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The growing popularity of 4 G/5 G mobile devices has led to an increase in demand for wireless security. Radio frequency fingerprint (RFF) technique is an emerging approach for device authentication using intrinsic and unique hardware impairments. In this paper, we propose an RFF-based method to identify rogue/unknown long term evolution (LTE) terminals. This is achieved by combining wavelet transform (WT) coefficient graphs and differential spectrum. The proposed method involves extracting 48 levels of wavelet coefficients from the transient power-off of the physical random access channel (PRACH) signal and representing them in a WT graph. The steady-state part of the PRACH signal after a frequency domain differential processing between the adjacent spectrum is extracted. To detect unknown attack devices, an identification scheme based on an autoencoder (AE) is designed. Two different AE network structures are designed based on the proposed features, and a hybrid identification structure is proposed. An experimental evaluation system is set up with seven mobile phones from three categories and one universal software radio peripheral (USRP) software-defined radio (SDR) platform. Training and testing datasets are collected under different conditions such as location, working times, and dates. Experimental results show that rogue devices can be identified with an accuracy up to 98.84% for different categories and 90.27% for different individuals.

Exercise training is critical for the early prevention and treatment of obesity and diabetes mellitus. However, the mechanism with gut microbiota and fecal metabolites underlying the effects of voluntary wheel running on high-fat diet induced abnormal glucose metabolism has not been fully elaborated. C57BL/6 male mice were randomly assigned to 4 groups according to diets (fed with normal chow diet or high-fat diet) and running paradigm (housed in static cage or with voluntary running wheel). An integrative 16S rDNA sequencing and metabolites profiling was synchronously performed to characterize the effects of voluntary wheel running on gut microbiota and metabolites. It showed that voluntary wheel running prevented the detrimental effects of high-fat feeding on glucose metabolism. 16S rDNA sequencing showed remarkable changes in Rikenellaand Marvinbryantiagenera. Metabolic profiling indicated multiple altered metabolites, which were enriched in secondary bile acid biosynthesis signaling. In conclusion, our study indicated that voluntary wheel running significantly improved glucose metabolism and counteracted the deleterious effects of high-fat feeding on body weight and glucose intolerance. We further found that voluntary wheel running could integratively program gut microbiota composition and fecal metabolites changes, and may regulate muricholic acid metabolism and secondary bile acid biosynthesis in high-fat fed mice.

Recently, ammonia/methane mixtures have been considered as potential alternative fuels. The present study experimentally investigates the blow-off limits, flame structure, and pollutant emission of ammonia/methane mixtures in a partially premixed swirl-stabilized burner. The effects of fuel composition and the equivalence ratio are also studied. The results show that the NH3/CH4flame can be stabilized at an equivalence ratio of 0.55. The addition of methane has a positive effect on the blow-off limits. For the chemiluminescence profile, the OH* distribution and CH* distribution of NH3/CH4flames show a similar tendency under various conditions. The peak OH* and CH* radiances monotonically decrease with increasing ENH3, while the maximum NH2* shows an opposite trend. The influence of the equivalence ratio on OH* and CH* in the NH3/CH4flames is negligible. However, when ENH3is 60%, the equivalence ratio has a significant effect on NH2*. In terms of pollutant emissions, the peaks of NO and NO2emissions are all found around an ENH3of 20%. When the equivalence ratio reaches 1.0, NO and NO2emissions are as low as 15 and 10 mg/m3, respectively. At the same time, both CO and unburned NH3emissions increase. Therefore, further studies on the application of secondary air or improvement of the fuel injection method to improve the combustion efficiency and reduce the pollutant emissions for ammonia combustion are still needed.

