Cavitation-on-a-Chip Enabled Size-Specific Liposomal Drugs for Selective Pharmacokinetics and Pharmacodynamics.

The size of liposomal drugs has been demonstrated to strongly correlate with their pharmacokinetics and pharmacodynamics. While the microfluidic method successfully achieves the production of liposomes with well-controlled sizes across various buffer/lipid flow rate ratio (FRR) settings, any adjustments to the FRR inevitably influence the concentration, encapsulation efficiency (EE), and stability of liposomal drugs. Here we describe a controllable cavitation-on-a-chip (CCC) strategy that facilitates the precise regulation of liposomal drug size at any desired FRR. The CCC-enabled size-specific liposomes exhibited striking differences in uptake and biodistribution behaviors, thereby demonstrating distinct antitumor efficacy in both tumor-bearing animal and melanoma patient-derived organoid (PDO) models. Intriguingly, as the liposome size decreased to approximately 80 nm, the preferential accumulation of liposomal drugs in the liver transitioned to a predominant enrichment in the kidneys. These findings underscore the considerable potential of our CCC approach in influencing the pharmacokinetics and pharmacodynamics of liposomal nanomedicines.

Corrigendum: The utility of high-frequency 18 MHz ultrasonography for preoperative evaluation of acral melanoma thickness in Chinese patients.

[This corrects the article DOI: 10.3389/fonc.2023.1185389.].

A real-time augmented reality system integrated with artificial intelligence for skin tumor surgery: experimental study and case series.

BACKGROUND: Skin tumors affect many people worldwide, and surgery is the first treatment choice. Achieving precise preoperative planning and navigation of intraoperative sampling remains a problem and is excessively reliant on the experience of surgeons, especially for Mohs surgery for malignant tumors. MATERIALS AND METHODS: To achieve precise preoperative planning and navigation of intraoperative sampling, we developed a real-time augmented reality (AR) surgical system integrated with artificial intelligence (AI) to enhance three functions: AI-assisted tumor boundary segmentation, surgical margin design, and navigation in intraoperative tissue sampling. Non-randomized controlled trials were conducted on manikin, tumor-simulated rabbits, and human volunteers in Hunan Engineering Research Center of Skin Health and Disease Laboratory to evaluate the surgical system. RESULTS: The results showed that the accuracy of the benign and malignant tumor segmentation was 0.9556 and 0.9548, respectively, and the average AR navigation mapping error was 0.644 mm. The proposed surgical system was applied in 106 skin tumor surgeries, including intraoperative navigation of sampling in 16 Mohs surgery cases. Surgeons who have used this system highly recognize it. CONCLUSIONS: The surgical system highlighted the potential to achieve accurate treatment of skin tumors and to fill the gap in global research on skin tumor surgery systems.

Association between alopecia areata, anxiety, and depression: Insights from a bidirectional two-sample Mendelian randomization study.

BACKGROUND: As research progresses, there has been growing interest in the association between Alopecia areata (AA) and anxiety, as well as depression. However, there have been limited reports on the genetic variation level of AA in relation to mental disorders. METHOD: We performed large-scale Two sample Mendelian randomization (MR) analyses to examine whether there is a association between AA with anxiety and depression. The data utilized for AA analysis were sourced from the FinnGen release 9 databases, including 682 cases and 361,822 controls. Summary statistics for major depression disorder (MDD) were obtained from a genome-wide meta-analysis dataset, incorporating 170,756 cases and 329,443 controls. The anxiety disorder data was conducted by the Anxiety Neuro Genetics Study Consortium, including 5580 cases and 11,730 controls. We employed four distinct approaches, including MR-Egger, weighted median, random-effect inverse variance weighted (IVW), and weighted mode, to conduct the MR analysis. RESULTS: Genetic liability to AA was associated with an increased risk of Major depression disorder (MDD) and anxiety demonstrated an odds ratio (OR) of 1.01 (ßivw = 0.011, PIVW = 0.023) and OR of 1.16 (ßivw = 0.150, PIVW = 0.002). Upon conducting the Bonferroni correction, the P-values were 0.046 and 0.004, respectively. For reverse analysis, we observed no significant association between anxiety and MDD with the risk of AA. CONCLUSIONS: Our research unveil a unidirectional causal association whereby AA exerts a risk effect against MDD and anxiety, which serves as a valuable complement to prior meta-analyses, enriching the existing body of knowledge on the subject matter.