Thursday, March 28, 2024

 

Occurrence of antibiotic resistance genes in the western Qinghai Lake basin



KEAI COMMUNICATIONS CO., LTD.
Nitrate increased the diversity and abundances of microbial community in water ecosystem of the western Qinghai Lake basin 

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NITRATE INCREASED THE DIVERSITY AND ABUNDANCES OF MICROBIAL COMMUNITY IN WATER ECOSYSTEM OF THE WESTERN QINGHAI LAKE BASIN, BUT HAS NO EFFECT ON THE DISTRIBUTION OF ARGS. IN CONTRAST TO MICROBIOLOGY, INTI1 PROMOTED THE SPREAD OF ARGS IN THAT WATER ECOSYSTEM.

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CREDIT: CHENXI WU, ET AL.




Antibiotic resistance genes (ARGs) have been widely detected in water, sediment, gut and even the phycosphere of algae. In strong anthropogenic activity areas, antibiotic resistance caused by ARGs can pose a significant threat to human health. Despite the numerous published studies on the occurrence and distribution of ARGs in these areas, there is a dearth of literature on the presence and dispersal of ARGs in remote and pristine environments with limited antibiotic usage.

Qinghai Lake, located in the northeastern part of the Qinghai-Tibet Plateau, is the largest saltwater lake in mainland China. Notably, it is an important water body for maintaining ecological security. The typical geographical and humanistic features of the Qinghai Lake basin, especially in the northern region, are high altitude (more than 3,000 m), oxygen-deficient environment, low temperature, and sparse human population. Due to governmental protection and national nature reserve policies, the Qinghai Lake basin is less affected by anthropogenic activity. Nevertheless, it must be acknowledged that the Qinghai Lake basin is a closed watershed with no river outflow. As such, the lake can easily become a sink of ARGs from the watershed and surrounding rivers. In light of this unique geographical background, no prior investigations have explored the occurrence and transmission of ARGs under varied nutrient conditions within the Qinghai Lake basin.

To that end, a team of researchers in China investigated the microbial community and ARGs in two typical rivers of the western Qinghai Lake basin.

“We found that the microbial community was unique in the western Qinghai Lake basin,” shares Chenxi Wu, corresponding author of the study.“Specifically, cold-resistant Planomicrobium sp. was the predominant genus due to the low temperature.”

Furthermore, the team noted that although ARGs in the western Qinghai Lake basin were significantly lower than that in strong anthropogenic activity areas, a strong correlation between ARGs and intI1 indicated the potential rapid proliferation and spread of ARGs through cross- or co-selection if antibiotic pollution occurs in that area.

The team's findings, published in the KeAi journal Water Biology and Security, emphasized the adaptation of bacteria to the environment and the facilitation of anthropogenic activity in the propagation of ARGs in natural environments.

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Contact the author: Jia Jia & Chenxi Wu, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China, jia263319@ihb.ac.cn; chenxi.wu@ihb.ac.cn

The publisher KeAi was established by Elsevier and China Science Publishing & Media Ltd to unfold quality research globally. In 2013, our focus shifted to open access publishing. We now proudly publish more than 100 world-class, open access, English language journals, spanning all scientific disciplines. Many of these are titles we publish in partnership with prestigious societies and academic institutions, such as the National Natural Science Foundation of China (NSFC).

 Case Western Reserve University researchers report rise in global fungal drug-resistant infections


Researchers issue call to action to address and prevent growing problem



CASE WESTERN RESERVE UNIVERSITY


CLEVELAND—A global wave of infections caused by fungi growing drug-resistant has the medical community issuing precautions on how to protect yourself.

Skin contact with microorganisms found in soil or on hard surfaces, such as common shower facilities, or exposure to infected pets, can result in fungal infections known as dermatomycoses. Rashes, itching, burning and skin irritation are among the symptoms. 

