NtHD9 modulates plant salt tolerance by regulating the formation of glandular trichome heads in Nicotiana tabacum.

Salt stress is one of the main abiotic factor affecting plant growth. We have previously identified a key gene (NtHD9) in Nicotiana tabacum L. that positively regulates the formation of long glandular trichomes (LGTs). Here, we verified that both abiotic stress (aphids, drought and salt stress) could restore the phenotype lacking LGTs in NtHD9-knockout (NtHD9-KO) plants. The abiotic stress response assays indicated that NtHD9 is highly sensitive to salt stress. Compared with cultivated tobacco "K326" (CK) plants, NtHD9-overexpressing (NtHD9-OE) plants with more LGTs exhibited stronger salt tolerance, whereas NtHD9-KO with no LGTs showed weaker tolerance to salt. The densities and sizes of the glandular heads gradually increased with increasing NaCl concentrations in NtHD9-KO plants. Mineral element determination showed that leaves and trichomes of NtHD9-OE plants accumulated less Na+ but had higher K+ contents under salt stress, thus maintaining ion homeostasis in plants, which could contribute to a robust photosynthetic and antioxidant system under salt stress. Therefore, NtHD9-OE plants maintained a larger leaf area and root length under high-salt conditions than CK and NtHD9-KO plants. We verified that NtHD9 could individually interact with NtHD5, NtHD7, NtHD12, and NtJAZ10 proteins. Salt stress led to an increase in jasmonic acid (JA) levels and activated the expression of NtHDs while inhibiting the expression of NtJAZ. This study suggests that the glandular heads play an important role in plant resistance to salt stress. The activation of JA signaling leading to JAZ protein degradation may be key factors regulating the glandular heads development under salt stress.

Reconstruction Strategy for Upper Extremity Defects After Bone Tumor Resection Based on 3D Customized Bone Cement Mold.

BACKGROUND: Reconstructing bone defects in the upper extremities and restoring their functions poses a significant challenge. In this study, we describe a novel workflow for designing and manufacturing customized bone cement molds using 3D printing technology to reconstruct upper extremity defects after bone tumor resection. METHODS: Computer tomography data was acquired from the unaffected upper extremities to create a detachable mold, which can be customized to fit the joint precisely by shaping the bone cement accordingly. Fourteen patients who underwent reconstructive surgery following bone tumor resection in the proximal humerus (13 cases) or distal radius (1 case) between January 2014 and December 2022 were retrospectively evaluated. The medical records of this case series were reviewed for the demographic, radiological, and operative data. Metastasis, local recurrence, and complication were also reviewed. Additionally, Musculoskeletal Tumor Society Score (MSTS) and Visual Analogue Scale (VAS) were used to assess clinical outcomes. RESULTS: The mean follow-up period was 49.36 ± 15.18 months (range, 27-82 months). At the end of follow-up, there were no cases of metastasis or recurrence, and patients did not experience complications such as infection, dislocation, or implant loosening. Two cases complicated with subluxation (14.3%), and 1 case underwent revision surgery for prosthetic fracture (7.1%). The average MSTS score was 23.2 ± 1.76 (77.4%, range, 66.7%-86.7%), and the postoperative VAS score was 1.86 ± 1.03 (range, 1-4), which was significantly lower than that before surgery (average preoperative VAS score was 5.21 ± 2.00 (range, 2-8)) (P < .001). CONCLUSION: Customized 3D molds can be utilized to shape bone cement prostheses, which may serve as a potential alternative for reconstructing the proximal humerus and distal radius following en bloc resection of bone tumors. This reconstruction strategy offers apparent advantages, including precise matching of articular surfaces and comparatively reduced costs.

SF-TMN: SlowFast temporal modeling network for surgical phase recognition.

