DataSheet1_Performances of Machine Learning Algorithms in Predicting the Productivity of Conservation Agriculture at a Global Scale.pdf

Assessing the productive performance of conservation agriculture (CA) has become a major issue due to growing concerns about global food security and sustainability. Numerous experiments have been conducted to assess the performance of CA under various local conditions, and meta-analysis has become a standard approach in agricultural sector for analysing and summarizing the experimental data. Meta-analysis provides valuable synthetic information based on mean effect size estimation. However, summarizing large amounts of information by way of a single mean effect value is not always satisfactory, especially when considering agricultural practices. Indeed, their impacts on crop yields are often non-linear, and vary widely depending on a number of factors, including soil properties and local climate conditions. To address this issue, here we present a machine learning approach to produce data-driven global maps describing the spatial distribution of the productivity of CA versus conventional tillage (CT). Our objective is to evaluate and compare several machine-learning models for their ability in estimating the productivity of CA systems, and to analyse uncertainty in the model outputs. We consider different usages, including classification, point regression and quantile regression. Our approach covers the comparison of 12 different machine learning algorithms, model training, tuning with cross-validation, testing, and global projection of results. The performances of these algorithms are compared based on a recent global dataset including more than 4,000 pairs of crop yield data for CA vs. CT. We show that random forest has the best performance in classification and regression, while quantile regression forest performs better than quantile neural networks in quantile regression. The best algorithms are used to map crop productivity of CA vs. CT at the global scale, and results reveal that the performance of CA vs. CT is characterized by a strong spatial variability, and that the probability of yield gain with CA is highly dependent on geographical locations. This result demonstrates that our approach is much more informative than simply presenting average effect sizes produced by standard meta-analyses, and paves the way for such probabilistic, spatially-explicit approaches in many other fields of research.</p

Supplementary Fig. S3 from Manipulation of Cell-Type Selective Antibody Internalization by a Guide-Effector Bispecific Design

Surface antigen removal.</p

Supplementary Fig. S4 from Manipulation of Cell-Type Selective Antibody Internalization by a Guide-Effector Bispecific Design

Bispecific ADC and site-specific drug conjugation.</p

The N‑Terminal T–T Motif of a Third-Generation HIV‑1 Fusion Inhibitor Is Not Required for Binding Affinity and Antiviral Activity

The highlighted next-generation HIV-1 fusion inhibitor peptide <b>1</b> is capped by two threonines. Here, we generated peptide <b>2</b> by deleting the T–T motif and compared their structural and antiviral properties. Significantly, two peptides showed similar helical and oligomeric states in solution, comparable binding affinities to the target, and no significant difference to inhibit HIV-1 fusion and infection. Also, the T–T motif was not associated with peptide <b>1</b> resistant mutations and its deletion did not affect peptide <b>1</b> against enfuvirtide-resistant HIV-1 mutants. The redundancy of the T–T motif was further verified by the model peptide C34 and short peptide inhibitors that mainly target the gp41 pocket, suggesting that the N-terminal T–T motif of peptide <b>1</b> could be removed or modified toward the development of new anti-HIV-1 drugs. Consistently, our data have verified that the M–T hook structure rather than the T–T motif is an efficient strategy for short peptide fusion inhibitors

Internal Electric Field Assisted Photocatalytic Generation of Hydrogen Peroxide over BiOCl with HCOOH

Hydrogen peroxide (H₂O₂) is a superb, clean, and versatile reagent. However, large-scale production of H₂O₂ is manufactured through nongreen methods that motivate people to develop more efficient and green technologies as alternatives. As a novel and green technology used for H₂O₂ generation, the efficiency of photocatalysis is still far from satisfactory. Here, we demonstrate a novel and efficient path of the generation of H₂O₂ in BiOCl photocatalysis but not the direct electron reduction of O₂ or hole oxidation of OH^– to H₂O₂. Super high production (685 μmol/h) of H₂O₂ by the addition of HCOOH as the hole shuttle was realized over BiOCl nanoplates. In this photocatalytic system, the BiOCl supplied abundant photoinduced holes to initiate HCOO^• radical. The HCOO^• further reacts with OH^– to •OH which is proven to be the source of the H₂O₂. Apart from HCOOH, O₂ also played important roles. The O₂ not only promoted the reaction through the cycle between Bi³⁺ and Bi, which decreased the combination of carriers, but also avoided the carbonation of surfaces, thus achieving the high production of H₂O₂ (1020 μmol/h). In this work, we shed light on a deep understanding of the photocatalytic evolution of H₂O₂ in a novel perspective and achieve high production

Supplementary Fig. S5 from Manipulation of Cell-Type Selective Antibody Internalization by a Guide-Effector Bispecific Design

Cell-type selective ADC cytotoxicity.</p

Positive and negative effects of graphite flake and monolayer graphene oxide templates on protein crystallization

Heterogeneous template-induced nucleation is a promising way to regulate protein crystallization events and could be employed for purification processes and crystallographic studies. Protein crystallization process with graphite and graphene oxide, as heterogeneous templates, were investigated. More than 640 hanging drops with different concentrations of Lysozyme (30, 50, 70, 100 mg/mL) and NaCl (0.7, 0.9, 1.1, 1.3, 1.5 M) were crystallised at 4 °C with or without graphite/graphene oxide templates. The induction times and crystallization process were observed under the microscope. The lysozyme in the solutions with graphite flakes nucleated faster under all the conditions than the lysozyme with equal experimental conditions without templates. The crystals preferred to grow around the edge of graphite flakes than on the flat surfaces. In the droplets with monolayer graphene oxide, more crystals appeared around graphene oxide particles, and the faster or slower nucleation processes with templates were dependent on the lysozyme and NaCl concentrations. Graphene oxide templates strongly inhibited nucleation at high lysozyme concentrations but promoted nucleation at low lysozyme concentrations. Both heterogeneous templates changed the crystal morphology and the crystallization kinetics. More crystals were observed in the solution with graphite templatesthan with graphene oxide templates and without any template

Supplementary Fig. S1 from Manipulation of Cell-Type Selective Antibody Internalization by a Guide-Effector Bispecific Design

Selection and characterization of anti-ALCAM scFvs from phage display library.</p

Supplementary Table S1 from Manipulation of Cell-Type Selective Antibody Internalization by a Guide-Effector Bispecific Design

Summary of antigen density and EphA2/ALCAM ratio in various tumor cell lines studied.</p

Supplementary Fig. S2 from Manipulation of Cell-Type Selective Antibody Internalization by a Guide-Effector Bispecific Design

Characterization of the anti-ALCAMxEphA2 bispecific.</p