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Abstract The size of InGaN micro-LEDs is continuously decreasing to meet the demands of various emerging applications, especially in tiny micro-displays such as AR/VR. However, the conventional pixel definition based on plasma etching significantly damages the mesa sidewalls, leading to a severe reduction in efficiency as the micro-LED size decreases. This seriously impedes the development and application of micro-LEDs. In this work, we comprehensively explain the origin of micro-LED sidewall effects and corresponding physical models. Subsequently, we systematically review recent progress in micro-LED fabrication aiming at suppressing sidewall effects. Furthermore, we discuss advancements in micro-LED fabrication with “damage-free” techniques, which hold the potential to fundamentally address the issue of plasma damage in the micro-LED process. We believe this review will deepen the understanding of micro-LED sidewall effects and provide a better insight into the latest associated fabrication technologies for high-efficient InGaN micro-LEDs.

Abstract We explore the decay of bound neutrons in the JUNO liquid scintillator detector into invisible particles (e.g., $$n\rightarrow 3 \nu $$ n → 3 ν or $$nn \rightarrow 2 \nu $$ n n → 2 ν ), which do not produce an observable signal. The invisible decay includes two decay modes: $$ n \rightarrow { inv} $$ n → inv and $$ nn \rightarrow { inv} $$ n n → inv . The invisible decays of s-shell neutrons in $$^{12}\textrm{C}$$ 12 C will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $${\bar{\nu }}_e$$ ν ¯ e , natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $$\tau /B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, \textrm{years}$$ τ / B ( n → inv ) > 5.0 × 10 31 years and $$\tau /B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, \textrm{years}$$ τ / B ( n n → inv ) > 1.4 × 10 32 years .

Abstract Poly (ADP-ribose) polymerase 1 (PARP1) catalyzes poly (ADP) ribosylation reaction, one of the essential post-translational modifications of proteins in eukaryotic cells. Given that PARP1 inhibition can lead to synthetic lethality in cells with compromised homologous recombination, this enzyme has been identified as a potent target for anti-cancer therapeutics. However, the clinical application of existing PARP1 inhibitors is restrained by side effects associated with DNA trapping and off-target effects, highlighting the need for improved therapeutic strategies. By integrating protein degradation technology, we synthesized a PROTAC molecule 180055 based on the Rucaparib junction and VHL ligand, which efficiently and selectively degraded PARP1 and inhibited PARP1 enzyme activity without a noticeable DNA trapping effect. Furthermore, 180055 kills tumor cells carrying BRCA mutations with a minor impact on the growth of normal cells both in vitro and in vivo. This suggests that 180055 is a PARP1-degrading compound with excellent pharmacological efficacy and extremely high biological safety that deserves further exploration and validation in clinical trials.

Abstract Strong light-matter interaction provides opportunities for tailoring the physical properties of quantum materials on the ultrafast timescale by forming photon-dressed electronic states, i.e., Floquet-Bloch states. While the light field can in principle imprint its symmetry properties onto the photon-dressed electronic states, so far, how to experimentally detect and further engineer the symmetry of photon-dressed electronic states remains elusive. Here by utilizing time- and angle-resolved photoemission spectroscopy (TrARPES) with polarization-dependent study, we directly visualize the parity symmetry of Floquet-Bloch states in black phosphorus. The photon-dressed sideband exhibits opposite photoemission intensity to the valence band at the Γ point, suggesting a switch of the parity induced by the light field. Moreover, a “hot spot” with strong intensity confined near Γ is observed, indicating a momentum-dependent modulation beyond the parity switch. Combining with theoretical calculations, we reveal the light-induced engineering of the wave function of the Floquet-Bloch states as a result of the hybridization between the conduction and valence bands with opposite parities, and show that the “hot spot” is intrinsically dictated by the symmetry properties of black phosphorus. Our work suggests TrARPES as a direct probe for the parity of the photon-dressed electronic states with energy- and momentum-resolved information, providing an example for engineering the wave function and symmetry of such photon-dressed electronic states via Floquet engineering.

Highlights A double-layered protective film based on zinc-based coordination compound and ZnF2-rich solid electrolyte interphase layer has been successfully fabricated on the zinc metal anode via electrode/electrolyte synergistic optimization. The double-layered architecture can effectively modulate Zn2+ flux and suppress the zinc dendrite growth, thus facilitating the uniform zinc deposition. The as-developed zinc-(dual) halogen batteries based on double-layered protective film can present high areal capacity and satisfactory cycling stability.

Nowadays, Wireless Mesh Networks (WMNs) are widely deployed in communication areas due to their ease of implementation, dynamic self-organization, and cost-effectiveness. The design of routing protocols is critical for ensuring the performance and reliability of WMNs. Although there have been numerous experimental works on WMNs in the past decade, only a few of them have been tested in real-world scenarios. This article presents a comparative analysis of three proactive routing protocols, OLSR, BATMAN, and Babel, using Raspberry Pi 4 devices. The evaluation, conducted at Al-Farabi Kazakh National University, covers both indoor and outdoor scenarios, focusing on key metrics such as bandwidth, Packet Delivery Ratio (PDR), and jitter. In outdoor scenarios, OLSR achieved the highest bandwidth at 2.9 Mbps, while BATMAN and Babel lagged. Indoor tests revealed that Babel initially outperformed with the highest bandwidth of 57.19 Mb/s but suffered from scalability issues, while BATMAN and OLSR exhibited significant declines in performance as network size increased. For PDR, BATMAN performed best with a decline from 100% to 42.8%, followed by OLSR with a moderate drop, and Babel with the greatest decrease. For jitter, OLSR showed the most stable performance, increasing from 0.281 ms to 2.58 ms at eleven nodes, BATMAN exhibited moderate increases, and Babel experienced the highest rise.

Abstract Objective To verify whether the bleeding risk assessment guidelines from the 9th American College of Chest Physicians (ACCP) are prognostic for respiratory intensive care unit (RICU) patients and to explore risk factors for hemorrhages, we conducted a secondary data analysis based on our previously published cohort study of venous thromboembolism. Patients and methods We performed a secondary data analysis on the single-center prospective cohort from our previous study. Patients admitted to the RICU at Beijing Chao-Yang Hospital from August 1, 2014 to December 31, 2020 were included and followed up until discharge. Results The study enrolled 931 patients, of which 715 (76.8%) were at high risk of bleeding, while the remaining were at low risk. Of the total, 9.2% (86/931) suffered major bleeding, and no significant difference was found between the two risk groups (p = 0.601). High-risk patients had poor outcomes, including higher mortality and longer stays. Independent risk factors for major bleeding were APACHE II score ≥ 15; invasive pulmonary aspergillosis; therapeutic dose of anticoagulants; extracorporeal membrane oxygenation; and continuous renal replacement therapy. Blood transfusion not related to bleeding appeared to be an independent protective factor for major bleeding (OR 0.099, 95% CI 0.045–0.218, p

Abstract High‐temperature in situ growth of Ga2O3 thin film on flexible substrates for flexible/portable electronic devices is never realized because the conventional polymer substrates cannot meet the thermal‐stability requirements. In the research, for the first time, Ga2O3 thin films are directly grown on SiOx/Al2Ox buffered Hastelloy substrates. With pulsed laser deposition under high temperature, as‐grown Ga2O3 thin films have a fabric texture with a preferred out‐of‐plane orientation along (−201) and a good field‐effect mobility of 18.07 cm2 V−1 s−1. The Ga2O3 coated tape is patterned with transistor arrays and exhibited good performance homogeneity. The representative transistor devices have a threshold voltage of ≈−2.75 V and a breakdown voltage of 116 V measured under a −20 V gate voltage. Moreover, the tape transistors also have good mechanical robustness. The transistors’ good electrical performance, high uniformity, and mechanical robustness suggest that the in situ deposition technique using Hastelloy tape is promising for fabricating various flexible Ga2O3 channeled electronic circuits. Furthermore, it is believed that this technique can be extended to other flexible semiconductor devices that require high‐temperature processing.