PURPOSE: Automatic surgical phase recognition is crucial for video-based assessment systems in surgical education. Utilizing temporal information is crucial for surgical phase recognition; hence, various recent approaches extract frame-level features to conduct full video temporal modeling. METHODS: For better temporal modeling, we propose SlowFast temporal modeling network (SF-TMN) for offline surgical phase recognition that can achieve not only frame-level full video temporal modeling but also segment-level full video temporal modeling. We employ a feature extraction network, pretrained on the target dataset, to extract features from video frames as the training data for SF-TMN. The Slow Path in SF-TMN utilizes all frame features for frame temporal modeling. The Fast Path in SF-TMN utilizes segment-level features summarized from frame features for segment temporal modeling. The proposed paradigm is flexible regarding the choice of temporal modeling networks. RESULTS: We explore MS-TCN and ASFormer as temporal modeling networks and experiment with multiple combination strategies for Slow and Fast Paths. We evaluate SF-TMN on Cholec80 and Cataract-101 surgical phase recognition tasks and demonstrate that SF-TMN can achieve state-of-the-art results on all considered metrics. SF-TMN with ASFormer backbone outperforms the state-of-the-art Swin BiGRU by approximately 1% in accuracy and 1.5% in recall on Cholec80. We also evaluate SF-TMN on action segmentation datasets including 50salads, GTEA, and Breakfast, and achieve state-of-the-art results. CONCLUSION: The improvement in the results shows that combining temporal information from both frame level and segment level by refining outputs with temporal refinement stages is beneficial for the temporal modeling of surgical phases.

Extreme risk spillovers between US and Chinese agricultural futures markets in crises: A dependence-switching copula-CoVaR model.

The linkages between the US and China, the world's two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises.

Conformational and static properties of tagged chains in solvents: effect of chain connectivity in solvent molecules.

Polymer chains immersed in different solvent molecules exhibit diverse properties due to multiple spatiotemporal scales and complex interactions. Using molecular dynamics simulations, we study the conformational and static properties of tagged chains in different solvent molecules. Two types of solvent molecules were examined: one type consisted of chain molecules connected by bonds, while the other type consisted of individual bead molecules without any bonds. The only difference between the two solvent molecules lies in the chain connectivity. Our results show a compression of the tagged chains with the addition of bead or chain molecules. Chain molecule confinement induces a stronger compression compared to bead molecule confinement. In chain solvent molecules, the tagged chain's radius of gyration reached a minimum at a monomer volume fraction of ∼0.3. Notably, the probability distributions of chain size remain unchanged at different solvent densities, irrespective of whether the solvent consists of beads or polymers. Furthermore, as solvent density increases, a crossover from a unimodal to a bimodal distribution of bond angles is observed, indicating the presence of both compressed and expanded regions within the chain. The effective monomer-solvent interaction is obtained by calculating the partial radial distribution function and the potential of the mean force. In chain solvents, the correlation hole effect results in a reduced number of nearest neighbors around tagged monomers compared to bead solvents. The calculation of pore size distribution reveals that the solvent nonhomogeneity induced by chain connectivity leads to a broader distribution of pore sizes and larger pore dimensions at low volume fractions. These findings provide a deeper understanding of the conformational behavior of polymer chains in different solvent environments.

Dirac t-Boron Nitride Monolayer as an Appealing Binder-Free Anode for Alkali Metal Ion Batteries.

The development of universal anode materials with superlative electrochemical performance poses a great challenge for rechargeable alkali metal (AM) ion battery technologies. In the present work, the viability of the gapless Dirac t-BN (tetragonal boron nitride) monolayer as a lightweight binder-free anode has been systematically evaluated via comprehensive first-principles calculations. Aside from the desirable electronic conductivity, the t-BN monolayer exhibits an excellent ionic conductivity as well due to its moderate affinity for Li, Na, and K atoms with favorable in-plane barriers of 0.36, 0.18, and 0.19 eV, respectively. Meanwhile, the presence of B4N4 octagons allows the AM atoms to penetrate through the t-BN monolayer. Excitingly, the host material delivers an ultrahigh specific capacity up to 1080 mA h g-1 for Li, 5400 mA h g-1 for Na, and 2160 mA h g-1 for K in the wake of low mean open-circuit voltages of 0.033, 0.203, and 0.300 V at the half-cell level. According to the standard hydrogen electrode methodology, the energy densities are forecasted to be as large as 3240, 13500, and 5680 mW h g-1 for Li, Na, and K ion batteries, respectively, with robust thermal stability up to at least 400 K. The safety and cycling durability of the t-BN monolayer are jointly corroborated via the moderate mechanical strengths and ab initio molecular dynamics simulations at the maximum intercalated states, as well as via the small lattice changes and its ultrahigh tolerable ultimate tensile strain. These findings unambiguously promise that the t-BN monolayer can serve as an appealing candidate for anode applications in AM ion batteries.

