Integrating forest restoration into land-use planning at large spatial scales.

Forest restoration is being scaled up globally, carrying major expectations of environmental and societal benefits. Current discussions on ensuring the effectiveness of forest restoration are predominantly focused on the land under restoration per se. But this focus neglects the critical issue that land use and its drivers at larger spatial scales have strong implications for forest restoration outcomes, through the influence of landscape context and, importantly, potential off-site impacts of forest restoration that must be accounted for in measuring its effectiveness. To ensure intended restoration outcomes, it is crucial to integrate forest restoration into land-use planning at spatial scales large enough to account for - and address - these larger-scale influences, including the protection of existing native ecosystems. In this review, we highlight this thus-far neglected issue in conceptualizing forest restoration for the delivery of multiple desirable benefits regarding biodiversity and ecosystem services. We first make the case for the need to integrate forest restoration into large-scale land-use planning, by reviewing current evidence on the landscape-level influences and off-site impacts pertaining to forest restoration. We then discuss how science can guide the integration of forest restoration into large-scale land-use planning, by laying out key features of methodological frameworks required, reviewing the extent to which existing frameworks carry these features, and identifying methodological innovations needed to bridge the potential shortfall. Finally, we critically review the status of existing methods and data to identify future research efforts needed to advance these methodological innovations and, more broadly, the effective integration of forest restoration design into large-scale land-use planning.

Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development.

Goal: Distance information is highly requested in assistive smartphone Apps by people who are blind or low vision (PBLV). However, current techniques have not been evaluated systematically for accuracy and usability. Methods: We tested five smartphone-based distance-estimation approaches in the image center and periphery at 1-3 meters, including machine learning (CoreML), infrared grid distortion (IR_self), light detection and ranging (LiDAR_back), and augmented reality room-tracking on the front (ARKit_self) and back-facing cameras (ARKit_back). Results: For accuracy in the image center, all approaches had <±2.5 cm average error, except CoreML which had ±5.2-6.2 cm average error at 2-3 meters. In the periphery, all approaches were more inaccurate, with CoreML and IR_self having the highest average errors at ±41 cm and ±32 cm respectively. For usability, CoreML fared favorably with the lowest central processing unit usage, second lowest battery usage, highest field-of-view, and no specialized sensor requirements. Conclusions: We provide key information that helps design reliable smartphone-based visual assistive technologies to enhance the functionality of PBLV.

Oxidized/unmodified-polyethylene microplastics neurotoxicity in mice: Perspective from microbiota-gut-brain axis.

Microplastics (MPs) are inevitably oxidized in the environment, and their potential toxicity to organisms has attracted wide attention. However, the neurotoxicity and mechanism of oxidized polyethylene (Ox-PE) MPs to organisms remain unclear. Herein, we prepared oxidized low-density polyethylene (Ox-LDPE) and established a model of MPs exposure by continuously orally gavage of C57BL/6 J mice with LDPE-MPs/Ox-LDPE-MPs for 28 days with or without oral administration of Lactobacillus plantarum DP189 and galactooligosaccharides (DP189&GOS). The experimental results indicated that LDPE-MPs or Ox-LDPE-MPs caused several adverse effects in mice, mainly manifested by behavioral changes, disruption of the intestinal and blood-brain barrier (BBB), and simultaneous oxidative stress, inflammatory reactions, and pathological damage in the brain and intestines. Brain transcriptomic analysis revealed that the cholinergic synaptic signaling pathways, which affect cognitive function, were significantly disrupted after exposure to LDPE-MPs or Ox-LDPE-MPs. Real-time quantitative polymerase chain reaction and Western Blotting results further demonstrated that the critical genes (Slc5a7, Chat and Slc18a3) and proteins (Chat and Slc18a3) in the cholinergic synaptic signaling pathway were significantly down-regulated after exposure to LDPE-MPs or Ox-LDPE-MPs. These alterations lead to reduced acetylcholine concentration, which causes cognitive dysfunction in mice. Importantly, the DP189&GOS interventions effectively mitigated the MPs-induced cognitive dysfunction and intestinal microbiota alteration, improved intestinal and BBB integrity, attenuated the oxidative stress and inflammatory response, and also saw a rebound in the release of acetylcholine. These results indicated that LDPE-MPs and Ox-LDPE-MPs exert neurotoxic effects on mice by inducing oxidative stress, inflammatory responses, and dysregulation of cholinergic signaling pathways in the mouse brain. That probiotic supplementation is effective in attenuating MPs-induced neurotoxicity in mice. Overall, this study reveals the potential mechanisms of neurotoxicity of LDPE-MPs and Ox-LDPE-MPs on mice and their improvement measures, necessary to assess the potential risks of plastic contaminants to human health.

