Contribution to Natural Rubber Production without Exogenous Hormonal Stimulation

Rubber production and especially its increase absolutely depend on the activation of the latex-producing metabolism. Can the latex-producing metabolism activation mechanism developed by rubber tree lead to higher yield without exogenous hormonal stimulation? In order to verify this decisive hypothesis, several works, carried out for nine years in Southern Côte d’Ivoire, were conducted on some 15 clones (IRCA 18, IRCA 209, IRCA 111, IRCA 130, PB 235, PB 260, PB 280, PB 330, PB 310; GT 1, BPM 24, RRIC 100; PB 217 and PR 107) of the three metabolisms respectively, active, moderate and slow, with two main statistical designs. On a small scale, in a “one-tree plot” design, the same latex harvesting system, tapping in d4 with different hormonal stimulation regimes (0/y; 2/y; 4/y; 6/y; 8/y; 13/y; 18/y; 26/y, 39/y and 78/y), has been applied to all treatments. In a randomized complete block design, different tapping frequencies (d2, d3, d4, d5 and d6) and hormonal stimulation (0/y, 4/y, 8/y and 10/y) were applied. Whatever the stimulation regime, the average g.t-1.t-1 of the unstimulated control (56) of the active metabolism clones (PB 235, PB 310, IRCA 111 and IRCA 130) over 9 years was statistically the same order that of the stimulated patterns (54). The average g.t-1.t-1 of the control (60) was lower than that of the highest yielding stimulated patterns (67) of the clones (PB 330, PB 280, PB 260, IRCA 18 and IRCA 209). The average g.t-1.t-1of the unstimulated control (49) was significantly lower than that of the highest yielding stimulated treatment (57) of moderate metabolism clones (GT 1, BPM 24 and RRIC 100). The average g.t-1.t-1 of the unstimulated control (39) was significantly lower than that of the highest yielding stimulated treatment (70) of slow metabolism clones (PB 217 and PR 107). On a large scale and at tapping frequency (d2), the unstimulated latex harvesting system (d2 0/y) showed an average yield of (2341; 2266 and 1849 kg.ha-1.year-1 for the active, moderate and slow metabolisms, respectively) statistically comparable to those of the highest yielding tapping frequencies d3, d4, d5 and d6 all latex harvesting systems combined for the clones studied (2388; 2348 and 2256 kg.ha-1.year-1). These results show that it is possible to produce natural rubber without exogenous hormonal stimulation by judiciously playing on tapping intensity.

Stemflow Infiltration Hotspots Create Soil Microsites Near Tree Stems in an Unmanaged Mixed Beech Forest

In stemflow, rainfall is collected and channeled to a concentrated soil water input. It can constitute up to 30% of incident precipitation in some ecosystems. However, the size of the zone influenced by stemflow is unclear, and statistically representative measurement of stemflow (on and in between sites) is scarce. Therefore, whether stemflow creates hotspots of infiltration and potential impacts on forest soils remain subject to controversy. In this study, we investigated the areal dimension of infiltrating stemflow fluxes as well as effects on near-stem soils. We measured throughfall, stemflow and soil properties in high-resolution statistical designs on a mixed forest plot in Germany receiving moderate stemflow. From this data, we modeled the spatial distribution of net precipitation infiltration depth on the plot. Furthermore, we examined soil chemical and physical properties around tree stems to test for and assess a stemflow impact. Results show that stemflow infiltration areas are much smaller than typically assumed and constitute strong infiltration hotspots compared to throughfall. This is also mirrored in soil properties, which are significantly altered near stems. Here, accelerated soil formation and enhanced translocation processes indicate increased soil water fluxes due to high inputs. Additionally, altered soil hydraulic properties enable quicker soil water fluxes near stems. Our findings attest that even comparatively low stemflow fractions (of gross precipitation) can generate strong hotspots of water and matter inputs, which are impactful to subsequent hydrological and biogeochemical processes and properties. Trees shape their direct soil environment, thereby establishing pathways of preferential water flow connecting the canopy and the deeper subsurface.

