Metabolic interactions of host-gut microbiota: New possibilities for the precise diagnosis and therapeutic discovery of gastrointestinal cancer in the future-a review.

Gastrointestinal (GI) cancer continues to pose a significant global health challenge. Recent advances in our understanding of the complex relationship between the host and gut microbiota have shed light on the critical role of metabolic interactions in the pathogenesis and progression of GI cancer. In this study, we examined how microbiota interact with the host to influence signalling pathways that impact the formation of GI tumours. Additionally, we investigated the potential therapeutic approach of manipulating GI microbiota for use in clinical settings. Revealing the complex molecular exchanges between the host and gut microbiota facilitates a deeper understanding of the underlying mechanisms that drive cancer development. Metabolic interactions hold promise for the identification of microbial signatures or metabolic pathways associated with specific stages of cancer. Hence, this study provides potential strategies for the diagnosis, treatment and management of GI cancers to improve patient outcomes.

The dual role of CCND1 in heterotopic ossification: A Non-canonical Pathway for Celecoxib treatment.

Objective: To explore the effective targets of Celecoxib in the treatment of heterotopic ossification using network pharmacology methods. Methods: Potential molecules related to heterotopic ossification were obtained by retrieving the GEO and CTD databases and intersecting them. Potential binding targets of Celecoxib were acquired from the STITCH database. A protein-protein interaction network was constructed between potential binding targets of Celecoxib and potential related molecules of heterotopic ossification using the STRING database. Molecules in the protein-protein interaction network were further analyzed using GO and KEGG enrichment analysis in R software, followed by enrichment analysis of active molecules in the Celecoxib-heterotopic ossification target dataset. Hub genes were selected based on the "degree" value and enrichment within the protein-protein interaction network. The binding affinity of hub genes to Celecoxib was observed using molecular docking techniques. Finally, in vitro experiments were conducted to validate the effectiveness of hub genes and explore their regulatory role in the progression of heterotopic ossification. Additionally, the therapeutic effect of Celecoxib, which modulates the expression of the hub genes, was investigated in the treatment of heterotopic ossification. Results: 568 potential molecules related to heterotopic ossification and 76 potential binding targets of Celecoxib were identified. After intersection, 13 potential functional molecules in Celecoxib's treatment of heterotopic ossification were obtained. KEGG analysis suggested pathways such as Rheumatoid arthritis, NF-kappa B signaling pathway, Pathways in cancer, Antifolate resistance, MicroRNAs in cancer play a role in the treatment of heterotopic ossification by Celecoxib. Further enrichment analysis of the 13 potential functional molecules identified 5 hub genes: IL6, CCND1, PTGS2, IGFBP3, CDH1. Molecular docking results indicated that Celecoxib displayed excellent binding affinity with CCND1 among the 5 hub genes. Experimental validation found that CCND1 is highly expressed in the progression of heterotopic ossification, promoting heterotopic ossification in the early stages and inhibiting it in the later stages, with Celecoxib's treatment of heterotopic ossification depending on CCND1. Conclusion: In the process of treating heterotopic ossification with Celecoxib, immune and inflammatory signaling pathways play a significant role. The therapeutic effect of Celecoxib on heterotopic ossification depends on the hub gene CCND1, which plays different roles at different stages of the progression of heterotopic ossification, ultimately inhibiting the occurrence of heterotopic ossification.

Prediction and Interpretability Study of the Glass Transition Temperature of Polyimide Based on Machine Learning with Quantitative Structure-Property Relationship (Tg-QSPR).

