BACKGROUND: Comfort gloves are used in the management of hand dermatoses.
OBJECTIVE: To compare the acceptance and tolerability of comfort gloves made of different materials in patients with hand dermatoses and their effects on skin lesions.
METHODS: In a prospective multicenter study, 284 patients with hand dermatoses were invited to wear either a cotton glove (COT) or a semipermeable Sympatex glove underneath a cotton glove (SYM/COT) for two subsequent phases of 19 consecutive nights each. A total of 88 controls were asked not to wear any comfort gloves overnight. The severity of skin lesions over time was examined. Questionnaires were used to assess health-related quality of life (HRQoL) and acceptance and tolerability of the gloves.
RESULTS: The hand dermatoses improved in all groups. No substantial intergroup differences regarding severity and HRQoL were observed. SYM/COT received better ratings regarding climate conditions and tactility while COT showed superiority in fit, wearing comfort, and practicality.
CONCLUSIONS: We confirmed that SYM/COT and COT are well tolerated and accepted suggesting that SYM/COT is a good alternative for COT as comfort gloves in patients with hand dermatoses. Individual requirements, needs, and preferences may direct the material choice.

Over the years, thrips have transitioned from a minor nuisance to a major problem, significantly impacting the yield and quality of cotton. Unmanned aerial vehicles (UAVs) for plant protection have emerged as an effective alternative to traditional pesticide spraying equipment. UAVs offer advantages such as avoiding crop damage and enhancing pesticide deposition on the plants and have become the primary choice for pesticide application in cotton fields. In this study, a 2-year field experiment found that the thrips population in a cotton field in Xinjiang, China, exhibited gradual growth during the early flowering phase, peaking in late July. The thrips population gradually shifted from the lower canopy to the upper canopy as the cotton flowers opened layer by layer. From 09:00 to 11:00 (GMT+8) and 19:00 to 21:00 (GMT+8), thrips mainly flew outside the flowers, while from 17:00 to 19:00 (GMT+8), they mostly inhabited the inner whorls of flowers. The insecticides 10% cyantraniliprole oil dispersion and 10% spinetoram suspension concentrate, sprayed by UAV, had the best control effect on thrips, with 80.51% and 79.22% control effect after 7 days of spraying, respectively. The optimal spraying time for 10% cyantraniliprole oil dispersion was 19:00 (GMT+8), and the control effect on thrips reached 91.16% at 7 days of spraying. During the cotton flowering period, thrips inhabited flowers in the evening and flew outside during the day. The best control effect on thrips was achieved with UAV-sprayed 10% cyantraniliprole oil dispersion at 19:00 (GMT+8).

SET-domain group histone methyltransferases (SDGs) are known to play crucial roles in plant responses to abiotic stress. However, their specific function in cotton\'s response to drought stress has not been well understood. This study conducted a comprehensive analysis of the SDG gene family in Gossypium hirsutum, identifying a total of 82 SDG genes. An evolutionary analysis revealed that the SDG gene family can be divided into eight subgroups. The expression analysis shows that some GhSDG genes are preferentially expressed in specific tissues, indicating their involvement in cotton growth and development. The transcription level of some GhSDG genes is induced by PEG, with GhSDG59 showing significant upregulation upon polyethylene glycol (PEG) treatment. Quantitative polymerase chain reaction (qPCR) analysis showed that the accumulation of transcripts of the GhSDG59 gene was significantly upregulated under drought stress. Further functional studies using virus-induced gene silencing (VIGS) revealed that silencing GhSDG59 reduced cotton tolerance to drought stress. Under drought conditions, the proline content, superoxide dismutase (SOD) and peroxidase (POD) enzyme activities in the GhSDG59-silenced plants were significantly lower than in the control plants, while the malondialdehyde (MDA) content was significantly higher. Transcriptome sequencing showed that silencing the GhSDG59 gene led to significant changes in the expression levels of 1156 genes. The KEGG enrichment analysis revealed that these differentially expressed genes (DEGs) were mainly enriched in the carbon metabolism and the starch and sucrose metabolism pathways. The functional annotation analysis identified known drought-responsive genes, such as ERF, CIPK, and WRKY, among these DEGs. This indicates that GhSDG59 is involved in the drought-stress response in cotton by affecting the expression of genes related to the carbon metabolism and the starch and sucrose metabolism pathways, as well as known drought-responsive genes. This analysis provides valuable information for the functional genomic study of SDGs and highlights potential beneficial genes for genetic improvement and breeding in cotton.

