The U.S. Food and Drug Administration has approved a total of 37 new drugs in 2022, which are composed of 20 chemical entities and 17 biologics. In particular, 20 chemical entities, including 17 ...small molecule drugs, 1 radiotherapy, and 2 diagnostic agents, provide privileged scaffolds, breakthrough clinical benefits, and a new mechanism of action for the discovery of more potent clinical candidates. The structure-based drug development with clear targets and fragment-based drug development with privileged scaffolds have always been the important modules in the field of drug discovery, which could easily bypass the patent protection and bring about improved biological activity. Therefore, we summarized the relevant valuable information about clinical application, mechanism of action, and chemical synthesis of 17 newly approved small molecule drugs in 2022. We hope this timely and comprehensive review could bring about creative and elegant inspiration on the synthetic methodologies and mechanism of action for the discovery of new drugs with novel chemical scaffolds and extended clinical indications.
1 In this paper, “overseas clinical trial data” refers to data generated from a clinical trial(s) conducted in a foreign country or jurisdiction and proposed to be used as clinical evidence for a ...pre-market registration application in China. Medical devices differ in mechanisms of action in or on the human body, type, and duration of contact with the human body, and expected clinical effects. ...a medical device may have different risks and clinical performances across populations. The working mechanism is based on time-dependent changes in optical tissue properties caused by pulsatile flow. Since the operating principle involves the interaction between optical signals and tissues, issues related to melanin deposition should be considered. Specifically, the overseas subjects and Chinese target group may have differences in skin color. ...a bridging clinical study may be needed. Ju S, Liu YH, Zhang YD, Wu CS, Xiao L, Sun L. Acceptance of overseas clinical trial data of medical devices for pre-market registration: general principles and considerations of the National Medical Products Administration.
As an early complication after liver transplantation, early allograft dysfunction (EAD) indicates a poor prognosis. This study analyzes the risk factors related to early allograft dysfunction (EAD) ...after liver transplantation using grafts from donation after citizen death (DCD) to provide a reference for the prevention of EAD after DCD liver transplantation.
A total of 32 patients who underwent DCD liver transplantation in the organ transplantation center of our hospital from September 2013 to January 2021 were enrolled in this study. The patients were divided into the EAD group and non-EAD group according to whether they developed EAD after transplantation. The general data of the donors and recipients before transplantation, intraoperative conditions, and clinical data within one week after transplantation were compared between the two groups, and related complications were statistically analyzed. The follow-up time was one week postoperatively or, if they died within the first week postoperatively, until the patient died.
The subjects included 10 females and 22 males, and the incidence of postoperative EAD was 25% (8/32). Four patients (12%) had primary malignant tumors (primary liver cancer and cholangiocarcinoma), and five donors (15%) had fatty liver. The univariate analysis revealed that the donor BMI (P = 0.005), degree of fatty liver (P = 0.025), aspartate aminotransferase (P = 0.001), alanine aminotransferase (P < 0.001), and total bilirubin (P = 0.009) were related to the occurrence of EAD after DCD liver transplantation. By analyzing the correlation between the incidence EAD and postoperative complications after liver transplantation using grafts from DCD donors, it was shown that the incidence of primary nonfunction (PNF) is related to EAD (P = 0.024).
Donor BMI, the degree of fatty liver, and preoperative liver function are risk factors for EAD after DCD liver transplantation, and the occurrence of EAD after DCD liver transplantation significantly increases the probability of PNF.
Introduction
Little is known about the effects of boiling on nutrient levels in fishes that have a relatively high phosphorus‐to‐protein ratio (PPR), which are important sources of omega‐3 ...polyunsaturated fatty acids. We hypothesized that the beneficial effects of boiling for a shorter duration (15 min) on nutrient contents in fishes were similar to those of boiling for a longer duration (30 min), which has been shown to decrease the PPR in meat.
Methods
The protein, fat, and phosphorus contents and the PPR of three cooked fish species and their corresponding fish broths were chemically analyzed. The effects of boiling on changes in protein, fat, phosphorus, and the PPR was examined by comparing fish that were prepared with usual cooking methods (no boiling), boiled for 15 min, and boiled for 30 min. The nutrients in fish broths that were boiled for 15 min were also compared with those boiled for 30 min.
Findings
There were no significant differences in the changes in phosphorus, PPR, protein, and fat content in fish and fish broths prepared with the two boiling methods. In the fish boiled for 15 min, the phosphorus content was 24% lower (p = 0.001), and the PPR was 20% lower (p = 0.04) than those in nonboiled fish. Additionally, boiling for 30 min reduced the phosphorus content by 31% (p = 0.001), and the PPR by 27% (p = 0.04) compared to nonboiled fish, but the protein and fat contents were unchanged after both 15 and 30 min of boiling.
Discussion
The 15‐ and 30‐min boiling methods resulted in a similar reduction in phosphorus and the PPR in fish, with minimal effects on protein and fat. A shorter duration of boiling is recommended to achieve better nutrient profiles in fishes consumed by dialysis patients.