Background: Our study aimed to investigate the prevalence and demographic characteristics of immune checkpoint inhibitor-associated hypophysitis (ICI-hypophysitis) using data from the FAERS, and the risk factors of prognosis were explored. Methods: In this retrospective study, all cases of newly-diagnosed hypophysitis associated with FDA approved ICIs from 1st January 2007 to 31st December 2022 were accumulated using FAERS. Demographic data including age, sex, body weight, the prognosis of cases, and other co-occurred endocrinopathies induced by ICIs were analyzed and compared between different subgroups of immunotherapy. Results: The reporting frequency of ICI-hypophysitis was 1.46% (2343/160089). Patients on the combination therapy had higher risk of hypophysitis reporting, followed by anti-CTLA-4 agent compared with other monotherapies (p< 0.001). Male subjects displayed higher reporting risk of ICI-hypophysitis (p= 0.015). Patients on anti-PD-1 therapy or the combination therapy showed higher occurrence rate of type 1 diabetes (anti-PD-1 vs. anti-PD-L1 vs. anti-CTLA-4 vs. combination therapy, 4.2% vs. 0.7% vs. 0.3% vs. 8.4%, p< 0.001). The occurrence rate of new-onset thyroid diseases in patients receiving combination therapy was higher than anti-PD-1 monotherapy (12.3% vs. 8.4%, p= 0.010). Elder age, lung cancer, and renal cancer emerged to be positively associated with severe clinical outcomes [>65 years, OR 1.042, 95%CI (1.022–1.063), p< 0.001; lung cancer, OR 1.400, 95%CI (1.019–1.923), p= 0.038; renal cancer, OR 1.667, 95%CI (1.153–2.412), p= 0.007]. Anti-CTLA-4 monotherapy was discovered to be a protective factor of severe outcomes [OR 0.433, 95%CI (0.335-0.558), p< 0.001]. Female sex and co-occurrence of ICI-related diabetes exhibited lower risk of death [female, OR 0.571, 95%CI (0.361–0.903), p= 0.017; diabetes, OR 0.090, 95%CI (0.016–0.524), p= 0.007]. Conclusions: ICI-induced hypophysitis is male-predominant irAE, most commonly seen in patients on anti-CTLA-4 mono- or combination therapy. Awareness among clinicians is critical when patients with elder age, lung or renal cancer develop hypophysitis, which indicates poor clinical outcomes. Female sex, anti-CTLA-4 monotherapy and co-occurrence of ICI-related diabetes are protective risk factors for poor prognosis.

Radio frequency fingerprint identification (RFFI) is an emerging device authentication technique, which exploits the hardware characteristics of the RF front-end as device identifiers. The receiver hardware impairments interfere with the feature extraction of transmitter impairments, but their effect and mitigation have not been comprehensively studied. In this paper, we propose a receiver-agnostic RFFI system by employing adversarial training to learn the receiver-independent features. Moreover, when there are multiple receivers, collaborative inference are designed to enhance classification accuracy. Finally, we show how it is possible to leverage fine-tuning for further improvement with fewer collected signals. To validate the approach, we have conducted extensive experimental evaluation by applying the approach to a LoRaWAN case study involving ten LoRa devices and 20 software-defined radio (SDR) receivers. The results show that receiver-agnostic training enables the trained neural network to become robust to changes in receiver characteristics. The collaborative inference improves classification accuracy by up to 20% beyond a single-receiver RFFI system and fine-tuning can bring a 40% improvement for underperforming receivers. The system is further evaluated on a more practical testbed. By making additional use of online augmentation and multi-packet inference, the identification accuracy is improved from 50% to 90% at 10 dB.

Deep learning-based physical-layer secret key generation (PKG) has been used to overcome the imperfect uplink/downlink channel reciprocity in frequency division duplexing (FDD) orthogonal frequency division multiplexing (OFDM) systems. However, existing efforts have focused on key generation for users in a specific environment where the training samples and test samples follow the same distribution, which is unrealistic for real-world applications. This article formulates the PKG problem in multiple environments as a learning-based problem by learning the knowledge such as data and models from known environments to generate keys quickly and efficiently in multiple new environments. Specifically, we propose deep transfer learning (DTL) and meta-learning-based channel feature mapping algorithms for key generation. The two algorithms use different training methods to pre-train the model in the known environments, and then quickly adapt and deploy the model to new environments. Simulation and experimental results show that compared with the methods without adaptation, the DTL and meta-learning algorithms both can improve the performance of generated keys. In addition, the complexity analysis shows that the meta-learning algorithm can achieve better performance than the DTL algorithm with less cost.

