Physician and Artificial Intelligence Chatbot Responses to Cancer Questions From Social Media.

Importance: Artificial intelligence (AI) chatbots pose the opportunity to draft template responses to patient questions. However, the ability of chatbots to generate responses based on domain-specific knowledge of cancer remains to be tested. Objective: To evaluate the competency of AI chatbots (GPT-3.5 [chatbot 1], GPT-4 [chatbot 2], and Claude AI [chatbot 3]) to generate high-quality, empathetic, and readable responses to patient questions about cancer. Design, Setting, and Participants: This equivalence study compared the AI chatbot responses and responses by 6 verified oncologists to 200 patient questions about cancer from a public online forum. Data were collected on May 31, 2023. Exposures: Random sample of 200 patient questions related to cancer from a public online forum (Reddit r/AskDocs) spanning from January 1, 2018, to May 31, 2023, was posed to 3 AI chatbots. Main Outcomes and Measures: The primary outcomes were pilot ratings of the quality, empathy, and readability on a Likert scale from 1 (very poor) to 5 (very good). Two teams of attending oncology specialists evaluated each response based on pilot measures of quality, empathy, and readability in triplicate. The secondary outcome was readability assessed using Flesch-Kincaid Grade Level. Results: Responses to 200 questions generated by chatbot 3, the best-performing AI chatbot, were rated consistently higher in overall measures of quality (mean, 3.56 [95% CI, 3.48-3.63] vs 3.00 [95% CI, 2.91-3.09]; P < .001), empathy (mean, 3.62 [95% CI, 3.53-3.70] vs 2.43 [95% CI, 2.32-2.53]; P < .001), and readability (mean, 3.79 [95% CI, 3.72-3.87] vs 3.07 [95% CI, 3.00-3.15]; P < .001) compared with physician responses. The mean Flesch-Kincaid Grade Level of physician responses (mean, 10.11 [95% CI, 9.21-11.03]) was not significantly different from chatbot 3 responses (mean, 10.31 [95% CI, 9.89-10.72]; P > .99) but was lower than those from chatbot 1 (mean, 12.33 [95% CI, 11.84-12.83]; P < .001) and chatbot 2 (mean, 11.32 [95% CI, 11.05-11.79]; P = .01). Conclusions and Relevance: The findings of this study suggest that chatbots can generate quality, empathetic, and readable responses to patient questions comparable to physician responses sourced from an online forum. Further research is required to assess the scope, process integration, and patient and physician outcomes of chatbot-facilitated interactions.

The clinical manifestations and molecular pathogenesis of radiation fibrosis.

Advances in radiation techniques have enabled the precise delivery of higher doses of radiotherapy to tumours, while sparing surrounding healthy tissues. Consequently, the incidence of radiation toxicities has declined, and will likely continue to improve as radiotherapy further evolves. Nonetheless, ionizing radiation elicits tissue-specific toxicities that gradually develop into radiation-induced fibrosis, a common long-term side-effect of radiotherapy. Radiation fibrosis is characterized by an aberrant wound repair process, which promotes the deposition of extensive scar tissue, clinically manifesting as a loss of elasticity, tissue thickening, and organ-specific functional consequences. In addition to improving the existing technologies and guidelines directing the administration of radiotherapy, understanding the pathogenesis underlying radiation fibrosis is essential for the success of cancer treatments. This review integrates the principles for radiotherapy dosimetry to minimize off-target effects, the tissue-specific clinical manifestations, the key cellular and molecular drivers of radiation fibrosis, and emerging therapeutic opportunities for both prevention and treatment.

Progress in site-specific cancer mortality in Canada over the last 70 years.

