Fabrication of an Fe-Doped ZIF-67 Derived Magnetic Fe/Co/C Composite for Effective Removal of Congo Red.

The dyes in printing and dyeing wastewater are harmful to the human body and the environment. It is essential to develop practical and effective adsorbents to deal with them. In this study, an Fe-doped, ZIF-67 derived Fe/Co/C composite material with strong magnetism was successfully synthesized. The effects of pH, initial concentration, and adsorption time on the properties of the adsorbent were investigated. To further improve the removal efficiency and enhance the practicality, potassium peroxymonosulfate (PMS) was added to the system due to its Fenton-like effect. Then, an Fe/Co/C composite was used with PMS to remove Congo red (CR) with a 98% removal of 250 mg·L-1. Moreover, for its high saturation magnetization of 85.4 emu·g-1, the Fe/Co/C composite can be easily recovered by applying a magnetic field, solving the problem that powdery functional materials are difficult to recover and, thus, avoiding secondary pollution. Furthermore, since the composite material was doped before carbonization, this synthetic strategy is flexible and the required metal elements can be added at will to achieve different purposes. This study demonstrates that this Fe-doped, ZIF-67 derived magnetic material has potential application prospects for dye adsorption.

Drivers of coastal benthic communities in a complex environmental setting.

Analyzing the environmental factors affecting benthic communities in coastal areas is crucial for uncovering key factors that require conservation action. Here, we collected benthic and environmental (physical-chemical-historical and land-based) data for 433 transects in Taiwan. Using a k-means approach, five communities dominated by crustose coralline algae, turfs, stony corals, digitate, or bushy octocorals were first delineated. Conditional random forest models then identified physical, chemical, and land-based factors (e.g., light intensity, nitrite, and population density) relevant to community delineation and occurrence. Historical factors, including typhoons and temperature anomalies, had only little effect. The prevalent turf community correlated positively with chemical and land-based drivers, which suggests that anthropogenic impacts are causing a benthic homogenization. This mechanism may mask the effects of climate disturbances and regional differentiation of benthic assemblages. Consequently, management of nutrient enrichment and terrestrial runoff is urgently needed to improve community resilience in Taiwan amidst increasing challenges of climate change.

Stochastic processes shape microbial community assembly in biofilters: Hidden role of rare taxa.

Stochastic and deterministic processes are the major themes governing microbial community assembly; however, their roles in bioreactors are poorly understood. Herein, the mechanisms underlying microbial assembly and the effect of rare taxa were studied in biofilters. Phylogenetic tree analysis revealed differences in microbial communities at various stages. Null model analysis showed that stochastic processes shaped the community assembly, and deterministic processes emerged only in the inoculated activated sludge after domestication. This finding indicates the dominant role of stochastic factors (biofilm formation, accumulation, and aging). The Sloan neutral model corroborated the advantages of stochastic processes and mainly attributed these advantages to rare taxa. Cooccurrence networks revealed the importance of rare taxa, which accounted for more than 85% of the keystones. Overall, these results provide good foundations for understanding community assembly, especially the role of rare taxa, and offer theoretical support for future community design and reactor regulation.

Biological optimization for hybrid proton-photon radiotherapy.

OBJECTIVE: Hybrid proton-photon radiotherapy (RT) is a cancer treatment option to broaden access to proton RT. Additionally, with a refined treatment planning method, hybrid RT has the potential to offer superior plan quality compared to proton-only or photon-only RT, particularly in terms of target coverage and sparing organs-at-risk (OAR), when considering robustness to setup and range uncertainties. However, there is a concern regarding the underestimation of the biological effect of protons on OAR, especially those in close proximity to targets. This study seeks to develop a hybrid treatment planning method with biological dose optimization, suitable for clinical implementation on existing proton and photon machines, with each photon or proton treatment fraction delivering a uniform target dose. Approach: The proposed hybrid biological dose optimization method optimizes proton and photon plan variables, along with the number of fractions, minimizing biological dose to OAR and surrounding normal tissues. Hybrid plans are designed to be deliverable separately and robustly on existing proton and photon machines, with enforced uniform target dose constraints for proton and photon fraction doses. Probabilistic formulation is utilized for robust optimization of setup and range uncertainties for protons and photons. The nonconvex optimization problem, arising from minimum monitor unit (MMU) constraint and dose-volume histogram (DVH) constraints, is solved using an iterative convex relaxation method. Main results: Hybrid planning with biological dose optimization effectively eliminated hot spots of biological dose, particularly in normal tissues surrounding the target, outperforming proton-only planning. It also provided superior overall plan quality and OAR sparing compared to proton-only or photon-only planning strategies. Significance: This study presents a novel hybrid biological treatment planning method capable of generating plans with minimized biological hot spots, superior plan quality to proton-only or photon-only plans, and clinical deliverability on existing proton and photon machines, separately and robustly. .

