As an alternative, 3D hydrogels have begun to emerge as simple, time‐, and cost‐saving systems. One of the most promising candidates, synthetic alkoxysilane‐PEG (polyethylene glycol)‐based hydrogels, are formed by “sol–gel” polymerization in an aqueous medium, which allows control over the incorporated elements. Our aims were to optimize siloxane‐PEG hydrogels for three different cell lines of skin origin and utilize these 3D hydrogels as a feasible drug  screening assay. A drastic increase in survival and the formation of cellular aggregates (spheroids) could be observed in A2058 melanoma cells, but not in keratinocyte and endothelial cell lines. A deep‐learning neural network was trained to recognize and distinguish between the cellular formations and allowed the fast processing of hundreds of microscopic images. We developed an artificial intelligence (AI)‐assisted application ( Our aim was to utilize siloxane‐polyethylene glycol (PEG) hydrogels as a feasible viability assay against daunorubicin. The formation of cellular aggregates (spheroids) could be observed in melanoma cells but not in keratinocyte and endothelial cell lines. An artificial intelligence (AI)‐assisted application that we developed indicated that melanoma cell spheroids treated with daunorubicin have better survival in a hydrogel containing 15% bis‐mono‐ethoxysilane‐PEG. Often, due to these misleading preclinical in vitro models, many anticancer candidates fail long before clinical trials [As the numbers of cancer patients increase worldwide, both pharmaceutical companies and the scientific community try to invest more into the development of novel chemotherapeutic drugs . During l trials .in vitro setting [Over the last decade, several sophisticated culture platforms were developed to mimic the tumor niche  in an  setting , 4. The in vitro assays, since the qualitative and quantitative composition of the synthetic materials can be controlled.Commercially available hydrogels are usually biomaterial‐based . Although they are theoretically ideal for 3D cell cultures, the tricky handling and varying lot‐to‐lot qualities do not make them suitable for high‐throughput screening of drugs. The question of reproducibility is a general problem with hydrogels of biological origin . Howeveret al. [Polyethylene glycol (PEG) is one of the most common synthetic building blocks for hydrogels due to their high hydrophilicity and biological inertness . PEG‐baset al. . The hydDespite the favorable properties of the aforementioned hydrogel, it was questionable whether this gel would be suitable for culturing melanoma cells, one of the most studied tumor types, and other skin related, but normal cells such as keratinocytes or microvascular endothelial cells, which may contribute to melanoma microenvironment. The 3D spatial arrangement of cells is crucial in the pathobiology of the melanoma as well as in the response to antitumor agent . It is aIn order to answer these questions, three cell lines of skin origin were chosen . Several PEG‐based hydrogels with increasing mesh size (“loosened network”) were synthetized and used as 3D model matrices, against a clinically used chemotherapeutic agent, daunorubicin (Dau). We chose Dau, an anthracycline‐type chemotherapeutic agent, since its efficacy is affected by dose‐limiting side‐effects  and drug‐resistance that can emerge easily . Our prehttps://github.com/enyecz/CancerDetector2), which uses only simple microscopic images for analysis.Since different cell aggregates and other cellular structures, which are more likely to form in hydrogels, can contribute to drug resistance, we also aimed to simplify the analysis of cellular morphology and aggregate formation in such gels. Z‐stacking is a commonly used method in microscopic analysis for 3D systems. However, it can be time‐consuming and requires instruments capable of Z‐stacking; therefore, it is not compatible with examining a wider sample size. Artificial intelligence (AI) supported recognition and processing can be an option in such cases. Therefore, in this project, we also aimed to design a neural network‐based application . Daunorubicin was a kind gift from Dr. Gábor Mező .Bis‐triethoxy‐sylilated‐PEG and bis‐dimethyl‐monoethoxy‐sililated PEG monomers were prepared as earlier reported , 14. Full‐glutamine, and 1% penicillin/streptomycin .Human melanoma cell line A2058, obtained from the European Collection of Authenticated Cell Cultures , was cultured in RPMI 1640 medium supplemented with 10% (v/v %) fetal bovine serum , 1% l‐glutamine, 1% pyruvate, 1% penicillin/streptomycin , and 1% nonessential amino acid and 4500 mg·L−1 glucose.HaCaT  cells were cultured in DMEM medium, supplemented with 10% FBS , 1% l‐glutamine, 1% penicillin/streptomycin , 1 μg·mL−1 hydrocortisone, and 10 ng·mL−1 EGF . The T25 culture flask  was coated previously with 0.02% gelatin solved in PBS .Human microvascular endothelial cell line, HMEC‐1 , was cultured in MCDB‐131 medium, supplemented with 10% FBS , 2% 2).All cells were propagated in standard cell culture conditions  was added to the monomer mixture with a final concentration of 3 mg·mL−1 and the hydrogel‐solution was diluted to 20 w/w % final concentration. This was directly followed by the distribution of 50–50 μL of monomer solution into a 96‐well optical bottom plate and was incubated for 24 h. Before cell seeding, the coated wells were washed two times with incomplete medium and three times with serum containing, complete cell culture medium.Hydrogels were prepared 24 h prior to cell seeding. A 25 w/w % solution of the monomers in incomplete, serum‐free RPMI 1640 medium with 1% m). After 24 h of treatment, 100–100 μL CellTiterGlo reagent was added to each well and the luminescence signal was measured by Fluoroskan FL Microplate Fluorometer and Luminometer .To define the IC50 values of Dau in 2D monolayer culture, CellTiterGlo  viability reagent was used. A2058 cells were seeded at a density of 10 000 cells/well; HaCaT cells were seeded at a density of 5000 cells/well; and HMEC‐1 cells were seeded at a density of 20 000 cells/well in 50–50 μL FBS containing medium on a 96‐well plate with optical bottom. Cells were then incubated for 48 h and then 50 μL/well of fresh, serum‐containing medium was added. At 96 h of culturing, cells were treated and incubated with Dau  , 16. At In case of measuring the cell viability in hydrogels, the cell viability data of the untreated cells were normalized to that of the 2D system and expressed as a percentage . When cell viability was evaluated after Dau treatment, the viable cell number in the Dau‐treated group was normalized to that of the corresponding untreated cells in each hydrogel type and 2D condition.zen blue 2.6 software .Images were captured (5 × Plan‐Apochromat λ/0.35 NA objective with 2 × tube lens) after treatment with Dau with Celldiscoverer 7 system  using the https://github.com/ultralytics/yolov5, Ultralytics YOLOv8, available online: https://github.com/ultralytics/ultralytics) perform very well. Note that YOLO has been in active development since 2015 by many large research groups and although it is using techniques slightly inferior to, for example, vision transformers such as Segformer, it is still an extremely sophisticated solution. The final source code doing complete image processing and its usage guide can be found at https://github.com/enyecz/CancerDetector2.For the evaluation of the cellular structures formed in the gels, we developed an AI‐assisted application by using a deep‐learning neural network. The application is based on semantic image segmentation. It is a process where a semantic label is assigned to each of the pixels of a given image. The goal is to identify semantically meaningful areas: in our case, to identify pixels belonging to cellular aggregations and “other pixels”, that is the segments of the background. There are many solutions for such a task. First, we made experiments with Google's Deeplab v3+  and SegfTriplicates were used for each assay and each measurement was repeated with different batches of the hydrogel. All quantitative data are presented as mean ± standard deviation (SD).originpro 2020 software . In case of the viability measurements, the statistical significance was determined by one‐way analysis of variance (ANOVA) followed by Tukey's post hoc test. When analyzing the number of the spheroids and average area of spheroids, the levels of significance were determined by paired, two‐tailed t‐test if the values of a given data series were compared to the 0‐h time point. Unpaired two‐tailed t‐test was used to determine significance if at given time points the values of the two hydrogels were compared. The changes were considered statistically significant if P‐value is < 0.05.The results were evaluated by MS Excel and et al. was intended for chondrocytes, but our goal was to optimize it for different cell lines representing tumor cells (A2058 cell line) or normal cells .in vitro chemotherapeutic drug screening. Three cell lines of skin origin were chosen: A2058 (human melanoma), HaCaT (human keratinocytes), and HMEC‐1 . First, the IC50 values of Dau—a clinically used chemotherapeutic drug—was determined for each cell line growing in monolayer (2D)  Figs . In the Overall, each cell line showed good cell viability in the matrices, which demonstrated that the hydrogels provided a suitable condition for cell cultures. However, prominent differences could be observed in terms of live/dead cell ratio after Dau treatment and in aggregate (spheroid) formation.In the case of HaCaT keratinocytes, neither 2D nor 3D hydrogels were preferred exclusively. The only significant difference was found in 15 mol% mPEG hydrogels. In case of the nontreated groups, ~ 20% more cells could be observed, compared with 2D control Fig. . HoweverHMEC‐1 endothelial cells showed less compatibility with the 3D system: Lower cell viability (~ 65–80%) was detected for the cells growing in the hydrogels than the cells cultured in 2D model (100%) Fig. . HoweverA2058 human melanoma cell line showed very different behavior compared with the previously mentioned HaCaT and HMEC‐1 cell lines representing normal cells. In case of the untreated living cells, a slow decrease in the ratio of the living cells was detected comparing to the 2D control with the increasing concentrations of mPEG in hydrogels Fig. .Like the other two cell lines, A2058 cells also tolerated the hydrogel matrices. A significant difference in the survival rate could be observed in case of the 15–20 mol% mPEG hydrogels, where the live/dead cell ratio was ~ 80–75% after Dau treatment, while in the 2D group, this was only ~ 42% Fig. . Unlike in vitro 3D model. Our system is unique as spheroid development is independent of these forces and both the individual cells and the spheroids coexist in the system.A2058 melanoma cell line showed the most prominent differences in hydrogel matrices, compared with 2D condition. In hydrogels containing 5–30 mol% mPEG, not only did the viability change, but elongated multicellular aggregates, called “spheroids” were also observed , we developed a deep learning‐based AI‐based image analysis application to quantify the changes in the number and the dimensions/extent of spheroids after Dau treatment. The trained neural‐network can distinguish between debris/spots/uncommon shapes and small spheroids on microscopic images in our hydrogel system. The application even allows the exclusion of small aggregates and partly out‐of‐picture spheroids, this feature is adjustable  of classical image analysis software  of the Dau treatment, new small cellular clusters appeared in both hydrogels, presumably in response to treatment. As a result, the number of