Value creation through modernizing Chinese medicine

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2007.Includes bibliographical references (leaves 110-114).My first hypothesis in this thesis is that there is significant value vested in traditional Chinese medicine that can be captured by converting them into ethical drugs through scientific analysis, screening and validation. Further, holistic treatment is a key difference between traditional Chinese medicine and western-type chemical drugs, which makes Chinese medicine a very valuable category of knowledge. Using mixed formula is a primary method of treatment in Chinese medicine. It is the application of distinctive medical philosophies of Chinese herbal medicines in practices, reflecting the uniqueness and advantages of Chinese medicine. For example, there are 96,592 mixed formula recorded by "Dictionary of Chinese Medicine Mixed Formula" published in 1997. My second hypothesis in this thesis is that value can be created and captured, under the globalization context, from mixed herbal formulas for the mainstream world market with the aid of fingerprint technologies. To enter western markets as officially approved drugs through critical pathways, both scientific and regulatory, Chinese herb drugs must demonstrate sound evidence for safety and efficacy. I address in this thesis one of the central concerns of the pharmaceutical companies and FDA, that is, how quality control and material consistency is assured and how toxicity and drug kinetics of Chinese herbal medicines, either in its raw form, its purified form, its composite extract form or its mixed formula form, may be measured with reasonable scientific certainty and what would be the likely trajectory of further research.(cont.) My thesis research involves the following aspects: firstly, I characterize, by and through historical review and analysis, the formation of unique Chinese holistic medical philosophy to apply herbal medicines, particularly mixed herbal formulas, to systematically modulate the human body to prevent illnesses, to combat health problems and to restore balanced health; secondly, I performed a comparative study on the regulatory systems between Chinese SFDA and US FDA to provide insights on the trend of harmonic convergence of laws and regulations and challenges going forward, including collection and extrapolation of relevant statistical data; thirdly, I researched emerging fingerprint technologies to address the central issues of standardization, quality control, material consistency, safety and efficacy measurements of Chinese herbal medicines; fourthly, I performed data collection on major Chinese sources of published literatures and patent applications/grants for public and private medicinal knowledge formation, which may be viewed as a surrogate indicator for embedded economic value in the system, to compare trend and gaps between China and developed countries; and lastly, I presented three case studies of development of an-diabetic drugs from herbal sources, to illustrate how value may be created and captured through using modern technologies to tap into the accumulative knowledge base in herbal medicine. The thesis concludes that there are significant values to be captured, by and through cross-border collaborations under the globalization context, from Chinese herbal medicine. Both ethical single molecular entity (singleton) herb-derived drugs and mixed formula herb-derived drugs may be created going forward.by Lizhe Sun.S.M

DeepMatch: Toward Lightweight in Point Cloud Registration

From source to target, point cloud registration solves for a rigid body transformation that aligns the two point clouds. IterativeClosest Point (ICP) and other traditional algorithms require a long registration time and are prone to fall into local optima. Learning-based algorithms such as Deep ClosestPoint (DCP) perform better than those traditional algorithms and escape from local optimality. However, they are still not perfectly robust and rely on the complex model design due to the extracted local features are susceptible to noise. In this study, we propose a lightweight point cloud registration algorithm, DeepMatch. DeepMatch extracts a point feature for each point, which is a spatial structure composed of each point itself, the center point of the point cloud, and the farthest point of each point. Because of the superiority of this per-point feature, the computing resources and time required by DeepMatch to complete the training are less than one-tenth of other learning-based algorithms with similar performance. In addition, experiments show that our algorithm achieves state-of-the-art (SOTA) performance on both clean, with Gaussian noise and unseen category datasets. Among them, on the unseen categories, compared to the previous best learning-based point cloud registration algorithms, the registration error of DeepMatch is reduced by two orders of magnitude, achieving the same performance as on the categories seen in training, which proves DeepMatch is generalizable in point cloud registration tasks. Finally, only our DeepMatch completes 100% recall on all three test sets

A parallel self-organizing overlapping community detection algorithm based on swarm intelligence for large scale complex networks