Abstract Background A combination of prone positioning (PP) and venovenous extracorporeal membrane oxygenation (VV-ECMO) is safe, feasible, and associated with potentially improved survival for severe acute respiratory distress syndrome (ARDS). However, whether ARDS patients, especially non-COVID-19 patients, placed in PP before VV-ECMO should continue PP after a VV-ECMO connection is unknown. This study aimed to test the hypothesis that early use of PP during VV-ECMO could increase the proportion of patients successfully weaned from ECMO support in severe ARDS patients who received PP before ECMO. Methods In this prospective observational study, patients with severe ARDS who were treated with VV-ECMO were divided into two groups: the prone group and the supine group, based on whether early PP was combined with VV-ECMO. The proportion of patients successfully weaned from VV-ECMO and 60-day mortality were analyzed before and after propensity score matching. Results A total of 165 patients were enrolled, 50 in the prone and 115 in the supine group. Thirty-two (64%) and 61 (53%) patients were successfully weaned from ECMO in the prone and the supine groups, respectively. The proportion of patients successfully weaned from VV-ECMO in the prone group tended to be higher, albeit not statistically significant. During PP, there was a significant increase in partial pressure of arterial oxygen (PaO2) without a change in ventilator or ECMO settings. Tidal impedance shifted significantly to the dorsal region, and lung ultrasound scores significantly decreased in the anterior and posterior regions. Forty-five propensity score-matched patients were included in each group. In this matched sample, the prone group had a higher proportion of patients successfully weaned from VV-ECMO (64.4% vs. 42.2%; P = 0.035) and lower 60-day mortality (37.8% vs. 60.0%; P = 0.035). Conclusions Patients with severe ARDS placed in PP before VV-ECMO should continue PP after VV-ECMO support. This approach could increase the probability of successful weaning from VV-ECMO. Trial Registration ClinicalTrials.Gov: NCT04139733. Registered 23 October 2019.

Abstract Plasmonic materials can generate strong electromagnetic fields to boost the Raman scattering of surrounding molecules, known as surface-enhanced Raman scattering. However, these electromagnetic fields are heterogeneous, with only molecules located at the ‘hotspots’, which account for ≈ 1% of the surface area, experiencing efficient enhancement. Herein, we propose patterned plasmonic trimers, consisting of a pair of plasmonic dimers at the bilateral sides and a trap particle positioned in between, to address this challenge. The trimer configuration selectively directs probe molecules to the central traps where ‘hotspots’ are located through chemical affinity, ensuring a precise spatial overlap between the probes and the location of maximum field enhancement. We investigate the Raman enhancement of the Au@Al2O3-Au-Au@Al2O3 trimers, achieving a detection limit of 10−14 M of 4-methylbenzenethiol, 4-mercaptopyridine, and 4-aminothiophenol. Moreover, single-molecule SERS sensitivity is demonstrated by a bi-analyte method. Benefiting from this sensitivity, our approach is employed for the early detection of lung tumors using fresh tissues. Our findings suggest that this approach is sensitive to adenocarcinoma but not to squamous carcinoma or benign cases, offering insights into the differentiation between lung tumor subtypes.

BackgroundUnderstanding the HPV genotype distribution in invasive cervical cancer (ICC) is essential for vaccine optimization. This study presents a comprehensive analysis of HPV genotypes in ICC tissues from patients in western China, with the aim of informing regional vaccine policy and prevention strategies.MethodsDNA was extracted from 1,908 paraffin-embedded ICC samples, and 23 HPV genotypes were detected via PCR and reverse dot hybridization gene chip assays. The genotypic distribution of HPV infections was analyzed, the attribution of each HPV genotype found in multiple infection cases was calculated using the fractional contribution approximation. Furthermore, the cumulative attribution rates of HPV genotypes included in each vaccine combination were totaled to estimate the potential vaccination coverage of ICC across various histologic types and age groups.ResultsThe overall prevalence of HPV infection was 94.9% (95% CI 93.8–95.8) among 1,908 women with ICC. HPV genotypes 16 and 18 were detected in 1645 of 1810 HPV-positive patients (90.9, 95% CI 89.5–92.1) of ICC. HPV16, 18, 33, 52, and 58 were detected in 1,749 patients (96.6, 95% CI 95.7–97.4), the five most common genotypes in different age groups. HPV genotypes contained in the 9-valent vaccine were detected in 1776 patients (98.1, 95% CI 97.4–98.7). By weighted imputation analysis, the cumulative attribution rates of the bivalent vaccine was 83.4%, and that of the nine-valent vaccine was 89.8%. Optimization group A included the five genotypes with the highest prevalence, HPV16, 18, 33, 52, and 58, with a cumulative attribution rates of 88.5%, and optimization group B included the nine most common HPV genotypes, HPV16, 18, 31, 33, 35, 45, 52, 58, and 59, with a cumulative attribution rates of 90.5%.ConclusionOur comprehensive postsurgical analysis of HPV in ICC patients in western China revealed that the incorporation of the bivalent vaccine into the national program is cost-effective, with group A optimization closely matching the vaccination coverage of the 9-valent vaccine, which can be used to guide future prevention strategies.

Urban traffic accidents pose significant challenges to public safety and transportation management. Previous studies have revealed that temporal and meteorological factors are the key contributors to accident rate. Besides the inconsistent observations or lack of exploration in some aspects such as snowfall, fog, wind and daily temperatures, it has been shown that these factors are essentially entangled. Furthermore, existing methodologies of analysis or prediction have been limited to relative risk or traditional models. Hence, this study is centered on understanding the detailed correlations between temporal and meteorological factors and accident rate of two types of crashes – moving vehicle and fixed-object crashes using the traffic accident data from Dalian. Further, by incorporating a diverse set of the features, a prediction model leveraging the random forest algorithm is proposed and proved effective in anticipating accident occurrences on the district level. The feature importance analysis has shown that time period and factors such as holiday, temperature and season are most important factors. The rate is higher on working days and in spring, and collisions of both types peak at 6–7 am. When the highest daily temperature is 27 °C and the lowest is 20 °C or -8 °C, the incidence is relatively higher. On the basis, the recommendations are aimed at optimizing transportation systems, mitigating accident risks, and enhancing public safety in urban environments.

To address the issues of poor robustness and weak generalization in existing infrared image deblurring methods, a fuzzy operator-based algorithm is proposed to solve the fuzzy imaging in dragon boat races. The experiment showed that the models trained utilizing original and synthesized datasets had very small differences in peak signal-to-noise ratio and structural similarity performance indicators, and the evaluation results were close. For a blurry image with 19 pixels, the number of blurry pixels extracted by the research algorithm was 22, with a difference of 3 pixels. For a blurry image with 35 pixels, the algorithm extracted 34 blurry pixels, with a difference of 1 pixel. This indicated that the deblurring result of the algorithm was accurate. In terms of peak signal-to-noise ratio and structural similarity, the peak signal-to-noise ratio and structure similarity were 30.98 dB and 0.921, respectively, both of which were the optimal values in all algorithms. In terms of the change of pixel gray value, the simulated blur length of the research method was 19 pixels, and the actual blur length was 20 pixels far less than 30 pixels. The results verified the effectiveness and significance of the algorithm for deblurring of dragon boat competition infrared images.