Integrated Utilization of Dairy Whey in Probiotic β-Galactosidase Production and Enzymatic Synthesis of Galacto-Oligosaccharides

This work established an integrated utilization of dairy whey in β-galactosidase production from Lactobacillus bulgaricus and prebiotics synthesis by the probiotic enzyme. A cost-effective whey-based medium was newly developed for culturing Lactobacillus bulgaricus to produce β-galactosidase. The medium was optimized through response surface methodology (RSM) involving a series of statistical designs, such as the Plackett–Burman design, steepest ascent experiment, and central composite design. Under the optimized medium, the β-galactosidase activity of L. bulgaricus reached 2034 U/L, which was twice that produced from the traditional MRS medium. The cells of L. bulgaricus harvested from the whey-based medium were subsequently treated with lysozyme. The resulting crude enzyme was used as an efficient catalyst, which catalyzed the synthesis of the prebiotic galacto-oligosaccharides (GOS) in a high yield of 44.7% by using whey (200 g/L) as the substrate. The sugar mixture was further purified by activated charcoal adsorption, thereby yielding a high-purity level of 77.6% GOS.

Genomics and breeding innovations for enhancing genetic gain for climate resilience and nutrition traits

Key message Integrating genomics technologies and breeding methods to tweak core parameters of the breeder’s equation could accelerate delivery of climate-resilient and nutrient rich crops for future food security. Abstract Accelerating genetic gain in crop improvement programs with respect to climate resilience and nutrition traits, and the realization of the improved gain in farmers’ fields require integration of several approaches. This article focuses on innovative approaches to address core components of the breeder’s equation. A prerequisite to enhancing genetic variance (σ2g) is the identification or creation of favorable alleles/haplotypes and their deployment for improving key traits. Novel alleles for new and existing target traits need to be accessed and added to the breeding population while maintaining genetic diversity. Selection intensity (i) in the breeding program can be improved by testing a larger population size, enabled by the statistical designs with minimal replications and high-throughput phenotyping. Selection priorities and criteria to select appropriate portion of the population too assume an important role. The most important component of breeder′s equation is heritability (h2). Heritability estimates depend on several factors including the size and the type of population and the statistical methods. The present article starts with a brief discussion on the potential ways to enhance σ2g in the population. We highlight statistical methods and experimental designs that could improve trait heritability estimation. We also offer a perspective on reducing the breeding cycle time (t), which could be achieved through the selection of appropriate parents, optimizing the breeding scheme, rapid fixation of target alleles, and combining speed breeding with breeding programs to optimize trials for release. Finally, we summarize knowledge from multiple disciplines for enhancing genetic gains for climate resilience and nutritional traits.

Beyond the average patient: how neuroimaging models can address heterogeneity in dementia

Dementia is a highly heterogeneous condition, with pronounced individual differences in onset age, clinical presentation, progression rates and neuropathological hallmarks, even within a specific diagnostic group. However, the most common statistical designs used in dementia research studies and clinical trials overlook this heterogeneity, instead relying on the comparison of group average differences (e.g., patient versus control, treatment versus placebo), implicitly assuming within-group homogeneity. This one-size-fits-all approach potentially limits our understanding of dementia aetiology, hindering the identification of effective treatments. Neuroimaging has enabled characterisation of the average neuroanatomical substrates of dementias; however, the increasing availability of large open neuroimaging datasets provides the opportunity to examine patterns of neuroanatomical variability in individual patients. In this Update review we outline the causes and consequences of heterogeneity in dementia and discuss recent research which aims to directly tackle heterogeneity, rather than assume that dementia affects everyone in the same way. We introduce spatial normative modelling as an emerging data-driven technique which can be applied to dementia data to model neuroanatomical variation, capturing individualised neurobiological “fingerprints”. Such methods have the potential to detect clinically relevant subtypes, track an individual’s disease progression or evaluate treatment responses, with the goal of moving towards precision medicine for dementia.

