DIENELACTONE HYDROLASE LIKE PROTEIN1 negatively regulates the KAI2-ligand pathway in Marchantia polymorpha.

Karrikins are smoke-derived butenolides that induce seed germination and photomorphogenesis in a wide range of plants.1,2,3 KARRIKIN INSENSITIVE2 (KAI2), a paralog of a strigolactone receptor, perceives karrikins or their metabolized products in Arabidopsis thaliana.4,5,6,7 Furthermore, KAI2 is thought to perceive an unidentified plant hormone, called KAI2 ligand (KL).8,9 KL signal is transduced via the interaction between KAI2, MORE AXILLARY GROWTH2 (MAX2), and SUPPRESSOR of MORE AXILLARY GROWTH2 1 LIKE family proteins (SMXLs), followed by the degradation of SMXLs.4,7,10,11,12,13,14 This signaling pathway is conserved both in A. thaliana and the bryophyte Marchantia polymorpha.14 Although the KL signaling pathway is well characterized, the KL metabolism pathways remain poorly understood. Here, we show that DIENELACTONE HYDROLASE LIKE PROTEIN1 (DLP1) is a negative regulator of the KL pathway in M. polymorpha. The KL signal induces DLP1 expression. DLP1 overexpression lines phenocopied the Mpkai2a and Mpmax2 mutants, while dlp1 mutants phenocopied the Mpsmxl mutants. Mutations in the KL signaling genes largely suppressed these phenotypes, indicating that DLP1 acts upstream of the KL signaling pathway, although DLP1 also has KL pathway-independent functions. DLP1 exhibited enzymatic activity toward a potential substrate, suggesting the possibility that DLP1 works through KL inactivation. Investigation of DLP1 homologs in A. thaliana revealed that they do not play a major role in the KL pathway, suggesting different mechanisms for the KL signal regulation. Our findings provide new insights into the regulation of the KL signal in M. polymorpha and the evolution of the KL pathway in land plants.

An ancestral function of strigolactones as symbiotic rhizosphere signals.

In flowering plants, strigolactones (SLs) have dual functions as hormones that regulate growth and development, and as rhizosphere signaling molecules that induce symbiosis with arbuscular mycorrhizal (AM) fungi. Here, we report the identification of bryosymbiol (BSB), an SL from the bryophyte Marchantia paleacea. BSB is also found in vascular plants, indicating its origin in the common ancestor of land plants. BSB synthesis is enhanced at AM symbiosis permissive conditions and BSB deficient mutants are impaired in AM symbiosis. In contrast, the absence of BSB synthesis has little effect on the growth and gene expression. We show that the introduction of the SL receptor of Arabidopsis renders M. paleacea cells BSB-responsive. These results suggest that BSB is not perceived by M. paleacea cells due to the lack of cognate SL receptors. We propose that SLs originated as AM symbiosis-inducing rhizosphere signaling molecules and were later recruited as plant hormone.

Major components of the KARRIKIN INSENSITIVE2-dependent signaling pathway are conserved in the liverwort Marchantia polymorpha.

KARRIKIN INSENSITIVE2 (KAI2) was first identified as a receptor of karrikins, smoke-derived germination stimulants. KAI2 is also considered a receptor of an unidentified endogenous molecule called the KAI2 ligand. Upon KAI2 activation, signals are transmitted through the degradation of D53/SMXL proteins via MAX2-dependent ubiquitination. Although components in the KAI2-dependent signaling pathway, namely MpKAI2A and MpKAI2B, MpMAX2, and MpSMXL, exist in the genome of the liverwort Marchantia polymorpha, their functions remain unknown. Here, we show that early thallus growth is retarded and gemma dormancy in the dark is suppressed in Mpkai2a and Mpmax2 loss-of-function mutants. These defects are counteracted in Mpkai2a Mpsmxl and Mpmax2 Mpsmxl double mutants indicating that MpKAI2A, MpMAX2, and MpSMXL act in the same genetic pathway. Introduction of MpSMXLd53, in which a domain required for degradation is mutated, into wild-type plants mimicks Mpkai2a and Mpmax2 plants. In addition, the detection of citrine fluorescence in Nicotiana benthamiana cells transiently expressing a SMXL-Citrine fusion protein requires treatment with MG132, a proteasome inhibitor. These findings imply that MpSMXL is subjected to degradation, and that the degradation of MpSMXL is crucial for MpKAI2A-dependent signaling in M. polymorpha. Therefore, we claim that the basic mechanisms in the KAI2-dependent signaling pathway are conserved in M. polymorpha.

Cuffless Blood Pressure Estimation from only the Waveform of Photoplethysmography using CNN.

Although the pulse transit time is generally used for blood pressure estimation without a cuff, a method of estimating blood pressure only from photoplethysmography (PPG) based on the relationship between pulse waveform and blood pressure has been studied. This can eliminate the need for an electrocardiogram and allow more continuous and simpler blood pressure measurement. Previous studies have proposed methods of machine learning by extracting features such as wave height and time difference, or generating features with an auto-encoder. In this paper, we propose a method to estimate blood pressure and to automatically generate features from pulse wave using the convolutional neural networks (CNN). By comparing the accuracy of the proposed method with that of the conventional method, the effectiveness of cuffless blood pressure estimation from only PPG by using CNN is examined.

Features Extraction for Cuffless Blood Pressure Estimation by Autoencoder from Photoplethysmography.

Several studies have been proposed to estimate blood pressure (BP) with cuffless devices using only a Photoplethysmograph (PPG) sensor on the basis of the physiological knowledge that the PPG changes depend on the state of the cardiovascular system. In these studies, machine learning algorithms were used to extract various features from the wave height and the elapsed time from the rising point of the pulse wave to feature points have been used to estimate the BP. However, the accuracy is still not adequate to be used as medical equipment because their features cannot express fully information of the pulse waveform which changes according to the BP. And, no other effective knowledge about the pulse waveform for estimating BP has been found yet. Therefore, in this study, we focus on the autoencoder which can extract complex features and can add new features of the pulse waveform for estimating the BP. By using autoencoder, we extracted 100 features from the coupling signal of the pulse wave and from its first-order differentiation and second-order differentiation. The result of examination with 1363 test subjects show that the correlation coefficients and the standard deviation of the difference between the measured BP and the estimated BP got improved from R = 0.67, SD = 13.97 without autoencoder to R = 0.78, SD = 11.86 with autoencoder.