Abstract Background To discuss the risk factors affecting the recurrence of pheochromocytoma after surgery. Methods We retrospectively reviewed patients who were hospitalized and underwent surgery for PCC between January 2012 and December 2020 at Chinese PLA General Hospital. Inclusion criteria were pathological diagnosis of PCC and availability of follow up. Results In total, 451 patients met the inclusion criteria. The average age was 45.89 years, and the median tumor diameter was 5.75 cm. The mean recurrence time was 34.24 months. Of the 451 patients receiving surgery, there were 35 recurrent cases (7.85%). The univariate test showed that age, hypertension, history of PCC recurrence, Ki-67 index ≥ 5, bilateral tumor, duration of phenazopyridine administration, DBP at admission, open operation, intraoperative HR minimum, intraoperative times of HR over 120, times of instability, and intraoperative bleeding were associated with recurrence after radical surgery. Multivariate COX regression analysis of age (HR(hazard ratio) 0.95), hypertension (HR 7.14), history of PCC recurrence (HR 69.35), family history of hypertension (HR 16.30), bilateral tumor (HR 7.38), tumor size (HR 1.05), times of instability (HR 114.91) and length of instability in minutes (HR 1.12) were the independent influences on recurrence after pheochromocytoma resection. Conclusions Age, hypertension, history of PCC recurrence, family history of hypertension, bilateral tumor, tumor size, intraoperative times of instability, and intraoperative instability minutes were independent influences on recurrence after pheochromocytoma resection.
Abstract Background This study aimed to evaluate the efficiency of hippocampal avoidance whole-brain radiotherapy with a simultaneous integrated boost (HA-WBRT-SIB) treating brain metastases (BM) and utility of the Hopkins Verbal Learning Test-Revised (HVLT-R) (Chinese version) in Chinese lung cancer patients. Methods Lung cancer patients with BM undergone HA-WBRT-SIB at our center were enrolled. Brain magnetic resonance imaging, The HVLT total learning score, and side effects were evaluated before radiotherapy and 1, 3, 6, and 12 months after radiotherapy. This study analyzed the overall survival rate, progression-free survival rate, and changes in HVLT-R immediate recall scores. Results Forty patients were enrolled between Jan 2016 and Jan 2020. The median follow-up time was 14.2 months. The median survival, progression-free survival, and intracranial progression-free survival of all patients were 14.8 months, 6.7 months and 14.8 months, respectively. Multivariate analysis indicated that male sex and newly diagnosed stage IV disease were associated with poor overall survival and progression-free survival, respectively. HVLT-R scores at baseline and 1, 3, and 6 months after radiotherapy were 21.94 ± 2.99, 20.88 ± 3.12, 20.03 ± 3.14, and 19.78 ± 2.98, respectively. The HVLT-R scores at 6 months after radiotherapy decreased by approximately 9.8% compared with those at baseline. No grade 3 toxicities occurred in the entire cohort. Conclusions HA-WBRT-SIB is of efficiency and cognitive-conserving in treating Chinese lung cancer BM. Trial registration This study was retrospectively registered on ClinicalTrials.gov in 24th Feb, 2024. The ClinicalTrials.gov ID is NCT06289023.
Avian pathogenic Escherichia coli (APEC) infections result in significant economic losses and reduced animal welfare. Historically, antibiotics and vaccinations currently control APEC infections in poultry, however, antibiotic-resistant strains and heterologous serotypes limit their effectiveness. Meanwhile, antibiotic-resistant strains can be transmitted to humans via contact with animals, food or their environment. Probiotics and antimicrobial peptides (AMPs) are potential alternatives to antibiotics and represent promising strategies to combat APEC. Bovine lactoferricin and lactoferrampin possess anti-bacterial, anti-inflammatory, and anti-oxidant properties. Lactococcus lactis (L. lactis) is an excellent vector for delivering recombinant proteins. In this research, we generated a recombinant L. lactis strain MG1363 expressing lactoferrin peptides, which was labeled with a fluorescent marker mCherry and lacked an antibiotic resistance gene (LL-EFLmC). Our investigation focused on the impact of LL-EFLmC strain on the gut microbiota composition and avian pathogenic E. coli O78 challenge. Our findings indicate that LL-EFLmC exhibits inhibitory effects against APEC-O78 and Staphylococcus aureus CVCC26003 (S. aureus CVCC26003) in vitro. Furthermore, the inclusion of LL-EFLmC in chicken feed significantly improved the average daily intake and gain to feed ratio. Additionally, LL-EFLmC treatment resulted in a significant increase in serum IgG and intestinal mucus SIgA levels. Administration of LL-EFLmC was found to effectively suppress APEC-O78 infection and mitigate the expression of pro-inflammatory cytokines, including IL-1β, IL-12, IFN-γ, and TNF-α. Additionally, 16S rDNA sequencing data revealed that LL-EFLmC was able to restore the intestinal flora that had been disrupted by APEC-O78. These findings suggest that LL-EFLmC may serve as a promising feed additive and antibiotic alternative in chicken production, due to its potential to enhance immune regulation, promote growth, and confer resistance against APEC-O78 infection.
Response Surface Method (RSM) has been widely used for flammable cloud size prediction as it can reduce computational intensity for further Explosion Risk Analysis (ERA) especially during the early design phase of offshore platforms. However, RSM encounters the overfitting problem under very limited simulations. In order to overcome the disadvantage of RSM, Bayesian Regularization Artificial Neural (BRANN)-based model has been recently developed and its robustness and efficiency have been widely verified. However, for ERA during the early design phase, there seems to be room to further reduce the computational intensity while ensuring the model's acceptable accuracy. This study aims to develop an integrated method, namely the combination of Center Composite Design (CCD) method with Bayesian Regularization Artificial Neural Network (BRANN), for flammable cloud size prediction. A case study with constant and transient leakages is conducted to illustrate the feasibility and advantage of this hybrid method. Additionally, the performance of CCD-BRANN is compared with that of RSM. It is concluded that the newly developed hybrid method is more robust and computational efficient for ERAs during early design phase.
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