spheroids evened out in the two gels (5–9 h), but later (12–22 h) spheroids number declined due to the cytotoxicity of Dau Fig. . These dNevertheless, it is important to note, that this analysis focused only on the changes in the multicellular aggregates and did not take into consideration the full number of individual cells.In the present study, we aimed to utilize a synthetic, PEG‐based 3D hydrogel that is easy to handle, compatible with wide variety of cells and can be used as a feasible and rapid viability assay against chemotherapeutic drug to test and compare the cellular responses. To this end, the hydrogels were optimized for three, different cell lines of skin origin representing tumor (A2058 melanoma cells) and normal cells  and were used in testing a chemotherapeutic drug, daunorubicin.https://github.com/enyecz/CancerDetector2).The inert matrices were tolerated well by all studied cell types; however, different changes in morphology and cell‐vitality could be observed. Hydrogels caused the most conspicuous differences in case of A2058 human melanoma cell line. Distinct cell‐assembly and aggregation could be observed in together with the increase in survival rate after Dau treatment. To analyze this phenomenon, an AI‐based application was developed to automatize the microscopic image processing. The application is free to use , the average area of spheroids are not only maintained, but also even increased after Dau treatment, which would suggest better survival. It was also observed that smaller cellular clusters appeared not long after treatment (3–6 h), but they were later destroyed. Early development of these smaller, short‐lived aggregates/spheroids is probably a response to treatment, but further studies are needed to fully understand the reason behind this phenomenon.It is also important to highlight the difference between the melanoma cells and the skin‐related normal cells in terms of spheroid formation and resistance against Dau treatment in our PEG‐based hydrogels. The highest survival rate after Dau treatment and in parallel the biggest 3D multicellular aggregates were detected in the case of A2058 melanoma cells. It is possible, that the spheroids, the formation of 3D aggregates by cell–cell interactions, protect against antitumor effects, because the cells in the spheroids are subjected a heterogeneous exposure to antitumor agent . The difIn conclusion, our 3D model and the application may not only be a more reliable model for drug screening assays but may also provide new insights into the mechanisms of tumorigenesis and drug‐resistance.The authors declare no conflict of interest.https://www.webofscience.com/api/gateway/wos/peer‐review/10.1002/2211‐5463.13719.The peer review history for this article is available at KNE was involved in conceptualization, methodology, investigation, writing—original draft, visualization, and funding acquisition. GE was involved in application development and writing—review & editing. EL was involved in methodology, investigation, writing—original draft, writing—review & editing, and supervision.Appendix S1. Full description of the synthesis of bis‐triethoxy‐sylilated‐PEG and bis‐dimethyl‐monoethoxy‐sililated PEG monomers.Fig. S1. Cytotoxic effect of daunorubicin (Dau) on A2058 human melanoma cell line.Fig. S2. Cytotoxic effect of daunorubicin (Dau) on HMEC‐1 human dermal microvascular endothelial cell line.Fig. S3. Cytotoxic effect of daunorubicin (Dau) on HaCaT human keratinocyte cell line.Fig. S4. Results of the image analysis of 10% mPEG hydrogels after treatment with daunorubicin (Dau) in comparison with untreated cells.Fig. S5. Results of the image analysis of 15% mPEG hydrogels after treatment with daunorubicin (Dau) in comparison with untreated cells.Click here for additional data file.Video S1. Video showing the effect of daunorubicin in A2058 cell spheroids in 10 mol% mPEG hydrogels.Click here for additional data file.Video S2. Video showing the effect of daunorubicin in A2058 cell spheroids in 15 mol% mPEG hydrogels.Click here for additional data file.


Colonoscopy is an important colorectal cancer (CRC) screening modality; however, not all high‐risk groups identified by fecal immunochemical test (FIT) and/or high‐risk factor questionnaire (HRFQ) undergo colonoscopy in time. The impact of delays in colonoscopy on CRC detection among high‐risk populations remains poorly understood, warranting further clarification.A retrospective study was conducted among CRC high‐risk population identified by Tianjin CRC screening program. According to the colonoscopy results after HRFQ and FIT, patients were classified into CRC, advanced adenoma, non‐advanced adenoma, and normal groups. The time interval between CRC screening and colonoscopy was investigated and its relationship with colonoscopy results. Logistic regression was performed to explore the risk factors of CRC detection.n = 39,630). People with positive FIT were more likely to undergo colonoscopy within 6 months, and detection rates of CRC and/or advanced adenoma were positively related to time intervals. Similar results were found in people with a negative FIT but positive HRFQ. A time interval longer than 6 months was a significant predictor of CRC detection in high‐risk populations.Among the high‐risk population without a history of CRC or polyps, 49,810 underwent HRFQ, FIT, and colonoscopy, and a time interval of fewer than 6 months was found for 79.56% of patients (For high‐risk people identified by CRC screening, especially those with a positive FIT, a time interval of 6 months was associated with an increased probability of CRC detection. Our findings emphasize that populations at high risk should undergo colonoscopy at least within 6 months. Delayed colonoscopy is associated with increased colorectal cancer detection in people at high risk for colorectal cancer. The main screening population was residents aged 60–74 years in 2012, 50–60 years in 2013, and 40–50 years in 2014. The same protocol was carried out from 2015 to 2017 and from 2018 to 2020. After providing informed consent, all participants answered a HRFQ followed by FIT. Patients that met one of the following conditions were attributed to the positive HRFQ: (a) patients with a first‐degree relative with CRC; (b) a history of cancer or intestinal polyps; (c) patients with two or more of the following: a history of chronic constipation, a history of chronic diarrhea, a history of bloody mucous stools, adverse life events  a history of chronic appendicitis or appendectomy, a history of chronic cholecystitis or gallstones. High‐risk population were defined as positive HRFQ or positive FIT. These high‐risk population were then recommended to undergo a free colonoscopy, and for those at risk who decide to have a colonoscopy, the procedure is usually completed within a month. Those who did not undergo the colonoscopy were reminded by telephone annually until completion. No deadlines were set for undergoing the colonoscopy.2.2Data were collected and entered into a database by experienced physicians. We analyzed data of all high‐risk individuals that underwent colonoscopy from 2012 to 2020, including demographics , time and results of HRFQ, FIT, and colonoscopy. Abnormal findings on colonoscopy were classified as CRC, advanced adenoma , and non‐advanced adenoma. Patients with benign diseases such as lipoma, diverticulum, and colitis were incorporated into the normal group for analysis. Patients were excluded from the study based on the following criteria: (a) a history of colonic polyps or CRC; (b) missing data; (c) unable to complete colonoscopy due to poor bowel preparation during the whole screening program . Unlike our previous article,2.3Calculated based on the time interval were the following indicators: (1) percentage distribution of colonoscopies; (2) detection of CRCs by TNM stages (% colonoscopies); (3) detection of advanced and non‐advanced adenoma (% colonoscopies). We divided the population into FIT‐negative or ‐positive groups and analyzed the changes in the detection rate of CRC at different intervals.2.4The primary exposure (predictor) variable was the time interval between CRC screenings and colonoscopy. Time intervals were divided into 10 groups: within 1 month (≤30 days), 1–2 months (31–60 days), 2–3 months (60–90 days), 3–4 months (91–120 days), 4–5 months (121–150 days), 5–6 months (151–180 days), 6–12 months (181–360 days), 13–24 months (361–720 days), 25–36 months (721–1080 days), and more than 36 months (≥1081 days).2.5p < 0.05 was statistically significant. All statistical analyses were conducted using R software, Version 4.1.2.A descriptive analysis was conducted to characterize demographics and clinical factors in the study cohort and CRC outcome rates based on the time to colonoscopy. We used logistic regression models to analyze the relationship between time to colonoscopy and outcome indicators, for example, CRC. Differences in CRC, advanced adenoma and non‐advanced adenoma between groups were assessed by univariate analysis. In multivariate logistic regression analysis, the significant factors from univariate analysis were further used to identify independent risk factors for advanced adenoma, CRC, and non‐advanced adenoma. All multivariate models were adjusted for age, gender, education, occupation, residence, FIT, history of chronic diarrhea, history of chronic constipation, history of bloody mucous stools, history of chronic appendicitis or appendectomy, history of chronic cholecystitis or gallstones, adverse life events, history of cancer, and history of CRC in a first‐degree relative at the time of FIT. The corresponding odds ratios (ORs) and confidence intervals (CIs) with 95% confidence were calculated for each independent risk factor. We used completion of colonoscopy within 1 month as our reference group. In sensitivity analyses, the reference group was redefined to include patients who had their colonoscopies within 8–30 days , <3 months and <6 months after identified as high risk; including members who had a history of colonic polyps prior to CRC screening; and then adding an exposure category of 1–7 days when 8–30 days was the reference group. Numerical data were described by the number of cases or constituent ratio. A value of 33.1n = 22,307, 44.78%). There were 33,469 (67.19%) positive FIT, and 21,915 (44.00%) were assessed as high risk by the questionnaire‐based risk assessment. A total of 1328 cases (2.67%) of CRC, 3150 cases (6.32%) of advanced adenoma, 17,297 cases (34.73%) of non‐advanced adenoma, and 28,035 cases (56.28%) of normal group were detected. Among the CRCs, there were 56 (4.22%) cases of stage 0, 255 (19.20%) cases of stage I, 328 (24.70%) cases of stage II, 296 (22.29%) cases of advanced CRC of stage III, and 55 (4.14%) cases of stage IV. The interval was less than 30 days for 19,631 (39.41%) participants, less than 6 months for 39,630 (79.56%) participants and more than 6 months for 10,180 (20.44%) participants  CRC cases, including 56 (4.22%), 255 (19.20%), and 328 (24.70%) cases at stages 0, I, and II, respectively. The proportion of advanced cases  increased in patients with intervals longer than 6 months  Figure . In cont3.3min 1.89, 95% CI 1.46–2.43)  and subgroup data (FIT positive/negative) could be considered as sensitivity analyses, we further performed sensitivity analyses by setting different reference groups in the time intervals. In sensitivity analyses Table , The fin4min 1.70, 95% CI 1.34–2.14), regardless of positive FIT or HRFQ results. Furthermore, CRC detection in populations with a positive FIT was significantly increased at longer intervals . These results provide an important reference for the optimal time of colonoscopy