Response of nitrifiers to gradually increasing pH conditions in a membrane nitrification bioreactor: Microbial dynamics and alkali-resistant mechanism.

Nitrification and nitrifiers are pH-sensitive especially under the alkaline environment in the activated sludge system. However, it is unclear how nitrifiers and nitrification respond to long-term alkaline environment. This study employed a continuous flow membrane nitrification bioreactor to investigate the dynamics of nitrification efficiency and microbial community adaptation under a 320-day alkaline operation. Results showed that activated sludge adapted remarkably to a progressive increase in pH from 7.5 to 10.0, achieving robust nitrification with average ammonia removal efficiencies of 96.6 ± 2.2%. Subsequently, an integrated alkali-resistant mechanism of nitrifiers was proposed. Specifically, under the long-term operation of pH 10.0, certain bacteria secreted enhanced extracellular acidic polysaccharides (i.e., up to 10.95 ± 0.27 mg·g-1 MLVSS in soluble extracellular polymeric substances (EPS)) and acidic organic compounds (e.g., humic acids increased by 1.47-fold in tightly bounded EPS) to neutralize external alkalinity. Moreover, significant enrichments in both the ammonia oxidizing bacteria Nitrosomonas (by 1.3%) and the nitrite oxidizing bacteria Nitrospira (by 5.4%) were observed in a 170-day operation of pH 10.0 condition. Meanwhile, norank_f__JG30-KF-CM45 (2.0%) and Rhodobacter (0.9%) also contributed to ammonia removal at pH 10.0. On the cellular-level, bacteria enabled to maintain intracellular pH stabilization primarily through cation/proton antiporters, evidenced by significant increases in NhaA, TrkA and KefB activities by 98.0%, 151.7% and 115.2%, respectively. A 43.1% increase in carbonic anhydrase activity also facilitated consumption of aqueous OH- ions through biomineralization, leading to CaCO3 deposition on microbial surface. These findings further enhanced understandings of physiological adaptation of nitrifiers in the long-term alkaline activated sludge system.

Nanozymes in cancer immunotherapy: metabolic disruption and therapeutic synergy.

Over the past decade, there has been a growing emphasis on investigating the role of immunotherapy in cancer treatment. However, it faces challenges such as limited efficacy, a diminished response rate, and serious adverse effects. Nanozymes, a subset of nanomaterials, demonstrate boundless potential in cancer catalytic therapy for their tunable activity, enhanced stability, and cost-effectiveness. By selectively targeting the metabolic vulnerabilities of tumors, they can effectively intensify the destruction of tumor cells and promote the release of antigenic substances, thereby eliciting immune clearance responses and impeding tumor progression. Combined with other therapies, they synergistically enhance the efficacy of immunotherapy. Hence, a large number of metabolism-regulating nanozymes with synergistic immunotherapeutic effects have been developed. This review summarizes recent advancements in cancer immunotherapy facilitated by nanozymes, focusing on engineering nanozymes to potentiate antitumor immune responses by disturbing tumor metabolism and performing synergistic treatment. The challenges and prospects in this field are outlined. We aim to provide guidance for nanozyme-mediated immunotherapy and pave the way for achieving durable tumor eradication.

Heavy-atom-free BODIPY dendrimer: utilizing the spin-vibronic coupling mechanism for two-photon photodynamic therapy in zebrafish.

