Shanghai Jiao Tong University

Based on the size of bacterial cells and bacterial surface hydrophobicity, some bacteria meets the requirements of Pickering particles to stabilize Pickering emulsions. Here, we discuss the oil-water interfaces of bacteria-stabilized Pickering emulsions as microhabitats for microbial metabolism of oil-soluble chemicals. The correlation between living bacteria-stabilized Pickering emulsions and microhabitats of living bacteria at oil-water interfaces offers a new perspective to study bioprocess engineering at the mesoscale between cell and reactor scales, which not only provides some novel parameters to optimize the bioprocess engineering, but also unravels the paradox of some natural phenomena related to living cell biocatalysis.

Objective The distribution and size of the zone of the centers of resistance (ZCR) are critical for accurate orthodontic treatments and minimizing unexpected tooth movements. However, this information remains unclear for mandibular incisors and canines. This study aims to address these gaps in knowledge. Methods Finite element models of four incisors and canines from four individuals were created. Four centers of resistance (CRs) under four orthodontic directions (0° ~ 45° ~ 90° ~ 135° to the sagittal plane in the horizontal plane) were assessed by a novel method. The height of the CRs was normalized to a percentage of the long axis, and the offsets were expressed as a distance value after normalization. The ZCR was obtained by fitting a 90% confidence sphere of the CR distribution. Validation was conducted to find the perturbations when the positions out of the zone were applied. Results The maximum variation of CR in the heights under four directions was 5.17% and 3.70% for the incisors and canines, respectively. The maximum offset between the CR and long axis was 0.14 mm in incisors and 0.99 mm in canines. The height of the zone in the incisor and canine was 57.75% and 59.72%, and the radius of the zone was 0.60 mm and 0.65 mm, respectively. The force-acting point outside the zone produced a large rotation, which was unexpected. Conclusions The ZCR of mandibular incisors located slightly lower than that of canines, but they were almost the same size. The ZCR was recommended as the “gold reference” for orthodontics to reduce unexpected movement.

We propose a dual-comb broadband microwave vector network analyzer (VNA). One of the optical frequency combs (OFCs) beats with a continuous wave (CW) light to generate the stimulus signal of the device under test, which is a multi-tone signal within a wide bandwidth. Another OFC with slightly different repetition frequency samples the scattering signal and then coherently beats with the CW light, to convert the scattering signal into the intermediate frequency (IF) signal. Thanks to the dual-comb technology, the requirement for the electrical devices is lessened. A wide measurement frequency range can be achieved by sweeping the frequency of the CW light within a narrow range, giving the credit that the multi frequencies in the stimulus signal sweep simultaneously. An electrical back end with narrow bandwidth and low sampling rate can be used to acquire the scattering parameters (S parameters), owing to the fact that the IF signal locates at the low-frequency band and has the fixed frequencies during frequency sweeping. In the experiments, the S parameters of a 25-GHz low-pass filter within 0.001-69.88 GHz is measured by the proposed VNA, utilizing a microwave signal with a frequency sweeping range of about 5 GHz and an electrical back end with a bandwidth of 200 MHz and a sampling rate of 312.5 MHz.

Continuous wave (CW) photomixing is a widely utilized method for terahertz (THz) radiation generation, with diverse applications in sensing, spectroscopy, and wireless communication. However, most existing systems are dependent on discrete, bulky components, highlighting the demand for integrated solutions that can enhance energy efficiency, flexibility, and stability. Here, we exploit the advantages of silicon photonics within the THz domain utilizing a hybrid-integrated dual III-V/Si3N4 narrow-linewidth laser module to generate widely tunable THz waves, whose frequency is determined by the frequency difference of the lasers. To enhance the frequency stability of the produced THz signal, we synchronize thermal noise by integrating two external laser cavities on the same chip. Further, synchronization of electrical noise is accomplished by electrically connecting the two gain sections in series using a low-noise current source. The external cavity lasers incorporating low-loss Si3N4 microring resonator (MRR) filters, deliver optical power up to 13 dBm, exhibit a broad wavelength tuning range of approximately 55 nm, and maintain a narrow optical intrinsic linewidth below 0.77 kHz. By adjusting the laser frequency interval in the heterodyne synthesis setup, we achieved CW THz generation over a wide tuning range from 95.2 GHz to 1.012 THz. The 3-dB THz electrical linewidth is estimated to be less than 31 kHz. As far as we know, this represents the narrowest linewidth for THz signals generated by heterodyne synthesis with free-running integrated sources over such a wide tuning range. The hybrid-integrated narrow-linewidth compact dual laser module possesses a long-term THz frequency drift of 65 MHz, measured for 10 hours. Our study therefore highlights the huge potential of silicon photonics technology in the THz domain.