in high‐risk CRC populations.In this study, we analyzed the results of 49,810 people at high risk of CRC who underwent colonoscopy in the CRC screening program in Tianjin, China, and no significant increase in CRC risk was found with colonoscopy within 6 months after screening. When colonoscopy was performed more than 6 months later, the detection rate of CRC increased significantly , and the incidence of detection of advanced CRC was increased . Therefore, we recommend that colonoscopy for high‐risk populations should not exceed 6 months.Currently, the appropriate time interval is subject to significant heterogeneity due to differences in countries, medical institutions, medical personnel.min 1.82, 95% CI 1.10–2.97). But the significance of the risk stratification questionnaire for detecting CRC and advanced adenomas may be inferior to FIT.Risk stratification of various types of CRC plays a crucial role in screening.Even in people at low risk of CRC,There are many uncertainties in the development of CRC, and the association between detection rate and interval time is not a simple linear relationship. The main factors affecting CRC detection rate may be the transformation rate from advanced adenoma to CRC and from polyp to advanced adenoma. The annual progress rate from advanced adenoma to cancer is around 5%, and gradually increases with age. Even though FIT is not sensitive enough in such a long interval, it is still possible to recognize advanced adenoma before carcinogenesis. Therefore, we carried out CRC screening on a 3‐year cycle to improve the screening effect of CRC as much as possible.Compared with colonoscopy within 1 month, the risk of CRC and advanced adenoma detection in high‐risk populations was slightly reduced at intervals of less than 6 months. The possible reason might be the presence of prompting factor of colonoscopy among high‐risk people despite the screening program focused on asymptomatic people, which was consistent with conclusions of other studies.There were some limitations in our study. First, our data was based on a large‐scale screening among the population. Although we tried to collect all colonoscopy data, the overall colonoscopy compliance was not high, which might bias the sample data. Moreover, the information and influencing factors of patients in our statistics were limited; in some cases, patients might have undergone colonoscopy due to factors we failed to cover. Moreover, we were not able to obtain all CRC staging data because these data were not in our database for CRC screening. Last, no follow‐up was conducted to assess patient prognosis and hence, we could not assess the impact of delayed colonoscopy on survival, although we provided compelling evidence of the benefit of timely colonoscopy in high‐risk population.By analyzing CRC screening data in Tianjin, we confirmed that colonoscopy should be performed in time for asymptomatic people at high risk of CRC, especially those with a positive FIT. With an interval of more than 6 months, the risk of CRC detection was increased, while with an interval of more than 36 months, the risk of advanced adenomas and non‐advanced adenoma detection is increased in high‐risk groups. Therefore, it is essential to encourage high‐risk groups to undergo colonoscopy as early as possible using follow‐up or repeat screening.Mingqing Zhang: Conceptualization ; formal analysis ; funding acquisition ; investigation ; methodology ; project administration ; resources ; validation ; writing – original draft (lead). Yongdan Zhang: Formal analysis ; investigation ; methodology ; writing – review and editing . Wen Zhang: Data curation . Lizhong Zhao: Formal analysis ; investigation ; methodology ; project administration ; writing – review and editing . Haoren Jing: Investigation ; validation . Xiaojing Wu: Formal analysis ; validation . Lu Guo: Data curation . Haixiang Zhang: Data curation ; software . Yong Zhang: Data curation ; software . Siwei Zhu: Conceptualization ; supervision ; visualization . Shiwu Zhang: Conceptualization ; resources ; visualization ; writing – review and editing . Xipeng Zhang: Conceptualization ; funding acquisition ; resources ; supervision .This study was funded by Foundation of Tianjin Union Medical Center ; This work was funded by the foundation of committee on science and technology of Tianjin (21JCYBJC01090 and 21JCZDJC00990); This work was funded by Tianjin Key Medical Discipline  Construction Project (Number: TJYXZDXK‐044A). The funding source had no role in study design, data collection, analysis, or interpretation, report writing, or the decision to submit this paper for publication.The authors disclose no conflicts.The approval of a research ethics committee was not required, since this study is a descriptive analysis of individual data without any direct or indirect intervention on patients. And all investigations and methods used were in accordance with the Declaration of Helsinki.Data S1: Supporting InformationClick here for additional data file.


Ankylosing spondylitis (AS) is a condition that is treated with nonsteroidal anti‐inflammatory drugs and biological drugs such as anti tumor necrosis factor alpha (TNF‐α). This study examined the prevalence of COVID‐19 among individuals with AS and compare it between those receiving and not receiving TNF‐α inhibitors.A cross‐sectional study was conducted at the rheumatology clinic of Imam Khomeini Hospital in Tehran, Iran. The study included patients with AS who sought treatment at the clinic. Demographic information, laboratory and radiographic findings, and disease activity were recorded through interviews and examinations using a questionnaire.A total of 40 patients were studied over the course of 1 year. Among them, 31 patients were administered anti‐TNF‐α drugs, with 15 patients (48.3%) receiving subcutaneous Altebrel (Etanercept), 3 patients (9.6%) receiving intravenous Infliximab, and 13 patients (41.9%) receiving subcutaneous Cinnora . Of the total, 7 patients (17.5%) tested positive for COVID‐19, 1 of whom was confirmed through both CT scan and polymerase chain reaction (PCR) testing, while the remaining 6 patients were confirmed only through PCR testing. All patients tested positive for COVID‐19 were male, and 6 of them had received Altebrel. Among the 9 AS patients who did not receive TNF inhibitors, 1 patient contracted SARS‐CoV‐2. The clinical symptoms experienced by these patients were mild, and hospitalization was not required. However, 1 patient who had insulin‐dependent type 1 diabetes and was receiving Infliximab required hospitalization. This patient exhibited more severe COVID‐19 symptoms, including high fever, pulmonary involvement, dyspnea, and decreased oxygen saturation. No cases of COVID‐19 were reported in the Cinnora treatment group. The use of any of the drugs did not demonstrate a significant relationship with the occurrence of COVID‐19 in patients.The use of the TNF‐α inhibitors in patients with AS, may be associated with reduced hospitalization and death rate in COVID‐19 cases. The use of the biological drugs in patients with ankylosing spondylitis, may be related to reducing hospitalization and death rate of COVID‐19. Spearman's or Pearson's tests were used to examine the relationship between continuous variables, while the χ2 test was used to investigate the relationship between categorical variables. p < 0.05 values were considered statistically significant. Also, the likelihood ratio was reported to indicate the value of the Pearson's correlation.Data analysis was performed using SPSS software  for both descriptive and inferential statistics. The normality was assessed using Kolmogorov−Smirnov 3A total of 40 patients were studied during the 1‐year study period. The mean age of patients was 38.03 ± 10.84 years. The mean duration of the disease was 6.41 ± 4.41 years (range: 1−20). Seven male patients (17.5%) had COVID‐19, of which 6 were positive by PCR test. One patient had more acute symptoms such as severe fever and pulmonary involvement on CT scan due to COVID‐19. Demographic and disease history information of patients are depicted in Table The mean age (±SD) was 37.7 ± 11.9 and 38.09 ± 10.8 years for COVID‐19 positive and negative groups, respectively. There was no significant association between age and infection rate. The ASDAS, BASDAI, and C‐reactive protein (CRP) values in both groups are presented in Table The mean ASDAS and BASDAI scores in patients who tested positive for COVID‐19 were higher, while CRP values were lower in these patients; however, the differences were not statistically significant. The mean ASDAS and CRP scores were higher in those who were AS patients ≤10 years, while BASDAI score was lower in these patients; also, the differences were not statistically significant. The frequency of use of NSAIDs and anti‐TNF drugs is presented in Table Six patients who tested positive for COVID‐19 were receiving Altebrel medication. The clinical symptoms experienced by these individuals, including cough and myalgia, were so mild that hospitalization was not required for any of them. However, 1 patient who was receiving Infliximab and had type 1 diabetes, requiring insulin treatment, needed to be hospitalized. This particular patient exhibited more severe COVID‐19 symptoms, such as high fever and pulmonary involvement observed on a CT scan, dyspnea, and decreased oxygen saturation. Additionally, no cases of COVID‐19 were reported in the Cinnora treatment group. The use of anti‐inflammatory and anti‐TNF drugs did not show a significant correlation with COVID‐19.44.1The treatment with anti‐TNF‐α agents is beneficial for patients with AS by improving pain, function, and disability.Anti‐TNF therapy has shown an inverse association with the outcome of death or hospital admission in COVID‐19 patients with inflammatory bowel diseases.Monotherapy of anti‐TNF in rheumatic disease has been associated with a lower rate of hospital admission for COVID‐19 patients.d‐dimer and pro‐thrombin fragments within 1 h of drug administration.Administration of anti‐TNF has been observed to result in the reduction of acute‐phase proteins, including CRP, serum amyloid A, haptoglobin, and fibrinogen, which are elevated in patients with rheumatoid arthritis (RA).4.2The first randomized controlled phase 3 trial of tocilizumab, an IL‐6 antagonist, in COVID‐19 infection did not show any difference in clinical status or mortality.4.3Studies in patients infected with coronavirus and influenza virus treated with corticosteroids showed a higher risk of complications and death.5The use of anti‐TNF drugs in AS patients who were infected with COVID‐19 was associated with a mild form of infection, without the need for hospitalization. However, no statistically significant correlation was found between anti‐TNF therapy and the severity or outcomes of COVID‐19. Due to the small sample size, the results of this study should not be generalized to all AS patients with COVID‐19 infection. Although the modest effect observed with these agents is promising, further studies should be conducted to explore the efficacy of other agents with higher efficiency. The potential of anti‐TNF therapy as a treatment for COVID‐19 is supported by both biological plausibility and observational clinical data. Further multicenter studies are needed to investigate this hypothesis.Shafieh Movassaghi and Elham Nezhadseifi: Conceptualization, writing—original draft. SeyedAhmad SeyedAlinaghi and Abdolrahman Rostamian: Analyzed the data, and reviewed and edited it. Seyed Reza Nejafizadeh: Contributed to the questionnaire, review, and editing. All the authors have read and approved the final manuscript.The authors declare no conflict of interest.


