Background To describe a technique of non-intubated uniportal subxiphoid thoracoscopic extended thymectomy. Methods Data were collected retrospectively. A single 3-cm transverse incision was made below the xiphoid process. This method for extended thymectomy entails adoption of uniportal subxiphoid VATS combined with using of non-intubated anesthesia for thymoma associated with myasthenia gravis. Results Ten consecutive patients underwent this procedure successfully. Mean operative time was 102.5 min. Conversion to intubated ventilation or thoracotomy was not required. Mean chest tube duration was 3.5 days. Mean postoperative hospital stay was 4.7 days. Histologic examination showed early-stage thymomas. Side effects were rare. Quantitative MG scores decreased during follow-up. Conclusions Patients were uneventfully discharged with fast recovery. This technique may merge the potential benefits of a subxiphoid incision and the non-intubated anesthesia protocol.

The σ1A subunit of the adaptor protein 1 (AP1S1) participates in intracellular transport pathways, which is pivotal in carcinogenesis. It is therefore rational to presume that AP1S1 might also be involved in carcinogenesis. In this hospital-based case–control study, we investigated the genetic susceptibility to esophageal squamous cell carcinoma (ESCC) in relation to Single Nucleotide Polymorphisms (SNPs) of AP1S1 among Chinese population and made a preparation for the subsequent esophageal SNP risk model building. A database containing a total of 1143 controls and 1043 ESCC patients were retrospectively studied. The AP1S1 SNPs were analyzed based on ligation detection reaction (LDR) method. Then the relationship between ESCC and SNPs of AP1S1 was determined with a significant crude P < 0.05. Then the logistic regression analysis was used for the calculation for adjusted P in the demographic stratification comparison if a significant difference was observed in the previous step. AP1S1 rs77387752 C > T mutated homozygous TT was an independent risk factor for ESCC, while SNP rs4729666 C > T and rs35208462 C > T mutated heterozygote TC were associated with a lower risk for ESCC, especially in co-dominant model and allelic test for younger, male subjects who are not alcohol-drinkers nor cigarette smokers. These three AP1S1 SNP sites could be incorporated into subsequent SNPs risk models for ESCC in specific populations. AP1S1 rs77387752, rs4729666 and rs35208462 polymorphisms are associated with susceptibility to ESCC in Chinese individuals. AP1S1 SNPs may exert an important role in esophageal carcinogenesis and could serve as potential diagnostic biomarkers. These SNP sites might be added into the building of risk model and then the early diagnosis of ESCC. Besides, further mechanical exploration is required. Table. Logistic regression analyses of associations between AP1S1 SNPs rs77387752 C > T, rs4729666 C > T, rs35208462 C > T and risk of ESCC.

A different drug–drug interaction (DDI) scenario may exist in patients with chronic kidney disease (CKD) compared with healthy volunteers (HVs), depending on the interplay between drug–drug and disease (drug‐drug‐disease interaction (DDDI)). Physiologically‐based pharmacokinetic (PBPK) modeling, in lieu of a clinical trial, is a promising tool for evaluating these complex DDDIs in patients. However, the prediction confidence of PBPK modeling in the severe CKD population is still low when nonrenal pathways are involved. More mechanistic virtual disease population and robust validation cases are needed. To this end, we aimed to: (i) understand the implications of severe CKD on statins (atorvastatin, simvastatin, and rosuvastatin) pharmacokinetics (PK) and DDI; and (ii) predict untested clinical scenarios of statin‐roxadustat DDI risks in patients to guide suitable dose regimens. A novel virtual severe CKD population was developed incorporating the disease effect on both renal and nonrenal pathways. Drug and disease PBPK models underwent a four‐way validation. The verified PBPK models successfully predicted the altered PKs in patients for substrates and inhibitors and recovered the observed statin‐rifampicin DDIs in patients and the statin‐roxadustat DDIs in HVs within 1.25‐ and 2‐fold error. Further sensitivity analysis revealed that the severe CKD effect on statins PK is mainly mediated by hepatic BCRP for rosuvastatin and OATP1B1/3 for atorvastatin. The magnitude of statin‐roxadustat DDI in patients with severe CKD was predicted to be similar to that in HVs. PBPK‐guided suitable dose regimens were identified to minimize the risk of side effects or therapeutic failure of statins when co‐administered with roxadustat.