinoma. Early detection and timely treatment of CIN are crucial for preventing the progression of the disease. However, no bibliometric analysis has been conducted in this area. This research aimed to employ bibliometric analysis to summarize the current research hotspots and estimate future research trends in the CIN field. Methods: Publications related to CIN (2013-2023) were retrieved from the Science-Citation-Index-Expanded-of-Web-of-Science-Core-Collection. CiteSpace, VOSviewer, and the bibliometric-Online-Analysis-Platform-of-Literature-Metrology were employed to analyze the yearly research output, collaborating institutions or countries, leading researchers, principal journals, co-referenced sources, and emerging keywords. Results: In total, 4677 articles on CIN that were published from 2013 to 2023 and met our criteria were extracted. Major publishing platforms were predominantly USA until 2017 when China emerged as the leading source of publications about CIN. The USA was the leading nation in international collaborations. The National-Cancer-Institute (NCI) was the institution with the most publications. Schiffman Mark produced the highest number of articles, with a total of 92. Ten major clusters were identified through co-cited keyword clustering, including prevalence, human papillomavirus, DNA methylation, p16, methylation, conization, HPV genotyping tests (VALGENT), deep learning, vaginal microbiome, and immunohistochemistry. Keyword burst analysis showed that photodynamic therapy and deep learning emerged as prominent research focal points with significant impact in resent three years. Conclusion: Global publications on CIN research showed a relatively stable trend over the past eleven years. Current research hotspots are deep learning and photodynamic therapy. This research offered organized data and insightful guidance for future studies, which may help better prevent, screen, and treat CIN.

SAGL: A self-attention-based graph learning framework for predicting survival of colorectal cancer patients.

BACKGROUND AND OBJECTIVE: Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. The accurate survival prediction for CRC patients plays a significant role in the formulation of treatment strategies. Recently, machine learning and deep learning approaches have been increasingly applied in cancer survival prediction. However, most existing methods inadequately represent and leverage the dependencies among features and fail to sufficiently mine and utilize the comorbidity patterns of CRC. To address these issues, we propose a self-attention-based graph learning (SAGL) framework to improve the postoperative cancer-specific survival prediction for CRC patients. METHODS: We present a novel method for constructing dependency graph (DG) to reflect two types of dependencies including comorbidity-comorbidity dependencies and the dependencies between features related to patient characteristics and cancer treatments. This graph is subsequently refined by a disease comorbidity network, which offers a holistic view of comorbidity patterns of CRC. A DG-guided self-attention mechanism is proposed to unearth novel dependencies beyond what DG offers, thus augmenting CRC survival prediction. Finally, each patient will be represented, and these representations will be used for survival prediction. RESULTS: The experimental results show that SAGL outperforms state-of-the-art methods on a real-world dataset, with the receiver operating characteristic curve for 3- and 5-year survival prediction achieving 0.849±0.002 and 0.895±0.005, respectively. In addition, the comparison results with different graph neural network-based variants demonstrate the advantages of our DG-guided self-attention graph learning framework. CONCLUSIONS: Our study reveals that the potential of the DG-guided self-attention in optimizing feature graph learning which can improve the performance of CRC survival prediction.

Concurrent brain structural and functional alterations in the thalamus of adult survivors of childhood brain tumors: a multimodal MRI study.

Adult survivors of childhood brain tumors often present with cognitive deficits that affect their quality of life. Studying brain structure and function in brain tumor survivors can help understand the underlying mechanisms of their cognitive deficits to improve long-term prognosis of these patients. This study analyzed voxel-based morphometry (VBM) derived from T1-weighted MRI and the amplitude of low-frequency fluctuation (ALFF) from resting-state functional magnetic resonance imaging (rs-fMRI) to examine the structural and functional alterations in 35 brain tumor survivors using 35 matching healthy individuals as controls. Compared with healthy controls, brain tumor survivors had decreased gray matter volumes (GMV) in the thalamus and increased GMV in the superior frontal gyrus. Functionally, brain tumor survivors had lower ALFF values in the inferior temporal gyrus and medial prefrontal area and higher ALFF values in the thalamus. Importantly, we found concurrent but negatively correlated structural and functional alterations in the thalamus based on observed significant differences in GMV and ALFF values. These findings on concurrent brain structural and functional alterations provide new insights towards a better understanding of the cognitive deficits in brain tumor survivors.

