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Abstract Background This study aimed to construct a novel nomogram based on the number of positive lymph nodes to predict the overall survival of patients with pancreatic head cancer after radical surgery. Materials and methods 2271 and 973 patients in the SEER Database were included in the development set and validation set, respectively. The primary clinical endpoint was OS (overall survival). Univariate and multivariate Cox regression analyses were used to screen independent risk factors of OS, and then independent risk factors were used to construct a novel nomogram. The C-index, calibration curves, and decision analysis curves were used to evaluate the predictive power of the nomogram in the development and validation sets. Results After multivariate Cox regression analysis, the independent risk factors for OS included age, tumor extent, chemotherapy, tumor size, LN (lymph nodes) examined, and LN positive. A nomogram was constructed by using independent risk factors for OS. The C-index of the nomogram for OS was 0.652 [(95% confidence interval (CI): 0.639–0.666)] and 0.661 (95%CI: 0.641–0.680) in the development and validation sets, respectively. The calibration curves and decision analysis curves proved that the nomogram had good predictive ability. Conclusions The nomogram based on the number of positive LN can effectively predict the overall survival of patients with pancreatic head cancer after surgery.

BackgroundSolid pseudopapillary neoplasm of the pancreas (SPN) is a rare and low-grade malignant tumor. It mainly occurs in women of reproductive age, accounting for approximately 1-3% of all pancreatic tumors. SPN has a low incidence rate and is difficult to diagnose before surgery. Some cases may show local infiltration, but distant metastasis rarely occurs. Currently, there is no standardized treatment protocol for SPN.Patient and methodsWe have collected clinical data from 5 patients with solid pseudopapillary neoplasm (SPN) of the pancreas who presented with distant metastasis at our hospital. This study retrospectively analyzes their clinical manifestations, imaging characteristics, pathological findings, and treatment outcomes. The aim is to summarize the clinical features of SPN with distant metastasis, thereby improving the diagnosis, treatment, and prognosis prediction of this disease. This study also reviews relevant literature.ResultsThe median age of the 5 patients was 32 years old, with a male-to-female ratio of 1:4. All patients underwent enhanced CT scans and were diagnosed with SPN through biopsy or surgical pathology. All 5 patients had liver metastases, and one patient had clavicular lymph node metastasis. Another patient had both lung and clavicular lymph node metastases. Three patients underwent curative surgery, one patient received chemotherapy combined with targeted immunotherapy and subsequently underwent TACE(Transcatheter arterial chemoembolization) and HAIC (Hepatic artery infusion chemotherapy) treatments due to progression. One patient received internal radiation therapy but experienced multiple relapses and eventually died due to complications. The follow-up period ranged from 7 to 53 months, with 2 patients succumbing to the disease.ConclusionAs a low-grade tumor, SPN has a low rate of distant metastasis, typically occurring in only 5%-15% of cases. These metastases often lack characteristic clinical symptoms. Diagnosis can only be confirmed after exclusion of other lesions through imaging and pathological examination. The primary treatment for metastatic SPN is curative surgery, which can lead to a favorable prognosis.

Abstract Extensive investigations on the moiré magic angle in twisted bilayer graphene have unlocked the emerging field—twistronics. Recently, its optics analogue, namely opto-twistronics, further expands the potential universal applicability of twistronics. However, since heat diffusion neither possesses the dispersion like photons nor carries the band structure as electrons, the real magic angle in electrons or photons is ill-defined for heat diffusion, making it elusive to understand or design any thermal analogue of magic angle. Here, we introduce and experimentally validate the twisted thermotics in a twisted diffusion system by judiciously tailoring thermal coupling, in which twisting an analog thermal magic angle would result in the function switching from cloaking to concentration. Our work provides insights for the tunable heat diffusion control, and opens up an unexpected branch for twistronics -- twisted thermotics, paving the way towards field manipulation in twisted configurations including but not limited to fluids.

