Photoluminescent Multicolor Carbon Dots for UV Detection and Dynamic Anticounterfeiting.

Carbon dots (CDs) are an emerging type of fluorescent carbon nanomaterial with broad application prospects. Among them, photochromic CDs have been widely used in the field of optoelectronic devices but rarely in ultraviolet (UV) detection. In this work, we successfully developed photochromic CDs that exhibit reversible emission under light stimulation in an amine solvent system. Notably, the CDs showed ultrafast photochromic behavior in diethylamine solvent, shifting the fluorescence color from cyan-green to orange-red after 2 s of irradiation, with the solution color changing from pale yellow to pale purple. Furthermore, this performance could recover without additional stimuli, simply by standing for several tens of seconds. Structural analysis indicated that rapid photochromism arises from changes in the surface functional group radicals of the CDs, with the reversibility attributed to fluctuation in these radicals. Leveraging the excellent photochromic properties of CDs, we further developed a device for detecting UV indices in sunlight. This opens up broad prospects for developing high-performance UV detection devices based on CDs.

All-Metal Flexible Fiber by Continuously Assembling Nanowires for High Electrical Conductivity.

Fiber electronics booms as a new important field but is currently limited by the challenge of finding both highly flexible and conductive fiber electrodes. Here, all-metal fibers based on nanowires are discovered. Silver nanowires are continuously assembled into robust fibers by salt-induced aggregation and then firmly stabilized by plasmonic welding. The nanowire network structures provide them both high flexibility with moduli at the level of MPa and conductivities up to 106 S m-1. They also show excellent electrochemical properties such as low impedance and high electrochemically active surface area. Their stable chronic single-neuron recording is further demonstrated with good biocompatibility in vivo. These new fiber materials may provide more opportunities for the future development of fiber electronics.

Knockdown of SMYD3 by RNA Interference Regulates the Expression of Autophagy-Related Proteins and Inhibits Bone Formation in Fluoride-Exposed Osteoblasts.

This study aimed to explore the role of histone methyltransferase SET and MYND domain containing 3 (SMYD3) in bone metabolism of osteoblasts exposed to fluoride. The levels of urine fluoride, BALP, and OC and the mRNA expression of SMYD3 were determined in patients with skeletal fluorosis and non-fluoride-exposed people on informed consent. The expression of SMYD3 protein, OC contents, and BALP activities were detected in human osteoblast-like MG63 cells and rat primary osteoblasts treated with sodium fluoride (NaF) for 48 h. The autophagosomes were observed by transmission electron microscopy. Then, we knocked down SMYD3 to confirm whether it was involved in the regulation of bone formation and related to autophagy and Wnt/ß-catenin pathway. We observed that OC and BALP levels in patients with skeletal fluorosis significantly increased, while the mRNA expression of SMYD3 significantly decreased in the skeletal fluorosis groups. In vitro, the OC contents, BALP activities, and expression of SMYD3 significantly increased, and many autophagosomes were observed in NaF treated osteoblasts. The downregulation of SMYD3 significantly inhibited OC contents, BALP activities, and expression of autophagy-related proteins, but with no significant changes in the Wnt/ß-catenin pathway. Our results demonstrated that fluoride exposure with coal-burning pollution caused orthopedic injuries and abnormalities in the levels of OC and BALP and hindered normal bone metabolism. Silencing the SMYD3 gene could significantly reduce OC and BALP levels via inhibiting the increase in autophagy induced by fluoride.

A Soft-Fiber Bioelectronic Device with Axon-Like Architecture Enables Reliable Neural Recording In Vivo under Vigorous Activities.