In Canada, the absolute number of cancer deaths has been steadily increasing, however, age-standardized cancer mortality rates peaked decades ago for most cancers. The objective of this study was to estimate the reduction in deaths for each cancer type under the scenario where peak mortality rates had remained stable in Canada. Data for this study were obtained the Global Cancer Observatory and Statistics Canada. We estimated age-standardized mortality rates (ASMR, per 100,000) from 1950 to 2022, standardized to the 2011 Canadian standard population. We identified peak mortality rates and applied the age-specific mortality rates from the peak year to the age-specific Canadian population estimates for subsequent years (up to 2022) to estimate the number of expected deaths. Avoided cancer deaths were the difference between the observed and expected number of cancer deaths. There have been major reductions in deaths among cancers related to tobacco consumption and other modifiable lifestyle habits (417,561 stomach; 218,244 colorectal; 186,553 lung; 66,281 cervix; 32,732 head and neck; 27,713 bladder; 22,464 leukemia; 20,428 pancreas; 8863 kidney; 3876 esophagus; 290 liver). There have been 201,979 deaths avoided for female-specific cancers (breast, cervix, ovary, uterus). Overall, there has been a 34% reduction in mortality for lung cancer among males and a 9% reduction among females. There has been a significant reduction in cancer mortality in Canada since site-specific cancer mortality rates peaked decades ago for many cancers. This shows the exceptional progress made in cancer control in Canada due to substantial improvements in prevention, screening, and treatment. This study highlights priority areas where more attention and investment are needed to achieve progress.

Reliability and Variability of Ki-67 Digital Image Analysis Methods for Clinical Diagnostics in Breast Cancer.

Ki-67 is a nuclear protein associated with proliferation, and a strong potential biomarker in breast cancer, but is not routinely measured in current clinical management owing to a lack of standardization. Digital image analysis (DIA) is a promising technology that could allow high-throughput analysis and standardization. There is a dearth of data on the clinical reliability as well as intra- and interalgorithmic variability of different DIA methods. In this study, we scored and compared a set of breast cancer cases in which manually counted Ki-67 has already been demonstrated to have prognostic value (n = 278) to 5 DIA methods, namely Aperio ePathology (Lieca Biosystems), Definiens Tissue Studio (Definiens AG), Qupath, an unsupervised immunohistochemical color histogram algorithm, and a deep-learning pipeline piNET. The piNET system achieved high agreement (interclass correlation coefficient: 0.850) and correlation (R = 0.85) with the reference score. The Qupath algorithm exhibited a high degree of reproducibility among all rater instances (interclass correlation coefficient: 0.889). Although piNET performed well against absolute manual counts, none of the tested DIA methods classified common Ki-67 cutoffs with high agreement or reached the clinically relevant Cohen's κ of at least 0.8. The highest agreement achieved was a Cohen's κ statistic of 0.73 for cutoffs 20% and 25% by the piNET system. The main contributors to interalgorithmic variation and poor cutoff characterization included heterogeneous tumor biology, varying algorithm implementation, and setting assignments. It appears that image segmentation is the primary explanation for semiautomated intra-algorithmic variation, which involves significant manual intervention to correct. Automated pipelines, such as piNET, may be crucial in developing robust and reproducible unbiased DIA approaches to accurately quantify Ki-67 for clinical diagnosis in the future.

Study on the effects and mechanisms of Wenzhong Bushen Formula in improving ovarian reserve decline in mice based on network pharmacology.

ETHNOPHARMACOLOGICAL RELEVANCE: The Wenzhong Bushen Formula (WZBSF) is a traditional Chinese medicine empirical formula known for its effects in tonifying qi, strengthening the spleen, warming the kidneys, promoting yang, regulating blood circulation, and balancing menstruation. Clinical evidence has demonstrated its significant efficacy in treating Diminished Ovarian Reserve (DOR) by improving ovarian reserves. However, the specific pharmacological mechanisms of WZBSF remain unclear. AIM OF THE STUDY: This study aims to investigate the mechanisms by which WZBSF improves ovarian reserve decline through network pharmacology and animal experiments. METHODS AND MATERIALS: WZBSF was analyzed using a dual UPLC-MS/MS and GC-MS platform. Effective components and targets of WZBSF were obtained from the TCMSP database and standardized using UniProt. Disease targets were collected from GeneCard, OMIM, PHARMGKB, and DisGeNET databases, with cross-referencing between the two sets of targets. A PPI protein interaction network was constructed using Cytoscape3.9.1 and STRING database, followed by KEGG and GO enrichment analysis using the Metascape database. Finally, an ovarian reserve decline model was established in mice, different doses of WZBSF were administered, and experimental validation was conducted through serum hormone detection, H&E staining, immunofluorescence (IF), immunohistochemistry (IHC), and Western blot analysis (WB). RESULTS: WZBSF shares 145 common targets with ovarian reserve decline. GO enrichment analysis revealed involvement in biological processes such as response to hormone stimulation and phosphatase binding, while KEGG analysis implicated pathways including the PI3K-AKT signaling pathway and FoxO signaling pathway. In mice with ovarian reserve decline, WZBSF restored weight gain rate, increased ovarian index, normalized estrous cycles, reversed serum hormone imbalances, restored various follicle counts, and improved ovarian morphology. Additionally, WZBSF reduced p-AKT and p-FOXO3a levels, preventing excessive activation of primordial follicles and maintaining ovarian reserve. CONCLUSION: WZBSF can ameliorate cyclophosphamide and busulfan-induced ovarian reserve decline, and its mechanism may be associated with the inhibition of the PI3K/AKT/FOXO3a signaling pathway.

