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BackgroundWood harvesting and storage (WHS) is a hybrid Nature-Engineering combination method to combat climate change by harvesting wood sustainably and storing it semi-permanently for carbon sequestration. To date, the technology has only been purposefully tested in small-scale demonstration projects. This study aims to develop a concrete way to carry out WHS at large-scale.ResultsWe describe a method of constructing a wood storage facility, named Wood Vault, that can bury woody biomass on a mega-tonne scale in specially engineered enclosures to ensure anaerobic environments, thus preventing wood decay. The buried wood enters a quasi-geological reservoir that is expected to stay intact semi-permanently. Storing wood in many environments is possible, leading to seven versions of Wood Vault: (1) Burial Mound (Tumulus or Barrow), (2) Underground (Pit, Quarry, or Mine), (3) Super Vault, (4) Shelter, (5) AquaOpen or AquaVault with wood submerged under water, (6) DesertOpen or DesertVault in dry regions, (7) FreezeVault in cold regions such as Antarctica. Smaller sizes are also possible, named Baby Vault. A prototype Wood Vault Unit (WVU) occupies 1 hectare (ha, 100 m by 100 m) of surface land, 20 m tall, stores up to 100,000 m3 of wood, sequestering 0.1 MtCO2. A 1 MtCO2 y−1 sequestration rate can be achieved by collecting currently unused wood residuals (WR) on an area of 25,000 km2, the size of 10 typical counties in the eastern US, corresponding to an average transportation distance of less than 100 km. After 30 years of operation, such a Wood Vault facility would have sequestered 30 MtCO2, stored in 300 WVUs, occupying a land surface of 300 ha. The cost is estimated at $10–50/tCO2 with a mid-point price of $30/tCO2. To sequester 1 GtCO2 y−1, wood can be sourced from currently unexploited wood residuals on an area of 9 Mkm2 forested land (9 million square kilometers, size of the US), corresponding to a low areal harvesting intensity of 1.1 tCO2 ha−1 y−1. Alternatively, giga-tonne scale carbon removal can be achieved by harvesting wood at a medium harvesting intensity of 4 tCO2 ha−1 y−1 on 3 Mkm2 of forest (equivalent to increasing current world wood harvest rate by 25%), or harvest on 0.8 Mkm2 forest restored from past Amazon deforestation at high harvest intensity, or many combinations of these and other possibilities. It takes 1000 facilities as discussed above to store 1 GtCO2 y−1, compared to more than 6000 landfills currently in operation in the US. After full closure of a Wood Vault, the land can be utilized for recreation, agriculture, solar farm, or agrivoltaics. A more distributed small operator model (Baby Vault) has somewhat different operation and economic constraints. A 10 giga-tonne sequestration rate siphons off only 5% of total terrestrial net primary production, thus possible with WHS, but extreme caution needs to be taken to ensure sustainable wood sourcing.ConclusionsOur technical and economic analysis shows that Wood Vault can be a powerful tool to sequester carbon reliably, using a variety of wood sources. Most pieces of the technology already exist, but they need to be put together efficiently in practice. Some uncertainties need to be addressed, including how durability of buried wood depends on detailed storage methods and burial environment, but the science and technology are known well enough to believe the practicality of the method. The high durability, verifiability and low-cost makes it already an attractive option in the current global carbon market. Woody biomass stored in Wood Vaults is not only a carbon sink to combat current climate crisis, but also a valuable resource for the future that can be used as biomass/bioenergy and carbon supply. The quantity of this wood utilization can be controlled carefully to maintain a desired amount of CO2 in the atmosphere to keep the Earth’s climate from diving into the next ice age, acting as a climate thermostat. The CO2 drawdown time is on the order of 100 years while the ramp-up time is a decade. A sense of urgency is warranted because the CO2 removal rate is limited by biosphere productivity, thus delayed action means a loss of opportunity. In conclusion, WHS provides a tool for managing our Earth system, which will likely remain forever in the Anthropocene.