Implantable neural devices that record neurons in various states, including static states, light activities such as walking, and vigorous activities such as running, offer opportunities for understanding brain functions and dysfunctions. However, recording neurons under vigorous activities remains a long-standing challenge because it leads to intense brain deformation. Thus, three key requirements are needed simultaneously for neural devices, that is, low modulus, low specific interfacial impedance, and high electrical conductivity, to realize stable device/brain interfaces and high-quality transmission of neural signals. However, they always contradict each other in current material strategies. Here, a soft fiber neural device capable of stably tracking individual neurons in the deep brain of medium-sized animals under vigorous activity is reported. Inspired by the axon architecture, this fiber neural device is constructed with a conductive gel fiber possessing a network-in-liquid structure using conjugated polymers and liquid matrices and then insulated with soft fluorine rubber. This strategy reconciles the contradictions and simultaneously confers the fiber neural device with low modulus (300 kPa), low specific impedance (579 kΩ µm2), and high electrical conductivity (32 700 S m-1) - ≈1-3 times higher than hydrogels. Stable single-unit spike tracking in running cats, which promises new opportunities for neuroscience is demonstrated.

A Biodegradable Fiber Calcium Ion Sensor by Covalently Bonding Ionophores on Bioinert Nanoparticles.

Implantable sensors, especially ion sensors, facilitate the progress of scientific research and personalized healthcare. However, the permanent retention of implants induces health risks after sensors fulfill their mission of chronic sensing. Biodegradation is highly anticipated; while; biodegradable chemical sensors are rare due to concerns about the leakage of harmful active molecules after degradation, such as ionophores. Here, a novel biodegradable fiber calcium ion sensor is introduced, wherein ionophores are covalently bonded with bioinert nanoparticles to replace the classical ion-selective membrane. The fiber sensor demonstrates comparable sensing performance to classical ion sensors and good flexibility. It can monitor the fluctuations of Ca2+ in a 4-day lifespan in vivo and biodegrade in 4 weeks. Benefiting from the stable bonding between ionophores and nanoparticles, the biodegradable sensor exhibits a good biocompatibility after degradation. Moreover, this approach of bonding active molecules on bioinert nanoparticles can serve as an effective methodology for minimizing health concerns about biodegradable chemical sensors.

High-performing fiber electrodes based on a gold-shelled silver nanowire framework for bioelectronics.

Flexible fiber electrodes offer new opportunities for bioelectronics and are reliable in vivo applications, high flexibility, high electrical conductivity, and satisfactory biocompatibility are typically required. Herein, we present an all-metal flexible and biocompatible fiber electrode based on a metal nanowire hybrid strategy, i.e., silver nanowires were assembled on a freestanding framework, and further to render them inert, they were plated with a gold nanoshell. Our fiber electrodes exhibited a low modulus of ∼75 MPa and electrical conductivity up to ∼4.8 × 106 S m-1. They can resist chemical erosion with negligible leakage of biotoxic silver ions in the physiological environment, thus ensuring satisfactory biocompatibility. Finally, we demonstrated the hybrid fiber as a neural electrode that stimulated the sciatic nerve of a mouse, proving its potential for applications in bioelectronics.

Design and fabrication of wearable electronic textiles using twisted fiber-based threads.

Mono-dimensional fiber-based electronics can effectively address the growing demand for improved wearable electronic devices because of their exceptional flexibility and stretchability. For practical applications, functional fiber electronic devices need to be integrated into more powerful and versatile systems to execute complex tasks that cannot be completed by single-fiber devices. Existing techniques, such as printing and sintering, reduce the flexibility and cause low connection strength of fiber-based electronic devices because of the high curvature of the fiber. Here, we outline a twisting fabrication process for fiber electrodes, which can be woven into functional threads and integrated within textiles. The design of the twisted thread structure for fiber devices ensures stable interfacing and good flexibility, while the textile structure features easily accessible, interlaced points for efficient circuit connections. Electronic textiles can be customized to act as displays, health monitors and power sources. We detail three main fabrication sections, including the fabrication of the fiber electrodes, their twisting into electronic threads and their assembly into functional textile-based devices. The procedures require ~10 d and are easily reproducible by researchers with expertise in fabricating energy and electronic devices.

The management of uterine tumor resembling an ovarian sex cord tumor (UTROSCT): case series and literature review.