Comprehensive clinical application analysis of artificial intelligence-enabled electrocardiograms for screening multiple valvular heart diseases.

BACKGROUND: Valvular heart disease (VHD) is becoming increasingly important to manage the risk of future complications. Electrocardiographic (ECG) changes may be related to multiple VHDs, and (AI)-enabled ECG has been able to detect some VHDs. We aimed to develop five deep learning models (DLMs) to identify aortic stenosis, aortic regurgitation, pulmonary regurgitation, tricuspid regurgitation, and mitral regurgitation. METHODS: Between 2010 and 2021, 77,047 patients with echocardiography and 12-lead ECG performed within 7 days were identified from an academic medical center to provide DLM development (122,728 ECGs), and internal validation (7,637 ECGs). Additional 11,800 patients from a community hospital were identified to external validation. The ECGs were classified as with or without moderate-to-severe VHDs according to transthoracic echocardiography (TTE) records, and we also collected the other echocardiographic data and follow-up TTE records to identify new-onset valvular heart diseases. RESULTS: AI-ECG adjusted for age and sex achieved areas under the curves (AUCs) of >0.84, >0.80, >0.77, >0.83, and >0.81 for detecting aortic stenosis, aortic regurgitation, pulmonary regurgitation, tricuspid regurgitation, and mitral regurgitation, respectively. Since predictions of each DLM shared similar components of ECG rhythms, the positive findings of each DLM were highly correlated with other valvular heart diseases. Of note, a total of 37.5-51.7% of false-positive predictions had at least one significant echocardiographic finding, which may lead to a significantly higher risk of future moderate-to-severe VHDs in patients with initially minimal-to-mild VHDs. CONCLUSION: AI-ECG may be used as a large-scale screening tool for detecting VHDs and a basis to undergo an echocardiography.

Decoding the influence of low temperature on biofilm development: The hidden roles of c-di-GMP.

Biofilms are widely used and play important roles in biological processes. Low temperature of wastewater inhibits the development of biofilms derived from wastewater activated sludge. However, the specific mechanism of temperature on biofilm development is still unclear. This study explored the mechanism of temperature on biofilm development and found a feasible method to enhance biofilm development at low temperature. The amount of biofilm development decreased by approximately 66 % and 55 % at 4 °C and 15 °C, respectively, as compared to 28 °C. The cyclic dimeric guanosine monophosphate (c-di-GMP) concentration also decreased at low temperature and was positively correlated with extracellular polymeric substance (EPS) content, formation, and adhesion strength. Microbial community results showed that low temperature inhibited the normal survival of most microorganisms, but promoted the growth of some psychrophile bacteria like Sporosarcina, Caldilineaceae, Gemmataceae, Anaerolineaceae and Acidobacteriota. Further analysis of functional genes demonstrated that the abundance of functional genes related to the synthesis of c-di-GMP (K18968, K18967 and K13590) decreased at low temperature. Subsequently, the addition of exogenous spermidine increased the level of intracellular c-di-GMP and alleviated the inhibition effect of low temperature on biofilm development. Therefore, the possible mechanism of low temperature on biofilm development could be the inhibition of the microorganism activity and reduction of the communication level between cells, which is the closely related to the EPS content, formation, and adhesion strength. The enhancement of c-di-GMP level through the exogenous addition of spermidine provides an alternative strategy to enhance biofilm development at low temperatures. The results of this study enhance the understanding of the influence of temperature on biofilm development and provide possible strategies for enhancing biofilm development at low temperatures.

CCR5 and inflammatory storm.

