Study of impacts of two types of cellular aging on the yeast bud morphogenesis.

Understanding the mechanisms of the cellular aging processes is crucial for attempting to extend organismal lifespan and for studying age-related degenerative diseases. Yeast cells divide through budding, providing a classical biological model for studying cellular aging. With their powerful genetics, relatively short cell cycle, and well-established signaling pathways also found in animals, yeast cells offer valuable insights into the aging process. Recent experiments suggested the existence of two aging modes in yeast characterized by nucleolar and mitochondrial declines, respectively. By analyzing experimental data, this study shows that cells evolving into those two aging modes behave differently when they are young. While buds grow linearly in both modes, cells that consistently generate spherical buds throughout their lifespan demonstrate greater efficacy in controlling bud size and growth rate at young ages. A three-dimensional multiscale chemical-mechanical model was developed and used to suggest and test hypothesized impacts of aging on bud morphogenesis. Experimentally calibrated model simulations showed that during the early stage of budding, tubular bud shape in one aging mode could be generated by locally inserting new materials at the bud tip, a process guided by the polarized Cdc42 signal. Furthermore, the aspect ratio of the tubular bud could be stabilized during the late stage as observed in experiments in this work. The model simulation results suggest that the localization of new cell surface material insertion, regulated by chemical signal polarization, could be weakened due to cellular aging in yeast and other cell types, leading to the change and stabilization of the bud aspect ratio.

Photo-protection and photo-inhibition during light induction in Barbula indica and Conocephalum conicum under different light gradients.

The objectives of this study were to measure the chlorophyll fluorescence (ChlF) parameters of Barbula indica (Hook.) Spreng and Conocephalum conicum (L.) Dumort subjected to various light intensities (LI) as a reflection of their adaptability to their habitats. The electron transport rate (ETR) of all plants under 500 µmol m-2 s-1 photosynthetic photon flux density (PPFD) was significantly higher than other LI treatments, implying that these plants could be grown under a specific and optimal light intensity adapted to 500 PPFD conditions. As LI increased from 50 to 2,000 PPFD, we observed in all plants increased non-photochemical quenching (NPQ) and photo-inhibitory quenching (qI) and decreased photosystem II efficiency (ΦPSII), potential quantum efficiency of PSII (Fv/Fm), actual PSII efficiency (ΔF/Fm'%), and Fv/Fm%. In addition, energy-dependent quenching (qE), the light protection system (qE + qZ + qT), and qI increased as ΦPSII decreased and photo-inhibition% increased under 1000, 1500, and 2000 PPFD conditions, suggesting that these plants had higher photo-protective ability under high LI treatments to maintain higher photosynthetic system performance. B. indica plants remained photochemically active and maintained higher qE under 300, 500, and 1000 PPFD, whereas C. conicum qZ + qT exhibited higher photo-protection under 500, 1000, and 1500 PPFD conditions. These ChlF indices can be used for predicting photosynthetic responses to light induction in different bryophytes and provide a theoretical basis for ecological monitoring.

Clinic Analysis and Effective Improvement Tips for Poor Eyebrow Transplantation.

BACKGROUND: Follicular unit hair transplantation has greatly elevated the results of eyebrow restoration. However, unnatural and unbeautiful-looking results are still often seen after the surgery. OBJECTIVES: This study focused on poor eyebrow transplantation, discussed its possible reasons, and offered refined proposals. METHODS: A retrospective analysis was performed on 100 patients who were dissatisfied with the results of eyebrow grafting and came to our department from 2011 to 2021. Demographic characteristics, primary disease, and clinical data were objectively summarized and analyzed for these patients. RESULTS: The patients' medical charts and photographs were analyzed and summarized into the following outcomes: Thirty-six patients (36%) had sparse eyebrows. Forty-one patients (41%) had eyebrows with inhomogeneous density and disordered growth direction. Eleven patients (11%) did not have single-hair grafting. Seven reconstructed eyebrows (7%) had a poor connection with the remaining eyebrows. Five new eyebrows (5%) had inconsistent hair characteristics with the original eyebrows. Lower hair survival rates, insufficient understanding of naturally beautiful eyebrows, and inadequate communication with patients were the main reasons for poor outcomes. CONCLUSIONS: Good reconstructed eyebrows should have a high hair survival rate, and hair growth direction and characteristics should also be consistent with the natural eyebrow to achieve ideal surgical effects. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Comparison of 2 Incisional Methods in Hair Transplantation.

