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Overview

Tags

Neoplasms

Respiratory Diseases

Synthetic peptide

Small molecule drug

Disease domain score

A glimpse into the focused therapeutic areas

Technology Platform

Most used technologies in drug development

Targets

Most frequently developed targets

Disease Domain	Count

Neoplasms	2

Top 5 Drug Type	Count

Small molecule drug	1
Synthetic peptide	1

Top 5 Target	Count

GDF15(Growth/differentiation factor 15)	1
EGFR x c-Met	1

BACKGROUNDEucalyptol (1,8-cineole), a naturally occurring monoterpenoid compound, is ubiquitously distributed across plant, animal, and microbial organisms. This bioactive molecule demonstrates significant therapeutic potential for various neurological and respiratory disorders, including cancer, epilepsy, and tracheitis, attributable to its potent antioxidant, anti-inflammatory, and antimicrobial properties.SCOPE AND THRUSTThe present review systematically examines the biosynthetic pathways and metabolic routes of eucalyptol, while elucidating its molecular mechanisms underlying microbial inhibition. We comprehensively summarize its principal therapeutic pathways in major disease interventions, with particular emphasis on its multi-target pharmacological actions. Furthermore, this analysis addresses potential toxicological concerns associated with eucalyptol application and discusses emerging strategies utilizing biological agents for active enhancement.CONCLUSION AND SIGNIFICANCEThis comprehensive evaluation not only enhances our understanding of eucalyptol's therapeutic mechanisms but also provides critical insights for its development as a promising phytopharmaceutical agent in clinical practice.

01 Oct 2025·Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

A novel AIEgen fluorescent probe based on quinoline-malononitrile for monitoring and imaging ClO− and viscosity in biosystem

Article

Author: Tan, Zhenkuan ; Huang, Yiyan ; Pu, Shouzhi ; Ji, Yuan ; Liu, Gang ; Ding, Haichang ; Gong, Zhihong ; Fan, Congbin ; Wu, Miaojie

Hypochlorite (ClO^-) and viscosity play a pivotal role in biological immune defense systems, it has been demonstrated that alterations in ClO^- may link to the modifications in intracellular viscosity. Consequently, it is crucial to develop a tool that can accurately assess these changes of ClO^- and viscosity concurrently. In this work, a dual-responsive fluorescent probe QM-WV based on the ICT effect for simultaneous detection of ClO^- and viscosity was constructed. QM-WV exhibited a signally turn-on fluorescence signal at 552 nm for ClO^- with favorable selectivity. Meanwhile, QM-WV displayed an exceptional 'off-on' fluorescence response at 650 nm to viscosity changes in glycerol-ethanol system. More importantly, QM-WV is capable of visually detecting ClO^- by using smartphone as a portable signal processing device. Based on its low cytotoxicity and stability under physiological conditions, QM-WV further enabled the detection and imaging of ClO^- and viscosity in HeLa cells and zebrafish.

01 Oct 2025·Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Quantitative detection of serum biochemical indexes via UV–Vis-NIRS combined with deep neural networks

Article

Author: Liang, Gaoqiang ; Ren, Zhong ; Zhang, Haibin

To achieve rapid, cost-efficient, convenient and accurate detection of five clinical serum biochemical indexes, namely glucose (GLU), triglycerides (TG), total cholesterol (TC), total protein (TP) and albumin (ALB), ultraviolet-visible-near infrared spectroscopy (UV-Vis-NIRS) technology combined with deep neural network (DNN) is firstly proposed in this study. The absorption spectra of 992 human serum are collected in 200-2500 nm. Different spectra preprocessing methods are studied and compared to eliminate interference, baseline offset, and highlight specificity information of biochemical indexes in the raw spectra. Moreover, the competitive adaptive reweighted sampling (CARS) algorithm is utilized to optimally select characteristic wavelengths related to biochemical indexes. A DNN, i.e., 1DCNN-LSTM model is established to quantitatively predict five biochemical indexes using stratified sampling with the training set and testing set divided in 7:3. Compared with the traditional machine learning (ML) and artificial neural network (ANN) algorithms, the results show that the quantitative prediction performances of 1DCNN-LSTM model are significant superior. Root mean square error of prediction (RMSEP) and determination coefficient (R²) of GLU, TG, TC, TP and ALB are 0.39 mmol/L, 0.36 mmol/L, 0.31 mmol/L, 1.26 g/L and 1.28 g/L, 0.97, 0.90, 0.93, 0.96 and 0.93, respectively. Finally, the advantage of UV-Vis-NIRS are verified by comparing with NIRS and UV-Vis alone. Results show that UV-Vis-NIRS combined with DNN can provide new idea and strong technical support in the clinical application of serum biochemical indexes detection.

100 Deals associated with Jiangxi Science & Technology Normal University

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100 Translational Medicine associated with Jiangxi Science & Technology Normal University

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Pipeline

Pipeline Snapshot as of 14 Jun 2025

The statistics for drugs in the Pipeline is the current organization and its subsidiaries are counted as organizations,Early Phase 1 is incorporated into Phase 1, Phase 1/2 is incorporated into phase 2, and phase 2/3 is incorporated into phase 3

Preclinical

2

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