The glass transition temperature (Tg) is a crucial characteristic of polyimides (PIs). Developing a Tg predictive model using machine learning methodologies can facilitate the design of PI structures and expedite the development process. In this investigation, a data set comprising 1257 PIs was assembled, with Tg values determined using differential scanning calorimetry. 210 molecular descriptors were computed using RDKit, and subsequently, six distinct feature selection methodologies were employed to refine the descriptor set. Quantitative structure-property relationship models targeting Tg (Tg-QSPR) were then constructed using five ensemble learning algorithms and one deep learning algorithm. These models exhibited high predictive accuracy and robustness, with the CATBoost model demonstrating the highest accuracy, achieving a coefficient of determination of 0.823 for the test set, a mean absolute error of 20.1 °C, and a root-mean-square error of 29.0 °C. The study identified the NumRotatableBonds descriptor as particularly influential on Tg, showing a negative correlation with the property. Additionally, the model's accuracy was validated using ten new PI films not included in the original data set, resulting in absolute errors ranging from 2.5 to 26.9 °C and absolute percentage error rates of 1.0-12.8%. These findings underscore the importance of utilizing extensive and diverse data sets for predictive modeling to enhance accuracy and stability. Furthermore, exploring the interpretability of the model and experimentally validating newly synthesized PIs have augmented the practical utility of the model. Under the guidance of the Tg-QSPR models, it will be possible to accelerate the performance prediction and structural design of PIs in the future.

Cartilage decellularized matrix hydrogel loaded with protocatechualdehyde for targeted epiphycan treatment of osteoarthritis.

Osteoarthritis (OA) is a prevalent chronic disease, characterized by chronic inflammation and cartilage degradation. This study aims to deepen the understanding of OA's pathophysiology and to develop novel therapeutic strategies. Our study underscores the pivotal role of Epiphycan (EPYC) and the IL-17 signaling pathway in OA. EPYC, an essential extracellular matrix constituent, has been found to exhibit a positive correlation with the severity of OA. We have discovered that EPYC modulates the activation of the IL-17 signaling pathway within chondrocytes by regulating the interaction between IL-17A and its receptor, IL-17RA. This regulatory mechanism underscores the intricate interplay between the extracellular matrix and immune signaling in the pathogenesis of OA Another finding of our study is the therapeutic effectiveness of protocatechualdehyde (PAH) in OA. PAH significantly reduces chondrocyte hypertrophy and supports cartilage tissue recovery.by targets EPYC. To reduce the side effects of orally administered PAH and maintain its effective drug concentration, we have developed a decellularized matrix hydrogel loaded with PAH for intra-articular injection. This novel drug delivery system is advantageous in minimizing drug-related side effects and ensuring sustained release PAH within the joint cavity.

Extracellular matrix hydrogels with fibroblast growth factor 2 containing exosomes for reconstructing skin microstructures.

Decellularized extracellular matrix hydrogel (ECM hydrogel), a natural material derived from normal tissue with unique biocompatibility properties, is widely used for tissue repair. However, there are still problems such as poor biological activity and insufficient antimicrobial property. To overcome these drawbacks, fibroblast growth factor 2 (FGF 2) containing exosome (exoFGF 2) was prepared to increase the biological activity. Furthermore, the antimicrobial capacity of ECM hydrogel was optimised by using copper ions as a ligand-bonded cross-linking agent. The decellularized extracellular matrix hydrogel, intricately cross-linked with copper ions through ligand bonds and loaded with FGF 2 containing exosome (exoFGF 2@ECM/Cu2+ hydrogel), has demonstrated exceptional biocompatibility and antimicrobial properties. In vitro, exoFGF 2@ECM/Cu2+ hydrogel effectively promoted cell proliferation, migration, antioxidant and inhibited bacterial growth. In vivo, the wound area of rat treated with exoFGF 2@ECM/Cu2+ hydrogels were significantly smaller than that of other groups at Day 5 (45.24% ± 3.15%), Day 10 (92.20% ± 2.31%) and Day 15 (95.22% ± 1.28%). Histological examination showed that exoFGF 2@ECM/Cu2+ hydrogels promoted angiogenesis and collagen deposition. Overall, this hydrogel has the potential to inhibit bacterial growth and effectively promote wound healing in a variety of clinical applications.

The Use of Big Data Analysis in Digital Empowerment of Sustainable Technological Innovation Management of Ecological Enterprises.