AIMS: To present a case series of 11 rare uterine tumors resembling ovarian sex cord tumors (UTROSCTs), and review the literature on this topic to offer up-to-date treatment management for UTROSCTs. METHOD: Eight cases from Fujian Cancer Hospital between January 2017 and May 2023 and three patients from Fujian Union Hospital between October 2012 and October 2020 were retrospectively reviewed. All cases were pathologically confirmed as UTROSCTs by two senior and experienced pathologists. Clinical behaviors, medical data, histopathological features, therapy approaches, and survival outcomes were discussed. RESULTS: The median age at initial diagnosis was 53 years (29-70 years). 3 (27.3%) patients were under 40. Seven cases presented with abnormal vaginal bleeding, one with menstrual disorder, one with abnormal vaginal secretion, and two patients were accidentally found by physical examination without any symptoms. Three patients were initially misdiagnosed with endometrial cancer by MRI. Curettage was performed in all cases. Nine of them were well diagnosed by routine curettage, except for two samples, which were identified after surgery. Immunohistochemical biomarkers, such as CD99, Desmin, WT-1, CK, Vimentin, SMA, α-Inhibin, Ki67, CD56, ER, PR, and CR, tend to be positive in UTRO SCs patients. Six patients underwent hysterectomy with bilateral salpingo-oophorectomy. Two cases received a radical hysterectomy with bilateral salpingo-oophorectomy, retroperitoneal lymph node dissection, and omentum dissection. Three UTROSCTs were under observation after mass resection. The median PFS was 24 months (range 1-125 months). CONCLUSION: UTROSCT is a rare mesenchymal tumor with low malignant potential. Treatment modalities should be carefully considered to balance the therapy outcomes and patient needs. Surgery conservative management might be suitable for young women with fertility desires.

An artificial nickel chlorinase based on the biotin-streptavidin technology.

Herein, we report on an artificial nickel chlorinase (ANCase) resulting from anchoring a biotinylated nickel-based cofactor within streptavidin (Sav). The resulting ANCase was efficient for the chlorination of diverse C(sp3)-H bonds. Guided by the X-ray analysis of the ANCase, the activity of the artificial chlorinase could be significantly improved. This approach opens interesting perspectives for late-stage functionalization of organic intermediates as it complements biocatalytic chlorination strategies.

Opto-thermal deformation fitting method based on a neural network and a transfer learning.

The thermal deformation fitting result of an optical surface is an important factor that affects the reliability of optical-mechanical-thermal integrated analysis. The traditional numerical methods are challenging to balance fitting accuracy and efficiency, especially the insufficient ability to deal with high-order Zernike polynomials. In this Letter, we innovatively proposed an opto-thermal deformation fitting method based on a neural network and a transfer learning to overcome shortcomings of numerical methods. The one-dimensional convolutional neural network (1D-CNN) model, which can represent deformation of the optical surface, is trained with Zernike polynomials as the input and the optical surface sag change as the output, and the corresponding Zernike coefficients are predicted by the identity matrix. Meanwhile, the trained 1D-CNN is further combined with the transfer learning to efficiently fit all thermal deformations of the same optical surface at different temperature conditions and avoids repeated training of the network. We performed thermal analysis on the main mirror of an aerial camera to verify the proposed method. The regression analysis of 1D-CNN training results showed that the determination coefficient is greater than 99.9%. The distributions of Zernike coefficients predicted by 1D-CNN and transfer learning are consistent. We conducted an error analysis on the fitting results, and the average values of the peak-valley, root mean square, and mean relative errors of the proposed method are 51.56%, 60.51, and 45.14% of the least square method, respectively. The results indicate that the proposed method significantly improves the fitting accuracy and efficiency of thermal deformations, making the optical-mechanical-thermal integrated analysis more reliable.

Enhanced expression of RAGE/NADPH oxidase signaling pathway and increased level of oxidative stress in brains of rats with chronic fluorosis and the protective effects of blockers.

