Lessons Learned as President of the Institute for Systems Biology(2000–2018)

I stepped down as president of the Institute for Systems Biol- ogy （ISB） on Jan 1, 2018. As I think about my 17-year term as President, I am astounded at how much I have learned, not only about science but also about, among other things, what it takes to build a unique world-class institution.

Organotypic Models for Functional Drug Testing of Human Cancers

In the era of personalized oncology,there have been accelerated efforts to develop clinically relevant platforms to test drug sensitivities of individual cancers.An ideal assay will serve as a diagnostic companion to inform the oncologist of the various treatments that are sensitive and insensitive,thus improving outcome while minimizing unnecessary toxicities and costs.To date,no such platform exists for clinical use,but promising approaches are on the horizon that take advantage of improved techniques in creating human cancer models that encompass the entire tumor microenvironment,alongside technologies for assessing and analyzing tumor response.This review summarizes a number of current strategies that make use of intact human cancer tissues as organotypic cultures in drug sensitivity testing.

Expression and regulation of IL-22 in the IL-17.producing CD4+T lymphocytes

IL-22 是在工作对感染支持纸巾的天生的免疫的 IL-10 家庭的新奇 cytokine。尽管 CD4+ 助手 T 淋巴细胞(TH ) 作为 IL-22 的来源被发现，这 cytokine 的规定糟糕被理解。这里，我们证明 IL-22 被也做 IL-17 的 TH 房间的一个新奇子集在 mRNA 和蛋白质层次表示。IL-22 和 IL-17 被发现被即时 PCR 以及 ELISA 分析被 TGFbeta 和 IL-6 并列地在 TH 区别期间调整。然而， IL-22 不调整 TH 区别；外长的 IL-22 或一个 IL-22 对手没在 TH 区别上有效果。这些数据表明 IL-17-producing T 房间表示的新奇 cytokine，并且建议在组织发炎和自体免疫的疾病表明小径的 IL-22 和 IL-17 的相互作用和协同作用。

Systems Approaches to Biology and Disease Enable Translational Systems Medicine

The development and application of systems strategies to biology and disease are transforming medical research and clinical practice in an unprecedented rate. In the foreseeable future, clinicians, medical researchers, and ultimately the consumers and patients will be increasingly equipped with a deluge of personal health information, e.g., whole genome sequences, molecular profiling of diseased tissues, and periodic multi-analyte blood testing of biomarker panels for disease and wellness. The convergence of these practices will enable accurate prediction of disease susceptibility and early diagnosis for actionable preventive schema and personalized treatment regimes tailored to each individual. It will also entail proactive participation from all major stakeholders in the health care system. We are at the dawn of predictive, preventive, personalized, and participatory （P4） medicine, the fully implementation of which requires marrying basic and clinical researches through advanced systems thinking and the employment of high-throughput technologies in genomics, pro- teomics, nanofluidics, single-cell analysis, and computation strategies in a highly-orchestrated discipline we termed translational systems medicine.

Large-scale molecular characterization and analysis of gastric cancer

The recent effort by The Cancer Genome Atlas(TCGA)Network has revealed that gastric cancer,which is a leading cause of cancerrelated deaths worldwide with a 5-year survival rate less than 25%,is a much more heterogeneous disease than previously thought.And yet,conventional treatment approaches and clinical trials have assumed it is a single disease.

Key nodes of a micro RNA network associated with the integrated mesenchymal subtype of high-grade serous ovarian cancer

Metastasis is the main cause of cancer mortality. One of the initiating events of cancer metastasis of epithelial tumors is epithelial-to-mesenchymal transition(EMT), during which cells dedifferentiate from a relatively rigid cell structure/morphology to a flexible and changeable structure/morphology often associated with mesenchymal cells. The presence of EMT in human epithelial tumors is reflected by the increased expression of genes and levels of proteins that are preferentially present in mesenchymal cells. The combined presence of these genes forms the basis of mesenchymal gene signatures, which are the foundation for classifying a mesenchymal subtype of tumors. Indeed, tumor classification schemes that use clustering analysis of large genomic characterizations, like The Cancer Genome Atlas(TCGA), have defined mesenchymal subtype in a number of cancer types, such as high-grade serous ovarian cancer and glioblastoma. However, recent analyses have shown that gene expression-based classifications of mesenchymal subtypes often do not associate with poor survival. This "paradox" can be ameliorated using integrated analysis that combines multiple data types. We recently found that integrating m RNA and micro RNA(mi RNA) data revealed an integrated mesenchymal subtype that is consistently associated with poor survival in multiple cohorts of patients with serous ovarian cancer. This network consists of 8 major mi RNAs and 214 m RNAs. Among the 8 mi RNAs, 4 are known to be regulators of EMT. This review provides a summary of these 8 mi RNAs, which were associated with the integrated mesenchymal subtype of serous ovarian cancer.