With the social economy's rapid progress and the popularization of environmental awareness, ecological enterprises have gradually become a crucial trend in the development of modern enterprises. This work intends to promote the development of ecological enterprises to a higher level. This work first analyzes the management mode of ecological enterprises in the context of big data in China. Then, it establishes various indicators to analyze the role of sustainable technological innovation in enterprise development and the impact of digital empowerment on enterprise development. Finally, this work takes China's manufacturing industry and ecological enterprises in Hubei Province as examples to summarize the digital empowerment of sustainable technological innovation management of ecological enterprises under the background of big data. The final result indicates that sustainable technological innovation significantly reduces ecological enterprises' resource consumption and waste emissions. Additionally, it has a significant positive effect on improving enterprise output value and economic benefits. The digital empowerment of enterprises has a significant driving effect on sustainable technological innovation, with a digital driving coefficient of 26. This work provides a feasible scheme for the specific application of big data analysis in the technology innovation management of ecological enterprises, including market demand analysis, environmental monitoring and governance, technology assessment and risk management. This work expounds the role of big data analysis technology in improving decision-making efficiency, optimizing resource allocation and enhancing the competitiveness of enterprises in the digital empowerment of ecological enterprises.

Analyzing Differences in Hematological and Immunological Characteristics Related to Common Gene Mutations in Myelodysplastic Syndromes.

BACKGROUND: Genetic mutations play a crucial role in the development and progression of myelodysplastic syndromes (MDS), impacting the immune microenvironment and influencing the choice of treatment regimen, as well as the efficacy and prognosis of patients. The objective of this study was to examine variations in hematological and immunological characteristics associated with common gene mutations in MDS patients and establish a foundation for the precise treatment of MDS. METHODS: The hematological, immunological, and other clinical features of 71 recently diagnosed MDS patients from January 1, 2019, to July 31, 2023, were retrospectively analyzed. These patients were categorized based on their gene mutations, and the variances in hematological and immunological characteristics among distinct groups were compared. RESULTS: Hematological variances were observed among different gene mutation groups. Specifically, platelet counts in the splicing factor 3B subunit 1 (SF3B1) mutation group were notably higher compared to the wild-type group (p = 0.009). Conversely, in the additional sex combs like 1 (ASXL1) mutation groups, monocyte ratios were significantly elevated in comparison to the wild-type group (p = 0.046), and in the ten-eleven translocation 2 (TET2) mutation group, lymphocyte ratios were significantly lower (p = 0.022). Additionally, the leukocyte (p = 0.005), neutrophil ratio (p = 0.002), and lymphocyte ratio (p = 0.001) were significantly higher in the Runt-related transcription factor 1 (RUNX1) mutation group. Regarding immunological distinctions, the Natural Killer (NK) cell ratio demonstrated a significant increase in the SF3B1 mutation group (p = 0.005). Moreover, the TET2 mutation group exhibited a significantly higher Interleukin-8 (IL-8) level (p = 0.017). In contrast, the U2 small nuclear RNA auxiliary factor 1 (U2AF1) group displayed significantly lower levels of IL-1ß (p = 0.033), IL-10 (p = 0.033), and Tumour Necrosis Factor-α (TNF-α) (p = 0.009). CONCLUSION: Distinct variations exist in the immune microenvironment of MDS associated with different genetic mutations. Further studies are imperative to delve into the underlying mechanisms that drive these differences.

Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis.

Today's AI systems for medical decision support often succeed on benchmark datasets in research papers but fail in real-world deployment. This work focuses on the decision making of sepsis, an acute life-threatening systematic infection that requires an early diagnosis with high uncertainty from the clinician. Our aim is to explore the design requirements for AI systems that can support clinical experts in making better decisions for the early diagnosis of sepsis. The study begins with a formative study investigating why clinical experts abandon an existing AI-powered Sepsis predictive module in their electrical health record (EHR) system. We argue that a human-centered AI system needs to support human experts in the intermediate stages of a medical decision-making process (e.g., generating hypotheses or gathering data), instead of focusing only on the final decision. Therefore, we build SepsisLab based on a state-of-the-art AI algorithm and extend it to predict the future projection of sepsis development, visualize the prediction uncertainty, and propose actionable suggestions (i.e., which additional laboratory tests can be collected) to reduce such uncertainty. Through heuristic evaluation with six clinicians using our prototype system, we demonstrate that SepsisLab enables a promising human-AI collaboration paradigm for the future of AI-assisted sepsis diagnosis and other high-stakes medical decision making.