This investigation was designed to examine the potential involvement of RAGE/NADPH oxidase signaling in the damage to the brain caused by chronic fluorosis. Sprague-Dawley rats were divided randomly into 9 groups each containing 20 animals, Controls (C); rats receiving low (i.e., 10 ppm) (LF) or high does ( i.e., 50 ppm) (HF) of fluoride in their drinking water; and these same groups injected with FPS-ZM1, an inhibitor of RAGE, (CF, LFF and HFF, respectively) or administered EGb761, an active ingredient of Ginkgo biloba extract, intragastrically (CE, LFE, and HFE). Following 3 and 6 months of such treatment, the spatial learning and memory of the animals were assessed with the Morris water maze test; the levels of malondialdehyde (MDA), hydrogen peroxide (H2O2) and superoxide dismutase (SOD) assayed by biochemical methods; and the levels of proteins related to the RAGE/NADPH pathway determined by Western blot and of the corresponding mRNAs by qPCR. After 6 months, the spatial learning and memory of the LF and HF groups had declined; their brain contents of MDA and H2O2 increased and SOD activity decreased; and the levels of the RAGE, gp91, P47, phospho-P47phox and P22 proteins and corresponding mRNAs in their brains were all elevated. Interestingly, all of these pathological changes caused by fluorosis could be attenuated by both FPS-ZM1 and EGb761. These findings indicate that the brain damage induced by fluorosis may be caused, at least in part, by enhanced RAGE/NADPH oxidase signaling and that FPS-ZM1 or EGb761 might be of clinical value in connection with the treatment of this condition.

A Customized Bayesian Algorithm to Optimize Enzyme-Catalyzed Reactions.

Design of experiments (DoE) plays an important role in optimizing the catalytic performance of chemical reactions. The most commonly used DoE relies on the response surface methodology (RSM) to model the variable space of experimental conditions with the fewest number of experiments. However, the RSM leads to an exponential increase in the number of required experiments as the number of variables increases. Herein we describe a Bayesian optimization algorithm (BOA) to optimize the continuous parameters (e.g., temperature, reaction time, reactant and enzyme concentrations, etc.) of enzyme-catalyzed reactions with the aim of maximizing performance. Compared to existing Bayesian optimization methods, we propose an improved algorithm that leads to better results under limited resources and time for experiments. To validate the versatility of the BOA, we benchmarked its performance with biocatalytic C-C bond formation and amination for the optimization of the turnover number. Gratifyingly, up to 80% improvement compared to RSM and up to 360% improvement vs previous Bayesian optimization algorithms were obtained. Importantly, this strategy enabled simultaneous optimization of both the enzyme's activity and selectivity for cross-benzoin condensation.

Simultaneous quantitative chiral analysis of four isomers by ultraviolet photodissociation mass spectrometry and artificial neural network.

Although mass spectrometry (MS) has its unique advantages in speed, specificity and sensitivity, its application in quantitative chiral analysis aimed to determine the proportions of multiple chiral isomers is still a challenge. Herein, we present an artificial neural network (ANN) based approach for quantitatively analyzing multiple chiral isomers from their ultraviolet photodissociation mass spectra. Tripeptide of GYG and iodo-L-tyrosine have been applied as chiral references to fulfill the relative quantitative analysis of four chiral isomers of two dipeptides of L/D His L/D Ala and L/D Asp L/D Phe, respectively. The results show that the network can be well-trained with limited sets, and have a good performance in testing sets. This study shows the potential of the new method in rapid quantitative chiral analysis aimed at practical applications, with much room for improvement in the near future, including selecting better chiral references and improving machine learning methods.

A novel five-gene metabolism-related risk signature for predicting prognosis and immune infiltration in endometrial cancer: A TCGA data mining.