Aim The prognosis for gastric cancer (GC) remains grim, underscoring the importance of accurate staging and treatment. Given the potential benefits of using lymph node ratio (LNR) for improved prognostication and treatment planning, it is critical to incorporate examined lymph nodes (ELN) count in an integrated GC staging system. Methods Patients data from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 was utilized as training set. The Mantel-Cox survival test was used to calculate chi-square values for 40 LNR segments with a 0.025 interval, defining a novel LNR-based N (rN) classification based on the cutoff points. A revised AJCC (rAJCC) staging system was established by replacing the 8th AJCC N staging with a rN classification. The relationship between the ELN count and prognosis or positive lymph node detection was conducted by using multivariable models. The series of the odds ratios and hazard ratios were fitted with a locally weighted scatterplot smoothing (LOWESS) smoother, and the structural break points were determined by Chow test to clarify an optimal minimum ELN count. The integrated GC staging system incorporated both rAJCC system and the ideal ELN count. Discriminatory ability and prognostic homogeneity of the rAJCC and integrated staging system was compared with AJCC staging system in the SEER validation set (2016–2017), the Cancer Genome Atlas Program (TCGA) database, and the Third Affiliated Hospital of Sun Yat-sen University database. Results The current study found that LNR and ELN count are both significantly associated with the prognosis of GC patients (HR = 0.98, p < 0.001 and HR = 2.51, p < 0.001). Four peaks of the chi-square value were identified as LNR cut-off points at 0.025, 0.175, 0.45 and 0.6 to define a novel rN stage. In comparison to the 8th AJCC staging system, the rAJCC staging system demonstrated significant prognostic advantages and discriminatory ability in the training set (5-Y OS AUC: 71.7 vs. 73.0; AIC: 57,290.7 vs. 57,054.9). The superiority of the rAJCC staging system was confirmed in all validation sets. Using a LOWESS smoother and Chow test, a threshold ELN count of 30 was determined to maximum improvement in the prognosis of node-negative patients without downgrading due to potential metastasis, while also maximizing the detection efficiency of at least one involved lymph node. The integrated staging system, combining the refined rAJCC classification with an optimized ELN count threshold, has demonstrated superior discriminatory performance compared to the standalone rAJCC or the traditional AJCC system. Conclusion The development of a novel GC staging system, which integrated the LNR-based N classification and the minimum ELN count, has exhibited superior prognostic accuracy, holding promise as a valuable asset in the clinical management of GC. However, it is crucial to recognize the limitations from the retrospective database, which should be addressed in subsequent analyses.

With the rapid development of the economy and society, the demand for power quality is constantly increasing. As a crucial part of grid situational awareness, distribution network state estimation plays a vital role in providing critical data support for other advanced applications, which is significant for ensuring the safe and reliable operation of the distribution network. Therefore, this paper proposes a dynamic state awareness method for distribution networks based on the robust adaptive cubature Kalman filter (RACKF). The proposed solution, grounded on the core computational concept of the cubature Kalman filter (CKF), constructs a robust noise statistical estimator (NSE) composed of a biased NSE and an unbiased NSE to adapt to the unknown and time-varying process noise parameters in the dynamic state estimation process. The proposed solution can ensure that the calculated process noise parameters always meet the constraints and guarantee the robustness of the algorithm. In addition, an estimation strategy for the fusion of multi-time scale measurement data is developed according to the RACKF-based dynamic state estimation features in order to realize system state corrections and updates. The results of simulation experiments and comparisons with traditional CKF methods demonstrate the accuracy and superiority of the proposed solution.

Abstract Entanglement plays a vital role in quantum information processing. Owing to its unique material properties, silicon carbide recently emerged as a promising candidate for the scalable implementation of advanced quantum information processing capabilities. To date, however, only entanglement of nuclear spins has been reported in silicon carbide, while an entangled photon source, whether it is based on bulk or chip-scale technologies, has remained elusive. Here, we report the demonstration of an entangled photon source in an integrated silicon carbide platform for the first time. Specifically, strongly correlated photon pairs are efficiently generated at the telecom C-band wavelength through implementing spontaneous four-wave mixing in a compact microring resonator in the 4H-silicon-carbide-on-insulator platform. The maximum coincidence-to-accidental ratio exceeds 600 at a pump power of 0.17 mW, corresponding to a pair generation rate of (9 ± 1) × 103 pairs/s. Energy-time entanglement is created and verified for such signal-idler photon pairs, with the two-photon interference fringes exhibiting a visibility larger than 99%. The heralded single-photon properties are also measured, with the heralded g (2)(0) on the order of 10−3, demonstrating the SiC platform as a prospective fully integrated, complementary metal-oxide-semiconductor compatible single-photon source for quantum applications.

Abstract The traditional plasma etching process for defining micro-LED pixels could lead to significant sidewall damage. Defects near sidewall regions act as non-radiative recombination centers and paths for current leakage, significantly deteriorating device performance. In this study, we demonstrated a novel selective thermal oxidation (STO) method that allowed pixel definition without undergoing plasma damage and subsequent dielectric passivation. Thermal annealing in ambient air oxidized and reshaped the LED structure, such as p-layers and InGaN/GaN multiple quantum wells. Simultaneously, the pixel areas beneath the pre-deposited SiO2 layer were selectively and effectively protected. It was demonstrated that prolonged thermal annealing time enhanced the insulating properties of the oxide, significantly reducing LED leakage current. Furthermore, applying a thicker SiO2 protective layer minimized device resistance and boosted device efficiency effectively. Utilizing the STO method, InGaN green micro-LED arrays with 50-, 30-, and 10-µm pixel sizes were manufactured and characterized. The results indicated that after 4 h of air annealing and with a 3.5-μm SiO2 protective layer, the 10-µm pixel array exhibited leakage currents density 1.2 × 10−6 A/cm2 at −10 V voltage and a peak on-wafer external quantum efficiency of ~6.48%. This work suggests that the STO method could become an effective approach for future micro-LED manufacturing to mitigate adverse LED efficiency size effects due to the plasma etching and improve device efficiency. Micro-LEDs fabricated through the STO method can be applied to micro-displays, visible light communication, and optical interconnect-based memories. Almost planar pixel geometry will provide more possibilities for the monolithic integration of driving circuits with micro-LEDs. Moreover, the STO method is not limited to micro-LED fabrication and can be extended to design other III-nitride devices, such as photodetectors, laser diodes, high-electron-mobility transistors, and Schottky barrier diodes.

ObjectiveParkinson’s disease (PD) is the second most common neurodegenerative disease in the world, and type 2 diabetes (T2DM) and PD are influenced by common genetic and environmental factors. Mitochondrial dysfunction and inflammation are common pathogenic mechanisms of both diseases. However, the close association between PD and T2DM and the specific relationship between them are not yet clear. This study aimed to reveal the specific connection between the two diseases by establishing a mouse model of comorbid PD and T2DM, as well as a Bv2 cell model.MethodsC57BL/6 mouse were used to construct a model of PD with T2DM using streptozotocin and rotenone, while Bv2 cells were used to simulate the microenvironment of PD and T2DM using rotenone and palmitate. Behavioral tests were conducted to assess any differences in motor and cognitive functions in mouse. Immunohistochemistry was used to analyze the number of dopaminergic neurons in the substantia nigra region of mouse. Western blotting was used to detect the expression levels of TH, P-NFκB, NFκB, Cyclic GMP-AMP synthase (cGAS), and Stimulator of interferon genes (STING) proteins in the substantia nigra region of mouse and Bv2 cells. qRT-PCR was used to analyze the expression levels of IL1β, IL6, and TNF-α. Seahorse technology was used to assess mitochondrial function in Bv2 cells.Results:T2DM exacerbated the motor and cognitive symptoms in mouse with PD. This effect may be mediated by disrupting mitochondrial function in microglial cells, leading to damaged mtDNA leakage into the cytoplasm, subsequently activating the cGAS-STING pathway and downstream P-NFκB/NFκB proteins, triggering an inflammatory response in microglial cells. Microglial cells release inflammatory factors such as IL1β, IL6, and TNF-α, exacerbating neuronal damage caused by PD.ConclusionOur study results suggest that T2DM may exacerbate the progression of PD by damaging mitochondrial function, and activating microglial cell inflammation. The detrimental effects on Parkinson’s disease may be achieved through the activating of the cGAS-STING protein pathway.

