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Abstract Objective This study investigated the association of Time In Range (TIR) obtained from Blood Glucose Monitoring (BGM) with Cognitive Impairment (CI) inpatients with middle-aged Type 2 Diabetes Mellitus (T2DM) and further explored whether a TIR goal for T2DM in adults with > 70% possess a protective effect on cognitive function. Research design and methods A total of 274 inpatients with T2DM aged 40–64 years, who underwent seven-point BGM ( pre meals and 120 min post meals and at bedtime) were recruited in this cross-sectional study. TIR was defined as the percentage of blood glucose within the target range of 3.9-10.0mmol/L. Subjects were divided into Normal Cognitive Function (NCF) (n = 160) and CI (n = 114) groups according to the results of the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). The association of TIR and other glycemic metrics, calculated from seven-point BGM data, with cognitive dysfunction was analyzed. Results The prevalence of CI was 41.6% in patients with middle-aged T2DM (median age 58 years). TIR was lower in CI group than in NCF group (28.6% vs. 42.9%, P = 0.004). The prevalence of CI decreased with ascending tertiles of TIR (p for trend 70% probably possessed independent protective effect on cognitive function (OR = 0.25, p = 0.001) after controlling for confounders above. Conclusions TIR obtained from BGM was related to CI in middle-aged T2DM individuals and a TIR goal of > 70% probably possessed a protective effect on cognitive function for middle-aged T2DM .

Abstract Background The objective of this study is to investigate the incidence, potential risk factors, and clinical outcomes of incomplete device endothelialization (IDE) in atrial fibrillation (AF) patients undergoing Watchman left atrial appendage closure (LAAC). Methods In this study, 68 AF patients who underwent successful implantation of the Watchman device without peri-device leak (PDL) during follow-up were included. The endothelialization status was assessed using Transesophageal echocardiography (TEE) and LAA computed tomography angiography (CTA) at 6 weeks and 6 months post-implantation. Adverse cerebro-cardiac events were documented at one-year follow-up. Baseline characteristics, including age, device sizes, and clinical indicators, were analyzed as potential predictors for IDE. Results IDE was observed in 70.6% and 67.6% of patients at 6 weeks and 6 months after implantation, respectively. Higher levels of high-density lipoprotein cholesterol (HDL-C) [odds ratio (OR): 15.109, 95% confidence interval (CI): 1.637-139.478, p = 0.017 and OR: 11.015, 95% CI: 1.365–88.896, p = 0.024] and lower aspartate aminotransferase (AST) (OR 0.924, 95% CI: 0.865–0.986, p = 0.017 and OR: 0.930, 95% CI: 0.874–0.990, p = 0.023) at baseline were found to be significantly associated with IDE at 6 weeks and 6 months, respectively, although no significant difference in adverse cerebro-cardiac events was noted between incomplete and complete DE groups during 1-year follow-up Conclusions IDE is found to be a prevalent occurrence in humans following LAAC. Elevated HDL-C and reduced AST levels are shown to be linked to an increased risk of IDE after LAAC

Abstract Visual adaptive devices have potential to simplify circuits and algorithms in machine vision systems to adapt and perceive images with varying brightness levels, which is however limited by sluggish adaptation process. Here, the avalanche tuning as feedforward inhibition in bionic two-dimensional (2D) transistor is proposed for fast and high-frequency visual adaptation behavior with microsecond-level accurate perception, the adaptation speed is over 104 times faster than that of human retina and reported bionic sensors. As light intensity changes, the bionic transistor spontaneously switches between avalanche and photoconductive effect, varying responsivity in both magnitude and sign (from 7.6 × 104 to −1 × 103 A/W), thereby achieving ultra-fast scotopic and photopic adaptation process of 108 and 268 μs, respectively. By further combining convolutional neural networks with avalanche-tuned bionic transistor, an adaptative machine vision is achieved with remarkable microsecond-level rapid adaptation capabilities and robust image recognition with over 98% precision in both dim and bright conditions.

Abstract Resistive switching memories have garnered significant attention due to their high‐density integration and rapid in‐memory computing beyond von Neumann's architecture. However, significant challenges are posed in practical applications with respect to their manufacturing process complexity, a leakage current of high resistance state (HRS), and the sneak‐path current problem that limits their scalability. Here, a mild‐temperature thermal oxidation technique for the fabrication of low‐power and ultra‐steep memristor based on Ag/TiOx/SnOx/SnSe2/Au architecture is developed. Benefiting from a self‐assembled oxidation layer and the formation/rupture of oxygen vacancy conductive filaments, the device exhibits an exceptional threshold switching behavior with high switch ratio exceeding 106, low threshold voltage of ≈1 V, long‐term retention of >104 s, an ultra‐small subthreshold swing of 2.5 mV decade−1 and high air‐stability surpassing 4 months. By decreasing temperature, the device undergoes a transition from unipolar volatile to bipolar nonvolatile characteristics, elucidating the role of oxygen vacancies migration on the resistive switching process. Further, the 1T1R structure is established between a memristor and a 2H‐MoTe2 transistor by the van der Waals (vdW) stacking approach, achieving the functionality of selector and multi‐value memory with lower power consumption. This work provides a mild‐thermal oxidation technology for the low‐cost production of high‐performance memristors toward future in‐memory computing applications.

Ecological vulnerability assessment is crucial for environment protection, ecological restoration and resource utilization. However, many former studies have limitations in the indicator system of the assessment, which were not comparable for different types of ecologically vulnerable areas. It is difficult to apply directly to the ecological vulnerability assessment of different types and in various regions. Aiming to solve these problems, the study proposed a well-established and comprehensive indicator system for ecological vulnerability assessment and conducted ecological vulnerability assessment application of five types of typical ecologically vulnerable areas of China based on remote sensing, meteorological, geographic and other data. The results show that the average EVIs value of Zhangbei County ranging from 0.525 to 0.559 are the highest among the five research areas during the four periods, followed by Zoige region and Xiamen bay. However, the region with the lowest average EVI value varies. In 2005 and 2015, it was Taihe County, while in 2010 and 2020, it was the Sanjiangyuan region. The variation of average EVIs in the five typical areas presents slight fluctuation and remains generally stable from 2005 to 2020. It indicates that the environmental protection measures and projects undertaken by the Chinese government in recent years have had a striking effect, curbing the trend of ecological environment deterioration.