Chemokines and their corresponding receptors play crucial roles in orchestrating inflammatory and immune responses, particularly in the context of pathological conditions disrupting the internal environment. Among these receptors, CCR5 has garnered considerable attention due to its significant involvement in the inflammatory cascade, serving as a pivotal mediator of neuroinflammation and other inflammatory pathways associated with various diseases. However, a notable gap persists in comprehending the intricate mechanisms governing the interplay between CCR5 and its ligands across diverse and intricate inflammatory pathologies. Further exploration is warranted, especially concerning the inflammatory cascade instigated by immune cell infiltration and the precise binding sites within signaling pathways. This study aims to illuminate the regulatory axes modulating signaling pathways in inflammatory cells by providing a comprehensive overview of the pathogenic processes associated with CCR5 and its ligands across various disorders. The primary focus lies on investigating the pathomechanisms associated with CCR5 in disorders related to neuroinflammation, alongside the potential impact of aging on these processes and therapeutic interventions. The discourse culminates in addressing current challenges and envisaging potential future applications, advocating for innovative research endeavors to advance our comprehension of this realm.

Development and characterization of the first proton minibeam system for single-gantry proton facility.

BACKGROUND: Minibeam represents a preclinical spatially fractionated radiotherapy modality with great translational potential. The advantage lies in its high therapeutic index (compared to GRID and LATTICE) and ability to treat at greater depth (compared to microbeam). Proton minibeam radiotherapy (pMBRT) is a synergy of proton and minibeam. While the single-gantry proton facility has gained popularity due to its affordability and compact design, it often has limited beam time available for research purposes. Conversely, given the current requirement of pMBRT on specific minibeam hardware collimators, necessitates a reproducible and fast setup to minimize pMBRT treatment time and streamline the switching time between pMBRT and conventional treatment for clinically translation. PURPOSE: The contribution of this work is the development and characterization of the first pMBRT system tailored for single-gantry proton facility. The system allows for efficient and reproducible plug-and-play setup, achievable within minutes. METHODS: The single room pMBRT system is constructed based on IBA ProteusONE proton machine. The end of nozzle is attached with beam modifying accessories though an accessory drawer. A small snout is attached to the accessory drawer and used to hold apertures and range shifters. The minibeam aperture consists of two components: a fitting ring and an aperture body. Three minibeam apertures were manufactured. The first-generation apertures underwent qualitatively analysis with film, and the second generation aperture underwent more comprehensive quantitative measurement. The reproducibility of the setup is accessed, and the film measurements are performed to characterize the pMBRT system in cross validation with Monte Carlo (MC) simulations. RESULTS: We presented initial results of large field pMBRT aperture and the film measurements indicates the effect of source-to-isocenter distance = 930 cm in Y proton scanning direction. Consistent with TOPAS MC simulation, the dose uniformity of pMBRT field <2 cm is demonstrated to be better than 2%, rendering its suitability for pre-clinical studies. Subsequently, we developed the second generation of aperture with five slits and characterized the aperture with film dosimetry studies and compared the results to the benchmark MC. Comprehensive film measurements were also performed to evaluate the effect of divergence, air gap and gantry-angle dependency and repeatability and revealing a consistent performance within 5%. Furthermore, the 2D gamma analysis indicated a passing rate exceeding 99% using 3% dose difference and 0.2 mm distance agreement criteria. We also establish the peak valley dose ratio and the depth dose profile measurements, and the results are within 10% from MC simulation. CONCLUSIONS: We have developed the first pMBRT system tailored for a single-gantry proton facility, which has demonstrated accuracy in benchmark with MC simulations, and allows for efficient plug-and-play setup, emphasizing efficiency.

Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study.

BACKGROUND: Triage is the process of accurately assessing patients' symptoms and providing them with proper clinical treatment in the emergency department (ED). While many countries have developed their triage process to stratify patients' clinical severity and thus distribute medical resources, there are still some limitations of the current triage process. Since the triage level is mainly identified by experienced nurses based on a mix of subjective and objective criteria, mis-triage often occurs in the ED. It can not only cause adverse effects on patients, but also impose an undue burden on the health care delivery system. OBJECTIVE: Our study aimed to design a prediction system based on triage information, including demographics, vital signs, and chief complaints. The proposed system can not only handle heterogeneous data, including tabular data and free-text data, but also provide interpretability for better acceptance by the ED staff in the hospital. METHODS: In this study, we proposed a system comprising 3 subsystems, with each of them handling a single task, including triage level prediction, hospitalization prediction, and length of stay prediction. We used a large amount of retrospective data to pretrain the model, and then, we fine-tuned the model on a prospective data set with a golden label. The proposed deep learning framework was built with TabNet and MacBERT (Chinese version of bidirectional encoder representations from transformers [BERT]). RESULTS: The performance of our proposed model was evaluated on data collected from the National Taiwan University Hospital (901 patients were included). The model achieved promising results on the collected data set, with accuracy values of 63%, 82%, and 71% for triage level prediction, hospitalization prediction, and length of stay prediction, respectively. CONCLUSIONS: Our system improved the prediction of 3 different medical outcomes when compared with other machine learning methods. With the pretrained vital sign encoder and repretrained mask language modeling MacBERT encoder, our multimodality model can provide a deeper insight into the characteristics of electronic health records. Additionally, by providing interpretability, we believe that the proposed system can assist nursing staff and physicians in taking appropriate medical decisions.

