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Undoubtedly, high-fidelity 3D hair is crucial for achieving realism, artistic expression, and immersion in computer graphics. While existing 3D hair modeling methods have achieved impressive performance, the challenge of achieving high-quality hair reconstruction persists: they either require strict capture conditions, making practical applications difficult, or heavily rely on learned prior data, obscuring fine-grained details in images. To address these challenges, we propose MonoHair,a generic framework to achieve high-fidelity hair reconstruction from a monocular video, without specific requirements for environments. Our approach bifurcates the hair modeling process into two main stages: precise exterior reconstruction and interior structure inference. The exterior is meticulously crafted using our Patch-based Multi-View Optimization (PMVO). This method strategically collects and integrates hair information from multiple views, independent of prior data, to produce a high-fidelity exterior 3D line map. This map not only captures intricate details but also facilitates the inference of the hair's inner structure. For the interior, we employ a data-driven, multi-view 3D hair reconstruction method. This method utilizes 2D structural renderings derived from the reconstructed exterior, mirroring the synthetic 2D inputs used during training. This alignment effectively bridges the domain gap between our training data and real-world data, thereby enhancing the accuracy and reliability of our interior structure inference. Lastly, we generate a strand model and resolve the directional ambiguity by our hair growth algorithm. Our experiments demonstrate that our method exhibits robustness across diverse hairstyles and achieves state-of-the-art performance. For more results, please refer to our project page https://keyuwu-cs.github.io/MonoHair/., Comment: Accepted by IEEE CVPR 2024

Numerous methods have been proposed to detect, estimate, and analyze properties of people in images, including the estimation of 3D pose, shape, contact, human-object interaction, emotion, and more. Each of these methods works in isolation instead of synergistically. Here we address this problem and build a language-driven human understanding system -- ChatHuman, which combines and integrates the skills of many different methods. To do so, we finetune a Large Language Model (LLM) to select and use a wide variety of existing tools in response to user inputs. In doing so, ChatHuman is able to combine information from multiple tools to solve problems more accurately than the individual tools themselves and to leverage tool output to improve its ability to reason about humans. The novel features of ChatHuman include leveraging academic publications to guide the application of 3D human-related tools, employing a retrieval-augmented generation model to generate in-context-learning examples for handling new tools, and discriminating and integrating tool results to enhance 3D human understanding. Our experiments show that ChatHuman outperforms existing models in both tool selection accuracy and performance across multiple 3D human-related tasks. ChatHuman is a step towards consolidating diverse methods for human analysis into a single, powerful, system for 3D human reasoning., Comment: Project page: https://chathuman.github.io

We address the problem of regressing 3D human pose and shape from a single image, with a focus on 3D accuracy. The current best methods leverage large datasets of 3D pseudo-ground-truth (p-GT) and 2D keypoints, leading to robust performance. With such methods, we observe a paradoxical decline in 3D pose accuracy with increasing 2D accuracy. This is caused by biases in the p-GT and the use of an approximate camera projection model. We quantify the error induced by current camera models and show that fitting 2D keypoints and p-GT accurately causes incorrect 3D poses. Our analysis defines the invalid distances within which minimizing 2D and p-GT losses is detrimental. We use this to formulate a new loss Threshold-Adaptive Loss Scaling (TALS) that penalizes gross 2D and p-GT losses but not smaller ones. With such a loss, there are many 3D poses that could equally explain the 2D evidence. To reduce this ambiguity we need a prior over valid human poses but such priors can introduce unwanted bias. To address this, we exploit a tokenized representation of human pose and reformulate the problem as token prediction. This restricts the estimated poses to the space of valid poses, effectively providing a uniform prior. Extensive experiments on the EMDB and 3DPW datasets show that our reformulated keypoint loss and tokenization allows us to train on in-the-wild data while improving 3D accuracy over the state-of-the-art. Our models and code are available for research at https://tokenhmr.is.tue.mpg.de., Comment: CVPR 2024

Massive stars are formed in molecular clouds, and produce H II regions when they evolve onto the main sequence. The expansion of H II region can both suppress and promote star formation in the vicinity. M17 H II region is a giant cometary H II region near many massive clumps containing starless and protostellar sources. It is an appropriate target to study the effect of feedback from previously formed massive stars on the nearby star-forming environments. Observations of SiO 2-1, HCO$^+$ 1-0, H$^{13}$CO$^+$ 1-0, HC$_3$N 10-9, and H41$\alpha$ lines are performed toward M17 H II region with ambient candidates of massive clumps. In the observations, the widespread shocked gas surrounding M17 H II region is detected: it probably originates from the collision between the expanding ionized gas and the ambient neutral medium. Some massive clumps are found in the overlap region of the shock and dense-gas tracing lines while the central velocities of shocked and high-density gases are similar. This suggests that part of massive clumps are located in the shell of H II region, and may be formed from the accumulated neutral materials in the shell. In addition, by comparing the observations toward M17 H II region with the simulation of cometary H II region, we infer the presence of one or more massive stars travelling at supersonic velocity with respect to the natal molecular cloud in the H II region., Comment: 13 pages, 11 figures

Shocks are abundant in star-forming regions, and are often related with star formation. In our previous observations toward 100 starless clump candidates (SCCs) in the Galaxy, a sample of 34 SCCs associated with shocks is identified. In this work, we perform mapping observations of the SiO 2-1, 3-2, HC$_3$N 10-9, HCO$^+$ 1-0, H$^{13}$CO$^+$ 1-0, and H41$\alpha$ lines toward 9 out of the detected sources by using IRAM 30-m radio telescope to study the origins of the shocks in the SCCs. We find shocks in three sources (BGPS 3110, 3114, and 3118) are produced by collisions between the expanding ionized gas and ambient molecular gas, instead of by the star formation activity inside SCCs. On the other hand, shocks in the other six sources are related to star formation activity of SCCs. The signatures of protostellar outflows are clearly shown in the molecular lines toward BGPS 4029, 4472, 5064. Comparing our results with the previous ALMA observations performed in the same region, the shocks in BGPS 3686 and 5114 are also likely to be due to protostellar activity. The origin of shock in BGPS 5243 is still unclear although some features in the SiO spectra imply the presence of protostellar activity., Comment: 21 pages, 21 figues

We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation. Compared to other 3D representations like voxels and point clouds, meshes are more desirable in practice, because (1) they enable easy and arbitrary manipulation of shapes for relighting and simulation, and (2) they can fully leverage the power of modern graphics pipelines which are mostly optimized for meshes. Previous scalable methods for generating meshes typically rely on sub-optimal post-processing, and they tend to produce overly-smooth or noisy surfaces without fine-grained geometric details. To overcome these shortcomings, we take advantage of the graph structure of meshes and use a simple yet very effective generative modeling method to generate 3D meshes. Specifically, we represent meshes with deformable tetrahedral grids, and then train a diffusion model on this direct parametrization. We demonstrate the effectiveness of our model on multiple generative tasks., Comment: ICLR 2023 (Spotlight, Notable-top-25%)

Hydrogen recombination lines (RRLs) are one of the major diagnostics of the physical properties of H{\sc ii} regions. We use RRL H40$\alpha$, He40$\alpha$ and 3 mm continuum emission to investigate the properties of a large sample of resolved UC H{\sc ii} regions identified in the ATOMS survey. In total, we identify 94 UC H{\sc ii} regions from H40$\alpha$ emission. The basic parameters for these UC H{\sc ii} regions such as electron density, emission measure, electron temperature, ionic abundance ratio (n$_{\rm He^+}$/n$_{\rm H^+}$), and line width are derived. The median electron density and the median n$_{\rm He^+}$/n$_{\rm H^+}$ ratio of these UC H{\sc ii} regions derived from RRLs are $\sim$9000 cm$^{-3}$ and 0.11, respectively. Within UC H{\sc ii} regions, the n$_{\rm He^+}$/n$_{\rm H^+}$ ratios derived from the intensity ratio of the He40$\alpha$ and H40$\alpha$ lines seems to be higher in the boundary region than in the center. The H40$\alpha$ line width is mainly broadened by thermal motion and microturbulence. The electron temperature of these UC H{\sc ii} regions has a median value of $\sim$6700 K, and its dependence on galactocentric distance is weak.