Abstract Background Fat to muscle mass ratio (FMR), a novel index integrating fat and muscle composition, has garnered attention in age-related conditions such as type 2 diabetes mellitus (T2DM) and neurodegenerative diseases. Despite this research on the relationship between FMR and cognitive impairment (CI) in T2DM remains scarce. This study aimed to investigate the sex-specific association between FMR and CI in elderly T2DM patients. Methods A total of 768 elderly (> 60 years) T2DM in-patients (356 men and 412 women) were recruited from the Department of Endocrinology at Tianjin Nankai University affiliated hospital. Bioelectrical Impedance Analysis (BIA) was used to assess body composition, and Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive performance. T2DM patients were categorized into normal cognitive function (NC) and cognitive impairment (CI) groups based on MoCA scores and stratified by sex. Binary logistic regression was employed to examine the association between FMR and CI. Results Among the participants, 42.7% of men and 56.3% of women experienced cognitive deterioration. Women with CI exhibited lower body mass index (BMI) and skeletal muscle mass index (SMI), while men with cognitive disorders showed lower SMI, FMR, and higher fat mass index (FMI). FMR was consistently unrelated to cognition in females, irrespective of adjustment made. However, in males, FMR was significantly associated with an increasing risk of cognitive dysfunction after adjusting for demographic and clinical variables (OR: 1.175, 95% CI: 1.045–1.320, p = 0.007). Furthermore, for each 0.1 increase in FMR, the incidence of CI rose by 31.1% after additional adjustment for BMI. In males, the prevalence of CI increased sequentially across FMR quartiles (p

Abstract The islet of Langerhans, functioning as a “mini organ”, plays a vital role in regulating endocrine activities due to its intricate structure. Dysfunction in these islets is closely associated with the development of diabetes mellitus (DM). To offer valuable insights for DM research and treatment, various approaches have been proposed to create artificial islets or islet organoids with high similarity to natural islets, under the collaborative effort of biologists, clinical physicians, and biomedical engineers. This review investigates the design and fabrication of artificial islets considering both biological and tissue engineering aspects. It begins by examining the natural structures and functions of native islets and proceeds to analyze the protocols for generating islets from stem cells. The review also outlines various techniques used in crafting artificial islets, with a specific focus on hydrogel‐based ones. Additionally, it provides a concise overview of the materials and devices employed in the clinical applications of artificial islets. Throughout, the primary goal is to develop artificial islets, thereby bridging the realms of developmental biology, clinical medicine, and tissue engineering.

Background: Oxidative stress, imbalance of neurotransmitters and multidrug resistant transporters play pivotal roles in the development and treatment of seizures. Classical formula Baijin Pills (BJP) has been used to treat brain damage caused by epilepsy for thousands of years. However, little information on the anti-seizure effects of BJP has been reported so far. Purpose: To investigate the effects of BJP on Lithium-pilocarpine- induced seizures and its role in the regulation of oxidative stress and neurotransmission. Study Design: The present study elucidates the anti-epileptic effects and mechanisms of action of BJP, using a mouse model of Lithium-pilocarpine- induced seizures. Methods: The antiepileptic effect of BJP was tested by fear conditioning test of mice model. Nissl staining showed neural loss and apoptosis in the hippocampus seizure mice and BJP treatment. Immunohistochemistry analysis of Bcl-2 and Bax inflected anti-apoptotic effects of BJP. The chemical colorimetric method was utilized to determine the effects of BJP on oxidative stress. The levels of excitatory and inhibitory neurotransmitters in cerebrospinal fluid (CSF) were detected by ELISA. Whole-cell votage-clamp recording was made to detect currents of receptor gated channels. Results: We found that BJP can significantly improve the cognitive disorders of epileptic mice, prolonged the latency of seizures and reduced the duration of epilepsy. BJP also effectively ameliorate neural injury in the hippocampus, up-regulated Bcl-2 protein level whereas decreased Bax expression. Moreover, the levels of SOD, GSH as well as γ-aminobutyric acid (GABA) were increased, while the levels of MDA, aminomethyl phosphonic acid (AMPA) and N-Methyl-D-aspartic acid (NMDA) were decreased in the hippocampus with BJP treatment. Patch clamp recording showed that BJP had no significant effect on the current induced by GABA, NMDA and AMPA in acutely isolated mice hippocampal neurons. Furthermore, BJP inhibited the expression of P-gp, MRP1 and MDR1 protein. Conclusions: Our study provides the first experimental basis that BJP can exert anti-seizure effects by attenuating oxidative stress, regulating neurotransmission and inhibit drug-resistant associated proteins. BJP may be developed as a drug candidate to treat epilepsy in clinical practice.

Abstract Background Perfluoroalkyl and polyfluoroalkyl substances (PFAS) represent a category of pervasive and enduring environmental pollutants that present a risk to human health. Although growing evidence suggests that probiotics can potentially alleviate the adverse effects of PFAS, large cross-sectional studies on the relationship between probiotic consumption and PFAS remain lacking. Objective The objective of this study is to assess the association between the exposure of probiotics and serum levels of PFAS. Methods This analysis included individuals aged 20 and above who took part in the National Health and Nutrition Examination Survey (NHANES) between 2003 and 2018. Probiotic consumption was considered when a participant reported consuming yogurt during the two 24-h dietary recall or using a probiotic supplement in dietary supplement questionnaires over the past 30 days. Results This study involved 9469 adults, out of which 1333 had been exposed to probiotics. We found negative associations between probiotic consumption and serum concentrations of perfluorooctanoic acid (PFOA) (β: − 0.19, 95% CI − 0.35 to − 0.02; P = 0.027), and perfluorooctane sulfonic acid (PFOS) (β: − 0.1.27, 95% CI − 2.23 to − 0.32; P = 0.010). The consumption of probiotic supplements alone was associated with reduced perfluorononanoic acid (PFNA) (β: − 0.19, 95% CI − 0.28 to − 0.10; P

Zinc alloys have great potential to become a new generation of biodegradable implant materials for biomedical applications due to their moderate corrosion rates. However, the poor mechanical properties restrict the application of pure zinc as biomedical materials. In this study, Zn–0.1Mg–0.02Mn alloy was rolled to different reductions at room temperature. The 80% reduction rolled alloy showed the best mechanical performance with ultimate tensile strength and elongation of 397.7 MPa and 15.9%, respectively, which satisfy the requirement of biomedical implant materials. Grain refinement mainly promoted the strength enhancement with increased rolling reductions. The microstructure evolution reveals that the basal-oriented grains and non-basal-oriented grains had different deformation mechanisms to induce DRX process during rolling. DRX could be directly accelerated in basal-oriented grains by basal slip, while twinning and de-twinning process operate to refine the non-basal-oriented grains.

In view of the new scenario and time-sensitive requirements of sensing-transmission end to computing end in the industrial Internet, and to solve the problem of end-to-end delay in applications that were not up to standard, a network optimized design scheme for sensing-transmission cooperative computing was proposed.First, the sensing-transmission computing cooperative network architecture based on cloud-edge-end was proposed to promote the deep integration of multidimensional systems and heterogeneous resources.Secondly, the network topology construction mode was optimized to reduce the average path length of the network, shorten the propagation distance, and offset the problem of signal decay due to the use of higher frequencies.Finally, the routing method was improved, and an integrated algorithm of topology optimization and routing strategy was designed to reduce the queuing delay in the network, control the end-to-end delay within a bounded range, and weaken the “long tail phenomenon”.The experimental results show that the scheme reduces the end-to-end delay and ensures the real-time and reliability of the network by optimizing the network topology and routing strategy and integrating the design.