A significant proportion of currently enrolled college students receive support for attention deficit/hyperactivity disorder (ADHD) and these students are often at risk of academic failure. Retrieval practice or self-testing is an effective, accessible, and affordable tool for improving academic performance. Three recent studies found conflicting results with regards to the effectiveness of retrieval practice in this population.The present study compared 36 individuals with ADHD to 36 controls. Participants studied Swahili-English word pairs that varied in difficulty. Half of the pairs were repeatedly studied, and the other half repeatedly tested.On a final test, all participants showed a benefit of retrieval practice relative to restudy and participant status did not moderate the effect. However, unmedicated individuals with ADHD performed worse overall, both during the encoding phase and on the final test, whereas medicated participants were not significantly different from controls.An examination of self-reported encoding strategies found unmedicated participants used fewer deep strategies at encoding, consistent with prior work on ADHD and memory. Although retrieval practice is effective in this group, improved strategy use may be necessary to ensure performance that is fully equivalent to that of students without ADHD. Attention deficit/hyperactivity disorder (ADHD) is characterized by inattentiveness and/or hyperactivity/impulsivity, high levels of distractibility, difficulty maintaining focus and sustaining attention . InitialLong-term memory is important for academic success, and adults with ADHD perform worse on tests of verbal long-term memory . Two soutesting effect (TE) and has been found across different types of materials and different populations , selected from a larger sample of over 300 participants who participated in a previous study on the benefits of retrieval practice. Control participants were selected from this pool to match individuals with ADHD in age, biological sex, GPA, and measures of cognitive performance  and via email, and the remaining 21 students signed up via the participant sign-up pools at the college as well as a state university and self-identified as having a diagnosis. Participants reported the diagnosis was made by a doctoral level therapist in seven cases, by a practitioner holding a master’s degree in two, and by a medical doctor in the remaining cases. Participants were asked to answer yes or no whether they were currently taking medication to treat their ADHD but were not asked to report the type(s) of medication used. Twenty-one participants (58%) reported taking medication at the time of the study and one regularly took medication but did not take it the day of the study. In addition to self-report, all participants, except for two individuals with ADHD, completed a current symptom checklist  that meaWe aimed to recruit as many participants as possible, and, at minimum, a sample size for participants with ADHD comparable to previous studies  were selected from the SD = 0.05), 0.55 (SD = 0.04), 0.72 (SD = 0.04), and 0.84 (SD = 0.07), from most difficult to easiest, respectively. The 24 pairs drawn from the two easiest levels constituted the Easy set of items and the 24 pairs drawn from the two hardest difficulty levels constituted the Difficult set. Half of the pairs from each difficulty set were assigned to the repeated study condition and half to the repeated test condition with the stimulus condition counterbalanced across participants.A set of 48 Swahili-English word pairs  appear for 7 s, during which time participants typed their response using the computer’s keyboard, followed by the intact pair for 1 s . Thus, the repeated test block included feedback. Pair order within blocks was randomized anew on each block. Responses during the encoding and final test phases were coded as correct if participants recalled the correct answer or minor spelling/morphological variations . See Participants first studied all 48 pairs, in random order, for 8 s each. They next completed four additional blocks of repeated study and repeated testing. The re-study block always preceded the repeated test block to avoid contamination from prior retrieval cf.. In the Two days later, participants returned to the lab and completed a final cued recall test. All 48 Swahili cues were presented, one at a time, in random order. Participants had unlimited time to respond and no feedback was given.Participants completed a set of cognitive tasks to measure individual differences in intelligence and working memory. As noted in the Participants section, this task battery was administered to allow us to match participants with ADHD to participants without ADHD on fluid intelligence, working memory and vocabulary.We used a computerized version of this measure of general fluid intelligence. On each trial, participants were presented a matrix of eight shapes/complex patterns and had to select one of four options that best completed the matrix across rows and columns. The task was self-paced and consisted of 48 trials of increasing difficulty .We used the automated version of this measure of verbal working memory as developed by In this computerized measure of visuospatial working memory, participants had to remember the order in which 2–5 locations lit up on a 4 × 4 grid . BetweenA computerized version of never or rarely) to 4 (very often) scale and higher scores (max = 72) reflect greater severity of symptoms.The measure consists of 18 questions asking participants to indicate how often, in the previous 6 months, they experienced specific behaviors, such as interrupting others, not finishing work, or feeling restless . ResponsThis measure consists of 12 questions assessing how students typically study and is a modification of a survey developed by Definitely cannot do it) to 100  to 3  scale with higher scores (max = 81) indicating greater test anxiety . The tasks were administered in such a manner that the two sessions lasted approximately an equal amount of time (90 min). At the conclusion of the second session, participants were thanked, debriefed, and compensated.We begin our results section by first reporting the demographic characteristics of each group. Although we matched participants on fluid intelligence, working memory and vocabulary, we measured other traits, academic self-efficacy and test anxiety, that we expected to differ between groups based on prior ADHD research . We thent values < 1. As expected, there was a significant difference in reported ADHD symptoms, t(68) = −4.47, p < 0.001, d = 1.1. There was also a significant difference in academic self-efficacy, t(70) = 2.94, p < 0.01, d = 0.69, with lower self-efficacy for learning in our ADHD group which is consistent with prior reports (t(70) = −1.26, p = 0.21. Greater test anxiety in ADHD has been reported in prior studies  = 9, p = 0.003. Whereas all of the control participants reported using self-testing, eight (22%) individuals with ADHD indicated they did not. Among those who did use self-testing, the groups did not differ with respect as to why , all ps > 0.23. The two groups did not differ in their responses to any of the other items, all ps > 0.08, suggesting that the groups were well matched in terms of their academic skills and learning habits.An examination of the responses to the study habits measure indicated few differences between participant groups. The two groups did not differ in their use of spacing or cramming, the extent to which they re-read textbooks or notes, or time of day during which they studied. However, consistent with previous research , individM = 0.33, SE = 0.03) performed worse than the cognitively matched control participants  during the encoding phase, F = 5.64, p = 0.020, p2η = 0.08. Performance improved across learning blocks, F = 212.56, p < 0.001, p2η = 0.75. All pairwise comparisons were significant at the 0.001 level following a Bonferroni correction for multiple comparisons. There was also a main effect of difficulty, F = 230.37, p < 0.001, p2η = 0.77. All pairwise comparisons were significant, ps ≤ 0.001. Pair difficulty and block interacted, F = 6.87, p = 0.001, p2η = 0.09. To explore the interaction, we examined the effect of block within each level of difficulty. All effects were significant, all Fs > 46.5, all ps < 0.001, as were all pairwise comparisons . The interaction was driven by a steeper increase in retention from Block 1 to Block 2 for easy items compared to difficult items  × 2 (difficulty) × 2 (participant group) mixed ANOVA, in which block and difficulty were within-subjects factors and group was a between-subjects factor. Overall, participants with ADHD ; intermediate processing ; or deep processing . Coders also noted the use of the keyword method . Proportions of reported strategies are presented in 2χ(1) = 5.10, p = 0.024, although the total number of strategies and use of shallow strategies did not differ across groups.Participants were asked to describe the encoding strategies they used to learn the word pairs. Participants could report multiple strategies. However, we did not ask for any information about the timing of these strategies . These self-reports were independently coded by two coders with an inter-rater reliability measured using the intraclass correlation coefficient (ICC). The ICC was 0.9 indicating excellent agreement between the coders. Responses were coded in terms of the strategies indicated using the following criteria: d method , which iM = 0.52, SE = 0.03) than pairs that were restudied , F = 10.27, p = 0.002, p2η = 0.13, thus demonstrating a TE. Easy pairs were recalled more successfully  than difficult pairs , F = 265.67, p < 0.001, p2η = 0.79 consistent with the norming data  x 2 (pair difficulty) x 2 (participant group) mixed ANOVA, in which condition and pair difficulty were within-subjects factors and group a between-subjects factor see . Pairs ting data . No intetudy cf., 2020.F = 4946.19, p < 0.001, p2η = 0.53, as final recall increased from 0.07 proportion correct for items never recalled during the encoding phase to 0.56 for items recalled once, to 0.78 for items recalled twice, to 0.90 for items recalled three times, and to 0.97 for items recalled four times. There was no main effect of group, F = 1.98, p = 0.16, or of difficulty, F = 3.56, p = 0.06, and no interactions, all Fs < 1.2. In sum, both groups’ final test performance was similarly improved as a function of initial retrieval success.Retrieval success has been shown to moderate the magnitude of the TE with final test performance higher for items correctly retrieved more often during the encoding phase . We condF = 11.6, p < 0.001 2R = 0.25, with deep strategy use significantly predicting performance, t = 4.80, p < 0.001, whereas the use of shallow strategies did not, t = 1.05, p = 0.30. We then reexamined the group difference in memory performance at encoding including deep strategy use as a covariate and found the effect of group was no longer significant at encoding, F = 1.97, p = 0.17, p2η = 0.03. This suggests that the encoding differences found between the students with and without ADHD may be due to differential use of deep strategies.Although our groups were matched on fluid intelligence and working memory capacity, we did see a difference in self-reported encoding strategies with non-ADHD participants reporting significantly greater use of deep encoding strategies. Deeper encoding strategies have long been shown to improve memory performance . We examn = 20) and unmedicated (n = 16) participants with ADHD now as separate groups compared to the control group. Group assignment for participants with ADHD was based on whether they reported taking medication on the days of the study. A