We introduce ChatPose, a framework employing Large Language Models (LLMs) to understand and reason about 3D human poses from images or textual descriptions. Our work is motivated by the human ability to intuitively understand postures from a single image or a brief description, a process that intertwines image interpretation, world knowledge, and an understanding of body language. Traditional human pose estimation and generation methods often operate in isolation, lacking semantic understanding and reasoning abilities. ChatPose addresses these limitations by embedding SMPL poses as distinct signal tokens within a multimodal LLM, enabling the direct generation of 3D body poses from both textual and visual inputs. Leveraging the powerful capabilities of multimodal LLMs, ChatPose unifies classical 3D human pose and generation tasks while offering user interactions. Additionally, ChatPose empowers LLMs to apply their extensive world knowledge in reasoning about human poses, leading to two advanced tasks: speculative pose generation and reasoning about pose estimation. These tasks involve reasoning about humans to generate 3D poses from subtle text queries, possibly accompanied by images. We establish benchmarks for these tasks, moving beyond traditional 3D pose generation and estimation methods. Our results show that ChatPose outperforms existing multimodal LLMs and task-specific methods on these newly proposed tasks. Furthermore, ChatPose's ability to understand and generate 3D human poses based on complex reasoning opens new directions in human pose analysis., Comment: Home page: https://yfeng95.github.io/ChatPose

Large foundation models are becoming ubiquitous, but training them from scratch is prohibitively expensive. Thus, efficiently adapting these powerful models to downstream tasks is increasingly important. In this paper, we study a principled finetuning paradigm -- Orthogonal Finetuning (OFT) -- for downstream task adaptation. Despite demonstrating good generalizability, OFT still uses a fairly large number of trainable parameters due to the high dimensionality of orthogonal matrices. To address this, we start by examining OFT from an information transmission perspective, and then identify a few key desiderata that enable better parameter-efficiency. Inspired by how the Cooley-Tukey fast Fourier transform algorithm enables efficient information transmission, we propose an efficient orthogonal parameterization using butterfly structures. We apply this parameterization to OFT, creating a novel parameter-efficient finetuning method, called Orthogonal Butterfly (BOFT). By subsuming OFT as a special case, BOFT introduces a generalized orthogonal finetuning framework. Finally, we conduct an extensive empirical study of adapting large vision transformers, large language models, and text-to-image diffusion models to various downstream tasks in vision and language., Comment: ICLR 2024 (v2: 34 pages, 19 figures)

The creation of photorealistic virtual worlds requires the accurate modeling of 3D surface geometry for a wide range of objects. For this, meshes are appealing since they 1) enable fast physics-based rendering with realistic material and lighting, 2) support physical simulation, and 3) are memory-efficient for modern graphics pipelines. Recent work on reconstructing and statistically modeling 3D shape, however, has critiqued meshes as being topologically inflexible. To capture a wide range of object shapes, any 3D representation must be able to model solid, watertight, shapes as well as thin, open, surfaces. Recent work has focused on the former, and methods for reconstructing open surfaces do not support fast reconstruction with material and lighting or unconditional generative modelling. Inspired by the observation that open surfaces can be seen as islands floating on watertight surfaces, we parameterize open surfaces by defining a manifold signed distance field on watertight templates. With this parameterization, we further develop a grid-based and differentiable representation that parameterizes both watertight and non-watertight meshes of arbitrary topology. Our new representation, called Ghost-on-the-Shell (G-Shell), enables two important applications: differentiable rasterization-based reconstruction from multiview images and generative modelling of non-watertight meshes. We empirically demonstrate that G-Shell achieves state-of-the-art performance on non-watertight mesh reconstruction and generation tasks, while also performing effectively for watertight meshes., Comment: ICLR 2024 Oral (v3: 30 pages, 19 figures, Project Page: https://gshell3d.github.io/)

In this paper, we focus on a general yet important learning problem, pairwise similarity learning (PSL). PSL subsumes a wide range of important applications, such as open-set face recognition, speaker verification, image retrieval and person re-identification. The goal of PSL is to learn a pairwise similarity function assigning a higher similarity score to positive pairs (i.e., a pair of samples with the same label) than to negative pairs (i.e., a pair of samples with different label). We start by identifying a key desideratum for PSL, and then discuss how existing methods can achieve this desideratum. We then propose a surprisingly simple proxy-free method, called SimPLE, which requires neither feature/proxy normalization nor angular margin and yet is able to generalize well in open-set recognition. We apply the proposed method to three challenging PSL tasks: open-set face recognition, image retrieval and speaker verification. Comprehensive experimental results on large-scale benchmarks show that our method performs significantly better than current state-of-the-art methods., Comment: Published in ICCV 2023 (Project page: https://simple.is.tue.mpg.de/)

Tremendous efforts have been made to learn animatable and photorealistic human avatars. Towards this end, both explicit and implicit 3D representations are heavily studied for a holistic modeling and capture of the whole human (e.g., body, clothing, face and hair), but neither representation is an optimal choice in terms of representation efficacy since different parts of the human avatar have different modeling desiderata. For example, meshes are generally not suitable for modeling clothing and hair. Motivated by this, we present Disentangled Avatars~(DELTA), which models humans with hybrid explicit-implicit 3D representations. DELTA takes a monocular RGB video as input, and produces a human avatar with separate body and clothing/hair layers. Specifically, we demonstrate two important applications for DELTA. For the first one, we consider the disentanglement of the human body and clothing and in the second, we disentangle the face and hair. To do so, DELTA represents the body or face with an explicit mesh-based parametric 3D model and the clothing or hair with an implicit neural radiance field. To make this possible, we design an end-to-end differentiable renderer that integrates meshes into volumetric rendering, enabling DELTA to learn directly from monocular videos without any 3D supervision. Finally, we show that how these two applications can be easily combined to model full-body avatars, such that the hair, face, body and clothing can be fully disentangled yet jointly rendered. Such a disentanglement enables hair and clothing transfer to arbitrary body shapes. We empirically validate the effectiveness of DELTA's disentanglement by demonstrating its promising performance on disentangled reconstruction, virtual clothing try-on and hairstyle transfer. To facilitate future research, we also release an open-sourced pipeline for the study of hybrid human avatar modeling., Comment: home page: https://yfeng95.github.io/delta. arXiv admin note: text overlap with arXiv:2210.01868

Our goal is to create a realistic 3D facial avatar with hair and accessories using only a text description. While this challenge has attracted significant recent interest, existing methods either lack realism, produce unrealistic shapes, or do not support editing, such as modifications to the hairstyle. We argue that existing methods are limited because they employ a monolithic modeling approach, using a single representation for the head, face, hair, and accessories. Our observation is that the hair and face, for example, have very different structural qualities that benefit from different representations. Building on this insight, we generate avatars with a compositional model, in which the head, face, and upper body are represented with traditional 3D meshes, and the hair, clothing, and accessories with neural radiance fields (NeRF). The model-based mesh representation provides a strong geometric prior for the face region, improving realism while enabling editing of the person's appearance. By using NeRFs to represent the remaining components, our method is able to model and synthesize parts with complex geometry and appearance, such as curly hair and fluffy scarves. Our novel system synthesizes these high-quality compositional avatars from text descriptions. The experimental results demonstrate that our method, Text-guided generation and Editing of Compositional Avatars (TECA), produces avatars that are more realistic than those of recent methods while being editable because of their compositional nature. For example, our TECA enables the seamless transfer of compositional features like hairstyles, scarves, and other accessories between avatars. This capability supports applications such as virtual try-on., Comment: Home page: https://yfeng95.github.io/teca

Large text-to-image diffusion models have impressive capabilities in generating photorealistic images from text prompts. How to effectively guide or control these powerful models to perform different downstream tasks becomes an important open problem. To tackle this challenge, we introduce a principled finetuning method -- Orthogonal Finetuning (OFT), for adapting text-to-image diffusion models to downstream tasks. Unlike existing methods, OFT can provably preserve hyperspherical energy which characterizes the pairwise neuron relationship on the unit hypersphere. We find that this property is crucial for preserving the semantic generation ability of text-to-image diffusion models. To improve finetuning stability, we further propose Constrained Orthogonal Finetuning (COFT) which imposes an additional radius constraint to the hypersphere. Specifically, we consider two important finetuning text-to-image tasks: subject-driven generation where the goal is to generate subject-specific images given a few images of a subject and a text prompt, and controllable generation where the goal is to enable the model to take in additional control signals. We empirically show that our OFT framework outperforms existing methods in generation quality and convergence speed., Comment: NeurIPS 2023 (v3: fixed formula typos in Section 3.5, 43 pages, 34 figures, project page: https://oft.wyliu.com/)

We have conducted a line survey toward Orion KL using the Q-band receiver of the Tianma 65 m radio telescope (TMRT), covering 34.8-50 GHz with a velocity resolution between 0.79 and 0.55 km s(-1), respectively. The observations reach a sensitivity of the level of 1-8 mK, proving that the TMRT is sensitive for conducting deep-line surveys. In total, 597 Gaussian features are extracted. Among them, 177 radio recombination lines (RRLs) are identified, including 126, 40, and 11 RRLs of hydrogen, helium, and carbon, with a maximum delta n of 16, 7, and 3, respectively. The carbon RRLs are confirmed to originate from photodissociation regions with a V (LSR) similar to 9 km s(-1). In addition, 371 molecular transitions of 53 molecular species are identified. Twenty-one molecular species of this survey were not firmly detected in the Q band by Rizzo et al., including species such as H2CS, HCOOH, C2H5OH, H-2(13) CO, H2CCO, CH3CHO, CH2OCH2, HCN upsilon (2) = 1, and CH3OCHO upsilon ( t ) = 1. In particular, the vibrationally excited states of ethyl cyanide (C2H5CN upsilon 13/upsilon 21) are for the first time firmly detected in the Q band. NH3 (15,15) and (16,16) are identified, and they are so far the highest transitions of the NH3 inversion lines detected toward Orion KL. All of the identified lines can be reproduced by a radiative transfer model.