N/P-doped NiFeV oxide nanosheets with oxygen vacancies as an efficient electrocatalyst for the oxygen evolution reaction.

Plasma treatment as an effective strategy can simultaneously achieve surface modification and heteroatom doping. Here, an N/P-doped NiFeV oxide nanosheet catalyst (N/P-NiFeVO) constructed by Ar/PH3 plasma treatment is used to drive the oxygen evolution reaction (OER). The introduction of V species leads to the formation of an ultrathin ordered nanostructure and exposure of more active sites. Compared to the 2D NiFeV LDH, the prepared N/P-NiFeVO by plasma treatment possesses multiple-valence Fe, V and Ni species, which regulate the intrinsic electronic structure and enable a superior catalytic activity for the OER in alkaline media. Specifically, the N/P-NiFeVO only require an overpotential of 273 mV to drive the current density of 100 mA cm-2. What's more, the electrode can maintain a stable current density in a long-term oxygen evolution reaction (∼120 h) under alkaline conditions. This work provides new insight for the rational design of mixed metal oxides for OER electrocatalysts.

Upgraded durian genome reveals the role of chromosome reshuffling during ancestral karyotype evolution, lignin biosynthesis regulation, and stress tolerance.

Durian (Durio zibethinus) is a tropical fruit that has a unique flavor and aroma. It occupies a significant phylogenetic position within the Malvaceae family. Extant core-eudicot plants are reported to share seven ancestral karyotypes that have undergone reshuffling, resulting in an abundant genomic diversity. However, the ancestral karyotypes of the Malvaceae family, as well as the evolution trajectory leading to the 28 chromosomes in durian, remain poorly understood. Here, we report the high-quality assembly of the durian genome with comprehensive comparative genomic analyses. By analyzing the collinear blocks between cacao and durian, we inferred 11 Malvaceae ancestral karyotypes. These blocks were present in a single-copy form in cacao and mainly in triplicates in durian, possibly resulting from a recent whole genome triplication (WGT) event that led to hexaploidization of the durian genome around 20 (17-24) million years ago. A large proportion of the duplicated genes in durian, such as those involved in the lignin biosynthesis module for phenylpropane biosynthesis, are derived directly from whole genome duplication, which makes it an important force in reshaping its genomic architecture. Transcriptome studies have revealed that genes involved in feruloyl-CoA formations were highly preferentially expressed in fruit peels, indicating that the thorns produced on durian fruit may comprise guaiacyl and syringyl lignins. Among all the analyzed transcription factors (TFs), members of the heat shock factor family (HSF) were the most significantly upregulated under heat stress. All subfamilies of genes encoding heat shock proteins (HSPs) in the durian genome appear to have undergone expansion. The potential interactions between HSF Dzi05.397 and HSPs were examined and experimentally verified. Our study provides a high-quality durian genome and reveals the reshuffling mechanism of ancestral Malvaceae chromosomes to produce the durian genome. We also provide insights into the mechanism underlying lignin biosynthesis and heat stress tolerance.

Enhanced Surgical Outcomes of Popliteal Cyst Excision: A Retrospective Study Comparing Arthroscopic Debridement with and without Methylene Blue Injection.

BACKGROUND This retrospective study of 42 patients with popliteal cysts (or Baker cysts) aimed to compare the effects on duration and outcomes of arthroscopic surgical debridement with and without the use of cyst injection with methylene blue (MB). MATERIAL AND METHODS Medical records of patients who underwent conventional arthroscopic surgery (n=20) or arthroscopic surgery after MB injection (n=22) for popliteal cysts between 2018 and 2021 were reviewed. The MB group underwent arthroscopic popliteal cystectomy with MB as the marker, and the control group underwent conventional arthroscopic popliteal cystectomy. Surgical time of cyst resection, postoperative bruising extent, complication rate, and cyst recurrence rate of the 2 groups were compared. RESULTS The MB group had a faster surgical cyst removal time (16.5±1.5 min) than the control group (24.5±1.6 min; P<0.05). The MB group had less postoperative bruising (1 case, 4.5%) than the control group (5 cases, 25%; P<0.05). The surgical results were similar in both groups, with a Lysholm score of 87.23±1.80 in the MB group and 87.23±1.62 (P>0.05) in the control group. CONCLUSIONS This study showed that preoperative injection of MB for popliteal cysts before arthroscopic debridement improved cyst localization and ease and accuracy of surgery and reduced operative time, adjacent tissue damage, postoperative complications, and recurrence rate.

