Energy Migration Control of Multimodal Emissions in an Er3+ -Doped Nanostructure for Information Encryption and Deep-Learning Decoding.

Modulating the emission wavelengths of materials has always been a primary focus of fluorescence technology. Nanocrystals (NCs) doped with lanthanide ions with rich energy levels can produce a variety of emissions at different excitation wavelengths. However, the control of multimodal emissions of these ions has remained a challenge. Herein, we present a new composition of Er3+ -based lanthanide NCs with color-switchable output under irradiation with 980, 808, or 1535 nm light for information security. The variation of excitation wavelengths changes the intensity ratio of visible (Vis)/near-infrared (NIR-II) emissions. Taking advantage of the Vis/NIR-II multimodal emissions of NCs and deep learning, we successfully demonstrated the storage and decoding of visible light information in pork tissue.

The collaborative incentive effect in adsorption-photocatalysis: A special perspective on phosphorus recovery and reuse.

Achieving efficient recovery and direct utilization of phosphorus as one of the important components of the green economy is a huge challenge. Herein, we innovatively constructed a coupling adsorption-photocatalytic (CAP) process using synthetic dual-functional Mg-modified carbon nitride (CN-MgO). The CAP could utilize the recovered phosphorus from wastewater to promote the in-situ degradation of refractory organic pollutants via CN-MgO, where its phosphorus adsorption capacity and photocatalytic activity were significantly and synergistically increased. It was specifically reflected in the high phosphorus adsorption capacity of CN-MgO (218 mg/g), which was 153.5 times that of carbon nitride (1.42 mg/g), and its theoretical maximum adsorption capacity could reach 332 mg P/g. Subsequently, the phosphorus-enriched sample (CN-MgO-P) was employed as a photocatalyst to remove tetracycline with a reaction rate (k = 0.07177 min-1) 2.33 times higher than that of carbon nitride (k = 0.0327 min-1). Notably, the coordinated incentive mechanism present in this CAP between adsorption and photocatalysis may be attributed to the more adsorption sites of CN-MgO and the facilitation of hydroxyl production through adsorbed phosphorus, which ensured the feasibility of creating environmental value from the phosphorus in wastewater by means of CAP. This study provides a new perspective on the recovery and reuse of phosphorus resources in wastewater and the integration of environmental technologies in multiple fields.

Photocatalytic hydrogel film assisted forward osmosis (PFO) for water treatment: Sustainable performance and contaminant control.

The integration of catalytic oxidation with forward osmosis (FO) holds promising potential to address two crucial challenges encountered by FO: fouling and unsustainable performance, but suitable approaches are still rare. Herein, we have successfully developed a photocatalysis-assisted forward osmosis (PFO) system. In the PFO, a self-made porous carbon nitride doped functional carbon nanotube photocatalytic hydrogel film (PCN@CNTM) was engaged in the FO process in an inventive way by simply sticking to the commercial FO membrane surface, preventing damage to the membrane from the catalyst's direct insertion and delaying the assault from the oxidation groups. PFO allowed organic pollutants to decompose in the feed solution (90%) and on the membrane surface, regulating the water chemical potential and giving the FO membrane antifouling properties. This resulted in sustainable water flux (11.8 LMH) with no significant membrane fouling in PFO, whereas in FO alone there was a significant fouling and flux drop (from 12.73 to 7.23 LMH in 4 h). Moreover, the expensive FO membrane was protected while the hydrogel film can be replaced on demand. The PFO exemplifies the concept of synergistic technology integration, presenting a new perspective on harnessing the strengths of distinct technologies in a mutually beneficial manner.

Association of Sodium and Sugar-Sweetened Beverage Intake With Cardiovascular Disease Risk Factors in Adolescents and Young Adults With Obesity.

Cardiovascular disease (CVD) risk factors in children have increased in prevalence. Dietary intake may modify risk. Data collected during a randomized trial testing the effect of a behavioral intervention on adiposity, blood pressure (BP), and left ventricular mass index (LVMI) were analyzed using multivariable regression to determine independent associations of sodium, sugar-sweetened beverage (SSB), and artificially sweetened beverage (ASB) intake with outcomes. High sodium intake (≥3.5 g) was associated with hypertensive BP (odds ratio 12.8; P = .027) in minimally adjusted models. High SSB intake (≥4 oz) was independently associated with body mass index z-score (ß = .34; P = .035) and waist circumference z-score (ß = .49; P = .022) in fully adjusted models. Any ASB intake was associated with LVMI in fully adjusted model (% change 38.22; P = .004). There was no effect modification between sodium and SSB on outcomes. Dietary factors explored in this study independently impacted CVD risk. Further effect measure modification should be explored in larger cohorts.

