A Milky Way-like barred spiral galaxy at a redshift of 3.

The majority of massive disk galaxies in the local Universe show a stellar barred structure in their central regions, including our Milky Way1,2. Bars are supposed to develop in dynamically cold stellar disks at low redshift, as the strong gas turbulence typical of disk galaxies at high redshift suppresses or delays bar formation3,4. Moreover, simulations predict bars to be almost absent beyond z = 1.5 in the progenitors of Milky Way-like galaxies5,6. Here we report observations of ceers-2112, a barred spiral galaxy at redshift zphot ≈ 3, which was already mature when the Universe was only 2 Gyr old. The stellar mass (M★ = 3.9 × 109 M⊙) and barred morphology mean that ceers-2112 can be considered a progenitor of the Milky Way7-9, in terms of both structure and mass-assembly history in the first 2 Gyr of the Universe, and was the closest in mass in the first 4 Gyr. We infer that baryons in galaxies could have already dominated over dark matter at z ≈ 3, that high-redshift bars could form in approximately 400 Myr and that dynamically cold stellar disks could have been in place by redshift z = 4-5 (more than 12 Gyrs ago)10,11.

EGFR activation limits the response of liver cancer to lenvatinib.

Hepatocellular carcinoma (HCC)-the most common form of liver cancer-is an aggressive malignancy with few effective treatment options1. Lenvatinib is a small-molecule inhibitor of multiple receptor tyrosine kinases that is used for the treatment of patients with advanced HCC, but this drug has only limited clinical benefit2. Here, using a kinome-centred CRISPR-Cas9 genetic screen, we show that inhibition of epidermal growth factor receptor (EGFR) is synthetic lethal with lenvatinib in liver cancer. The combination of the EGFR inhibitor gefitinib and lenvatinib displays potent anti-proliferative effects in vitro in liver cancer cell lines that express EGFR and in vivo in xenografted liver cancer cell lines, immunocompetent mouse models and patient-derived HCC tumours in mice. Mechanistically, inhibition of fibroblast growth factor receptor (FGFR)  by lenvatinib treatment leads to feedback activation of the EGFR-PAK2-ERK5 signalling axis, which is blocked by EGFR inhibition. Treatment of 12 patients with advanced HCC who were unresponsive to lenvatinib treatment with the combination of lenvatinib plus gefitinib (trial identifier NCT04642547) resulted in meaningful clinical responses. The combination therapy identified here may represent a promising strategy for the approximately 50% of patients with advanced HCC who have high levels of EGFR.

Dual Inhibition of CDK4/6 and XPO1 Induces Senescence With Acquired Vulnerability to CRBN-Based PROTAC Drugs.

BACKGROUND & AIMS: Despite the increasing number of treatment options available for liver cancer, only a small proportion of patients achieve long-term clinical benefits. Here, we aim to develop new therapeutic approaches for liver cancer. METHODS: A compound screen was conducted to identify inhibitors that could synergistically induce senescence when combined with cyclin-dependent kinase (CDK) 4/6 inhibitor. The combination effects of CDK4/6 inhibitor and exportin 1 (XPO1) inhibitor on cellular senescence were investigated in a panel of human liver cancer cell lines and multiple liver cancer models. A senolytic drug screen was performed to identify drugs that selectively killed senescent liver cancer cells. RESULTS: The combination of CDK4/6 inhibitor and XPO1 inhibitor synergistically induces senescence of liver cancer cells in vitro and in vivo. The XPO1 inhibitor acts by causing accumulation of RB1 in the nucleus, leading to decreased E2F signaling and promoting senescence induction by the CDK4/6 inhibitor. Through a senolytic drug screen, cereblon (CRBN)-based proteolysis targeting chimera (PROTAC) ARV-825 was identified as an agent that can selectively kill senescent liver cancer cells. Up-regulation of CRBN was a vulnerability of senescent liver cancer cells, making them sensitive to CRBN-based PROTAC drugs. Mechanistically, we find that ubiquitin specific peptidase 2 (USP2) directly interacts with CRBN, leading to the deubiquitination and stabilization of CRBN in senescent liver cancer cells. CONCLUSIONS: Our study demonstrates a striking synergy in senescence induction of liver cancer cells through the combination of CDK4/6 inhibitor and XPO1 inhibitor. These findings also shed light on the molecular processes underlying the vulnerability of senescent liver cancer cells to CRBN-based PROTAC therapy.