BACKGROUND: Metabolism dysfunction can affect the biological behavior of tumor cells and result in carcinogenesis and the development of various cancers. However, few thoughtful studies focus on the predictive value and efficacy of immunotherapy of metabolism-related gene signatures in endometrial cancer (EC). This research aims to construct a predictive metabolism-related gene signature in EC with prognostic and therapeutic implications. METHODS: We downloaded the RNA profile and clinical data of 503 EC patients and screened out different expressions of metabolism-related genes with prognosis influence of EC from The Cancer Genome Atlas (TCGA) database. We first established a metabolism-related genes model using univariate and multivariate Cox regression and Lasso regression analysis. To internally validate the predictive model, 503 samples (entire set) were randomly assigned into the test set and the train set. Then, we applied the receiver operating characteristic (ROC) curve to confirm our previous predictive model and depicted a nomogram integrating the risk score and the clinicopathological feature. We employed a gene set enrichment analysis (GSEA) to explore the biological processes and pathways of the model. Afterward, we used ESTIMATE to evaluate the TME. Also, we adopted CIBERSORT and ssGSEA to estimate the fraction of immune infiltrating cells and immune function. At last, we investigated the relationship between the predictive model and immune checkpoint genes. RESULTS: We first constructed a predictive model based on five metabolism-related genes (INPP5K, PLPP2, MBOAT2, DDC, and ITPKA). This model showed the ability to predict EC patients' prognosis accurately and performed well in the train set, test set, and entire set. Then we confirmed the predictive signature was a novel independent prognostic factor in EC patients. In addition, we drew and validated a nomogram to precisely predict the survival rate of EC patients at 1-, 3-, and 5-years (ROC1-year = 0.714, ROC3-year = 0.750, ROC5-year = 0.767). Furthermore, GSEA unveiled that the cell cycle, certain malignant tumors, and cell metabolism were the main biological functions enriched in this identified model. We found the five metabolism-related genes signature was associated with the immune infiltrating cells and immune functions. Most importantly, it was linked with specific immune checkpoints (PD-1, CTLA4, and CD40) that could predict immunotherapy's clinical response. CONCLUSION: The metabolism-related genes signature (INPP5K, PLPP2, MBOAT2, DDC, and ITPKA) is a valuable index for predicting the survival outcomes and efficacy of immunotherapy for EC in clinical settings.

Adaptive Aquila Optimizer Combining Niche Thought with Dispersed Chaotic Swarm.

The Aquila Optimizer (AO) is a new bio-inspired meta-heuristic algorithm inspired by Aquila's hunting behavior. Adaptive Aquila Optimizer Combining Niche Thought with Dispersed Chaotic Swarm (NCAAO) is proposed to address the problem that although the Aquila Optimizer (AO) has a strong global exploration capability, it has an insufficient local exploitation capability and a slow convergence rate. First, to improve the diversity of populations in the algorithm and the uniformity of distribution in the search space, DLCS chaotic mapping is used to generate the initial populations so that the algorithm is in a better exploration state. Then, to improve the search accuracy of the algorithm, an adaptive adjustment strategy of de-searching preferences is proposed. The exploration and development phases of the NCAAO algorithm are effectively balanced by changing the search threshold and introducing the position weight parameter to adaptively adjust the search process. Finally, the idea of small habitats is effectively used to promote the exchange of information between groups and accelerate the rapid convergence of groups to the optimal solution. To verify the optimization performance of the NCAAO algorithm, the improved algorithm was tested on 15 standard benchmark functions, the Wilcoxon rank sum test, and engineering optimization problems to test the optimization-seeking ability of the improved algorithm. The experimental results show that the NCAAO algorithm has better search performance and faster convergence speed compared with other intelligent algorithms.

Double-Barreled Micropipette Enables Neuron-Compatible In Vivo Analysis.

The sensors based on ion transport in a confined nano-/microchannel (i.e., iontronic sensors) have brought new opportunities for in vivo neurochemical assay, especially for electroinactive molecules. However, the interference on spontaneous neuronal activity induced by the electric field around the sensors has not been addressed. Here, the electric field distribution with a double-barreled micropipette was shrunk and quantified by finite element simulation, which can explain and minimize the influence on spontaneous neuronal activity. The parameters affecting the electric field distribution, including the pore size, applied voltage, and angle degree, were studied to balance the sensitivity and interference on spontaneous neuronal activity. The double-barreled micropipette, as a pH sensor with high selectivity and sensitivity, has been successfully applied to real-time pH sensing in rat brain. This study offers a new way for in vivo monitoring neurochemical dynamics with neuron-compatibility.

Expression of expanded GGC repeats within NOTCH2NLC causes behavioral deficits and neurodegeneration in a mouse model of neuronal intranuclear inclusion disease.