Abstract Background The purpose of this propensity score matching (PSM) analysis was to compare the effects of preoperative transcatheter arterial chemoembolization (TACE) and non-TACE on the long-term survival of patients who undergo radical hepatectomy. Methods PSM analysis was performed for 387 patients with hepatocellular carcinoma (HCC) (single > 3 cm or multiple) who underwent radical resection of HCC at our centre from January 2011 to June 2018. The patients were allocated to a preoperative TACE group (n = 77) and a non-TACE group (n = 310). The main outcome measures were progression-free survival (PFS) and overall survival (OS) since the treatment date. Results After PSM, 67 patients were included in each of the TACE and non-TACE groups. The median PFS times in the preoperative TACE and non-TACE groups were 24.0 and 11.3 months, respectively (p = 0.0117). The median OS times in the preoperative TACE and non-TACE groups were 41.5 and 29.0 months, respectively (p = 0.0114). Multivariate Cox proportional hazard regression analysis revealed that preoperative TACE (hazard ratio, 1.733; 95% CI, 1.168–2.570) and tumour thrombosis (hazard ratio, 0.323; 95% CI, 0.141–0.742) were independent risk factors significantly associated with OS. Conclusions Preoperative TACE is related to improving PFS and OS after resection of HCC. Preoperative TACE and tumour thrombus volume were also found to be independent risk factors associated with OS.

One-time application of blended controlled-release nitrogen fertilizer (CRN) has the potential to solve the difficulty of top-dressing fertilizer in the cultivation of rice and reduce the cost of CRN fertilizer application. However, its effects on rice dry matter and nitrogen (N) accumulation and translocation, yield and N-use efficiency (NUE) remain uncertain. Field experiments were carried out at three sites (Mingguang, Chaohu, and Guichi) in the Yangtze River Delta in China to compare the effects of the conventional split applications of urea and the blended CRN and on post-anthesis dry matter and N accumulation and translocation, yield, and NUE in rice at 0, 60, 120, 180, and 240 kg N ha-1. The results showed that at the equal N application rates, compared under the conventional N fertilizer treatment, the blended CRN application significantly increased the rice yield by an average of 0.9-6.9%, mainly due to increase the number of spikelets per panicle. The highest yield achieved with blended CRN treatment occurred at 200 kg N ha-1, with an NUE of 45.9%. Moreover, in comparison to the conventional N fertilizer, the blended CRN treatment increased pre-anthesis N translocation (Pre-NT) by 1.0-19.8%, and the contribution of pre-NT to grain N by 0.2-8.7%, and NUE by 3.2-28.4%. Meanwhile, the blended CRN treatment reduced labor costs by 1800 Yuan ha-1 and enhanced the economic gains by 21.5-68.8%. Therefore, one-time application of blended CRN ≤ 200 kg N ha-1 application rate improved rice yield, NUE, and economic profit compared to equivalent rates of split applied conventional N fertilizers.

Abstract Wavelength-selective thermal emitters (WS-TEs) have been frequently designed to achieve desired target emissivity spectra, as a typical emissivity engineering, for broad applications such as thermal camouflage, radiative cooling, and gas sensing, etc. However, previous designs require prior knowledge of materials or structures for different applications and the designed WS-TEs usually vary from applications to applications in terms of materials and structures, thus lacking of a general design framework for emissivity engineering across different applications. Moreover, previous designs fail to tackle the simultaneous design of both materials and structures, as they either fix materials to design structures or fix structures to select suitable materials. Herein, we employ the deep Q-learning network algorithm, a reinforcement learning method based on deep learning framework, to design multilayer WS-TEs. To demonstrate the general validity, three WS-TEs are designed for various applications, including thermal camouflage, radiative cooling and gas sensing, which are then fabricated and measured. The merits of the deep Q-learning algorithm include that it can (1) offer a general design framework for WS-TEs beyond one-dimensional multilayer structures; (2) autonomously select suitable materials from a self-built material library and (3) autonomously optimize structural parameters for the target emissivity spectra. The present framework is demonstrated to be feasible and efficient in designing WS-TEs across different applications, and the design parameters are highly scalable in materials, structures, dimensions, and the target functions, offering a general framework for emissivity engineering and paving the way for efficient design of nonlinear optimization problems beyond thermal metamaterials.