Community detection is a critical task for complex network analysis. It helps us to understand the properties of the system that a complex network represents and has significance to a wide range of applications. Though a large number of algorithms have been developed, the detection of overlapping communities from large scale and (or) dynamic networks still remains challenging. In this paper, a Parallel Self-organizing Overlapping Community Detection (PSOCD) algorithm ground on the idea of swarm intelligence is proposed. The PSOCD is designed based on the concept of swarm intelligence system where an analyzed network is treated as a decentralized, self-organized, and self-evolving systems, in which each vertex acts iteratively to join to or leave from communities based on a set of predefined simple vertex action rules. The algorithm is implemented on a distributed graph processing platform named Giraph++; therefore it is capable of analyzing large scale networks. The algorithm is also able to handle overlapping community detection well because a vertex can naturally joins to multiple communities simultaneously. Moreover, if some vertexes and edges are added to or deleted from the analyzed network, the algorithm only needs to adjust community assignments of affected vertexes in the same way as its ending joining communities for a vertex, i.e., it inherently supports dynamic network analysis. The proposed PSOCD is evaluated using a number of variety large scale synthesized and real world networks. Experimental results indicate that the proposed algorithm can effectively discover overlapping communities on large-scale network and the quality of its detected overlapping community structures is superior to two state-of-the-art algorithms, namely Speaker Listener Label Propagation Algorithm (SLPA) and Order Statistics Local Optimization Method (OSLOM), especially on high overlapping density networks and (or) high overlapping diversity networks

Association Analysis of MET

To investigate the association of MET SNPs with gender disparity in thyroid tumors, as well as the metastasis and prognosis of patients, 858 patients with papillary thyroid carcinoma (PTC), 556 patients with nodular goiter, and 896 population-based normal controls were recruited. The genotyping of MET SNPs was carried out using the Sequenom MassARRAY system. The distribution of MET SNPs (rs1621 and rs6566) was different among groups. Gender stratification analysis revealed a significant association between the rs1621 genotype and PTC in female patients (P=0.037), but not in male patients (P>0.05). For female patients, the rs1621 AG genotype was significantly higher in patients with PTC than in normal controls (P=0.01) and revealed an increasing risk of PTC (OR: 1.465, 95% CI: 1.118–1.92). However, association analysis of the rs1621 genotype with metastasis and prognosis revealed no significant correlation in both male and female patients. The findings of our study showed that polymorphism of SNP locus rs1621 in MET gene may be associated with gender disparity in PTC. Higher AG genotypes in rs1621 were correlated with PTC in female patients, but not in male patients

Association of ATM Gene Polymorphism with PTC Metastasis in Female Patients

Ataxia telangiectasia mutated (ATM) gene is critical in the process of recognizing and repairing DNA lesions and is related to invasion and metastasis of malignancy. The incidence rate of papillary thyroid cancer (PTC) has increased for several decades and is higher in females than males. In this study, we want to investigate whether ATM polymorphisms are associated with gender-specific metastasis of PTC. 358 PTC patients in Northern China, including 109 males and 249 females, were included in our study. Four ATM single nucleotide polymorphisms (SNPs) were genotyped using Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF-MS). Association between genotypes and the gender-specific risk of metastasis was assessed by odds ratios (OR) and 95% confidence intervals (CI) under the unconditional logistic regression analysis. Significant associations were observed between rs189037 and metastasis of PTC in females under different models of inheritance (codominant model: OR=0.15, 95% CI 0.04–0.56, P=0.01 for GA versus GG and OR=0.08, 95% CI 0.01–0.74, P=0.03 for AA versus GG, resp.; dominant model: OR=0.49, 95% CI 0.25–0.98, P=0.04; overdominant model: OR=0.47, 95% CI 0.25–0.89, P=0.02). However, no association remained significant after Bonferroni correction. Our findings suggest a possible association between ATM rs189037 polymorphisms and metastasis in female PTCs

Twenty Novel Disease Group-Specific and 12 New Shared Macrophage Pathways in Eight Groups of 34 Diseases Including 24 Inflammatory Organ Diseases and 10 Types of Tumors.

The mechanisms underlying pathophysiological regulation of tissue macrophage (Mφ) subsets remain poorly understood. From the expression of 207 Mφ genes comprising 31 markers for 10 subsets, 45 transcription factors (TFs), 56 immunometabolism enzymes, 23 trained immunity (innate immune memory) enzymes, and 52 other genes in microarray data, we made the following findings. (1) When 34 inflammation diseases and tumor types were grouped into eight categories, there was differential expression of the 31 Mφ markers and 45 Mφ TFs, highlighted by 12 shared and 20 group-specific disease pathways. (2) Mφ in lung, liver, spleen, and intestine (LLSI-Mφ) express higher M1 Mφ markers than lean adipose tissue Mφ (ATMφ) physiologically. (3) Pro-adipogenic TFs C/EBPα and PPARγ and proinflammatory adipokine leptin upregulate the expression of M1 Mφ markers. (4) Among 10 immune checkpoint receptors (ICRs), LLSI-Mφ and bone marrow (BM) Mφ express higher levels of CD274 (PDL-1) than ATMφ, presumably to counteract the M1 dominant status via its reverse signaling behavior. (5) Among 24 intercellular communication exosome mediators, LLSI- and BM- Mφ prefer to use RAB27A and STX3 than RAB31 and YKT6, suggesting new inflammatory exosome mediators for propagating inflammation. (6) Mφ in peritoneal tissue and LLSI-Mφ upregulate higher levels of immunometabolism enzymes than does ATMφ. (7) Mφ from peritoneum and LLSI-Mφ upregulate more trained immunity enzyme genes than does ATMφ. Our results suggest that multiple new mechanisms including the cell surface, intracellular immunometabolism, trained immunity, and TFs may be responsible for disease group-specific and shared pathways. Our findings have provided novel insights on the pathophysiological regulation of tissue Mφ, the disease group-specific and shared pathways of Mφ, and novel therapeutic targets for cancers and inflammations