AI improves accuracy, agreement and efficiency of pathologists for Ki67 assessments in breast cancer.

The Ki-67 proliferation index (PI) guides treatment decisions in breast cancer but suffers from poor inter-rater reproducibility. Although AI tools have been designed for Ki-67 assessment, their impact on pathologists' work remains understudied. 90 international pathologists were recruited to assess the Ki-67 PI of ten breast cancer tissue microarrays with and without AI. Accuracy, agreement, and turnaround time with and without AI were compared. Pathologists' perspectives on AI were collected. Using AI led to a significant decrease in PI error (2.1% with AI vs. 5.9% without AI, p < 0.001), better inter-rater agreement (ICC: 0.70 vs. 0.92; Krippendorff's α: 0.63 vs. 0.89; Fleiss' Kappa: 0.40 vs. 0.86), and an 11.9% overall median reduction in turnaround time. Most pathologists (84%) found the AI reliable. For Ki-67 assessments, 76% of respondents believed AI enhances accuracy, 82% said it improves consistency, and 83% trust it will improve efficiency. This study highlights AI's potential to standardize Ki-67 scoring, especially between 5 and 30% PI-a range with low PI agreement. This could pave the way for a universally accepted PI score to guide treatment decisions, emphasizing the promising role of AI integration into pathologist workflows.

Ambient ozone pollution impairs glucose homeostasis and contributes to renal function decline: Population-based evidence.

Particulate matter pollution could increase the risk of kidney disease, while evidence for ozone exposure is less well-established. Here, we aimed to evaluate the effect of ozone pollution on renal function and explore mechanisms. We first conducted a cross-sectional study based on Wuhan Chronic Disease Cohort Study baseline information. We recruited 2699 eligible participants, estimated their residential ozone concentrations, collected fasting peripheral blood samples for biochemical analysis and calculated the estimated glomerular filtration rate (eGFR). The linear regression model was applied to evaluate the long-term association between ozone pollution and eGFR. Then, we recruited another 70 volunteers as a panel with 8 rounds follow-up visits. We calculated the eGFR and measured fasting blood glucose and lipid levels. The linear mixed-effect model along with mediation analysis were performed to confirm the short-term association and explore potential mechanisms, respectively. For the long-term association, a 10.95 µg/m3 increment of 3-year ozone exposure was associated with 2.96 mL/min/1.73 m2 decrease in eGFR (95%CI: -4.85, -1.06). Furthermore, the drinkers exhibited a pronounced declination of eGFR (-7.46 mL/min/1.73 m2, 95%CI: -11.84, -3.08) compared to non-drinkers in relation to ozone exposure. Additionally, a 19.02 µg/m3 increase in 3-day ozone concentrations was related to 2.51 mL/min/1.73 m2 decrease in eGFR (95%CI: -3.78, -1.26). Hyperglycemia and insulin resistance mediated 12.2% and 16.5% of the aforementioned association, respectively. Our findings indicated that higher ozone pollution could affect renal function, and the hyperglycemia and insulin resistance linked to ozone might be the underlying mechanisms.