Wi-Fi sensing can classify human activities because each activity causes unique changes to the channel state information (CSI). Existing WiFi sensing suffers from limited scalability as the system needs to be retrained whenever new classes are added, which causes overheads of data collection and retraining. Cross-domain sensing may fail because the mapping between activities and CSI variations is destroyed when a different environment or user (domain) is involved. This paper proposed a few-shot learning-based WiFi sensing system, named FewSense, which can recognise novel classes in unseen domains with only a few samples. Specifically, a feature extractor was pre-trained offline using the source domain data. When the system was applied in the target domain, a few samples were used to fine-tune the feature extractor for domain adaptation. Inference was made by computing the cosine similarity. FewSense can further boost the classification accuracy by collaboratively fusing inference from multiple receivers. We evaluated the performance of FewSense using three public datasets, i.e., SignFi, Widar, and Wiar. The results show that FewSense with five-shot learning recognised novel classes in unseen domains with an accuracy of 93.9%, 96.5%, and 82.7% on the SignFi, Widar, and Wiar datasets, respectively. Our collaborative sensing model improved system performance by an average of 29.2%.

Anaerobic bacteria infections remain a major threat to humans. Oxidative stress mediated by photodynamic therapy (PDT) has shown great potential in antimicrobial applications, attributing to its controllability and non-resistance. However, the hypoxic infection microenvironment severely compromises the therapeutic outcomes. Here, we designed a nanoplatform comprising the initiator of alkyl radicals(R·), 2,2′-azobis[2-(2-imidazolin-2-yl)propane] dihydrochloride (AIPH) -loaded oxidized mesoporous carbon nanoparticles (OMCN) and then coated with a phase change material (PCM) nanoparticle for oxygen-independent PDT to combat anaerobic infections. Upon near-infrared (NIR) light irradiation, OMCN mediates the generation of heat to melt PCM, which could trigger the liberation and decomposition of AIPH to produce R· and further induce the oxidative damage to bacteria, and cooperate with optothermal effects to eradicate anaerobic bacteria. As results, the nanoplatform displays strong synergistic antibacterial behavior, effectively eliminating anaerobic Propionibacterium acnes(P. acnes) in vitro under hypoxic conditions, and successfully treating P. acnes-infected cutaneous abscess in mice models. Moreover, no distinct toxicity appears through the entire course of treatment. Collectively, this light-activated oxygen-independent PDT offers a novel approach to combat anaerobic bacteria infections.

Wireless body area network is a key enabler for connected healthcare but recent cyberattacks have compromised its security and trustworthiness. This paper investigates heartbeat-based key generation to secure body area networks. The interpulse intervals (IPIs) between any two adjacent peaks of heartbeat signals are random and state-of-the-art literature has demonstrated that IPI is a good random source to be extracted as cryptographic keys. Heartbeat signals can be measured by electrocardiography (ECG) and photoplethysmography (PPG) sensors. A general heartbeat-based key generation framework applicable to both ECG and PPG signals is proposed. A robust peak detection algorithm is designed to capture noisy peaks and a simple yet efficient IPI alignment algorithm to align the common IPIs. A key establishment protocol is used to convert analog IPIs to digital binaries and reconcile them between legitimate devices. We evaluate the performance for both ECG signals from an online public database, MIT PhysioBank, and PPG signals collected from our testbed. The results demonstrate that our algorithm is robust and heartbeat-based key generation can be completed for both ECG and PPG signals. We finally create a PPG-based prototype and a demonstration video to show the practicality of our framework.

Device authentication of wireless devices at the physical layer could augment security enforcement before fully decoding packets. At the upper layers of the stack, this is conventionally handled by cryptographic schemes. However, the associated computing overhead may make such regular approaches unsuitable for the emerging class of Internet of Things devices, which are typically resource-constrained and embedded in areas that make them difficult to retrieve and re-program. In contrast, radio frequency fingerprint identification (RFFI) exploits the unique hardware features as device identifiers at the physical layer. This article reviews both the state-of-the-art in engineered feature-based RFFI protocol design and advances in recent deep learning-based protocols, as well as a hybrid protocol that combines their advantages. Specifically, the hybrid approach leverages two methods: a more versatile distance-based classifier and an automatic feature extractor. This article also summarizes the goals of identification, verification and classification as applicable to RFFI, and how they can be achieved by the above protocols.