Recent advances of data-driven machine learning have revolutionized fields like computer vision, reinforcement learning, and many scientific and engineering domains. In many real-world and scientific problems, systems that generate data are governed by physical laws. Recent work shows that it provides potential benefits for machine learning models by incorporating the physical prior and collected data, which makes the intersection of machine learning and physics become a prevailing paradigm. By integrating the data and mathematical physics models seamlessly, it can guide the machine learning model towards solutions that are physically plausible, improving accuracy and efficiency even in uncertain and high-dimensional contexts. In this survey, we present this learning paradigm called Physics-Informed Machine Learning (PIML) which is to build a model that leverages empirical data and available physical prior knowledge to improve performance on a set of tasks that involve a physical mechanism. We systematically review the recent development of physics-informed machine learning from three perspectives of machine learning tasks, representation of physical prior, and methods for incorporating physical prior. We also propose several important open research problems based on the current trends in the field. We argue that encoding different forms of physical prior into model architectures, optimizers, inference algorithms, and significant domain-specific applications like inverse engineering design and robotic control is far from being fully explored in the field of physics-informed machine learning. We believe that the interdisciplinary research of physics-informed machine learning will significantly propel research progress, foster the creation of more effective machine learning models, and also offer invaluable assistance in addressing long-standing problems in related disciplines.

Model-based reinforcement learning usually suffers from a high sample complexity in training the world model, especially for the environments with complex dynamics. To make the training for general physical environments more efficient, we introduce Hamiltonian canonical ordinary differential equations into the learning process, which inspires a novel model of neural ordinary differential auto-encoder (NODA). NODA can model the physical world by nature and is flexible to impose Hamiltonian mechanics (e.g., the dimension of the physical equations) which can further accelerate training of the environment models. It can consequentially empower an RL agent with the robust extrapolation using a small amount of samples as well as the guarantee on the physical plausibility. Theoretically, we prove that NODA has uniform bounds for multi-step transition errors and value errors under certain conditions. Extensive experiments show that NODA can learn the environment dynamics effectively with a high sample efficiency, making it possible to facilitate reinforcement learning agents at the early stage.

While recent work has shown progress on extracting clothed 3D human avatars from a single image, video, or a set of 3D scans, several limitations remain. Most methods use a holistic representation to jointly model the body and clothing, which means that the clothing and body cannot be separated for applications like virtual try-on. Other methods separately model the body and clothing, but they require training from a large set of 3D clothed human meshes obtained from 3D/4D scanners or physics simulations. Our insight is that the body and clothing have different modeling requirements. While the body is well represented by a mesh-based parametric 3D model, implicit representations and neural radiance fields are better suited to capturing the large variety in shape and appearance present in clothing. Building on this insight, we propose SCARF (Segmented Clothed Avatar Radiance Field), a hybrid model combining a mesh-based body with a neural radiance field. Integrating the mesh into the volumetric rendering in combination with a differentiable rasterizer enables us to optimize SCARF directly from monocular videos, without any 3D supervision. The hybrid modeling enables SCARF to (i) animate the clothed body avatar by changing body poses (including hand articulation and facial expressions), (ii) synthesize novel views of the avatar, and (iii) transfer clothing between avatars in virtual try-on applications. We demonstrate that SCARF reconstructs clothing with higher visual quality than existing methods, that the clothing deforms with changing body pose and body shape, and that clothing can be successfully transferred between avatars of different subjects. The code and models are available at https://github.com/YadiraF/SCARF., Comment: 7 pages main paper, 2 pages supp. mat

Context. Level population inversion of hydrogen atoms in ionized gas may lead to stimulated emission of hydrogen recombination lines, and the level populations can in turn be affected by powerful stimulated emissions. Aims. In this work the interaction of the radiation fields and the level population inversion of hydrogen atoms is studied. The effect of the stimulated emissions on the line profiles is also investigated. Methods. Our previous nl-model for calculating level populations of hydrogen atoms and hydrogen recombination lines is improved. The effects of line and continuum radiation fields on the level populations are considered in the improved model. By using this method the properties of simulated hydrogen recombination lines and level populations are used in analyses. Results. The simulations show that hydrogen radio recombination lines are often emitted from the energy level with an inverted population. The widths of Hn$\alpha$ lines can be significantly narrowed by strong stimulated emissions to be even less than 10 km s$^{-1}$. The amplification of hydrogen recombination lines is more affected by the line optical depth than by the total optical depth. The influence of stimulated emission on the estimates of electron temperature and density of ionized gas is evaluated. We find that comparing multiple line-to-continuum ratios is a reliable method for estimating the electron temperature, while the effectiveness of the estimation of electron density is determined by the relative significance of stimulated emission., Comment: Accepted for published in A&A. 25 pages, 13 figures

This Ph.D. thesis is composed of three parts each summarizing an accepted publication. The first part is presented the Nowotny Phase (NP) embedded in a porous SiC/C nanocomposite matrix synthesized via a single-source-precursor approach involving the reaction of allylhydridopolycarbosilane with MoO2(acac)2. It is discovered for the first time that NP/C/SiC ceramic nanocomposites exhibit outstanding electrocatalytic properties suitable for the electrochemical hydrogen evolution. The second part reports how divinylbenzene (DVB) is used as a carbon-rich source to synthesize mesoporous NP/C/SiC ceramic nanocomposites with higher carbon content. The HER activity of the carbon-rich NP/C/SiC ceramic nanocomposites is further improved, due to their enhanced conductivity and high surface area. Finally, the third part of the thesis describes the discovery of interesting dielectric properties and outstanding EMA performance of the as-synthesized NP/C/SiC ceramic nanocomposites. This part is discussed also the high-temperature phase evolution of the respective nanocomposites.

(1) Background: Antifolate methotrexate (MTX) is the most common disease-modifying antirheumatic drug (DMARD) for treating human rheumatoid arthritis (RA). The mitochondrial-produced formate is essential for folate-mediated one carbon (1C) metabolism. The impacts of MTX on formate homeostasis in unknown, and rigorously controlled kinetic studies can greatly help in this regard. (2) Methods: Combining animal model (8-week old female C57BL/6JNarl mice, n = 18), cell models, stable isotopic tracer studies with gas chromatography/mass spectrometry (GC/MS) platforms, we systematically investigated how MTX interferes with the partitioning of mitochondrial and cytosolic formate metabolism. (3) Results: MTX significantly reduced de novo deoxythymidylate (dTMP) and methionine biosyntheses from mitochondrial-derived formate in cells, mouse liver, and bone marrow, supporting our postulation that MTX depletes mitochondrial 1C supply. Furthermore, MTX inhibited formate generation from mitochondria glycine cleavage system (GCS) both in vitro and in vivo. Folinate selectively rescued 1C metabolic pathways in a tissue-, cellular compartment-, and pathway-specific manner: folinate effectively reversed the inhibition of mitochondrial formate-dependent 1C metabolism in mouse bone marrow (dTMP, methionine, and GCS) and cells (dTMP and GCS) but not methionine synthesis in liver/liver-derived cells. Folinate failed to fully recover hepatic mitochondrial-formate utilization for methionine synthesis, suggesting that the efficacy of clinical folinate rescue in MTX therapy on hepatic methionine metabolism is poor. (4) Conclusion: Conducting studies in mouse and cell models, we demonstrate novel findings that MTX specifically depletes mitochondrial 1C supply that can be ameliorated by folinate supplementation except for hepatic transmethylation. These results imply that clinical use of low-dose MTX may particularly impede 1C metabolism via depletion of mitochondrial formate. The MTX induced s