Phytophthora RxLR effector PcSnel4B promotes degradation of resistance protein AtRPS2.

Phytophthora capsici deploys effector proteins to manipulate host immunity and facilitate its colonization. However, the underlying mechanisms remain largely unclear. In this study, we demonstrated that a Sne-like (Snel) RxLR effector gene PcSnel4 is highly expressed at the early stages of P. capsici infection in Nicotiana benthamiana. Knocking out both alleles of PcSnel4 attenuated the virulence of P. capsici, while expression of PcSnel4 promoted its colonization in N. benthamiana. PcSnel4B could suppress the hypersensitive reaction (HR) induced by Avr3a-R3a and RESISTANCE TO PSEUDOMONAS SYRINGAE 2 (AtRPS2), but it did not suppress cell death elicited by Phytophthora infestin 1 (INF1) and Crinkler 4 (CRN4). COP9 signalosome 5 (CSN5) in N. benthamiana was identified as a host target of PcSnel4. Silencing NbCSN5 compromised the cell death induced by AtRPS2. PcSnel4B impaired the interaction and colocalization of Cullin1 (CUL1) and CSN5 in vivo. Expression of AtCUL1 promoted the degradation of AtRPS2 and disrupted HR, while AtCSN5a stabilized AtRPS2 and promoted HR, regardless of the expression of AtCUL1. PcSnel4 counteracted the effect of AtCSN5 and enhanced the degradation of AtRPS2, resulting in HR suppression. This study deciphered the underlying mechanism of PcSnel4-mediated suppression of HR induced by AtRPS2.

IncidencePrevalence: An R package to calculate population-level incidence rates and prevalence using the OMOP common data model.

PURPOSE: Real-world data (RWD) offers a valuable resource for generating population-level disease epidemiology metrics. We aimed to develop a well-tested and user-friendly R package to compute incidence rates and prevalence in data mapped to the observational medical outcomes partnership (OMOP) common data model (CDM). MATERIALS AND METHODS: We created IncidencePrevalence, an R package to support the analysis of population-level incidence rates and point- and period-prevalence in OMOP-formatted data. On top of unit testing, we assessed the face validity of the package. To do so, we calculated incidence rates of COVID-19 using RWD from Spain (SIDIAP) and the United Kingdom (CPRD Aurum), and replicated two previously published studies using data from the Netherlands (IPCI) and the United Kingdom (CPRD Gold). We compared the obtained results to those previously published, and measured execution times by running a benchmark analysis across databases. RESULTS: IncidencePrevalence achieved high agreement to previously published data in CPRD Gold and IPCI, and showed good performance across databases. For COVID-19, incidence calculated by the package was similar to public data after the first-wave of the pandemic. CONCLUSION: For data mapped to the OMOP CDM, the IncidencePrevalence R package can support descriptive epidemiological research. It enables reliable estimation of incidence and prevalence from large real-world data sets. It represents a simple, but extendable, analytical framework to generate estimates in a reproducible and timely manner.

Depression risk in chronic tonsillitis patients underwent tonsillectomy: a global federated health network analysis.