Abstract SEMA7A belongs to the Semaphorin family and is involved in the oncogenesis and tumor progression. Aberrant glycosylation has been intricately linked with immune escape and tumor growth. SEMA7A is a highly glycosylated protein with five glycosylated sites. The underlying mechanisms of SEMA7A glycosylation and its contribution to immunosuppression and tumorigenesis are unclear. Here, we identify overexpression and aberrant N-glycosylation of SEMA7A in head and neck squamous cell carcinoma, and elucidate fucosyltransferase FUT8 catalyzes aberrant core fucosylation in SEMA7A at N-linked oligosaccharides (Asn 105, 157, 258, 330, and 602) via a direct protein‒protein interaction. A glycosylated statue of SEMA7A is necessary for its intra-cellular trafficking from the cytoplasm to the cytomembrane. Cytokine EGF triggers SEMA7A N-glycosylation through increasing the binding affinity of SEMA7A toward FUT8, whereas TGF-β1 promotes abnormal glycosylation of SEMA7A via induction of epithelial–mesenchymal transition. Aberrant N-glycosylation of SEMA7A leads to the differentiation of CD8+ T cells along a trajectory toward an exhausted state, thus shaping an immunosuppressive microenvironment and being resistant immunogenic cell death. Deglycosylation of SEMA7A significantly improves the clinical outcome of EGFR-targeted and anti-PD-L1-based immunotherapy. Finally, we also define RBM4, a splice regulator, as a downstream effector of glycosylated SEMA7A and a pivotal mediator of PD-L1 alternative splicing. These findings suggest that targeting FUT8-SEMA7A axis might be a promising strategy for improving antitumor responses in head and neck squamous cell carcinoma patients.

Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency. To tackle this problem, we propose an Unmanned Aerial Vehicle (UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded cell. To fully exploit its potential, we jointly optimize the UAV position, user association, spectrum allocation, and power allocation to maximize the sum-log-rate of all users in two adjacent cells. To tackle the complicated joint optimization problem, we first design a genetic-based algorithm to optimize the UAV position. Then, we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method, so as to obtain the optimal user association and spectrum allocation schemes. We further propose an iterative power allocation algorithm based on the sequential convex approximation theory. The simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput, and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.

With the continuous acceleration of urbanization, the parking problem is becoming increasingly serious. How to better manage parking resources has become an urgent problem to be solved in urban development. In this context, according to the historical data and real-time video data collected by the parking camera, this paper proposes an algorithm for parking space detection and state recognition. Through image preprocessing, region of interest selection, Hough line detection, and parking information recognition of the input test image, an intelligent parking space detection model is constructed, which improves the utilization rate of parking space and reduces the management cost. On this basis, according to the free parking space data obtained by the detection algorithm, a short-term demand prediction algorithm for on-road parking based on Convolutional Neural Network (CNN) and Long Short-Term Memory Neural Network (LSTM) was proposed. Through the preprocessing of input parking space data, time vector transformation, data separation, model training, and prediction, the parking demand data is predicted and analyzed. By comparing the prediction results of multiple models, it was found that the CNN-LSTM prediction model had the best model stability and goodness of fit, the lowest Mean Error (MAE) and Root Mean Square Error (RMSE), the errors of working days were 13.301 and 21.156, and the errors of rest days were 12.573 and 20.739, respectively. It shows that CNN-LSTM can effectively capture the time and spatial feature information of parking lot free parking space data, and the prediction accuracy is good, which can be used to predict the number of free parking spaces in parking lots.

Synthetic aperture radar (SAR) is widely used for ship target detection with the application of deep learning techniques. However, in certain complex environments, such as near shore or with small ships, the problem of false alarms and missed detections still exists. To address these issues, a high-precision ship target detection method named DBW-YOLO, which builds upon YOLOv7-tiny as its foundational network, is proposed in this article. The proposed method consists of the following main steps. First, a feature extraction enhancement network based on deformable convolution network is introduced to obtain more comprehensive feature representations across various ship types. Second, an adaptive feature recognition method based on BiFormer attention mechanism is proposed to strengthen detection accuracy, which is more beneficial to capture near shore ships and small ships. Third, a wise intersection-over-union based on dynamic nonmonotonic focusing mechanism is proposed to generate the loss function, which improves the convergence speed and generalization ability. Consequently, the DBW-YOLO method trains a more robust model that better utilizes samples from near shore and small ships. To verify the effectiveness of this method, two SAR datasets, HRSID and SSDD, are employed for performance evaluation. Compared to other widely-used methods, the mAP value of DBW-YOLO reachs 88.84% and 99.18% on the HRSID and SSDD datasets, respectively. The findings indicate that DBW-YOLO method outperforms other representative SAR ship detection methods in both accuracy and overall performance.

In order to effectively suppress rotor periodic synchronous vibration caused by the rotor mass eccentricity and sensor detection error of bearingless induction motor (BIM), a rotor vibration suppression control strategy with improved repetitive control is proposed based on the analysis of the problems existing in the traditional repetitive control. On the basis of the vector control model of the BIM system, a simplified suspension control model is derived. The fractional delay filter is used to optimize the repetitive control internal model. Furthermore, for enhancing the stability of the BIM control system, the design method of the repetitive control compensators in high-, middle- and low-frequency region is given in detail. The simulation and experimental results show that the vibration suppression control strategy with the improved repetitive control can effectively suppress the vibration of the rotor in steady state and improve the suspension accuracy of the BIM.

Automatic Modulation Classification (AMC) is an essential technology that is widely applied into various communications scenarios. In recent years, many Machine Learning and Deep-Learning methods have been introduced into AMC, and a lot of them apply different approaches to eliminate interference in complex Multiple-Input and Multiple-Output (MIMO) signals and improve classification performance. However, in practical communication systems, the perfect elimination of MIMO signal interference is impossible, and therefore classification performance suffers. In this paper, we propose a new AMC algorithm for MIMO system based on mutual information (MI) features extraction, which does not require a large amount of training data and the elimination of MIMO signal interference. In this approach, features based on mutual information are extracted using In-Phase and Quadrature (IQ) constellation diagrams of MIMO signals, which have not been explored previously. Our method can be effective since mutual information considers the interdependencies among variables and measures how much information about one variable reduces uncertainty about another, providing a valuable perspective for extracting higher-level and interesting features from the data. The effectiveness of our method is evaluated on several model and real-world datasets, and its applicability is proven.