Telocinobufagin, a PLK1 suppressor that inhibits tumor growth and metastasis by modulating CDC25c and CTCF in HNSCC cells.

BACKGROUND: The high metastasis and mortality rates of head and neck squamous cell carcinoma (HNSCC) urgently require new treatment targets and drugs. A steroidal component of ChanSu, telocinobufagin (TBG), was verified to have anti-cancer effects in various tumors, but its activity and mechanism in anti-HNSCC were still unknown. PURPOSE: This study tried to demonstrate the anti-tumor effect of TBG on HNSCC and verify its potential mechanism. METHODS: The effect of TBG on cell proliferation and metastasis were performed and the TBG changed genes were detected by RNA-seq analysis in HNSCC cells. The GSEA and PPI analysis were used to identify the pathways targeted for TBG-regulated genes. Meanwhile, the mechanism of TBG on anti-proliferative and anti-metastasis were investigated in vitro and in vivo. RESULTS: The in vitro and in vivo experiments confirmed that TBG has favorable anti-tumor effects by induced G2/M phase arrest and suppressed metastasis in HNSCC cells. Further RNA-seq analysis demonstrated the genes regulated by TBG were enriched at the G2/M checkpoint and PLK1 signaling pathway. Then, the bioinformatic analysis of clinical data found that high expressed PLK1 were closely associated with poor overall survival in HNSCC patients. Furthermore, PLK1 directly and indirectly modulated G2/M phase and metastasis (by regulated CTCF) in HNSCC cells, simultaneously. TBG significantly inhibited the protein levels of PLK1 in both phosphorylated and non-phosphorylated forms and then, in one way, inactivated PLK1 failed to activate G2/M phase-related proteins (including CDK1, CDC25c, and cyclin B1). In another way, be inhibited PLK1 unable promote the nuclear translocation of CTCF and thus suppressed HNSC cell metastasis. In contrast, the anti-proliferative and anti-metastasis effects of TBG on HNSCC cell were vanished when cells high-expressed PLK1. CONCLUSION: The present study verified that PLK1 mediated TBG induced anti-tumor effect by modulated G2/M phase and metastasis in HNSCC cells.

GhCTSF1, a short PPR protein with a conserved role in chloroplast development and photosynthesis, participates in intron splicing of rpoC1 and ycf3-2 transcripts in cotton.

Cotton is one of the most important textile fibers worldwide. As crucial agronomic traits, leaves play an essential role in the growth, disease resistance, fiber quality, and yield of cotton plants. Pentatricopeptide repeat (PPR) proteins are a large family of nuclear-encoded proteins involved in organellar or nuclear RNA metabolism. Using a virus-induced gene silencing assay, we found that cotton plants displayed variegated yellow leaf phenotypes with decreased chlorophyll content when expression of the PPR gene GhCTSF1 was silenced. GhCTSF1 encodes a chloroplast-localized protein that contains only two PPR motifs. Disruption of GhCTSF1 substantially reduces the splicing efficiency of rpoC1 intron 1 and ycf3 intron 2. Loss of function of the GhCTSF1 ortholog EMB1417 causes splicing defects in rpoC1 and ycf3-2, leading to impaired chloroplast structure and decreased photosynthetic rates in Arabidopsis. We also found that GhCTSF1 interacts with two splicing factors, GhCRS2 and GhWTF1. Defects in GhCRS2 and GhWTF1 severely affect intron splicing of rpoC1 and ycf3-2 in cotton, leading to defects in chloroplast development and a reduction in photosynthesis. Our results suggest that GhCTSF1 is specifically required for splicing rpoC1 and ycf3-2 in cooperation with GhCRS2 and GhWTF1.