Abstract Amphiphilic polymers (HA-ANI) were prepared by grafting hyaluronic acid (HA) and 6-(2-nitroimidazole)hexylamine (ANI) and then self-assemble in water to form nanoparticles (NPs) that could be loaded with paclitaxel (PTX) and gemcitabine (GEM) by dialysis. Infrared spectroscopy and 1H-NMR indicated the successful synthesis of HA-ANI. Three different ratios of NPs were prepared by adjusting the ratios of hydrophilic and hydrophobic materials, and the particle size decreased as the ratio of hydrophilic materials increased. When HA:ANI = 2.0:1, the nanoparticles had the smallest size distribution, good stability and near spherical shape and had high drug loading and encapsulation rates. In vitro release experiments revealed that NADPH could accelerate the drug release from NPs. Cellular uptake rate reached 86.50% at 6 h. The toxic effect of dual drug-loaded nanoparticles (P/G NPs) on MDA-MB-231 cells at 48 h was stronger than that of the free drug. The AO/EB double-staining assay revealed that a large number of late apoptotic cells appeared in the P/G NPs group, and the degree of cell damage was significantly stronger than that of the free drug group. In the cell migration assay, the 24 h-cell migration rate of the P/G NPs group was 5.99%, which was much lower than that of the free group (13.87% and 17.00%). In conclusion, MDA-MB-231 cells could effectively take up P/G NPs, while the introduction of the nano-codelivery system could significantly enhance the toxicity of the drug to MDA-MB-231 cells as well as the migration inhibition effect.

Abstract Multispectral camouflage technologies, especially in the most frequently-used visible and infrared (VIS-IR) bands, are in increasing demand for the ever-growing multispectral detection technologies. Nevertheless, the efficient design of proper materials and structures for VIS-IR camouflage is still challenging because of the stringent requirement for selective spectra in a large VIS-IR wavelength range and the increasing demand for flexible color and infrared signal adaptivity. Here, a material-informatics-based inverse design framework is proposed to efficiently design multilayer germanium (Ge) and zinc sulfide (ZnS) metamaterials by evaluating only ~1% of the total candidates. The designed metamaterials exhibit excellent color matching and infrared camouflage performance from different observation angles and temperatures through both simulations and infrared experiments. The present material informatics inverse design framework is highly efficient and can be applied to other multi-objective optimization problems beyond multispectral camouflage.

Ratoon rice cultivation has expanded to improve resource use efficiency, increase economic profits, and ensure food security in China in recent years. This article reviewed the development history and research progress of ratoon rice in Anhui Province, located in the lower reaches of the Yangtze River. Key cultivation technologies related to rice variety selection, planting patterns, fertilizer and water management strategies, as well as harvesting methods and stubble heights of the main crop for high-yielding ratoon rice were summarized. Particularly, we described three types of rice ratooning technologies in Anhui, including the technologies for medium-duration indica hybrid variety with the main crop harvested mechanically at high stubble height, for indica-japonica hybrid variety with the main crop harvested mechanically at medium stubble height, and for short-duration indica variety with the main crop harvested mechanically at low stubble height. Additionally, this review analyzed several challenges for the sustainable development of ratoon rice in Anhui, such as poor understanding of mechanisms underlying simultaneous improvement of high yield and high quality, the lack of rice varieties with strong ratooning ability, the yield loss from mechanical harvesting of the main crop, the unstable grain yield due to adverse weather, and the insufficient financial support for R&D. Finally, the prospects for further development of ratoon rice were proposed, including technology development and dissemination, farmers' training, and profit-boosting from premium products.