Hair transplantation has been an effective technique for facial contour modification. Hair follicular units (FU) harvested from scalp strip is the gold-standard method for hair transplantation. The difference in obtaining FU from different shapes of scalp strips is not clear yet. Follicular units of 127 patients were harvested from scalp strip through parallelogram incision or fusiform incision from October 2017 to January 2020. The number of FU in 1 cm 2 scalp strip were calculated and paired t test were used to compare the difference in hair follicle acquirement rate between 2 incisions. The number and acquisition rate of FU by parallelogram incision were significantly higher than that by fusiform incision. Therefore, parallelogram incision might be more suitable to harvest FU for hair transplantation surgery.

Computer-aided directed evolution ofl-threonine aldolase for asymmetric biocatalytic synthesis of a chloramphenicol intermediate.

l-Threonine aldolases (LTAs) employing pyridoxal phosphate (PLP) as cofactor can convert low-cost achiral substrates glycine and aldehyde directly into valuable ß-hydroxy-α-amino acids such as (2R,3S)-2-amino-3-hydroxy-3-(4-nitrophenyl) propanoic acid ((R,S)-AHNPA), which is utilized broadly as crucial chiral intermediates for bioactive compounds. However, LTAs' stereospecificity towards the ß carbon is rather moderate and their activity and stability at high substrate load is low, which limits their industrial application. Here, computer-aided directed evolution was applied to improve overall activity, selectivity and stability under desired process conditions of a l-threonine aldolase in the asymmetric synthesis of (R,S)-AHNPA. Selectivity and stability determining regions were computationally identified for structure-guided directed evolution of LTA-variants under efficient biocatalytic process conditions using 40% ethanol as cosolvent. We applied molecular modeling to rationalize selectivity improvement and design focused libraries targeting the substrate binding pocket, and we also used MD simulations in nonaqueous process environment as an effective and promising method to predict potential unstable loop regions near the tetramer interface which are hot-spots for cosolvent resistance. An excellent LTA variant EM-ALDO031 with 18 mutations was obtained, which showed âˆ¼ 30-fold stability improvement in 40% ethanol and diastereoselectivity (de) raised from 31.5% to 85% through a three-phase evolution campaign. Our fast and efficient data-driven methodology utilizing a combination of experimental and computational tools enabled us to evolve an aldolase variant to achieve the target of 90% conversion at up to 150 g/L substrate load in 40% ethanol, enabling the biocatalytic production of ß-hydroxy-α-amino acids from cheap achiral precursors at multi-ton scale.

Study of Impacts of Two Types of Cellular Aging on the Yeast Bud Morphogenesis.

Understanding the mechanisms of cellular aging processes is crucial for attempting to extend organismal lifespan and for studying age-related degenerative diseases. Yeast cells divide through budding, providing a classical biological model for studying cellular aging. With their powerful genetics, relatively short lifespan and well-established signaling pathways also found in animals, yeast cells offer valuable insights into the aging process. Recent experiments suggested the existence of two aging modes in yeast characterized by nucleolar and mitochondrial declines, respectively. In this study, by analyzing experimental data it was shown that cells evolving into those two aging modes behave differently when they are young. While buds grow linearly in both modes, cells that consistently generate spherical buds throughout their lifespan demonstrate greater efficacy in controlling bud size and growth rate at young ages. A three-dimensional chemical-mechanical model was developed and used to suggest and test hypothesized mechanisms of bud morphogenesis during aging. Experimentally calibrated simulations showed that tubular bud shape in one aging mode could be generated by locally inserting new materials at the bud tip guided by the polarized Cdc42 signal during the early stage of budding. Furthermore, the aspect ratio of the tubular bud could be stabilized during the late stage, as observed in experiments, through a reduction on the new cell surface material insertion or an expansion of the polarization site. Thus model simulations suggest the maintenance of new cell surface material insertion or chemical signal polarization could be weakened due to cellular aging in yeast and other cell types.