C-TERMINALLY ENCODED PEPTIDEs (CEPs) are a class of peptide hormones that have been shown in previous studies to play an important role in regulating the development and response to abiotic stress in model plants. However, their role in cotton is not well understood. In this study, we identified 54, 59, 34, and 35 CEP genes from Gossypium hirsutum (2n = 4x = 52, AD1), G. barbadense (AD2), G. arboreum (2n = 2X = 26, A2), and G. raimondii (2n = 2X = 26, D5), respectively. Sequence alignment and phylogenetic analyses indicate that cotton CEP proteins can be categorized into two subgroups based on the differentiation of their CEP domain. Chromosomal distribution and collinearity analyses show that most of the cotton CEP genes are situated in gene clusters, suggesting that segmental duplication may be a critical factor in CEP gene expansion. Expression pattern analyses showed that cotton CEP genes are widely expressed throughout the plant, with some genes exhibiting specific expression patterns. Ectopic expression of GhCEP46-D05 in Arabidopsis led to a significant reduction in both root length and seed size, resulting in a dwarf phenotype. Similarly, overexpression of GhCEP46-D05 in cotton resulted in reduced internode length and plant height. These findings provide a foundation for further investigation into the function of cotton CEP genes and their potential role in cotton breeding.

BACKGROUND: Optimizing biochar application is vital for enhancing crop production and ensuring sustainable agricultural production. A 3-year field experiment was established to explore the effects of varying the biochar application rate (BAR) on crop growth, quality, productivity and yields. BAR was set at 0, 10, 50 and 100 t ha-1 in 2018; 0, 10, 25, 50 and 100 t ha-1 in 2019; and 0, 10, 25 and 30 t ha-1 in 2020. Crop quality and growth status and production were evaluated using the dynamic technique for order preference by similarity to ideal solution with the entropy weighted method (DTOPSIS-EW), principal component analysis (PCA), membership function analysis (MFA), gray relation analysis (GRA) and the fuzzy Borda combination evaluation method.
RESULTS: Low-dose BAR (≤ 25 t ha-1 for cotton; ≤ 50 t ha-1 for sugar beet) effectively increased biomass, plant height, leaf area index (LAI), water and fertility (N, P and K) productivities, and yield. Biochar application increased the salt absorption and sugar content in sugar beet, with the most notable increases being 116.45% and 20.35%, respectively. Conversely, BAR had no significant effect on cotton fiber quality. The GRA method was the most appropriate for assessing crop growth and quality. The most indicative parameters for reflecting cotton and sugarbeet growth and quality status were biomass and LAI. The 10 t ha-1 BAR consistently produced the highest scores and was the most economically viable option, as evaluated by DTOPSIS-EW.
CONCLUSIONS: The optimal biochar application strategy for improving cotton and sugar beet cultivation in Xinjiang, China, is 10 t ha-1 biochar applied continuously. © 2024 Society of Chemical Industry.

Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.