Background: Tonsillectomy is a common surgery in the US, with possible postoperative complications. While small studies indicate postoperative depressive symptoms may occur, large-scale evidence is lacking on the tonsillectomy-depression link. Methods: We conducted a retrospective cohort study using the TriNetX US collaborative network, offering de-identified electronic health data from 59 collaborative healthcare organizations (HCOs) in the United States. In this study, people being diagnosed of chronic tonsillitis between January 2005 and December 2017 were enrolled. Patients deceased, with previous record of cancers or psychiatric events before index date were excluded. 14,874 chronic tonsillitis patients undergoing tonsillectomy were propensity score matched 1:1 to controls for age, sex, and race. New-onset depression risks were evaluated over 5 years post-tonsillectomy and stratified by age and sex. Confounders were adjusted for including demographics, medications, comorbidities and socioeconomic statuses. Results: After matching, the difference of key baseline characteristics including age, sex, comedications status and obesity status was insignificant between tonsillectomy and non-tonsillectomy groups. Tonsillectomy had a 1.29 times higher 5-year depression risk versus matched controls (95% CI, 1.19-1.40), with elevated risks seen at 1 year (HR=1.51; 95% CI, 1.28-1.79) and 3 years (HR=1.30; 95% CI, 1.18-1.43). By stratifications, risks were increased for both males (HR=1.30; 95% CI, 1.08-1.57) and females (HR=1.30; 95% CI, 1.18-1.42), and significantly higher in ages 18-64 years (HR=1.37; 1.26-1.49), but no significance observed for those 65 years and older. After performing sensitivity analyses and applying washout periods of 6, 12, and 36 months, the outcome remained consistent with unadjusted results. Conclusion: This real-world analysis found tonsillectomy was associated with a 30% higher 5-year depression risk versus matched non-tonsillectomy patients with chronic tonsillitis. Further mechanistic research is needed to clarify the pathophysiologic association between depression and tonsillectomy. Depression is not commonly mentioned in the current post-tonsillectomy care realm; however, the outcome of our study emphasized the possibility of these suffering condition after operation. Attention to psychological impacts following tonsillectomy is warranted to support patient well-being, leading to better management of post-tonsillectomy individuals.

Association between hidradenitis suppurativa and atopic diseases: a multi-center, propensity-score-matched cohort study.

Background: Cross-sectional evidence has suggested a high prevalence of atopic diseases in patients with hidradenitis suppurativa (HS). However, there is a lack of evidence based on longitudinal studies. This study aimed to assess the risk of different atopic diseases, including asthma, atopic dermatitis, and allergic rhinitis, in patients with HS. Methods: In this retrospective cohort study, data from the TriNetX research network were obtained. Patients with HS were enrolled, and a 1:1 propensity score matching was performed to select a non-HS control group. Matching covariates included age, sex, race, comorbidities, comedications, socioeconomic status, lab data, and medical utilization status. Hazard ratios (HR) for atopic diseases were assessed. Results: Over a 15-year follow-up period, patients with HS were found to be at a higher risk for atopic dermatitis (HR = 1.65; 95% CI, 1.44-1.90), asthma (HR = 1.41; 95% CI, 1.33-1.49), and allergic rhinitis (HR = 1.08; 95% CI, 1.03-1.13). A similar trend was observed in shorter follow-up periods. The association between HS, atopic dermatitis, and asthma was consistent across different age and sex subgroups. Conclusion: Atopic diseases including atopic dermatitis, asthma and allergic rhinitis are associated with HS. Further investigation is needed to assess the necessity of early screening for atopic diseases in patients with HS.

Hidradenitis suppurativa as a potential risk factor of periodontitis: a multi-center, propensity-score-matched cohort study.

Background: Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease associated with systemic symptoms. Periodontitis, a prevalent dental disease, shares immune-mediated inflammatory characteristics with HS. This cohort study aims to evaluate the association between HS and periodontitis. Methods: Using the TriNetX research network, a global-federated database of electronic health records, we conducted a retrospective cohort study. People being diagnosed of HS were identified and propensity score matching was performed to identify proper control group, via balancing critical covariates Within the follow-up time of 1 year, 3 year and 5 years, hazard ratios were calculated to assess the risk of periodontitis in HS patients compared to controls. Results: Within the 53,968 HS patients and the same number of matched controls, the HS patients exhibited a significantly increased risk of developing periodontitis compared to controls after 3 years of follow-up (HR: 1.64, 95% CI: 1.11, 2.44) and 5 years of follow-up (HR: 1.64, 95% CI: 1.21, 2.24) of follow-up. Sensitivity analyses supported these findings under various matching models and washout periods. While comparing with patients with psoriasis, the association between HS and periodontitis remained significant (HR: 1.73, 95% CI: 1.23, 2.44). Conclusion: The observed increased risk suggests the need for heightened awareness and potential interdisciplinary care for individuals with HS to address periodontal health.