Radio frequency fingerprint identification (RFFI) is an authentication technique that identifies wireless devices by analyzing the characteristics of the received physical layer signals. In recent years, RFFI has been significantly enhanced by deep learning. A neural network (NN) is often leveraged to predict device identity. As a data-driven approach, deep learning requires the collection of large amounts of data for NN training. In addition, the RFFI system should be evaluated on datasets collected under various conditions to assess the system's robustness. However, only a few RFFI datasets are publicly available, and there are no clear guidelines for building an RFFI testbed for data collection. This article presents a tutorial to build both closed-set and openset RFFI systems. A LoRa-RFFI testbed is created as a case study and the implementation details are described in depth. The LoRa-RFFI testbed involves 60 commercial-off-the-shelf (COTS) LoRa development boards as devices to be identified, and a USRP N210 software-defined radio (SDR) platform for physical layer signal reception. Experiments are carried out using the implemented LoRa-RFFI testbed, and the collected datasets are made publicly available online. It is anticipated that this work can aid the research community in constructing RFFI testbeds and facilitate the development of RFFI research.

Personal sound zone (PSZ) refers to the technique that uses an array of loudspeakers and digital signal processing tools to achieve spatial soundfield control. To generate the target sound zones, this technique generally requires to know the acoustic transfer functions (ATFs) between the loudspeakers and the spots where soundfields are to be controlled. In practical applications, however, the true ATFs are never accessible and they have to be measured or estimated. Due to many sophisticated reasons, the measured ATFs generally deviate from the true ones, which may lead to significant degradation in performance of sound zone reproduction. In this work, a robust pressure matching (RPM) algorithm is presented for sound zone generation. It exploits a complex Gaussian mixture model (CGMM) to model the ATFs and their perturbations. The CGMM parameters are estimated using the expectation-maximization (EM) algorithm. To improve the robustness of the pressure matching method, an uncertainty constraint is applied to the ATF estimates and the pressure matching problem is then formulated as one of biconvex optimization. The coordinate descent algorithm is subsequently used to solve the optimization problem, thereby obtaining the optimal control filter. In comparison with the existing pressure matching methods without considering the effect of ATF perturbations, the presented algorithm is able to achieve lower normalized signal distortion energy and higher signal to interference ratio. Numerical simulations justify the effectiveness of the presented algorithm as well as its advantages over the traditional methods.

The sluggish reaction kinetics at the oxygen cathode is one of the important issues hindering the commercialization of the metal-air batteries. Although the noble metal can be used as the high-efficiency electrocatalyst to solve the problems to some extent, the high cost and scarcity of these noble-metal catalysts have limited their application in electrocatalysis. In this review, we discussed the mechanisms of the ORR and OER, and proposed the principles for the bifunctional electrocatalysts firstly, and then the state-of-the-art bifunctional catalysts, including carbon-based materials and transition-metal-based materials. On the basis of that, the self-supporting 3D noble-metal-free bifunctional ORR/OER catalysts were also discussed. Finally, the perspectives for the bifunctional electrocatalysts were discussed.

Objective:Thyroglobulin antibodies (TgAb), principally comprising immunoglobulin G (IgG), are frequently found in healthy individuals. Previously, we showed that the glycosylation levels of TgAb IgG differed across various thyroid diseases, suggesting an important role of glycosylation on antibodies in the pathogenesis of thyroid diseases. Since IgG1 and IgG4 are the primary TgAb IgG subclasses, this study aimed to investigate the glycosylation of TgAb IgG1 and IgG4 subclasses in thyroid diseases. Methods:TgAb IgG was purified by affinity chromatography from the serum of patients with Hashimoto’s thyroiditis (HT) (n= 16), Graves’ disease (GD) (n= 8), papillary thyroid carcinoma (PTC) (n= 6), and PTC with histological lymphocytic thyroiditis (PTC-T) (n= 9) as well as healthy donors (n= 10). TgAb IgG1 and IgG4 concentrations were determined by enzyme-linked immunosorbent assay, and a lectin microassay was used to assess TgAb IgG1 and IgG4 glycosylation. Results:Significantly elevated mannose, sialic acid, and galactose levels on TgAb IgG1 were found in HT and PTC patients compared to GD patients and healthy controls (all p< 0.05). The mannose, sialic acid, and core fucose levels on TgAb IgG1 in PTC-T patients were higher than in healthy controls (all p< 0.05). Additionally, TgAb IgG1 from PTC-T patients exhibited lower sialylation than that from patients with PTC and higher fucosylation than that from patients with HT (both p< 0.05). However, TgAb IgG4 glycosylation did not differ among the five groups (p< 0.05). Conclusion:Our study describes different distributions of TgAb IgG1 glycosylation in various thyroid diseases. The aberrantly increased glycosylation levels of TgAb IgG1 observed in HT, PTC, and PTC-T might be indicative of immune disorders and participate in the pathogenesis of these diseases.