Abstract The discovery of semiconductor has witnessed remarkable strides toward high performance of photodetectors attributed to its excellent carrier properties. However, semimetal, owning to the high carrier concentration and low carrier mobility compared to those of semiconductor, is generally considered unsuitable for photodetection. Herein, we demonstrate an outstanding photodetection in a layered semimetal titanium diselenide (TiSe2) in Bose–Einstein condensation (BEC) state. High sensitivity of semimetal photodetector is realized in the range of visible, infrared and terahertz bands. The noise equivalent power (NEP) has threefold improvement at the visible and infrared wavebands, and significant decrease by one order of magnitude in the terahertz frequencies via BEC phenomenon, attributed to the electrical parameter variation after condensation. The best NEP value in the terahertz frequency is comparable to that of commercial Si photodetector. Our results show another recipe to fabricate high performance of photodetection via semimetal except for semiconductor and pave the way to exploit macroscopic quantum phenomena for optoelectronics.

Islet transplantation has now become a promising treatment for insulin-deficient diabetes mellitus. Compared to traditional diabetes treatments, cell therapy can restore endogenous insulin supplementation, but its large-scale clinical application is impeded by donor shortages, immune rejection, and unsuitable transplantation sites. To overcome these challenges, an increasing number of studies have attempted to transplant hydrogel-encapsulated islet cells to treat diabetes. This review mainly focuses on the strategy of hydrogel-encapsulated pancreatic islet cells for diabetic cell therapy, including different cell sources encapsulated in hydrogels, encapsulation methods, hydrogel types, and a series of accessorial manners to improve transplantation outcomes. In addition, the formation and application challenges as well as prospects are also presented.

The continuous retrieval of clear-sky land surface temperature (LST) holds paramount importance in monitoring vegetation temperature and assessing water stress conditions. Nonetheless, the extensive cloud cover results in a widespread lack of LST data, posing challenges in accurately forecasting LST in regions characterized by diverse vegetation types and complex terrains. Therefore, this paper proposes a synthetic aperture radar (SAR)- and digital elevation model (DEM)-integrated LST reconstruction model (SDX-LST) to generate realistic and high-spatial-resolution (30 m) clear-sky LST data. To assess the practicality and robustness of the SDX-LST model, this paper selects the study areas of Loess Plateau (LP), Qinghai-Tibet Plateau, Northeast China Plain, Nanling Mountains, and North China Plain in China, Desert Rock, Nevada in America, spanning a wide range of longitude and latitude and having obvious differences in topography, landforms, and vegetation. The analysis of the reconstruction results in different spatial location distributions, vegetation cover types, and multidate and time distributions throughout the year indicate that the SDX-LST model achieves excellent performance and high stability (with a mean absolute error lower than 2K). The SDX-LST predictions demonstrate a commendable level of consistency with the ERA5-hourly product and in situ data. We conclude that the integration of SAR and DEM within the SDX-LST model enables precise predictions of LST for various vegetation types and intricate terrains. The study quantitatively analyzes the effects of SAR and DEM on LST and introduces novel insights for exploring SAR-based reconstruction of LST.

Abstract In recent years, 2D reconfigurable phototransistors (RPTs) have been applied in broadband convolutional processing, retinomorphic hardware devices, and non‐volatile memorizers. However, there has been a lack of investigation into all‐2D Schottky junctions used in RPT with polarity control behavior. Herein, a vertically stacked multilayered WS2/WTe2 Schottky RPT is reported. The semimetal characteristics of 1T’‐WTe2 is designed to form a built‐in electric field of 69 meV across the heterojunction and WS2 exhibits gate‐tunable characteristics. Therefore, reconfigurable rectifying behavior and self‐driven bidirectional photo response can be achieved. The phototransistor possesses a gate‐tunable rectification ratio ranging from 10−2 to 105, and the corresponding logic half‐wave rectifier shows excellent switchable rectifying states. Under 635 nm illumination, the responsivity can be adjusted from −1325 to 430 mA W−1 with reversed signs. Meanwhile, the maximum power conversion efficiency is 2.84%, and the specific detectivity is 1.47 × 1012 Jones. The device shows both negative and positive responsivity with linear gate dependence within a voltage window of 10 V. Impressively, nonvolatile photovoltaic performance can be demonstrated by reversing short‐circuit current and open‐circuit voltage by applying and releasing pulsed gate voltage. Finally, reconfigurable polarization behavior, single‐pixel imaging, and the optical logic circuit are applicable to the heterostructure.

As an essential ecological barrier in the north of China, the grassland degradation situation in the Xilin Gol League of Inner Mongolia has remained severe in recent years. Based on data spanning from 2010 to 2022, this study utilizes a set of ten indicators, encompassing altitude, temperature, precipitation, wind speed, FVC, LAI, FRAR, NPP, ET, and above-ground biomass, to construct a Bayesian model for assessing ecological risks associated with vegetation change in the Xilin Gol League. In the case of the most crucial parameter, above-ground biomass, we integrate spectral bands, vegetation indices, and ground-truth data, employing the Random Forest algorithm to estimate the above-ground biomass in the Xilin Gol League. The study further applies the Mann-Kendall trend test and Sen's slope estimation to analyze changes in this parameter and employs it as an indicator for assessing grassland degradation. The results showed that (1) Overall, the risk level decreases gradually from the west to the east and aligns with the grassland types of the Xilin Gol League. (2) In terms of spatial and temporal distribution, medium and high-risk areas are primarily located in the western region of the Xilin Gol League, showing a distinct westward shift from 2010 to 2022. (3) Areas with higher grassland degradation risk are characterized by lower altitudes, higher temperatures, less precipitation, lower vegetation coverage, and reduced potential evapotranspiration. (4) Under the pressures of both climate warming and vegetation change, there has been a significant shift in grassland degradation risk levels in the Xilin Gol League. The application of the Bayesian model effectively reveals intricate causal relationships among various variables, such as climate, terrain, and vegetation dynamics. This study could provide guidance for the prevention and control of grassland degradation in the Xilin Gol League.

The effectiveness of silicon (Si) and silicon-based materials in catalyzing photoelectrochemistry (PEC) CO2 reduction is limited by poor visible light absorption. In this study, we prepared two-dimensional (2D) silicon-based photonic crystals (SiPCs) with circular dielectric pillars arranged in a square array to amplify the absorption of light within the wavelength of approximately 450 nm. By investigating five sets of n + p SiPCs with varying dielectric pillar sizes and periodicity while maintaining consistent filling ratios, our findings showed improved photocurrent densities and a notable shift in product selectivity towards CH4 (around 25% Faradaic Efficiency). Additionally, we integrated platinum nanoparticles, which further enhanced the photocurrent without impacting the enhanced light absorption effect of SiPCs. These results not only validate the crucial role of SiPCs in enhancing light absorption and improving PEC performance but also suggest a promising approach towards efficient and selective PEC CO2 reduction.