Light-Driven Three-Component Carbonylation of Aryl Halides Using Abundant Metal Carbonyl.

Carbonyl compounds are widely found in various pharmaceutical intermediates and synthetic precursors. Herein we report a simple light-driven three-component aryl halide process for synthesizing a variety of carbonylation products, utilizing Co2(CO)8 as an abundant solid carbonyl source, in good to excellent yields. The products can easily be subjected to further functionalization in synthesis. Mechanism studies indicated that this reaction is enabled by aryl radical generation and the subsequent CO insertion, alkene insertion, and protonation process.

Exploiting Geometric Features via Hierarchical Graph Pyramid Transformer for Cancer Diagnosis using Histopathological Images.

Cancer is widely recognized as the primary cause of mortality worldwide, and pathology analysis plays a pivotal role in achieving accurate cancer diagnosis. The intricate representation of features in histopathological images encompasses abundant information crucial for disease diagnosis, regarding cell appearance, tumor microenvironment, and geometric characteristics. However, recent deep learning methods have not adequately exploited geometric features for pathological image classification due to the absence of effective descriptors that can capture both cell distribution and gathering patterns, which often serve as potent indicators. In this paper, inspired by clinical practice, a Hierarchical Graph Pyramid Transformer (HGPT) is proposed to guide pathological image classification by effectively exploiting a geometric representation of tissue distribution which was ignored by existing state-of-the-art methods. First, a graph representation is constructed according to morphological feature of input pathological image and learn geometric representation through the proposed multi-head graph aggregator. Then, the image and its graph representation are feed into the transformer encoder layer to model long-range dependency. Finally, a locality feature enhancement block is designed to enhance the 2D local representation of feature embedding, which is not well explored in the existing vision transformers. An extensive experimental study is conducted on Kather-5K, MHIST, NCT-CRC-HE, and GasHisSDB for binary or multi-category classification of multiple cancer types. Results demonstrated that our method is capable of consistently reaching superior classification outcomes for histopathological images, which provide an effective diagnostic tool for malignant tumors in clinical practice.

Light-Driven Photocatalyst-Free Synthesis of ß, δ-Functionalized Ketones from Aldehydes.

The synthesis of ketones has been a long focus of chemistry research, on account of its unique reactivity. Herein, we report a simple light-driven photocatalyst-free synthesis of ß, δ-functionalized ketones from aldehydes, using inexpensive and commercially abundant feedstock chemicals. This reaction is enabled by the direct acyl radical generation via hydrogen atom transfer and the subsequent radical addition process, avoiding the need for prefunctionalized substrates and organometallic reagent.

Velocity-aware spatial-temporal attention LSTM model for inverse dynamic model learning of manipulators.

