Small GTPase Ras homologue enriched in brain (RHEB) binds and activates the key metabolic regulator mTORC1, which has an important role in cancer cells, but the role of RHEB in cancer pathogenesis has not been shown. By performing a meta-analysis of published cancer cytogenetic and transcriptome databases, we defined a gain of chromosome 7q36.1-q36.3 containing the RHEB locus, an overexpression of RHEB mRNA in several different carcinoma histotypes, and an association between RHEB upregulation and poor prognosis in breast and head and neck cancers. To model gain of function in epithelial malignancy, we targeted Rheb expression to murine basal keratinocytes of transgenic mice at levels similar to those that occur in human squamous cancer cell lines. Juvenile transgenic epidermis displayed constitutive mTORC1 pathway activation, elevated cyclin D1 protein, and diffuse skin hyperplasia. Skin tumors subsequently developed with concomitant stromal angio-inflammatory foci, evidencing induction of an epidermal hypoxia-inducible factor-1 transcriptional program, and paracrine feed-forward activation of the interleukin-6-signal transducer and activator of transcription 3 pathway. Rheb-induced tumor persistence and neoplastic molecular alterations were mTORC1 dependent. Rheb markedly sensitized transgenic epidermis to squamous carcinoma induction following a single dose of Ras-activating carcinogen 7,12-dimethylbenz(a)anthracene. Our findings offer direct evidence that RHEB facilitates multistage carcinogenesis through induction of multiple oncogenic mechanisms, perhaps contributing to the poor prognosis of patients with cancers overexpressing RHEB. Cancer Res; 70(8); 3287-98. ©2010 AACR.

Background Incisional hernia is a frequent complication of abdominal wall incision. Surgical technique is an important risk factor for the development of incisional hernia. The aim of these updated guidelines was to provide recommendations to decrease the incidence of incisional hernia. Methods A systematic literature search of MEDLINE, Embase, and Cochrane CENTRAL was performed on 22 January 2022. The Scottish Intercollegiate Guidelines Network instrument was used to evaluate systematic reviews and meta-analyses, RCTs, and cohort studies. The GRADE approach (Grading of Recommendations, Assessment, Development and Evaluation) was used to appraise the certainty of the evidence. The guidelines group consisted of surgical specialists, a biomedical information specialist, certified guideline methodologist, and patient representative. Results Thirty-nine papers were included covering seven key questions, and weak recommendations were made for all of these. Laparoscopic surgery and non-midline incisions are suggested to be preferred when safe and feasible. In laparoscopic surgery, suturing the fascial defect of trocar sites of 10 mm and larger is advised, especially after single-incision laparoscopic surgery and at the umbilicus. For closure of an elective midline laparotomy, a continuous small-bites suturing technique with a slowly absorbable suture is suggested. Prophylactic mesh augmentation after elective midline laparotomy can be considered to reduce the risk of incisional hernia; a permanent synthetic mesh in either the onlay or retromuscular position is advised. Conclusion These updated guidelines may help surgeons in selecting the optimal approach and location of abdominal wall incisions.

Aim The aim of this work was to investigate the sensitivity and utility of CT of the chest in diagnosing active SARS-Cov-2 (COVID-19) infection, and its potential application to the surgical setting. Method A literature review was conducted using Google Scholarâ and MEDLINEâ/PubMedâ to identify current available evidence regarding the sensitivity of CT chest compared with RT-PCR for the diagnosis of COVID-19-positive patients. GRADE criteria and the QUADAS 2 tool were used to assess the level of evidence. Results A total of 20 articles were identified that addressed the question of sensitivity of CT for diagnosis of symptomatic and asymptomatic COVID-19-positive patients. Overall sensitivity of CT scan ranged from 57%-100% for symptomatic and 46%-100% for asymptomatic COVID-19 patients, while that of RT-PCR ranged from 39%-89%. CT chest was a better diagnostic modality and capable of detecting active infection earlier in the time course of infection than RT-PCR in symptomatic patients. In asymptomatic patients, disease prevalence seems to play a role in the positive predictive value. Minimal evidence exists regarding the sensitivity of CT in patients who are asymptomatic. Conclusions In surgical patients, CT chest should be considered as an important adjunct for detection of COVID-19 infection in patients who are symptomatic with negative RT-PCR prior to any operation. For surgical patients who are asymptomatic, there is insufficient evidence to recommend routine preoperative CT chest for COVID-19 screening.