ABSTRACTTraditional ferroptosis activators typically suppress antitumor immunity. Our discovery shows that N6F11, a small molecule compound, can selectively induce ferroptosis by targeting TRIM25-mediated GPX4 degradation in cancer cells while sparing immune cells. This breakthrough establishes a safe and effective strategy to enhance ferroptosis-driven antitumor immunity.

Olivine, the most abundant mineral in the upper mantle, exhibits elastic anisotropy. Understanding the seismic anisotropy and flow patterns in the upper mantle hinges on the crystallographic preferred orientation (CPO) of olivine. Similarly, hydrous minerals, which also display elastic anisotropy, play a crucial role in explaining seismic anisotropy in numerous subduction zones. High-temperature and -pressure simple shear experiments reveal that the CPO of amphibole can lead to significant seismic anisotropy. In this study, peridotite samples originating from the southern end of the Mariana Trench, commonly containing amphibole, were analyzed. The microdeformation fabric and seismic anisotropy were examined. The results indicate a weak fabric strength in olivine, yet identifiable deformation fabrics of A/D, D, and AG were observed. Various dislocation structures suggest that olivine experiences complex deformation across various temperatures. Not only can the original slip system transform, but the melt/fluid resulting from melting also has a substantial impact on the peridotite. Deformation precedes the melt/rock interaction, resulting in a strong melt/rock reaction under near-static conditions. Furthermore, the modal content of amphibole significantly alters the seismic anisotropy of peridotite. An increase in amphibole content (types I, III, and IV) enhances seismic anisotropy, particularly for type I amphibole. Notably, the presence of type I fabric amphibole promotes the Vs1 polarization direction parallel to the trench in subduction zones, a phenomenon observed in other subduction zones. Therefore, when considering mantle peridotite regions rich in amphibole, the impact of amphibole on seismic anisotropy must be accounted for.

Atrial fibrillation (AF) is a common disease and is effectively managed through catheter ablation (CA). However, post-ablation AF recurrence can compromise patient outcomes, making the identification of associated risk factors crucially important. Factors influencing poor clinical outcomes include age, female sex, body mass index (BMI), non-paroxysmal AF, and comorbidities including diabetes mellitus (DM) and obstructive sleep apnea (OSA). Furthermore, the selected ablation strategy and employed technology are pivotal to long-term success in maintaining sinus rhythm control. The mechanisms of AF recurrence are complex and multifactorial; no single predictor is definitive. Thus, a personalized assessment of each patient should be tailored to the individual situation. A high risk of relapse does not preclude the option of ablation therapy, but rather underscores the necessity to address and manage underlying conditions contributing to AF pathogenesis, aiming to mitigate the risk of recurrence.

BackgroundPatients with inflammatory bowel disease (IBD) have a higher prevalence of depression. Gut microbiota dysbiosis plays an important role in IBD and depression. However, few studies have explored the characteristic microbiota of patients with IBD and depression (IBDD), or their role in IBDD.MethodsWe performed deep metagenomic sequencing and 16S rDNA quantitative PCR to characterise the gut microbial communities of patients with IBDD and patients with IBD without depression (IBDND). We then assessed the effect of the microbiota on colitis and depression in mouse models of dextran sulfate sodium salt (DSS)-induced colitis and lipopolysaccharide (LPS)-induced depression. Furthermore, liquid chromatography–tandem mass spectrometry was used to analyse the microbiota-derived metabolites involved in gut–brain communication. Evans Blue tracer dye was used to assess blood–brain barrier (BBB) permeability.ResultsOur results showed that the faecal abundance of Bacteroides vulgatus (B. vulgatus) was lower in patients with IBDD than in those with IBDND. In the DSS-induced colitis mouse model, the B. vulgatus group showed a significantly lower disease activity index score, lesser weight loss, and longer colon length than the DSS group. Moreover, B. vulgatus relieved depression-like behaviour in the DSS-induced colitis mouse model and in the LPS-induced depression mouse model. Furthermore, the key metabolite of B. vulgatus was p-hydroxyphenylacetic acid (4-HPAA), which was found to relieve intestinal inflammation and alleviate depression-like behaviours in mouse models. By increasing the expression of the tight junction protein claudin-5 in the vascular endothelium of the BBB, B. vulgatus and 4-HPAA play critical roles in gut–brain communication.ConclusionB. vulgatus and B. vulgatus-derived 4-HPAA ameliorated intestinal inflammation and relieved depressive symptoms through the gut–brain axis. Thus, administration of B. vulgatus or 4-HPAA supplementation is a promising therapeutic strategy for treating IBD, particularly IBDD.

BackgroundPancreatic cancer is renowned for its elevated incidence and mortality rates on a global scale. The disease burden of pancreatic cancer is anticipated to increase, particularly in Asia, due to its vast and rapidly aging population.MethodsData from the Global Burden of Disease 2019 were analyzed for pancreatic cancer burden across 52 countries in Asia, including the incidence, mortality, and disability-adjusted life years (DALY) for pancreatic cancer, with a focus on risk factors such as high body mass index (BMI), elevated fasting plasma glucose, and smoking. We applied the Estimated Annual Percentage Change, the Age–Period–Cohort model, and decomposition analysis to evaluate incidence trends and effects.ResultsFrom 1990 to 2019, both incidence and mortality rates of pancreatic cancer in Asia significantly increased, with an average annual standardized incidence rate change of 1.73%. Males consistently exhibited higher rates than females, with smoking as a key risk factor. Central Asia reported the highest rates, and South Asia the lowest. The incidence rose with age, peaking in those aged 70~74. The disease burden increased in all age groups, particularly in populations aged 55 and above, representing 84.41% of total cases in 2019, up from 79.01% in 1990. Pancreatic cancer ranked the fifth in incidence among six major gastrointestinal tumors but presented a significant growth rate of mortality and DALY.ConclusionWith the growing, aging population in Asia, the pancreatic cancer burden is projected to escalate, bringing a significant public health challenge. Hence, comprehensive public health strategies emphasizing early detection, risk modification, and optimized treatment of pancreatic cancer are imperative.

Abstract Achieving satisfactory performance for a solid‐state Na‐metal battery (SSNMB) with an inorganic solid electrolyte (SE), especially under freezing temperatures, poses a challenge for stabilizing a Na‐metal anode. Herein, this challenge is addressed by utilizing a Natrium super ionic conductor (NASICON) NASICON‐type solid electrolyte, enabling the operation of a rechargeable SSNMB over a wide temperature range from −20 to 45 °C. The interfacial resistance at the Na metal/SE interface is only 0.4 Ω cm2 at 45 °C and remains below 110 Ω cm2 even at −20 °C. Remarkably, long‐term Na‐metal plating/stripping cycles lasting over 2000 h at −20 °C are achieved with minimal polarization voltages at 0.1 mA cm−2. Further analysis reveals the formation of a uniform Na3−xCaxPO4 interphase layer at the interface, which significantly contributes to the exceptional interfacial performance observed. By employing a Na3V1.5Al0.5(PO4)3 cathode, the full battery system demonstrates excellent adaptability to low temperatures, exhibiting a capacity of 80 mA h g−1 at −20 °C over 50 cycles and retaining a capacity of 108 mAh g−1 (88.5% of the capacity at 45 °C) at 0 °C over 275 cycles. This research significantly reduces the temperature threshold for SSNMB operation and paves the way toward solid‐state batteries suitable for all‐season applications.