A Gas Therapy Strategy for Intestinal Flora Regulation and Colitis Treatment by Nanogel-Based Multistage NO Delivery Microcapsules.

Current approaches to treating inflammatory bowel disease focus on the suppression of overactive immune responses, the removal of reactive intestinal oxygen species, and regulation of the intestinal flora. However, owing to the complex structure of the gastrointestinal tract and the influence of mucus, current small-molecule and biologic-based drugs for treating colitis cannot effectively act at the site of colon inflammation, and as a result, they tend to exhibit low efficacies and toxic side effects. In this study, nanogel-based multistage NO delivery microcapsules are developed to achieve NO release at the inflammation site by targeting the inflammatory tissues using the nanogel. Surprisingly, oral administration of the microcapsules suppresses the growth of pathogenic bacteria and increases the abundance of probiotic bacteria. Metabolomics further show that an increased abundance of intestinal probiotics promotes the production of metabolites, including short-chain fatty acids and indole derivatives, which modulate the intestinal immunity and restore the intestinal barrier via the interleukin-17 and PI3K-Akt signaling pathways. This work reveals that the developed gas therapy strategy based on multistage NO delivery microcapsules modulates the intestinal microbial balance, thereby reducing inflammation and promoting intestinal barrier repair, ultimately providing a new therapeutic approach for the clinical management of colitis.

Real-world use of first-line pembrolizumab + platinum + taxane combination regimens in recurrent / metastatic head and neck squamous cell carcinoma.

Introduction: The programmed death-1 (PD-1) immune checkpoint inhibitor pembrolizumab is currently approved in the US for the first-line (1L) treatment of recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC), either alone or in combination with platinum and 5-fluorouracil (5-FU). However, the toxicity of 5-FU has motivated the study of alternate combinations that replace 5-FU with a taxane. The objective of the current study was to describe the baseline characteristics, treatment patterns and sequences, and real-world outcomes of individuals receiving pembrolizumab + platinum + taxane as 1L treatment for R/M HNSCC in the US. Methods: This was a retrospective study of US adults ≥18 years of age receiving pembrolizumab + platinum + taxane as 1L treatment for R/M HNSCC, using electronic health record data from a nationwide de-identified database. Real-world overall survival (rwOS), time on treatment (rwToT), and time to next treatment (rwTTNT) outcomes were assessed using Kaplan-Meier analysis. Results: The study population comprised 83 individuals (80.7% male) with a median age of 64 years. The most common tumor site was the oropharynx (48.2%); 70.0% of these tumors were HPV-positive. A total of 71.1% of the study population had an Eastern Cooperative Oncology Group performance status of 0-1 at index date, 71.8% had a combined positive score for programmed death ligand-1 (PD-L1) expression of ≥1, and 30.8% had a score of ≥20. The median (95% CI) rwOS was 14.9 (8.8-23.3) months, rwToT was 5.3 (4.0-8.2) months, and rwTTNT was 8.7 (6.8-12.3) months. Among the 24 individuals who received a subsequent therapy, the most common second-line therapies were cetuximab-based (n = 9) or pembrolizumab-containing (n = 8) regimens. Conclusions: The rwOS and other real-world outcomes observed for this study population further support pembrolizumab + platinum + taxane combination therapy as a potential 1L treatment option for R/M HNSCC.

Minocycline-Induced Hyperpigmentation: Importance of Early Diagnosis.