Scalable Electrodeposition of Liquid Metal from an Acetonitrile-Based Electrolyte for Highly Integrated Stretchable Electronics.

The advancement of highly integrated stretchable electronics requires the development of scalable sub-micrometer conductor patterning. Eutectic gallium indium (EGaIn) is an attractive conductor for stretchable electronics, as its liquid metallic character grants it high electrical conductivity upon deformation. However, its high surface tension makes its patterning with sub-micrometer resolution challenging. In this work, this limitation is overcome by way of the electrodeposition of EGaIn. A non-aqueous acetonitrile-based electrolyte that exhibits high electrochemical stability and chemical orthogonality is used. The electrodeposited material leads to low-resistance lines that remain stable upon (repeated) stretching to a 100% strain. Because electrodeposition benefits from the resolution of mature nanofabrication methods used to pattern the base metal, the proposed "bottom-up" approach achieves a record-high density integration of EGaIn regular lines of 300 nm half-pitch on an elastomer substrate by plating on a gold seed layer prepatterned by nanoimprinting. Moreover, vertical integration is enabled by filling high-aspect-ratio vias. This capability is conceptualized by the fabrication of an omnidirectionally stretchable 3D electronic circuit, and demonstrates a soft-electronic analog of the stablished damascene process used to fabricate microchip interconnects. Overall, this work proposes a simple route to address the challenge of metallization in highly integrated (3D) stretchable electronics.

Piezoelectricity and valley polarization in a semilithiated 2H-TiTe2 monolayer with near room-temperature ferromagnetism.

Two-dimensional ferromagnetic semiconductors with coupled valley physics and piezoelectric responses offer unprecedented opportunities to miniaturize low-power multifunctional integrated devices. Prompted by epitaxial fabrication of nonmagnetic 2H-TiTe2 monolayer on the Au(111) substrate, we predict through both density functional theory and Monte Carlo simulations that the semilithiated 2H-TiTe2 monolayer (Li@2H-TiTe2) is a stable near room-temperature semiconducting ferromagnet. Under an out-of-plane magnetization, Li@2H-TiTe2 exhibits a clean valley polarization up to 160 meV in its conduction band and a valley-contrasting Berry curvature due to the broken inversion and time-reversal symmetries, in favor of achievable anomalous valley Hall effect. Alternatively, the simultaneous charge, spin, valley Hall currents can be realized as well in the ferromagnetic system with circularly polarized light. Furthermore, the missing mirror symmetry generates a scarce vertical piezoelectricity as large as 0.89 pm V-1. These findings indicate that asymmetric surface functionalization by Li deposition on the 2H-TiTe2 monolayer opens up a vital avenue to predesign superior and tailored multifunctional materials.

Horizontal inequity trends of health care utilization in rural China after the medicine and healthcare system reform: based on longitudinal data from 2010 to 2018.

BACKGROUND: To assess the effectiveness of China's medicine and health care reform in promoting equity in health care utilization among rural residents, it is necessary to analyze temporal trends in equity in health care utilization among rural residents in China. This study is the first to assess horizontal inequity trends in health care utilization among rural Chinese residents from 2010 to 2018 and provides evidence for improving government health policies. METHODS: Longitudinal data obtained from China Family Panel Studies from 2010 to 2018 were used to determine trends in outpatient and inpatient utilization. Concentration index, concentration curve, and horizontal inequity index were calculated to measure inequalities. Decomposition analysis was applied to measure the contribution of need and non-need factors to the unfairness. RESULTS: From 2010 to 2018, outpatient utilization among rural residents increased by 35.10%, while inpatient utilization increased by 80.68%. Concentration indices for health care utilization were negative in all years. In 2012, there was an increase in the concentration index for outpatient utilization (CI = -0.0219). The concentration index for inpatient utilization decreased from -0.0478 in 2010 to -0.0888 in 2018. Except for outpatient utilization in 2012 (HI = 0.0214), horizontal inequity indices for outpatient utilization were negative in all years. The horizontal inequity index for inpatient utilization was highest in 2010 (HI = -0.0068) and lowest in 2018 (HI = -0.0303). The contribution of need factors to the inequity exceeded 50% in all years. CONCLUSIONS: Between 2010 and 2018, low-income groups in rural China used more health services. This seemingly pro-poor income-related inequality was due in large part to the greater health care need among low-income groups. Government policies aimed at increasing access to health services, particularly primary health care had helped to make health care utilization in rural China more equitable. It is necessary to design better health policies for disadvantaged groups to reduce future inequities in the use of health services by rural populations.