Intermediate Transfer Rates and Solid-State Ion Exchange are Key Factors Determining the Bifunctionality of In2O3/HZSM-5 Tandem CO2 Hydrogenation Catalyst.

Identifying the descriptors for the synergistic catalytic activity of bifunctional oxide-zeolite catalysts constitutes a formidable challenge in realizing the potential of tandem hydrogenation of CO2 to hydrocarbons (HC) for sustainable fuel production. Herein, we combined CH3OH synthesis from CO2 and H2 on In2O3 and methanol-to-hydrocarbons (MTH) conversion on HZSM-5 and discerned the descriptors by leveraging the distance-dependent reactivity of bifunctional In2O3 and HZSM-5 admixtures. We modulated the distance between redox sites of In2O3 and acid sites of HZSM-5 from milliscale (∼10 mm) to microscale (∼300 µm) and observed a 3-fold increase in space-time yield of HC and CH3OH (7.5 × 10-5 molC gcat-1 min-1 and 2.5 × 10-5 molC gcat-1 min-1, respectively), due to a 10-fold increased rate of CH3OH advection (1.43 and 0.143 s-1 at microscale and milliscale, respectively) from redox to acid sites. Intriguingly, despite the potential of a three-order-of-magnitude enhanced CH3OH transfer at a nanoscale distance (∼300 nm), the sole product formed was CH4. Our reactivity data combined with Raman, Fourier transform infrared (FTIR), and X-ray photoelectron spectroscopy (XPS) revealed the occurrence of solid-state-ion-exchange (SSIE) between acid sites and Inδ+ ions, likely forming In2O moieties, inhibiting C-C coupling and promoting CH4 formation through CH3OH hydrodeoxygenation (HDO). Density functional theory (DFT) calculations further revealed that CH3OH adsorption on the In2O moiety with preadsorbed and dissociated H2 forming an H-In-OH-In moiety is the likely reaction mechanism, with the kinetically relevant step appearing to be the hydrogenation of the methyl species. Overall, our study revealed that efficient CH3OH transfer and prevention of ion exchange are the key descriptors in achieving catalytic synergy in bifunctional In2O3/HZSM-5 systems.

Construction and Analysis of a Mitochondrial Metabolism-Related Prognostic Model for Breast Cancer to Evaluate Survival and Immunotherapy.

As one of the most prevalent malignancies among women, breast cancer (BC) is tightly linked to metabolic dysfunction. However, the correlation between mitochondrial metabolism-related genes (MMRGs) and BC remains unclear. The training and validation datasets for BC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. MMRG-related data were obtained from the Molecular Signatures Database. A risk score prognostic model incorporating MMRGs was established based on univariate, LASSO, and multivariate Cox regression analyses. Independent factors affecting BC prognosis were identified through regression analysis and presented in a nomogram. Single-sample gene set enrichment analysis was employed to assess the immune levels of high-risk (HR) and low-risk (LR) groups. The sensitivity of BC patients in the two groups to common anti-tumor drugs was evaluated by utilizing the Genomics of Drug Sensitivity in Cancer database. 12 MMRGs significantly associated with survival were selected from 1234 MMRGs. A 12-gene risk score prognostic model was built. In the multivariate regression analysis incorporating classical clinical factors, the MMRG-related risk score remained an independent prognostic factor. As revealed by tumor immune microenvironment analysis, the LR group with higher survival rates had elevated immune levels. The drug sensitivity results unmasked that the LR group demonstrated higher sensitivity to Irinotecan, Nilotinib, and Oxaliplatin, while the HR group demonstrated higher sensitivity to Lapatinib. The development of MMRG characteristics provides a comprehensive understanding of mitochondrial metabolism in BC, aiding in the prediction of prognosis and tumor microenvironment, and offering promising therapeutic choices for BC patients with different MMRG risk scores.

