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Abstract This study examines December-January-February (DJF) soil moisture responses to multi-year (MY) and single-year (SY) La Niñas using a 2200-year CESM1 simulation, AGCM experiments, and observational data. Four regions where MY La Niñas amplify SY La Niñas’ impacts on soil moisture were identified: North America, Australia, the Middle East, and the Sahel. SY La Niñas typically cause soil moisture drying in the Middle East and North America and wetting in Australia and the Sahel. MY La Niñas enhance these effects in the second DJF due to the strengthening of precipitation anomalies or the accumulation of precipitation-induced soil moisture anomalies, except in the Sahel where wetting is driven in part by evapotranspiration anomalies. Soil moisture variations are linked to La Niña-induced sea surface temperature changes in the Indian Ocean (for Australia and the Middle East) and the Pacific Ocean (for North America). These amplified effects are largely supported by the observed MY La Niña events from 1948 to 2022. These findings emphasize the need to integrate MY La Niñas into regional agriculture and water resource management strategies to better anticipate and mitigate their impacts. 

Surrogate selection is an experimental design that without sequencing any DNA can restrict a sample of cells to those carrying certain genomic mutations. In immunological disease studies, this design may provide a relatively easy approach to enrich a lymphocyte sample with cells relevant to the disease response because the emergence of neutral mutations associates with the proliferation history of clonal subpopulations. A statistical analysis of clonotype sizes provides a structured, quantitative perspective on this useful property of surrogate selection. Our model specification couples within-clonotype birth-death processes with an exchangeable model across clonotypes. Beyond enrichment questions about the surrogate selection design, our framework enables a study of sampling properties of elementary sample diversity statistics; it also points to new statistics that may usefully measure the burden of somatic genomic alterations associated with clonal expansion. We examine statistical properties of immunological samples governed by the coupled model specification, and we illustrate calculations in surrogate selection studies of melanoma and in single-cell genomic studies of T cell repertoires. 

This study demonstrated a sustainable, zero-waste approach to produce carboxylated lignin-containing cellulose nanofibers (LCNFs) directly from untreated sugarcane bagasse (SCB) using nitro-oxidation process (NOP) fol lowed by high-pressure homogenization. Systematic optimization of reaction parameters was conducted, including reaction time, HNO3-to-SCB ratio, HNO3 concentration, temperature, and co-oxidant addition (KNO₂). The results revealed that HNO3 concentration played the most dominant role in tailoring LCNF properties. Notably, the resulting LCNFs exhibited high dispersibility, with zeta potential values ranging from 􀀀38 to 􀀀65 mV due to the increasing surface carboxyl content (0.43 to 1.21 mmol/g) even under relatively mild conditions (e.g., 50 ◦C, 5 h). Lowering the acid concentration significantly increased the lignin content, enhancing the thermal stability. All LCNFs exhibited nanoscale diameters (7–13 nm), high crystallinity (54 to 70 %), and shear- thinning behavior. Elemental analysis of NOP effluents confirmed their enrichment with macro- and micro- nutrients, enabling their reuse as biofertilizers. This dual valorization of solid and liquid products positions NOP as a viable nanocellulose production and nutrient recovery pathway from lignocellulosic biomass. Resulting LCNFs, with their amphiphilic, biodegradable, and tunable surface properties, represent a compelling platform to make new materials to replace some synthetic polymers and reduce microplastic and chemical pollution.