A Retrospective Paired Study: Efficacy and Safety of Nimotuzumab Combined with Radiochemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma

Objective: To evaluate the efficacy and safety of nimotuzumab in combination with radiochemotherapy as the primary treatment in patients with locoregionally advanced nasopharyngeal carcinoma (NPC). Methods: We retrospectively reviewed patients with locoregionally advanced nasopharyngeal carcinoma from September 2012 to December 2016. 188 newly diagnosed patients with stage III–IVB nasopharyngeal carcinoma were treated with at least 1-2 cycles of chemotherapy concurrently with planned IMRT. 88 patients received nimotuzumab 200 mg/week. Acute and late radiation-related toxicities were graded according to the Acute and Late Radiation Morbidity Scoring Criteria of Radiation Therapy Oncology Group. Results: After 3 months of treatment, the complete response rates of nasopharyngeal tumors in the study group and the control group were 78.4% and 65.5%, respectively (?2=4.070, P=0.044). The total complete response rates of cervical lymph nodes in the study group and the control group were 80.7% and 67.6% respectively (?2=4.022, P=0.045).The median cycle for nimotuzumab addition was 6.3 weeks. With a median follow-up of 36.3 months (range, 12–72 months), the estimated 3-year progression failure-free survival and overall survival rates for the study group and the control group were 85.24% vs 81.97% and 96.67% vs 90.0%, respectively. The 3-year local recurrence-free survival rates for the study group and the control group were 96.67% vs 83.60%, respectively (P=0.047). Grade 3 radiation-induced mucositis accounted for 36.4% of treated patients. No skin rash and infusion reaction were observed, distinctly from what is reported in control patients. Conclusion: Nimotuzumab plus chemoradiotherapy in the treatment of locoregionally advanced nasopharyngeal carcinoma showed promising outcomes in terms of locoregional control, without increasing the incidence of radiation-related toxicities for patients

Cooperative Search by Multiple Unmanned Aerial Vehicles in a Nonconvex Environment

This paper presents a distributed cooperative search algorithm for multiple unmanned aerial vehicles (UAVs) with limited sensing and communication capabilities in a nonconvex environment. The objective is to control multiple UAVs to find several unknown targets deployed in a given region, while minimizing the expected search time and avoiding obstacles. First, an asynchronous distributed cooperative search framework is proposed by integrating the information update into the coverage control scheme. And an adaptive density function is designed based on the real-time updated probability map and uncertainty map, which can balance target detection and environment exploration. Second, in order to handle nonconvex environment with arbitrary obstacles, a new transformation method is proposed to transform the cooperative search problem in the nonconvex region into an equivalent one in the convex region. Furthermore, a control strategy for cooperative search is proposed to plan feasible trajectories for UAVs under the kinematic constraints, and the convergence is proved by LaSalle’s invariance principle. Finally, by simulation results, it can be seen that our proposed algorithm is effective to handle the search problem in the nonconvex environment and efficient to find targets in shorter time compared with other algorithms

The effect of prehabilitation on the postoperative outcomes of patients undergoing colorectal surgery: A systematic review and meta-analysis

Study objectivePrehabilitation is analogous to marathon training and includes preoperative preparation for exercise, as well as nutrition and psychology. However, evidence-based recommendations to guide prehabilitation before colorectal surgery are limited. We aimed to evaluate the effect of prehabilitation on the postoperative outcomes of patients undergoing colorectal surgery.DesignThis study is a systematic review and meta-analysis.MethodsThe PubMed, Embase, and Cochrane databases were searched for studies reporting the effect of prehabilitation strategies versus standard care or rehabilitation in patients undergoing colorectal surgery. The primary outcomes were overall postoperative complications and length of hospital stay (LOS), and the secondary outcome was functional capacity (measured using the 6-min walk test [6MWT]) at 4 and 8 weeks after surgery.Main resultsFifteen studies with 1,306 participants were included in this meta-analysis. The results showed no significant reduction in the number of overall postoperative complications (risk ratio = 1.02; 95% confidence interval [CI] = 0.79–1.31; p = 0.878) or LOS (standardized mean difference = 0.04; 95% CI = −0.11 to 0.20; p = 0.589) in patients who underwent colorectal surgery with or without prehabilitation strategy. Additionally, there were no significant differences in the functional capacity estimated using the 6MWT at 4 and 8 weeks postoperatively.ConclusionsPrehabilitation did not significantly affect the number of postoperative complications, LOS, or functional capacity of patients undergoing colorectal surgery. Whether prehabilitation should be recommended deserves further consideration.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=290108, identifier CRD4202129010

From Static to Dynamic Structures: Improving Binding Affinity Prediction with a Graph-Based Deep Learning Model