Multi-site isomerization of synergistically regulated stimuli-responsive AIE materials toward multi-level decryption.

Stimuli-responsive aggregation-induced emission (AIE) materials are highly sensitive and rapidly responsive to external signals, making them ideal solid materials for anti-counterfeiting encryption. However, the limited conformational and packing variations resulting from regio-isomerization with a single substituent restricts the stimuli-responsive behavior of these materials. In this work, several AIE-active regio-structural isomers based on the salicylaldehyde Schiff base scaffold have been straightforwardly obtained through multiple substitutions with bromide and triphenylamine moieties. Solvent-effect experiments demonstrate their different orders of charge-transfer and excited-state intramolecular proton transfer upon photoexcitation, indicating the regulation of excited-state processes via multi-site isomerization. These isomers also demonstrate mechanochromism and acidichromism, allowing for adjustable stimuli-responsive effects. As a demonstration, p-Br-TPA with both mechanochromism and acidichromism can be synergistically utilized for multi-level decryption. This study successfully regulates the evolution of excited states through multi-site isomerization, offering a general approach for achieving tunable stimuli-responsive properties in AIE-active salicylaldehyde Schiff bases toward multi-level decryption.

Hand Castings of Children With Terminal Illnesses From Cancer Can Provide Comfort to Grieving Families.

Registered nurses have voluntarily created hand casts for families, providing comfort during challenging moments. Hand casting moves the patient's family and nurses. As requested by parents, staff apply a quick-drying gel to sick children's hands and feet. After preparing the gel mold, alginate molding powder is poured in and hardened for many days. Parents mourn their children with great sensitivity. Every mold and hospital bedside we go to offers closure to the lost child's dying moments. A compelling benefit of a three-dimensional hand-cast is preserving a passing moment.

The SMAC mimetic GDC-0152 is a direct ABCB1-ATPase activity modulator and BIRC5 expression suppressor in cancer cells.

Upregulation of the multidrug efflux pump ABCB1/MDR1 (P-gp) and the anti-apoptotic protein BIRC5/Survivin promotes multidrug resistance in various human cancers. GDC-0152 is a DIABLO/SMAC mimetic currently being tested in patients with solid tumors. However, it is still unclear whether GDC-0152 is therapeutically applicable for patients with ABCB1-overexpressing multidrug-resistant tumors, and the molecular mechanism of action of GDC-0152 in cancer cells is still incompletely understood. In this study, we found that the potency of GDC-0152 is unaffected by the expression of ABCB1 in cancer cells. Interestingly, through in silico and in vitro analysis, we discovered that GDC-0152 directly modulates the ABCB1-ATPase activity and inhibits ABCB1 multidrug efflux activity at sub-cytotoxic concentrations (i.e., 0.25×IC50 or less). Further investigation revealed that GDC-0152 also decreases BIRC5 expression, induces mitophagy, and lowers intracellular ATP levels in cancer cells at low cytotoxic concentrations (i.e., 0.5×IC50). Co-treatment with GDC-0152 restored the sensitivity to the known ABCB1 substrates, including paclitaxel, vincristine, and YM155 in ABCB1-expressing multidrug-resistant cancer cells, and it also restored the sensitivity to tamoxifen in BIRC5-overexpressing tamoxifen-resistant breast cancer cells in vitro. Moreover, co-treatment with GDC-0152 restored and potentiated the anticancer effects of paclitaxel in ABCB1 and BIRC5 co-expressing xenograft tumors in vivo. In conclusion, GDC-0152 has the potential for use in the management of cancer patients with ABCB1 and BIRC5-related drug resistance. The findings of our study provide essential information to physicians for designing a more patient-specific GDC-0152 clinical trial program in the future.

General anesthesia is not associated with dementia in older adults with osteoarthritis for hip/knee replacements, a national population-based nested case-control study.