(1) Background: methionine cycle is not only essential for cancer cell proliferation but is also critical for metabolic reprogramming, a cancer hallmark. Hepatic and extrahepatic tissues methionine adenosyltransferases (MATs) are products of two genes, MAT1A and MAT2A that catalyze the formation of S-adenosylmethionine (SAM), the principal biological methyl donor. Glycine N-methyltransferase (GNMT) further utilizes SAM for sarcosine formation, thus it regulates the ratio of SAM:S-adenosylhomocysteine (SAH). (2) Methods: by analyzing the TCGA/GTEx datasets available within GEPIA2, we discovered that breast cancer patients with higher MAT2A had worse survival rate (p = 0.0057). Protein expression pattern of MAT1AA, MAT2A and GNMT were investigated in the tissue microarray in our own cohort (n = 252) by immunohistochemistry. MAT2A C/N expression ratio and cell invasion activity were further investigated in a panel of breast cancer cell lines. (3) Results: GNMT and MAT1A were detected in the cytoplasm, whereas MAT2A showed both cytoplasmic and nuclear immunoreactivity. Neither GNMT nor MAT1A protein expression was associated with patient survival rate in our cohort. Kaplan-Meier survival curves showed that a higher cytoplasmic/nuclear (C/N) MAT2A protein expression ratio correlated with poor overall survival (5 year survival rate: 93.7% vs. 83.3%, C/N ratio ≥ 1.0 vs. C/N ratio < 1.0, log-rank p = 0.004). Accordingly, a MAT2A C/N expression ratio ≥ 1.0 was determined as an independent risk factor by Cox regression analysis (hazard ratio = 2.771, p = 0.018, n = 252). In vitro studies found that breast cancer cell lines with a higher MAT2A C/N ratio were more invasive. (4) Conclusions: the subcellular localization of MAT2A may affect its functions, and elevated MAT2A C/N ratio in breast cancer cells is associated with increased invasiveness. MAT2A C/N expression ratio determined by IHC staining could serve as a novel independent prognostic marker for breast cancer.

Folate depletion causes chromosomal instability by increasing DNA strand breakage, uracil misincorporation, and defective repair. Folate mediated one-carbon metabolism has been suggested to play a key role in the carcinogenesis and progression of hepatocellular carcinoma (HCC) through influencing DNA integrity. Methylenetetrahydrofolate reductase (MTHFR) is the enzyme catalyzing the irreversible conversion of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate that can control folate cofactor distributions and modulate the partitioning of intracellular one-carbon moieties. The association between MTHFR polymorphisms and HCC risk is inconsistent and remains controversial in populational studies. We aimed to establish an in vitro cell model of liver origin to elucidate the interactions between MTHFR function, folate status, and chromosome stability. In the present study, we (1) examined MTHFR expression in HCC patients; (2) established cell models of liver origin with stabilized inhibition of MTHFR using small hairpin RNA delivered by a lentiviral vector, and (3) investigated the impacts of reduced MTHFR and folate status on cell cycle, methyl group homeostasis, nucleotide biosynthesis, and DNA stability, all of which are pathways involved in DNA integrity and repair and are critical in human tumorigenesis. By analyzing the TCGA/GTEx datasets available within GEPIA2, we discovered that HCC cancer patients with higher MTHFR had a worse survival rate. The shRNA of MTHFR (shMTHFR) resulted in decreased MTHFR gene expression, MTHFR protein, and enzymatic activity in human hepatoma cell HepG2. shMTHFR tended to decrease intracellular S-adenosylmethionine (SAM) contents but folate depletion similarly decreased SAM in wildtype (WT), negative control (Neg), and shMTHFR cells, indicating that in cells of liver origin, shMTHFR does not exacerbate the methyl group supply in folate depletion. shMTHFR caused cell accumulations in the G2/M, and cell population in the G2/M wa

Treatment of pancreatic cancer by inhibiting the aberrant activation of the survival signaling pathways has received considerable attention. We investigated the probable action of DHA on the suppression of cell proliferation in human pancreatic ductal adenocarcinoma (PDAC) cells. Our results demonstrated that DHA dose-dependently inhibited cell proliferation through an induction of cell cycle arrest in human PDAC cells. DHA suppressed the expression of phosphorylated-Rb (p-Rb), cyclin D1, cyclin E, cyclin A, E2F1 and c-Myc proteins. Blocking the activation of STAT3 signaling pathway led to an inactivation of CAMKII and increased phosphorylation of c-Myc (T58) protein accompanied with decreased expression of c-Myc protein. Treatment of DHA effectively inhibited cell survival through decreased phosphorylation levels of EGFR, STAT3 and CAMKII proteins. The mechanisms of action were associated with increased phosphorylation levels of c-Myc (T58) and instability of c-Myc proteins. DHA inhibited cell survival through an increased GSSG/GSH ratio and oxidative stress level in HPAF-II cells. DHA induced cell apoptosis through increased expression of Bax, c-caspase 3 and c-PARP proteins in HPAF-II cells. Moreover, treatment of DHA significantly inhibited nucleotide synthesis. In conclusion, DHA might significantly suppress the proliferation of PDAC cells and therefore have potential as an anti-cancer therapeutic agent.

Folate depletion causes chromosomal instability by increasing DNA strand breakage, uracil misincorporation, and defective repair. Folate mediated one-carbon metabolism has been suggested to play a key role in the carcinogenesis and progression of hepatocellular carcinoma (HCC) through influencing DNA integrity. Methylenetetrahydrofolate reductase (MTHFR) is the enzyme catalyzing the irreversible conversion of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate that can control folate cofactor distributions and modulate the partitioning of intracellular one-carbon moieties. The association between MTHFR polymorphisms and HCC risk is inconsistent and remains controversial in populational studies. We aimed to establish an in vitro cell model of liver origin to elucidate the interactions between MTHFR function, folate status, and chromosome stability. In the present study, we (1) examined MTHFR expression in HCC patients; (2) established cell models of liver origin with stabilized inhibition of MTHFR using small hairpin RNA delivered by a lentiviral vector, and (3) investigated the impacts of reduced MTHFR and folate status on cell cycle, methyl group homeostasis, nucleotide biosynthesis, and DNA stability, all of which are pathways involved in DNA integrity and repair and are critical in human tumorigenesis. By analyzing the TCGA/GTEx datasets available within GEPIA2, we discovered that HCC cancer patients with higher MTHFR had a worse survival rate. The shRNA of MTHFR (shMTHFR) resulted in decreased MTHFR gene expression, MTHFR protein, and enzymatic activity in human hepatoma cell HepG2. shMTHFR tended to decrease intracellular S-adenosylmethionine (SAM) contents but folate depletion similarly decreased SAM in wildtype (WT), negative control (Neg), and shMTHFR cells, indicating that in cells of liver origin, shMTHFR does not exacerbate the methyl group supply in folate depletion. shMTHFR caused cell accumulations in the G2/M, and cell population in the G2/M wa

(1) Background: methionine cycle is not only essential for cancer cell proliferation but is also critical for metabolic reprogramming, a cancer hallmark. Hepatic and extrahepatic tissues methionine adenosyltransferases (MATs) are products of two genes, MAT1A and MAT2A that catalyze the formation of S-adenosylmethionine (SAM), the principal biological methyl donor. Glycine N-methyltransferase (GNMT) further utilizes SAM for sarcosine formation, thus it regulates the ratio of SAM:S-adenosylhomocysteine (SAH). (2) Methods: by analyzing the TCGA/GTEx datasets available within GEPIA2, we discovered that breast cancer patients with higher MAT2A had worse survival rate (p = 0.0057). Protein expression pattern of MAT1AA, MAT2A and GNMT were investigated in the tissue microarray in our own cohort (n = 252) by immunohistochemistry. MAT2A C/N expression ratio and cell invasion activity were further investigated in a panel of breast cancer cell lines. (3) Results: GNMT and MAT1A were detected in the cytoplasm, whereas MAT2A showed both cytoplasmic and nuclear immunoreactivity. Neither GNMT nor MAT1A protein expression was associated with patient survival rate in our cohort. Kaplan-Meier survival curves showed that a higher cytoplasmic/nuclear (C/N) MAT2A protein expression ratio correlated with poor overall survival (5 year survival rate: 93.7% vs. 83.3%, C/N ratio ≥ 1.0 vs. C/N ratio < 1.0, log-rank p = 0.004). Accordingly, a MAT2A C/N expression ratio ≥ 1.0 was determined as an independent risk factor by Cox regression analysis (hazard ratio = 2.771, p = 0.018, n = 252). In vitro studies found that breast cancer cell lines with a higher MAT2A C/N ratio were more invasive. (4) Conclusions: the subcellular localization of MAT2A may affect its functions, and elevated MAT2A C/N ratio in breast cancer cells is associated with increased invasiveness. MAT2A C/N expression ratio determined by IHC staining could serve as a novel independent prognostic marker for breast cancer.