Fiber-form optics extends the high-resolution tomographic imaging capabilities of optical coherence tomography (OCT) to the inside of the human body, i.e., endoscopic OCT. However, it still faces challenges due to the trade-off between probe size, resolution, and depth of focus (DOF). Here we introduce a method for extending the DOF in endoscopic OCT with high uniformity and efficiency. On the basis of multi-level diffractive optics, we leverage the multi-dimensional light-field modulation capabilities of computer-generated holography (CGH) to achieve precise control of the intensity distribution of the off-axis portion of the OCT probe light. Our method eliminates the need for an objective lens, allowing for direct fabrication at the distal facet of a single-mode fiber using femtosecond laser two-photon 3D printing. The superiority of our method has been verified through numerical simulation, beam measurement, and imaging results obtained with our home-built endoscopic OCT system.

The far-lateral approach, frequently employed by skull base surgeons, targets lesions in the ventrolateral region of the craniovertebral junction (CVJ). Although various incisions can be utilized, the linear incision is notably less invasive and more efficient. Despite its advantages, the literature lacks a comprehensive description of the technical steps involved in this approach. We discuss the pertinent surgical anatomy and provide a step-by-step intraoperative description of performing the linear incision far-lateral approach, accompanied by clear intraoperative photographs. The linear incision for the far-lateral approach reduces the extent of soft tissue dissection while having a negligible impact on surgical exposure. Key factors for ensuring the procedure safe and effective include: (1) a comprehensive understanding of the surgical anatomy in the suboccipital region and accurate identification of the midline from this specific position and incision; and (2) employing the “interfascial-subperiosteal-interdural dissection” technique to manage the soft tissues around the CVJ, thereby minimizing the risk of vertebral artery injury.

Study design Retrospective. Objective To explore the value of time-resolved CE-MRA in evaluating and locating the SVM prior to digital subtraction angiography (DSA). Summary of Background Data Spinal vascular malformations (SVM) can be detected with time-resolved contrast-enhanced MRA(CE-MRA). Materials and Methods 178 patients with suspected SVM who underwent time-resolved CE-MRA examination and DSA were included in this study. DSA served as the reference standard. The type of SVM, feeding arteries, fistula/nidus, and proximal segment of draining veins were evaluated on time-resolved CE-MRA. The diagnostic performance and classification performance of time-resolved CE-MRA in the diagnosis of SVM is summarized in terms of overall accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV). The difference of catheterized vessels during spinal vascular DSA between actual and estimated number was also analyzed. Results 147 patients were diagnosed with SVM (20 cervical, 118 thoracolumbar, and 9 deep lumbosacral) and 31 patients were diagnosed with non-SVM according to DSA findings. The diagnostic sensitivity, specificity, PPV, NPV, and accuracy of time-resolved CE-MRA for subtype of SVM were 0.961, 0.961, 0.993, 0.806 and 0.961, respectively. The overall accuracy of time-resolved CE-MRA for the diagnosis of SVM was 0.821, and was 0.783, 0.793, and 0.778 for cervical, thoracolumbar, and deep lumbosacral SVM, respectively. The actual number of catheterized vessels during spinal vascular DSA with time-resolved CE-MRA as the reference was lower than the estimated number of catheterized vessels in both SVM and non-SVM patients ( P <0.001). Conclusion Time-resolved CE-MRA could accurately evaluate SVM and reduce the number of catheterized vessels during spinal vascular DSA.