The molecular mechanisms of ferroptosis and its role in glioma progression and treatment.

Ferroptosis is one of the programmed modes of cell death that has attracted widespread attention recently and is capable of influencing the developmental course and prognosis of many tumors. Glioma is one of the most common primary tumors of the central nervous system, but effective treatment options are very limited. Ferroptosis plays a critical role in the glioma progression, affecting tumor cell proliferation, angiogenesis, tumor necrosis, and shaping the immune-resistant tumor microenvironment. Inducing ferroptosis has emerged as an attractive strategy for glioma. In this paper, we review ferroptosis-related researches on glioma progression and treatment.

Artifact removal in photoacoustic tomography with an unsupervised method.

Photoacoustic tomography (PAT) is an emerging biomedical imaging technology that can realize high contrast imaging with a penetration depth of the acoustic. Recently, deep learning (DL) methods have also been successfully applied to PAT for improving the image reconstruction quality. However, the current DL-based PAT methods are implemented by the supervised learning strategy, and the imaging performance is dependent on the available ground-truth data. To overcome the limitation, this work introduces a new image domain transformation method based on cyclic generative adversarial network (CycleGAN), termed as PA-GAN, which is used to remove artifacts in PAT images caused by the use of the limited-view measurement data in an unsupervised learning way. A series of data from phantom and in vivo experiments are used to evaluate the performance of the proposed PA-GAN. The experimental results show that PA-GAN provides a good performance in removing artifacts existing in photoacoustic tomographic images. In particular, when dealing with extremely sparse measurement data (e.g., 8 projections in circle phantom experiments), higher imaging performance is achieved by the proposed unsupervised PA-GAN, with an improvement of ∼14% in structural similarity (SSIM) and ∼66% in peak signal to noise ratio (PSNR), compared with the supervised-learning U-Net method. With an increasing number of projections (e.g., 128 projections), U-Net, especially FD U-Net, shows a slight improvement in artifact removal capability, in terms of SSIM and PSNR. Furthermore, the computational time obtained by PA-GAN and U-Net is similar (∼60 ms/frame), once the network is trained. More importantly, PA-GAN is more flexible than U-Net that allows the model to be effectively trained with unpaired data. As a result, PA-GAN makes it possible to implement PAT with higher flexibility without compromising imaging performance.

Effectiveness of Melodic Intonation Therapy in Chinese Mandarin on Non-fluent Aphasia in Patients After Stroke: A Randomized Control Trial.

Melodic intonation therapy (MIT) positively impacts the speech function of patients suffering from aphasia and strokes. Fixed-pitch melodies and phrases formulated in MIT provide the key to the target language to open the language pathway. This randomized controlled trial compared the effects of music therapy-based MIT and speech therapy on patients with non-fluent aphasia. The former is more effective in the recovery of language function in patients with aphasia. Forty-two participants were enrolled in the study, and 40 patients were registered. The participants were randomly assigned to two groups: the intervention group (n = 20; 16 males, 4 females; 52.90 ± 9.08 years), which received MIT, and the control group (n = 20; 15 males, 5 females; 54.05 ± 10.81 years), which received speech therapy. The intervention group received MIT treatment for 30 min/day, five times a week for 8 weeks, and the control group received identical sessions of speech therapy for 30 min/day, five times a week for 8 weeks. Each participant of the group was assessed by a Boston Diagnostic Aphasia Examination (BDAE) at the baseline (t1, before the start of the experiment), and after 8 weeks (t2, the experiment was finished). The Hamilton Anxiety Scale (HAMA) and Hamilton Depression Scale (HAMD) were also measured on the time points. The best medical care of the two groups is the same. Two-way ANOVA analysis of variance was used only for data detection. In the spontaneous speech (information), the listening comprehension (right or wrong, word recognition, and sequential order) and repetitions of the intervention group were significantly higher than the control group in terms of the cumulative effect of time and the difference between groups after 8 weeks. The intervention group has a significant time effect in fluency, but the results after 8 weeks were not significantly different from those in the control group. In terms of naming, the intervention group was much better than the control group in spontaneous naming. Regarding object naming, reaction naming, and sentence completing, the intervention group showed a strong time accumulation effect. Still, the results after 8 weeks were not significantly different from those in the control group. These results indicate that, compared with speech therapy, MIT based on music therapy is a more effective musical activity and is effective and valuable for the recovery of speech function in patients with non-fluent aphasia. As a more professional non-traumatic treatment method, MIT conducted by qualified music therapists requires deeper cooperation between doctors and music therapists to improve rehabilitating patients with aphasia. The Ethics Committee of the China Rehabilitation Research Center approved this study (Approval No. 2020-013-1 on April 1, 2020) and was registered with the Chinese Clinical Trial Registry (Registration number: Clinical Trials ChiCTR2000037871) on September 3, 2020.