This paper presents an improved sensorless controller scheme for a robust permanent magnet synchronous motor. Firstly, a sliding mode observer based on a variable rate approach rate is designed to observe the back electromotive force, enhance the robustness of the back electromotive force acquisition process, and reduce the system buffeting. Secondly, the concept of finite control set model predictive control is introduced, and the position angles are divided into small angles to form finite control sets. Then the position Angle of the finite control set is entered into the sliding mode observer to calculate the back electromotive force. At the same time, the optimal position angle is obtained based on the cost function of the back electromotive force. In order to reduce the number of iterations, the dichotomy is adopted to reduce unnecessary calculations. The proposed finite position-set phase-locked loop (PLL) avoids the PI controller in the traditional PLL and further improves the robustness of the system. Finally, the effectiveness of the proposed scheme is verified by relevant experiments.

Aiming at the problem that the multi-object tracking algorithm is difficult to accurately design the object feature model and data association algorithm in the process of unmanned vehicle autonomous driving, a multi-object tracking algorithm based on online spatiotemporal feature correlation for unmanned vehicle autonomous driving scene (MOTA-BOSFCFUVADS) is proposed. Firstly, the algorithm performs object detection on the training samples, calibrates the coordinates of the detection results in the time dimension and the coordinates of the space dimension, eliminates the detection results whose confidence is less than the set value, and eliminates the overlapping boundaries in the detection through non-maximum suppression. Secondly, we use Kalman filter to predict the position of the tracking object in the current frame, then build the feature model of the object in the time dimension and the space dimension respectively, and fuse the temporal feature model of the tracking object with the spatial feature model, thereby, the spatiotemporal feature model of the tracking object is obtained. Finally, the spatiotemporal feature response of the object in the current frame is detected online, and the spatiotemporal feature response is correlated with the spatiotemporal object feature model of the tracking object, and then the similarity metric matching matrix obtained by fusion is calculated, and the tracking is solved by using the Hungarian algorithm. The optimal correlation pair between the object historical trajectory and the detection response, and update the parameters of the object spatiotemporal feature model. In addition, we use the MOT2015 database to test the effectiveness of the algorithm. The results show that the proposed algorithm has better tracking performance than the other two algorithms, and can effectively track multiple object continuously in time and space.

Utilizing massive spatio-temporal sequence data and real-time synthetic aperture radar (SAR) ship target monitoring technology, it is possible to effectively predict the future trajectories and intents of ships. While real-time monitoring technology validates and adjusts spatio-temporal sequence prediction models, it still faces challenges, such as manual anchor box sizing and slow inference speeds due to large computational parameters. To address this challenge, a SAR ship target real-time detection method based on CenterNet is introduced in this article. The proposed method comprises the following steps. First, to improve the feature extraction capability of the original CenterNet network, we introduce a feature pyramid fusion structure and replace upsampled deconvolution with Deformable Convolution Networks (DCNets), which enable richer feature map outputs. Then, to identify nearshore and small target ships better, BiFormer attention mechanism and spatial pyramid pooling module are incorporated to enlarge the receptive field of network. Finally, to improve accuracy and convergence speed, we optimize the Focal loss of the heatmap and utilize Smooth L1 loss for width, height, and center point offsets, which enhance detection accuracy and generalization. Performance evaluations on two SAR image ship datasets, HRSID and SSDD, validate the method's effectiveness, achieving Average Precision (AP) values of 82.87% and 94.25%, representing improvements of 5.26% and 4.04% in AP compared to the original models, with detection speeds of 49 FPS on both datasets. These results underscore the superiority of the improved CenterNet method over other representative methods for SAR ship detection in overall performance.

For metal-free low-dimensional ferromagnetic materials, a hopeful candidate for next-generation spintronic devices, investigating their magnetic mechanisms and exploring effective ways to regulate their magnetic properties are crucial for advancing their applications. Our work systematically investigated the origin of magnetism of a graphitic carbon nitride (Pca21 C4N3) monolayer based on the analysis on the partial electronic density of states. The magnetic moment of the Pca21 C4N3 originates from the spin-split of the 2pz orbit from special carbon (C) atoms and 2p orbit from N atoms around the Fermi energy, which was caused by the lone pair electrons in nitrogen (N) atoms. Notably, the magnetic moment of the Pca21 C4N3 monolayer could be effectively adjusted by adsorbing nitric oxide (NO) or oxygen (O2) gas molecules. The single magnetic electron from the adsorbed NO pairs with the unpaired electron in the N atom from the substrate, forming a Nsub-Nad bond, which reduces the system’s magnetic moment from 4.00 μB to 2.99 μB. Moreover, the NO adsorption decreases the both spin-down and spin-up bandgaps, causing an increase in photoelectrical response efficiency. As for the case of O2 physisorption, it greatly enhances the magnetic moment of the Pca21 C4N3 monolayer from 4.00 μB to 6.00 μB through ferromagnetic coupling. This method of gas adsorption for tuning magnetic moments is reversible, simple, and cost-effective. Our findings reveal the magnetic mechanism of Pca21 C4N3 and its tunable magnetic performance realized by chemisorbing or physisorbing magnetic gas molecules, providing crucial theoretical foundations for the development and utilization of low-dimensional magnetic materials.

Over the past decade, wireless mesh networks (WMNs) have seen significant advancements due to their simple deployment, cost-effectiveness, ease of implementation, and reliable service coverage. However, despite these advantages, the placement of nodes in WMNs presents a critical challenge that significantly impacts their performance. This issue is recognized as an NP-hard problem, underscoring the necessity of development optimization algorithms, such as heuristic and metaheuristic approaches. This motivated us to develop the Maximum Entropy Genetic Algorithm (MEGA) to address the issue of mesh router node placement in WMNs. To assess the proposed method, we conducted experiments across various scenarios with different settings, focusing on key metrics such as network connectivity and user coverage. The simulation results showed the comparative performance of MEGA in relation to other prominent algorithms, such as the Coyote Optimization Algorithm (COA), Firefly Algorithm (FA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), revealing MEGA’s effectiveness and usability in determining optimal locations for mesh routers.

After the resumption of work and production following the COVID-19 pandemic, many cities entered a “transition phase”, characterized by the gradual recovery of emission levels from various sources. Although the overall PM2.5 emission trends have recovered, the specific changes in different sources of PM2.5 remain unclear. Here, we investigated the changes in source contributions and the evolution pattern of pollution episodes (PE) in Wuhan during the “transition period” and compared them with the same period during the COVID-19 lockdown. We found that vehicle emissions, industrial processes, and road dust exhibited significant recoveries during the transition period, increasing by 5.4%, 4.8%, and 3.9%, respectively, during the PE. As primary emissions increased, secondary formation slightly declined, but it still played a predominant role (accounting for 39.1∼ 43.0% of secondary nitrate). The reduction in industrial activities was partially offset by residential burning. The evolution characteristics of PE exhibited significant differences between the two periods, with PM2.5 concentration persisting at a high level during the transition period. The differences in the evolution patterns of the two periods were also reflected in their change rates at each stage, which mostly depend on the pre-PE concentration level. The transition period shows a significantly higher value (8.4 μg m–3 h–1) compared with the lockdown period, almost double the amount. In addition to local emissions, regional transport should be a key consideration in pollution mitigation strategies, especially in areas adjacent to Wuhan. Our study quantifies the variations in sources between the two periods, providing valuable insights for optimizing environmental planning to achieve established goals.