A novel nickel‐based metal organic framework (MOF) [Ni(FDC)(CH3OH)1.5(H2O)0.5](H2O)0.35 (UOW‐6) utilizing biomass‐derived 2,5‐furan dicarboxylate (FDC) as a ligand is reported as an electrocatalyst for anodic ethylene glycol oxidation with cathodic hydrogen evolution. The MOF structure was analyzed using single crystal X‐ray‐diffraction, TGA and thermodiffractometry, to establish its structure and verify phase purity. The material was dropcast on carbon fiber paper as a catalyst, and by using a three‐electrode system, UOW‐6 requires only 1.47 V to attain a current density of 50 mAcm‐2. During oxidation of the ethylene glycol (EG), UOW‐6 shows unprecedented selectivity towards formic acid with a Faradaic efficiency of 94% and remarkable stability over 20 days. The combination of electrochemical measurements and in situ Raman confirmed in situ formed NiOOH at the surface of UOW‐6 as the catalytically active sites for EG oxidation. This work not only presents a pioneering application of FDC‐based MOFs for polyethylene terephthalate (PET) upcycling but also underscores the potential of electrocatalysis in advancing sustainable plastic valorization strategies.

Interstitial cystitis/bladder pain syndrome is a chronic pain syndrome of elusive etiology, accompanied by lower urinary tract symptoms. Over the past decades, many studies have been carried out for exploration of more effective therapies against IC/BPS. However, the results have been inconsistent, probably due to the multifactorial nature of IC/BPS. We establish a model of IC/BPS in mice by combining protamine sulfate /lipopolysaccharide and phenylephrine. Typical histological changes and symptoms were observed. We then explored the effectiveness of artesunate (ART), which has been reported to alleviate autoimmune diseases. Phenotypic tests demonstrated a significant reduction in symptoms. Histological staining showed pathological improvement. WGCNA identified three gene modules specifically related to IC/BPS, and six genes were identified as hub genes. CIBERSORT analysis showed that the activated NK cells seem to be decreased in IC modeling group and partially restored in IC + ART group, whereas the resting NK cells showed the opposite trend. Single‐cell transcriptomic analysis elaborated on the changing trends of subgroups of infiltrated immune cells, including T cells, NK cells, and dendritic cells. Our study represents our effort in establishing a reliable and reproducible IC/BPS murine model, and the first study using scRNA‐seq in exploring the immune microenvironment of the IC/BPS murine model, and the possible molecular mechanisms of ART treatment in IC/BPS. Further studies are needed to confirm the effect of ART in IC/BPS patients.

Purpose The objective of this study is to generate reliable Ki parametric images from a shortened [¹⁸F]FDG total-body PET for clinical applications using a self-supervised neural network algorithm. Methods We proposed a self-supervised neural network algorithm with Patlak graphical analysis (SN-Patlak) to generate Ki images from shortened dynamic [¹⁸F]FDG PET without 60-min full-dynamic PET-based training. The algorithm deeply integrates neural network architecture with a Patlak method, employing the fitting error of the Patlak plot as the neural network’s loss function. As the 0–60 min blood time activity curve (TAC) required by the standard Patlak plot is unobtainable from shortened dynamic PET scans, a population-based “normalized time” (integral-to-instantaneous blood concentration ratio) was used for the linear fitting of Patlak plot of t* to 60 min, and the modified Patlak plot equation was then incorporated into the neural network. Ki images were generated by minimizing the difference between the input layer (measured tissue-to-blood concentration ratios) and the output layer (predicted tissue-to-blood concentration ratios). The effects of t* (20 to 50 min post injection) on the Ki images generated from the SN-Patlak and standard Patlak was evaluated using the normalized mean square error (NMSE), and Pearson’s correlation coefficient (Pearson’s r). Results The Ki images generated by the SN-Patlak are robust to the dynamic PET scan duration, and the Ki images generated by the SN-Patlak from just a 10-minute (50–60 min post-injection) dynamic [¹⁸F]FDG total-body PET scan are comparable to those generated by the standard Patlak method from 40-min (20–60 min post injection) with NMSE = 0.15 ± 0.03 and Pearson’s r = 0.93 ± 0.01. Conclusions The SN-Patlak parametric imaging algorithm is robust and reliable for quantification of 10-min dynamic [¹⁸F]FDG total-body PET.

