Microbial cell factories, akin to “chips” in biomanufacturing, concentrate the most intricate scientific challenges, technical bottlenecks, and densest intellectual property. However, despite extensive efforts in rational engineering, the inherent complexity of biological systems and the limited knowledge of their underlying mechanisms still incur substantial trial-and-error costs. This Perspective seeks to explore the potential of a prior-knowledge-independent approach for optimizing microbial cell factory phenotypes. We discuss the feasibility of stepwise genotypic navigation in genome engineering and emphasize its ability to generate high-quality genotype–phenotype association data, thereby advancing AI-assisted genome modeling and further enabling precision-guided optimization.
Heart failure (HF) is a common clinical syndrome marked by reduced cardiac output, elevated intracardiac pressures, and heart dysfunction. Chronic HF (CHF) is a syndrome characterized by a lack of blood flow and impaired pumping ability to the heart over time, while acute HF (AHF) arises suddenly due to incidents like myocardial infarction or cardiac arrest. HF has a significant impact on pulmonary health and function, leading to conditions such as pulmonary edema and restrictive lung patterns. Clinical evidence highlights the bidirectional relationship between HF and lung dysfunction. Declining lung function serves as a predictor for HF progression and severity, while HF contributes to worsening lung health. Animal models that induce HF through surgical methods further demonstrate the connection between heart and lung pathology. The main mechanisms linking HF and lung dysfunction are pressure overload and chronic systemic inflammation, with changes in the extracellular matrix (ECM) also playing a role. Additionally, environmental factors like air pollution exacerbate lung inflammation, increasing the risk of both HF and chronic obstructive pulmonary disease (COPD) incidence. Combined treatment approaches involving pharmaceutical drugs such as statins, Angiotensin-converting enzyme (ACE) inhibitors, and Angiotensin receptor blockers (ARBs) may benefit by reducing inflammation. This review will explore the complex interplay between HF and lung function, emphasizing their interconnected pathophysiology and potential integrated treatment strategies.
A smooth transition towards a clean and sustainable environment will heavily rely on the continuous increase of renewable energy (RE) integration. Malaysian authorities have set targets to increase the RE capacity to 31% by the end of 2025 and achieve 40% by 2035, specifically through the power generation plan. Solar PV systems have been widely used, from industries to residential homes, because Malaysia receives a high irradiation potential of up to 5000 Wh/year. The increase in the potential of solar PV usage has allowed solar companies to provide this system regardless of its complexity and system size. However, a drop in efficiency due to system parameters within the photovoltaic (PV) system is evident over time. This study aims to analyze the relationship between solar PV system parameters and their energy performance, particularly in a tropical climate region, for a large-scale solar (LSS) plant. This project was undertaken with two objectives: First, it is to develop an optimum solar PV system by adhering to and implementing GCPV standards in Malaysia. Stage 1 will primarily focus on managing and manipulating various PV system parameters to ensure the optimum energy yield received from the plant. The system parameters analyzed are tilt angle, module technology and its effect on different temperatures, the effect of the optimizer, sizing and thermal loss. Stage 2 will then incorporate the industry data of the LSS plant by creating a Pearson’s Correlation model on how energy yield is correlated against real time system parameter values obtained. An optimum tilt angle of 10°, monocrystalline module and inclusion of optimizer increases the overall energy production from 88,986 MWh/year to 89,782 MWh/year and performance ratio (PR) from 78.9% to 79.8%. The outcome of this study demonstrates the significant parameters of the PV system to maximize the energy output to the grid. This will further support the government’s plan to reduce GHG emissions by 45% through the use of renewable energy, with the aim of producing up to 2.5 GW from LSS systems by 2030.