Abstract It is widely adopted in thermal metamaterials that mixing different materials could conveniently result in effective thermal conductivities (ETCs) beyond naturally-occurring materials. When multiple materials are isotropically mixed, the ETC is a direct average governed by their filling fractions and given bulk conductivities. That could lead to an inhomogeneous and anisotropic value within the maximal and minimal thermal conductivities of constituent materials. Usually thermal metadevices rely on anisotropic thermal conductivity tensor, whose tensorial elements are frequently inter-dependent and confined within a limited parametric space. It is thus nontrivial to establish a design recipe for advanced thermal metamaterials whose ETCs could cover full-parameter anisotropic space. We demonstrate topological functional cells (TFCs) with copper and polydimethylsiloxane, and show that the anisotropic ETCs traverse their full-parameter space. Such robust scheme based on topology-optimized TFCs unlocks unexplored opportunities for functional thermal metadevices whose parameters may not be reached in previous mixing approaches. This study also sheds light on the developments in emerging acoustic, mechanical and electromagnetic composite materials.

Thermal metamaterials can be used to manipulate heat flow but experimental fabrication is challenging. Here, the authors report robustly printable freeform thermal metamaterials to tackle this challenge by topology optimization and 3D printing.

The dynamic evolution of particle size distributions (PSDs) during coagulation is of great importance in many atmospheric and engineering applications. To date, various numerical methods have been developed for solving the general dynamic equation under different scenarios. In this study, a radial basis function (RBF) method was proposed to solve particle coagulation evolution. This method uses a Gaussian function as the basis function to approximate the size distribution function. The original governing equation was then converted to ordinary differential equations (ODEs), along with numerical quadratures. The RBF method was compared with the analytical solutions and sectional method to validate its accuracy. The comparison results showed that the RBF method provided almost accurate predictions of the PSDs for different coagulation kernels. This method was also verified to be reliable in predicting the self-preserving distributions reached over long periods and for describing the temporal evolution of moments. For multimodal coagulation, the RBF method also accurately predicted the temporal evolution of a bimodal distribution owing to scavenging effects. Moreover, the computational times of the RBF method for these cases were usually of the order of seconds. Thus, the RBF method is verified as a reliable and efficient tool for predicting PSD evolution during coagulation.

Thermal conductivity of material is one of the basic physical properties and plays an important role in manipulating thermal energy. In order to accelerate the prediction of material structure with desired thermal property, machine learning algorithm has been widely adopted. However, in the optimization of multivariable material structure such as different lengths or proportions, the machine learning algorithm may be required to be reconducted again and again for each variable, which will consume a lot of computing resources. Recently, it has been found that the thermal conductivity of aperiodic superlattices is closely related to the degree of the structural randomness, which can also be reflected in their local pattern structures. Inspired by these, we propose a new pattern analysis method, in which machine learning only needs to be carried out for one time, and through which the optimal structure of different variables with low thermal conductivity can be obtained. To verify the method, we compare the thermal conductivities of the structure obtained by pattern analysis, conventional machine learning, and previous literature, respectively. The pattern analysis method is validated to greatly reduce the prediction time of multivariable structure with high enough accuracy and may promote further development of material informatics.

Yield loss of ratoon crops caused by the rolling damage to the left stubble from mechanically harvesting main crops has been reported in previous studies. However, limited attention has been paid to identify the effect of the mechanical harvesting of the main crop on the yield of a non-rolled zone (NRZ) of a ratoon crop. A two-year field experiment on ratoon rice with two harvest methods (mechanical harvesting: MEH; manual harvesting: MAH) of a main crop was conducted to identify whether there is a border effect on the yield of the NRZ, and to evaluate whether the border effect will compensate for the yield loss of the ratoon crop. On average, MEH reduced the grain yield of the ratoon crop by 17.6% compared with MAH. The yield of the rolled zone (RZ) in MEH was 66.1–70.3% lower than that of MAH, which was attributed to the lower panicle m−2, grain filling percentage, total dry weight, and harvest index. In contrast, the yield of the NRZ in MEH was 2.7–10.8% higher than that of MAH. The yield differences of the non-rolled single row (R1), side row (R2), and middle row (R3) in the NRZ compared with MAH were 22.9%, 8.5%, and −10.1%, respectively, which were mainly explained by the panicle m−2, spikelets m−2, total dry weight, and regeneration rate. These results suggest that rolling during the mechanical harvesting of the main crop induced a border effect on the yield of the NRZ, which reduced the yield loss of the ratoon crop. The yield gain of the NRZ was attributed to the increased yield of R1 and R2 rather than R3.