We have identified 453 compact dense cores in 3 mm continuum emission maps in the ATOMS (ALMA Three-millimeter Observations of Massive Star-forming regions) survey, and compiled three catalogues of high-mass star forming cores. One catalogue, referred to as H/UC-HII catalogue, includes 89 cores that enshroud hyper/ultra compact (H/UC) HII regions as characterized by associated compact H40alpha emission. A second catalogue, referred to as pure s-cHMC, includes 32 candidate Hot Molecular Cores (HMCs) showing rich spectra (N>20lines) of complex organic molecules (COMs) but not associated with H/UC-HII regions. The third catalogue, referred to as pure w-cHMC, includes 58 candidate HMCs with relatively low levels of COM richness and not associated with H/UC-HII regions. These three catalogues of dense cores provide an important foundation for future studies of the early stages of high-mass star formation across the Milky Way. We also find that nearly half of H/UC-HII cores are candidate HMCs. From the number counts of COM-containing and H/UC-HII cores, we suggest that the duration of high-mass protostellar cores showing chemically rich features is at least comparable to the lifetime of H/UC-HII regions. For cores in the H/UC-HII catalogue, the width of the H40alpha line increases as the core size decreases, suggesting that the non-thermal dynamical and/or pressure line-broadening mechanisms dominate on the smaller scales of the H/UC-HII cores., Comment: 17 pages, five tables, and 11 figures. Accepted for publication at MNRAS

(1) Background: Antifolate methotrexate (MTX) is the most common disease-modifying antirheumatic drug (DMARD) for treating human rheumatoid arthritis (RA). The mitochondrial-produced formate is essential for folate-mediated one carbon (1C) metabolism. The impacts of MTX on formate homeostasis in unknown, and rigorously controlled kinetic studies can greatly help in this regard. (2) Methods: Combining animal model (8-week old female C57BL/6JNarl mice, n = 18), cell models, stable isotopic tracer studies with gas chromatography/mass spectrometry (GC/MS) platforms, we systematically investigated how MTX interferes with the partitioning of mitochondrial and cytosolic formate metabolism. (3) Results: MTX significantly reduced de novo deoxythymidylate (dTMP) and methionine biosyntheses from mitochondrial-derived formate in cells, mouse liver, and bone marrow, supporting our postulation that MTX depletes mitochondrial 1C supply. Furthermore, MTX inhibited formate generation from mitochondria glycine cleavage system (GCS) both in vitro and in vivo. Folinate selectively rescued 1C metabolic pathways in a tissue-, cellular compartment-, and pathway-specific manner: folinate effectively reversed the inhibition of mitochondrial formate-dependent 1C metabolism in mouse bone marrow (dTMP, methionine, and GCS) and cells (dTMP and GCS) but not methionine synthesis in liver/liver-derived cells. Folinate failed to fully recover hepatic mitochondrial-formate utilization for methionine synthesis, suggesting that the efficacy of clinical folinate rescue in MTX therapy on hepatic methionine metabolism is poor. (4) Conclusion: Conducting studies in mouse and cell models, we demonstrate novel findings that MTX specifically depletes mitochondrial 1C supply that can be ameliorated by folinate supplementation except for hepatic transmethylation. These results imply that clinical use of low-dose MTX may particularly impede 1C metabolism via depletion of mitochondrial formate. The MTX induced s

Folate depletion causes chromosomal instability by increasing DNA strand breakage, uracil misincorporation, and defective repair. Folate mediated one-carbon metabolism has been suggested to play a key role in the carcinogenesis and progression of hepatocellular carcinoma (HCC) through influencing DNA integrity. Methylenetetrahydrofolate reductase (MTHFR) is the enzyme catalyzing the irreversible conversion of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate that can control folate cofactor distributions and modulate the partitioning of intracellular one-carbon moieties. The association between MTHFR polymorphisms and HCC risk is inconsistent and remains controversial in populational studies. We aimed to establish an in vitro cell model of liver origin to elucidate the interactions between MTHFR function, folate status, and chromosome stability. In the present study, we (1) examined MTHFR expression in HCC patients; (2) established cell models of liver origin with stabilized inhibition of MTHFR using small hairpin RNA delivered by a lentiviral vector, and (3) investigated the impacts of reduced MTHFR and folate status on cell cycle, methyl group homeostasis, nucleotide biosynthesis, and DNA stability, all of which are pathways involved in DNA integrity and repair and are critical in human tumorigenesis. By analyzing the TCGA/GTEx datasets available within GEPIA2, we discovered that HCC cancer patients with higher MTHFR had a worse survival rate. The shRNA of MTHFR (shMTHFR) resulted in decreased MTHFR gene expression, MTHFR protein, and enzymatic activity in human hepatoma cell HepG2. shMTHFR tended to decrease intracellular S-adenosylmethionine (SAM) contents but folate depletion similarly decreased SAM in wildtype (WT), negative control (Neg), and shMTHFR cells, indicating that in cells of liver origin, shMTHFR does not exacerbate the methyl group supply in folate depletion. shMTHFR caused cell accumulations in the G2/M, and cell population in the G2/M wa

Treatment of pancreatic cancer by inhibiting the aberrant activation of the survival signaling pathways has received considerable attention. We investigated the probable action of DHA on the suppression of cell proliferation in human pancreatic ductal adenocarcinoma (PDAC) cells. Our results demonstrated that DHA dose-dependently inhibited cell proliferation through an induction of cell cycle arrest in human PDAC cells. DHA suppressed the expression of phosphorylated-Rb (p-Rb), cyclin D1, cyclin E, cyclin A, E2F1 and c-Myc proteins. Blocking the activation of STAT3 signaling pathway led to an inactivation of CAMKII and increased phosphorylation of c-Myc (T58) protein accompanied with decreased expression of c-Myc protein. Treatment of DHA effectively inhibited cell survival through decreased phosphorylation levels of EGFR, STAT3 and CAMKII proteins. The mechanisms of action were associated with increased phosphorylation levels of c-Myc (T58) and instability of c-Myc proteins. DHA inhibited cell survival through an increased GSSG/GSH ratio and oxidative stress level in HPAF-II cells. DHA induced cell apoptosis through increased expression of Bax, c-caspase 3 and c-PARP proteins in HPAF-II cells. Moreover, treatment of DHA significantly inhibited nucleotide synthesis. In conclusion, DHA might significantly suppress the proliferation of PDAC cells and therefore have potential as an anti-cancer therapeutic agent.

(1) Background: methionine cycle is not only essential for cancer cell proliferation but is also critical for metabolic reprogramming, a cancer hallmark. Hepatic and extrahepatic tissues methionine adenosyltransferases (MATs) are products of two genes, MAT1A and MAT2A that catalyze the formation of S-adenosylmethionine (SAM), the principal biological methyl donor. Glycine N-methyltransferase (GNMT) further utilizes SAM for sarcosine formation, thus it regulates the ratio of SAM:S-adenosylhomocysteine (SAH). (2) Methods: by analyzing the TCGA/GTEx datasets available within GEPIA2, we discovered that breast cancer patients with higher MAT2A had worse survival rate (p = 0.0057). Protein expression pattern of MAT1AA, MAT2A and GNMT were investigated in the tissue microarray in our own cohort (n = 252) by immunohistochemistry. MAT2A C/N expression ratio and cell invasion activity were further investigated in a panel of breast cancer cell lines. (3) Results: GNMT and MAT1A were detected in the cytoplasm, whereas MAT2A showed both cytoplasmic and nuclear immunoreactivity. Neither GNMT nor MAT1A protein expression was associated with patient survival rate in our cohort. Kaplan-Meier survival curves showed that a higher cytoplasmic/nuclear (C/N) MAT2A protein expression ratio correlated with poor overall survival (5 year survival rate: 93.7% vs. 83.3%, C/N ratio ≥ 1.0 vs. C/N ratio < 1.0, log-rank p = 0.004). Accordingly, a MAT2A C/N expression ratio ≥ 1.0 was determined as an independent risk factor by Cox regression analysis (hazard ratio = 2.771, p = 0.018, n = 252). In vitro studies found that breast cancer cell lines with a higher MAT2A C/N ratio were more invasive. (4) Conclusions: the subcellular localization of MAT2A may affect its functions, and elevated MAT2A C/N ratio in breast cancer cells is associated with increased invasiveness. MAT2A C/N expression ratio determined by IHC staining could serve as a novel independent prognostic marker for breast cancer.

