Ropivacaine Mesylate

To study the postoperative analgesic effect of ropivacaine combined with dexmedetomidine for serratus anterior plane block (SAPB) under ultrasound visualization plus patient-controlled intravenous analgesia (PCIA) in patients undergoing thoracoscopic radical resection of lung cancer.

A total of 129 patients undergoing elective thoracoscopic surgery were enrolled. The patients were randomly assigned to three groups ( n=43 in each group), a normal saline group (control group), a ropivacaine mesylate group (Group R) and a ropivacaine mesylate combined with dexmetomidine hydrochloride group (Group RD). After operation, ultrasound-guided SAPB was performed and patients in the three groups received the injection of 0 mL of 0.9% normal saline, 25 mL of 0.5% ropivacaine, and 25 mL of 0.5% ropivacaine+1 μg/kg dextrometomidine hydrochloride mixture, respectively. In addition, PCIA was used for all the patients. The button on the PCIA pump was pressed when the postoperative pain visual analogue score (VAS)≥4 on coughing, and rescue analgesic of sufentanil was given intravenously at 2.5 μg/bolus. The primary outcome was the VAS scores at rest and on coughing at 10 min (T ₁), 6 h (T ₂), 12 h (T ₃), 24 h (T ₄), and 48 h (T ₅) after extubation. The secondary outcomes included hemodynamics, the quality of sleep for the first 3 nights after operation, number of times the button on the PCIA pump was pressed, intraoperative and postoperative opioid dosage, time of first postoperative rescue analgesic, duraion of intubation, length of stay at the hospital, adverse reactions, etc.

Compared with those of the control group, the VAS scores of the Group R and Group RD were significantly lower at 10 min, 6 h, and 12 h after extubation ( P<0.05). In comparison with Group R, the number of patients requiring rescue analgesia, the time of first postoperative rescue analgesic, the number of times the button on the PCIA pump was pressed, and the total dose of rescue sufentanil were all significantly lower ( P<0.05) in the Group RD. Patients in the Group RD had better sleep quality in the second and third nights after operation and lower incidence of nausea and vomiting ( P<0.05).

0.5% ropivacaine and 1 μg/kg dexmedetomidine SAPB combined with PCIA can significantly reduce postoperative pain and improve postoperative recovery quality in patients undergoing thoracoscopic radical resection of lung cancer.

To clarify the work done by using AI for identifying the genomic sequences, development of drugs and vaccines for COVID-19 and to recognize the advantages and challenges of using such technology.

A non-systematic review was done. All articles published on Pub-Med, Medline, Google, and Google Scholar on AI or digital health regarding genomic sequencing, drug development, and vaccines of COVID-19 were scrutinized and summarized.

The sequence of SARS- CoV-2 was identified with the help of AI. It can help also in the prompt identification of variants of concern (VOC) as delta strains and Omicron. Furthermore, there are many drugs applied with the help of AI. These drugs included Atazanavir, Remdesivir, Efavirenz, Ritonavir, and Dolutegravir, PARP1 inhibitors (Olaparib and CVL218 which is Mefuparib hydrochloride), Abacavir, Roflumilast, Almitrine, and Mesylate. Many vaccines were developed utilizing the new technology of bioinformatics, databases, immune-informatics, machine learning, and reverse vaccinology to the whole SARS-CoV-2 proteomes or the structural proteins. Examples of these vaccines are the messenger RNA and viral vector vaccines. AI provides cost-saving and agility. However, the challenges of its usage are the difficulty of collecting data, the internal and external validation, ethical consideration, therapeutic effect, and the time needed for clinical trials after drug approval. Moreover, there is a common problem in the deep learning (DL) model which is the shortage of interpretability.

The growth of AI techniques in health care opened a broad gate for discovering the genomic sequences of the COVID-19 virus and the VOC. AI helps also in the development of vaccines and drugs (including drug repurposing) to obtain potential preventive and therapeutic agents for controlling the COVID-19 pandemic.