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"Yang, Lei"
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Microenvironment‐Responsive Prodrug‐Induced Pyroptosis Boosts Cancer Immunotherapy
The absence of tumor antigens leads to a low response rate, which represents a major challenge in immune checkpoint blockade (ICB) therapy. Pyroptosis, which releases tumor antigens and damage‐associated molecular patterns (DAMPs) that induce antitumor immunity and boost ICB efficiency, potentially leads to injury when occurring in normal tissues. Therefore, a strategy and highly efficient agent to induce tumor‐specific pyroptosis but reduce pyroptosis in normal tissues is urgently required. Here, a smart tumor microenvironmental reactive oxygen species (ROS)/glutathione (GSH) dual‐responsive nano‐prodrug (denoted as MCPP) with high paclitaxel (PTX) and photosensitizer purpurin 18 (P18) loading is rationally designed. The ROS/GSH dual‐responsive system facilitates the nano‐prodrug response to high ROS/GSH in the tumor microenvironment and achieves optimal drug release in tumors. ROS generated by P18 after laser irradiation achieves controlled release and induces tumor cell pyroptosis with PTX by chemo‐photodynamic therapy. Pyroptotic tumor cells release DAMPs, thus initiating adaptive immunity, boosting ICB efficiency, achieving tumor regression, generating immunological memory, and preventing tumor recurrence. Mechanistically, chemo‐photodynamic therapy and control‐release PTX synergistically induce gasdermin E (GSDME)‐related pyroptosis. It is speculated that inspired chemo‐photodynamic therapy using the presented nano‐prodrug strategy can be a smart strategy to trigger pyroptosis and augment ICB efficiency. A smart tumor microenvironmental reactive oxygen species/glutathione dual‐responsive nano‐prodrug (denoted as MCPP) with high paclitaxel and photosensitizer purpurin 18 loading is designed. Chemo‐photodynamic therapy using the presented nano‐prodrug strategy can be a smart strategy to trigger pyroptosis and augment the efficiency of immune checkpoint blockade therapy.
Journal Article
Flavobacterium algoriphilum sp. nov., Flavobacterium arabinosi sp. nov., Flavobacterium cryoconiti sp. nov., Flavobacterium galactosi sp. nov., Flavobacterium melibiosi sp. nov., and Flavobacterium algoris sp. nov., six novel cold-adapted bacteria isolated from glaciers
Background
Six novel cold-adapted bacteria, LB3P122
T
, LT1R49
T
, ZT3R17
T
, ZT3R25
T
, XS2P12
T
, and GB2R13
T
, were isolated from glaciers on the Tibetan Plateau. This study aimed to characterize their taxonomic status and elucidate their molecular adaptations to cold environments using a polyphasic approach.
Results
All strains were Gram-stain-negative, rod-shaped, and psychrophilic, growing at 0 °C with an optimum at 14–20 °C and at pH values of 6.0–8.0 (optimum pH 7.0). Analysis of the 16S rRNA gene sequences placed their taxonomic positions within the genus
Flavobacterium
, with similarities ranging from 97.2 to 98.4% to species with validly published names. Phylogenetic analysis of the 16S rRNA gene sequences revealed that the six strains formed distinct clades with
Flavobacterium gawalongense
GSP16
T
. Phylogenomic analysis showed that these strains clustered with
Flavobacterium gawalongense
GSP16
T
and exhibited a close relationship with
Flavobacterium urumqiense
CGMCC 1.9230
T
and
Flavobacterium xinjiangense
CGMCC 1.2749
T
. Average nucleotide identity (ANI) values ranging from 82.5 to 93.6% and digital DNA-DNA hybridization (dDDH) values ranging from 26.1 to 51.5% between these strains and their closest relatives were well below the bacterial species delineation thresholds (95–96% ANI, 70% dDDH). The predominant fatty acids were iso-C
15:0
and summed feature 3 (C
16:1
ω
7
c
and/or C
16:1
ω
6
c
). Genomic analysis identified genes associated with cryoprotection, oxidative stress response, cold-shock response, and osmoprotection in these strains, underscoring their adaptations to glacial environments.