The receiving performance of a frequency hopping receiver based on interference and frequency-to-time mapping are analyzed. The broadening of the receiving passband induced by high frequency hopping speed is theoretically analyzed. The spurious-free dynamic range (SFDR), the frequency-dependent RF gain, and the average signal-to-noise ratio (SNR) corresponding to the RF gain are theoretically derived to indicate the receiving performance. Experimental verifications on the SFDR and RF gain were conducted. The SFDR of the passband at 7.21 GHz is 77.23 dBc, and for the passbands located from 7 GHz to 23 GHz, the SFDR variance is below 3.2 dB, which fits well with the simulated results with the difference of less than 3.7 dB. The RF gain for passbands located from 2.6 GHz to 40.9 GHz were tested, and the difference is less than 2 dB compared to the theoretical results.

Abstract Bionic self‐cleaning coatings have exhibited scaling inhibition for their low surface free energy. The key issue is focused on the long‐term anti‐scaling performance for the hydrophobicity failure after scaled. Inspired by “grass‐to‐stone” phenomenon, we reported a polymer coating (WCA = 120°, WSA = 14°) with the water contact angle of its 720 h‐scaled surface increased to 135°and scaling reduced by 90–95%. The nucleation and growth of CaCO3 at “coating‐crystal” interface are investigated, and a physical model for self‐healing film interface inhibiting scaling is innovatively proposed, as an important step toward designing long‐term anti‐scaling coating for engineering application.

Achieving photodetectors with a wide spectral range and rapid response remains challenging. Here, Sb2Te3 nanosheets are used to construct a photodetector that covers visible to millimeter wavelengths, with a fast response time of 900 ns.

Ferroptosis is lipid peroxidation-dependent cell death that has potential to be harnessed as a cancer therapeutic. Here, the authors show that the translation initiation factor eIF4E can repress ALDH1B1 independent of translation, increasing lipid peroxidation levels to promote ferroptosis.

The real-world crowns of broadleaf tree species feature green leaves surrounding branches, resulting in leaf spatial aggregation effect in the crown. However, the impact of such leaf spatial aggregation on chlorophyll content retrieval has not yet been determined. This study investigated the effect of leaf spatial aggregation on chlorophyll content retrieval in two distinct apple orchards with open canopies. The “PROSPECT + LESS” model was used for canopy reflectance simulation, and 25 hyperspectral vegetation indices (VIs) were analyzed to identify universal VIs for various leaf aggregations. Sensitivity analysis was conducted to evaluate the impact of leaf aggregation on the relationships between VIs and chlorophyll content. An artificial neural network regression algorithm was used to retrieve chlorophyll content by reversing the radiative transfer model (RTMs). The results show that leaf aggregation significantly affects the relationships between VIs and chlorophyll content as a result of the variability in the ratio of photosynthetic vegetation pixels to background pixels captured by the sensor at the top of the canopy. TCARI/OSAVI was found to be resistant to confounding factors (e.g., leaf area index and dry matter content) and maintained stable relationships with chlorophyll content. Leaf spatial aggregation had a significant impact on chlorophyll content retrieval, especially when leaves were highly aggregated. In such cases, the spectral variation driven by the photosynthetic vegetation was masked by the background, leading to a large divergence between simulated and observed spectra. Low to moderate levels of leaf aggregation, on the other hand, provided accurate chlorophyll content retrieval in both apple orchards (R2 = 0.49 to 0.67). In conclusion, when using 3D RTMs to retrieve chlorophyll content, it is recommended to configure low to moderate levels of leaf aggregation to ensure high accuracy and efficiency.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a fatal malignant tumor with an unfavorable prognosis. Increasing evidence indicated circRNAs were associated with the pathogenesis and progression of tumors, but data on the expression of serum exosomal circRNAs in PDAC are scarce. This study attempted to explore the prognostic value and function of serum exosomes in PDAC patients. Methods: Microarray-based circRNA expression was determined in PDAC and paired with normal serum samples, and the intersection of differentially expressed circRNAs (DECs) in serum exosomal samples and GSE79634 tissue samples was conducted. A specific CircRNA database was applied to investigate DECs binding miRNAs. Target genes were predicted using the R package multiMiR. Cox regression analyses were applied for constructing a prognostic model. The immunological characteristics analysis was carried out through the TIMER, QUANTISEQ, XCELL, EPIC, and ssGSEA algorithms. Results: 15 DECs were finally identified, and a circRNA-miRNA-mRNA network was established. A prognostic risk model was developed to categorize patients according to the risk scores. Furthermore, the association between risk score and immune checkpoint genes including CD80, TNFSF9, CD276, CD274, LGALS9, and CD44 were significantly elevated in the high-risk group, while ICOSLG and ADORA2A were upregulated in the low-risk group. Conclusions: Our results may provide new clues for the prognosis and treatment of PDAC.

Abstract In this work, a simple anti‐fingerprint strategy (reduced ≈40–60%) to rearrange fingerprint droplets by patterned micro/nano‐pore/spoons texture, air cushion and low surface energy is reported. Superior to previous precise and complex preparation methods, the micro/nano‐texture are fabricated through conventional process of spray and dip. The pore and spoon can be freely switched by changing the process. The number (N) and size (r) of pores and spoons are controlled intelligently by solvent volatilization and interfacial tension (γFP/PU−H2O and γFP/PU − Solvent), the key for pore/spoon's forming and expanding. A physical model of interface intelligent controlling the micro/nano‐pore/spoon surface texture induced by “Vacancy‐Capture” is proposed. The description is being reported, for the first time, to the knowledge, expecting to make it possible to prepare anti‐fingerprint engineering materials with newly potential industrial applications on optical device for large‐scale in the future.

Abstract Icephobic material is of great importance in power transportation, communication, aerospace, and so on. Bionic lotus superhydrophobic surfaces show good application prospects in anti‐icing by repelling impacting droplets. However, the boundary (criterion) between droplet bounce and deposition on superhydrophobic surface under cold freezing rain is unclear. Here, from the view of statistics, the boundary and internal heat transfer mechanism of the droplet bounce, pinning, and three kinds of deposition including icing at later, early retraction, and spread. are clarified Droplet viscosity increase reduces droplet contact with surface and inhibited splash at high We. Surfaces with temperature above −20.6 °C showed 100% droplet bounce after impact on We = 64.7, and the probability of water adhesion and ice nucleation decreases to ≈0%, resulting in completely anti‐icing. Droplet bounce transition mainly ascribe to the decrease retraction driven force caused by interface freezing and transition temperature increases approximately linearly from −25.9 to −21.1 °C within 21.6 < We < 75.5. Ice nuclei brought by condensation in humid environment (60–100 RH%) further cause droplet eccentric retraction and transition temperature increases to −6 to −10 °C. The fundamental understanding of droplet behaviors on supercooled superhydrophobic surface is beneficial for icephobic surfaces applications.