comparison of self-reported symptomatology between our medicated and unmedicated groups was not significant, p < 0.99. As in our initial analysis of encoding performance, there were main effects of difficulty, F = 236.37, p < 0.001, p2η = 0.77, block . The main effect of group was also significant, F = 4.54, p = 0.014, p2η = 0.12, and did not interact with any other factors. Post-hoc comparisons using a Bonferroni correction revealed a significant difference in performance between the control group and the unmedicated ADHD group, p = 0.011, whereas the differences between the medicated ADHD group and the control group (p = 0.86) and between the medicated and unmedicated ADHD groups (p = 0.23) were not significant. These data are shown in 2χ(1) = 8.92, p = 0.003 and the medicated ADHD group (9 out of 20), 2χ(1) = 4.43, p = 0.04, whereas the medicated ADHD group did not differ from the control group, 2χ(1) = 0.75, p = 0.39.As we reported in the Participants section, 20 out of 36 participants with ADHD reported taking medication for their ADHD diagnosis at the time of the study. Given research suggesting that ADHD medication can improve memory performance , we examFs < 1. However, now the main effect of group was significant, F = 3.26, p = 0.04, p2η = 0.09. Post hoc comparisons revealed that the difference between the unmedicated ADHD group and the control group was significant (p = 0.04), whereas the difference between the two ADHD groups (p = 0.27) and between the medicated ADHD group and the control group (p > 0.99) were not. These data are shown in ps > 0.10.Turning to performance at final test, we reanalyzed the data using a 2 (condition: repeated study vs. repeated test) × 2 (pair difficulty) × 3 (participant group) mixed ANOVA. There were significant main effects of condition and difficulty with no interactions, Overall, our results are consistent with the prior literature both in terms of the benefits of retrieval practice for college students with ADHD , 2020 anHowever, our examination of the effects of medication status found unmedicated students performed significantly worse than the control group at both encoding and final test, while medicated students performed similarly to the controls. The unmedicated group also reported significantly less use of deep encoding strategies than both the medicated group and the controls. Although these results are preliminary, they are consistent with work conducted with unmedicated children and adolescents with ADHD that reports poorer memory performance due to less effortful encoding strategies  and a meRelating our study to the prior studies of the testing effect in ADHD, our results are consistent with Another important takeaway from our results is that although retrieval practice is equally effective, it does not make up for the deficits at encoding seen in the unmedicated participants with ADHD. Consistent with prior work showing that the performance deficits in ADHD are largely due to poor encoding, this suggests that, once encoding is successful, retrieval can and does occur. However, although retrieval practice appears to promote better encoding than re-study, it does not compensate for poor encoding strategies. Thus, an emphasis on the remediation of deficits at encoding may be needed for some students with ADHD to perform optimally. Participants using deeper encoding strategies have been shown to outperform those benefiting from retrieval practice . HoweverOur results suggest that the significant difference seen during encoding between the ADHD group and control group in our initial analysis may have been due to having a mixture of medicated participants with ADHD who performed similarly to controls and un-medicated participants with ADHD who performed significantly worse than the control group. This is consistent with a number of studies demonstrating improved memory performance with use of stimulant medication . Howeverhttps://doi.org/10.15786/20520690.v1, University of Wyoming libraries data repository.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: The studies involving human participants were reviewed and approved by Colby College Institutional Review Board and University of Wyoming Institutional Review Board. The patients/participants provided their written informed consent to participate in this study.JC and MM contributed to the concept, stimulus development, data collection, and analyses. LC and SB collected, scored, and coded data. MM, JC, LC, SB, and JS contributed to the writing. All authors contributed to the article and approved the submitted version.The research was supported by a Social Sciences Division Grant from Colby College awarded to JC. At the time of the analyses and writing, JC was supported by a James S. McDonnell Foundation Understanding Human Cognition award # 220020426 and MM was supported by National Science Foundation Grant # 1660996.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Contrast‐enhanced cross‐sectional imaging is the cornerstone in the diagnosis, staging, and management of HCC, including eligibility for liver transplantation (LT). Radiological‐histopathological discordance may lead to improper staging and may impact patient outcomes. We aimed to assess the radiological‐histopathological discordance at the time of LT in HCC patients and its impact on the post‐LT outcomes.We analyzed further the effect of 6‐month waiting policy on the discordance. Using United Network for Organ Sharing—Organ Procurement and Transplantation Network (UNOS‐OPTN) database, we examined the discordance between pre‐LT imaging and explant histopathology for all adult HCC patients who received liver transplants from deceased donors between April 2012 and December 2017. Kaplan–Meier methods and Cox regression analyses were used to evaluate the impact of discordance on 3‐year HCC recurrence and mortality.Of 6842 patients included in the study, 66.7% were within Milan criteria on both imaging and explant histopathology, and 33.3% were within the Milan based on imaging but extended beyond Milan on explant histopathology. Male gender, increasing numbers of tumors, bilobar distribution, larger tumor size, and increasing AFP are associated with increased discordance. Post‐LT HCC recurrence and death were significantly higher in patients who were discordant, with histopathology beyond Milan . Graft allocation policy with 6‐month waiting time led to increased discordance , although it did not impact post‐LT outcome.Current practice for staging of HCC based on radiological imaging features alone results in underestimation of HCC burden in one out of three patients with HCC. This discordance is associated with a higher risk of post‐LT HCC recurrence and mortality. These patients will need enhanced surveillance to optimize patient selection and aggressive LRT to reduce post‐LT recurrence and increase survival. Contrast‐enhanced Imaging is the cornerstone in the diagnosis, staging, and decision for LT in patients with HCC. In this study of nearly 7000 patients, there was a discrepancy between the imaging and explanted liver in tumor size, number, and presence of vascular invasion in one of three patients. Male gender, increasing numbers of tumors, bilobar distribution, larger tumor size, and increasing AFP were associated with increased discrepancy. There was increased mortality and recurrence after liver transplantation in this group. Six‐month waiting policy after listing for transplantation led to increased discordance. We analyzed further the effect of 6‐month waiting policy on the discordance and post‐LT outcomes. Secondary aim was to explore the difference between contrast‐enhanced liver protocol imaging (CT and MRI) in predicting radiological‐histopathological discordance.22.1We retrospectively analyzed data for adult patients > = 18 years) with deceased donor liver‐alone transplants in the UNOS/OPTN STAR  file between April 1, 2012 and December 31, 2017 and an explant form confirming the diagnosis of HCC based on histopathology. UNOS started to incorporate data from explant pathology starting in April 2012. Figure 8 years wThe 6‐month waiting policy for HCC patients was implemented in October 2015 to optimize organ allocation, and we tested the effect of the policy on radiology‐histopathology discordance and post‐LT outcomes.2.2We analyzed recipient characteristics including age, gender, race/ethnicity, and body mass index (BMI). Patients' laboratory and clinical data included MELD score, waiting time on a transplant list, alpha‐fetoprotein (AFP), Trans‐jugular intrahepatic portosystemic shunt (TIPSS), spontaneous bacterial peritonitis (SBP), previous abdominal surgeries, number and type of down‐staging treatments received, and other comorbidities. We also collected data for donor characteristics including age, gender, race/ethnicity, BMI, cold ischemia time, comorbidities, HCV (Hepatitis C virus) Antibody (HCV Ab), and hepatitis B core Ab (HBcAb) status.To explore discordance, we collected data for explant pathology parameters including tumor differentiation, number of tumors, vascular invasion, extrahepatic spread, satellite lesions, and lymph nodes involvement. A contrast‐enhanced imaging study with MRI (magnetic resonance imaging) or CT scan within 90 days pre‐LT was analyzed to assess the number of tumors, tumor size, and extrahepatic spread. We defined radiology‐histopathological discordance as the disagreement between pre‐LT radiology and explant histopathology regarding number of tumors, size of tumors, and presence of vascular invasion.2.3We tested the effect of discordance on post‐LT outcomes that includes 3‐year mortality, tumor recurrence , and graft failure (defined as graft nonfunction with deterioration of liver synthetic function). We analyzed the effect of 6‐month waiting policy on the discordance and post‐LT outcomes. We also explored the difference between contrast‐enhanced imaging by CT and MRI to detect the discordance between radiology and explant histopathology.This study received Institutional Review Board approval from Baylor College of Medicine, Houston, Texas. Data collected through UNOS/OPTN STAR file comply with relevant data protection and privacy regulations.2.4t‐test, or nonparametric tests as appropriate to assess statistical differences. We used Kaplan–Meier method to determine the HCC recurrence, graft failure, and mortality at 3 years.Clinical and tumor characteristics were described in medians and interquartile ranges (IQRs) or frequency and percentages. Patient and tumor characteristics were compared between the explant pathology and the most recent pretransplant radiology with the use of chi‐square, Multivariable Cox proportional hazards models were used to assess the effect of being outside Milan at explant on the post‐LT outcomes while adjusting for patient clinical, and tumor characteristics. All patients were censored at the loss of follow‐up, the end of the follow‐up period (3 years), or at the end of the study period (12/31/2018), whichever occurred first. In the analysis of graft failure and HCC recurrence, patients were also censored at death if it occurred first. A multivariable model was constructed with all significant variables from the univariate analyses. Baseline demographics and clinical characteristics and HCC characteristics were added to the final model regardless of their significance in the univariate analyses.We created a logistic regression analysis to study the factors associated with discordance. A multivariable logistic regression model was constructed to determine the effect of 6‐month waiting policy on the risk of being outside Milan at explant. All analyses were conducted using SAS 9.4 .33.1A total of 6842 adult patients underwent LT for HCC with imaging inside Milan within 90 days