This paper introduces a design of an annular water-cooled automotive exhaust-based thermoelectric generator (TEG). A comprehensive numerical model of TEG system is established to investigate the relationship between automotive exhaust temperature and coolant flow rate. Through numerical simulations, it is demonstrated that the implementation of this device can effectively enhance the temperature uniformity at the hot side of the heat exchanger, consequently increasing the TEG's power output. After introducing the annular water-cooled radiator, the temperature uniformity of the thermoelectric module increased by 18.8%. By utilizing the numerical simulation outcomes alongside empirical formulas, calculations for the pump power consumption, maximum output power, and maximum net output power of the thermoelectric module (TEM) are conducted. The maximum net output power can be increased by 3.30%–53.24% by controlling the coolant flow rate. As a result, a relationship curve depicting the average temperature difference between the hot and cold ends of the TEM, in relation to the optimum coolant flow rate, is obtained. This relationship curve serves as a valuable tool for adjusting the radiator's coolant flow rate and augmenting the TEG's net output power, ultimately achieving the objective of heightening the power generation efficiency of the TEG.

Abstract Introduction Psittacosis can cause severe community-acquired pneumonia (CAP). The clinical manifestations of psittacosis range from subclinical to fulminant psittacosis with multi-organ failure. It is essential to summarize the clinical characteristic of patients with severe psittacosis accompanied by acute hypoxic respiratory failure (AHRF). Methods This retrospective study included patients with severe psittacosis caused CAP accompanied by AHRF from 19 tertiary hospitals of China. We recorded the clinical data, antimicrobial therapy, respiratory support, complications, and outcomes. Chlamydia psittaci was detected on the basis of metagenomic next-generation sequencing performed on bronchoalveolar lavage fluid samples. Patient outcomes were compared between the treatment methods. Results This study included 45 patients with severe CAP and AHRF caused by psittacosis from April 2018 to May 2021. The highest incidence of these infections was between September and April. There was a history of poultry contact in 64.4% of the patients. The median PaO2/FiO2 of the patients was 119.8 (interquartile range, 73.2 to 183.6) mmHg. Four of 45 patients (8.9%) died in the ICU, and the median ICU duration was 12 days (interquartile range, 8 to 21) days. There were no significant differences between patients treated with fluoroquinolone initially and continued after the diagnosis, fluoroquinolone initially followed by tetracycline, and fluoroquinolone combined with tetracycline. Conclusion Psittacosis caused severe CAP seems not rare, especially in the patients with the history of exposure to poultry or birds. Empirical treatment that covers atypical pathogens may benefit such patients, which fluoroquinolones might be considered as an alternative.

Abstract Esophageal stricture is a common complication after endoscopic submucosal dissection (ESD) for superficial esophageal cancer and precancerous lesions, we intend to investigate the independent risk factors of esophageal stricture after ESD by adding the data of included living habits, established a nomogram model to predict the risk of esophageal stricture, and verified it by external data. The clinical data and living habits of patients with early esophageal cancer and precancerous lesions who underwent ESD in the Affiliated Hospital of North Sichuan Medical College and Langzhong People's Hospital from March 2017 to August 2021 were retrospectively collected. The data collected from the two hospitals were used as the development group (n = 256) and the validation group (n = 105), respectively. Univariate and multivariate logistic regression analyses were used to determine independent risk factors for esophageal stricture after ESD and establish a nomogram model for the development group. The prediction performance of the nomogram model is internally and externally verified by calculating C-Index and plotting the receiver operating characteristic curve (ROC) and calibration curve, respectively. The results showed that Age, drinking water temperature, neutrophil–lymphocyte ratio, the extent of esophageal mucosal defect, longitudinal diameter of resected mucosa, and depth of tissue invasion (P

To compare the differences in floral composition and functions between the two types of microbiota, ileal contents and feces were collected from Sprague Dawley (SD) rats fed in a conventional or specific-pathogen free (SPF) environment and rats fed a high-fat diet (HFD), and the V3–V4 region of the 16S ribosomal ribonucleic acid (rRNA) gene in these rats was then amplified and sequenced. Compared with feces, about 60% of the bacterial genera in the ileum were exclusive, with low abundance (operational taxonomic units (OTUs) < 1000). Of bacteria shared between the ileum and feces, a few genera were highly abundant (dominant), whereas most had low abundance (less dominant). The dominant bacteria differed between the ileum and feces. Ileal bacteria showed greater β-diversity, and the distance between in-group samples was nearer than that between paired ileum–feces samples. Moreover, the ileum shared various biomarkers and functions with feces (p < 0.05). The HFD and SPF conditions had a profound influence on α-diversity and abundance but not on the exclusive/shared features or β-diversity of samples. The present findings suggested that, under conventional circumstances, fecal bacteria can represent approximately 40% of the low abundant ileal bacterial genera and that dominant fecal bacteria failed to represent the ileal dominant flora. Moreover, fecal flora diversity does not reflect β-diversity in the ileum.

Spin-gapless semiconductor (SGS), a class of zero-gap materials with fully spin-polarized electrons and holes, offers significant potential for high-speed, low-energy consumption applications in spintronics, electronics, and optoelectronics. Our first-principles calculations revealed that the Pca21 C4N3 monolayer exhibits a ferromagnetic ground state. Its band structure displays SGS-like characteristics, with the energy gap between the valence and conduction bands near the Fermi level in the spin-down channel much smaller than the one in the other spin channel. To enhance its SGS properties, we introduced electrons into the Pca21 C4N3 monolayer by adsorbing the CO gas molecule on its surface. Stable gas adsorption (CO@C4N3) effectively narrowed the band gap in the spin-down channel without changing the band gap in the spin-up channel obviously. Moreover, injecting holes into the CO@C4N3 system could increase the net magnetic moments and induce an SGS-to-metallic phase transition, while injecting electrons into the CO@C4N3 system is able to lower the net magnetic moments and cause an SGS-to-half-metallic phase transition. Our findings not only underscore a new promising material for practical metal-free spintronics applications but also illustrate a viable pathway for designing SGSs.

Nitrogen (N) availability determines higher plant productivity and yield. However, the molecular mechanisms governing N acquisition and utilization remain largely unknown in maize. In this study, ATAC-seq, RNA-seq, and Ribo-seq analyses were conducted in maize roots under different N supply conditions. A set of differentially expressed genes enriched in N and phenylpropanoid metabolisms at both the transcription and translation levels were highlighted. Interestingly, less than half of low-N responsive genes were shared between transcription and translation. The alteration of translational efficiency (TE) is also an important mechanism by which maize responds to LN. In addition, we identified low-N-induced open chromatin regions (OCRs) and observed an enrichment of transcription factor (TF) binding motifs. Furthermore, we constructed a transcriptional regulatory network for maize roots subjected to low-N. These findings extend our understanding of N availability response and provide new insights for improving N use efficiency (NUE).

A two-stage robust planning method for energy storage in distribution networks based on load prediction is proposed to address the uncertainty of active load in energy storage planning. First, considering the uncertainty of active load, a short-term load forecasting model combining the mutual information method and BiLSTM is established based on k-means++ clustering. Second, based on the results of load forecasting, a comprehensive norm-constrained uncertainty set is constructed, and a two-stage robust model for distribution network energy storage planning is established. The first stage aims to minimize the annual investment cost of the energy storage system, while the second stage aims to minimize the daily operating cost of the distribution network. At the same time, a second-order cone relaxation transformation model with non-convex constraints is introduced to ultimately achieve the optimal economy of the distribution network in energy storage planning. Finally, the effectiveness of the proposed method and model is validated on the IEEE 33-node distribution network model using the MATLAB platform.

