garded as a general introduction to the interesting new field of atomic medicine, it covers a vast amount of information on radioisotopes which are used in medical research, diagnosis, and therapy. The background of nuclear physics on each aspect of this new field of medicine is concisely explained. The medical use of high energy particle accelerators such as cyclotron, betatron, synchrotron, and linear accelerators are briefly described. The linear accelerator is considered as the machine which has real practical value in radiotherapy. In radiotherapy today in England there is considerable competition between linear accelerator and large telecurie units, such as Cobalt-60 or Cesium-137. Both these developments are important by-products of atomic energy development. The three dangerous biological effects of radiation to man are discussed in some detail: (1) immediate danger of tissue damage from individual high exposure, (2) long-term danger of chronic damage to tissue with possible induction of cancer, (3) remote but important danger of permanent genetic damage that may seriously affect future generations. The common levels of radiation exposure are listed in detail based on the data published in Great Britain. Some interesting estimated figures on radiation received by the whole population of Great Britain to reproductive organs in the first 30 years of life as a genetic hazard are abstracted as follows: Natural body radioactivity, 690 mr. The dose required to double human mutation rate is estimated to be 50,000 mr. The author also stresses the opinion that genetic damage by radiation is not yet fully understood and must be worked out as one of our most urgent problems. The material chosen is mainly from the British sources and is based on a comprehensive review of the literature of the subject. The illustrations .are excellent but no bibliography is appended. It is easy and pleasing to read and it should be recommended to medical students, nurses, and physicians who want to have a general and up-to-date view of this subject. "How does development produce entities which have Form, in the sense of integration or wholeness; how does evolution bring into being organisms which have Ends, in the sense of goal-seeking or directiveness?" An examination of these questions provides the unifying theme for this collection of essays which are Professor Waddington's most recent contribution to theoretical biology. Although portions of four of the five essays have appeared elsewhere in different form, they are essentially new and contain much …
In order to study the law of influence of rubber particle size on concrete frost resistance characteristics, this paper systematically evaluates the freeze–thaw characteristics of rubber concrete containing different particle sizes. Rubber concrete containing different particle sizes is subjected to 25, 50, 75, 100, and 125 freeze–thaw cycles. After the freeze–thaw cycles, the specimens are observed or measured for appearance, mass change rate, relative dynamic elastic modulus, internal damage degree, compressive strength, and tensile strength. The results show that the frost resistance of concrete mixed with rubber of different particle sizes is more excellent, and the surface of concrete specimens after different numbers of freezing and thawing cycles shows different degrees of spalling. Meanwhile, due to the presence of rubber, the compressive and tensile strengths of rubberized concrete are significantly inferior. Finally, the microscopic scanning results reveal the mechanism of rubber’s incorporation into concrete. The incorporation of rubber effectively reduces its internal pore development. To summarize, it can be seen that rubber incorporated into concrete is a worthwhile method to consider for frost resistance of engineering materials.
ABSTRACT The Diffusion of Innovations (DOI) model can be used to explore how faculty prioritize learning about and adopting new pedagogical approaches. Here, we use the DOI framework to contextualize biology faculty perceptions of a professional development (PD) program designed to help them create a full semester course-based undergraduate research experience (CURE) class at a large, public comprehensive university. PD sessions included exploring self-reflexive identity while fostering inclusive classroom spaces through understanding and interrupting implicit bias and microaggressions. This qualitative study sought to determine 11 biology faculty members’ beliefs about the influence of their year-long PD on their CURE development and teaching practices. Findings suggest that faculty were motivated to teach CUREs for a variety of reasons. A common incentive was integrating research into a CURE to bring their passion into their classroom and to engage more students in research. This may be particularly important at institutions where faculty have a heavy teaching load. Faculty also reported modifying their teaching in their CUREs and other courses to be more inclusive and equitable. The importance of peer interactions in the PD was emphasized repeatedly as faculty learned from experts, the literature, and faculty who had already developed a CURE. Our results illustrate that a community of practice structure can enhance the learning aspect of the community, helping faculty consider their implementation of inclusive, equitable, and high-impact practices as an ongoing educational process for themselves and emphasizing the importance of reflection and iteration in a DOI framework.