Differences in the bacterial community structure associated with 7 skin sites in 71 healthy people over five days showed significant correlations with age, gender, physical skin parameters, and whether participants lived in urban or rural locations in the same city. While body site explained the majority of the variance in bacterial community structure, the composition of the skin-associated bacterial communities were predominantly influenced by whether the participants were living in an urban or rural environment, with a significantly greater relative abundance of Trabulsiella in urban populations. Adults maintained greater overall microbial diversity than adolescents or the elderly, while the intragroup variation among the elderly and rural populations was significantly greater. Skin-associated bacterial community structure and composition could predict whether a sample came from an urban or a rural resident ~5x greater than random.

Energy generation by wind and solar farms could reduce carbon emissions and thus mitigate anthropogenic climate change. But is this its only benefit? Li et al. conducted experiments using a climate model to show that the installation of large-scale wind and solar power generation facilities in the Sahara could cause more local rainfall, particularly in the neighboring Sahel region. This effect, caused by a combination of increased surface drag and reduced albedo, could increase coverage by vegetation, creating a positive feedback that would further increase rainfall. Science , this issue p. 1019 Large wind and solar farms could increase local rainfall and vegetation cover in the Sahara. Wind and solar farms offer a major pathway to clean, renewable energies. However, these farms would significantly change land surface properties, and, if sufficiently large, the farms may lead to unintended climate consequences. In this study, we used a climate model with dynamic vegetation to show that large-scale installations of wind and solar farms covering the Sahara lead to a local temperature increase and more than a twofold precipitation increase, especially in the Sahel, through increased surface friction and reduced albedo. The resulting increase in vegetation further enhances precipitation, creating a positive albedo–precipitation–vegetation feedback that contributes ~80% of the precipitation increase for wind farms. This local enhancement is scale dependent and is particular to the Sahara, with small impacts in other deserts.

BackgroundUnderstanding the internal anatomy of the liver remains a major challenge in anatomical liver resection. Although virtual hepatectomy and indocyanine green (ICG) fluorescence imaging techniques have been widely used in hepatobiliary surgery, limitations in their application for real-time navigation persist.ObjectiveThe aim of the present study was to evaluate the feasibility and clinical utility of the novel laparoscopic hepatectomy navigation system (LHNS), which fuses preoperative three-dimensional (3D) models with ICG fluorescence imaging to achieve real-time surgical navigation.MethodsWe conducted a retrospective review of clinical outcome for 64 patients who underwent laparoscopic hepatectomy from January 2018 to December 2018, including 30 patients who underwent the procedure using the LHNS (LHNS group) and 34 patients who underwent the procedure without LHNS guidance (Non-LHNS group).ResultsThere was no significant difference in preoperative characteristics between the two groups. The LHNS group had a significantly less blood loss (285.0 ± 163.0 mL vs. 391.1 ± 242.0 mL; P = 0.047), less intraoperative blood transfusion rate (13.3% vs. 38.2%; P = 0.045), and shorter postoperative hospital stay (7.8 ± 2.1 days vs. 10.6 ± 3.8 days; P < 0.001) than the Non-LHNS group. There was no statistical difference in operative time and the overall complication rate between the two groups. The liver transection line was clearly delineated by the LHNS in 27 patients; however, the projection of boundary was unclear in 2 cases, and in 1 case, the boundary was not clearly displayed by ICG fluorescence imaging.ConclusionsWe developed the LHNS to address limitations of current intraoperative imaging systems. The LHNS is hopefully to become a promising real-time navigation system for laparoscopic hepatectomy.