Islet transplantation is a promising strategy for diabetes mellitus treatment as it can recapitulate endogenous insulin secretion and provide long-term glycemic control. Islet models constructed in biomaterial scaffolds that reproduce biological characteristics of native islets is a feasible option to circumvent the dilemma of donor shortage and the requirement of chronic immunosuppression. Herein, we developed bioinspired artificial microcapsule-based islet models with microvessels for glycemic control using microfluidic electrospray strategy. Microfluidic electrospray can generate uniform hydrogel microcapsules with core-shell structure for encapsulating islet cells. The cell-laden microcapsules enabled the efficient transportation of nutrient, oxygen, and insulin; as well as the incorporation with microvessels for prompting glucose responsiveness and molecular exchange. We demonstrated by in vivo experiments that the blood glucose, food intake, and body weight of diabetic mouse models were alleviated, and the glucose tolerance was promoted after the engraftment of islet microcapsules. We further demonstrated the improved functionality of transplanted islet model in insulin secretion, immune escape, and microcirculation using standard histological and molecular analysis. These results indicated that the microcapsules with microvessels are promising artificial islet models and are valuable for treating diabetes.

Long-term exposure to high concentrations of fine particles can cause irreversible damage to people’s health. Therefore, it is of extreme significance to conduct large-scale continuous spatial fine particulate matter (PM2.5) concentration prediction for air pollution prevention and control in China. The distribution of PM2.5 ground monitoring stations in China is uneven with a larger number of stations in southeastern China, while the number of ground monitoring sites is also insufficient for air quality control. Remote sensing technology can obtain information quickly and macroscopically. Therefore, it is possible to predict PM2.5 concentration based on multi-source remote sensing data. Our study took China as the research area, using the Pearson correlation coefficient and GeoDetector to select auxiliary variables. In addition, a long short-term memory neural network and random forest regression model were established for PM2.5 concentration estimation. We finally selected the random forest regression model (R2 = 0.93, RMSE = 4.59 μg m−3) as our prediction model by the model evaluation index. The PM2.5 concentration distribution across China in 2021 was estimated, and then the influence factors of high-value regions were explored. It is clear that PM2.5 concentration is not only related to the local geographical and meteorological conditions, but also closely related to economic and social development.

Grassland desertification stands as an ecological concern globally. It is crucial for desertification prevention and control to comprehend the variation in area and severity of desertified grassland (DGL), clarify the intensities of conversion among DGLs of different desertification levels, and explore the spatial and temporal driving factors of desertification. In this study, a Desertification Difference Index (DDI) model was constructed based on albedo-EVI to extract desertification information. Subsequently, intensity analysis, the Geo-detector model, and correlation analysis were applied to analyze the dynamics and driving factors of desertification. The results showed the following: (1) Spatially, the DGL in Xilingol exhibited a zonal distribution. Temporally, the degree of DGL decreased, with the proportion of severely and moderately desertified areas decreasing from 51.77% in 2000 to 37.23% in 2020, while the proportion of nondesertified and healthy areas increased from 17.85% in 2000 to 37.40% in 2020; (2) Transition intensities among different desertification levels were more intense during 2000–2012, stabilizing during 2012–2020; (3) Meteorological factors and soil conditions primarily drive the spatial distribution of DDI, with evapotranspiration exhibiting the most significant influence (q-value of 0.83), while human activities dominate interannual DDI variations. This study provides insights into the conversion patterns among different desertification levels and the divergent driving forces shaping desertification in both spatial and temporal dimensions in Xilingol.

Abstract Droplet bouncing on special wettability surface is common and important in daily life and engineering applications (anti‐icing and drag reduction, etc.). However, there are few studies on the multiple droplets impact and there is a lack of systematic research on the interaction of oscillation and bounce. Here, the impact and oscillation of multiple droplets on the porous superhydrophobic bionic lotus surface are studied by a high‐speed camera system. On the bionic lotus surface (Surf‐1), an impacting droplet can merge another larger sessile droplet and bounce off. Comparing with single droplet impact, it is suggested that multiple droplets impact make more efficient use of the air cushion on the micrometer‐nanometer‐scale binary structure (MNBS) and show the self‐cleaning performance of Surf‐1 better. Moreover, with the theory for damped harmonic oscillators, it is found that Surf‐1 can prolong the oscillation of droplets (last >250 ms) and slow down the attenuation of energy. The energy can be efficiently recycled to the bounce by shortening the droplet impact interval (ti). The fundamental understanding of multiple droplets impact and the reclamation of oscillating energy are beneficial for scientific design of new surface and engineering applications.

Abstract Few‐layer transition metal dichalcogenides (TMDs) and their combination as van der Waals heterostructures provide a promising platform for high‐performance optoelectronic devices. However, the ultrathin thickness of TMD flakes limits efficient light trapping and absorption, which triggers the hybrid construction with optical resonant cavities for enhanced light absorption. The optical structure enriched photodetectors can also be wavelength‐ and polarization‐sensitive but require complicated fabrication. Herein, a new‐type TMD‐based photodetector embedded with nanoslits is proposed to enhance light trapping. Taking ReS2 as an example, strong anisotropic Mie‐type optical responses arising from the intrinsic in‐plane anisotropy and nanoslit‐enhanced anisotropy are discovered. Owing to the nanoslit‐enhanced optical resonances and band engineering, excellent photodetection performances are demonstrated with high responsivity of 27 A W−1 and short rise/decay times of 3.7/3.7 ms. More importantly, through controlling the angle between the nanoslit orientation and the polarization direction to excite different resonant modes, polarization‐sensitive photodetectors with anisotropy ratios from 5.9 to 12.6 can be achieved, representing one of the most polarization‐sensitive TMD‐based photodetectors. The depth and orientation of nanoslits are demonstrated crucial for optimizing the anisotropy ratio. The findings bring an effective scheme to construct high‐performance and polarization‐sensitive photodetectors.

Abstract In this work, a vertical gallium nitride (GaN)-based trench MOSFET on 4-inch free-standing GaN substrate is presented with threshold voltage of 3.15 V, specific on-resistance of 1.93 mΩ·cm2, breakdown voltage of 1306 V, and figure of merit of 0.88 GW/cm2. High-quality and stable MOS interface is obtained through two-step process, including simple acid cleaning and a following (NH4)2S passivation. Based on the calibration with experiment, the simulation results of physical model are consistent well with the experiment data in transfer, output, and breakdown characteristic curves, which demonstrate the validity of the simulation data obtained by Silvaco technology computer aided design (Silvaco TCAD). The mechanisms of on-state and breakdown are thoroughly studied using Silvaco TCAD physical model. The device parameters, including n−-GaN drift layer, p-GaN channel layer and gate dielectric layer, are systematically designed for optimization. This comprehensive analysis and optimization on the vertical GaN-based trench MOSFETs provide significant guide for vertical GaN-based high power applications.