A multilevel pan-cancer map links gene mutations to cancer hallmarks

Background:A central challenge in cancer research is to create models that bridge the gap between the molecular level on which interventions can be designed and the cellular and tissue levels on which the disease phenotypes are manifested.This study was undertaken to construct such a model from functional annotations and explore its use when integrated with large-scale cancer genomics data.Methods:We created a map that connects genes to cancer hallmarks via signaling pathways.We projected gene mutation and focal copy number data from various cancer types onto this map.We performed statistical analyses to uncover mutually exclusive and co-occurring oncogenic aberrations within this topology.Results:Our analysis showed that although the genetic fingerprint of tumor types could be very different,there were less variations at the level of hallmarks,consistent with the idea that different genetic alterations have similar functional outcomes.Additionally,we showed how the multilevel map could help to clarify the role of infrequently mutated genes,and we demonstrated that mutually exclusive gene mutations were more prevalent in pathways,whereas many co-occurring gene mutations were associated with hallmark characteristics.Conclusions:Overlaying this map with gene mutation and focal copy number data from various cancer types makes it possible to investigate the similarities and differences between tumor samples systematically at the levels of not only genes but also pathways and hallmarks.

Effects of anthropogenic disturbances on natural regeneration and population structure of gum arabic tree (Acacia senegal)in the woodlands of Lake Baringo ecosystem, Kenya

Despite the ecological and economic importance of Acacia senegal, little is known about the effects of anthropogenic disturbances on its natural regeneration patterns and population structure. We investigated the effects of these factors within the Lake Baringo woodland ecosystem. Data was collected from 60 plots of 20 m?×?20 m systematically distributed in four A. senegal-dominated populations within the Lake Baringo woodland. Sample populations spanned a degradation gradient measured by a population disturbance index (PDI). Trees were measured for diameter at breast height (DBH) and categorized by growth stages: seedling, sapling and adult tree. Higher seedling and sapling densities were recorded in lightly than heavily disturbed populations, but only sapling density was significantly different between the two disturbance levels (P = 0.02). Lightly disturbed populations revealed a reversed J-shape size-class distribution (SCD) indicative of stable structure unlike the heavily disturbed populations. The quotient and permutation indices indicated unstable populations with episodic recruitment and mortality. Our study reveals that natural regeneration and population structure of A. senegal were affected majorly by selective harvesting and heavy browsing. Suitable management strategies to control livestock grazing and illegal tree harvesting within the woodland is required to promote conservation of the species genetic resources

上海地区有治疗史患者中结核分枝杆菌耐药菌株的传播

根据耐药产生的原因，理论上可将耐药结核病分为直接感染耐药结核分枝杆菌引起的原发性耐药和结核分枝杆菌菌株的基因组发生突变而产生的获得性耐药，由于结核病的发病特点及结核分枝杆菌菌株的特性，传统方法无法鉴别耐药是否由同一菌株引起，因此目前简单地将原发性耐药定义为未经治疗的患者对某种抗结核药物的耐药，而获得性耐药是既往有结核病治疗史（超过1个月）的耐药结核病。实际上此种获得性耐药包括以下3种情况：

Human Gut Microbiota and Gastrointestinal Cancer

Human gut microbiota play an essential role in both healthy and diseased states of humans. In the past decade, the interactions between microorganisms and tumors have attracted much attention in the efforts to understand various features of the complex microbial communities, as well as the possible mechanisms through which the microbiota are involved in cancer prevention, carcinogenesis, and anti-cancer therapy. A large number of studies have indicated that microbial dysbiosis contributes to cancer susceptibility via multiple pathways. Further studies have suggested that the microbiota and their associated metabolites are not only closely related to carcinogenesis by inducing inflammation and immune dysregulation, which lead to genetic instability, but also inter- fere with the pharmacodynamics of anticancer agents. In this article, we mainly reviewed the influ- ence of gut microbiota on cancers in the gastrointestinal （GI） tract （including esophageal, gastric, colorectal, liver, and pancreatic cancers） and the regulation of microbiota by diet, prebiotics, pro- biotics, synbiotics, antibiotics, or the Traditional Chinese Medicine. We also proposed some new strategies in the prevention and treatment of GI cancers that could be explored in the future. We hope that this review could provide a comprehensive overview of the studies on the interactions between the gut microbiota and GI cancers, which are likely to yield translational opportunities to reduce cancer morbidity and mortality by improving prevention, diagnosis, and treatment.

