Impact Comparison of El Niño and Ageing Crops on Malaysian Oil Palm Yield.

Ageing oil palm crops show a significant correlation with the declining oil palm yield in Malaysia. Not only do aged crops result in lower production, but they are also more costly and difficult to harvest. The Malaysian oil palm yield recovered to the pre-El Niño level after the 1997/98 El Niño event. However, the oil palm yield failed to recover after the recent 2015/16 El Niño. Due to the accumulation of aged oil palm plantations in Malaysia, the financial losses from different magnitudes of El Niño events are increasing. Thirty-four years of monthly oil palm yield trends in Malaysia were compared with the El Niño-free yield dataset to show that the oil palm yield downtrend pattern is the same with or without El Niño events in Malaysia for the most recent 15 years (2005 to 2019). The performance of oil palm yield did not show any significant difference from 2000 to 2019. This study estimates that ageing oil palms would lead to a minimum opportunity loss of USD 431 million by December 2022. Without a proper replanting program, the total combined loss attributable to the ageing crops from 2009 to 2022 is estimated to be USD 3.94 billion, which is more profound than losses due to El Niño events within the same period. This study also concluded that a continuous 7-year replanting scheme of at least 115,000 hectares per year is needed to address the adverse impact of ageing crops on the Malaysian oil palm yield, which accounts for nearly 30% of the global palm oil production.

Addressing the Clinical Feasibility of Adopting Circulating miRNA for Breast Cancer Detection, Monitoring and Management with Artificial Intelligence and Machine Learning Platforms.

Detecting breast cancer (BC) at the initial stages of progression has always been regarded as a lifesaving intervention. With modern technology, extensive studies have unraveled the complexity of BC, but the current standard practice of early breast cancer screening and clinical management of cancer progression is still heavily dependent on tissue biopsies, which are invasive and limited in capturing definitive cancer signatures for more comprehensive applications to improve outcomes in BC care and treatments. In recent years, reviews and studies have shown that liquid biopsies in the form of blood, containing free circulating and exosomal microRNAs (miRNAs), have become increasingly evident as a potential minimally invasive alternative to tissue biopsy or as a complement to biomarkers in assessing and classifying BC. As such, in this review, the potential of miRNAs as the key BC signatures in liquid biopsy are addressed, including the role of artificial intelligence (AI) and machine learning platforms (ML), in capitalizing on the big data of miRNA for a more comprehensive assessment of the cancer, leading to practical clinical utility in BC management.