Objective:Thyroglobulin antibodies (TgAb), principally comprising immunoglobulin G (IgG), are frequently found in healthy individuals. Previously, we showed that the glycosylation levels of TgAb IgG differed across various thyroid diseases, suggesting an important role of glycosylation on antibodies in the pathogenesis of thyroid diseases. Since IgG1 and IgG4 are the primary TgAb IgG subclasses, this study aimed to investigate the glycosylation of TgAb IgG1 and IgG4 subclasses in thyroid diseases. Methods:TgAb IgG was purified by affinity chromatography from the serum of patients with Hashimoto’s thyroiditis (HT) (n= 16), Graves’ disease (GD) (n= 8), papillary thyroid carcinoma (PTC) (n= 6), and PTC with histological lymphocytic thyroiditis (PTC-T) (n= 9) as well as healthy donors (n= 10). TgAb IgG1 and IgG4 concentrations were determined by enzyme-linked immunosorbent assay, and a lectin microassay was used to assess TgAb IgG1 and IgG4 glycosylation. Results:Significantly elevated mannose, sialic acid, and galactose levels on TgAb IgG1 were found in HT and PTC patients compared to GD patients and healthy controls (all p< 0.05). The mannose, sialic acid, and core fucose levels on TgAb IgG1 in PTC-T patients were higher than in healthy controls (all p< 0.05). Additionally, TgAb IgG1 from PTC-T patients exhibited lower sialylation than that from patients with PTC and higher fucosylation than that from patients with HT (both p< 0.05). However, TgAb IgG4 glycosylation did not differ among the five groups (p< 0.05). Conclusion:Our study describes different distributions of TgAb IgG1 glycosylation in various thyroid diseases. The aberrantly increased glycosylation levels of TgAb IgG1 observed in HT, PTC, and PTC-T might be indicative of immune disorders and participate in the pathogenesis of these diseases.

The inhibition performance of a mixture of an imidazoline quaternary ammonium salt (IM) and octylphenol polyoxyethene ether (OP) (IMO) toward carbon dioxide (CO2) corrosion of L245 steel in 3 wt% sodium chloride (NaCl) solution at 25°C was studied using electrochemical measurements. Notably, the inhibition efficiency of the IMO inhibitor stayed steadily in the long-term immersion test, and the inhibition efficiency increased with time. This was attributed to the improved electron-transfer performance between the inhibitor molecules and the metal surface. OP molecules promoted electrons to the metal, while IM molecules accepted electrons from the metal. The interactions between the inhibitor molecules and metal surface were enhanced, and the relative bonding intensities were improved. Moreover, the adsorption configurations of the mixture of IM and OP facilitated the improvement of the thickness and the compactness of the inhibitor layer. OP and IM showed a good synergistic inhibition effect.

All spatial active noise control (ANC) systems, when deployed in typical room environments, have time-varying acoustic channels between the secondary sources and the error microphones. The conventional online secondary path modeling techniques, which introduce additive auxiliary random noise to estimate the secondary paths, become challenging especially in a multichannel setup. In this work, we propose to use higher-order variable-directivity sound sources as secondary sources for spatial ANC, in which both the interior residual noise field within the control region and exterior sound field due to secondary source radiation are jointly controlled. The aim of controlling the exterior sound field is to minimize room reverberation generated by the secondary sources so that the secondary paths in the proposed algorithm can be approximated as free-field propagation and thus can be pre-calibrated. The system is implemented in an adaptive manner to track noise variations. The results show that the proposed method can effectively cancel spatial noise field and control exterior sound field at an acceptable low level in time-varying room environments.