Epidemiological data published in Microbial Cell indicates that a rise in severe fungal infections has resulted in over 150 million cases annually and almost 1.7 million fatalities globally.

In a recent study published in Pathogens and Immunity, Thomas McCormick and Mahmoud Ghannoum, professors of dermatology at the Case Western Reserve University School of Medicine and affiliated with University Hospitals Cleveland Medical Center, explain how rising antifungal resistance is worsening the problem of invasive fungal infections.

“This is not just an issue that affects individual patients,” McCormick said. “The World Health Organization has recognized it as a widespread threat that has the potential to impact entire healthcare systems if left unchecked.”

Based on their findings, the researchers issued precautions and a “call to action” for the medical community to help protect people from multidrug-resistant fungi—starting with awareness and education.

“Healthcare providers must prioritize the use of diagnostic tests when faced with an unknown fungal infection,” Ghannoum said. “Early detection can make all the difference in improving patient outcomes.”

Patients treated with medications to protect the immune system after cancer and transplant procedures are more vulnerable to fungal infections—making them especially more vulnerable to infections from drug-resistant fungi, the researchers said. 

The emergence of multidrug-resistant fungal species, such as Candida auris and Trichophyton indotineae, is especially troubling and requires urgent attention, they reported. 

In a study recently published in Emerging Infectious Diseases, Ghannoum’s research team and the Centers for Disease Control and Prevention (CDC), detailed a case that demonstrated Trichophyton indotineae, in addition to becoming drug-resistant, was also sexually transmissible.  

To address the growing health concern, McCormick and Ghannoum suggest several measures:

  • Increased awareness and education: Raising awareness in the general healthcare setting to obtain a more accurate understanding of the rise of antifungal-resistant infections.
  • Diagnostic Testing:  Routine use of diagnostic tests can guide appropriate treatment strategies.
  • Antifungal Susceptibility Testing (AST): Improving insurance reimbursement rates for AST and increasing the number of qualified laboratories with the capacity to perform these tests.
  • Call to Action: Addressing the emerging challenge of antifungal resistance involves concerted efforts from healthcare professionals, researchers, policymakers and the pharmaceutical industry to develop and implement strategies for managing and preventing antifungal resistance.

“The ultimate goal of these measures,” Ghannoum said, “is to improve the quality of patient care by ensuring effective treatment and preventing further escalation of the problem.” 

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About Case Western Reserve University

Case Western Reserve University is one of the country's leading private research institutions. Located in Cleveland, we offer a unique combination of forward-thinking educational opportunities in an inspiring cultural setting. Our leading-edge faculty engage in teaching and research in a collaborative, hands-on environment. Our nationally recognized programs include arts and sciences, dental medicine, engineering, law, management, medicine, nursing, and social work. About 6,200 undergraduate and 6,100 graduate students comprise our student body. Visit case.edu to see how Case Western Reserve thinks beyond the possible.

About University Hospitals / Cleveland, Ohio
Founded in 1866, University Hospitals serves the needs of patients through an integrated network of 21 hospitals (including five joint ventures), more than 50 health centers and outpatient facilities, and over 200 physician offices in 16 counties throughout northern Ohio. The system’s flagship quaternary care, academic medical center, University Hospitals Cleveland Medical Center, is affiliated with Case Western Reserve University School of Medicine, Northeast Ohio Medical University, Oxford University, the Technion Israel Institute of Technology and National Taiwan University College of Medicine. The main campus also includes the UH Rainbow Babies & Children's Hospital, ranked among the top children’s hospitals in the nation; UH MacDonald Women's Hospital, Ohio's only hospital for women; and UH Seidman Cancer Center, part of the NCI-designated Case Comprehensive Cancer Center. UH is home to some of the most prestigious clinical and research programs in the nation, with more than 3,000 active clinical trials and research studies underway. UH Cleveland Medical Center is perennially among the highest performers in national ranking surveys, including “America’s Best Hospitals” from U.S. News & World Report. UH is also home to 19 Clinical Care Delivery and Research Institutes. UH is one of the largest employers in Northeast Ohio with more than 30,000 employees. Follow UH on LinkedIn
Facebook and Twitter. For more information, visit UHhospitals.org.