Prospective study of e-cigarette use and respiratory symptoms in adolescents and young adults.

RATIONALE: Electronic cigarette (e-cigarette) aerosol contains volatile aldehydes, including flavourings and oxidant metals with known pulmonary toxicity. OBJECTIVES: To evaluate the associations of e-cigarette use with symptoms of wheeze, bronchitic symptoms and shortness of breath (SOB) across 4 years of prospective data. METHODS: Participants completed questionnaires on respiratory symptoms and past 30-day e-cigarette, cigarette and cannabis use in 2014 (wave 1; N=2094; mean age 17.3 years, SD=0.6 years). Follow-up information was collected in 2015 (wave 2; n=1609), 2017 (wave 3; n=1502) and 2018 (wave 4; n=1637) using online surveys. Mixed-effects logistic regression models evaluated associations of e-cigarette use with respiratory symptoms. MEASUREMENTS AND MAIN RESULTS: Participants were mostly Hispanic white (51.8%) and evenly representative by sex (49.6% female; 50.4% male). Compared with never e-cigarette users, past 30-day e-cigarette users reported increased odds of wheeze (OR 1.81; 95% CI 1.28, 2.56), bronchitic symptoms (OR 2.06; 95% CI 1.58, 2.69) and SOB (OR 1.78; 95% CI 1.23, 2.57), adjusting for study wave, age, sex, race, lifetime asthma diagnosis and parental education. Effect estimates were attenuated (wheeze (OR 1.41; 95% CI 0.99, 2.01), bronchitic symptoms (OR 1.55; 95% CI 1.18, 2.05), SOB (OR 1.48; 95% CI 1.01, 2.18)), after adjusting additionally for current cigarette use, cannabis use and secondhand exposure to e-cigarettes/cigarettes/cannabis. CONCLUSIONS: E-cigarette use in young adults was associated with respiratory symptoms, independent of combustible cannabis and cigarette exposures.

Progress in cancer control leads to a substantial number of cancer deaths avoided in Canada.

It is currently not known how many more cancer deaths would have occurred among Canadians if cancer mortality rates were unchanged following various modern human interventions. The objective of this study was to estimate the number of cancer deaths that have been avoided in Canada since the age-standardized overall cancer mortality rate peaked in 1988. We applied the age-specific overall cancer mortality rates from 1988 to the Canadian population for all subsequent years to estimate the number of expected deaths. Avoided cancer deaths were estimated as the difference between the observed and expected number of cancer deaths for each year. Since 1988, there have been 372 584 (standardized mortality ratio = 0.77) and 120 045 (standardized mortality ratio = 0.90) avoided cancer deaths in males and females, respectively (492 629 total). Nearly half a million cancer deaths have been avoided in Canada since the overall cancer mortality rate peaked, which demonstrates the exceptional progress made in modern cancer control in Canada.

An immunomodulating peptide with potential to suppress tumour growth and autoimmunity.

Cancers and autoimmune diseases commonly co-exist and immune checkpoint inhibitor therapy (ICI) exacerbates autoimmune pathologies. We recently described a lipidic peptide, designated IK14004, that promotes expansion of immunosuppressive T regulatory (Treg) cells and uncouples interleukin-2 from interferon-gamma production while activating CD8+ T cells. Herein, we report IK14004-mediated inhibition of Lewis lung cancer (LLC) growth and re-invigoration of splenocyte-derived exhausted CD4+ T cells. In human immune cells from healthy donors, IK14004 modulates expression of the T cell receptor α/ß subunits, induces Type I IFN expression, stimulates natural killer (NK) cells to express NKG2D/NKp44 receptors and enhances K562 cytotoxicity. In both T and NK cells, IK14004 alters the IL-12 receptor ß1/ß2 chain ratio to favour IL-12p70 binding. Taken together, this novel peptide offers an opportunity to gain further insight into the complexity of ICI immunotherapy so that autoimmune responses may be minimised without promoting tumour evasion from the immune system.