DNA methylation polymorphism and stability in Chinese indica hybrid rice

Conventional rice breeding has long focused on exploiting the DNA sequence diversity.However,epigenetic diversity,reflected particularly in DNA methylation,can also contribute to phenotypic variation and should not be overlooked in rice breeding.In this study,20 parental lines of indica rice,which are widely used in hybrid rice breeding in China,were analyzed to investigate variations of DNA methylation and its inheritance.The results revealed a wide diversity in DNA methylation among these breeding lines.A positive correlation was seen between DNA methylation and genetic diversity.Furthermore,some of the methylated DNA was inherited in the subsequent generation,regardless of whether they were produced by selfing or hybrid-crossing.This study provides insight into the methylation patterns in rice,and suggests the importance of epigenetic diversity in rice breeding.

Bacillus cereus AR156 primes induced systemic resistance by suppressing miR825/825 and activating defense-related genes in Arabidopsis

Small RNAs play an important role in plant immune responses. However, their regulatory function in induced systemic resistance（ISR） is nascent. Bacillus cereus AR156 is a plant growth-promoting rhizobacterium that induces ISR in Arabidopsis against bacterial infection. Here,by comparing small RNA profiles of Pseudomonas syringae pv. tomato（Pst） DC3000-infected Arabidopsis with and without AR156 pretreatment, we identified a group of Arabidopsis micro RNAs（mi RNAs） that are differentially regulated by AR156 pretreatment. mi R825 and mi R825 are two mi RNA generated from a single mi RNA gene.Northern blot analysis indicated that they were significantly downregulated in Pst DC3000-infected plants pretreated with AR156, in contrast to the plants without AR156 pretreatment. mi R825 targets two ubiquitin-protein ligases,while mi R825 targets toll-interleukin-like receptor（TIR）-nucleotide binding site（NBS） and leucine-rich repeat（LRR）type resistance（R） genes. The expression of these target genes negatively correlated with the expression of mi R825 and mi R825. Moreover, transgenic plants showing reduced expression of mi R825 and mi R825 displayed enhanced resistance to Pst DC3000 infection, whereas transgenic plants overexpressing mi R825 and mi R825 were more susceptible. Taken together, our data indicates that Bacillus cereus AR156 pretreatment primes ISR to Pst infection by suppressing mi R825 and mi R825 and activating the defense related genes they targeted.

A comparative analysis of epidemiological characteristics of MERS-CoV and SARS-CoV-2 in Saudi Arabia

In this study,we determine and compare the incubation duration,serial interval,pre-symptomatic transmission,and case fatality rate of MERS-CoV and COVID-19 in Saudi Arabia based on contact tracing data we acquired in Saudi Arabia.The date of infection and infector-infectee pairings are deduced from travel history to Saudi Arabia or exposure to confirmed cases.The incubation times and serial intervals are estimated using parametric models accounting for exposure interval censoring.Our estimations show that MERS-CoV has a mean incubation time of 7.21(95%CI:6.59–7.85)days,whereas COVID-19(for the circulating strain in the study period)has a mean incubation period of 5.43(95%CI:4.81–6.11)days.MERS-CoV has an estimated serial interval of 14.13(95%CI:13.9–14.7)days,while COVID-19 has an estimated serial interval of 5.1(95%CI:5.0–5.5)days.The COVID-19 serial interval is found to be shorter than the incubation time,indicating that pre-symptomatic transmission may occur in a significant fraction of transmission events.We conclude that during the COVID-19 wave studied,at least 75%of transmission happened prior to the onset of symptoms.The CFR for MERS-CoV is estimated to be 38.1%(95%CI:36.8–39.5),while the CFR for COVID-191.67%(95%CI:1.63–1.71).This work is expected to help design future surveillance and intervention program targeted at specific respiratory virus outbreaks,and have implications for contingency planning for future coronavirus outbreaks.

Angiotensin-Converting Enzyme(ACE)Inhibitors May Moderate COVID-19 Hyperinflammatory Response:An Observational Study with Deep Immunophenotyping