Conclusions
Based on polyphasic taxonomic evidence, the strains represent six novel species within the genus
Flavobacterium
, with the proposed names
Flavobacterium algoriphilum
sp. nov. (LB3P122
T
= CGMCC 1.11443
T
= NBRC 114820
T
),
Flavobacterium arabinosi
sp. nov. (LT1R49
T
= CGMCC 1.11617
T
= NBRC 114822
T
),
Flavobacterium cryoconiti
sp. nov. (ZT3R17
T
= CGMCC 1.11707
T
= NBRC 114824
T
),
Flavobacterium galactosi
sp. nov. (ZT3R25
T
= CGMCC 1.11711
T
= NBRC 114825
T
),
Flavobacterium melibiosi
sp. nov. (XS2P12
T
= CGMCC 1.23198
T
= NBRC 114826
T
), and
Flavobacterium algoris
sp. nov. (GB2R13
T
= CGMCC 1.24741
T
= NBRC 114830
T
). These findings enhance our understanding of
Flavobacterium
diversity and cold adaptation in cryospheric ecosystems.
Journal Article
Energy metabolism in health and diseases
Energy metabolism is indispensable for sustaining physiological functions in living organisms and assumes a pivotal role across physiological and pathological conditions. This review provides an extensive overview of advancements in energy metabolism research, elucidating critical pathways such as glycolysis, oxidative phosphorylation, fatty acid metabolism, and amino acid metabolism, along with their intricate regulatory mechanisms. The homeostatic balance of these processes is crucial; however, in pathological states such as neurodegenerative diseases, autoimmune disorders, and cancer, extensive metabolic reprogramming occurs, resulting in impaired glucose metabolism and mitochondrial dysfunction, which accelerate disease progression. Recent investigations into key regulatory pathways, including mechanistic target of rapamycin, sirtuins, and adenosine monophosphate-activated protein kinase, have considerably deepened our understanding of metabolic dysregulation and opened new avenues for therapeutic innovation. Emerging technologies, such as fluorescent probes, nano-biomaterials, and metabolomic analyses, promise substantial improvements in diagnostic precision. This review critically examines recent advancements and ongoing challenges in metabolism research, emphasizing its potential for precision diagnostics and personalized therapeutic interventions. Future studies should prioritize unraveling the regulatory mechanisms of energy metabolism and the dynamics of intercellular energy interactions. Integrating cutting-edge gene-editing technologies and multi-omics approaches, the development of multi-target pharmaceuticals in synergy with existing therapies such as immunotherapy and dietary interventions could enhance therapeutic efficacy. Personalized metabolic analysis is indispensable for crafting tailored treatment protocols, ultimately providing more accurate medical solutions for patients. This review aims to deepen the understanding and improve the application of energy metabolism to drive innovative diagnostic and therapeutic strategies.
Journal Article
A review on medical imaging synthesis using deep learning and its clinical applications
This paper reviewed the deep learning‐based studies for medical imaging synthesis and its clinical application. Specifically, we summarized the recent developments of deep learning‐based methods in inter‐ and intra‐modality image synthesis by listing and highlighting the proposed methods, study designs, and reported performances with related clinical applications on representative studies. The challenges among the reviewed studies were then summarized with discussion.
Journal Article
Array Sensor Output Signal Detection System Signal Conditioning Circuit Design
The signal output by the array sensor is generally very weak, with a large dynamic range and a wide range of signal frequencies. In order to solve the problem of accurate measurement of weak signals with wide frequency and large dynamic range, this paper proposes a design method of sub-band filtering and variable gain amplifying circuit based on the analog switch, divides the signal into four frequency bands, and designs four groups of second-order voltage control filter, and adjust the magnification for different frequency signals, and only need to switch the corresponding resistance and capacitance to realize the switching of signal processing circuits of different frequency bands, which greatly optimizes the circuit structure. In order to reduce the interference in the transmission process, a single-ended differential circuit is designed to transmit the processed signal to the subsequent acquisition system for acquisition. After the simulation test, the signal conditioning circuit can effectively improve the signal-to-noise ratio of the detection signal and improve the measurement accuracy.