A 75-year-old woman on hemodialysis for end-stage renal failure due to polycystic kidney disease developed dark spots on her limbs. She had been treated for extended spectrum beta-lactamase-producing Escherichia coli bacteremia by a rectovaginal fistula and was on long-term oral minocycline (cumulative dose 45 g). Physical examination revealed dark patches on her forearms and lower legs but no trunk hyperpigmentation or visual impairment. Blood tests were normal. Skin biopsy confirmed minocycline-induced hyperpigmentation. Minocycline-induced pigmentation is categorized into types I-IV, each with unique clinical and histopathological features. Types I and II are reversible upon discontinuing minocycline, whereas types III and IV are permanent. The patient was diagnosed with type II pigmentation, generally occurring with a cumulative dose exceeding 70-100 g; however, her lower dose (45 g) led to pigmentation, possibly influenced by her vitamin D deficiency. Clinicians should evaluate the antimicrobial indication and treatment period, considering not only the benefits but also the side effects and antimicrobial resistance. If minocycline is used, attention should be paid to minocycline-induced hyperpigmentation, and this possibility should be communicated to patients to enable early detection.

Predicting Colorectal Cancer Survival Using Time-to-Event Machine Learning: Retrospective Cohort Study.

BACKGROUND: Machine learning (ML) methods have shown great potential in predicting colorectal cancer (CRC) survival. However, the ML models introduced thus far have mainly focused on binary outcomes and have not considered the time-to-event nature of this type of modeling. OBJECTIVE: This study aims to evaluate the performance of ML approaches for modeling time-to-event survival data and develop transparent models for predicting CRC-specific survival. METHODS: The data set used in this retrospective cohort study contains information on patients who were newly diagnosed with CRC between December 28, 2012, and December 27, 2019, at West China Hospital, Sichuan University. We assessed the performance of 6 representative ML models, including random survival forest (RSF), gradient boosting machine (GBM), DeepSurv, DeepHit, neural net-extended time-dependent Cox (or Cox-Time), and neural multitask logistic regression (N-MTLR) in predicting CRC-specific survival. Multiple imputation by chained equations method was applied to handle missing values in variables. Multivariable analysis and clinical experience were used to select significant features associated with CRC survival. Model performance was evaluated in stratified 5-fold cross-validation repeated 5 times by using the time-dependent concordance index, integrated Brier score, calibration curves, and decision curves. The SHapley Additive exPlanations method was applied to calculate feature importance. RESULTS: A total of 2157 patients with CRC were included in this study. Among the 6 time-to-event ML models, the DeepHit model exhibited the best discriminative ability (time-dependent concordance index 0.789, 95% CI 0.779-0.799) and the RSF model produced better-calibrated survival estimates (integrated Brier score 0.096, 95% CI 0.094-0.099), but these are not statistically significant. Additionally, the RSF, GBM, DeepSurv, Cox-Time, and N-MTLR models have comparable predictive accuracy to the Cox Proportional Hazards model in terms of discrimination and calibration. The calibration curves showed that all the ML models exhibited good 5-year survival calibration. The decision curves for CRC-specific survival at 5 years showed that all the ML models, especially RSF, had higher net benefits than default strategies of treating all or no patients at a range of clinically reasonable risk thresholds. The SHapley Additive exPlanations method revealed that R0 resection, tumor-node-metastasis staging, and the number of positive lymph nodes were important factors for 5-year CRC-specific survival. CONCLUSIONS: This study showed the potential of applying time-to-event ML predictive algorithms to help predict CRC-specific survival. The RSF, GBM, Cox-Time, and N-MTLR algorithms could provide nonparametric alternatives to the Cox Proportional Hazards model in estimating the survival probability of patients with CRC. The transparent time-to-event ML models help clinicians to more accurately predict the survival rate for these patients and improve patient outcomes by enabling personalized treatment plans that are informed by explainable ML models.

A monoclonal antibody-based sandwich ELISA for measuring canine Thymidine kinase 1 protein and its role as biomarker in canine lymphoma.