LncRNA HOTAIR regulates the PI3K/AKT pathway via the miR-126-3p/PIK3R2 axis to participate in synovial angiogenesis in rheumatoid arthritis.

BACKGROUND: The abnormal expression of long noncoding RNA (LncRNA) HOTAIR has been associated with synovial angiogenesis in rheumatoid arthritis (RA). The aim of this study is to investigate whether LncRNA HOTAIR plays a role in synovial angiogenesis in RA by regulating the phosphoinositide 3-kinase/protein kinase B (PI3K/AKT) pathway through the miR-126-3p/PIK3R2 axis. METHODS: In this study, we conducted in vitro experiments by designing overexpression plasmids and small interfering RNAs targeting LncRNA HOTAIR and then transfected them into rheumatoid arthritis fibroblast-like synoviocytes (RA-FLS). We then co-cultured the RA-FLS with human umbilical vein endothelial cells (HUVEC) to establish a RA-FLS-induced HUVEC model. We investigated the effects of LncRNA HOTAIR on the proliferation, migration, lumen forming ability of HUVEC, as well as the expression of synovial endothelial cell markers, angiogenic factors, and the PI3K/AKT pathway. To validate the interactions between LncRNA HOTAIR, miR-126-3p, and PIK3R2, we used bioinformatics and luciferase reporter experiments. We also employed real-time fluorescence quantitative, Western blotanalysis, and immunofluorescence techniques to analyze the target genes and proteins. RESULTS: The expression of LncRNA HOTAIR was upregulated in HUVEC induced by RA-FLS. The overexpression of LncRNA HOTAIR significantly increased the expression of vascular endothelial growth factor, basic fibroblast growth factor, CD34, and CD105 in HUVEC, promoting their proliferation, migration, and lumen formation. At the same time, the overexpression of LncRNA HOTAIR inhibited the expression of miR-126-3p, promoted the expression of PIK3R2, activated the PI3K/AKT pathway, and promoted the expression of PI3K, AKT and phosphorylated-AKT, while the silence of LncRNA HOTAIR reversed these expressions. Bioinformatics and double luciferase reporter gene experiments confirmed the targeting relationship among LncRNA HOTAIR, miR-126-3p, and PIK3R2. Finally, the rescue experiments showed that PI3K agonists could reverse the inhibitory effect of silent LncRNA HOTAIR on HUVEC. CONCLUSION: LncRNA HOTAIR has the potential to activate the PI3K/AKT pathway, likely through the regulatory axis involving miR-126-3p/PIK3R2, consequently contributing to synovial angiogenesis in RA.

Diagnostic value of high-risk HPV E6/E7 mRNA in patients with ASCUS.

OBJECTIVE: To investigate the infection status of high-risk human papillomavirus (HR-HPV) E6/E7 mRNA in patients with a cytological diagnosis of "atypical squamous cells of undetermined significance" (ASCUS) and to analyze the pathogenic rate of different high-risk HPV subtypes combined with biopsy pathological results to provide a more accurate basis for managing ASCUS patients. METHODS: A total of 1387 patients with ASCUS and HPV E6/E7 mRNA positivity who were referred for colposcopy were retrospectively analyzed. They were divided into HPV16+, 18/45 + and other HR-HPV + groups premenopausal and postmenopausal groups. The pathological results of the biopsy were divided into the LSIL- group (including normal and low-grade squamous intraepithelial lesions) and the HSIL + group (including high-grade squamous intraepithelial lesions and higher lesions). SPSS was used for the analysis. RESULTS: The age group 31-40 years had the highest level of HPV16+, and HPV18/45 + was the highest in the 41-50 years group. The detection rates of HSIL + in the HPV16+, HPV18/45+, HPV 16/18/45 + and Other HR-HPV + groups were 48.4%, 18.8%, 43.9% and 15.0%, respectively. The infection rates of HPV16/18/45 in postmenopausal and premenopausal women were 42.4% and 34.3%, respectively. In the HPV18/45 group, the incidence of HSIL + was 30.0% in postmenopausal women and 15.0% in premenopausal women (P < 0.01). In the HPV 16 + and Other HR-HPV + groups, the incidence of HSIL + in postmenopausal patients was not significantly different from that in premenopausal patients. The incidence of cervical cancer in postmenopausal patients is significantly higher than that in premenopausal patients. CONCLUSIONS: Colposcopy referral or further biopsy is recommended for all ASCUS patients with HPV16/18/45E6/E7 mRNA positivity and postmenopausal patients with HR-HPVE6/E7 mRNA positivity. For premenopausal ASCUS patients with other HR-HPV E6/E7 mRNA positivity, colposcopy should be performed if possible, depending on the specific situation, to achieve early detection and diagnosis.