Journal Article
Heritable transgene-free genome editing in plants by grafting of wild-type shoots to transgenic donor rootstocks
Generation of stable gene-edited plant lines using clustered regularly interspaced short palindromic repeats (CRISPR)–CRISPR-associated protein 9 (Cas9) requires a lengthy process of outcrossing to eliminate CRISPR–Cas9-associated sequences and produce transgene-free lines. We have addressed this issue by designing fusions of
Cas9
and guide RNA transcripts to tRNA-like sequence motifs that move RNAs from transgenic rootstocks to grafted wild-type shoots (scions) and achieve heritable gene editing, as demonstrated in wild-type
Arabidopsis thaliana
and
Brassica rapa
. The graft-mobile gene editing system enables the production of transgene-free offspring in one generation without the need for transgene elimination, culture recovery and selection, or use of viral editing vectors. We anticipate that using graft-mobile editing systems for transgene-free plant production may be applied to a wide range of breeding programs and crop plants.
Gene-edited plants free of CRISPR-associated sequences are generated by grafting.
Journal Article
A preliminary study of rare-metal mineralization in the Himalayan leucogranite belts, South Tibet
The Himalayan leucogranite occurs as two extensive（〉1000 km） E-W trending belts on the Tibetan Plateau with the unique features. The leucogranite comprised biotite granite, two-mica/muscovite granite, tourmaline granite and garnet granite, which have been identified in previous studies, as well as albite granite and granitic pegmatite that were identified in this investigation. Fifteen leucogranite plutons were studied and 12 were found to contain rare-metal bearing minerals such as beryl（the representative of Be mineralization）, columbite-group minerals, tapiolite, pyrochlore-microlite, fergusonite, Nb-Ta rutile（the representative of Nb-Ta mineralization）, and cassiterite（the representative of Sn mineralization） mainly based on the field trip,microscope observation and microprobe analysis. The preliminary result shows that the Himalayan leucogranite is commonly related to the rare-metal mineralization and warrants future investigation. Further exploration and intensive research work is important in determining the rare-metal resource potential of this area.
Journal Article
Deep eutectic solvents (DESs) for cellulose dissolution: a mini-review
Deep eutectic solvents (DESs), which are a novel class of sustainable designer solvents, have attracted considerable attentions in the field of cellulose chemistry. Due to their low cost and analogous physico-chemical properties to ionic liquids, DESs are expected to be alternative solvents for dissolving cellulose. However, at present, the solubility of cellulose in DESs is much lower than in most ionic liquids. In this mini-review, we briefly summarize the current state of knowledge about cellulose dissolution in DESs. By comparing with similar solvents, it was found that the components of current DESs are usually involved in hydrogen bond interaction making difficult their interaction with the hydrogen bond network of cellulose. Accordingly, we propose a strategy that the components which have good hydrogen bond accepting ability, such as Cl
-
, OAc
-
, HCOO
-
, (MeO)
2
PO
2
-
, morpholine and imidazole, are promising choices to form DESs for cellulose dissolution. Ultrasound-assisted treatment and adding a surfactant are effective ways to promote cellulose solubility by enhancing the permeability of DESs.
Journal Article
Application of improved GAN-LSTM-based fake face detection technique in electronic data forensics
This study proposes a detection method based on an improved GAN-LSTM fusion model to address the challenges of insufficient feature extraction and poor robustness in face forgery detection during electronic data forensics. Core innovations include designing a composite LSTM module that integrates multiple LSTM units to enhance time feature processing capabilities. In addition, a relative average discriminator is introduced to optimize the balance of adversarial training. On the CelebA benchmark dataset, the model achieved a detection accuracy of 97.26% (significantly higher than the baseline model’s 92.14%), reduced inference time to 1.43 s, and reached an mean average precision (mAP) of 97.56%. During a 90-hour real-world simulation test, the model achieved a detection accuracy rate of 96.84%, with only 4.57% false positives. This performance surpassed that of mainstream comparison methods in terms of both computational efficiency and accuracy. This research demonstrates that the proposed method can efficiently identify complex forged faces. It provides a high-precision, low-cost solution for electronic data forensics, which is significant in preventing the abuse of forgery techniques. This approach provides a high-precision, low-computational-cost solution for forged facial recognition in digital forensics, demonstrating significant application value for safeguarding digital security.
Journal Article