Evidence map›Paper›PMID 38292137›Full record

ReviewEnvironmental science and ecotechnology2024

Global WWTP Microbiome-based Integrative Information Platform: From experience to intelligence.

Fuzhong Xiong, Zhiguo Su, Yushi Tang, Tianjiao Dai, Donghui Wen

Abstract readReview
In one paragraph

Review in Environmental science and ecotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Fuzhong XiongCollege of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
Zhiguo SuSchool of Environment, Tsinghua University, Beijing, 100084, China.
Yushi TangLewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, 08544, USA.
Tianjiao DaiSchool of Water Resources and Environment, China University of Geosciences (Beijing), Beijing, 100083, China.
Donghui WenCollege of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Domestic and industrial wastewater treatment plants (WWTPs) are facing formidable challenges in effectively eliminating emerging pollutants and conventional nutrients. In microbiome engineering, two approaches have been developed: a top-down method focusing on domesticating seed microbiomes into engineered ones, and a bottom-up strategy that synthesizes engineered microbiomes from microbial isolates. However, these approaches face substantial hurdles that limit their real-world applicability in wastewater treatment engineering. Addressing this gap, we propose the creation of a Global WWTP Microbiome-based Integrative Information Platform, inspired by the untapped microbiome and engineering data from WWTPs and advancements in artificial intelligence (AI). This open platform integrates microbiome and engineering information globally and utilizes AI-driven tools for identifying seed microbiomes for new plants, providing technical upgrades for existing facilities, and deploying microbiomes for accidental pollution remediation. Beyond its practical applications, this platform has significant scientific and social value, supporting multidisciplinary research, documenting microbial evolution, advancing Wastewater-Based Epidemiology, and enhancing global resource sharing. Overall, the platform is expected to enhance WWTPs' performance in pollution control, safeguarding a harmonious and healthy future for human society and the natural environment.

Indexed as

Artificial intelligenceEnvironmental engineeringInformation platformMicrobiomeWastewater treatment plants

Identifiers

PMID38292137
PMCPMC10826124

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.