Decoding University Hierarchy and Prestige in China through Domestic Ph.D. Hiring Network

The academic job market for fresh Ph.D. students to pursue postdoctoral and junior faculty positions plays a crucial role in shaping the future orientations, developments, and status of the global academic system. In this work, we focus on the domestic Ph.D. hiring network among universities in China by exploring the doctoral education and academic employment of nearly 28,000 scientists across all Ph.D.-granting Chinese universities over three decades. We employ the minimum violation rankings algorithm to decode the rankings for universities based on the Ph.D. hiring network, which offers a deep understanding of the structure and dynamics within the network. Our results uncover a consistent, highly structured hierarchy within this hiring network, indicating the imbalances wherein a limited number of universities serve as the main sources of fresh Ph.D. across diverse disciplines. Furthermore, over time, it has become increasingly challenging for Chinese Ph.D. graduates to secure positions at institutions more prestigious than their alma maters. This study quantitatively captures the evolving structure of talent circulation in the domestic environment, providing valuable insights to enhance the organization, diversity, and talent distribution in China's academic enterprise

Talent hat, cross-border mobility, and career development in China

This study aims to investigate the influence of cross-border recruitment program in China, which confers scientists with a 'talent hat' including a startup package comprising significant bonuses, pay, and funding, on their future performance and career development. By curating a unique dataset from China's 10-year talent recruitment program, we employed multiple matching designs to quantify the effects of the cross-border recruitment with 'talent hat' on early career STEM scholars. Our findings indicate that the cross-border talents perform better than their comparable contenders who move without talent hats and those who do not move, given equivalent scientific performance before relocation. Moreover, we observed that scholars in experimental fields derive greater benefits from the talent program than those in non-experimental fields. Finally, we investigated how the changes in scientific environment of scientists affect their future performance. We found that talents who reassembled their collaboration network with new collaborators in new institutions after job replacement experienced significant improvements in their academic performance. However, shifting research directions entails risks, which results in a subsequent decrease of future productivity and citation impact following the relocation. This study has significant implications for young scientists, research institutions, and governments concerning cultivating cross-border talents

Quantifying the hierarchical scales of scientists'mobility

Human behaviors, including scientific activities, are shaped by the hierarchical divisions of geography. As a result, researchers' mobility patterns vary across regions, influencing several aspects of the scientific community. These aspects encompass career trajectories, knowledge transfer, international collaborations, talent circulation, innovation diffusion, resource distribution, and policy development. However, our understanding of the relationship between the hierarchical regional scale and scientific movements is limited. This study aims to understand the subtle role of the geographical scales on scientists' mobility patterns across cities, countries, and continents. To this end, we analyzed 2.03 million scientists from 1960 to 2021, spanning institutions, cities, countries, and continents. We built a model based on hierarchical regions with different administrative levels and assessed the tendency for mobility from one region to another and the attractiveness of each region. Our findings reveal distinct nested hierarchies of regional scales and the dynamic of scientists' relocation patterns. This study sheds light on the complex dynamics of scientists' mobility and offers insights into how geographical scale and administrative divisions influence career decisions.Comment: 20 pages, 5 figure

Clinical and prognostic significance of Hec1 expression in patients with Cervical Cancer