Introduction: An accurate inverse dynamics model of manipulators can be effectively learned using neural networks. However, further research is required to investigate the impact of spatiotemporal variations in manipulator motion sequences on network learning. In this work, the Velocity Aware Spatial-Temporal Attention Residual LSTM neural network (VA-STA-ResLSTM) is proposed to learn a more accurate inverse dynamics model, which uses a velocity-aware spatial-temporal attention mechanism to extract dynamic spatiotemporal features selectively from the motion sequence of the serial manipulator. Methods: The multi-layer perception (MLP) attention mechanism is adopted to capture the correlation between joint position and velocity in the motion sequence, and the state correlation between hidden units in the LSTM network to reduce the weight of invalid features. A velocity-aware state fusion approach of LSTM network hidden units' states is proposed, which utilizes variation in joint velocity to adapt to the temporal characteristics of the manipulator dynamic motion, improving the generalization and accuracy of the neural network. Results: Comparative experiments have been conducted on two open datasets and a self-built dataset. Specifically, the proposed method achieved an average accuracy improvement of 61.88% and 43.93% on the two different open datasets and 71.13% on the self-built dataset compared to the LSTM network. These results demonstrate a significant advancement in accuracy for the proposed method. Discussion: Compared with the state-of-the-art inverse dynamics model learning methods of manipulators, the modeling accuracy of the proposed method in this paper is higher by an average of 10%. Finally, by visualizing attention weights to explain the training procedure, it was found that dynamic modeling only relies on partial features, which is meaningful for future optimization of inverse dynamic model learning methods.

Digitalization and innovation in green ports: A review of current issues, contributions and the way forward in promoting sustainable ports and maritime logistics.

As a fundamental transportation mode, maritime logistics has become an indispensable component on a global scale. However, there are multiple drawbacks associated with ports operating in traditional ways, such as higher cost, lower efficiency and generating more environmental pollution. Digital technologies have been researched and implemented gradually in green ports, especially in data collection and real-time monitoring, and these advances help to promote higher work efficiency and reduce detrimental environmental impacts. It was found that green ports (e.g. ports of Raffina, Los Angeles, and Long Beach) generally perform better in energy conservation and pollutant emission reduction. However, considering the variability in the level of digitalization, there are challenges in achieving effective communications between individual ports. Therefore, to optimize and update green port practices, a systematic review is necessary to comprehensively analyze the beneficial contributions of green ports. This review adopted bibliometric analysis to examine the shipping framework focusing on green ports digitalization and innovation. After that, with regards to the bibliometric results, five aspects were analyzed, including environment, performance, policy, technology, and management. Besides, intelligent life-cycle management was systematically discussed to improve green ports and maritime logistics performance and sustainability in three aspects, namely waste discharge, shipping management system and green ports management. The findings revealed that green ports and maritime logistics require digital cooperation, transformation, and management to achieve sustainable development goals, including route selection and control of ships' numbers, weather prediction, and navigational effluent monitoring, albeit with some obstacles.

[Comparison of Quality of Life of the Patients Three Months after Uniportal 
and Multiportal Thoracoscopic Lobectomy].

BACKGROUND: The relationship between quality of life at three months after lung cancer surgery and different surgical approaches is remains unclear. This study aimed to compare the quality of life of patients three months after uniportal and multiportal thoracoscopic lobectomy. METHODS: Data from patients who underwent lung surgery at the Department of Thoracic Surgery, Sichuan Cancer Hospital between April 2021 and October 2021 were collected. The European Organization for Research and Treatment of Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) and Quality of Life Questionnaire-Lung Cancer 29 (EORTC QLQ-LC29) were used to collect quality of life data of the patients. Potential confounding factors in the baseline data were included in a multivariate regression model for adjustment, and the quality of life of the two groups three months postoperatively was compared with traditional clinical outcomes. RESULTS: A total of 130 lung cancer patients were included, with 57 males (43.8%) and 73 females (56.2%), and an average age of (57.1±9.5) yr. In the baseline data of the two groups, there was a statistical difference in the number of chest drainage tubes placed (P<0.001). After adjustment with the regression model, at three months postoperatively, there were no significant differences in all symptoms and functional status scores between the two groups (all P>0.05). The multiportal group had longer surgery time (120.0 min vs 85.0 min, P=0.001), postoperative hospital stay (6.0 d vs 4.0 d, P=0.020), and a higher incidence of early ≥ grade 2 complications (39.0% vs 10.1%, P=0.011) compared to the uniportal group. CONCLUSIONS: Patients undergoing uniportal and multiportal thoracoscopic lobectomy have similar quality of life at three months postoperatively. The uniportal group may have certain advantages in terms of traditional clinical outcome indicators such as operation time, postoperative hospital stay, and early postoperative complications.