BACKGROUND: Dementia is a prevalent neurological condition, yet the relationship between dementia and general anesthesia remains uncertain. The study aimed to explore the association between general anesthesia and dementia using a nationwide population-based database. METHODS: The study extracted data from Taiwan's national health insurance, which encompassed the records of one million insured residents. A total of 59,817 patients aged 65 years and above, diagnosed with osteoarthritis between 2002 and 2010, were included. Among these patients, 3277 individuals with an initial diagnosis of dementia between 2004 and 2013 were matched with non-dementia patients based on age, gender, and the date of osteoarthritis diagnosis. Following a 1:2 random matching, the case group included 2171 patients with dementia, while the control group consisted of 4342 patients without dementia. The data was analyzed using conditional and unconditional logistic regressions. RESULTS: No significant differences in the odds of dementia were found between individuals exposed to general and regional anesthesia during hip/knee replacement surgeries (OR = 1.11; 95%CI: 0.73-1.70), after adjusting for age, sex, and co-morbidities. Similarly, there were no significant differences in the odds of dementia based on different durations of anesthesia exposure (General: <2 h: OR = 0.91, 95%CI = 0.43-1.92; 2-4 h: OR = 1.21, 95%CI = 0.82-1.79; >4 h: OR = 0.39, 95%CI = 0.15-1.01; compared to no exposure. Regional: <2 h: OR = 1.18, 95%CI = 0.85-1.62; 2-4 h: OR = 0.9, 95%CI = 0.64-1.27; >4 h: OR = 0.55, 95%CI = 0.15-1.96; compared to no exposure). Likewise, no significant differences were observed in the odds of dementia based on the number of replacement surgeries (twice: OR = 0.74, 95%CI = 0.44-1.23, compared to once). CONCLUSION: Neither general anesthesia nor regional anesthesia in hip/knee surgery was associated with dementia. Different numbers and durations of anesthesia exposure showed no significant differences in the odds for dementia.

Unsupervised ensembling of multiple software sensors with phase synchronization: a robust approach for electrocardiogram-derived respiration.

Objective.We aimed to fuse the outputs of different electrocardiogram-derived respiration (EDR) algorithms to create one higher quality EDR signal.Methods.We viewed each EDR algorithm as a software sensor that recorded breathing activity from a different vantage point, identified high-quality software sensors based on the respiratory signal quality index, aligned the highest-quality EDRs with a phase synchronization technique based on the graph connection Laplacian, and finally fused those aligned, high-quality EDRs. We refer to the output as the sync-ensembled EDR signal. The proposed algorithm was evaluated on two large-scale databases of whole-night polysomnograms. We evaluated the performance of the proposed algorithm using three respiratory signals recorded from different hardware sensors, and compared it with other existing EDR algorithms. A sensitivity analysis was carried out for a total of five cases: fusion by taking the mean of EDR signals, and the four cases of EDR signal alignment without and with synchronization and without and with signal quality selection.Results.The sync-ensembled EDR algorithm outperforms existing EDR algorithms when evaluated by the synchronized correlation (γ-score), optimal transport (OT) distance, and estimated average respiratory rate score, all with statistical significance. The sensitivity analysis shows that the signal quality selection and EDR signal alignment are both critical for the performance, both with statistical significance.Conclusion.The sync-ensembled EDR provides robust respiratory information from electrocardiogram.Significance.Phase synchronization is not only theoretically rigorous but also practical to design a robust EDR.

Injectable, Antioxidative, and Tissue-Adhesive Nanocomposite Hydrogel as a Potential Treatment for Inner Retina Injuries.

Reactive oxygen species (ROS) have been recognized as prevalent contributors to the development of inner retinal injuries including optic neuropathies such as glaucoma, non-arteritic anterior ischemic optic neuropathy, traumatic optic neuropathy, and Leber hereditary optic neuropathy, among others. This underscores the pivotal significance of oxidative stress in the damage inflicted upon retinal tissue. To combat ROS-related challenges, this study focuses on creating an injectable and tissue-adhesive hydrogel with tailored antioxidant properties for retinal applications. GelCA, a gelatin-modified hydrogel with photo-crosslinkable and injectable properties, is developed. To enhance its antioxidant capabilities, curcumin-loaded polydopamine nanoparticles (Cur@PDA NPs) are incorporated into the GelCA matrix, resulting in a multifunctional nanocomposite hydrogel referred to as Cur@PDA@GelCA. This hydrogel exhibits excellent biocompatibility in both in vitro and in vivo assessments, along with enhanced tissue adhesion facilitated by NPs in an in vivo model. Importantly, Cur@PDA@GelCA demonstrates the potential to mitigate oxidative stress when administered via intravitreal injection in retinal injury models such as the optic nerve crush model. These findings underscore its promise in advancing retinal tissue engineering and providing an innovative strategy for acute neuroprotection in the context of inner retinal injuries.

Microenvironment-induced CREPT expression by cancer-derived small extracellular vesicles primes field cancerization.