ObjectiveHec1 is a component of the Ndc80 kinetochore complex and is frequently upregulated in various cancers. However, the clinical significance of Hec1 in cervical cancer remains largely unknown. This study aimed to investigate the expression patterns of Hec1 in cervical cancer and its relationship with the clinicopathological characteristics of patients diagnosed with the disease.MethodsImmunohistochemistry was used to assess the expression of Hec1 in 136 cervical cancer tissue samples and 82 normal cervical tissue samples. The relationship between Hec1 protein expression and the clinicopathological characteristics of cervical cancer patients was analyzed using the Chi-square test. Additionally, the association between Hec1 protein expression and patient survival was examined using Kaplan-Meier survival curves. Independent risk factors affecting the prognosis of cervical cancer patients were analyzed using the Cox proportional hazards regression model.ResultsThe positive expression rate of Hec1 protein in cervical cancer tissues was 83.82%, significantly higher than the 7.31% in normal cervical tissues. Compared to patients with negative Hec1 expression, those with positive expression exhibited significantly higher FIGO staging, increased lymph node metastasis, greater depth of tumor stromal infiltration, and larger tumor diameter. Multivariable analysis using the Cox proportional hazards regression model indicated that Hec1 positive expression was an independent risk factor for both overall survival (HR = 2.79, 95% CI: 1.65–4.05, p = 0.012) and progression-free survival (HR = 1.81, 95% CI: 1.22-3.18, p = 0.002) in cervical cancer patients. Kaplan-Meier survival curve analysis showed that patients with positive Hec1 expression experienced a lower overall survival (HR: 2.72, 95% CI: 1.15–4.52, p = 0.004) and progression-free survival (HR: 3.12, 95% CI: 1.62–5.03, p = 0.002) when compared to those with negative Hec1 expression.ConclusionHec1 is significantly upregulated in cervical cancer tissues and associated with poor prognosis in cervical cancer patients. Therefore, Hec1 could be a novel biomarker, not only for the diagnosis and treatment evaluation of cervical cancer but also as an indicator for predicting the prognosis of cervical cancer patients

Multiomics Analyses Reveal DARS1-AS1/YBX1-Controlled Posttranscriptional Circuits Promoting Glioblastoma Tumorigenesis/Radioresistance

The glioblastoma (GBM) stem cell-like cells (GSCs) are critical for tumorigenesis/therapeutic resistance of GBM. Mounting evidence supports tumor-promoting function of long noncoding RNAs (lncRNAs), but their role in GSCs remains poorly understood. By combining CRISPRi screen with orthogonal multiomics approaches, we identified a lncRNA DARS1-AS1-controlled posttranscriptional circuitry that promoted the malignant properties of GBM cells/GSCs. Depleting DARS1-AS1 inhibited the proliferation of GBM cells/GSCs and self-renewal of GSCs, prolonging survival in orthotopic GBM models. DARS1-AS1 depletion also impaired the homologous recombination (HR)-mediated double-strand break (DSB) repair and enhanced the radiosensitivity of GBM cells/GSCs. Mechanistically, DARS1-AS1 interacted with YBX1 to promote target mRNA binding and stabilization, forming a mixed transcriptional/posttranscriptional feed-forward loop to up-regulate expression of the key regulators of G1-S transition, including E2F1 and CCND1. DARS1-AS1/YBX1 also stabilized the mRNA of FOXM1, a master transcription factor regulating GSC self-renewal and DSB repair. Our findings suggest DARS1-AS1/YBX1 axis as a potential therapeutic target for sensitizing GBM to radiation/HR deficiency-targeted therapy

Practical operation and theoretical basis of difference-in-difference regression in science of science: The comparative trial on the scientific performance of Nobel laureates versus their coauthors

Abstract Purpose In recent decades, with the availability of large-scale scientific corpus datasets, difference-in-difference (DID) is increasingly used in the science of science and bibliometrics studies. DID method outputs the unbiased estimation on condition that several hypotheses hold, especially the common trend assumption. In this paper, we gave a systematic demonstration of DID in the science of science, and the potential ways to improve the accuracy of DID method. Design/methodology/approach At first, we reviewed the statistical assumptions, the model specification, and the application procedures of DID method. Second, to improve the necessary assumptions before conducting DID regression and the accuracy of estimation, we introduced some matching techniques serving as the pre-selecting step for DID design by matching control individuals who are equivalent to those treated ones on observational variables before the intervention. Lastly, we performed a case study to estimate the effects of prizewinning on the scientific performance of Nobel laureates, by comparing the yearly citation impact after the prizewinning year between Nobel laureates and their prizewinning-work coauthors. Findings We introduced the procedures to conduct a DID estimation and demonstrated the effectiveness to use matching method to improve the results. As a case study, we found that there are no significant increases in citations for Nobel laureates compared to their prizewinning coauthors. Research limitations This study ignored the rigorous mathematical deduction parts of DID, while focused on the practical parts. Practical implications This work gives experimental practice and potential guidelines to use DID method in science of science and bibliometrics studies. Originality/value This study gains insights into the usage of econometric tools in science of science. </jats:sec