Generation of realistic virtual adult populations using a model-based copula approach.

Incorporating realistic sets of patient-associated covariates, i.e., virtual populations, in pharmacometric simulation workflows is essential to obtain realistic model predictions. Current covariate simulation strategies often omit or simplify dependency structures between covariates. Copula models are multivariate distribution functions suitable to capture dependency structures between covariates with improved performance compared to standard approaches. We aimed to develop and evaluate a copula model for generation of adult virtual populations for 12 patient-associated covariates commonly used in pharmacometric simulations, using the publicly available NHANES database, including sex, race-ethnicity, body weight, albumin, and several biochemical variables related to organ function. A multivariate (vine) copula was constructed from bivariate relationships in a stepwise fashion. Covariate distributions were well captured for the overall and subgroup populations. Based on the developed copula model, a web application was developed. The developed copula model and associated web application can be used to generate realistic adult virtual populations, ultimately to support model-based clinical trial design or dose optimization strategies.

What affects the selection of diverting ileostomy in rectal cancer surgery: a single-center retrospective study.

BACKGROUND: The selection of diverting ileostomy (DI) is controversial. This study aimed to explore the factors affecting the selection of diverting ileostomy (DI) following laparoscopic low anterior resection for rectal cancer. METHODS: This retrospective, case-control study included patients who underwent laparoscopic-assisted sphincter-saving surgery for mid-low rectal cancer from January 2019 to June 2021. Univariate and multivariate analyses were performed on the patient's clinicopathological characteristics and pelvic dimensions measured by abdominopelvic electron beam computed tomography. RESULTS: A total of 382 patients were included in the analysis, of which 182 patients (47.6%) did not undergo DI, and 200 patients (52.4%) underwent DI. The univariate analysis suggested that male sex (p = 0.003), preoperative radiotherapy (p < 0.001), patients with an anastomosis below the levator ani plane (p < 0.001), the intertuberous distance (p < 0.001), the sacrococcygeal distance (p = 0.025), the mid pelvis anteroposterior diameter (p = 0.009), and the interspinous distance (p < 0.001) were associated with performing DI. Multivariate analysis confirmed that preoperative radiotherapy (p = 0.037, odds ratio [OR] = 2.98, 95% confidence interval [CI] = 1.07-8.30), anastomosis below the levator ani plane (p < 0.001, OR = 7.09, 95% CI = 4.13-12.18), and the interspinous distance (p = 0.047, OR = 0.97, 95% CI = 0.93-1.00) were independently associated with performing DI. CONCLUSION: Pelvic parameters also influence the choice of DI. According to this single-center experience, patients with a shorter interspinous distance, particularly narrow pelvic with an interspinous distance of < 94.8 mm, preoperative radiotherapy, and anastomosis below the levator ani plane, prefer to have a DI and should be adequately prepared by the physician.

DNA demethylase ALKBH1 promotes adipogenic differentiation via regulation of HIF-1 signaling.

DNA N6-adenine methylation (6mA), as a novel adenine modification existing in eukaryotes, shows essential functions in embryogenesis and mitochondrial transcriptions. ALKBH1 is a demethylase of 6mA and plays critical roles in osteogenesis, tumorigenesis, and adaptation to stress. However, the integrated biological functions of ALKBH1 still require further exploration. Here, we demonstrate that knockdown of ALKBH1 inhibits adipogenic differentiation in both human mesenchymal stem cells (hMSCs) and 3T3-L1 preadipocytes, while overexpression of ALKBH1 leads to increased adipogenesis. Using a combination of RNA-seq and N6-mA-DNA-IP-seq analyses, we identify hypoxia-inducible factor-1 (HIF-1) signaling as a crucial downstream target of ALKBH1 activity. Depletion of ALKBH1 leads to hypermethylation of both HIF-1α and its downstream target GYS1. Simultaneous overexpression of HIF-1α and GYS1 restores the adipogenic commitment of ALKBH1-deficient cells. Taken together, our data indicate that ALKBH1 is indispensable for adipogenic differentiation, revealing a novel epigenetic mechanism that regulates adipogenesis.

Pathogenic gene prediction based on network embedding.