CholecTriplet2021: A benchmark challenge for surgical action triplet recognition.

Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works recognize surgical activities at a coarse-grained level, such as phases, steps or events, leaving out fine-grained interaction details about the surgical activity; yet those are needed for more helpful AI assistance in the operating room. Recognizing surgical actions as triplets of combination delivers more comprehensive details about the activities taking place in surgical videos. This paper presents CholecTriplet2021: an endoscopic vision challenge organized at MICCAI 2021 for the recognition of surgical action triplets in laparoscopic videos. The challenge granted private access to the large-scale CholecT50 dataset, which is annotated with action triplet information. In this paper, we present the challenge setup and the assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge. A total of 4 baseline methods from the challenge organizers and 19 new deep learning algorithms from the competing teams are presented to recognize surgical action triplets directly from surgical videos, achieving mean average precision (mAP) ranging from 4.2% to 38.1%. This study also analyzes the significance of the results obtained by the presented approaches, performs a thorough methodological comparison between them, in-depth result analysis, and proposes a novel ensemble method for enhanced recognition. Our analysis shows that surgical workflow analysis is not yet solved, and also highlights interesting directions for future research on fine-grained surgical activity recognition which is of utmost importance for the development of AI in surgery.

Theoretical determination of superior high-temperature thermoelectricity in an n-type doped 2H-ZrI2 monolayer.

Two-dimensional materials with a competitive figure of merit zT are extremely desirable for the fabrication of thermoelectric modules. In the present work, we systematically evaluated the thermoelectricity of monolayer 2H-ZrI2 through first-principles calculations and semiclassical Boltzmann transport theory. Apart from its all-round structural stability and feasibility of experimental preparation, the semiconducting material with a moderate indirect bandgap of 1.07 eV at the HSE06 level exhibits an acceptable lattice thermal conductivity κL of 6.69 W m-1 K-1 at 900 K contributed dominantly by acoustic modes. The four-phonon scattering is found to exert a minor effect on the κL of the monolayer. Moreover, a quite large power factor of up to 147.89 mW m-1 K-2 can be achieved due to the conduction band valley degeneracy near the Fermi level. These transport coefficients eventually give rise to a significant optimal n-type zT value as high as 3.57 at 900 K at a certain experimentally achievable electron doping concentration. Our study demonstrates the potential application of monolayer 2H-ZrI2 in high-temperature thermoelectric devices.

LYSET/TMEM251/GCAF is critical for autophagy and lysosomal function by regulating the mannose-6-phosphate (M6P) pathway.

Vertebrate cells rely on mannose-6-phosphate (M6P) modifications to deliver most lumenal hydrolases to the lysosome. As a critical trafficking signal for lysosomal enzymes, the M6P biosynthetic pathway has been thoroughly investigated. However, its regulatory mechanism is largely unknown. Here, we summarize three recent studies that independently discovered LYSET/TMEM251/GCAF as a key regulator of the M6P pathway. LYSET/TMEM251 directly interacts with GNPT, the enzyme that catalyzes the transfer of M6P, and is critical for its activity and stability. Deleting LYSET/TMEM251 impairs the GNPT function and M6P modifications. Consequently, lysosomal enzymes are mistargeted for secretion. Defective lysosomes fail to degrade cargoes such as endocytic vesicles and autophagosomes, leading to a newly identified lysosomal storage disease in humans. These discoveries open up a new direction in the regulation of the M6P biosynthetic pathway.Abbreviations: ER: endoplasmic reticulum; GNPT: GlcNAc-1-phosphotransferase; KO: knockout; LMP: lysosome membrane protein; LYSET: lysosomal enzyme trafficking factor; MAP1LC3/LC3: microtubule-associated protein 1 light chain 3; M6P: mannose-6-phosphate; MBTPS1/S1P: membrane-bound transcription factor peptidase, site 1; MPR: mannose-6-phosphate receptor; SQSTM1: sequestosome 1; TEM: transmission electron microscopy; TGN: trans-Golgi network.

An artificial intelligence model that automatically labels roux-en-Y gastric bypasses, a comparison to trained surgeon annotators.