 

AS ABOVE, SO BELOW

Harnessing computational intelligence for 3D modeling of maize canopies



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Fig. 1. 

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THE COMPLETE METHODOLOGICAL PROCESS.

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CREDIT: PLANT PHENOMICS




Understanding the structure of crop canopies is essential for optimizing crop production as it significantly influences resource utilization efficiency, yield and stress resistance. While research has integrated canopy studies into various agricultural practices, the construction of  accurate 3D models remains challenging due to complex spatial distributions and technological limitations. Current methods struggle to capture detailed morphological data due to issues such as resolution and cost. To address these issues, there is an emerging interest in applying Computational Intelligence (CI) techniques. These techniques have shown promise in various agricultural applications but haven’t  yet been  explored for constructing  3D models of maize canopies.

In March 2024, Plant Phenomics published a research article entitled by “Three-dimensional modelling of maize canopies based on computational intelligence”. This research aims to integrate CI into 3D plant canopy modeling, particularly focusing on overcoming the challenges of internal occlusion and resource competition among densely planted crops.

The study presents a computational intelligence-based 3D modeling method for maize canopies, focusing on visualizing and validating the structure of maize canopies across different planting densities and varieties. Using this method, 3D models for the JNK728 and JK968 maize varieties were constructed at densities of 3, 6, and 9×10^4 plants per hectare. The mothed demonstrated the method's ability to capture the effects of planting density on canopy structure, including increased shading and adjustments in leaf azimuth angles to optimize light capture. The  models were validated and showed significant improvements in simulating the distribution of leaf azimuth angles, The R2 values indicated a high degree of consistency with measured data, especially after optimization through a reflective approach.

 The study also validated the models' accuracy in representing canopy coverage, showing a correlation with actual canopy conditions and highlighting the models' limitations in capturing elements like fallen leaves and weeds. The distribution of leaf azimuth angles close to 90° increases with planting density, suggesting an adaptive response of maize leaves to environmental stress by aligning more perpendicular to the row direction. This trend was further validated through the construction of 3D models across a gradient of planting densities.

The computational process, though time-intensive, highlights the efficiency and potential of computational intelligence in 3D canopy modeling. The iterative optimization of sunlit leaf area ratios and the intelligent adjustment of 3D phytomers' azimuth angles reflect the application of swarm intelligence principles to crop canopy modeling. The study highlights the significance of  precise crop  canopy modeling to comprehend plant competition for light resources. It suggests further enhancements and future work to improve the models' accuracy and practicality by considering a broader range of environmental factors and incorporating more detailed phenotypic and growth information.

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References

Authors

Yandong  Wu1,2 ,  Weiliang  Wen2,3,4 ,  Shenghao  Gu2,3,  Guanmin  Huang2,3,4,  Chuanyu Wang2,3, Xianju Lu2,3,4, Pengliang Xiao1,2, Xinyu Guo2,3*, Linsheng Huang1*

†  These authors contributed equally to the article.

Affiliations

1National Engineering Research Center for Agro-Ecological Big Data Analysis & Application, Anhui University, Hefei 230601, China.

2Information  Technology  Research  Center,  Beijing  Academy  of  Agriculture  and  Forestry  Sciences,  Beijing  100097, China.

3Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China.

4Nongxin Science & Technology (Beijing) Co., Ltd, Beijing 100097, China

About Linsheng Huang

He is currently a Professor and the Deputy Director of the National Engineering Research Center for Agro-Ecological Big Data Analysis and Application, Anhui University. His research interests include quantitative remote sensing applications in crop diseases and insect pests.