In disease research, the study of gene-disease correlation has always been an important topic. With the emergence of large-scale connected data sets in biology, we use known correlations between the entities, which may be from different sets, to build a biological heterogeneous network and propose a new network embedded representation algorithm to calculate the correlation between disease and genes, using the correlation score to predict pathogenic genes. Then, we conduct several experiments to compare our method to other state-of-the-art methods. The results reveal that our method achieves better performance than the traditional methods.

Construction of Non-Hermitian Parent Hamiltonian from Matrix Product States.

There are various research strategies used for non-Hermitian systems, which typically involve introducing non-Hermitian terms to preexisting Hermitian Hamiltonians. It can be challenging to directly design non-Hermitian many-body models that exhibit unique features not found in Hermitian systems. In this Letter, we propose a new method for constructing non-Hermitian many-body systems by generalizing the parent Hamiltonian method into non-Hermitian regimes. This allows us to build a local Hamiltonian using given matrix product states as its left and right ground states. We demonstrate this method by constructing a non-Hermitian spin-1 model from the asymmetric Affleck-Kennedy-Lieb-Tasaki state, which preserves both chiral order and symmetry-protected topological order. Our approach opens up a new paradigm for systematically constructing and studying non-Hermitian many-body systems, providing guiding principles for exploring new properties and phenomena in non-Hermitian physics.

Interaction analysis of high-risk pathological features on adjuvant chemotherapy survival benefit in stage II colon cancer patients: a multi-center, retrospective study.

BACKGROUND: We aimed to analyze the benefit of adjuvant chemotherapy in high-risk stage II colon cancer patients and the impact of high-risk factors on the prognostic effect of adjuvant chemotherapy. METHODS: This study is a multi-center, retrospective study, A total of 931 patients with stage II colon cancer who underwent curative surgery in 8 tertiary hospitals in China between 2016 and 2017 were enrolled in the study. Cox proportional hazard model was used to assess the risk factors of disease-free survival (DFS) and overall survival (OS) and to test the multiplicative interaction of pathological factors and adjuvant chemotherapy (ACT). The additive interaction was presented using the relative excess risk due to interaction (RERI). The Subpopulation Treatment Effect Pattern Plot (STEPP) was utilized to assess the interaction of continuous variables on the ACT effect. RESULTS: A total of 931 stage II colon cancer patients were enrolled in this study, the median age was 63 years old (interquartile range: 54-72 years) and 565 (60.7%) patients were male. Younger patients (median age, 58 years vs 65 years; P < 0.001) and patients with the following high-risk features, such as T4 tumors (30.8% vs 7.8%; P < 0.001), grade 3 lesions (36.0% vs 22.7%; P < 0.001), lymphovascular invasion (22.1% vs 6.8%; P < 0.001) and perineural invasion (19.4% vs 13.6%; P = 0.031) were more likely to receive ACT. Patients with perineural invasion showed a worse OS and marginally worse DFS (hazardous ratio [HR] 2.166, 95% confidence interval [CI] 1.282-3.660, P = 0.004; HR 1.583, 95% CI 0.985-2.545, P = 0.058, respectively). Computing the interaction on a multiplicative and additive scale revealed that there was a significant interaction between PNI and ACT in terms of DFS (HR for multiplicative interaction 0.196, p = 0.038; RERI, -1.996; 95%CI, -3.600 to -0.392) and OS (HR for multiplicative interaction 0.112, p = 0.042; RERI, -2.842; 95%CI, -4.959 to -0.725). CONCLUSIONS: Perineural invasion had prognostic value, and it could also influence the effect of ACT after curative surgery. However, other high-risk features showed no implication of efficacy for ACT in our study. TRIAL REGISTRATION: This study is registered on ClinicalTrials.gov, NCT03794193 (04/01/2019).

Application of a count data model to evaluate the anti-metastatic efficacy of QAP14 in 4T1 breast cancer allografts.