Proteomics-driven noninvasive screening of circulating serum protein panels for the early diagnosis of hepatocellular carcinoma.

Early diagnosis of hepatocellular carcinoma (HCC) lacks highly sensitive and specific protein biomarkers. Here, we describe a staged mass spectrometry (MS)-based discovery-verification-validation proteomics workflow to explore serum proteomic biomarkers for HCC early diagnosis in 1002 individuals. Machine learning model determined as P4 panel (HABP2, CD163, AFP and PIVKA-II) clearly distinguish HCC from liver cirrhosis (LC, AUC 0.979, sensitivity 0.925, specificity 0.915) and healthy individuals (HC, AUC 0.992, sensitivity 0.975, specificity 1.000) in an independent validation cohort, outperforming existing clinical prediction strategies. Furthermore, the P4 panel can accurately predict LC to HCC conversion (AUC 0.890, sensitivity 0.909, specificity 0.877) with predicting HCC at a median of 11.4 months prior to imaging in prospective external validation cohorts (No.: Keshen 2018_005_02 and NCT03588442). These results suggest that proteomics-driven serum biomarker discovery provides a valuable reference for the liquid biopsy, and has great potential to improve early diagnosis of HCC.

Palladium nanoparticles on gallium nitride as a Mott-Schottky catalyst for efficient and durable photoactivation of unactivated alkanes.

The direct functionalization of inert C-H bonds has long been a "holy grail" for the chemistry world. In this report, the direct C(sp3)-N bond formation of unactivated alkanes is reported with a GaN based Mott-Schottky catalyst under photocatalytic reaction conditions. Long term stability and reaction efficiency (up to 92%) were achieved with this photocatalyst. The deposition of a Pd co-catalyst on the surface of GaN significantly enhanced the reaction efficiency. Microscopic investigation suggested a remarkable interaction in the Pd/GaN Schottky junction, giving a significant Pd/GaN depletion layer. In addition, density functional theory (DFT) calculations were performed to show the distinct performance of Pd nanoparticles at the atomic level.

Knockout of CAFFEOYL-COA 3-O-METHYLTRANSFERASE 6/6L enhances the S/G ratio of lignin monomers and disease resistance in Nicotiana tabacum.

Background: Nicotiana tabacum is an important economic crop, which is widely planted in the world. Lignin is very important for maintaining the physiological and stress-resistant functions of tobacco. However, higher lignin content will produce lignin gas, which is not conducive to the formation of tobacco quality. To date, how to precisely fine-tune lignin content or composition remains unclear. Results: Here, we annotated and screened 14 CCoAOMTs in Nicotiana tabacum and obtained homozygous double mutants of CCoAOMT6 and CCoAOMT6L through CRSIPR/Cas9 technology. The phenotype showed that the double mutants have better growth than the wild type whereas the S/G ratio increased and the total sugar decreased. Resistance against the pathogen test and the extract inhibition test showed that the transgenic tobacco has stronger resistance to tobacco bacterial wilt and brown spot disease, which are infected by Ralstonia solanacearum and Alternaria alternata, respectively. The combined analysis of metabolome and transcriptome in the leaves and roots suggested that the changes of phenylpropane and terpene metabolism are mainly responsible for these phenotypes. Furthermore, the molecular docking indicated that the upregulated metabolites, such as soyasaponin Bb, improve the disease resistance due to highly stable binding with tyrosyl-tRNA synthetase targets in Ralstonia solanacearum and Alternaria alternata. Conclusions: CAFFEOYL-COA 3-O-METHYLTRANSFERASE 6/6L can regulate the S/G ratio of lignin monomers and may affect tobacco bacterial wilt and brown spot disease resistance by disturbing phenylpropane and terpene metabolism in leaves and roots of Nicotiana tabacum, such as soyasaponin Bb.