Quantitative analysis of contrast-enhanced ultrasonography in rat models of hepatic acute graft-versus-host disease.

Background: Hepatic acute graft-versus-host disease (aGVHD) is a major life-threatening complication of allogeneic hematopoietic stem cell transplantation (allo-HSCT). We hypothesized that contrast-enhanced ultrasound (CEUS) could serve as a new imaging biomarker in early diagnosis of hepatic aGVHD by detecting liver microcirculation. Methods: Thirty Wistar rats received allo-HSCT were finally included after excluding 9 rats, and they were randomly divided into 5 groups (1- to 5-week groups, 6 per group). Six rats were used for the control group without any intervention. We observed the clinical scores, serum liver enzyme levels and liver CEUS parameters of rats in each group. Hepatic aGVHD was finally confirmed by histopathologic analysis. The diagnostic performance of CEUS parameters in detecting GVHD was evaluated by comparing the area under the receiver operating curve (AUC) values. Results: After HSCT, the rats developed ruffling of fur, maculopapular rash, weight loss, accompanied by increased clinical scores. Serum liver enzymes were significantly higher than those in the control group from the third week, especially alkaline phosphatase, while CEUS parameters, peak intensity (PI) and mean transit time (MTT), changed in the second week (P<0.001). Compared with non-aGVHD group, the PI was significantly decreased while time to peak and MTT were prolonged in aGVHD group. CEUS parameters were more strongly correlated with pathological grade than serology. PI was an independent predictor for hepatic aGVHD. The AUC of CEUS parameters for diagnosing hepatic aGVHD was 0.933 (95% CI: 0.779-0.992), which was higher than that of clinical scores (AUC =0.748, 95% CI: 0.557-0.888, P=0.032) and serological markers (AUC =0.902, 95% CI: 0.737-0.980, P=0.694). Conclusions: CEUS exhibits promising applications as a quantitative method to detect hepatic aGVHD and early liver damage.

Omitting Radiotherapy after Breast-Conserving Surgery in Luminal A Breast Cancer.

BACKGROUND: Adjuvant radiotherapy is prescribed after breast-conserving surgery to reduce the risk of local recurrence. However, radiotherapy is inconvenient, costly, and associated with both short-term and long-term side effects. Clinicopathologic factors alone are of limited use in the identification of women at low risk for local recurrence in whom radiotherapy can be omitted. Molecularly defined intrinsic subtypes of breast cancer can provide additional prognostic information. METHODS: We performed a prospective cohort study involving women who were at least 55 years of age, had undergone breast-conserving surgery for T1N0 (tumor size <2 cm and node negative), grade 1 or 2, luminal A-subtype breast cancer (defined as estrogen receptor positivity of ≥1%, progesterone receptor positivity of >20%, negative human epidermal growth factor receptor 2, and Ki67 index of ≤13.25%), and had received adjuvant endocrine therapy. Patients who met the clinical eligibility criteria were registered, and Ki67 immunohistochemical analysis was performed centrally. Patients with a Ki67 index of 13.25% or less were enrolled and did not receive radiotherapy. The primary outcome was local recurrence in the ipsilateral breast. In consultation with radiation oncologists and patients with breast cancer, we determined that if the upper boundary of the two-sided 90% confidence interval for the cumulative incidence at 5 years was less than 5%, this would represent an acceptable risk of local recurrence at 5 years. RESULTS: Of 740 registered patients, 500 eligible patients were enrolled. At 5 years after enrollment, recurrence was reported in 2.3% of the patients (90% confidence interval [CI], 1.3 to 3.8; 95% CI, 1.2 to 4.1), a result that met the prespecified boundary. Breast cancer occurred in the contralateral breast in 1.9% of the patients (90% CI, 1.1 to 3.2), and recurrence of any type was observed in 2.7% (90% CI, 1.6 to 4.1). CONCLUSIONS: Among women who were at least 55 years of age and had T1N0, grade 1 or 2, luminal A breast cancer that were treated with breast-conserving surgery and endocrine therapy alone, the incidence of local recurrence at 5 years was low with the omission of radiotherapy. (Funded by the Canadian Cancer Society and the Canadian Breast Cancer Foundation; LUMINA ClinicalTrials.gov number, NCT01791829.).