INTRODUCTION: Artificial intelligence (AI) can automate certain tasks to improve data collection. Models have been created to annotate the steps of Roux-en-Y Gastric Bypass (RYGB). However, model performance has not been compared with individual surgeon annotator performance. We developed a model that automatically labels RYGB steps and compares its performance to surgeons. METHODS AND PROCEDURES: 545 videos (17 surgeons) of laparoscopic RYGB procedures were collected. An annotation guide (12 steps, 52 tasks) was developed. Steps were annotated by 11 surgeons. Each video was annotated by two surgeons and a third reconciled the differences. A convolutional AI model was trained to identify steps and compared with manual annotation. For modeling, we used 390 videos for training, 95 for validation, and 60 for testing. The performance comparison between AI model versus manual annotation was performed using ANOVA (Analysis of Variance) in a subset of 60 testing videos. We assessed the performance of the model at each step and poor performance was defined (F1-score < 80%). RESULTS: The convolutional model identified 12 steps in the RYGB architecture. Model performance varied at each step [F1 > 90% for 7, and > 80% for 2]. The reconciled manual annotation data (F1 > 80% for > 5 steps) performed better than trainee's (F1 > 80% for 2-5 steps for 4 annotators, and < 2 steps for 4 annotators). In testing subset, certain steps had low performance, indicating potential ambiguities in surgical landmarks. Additionally, some videos were easier to annotate than others, suggesting variability. After controlling for variability, the AI algorithm was comparable to the manual (p < 0.0001). CONCLUSION: AI can be used to identify surgical landmarks in RYGB comparable to the manual process. AI was more accurate to recognize some landmarks more accurately than surgeons. This technology has the potential to improve surgical training by assessing the learning curves of surgeons at scale.

A Morphometric Study of the Distal Femoral Resected Surface In Osteoarthritis Knees of the Patients in Southwest China and a Comparison with Femoral Components in Six Total Knee Arthroplasty Systems.

OBJECTIVE: Mismatch between the femoral component and the resected surface is related to the postoperative clinical outcome. This study aimed to measure the morphometric features of the distal femoral resected surfaces in patients with osteoarthritis in southwestern China and to compare the measured morphometric data with six commonly used total knee arthroplasty (TKA) femoral components in China. METHOD: The computer tomography (CT) images of a total of 406 knees from 203 osteoarthritis patients who underwent TKA from January 2018 to December 2021 were imported into Mimics 21.0 software to reconstruct the three-dimensional (3D) model of the femur. Morphometric data of the distal femoral resected surfaces were measured after the completion of simulated bone resection in the software. The data included the medial-lateral (ML) dimension, anterior-posterior (AP) dimension, and the aspect ratio (AR) (AR = ML/AP), which were compared between genders with independent sample t-tests. In addition, we plotted the scatter diagram of those morphometric data in Origin software, and the linear fits of ML versus AP and AR versus AP were performed and compared for the six femoral components commonly used in enrolled patients in China. RESULTS: The mean ML dimension, the mean AP dimension, and the mean AR value measured for Chinese knees were 66.62 ± 4.57 mm, 58.10 ± 3.74 mm, and 1.15 ± 0.06 respectively. All dimensions were significantly larger in males than in females, including the calculated values for AR (P < 0.05). The fitted lines for males showed that the ML dimensions tended to be wider compared to femoral components of a given AP dimension. Females tended to have wider ML dimensions compared to small femoral components and, on the other hand, narrower ML dimensions compared to large femoral components. CONCLUSION: The femoral component of the current commonly used TKA prosthesis in China may not be perfectly matched to the distal femoral resected surface of patients in southwestern China. Male patients tended to underhang in all dimensions of the ML dimension. Female patients with shorter AP lengths are more likely to experience underhang, whereas those with longer AP lengths are more likely to develop overhangs. Therefore, we recommend multiple ML width options for a given AP length to more appropriately match the Chinese femoral anatomy.

Surgical workflow recognition with temporal convolution and transformer for action segmentation.