Nucleophilic Carbenes Derived from Dichloromethane.

Nickel PyBox catalysts promote nucleophilic cyclopropanation reactions using CH2 Cl2 as a methylene source and Mn as a stoichiometric reductant. The substrate scope includes a broad range of alkenes bearing electron-withdrawing substituents, including esters, amides, ketones, nitriles, sulfones, phosphonate esters, trifluoromethyl groups, and electron-deficient arenes. Enantioselective cyclopropanations of α,ß-unsaturated esters have been developed using chiral PyBox ligands. Mechanistic studies suggest the intermediacy of a (PyBox)Ni=CH2 species, which adds to the alkene by a stepwise [2+2]-cycloaddition/C-C reductive elimination mechanism. DFT models provide a rationale for the nucleophilic character of the nickel carbene and the sense of enantioinduction.

Photocatalytic Decarboxylative Minisci Reaction Catalyzed by Palladium-Loaded Gallium Nitride.

The decarboxylative Minisci reaction is a versatile tool for the direct C-H alkylation of heteroarenes, where stoichiometric amounts of oxidants or expensive, precious metal reagents are commonly used. Herein, we reported a photodriven decarboxylative Minisci reaction enabled by a gallium nitride-based heterogeneous photocatalyst under mild conditions. This method can be effectively applied to a broad substrate scope of acids, including primary, secondary, and tertiary carboxylic acids and N-heteroarenes effectively. The practicability and robustness of the approach are demonstrated for the functionalization of biologically active compounds.

Effect of temperature on the reaction path of pyrite (FeS2)-based catalyst catalyzed CO reduction of SO2 to sulfur.

To understand the physical phase structural variation and activation pathway of the active component during the catalytic reduction of pyrite (FeS2)-based catalysts, multiple methods, including X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and high-temperature in situ XRD, were applied to characterize the catalyst and reaction process. The reaction mechanism was simulated and verified using density functional theory. The results indicated that pyrite-based catalysts promote the CO reduction of SO2 to S through the dynamic transformation of three phases (FeS2, Fe7S8, and FeS), in which S-vacancy formation is the most important step. As the critical temperature for the reaction of FeS2 and CO was initiated at approximately 525 °C, the active component's physical phase structure and activation pathway could be controlled by adjusting the temperature.

The enhancement in toxic potency of oxidized functionalized polyethylene-microplastics in mice gut and Caco-2 cells.

Microplastics (MPs) are inevitably oxidized in the environment, however, to date, no studies have discussed the biological toxicity of oxidized polyethylene (Ox-PE) MPs. In this study, oxidized low-density polyethylene (Ox-LDPE), a representative Ox-PE, was prepared using a selective oxidation method. The difference in toxicity between LDPE-MPs and Ox-LDPE-MPs were evaluated in C57BL/6 mice and Caco-2 cells. The proton nuclear magnetic resonance (1H NMR) and Fourier transform infrared (FTIR) spectroscopy analyses revealed that some hydrocarbon-containing groups were transformed into carboxyl and ketone groups during selective oxidation. In vivo experiment results showed that LDPE-MPs and Ox-LDPE-MPs exists in the intestinal (duodenum and colon) of mice, and Ox-LDPE-MPs caused more severe intestinal histological changes, oxidative stress, and inflammatory response. The gut microbiota data showed that the relative abundance of Lactobacillus decreased significantly in the LDPE-MP- and Ox-LDPE-MP-exposed groups (P < 0.05). The predicted Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway suggested that exposure to LDPE-MPs or Ox-LDPE-MPs inhibited glycan biosynthesis and metabolism in the flora (P < 0.05). In vitro experiment results showed that selective oxidation to LDPE promoted its uptake by cells and aggravated adverse effects on cells, including reduced cell viability, damaged cell membrane, oxidative stress, and mitochondrial depolarization. The major mechanism of the increased toxicity of Ox-LDPE-MPs may be its easier accumulation and the ionic effect of oxygen-containing functional groups. Overall, these findings provide insights on the differences in toxicity between LDPE-MPs and Ox-LDPE-MPs. They also provide new perspectives for understanding the biohazards of MPs, which are necessary to accurately assess the potential environmental and health risks of these plastic pollutants.