Introduction: Dogs play an important role in society, which increased during the covid epidemics. This has led to a much higher workload for the veterinarians. Therefore, there is a need for efficient diagnostic tools to identify risk of malignant diseases. Here the development of a new test that can solve some of these problems is presented. It is based on serum Thymidine Kinase 1 (TK1), which is a biomarker for cell proliferation and cell lysis. Methods: Anti-TK1 monoclonal antibodies were produced against two different epitopes, the active site of the TK1 protein and the C-terminal region of canine TK1. The antibodies were developed with hybridoma technology and validated using dot blot, Quartz Crystal Microbalance (QCM) technology, western blots, immunoprecipitation (IP), and enzyme-linked immunosorbent assay (ELISA). Clinical evaluation of Canine TK1 ELISA was done by using sera from 131 healthy dogs and 93 dogs with lymphoma. The two selected Anti-TK1 monoclonal antibodies have Kd values in the range of 10-9 M and further analysis with dot and western blots confirmed the high affinity binding of these antibodies. A sandwich Canine TK1 ELISA was developed using the anti-TK1 antibodies, and TK1 concentrations in serum samples were determined using dog recombinant TK1 as a standard. Results: Serum TK1 protein levels were significantly higher in dogs with lymphoma compared to those in healthy dogs (p < 0.0001). Receiver operating curve analysis showed that the canine TK1-ELISA obtain a sensitivity of 0.80, at a specificity of 0.95. Moreover, the Canine TK1 ELISA has a positive predictive value (PPV) of 97%, and the negative predictive value (NPV) of 83%, reflecting the proportion of test results that are truly positive and negative. Furthermore, Canine TK1 ELISA had significantly higher capacity to differentiate dogs with T-cell lymphoma from those with B-cell lymphoma compared to earlier used TK1 activity assays. Discussion: These results demonstrate that the Canine TK1 ELISA can serve as an efficient tool in the diagnosis and management of dogs with lymphomas.

Comorbidity Patterns in Patients Newly Diagnosed With Colorectal Cancer: Network-Based Study.

BACKGROUND: Patients with colorectal cancer (CRC) often present with multiple comorbidities, and many of these can affect treatment and survival. However, previous comorbidity studies primarily focused on diseases in commonly used comorbidity indices. The comorbid status of CRC patients with respect to the entire spectrum of chronic diseases has not yet been investigated. OBJECTIVE: This study aimed to systematically analyze all chronic diagnoses and diseases co-occurring, using a network-based approach and large-scale administrative health data, and provide a complete picture of the comorbidity pattern in patients newly diagnosed with CRC from southwest China. METHODS: In this retrospective observational study, the hospital discharge records of 678 hospitals from 2015 to 2020 in Sichuan Province, China were used to identify new CRC cases in 2020 and their history of diseases. We examined all chronic diagnoses using ICD-10 (International Classification of Diseases, 10th Revision) codes at 3 digits and focused on chronic diseases with >1% prevalence in at least one subgroup (1-sided test, P<.025), which resulted in a total of 66 chronic diseases. Phenotypic comorbidity networks were constructed across all CRC patients and different subgroups by sex, age (18-59, 60-69, 70-79, and ≥80 years), area (urban and rural), and cancer site (colon and rectum), with comorbidity as a node and linkages representing significant correlations between multiple comorbidities. RESULTS: A total of 29,610 new CRC cases occurred in Sichuan, China in 2020. The mean patient age at diagnosis was 65.6 (SD 12.9) years, and 75.5% (22,369/29,610) had at least one comorbidity. The most prevalent comorbidities were hypertension (8581/29,610, 29.0%; 95% CI 28.5%-29.5%), hyperplasia of the prostate (3816/17,426, 21.9%; 95% CI 21.3%-22.5%), and chronic obstructive pulmonary disease (COPD; 4199/29,610, 14.2%; 95% CI 13.8%-14.6%). The prevalence of single comorbidities was different in each subgroup in most cases. Comorbidities were closely associated, with disorders of lipoprotein metabolism and hyperplasia of the prostate mediating correlations between other comorbidities. Males and females shared 58.3% (141/242) of disease pairs, whereas male-female disparities occurred primarily in diseases coexisting with COPD, cerebrovascular diseases, atherosclerosis, heart failure, or renal failure among males and with osteoporosis or gonarthrosis among females. Urban patients generally had more comorbidities with higher prevalence and more complex disease coexistence relationships, whereas rural patients were more likely to have co-existing severe diseases, such as heart failure comorbid with the sequelae of cerebrovascular disease or COPD. CONCLUSIONS: Male-female and urban-rural disparities in the prevalence of single comorbidities and their complex coexistence relationships in new CRC cases were not due to simple coincidence. The results reflect clinical practice in CRC patients and emphasize the importance of measuring comorbidity patterns in terms of individual and coexisting diseases in order to better understand comorbidity patterns.

