Objective To investigate the effect of parecoxib on postoperative hyperalgesia induced by remifentanil-based anesthesia.Methods One hundred ASA Ⅰ or Ⅱ patients,aged 21-64 yr,weighing 50-80 kg,undergoing elective laparoscopic operation,were randomly divided into 5 groups ( n =20 each):parecoxib group (group P),small dose remifentanil group (group S),large dose remifentanil group (group L),small dose remifentanil + parecoxib group (group SP) and large dose remifentanil + parecoxib group (group LP).Parecoxib 40 mg was injected intravenously at 30 min before anesthesia in groups P,SP and LP.Anesthesia was induced with midazolam0.05 mg/kg,etomidate 0.2 mg/kg,cisatracurium 0.15 mg/kg and remifentanil 1 μg/kg (fentanyl 4 μg/kg in group P).The patients was tracheal intubated and mechanically ventilated.PETCO2 was maintained at 35-45 mm Hg.Anesthesia was maintained with infusion of remifentanil at 0.05 μg·kg-1 ·min-1 (in groups S and SP) or at 0.3 μg· kg- 1· min- 1 (in groups L and LP) combined with inhalation of sevoflurane and infusion of cisatracurium at 0.12 mg·kg-1·h-1.At 30 min after operation,numeric rating scale (NRS) was used to assess the degree of pain at rest and during activity.Tramadol 1.5 mg/kg was injected intravenously after operation if needed.NRS scores were maintained ≤5.The use of tramadol and adverse effects during 24 h after operation were recorded.Results Compared with group P,NRS scores at rest and during activity were significantly increased at 30 min after operation in groups S and L,the incidence of shivering and the number of patients who needed tramadol were significantly increased in group L,and no change was found in NPS scores at rest and during activity at 30 min after operation,the incidence of adverse effects and the number of patients who needed tramadol in groups SP and LP.Compared with group S,NRS scores at rest and during activity at 30 min after operation,the incidence of shivering and the number of patients who needed tramadol were significantly increased in group L,NRS scores at rest and during activity at 30 min after operation were significantly decreased and no change was found in the incidence of adverse effects and the number of patients who needed tramadol in group SP.Compared with group L,NRS scores at rest and during activity at 30 min after operation,the incidence of shivering and the number of patients who needed tramadol were significantly decreased in group LP.Conclusion Intravenous injection of parecoxib 40 mg at 30 min before anesthesia can attenuate postoperative hyperalgesia induced by remifentanil-based anesthesia.

OBJECTIVETo develop a method for detecting the topical concentration of hydrocortisone (HC) in the subcutaneous adipose of rats using microdialysis sampling technique and liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS).

METHODSTopical samples were collected by applying the probe into the subcutaneous adipose of rats, with alcohol (5%)-ringers solution as the perfusion solution. A LC-MS/MS method was established for detecting the HC concentration in the dialysates.

RESULTSThe protonated precursor to produce ion transitions monitored for HC was m/z 363.2→121.1. The calibration curve was linear over the range of 0.5-1000 ng/ml, with the intra- and inter-day precision and accuracy within ∓15%, and no significant matrix effect was noted. The in vivo recovery of the probe was about 59%.

CONCLUSIONA selective and sensitive method has been successfully established for the on-line HC detection in the subcutaneous adipose of rats.

Administration, Cutaneous ; Animals ; Chromatography, Liquid ; methods ; Hydrocortisone ; administration & dosage ; pharmacokinetics ; Male ; Microdialysis ; methods ; Rats ; Rats, Wistar ; Subcutaneous Fat ; chemistry ; metabolism ; Tandem Mass Spectrometry ; methods

Objective:To investigate the influencing factors for the recurrence of TNM(T3~4N0M0)stage Ⅱ colorectal cancer in patients aged 75 years and over after radical resection.Methods:Clinicopathologic data of 161 colorectal cancer patients aged 75 years and over undergone radical resection in our hospital from January 2012 to August 2017 were retrospectively analyzed.They were followed up for 49 months(range: 2-84 months). Survival analysis was conducted by the Kaplan-Meier method and the survival rate was examined using the Log-rank method.Multivariate analysis was conducted by the proportional hazards regression model.Results:Univariate analysis showed that age≥80 years, preoperative comorbidities involving more than 1 system, weight loss≥10%, preoperative intestinal obstruction or perforation, preoperative CEA elevation, preoperative CA199 elevation, depth of primary tumor invasion T4, dissection of lymph nodes<12, vascular invasion, nerve invasion, deficient mismatch repair(dMMR), risk stratification and adjuvant chemotherapy were related factors for the prognosis in patients with TNM stage Ⅱ colorectal cancer aged 75 years and over after radical resection.Multivariate analysis showed that preoperative comorbidities involving more than 1 system, weight loss≥10%, preoperative intestinal obstruction or perforation, preoperative CEA elevation, depth of primary tumor invasion T4, dissection of lymph nodes<12 and vascular invasion were independent risk factors for poor prognosis, and adjuvant chemotherapy was an independent factor for favorable prognosis.The 5-year-disease-free survival(DFS)rate was 41.6% in all patients.The Kaplan-Meier curves indicated that disease-free survival(DFS)between the low-risk, middle-risk and high-risk groups had a statistically significant difference( χ2=14.632, P=0.001). Kaplan-Meier survival analysis showed that high-risk patients receiving Oxaliplatin combined with Capecitabine adjuvant chemotherapy had better DFS than those receiving Capecitabine or non-adjuvant chemotherapy( χ2=11.157, P=0.004). Conclusions:DFS is improved in strictly selected patients with stage Ⅱ colorectal cancer aged 75 years and over and at high risk who receive Oxaliplatin combined with Capecitabine adjuvant chemotherapy.

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks, which profoundly impact various fields. This paper mainly discusses the future applications of LLMs in dentistry. We introduce two primary LLM deployment methods in dentistry, including automated dental diagnosis and cross-modal dental diagnosis, and examine their potential applications. Especially, equipped with a cross-modal encoder, a single LLM can manage multi-source data and conduct advanced natural language reasoning to perform complex clinical operations. We also present cases to demonstrate the potential of a fully automatic Multi-Modal LLM AI system for dentistry clinical application. While LLMs offer significant potential benefits, the challenges, such as data privacy, data quality, and model bias, need further study. Overall, LLMs have the potential to revolutionize dental diagnosis and treatment, which indicates a promising avenue for clinical application and research in dentistry.
Dentistry ; Artificial Intelligence