OCTA-500: A retinal dataset for optical coherence tomography angiography study.

Optical coherence tomography angiography (OCTA) is a novel imaging modality that has been widely utilized in ophthalmology and neuroscience studies to observe retinal vessels and microvascular systems. However, publicly available OCTA datasets remain scarce. In this paper, we introduce the largest and most comprehensive OCTA dataset dubbed OCTA-500, which contains OCTA imaging under two fields of view (FOVs) from 500 subjects. The dataset provides rich images and annotations including two modalities (OCT/OCTA volumes), six types of projections, four types of text labels (age/gender/eye/disease) and seven types of segmentation labels (large vessel/capillary/artery/vein/2D FAZ/3D FAZ/retinal layers). Then, we propose a multi-object segmentation task called CAVF, which integrates capillary segmentation, artery segmentation, vein segmentation, and FAZ segmentation under a unified framework. In addition, we optimize the 3D-to-2D image projection network (IPN) to IPN-V2 to serve as one of the segmentation baselines. Experimental results demonstrate that IPN-V2 achieves an about 10% mIoU improvement over IPN on CAVF task. Finally, we further study the impact of several dataset characteristics: the training set size, the model input (OCT/OCTA, 3D volume/2D projection), the baseline networks, and the diseases. The dataset and code are publicly available at: https://ieee-dataport.org/open-access/octa-500.

Self-Supervised Sequence Recovery for Semi-Supervised Retinal Layer Segmentation.

Automated layer segmentation plays an important role for retinal disease diagnosis in optical coherence tomography (OCT) images. However, the severe retinal diseases result in the performance degeneration of automated layer segmentation approaches. In this paper, we present a robust semi-supervised layer segmentation network to relieve the model failures on abnormal retinas. We obtain the lesion features from the labeled images with disease-balanced distribution, and utilize the unlabeled images to supplement the layer structure information. Specifically, in our method, the cross-consistency training is utilized over the predictions of different decoders, and we enforce a consistency between different decoder predictions to improve the encoder's representation. Then, we propose a sequence prediction branch based on self-supervised manner, which is designed to predict the position of each jigsaw puzzle to obtain sensory perception of the retinal layer structure. To this task, a layer spatial pyramid pooling (LSPP) module is designed to extract multi-scale layer spatial features. Furthermore, we use the optical coherence tomography angiography (OCTA) to supplement the information damaged by diseases. The experimental results illustrate that our method achieves more robust results compared with current supervised segmentation methods. Meanwhile, advanced segmentation performance can be obtained compared with state-of-the-art semi-supervised segmentation methods.

Hippo signaling dysfunction induces cancer cell addiction to YAP.

Over the past decades, the Hippo has been established as a crucial pathway involved in organ size control and cancer suppression. Dysregulation of Hippo signaling and hyperactivation of its downstream effector YAP are frequently associated with various human cancers. However, the underlying significance of such YAP activation in cancer development and therapy has not been fully characterized. In this study, we reported that the Hippo signaling deficiency can lead to a YAP-dependent oncogene addiction for cancer cells. Through a clinical compound library screen, we identified histone deacetylase (HDAC) inhibitors as putative inhibitors to suppress YAP expression. Importantly, HDAC inhibitors specifically targeted the viability and xenograft tumor growth for the cancer cells in which YAP is constitutively active. Taken together, our results not only establish an active YAP-induced oncogene addiction in cancer cells, but also lay the foundation to develop targeted therapies for the cancers with Hippo dysfunction and YAP activation.