In this study, the heavy-atom-free BODIPY dendrimer TM4-BDP was synthesized for near-infrared photodynamic therapy, and was composed of a triphenylamine-BODIPY dimer and four 1-(2-morpholinoethyl)-1H-indole-3-ethenyl groups. The TM4-BDP could achieve near-infrared photodynamic therapy through two different photosensitive pathways, which include one-photon excitation at 660 nm and two-photon excitation at 1000 nm. In the one-photon excitation pathway, the TM4-BDP could generate singlet oxygen and superoxide radicals under 660 nm illumination. In addition, the one-photon PDT experiment in human nasopharyngeal carcinoma (CNE-2) cells also indicated that the TM4-BDP could specifically accumulate in lysosomes and show great cell phototoxicity with an IC50 of 22.1 µM. In the two-photon excitation pathway, the two-photon absorption cross-section at 1030 nm of TM4-BDP was determined to be 383 GM, which means that it could generate reactive oxygen species (ROS) under 1000 nm femtosecond laser excitation. Moreover, the two-photon PDT experiment in zebrafish also indicated the TM4-BDP could be used for two-photon fluorescence imaging and two-photon induced ROS generation in biological environments. Furthermore, in terms of the ROS generation mechanism, the TM4-BDP employed a novel spin-vibronic coupling intersystem crossing (SV-ISC) process for the mechanism of ROS generation and the femtosecond transient absorption spectra indicated that this novel SV-ISC mechanism was closely related to its charge transfer state lifetime. These above experiments of TM4-BDP demonstrate that the dendrimer design is an effective strategy for constructing heavy-atom-free BODIPY photosensitizers in the near-infrared region and lay the foundation for two-photon photodynamic therapy in future clinical trials.

Prognosis Prediction of Sudden Sensorineural Hearing Loss Using Ensemble Artificial Intelligence Learning Models.

OBJECTIVE: We used simple variables to construct prognostic prediction ensemble learning models for patients with sudden sensorineural hearing loss (SSNHL). STUDY DESIGN: Retrospectively study. SETTING: Tertiary medical center. PATIENTS: 1,572 patients with SSNHL. INTERVENTION: Prognostic. MAIN OUTCOME MEASURES: We selected four variables, namely, age, days after onset of hearing loss, vertigo, and type of hearing loss. We also compared the accuracy between different ensemble learning models based on the boosting, bagging, AdaBoost, and stacking algorithms. RESULTS: We enrolled 1,572 patients with SSNHL; 73.5% of them showed improving and 26.5% did not. Significant between-group differences were noted in terms of age ( p = 0.011), days after onset of hearing loss ( p < 0.001), and concurrent vertigo ( p < 0.001), indicating that the patients who showed improving to treatment were younger and had fewer days after onset and fewer vertigo symptoms. Among ensemble learning models, the AdaBoost algorithm, compared with the other algorithms, achieved higher accuracy (82.89%), higher precision (86.66%), a higher F1 score (89.20), and a larger area under the receiver operating characteristics curve (0.79), as indicated by test results of a dataset with 10 independent runs. Furthermore, Gini scores indicated that age and days after onset are two key parameters of the predictive model. CONCLUSIONS: The AdaBoost model is an effective model for predicting SSNHL. The use of simple parameters can increase its practicality and applicability in remote medical care. Moreover, age may be a key factor influencing prognosis.

Proteomic Profiling of Serum Extracellular Vesicles Identifies Diagnostic Signatures and Therapeutic Targets in Breast Cancer.

Analysis of extracellular vesicles (EV) is a promising noninvasive liquid biopsy approach for breast cancer detection, prognosis, and therapeutic monitoring. A comprehensive understanding of the characteristics and proteomic composition of breast cancer-specific EVs from human samples is required to realize the potential of this strategy. In this study, we applied a mass spectrometry-based, data-independent acquisition proteomic approach to characterize human serum EVs derived from patients with breast cancer (n = 126) and healthy donors (n = 70) in a discovery cohort and validated the findings in five independent cohorts. Examination of the EV proteomes enabled the construction of specific EV protein classifiers for diagnosing breast cancer and distinguishing patients with metastatic disease. Of note, TALDO1 was found to be an EV biomarker of distant metastasis of breast cancer. In vitro and in vivo analysis confirmed the role of TALDO1 in stimulating breast cancer invasion and metastasis. Finally, high-throughput molecular docking and virtual screening of a library consisting of 271,380 small molecules identified a potent TALDO1 allosteric inhibitor, AO-022, which could inhibit breast cancer migration in vitro and tumor progression in vivo. Together, this work elucidates the proteomic alterations in the serum EVs of breast cancer patients to guide the development of improved diagnosis, monitoring, and treatment strategies. Significance: Characterization of the proteomic composition of circulating extracellar vesicles in breast cancer patients identifies signatures for diagnosing primary and metastatic tumors and reveals tumor-promoting cargo that can be targeted to improve outcomes.