This Ph.D. thesis is composed of three parts each summarizing an accepted publication. The first part is presented the Nowotny Phase (NP) embedded in a porous SiC/C nanocomposite matrix synthesized via a single-source-precursor approach involving the reaction of allylhydridopolycarbosilane with MoO2(acac)2. It is discovered for the first time that NP/C/SiC ceramic nanocomposites exhibit outstanding electrocatalytic properties suitable for the electrochemical hydrogen evolution. The second part reports how divinylbenzene (DVB) is used as a carbon-rich source to synthesize mesoporous NP/C/SiC ceramic nanocomposites with higher carbon content. The HER activity of the carbon-rich NP/C/SiC ceramic nanocomposites is further improved, due to their enhanced conductivity and high surface area. Finally, the third part of the thesis describes the discovery of interesting dielectric properties and outstanding EMA performance of the as-synthesized NP/C/SiC ceramic nanocomposites. This part is discussed also the high-temperature phase evolution of the respective nanocomposites.

We have identified 453 compact dense cores in 3 mm continuum emission maps in the ATOMS (ALMA Three-millimeter Observations of Massive Star-forming regions) survey, and compiled three catalogues of high-mass star forming cores. One catalogue, referred to as H/UC-HII catalogue, includes 89 cores that enshroud hyper/ultra compact (H/UC) HII regions as characterized by associated compact H40alpha emission. A second catalogue, referred to as pure s-cHMC, includes 32 candidate Hot Molecular Cores (HMCs) showing rich spectra (N>20lines) of complex organic molecules (COMs) but not associated with H/UC-HII regions. The third catalogue, referred to as pure w-cHMC, includes 58 candidate HMCs with relatively low levels of COM richness and not associated with H/UC-HII regions. These three catalogues of dense cores provide an important foundation for future studies of the early stages of high-mass star formation across the Milky Way. We also find that nearly half of H/UC-HII cores are candidate HMCs. From the number counts of COM-containing and H/UC-HII cores, we suggest that the duration of high-mass protostellar cores showing chemically rich features is at least comparable to the lifetime of H/UC-HII regions. For cores in the H/UC-HII catalogue, the width of the H40alpha line increases as the core size decreases, suggesting that the non-thermal dynamical and/or pressure line-broadening mechanisms dominate on the smaller scales of the H/UC-HII cores., Comment: 17 pages, five tables, and 11 figures. Accepted for publication at MNRAS

Recovering expressive humans from images is essential for understanding human behavior. Methods that estimate 3D bodies, faces, or hands have progressed significantly, yet separately. Face methods recover accurate 3D shape and geometric details, but need a tight crop and struggle with extreme views and low resolution. Whole-body methods are robust to a wide range of poses and resolutions, but provide only a rough 3D face shape without details like wrinkles. To get the best of both worlds, we introduce PIXIE, which produces animatable, whole-body 3D avatars with realistic facial detail, from a single image. For this, PIXIE uses two key observations. First, existing work combines independent estimates from body, face, and hand experts, by trusting them equally. PIXIE introduces a novel moderator that merges the features of the experts, weighted by their confidence. All part experts can contribute to the whole, using SMPL-X's shared shape space across all body parts. Second, human shape is highly correlated with gender, but existing work ignores this. We label training images as male, female, or non-binary, and train PIXIE to infer "gendered" 3D body shapes with a novel shape loss. In addition to 3D body pose and shape parameters, PIXIE estimates expression, illumination, albedo and 3D facial surface displacements. Quantitative and qualitative evaluation shows that PIXIE estimates more accurate whole-body shape and detailed face shape than the state of the art. Models and code are available at https://pixie.is.tue.mpg.de., Comment: 21 pages. The first two authors contributed equally to this work

Humans can master a new task within a few trials by drawing upon skills acquired through prior experience. To mimic this capability, hierarchical models combining primitive policies learned from prior tasks have been proposed. However, these methods fall short comparing to the human's range of transferability. We propose a method, which leverages the hierarchical structure to train the combination function and adapt the set of diverse primitive polices alternatively, to efficiently produce a range of complex behaviors on challenging new tasks. We also design two regularization terms to improve the diversity and utilization rate of the primitives in the pre-training phase. We demonstrate that our method outperforms other recent policy transfer methods by combining and adapting these reusable primitives in tasks with continuous action space. The experiment results further show that our approach provides a broader transferring range. The ablation study also shows the regularization terms are critical for long range policy transfer. Finally, we show that our method consistently outperforms other methods when the quality of the primitives varies., Comment: Accepted by AAAI 2021

This Ph.D. thesis is composed of three parts each summarizing an accepted publication. The first part is presented the Nowotny Phase (NP) embedded in a porous SiC/C nanocomposite matrix synthesized via a single-source-precursor approach involving the reaction of allylhydridopolycarbosilane with MoO2(acac)2. It is discovered for the first time that NP/C/SiC ceramic nanocomposites exhibit outstanding electrocatalytic properties suitable for the electrochemical hydrogen evolution. The second part reports how divinylbenzene (DVB) is used as a carbon-rich source to synthesize mesoporous NP/C/SiC ceramic nanocomposites with higher carbon content. The HER activity of the carbon-rich NP/C/SiC ceramic nanocomposites is further improved, due to their enhanced conductivity and high surface area. Finally, the third part of the thesis describes the discovery of interesting dielectric properties and outstanding EMA performance of the as-synthesized NP/C/SiC ceramic nanocomposites. This part is discussed also the high-temperature phase evolution of the respective nanocomposites.

This Ph.D. thesis is composed of three parts each summarizing an accepted publication. The first part is presented the Nowotny Phase (NP) embedded in a porous SiC/C nanocomposite matrix synthesized via a single-source-precursor approach involving the reaction of allylhydridopolycarbosilane with MoO2(acac)2. It is discovered for the first time that NP/C/SiC ceramic nanocomposites exhibit outstanding electrocatalytic properties suitable for the electrochemical hydrogen evolution. The second part reports how divinylbenzene (DVB) is used as a carbon-rich source to synthesize mesoporous NP/C/SiC ceramic nanocomposites with higher carbon content. The HER activity of the carbon-rich NP/C/SiC ceramic nanocomposites is further improved, due to their enhanced conductivity and high surface area. Finally, the third part of the thesis describes the discovery of interesting dielectric properties and outstanding EMA performance of the as-synthesized NP/C/SiC ceramic nanocomposites. This part is discussed also the high-temperature phase evolution of the respective nanocomposites.

This Ph.D. thesis is composed of three parts each summarizing an accepted publication. The first part is presented the Nowotny Phase (NP) embedded in a porous SiC/C nanocomposite matrix synthesized via a single-source-precursor approach involving the reaction of allylhydridopolycarbosilane with MoO2(acac)2. It is discovered for the first time that NP/C/SiC ceramic nanocomposites exhibit outstanding electrocatalytic properties suitable for the electrochemical hydrogen evolution. The second part reports how divinylbenzene (DVB) is used as a carbon-rich source to synthesize mesoporous NP/C/SiC ceramic nanocomposites with higher carbon content. The HER activity of the carbon-rich NP/C/SiC ceramic nanocomposites is further improved, due to their enhanced conductivity and high surface area. Finally, the third part of the thesis describes the discovery of interesting dielectric properties and outstanding EMA performance of the as-synthesized NP/C/SiC ceramic nanocomposites. This part is discussed also the high-temperature phase evolution of the respective nanocomposites.

RNA-Sequencing (RNA-Seq), the most commonly used sequencing application tool, is not only a method for measuring gene expression but also an excellent media to detect important structural variants such as single nucleotide variants (SNVs), insertion/deletion (Indels), or fusion transcripts. The Cancer Genome Atlas (TCGA) contains genomic data from a variety of cancer types and also provides the raw data generated by TCGA consortium. p53 is among the top 10 somatic mutations associated with hepatocellular carcinoma (HCC). The aim of the present study was to analyze concordant different gene profiles and the priori defined set of genes based on p53 mutation status in HCC using RNA-Seq data. In the study, expression profile of 11 799 genes on 42 paired tumor and adjacent normal tissues was collected, processed, and further stratified by the mutated versus normal p53 expression. Furthermore, we used a knowledge-based approach Gene Set Enrichment Analysis (GSEA) to compare between normal and p53 mutation gene expression profiles. The statistical significance (nominal P value) of the enrichment score (ES) genes was calculated. The ranked gene list that reflects differential expression between p53 wild-type and mutant genotypes was then mapped to metabolic process by KEGG, an encyclopedia of genes and genomes to assign functional meanings. These approaches enable us to identify pathways and potential target gene/pathways that are highly expressed in p53 mutated HCC. Our analysis revealed 2 genes, the hexokinase 2 (HK2) and Enolase 1 (ENO1), were conspicuous of red pixel in the heatmap. To further explore the role of these genes in HCC, the overall survival plots by Kaplan-Meier method were performed for HK2 and ENO1 that revealed high HK2 and ENO1 expression in patients with HCC have poor prognosis. These results suggested that these glycolysis genes are associated with mutated-p53 in HCC that may contribute to poor prognosis. In this proof-of-concept study, we proposed an