 

Cogeneration of innovative audio-visual content: A new challenge for computing art



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Summary of AI-based visual art generation 

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SUMMARY OF AI-BASED VISUAL ART GENERATION  

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CREDIT: BEIJING ZHONGKE JOURNAL PUBLISING CO. LTD.




Walter Benjamin came up with aura and authenticity in The Work of Art in the Age of Mechanical Reproduction in 1936 to describe the value of original artworks created by artists instead of mechanical copies. He wanted to defend artificiality and support traditional fine arts. Not singly but in pairs, Mitchell’s core concern was about the work of art in the age of biocybernetic reproduction in What Do Pictures Want?: The Lives and Loves of Images (2005) followed Benjamin’s train of thought. He especially mentioned the first cloned sheep, Dolly, and regarded it as a living image. Mitchell is one of the most representative and influential theorists in the arts and human sciences. He developed a series of concepts to explain the value of biocybernetic artworks. However, based on carbon, artists in this field are limited by the development of biotechnology, and their creation is sometimes repressed instead of released. Some disappointing cooperation between biologists and artists seems to popularize scientific knowledge by entertaining visual culture and show a lack of critical thinking. Therefore, researchers need to reflect on what artists can do with advanced technology.

 

Humans have faced new challenges in the era of the metaverse. Humans have not only mechanical copies of artworks or biocybernetic replicas but also avatars of humans themselves. This paper proposes the concept of artificial intelligent (AI) art, thus summarizing the main features of artworks produced by artificial intelligent technology, such as extended reality (XR, the combination of VR/AR/MR), cyber-physical system (CPS), cloud computing, and blockchain. The cooperation between AI technical staff and artists is more intimate than that between biologists and artists. AI technology discharges artists from laborious work, which was primarily accused by Marx et al., and encourages them to realize their full potential in art. As a result, AI is like a capable partner in the team who always understands the artist in time and does intense work to bring the artist’s romantic conceiving into reality.

 

With bright prospects for development, AI technology plays essential roles in design, creation, and exhibition in art circles. The concept of AI art may be easily confused with computer art. It is important to note that AI art is more advanced than computer art and can cover more perceptual requirements, including optical and acoustical requirements. AI art usually presents a fusion of the human senses. Art appreciators obtain visual, aural, and tactual feelings simultaneously. In other words, AI technology provides a rich audio-visual feast for modern art exhibitions.

 

The development plan for AI art is still in its infancy. There are some concerns in society about the general applicability of AI technology. Here is an interesting question that has always been mentioned. Do AI dream of electric sheep? In 1968, Philip K. Dick first put this question forward in his science fiction: Do Androids dream of electric sheep? The inspiration for the films Blade Runner and Blade Runner 2049. After discussing AI ethical issues, this title has become the core question that represents the fear that AI would replace humans. Such fears soon spread to the humanities. Some intellectuals believe there should be limits to AI technology. However, if one has sufficient knowledge of AI technology, one will find such fears laughable. People’s fear is nothing more than a rejection of the unknown. Cutting-edge AI technology still needs to reach the emotional level of humans. The urgent need to work on developing and applying AI technology remains as strong as possible.

 

AI technology is currently used in the art field for technique classification, style migration, interactive design, manufacturing, and cultural industry, and so on. AI art has produced AI-generated poetry, VR painting, digital media art, AI voiceovers, and smart electrical appliances. These examples show the solid creative power of AI art. However, some artists are not happy with it. In 1972, the German artist Joseph Beuys gave a speech at Documenta in Kassel, presenting the idea that “everyone is an artist.” His views have caused an uproar. In those days, it was nothing more than an imagination. After all, not everyone was skilled in creating art. With the development of AI art, this idea seems to be becoming a reality. AI is powerful enough to allow anyone to become an artist. It should be noted that the creative ability of AI is not endless. It comes from humans who have talents in creating art. The development of AI art is, therefore, not incompatible with the training of artists. In contrast, the spread of AI art enables artists to do what they do best. In this way, AI art development and traditional art innovation can hold a win-win situation.