This study numerically investigates the combustion characteristics in a swirl burner for CO-H2syngas by large eddy simulation. Firstly, experimental data are used to verify the applicability of the Boivin mechanism and the Sandia mechanism. The simulation results show that the Boivin mechanism predicts a more reasonable flame structure. Then, Syngas25, Syngas45, and Syngas100 (composed of 25%, 45%, and 100% H2by volume, respectively) are set to numerically investigate the effect of hydrogen addition ratio on combustion characteristics by using the dynamic Smagorinsky model and the partially stirred reactor model. The detailed simulation data shows that the addition of hydrogen greatly influences the flame structure and flow field; with an increase in hydrogen addition, the flame length shortens, the temperature rises, and flashback caused by combustion induced vortex breakdown occurs. Furthermore, the precessing vortex core cannot exist stably in Syngas100, though it can be clearly observed in other cases.

Background: sex differences existed in animal behavioral adaption and activity rhythms when exposed to chronic disruption of the circadian rhythm. Whether these differences extend to cardiac performance has not been fully investigated by cardiac imaging technology.

Anti-CD19 chimeric antigen receptor (CAR) T cell therapies can cause severe cytokine-release syndrome (CRS) and neurotoxicity, impeding their therapeutic application. Here we generated a new anti-CD19 CAR molecule (CD19-BBz(86)) derived from the CD19-BBz prototype bearing co-stimulatory 4-1BB and CD3ζ domains. We found that CD19-BBz(86) CAR T cells produced lower levels of cytokines, expressed higher levels of antiapoptotic molecules and proliferated more slowly than the prototype CD19-BBz CAR T cells, although they retained potent cytolytic activity. We performed a phase 1 trial of CD19-BBz(86) CAR T cell therapy in patients with B cell lymphoma (ClinicalTrials.gov identifier NCT02842138). Complete remission occurred in 6 of 11 patients (54.5%) who each received a dose of 2 × 108–4 × 108CD19-BBz(86) CAR T cells. Notably, no neurological toxicity or CRS (greater than grade 1) occurred in any of the 25 patients treated. No significant elevation in serum cytokine levels after CAR T cell infusion was detected in the patients treated, including in those who achieved complete remission. CD19-BBz(86) CAR T cells persistently proliferated and differentiated into memory cells in vivo. Thus, therapy with the new CD19-BBz(86) CAR T cells produces a potent and durable antilymphoma response without causing neurotoxicity or severe CRS, representing a safe and potent anti-CD19 CAR T cell therapy.

Controlling the packing arrangements of dyes is a facile way of tuning their photophysical and/or photochemical properties, thus enabling new sensing mechanisms for photofunctional tools. Here, we present a general and robust strategy toward water-stable J-aggregated dye-templated nanoassemblies by incorporating an amphiphilic diblock copolymer and a stimuli-responsive dye as the only two building components. An iodo-substituted boron dipyrromethene (BODIPY) was adopted as a template to direct the self-assembly of poly(ethylene glycol)-block-polycaprolactone (PEG–PCL), forming a core–shell nanoplate with slip-stacked BODIPYs as core surrounded by hydrophilic PEG shell. The self-assembled nanoplate is stable in cell culture medium and possesses a built-in stimuli-responsiveness that arises from BODIPY bearing meso-carboxylate protecting group, which is efficiently removed upon treatment with peroxynitrite. The resulting negative charges lead to rearrangement of dyes from J-stacking to nonstacking, which activates photoinduced singlet oxygen production from the nanoassemblies. The stimuli-activatable photosensitivity has been exploited for specific photodynamic ablation of activated RAW 264.7 cells with excessive endogenous peroxynitrite. In light of the generality of the sensing mechanism, the concept described herein will significantly expand the palette of design principles to develop diverse photofunctional tools for biological research and clinical needs.