Intracerebral calcium deposition, classified into primary familial brain calcification (PFBC) and secondary brain calcification, occurs within the brain parenchyma and vasculature. PFBC manifests with progressive motor decline, dysarthria, and cognitive impairment, with limited treatment options available. Recent research has suggested a link between dysfunction of the blood–brain barrier (BBB) and PFBC, with certain genetic variants potentially affecting neurovascular unit (NVU) function, thereby contributing to BBB integrity disruption and brain calcification. Cell junctions play an indispensable role in maintaining the function of NVUs. The pathogenic mechanisms of PFBC‐causative genes, such as PDGFRB, PDGFB, MYORG, and JAM2, involve NVU disruption. Cell junctions, such as tight junctions, gap junctions, adherens junctions, desmosomes, hemidesmosomes, and focal adhesions, are vital for cell–cell and cell–extracellular matrix connections, maintaining barrier function, cell adhesion, and facilitating ion and metabolite exchange. Several recent studies have highlighted the role of mutations in genes encoding cell junction proteins in the onset and progression of brain calcification and its related phenotypes. This emerging body of research offers a unique perspective for investigating the underlying mechanisms driving brain calcification. In this review, we conducted an examination of the literature reporting on genetic variants in cell junction proteins associated with brain calcification to delineate potential molecular pathways and investigate genotype–phenotype correlations. This approach not only reinforces the rationale for molecular subtyping of brain calcification but also lays the groundwork for the discovery of novel causative genes involved in pathogenesis. © 2024 International Parkinson and Movement Disorder Society.

Background Second-generation antipsychotics (SGAs) frequently cause metabolic syndrome (MetS), which raises the risk of heart disease, type 2 diabetes, morbid obesity, atherosclerosis, and hypertension. MetS also impairs cognitive function in patients with schizophrenia. However, the fundamental reasons of MetS caused by SGAs are not yet fully understood. Thus, we aimed to identify potential therapeutic targets for MetS induced by SGAs. Methods The serum biochemical parameters and the RNA-sequencing of peripheral blood mononuclear cells were measured in three groups (healthy controls and patients with schizophrenia with and without MetS taking SGAs). The study of the weighted gene co-expression network was utilized to pinpoint modules that were significantly connected to clinical markers. Results Statistical analysis showed significant differences in triglyceride and high-density lipoprotein among the three groups. The TNF signaling pathway, TGF-β signaling pathway, fatty acid metabolism, NF-kappa B signaling pathway, MAPK signaling pathway, and Toll-like receptor signaling pathway were the pathways that were primarily enriched in the two unique co-expression network modules that were found. Finally, five specific genes (TNF, CXCL8, IL1B, TIMP1, and ESR1) associated with metabolism and immunity pathways were identified. Conclusions This study indicated that SGAs differentially induced MetS of patients with schizophrenia through metabolic and inflammation-related pathways. Therefore, the potential side effects of drugs on inflammatory processes need to be considered when using SGAs for the treatment of schizophrenia.