pre‐LT. Table The baseline characteristics of 6842 transplant recipients with pre‐LT imaging within Milan are summarized in Table 3.2p < 0.0001). Table n = 583) compared with group 1 , p < 0.0001. Macrovascular invasion was noted in histopathology in 5.5% (n = 126) patients described within Milan by pre‐LT radiology. No statistical difference was found between the time elapsed from last imaging to receipt of liver transplantation with a median (IQR) of 35 days (15–58) for group 1 and 35 days (16–61) in group 2, p = 0.77. Table Fifty percent of patients had more than one tumor on explant pathology. More tumors were found on right lobe of the liver, 48% and 23% of the tumors were moderately or well differentiated, respectively, and vascular invasion was found in 16% of the explants. Table 3.3p < 0.0015. Table p = 0.001. Table Due to a change in allocation policy with mandatory 6‐month wait time before getting exception point in October 2015, we created a model testing the impact of this policy on the likelihood of being outside Milan at explant. Patients listed before October 2015 but transplanted afterwards were not included in this model, resulting in a total of 5783 patients (4328 before and 1455 after October 2015). After the implementation of the new policy, more patients were transplanted with an explant outside Milan 36.4% versus 31.8% before the policy, We examined factors associated with discordant results to patients who were listed and transplanted according to the same allocation policy in this model. On the multivariable analysis male gender, higher number of tumors, larger tumor size, and multifocality of tumors were associated with increased discordance. Table 3.4HCC recurrence occurred in 6.26% patients after a median follow‐up of 364 (IQR: 193–626) days.p < 0.0001). Table Group 1 had 4.1% recurrence while group 2 had 10.6% recurrence at 3 years post‐LT (p < 0.0001), and higher mortality  than inside Milan on explant. Figure p < 0.001, decreased survival p < 0.001, and increased graft failure p = 0.04, respectively, in this group compared with inside Milan in explant.As shown in Table p < 0.023). Advancing age was associated with increased mortality . AFP >500 ng/mL was associated with high recurrence and increased mortality  and , respectively. Poor tumor differentiation was associated with increased recurrence and mortality  and , respectively. A higher tumor diameter was associated with increased recurrence and mortality  and , respectively. Receiving no LRT pre‐LT led to increased risk of recurrence . Predictors of 3‐year graft failure include higher donor risk index (DRI), p < 0.0001, donors with hypertension, P = 0.02, and poor tumor differentiation, p = 0.004.Males had increased risk of recurrence .3.5p = 0.18. There was no statistically significant difference between CT and MRI in the detection of tumor size (p < 0.07), total tumor diameter (p = 0.07), and the number of tumors in imaging versus explant (p = 0.37). Table There was no statistically significant difference between the diagnostic yield of contrast‐enhanced CT or contrast‐enhanced MRI in agreement with explant pathology, 4In the largest to date study cohort of 6842 patients with HCC with LT, we found discordant results between pre‐LT radiology (within 90 days) and histopathology in 33.3% of study subjects. The Median time from last imaging to liver transplantation was 35 days (15–59). Male gender, higher number (>1) of tumor, larger size (>3.5 cm), bilaterality of tumors, increasing AFP (>20 ng/mL), and treatment with LRT were predictors of radiological‐histopathological discordance. The discordance led to significantly increased 3‐year mortality and recurrence. In addition, graft allocation policy with 6‐month waiting time implemented in 2015 led to increased discordance, although it did not impact post‐LT outcomes. We found no difference between contrast‐enhanced liver protocol CT and MRI in predicting the discordance.In our study, we collected data for tumor number, size and presence or absence of vascular invasion in the explant histopathology to correlate Milan stage in pre‐LT imaging. Previous reports attributed discordance between pre‐LT scans and explant histopathology to multiple factors, including nonstandardized sectioning techniques, differences in sensitivity and specificity of imaging modalities, and the affinity of tumors to contrast material.Liver transplantation is a curative option for HCC management with a good outcome and plausible survival benefit (75% at 5 years).p < 0.001) and lower odds of wait‐list dropout  as compared with non‐HCC patients.Since 2002, the United States adopted MELD‐based allocation system to liver transplantation to decrease wait‐list mortality. However, HCC patients were subjected to increased mortality on the waiting list as MELD score alone did not allow for a timely transplantation.To optimize organ allocation and improve post‐LT outcome, UNOS/ OPTN (Organ Procurement and Transplantation Network) implemented the 6‐month waiting policy. The mandatory wait time allowed observation of tumor behavior, and locoregional treatment to reduce tumor burden.Earlier reports emphasized the reliability of MRI in detection of small or indeterminate lesions compared to CT.Our study had limitations using a large heterogeneous national database with a potential risk of nondifferential misclassification bias. Moreover, some patients did not have pretransplant imaging in their records, and some had their post‐LRT assessment by ultrasound only. To address that, we excluded records with missing CT/MRI pre‐LT from our analysis. The LIRADS system was adopted to alleviate discordance in reporting of HCC.In conclusion, the results of our study showed that staging of HCC based on current radiological techniques has a high discordance rate and leads to underestimation of HCC burden in one out of three patients. It accounts significantly for increased post‐LT HCC recurrence and mortality. The implementation of 6‐month waiting time policy led to increased discordance. Patients with risk factors for discordance may need enhanced surveillance and aggressive LRT to achieve complete tumor necrosis to improve post‐LT outcomes. Improvement in radiological assessment with possible incorporation of artificial intelligence is needed to identify patients at risk for discordance.Mohamed Ismail: Conceptualization (lead); formal analysis ; investigation ; methodology ; writing – original draft (supporting); writing – review and editing (supporting). Ahmed El Sabagh: Writing – original draft ; writing – review and editing . Ahmed M. Afifi Abdelwahab: Writing – review and editing . Efstathia Polychronopoulou: Formal analysis (lead); methodology (lead); writing – original draft (supporting); writing – review and editing (supporting). Yong‐Fang Kuo: Investigation (lead); methodology (lead); supervision ; writing – original draft ; writing – review and editing . Manal Hassan: Methodology ; supervision ; writing – original draft ; writing – review and editing . John Goss: Supervision (lead); writing – original draft ; writing – review and editing (lead). Fasiha Kanwal: Supervision (lead); writing – original draft ; writing – review and editing (lead). Prasun K Jalal: Conceptualization (lead); formal analysis ; investigation ; methodology ; supervision (lead); writing – original draft (lead); writing – review and editing (lead).There is none to declare for all authors related to the current study.Approval of the research protocol by an Institutional Reviewer Board: This study was conducted under IRB approval of Baylor College of medicine. Informed Consent: Consent waiver to unidentified data from UNOS registry.Tables S1‐S6Click here for additional data file.


Clostridia were significantly reduced in the R7I‐treated group, and Odoribacteraceae, an efficient isoalloLCA‐synthesizing strain, was the main dominant strain, protecting the gut from potential pathogens. In addition, we further discovered that R7I reduced the accumulation of negative organic acid metabolites. Overall, R7I exerted better therapeutic and immunomodulatory potential in the bacterial enteritis model, greatly reduced the risk of disease onset, and provided a reference for the in vivo application of antimicrobial peptides.Increased antibiotic resistance poses a major limitation in tackling inflammatory bowel disease and presents a large challenge for global health care. Antimicrobial peptides (AMPs) are a potential class of antimicrobial agents. Here, we have designed the potential oral route for antimicrobial peptide R7I with anti‐proteolytic properties to deal with bacterial enteritis in mice. The results revealed that R7I protected the liver and gut from damage caused by inflammation. RNA‐Seq analysis indicated that R7I promoted digestion and absorption in the small intestine by upregulating transmembrane transporter activity, lipid and small molecule metabolic processes and other pathways, in addition to upregulating hepatic steroid biosynthesis and fatty acid degradation. For the gut microbiota,  Given this, using antibiotics  to control the proliferation of Escherichia coli in intestinal mucosa may be a potential therapeutic strategy for IBD.Inflammatory bowel disease (IBD), a global health care problem, is a chronic recurrent gastrointestinal inflammatory disease of complex etiology, subdivided into two phenotypes: Crohn's disease (CD) and ulcerative colitis (UC).E. coli. Therefore, existing antibiotics have failed to satisfy clinical treatment needs, and there is an urgent need to develop novel antimicrobial agents against bacterial infection enteritis.However, numerous studies have recently proved that the extended use or misuse of antibiotics can cause a persistent expansion of antibiotic resistance genes in the human gut microbiota and disrupt the normal microbiota ecological structure and epithelial barrier function, causing serious secondary infection.https://www.transparencymarketresearch.com/peptide-therapeutics-market.html). However, most peptide drugs, including AMPs, are difficult to administer orally due to an enzymatic barrier that limits systemic bioavailability, yet oral administration is the recommended technique for treating gastrointestinal inflammatory illnesses.Antimicrobial peptides (AMPs), as an important component of the innate immune system, are expressed on the epithelial surface and in neutrophils in mammals, and have broad‐spectrum activity against bacteria, fungi, viruses, and so on. Consequently, AMPs have garnered immense attention as a potential class of peptide‐based antimicrobial agents for combating bacterial infections.2), which had great bactericidal activity against all 16 tested Gram‐negative bacteria (GMMBC = 4.97 μM) with low cytotoxicity. Additionally, R7I showed good salt tolerance and serum stability in vitro and still maintained excellent activity in a mouse peritonitis model. Importantly, compared with other anti‐proteolytic peptides containing unnatural amino acids, R7I was completely composed of natural amino acids and had dramatic resistance to a high concentration of protease hydrolysis , suggesting that R7I could be produced cheaply through biological expression systems and had a broader application prospect.E. coli‐infected mouse model of enteritis to investigate the efficacy of R7I. Herein, we stated that R7I has excellent stability. In the inflammation model, R7I protected intestinal barrier and function, reducing intestinal inflammation and balancing intestinal flora disorders. In addition, R7I reduced liver damage and promoted liver‐related metabolic functions.In earlier research, we successfully developed an anti‐proteolytic peptide R7I ‐labeled R7I in vivo. Figure Overall, the above data indicate that R7I had excellent