Porous Agarose Layered Magnetic Graphene Oxide Nanocomposite for Virus RNA Monitoring in Wastewater.

The detection of virus RNA in wastewater has been established as a valuable method for monitoring Coronavirus disease 2019. Carbon nanomaterials hold potential application in separating virus RNA owing to their effective adsorption and extraction capabilities. However, carbon nanomaterials have limited separability under homogeneous aqueous conditions. Due to the stabilities in their nanostructure, it is a challenge to efficiently immobilize them onto magnetic beads for separation. Here, we develop a porous agarose layered magnetic graphene oxide (GO) nanocomposite that is prepared by agglutinating ferroferric oxide (Fe3O4) beads and GO with agarose into a cohesive whole. With an average porous size of approximately 500 nm, the porous structure enables the unhindered entry of virus RNA, facilitating its interaction with the surface of GO. Upon the application of a magnetic field, the nucleic acid can be separated from the solution within a few minutes, achieving adsorption efficiency and recovery rate exceeding 90% under optimized conditions. The adsorbed nucleic acid can then be preserved against complex sample matrix for 3 days, and quantitatively released for subsequent quantitative reverse transcription polymerase chain reaction (RT-qPCR) detection. The developed method was successfully utilized to analyze wastewater samples obtained from a wastewater treatment plant, detecting as few as 10 copies of RNA molecules per sample. The developed aMGO-RT-qPCR provides an efficient approach for monitoring viruses and will contribute to wastewater-based surveillance of community infections.

Hydrogel Nanoparticles Enable Nucleation Barrier Regulation and Ion Anchoring as an Alternative Pathway for Monosodium Urate Monohydrate Crystallization Control.

Gout flare-up, commonly resulting from monosodium urate monohydrate (MSUM) crystallization, has led to painful inflammatory arthritis among hundreds of millions of people. Herein, a kind of hydrogel nanoparticles (HNPs) with specific properties was developed, aimed at providing a promising pathway for MSUM crystallization control. The experimental and molecular dynamics simulation results synchronously indicate that the fabricated HNPs achieve efficient inhibition of MSUM crystallization governed by the mechanism of "host-guest interaction" even under very low-dose administration. HNPs as the host dispersed in the hyperuricemic model effectively lift the relative heterogeneous nucleation barrier of the MSUM crystal and hinder solute aggregation with strong electronegativity and hydrophobicity. The initial appearance of MSUM crystals was then delayed from 94 to 334 h. HNPs as the guest on the surface of the formed crystal can decelerate the growth rate by anchoring ions and occupying the active sites on the surface, and the terminal yield of the MSUM crystal declined to less than 1% of the control group. The good biocompatibility of HNPs (cell viability > 94%) renders it possible for future clinical applications. This study can guide the rational design of inhibitory nanomaterials and the development of their application in the control of relevant pathological crystallization.

Effects of chronic unpredictable mild stress on gut microbiota and fecal amino acid and short-chain fatty acid pathways in mice.