The Role of lncRNA-miR-26a-mRNA Network in Cancer Progression and Treatment.

The role of non-coding RNAs in regulating biological processes associated with cancer progression, such as proliferation, migration, and apoptosis, has been extensively studied. Long non-coding RNAs (lncRNAs) play a role in regulating these processes through various mechanisms, including transcriptional and post-transcriptional modifications. In post-transcriptional regulation, lncRNAs can bind to specific miRNAs and affect their function, which can either promote or inhibit cancer development. The interaction between lncRNAs, miRNAs, and mRNAs forms a network known as competitive endogenous RNA (ceRNA), which is involved in cancer progression or inhibition. One specific miRNA called miR-26a-5p has been identified as having tumor-suppressive properties. However, when lncRNAs bind to and inhibit miR-26a-5p, it can lead to cancer progression. Therefore, targeting this ceRNA network could be a promising strategy for preventing cancer development. This review will first discuss the anticancer effects of miR-26a-5p and then explore the involvement of the lncRNA-miR26a-5p-mRNA axis in cancer progression and potential targeted therapies.

Real-world study of patients with locally advanced HNSCC in the community oncology setting.

Introduction: There is a need to understand the current treatment landscape for LA HNSCC in the real-world setting. Methods: This retrospective study assessed real-world outcomes and treatment patterns of 1,158 adult patients diagnosed with locally advanced (stage III-IVB) HNSCC initiating chemoradiotherapy (CRT) within the period January 2015 to December 2017 in a large network of US community oncology practices. Structured data were abstracted from electronic health records. Demographic, clinical and treatment characteristics were analyzed descriptively overall and stratified by index treatment (cisplatin + radiotherapy [RT], cisplatin + other chemotherapy + RT, or cetuximab + RT). Time to next treatment (TTNT) and overall survival (OS) were measured using the Kaplan-Meier method, and median duration of treatment was assessed. OS was compared across treatment cohorts using multinomial logistic regression with inverse probability treatment weighting. To identify covariates associated with OS, a multivariable adjusted Cox proportional hazard model was used. Results: This study examined 22,782 records, of which 2124 had stage III to stage IVB and no other cancers, and 1158 met all eligibility criteria. Among the treatment cohorts analyzed (cisplatin + RT, cisplatin + other chemotherapy + RT, or cetuximab + RT), cisplatin + RT was the most common concurrent chemotherapy (65.8%). Among 1158 patients, 838 (72.4%) did not initiate subsequent treatment and 139 (12.0%) died. The median TTNT and median OS were only reached by the cetuximab + RT cohort. Among patients with oropharynx primary tumor location, patients with human papilloma virus (HPV) positive status had the longest time on treatment and highest survival at 60 months. Covariates associated with improved survival were never/former tobacco use, HPV positive status, and overweight or obese body mass index. Covariates associated with poorer survival were age of 60+ years, primary tumor location of hypopharynx or oral cavity and Eastern Cooperative Oncology Group performance status score of 2+. Conclusion: These data describe real-world treatment patterns in locally advanced head and neck squamous cell cancer and sets the baseline to assess outcomes for future studies on the community oncology population.

The Expression Characteristics and Function of the RECQ Family in Pan-Cancer.