Background:Angiotensin-converting enzyme inhibitors(ACEi)and angiotensin-II receptor blockers(ARB),the most commonly prescribed antihypertensive medications,counter renin-angiotensin-aldosterone system(RAAS)activation via induction of angiotensin-converting enzyme 2(ACE2)expression.Considering that ACE2 is the functional receptor for SARS-CoV-2 entry into host cells,the association of ACEi and ARB with COVID-19 outcomes needs thorough evaluation.Methods:We conducted retrospective analyses using both unmatched and propensity score(PS)-matched cohorts on electronic health records(EHRs)to assess the impact of RAAS inhibitors on the risk of receiving invasive mechanical ventilation(IMV)and 30-day mortality among hospitalized COVID-19 patients.Additionally,we investigated the immune cell gene expression profiles of hospitalized COVID-19 patients with prior use of antihypertensive treatments from an observational prospective cohort.Results:The retrospective analysis revealed that there was no increased risk associated with either ACEi or ARB use.In fact,the use of ACEi showed decreased risk for mortality.Survival analyses using PS-matched cohorts suggested no significant relationship between RAAS inhibitors with a hospital stay and in-hospital mortality compared to non-RAAS medications and patients not on antihypertensive medications.From the analysis of gene expression profiles,we observed a noticeable up-regulation in the expression of 1L1R2(an anti-inflammatory receptor)and RETN(an immunosuppressive marker)genes in monocytes among prior users of ACE inhibitors.Conclusion:Overall,the findings do not support the discontinuation of ACEi or ARB treatment and suggest that ACEi may moderate the COVID-19 hyperinflammatory response.

From Phage lambda to human cancer： endogenous molecular-cellular network hypothesis

Experimental evidences and theoretical analyses have amply suggested that in cancer genesis and progression genetic information is very important but not the whole. Nevertheless, ＂cancer as a disease of the genome＂ is still currently the dominant doctrine. With such a background and based on the fundamental properties of biological systems, a new endogenous molecular-cellular network theory for cancer was recently proposed by us. Similar proposals were also made by others. The new theory attempts to incorporate both genetic and environmental effects into one single framework, with the possibility to give a quantitative and dynamical description. It is asserted that the complex regulatory machinery behind biological processes may be modeled by a nonlinear stochastic dynamical system similar to a noise perturbed Morse-Smale system. Both qualitative and quantitative descriptions may be obtained. The dynamical variables are specified by a set of endogenous molecular-cellular agents and the structure of the dynamical system by the interactions among those biological agents. Here we review this theory from a pedagogical angle which emphasizes the role of modularization, hierarchy and autonomous regulation. We discuss how the core set of assumptions is exemplified in detail in one of the simple, important and well studied model organisms, Phage lambda. With this concrete and quantitative example in hand, we show that the application of the hypothesized theory in human cancer, such as hepatocellular carcinoma （HCC）, is plausible, and that it may provide a set of new insights on understanding cancer genesis and progression, and on strategies for cancer prevention, cure, and care.

Model Failure and Context Switching Using Logic-Based Stochastic Models

This paper addresses parameter drift in stochastic models. We define a notion of context that represents invariant, stable-over-time behavior and we then propose an algorithm for detecting context changes in processing a stream of data. A context change is seen as model failure, when a probabilistic model representing current behavior is no longer able to ＂fit＂ newly encountered data. We specify our stochastic models using a first-order logic-based probabilistic modeling language called Generalized Loopy Logic （GLL）. An important component of GLL is its learning mechanism that can identify context drift. We demonstrate how our algorithm can be incorporated into a failure-driven context-switching probabilistic modeling framework and offer several examples of its application.

Non-pharmaceutical interventions and their relevance in the COVID-19 vaccine rollout in Saudi Arabia and Arab Gulf countries

In the early stages of the pandemic,Saudi Arabia and other countries in the Arab Gulf region relied on non-pharmaceutical therapies to limit the effect of the pandemic,much like other nations across the world.In comparison to other nations in the area or globally,these interventions were successful at lowering the healthcare burden.This was accomplished via the deterioration of the economy,education,and a variety of other societal activities.By the end of 2020,the promise of effective vaccinations against SARS-CoV-2 have been realized,and vaccination programs have begun in developed countries,followed by the rest of the world.Despite this,there is still a long way to go in the fight against the disease.In order to explore disease transmission,vaccine rollout and prioritisation,as well as behavioural dynamics,we relied on an age-structured compartmental model.We examine how individual and social behaviour changes in response to the initiation of vaccination campaigns and the relaxation of non-pharmacological treatments.Overall,vaccination remains the most effective method of containing the disease and resuming normal life.Additionally,we evaluate several vaccination prioritisation schemes based on age group,behavioural responses,vaccine effectiveness,and vaccination rollout speed.We applied our model to four Arab Gulf nations(Saudi Arabia,Bahrain,the United Arab Emirates,and Oman),which were chosen for their low mortality rate compared to other countries in the region or worldwide,as well as their demographic and economic settings.We fitted the model using actual pandemic data in these countries.Our results suggest that vaccinations focused on the elderly and rapid vaccine distribution are critical for reducing disease resurgence.Our result also reinforces the cautious note that early relaxation of safety measures may compromise the vaccine's short-term advantages.