PURPOSE: Automatic surgical workflow recognition enabled by computer vision algorithms plays a key role in enhancing the learning experience of surgeons. It also supports building context-aware systems that allow better surgical planning and decision making which may in turn improve outcomes. Utilizing temporal information is crucial for recognizing context; hence, various recent approaches use recurrent neural networks or transformers to recognize actions. METHODS: We design and implement a two-stage method for surgical workflow recognition. We utilize R(2+1)D for video clip modeling in the first stage. We propose Action Segmentation Temporal Convolutional Transformer (ASTCFormer) network for full video modeling in the second stage. ASTCFormer utilizes action segmentation transformers (ASFormers) and temporal convolutional networks (TCNs) to build a temporally aware surgical workflow recognition system. RESULTS: We compare the proposed ASTCFormer with recurrent neural networks, multi-stage TCN, and ASFormer approaches. The comparison is done on a dataset comprised of 207 robotic and laparoscopic cholecystectomy surgical videos annotated for 7 surgical phases. The proposed method outperforms the compared methods achieving a [Formula: see text] relative improvement in the average segmental F1-score over the state-of-the-art ASFormer method. Moreover, our proposed method achieves state-of-the-art results on the publicly available Cholec80 dataset. CONCLUSION: The improvement in the results when using the proposed method suggests that temporal context could be better captured when adding information from TCN to the ASFormer paradigm. This addition leads to better surgical workflow recognition.

Education level has an effect on the recovery of total knee arthroplasty: a retrospective study.

OBJECTIVE: This study aimed to observe the relationship between education level and outcomes after total knee arthroplasty (TKA). METHODS: One thousand two hundred sixty four patients after TKA in our hospital from April 2016 to April 2020 were reviewed. These patients were divided into 4 groups (A who were illiterate, B who had elementary school degree, C who had junior high school degree, D who had senior high school degree or higher) by the educational level, which was blinded to the observers. The postoperative outcomes of KSS score, pain, joint extension and flexion function were observed 1 year after discharged from hospital. RESULTS: Among 1253 patients met the inclusion criteria, the average age was 68.63 years, the average body mass was 57.73 kg. There are no distinctions among 4 groups one day after the surgery. However, the outcomes of the follow up were that, the KSS score was: 77.84 ± 10.635; 80.70 ± 8.956; 87.92 ± 8.123;91.27 ± 8.262, with significant differences (P < 0.05). The mean VAS scores were: 1.97 ± 1.60; 2.07 ± 1.66; 1.197 ± 1.5265, 1.044 ± 1.4662. Patients in Group C and D had significantly less pain than that in Group A and B (P < 0.05). The knee flexion range of motion (ROM) was: 91.21 ± 11.69°; 91.77 ± 11.95°; 102.12 ± 11.38°; 109.96 ± 10.64°, Group D performed best, with significant differences (P < 0.05). The knee extension ROM were: - 2.41 ± 4.49°; - 0.91 ± 2.82°; - 0.83 ± 2.87°; - 0.35 ± 1.60°, with significant difference between Group D and the others (P < 0.05). CONCLUSION: Education level affects the outcomes such as VAS score, KSS score, the extension and flexion ROM of the knee after TKA. The patients with higher education level have better outcomes.

A study of macrophage mechanical properties and functional modulation based on the Young's modulus of PLGA-PEG fibers.

The immune response of macrophages plays an important role in defending against viral infection, tumor deterioration and repairing of contused tissue. Macrophage functional differentiation induced by nanodrugs is the leading edge of current research, but nanodrugs have toxic side effects, and the influence of their physical properties on macrophages is not clear. Here we create an alternative way to modulate macrophage function through PLGA-PEG fibers' Young's modulus. Previously, we revealed that by controlling the Young's modulus of the fibers from kPa to MPa, all the fibers entered murine macrophage cells (RWA 264.7) in a similar manner, and based on that, we found that macrophages' mechanical properties were affected by the fibers' Young's modulus, that is, hard fibers with a Young's modulus of ∼1 MPa increased the cell average Young's modulus, but did not affect the cell shape, while soft fibers with a Young's modulus of ∼100 kPa decreased the cell average Young's modulus and modulated the cell shape to a more spherical one. On the other hand, only the soft fibers induced proinflammatory cytokine secretion, indicating an M1 macrophage functional modulation by low Young's modulus fibers. This study explored the mechanical properties of the interactions between PLGA-PEG fibers and cells, in particular, when guiding the direction of the modulation of macrophage function, which is of great significance for the applications of material biology in the biomedical field.

Potential Impact of FDA Flavor Enforcement Policy on Vaping Behavior on Twitter.