Spatial transcriptomics analysis of esophageal squamous precancerous lesions and their progression to esophageal cancer.

Esophageal squamous precancerous lesions (ESPL) are the precursors of esophageal squamous cell carcinoma (ESCC) including low-grade and high-grade intraepithelial neoplasia. Due to the absence of molecular indicators, which ESPL will eventually develop into ESCC and thus should be treated is not well defined. Indicators, for predicting risks of ESCC at ESPL stages, are an urgent need. We perform spatial whole-transcriptome atlas analysis, which can eliminate other tissue interference by sequencing the specific ESPL regions. In this study, the expression of TAGLN2 significantly increases, while CRNN expression level decreases along the progression of ESCC. Additionally, TAGLN2 protein level significantly increases in paired after-progression tissues compared with before-progression samples, while CRNN expression decreases. Functional studies suggest that TAGLN2 promotes ESCC progression, while CRNN inhibits it by regulating cell proliferation. Taken together, TAGLN2 and CRNN are suggested as candidate indicators for the risk of ESCC at ESPL stages.

Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics.

Artificial intelligence (AI) and machine learning (ML) are becoming critical in developing and deploying personalized medicine and targeted clinical trials. Recent advances in ML have enabled the integration of wider ranges of data including both medical records and imaging (radiomics). However, the development of prognostic models is complex as no modeling strategy is universally superior to others and validation of developed models requires large and diverse datasets to demonstrate that prognostic models developed (regardless of method) from one dataset are applicable to other datasets both internally and externally. Using a retrospective dataset of 2,552 patients from a single institution and a strict evaluation framework that included external validation on three external patient cohorts (873 patients), we crowdsourced the development of ML models to predict overall survival in head and neck cancer (HNC) using electronic medical records (EMR) and pretreatment radiological images. To assess the relative contributions of radiomics in predicting HNC prognosis, we compared 12 different models using imaging and/or EMR data. The model with the highest accuracy used multitask learning on clinical data and tumor volume, achieving high prognostic accuracy for 2-year and lifetime survival prediction, outperforming models relying on clinical data only, engineered radiomics, or complex deep neural network architecture. However, when we attempted to extend the best performing models from this large training dataset to other institutions, we observed significant reductions in the performance of the model in those datasets, highlighting the importance of detailed population-based reporting for AI/ML model utility and stronger validation frameworks. We have developed highly prognostic models for overall survival in HNC using EMRs and pretreatment radiological images based on a large, retrospective dataset of 2,552 patients from our institution.Diverse ML approaches were used by independent investigators. The model with the highest accuracy used multitask learning on clinical data and tumor volume.External validation of the top three performing models on three datasets (873 patients) with significant differences in the distributions of clinical and demographic variables demonstrated significant decreases in model performance. Significance: ML combined with simple prognostic factors outperformed multiple advanced CT radiomics and deep learning methods. ML models provided diverse solutions for prognosis of patients with HNC but their prognostic value is affected by differences in patient populations and require extensive validation.

HOXC13-driven TIMM13 overexpression promotes osteosarcoma cell growth.