A low-complexity, yet secure framework is proposed for protecting the IoT and for achieving both authentication and secure communication. In particular, the slight random difference among transceivers is extracted for creating a unique radio frequency fingerprint and for ascertaining the unique user identity. The wireless channel between any two users is a perfect source of randomness and can be exploited as cryptographic keys. This can be applied to the physical layer of the communications protocol stack. This article reviews these protocols and shows how they can be integrated to provide a complete IoT security framework. We conclude by outlining the future challenges in applying these compelling physical layer security techniques to the IoT.

Glycine exerts renoprotective effects, but the mechanism remains unclear. Glycine is increasingly recognized as a factor that attenuates oxidative stress, a key mechanism underlying diabetic nephropathy. In this study, we investigated the effects of glycine on diabetic renal injury and oxidative stress by adding 1% glycine in the drinking water of rats with streptozotocin-induced diabetes for 20 weeks. Glycine levels decreased in the plasma and kidney homogenates of diabetic rats but were restored by oral glycine administration. In these diabetic rats, glycine attenuated renal damage, as evidenced by the decreased mesangial expansion, tubular interstitial fibrosis, and neutrophil gelatinase-associated lipocalin (NGAL) expression. Glycine also ameliorated the raise in urinary malondialdehyde (MDA) levels and partially restored renal glutathione levels in diabetic rats. Renal levels of the Nox4 mRNA and protein, a major source of renal oxidative stress, were suppressed by the treatment with glycine. Immunohistological analysis revealed that glycine had protective effects on the tubular area rather than the glomerular area. Our results strongly suggest that the protective effect of glycine on renal oxidative stress and structural damage may be linked to enhancement of GSH synthesis and suppression of renal Nox4 expression in diabetic rats.

•LES coupled with PaSR model is employed for swirl-stabilized NH3/CH4combustion.•Swirl intensity has a non-linear contribution to ammonia combustion enhancement.•Selective non-catalytic reduction of NO is the key to controlling NO emission.•Medium swirl number is proper to control NO emission and ensure flame stability.

To investigate the clinical characteristics of Addison’s disease caused by adrenal tuberculosis in Tibet. After the anti-tuberculosis treatment, the clinical features between continuous glucocorticoid therapy and glucocorticoid withdrawal were analyzed.

Microarc oxidation (MAO) coating is effective in improving the corrosion resistance of magnesium (Mg) alloys in a simulated body fluid. MAO coatings were deposited on AZ31 magnesium alloy at different pulse frequencies. Samples were immersed in Earle’s balanced salt solution (EBSS) up to 21 d. Scanning electron microscopy, potentiodynamic polarisation testing, electrochemical impedance spectroscopy and X-ray diffraction (XRD) were performed to evaluate the corrosion behaviour of MAO coatings in EBSS compared to that of the uncoated AZ31. MAO-coated samples demonstrated improved corrosion resistance compared to the bare AZ31 throughout the corrosion period, indicating that MAO coating exhibited good corrosion protection of AZ31 in EBSS. Given the same immersion time, MAO-coated samples showed decreased corrosion current density and increased electrochemical impedance with increasing pulse frequency. The coating produced at 3000 Hz exhibited the best corrosion resistance compared to the ones produced at 300, 500 and 1000 Hz due to its uniform and dense structure. The XRD analysis showed that the corrosion products presented on the surface of the MAO-coated samples after immersion into the EBSS for 21 d were primarily composed of magnesium hydroxide, quintinite and hydroxyapatite. The corrosion mechanism of the MAO-coated AZ31 samples in EBSS is also discussed.