Diffusion models have emerged as a leading framework in generative modeling, poised to transform the traditionally slow and costly process of drug discovery. This review provides a systematic comparison of their application in designing two principal therapeutic modalities: small molecules and therapeutic peptides. We dissect how the unified framework of iterative denoising is adapted to the distinct molecular representations, chemical spaces, and design objectives of each modality. For small molecules, these models excel at structure-based design, generating novel, pocket-fitting ligands with desired physicochemical properties, yet face the critical hurdle of ensuring chemical synthesizability. Conversely, for therapeutic peptides, the focus shifts to generating functional sequences and designing de novo structures, where the primary challenges are achieving biological stability against proteolysis, ensuring proper folding, and minimizing immunogenicity. Despite these distinct challenges, both domains face shared hurdles: the scarcity of high-quality experimental data, the reliance on inaccurate scoring functions for validation, and the crucial need for experimental validation. We conclude that the full potential of diffusion models will be unlocked by bridging these modality-specific gaps and integrating them into automated, closed-loop Design-Build-Test-Learn (DBTL) platforms, thereby shifting the paradigm from mere chemical exploration to the on-demand engineering of novel~therapeutics.
Julian R. Greenwood, Vanica Lacorte-Apostol, Thomas Kroj
et al.
Abstract A critical step to maximize the usefulness of genome-wide association studies (GWAS) in plant breeding is the identification and validation of candidate genes underlying genetic associations. This is of particular importance in disease resistance breeding where allelic variants of resistance genes often confer resistance to distinct populations, or races, of a pathogen. Here, we perform a genome-wide association analysis of rice blast resistance in 500 genetically diverse rice accessions. To facilitate candidate gene identification, we produce de-novo genome assemblies of ten rice accessions with various rice blast resistance associations. These genome assemblies facilitate the identification and functional validation of novel alleles of the rice blast resistance genes Ptr and Pia. We uncover an allelic series for the unusual Ptr rice blast resistance gene, and additional alleles of the Pia resistance genes RGA4 and RGA5. By linking these associations to three thousand rice genomes we provide a useful tool to inform future rice blast breeding efforts. Our work shows that GWAS in combination with whole-genome sequencing is a powerful tool for gene cloning and to facilitate selection of specific resistance alleles for plant breeding.
Hubert Daisley, Oneka Acco, Martina Daisley
et al.
The vasa vasorum of the large pulmonary vessels is involved in the pathology of COVID-19. This specialized microvasculature plays a major role in the biology and pathology of the pulmonary vessel walls. We have evidence that thrombosis of the vasa vasorum of the large and medium-sized pulmonary vessels during severe COVID-19 causes ischemia and subsequent death of the pulmonary vasculature endothelium. Subsequent release of thrombi from the vasa interna into the pulmonary circulation and pulmonary embolism generated at the ischemic pulmonary vascular endothelium site, are the central pathophysiological mechanisms in COVID-19 responsible for pulmonary thromboembolism. The thrombosis of the vasa vasorum of the large and medium-sized pulmonary vessels is an internal event leading to pulmonary thromboembolism in COVID-19.
The impact of the built environment on the ridership of ride-hailing results depends on the spatial grid scale. The existing research on the demand model of ride-hailing ignores the modifiable areal unit problem (MAUP). Taking Chengdu as an example, and taking the density of pick-ups and drop-offs as dependent variables, 12 explanatory variables were selected as independent variables according to the “5D” built environment theory. The nugget–sill ratio (NSR) method and optimal parameter-based geographical detector (OPGD) model were used to determine the optimal grid scale for the aggregation of the built environment variables and the ridership of ride-hailing. Based on the optimal grid scale, the optimal data discretization method of the explanatory variables was determined by comparing the results of the geographic detector under different discretization methods (such as the natural break method, k-means clustering method, equidistant method, and quantile method); we utilized the geographic detector model to explore the relative importance and the interactive impacts of the explanatory variables on the ridership of ride-hailing under the optimal grid scale and optimal data discretization method. The results indicated that: (1) the suggested grid scale for the aggregation of the built environment and ride-hailing ridership in Chengdu is 1100 m; (2) the optimal data discretization method is the quantile method; (3) the floor area ratio (FAR), distance from the nearest subway station, and residential POI (point of interest) density resulted in a relatively high importance of the explanatory variable that affects the ridership of ride-hailing; and (4) the interactions of the diversity index of mixed land use ∩ FAR, distance to the nearest subway station ∩ FAR, transportation POI density ∩ FAR, and distance to the central business district (CBD) ∩ FAR made a higher contribution to ride-hailing ridership than the single-factor effect of FAR, which had the highest contribution compared with the other explanatory variables. The proposed grid scale can provide the basis for the partitioning management and scheduling optimization of ride-hailing. In the process of adjusting the ride-hailing demand, the ranking results of the importance and interaction of the built-environment explanatory variables offer valuable references for formulating the priority renewal order and proposing a scientific combination scheme of the built-environment factors.