TIMM13 (translocase of inner mitochondrial membrane 13) located at the mitochondrial intermembrane space is vital for the integrity and function of mitochondria. We found that the mitochondrial protein TIMM13 is upregulated in human OS tissues and cells. In patient-derived primary OS cells and established cell lines, TIMM13 shRNA or knockout provoked mitochondrial dysfunction, causing mitochondrial depolarization, reactive oxygen species production, and oxidative injury, as well as lipid peroxidation, DNA damage, and ATP depletion. Moreover, TIMM13 depletion provoked OS cell apoptosis and inhibited cell proliferation and migration. Conversely, ectopic TIMM13 overexpression increased ATP contents, enhancing OS cell proliferation and migration. Moreover, we discovered that Akt-mTOR activation was inhibited with TIMM13 depletion in primary OS cells. Further studies revealed that HOXC13 (Homeobox C13)-dependent TIMM13 transcription was significantly increased in OS tissues and cells. Whereas TIMM13 transcription and expression were decreased following HOXC13 silencing in primary OS cells. In vivo, TIMM13 KO potently inhibited OS xenograft growth in the proximal tibia of nude mice. TIMM13 KO also induced Akt-mTOR inactivation, ATP depletion, oxidative injury, and apoptosis in the in situ OS tumors. Together, upregulation of the mitochondrial protein TIMM13 is important for OS cell growth, representing a novel and promising therapeutic target.

An immunomodulating peptide to counteract solar radiation-induced immunosuppression and DNA damage.

Ultraviolet radiation (UVR) induces immunosuppression and DNA damage, both of which contribute to the rising global incidence of skin cancer including melanoma. Nucleotide excision repair, which is activated upon UVR-induced DNA damage, is linked to expression of interleukin-12 (IL-12) which serves to limit immunosuppression and augment the DNA repair process. Herein, we report an immunomodulating peptide, designated IK14800, that not only elicits secretion of IL-12, interleukin-2 (IL-2) and interferon-gamma (IFN-γ) but also reduces DNA damage in the skin following exposure to UVR. Combined with re-invigoration of exhausted CD4+ T cells, inhibition of UVR-induced MMP-1 release and suppression of B16F10 melanoma metastases, IK14800 offers an opportunity to gain further insight into mechanisms underlying the development and progression of skin cancers.

Automatic knowledge extraction from Chinese electronic medical records and rheumatoid arthritis knowledge graph construction.

Background: Knowledge graphs are a powerful tool for organizing knowledge, processing information and integrating scattered information, effectively visualizing the relationships among entities and supporting further intelligent applications. One of the critical tasks in building knowledge graphs is knowledge extraction. The existing knowledge extraction models in the Chinese medical domain usually require high-quality and large-scale manually labeled corpora for model training. In this study, we investigate rheumatoid arthritis (RA)-related Chinese electronic medical records (CEMRs) and address the automatic knowledge extraction task with a small number of annotated samples from CEMRs, from which an authoritative RA knowledge graph is constructed. Methods: After constructing the domain ontology of RA and completing manual labeling, we propose the MC-bidirectional encoder representation from transformers-bidirectional long short-term memory-conditional random field (BERT-BiLSTM-CRF) model for the named entity recognition (NER) task and the MC-BERT + feedforward neural network (FFNN) model for the entity extraction task. The pretrained language model (MC-BERT) is trained with many unlabeled medical data and fine-tuned using other medical domain datasets. We apply the established model to automatically label the remaining CEMRs, and then an RA knowledge graph is constructed based on the entities and entity relations, a preliminary assessment is conducted, and an intelligent application is presented. Results: The proposed model achieved better performance than that of other widely used models in knowledge extraction tasks, with mean F1 scores of 92.96% in entity recognition and 95.29% in relation extraction. This study preliminarily confirmed that using a pretrained medical language model could solve the problem that knowledge extraction from CEMRs requires a large number of manual annotations. An RA knowledge graph based on the above identified entities and extracted relations from 1,986 CEMRs was constructed. Experts verified the effectiveness of the constructed RA knowledge graph. Conclusions: In this paper, an RA knowledge graph based on CEMRs was established, the processes of data annotation, automatic knowledge extraction, and knowledge graph construction were described, and a preliminary assessment and an application were presented. The study demonstrated the viability of a pretrained language model combined with a deep neural network for knowledge extraction tasks from CEMRs based on a small number of manually annotated samples.