GGC repeat expansions within NOTCH2NLC have been identified as the genetic cause of neuronal intranuclear inclusion disease (NIID). To understand the molecular pathogenesis of NIID, here, we established both a transgenic mouse model and a human neural progenitor cells (hNPCs) model. Expression of the NOTCH2NLC with expanded GGC repeats produced widespread intranuclear and perinuclear polyglycine (polyG), polyalanine (polyA), and polyarginine (polyR) inclusions, leading to behavioral deficits and severe neurodegeneration, which faithfully mimicked the clinical and pathological features associated with NIID. Furthermore, conserved alternative splicing events were identified between the NIID mouse and hNPC models, among which was the enrichment of the binding motifs of hnRNPM, an RNA binding protein known as alternative splicing regulator. Expanded NOTCH2NLC-polyG and NOTCH2NLC-polyA could interact with and sequester hnRNPM, while overexpression of hnRNPM could ameliorate the cellular toxicity. These results together suggested that dysfunction of hnRNPM could play an important role in the molecular pathogenesis of NIID.

Genetic Analysis of Six Transmembrane Protein Family Genes in Parkinson's Disease in a Large Chinese Cohort.

Objectives: Parkinson's disease (PD) is a neurodegenerative disorder with the manifestation of motor symptoms and non-motor symptoms. Previous studies have indicated the role of several transmembrane (TMEM) protein family genes in PD pathogenesis. Materials and Methods: In order to better investigate the genetic role of PD-related TMEM protein family genes in PD, including TMEM230, TMEM59, TMEM108, TMEM163, TMEM175, and TMEM229B, 1,917 sporadic early onset PD (sEOPD) or familial PD (FPD) patients and 1,652 healthy controls were analyzed by whole-exome sequencing (WES) while 1,962 sporadic late-onset PD (sLOPD) and 1,279 healthy controls were analyzed by whole-genome sequencing (WGS). Rare and common variants for each gene were included in the analysis. Results: One hundred rare damaging or loss of function variants of six genes were found at the threshold of MAF < 0.1%. Three rare Dmis variants of TMEM230 were specifically identified in PD. Rare missense variants of TMEM59 were statistically significantly associated with PD in the WES cohort, indicating the role of TMEM59 in FPD and sEOPD. Rare missense variants of TMEM108 were suggestively associated with PD in the WGS cohort, indicating the potential role of TMEM108 in sLOPD. The rare variant of the other three genes and common variants of six genes were not significantly associated with PD. Conclusion: We performed a large case-control study to systematically investigate the role of several PD-related TMEM protein family genes in PD. We identified three PD-specific variants in TMEM230, the significant association of TMEM59 with FPD, and sEOPD and the suggestive association of TMEM108 with sLOPD.

Genetic Analysis of HSP40/DNAJ Family Genes in Parkinson's Disease: a Large Case-Control Study.

Molecular chaperones were reported to play an important role in PD pathogenesis. Recent studies revealed the association of several HSP40/DNAJ family genes with PD, but no genetic analysis of all the DNAJ family genes in PD has been conducted. To systematically analyze the genetic impact of all the DNAJ family genes in PD, we performed genetic analysis for these genes in a large case-control study. We analyzed the rare variants in 49 DNAJ family genes from 3879 PD patients and 2931 healthy controls by whole-exome sequencing and whole-genome sequencing. All rare missense variants and the subgroups of rare damaging missense (Dmis) and loss-of-function (LoF) variants were gathered to test the accumulated association of these variants in each gene with PD. In total, 1617 rare nonsynonymous variants of DNAJ family genes with minor allele frequency less than 1% were identified in our cohort. We identified 82 rare missense variants for DNAJC26 in sporadic early-onset PD (sEOPD) or familial PD (FPD), and 17 Dmis and one LoF variant were detected among them. Gene-based burden analysis showed that the rare Dmis variants alone or Dmis plus LoF variants together of DNAJC26 were significantly enriched in PD patients. We also found suggestive associations of DNAJB2 and DNAJC18 with PD in sEOPD or FPD and DNAJC2, DNAJC10, DNAJC22, DNAJC24, DNAJC27, DNAJC28, and DNAJC29 with PD in sporadic late-onset PD. In conclusion, rare missense variants of DNAJC26 were significantly enriched in FPD or sEOPD. Moreover, DNAJB2, DNAJC2, DNAJC10, DNAJC18, DNAJC22, DNAJC24, DNAJC27, DNAJC28, and DNAJC29 were suggestively associated with PD.