Toward application of biocontrol to inhibit wine spoilage yeasts: The use of statistical designs for screening and optimisation

Spoilage yeasts generate considerable economic losses in the wine industry, and although sulphur dioxide (SO2) is traditionally used for control, its use has become controversial because of its negative effects on health. Biocontrol has emerged as a partial alternative to SO2, and most research has focused on the selection of biocontrol yeasts and/or the mechanisms involved, while little research has been directed to the environmental conditions that make biocontrol effective for application. When there are two or more interacting yeasts, the physicochemical factors that affect their antagonism are many and therefore the application of biocontrol is complex. To reduce SO2, the present study aimed to elucidate biocontrol mechanisms of two yeast interactions and to establish optimal physicochemical conditions for biocontrol of the spoilage yeast during grape must fermentation. Through the use of statistical design, it was possible to find relevant physicochemical factors and optimise them. Wickerhamomyces anomalus “BWa156” developed an active supernatant against ZygoSaccharomyces rouxii “BZr6” while supernatant from Metschnikowia pulcherrima “BMp29” was ineffective. In mixed must fermentations, the first interaction (BWa156 vs. BZr6) showed fewer physicochemical factors impacting biocontrol compared to the second interaction (BMp29 vs. BZr6). However, the fewer factors of the first interaction had a stronger effect on the decline in the spoilage population. Validations showed that the optimal conditions for biocontrol with the first interaction could be predicted. Analysis of the results with BWa156 vs. BZr6 and BMp29 vs. BZr6 suggests that the first interaction is a competition that includes a killer toxin, while the second interaction involves competition for iron resources. Response surface methodology (RSM) allowed a reduction in the number of experiments and permitted to find the optimal biocontrol conditions (SO2: 0 mg mL-1; pH: 3.7; Reducing sugars: 23 °Brix) for the interaction between BWa156 and BZr6.

Statistically Designed Extraction of Herbs Using Ultrasound Waves: A Review

Background: Extraction is the foremost step to isolate the natural constituents from a medicinal plant and leads the process of development of herbal formulation from bench to bed. Introduction: In the field of extraction, the optimization approach helps in achieving better yield and quality where a response of concern is determined or influenced by various variables. This review aimed at congregating the application of different statistical designs (CCD/BBD) to optimize the Ultrasound assisted extraction (UAE) parameters for the recovery of various plant actives belonging to different categories. Methodology: The literature published during last decade in the various reputed databases (Web of Science, Pubmed, Scopus) was reviewed and compiled to reveal the role of response surface methodology in optimizing the influential parameters involved in the ultrasound assisted extraction of herbs. Conclusion: From the present investigations, it can be concluded that the different variables such as sonication power, temperature, time, solute to solvent ratio are generally optimized in UAE of herbs. Moreover, it has also been evidenced from the review of published data that the flavonoids/phenolic acids (>50%) leads the race for the extraction of plants using sound waves. It can be said that the statistically designed UAE has vast prospective in bringing about a green mutiny in herbal drug industry and the modeling of various parameters shall be able to absolutely build up a complete drug innovation course (bench to bed).

Probability intervals of toxicity and efficacy design for dose-finding clinical trials in oncology

Immunotherapy, gene therapy or adoptive cell therapies, such as the chimeric antigen receptor+ T-cell therapies, have demonstrated promising therapeutic effects in oncology patients. We consider statistical designs for dose-finding adoptive cell therapy trials, in which the monotonic dose–response relationship assumed in traditional oncology trials may not hold. Building upon a previous design called “TEPI”, we propose a new dose finding method – Probability Intervals of Toxicity and Efficacy (PRINTE), which utilizes toxicity and efficacy jointly in making dosing decisions, does not require a pre-elicited decision table and at the same time can handle Ockham’s razor properly in the statistical inference. We show that optimizing the joint posterior expected utility of toxicity and efficacy under a 0–1 loss is equivalent to maximizing the marginal model posterior probability in the two-dimensional probability space. An extensive simulation study under various scenarios are conducted and results show that PRINTE outperforms existing designs in the literature since it assigns more patients to optimal doses and less to toxic ones, and selects optimal doses with higher percentages. The simple and transparent features together with good operating characteristics make PRINTE an improved design for dose-finding trials in oncology trials.