Protein-protein interaction network study of metallo-beta-lactamase-L1 present in

K H Sreenithya, Shobana Sugumar

Abstract read

In one paragraph

Article in In silico pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it

0cells of the map it votes in

2citing 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

2 citing papers in PubMed.

Utilises Machine Learning Techniques to Deeply Analyse the Role of Lysosome-Dependent Cell Death in Endometrial Cancer and Its Interactions With the Tumour Microenvironment.Journal of cellular and molecular medicine · 2025
Article
Multidimensional bioinformatics analysis of chondrosarcoma subtypes and TGF-β signaling networks using big data approaches.Discover oncology · 2025
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

2 authors.

K H SreenithyaDepartment of Genetic Engineering, School of Bioengineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, India.

Shobana SugumarDepartment of Genetic Engineering, School of Bioengineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microorganisms are evolving to withstand the effect of antimicrobial agents and thereby pose a global threat known as antimicrobial resistance. Resistance towards multiple drugs due to various intrinsic as well environmental factors leads to an even more dangerous drug resistance property known as multi-drug resistance (MDR). WHO has recognized MDR bacteria as a top global threat as they complicate the treatment and augment mortality and morbidity risks. Gram-negative bacteria produce beta-lactamase enzymes that can hydrolyze beta-lactam antibiotics, impacting drug susceptibility. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00270-9.

Indexed as

CytoscapeL1 beta-lactamaseMulti-drug resistanceNetwork analysisProtein-protein interactionSmlt2667

Identifiers

PMID39479381

DOI10.1007/s40203-024-00270-9

PMCPMC11519282

What OpenQuestion holds

Textmetadata

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.