Substrate inhibition has not been widely studied in the context of synthetic biology and metabolic engineering. Here, the authors report removal of lycopene substrate inhibition by two different strategies and enable high carotenoid productivity in Yarrowia lipolytica.

Purpose: We aim to present effective and computer aided diagnostics in the field of ophthalmology and improve eye health. This study aims to create an automated deep learning based system for categorizing fundus images into three classes: normal, macular degeneration and tessellated fundus for the timely recognition and treatment of diabetic retinopathy and other diseases.Methods: A total of 1,032 fundus images were collected from 516 patients using fundus camera from Health Management Center, Shenzhen University General Hospital Shenzhen University, Shenzhen 518055, Guangdong, China. Then, Inception V3 and ResNet-50 deep learning models are used to classify fundus images into three classes, Normal, Macular degeneration and tessellated fundus for the timely recognition and treatment of fundus diseases.Results: The experimental results show that the effect of model recognition is the best when the Adam is used as optimizer method, the number of iterations is 150, and 0.00 as the learning rate. According to our proposed approach we, achieved the highest accuracy of 93.81% and 91.76% by using ResNet-50 and Inception V3 after fine-tuned and adjusted hyper parameters according to our classification problem.Conclusion: Our research provides a reference to the clinical diagnosis or screening for diabetic retinopathy and other eye diseases. Our suggested computer aided diagnostics framework will prevent incorrect diagnoses caused by the low image quality and individual experience, and other factors. In future implementations, the ophthalmologists can implement more advanced learning algorithms to improve the accuracy of diagnosis.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with poor outcomes. Although the management strategies have evolved in recent years, the PDAC 5-year survival rate remains at only 9%; it may become the second leading cause of cancer death in the USA by 2030. Only 15–20% of PDAC patients are eligible to undergo surgery; diagnostic biopsies and individualized treatment present a more significant challenge for the remaining group. Endoscopic ultrasound-guided tissue acquisition (EUS-TA) has been widely used in the diagnosis of pancreatic masses. With the advancement of this sampling technique, adequate specimens can be obtained from all patients with PDAC in both early and late clinical stages. Recent data suggest that the specimens obtained from EUS-TA might be used to establish viable preclinical models, which conserve the genetic mutation and preserve the heterogeneity of the original tumors. Additionally, any drug sensitivity evident in the EUS-TA-derived preclinical models might predict the clinical response, thus guiding the prospective therapeutic selection. As we move toward the era of precision medicine, this review provides an update on the role of EUS-TA as a method for obtaining genetic material used in preclinical models that can assess and stratify individuals according to their individual cancer biology.

BackgroundThe mechanism of copper-induced cellular death was newly discovered and termed cuproptosis. Inducing cuproptosis in cancer cells is well anticipated for its curative potential in treating tumor diseases. However, ferredoxin 1 (FDX1), the core regulatory gene in cuproptosis, is rarely studied, and the regulation of FDX1 in tumor biology remains obscure. A comprehensive pan-cancer analysis of FDX1 is needed.MethodsThirty-three types of tumors were included with paired normal tissues in The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets. The interaction between transcription, protein, phosphorylation, and promoter methylation levels was analyzed. Survival, immune infiltration, single-cell FDX1 expression, FDX1-related tumor mutational burden (TMB), microsatellite instability (MSI), stemness, tumor immune dysfunction and exclusion (TIDE), and immunotherapy-related analyses were performed. FDX1 protein expression was assessed by kidney renal clear cell carcinoma (KIRC) tissue microarray immunohistochemistry. The function of FDX1 in KIRC was further explored by experiments in 786-O cell lines in vitro.ResultsFDX1 is highly expressed in 15 tumor types and lowly expressed in 11 tumor types. The corresponding changes in protein expression, phosphorylation, and promoter methylation level of FDX1 have been described in several tumors. Survival analysis showed that FDX1 was related to favorable or poor overall survival in eight tumors and progression-free survival in nine tumors. Immune infiltration and single-cell analysis indicated the indispensable role of FDX1 expression in macrophages and monocytes. Multiple established immunotherapy cohorts suggested that FDX1 may be a potential predictor of treatment effects for tumor patients. Tissue microarray analysis showed decreased FDX1 expression in KIRC patients’ tumor tissues. Knockdown of FDX1 resulted in the downregulation of cuproptosis in kidney renal clear tumor cells. Mechanistically, the FDX1-associated gene expression signature in KIRC is related to the enrichment of genes involved in the tricarboxylic acid (TCA) cycle, NOTCH pathway, etc. Several NOTCH pathway genes were differentially expressed in the high- and low-FDX1 groups in KIRC.ConclusionOur analysis showed that the central regulatory gene of cuproptosis, FDX1, has differential expression and modification levels in various tumors, which is associated with cellular function, immune modulation, and disease prognosis. Thus, FDX1-dependent cuproptosis may serve as a brand-new target in future therapeutic approaches against tumors.

Abstract Due to the increase in computing power, it is possible to improve the feature extraction and data fitting capabilities of DNN networks by increasing their depth and model complexity. However, the big data and complex models greatly increase the training overhead of DNN, so accelerating their training process becomes a key task. The Tianhe-3 peak speed is designed to target E-class, and the huge computing power provides a potential opportunity for DNN training. We implement and extend LeNet, AlexNet, VGG, and ResNet model training for a single MT-2000+ and FT-2000+ compute nodes, as well as extended multi-node clusters, and propose an improved gradient synchronization process for Dynamic Allreduce communication optimization strategy for the gradient synchronization process base on the ARM architecture features of the Tianhe-3 prototype, providing experimental data and theoretical basis for further enhancing and improving the performance of the Tianhe-3 prototype in large-scale distributed training of neural networks.

ε-Caprolactone is traditionally produced through Baeyer-Villiger oxidation of cyclohexanone oxidized by peracids in industry, which inevitably results in large discard acid and environmental pollution. To this end, a green route to ε-caprolactone was developed by coupling the direct generation of hydrogen peroxide from aerobic oxidation of benzhydrol catalyzed by NHPI and Baeyer-Villiger oxidation of cyclohexanone with the in situ hydrogen peroxide over Sn-Beta zeolites in one pot. Molecular oxygen was employed as the terminal oxidant, and the effects of several reaction factors were studied. Compared with one-step process, the one-pot two-step method noticeably improved the selectivity of ε-caprolactone. When the amount of in situ hydrogen peroxide was 0.72 equivalent, the selectivity of ε-caprolactone was obtained 94.8% with 39.2% conversion of cyclohexanone, and the efficiency of H2O2 was up to 51.5%. As compared to the commercial 30 wt% aqueous H2O2 added directly, in situ H2O2 dramatically improved the selectivity of ε-caprolactone and had higher efficiency. Additionally, the catalyst could be easily separated from the reaction solution and reused several times without the remarkable loss of activity.