Dopamine D1 receptor (D1DR) is proved to be a promising target to prevent tumor metastasis, and our previous studies showed that QAP14, a potent anti-cancer agent, exerted inhibitory effect on lung metastasis via D1DR activation. Therefore, the purpose of the study was to establish count data models to quantitatively characterize the disease progression of lung metastasis and assess the anti-metastatic effect of QAP14. Data of metastatic progression were collected in 4T1 tumor-bearing mice. Generalized Poisson distribution best described the variability of metastasis counts among the individuals. An empirical PK/PD model was developed to establish mathematical relationships between steady plasma concentrations of QAP14 and metastasis growth dynamics. The latency period of metastasis was estimated to be 12 days after tumor implantation. Our model structure also fitted well to other D1DR agonists (fenoldopam and l-stepholidine) which had inhibitory impact on breast cancer lung metastasis likewise. QAP14 40 mg/kg showed the best inhibitory efficacy, for it provided the longest prolongation of metastasis-free periods compared with fenoldopam or l-stepholidine. This study provides a quantitative method to describe the lung metastasis progression of 4T1 allografts, as well as an alternative PD model structure to evaluate anti-metastatic efficacy.

(Thiolan-2-yl)diphenylmethanol Benzyl Ether-Catalyzed Asymmetric Cyclopropanation of Chalcones.

We devised a new method for asymmetric cyclopropanation by employing (S)-(thiolan-2-yl)diphenylmethanol benzyl ether as an organocatalyst. Under optimal conditions, an in situ generated sulfur ylide reacts with (E)-chalcones via a Johnson-Corey-Chaykovsky reaction to afford a variety of cyclopropanes in excellent yields and stereoselectivities. This strategy employs low-environmental-risk reaction conditions and reusable catalysts. Hence, it is a green and efficient method for constructing cyclopropane scaffolds.

An integrated PK/PD model investigating the impact of tumor size and systemic safety on animal survival in SW1990 pancreatic cancer xenograft.

Survival is one of the most important endpoints in cancer therapy, and parametric survival analysis could comprehensively reveal the overall result of disease progression, drug efficacy, toxicity as well as their interactions. In this study we investigated the efficacy and toxicity of dexamethasone (DEX) combined with gemcitabine (GEM) in pancreatic cancer xenograft. Nude mice bearing SW1990 pancreatic cancer cells derived tumor were treated with DEX (4 mg/kg, i.g.) and GEM (15 mg/kg, i.v.) alone or in combination repeatedly (QD, Q3D, Q7D) until the death of animal or the end of study. Tumor volumes and net body weight (NBW) were assessed every other day. Taking NBW as a systemic safety indicator, an integrated pharmacokinetic/pharmacodynamic (PK/PD) model was developed to quantitatively describe the impact of tumor size and systemic safety on animal survival. The PK/PD models with time course data for tumor size and NBW were established, respectively, in a sequential manner; a parametric time-to-event (TTE) model was also developed based on the longitudinal PK/PD models to describe the survival results of the SW1990 tumor-bearing mice. These models were evaluated and externally validated. Only the mice with good tumor growth inhibition and relatively stable NBW had an improved survival result after DEX and GEM combination therapy, and the simulations based on the parametric TTE model showed that NBW played more important role in animals' survival compared with tumor size. The established model in this study demonstrates that tumor size was not always the most important reason for cancer-related death, and parametric survival analysis together with safety issues was also important in the evaluation of oncology therapies in preclinical studies.

Surgical site infection after intracorporeal and extracorporeal anastomosis in laparoscopic left colectomy for colon cancer: a multicenter propensity score-matched cohort study.