resistance to enzymatic hydrolysis and had the potential for oral administration.2.22.2.1d‐lactic acid (DLA) and diamine oxidase (DAO) contents in the control group treated with the bacterial solution were significantly increased (p < 0.05) compared with the blank group. After oral administration of various R7I doses and 20 mg/kg colistin sulfate, DAO, and DLA levels in most treatment groups were significantly decreased (p < 0.05), with the best results in the 20 mg/kg R7I group. In addition, we reported that partial dose concentrations of R7I and colistin could raise secreted immunoglobulin A (SlgA) levels compared to the control group, without statistical significance, and the highest content in R7I‐20 group was 2.59 mg/L. In addition, R7I significantly increased total antioxidant levels and decreased MDA levels in the small intestine , while anti‐inflammatory factors IL‐4 and IL‐10 were significantly reduced (p < 0.05) (IL‐10 in the ileum was an exception). After being treated with 20 mg/kg R7I, the mRNA and protein relative expression levels of pro‐inflammatory factor IL‐6 were significantly lower in the ileum, and those of TNF‐α were significantly lower in the colon and ileum. Meanwhile, the mRNA and protein relative expression levels of anti‐inflammatory factors IL‐4 and IL‐10 significantly increased in the colon. These interesting results suggested that R7I might play different regulatory roles in the inflammatory factor pathway of the colon and ileum. Additionally, for tight junction proteins, the mRNA relative expression levels of Occludin and Claudin 1 in the colon of the control group were significantly reduced compared to the blank group (p < 0.05). However, the 20 mg/kg R7I increased the mRNA relative expression levels of Occludin and Claudin 1 in the colon without statistical significance (p > 0.05).Given the excellent performance of 20 mg/kg R7I, we further probed its effects on intestinal inflammation and tight junction proteins at mRNA and protein expression levels Figure . CompareSubsequently, we visually observed the protective effects of R7I on intestine injury by determining intestine histological changes. In Figure 2.2.2p < 0.05). After oral administration of various R7I doses and 20 mg/kg colistin sulfate, we found that 20 mg/kg R7I could significantly decrease AST, ALT, and TBIL levels in the serum of bacterially infected mice compared with the control group (p < 0.05), and relieve the elevation of LDH, CREA and CK levels, without statistical significance (p > 0.05). In contrast, other doses of R7I and colistin sulfate could also decrease the levels of AST, TBIL (p < 0.05), and ALT (p > 0.05), but had little effect (or even an increasing trend) on LDH and CREA levels. Given this, we preliminarily determined that R7I was more effective in protecting the liver function of bacteria‐infected mice.The weakened intestinal mucosal barrier functions propagated and translocated numerous intestinal pathogenic bacteria, and releasing several toxic substances, such as endotoxin, would cause a systemic inflammatory response and organ injuries. Consequently, the blood biochemical indices were performed to determine whether oral R7I administration could alleviate other organ injuries in bacteria‐infected mice. As displayed in Figure p < 0.05), increase SOD and GSH contents (p > 0.05), and restore T‐AOC levels (p > 0.05) in the liver in bacteria‐infected mice. In comparison, the antioxidant effects of other doses of R7I and colistin sulfate were slightly less.The inflammation releases multiple inflammatory cytokines causing oxidative stress, further aggravating the liver injury and even promoting hepatocytes apoptosis. Consequently, attenuated oxidative stress is one of the most important measures to treat liver injury. As described in Figure Based on the above results, 20 mg/kg R7I showed more effective protection effects against liver injury than other treatment groups. Similarly, histological observations of livers strongly supported the protective effect of 20 mg/kg R7I. As displayed in Figure E. coli infection.Overall, we considered that 20 mg/kg R7I had great protective effects on the liver injury caused by 2.3Each organ function is critical in the overall health system. Digestion and absorption in the small intestine provide energy and nutrients for various life activities, while the liver is primarily responsible for material metabolism. In addition to immunity and injury examinations, the intestinal tract and liver must be examined for the bacterial attack. Below, we employed transcriptome analysis to examine functional changes in the small intestine and liver in R7I‐20 group. The sequencing data were further filtered to remove some spliced and low‐quality reads, obtaining an average number of 40,309,056 high‐quality sequence reads. The average percentage of high‐quality sequence reads in sequencing reads was 90.71%. Principal components analysis (PCA) was conducted on each sample based on the amount of expression. PCA analysis can cluster similar samples together with closer proximity, indicating higher similarity. In the case of the small intestine Figure , R7I‐20 We next performed functional classification of differential genes in each combination by Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses to better understand the specific roles played by R7I, focusing on control and R7I‐20 groups. As revealed in Figure 2.42.4.1E. coli infection) reduced the proportion of ASVs at the family level while increasing them at the order level , compared with Control (4.76%) and Blank (0.59%) groups. Firmicutes in Control increased to 83.15%, and the ratio of Firmicutes to Bacteroidetes increased.Intestinal flora can influence intestinal health, especially in inflammatory bowel disease, irritable bowel syndrome, and other intestinal disorders. Following that, the cecal contents 16 S rRNA gene was sequenced to explore intestinal flora changes. Twelve samples from three groups  were sequenced, and 1,058,307 sequences matched the forward and reverse primers in the original data, with an average of 88,192 per sample. A total of 592,473 high‐quality sequences were generated by Dada2 method after denoising and clustering. Subsequently, species taxonomic annotation was conducted. The average sequence length of the entire sample was 415 bp. The taxonomic annotation unit disclosed that the control group .Figure Clostridia and Clostridiales, the difference advantage of R7I‐20 group was Proteobacteria, and the difference advantage of the Blank group was Lactobacillaceae, Lactobacillales, Lactobacillus, and bacillus. Only PWY0‐1338 (p < 0.05) and ALL‐CHORISMATE‐PWY (p < 0.01) pathways were upregulated in the Control group compared with the Blank group in the differential analysis of predicted metabolic pathways  format by Agilent Masshunter Qualitative Analysis B.08.00 software . In R software platform, XCMS program was used in peak identification, retention time correction, and automatic integration pretreatment. Following that, the data were subjected to internal standard normalization. Visualization matrices containing sample name, m/z‐RT pair, and peak area were obtained. A total of 2425 and 6580 features were acquired in positive and negative modes, respectively. After qualitative analysis, data matrices were imported into R, followed by multivariate analysis, focusing more on Control vs. R7I‐20.t test (p < 0.05) in Figure p < 0.05). Therefore, R7I‐20 group reduced the accumulation of harmful organic acid metabolites and increased lipid and glycerophospholipid metabolites. The differential metabolites were mapped to KEGG ID by the online software MetaboAnalyst. The differential metabolite pathway enrichment analysis is presented in Figure We used PCA modeling methods to examine the aggregation degree of QC samples Figure . In this33.1The protocols used in this experiment were approved by the Northeast Agricultural University Institutional Animal Care and Use Committee. All the Animal care and treatment were complied with the standards described in the “Laboratory Animal Management Regulations” (revised 2016) of Heilongjiang Province, China.3.22) and fluorescein isothiocyanate (FITC)‐labeled R7I were synthesized by GL Biochem Corporation , and it was determined by matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry . The peptide purity (>95%) and retention time were tested by reversed‐phase high‐performance liquid chromatography (HPLC).R7I  to give a final peptide concentration of 1.28 mM. The stomach  and the contents of the entire small intestine of the mice were collected and placed in a sterile eppendorf tube. Sterile PBS was added to gastric tissue  and small intestine contents , and mixed thoroughly by shaking. The mixture was centrifuged to obtain the supernatant as gastric juice and small intestine juice. R7I was dissolved with the corresponding pH PBS. The prepared gastric and small intestine fluids were then mixed separately with R7I (v/v = 1:1) to give a final peptide concentration of 1.28 mM. Melittin was used here as a control. The peptide mixture was incubated in a 37°C incubator for 1, 4 and 8 h. Finally, the minimum inhibitory concentrations (MICs) test was performed to verify peptide activity with Subsequently, the C57BL/6 male mice (6 weeks old) were fasted for 12 h before treatment, and the blank group was instilled with saline (200 μl), while the experimental group was instilled with 20 mg/kg of body weight FITC‐R7I (200 μl) to start the clock. Specimens were collected at 1 h, 4 h, and 8 h (each organ and each mid‐gut), respectively. The blank group served as a control, and all samples were photographed under a fluorescent microscope set up with a uniform light source.3.4n = 12), and they were fed adaptively for 3 days. During the whole experiment, mice can get clean water and a laboratory standard diet ad libitum, under controlled environmental conditions . The standard lab diet contained 18% crude protein, 4% crude fat, 5% crude fiber, 8% ash, and 10% moisture.C57BL/6 male mice that were 6 weeks old were provided by Liaoning Changsheng Biotechnology Co., Ltd., China. All mice  were randomly divided into 6 groups ; the administration group (E. coli + R7I) is set to three concentration gradients: (2) 20 mg/kg, (3) 30 mg/kg, and (4) 40 mg/kg of body weight; (5) the antibiotic group (E. coli + colistin sulfate), 20 mg/kg of body weight; and (6) the blank group with only normal saline  the control group . The bacterial broth was transferred to a new LB medium at a ratio of 1:100 for 3–5 h to reach the logarithmic growth period. The bacterial precipitate was centrifuged and washed three times with saline to adjust the colony count to 2.0 × 109 CFU/ml.Based on the results of the pre‐experiment, we determined the appropriate concentration of the bacteria. The strain E. coli ATCC 25922 (200 μl) once a day (d1‐2). R7I at different concentrations and colistin sulfate were given twice  on the d3 and once on d4‐5 by oral administration. Correspondingly, an equal amount of saline was given to the blank and control groups in the same way. On day 6, all mice were euthanized by cervical dislocation under full anesthesia with isoflurane.The detailed processing process was shown in Figure 3.5The collected blood was centrifuged for 10 min at 3000 rpm at 4°C. The supernatant was taken and stored at −80°C for subsequent testing. The liver and part of the middle ileum were cut and placed in precooled 4% paraformaldehyde for hematoxylin eosin (H&E) staining. The Liver, small intestine, colon, and cecum contents were stored separately in cryogenic vials at −80°C.3.6Serum biochemical indices of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), total bilirubin (TBIL), cholinesterase (CHE), creatinine (CREA), creatine