Born too soon: lifelong kidney risks and the importance of early intervention
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Evolving adeno-associated viruses for gene transfer to the kidney via cross-species cycling of capsid libraries
The difficulty of delivering genes to the kidney has limited the translation of genetic medicines, particularly for the more than 10% of the global population with chronic kidney disease. Here we show that new variants of adeno-associated viruses (AAVs) displaying robust and widespread transduction in the kidneys of mice, pigs and non-human-primates can be obtained by evolving capsid libraries via cross-species cycling in different kidney models. Specifically, the new variants, AAV.k13 and AAV.k20, were enriched from the libraries following sequential intravenous cycling through mouse and pig kidneys, ex vivo cycling in human organoid cultures, and ex vivo machine perfusion in isolated kidneys from rhesus macaques. The two variants transduced murine kidneys following intravenous administration, with selective tropism for proximal tubules, and led to markedly higher transgene expression than parental AAV9 vectors in proximal tubule epithelial cells within human organoid cultures and in autotransplanted pig kidneys. Following ureteral delivery, AAV.k20 efficiently transduced kidneys in pigs and macaques. The AAV.k13 and AAV.k20 variants are promising vectors for therapeutic gene-transfer applications in kidney diseases and transplantation.
A first-in-human study of quantitative ultrasound to assess transplant kidney fibrosis
Kidney transplantation is the optimal treatment for renal failure. In the United States, a biopsy at the time of organ procurement is often used to assess kidney quality to decide whether it should be used for transplant. This assessment is focused on renal fibrotic burden, because fibrosis is an important measure of irreversible kidney injury. Unfortunately, biopsy at the time of transplant is plagued by problems, including bleeding risk, inaccuracies introduced by sampling bias and rapid sample preparation, and the need for round-the-clock pathology expertise. We developed a quantitative algorithm, called renal H-scan, that can be added to standard ultrasound workflows to quickly and noninvasively measure renal fibrotic burden in preclinical animal models and human transplant kidneys. Furthermore, we provide evidence that biopsy-based fibrosis estimates, because of their highly localized nature, are inaccurate measures of whole-kidney fibrotic burden and do not associate with kidney function post-transplant. In contrast, we show that whole-kidney H-scan fibrosis estimates associate closely with post-transplant renal function. Taken together, our data suggest that the addition of H-scan to standard ultrasound workflows could provide a safe, rapid and easy-to-perform method for accurate quantification of transplant kidney fibrotic burden, and thus better prediction of post-transplant renal outcomes.
The risk effects of corporate digitalization: exacerbate or mitigate?
This study elaborates on the risk effects of corporate digital transformation (CDT). Using the ratio of added value of digital assets to total intangible assets as a measure of CDT, this study overall reveals an inverse relationship between CDT and revenue volatility, even after employing a range of technical techniques to address potential endogeneity. Heterogeneity analysis highlights that the firms with small size, high capital intensity, and high agency costs benefit more from CDT. It also reveals that advancing information infrastructure, intellectual property protection, and digital taxation enhances the effectiveness of CDT. Mechanism analysis uncovers that CDT not only enhances financial advantages such as bolstering core business and mitigating non-business risks but also fosters non-financial advantages like improving corporate governance and ESG performance. Further inquiries into the side effects of CDT and the dynamics of revenue volatility indicate that CDT might compromise cash flow availability. Excessive digital investments exacerbate operating risks. Importantly, the reduction in operating risk associated with CDT does not sacrifice the potential for enhanced company performance; rather, it appears to augment the value of real options.
ACOT12, a novel factor in the pathogenesis of kidney fibrosis, modulates ACBD5
Lipid metabolism, particularly fatty acid oxidation dysfunction, is a major driver of renal fibrosis. However, the detailed regulatory mechanisms underlying this process remain unclear. Here we demonstrated that acyl-CoA thioesterase 12 (Acot12), an enzyme involved in the hydrolysis of acyl-CoA thioesters into free fatty acids and CoA, is a key regulator of lipid metabolism in fibrotic kidneys. A significantly decreased level of ACOT12 was observed in kidney samples from human patients with chronic kidney disease as well as in samples from mice with kidney injuries. Acot12 deficiency induces lipid accumulation and fibrosis in mice subjected to unilateral ureteral obstruction (UUO). Fenofibrate administration does not reduce renal fibrosis in Acot12−/− mice with UUO. Moreover, the restoration of peroxisome proliferator-activated receptor α (PPARα) in Acot12−/−Pparα−/− kidneys with UUO exacerbated lipid accumulation and renal fibrosis, whereas the restoration of Acot12 in Acot12−/− Pparα−/− kidneys with UUO significantly reduced lipid accumulation and renal fibrosis, suggesting that, mechanistically, Acot12 deficiency exacerbates renal fibrosis independently of PPARα. In Acot12−/− kidneys with UUO, a reduction in the selective autophagic degradation of peroxisomes and pexophagy with a decreased level of ACBD5 was observed. In conclusion, our study demonstrates the functional role and mechanistic details of Acot12 in the progression of renal fibrosis, provides a preclinical rationale for regulating Acot12 expression and presents a novel means of preventing renal fibrosis.
Preserving and combining knowledge in robotic lifelong reinforcement learning
Humans can continually accumulate knowledge and develop increasingly complex behaviours and skills throughout their lives, which is a capability known as ‘lifelong learning’. Although this lifelong learning capability is considered an essential mechanism that makes up general intelligence, recent advancements in artificial intelligence predominantly excel in narrow, specialized domains and generally lack this lifelong learning capability. Here we introduce a robotic lifelong reinforcement learning framework that addresses this gap by developing a knowledge space inspired by the Bayesian non-parametric domain. In addition, we enhance the agent’s semantic understanding of tasks by integrating language embeddings into the framework. Our proposed embodied agent can consistently accumulate knowledge from a continuous stream of one-time feeding tasks. Furthermore, our agent can tackle challenging real-world long-horizon tasks by combining and reapplying its acquired knowledge from the original tasks stream. The proposed framework advances our understanding of the robotic lifelong learning process and may inspire the development of more broadly applicable intelligence.
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