BACKGROUND: The genes of the RECQ DNA helicase family play a part in preserving the stability of the genome and controlling different disease mechanisms. However, the expression features of RECQs in relation to pan-cancer, their correlation with the immune microenvironment of tumors, and the landscape of prognostic power are still undisclosed. METHODS: Various sequence and clinical data extracted from 33 cancers were utilized to generate a comprehensive overview of RECQs in the landscape. Afterward, we discovered variations in gene expression, potential enrichment of functions, genetic alterations, and analysis related to the immune response in tumors. Additionally, we explored the clinical characteristics and diagnostic significance of RECQs. And the important association of RECQL4 with liver hepatocellular carcinoma (LIHC) was investigated. RESULTS: RECQs exhibited extensive mutations in different types of cancers. The expression of RECQ may be influenced by an oncogenic mutation in certain types of cancer, resulting in the observed genomic and epigenetic changes in diverse tumor formations. Furthermore, RECQs originating from tumors exhibited a significant association with the immune microenvironment of the tumor, indicating their potential as promising targets for therapy. Patient prognosis was significantly associated with the majority of genes in the RECQ family. In LIHC, RECQL4 eventually emerged as a separate prognostic determinant. CONCLUSIONS: To summarize, RECQs are essential for the regulation of the immune system in tumors, and RECQL4 serves as a prognostic indicator in LIHC. The results of our study offer fresh perspectives on RECQs from a bioinformatics perspective and emphasize the importance of RECQs in the diagnosis and treatment of cancer.

Association Between SPARC Polymorphisms and Ankylosing Spondylitis and Its mRNA and Protein Expression in a Chinese Han Population: A Case-Control Study.

Objective: We explore the association of polymorphisms in Secreted protein acidic and rich in cysteine (SPARC) with ankylosing spondylitis (AS) and detect SPARC mRNA and protein expression in a Chinese Han population. Methods: Nine single-nucleotide polymorphisms (SNPs) of SPARC were genotyped in 768 AS patients and 768 controls by TaqMan genotyping assay. mRNA expression of SPARC was detected by real-time polymerase chain reaction (RT-PCR), and serum level of SPARC protein was detected by ELISA. Results: The frequency of A allele of rs171121187 was significantly higher in AS patients than in controls (Pc=0.003, odds ratio [OR]=1.45, 95% confidence interval [95% CI] = 1.18-1.77), the AA and AC genotypes increased the risk of AS when compared with CC genotype (Pc=0.003, OR=3.96, 95% CI=1.80-8.75, and Pc=0.003, OR=1.27, 95% CI=1.01-1.61, respectively). The frequency of G allele of rs4958487 was significantly lower in AS than in controls (Pc=0.001, OR=0.60, 95% CI=0.47-0.68), the GG and GA genotypes reduced the risk of AS when compared with AA genotype (Pc=0.005, OR=0.46, 95% CI 0.18-1.14, and Pc=0.005, OR=0.60, 95% CI=0.45-0.79, respectively). The haplotype AA of rs17112187/rs4958487 significantly increased the risk of AS (P=2.31E-5, OR=1.60, 95% CI=1.28-1.98), while haplotype CG decreased the risk of AS (P=5.42E-5, OR=0.55, 95% CI=0.41-0.74). Expression levels of SPARC mRNA were significantly lower in both Peripheral blood mononuclear cells (PBMC) and granulocytes in AS patients than in controls (P=0.008 and P=0.005, respectively). SPARC protein levels were also reduced in AS patients versus the controls (P=0.002). Conclusion: This study indicates that polymorphisms in SPARC are associated with AS susceptibility, and both mRNA and protein levels of SPARC are decreased in AS patients in a Chinese Han population.

Corrigendum: Real-world treatment patterns and outcomes among individuals receiving first-line pembrolizumab therapy for recurrent/metastatic head and neck squamous cell carcinoma.

[This corrects the article DOI: 10.3389/fonc.2023.1160144.].

Real-world treatment patterns and outcomes among individuals receiving first-line pembrolizumab therapy for recurrent/metastatic head and neck squamous cell carcinoma.