Recently, substantial research has been conducted on sequential recommendation, with the objective of forecasting the subsequent item by leveraging a user's historical sequence of interacted items. Prior studies employ both capsule networks and self-attention techniques to effectively capture diverse underlying intents within a user's interaction sequence, thereby achieving the most advanced performance in sequential recommendation. However, users could potentially form novel intents from fresh interactions as the lengths of user interaction sequences grow. Consequently, models need to be continually updated or even extended to adeptly encompass these emerging user intents, referred as incremental multi-intent sequential recommendation. In this paper, we propose an effective I ncremental learning framework for user M ulti-intent A daptation in sequential recommendation called IMA, which augments the traditional fine-tuning strategy with the existing-intents retainer, new-intents detector, and projection-based intents trimmer to adaptively expand the model to accommodate user's new intents and prevent it from forgetting user's existing intents. Furthermore, we upgrade the IMA into an E lastic M ulti-intent A daptation (EMA) framework which can elastically remove inactive intents and compress user intent vectors under memory space limit. Extensive experiments on real-world datasets verify the effectiveness of the proposed IMA and EMA on incremental multi-intent sequential recommendation, compared with various baselines.

This paper proposes a novel anti-intelligent jamming framework for unmanned aerial vehicle (UAV) networks. Multiple UAV-to-UAV communication pairs aim to maximize their sum rates with minimal power consumption, where each UAV adaptively adjusts its transmit channel and power in a distributed way to avoid intelligent jamming and co-channel interference. A ground jammer attempts to disrupt the communication quality of the UAV network by adaptively altering its jamming channel and power. We model the anti-jamming problem as a stochastic Stackelberg game, where the intelligent jammer is the leader and the UAV pairs are the followers. Considering that both parties are unwilling to share their utility functions and transmission policies, we propose reinforcement learning (RL) algorithms to solve the best response policies of each agent in the game. We adopt deep Q network (DQN) algorithm to decide the jamming policy at the jammer and propose a decentralized federated learning-assisted DQN algorithm to determine the collaborative anti-jamming policies at the UAV pairs. Simulation results demonstrate that the performance of the proposed algorithm achieves an improvement of 23.3% in anti-jamming performance compared with the independent DQN algorithm.

Human activity recognition (HAR) with wearables is one of the serviceable technologies in ubiquitous and mobile computing applications. The sliding-window scheme is widely adopted while suffering from the multi-class windows problem. As a result, there is a growing focus on joint segmentation and recognition with deep-learning methods, aiming at simultaneously dealing with HAR and time-series segmentation issues. However, obtaining the full activity annotations of wearable data sequences is resource-intensive or time-consuming, while unsupervised methods yield poor performance. To address these challenges, we propose a novel method for joint activity segmentation and recognition with timestamp supervision, in which only a single annotated sample is needed in each activity segment. However, the limited information of sparse annotations exacerbates the gap between recognition and segmentation tasks, leading to sub-optimal model performance. Therefore, the prototypes are estimated by class-activation maps to form a sample-to-prototype contrast module for well-structured embeddings. Moreover, with the optimal transport theory, our approach generates the sample-level pseudo-labels that take advantage of unlabeled data between timestamp annotations for further performance improvement. Comprehensive experiments on four public HAR datasets demonstrate that our model trained with timestamp supervision is superior to the state-of-the-art weakly-supervised methods and achieves comparable performance to the fully-supervised approaches.

Implementation aspects of fault-ride-through (FRT) operation in voltage source converter with virtual synchronous generator (VSG) control are discussed in this paper. The phenomenon of voltage decline during fault periods is recognized to be intricately associated with the interplay between power angle movement and the trajectory of current saturation resulting from the application of current limiters. It is explained how the output reactive power is restricted once the current reaches its limit, thus rendering the manipulation of reactive power not unconditionally achievable. It is also revealed that preferably voltage support and robust transient angle stability can be attained by minimizing power angle movement and allowing reactive power to be naturally generated instead of explicitly specifying reactive power commands from the controller. Motivated by these findings, a novel FRT strategy is proposed to attain the desired FRT performance, which features a smooth transition between fault and normal states, non-invasiveness in the existing control loop, and independence from system parameters and fault detection. The proposed FRT strategy is applicable for both symmetric and asymmetric faults, and its effectiveness is verified on four types of short circuit fault, various grid condition, and an IEEE-14 bus system. A comparative simulation with a previous FRT strategy is conducted to highlight the advantage of the proposed method. Furthermore, the proposed strategy is also verified through the controller hardware-in-loop (CHIL) experiment.