A trehalose biosynthetic enzyme doubles as an osmotic stress sensor to regulate bacterial morphogenesis

The dissacharide trehalose is an important intracellular osmoprotectant and the OtsA/B pathway is the principal pathway for trehalose biosynthesis in a wide range of bacterial species. Scaffolding proteins and other cytoskeletal elements play an essential role in morphogenetic processes in bacteria. Here we describe how OtsA, in addition to its role in trehalose biosynthesis, functions as an osmotic stress sensor to regulate cell morphology in Arthrobacter strain A3. In response to osmotic stress, this and other Arthrobacter species undergo a transition from bacillary to myceloid growth. An otsA null mutant exhibits constitutive myceloid growth. Osmotic stress leads to a depletion of trehalose-6-phosphate, the product of the OtsA enzyme, and experimental depletion of this metabolite also leads to constitutive myceloid growth independent of OtsA function. In vitro analyses indicate that OtsA can self-assemble into protein networks, promoted by trehalose-6-phosphate, a property that is not shared by the equivalent enzyme from E. coli, despite the latter's enzymatic activity when expressed in Arthrobacter. This, and the localization of the protein in non-stressed cells at the mid-cell and poles, indicates that OtsA from Arthrobacter likely functions as a cytoskeletal element regulating cell morphology. Recruiting a biosynthetic enzyme for this morphogenetic function represents an intriguing adaptation in bacteria that can survive in extreme environments

Aridity-driven shift in biodiversity–soil multifunctionality relationships

From Springer Nature via Jisc Publications RouterHistory: received 2021-01-07, accepted 2021-08-12, registration 2021-08-25, pub-electronic 2021-09-09, online 2021-09-09, collection 2021-12Publication status: PublishedFunder: National Natural Science Foundation of China (National Science Foundation of China); doi: https://doi.org/10.13039/501100001809; Grant(s): 31770430Abstract: Relationships between biodiversity and multiple ecosystem functions (that is, ecosystem multifunctionality) are context-dependent. Both plant and soil microbial diversity have been reported to regulate ecosystem multifunctionality, but how their relative importance varies along environmental gradients remains poorly understood. Here, we relate plant and microbial diversity to soil multifunctionality across 130 dryland sites along a 4,000 km aridity gradient in northern China. Our results show a strong positive association between plant species richness and soil multifunctionality in less arid regions, whereas microbial diversity, in particular of fungi, is positively associated with multifunctionality in more arid regions. This shift in the relationships between plant or microbial diversity and soil multifunctionality occur at an aridity level of ∼0.8, the boundary between semiarid and arid climates, which is predicted to advance geographically ∼28% by the end of the current century. Our study highlights that biodiversity loss of plants and soil microorganisms may have especially strong consequences under low and high aridity conditions, respectively, which calls for climate-specific biodiversity conservation strategies to mitigate the effects of aridification

Is the meiofauna a good indicator for climate change and anthropogenic impacts?

Our planet is changing, and one of the most pressing challenges facing the scientific community revolves around understanding how ecological communities respond to global changes. From coastal to deep-sea ecosystems, ecologists are exploring new areas of research to find model organisms that help predict the future of life on our planet. Among the different categories of organisms, meiofauna offer several advantages for the study of marine benthic ecosystems. This paper reviews the advances in the study of meiofauna with regard to climate change and anthropogenic impacts. Four taxonomic groups are valuable for predicting global changes: foraminifers (especially calcareous forms), nematodes, copepods and ostracods. Environmental variables are fundamental in the interpretation of meiofaunal patterns and multistressor experiments are more informative than single stressor ones, revealing complex ecological and biological interactions. Global change has a general negative effect on meiofauna, with important consequences on benthic food webs. However, some meiofaunal species can be favoured by the extreme conditions induced by global change, as they can exhibit remarkable physiological adaptations. This review highlights the need to incorporate studies on taxonomy, genetics and function of meiofaunal taxa into global change impact research