Immunologic characterization of newly diagnosed multiple myeloma patients with renal impairment / 中国肿瘤生物治疗杂志

@#[摘 要] 目的：探究伴有肾损害（RI）的多发性骨髓瘤（MM）患者与无RI患者间是否存在免疫学指标差异。方法：用2017年1月至2023年8月在兰州大学第二医院收治的134例首次确诊为MM的患者相关信息进行回顾性分析，研究对比RI组和非RI组及Durie⁃Salmon（DS）分期和危险分层两个亚组的10种免疫学指标和6个常规血液学参数的差异。结果：RI组外周血中性粒细胞/淋巴细胞比值（NLR）、外周血单核细胞/淋巴细胞比值（MLR）、CD8+ T细胞比例、IL-10均较非RI组高（均P<0.05），淋巴细胞绝对值、CD4/CD8比值均较非RI组低（均P<0.05）。DS-Ⅲ分期患者中，RI组NLR、MLR、CD8+ T细胞比例、IL-8、IL-10均较非RI组升高（均P<0.05），而DS-Ⅰ和DS-Ⅱ患者中，RI组和非RI组患者免疫指标无明显差异。高危MM患者RI组淋巴细胞数、NLR、IL-10均较非RI有明显差异（均P<0.05）。结论：伴RI的MM患者免疫相关指标异常更为明显，DS-Ⅲ分期和高危险度分层表现出明显的免疫指标异常，本研究结果对进一步阐明MM伴有RI患者预后较差的原因及个体化治疗提供参考依据。

Unveiling facial kinship: The BioKinVis dataset for facial kinship verification and genetic association studies.

Facial image-based kinship verification represents a burgeoning frontier within the realms of computer vision and biomedicine. Recent genome-wide association studies have underscored the heritability of human facial morphology, revealing its predictability based on genetic information. These revelations form a robust foundation for advancing facial image-based kinship verification. Despite strides in computer vision, there remains a discernible gap between the biomedical and computer vision domains. Notably, the absence of family photo datasets established through biological paternity testing methods poses a significant challenge. This study addresses this gap by introducing the biological kinship visualization dataset, encompassing 5773 individuals from 2412 families with biologically confirmed kinship. Our analysis delves into the distribution and influencing factors of facial similarity among parent-child pairs, probing the potential association between forensic short tandem repeat polymorphisms and facial similarity. Additionally, we have developed a machine learning model for facial image-based kinship verification, achieving an accuracy of 0.80 in the dataset. To facilitate further exploration, we have established an online tool and database, accessible at http://120.55.161.230:88/.

Recent Study Advances in Flexible Sensors Based on Polyimides.

With the demand for healthy life and the great advancement of flexible electronics, flexible sensors are playing an irreplaceably important role in healthcare monitoring, wearable devices, clinic treatment, and so on. In particular, the design and application of polyimide (PI)-based sensors are emerging swiftly. However, the tremendous potential of PI in sensors is not deeply understood. This review focuses on recent studies in advanced applications of PI in flexible sensors, including PI nanofibers prepared by electrospinning as flexible substrates, PI aerogels as friction layers in triboelectric nanogenerator (TENG), PI films as sensitive layers based on fiber Bragg grating (FBG) in relative humidity (RH) sensors, photosensitive PI (PSPI) as sacrificial layers, and more. The simple laser-induced graphene (LIG) technique is also introduced in the application of PI graphitization to graphene. Finally, the prospect of PIs in the field of electronics is proposed in the review.

Differences in morphology, mitochondrial genomes, and reproductive compatibility between two clades of parasitic wasps Aphelinus mali (Hymenoptera: Aphelindae) in China.