IntroductionSystematic evaluation of long-term outcomes in survivors of H1N1 is still lacking. This study aimed to characterize long-term outcomes of severe H1N1-induced pneumonia and acute respiratory distress syndrome (ARDS).MethodThis was a single-center, prospective, cohort study. Survivors were followed up for four times after discharge from intensive care unit (ICU) by lung high-resolution computed tomography (HRCT), pulmonary function assessment, 6-minute walk test (6MWT), and SF-36 instrument.ResultA total of 60 survivors of H1N1-induced pneumonia and ARDS were followed up for four times. The carbon monoxide at single breath (DLCO) of predicted values and the 6MWT results didn’t continue improving after 3 months. Health-related quality of life didn’t change during the 12 months after ICU discharge. Reticulation or interlobular septal thickening on HRCT did not begin to improve significantly until the 12-month follow-up. The DLCO of predicted values showed negative correlation with the severity degree of primary disease and reticulation or interlobular septal thickening, and a positive correlation with physical functioning. The DLCO of predicted values and reticulation or interlobular septal thickening both correlated with the highest tidal volume during mechanical ventilation. Levels of fibrogenic cytokines had a positive correlation with reticulation or interlobular septal thickening.ConclusionThe improvements in pulmonary function and exercise capacity, imaging, and health-related quality of life had different time phase and impact on each other during 12 months of follow-up. Long-term outcomes of pulmonary fibrosis might be related to the lung injury and excessive lung fibroproliferation at the early stage during ICU admission.

Background: There is currently no consensus regarding the optimal perioperative antiplatelet strategy for carotid artery surgery. This multicentre study aimed to analyse the association between preoperative aspirin monotherapy following postoperative dual antiplatelet therapy (DAPT) and the risk for stroke and death after carotid endarterectomy (CEA). Methods: This cohort study included 821 patients with carotid artery stenosis who underwent CEA. Primary outcomes included any stroke or death up to the one-month postoperative follow-up. Multilevel multivariate regression analyses and descriptive statistics were performed. Results: Patients were predominantly male (53 %), with a mean age of 66.2 years. The primary outcome occurred in 1.6 % of patients. Univariate and multivariate analyses revealed that patients with chronic obstructive pulmonary disease (COPD) exhibited a high risk for stroke or death (P = 0.011). The occurrence of any local complications in the neck was accompanied by an increase in diastolic blood pressure (DBP) (P = 0.007). Patients with a high systolic blood pressure (SBP) (P = 0.002) experienced a longer operative duration. The length of hospital stay was longer in the patients with COPD (P = 0.020), minor stroke (P = 0.011), and major stroke (P = 0.001). A positive linear correlation was found between SBP and operative duration in the overall population (β 0.4 [95 % confidence interval (CI) 0.1–0.7]; P = 0.002). The resultant curve for DBP and any local complications in the neck exhibited a two-stage change and one breakpoint in the entire population (k = 68 mmHg,

Abstract Spatiotemporal forecasting involves generating temporal forecasts for system state variables across spatial regions. Data‐driven methods such as Convolutional Long Short‐Term Memory (ConvLSTM) are effective in capturing both spatial and temporal correlations, but they suffer from error accumulation and accuracy loss as forecasting time increases due to the nonlinearity and uncertainty in physical processes. To address this issue, we propose to combine data‐driven and data assimilation (DA) methods for spatiotemporal forecasting. The accuracy of the data‐driven ConvLSTM model can be improved by periodically assimilating real‐time observations using the ensemble Kalman filter (EnKF) approach. This proposed hybrid ConvLSTM‐EnKF method is demonstrated through PM2.5 forecasting in China, which is a challenging task due to the complexity of topographical and meteorological conditions in the region, the need for high‐resolution forecasting over a large study area, and the scarcity of observations. The results show that the ConvLSTM‐EnKF method outperforms conventional methods and can provide satisfactory operational PM2.5 forecasts for up to 1 month with spatially averaged RMSE below 20 μg/m3 and correlation coefficient (R) above 0.8. In addition, the ConvLSTM‐EnKF method shows a substantial reduction in CPU time when compared to the commonly used NAQPMS‐EnKF method, up to three orders of magnitude. Overall, the use of data‐driven models provides efficient forecasts and speeds up DA. This hybrid ConvLSTM‐EnKF is a novel operational forecasting technique for spatiotemporal forecasting and is used in real spatiotemporal forecasting for the first time.

Personalized healthcare monitoring is a transformative tool for preventing potential risks and enhancing health status, particularly through molecular-level insights. Advances in nanotechnology, smart devices, and artificial intelligence (AI) have revolutionized personalized healthcare, especially in point-of-care testing (POCT), enabling early detection and timely intervention. Recently, surface-enhanced Raman spectroscopy (SERS) technology, particularly with flexible chips, has shown immense promise in this field due to its in situ, rapid, specific, and efficient detection capabilities. In this review, we highlight recent advancements in flexible SERS chips for personalized healthcare monitoring, demonstrating their effectiveness in target sampling and detection. Importantly, we provide a comprehensive overview of potential applications of flexible SERS chips in personalized healthcare, address current challenges, and propose future development directions. We also explore the future development of miniaturized Raman devices to broaden their applications in personalized healthcare monitoring. Additionally, we underscore the important role of AI in enhancing data processing and analysis. Our aim is to offer a thorough guide on integrating SERS into personalized healthcare monitoring, promising a new era of health management.

Purpose: To characterize changes in subfoveal choroidal thickness in preterm infants from 30 to 60 weeks' postmenstrual age (PMA). Design: The prospective, observational Study of Eye Imaging in Preterm infantS (BabySTEPS) enrolled infants eligible for retinopathy of prematurity screening per the American Association of Pediatrics guidelines. Subjects: Infants imaged with an investigational, handheld OCT at ≥ 4 distinct imaging sessions between 30 to 60 weeks' PMA as part of BabySTEPS. Methods: Average choroidal thickness across the central subfoveal 1 mm in each eye at each time point was measured using custom segmentation software, and errors were manually corrected by a trained grader. We prospectively collected birth history data. A segmented mixed model was used to analyze the change in choroidal thickness as a function of PMA, birth weight, and gestational age (GA). Main Outcome Measures: Characterization of normative subfoveal choroidal thickness values and choroidal growth rate between 30 to 60 weeks' PMA. Results: We included 592 imaging sessions of 79 preterm infants (152 eyes). Mean (± standard deviation) GA was 27.5 ± 2.5 weeks. Mean choroidal thickness was 141.4 ± 34.5 μm at 30 weeks, 272.2 ± 83.9 μm at 38 weeks, and 306.2 ± 77.4 μm between 56 and 60 weeks. Between 30 and 60 weeks' PMA, choroidal growth followed a biphasic model, with a linear growth rate of 14.8 μm per week (95% confidence interval [CI], 13.6–16.0) from 30 until 38.4 weeks, then cessation of growth, with a growth rate of 0.3 μm per week (95% CI, −1.1 to 1.6) from 38.4 to 60 weeks. Infants with extremely low birth weight (ELBW; < 1000 g) and extremely preterm (GA < 28 weeks) infants had significantly slower initial growth rates compared with very low and low birth weight and very preterm and preterm infants (ELBW 13.0 vs. 21.0 μm per week; P < 0.0001 and extremely preterm 13.2 vs. 18.0 μm per week; P = 0.003). Conclusions: Preterm infant choroidal thickness experiences rapid linear growth from 30 to 38 weeks' PMA, at which time growth nearly stops. These foundational measurements and identification of the impact of extremes of low birth weight and prematurity on choroidal development will be essential as researchers begin to understand the role of choroidal development in ocular and retinal health in human infants. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