The treatment of cancer cells obtained by blocking cellular metabolism has received a lot of attention recently. Previous studies have demonstrated that Kras mutation-mediated abnormal glucose metabolism would lead to an aberrant cell proliferation in human pancreatic ductal adenocarcinoma (PDAC) cells. Previous literature has suggested that consumption of fish oil is associated with lower risk of pancreatic cancer. In this study, we investigated the anti-cancer effects of docosahexaenoic acid (DHA) in human PDAC cells in vitro and in vivo. Omega-3 polyunsaturated fatty acids (PUFAs) such as DHA and eicosapentaenoic acid (EPA) significantly inhibited the proliferation of human PDAC cells. The actions of DHA were evaluated through an induction of cell cycle arrest at G1 phase and noticed a decreased expression of cyclin A, cyclin E and cyclin B proteins in HPAF-II cells. Moreover, it was found that co-treatment of DHA and gemcitabine (GEM) effectively induced oxidative stress and cell death in HPAF-II cells. Interestingly, DHA leads to an increased oxidative glutathione /reduced glutathione (GSSG/GSH) ratio and induced cell apoptosis in HPAF-II cells. The findings in the study showed that supplementation of GSH or N-Acetyl Cysteine (NAC) could reverse DHA-mediated cell death in HPAF-II cells. Additionally, DHA significantly increased cellular level of cysteine, cellular NADP/NADPH ratio and the expression of cystathionase (CTH) and SLCA11/xCT antiporter proteins in HPAF-II cells. The action of DHA was, in part, associated with the inactivation of STAT3 cascade in HPAF-II cells. Treatment with xCT inhibitors, such as erastin or sulfasalazine (SSZ), inhibited the cell survival ability in DHA-treated HPAF-II cells. DHA also inhibited nucleotide synthesis in HPAF-II cells. It was demonstrated in a mouse-xenograft model that consumption of fish oil significantly inhibited the growth of pancreatic adenocarcinoma and decreased cellular nucleotide level in tumor tissues. Fur

Folate-mediated one-carbon (1C) metabolism is a major target of many therapies in human diseases. Studies have focused on the metabolism of serine 3-carbon as it serves as a major source for 1C units. The serine 3-carbon enters the mitochondria transferred by folate cofactors and eventually converted to formate and serves as a major building block for cytosolic 1C metabolism. Abnormal glycine metabolism has been reported in many human pathological conditions. The mitochondrial glycine cleavage system (GCS) catalyzes glycine degradation to CO2 and ammonium, while tetrahydrofolate (THF) is converted into 5,10-methylene-THF. GCS accounts for a substantial proportion of whole-body glycine flux in humans, yet the particular metabolic route of glycine 2-carbon recycled from GCS during mitochondria glycine decarboxylation in hepatic or bone marrow 1C metabolism is not fully investigated, due to the limited accessibility of human tissues. Labeled glycine at 2-carbon was given to humans and primary cells in previous studies for investigating its incorporations into purines, its interconversion with serine, or the CO2 production in the mitochondria. Less is known on the metabolic fate of the glycine 2-carbon recycled from the GCS; hence, a model system tracing its metabolic fate would help in this regard. We took the direct approach of isotopic labeling to further explore the in vitro and in vivo metabolic fate of the 2-carbon from [2-13C]glycine and [2-13C]serine. As the 2-carbon of glycine and serine is decarboxylated and catabolized via the GCS, the original 13C-labeled 2-carbon is transferred to THF and yield methyleneTHF in the mitochondria. In human hepatoma cell-lines, 2-carbon from glycine was found to be incorporated into deoxythymidine (dTMP, dT + 1), M + 3 species of purines (deoxyadenine, dA and deoxyguanine, dG), and methionine (Met + 1). In healthy mice, incorporation of GCS-derived formate from glycine 2-carbon was found in serine (Ser + 2 via cytosolic serine

(1) Background: Tumor hypoxia leads to metastasis and certain immune responses, and interferes with normal biological functions. It also affects glucose intake, down-regulates oxidative phosphorylation, and inhibits fatty-acid desaturation regulated by hypoxia-inducible factor 1α (HIF-1α). Although tumor hypoxia has been found to promote tumor metastasis, the roles of HIF-1α-regulated genes and their application are not completely integrated in clinical practice. (2) Methods: We examined the correlation between HIF-1α, metadherin (MTDH), and interleukin (IL)-10 mRNA expression, as well as their expression patterns in the prognosis of breast cancer using the Gene Expression Profiling Interactive Analysis (GEPIA) databases via a web interface; tissue microarrays (TMAs) were stained for MTDH and IL-10 protein expression using immunohistochemistry. (3) Results: HIF-1α, MTDH, and IL-10 mRNA expression are highly correlated and strongly associated with poor prognosis. MTDH and IL-10 protein expression of breast cancer patients usually harbored negative estrogen receptor (ER) or progesterone receptor (PR) status, and late-stage tumors have higher IL-10 expression. With regard to MTDH and IL-10 protein expression status for using univariate and multivariate analysis, the results showed that the protein expression of MTDH and IL-10 in ER-negative or PR-negative breast cancer patients have the worse prognosis. (4) Conclusions: we propose a new insight into hypoxia tumors in the metabolism and immune evidence for breast cancer therapy.

The "ATOMS," standing for {\it ALMA Three-millimeter Observations of Massive Star-forming regions}, survey has observed 146 active star forming regions with ALMA Band 3, aiming to systematically investigate the spatial distribution of various dense gas tracers in a large sample of Galactic massive clumps, to study the roles of stellar feedback in star formation, and to characterize filamentary structures inside massive clumps. In this work, the observations, data analysis, and example science of the "ATOMS" survey are presented, using a case study for the G9.62+0.19 complex. Toward this source, some transitions, commonly assumed to trace dense gas, including CS $J = 2-1$, HCO$^+$ $J = 1-0$ and HCN $J = 1-0$, are found to show extended gas emission in low density regions within the clump; less than 25\% of their emission is from dense cores. SO, CH$_3$OH, H$^{13}$CN and HC$_3$N show similar morphologies in their spatial distributions and reveal well the dense cores. Widespread narrow SiO emission is present (over $\sim$1 pc), which may be caused by slow shocks from large--scale colliding flows or H{\sc ii} regions. Stellar feedback from an expanding H{\sc ii} region has greatly reshaped the natal clump, significantly changed the spatial distribution of gas, and may also account for the sequential high-mass star formation in the G9.62+0.19 complex. The ATOMS survey data can be jointly analyzed with other survey data, e.g., "MALT90", "Orion B", "EMPIRE", "ALMA\_IMF", and "ALMAGAL", to deepen our understandings of "dense gas" star formation scaling relations and massive proto-cluster formation., Comment: published on MNRAS

We report studies of the relationships between the total bolometric luminosity ($L_{\rm bol}$ or $L_{\rm TIR}$) and the molecular line luminosities of $J=1-0$ transitions of H$^{13}$CN, H$^{13}$CO$^+$, HCN, and HCO$^+$ with data obtained from ACA observations in the "ATOMS" survey of 146 active Galactic star forming regions. The correlations between $L_{\rm bol}$ and molecular line luminosities $L'_{\rm mol}$ of the four transitions all appear to be approximately linear. Line emission of isotopologues shows as large scatters in $L_{\rm bol}$-$L'_{\rm mol}$ relations as their main line emission. The log($L_{\rm bol}$/$L'_{\rm mol}$) for different molecular line tracers have similar distributions. The $L_{\rm bol}$-to-$L'_{\rm mol}$ ratios do not change with galactocentric distances ($R_{\rm GC}$) and clump masses ($M_{\rm clump}$). The molecular line luminosity ratios (HCN-to-HCO$^+$, H$^{13}$CN-to-H$^{13}$CO$^+$, HCN-to-H$^{13}$CN and HCO$^+$-to-H$^{13}$CO$^+$) all appear constant against $L_{\rm bol}$, dust temperature ($T_{\rm d}$), $M_{\rm clump}$ and $R_{\rm GC}$. Our studies suggest that both the main lines and isotopologue lines are good tracers of the total masses of dense gas in Galactic molecular clumps. The large optical depths of main lines do not affect the interpretation of the slopes in star formation relations. We find that the mean star formation efficiency (SFE) of massive Galactic clumps in the "ATOMS" survey is reasonably consistent with other measures of the SFE for dense gas, even those using very different tracers or examining very different spatial scales., Comment: Published on MNRAS. The full tables are included in Tables.pdf or Tables.tex files, which can be downloaded from source files