Background: Pembrolizumab, a PD-1 immune checkpoint inhibitor, is approved as first-line (1L) treatment for recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC) as monotherapy or in combination with platinum and 5-fluorouracil chemotherapy. Limited data exist on the use of these regimens in real-world settings. Objective: Our primary objectives were to describe baseline characteristics and real-world overall survival (rwOS), time on treatment (rwToT), and time to next treatment (rwTTNT) among individuals with R/M HNSCC receiving approved 1L pembrolizumab therapies. We also aimed to identify baseline factors associated with choice of 1L pembrolizumab therapy and with rwOS. Methods: This was a retrospective cohort study of adults with R/M HNSCC receiving 1L pembrolizumab monotherapy or pembrolizumab plus chemotherapy. We used Kaplan-Meier analyses to assess real-world outcomes, logistic regression modeling to identify factors associated with choice of 1L pembrolizumab therapy, and Cox proportional hazards models to identify factors associated with rwOS. Results: The study population included 431 individuals receiving 1L pembrolizumab monotherapy and 215 receiving 1L pembrolizumab plus chemotherapy. The use of 1L pembrolizumab monotherapy was associated with higher baseline combined positive score for PD-L1 expression, older age, higher Eastern Cooperative Oncology Group performance status (ECOG PS), laryngeal tumor site, and human papillomavirus (HPV)-positive tumor status. The pembrolizumab monotherapy group had a median (95% CI) rwOS of 12.1 (9.2-15.1) months, rwToT of 4.2 (3.5-4.6) months, and rwTTNT of 6.5 (5.4-7.4) months. Among this group, HPV-positive tumor status and lower ECOG PS were associated with longer rwOS, and oral cavity tumor site with shorter rwOS. The pembrolizumab plus chemotherapy cohort had a median (95% CI) rwOS of 11.9 (9.0-16.0) months, rwToT of 4.9 (3.8-5.6) months, and rwTTNT of 6.6 (5.8-8.3) months. In this group, HPV-positive tumor status was associated with longer rwOS. Conclusions: This study adds to clinical trial data by summarizing real-world treatment outcomes with 1L pembrolizumab-containing therapies in a more heterogeneous population. Overall survival outcomes in both treatment groups were similar to those observed in the registration clinical trial. These findings support the use of pembrolizumab as standard of care for R/M HNSCC.

All-Natural Immunomodulatory Bioadhesive Hydrogel Promotes Angiogenesis and Diabetic Wound Healing by Regulating Macrophage Heterogeneity.

Macrophages are highly heterogeneous and exhibit a diversity of functions and phenotypes. They can be divided into pro-inflammatory macrophages (M1) and anti-inflammatory macrophages (M2). Diabetic wounds are characterized by a prolonged inflammatory phase and difficulty in healing due to the accumulation of pro-inflammatory (M1) macrophages in the wound. Therefore, hydrogel dressings with macrophage heterogeneity regulation function hold great promise in promoting diabetic wound healing in clinical applications. However, the precise conversion of pro-inflammatory M1 to anti-inflammatory M2 macrophages by simple and biosafe approaches is still a great challenge. Here, an all-natural hydrogel with the ability to regulate macrophage heterogeneity is developed to promote angiogenesis and diabetic wound healing. The protocatechuic aldehyde hybridized collagen-based all-natural hydrogel exhibits good bioadhesive and antibacterial properties as well as reactive oxygen species scavenging ability. More importantly, the hydrogel is able to convert M1 macrophages into M2 macrophages without the need for any additional ingredients or external intervention. This simple and safe immunomodulatory approach shows great application potential for shortening the inflammatory phase of diabetic wound repair and accelerating wound healing.

Multiomics integration reveals the effect of Orexin A on glioblastoma.