When an object is illuminated, part of the incident light is absorbed by the object that does not contribute to the illumination. If the light source's spectrum can be optimized by decreasing the light energy along the absorbed wavelengths, substantial energy can be saved. In this study, a spectrum optimization method by means of a genetic algorithm to minimize the light energy along the absorbed wavelengths while maintaining the light quality of the light source was proposed. Under the constraint that the color differences of the object illuminated by the optimized illuminant and the reference illuminant do not exceed specified levels, maximum energy saving ratio (ESR) is achieved for various reference illuminants. It is found that through the proposed method effectively saving the energy, for a monochromatic object, the ESR can reach 49.5% with barely recognizable color difference, whereas for a polychromatic object, the ESR can reach 55.2% with an acceptable color difference for each patch of the object.

Our modern lives have been radically revolutionized by mechanical or electric machines that redefine and recreate the way we work, communicate, entertain, and travel. Whether being perceived or not, human-machine interfacing (HMI) technologies have been extensively employed in our daily lives, and only when the machines can sense the ambient through various signals, they can respond to human commands for finishing desired tasks. Metamaterials have offered a great platform to develop the sensing materials and devices from different disciplines with very high accuracy, thus enabling the great potential for HMI applications. For this regard, significant progresses have been achieved in the recent decade, but haven’t been reviewed systematically yet. In the Review, we introduce the working principle, state-of-the-art sensing metamaterials, and the corresponding enabled HMI applications. For practical HMI applications, four kinds of signals are usually used, i.e., light, heat, sound, and force, and therefore the progresses in these four aspects are discussed in particular. Finally, the future directions for the metamaterials-based HMI applications are outlined and discussed.

Lattice heat conduction can be modulated via nanostructure interfaces. Although advances have been made by viewing phonons as particles, the controllability should be enhanced by fully utilizing their wave nature. By considering phonons as coherent waves, herein we design an optimized aperiodic superlattice that minimizes the coherent phonon heat conduction by alternatingly coupling coherent phonon transport calculations and machine learning. The thermal conductivity of the fabricated aperiodic superlattice agrees well with the calculations over a temperature range of 77–300 K, indicating that complex aperiodic wave interference of coherent phonons can be controlled. The thermal conductivity of the aperiodic superlattice is significantly smaller than the conventional periodic superlattice due to enhanced phonon localization. The optimized aperiodic structure is formed by connecting weakly correlated local structures that introduce interference over broad phonon frequencies. Controlling coherent phonons by aperiodic interferences opens a new route for phonon engineering.

Directional heat transfer may be hard to realize due to the fact that heat transfer is diffusive. In this paper, we try to take one step forward based on the transformation thermodynamics. A special structure and meta-device is proposed to “reflect” the heat flow directionally–just like the mirror to the light beam, in which the heat flow just one-time changes the direction rather than gradually changing the directions in isotropic materials. The benefits of such thermal reflection meta-device are discussed by comparing the corresponding thermal resistance with the same structures of isotropic materials. The proposed meta-device is verified to possess the low thermal resistance and high heat transfer ability with least energy loss, and can be made by nature-existing isotropic materials with specific structures.

Abstract Single atomic catalysts have shown great potential in efficiently electro‐converting O2 to H2O2 with high selectivity. However, the impact of coordination environment and introduction of extra metallic aggregates on catalytic performance still remains unclear. Herein, first a series of carbon‐based catalysts with embedded coupling Ni single atomic sites and corresponding metallic nanoparticles at adjacent geometry is synthesized. Careful performance evaluation reveals NiSA/NiNP‐NSCNT catalyst with precisely controlled active centers of synergetic adjacent Ni‐N4S single sites and crystalline Ni nanoparticles exhibits a high H2O2 selectivity over 92.7% within a wide potential range (maximum selectivity can reach 98.4%). Theoretical studies uncover that spatially coupling single atomic NiN4S sites with metallic Ni aggregates in close proximity can optimize the adsorption behavior of key intermediates *OOH to achieve a nearly ideal binding strength, which thus affording a kinetically favorable pathway for H2O2 production. This strategy of manipulating the interaction between single atoms and metallic aggregates offers a promising direction to design new high‐performance catalysts for practical H2O2 electrosynthesis.