Accurate prediction of the protein-ligand binding affinities is an essential challenge in the structure-based drug design. Despite recent advance in data-driven methods in affinity prediction, their accuracy is still limited, partially because they only take advantage of static crystal structures while the actual binding affinities are generally depicted by the thermodynamic ensembles between proteins and ligands. One effective way to approximate such a thermodynamic ensemble is to use molecular dynamics (MD) simulation. Here, we curated an MD dataset containing 3,218 different protein-ligand complexes, and further developed Dynaformer, which is a graph-based deep learning model. Dynaformer was able to accurately predict the binding affinities by learning the geometric characteristics of the protein-ligand interactions from the MD trajectories. In silico experiments demonstrated that our model exhibits state-of-the-art scoring and ranking power on the CASF-2016 benchmark dataset, outperforming the methods hitherto reported. Moreover, we performed a virtual screening on the heat shock protein 90 (HSP90) using Dynaformer that identified 20 candidates and further experimentally validated their binding affinities. We demonstrated that our approach is more efficient, which can identify 12 hit compounds (two were in the submicromolar range), including several newly discovered scaffolds. We anticipate this new synergy between large-scale MD datasets and deep learning models will provide a new route toward accelerating the early drug discovery process.Comment: totally reorganize the texts and figure

Spatial-temporal Characteristics and Source Apportionment of Ambient VOCs in Southeast Mountain Area of China

Seasonal variations and sources of ambient volatile organic compounds (VOCs) were conducted at the county and rural sites in a mountain area of southeastern China. The results showed that the pattern of VOC concentrations was dominated by oxygenated VOCs (37.6%) and alkanes (25.8%), followed by halocarbons (16.8%), alkenes (11.9%), aromatics (6.87%), and alkynes (1.04%). Based on the OH radical loss rate (LOH) and ozone formation potential (OFP) analysis, alkenes had the highest chemical activity, especially the contribution of isoprene in rural areas. Aromatics contributed the most to secondary organic aerosols (SOA) formation in both county and rural areas. Source apportionment of VOCs were quantified by the positive matrix factorization (PMF) model, including industrial emissions and combustion burning (30.1% and 43.3% in the county and rural areas, respectively) and vehicle exhausts (30.3% and 10.8%), followed by solvent usage (17.1% and 5.2%), liquid petroleum gas (LPG) usage and fuel evaporation (14.2% and 10.0%), and biogenic source (8.3% and 30.6%). The backward air trajectories showed that air mass in spring was mainly originated from the intercity transmission, while the air clusters in autumn came from the northern areas through long-range transport. The study was helpful to understand the pollution characteristics in the mountainous area and provides a scientific basis for local O3 and PM2.5 pollution control

Aridity-driven shift in biodiversity–soil multifunctionality relationships

From Springer Nature via Jisc Publications RouterHistory: received 2021-01-07, accepted 2021-08-12, registration 2021-08-25, pub-electronic 2021-09-09, online 2021-09-09, collection 2021-12Publication status: PublishedFunder: National Natural Science Foundation of China (National Science Foundation of China); doi: https://doi.org/10.13039/501100001809; Grant(s): 31770430Abstract: Relationships between biodiversity and multiple ecosystem functions (that is, ecosystem multifunctionality) are context-dependent. Both plant and soil microbial diversity have been reported to regulate ecosystem multifunctionality, but how their relative importance varies along environmental gradients remains poorly understood. Here, we relate plant and microbial diversity to soil multifunctionality across 130 dryland sites along a 4,000 km aridity gradient in northern China. Our results show a strong positive association between plant species richness and soil multifunctionality in less arid regions, whereas microbial diversity, in particular of fungi, is positively associated with multifunctionality in more arid regions. This shift in the relationships between plant or microbial diversity and soil multifunctionality occur at an aridity level of ∼0.8, the boundary between semiarid and arid climates, which is predicted to advance geographically ∼28% by the end of the current century. Our study highlights that biodiversity loss of plants and soil microorganisms may have especially strong consequences under low and high aridity conditions, respectively, which calls for climate-specific biodiversity conservation strategies to mitigate the effects of aridification

Algorithm and Examples of an Agent-Based Evacuation Model

This research establishes a “detect-decide-action” agent-based evacuation model based on the social force model, introducing an active steering force into the basis of the dynamic equation with the combination of the behavioral decision model and the probability model. In the AEM, the detection algorithm is used to identify pedestrians or obstacles within the detection radius to provide the next walking direction and apply the active steering force. The obstacle avoidance algorithm is the core of the “action” link. This research focuses on the establishment of the following and bypassing algorithm when moving in the same direction, and the algorithm of a detour when moving in the opposite direction, applying C++ programming language to achieve the basic evacuation behavior simulation of avoiding pedestrians and obstacles in the actual scene. The results show that compared with the grid model and the general social force model, the agent model (AEM) solves the problem of the distortion of evacuation behavior to some extent, and the pedestrian is more flexible in the choice of evacuation path

Opposite Online Learning via Sequentially Integrated Stochastic Gradient Descent Estimators

Stochastic gradient descent algorithm (SGD) has been popular in various fields of artificial intelligence as well as a prototype of online learning algorithms. This article proposes a novel and general framework of one-sided testing for streaming data based on SGD, which determines whether the unknown parameter is greater than a certain positive constant. We construct the online-updated test statistic sequentially by integrating the selected batch-specific estimator or its opposite, which is referred to opposite online learning. The batch-specific online estimators are chosen strategically according to the proposed sequential tactics designed by two-armed bandit process. Theoretical results prove the advantage of the strategy ensuring the distribution of test statistic to be optimal under the null hypothesis and also supply the theoretical evidence of power enhancement compared with classical test statistic. In application, the proposed method is appealing for statistical inference of one-sided testing because it is scalable for any model. Finally, the superior finite-sample performance is evaluated by simulation studies