Depression is a serious disease that has a significant impact on social functioning. However, the exact causes of depression are still not fully understood. Therefore, it is necessary to explore new pathways leading to depression. In this study, we used 16 S rDNA to examine changes in gut microbiota and predict related pathways in depression-like mice. Additionally, we employed liquid chromatography-mass spectrometry (LC-MS) to identify changes in amino acids and gas chromatography-mass spectrometry (GC-MS) to identify changes in short-chain fatty acids (SCFAs) in fecal samples. We conducted Pearson/Spearman correlation analysis to investigate the associations between changes in amino acids/SCFAs and behavioral outcomes. The 16 S rDNA sequencing revealed significant alterations in gut microbiota at the phylum and genus levels in mice subjected to chronic unpredictable mild stress (CUMS). The relative abundances of Bacteroidetes, Proteobacteria, Bacteroides, and Alloprevotella were increased, while Firmicutes, Verrucomicrobia, Actinobacteria, Lactobacillus, Akkermansia, Lachnospirillum, and Enterobacter were decreased in the CUMS mice. We used PICRUSt software to annotate the kyoto encyclopedia of genes and genomes (KEGG) pathway function related to depression-like behavior in mice. Our analysis identified sixty functional pathways associated with the gut microbiota of mice exhibiting depression-like behavior. In the amino acid concentration analysis, we observed decreased levels of hydroxyproline and tryptophan, and increased levels of alanine in CUMS mice. In the SCFAs concentration assay, we found decreased levels of butyric acid and valeric acid, and increased levels of acetic acid in CUMS mice. Some of these changes were significantly correlated with depressive-like behaviors. Our study contributes to the understanding of the mechanism of the gut-brain axis in the occurrence and development of depression.

Developing a machine learning model for accurate nucleoside hydrogels prediction based on descriptors.

Supramolecular hydrogels derived from nucleosides have been gaining significant attention in the biomedical field due to their unique properties and excellent biocompatibility. However, a major challenge in this field is that there is no model for predicting whether nucleoside derivative will form a hydrogel. Here, we successfully develop a machine learning model to predict the hydrogel-forming ability of nucleoside derivatives. The optimal model with a 71% (95% Confidence Interval, 0.69-0.73) accuracy is established based on a dataset of 71 reported nucleoside derivatives. 24 molecules are selected via the optimal model external application and the hydrogel-forming ability is experimentally verified. Among these, two rarely reported cation-independent nucleoside hydrogels are found. Based on their self-assemble mechanisms, the cation-independent hydrogel is found to have potential applications in rapid visual detection of Ag+ and cysteine. Here, we show the machine learning model may provide a tool to predict nucleoside derivatives with hydrogel-forming ability.

Confined liquid crystallization governed by electric field for API crystal polymorphism screening and massive preparation.

Active pharmaceutical ingredients (APIs) crystal preparation is a significant issue for the pharmaceutical development attributed to the effect on anti-inflammatory, anti-bacteria, and anti-viral, etc. While, the massive preparation of API crystal with high polymorphism selectivity is still a pendent challenge. Here, we firstly proposed a criterion according to the molecular aggregation, molecular orientation, and hydrogen bond energy between INA molecules from molecular dynamics (MD) simulations, which predicted the hydrogen bond architecture in crystal under different electric fields, hinting the recognition of crystal polymorphism. Then, an electric field governing confined liquid crystallization was constructed to achieve the INA crystal polymorphism screening relying on the criterion. Further, magnifying confined liquid volume by 5000 times from 1.0 µL to 5.0 mL realized the massive preparation of INA crystal with high polymorphic purity (>98.4%), giving a unique pathway for crystal engineering and pharmaceutical industry on the development of innovative and generic API based drugs.

Normal Weight Central Obesity is a Poor Prognostic Factor for Sudden Sensorineural Hearing Loss.

OBJECTIVES: To investigate the role of normal weight central obesity (NWCO) in the prognosis of sudden sensorineural hearing loss (SSNHL). METHODS: We retrospectively investigated 807 cases of SSNHL from January of 2008 to August of 2019 from the Department of Otorhinolaryngology at Kaohsiung Medical University Hospital in southern Taiwan. We analyzed the association between overweight and obesity, NWCO, and the prognosis of SSNHL. The demographic and clinical characteristics, audiometry results, and outcomes were also reviewed. RESULTS: The nonobese (body mass index [BMI] < 24 kg/m2) and overweight and obese groups (BMI ≥ 24 kg/m2) comprised 343 (42.50%) and 464 (57.50%) patients, respectively. The favorable prognosis rates in the nonobese and the overweight and obese groups were 45.48% and 45.91%, respectively, without a significant difference (P = .9048). Multivariate logistic regression revealed that BMI (adjusted odds ratio [aOR] = 1.00, 95% CI = 0.948-1.062, P = .9165) was not significantly associated with SSNHL recovery. The normal weight noncentral obesity (NWNCO) and NWCO groups comprised 266 (77.55%) and 77 (22.45%) patients, respectively, and had favorable prognosis rates of 48.50% and 35.06%, respectively. The difference between the groups was significant (P = .0371). Multivariate logistic regression analysis revealed that NWCO (aOR = 2.51, 95% CI = 1.292-5.019, P = .0075) was significantly associated with SSNHL recovery. CONCLUSIONS: NWCO may significantly affect the prognosis of SSNHL.