The lipid peroxidation-derived DNA adduct γ-OHPdG as a diagnostic and prognostic biomarker in hepatocellular carcinoma.

PURPOSE: Chronic inflammation and lipid peroxidation (LPO) are associated with the pathogenesis of hepatocellular carcinoma (HCC), and γ-hydroxy-1, N2-propanodeoxyguanosine (γ-OHPdG) is a promutagenic DNA adduct derived from LPO. This study aimed to examine the relationship between γ-OHPdG and the progression of liver carcinogenesis. METHODS: Primary HCC specimens were obtained from 228 patients and cirrhosis specimens from 46 patients. The patients were followed up with after surgery via outpatient visits and telephone calls. The levels of γ-OHPdG were determined by immunohistochemical analysis in the carcinomatous tissues together with adjacent and cirrhosis tissues. RESULTS: γ-OHPdG levels in the cancerous tissues were significantly higher compared to adjacent tissues (P < 0.001) and also higher than the ones from the tissues of cirrhosis patients. Along with tumor size, histological grade, MVI grade, T stage, the percentage of ki67-positive cells and HCC progression, γ-OHPdG levels in cancerous tissues showed a gradually increasing trend. Moreover, prognostic analysis showed that higher γ-OHPdG levels in cancerous tissues were strongly correlated with lower overall survival (P < 0.001), lower intrahepatic recurrence-free survival (P < 0.001) and lower distant metastasis-free survival (P < 0.05). There was a trend, although not statistically significant, of increased levels of γ-OHPdG in cirrhosis cases that advanced to HCC, whereas γ-OHPdG levels reversely correlated with the period of time observed for cirrhosis advanced to HCC. CONCLUSIONS: These results suggest that γ-OHPdG is a prognostic biomarker for predicting outcomes in HCC, and may serve as a prospective indicator for predicting HCC in cirrhosis patients.

Intratumoral Microbiota Composition Regulates Chemoimmunotherapy Response in Esophageal Squamous Cell Carcinoma.

Neoadjuvant chemoimmunotherapy (NACI) has shown promise in the treatment of resectable esophageal squamous cell carcinoma (ESCC). The microbiomes of patients can impact therapy response, and previous studies have demonstrated that intestinal microbiota influences cancer immunotherapy by activating gut immunity. Here, we investigated the effects of intratumoral microbiota on the response of patients with ESCC to NACI. Intratumoral microbiota signatures of ß-diversity were disparate and predicted the treatment efficiency of NACI. The enrichment of Streptococcus positively correlated with GrzB+ and CD8+ T-cell infiltration in tumor tissues. The abundance of Streptococcus could predict prolonged disease-free survival in ESCC. Single-cell RNA sequencing demonstrated that responders displayed a higher proportion of CD8+ effector memory T cells but a lower proportion of CD4+ regulatory T cells. Mice that underwent fecal microbial transplantation or intestinal colonization with Streptococcus from responders showed enrichment of Streptococcus in tumor tissues, elevated tumor-infiltrating CD8+ T cells, and a favorable response to anti-PD-1 treatment. Collectively, this study suggests that intratumoral Streptococcus signatures could predict NACI response and sheds light on the potential clinical utility of intratumoral microbiota for cancer immunotherapy. SIGNIFICANCE: Analysis of intratumoral microbiota in patients with esophageal cancer identifies a microbiota signature that is associated with chemoimmunotherapy response and reveals that Streptococcus induces a favorable response by stimulating CD8+ T-cell infiltration. See related commentary by Sfanos, p. 2985.