RNA-Sequencing (RNA-Seq), the most commonly used sequencing application tool, is not only a method for measuring gene expression but also an excellent media to detect important structural variants such as single nucleotide variants (SNVs), insertion/deletion (Indels), or fusion transcripts. The Cancer Genome Atlas (TCGA) contains genomic data from a variety of cancer types and also provides the raw data generated by TCGA consortium. p53 is among the top 10 somatic mutations associated with hepatocellular carcinoma (HCC). The aim of the present study was to analyze concordant different gene profiles and the priori defined set of genes based on p53 mutation status in HCC using RNA-Seq data. In the study, expression profile of 11 799 genes on 42 paired tumor and adjacent normal tissues was collected, processed, and further stratified by the mutated versus normal p53 expression. Furthermore, we used a knowledge-based approach Gene Set Enrichment Analysis (GSEA) to compare between normal and p53 mutation gene expression profiles. The statistical significance (nominal P value) of the enrichment score (ES) genes was calculated. The ranked gene list that reflects differential expression between p53 wild-type and mutant genotypes was then mapped to metabolic process by KEGG, an encyclopedia of genes and genomes to assign functional meanings. These approaches enable us to identify pathways and potential target gene/pathways that are highly expressed in p53 mutated HCC. Our analysis revealed 2 genes, the hexokinase 2 (HK2) and Enolase 1 (ENO1), were conspicuous of red pixel in the heatmap. To further explore the role of these genes in HCC, the overall survival plots by Kaplan-Meier method were performed for HK2 and ENO1 that revealed high HK2 and ENO1 expression in patients with HCC have poor prognosis. These results suggested that these glycolysis genes are associated with mutated-p53 in HCC that may contribute to poor prognosis. In this proof-of-concept study, we proposed an

The treatment of cancer cells obtained by blocking cellular metabolism has received a lot of attention recently. Previous studies have demonstrated that Kras mutation-mediated abnormal glucose metabolism would lead to an aberrant cell proliferation in human pancreatic ductal adenocarcinoma (PDAC) cells. Previous literature has suggested that consumption of fish oil is associated with lower risk of pancreatic cancer. In this study, we investigated the anti-cancer effects of docosahexaenoic acid (DHA) in human PDAC cells in vitro and in vivo. Omega-3 polyunsaturated fatty acids (PUFAs) such as DHA and eicosapentaenoic acid (EPA) significantly inhibited the proliferation of human PDAC cells. The actions of DHA were evaluated through an induction of cell cycle arrest at G1 phase and noticed a decreased expression of cyclin A, cyclin E and cyclin B proteins in HPAF-II cells. Moreover, it was found that co-treatment of DHA and gemcitabine (GEM) effectively induced oxidative stress and cell death in HPAF-II cells. Interestingly, DHA leads to an increased oxidative glutathione /reduced glutathione (GSSG/GSH) ratio and induced cell apoptosis in HPAF-II cells. The findings in the study showed that supplementation of GSH or N-Acetyl Cysteine (NAC) could reverse DHA-mediated cell death in HPAF-II cells. Additionally, DHA significantly increased cellular level of cysteine, cellular NADP/NADPH ratio and the expression of cystathionase (CTH) and SLCA11/xCT antiporter proteins in HPAF-II cells. The action of DHA was, in part, associated with the inactivation of STAT3 cascade in HPAF-II cells. Treatment with xCT inhibitors, such as erastin or sulfasalazine (SSZ), inhibited the cell survival ability in DHA-treated HPAF-II cells. DHA also inhibited nucleotide synthesis in HPAF-II cells. It was demonstrated in a mouse-xenograft model that consumption of fish oil significantly inhibited the growth of pancreatic adenocarcinoma and decreased cellular nucleotide level in tumor tissues. Fur

Folate-mediated one-carbon (1C) metabolism is a major target of many therapies in human diseases. Studies have focused on the metabolism of serine 3-carbon as it serves as a major source for 1C units. The serine 3-carbon enters the mitochondria transferred by folate cofactors and eventually converted to formate and serves as a major building block for cytosolic 1C metabolism. Abnormal glycine metabolism has been reported in many human pathological conditions. The mitochondrial glycine cleavage system (GCS) catalyzes glycine degradation to CO2 and ammonium, while tetrahydrofolate (THF) is converted into 5,10-methylene-THF. GCS accounts for a substantial proportion of whole-body glycine flux in humans, yet the particular metabolic route of glycine 2-carbon recycled from GCS during mitochondria glycine decarboxylation in hepatic or bone marrow 1C metabolism is not fully investigated, due to the limited accessibility of human tissues. Labeled glycine at 2-carbon was given to humans and primary cells in previous studies for investigating its incorporations into purines, its interconversion with serine, or the CO2 production in the mitochondria. Less is known on the metabolic fate of the glycine 2-carbon recycled from the GCS; hence, a model system tracing its metabolic fate would help in this regard. We took the direct approach of isotopic labeling to further explore the in vitro and in vivo metabolic fate of the 2-carbon from [2-13C]glycine and [2-13C]serine. As the 2-carbon of glycine and serine is decarboxylated and catabolized via the GCS, the original 13C-labeled 2-carbon is transferred to THF and yield methyleneTHF in the mitochondria. In human hepatoma cell-lines, 2-carbon from glycine was found to be incorporated into deoxythymidine (dTMP, dT + 1), M + 3 species of purines (deoxyadenine, dA and deoxyguanine, dG), and methionine (Met + 1). In healthy mice, incorporation of GCS-derived formate from glycine 2-carbon was found in serine (Ser + 2 via cytosolic serine

In order to search for shocks in the very early stage of star formation, we performed single-point surveys of SiO J=1-0, 2-1 and 3-2 lines and the H$_2$CO $2_{12}-1_{11}$ line toward a sample of 100 high-mass starless clump candidates (SCCs) by using the Korean VLBI Network (KVN) 21-m radio telescopes. The detection rates of the SiO J=1-0, 2-1, 3-2 lines and the H$_2$CO line are $31.0\%$, $31.0\%$, $19.5\%$ and $93.0\%$, respectively. Shocks seem to be common in this stage of massive star formation. The widths of the observed SiO lines (full width at zero power (FWZP)) range from 3.4 to 55.1 km s$^{-1}$. A significant fraction ($\sim29\%$) of the detected SiO spectra have broad line widths (FWZP $>20~km~s^{-1}$), which are very likely associated with fast shocks driven by protostellar outflows. This result suggests that about one third of the SiO-detected SCCs are not really starless but protostellar. On the other hand, about 40$\%$ of the detected SiO spectra show narrow line widths (FWZP<10 $km~s^{-1}$) probably associated with low-velocity shocks which are not necessarily protostellar in origin. The estimated SiO column densities are mostly $0.31-4.32\times10^{12}~cm^{-2}$. Comparing the SiO column densities derived from SiO J=1-0 and 2-1 lines, we suggest that the SiO molecules in the SCCs may be in the non-LTE condition. The SiO abundances to H$_2$ are usually $0.20-10.92\times10^{-10}$., Comment: 19 pages, 13 figures

The "ATOMS," standing for {\it ALMA Three-millimeter Observations of Massive Star-forming regions}, survey has observed 146 active star forming regions with ALMA Band 3, aiming to systematically investigate the spatial distribution of various dense gas tracers in a large sample of Galactic massive clumps, to study the roles of stellar feedback in star formation, and to characterize filamentary structures inside massive clumps. In this work, the observations, data analysis, and example science of the "ATOMS" survey are presented, using a case study for the G9.62+0.19 complex. Toward this source, some transitions, commonly assumed to trace dense gas, including CS $J = 2-1$, HCO$^+$ $J = 1-0$ and HCN $J = 1-0$, are found to show extended gas emission in low density regions within the clump; less than 25\% of their emission is from dense cores. SO, CH$_3$OH, H$^{13}$CN and HC$_3$N show similar morphologies in their spatial distributions and reveal well the dense cores. Widespread narrow SiO emission is present (over $\sim$1 pc), which may be caused by slow shocks from large--scale colliding flows or H{\sc ii} regions. Stellar feedback from an expanding H{\sc ii} region has greatly reshaped the natal clump, significantly changed the spatial distribution of gas, and may also account for the sequential high-mass star formation in the G9.62+0.19 complex. The ATOMS survey data can be jointly analyzed with other survey data, e.g., "MALT90", "Orion B", "EMPIRE", "ALMA\_IMF", and "ALMAGAL", to deepen our understandings of "dense gas" star formation scaling relations and massive proto-cluster formation., Comment: published on MNRAS