Background Completing Patient‐Generated Subjective Global Assessment (PG‐SGA) questionnaires is time consuming. This study aimed to develop and validate an easy‐to‐use modified PG‐SGA (mPG‐SGA) for cancer patients. Methods Seventy professionals assessed the content validity, comprehensibility, and difficulty of the full PG‐SGA. A survey including the PG‐SGA and other questionnaires was completed by 34 071 adult hospitalized cancer patients with first cancer diagnosis or recurrent disease with any tumour comorbidities from the INSCOC study. Among them, 1558 patients were followed for 5 years after admission. Reliability and rank correlation were estimated to assess the consistency between PG‐SGA items and to select mPG‐SGA items. The external and internal validity, test–retest reliability, and predictive validity were tested for the mPG‐SGA via comparison with both the PG‐SGA and abridged PG‐SGA (abPG‐SGA). Results After deleting items that more than 50% of professionals considered difficult to evaluate (Worksheet 4) and items with an item‐total correlation <0.1, the mPG‐SGA was constructed. Nutritional status was categorized using mPG‐SGA scores as well‐nourished (0 points) or mildly (1–2 points), moderately (3–6 points), or severely malnourished (≥7 points) based on the area under curve (0.962, 0.989, and 0.985) and maximal sensitivity (0.924, 0.918, and 0.945) and specificity (1.000, 1.000, and 0.938) of the cut‐off scores. The external and internal validity and test–retest reliability were good. Significant median overall survival differences were found among nutritional status groups categorized by the mPG‐SGA: 24, 18, 14, and 10 months for well‐nourished, mildly malnourished, moderately malnourished, and severely malnourished, respectively (all Ps < 0.05). Neither the PG‐SGA nor the abridged PG‐SGA could discriminate the median overall survival differences between the well‐nourished and mildly malnourished groups. Conclusions We systematically developed and validated the mPG‐SGA as an easier‐to‐use nutritional assessment tool for cancer patients. The mPG‐SGA appears to have better predictive validity for survival than the PG‐SGA and abridged PG‐SGA.

Purpose Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI preoperatively. Methods In total, 405 patients were included. A total of 7302 radiomic features and 17 radiological features were extracted by a radiomics feature extraction package and radiologists, respectively. We developed a XGBoost model based on radiomics features, radiological features and clinical variables and a three-dimensional convolutional neural network (3D-CNN) to predict MVI status. Next, we compared the efficacy of the two models. Results Of the 405 patients, 220 (54.3%) were MVI positive, and 185 (45.7%) were MVI negative. The areas under the receiver operating characteristic curves (AUROCs) of the Radiomics-Radiological-Clinical (RRC) Model and 3D-CNN Model in the training set were 0.952 (95% confidence interval (CI) 0.923–0.973) and 0.980 (95% CI 0.959–0.993), respectively ( p  = 0.14). The AUROCs of the RRC Model and 3D-CNN Model in the validation set were 0.887 (95% CI 0.797–0.947) and 0.906 (95% CI 0.821–0.960), respectively ( p  = 0.83). Based on the MVI status predicted by the RRC and 3D-CNN Models, the mean recurrence-free survival (RFS) was significantly better in the predicted MVI-negative group than that in the predicted MVI-positive group (RRC Model: 69.95 vs. 24.80 months, p  < 0.001; 3D-CNN Model: 64.06 vs. 31.05 months, p  = 0.027). Conclusion The RRC Model and 3D-CNN models showed considerable efficacy in identifying MVI preoperatively. These machine learning models may facilitate decision-making in HCC treatment but requires further validation.

Pollutant gases, such as CO, NO2, O3, and SO2 affect human health, and low-cost sensors are an important complement to regulatory-grade instruments in pollutant monitoring. Previous studies focused on one or several species, while comprehensive assessments of multiple sensors remain limited. We conducted a 12-month field evaluation of four Alphasense sensors in Beijing and used single linear regression (SLR), multiple linear regression (MLR), random forest regressor (RFR), and neural network (long short-term memory (LSTM)) methods to calibrate and validate the measurements with nearby reference measurements from national monitoring stations. For performances, CO > O3 > NO2 > SO2 for the coefficient of determination (R2) and root mean square error (RMSE). The MLR did not increase the R2 after considering the temperature and relative humidity influences compared with the SLR (with R2 remaining at approximately 0.6 for O3 and 0.4 for NO2). However, the RFR and LSTM models significantly increased the O3, NO2, and SO2 performances, with the R2 increasing from 0.3–0.5 to >0.7 for O3 and NO2, and the RMSE decreasing from 20.4 to 13.2 ppb for NO2. For the SLR, there were relatively larger biases, while the LSTMs maintained a close mean relative bias of approximately zero (e.g., <5% for O3 and NO2), indicating that these sensors combined with the LSTMs are suitable for hot spot detection. We highlight that the performance of LSTM is better than that of random forest and linear methods. This study assessed four electrochemical air quality sensors and different calibration models, and the methodology and results can benefit assessments of other low-cost sensors.