 

To be on target, a paper by Prof. Gao Feng from Peking University focuses on AI-generated video and AI-generated audio. Audio-visual ability is often thought of as a composite human sensory ability. Their combination has rapidly improved the production efficiency of industries such as movies, short videos, and games. The summary of AI visual and auditory technology and the presentation of existing results can help practitioners in the industry determine art industry trends in the future.

 

Audio-visual art generation can be divided into visual art generation and auditory art generation. Section 2 of this paper provides a comprehensive overview of the datasets and methods in the two fields. Visual art generation part: first, researchers introduce ten classic image datasets; then, based on three tasks of AI painting, style transfer and text-to-image translation, researchers summarize the classic models in the field of visual content generation; finally, researchers show typical systems and products for it. Auditory art generation part: they use the form of sound expression as an indicator, specifically listing eight classic music datasets in the field of auditory art generation; then, regarding the model structure as standard, the music generation methods are divided into two categories, general model, and composite model. Researchers outline nine classical frameworks for music generation and identify related models and products.

 

There are two types of evaluation methods for algorithm performance: objective evaluation and subjective evaluation. Objective evaluation applies several metrics based on mathematical theory, which is quantitative, efficient, and widely used, but it is not suitable for content that requires subjective feelings. Subjective evaluation usually needs to design experiments, and observers evaluate the results of the algorithm, which is time-consuming, laborious, and difficult to quantify. Nevertheless, subjective evaluation is consistent with subjective feelings. In the field of art generation, subjective evaluation plays an important role in evaluating the creativity of the model. In Section 3, researchers provide an overview of measuring the quality of generated results from objective and subjective perspectives.

 

Section 4 introduces proposed materials and mechanism. Cogeneration of audio-visual content is a multimodal task and requires approaches to fuse information from different sources, including image, video, audio, text, etc. By weighing the strengths and limitations of various audio-visual art generation algorithms, researchers develop and propose a joint generation mechanism for generating digital audio-visual art works using multiple types of algorithms. The system is divided into a visual art generation module and an auditory art generation module. The former is responsible for generating dynamic video content of a specified style, and the latter generates the corresponding video soundtrack through the text features associated with the video. In Section 4.1, researchers introduce two datasets constructed for audio-visual joint tasks. In Sections 4.2 and 4.3, they demonstrate the visual art generation module and the auditory art generation module, respectively.

 

This paper has summarized the results of the technical development of audio-visual art generation. The technology of audio-visual art generation has a wide range of applications. It can be used at home to make entertainment more diverse. It can also be used in public places. For example, it can increase the attractiveness of commercial promotion and art exhibits. A study proposed a new museum archiving system that applies AI technology to the service of art institutions, including museums. Studies such as this show widespread interest in AI-based computing art, which can facilitate people’s daily lives and empower the development of cultural industries. Furthermore, visual art generation and auditory art generation will revolutionize the way art is produced and increase its productivity. However, this inevitably poses some challenging issues. Traditional artists have shown great anxiety about the development of computing art. They fear that computers will soon replace their jobs. This concern is not unwarranted. AI is increasingly replacing manual labor. There are two aspects involved in Section 5. On the one hand, researchers need to clarify whether computing art qualifies to replace artificial art. On the other hand, researchers need to know whether computing art instead of artificial art is more beneficial to the well-being of society. In summary, the main challenges of AI-based computing art can be summarized as the artificial and intelligent aspects of computing art.

 

This paper has provided a comprehensive survey on audio-visual content generation. Researchers hope that this review will help people better understand the research field of audio-visual art and the development tendency of AI-based generation.

 

See the article:

Cogeneration of Innovative Audio-visual Content: A New Challenge for Computing Art

http://doi.org/10.1007/s11633-023-1453-5