Reversibly controlling the dye arrangements in living systems has great potential to realize spatiotemporally controlled photomedicine. However, tuning or even maintaining a certain arrangement of dyes in a complex living environments is extremely challenging due to the interference of the various biological species. Herein, a conceptual supramolecular strategy to engineer a switchable photosensitizer (PS) via mitochondria‐mediated dynamic interconversion between monomer and J‐aggregation, enabling specific activation of the mitochondria‐targeting photodynamic therapy (PDT) and hibernation after mitochondria damage is presented. The presented mitochondria‐mediated “activate‐then‐hibernate” PS design enables a fascinating spatiotemporally controlled PDT in which spatially controlled mitochondrial‐targeting enhances therapeutic efficacy and temporally controlled activation‐then‐hibernation averts off‐target damage during PDT and tissue damage after clinical treatment, thus offering significant potential for biological research and clinical needs. A novel switchable photosensitizer (PS) based on mitochondria‐mediated dynamic interconversion between monomeric and J‐aggregation states is developed, allowing specific mitochondria‐targeted photoactivity activation and hibernation post cell apoptosis. The presented mitochondria‐mediated “activate‐then‐hibernate” PS design enables a fascinating spatiotemporally controlled PDT, thus offering significant potential for biological research and clinical needs.

Ten new phenylpropanoid glucosides, tadehaginosides A–J (1–10), and the known compound tadehaginoside (11) were obtained from Tadehagi triquetrum. These phenylpropanoid glucosides were structurally characterized through extensive physical and chemical analyses. Compounds 1and 2represent the first set of dimeric derivatives of tadehaginoside with an unusual bicyclo[2.2.2]octene skeleton, whereas compounds 3and 4contain a unique cyclobutane basic core in their carbon scaffolds. The effects of these compounds on glucose uptake in C2C12 myotubes were evaluated. Compounds 3–11, particularly 4, significantly increased the basal and insulin-elicited glucose uptake. The results from molecular docking, luciferase analyses, and ELISA indicated that the increased glucose uptake may be due to increases in peroxisome proliferator-activated receptor γ (PPARγ) activity and glucose transporter-4 (GLUT-4) expression. These results indicate that the isolated phenylpropanoid glucosides, particularly compound 4, have the potential to be developed into antidiabetic compounds.

Chromium-based pretreatments are among the most successful systems for aluminum-based alloys, however, due to environmental and health concerns, chromium-based compounds are a target for replacement. Sol–gel approach has emerged as a versatile method for preparing a host of sol–gel hybrid coatings that are candidates for use in protective coating applications. Organic–inorganic hybrid sol–gel coatings are among the most attractive alternatives to the use of chromium-based coatings because they are highly adherent and chemically inert coatings that are covalently bonded on the metal substrates at low temperature near ambient. In this review, the authors aim to summarize the latest achievements and strategies for the sol–gel process parameters as well as other factors that influence the corrosion properties of the organic–inorganic hybrid sol–gel coatings for the corrosion protection of aluminum-based alloys. The authors also discuss the existing issues and challenges in anticorrosion performance of the organic–inorganic hybrid sol–gel coatings.

Hashimoto’s thyroiditis (HT) can be divided into IgG4 HT and non-IgG4 HT based on IgG4 and IgG immunohistochemical staining. In clinical practice, it is often necessary to identify diseases such as primary thyroid lymphoma (PTL) and IgG4 HT when a patient presents with a rapidly enlarged thyroid. The aim of our study was to uncover the differential points between the two diseases.Clinical information from 19 IgG4 HT and 10 PTL patients was obtained from the patients’ medical records, including age, sex, main clinical manifestation, thyroid functional status, the presence of serum anti-thyroid peroxidase antibodies, anti-thyroglobulin antibodies, and thyroid ultrasonography results. Thyroid sections from all patients were collected to detect IgG4 and IgG expression by immunohistochemical staining.The IgG4 HT patients were significantly younger than those in the PTL group (39.68 ± 10.95 vs 66.20 ± 10.23 years, P< 0.001). There were no significant differences in the sex distribution or TgAb- or TPOAb-positive rates. The PTL group had a higher prevalence of clinical hypothyroidism than the IgG4 HT group (P= 0.016). In the PTL group, thyroid lesions were more likely to exhibit hypoechogenicity (6/6 vs 1/19, P< 0.001) on ultrasound images. In the PTL group, two patients met the immunohistochemical cut-off value of the criteria for IgG4 HT.Simply relying on immunohistochemistry for IgG4 cannot diagnose IgG4 HT correctly when a patient presents with rapid thyroid enlargement. A combination of clinical and pathological analyses will help distinguish IgG4 HT from PTL which may be with abundant IgG4-positive plasma cells.