The Naples prognostic score (NPS) is an effective inflammatory and nutritional scoring system widely applied as a prognostic factor in various cancers. We aimed to analyze the prognostic value of the NPS in patients diagnosed with non-small-cell lung cancer (NSCLC). We prospectively collected 395 patients diagnosed with NSCLC between January 2016 and December 2018 in two university-affiliated hospitals. Patients were divided into three groups according to their pretreatment NPS (Group 0: NPS = 0; Group 1: NPS = 1–2; Group 2: NPS = 3–4). Kaplan–Meier survival curves indicated that patients with higher NPS had a poorer overall survival (OS) and progress-free survival (PFS) (both P  < 0.05). NPS was further confirmed as an independent prognostic factors of OS and PFS by multivariable survival analysis (both P  < 0.05). Furthermore, stratifying by TNM stage, NPS also has significant predictive performance for OS and PFS in both early (I–IIIA) and advanced (IIIB–IV) stage NSCLC (all P  < 0.05). The time-dependent receiver operating characteristic curve analysis demonstrated that NPS was more superior to other prognostic factors in predicting OS and PFS. In conclusion, NPS may serve as an effective indicator to predict OS and PFS in NSCLC patients regardless of TNM stage.

•Age is the most important risk factor for sarcopenia.•Patients with cancer and sarcopenia had a significantly higher and earlier peak risk for mortality.•Sarcopenia was independently associated with mortality in the total population (hazard ratio, 1.429, P < 0.001) and most cancer types.•This was the first study to explore the prognostic effect of sarcopenia in a pan-cancer and large-scale population.•Hazard function is used to reveal the effects of sarcopenia on cancer death overtime in patients with cancer.•This study emphasized the adverse effects of sarcopenia and offered the possibility of using clinical prediction models to aid in the rapid diagnosis of sarcopenia. Although previous studies have implicated the negative outcomes of sarcopenia, evidence is limited to one or a few types of cancer. The aim of this study was to evaluate the distribution and influencing factors of sarcopenia, and explore the relationship between sarcopenia and cancer prognosis in a large oncological population. This observational cohort study included patients diagnosed with malignant cancer between May 2011 and January 2019. Hematologic and anthropometric parameters were collected prospectively. Low skeletal muscle mass and radiodensity were diagnosed using clinical indicators, according to the two prediction models. The importance of potential risk factors for sarcopenia was estimated by subtracting the predicted degrees of freedom from the partial χ2 statistic. Hazard rates of death were calculated using the hazard function and Cox regression analyses. We included 13 761 patients with cancer; the prevalence of sarcopenia was 33%. The median age was 58 y and 7135 patients (52%) were men. Patients with sarcopenia had a worse nutritional status and quality of life than those without sarcopenia. Age was the most important risk factor for sarcopenia compared with body mass index or TNM stage. Additionally, patients with sarcopenia had a significantly higher and earlier peak risk for mortality. After adjusting for baseline characteristics, sarcopenia was independently associated with mortality in the research population (hazard ratio, 1.429; P < 0.001) and most cancer types. Age is the most important risk factor for sarcopenia even in patients with cancer. Sarcopenia is strongly associated with a poor quality of life and reduced overall survival.

BackgroundThe septal extension graft is one of the most commonly used grafts in Asian tip plasty techniques. However, the septal extension graft usually induces a hard and immobile nasal tip. The purpose of this study was to evaluate the esthetic outcomes of the modified septal extension graft with M-shaped auricular cartilage by three-dimensional anthropometric analysis.MethodsA total of 36 patients received augmentation rhinoplasty with M-shaped auricular cartilage as septal extension graft combined with silicone implant. Thirteen measurement items were evaluated using three-dimensional anthropometric techniques, and the preoperative and postoperative results were compared.ResultsThe majority of patients (91.7%) were satisfied with the postoperative nasal shape. No infection, gross absorption, graft exposure, implant exposure, or implant migration was observed. Compared with the preoperative value, the nasal length, nasal height, nasal depth, nasion height, columella width, nasolabial angle, nasofrontal angle, and nasal depth-nasal width index significantly increased. The nasal width, nasal tip width, and nasal index significantly decreased.ConclusionWe performed tip plasty with the M-shaped auricular cartilage as modified septal extension graft, achieving a soft and mobile tip with satisfying tip projection in most patients.Level of Evidence IVThis journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.