Identification of genes related to growth and amino acid metabolism from the transcriptome profile of the liver of growing laying hens.

The growing period is a critical period for the growth and development of hens and affects their production performance during the laying period. During the early stage of growing, bone and muscle growth is rapid, making it necessary to provide sufficient amino acids (AA) to support the growth and development of laying hens. In this experiment, RNA-Sequencing (RNA-Seq) was applied to compare the liver tissues from 6- to 12-wk-old growing laying hens to identify candidate genes related to growth and AA transport and metabolism. In the liver tissues, 596 differentially expressed genes (DEG) were identified, of which 424 genes were up-regulated and 172 were down-regulated. Through enrichment analysis and DEGs analysis, some DEGs and pathways related to AA transport and metabolism were identified. Additionally, there were significantly increased activities in the liver of glutamate dehydrogenase (GDH), glutamic oxaloacetic transaminase (GOT), and glutamate pyruvate transaminase (GPT). Meanwhile, the level of serum insulin-like growth factor binding protein-5 (IGFBP-5) significantly elevated, and insulin-like growth factor-1 (IGF-1) levels significantly reduced at 12 wk compared to 6 wk. The AA contents in the breast muscle were not significantly altered, while the levels of the free AA in the serum underwent significant changes. This study discovered that the transport and metabolism of AAs in growing laying hens at different ages changed, which influenced the growth and development of growing laying hens. This contributes to future research on the mechanisms of growth and AA metabolism during the growing period of laying hens.

Predictive Factors and Audiometric Outcome Comparison Between Titanium Prosthesis and Autologous Incus in Traumatic Ossicular Injury.

OBJECTIVES: To investigate the etiology and ossicular pathology of traumatic ossicular injury in Taiwan and examine the hearing outcomes and predictive factors between the titanium prosthesis and autologous incus groups. METHODS: We retrospectively analyzed patients with traumatic ossicular injury from 2011 to 2020 in Taiwan. Patients were divided into the titanium or autologous group according to the surgical materials used. The audiometric outcomes and predictive factors of ossiculoplasty were analyzed between groups. RESULTS: Twenty patients with ossicular chain discontinuity were enrolled (8 in the titanium group and 12 in the autologous group). The postoperative hearing threshold (26.6 ± 8.9 dB) and air-bone gap (10.3 ± 5.6 dB) improved significantly compared with the preoperative hearing threshold (50.7 ± 13.3 dB) and air-bone gap (29.9 ± 11.0 dB). The improvements in the hearing threshold and air-bone gap were not significantly different between the titanium and autologous groups. Our patients presented an improvement in hearing restoration with 65% closure of the air-bone gap in 0 to 10 dB range and 30% in 11 to 20 dB range, without sensorineural hearing loss during surgery. Univariate regression analysis revealed that vertigo, benign paroxysmal positional vertigo, and temporal bone fracture may serve as negative factors influencing the air-bone gap gain. CONCLUSIONS: Ossiculoplasty with both titanium prosthesis and autologous materials demonstrated favorable hearing recovery in traumatic ossicular injury. Vertigo, benign paroxysmal positional vertigo, and temporal bone fracture may serve as negative predictive factors of the hearing benefit after surgery.

Artificial intelligence in serum protein electrophoresis: history, state of the art, and perspective.