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Background: Fascial closure significantly reduces postoperative complications and hernia recurrence after abdominal wall reconstruction (AWR), but can be challenging in massive ventral hernias.Methods: A prospective single-institution cohort study was performed to examine the effects of preoperative injection of botulinum toxin A (BTA) in patients undergoing AWR for midline or flank hernias.Results: A total of 108 patients underwent BTA injection with average 243 units, mean 32.5 days before AWR, without complications. Comorbidities included diabetes (31%), history of smoking (27%), and obesity (mean body mass index 30.5 AE 7.7). Hernias were recurrent in 57%, massive (mean defect width 15.3 AE 5.5 cm; hernia sac volume 2154 AE 3251 cm 3 ) and had significant loss of domain (mean 46% visceral volume outside abdominal cavity). Contamination was present in 38% of patients. Fascial closure was achieved in 91%, with 57% requiring component separation techniques (CSTs). Subxiphoidal hernias needed a form of CST in 88% compared with 50% for hernia not extending subxiphoidal (P < 0.001). Mesh augmentation was used in 98%. Postoperative complications occurred in 40%: 19% surgical site occurrences, 12% surgical site infections, and 7% respiratory failure requiring intubation, 2% mesh infection and no fascial dehiscence. Recurrence was identified in seven patients after mean 14 months of follow-up.Patients undergoing AWR with CST had more surgical site occurrences (29 versus 7%, p0.003) and respiratory failures (18 versus 0%, P ¼ 0.002) than patients who did not require CST.

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Image-based deep learning models (DLMs) have been used in other disciplines, but this method has yet to be used to predict surgical outcomes.OBJECTIVE To apply image-based deep learning to predict complexity, defined as need for component separation, and pulmonary and wound complications after abdominal wall reconstruction (AWR). DESIGN, SETTING, AND PARTICIPANTSThis quality improvement study was performed at an 874-bed hospital and tertiary hernia referral center from September 2019 to January 2020. A prospective database was queried for patients with ventral hernias who underwent open AWR by experienced surgeons and had preoperative computed tomography images containing the entire hernia defect. An 8-layer convolutional neural network was generated to analyze image characteristics. Images were batched into training (approximately 80%) or test sets (approximately 20%) to analyze model output. Test sets were blinded from the convolutional neural network until training was completed. For the surgical complexity model, a separate validation set of computed tomography images was evaluated by a blinded panel of 6 expert AWR surgeons and the surgical complexity DLM. Analysis started February 2020. EXPOSURES Image-based DLM. MAIN OUTCOMES AND MEASURESThe primary outcome was model performance as measured by area under the curve in the receiver operating curve (ROC) calculated for each model; accuracy with accompanying sensitivity and specificity were also calculated. Measures were DLM prediction of surgical complexity using need for component separation techniques as a surrogate and prediction of postoperative surgical site infection and pulmonary failure. The DLM for predicting surgical complexity was compared against the prediction of 6 expert AWR surgeons.RESULTS A total of 369 patients and 9303 computed tomography images were used. The mean (SD) age of patients was 57.9 (12.6) years, 232 (62.9%) were female, and 323 (87.5%) were White. The surgical complexity DLM performed well (ROC = 0.744; P < .001) and, when compared with surgeon prediction on the validation set, performed better with an accuracy of 81.3% compared with 65.0% (P < .001). Surgical site infection was predicted successfully with an ROC of 0.898 (P < .001). However, the DLM for predicting pulmonary failure was less effective with an ROC of 0.545 (P = .03).CONCLUSIONS AND RELEVANCE Image-based DLM using routine, preoperative computed tomography images was successful in predicting surgical complexity and more accurate than expert surgeon judgment. An additional DLM accurately predicted the development of surgical site infection.

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