The genetically engineered bollworm-resistant Bt cotton hybrid varieties offer opportunities for reducing crop losses and enhancing productivity. In Eastern Africa region, Sudan, Ethiopia, and Kenya have approved and released Bt cotton in 2012, in 2018, and in 2019, respectively. The region has potential to grow cotton in over 5 million hectares. For commercial plantings in Ethiopia, Sudan and Kenya, hybrid Bt cotton seeds have been imported from India. Due to the COVID-19 pandemic-induced supply chain disruptions, high shipment costs, bureaucratic procedures for importing seeds, and foreign exchange shortages, farmers have not been able to access Bt cotton seeds. Stakeholders are seeking local production of seeds to provide sustainable access by farmers at affordable cost. Country case studies reveal the importance of enhancing capacity for local seed production and extension advisory services. Revival of the cotton sector needs enhanced public-private partnerships to pave the way for sustainable seeds access in the region.

UNASSIGNED: Precise monitoring of cotton leaves\' nitrogen content is important for increasing yield and reducing fertilizer application. Spectra and images are used to monitor crop nitrogen information. However, the information expressed using nitrogen monitoring based on a single data source is limited and cannot consider the expression of various phenotypic and physiological parameters simultaneously, which can affect the accuracy of inversion. Introducing a multi-source data-fusion mechanism can improve the accuracy and stability of cotton nitrogen content monitoring from the perspective of information complementarity.
UNASSIGNED: Five nitrogen treatments were applied to the test crop, Xinluzao No. 53 cotton, grown indoors. Cotton leaf hyperspectral, chlorophyll fluorescence, and digital image data were collected and screened. A multilevel data-fusion model combining multiple machine learning and stacking integration learning was built from three dimensions: feature-level fusion, decision-level fusion, and hybrid fusion.
UNASSIGNED: The determination coefficients (R2) of the feature-level fusion, decision-level fusion, and hybrid-fusion models were 0.752, 0.771, and 0.848, and the root-mean-square errors (RMSE) were 3.806, 3.558, and 2.898, respectively. Compared with the nitrogen estimation models of the three single data sources, R2 increased by 5.0%, 6.8%, and 14.6%, and the RMSE decreased by 3.2%, 9.5%, and 26.3%, respectively.
UNASSIGNED: The multilevel fusion model can improve accuracy to varying degrees, and the accuracy and stability were highest with the hybrid-fusion model; these results provide theoretical and technical support for optimizing an accurate method of monitoring cotton leaf nitrogen content.

The objective of this work was to assess the possibility of dyeing a substrate composed of non-textile industrial hemp using natural dyes from common madder (Rubia Tinctorum L.) and calendula (Calendula Officialis) and tannin and alum as mordants. The substrate used for the dyeing had a 25/75 hemp/cotton composition. The hemp raw material is an agricultural by-product that was subjected to mechanical and chemical treatments in order to cottonize the fibers, blend them with cotton, and thus obtain first 40-tex open-end yarns and then a knitted fabric. The latter was subjected to different dyeing conditions by varying the dye, mordant, and method for its application, type of water, and rinsing after dyeing. Measurements of the difference (ΔE) and intensity (K/S) of color and fastness to washing and rubbing were carried out. The results showed that dyeing of a non-textile residual hemp substrate is possible, and that calendula is a good option for dyeing it with tap water, tannin-alum set in a meta-mordanting process, and rinsing after 24 h. In this way, a contribution has been made to the circular economy of the textile industry through the use of more sustainable sources and products.

Fruit branch angle (FBA), a pivotal component of cotton plant architecture, is vital for field and mechanical harvesting. However, the molecular mechanism of FBA formation is poorly understood in cotton. To uncover the genetic basis for FBA formation in cotton, we performed a genome-wide association study (GWAS) of 163 cotton accessions with re-sequencing data. A total of 55 SNPs and 18 candidate genes were significantly associated with FBA trait. By combining GWAS and transcriptome analysis, four genes underlying FBA were identified. An FBA-associated candidate gene Ghi_A09G08736, which is homologous to SAUR46 in Arabidopsis thaliana, was detected in our study. In addition, transcriptomic evidence was provided to show that gravity and light were implicated in the FBA formation. This study provides new insights into the genetic architecture of FBA that informs architecture breeding in cotton.