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Abstract Geological Culture Villages Towns (GCV(T)s) serve as rich repositories of geological resources, embodying significant historical and cultural values that mirror the dynamic interplay between Earth's evolution and human societies. Despite their importance, the theoretical underpinnings of GCV(T)s have not been thoroughly explored and elucidated. This study explores the relationship between geological culture and societal development, revealing the linkage between geological culture and societal advancement with the aim of promoting a harmonious coexistence between humanity and the environment. Focusing on 96 GCV(T)s in China, this study employs spatial analytical techniques such as the nearest-neighbor index, kernel density analysis, geographic connectivity, and geographic detector to scrutinize the spatial distribution patterns and identify key influencing factors. The findings reveal that (1) GCV(T)s exhibit uneven distribution, with concentrations in the Yangtze River Delta region, Beijing-Tianjin-Hebei region, and Shanxi-Gansu and Ningxia Provinces. (2) These sites tend to be situated in areas characterized by active geological formations, abundant geological relics, higher elevations, gentle topography, and ample rainfall. (3) The establishment and evolution of GCV(T)s are shaped by a complex interplay of geological heritage, natural factors, and human interventions. While the selection and spatial arrangement of these sites are predominantly influenced by geological and natural factors, the innovative development of their geological cultural heritage is driven by humanistic considerations. Overall, the distribution and evolution of GCV(T)s stem from multifaceted interactions among diverse factors. Recognizing this intricate web of influences is crucial for safeguarding geocultural diversity and formulating conservation strategies for geoheritage protection. The development of GCV(T)s transcends mere geoheritage preservation, it embodies a pivotal stride toward safeguarding the varied and multi-dimensional global geoheritage.

The study was conducted to determine the nutrient digestibility and digestible (DE) and metabolizable energy (ME) of 15 cereal processing by-products and to develop prediction equations for DE and ME based on the chemical composition in growing pigs. A total of 36 crossbred pigs were chosen and divided into three blocks according to a three 12 × 3 Youdin square experimental design. Twelve pigs in each block were allocated into six diets including a basal diet and five test diets. The feeding experiment included three periods, and each dietary treatment contained six replicates. Each period lasted 12 days, including 7 d of dietary adaption and 5 d of total feces and urine collection. The results showed that the coefficients of variation for EE, NDF, ADF, CP, and GE among 15 cereal processing by-products were 86.78%, 49.82%, 51.14%, 14.95%, and 6.26%, respectively. There were significant differences in DE, ME, and ME/DE (DM basis) among 15 cereal processing by-products (p < 0.05), ranging from 11.55 MJ/kg to 17.64 MJ/kg, from 10.90 MJ/kg to 17.40 MJ/kg, and from 89.41% to 98.63%, respectively. The digestibility of GE, DM, NDF, ADF, and CP showed a significant difference among 15 cereal processing by-products (p < 0.05). The DE and ME contents showed a negative correlation to NDF and ADF (p < 0.05), and the prediction equations for DE and ME (as-fed basis) were DE (MJ/kg) = −0.4597 × ADF (%) + 0.5988 × GE (MJ/kg) + 6.0138 (R2 = 0.74; p < 0.05) and ME (MJ/kg) = 1.0440 × DE (MJ/kg) − 1.1235 (R2 = 0.98; p < 0.05). On a DM basis, the optimal prediction equations for DE and ME were DE (MJ/kg DM) = −0.1451 × NDF (%) + 0.3026 × CP (%) + 13.8595 (R2 = 0.72; p < 0.05) and ME (MJ/kg DM) = 1.1155 × DE (MJ/kg DM) + 0.0363 × ADF (%) − 2.3412 (R2 = 0.99; p < 0.05). In conclusion, there were large variations in the chemical composition, nutrients digestibility, and available energy among the 15 different samples of cereal processing by-products. It is reasonable to develop prediction equations for DE and ME based on the chemical composition of cereal by-products for growing pigs.