Serum protein electrophoresis (SPEP) is a valuable laboratory test that separates proteins from the blood based on their electrical charge and size. The test can detect and analyze various protein abnormalities, and the interpretation of graphic SPEP features plays a crucial role in the diagnosis and monitoring of conditions, such as myeloma. Furthermore, the advancement of artificial intelligence (AI) technology presents an opportunity to enhance the organization and optimization of analytical procedures by streamlining the process and reducing the potential for human error in SPEP analysis, thereby making the process more efficient and reliable. For instance, AI can assist in the identification of protein peaks, the calculation of their relative proportions, and the detection of abnormalities or inconsistencies. This review explores the characteristics and limitations of AI in SPEP, and the role of standardization in improving its clinical utility. It also offers guidance on the rational ordering and interpreting of SPEP results in conjunction with AI. Such integration can effectively reduce the time and resources required for manual analysis while improving the accuracy and consistency of the results.

Protective effect and possible mechanisms of geniposide for ischemia-reperfusion injury: A systematic review with meta-analysis and network pharmacology of preclinical evidence.

Background: Geniposide, as a pharmacologically bioactive component, is derived from a classic and common Chinese herb, Gardenia jasminoides Ellis. Geniposide has been shown to be effective for treating I/R injury in recent studies. Current effectively pharmaceutical treatments are scarce, and treatment based on geniposide may become a novel option. As far as we know, this research is the initial systematic evaluation of the protective effects of geniposide in I/R injury. Aim of the study: This study is engrossed in evaluating the mechanism of action of geniposide in I/R injury through a preclinical systematic review with meta-analysis and network pharmacology. Materials and methods: We built a systematic review which provided a view of effect and mechanism of geniposide for I/R injury. Based on seven databases, an open-ended search from their inception to August 31st, 2022, was conducted. Animal studies on the effects of geniposide in I/R injury were considered. The data was analyzed using Review Manager 5.3, and bias was assessed using the CAMARADES 10-item scale. 13 articles including 279 animals were selected finally. And network pharmacology was joined to elucidate the mechanism. Results: According to the meta-analysis, in I/R injury, geniposide can attenuate cardiomyocytes viability and the size of MI, decrease the volume of cerebral infraction and neurological score, decrease serum ALT and AST activity, and downregulated serum Cr and BUN. The review found that geniposide protects against I/R injury by inhibiting apoptosis, oxidation, inflammation and improvement of autophagy and mitochondrial respiration, which is consistent with the results of the network pharmacology screening. Conclusion: This preclinical systematic review including meta-analysis and network pharmacology, which was the first one summarizing the relationship between geniposide and ischemia diseases, shows a novel therapy for I/R injury and appears an enticing implication of geniposide in I/R injury, and further research is looked forward. Given the restricted quantity of included researches and the unclear risk of bias of the studies, we should interpret the results with caution.

SUGAN: A Stable U-Net Based Generative Adversarial Network.

As one of the representative models in the field of image generation, generative adversarial networks (GANs) face a significant challenge: how to make the best trade-off between the quality of generated images and training stability. The U-Net based GAN (U-Net GAN), a recently developed approach, can generate high-quality synthetic images by using a U-Net architecture for the discriminator. However, this model may suffer from severe mode collapse. In this study, a stable U-Net GAN (SUGAN) is proposed to mainly solve this problem. First, a gradient normalization module is introduced to the discriminator of U-Net GAN. This module effectively reduces gradient magnitudes, thereby greatly alleviating the problems of gradient instability and overfitting. As a result, the training stability of the GAN model is improved. Additionally, in order to solve the problem of blurred edges of the generated images, a modified residual network is used in the generator. This modification enhances its ability to capture image details, leading to higher-definition generated images. Extensive experiments conducted on several datasets show that the proposed SUGAN significantly improves over the Inception Score (IS) and Fréchet Inception Distance (FID) metrics compared with several state-of-the-art and classic GANs. The training process of our SUGAN is stable, and the quality and diversity of the generated samples are higher. This clearly demonstrates the effectiveness of our approach for image generation tasks. The source code and trained model of our SUGAN have been publicly released.

Effects of Methyl Sulfonyl Methane and Selenium Yeast on Fatty Liver Syndrome in Laying Hens and Their Biological Mechanisms.