kinase (CK), urea nitrogen (BUN), lactate dehydrogenase (LDH), total protein (TP), albumin (ALB), and globulin (GLB) were measured by the automatic biochemical analyzer .3.7Histological analysis was performed by hematoxylin–eosin staining (H&E). In brief, liver, ileum, and colon of mice were fixed overnight with 4% paraformaldehyde‐PBS, dehydrated, and embedded in paraffin blocks. Then the samples were cut into 5 μm sections that were deparaffinized and hydrated and then stained with H&E for histological analysis.3.8Total antioxidant capacity (T‐AOC), superoxide dismutase (SOD), glutathione peroxidase (GSH‐Px), malondialdehyde (MDA), and catalase (CAT) enzyme activities in the liver were determined using commercially available kits  according to the manufacturer's instructions.3.9d‐lactic acid, and secretory immunoglobulin A (SlgA) in serum, using mouse ELISA kit instruction .To detect the content of diamine oxidase (DAO), 3.10−ΔΔCt approach. The expression of target gene mRNA in the control group was taken as the baseline relative to the treatment group .Briefly, total RNA was extracted with Trizol, and then RNA was reversely transcribed into cDNA after genomic DNA was removed by a two‐step method according to the instructions of the kit. SYBR Green method was used to analyze the mRNA expression of specific primers for different genes. The reagents and kits were purchased from Nanjing Vazyme Biotech Co., Ltd., China. Subsequently, real‐time PCR was performed using CFX Connect . Primer 5.0 software was used to design primers for specific genes Table . The int3.11Total protein from ileum and colon tissues was separated using commercial protein extraction reagents . Reducing SDS‐PAGE electrophoresis was conducted to separate 40 μg protein, which was then transferred to PVDF membranes . Afterward, membranes were blocked with 5% skimmed milk for 2 h in Tris‐Tween saline buffer, followed by incubation using primary antibodies. The HRP‐conjugated secondary antibodies were subsequently incubated for 2 h at room temperature. The Alpha Imager 2200 software  was employed to develop protein blots. Lastly, protein signals were quantified digitally and normalized to the relative expression of β‐actin. ImageJ software  was used to determine the band density. See 3.12http://ccb.jhu.edu/software/hisat2/index.shtml) software. Differential analysis of gene expression was performed using DESeq, and the conditions for screening differentially expressed genes were: expression difference ploidy |log2FoldChange| > 1 and significance p value <0.05. Based on the results of differential gene expression analysis, PPI pairs containing the differential genes with a score > 0.95 were screened using the STRING database (https://string-db.org/cgi/input.pl), and then protein interaction networks were mapped. GO enrichment analysis and KEGG enrichment analysis were performed using topGO and cluster profiler, respectively. In the analysis, the gene list and gene number of each term were calculated using the differential genes annotated by GO term, and the gene list and gene number of each pathway were calculated using the differential genes annotated by KEGG pathway, so as to determine the main biological functions of differential genes.The sequencing service was provided by Shanghai Personal Biotechnology Co., Ltd., China. Briefly, total RNA was extracted from the liver and ileum. The cDNA libraries were constructed and then sequenced using the Illumina NovaSeq sequence platform. A total of 24 samples with 4 biological replicates per treatment were available for RNA‐seq analysis. The filtered Reads were matched to the mouse reference genome (Mus_musculus.GRCm39.dna.primary_assembly.fa) using HISAT2  was added to it. The mixture was mixed by a vortex mixer for 1 min and homogenized for 3 min at 60 Hz twice. Then the mixture was centrifuged at 13,000 rpm, 4°C for 10 min. The supernatant was transferred to sampler vials for detection. An in‐house quality control (QC) was prepared by mixing an equal amount of each sample. Detailed information on the working model can be found in The metabolites in small intestine (ileum portion) of control group, R7I‐20 group, and blank group were detected. About 50 mg of each sample was weighted out and 400 μl methanol (containing 5 μg/ml 2‐chloro‐3.14http://greengenes.secondgenome.com/) was selected for species annotation. Sequencing service was provided by Shanghai Personal Biotechnology Co., Ltd., China. The data were analyzed by using the free online platform Personalbio GenesCloud (https://www.genescloud.cn/).Then, we determined the flora of cecum contents. The V3‐V4 hypervariable regions of 16 S rDNA were amplified , and the amplified products were then sequenced by the Illumina platform. DADA2 method mainly included primer removal, quality filtering, denoising, splicing, and clustering. Greengenes database  and evaluated with one‐way analysis of variance (ANOVA). The Tukey test was used to detect differences among treatments. The SPSS V25  software was used for all statistical analyses. A p value of <0.05 was considered statistically significant. All data was visualized using Graphpad Prism 8.0 .Results are reported as means ± standard errors of the mean  on the surface of monocytes, reducing their antigen‐presenting effects and downregulating T‐lymphocyte activity.E. coli infection. In addition, R7I reduced LDH and CREA levels at low concentrations, but R7I and Colistin did not clearly improve BUN, while CREA and BUN concentrations indirectly reflected glomerular filtration function.Regarding the relevant indicators of serum, it can be found that after the mice were administrated twice with the bacterial liquid, the violent increase of ALT and AST indicated that the liver was seriously damaged, and unexpected elevation of lactate dehydrogenase represents liver disease acute hepatitis or certain malignancies.Regarding liver antioxidant function, CAT levels in the control group were significantly higher than in the blank group. In contrast, CAT levels in R7I‐20 group were similar to the blank group status, indicating abnormal activation of the hepatic peroxisome pathway leading to abnormal CAT levels. No significant improvement was found for GSH and SOD. Bacterial treatment resulted in a decrease in T‐AOC and a slight increase in R7I‐20. In addition, oxygen radicals act on lipids to cause peroxidation, the end product of which is MDA, which causes cross‐linking and polymerization of proteins, nucleic acids, and other living macromolecules, damaging cell structure and function.E. coli damage in the gut can be treated quickly and effectively. PCA revealed similarities between the R7I‐20 group and the blank group in the intestine, which was a positive finding but not in the liver  compared to the control group, but there was no difference in the liver, indicating that r Figure . This mar Figure . It has Escherichia coli (AIEC), in which elevated intestinal propionic acid levels led to AIEC recovery and remarkably increased toxicity.Following that, R7I significantly reduced the increase of negative metabolites in the control group while upregulating some positive metabolites in the metabolite analysis of the small intestine. Research has indicated that mouse models were transfected with Crohn's disease‐associated adherent invasive E. coli infestation resulted in a noteworthy reduction in species composition differences (Control vs. Blank), with Control being much further away from Blank group than R7I‐20 in OPLS‐DA. In contrast, R7I‐20 did not cause a decrease in the composition and abundance of the intestinal flora due to its attributed antimicrobial activity, possibly linked to the lower concentration. The protective effect of R7I‐20 on the stability of intestinal flora was reflected in the taxonomic annotation unit of the species, the rarefaction curve, Chao1, and the total number of ASVs. Some studies have disclosed that colonization by clostridia is particularly deleterious. Clostridia were involved in developing of necrotizing enterocolitis (NEC), the dominant bacterium in the control group.Desulfovibrio in the Proteobacteria phylum, but another dominant strain, Odoribacteraceae, has been revealed to efficiently synthesize isoalloLCA.Clostridium difficile and Enterococcus faecalis.Lactobacillus was mainly present in the blank group, promoting digestion and inhibiting spoilage multiplication and pathogenic bacteria in the intestine.Numerous clinical investigations have demonstrated that inflammation alters gut microbes and their metabolites, and that the affected gut and gut microbes, in turn, stimulate immune responses and metabolic activity, leading to chronic inflammation.Enterobacteriaceae. PWY0‐1338 (MetaCyc Pathway: polymyxin resistance) was upregulated in the control group. Polymyxins are produced by Gram‐positive bacterium Paenibacillus polymyxa and can be selectively toxic to Gram‐negative bacteria by interacting with phospholipids, particularly lipid A, to disrupt the structure of bacterial cell membranes.Salmonella typhimurium and Escherichia coli, can become resistant to polymyxin by modifying their lipid A structure by the attaching of 4‐amino‐4‐deoxy‐l‐arabinopyranose (l‐Ara4N) groups to one or more phosphate groups.l‐tryptophan, l‐tyrosine, and l‐phenylalanine, as well as the essential compounds 5, 6, 7, 8‐tetrahydrofolate, ubiquinone‐8, menaquinol‐8 and enterobactin (enterochelin). Enterobactin is a catecholate siderophore produced almost exclusively by Enterobacteria, although it has been reported in some Streptomyces species. Additionally, research has proven that Enterobactin‐mediated high‐affinity iron acquisition is critically important for Gram‐negative bacterial pathogens to survive and infect the host.In the analysis of predicted metabolic pathway differences, we also identified pathway alterations caused by unclassified 5E. coli causing adverse effects on the organism, this study revealed that R7I greatly slowed down this process. This included reducing inflammatory factors, maintaining intestinal barrier function, facilitating small intestinal digestion and absorption and hepatic fatty acid metabolism, reducing negative organic acid metabolites while increasing lipid and glycerophospholipid metabolites, stabilizing microbial community composition and abundance, and effectively reducing the abnormal metabolic pathway by E. coli . In general, R7I exhibited good anti‐enzymatic stability and presented potential application prospects in treating bacterial infection‐associated inflammatory bowel disease. These efforts and results provided a thorough basis and reference for advancing orally administered therapeutic peptides and proteins and contributing to the strategy of alternative antibiotics.For Taotao Sun: Conceptualization ; data curation (lead); formal analysis (lead); methodology (lead); validation ; visualization (lead); writing – original draft (lead); writing – review and editing . Xuesheng Liu: Data curation ; methodology ; project administration ; validation . Yunzhe Su: Methodology ; project administration ; validation . Zihang Wang: Data curation ; methodology ; project administration ; validation . Baojing Cheng: Formal analysis ; methodology ; project administration ; validation . Na Dong: Formal analysis ; methodology ; project administration ; validation . Jiajun Wang: Conceptualization ; methodology ; project administration ; writing – review and editing . Anshan Shan: Conceptualization (lead); formal analysis ; funding acquisition (lead); project administration ; writing – review and editing (lead).The authors declare no competing interests.Appendix S1 Supporting InformationClick here for additional data file.Appendix S2 Supporting InformationClick here for additional data file.