Objectives: This study involved a multi-omics analysis of glioblastoma (GBM) samples to elaborate the potential mechanism of drug treatment. Methods: The GBM cells treated with or without orexin A were acquired from sequencing analysis. Differentially expressed genes/proteins/metabolites (DEGs/ DEPs/ DEMs) were screened. Next, combination analyses were conducted to investigate the common pathways and correlations between the two groups. Lastly, transcriptome-proteome-metabolome association analysis was carried out to determine the common pathways, and the genes in these pathways were analyzed through Kaplan-Meier (K-M) survival analysis in public databases. Cell and animal experiments were performed to investigate the anti-glioma activity of orexin A. Results: A total of 1,527 DEGs, 52 DEPs, and 153 DEMs were found. Moreover, the combination analyses revealed that 6, 4, and 1 common pathways were present in the transcriptome-proteome, proteome-metabolome, and transcriptome-metabolome, respectively. Certain correlations were observed between the two data sets. Finally, 11 common pathways were discovered in association analysis, and 138 common genes were screened out in these common pathways. Six genes showed significant differences in terms of survival in both TCGA and CGGA. In addition, orexin A inhibited the proliferation, migration, and invasion of glioma in vitro and in vivo. Conclusion: Eleven common KEGG pathways with six common genes were found among different omics participations, revealing the underlying mechanisms in different omics and providing theoretical basis and reference for multi-omics research on drug treatment.

Emerging trends and hotspots in metabolic dysfunction-associated fatty liver disease (MAFLD) research from 2012 to 2021: A bibliometric analysis.

Background: Metabolic dysfunction-associated fatty liver disease (MAFLD) has become the most common chronic liver disease. MAFLD is a major risk factor for end-stage liver disease including cirrhosis and primary liver cancer. The pathogenesis of MAFLD is complex and has not yet been clarified. To the best of our knowledge, few studies have conducted quantitative bibliometric analysis to evaluate published MAFLD research. In this study, we conducted a comprehensive analysis of MAFLD publications over the past decade to summarize the current research hotspots and predict future research directions in this field. Methods: Articles into MAFLD published from 2012 to 2021 were identified from the Science Citation Index-Expanded of Web of Science Core Collection. CiteSpace software, VOSviewer, the "bibliometrix" R package, and the Online Analysis Platform of Literature Metrology were used to analyze the current publication trends and hotspots. Results: We retrieved 13959 English articles about MAFLD published from 2012 to 2021. Primary sites of publication were dominated by the United States until 2014, when China became the source of most published MAFLD-related research papers. The United States was found to be the most engaged country in international cooperative efforts. Shanghai Jiao Tong University was the most productive institution. Loomba R was the most productive author with 123 articles. The co-cited keyword cluster tag showed ten main clusters: #0 liver fibrosis, #1 hemoglobin, #2 metabolic associated fatty liver disease, #3 egcg, #4 myocardial infarction, #5 heart disease, #6 pnpla3, #7 hepatocellular carcinoma, #8 noninvasive marker, and #9 children. Keyword burst analysis showed that gut microbiota was the highest-intensity research hotspot. Conclusion: In the past decade, the number of publications on MAFLD increased dramatically, especially in the last three years. Gut microbiota became an important research direction for etiological and therapeutic investigations into MAFLD. Insulin resistance was also a key factor in studying the development of MAFLD in recent years. Liver fibrosis was an important focus of disease development. This study provides systematic information, helps guide future research, and helps to identify mechanisms and new treatment methods for MAFLD.

Targeting RNA:protein interactions with an integrative approach leads to the identification of potent YBX1 inhibitors.

RNA-protein interactions (RPIs) are promising targets for developing new molecules of therapeutic interest. Nevertheless, challenges arise from the lack of methods and feedback between computational and experimental techniques during the drug discovery process. Here, we tackle these challenges by developing a drug screening approach that integrates chemical, structural and cellular data from both advanced computational techniques and a method to score RPIs in cells for the development of small RPI inhibitors; and we demonstrate its robustness by targeting Y-box binding protein 1 (YB-1), a messenger RNA-binding protein involved in cancer progression and resistance to chemotherapy. This approach led to the identification of 22 hits validated by molecular dynamics (MD) simulations and nuclear magnetic resonance (NMR) spectroscopy of which 11 were found to significantly interfere with the binding of messenger RNA (mRNA) to YB-1 in cells. One of our leads is an FDA-approved poly(ADP-ribose) polymerase 1 (PARP-1) inhibitor. This work shows the potential of our integrative approach and paves the way for the rational development of RPI inhibitors.