The purpose of this study was to explore the effects of MSM and Se-Y on FLS in laying hens during the late peak laying period and the underlying biological mechanisms. Therefore 240 55-week-old Jing-fen No. 6 laying hens were randomly divided into five groups, with eight replicates in each group and six laying hens in each replicate. The hens were fed a basal diet (Control) and diets supplemented with 350 and 700 mg/kg MSM and 25 and 50 mg/kg Se-Y, respectively, for four weeks. The results showed that MSM and Se-Y had no significant effects on the performance of laying hens. With the increasing dosage of MSM and Se-Y, the symptoms of liver steatosis in laying hens were reduced, and MSM and Se-Y could significantly reduce the content of malondialdehyde (MDA) in serum and liver (p < 0.05) and increase the contents of total superoxide dismutase (T-SOD) and glutathione peroxidase (GPX) in serum and liver (p < 0.05). The RNA-seq results showed that 700 mg/kg MSM significantly downregulated the expression levels of the ATP5I, ATP5G1, CYCS, and UQCRQ genes in the liver, and 50 mg/kg Se-Y significantly downregulated the expression levels of MAPK10, SRC, BMP2, and FGF9 genes in the liver. In conclusion, dietary supplementation with MSM and Se-Y can effectively reduce the FLS of laying hens in the late peak laying period and increase their antioxidant capacity. The underlying biological mechanism may be related to the downregulation of genes involved in liver oxidative phosphorylation and inflammation-related pathways.

A type I and II compatible vinyl-pyridine modified BODIPY dimer photosensitizer for photodynamic therapy in A-549 cells.

In this paper, the vinyl-pyridine group was used to modify the BODIPY dimer photosensitizer (T-BDP2) to obtain a VP-BDP2 photosensitizer. Compared with the T-BDP2 photosensitizer, the VP-BDP2 photosensitizer could work under pure water conditions, the singlet oxygen yield was increased from 9.38% to 22.2%, the charge transfer rate was increased from about 30 ps to about 10 ps, and the red emission was enhanced in fluorescence imaging. In addition, the VP-BDP2 photosensitizer could also generate the superoxide radical (O2˙-) under pure water conditions. The ROS generation mechanism of the VP-BDP2 photosensitizer was considered to be the spin-orbit charge-transfer intersystem crossing (SOCT-ISC) mechanism, which was verified by fs-transient absorption spectra and theoretical calculation. In the photodynamic therapy of A-549 cells, the VP-BDP2 photosensitizers could generate singlet oxygen and superoxide radicals (O2˙-) under biological conditions, and showed high phototoxicity with the IC50 value at 12.1 µM under light at 525 nm. Additionally, the multiple dipolar configuration meant that the VP-BDP2 photosensitizer could be used in two-photon fluorescence zebrafish imaging under 800 nm excitation, which sets the stage for future two-photon photodynamic therapy.

Effect of laser shock peening on microstructure and mechanical properties of laser cladding 30CrMnSiNi2A high-strength steel.

The effect of laser shock peening (LSP) on the microhardness and tensile properties of laser cladding (LC) 30CrMnSiNi2A high-strength steel was studied. After LSP, the microhardness of the cladding zone reached approximately 800 HV0.2, which was 25% higher than that of the substrate, while the cladding zone without LSP had an approximately 18% increase in its microhardness. Two strengthening processes were designed: groove LSP + LC + surface LSP versus LC + surface LSP. The former's tensile strength and yield strength were less than 10% weaker than those of forged materials, which is the best mechanical property recovery found in LC samples. The microstructural characteristics of the LC samples were analysed by scanning electron microscopy (SEM) and electron backscatter diffraction. Under the action of the laser-induced shock wave, the grain size of the LC sample surface was refined, the low-angle grain boundaries on the surface layer increased significantly, and the austenite grain length was reduced from 30-40 µm in the deep layer to 4-8 µm in the surface layer. In addition, LSP modulated the residual stress field, hence preventing the weakening effect of the LC process's thermal stress on the components' mechanical properties.