Customized thin and loose cake layer to mitigate membrane fouling in an electro-assisted anaerobic forward osmosis membrane bioreactor (AnOMEBR).

Anaerobic forward osmosis membrane bioreactor (AnOMBR) is a potential wastewater treatment technology, due to its low energy consumption and high effluent quality. However, membrane fouling is still a considerable problem which causes dwindling of water flux and shortening the membrane lifetime. In this study, electro-assisted anaerobic forward osmosis membrane bioreactor (AnOMEBR) was developed to treat wastewater and mitigate membrane fouling, in which the conductive FO membrane was used both as the separation unit and cathode. The formation, development and alleviation of membrane fouling in AnOMEBR were investigated. The results showed that the soluble microbial products (SMP) content and the proteins/polysaccharides (PN/PS) value in AnOMEBR were 26% and 15% lower than that in AnOMBR, respectively. The absolute value of Zeta of sludge mixture in AnOMEBR was 1.2 times that of the AnOMBR. The increase in the interaction between the membrane surface and the negatively charged foulants could inhibit the adsorption of foulants on membrane surface in the initial stage of membrane fouling. The strong interaction among foulants further affected the composition, structure and thickness of the cake layer on the FO membrane surface. AnOMEBR with a shorter hydraulic retention time, a higher organic loading rate and a lower osmotic pressure difference, could still obtain a lower flux decline rate of 0.063 LMH/h, which was 35.7% lower than AnOMBR. The wastewater treatment capacity of AnOMEBR was nearly 1.5 times that of the AnOMBR. This work provides an efficient strategy for mitigating membrane fouling and improving wastewater treatment capacity.

Deep Learning for Ultrasound Localization Microscopy.

By localizing microbubbles (MBs) in the vasculature, ultrasound localization microscopy (ULM) has recently been proposed, which greatly improves the spatial resolution of ultrasound (US) imaging and will be helpful for clinical diagnosis. Nevertheless, several challenges remain in fast ULM imaging. The main problems are that current localization methods used to implement fast ULM imaging, e.g., a previously reported localization method based on sparse recovery (CS-ULM), suffer from long data-processing time and exhaustive parameter tuning (optimization). To address these problems, in this paper, we propose a ULM method based on deep learning, which is achieved by using a modified sub-pixel convolutional neural network (CNN), termed as mSPCN-ULM. Simulations and in vivo experiments are performed to evaluate the performance of mSPCN-ULM. Simulation results show that even if under high-density condition (6.4 MBs/mm2), a high localization precision ( [Formula: see text] in the lateral direction and [Formula: see text] in the axial direction) and a high localization reliability (Jaccard index of 0.66) can be obtained by mSPCN-ULM, compared to CS-ULM. The in vivo experimental results indicate that with plane wave scan at a transmit center frequency of 15.625 MHz, microvessels with diameters of [Formula: see text] can be detected and adjacent microvessels with a distance of [Formula: see text] can be separated. Furthermore, when using GPU acceleration, the data-processing time of mSPCN-ULM can be shortened to ~6 sec/frame in the simulations and ~23 sec/frame in the in vivo experiments, which is 3-4 orders of magnitude faster than CS-ULM. Finally, once the network is trained, mSPCN-ULM does not need parameter tuning to implement ULM. As a result, mSPCN-ULM opens the door to implement ULM with fast data-processing speed, high imaging accuracy, short data-acquisition time, and high flexibility (robustness to parameters) characteristics.