As a class of novel biomaterials manufactured by synthetic biology technologies, recombinant collagens are candidates for a variety of medical applications. In this article, a regulatory scientific ...perspective on recombinant collagens and their medical devices is presented with a focus on the definition, translation, classification and technical review. Recombinant collagens are categorized as recombinant human collagen, recombinant humanized collagen and recombinant collagen-like protein, as differentiated by specific compositions and structures. Based on their intended uses and associated risks, recombinant collagen-based medical devices are generally classified as Class Ⅱ or Ⅲ in China. The regulatory review of recombinant collagen-based medical devices aims to assess their safety and efficacy demonstrated by scientific evidences generated from preclinical and clinical evaluations. Taken together, opportunities as well as challenges for their future clinical translation of recombinant collagen-based medical devices abound, which highlights the essential role of regulatory science to provide new tools, standards, guidelines and methods to evaluate the safety and efficacy of medical products.
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•Recombinant collagens are novel biomaterials manufactured by biosynthesis methods.•The first regulatory article on recombinant collagen-based medical devices.•Recombinant collagen-based medical devices are defined and classified by NMPA.•Regulatory review assesses the safety and efficacy of medical devices.•Translation of recombinant collagens from bench to clinic needs regulatory science.
Abstract
Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining comprehensive molecular characterization and cellular responses for a variety of cell lines, ...including those derived from underrepresented groups, is not trivial when resources are minimal. Using gene expression to predict other measurements has been actively explored; however, systematic investigation of its predictive power in various measurements has not been well studied. We evaluated commonly used machine learning methods and presented TransCell, a two-step deep transfer learning framework that utilized the knowledge derived from pan-cancer tumor samples to predict molecular features and responses. Among these models, TransCell has the best performance in predicting metabolite, gene effect score (or genetic dependency), and drug sensitivity, and has comparable performance in predicting mutation, copy number variation, and protein expression. Notably, TransCell improved the performance by over 50% in drug sensitivity prediction and achieved a correlation of 0.7 in gene effect score prediction. Furthermore, predicted drug sensitivities revealed potential repurposing candidates for new 100 pediatric cancer cell lines, and predicted gene effect scores reflected BRAF resistance in melanoma cell lines. Together, we investigated the predictive power of gene expression in six molecular measurement types and developed a web portal (http://apps.octad.org/transcell/) that enables the prediction of 352,000 genomic and cellular response features solely from gene expression profiles.
Using nanoscale electrical-discharge-induced rapid Joule heating, we developed a method for ultrafast shape change and joining of small-volume materials. Shape change is dominated by ...surface-tension-driven convection in the transient liquid melt, giving an extremely high strain rate of N106 s-1. In addition, the heat can be dissipated in small volumes within a few microseconds through thermal conduction, quenching the melt back to the solid state with cooling rates up to 108 K.s-1. We demonstrate that this approach can be utilized for the ultrafast welding of small-volume crystalline Mo （a refractory metal） and amorphous Cu49Zr51 without introducing obvious microstructural changes, distinguishing the process from bulk welding.
Abstract
Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining comprehensive molecular characterization and cellular responses for a variety of cell lines, ...including those derived from underrepresented groups, is not trivial when resources are minimal. Using gene expression to predict other measurements has been actively explored; however, systematic investigation of its predictive power in various measurements has not been well studied. We present TransCell, a two-step deep transfer learning framework that utilizes the knowledge derived from pan-cancer tumor samples to predict molecular features and responses. Compared to the five state-of-art methods, TransCell has the best performance in predicting metabolite, gene effect score (or genetic dependency), and drug sensitivity, and has comparable performance in predicting mutation, copy number variation, and protein expression. Notably, TransCell improved the performance by over 50% in drug sensitivity prediction and achieved a correlation of 0.7 in gene effect score prediction. Furthermore, predicted drug sensitivities revealed potential repurposing candidates for new 100 pediatric cancer cell lines, and predicted gene effect scores reflected BRAF resistance in melanoma cell lines. Together, TransCell demonstrates its remarkable predictive power that enables in silico molecular characterization of understudied cell lines.
Citation Format: Shan-Ju Yeh, Ruoqiao Chen, Jing Xing, Mengying Sun, Ke Liu, Shreya Paithankar, Jiayu Zhou, Bin Chen. Transcell: In silico characterization of genomic landscape and cellular responses from gene expressions through a two-step transfer learning abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1927.
High mobility group box1 （HMGB1）, as a damage-associated inflammatory factor, contributes to the pathogenesis of numerous chronic inflammatory and autoimmune diseases. In this study, we explored the ...role of HMGB1 in CDI （Clostridium difficile infection） by in vivo and in vitro experiments. Our results showed that HMGB1 might play an important role in the acute inflammatory responses to C. difficile toxin A （TcdA）, affect early inflammatory factors, and induce inflammation via the HMGB1-TLR4 pathway. Our study provides the essential information for better understanding the molecular mechanisms of CDI and the potential new therapeutic strategies for the treatment of this infection.
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