IntroductionSquamous cell carcinoma antigen (SCCA) is one of the auxiliary diagnostic indicators of lung squamous cell carcinoma, and an increase in serum SCCA can predict the occurrence of lung squamous cell carcinoma. However, whether SCCA is also elevated in pneumonia patients without malignancy is still not clear. Therefore, we studied influencing factors of elevated serum SCCA in patients with community-acquired pneumonia.MethodsWe retrospectively enrolled 309 patients who were admitted to the Respiratory department with normal serum Carcinoembryonic antigen (CEA), Neuron specific enolase (NSE), and Cytokeratin 19 fragment (CYFRA21-1) level and were diagnosed with community-acquired pneumonia (CAP). The patients’ serum SCCA level, body temperature, age, sex, white blood cell (WBC) count, hypersensitive C-reactive protein (Hs-CRP) level, and serum amyloid A (SAA) were recorded. Logistic regression models were used to analyze the risk factors of SCCA elevation. The dose-response relationship between temperature and risk of SCCA increase was analyzed using Restricted cubic splines (RCS).ResultsOf the 309 patients, 143(46.3%) showed elevated SCCA levels. The logistic regression analysis revealed a significant influence of age and body temperature on elevated SCCA (P

Abstract Aim The incidence and risk factors of low anterior resection syndrome (LARS) largely variate in different studies. In addition, there is lack of study on how patients evaluate the therapeutic effect of LARS. This single-center retrospective study aims to investigate the status of LARS in Chinese patients undergoing laparoscopic low anterior resection (LAR). Methods Consequent patients undergoing laparoscopic LAR and free from disease recurrence from January 2015 to May 2021 were issued with both LARS questionnaire and satisfaction survey. Related data were collected and analyzed. Results Both LARS questionnaires and self-made satisfaction survey were received from 261 eligible patients. The overall incidence of LARS was 47.1% (minor in 19.5%, major in 27.6%), decreased with the passage of postoperative time (64.7% within 12 months, and 41.7% within 12–36 months), and became stable 36 months later (39.7%). The most common symptoms were defecation clustering (n = 107/261, 41.0%) and defecation urgency (n = 101/261, 38.7%). According to the multivariable regression analysis, risk factors of major LARS were: 1 year increase in age (OR 1.035, 95% CI 1.004–1.068), protective stoma (OR 2.656, 95% CI 1.233–5.724) and T3 − 4 stage (OR 2.449, 95% CI 1.137–5.273). Most patients complained defecation disorder (87.3%) to doctors and 84.5% got suggestions or treatments for it. However, only 36.8% patients thought the treatments worked for them. Conclusions LARS frequently occurs after laparoscopic LAR, while the therapeutic effect is not satisfying. Elder, advanced T-stage and protective stoma were risk factors for postoperative major LARS.

Abstract Single-molecule localization microscopy (SMLM) can be used to resolve subcellular structures and achieve a tenfold improvement in spatial resolution compared to that obtained by conventional fluorescence microscopy. However, the separation of single-molecule fluorescence events that requires thousands of frames dramatically increases the image acquisition time and phototoxicity, impeding the observation of instantaneous intracellular dynamics. Here we develop a deep-learning based single-frame super-resolution microscopy (SFSRM) method which utilizes a subpixel edge map and a multicomponent optimization strategy to guide the neural network to reconstruct a super-resolution image from a single frame of a diffraction-limited image. Under a tolerable signal density and an affordable signal-to-noise ratio, SFSRM enables high-fidelity live-cell imaging with spatiotemporal resolutions of 30 nm and 10 ms, allowing for prolonged monitoring of subcellular dynamics such as interplays between mitochondria and endoplasmic reticulum, the vesicle transport along microtubules, and the endosome fusion and fission. Moreover, its adaptability to different microscopes and spectra makes it a useful tool for various imaging systems.

In interval-valued three-way decision, the reflection of decision-makers’ preference under the full consideration of interval-valued characteristics is particularly important. In this paper, we propose an interval-valued three-way decision model based on the cumulative prospect theory. First, by means of the interval distance measurement method, the loss function and the gain function are constructed to reflect the differences of interval radius and expectation simultaneously. Second, combined with the reference point, the prospect value function is utilized to reflect decision-makers’ different risk preferences for gains and losses. Third, the calculation method of cumulative prospect value for taking action is given through the transformation of the prospect value function and cumulative weight function. Then, the new decision rules are deduced based on the principle of maximizing the cumulative prospect value. Finally, in order to verify the effectiveness and feasibility of the algorithm, the prospect value for decision-making and threshold changes are analyzed under different risk attitudes and different radii of the interval-valued decision model. In addition, compared with the interval-valued decision rough set model, our method in this paper has better decision prospects.

Stalk strength increases resistance to stalk lodging, which causes maize (Zea mays L.) production losses worldwide. The genetic mechanisms regulating stalk strength remain unclear. In this study, three stalk strength-related traits (rind penetrometer resistance, stalk crushing strength, and stalk bending strength) and four plant architecture traits (plant height, ear height, stem diameter, stem length) were measured in three field trials. Substantial phenotypic variation was detected for these traits. A genome-wide association study (GWAS) was conducted using general and mixed linear models and 372,331 single-nucleotide polymorphisms (SNPs). A total of 94 quantitative trait loci including 241 SNPs were detected. By combining the GWAS data with public gene expression data, 56 candidate genes within 50 kb of the significant SNPs were identified, including genes encoding flavonol synthase (GRMZM2G069298, ZmFLS2), nitrate reductase (GRMZM5G878558, ZmNR2), glucose-1-phosphate adenylyltransferase (GRMZM2G027955), and laccase (GRMZM2G447271). Resequencing GRMZM2G069298 and GRMZM5G878558 in all tested lines revealed respectively 47 and 2 variants associated with RPR. Comparison of the RPR of the zmnr2 EMS mutant and the wild-type plant under high- and low-nitrogen conditions verified the GRMZM5G878558 function. These findings may be useful for clarifying the genetic basis of stalk strength. The identified candidate genes and variants may be useful for the genetic improvement of maize lodging resistance.

Abstract Background Perivascular epithelioid cell tumor (PEComa) occurring in the female genital tract are rare, and typically found in the uterine corpus. PEComa occurring in the cervix is extremely rare, and very few cases have been reported till now. Cytological diagnosis of cervical PEComa is even rarer. So far, only two cases of PEComa diagnosed by conventional cervical smears have been reported. Case presentation A 55-year-old postmenopausal woman presented with abnormal vagina discharge for 3 months. A liquid-based cytology test was performed. Microscopically, some loosely cohesive epithelioid cells were uniform with abundant clear cytoplasm, showing predominantly round or oval nuclei with finely stippled chromatin. Distinct round nucleoli were visible in some cells, notably with numerous melanin pigments in the cytoplasm. The cytopathological features were well correlated with cell block and histopathological findings. Upon immunohistochemistry (IHC), the tumor cells were positive for HMB45 and TFE3, focally positive for MelanA, while negative for muscle marker. Fluorescence in situ hybridization (FISH) confirmed TFE3 gene rearrangement. The final pathological diagnosis was PEComa identified by the liquid-based cytology, cell block, cervical biopsy, IHC and FISH result. The patient underwent a total hysterectomy with bilateral salpingo-oophorectomy and was followed up for 2 years with no evidence of disease. Conclusion The cytologic characteristics of the tumor can provide sufficient clues for PEComa diagnosis, which includes loosely cohesive, epithelioid morphology with abundant clear or eosinophilic cytoplasm, low-grade nuclear atypia, cytoplasmic melanin pigments. This will help cytopathologists to recognize this rare tumor that occurred in the cervix, and the combination of predictive morphology evaluation, immunophenotype, and molecular testing can achieve the definitive diagnosis of PEComa.