BACKGROUND: Intracorporeal anastomosis (IA) is associated with reduced surgical site infection (SSI) and other postoperative complications in laparoscopic right colectomy (LRC). However, evidence is inadequate for IA in laparoscopic left colectomy (LLC). This study aimed to determine the effect of IA and extracorporeal anastomosis (EA) on SSI and other short-term postoperative complications in LLC. METHODS: In this retrospective multicenter propensity score-matched (PSM) cohort study, we enrolled consecutive patients who underwent LLC with IA (TLLC/IA) and laparoscopic-assisted left colectomy with EA (LALC/EA) at two medical centers between January 2015 and September 2021. Propensity score matching with a 1:2 ratio was employed. The primary outcome was SSI occurrence. Secondary outcomes were operating time, intraoperative hemorrhage, other postoperative complications, and pathological outcomes. RESULTS: Overall, 574 and 99 patients received LALC/EA and TLLC/IA, respectively. After PSM, 84 patients with TLLC/IA were matched with 141 patients with LALC/EA. Thirty patients (13.3%) patients experienced SSI (17.0% in LALC/EA vs 7.1% in TLLC/IA). IA was associated with a reduced risk of overall SSI and superficial/deep SSI compared with EA after PSM, with OR of 0.375 (95% CI, 0.147-0.959, P = 0.041). and 0.148 (95% CI, 0.034-0.648, P = 0.011), respectively. Multivariate analysis of unmatched patients indicated similar results. In the analysis of secondary outcomes, LALC/EA may have a shorter operating time (absolute mean difference - 13.41 [95% CI, - 23.76 to - 3.06], P = 0.002) and a higher risk of intraoperative hemorrhage (absolute risk difference 4.96 [95% CI, - 0.09 to 9.89], P = 0.048). CONCLUSIONS: IA in LLC is associated with a reduced risk of overall SSI and superficial/deep SSI. However, it may require a longer operating time.

Role of exosomal non-coding RNAs from tumor cells and tumor-associated macrophages in the tumor microenvironment.

Exosomes have a crucial role in intercellular communication and mediate interactions between tumor cells and tumor-associated macrophages (TAMs). Exosome-encapsulated non-coding RNAs (ncRNAs) are involved in various physiological processes. Tumor-derived exosomal ncRNAs induce M2 macrophage polarization through signaling pathway activation, signal transduction, and transcriptional and post-transcriptional regulation. Conversely, TAM-derived exosomal ncRNAs promote tumor proliferation, metastasis, angiogenesis, chemoresistance, and immunosuppression. MicroRNAs induce gene silencing by directly targeting mRNAs, whereas lncRNAs and circRNAs act as miRNA sponges to indirectly regulate protein expressions. The role of ncRNAs in tumor-host interactions is ubiquitous. Current research is increasingly focused on the tumor microenvironment. On the basis of the "cancer-immunity cycle" hypothesis, we discuss the effects of exosomal ncRNAs on immune cells to induce T cell exhaustion, overexpression of programmed cell death ligands, and create a tumor immunosuppressive microenvironment. Furthermore, we discuss potential applications and prospects of exosomal ncRNAs as clinical biomarkers and drug delivery systems.

[Deep Learning-Based Identification of Common Complication Features of Surgical Incisions].

Objective: In recent years, due to the development of accelerated recovery after surgery and day surgery in the field of surgery, the average length-of-stay of patients has been shortened and patients stay at home for post-surgical recovery and healing of the surgical incisions. In order to identify, in a timely manner, the problems that may appear at the incision site and help patients prevent or reduce the anxiety they may experience after discharge, we used deep learning method in this study to classify the features of common complications of surgical incisions, hoping to realize patient-directed early identification of complications common to surgical incisions. Methods: A total of 1 224 postoperative photographs of patients' surgical incisions were taken and collected at a tertiary-care hospital between June 2021 and March 2022. The photographs were collated and categorized according to different features of complications of the surgical incisions. Then, the photographs were divided into training, validation, and test sets at the ratio of 8∶1∶1 and 4 types of convolutional neural networks were applied in the training and testing of the models. Results: Through the training of multiple convolutional neural networks and the testing of the model performance on the basis of a test set of 300 surgical incision images, the average accuracy of the four ResNet classification network models, SE-ResNet101, ResNet50, ResNet101, and SE-ResNet50, for surgical incision classification was 0.941, 0.903, 0.896, and 0.918, respectively, the precision was 0.939, 0.898, 0.868, and 0.903, respectively, and the recall rate was 0.930, 0.880, 0.850, and 0.894, respectively, with the SE-Resnet101 network model showing the highest average accuracy of 0.941 for incision feature classification. Conclusion: Through the combined use of deep learning technology and images of surgical incisions, problematic features of surgical incisions can be effectively identified by examining surgical incision images. It is expected that patients will eventually be able to perform self-examination of surgical incisions on smart terminals.