Abstract In recent years, the survival and development of traditional villages in China have been serious challenges. Rural tourism is regarded as an important way to solve rural problems, and the combination of rural culture and tourism has become a new power point for rural development. Therefore, it is necessary to explore the spatial distribution structure between traditional villages and rural tourism. In this paper, rural tourism was represented by the rural tourism characteristic village (RTCV), and Henan Province, China, was taken as a study area to analyze the distribution pattern and spatial correlation of rural tourism and traditional village (TV) and discuss the relationship between the spatial correlation and regional natural environment and socioeconomic factors. The results show that the coupling of the spatial correlation between RTCVs and TVs in Henan was clear. They could be divided into 5 regions based on geographical factors. In addition, the research summarized 4 typical spatial structures between TVs and RTCVs in Henan based on the regional symbiosis theory, and the spatial pattern formation mechanism of TVs and RTCVs was discussed based on three driving mechanisms. The spatial structure of the two can provide reference value for other developing countries and regions to achieve sustainable rural development.

Abstract Background The recombination-activating gene 1 (RAG1) protein is essential for the V (variable)-D (diversity)-J (joining) recombination process. Mutations in RAG1 have been reported to be associated with several types of immune disorders. Typical clinical features driven by RAG1 variants include persistent infections, severe lymphopenia, and decreased immunoglobulin levels . Case presentation In this study, a 2-month-24-days-old infant with recurrent fever was admitted to our hospital with multiple infections and absence of T and B lymphocytes. The infant was diagnosed with severe combined immunodeficiency (SCID). A homozygous variation c.2147G>A (NM_000448.2: exonme2: c.2147G>A (p.Arg716Gln)) was identified in the RAG1 gene using whole-exome sequencing and Sanger sequencing. The predicted 3D structure of variant RAG1 indicated altered protein stability. Additionally, decreased expression of variant RAG1 gene was detected at both the mRNA and protein levels. Conclusions Our study identified a novel homozygous variant in RAG1 gene that causes SCID. This finding expands the variant spectrum of RAG1 in SCID and provides further evidence for the clinical diagnosis of SCID.

为了对山核桃油产品流转过程中的品质控制提供理论基础，探究山核桃油在贮藏期间的品质变化规律及其货架期预测方法。对在5、20、35 ℃下贮藏的山核桃油进行感官评定，测定其酸值、过氧化值，并进行动力学分析，应用Arrhenius方程进行拟合，建立货架期预测模型。结果表明：山核桃油感官品质与酸值、过氧化值呈极强的相关性，随着贮藏时间的延长和温度的升高，山核桃油感官品质下降，酸值和过氧化值升高，且温度越高酸值和过氧化值的变化速率越快，过氧化值变化速率小于酸值；酸值和过氧化值的变化规律均符合一级反应动力学模型，建立的山核桃油货架期预测模型准确率在±10%以内。山核桃油在贮藏期间品质下降，通过酸值、过氧化值可较为准确地对5～35 ℃条件下贮藏的山核桃油货架期进行预测。In order to provide a theroretical basis for the quality control of hickory oil products in the flow process, the quality change law of hickory oil during storage and the prediction model of shelf life were explored, the sensory quality, acid value and peroxide value of hickory oil during storage at 5, 20 ℃ and 35 ℃ were measured, the kinetic analysis was conducted，the Arrhenius equation was used for fitting, and the shelf life prediction model was established. The results showed that the sensory quality of hickory oil had a strong correlation with acid value and peroxide value. With the prolonging of storage time and the increase of temperature, the sensory quality of hickory oil decreased, and the acid value and peroxide value increased. The higher the temperature, the faster the change rates of acid value and peroxide value, and the change rate of the acid value was greater than that of the peroxide value. The change law of acid value and peroxide value conformed to the first-order reaction kinetic model. The prediction accuracy of the shelf life of hickory oil established by this method was within ±10%. The quality of hickory oil decreased during storage. It has good accuracy in predicting the shelf life of hickory oil between 5-35 ℃ through acid value and peroxide value.