Summary: Silicon (Si) is the most important semiconductor material broadly used in both electronics and optoelectronics. However, the performance of Si-based room temperature detectors is far below the requirements for direct detection in the terahertz (THz) band, a very promising electromagnetic band for the next-generation technology. Here, we report a high sensitivity of room temperature THz photodetector utilizing the electromagnetic induced well mechanism with an SOI-based structure for easy integration. The detector achieves a responsivity of 122 kV W−1, noise equivalent power (NEP) of 0.16 pW Hz−1/2, and a fast response of 1.29 μs at room temperature. The acquired NEP of the detector is ∼2 orders lower in magnitude than that of other types of Si-based detectors. Our results pave the way to realize Si-based THz focal plane arrays, which can be used in a wide range of applications, such as medical diagnosis, remote sensing, and security inspection.

Electronegative guest‐filled skutterudites (EN‐SKDs) are considered one of the most promising thermoelectric materials for next‐generation thermoelectric generators (TEGs). However, the practical application of EN‐SKDs in TEGs is still a huge challenge because of their unsatisfactory zT value (less than 1.0). Herein, Ge, Te‐codoped electronegative sulfur‐filled skutterudites of S x Co4Sb11Ge0.2Te0.8 (x = 0, 0.05, 0.1, 0.2, 0.25) are synthesized. The optimal zT value of as high as 1.45 at 823 K with a low room‐temperature lattice thermal conductivity of 1.98 W m−1 K−1 is achieved by S0.25Co4Sb11Ge0.2Te0.8. Such performance is competitive with those of traditional TE materials and among one of the best EN‐SKDs. The excellence is attributed to the synergistic effect of the disorder caused by Ge, Te co‐doping at Sb‐site and the “rattling” effect of electronegative element S. Furthermore, a novel EN‐SKD‐based TEG is prepared for the first time through an integrated welding process and exhibits a high efficiency of 6.0% at the temperature difference of 475 K. This work provides valuable guidance for designing advanced thermoelectric materials and paves a way toward high‐performance EN‐SKD‐based TEGs.

Detection and counting of wheat heads are crucial for wheat yield estimation. To address the issues of overlapping and small volumes of wheat heads on complex backgrounds, this paper proposes the YOLOv7-MA model. By introducing micro-scale detection layers and the convolutional block attention module, the model enhances the target information of wheat heads and weakens the background information, thereby strengthening its ability to detect small wheat heads and improving the detection performance. Experimental results indicate that after being trained and tested on the Global Wheat Head Dataset 2021, the YOLOv7-MA model achieves a mean average precision (MAP) of 93.86% with a detection speed of 35.93 frames per second (FPS), outperforming Faster-RCNN, YOLOv5, YOLOX, and YOLOv7 models. Meanwhile, when tested under the three conditions of low illumination, blur, and occlusion, the coefficient of determination (R2) of YOLOv7-MA is respectively 0.9895, 0.9872, and 0.9882, and the correlation between the predicted wheat head number and the manual counting result is stronger than others. In addition, when the YOLOv7-MA model is transferred to field-collected wheat head datasets, it maintains high performance with MAP in maturity and filling stages of 93.33% and 93.03%, respectively, and R2 values of 0.9632 and 0.9155, respectively, demonstrating better performance in the maturity stage. Overall, YOLOv7-MA has achieved accurate identification and counting of wheat heads in complex field backgrounds. In the future, its application with unmanned aerial vehicles (UAVs) can provide technical support for large-scale wheat yield estimation in the field.

Xinjiang, in Northwestern China, was a key point in the prehistoric trans-Eurasian network of exchange and played an important role in facilitating the dispersal of crops across Eurasia. Millet crops were first cultivated and used ca. 10,000 years ago in Northern China, from where they spread via different routes, leaving intriguing traces in various sites across Xinjiang. This paper presents the latest data on millet in Xinjiang. By employing a multidisciplinary approach, including radiocarbon dating, archaeobotanical evidence, and carbon isotope datasets, this study explores potential routes by which millet entered Xinjiang and traces its expansion from the third millennium BC to the 10th century AD. The research highlights the significant role of millet in shaping the ancient economies and cultures of Xinjiang and Central Asia, while also underscoring the importance of further investigation to uncover the complex pathways of its dispersal across Eurasia.

Abstract Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignant disease with a unique tumor microenvironment surrounded by an interlaced network of cancer and noncancerous cells. Recent works have revealed that the dynamic interaction between cancer cells and neuronal cells leads to perineural invasion (PNI), a clinical pathological feature of PDAC. The formation and function of PNI are dually regulated by molecular (e.g., involving neurotrophins, cytokines, chemokines, and neurotransmitters), metabolic (e.g., serine metabolism), and cellular mechanisms (e.g., involving Schwann cells, stromal cells, T cells, and macrophages). Such integrated mechanisms of PNI not only support tumor development, growth, invasion, and metastasis but also mediate the formation of pain, all of which are closely related to poor disease prognosis in PDAC. This review details the modulation, signaling pathways, detection, and clinical relevance of PNI and highlights the opportunities for further exploration that may benefit PDAC patients.

The normalized difference vegetation index (NDVI) is crucial to many sustainable agricultural practices such as vegetation monitoring and health evaluation. However, optical remote sensing data often suffer from a large amount of missing information due to sensor failures and harsh atmospheric conditions. The synthetic aperture radar (SAR) offers a new approach to filling in missing optical data based on its excessive revisit density and its potential to image without interference from clouds and rain. Due to the difference in imaging mechanisms between SAR and optical sensors, it is very difficult to fuse the data. This paper developed an advanced deep learning Spatio-temporal fusion method, i.e., Transformer Temporal-spatial Model (TTSM), to synergize the SAR and optical time-series to reconstruct vegetation NDVI time series in cloudy regions. The proposed multi-head attention and end-to-end architecture achieved satisfactory accuracy (R2 greater than 0.88), outperforming the existing deep learning solutions. Extensive experiments were carried out to evaluate the TTSM method on large-scale areas (the spatial scale of megapixels) in northeast China with the main vegetation types of crops and forests. The R2, SSIM, RMSE, NRMSE, and MAE of our prediction results were 0.88, 0.80, 0.06, 0.16, and 0.05, respectively. The influence of training sample size was investigated through a transfer learning study, and the result indicated that the model had good generalizability. Overall, our proposed method can fill in the gap of optical data at an extensive regional scope over the vegetated area using SAR.

Abstract The demand to increase energy density of rechargeable batteries for portable electronic devices and electric vehicles and to reduce the cost for grid‐scale energy storage necessitates the exploration of new chemistries of electrode materials for rechargeable batteries. The open framework‐structure of Prussian‐blue materials has recently been demonstrated as a promising cathode host for a variety of monovalent and multivalent cations with the tunable working voltage and discharge capacities. Recent progress toward the application of Prussian‐blue cathode materials for rechargeable batteries is reviewed, with special emphasis on charge‐storage mechanisms of different insertion species, factors influencing electrochemical performances, and possible approaches to overcome their intrinsic limitations.