Rationale: Cancer local recurrence increases the mortality of patients, and might be caused by field cancerization, a pre-malignant alteration of normal epithelial cells. It has been suggested that cancer-derived small extracellular vesicles (CDEs) may contribute to field cancerization, but the underlying mechanisms remain poorly understood. In this study, we aim to identify the key regulatory factors within recipient cells under the instigation of CDEs. Methods: In vitro experiments were performed to demonstrate that CDEs promote the expression of CREPT in normal epithelial cells. TMT-based quantitative mass spectrometry was employed to investigate the proteomic differences between normal cells and tumor cells. Loss-of-function approaches by CRISPR-Cas9 system were used to assess the role of CREPT in CDEs-induced field cancerization. RNA-seq was performed to explore the genes regulated by CREPT during field cancerization. Results: CDEs promote field cancerization by inducing the expression of CREPT in non-malignant epithelial cells through activating the ERK signaling pathway. Intriguingly, CDEs failed to induce field cancerization when CREPT was deleted, highlighting the importance of CREPT. Transcriptomic analyses revealed that CDEs elicited inflammatory responses, primarily through activation of the TNF signaling pathway. CREPT, in turn, regulates the transduction of downstream signals of TNF by modulating the expression of TNFR2 and PI3K, thereby promoting inflammation-to-cancer transition. Conclusion: CREPT not only serves as a biomarker for field cancerization, but also emerges as a target for preventing the cancer local recurrence.

Characterisation of putative novel tick viruses and zoonotic risk prediction.

Tick-associated viruses remain a substantial zoonotic risk worldwide, so knowledge of the diversity of tick viruses has potential health consequences. Despite their importance, large amounts of sequences in public data sets from tick meta-genomic and -transcriptomic projects remain unannotated, sequence data that could contain undocumented viruses. Through data mining and bioinformatic analysis of more than 37,800 public meta-genomic and -transcriptomic data sets, we found 83 unannotated contigs exhibiting high identity with known tick viruses. These putative viral contigs were classified into three RNA viral families (Alphatetraviridae, Orthomyxoviridae and Chuviridae) and one DNA viral family (Asfarviridae). After manual checking of quality and dissimilarity towards other sequences in the data set, these 83 contigs were reduced to five contigs in the Alphatetraviridae from four putative viruses, four in the Orthomyxoviridae from two putative viruses and one in the Chuviridae which clustered with known tick-associated viruses, forming a separate clade within the viral families. We further attempted to assess which previously known tick viruses likely represent zoonotic risks and thus deserve further investigation. We ranked the human infection potential of 133 known tick-associated viruses using a genome composition-based machine learning model. We found five high-risk tick-associated viruses (Langat virus, Lonestar tick chuvirus 1, Grotenhout virus, Taggert virus and Johnston Atoll virus) that have not been known to infect human and two viral families (Nairoviridae and Phenuiviridae) that contain a large proportion of potential zoonotic tick-associated viruses. This adds to the knowledge of tick virus diversity and highlights the importance of surveillance of newly emerging tick-associated diseases.

Recent advances in biomaterial designs for assisting CAR-T cell therapy towards potential solid tumor treatment.

Chimeric antigen receptor T (CAR-T) cells have shown promising outcomes in the treatment of hematologic malignancies. However, CAR-T cell therapy in solid tumor treatment has been significantly hindered, due to the complex manufacturing process, difficulties in proliferation and infiltration, lack of precision, or poor visualization ability. Fortunately, recent reports have shown that functional biomaterial designs such as nanoparticles, polymers, hydrogels, or implantable scaffolds might have potential to address the above challenges. In this review, we aim to summarize the recent advances in the designs of functional biomaterials for assisting CAR-T cell therapy for potential solid tumor treatments. Firstly, by enabling efficient CAR gene delivery in vivo and in vitro, functional biomaterials can streamline the difficult process of CAR-T cell therapy manufacturing. Secondly, they might also serve as carriers for drugs and bioactive molecules, promoting the proliferation and infiltration of CAR-T cells. Furthermore, a number of functional biomaterial designs with immunomodulatory properties might modulate the tumor microenvironment, which could provide a platform for combination therapies or improve the efficacy of CAR-T cell therapy through synergistic therapeutic effects. Last but not least, the current challenges with biomaterials-based CAR-T therapies will also be discussed, which might be helpful for the future design of CAR-T therapy in solid tumor treatment.