In January 2020, the FDA announced an electronic cigarette (e-cigarette) flavor enforcement policy to restrict the sale of all unauthorized cartridge-based flavored e-cigarettes except tobacco and menthol flavors, which was implemented on 6 February 2020. This study aimed to understand the potential influence of this policy on one vaping behavior change-quitting vaping-using Twitter data. Twitter posts (tweets) related to e-cigarettes were collected between June 2019 and October 2020 through a Twitter streaming API. Based on the geolocation and keywords related to quitting vaping, tweets mentioning quitting vaping from the US were filtered. The demographics (age and gender) of Twitter users who mentioned quitting vaping were further inferred using a deep learning algorithm (deepFace). The proportion of tweets and Twitter users mentioning quitting vaping were compared between before and after the announcement and implementation of the flavor policy. Compared to before the FDA flavor policy, the proportion of tweets (from 0.11% to 0.20% and 0.24%) and Twitter users (from 0.15% to 0.70% and 0.86%) mentioning quitting vaping were significantly higher after the announcement and implementation of the policy (p-value < 0.001). In addition, there was an increasing trend in the proportion of female and young adults (18-35 years old) mentioning quitting vaping on Twitter after the announcement and implementation of the policy compared to that before the policy. Our results showed that the FDA flavor enforcement policy did have a positive impact on quitting vaping on Twitter. Our study provides an initial evaluation of the potential influence of the FDA flavor enforcement policy on user vaping behavior.

Intrinsic spin, valley and piezoelectric polarizations in room-temperature ferrovalley Janus TiXY (XY = SCl and SeBr) monolayers.

Two-dimensional room-temperature Janus ferrovalley semiconductors with large spin, valley and piezoelectric polarizations provide fertile platforms for designing multifunctional nanodevices. Little research has been reported to date on such materials. Here, using first-principles calculations, we predict two dynamically stable Janus titanium chalcohalide (TiSCl and TiSeBr) monolayers, which are excellent piezoelectric ferrovalley semiconductors with in-plane magnetization and high magnetic transition temperatures (738 and 884 K). When an extrinsic magnetic field is used to force the magnetization along the out-of-plane direction, a large valley polarization (64 and 146 meV) can be generated in the highest valence band with a large spin-orbit coupling by the breaking of time-reversal and space-inversion symmetry, which can be further clarified by a two-band k·p model. This robust valley-contrasting physics characterized by the valley-dependent Berry curvature leads to the anomalous valley Hall effect. It can be observed by suitable hole doping or light irradiation under an in-plane electric field. Besides, we find that the missing mirror symmetry results in giant out-of-plane piezoelectric polarization (2.05 and 2.04 pm V-1). These outstanding properties give the Janus TiSCl and TiSeBr monolayers potential for a wide variety of applications in nanoelectronics, spintronics, valleytronics, piezoelectrics and other demanding areas.

Who is More Likely to Report Medical Insurance Fraud in the Two Scenarios of Whether It Results in a Direct Loss of Individual Benefit? A Cross-Sectional Survey in China.

Purpose: An individual's willingness to report is largely related to whether he or she is a direct victim. This study takes two scenarios of whether medical insurance fraud results in a direct loss of personal benefit and explores the differences in individuals' willingness to report and influencing factors in the two scenarios. Methods: In this study, questionnaires were used and participants were selected from 571 individuals in eastern, central, and western China. Analysis was performed using descriptive statistics and logistic regression models. Results: 51.0% of individuals were willing to report when no direct loss of personal benefit was caused, and conversely, 78.3% of individuals were willing to report when direct loss of personal benefit was caused. The factors influencing the attitude dimension of individuals toward whistleblowing behavior were consistent in the two scenarios. In contrast, there were significant differences among the influences in the perceived behavioral control, consequence perception, and subjective norm dimensions. Conclusion: There were significant differences in the willingness of individuals to report medical insurance fraud and the factors influencing it in both scenarios. The most significantly influencing factor difference was perceived behavioral control, a dimension that had an effect only when it did not result in a direct loss of personal benefit. When an individual's direct interests are at stake, the individual's fear for his or her safety is not a deterrent to his or her willingness to report. And when there is no loss of direct personal benefit, individuals care more about government measures to protect whistleblowers. There are differences in the subjects that influence individuals' willingness to report in the two scenarios. The factors influencing the attitude dimension are the same in both scenarios, and the more supportive the attitude toward the whistleblower, the stronger the individual's willingness to report will be.