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Background In this study, we aimed to investigate the short-term clinical outcomes of laparoscopic duodenum-preserving pancreatic-head resection (LDPPHR) for the management of pancreatic-head cystic neoplasms. Methods This retrospective study included 60 patients who were treated with pancreatic-head cystic neoplasms at the Shandong Provincial Hospital Affiliated to Shandong First Medical University from December 2019 to July 2022. Results No significant difference was found between the two groups in terms of the baseline and pathological characteristics of patients (P > 0.05). The postoperative exhaust time was shorter in the LDPPHR group compared with the laparoscopic pancreaticoduodenectomy (LPD) group (2 (2 and 4) vs. 4 (3 and 5) days; P = 0.003). No significant difference was found between the two groups in terms of operative time, estimated blood loss, intraoperative transfusion, hemoglobin levels on the first postoperative day, total bilirubin before discharge, direct bilirubin before discharge, postoperative hospital stay, postoperative pancreatic fistula, bile leakage, hemorrhage, peritoneal effusion, abdominal infection, delayed gastric emptying, interventional embolization hemostasis, reoperation, and 30-day readmission (P > 0.05). No conversion and 90-day mortality were found in the two groups. The LDPPHR group showed a higher 3-month postoperative PNI, 6-month postoperative TG and 6-month postoperative BMI than the LPD group (P Conclusions Compared with LPD, LDPPHR can decrease the postoperative exhaust time of patients, improve the short-term postoperative nutritional status, and does not decrease the safety of the perioperative period.

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers and ranks third inmortality. Mitochondria are the energy manufacturers of cells. Disruption of mitochondrial energy metabolism pathways is strongly correlated with the onset and progression of HCC. Aberrant genes in mitochondrial energy metabolism pathways may represent a unique diagnostic and therapeutic targets that act as indicators for HCC.Gene expression data from 374 HCC patients and 50 controls were acquired from TCGA database. A total of 188 mitochondrial energy metabolism-related genes (MMRGs) were obtained from KEGG PATHWAY database. A total of 368 patients with survival data were randomly split into training and validation groups in a 7: 3 ratio. Prognosis-related MMRGs were selected by univariate Cox and LASSO analyses. Kaplan-Meier and ROC curves were employed to analyze the model precision, whereas the validation set was used for model verification. Furthermore, clinical examinations, immune infiltration analysis, GSVA, and immunotherapy analysis were conducted in the high- and low-risk groups. Finally, the risk model was combined with the clinical variables of HCC patients to perform univariate and multivariate Cox regression analyses to obtain independent risk indicators and draw a nomogram. Therefore, we evaluated the accuracy of the predictions using calibration curves.A total of 6032 differentially expressed genes (DEGs) were detected in the HCC and control samples. After overlapping DEGs with 188 MMRGs, 42 mitochondrial energy metabolism-related DEGs (DEMMRGs) were identified. A 17 specific genes-based risk score model of HCC was created, which revealed effectiveness in each TCGA training and validation dataset. Moreover, patients categorized by risk scores exhibited distinct immune infiltration status, immunotherapy responsiveness, and functional properties. Finally, univariate and multivariate Cox regression analyses revealed that risk score and stage T were independent predictive variables. Based on the T stage and risk score, a nomogram for estimating the survival of HCC patients was created. The calibration curves demonstrated that the prediction model had a high level of accuracy.Our study constructed a mitochondrial energy metabolism-related risk model, that may be utilized to anticipate HCC prognosis and represent the immunological microenvironment of HCC.