Abstract Background Intrahepatic cholangiocarcinoma (iCCA) is a highly heterogeneous and lethal hepatobiliary tumor with few therapeutic strategies. The metabolic reprogramming of tumor cells plays an essential role in the development of tumors, while the metabolic molecular classification of iCCA is largely unknown. Here, we performed an integrated multiomics analysis and metabolic classification to depict differences in metabolic characteristics of iCCA patients, hoping to provide a novel perspective to understand and treat iCCA. Methods We performed integrated multiomics analysis in 116 iCCA samples, including whole‐exome sequencing, bulk RNA‐sequencing and proteome analysis. Based on the non‐negative matrix factorization method and the protein abundance of metabolic genes in human genome‐scale metabolic models, the metabolic subtype of iCCA was determined. Survival and prognostic gene analyses were used to compare overall survival (OS) differences between metabolic subtypes. Cell proliferation analysis, 5‐ethynyl‐2'‐deoxyuridine (EdU) assay, colony formation assay, RNA‐sequencing and Western blotting were performed to investigate the molecular mechanisms of diacylglycerol kinase α (DGKA) in iCCA cells. Results Three metabolic subtypes (S1‐S3) with subtype‐specific biomarkers of iCCA were identified. These metabolic subtypes presented with distinct prognoses, metabolic features, immune microenvironments, and genetic alterations. The S2 subtype with the worst survival showed the activation of some special metabolic processes, immune‐suppressed microenvironment and Kirsten rat sarcoma viral oncogene homolog (KRAS)/AT‐rich interactive domain 1A (ARID1A) mutations. Among the S2 subtype‐specific upregulated proteins, DGKA was further identified as a potential drug target for iCCA, which promoted cell proliferation by enhancing phosphatidic acid (PA) metabolism and activating mitogen‐activated protein kinase (MAPK) signaling. Conclusion Via multiomics analyses, we identified three metabolic subtypes of iCCA, revealing that the S2 subtype exhibited the poorest survival outcomes. We further identified DGKA as a potential target for the S2 subtype.

Begonia longlingensis Y.H.Tan & H.B.Ding, a new species of Begoniaceae from Southwest Yunnan, China, is described and illustrated. Morphologically, it is primarily similar to B. wenshanensis in same section but differs by its hairy inflorescences and ovary (vs. glabrous), five tepals of pistillate flower (vs. three tepals), bracteoles under the ovary (vs. without) and rhizomes well developed (vs. poorly developed). [ABSTRACT FROM AUTHOR]

In order to consider the impact of source-load uncertainty on traditional power system planning methods, a medium- and long-term optimization planning method based on source-load uncertainty modeling and time-series production simulation is proposed. First, a new energy output probability model is developed using non-parametric kernel density estimation, and the spatial correlation of the new energy output is described using pair-copula theory to model the uncertainty analysis of the new energy output. Secondly, a large number of source-load scenarios are generated using the Markov chain Monte Carlo simulation method, and the optimal selection method for discrete state numbers is provided, and then the scenario reduction is carried out using the fast forward elimination technology. Finally, the typical time-series curves of the source-load uncertainty characteristics obtained are incorporated into the optimization planning method together with various flexible resources, such as the demand-side response and energy storage, and the rationality of the planning scheme is judged and optimized based on key indicators such as the cost, wind–light abandonment rate, and loss-of-load rate. Based on the above methods, this paper offers an example of the power supply planning scheme for a certain region in the next 30 years, providing effective guidance for the development of new energy in the region.