Aphelinus mali (Haldeman) (Hymenoptera: Aphelinidae) in China is comprised of two clades (termed, the Shandong and Liaoning clades). In order to clarify the genetic relationship between these two clades, we compared and analyzed the morphological characteristics and the mitochondrial genome of each, and performed a hybridization experiment. Morphological results showed that both males and females of the Liaoning clade were larger than Shandong clade, in terms of whole body, abdominal, wing and antennal lengths, however, there were no significant differences between clades for total length of the middle or hind leg of females. The length of the mitochondrial genome of the Shandong clade was 14415 bp and, for the Liaoning clade, it was 14804 bp. Each contained 31 genes, including 13 protein-encoded genes, 16 tRNA genes, and 2 rRNA genes. The highest AT level among the 13 protein-coding genes for the two clades were the same gene (ATP8) (Shandong clade, 91.52%; Liaoning clade, 90.91%). By hybridization and backcrossing, we found that there was no cross incompatibility between these two clades of A. mali. Our results indicate that the historic geographical isolation between these clades has not yet caused reproductive isolation of these populations, and they belong to the same species.

Preliminary Expression Analysis of the OSCA Gene Family in Maize and Their Involvement in Temperature Stress.

Hyperosmolality-gated calcium-permeable channels (OSCA) are characterized as an osmosensor in plants; they are able to recognize and respond to exogenous and endogenous osmotic changes, and play a vital role in plant growth and adaptability to environmental stress. To explore the potential biological functions of OSCAs in maize, we performed a bioinformatics and expression analysis of the ZmOSCA gene family. Using bioinformatics methods, we identified twelve OSCA genes from the genome database of maize. According to their sequence composition and phylogenetic relationship, the maize OSCA family was classified into four groups (Ⅰ, Ⅱ, Ⅲ, and Ⅳ). Multiple sequence alignment analysis revealed a conserved DUF221 domain in these members. We modeled the calcium binding sites of four OSCA families using the autodocking technique. The expression profiles of ZmOSCA genes were analyzed in different tissues and under diverse abiotic stresses such as drought, salt, high temperature, and chilling using quantitative real-time PCR (qRT-PCR). We found that the expression of twelve ZmOSCA genes is variant in different tissues of maize. Furthermore, abiotic stresses such as drought, salt, high temperature, and chilling differentially induced the expression of twelve ZmOSCA genes. We chose ZmOSCA2.2 and ZmOSCA2.3, which responded most strongly to temperature stress, for prediction of protein interactions. We modeled the calcium binding sites of four OSCA families using autodocking tools, obtaining a number of new results. These results are helpful in understanding the function of the plant OSCA gene family for study of the molecular mechanism of plant osmotic stress and response, as well as exploration of the interaction between osmotic stress, high-temperature stress, and low-temperature stress signal transduction mechanisms. As such, they can provide a theoretical basis for crop breeding.

Expression of Modified Snowdrop Lectin (Galanthus nivalis Agglutinin) Protein Confers Aphids and Plutella xylostella Resistance in Arabidopsis and Cotton.

Cotton is a major fiber crop in the world that can be severely infested by pests in agricultural fields. Identifying new insect-resistance genes and increasing the expression of known insect-resistance genes are imperative in cultivated cotton. Galanthus nivalis agglutinin (GNA), a lectin that is toxic to both chewing and sucking pests, is mainly expressed in monocotyledons. It is necessary to improve the expression of the GNA protein and to test whether the lectin confers insect resistance to dicotyledons plants. We report a modified GNA gene (ASGNA) via codon optimization, its insertion into Arabidopsis thaliana, and transient expression in cotton to test its efficacy as an insect-resistance gene against cotton aphids and Plutella xylostella. The amount of ASGNA in transgenic plants reached approximately 6.5 µg/g of fresh weight. A feeding bioassay showed that the survival rate of aphids feeding on the leaves of ASGNA transgenic plants was lower than those of aphids feeding on the leaves of non-optimized GNA (NOGNA) transgenic plants and wild-type plants. Meanwhile, the fertility rate was 36% when fed on the ASGNA transgenic plants, while the fertility was 70% and 95% in NOGNA transgenic plants and wild-type plants. Correspondingly, the highest mortality of 55% was found in ASGNA transgenic lines, while only 35% and 20% mortality was observed in NOGNA transgenic plants and wild-type plants, respectively. Similar results were recorded for aphids feeding on cotton cotyledons with transient expression of ASGNA. Taken together, the results show that ASGNA exhibited high insecticidal activity towards sap-sucking insects and thus is a promising candidate gene for improving insect resistance in cotton and other dicotyledonous plants.