This study focuses on understanding the behavior and activity patterns of the critically endangered Protobothrops mangshanensis in China in order to better provide scientific data for upcoming artificial breeding and propagation efforts. We conducted a long-term observation of 15 Mangshan pit vipers at different sites in Hunan Province during the summer and autumn of 2021. Our methods involved analyzing the influence of environmental factors such as temperature, relative humidity, and light condition on the snakes\' day and night activity and behaviors. The results revealed that the wild behaviors of Protobothrops mangshanensis include resting, sunbathing, crawling, and exploring, with distinct rhythms in their diel behavior. The snakes\' diel activity exhibits three peak periods which may be related to food activity and sunbathing. This study also highlights the complex interplay of environmental factors on the activity of Protobothrops mangshanensis. Relative humidity was identified as a critical factor accounting for the difference in activity between observation groups. There was little inter-individual variation among the 15 Protobothrops mangshanensis, even though these snakes used terrestrial and arboreal habitats under different environmental conditions. These findings enhance our understanding of Protobothrops mangshanensis behavior and provide a basis for effective conservation measures for this rare and critically endangered species.

Schizophrenia is one of the most disabling psychiatric disorders characterized by positive (hallucinations, delusions, formal thinking disorder) and negative symptoms (anhedonia, lack of speech and motivation). The present study aimed to identify the predictive factors of schizophrenia in adults, and potential differences in the environment of origin, sex, levels of occupational stress, intellectual level, marital status and age of onset of the disease depending on the severity of symptoms using analysis of data collected from 120 patients with a diagnosis of schizophrenia. The study was conducted at the \'Prof. Dr. Alexandru Obregia\' Clinical Psychiatric Hospital in Bucharest and included adult patients hospitalized between March 2018 and January 2021 diagnosed with schizophrenia and evaluated by general clinical examination, psychiatric, neurological and psychological evaluation. Results revealed that robust predictors of mild and moderate symptoms were affective symptoms, heredo-collateral history of schizophrenia, late onset, the presence of positive and negative symptoms, substance abuse, stress and marital status, unmarried, lower IQ and mental deficiency. For moderate-severe and severe symptoms, predictors were affective symptoms, heredo-collateral history of schizophrenia and affective disorders, substance abuse, stress, borderline IQ and mild mental deficiency. The present results can be used for further development of psychopharmacological management of schizophrenia.

Ecosystem stability arises from the interplay of species diversity, environmental conditions, and external disturbances. Understanding the structure of plant communities, interspecific relationships, and community stability in urban ecosystems is fundamental to ecological restoration and community development. This study utilized the karst city of Guiyang as a case study and employed the α diversity index, variance ratio method (VR), χ 2-test, Pearson correlation test, Spearman rank correlation test, M. Godron stability, and canonical correspondence analysis (CCA). The research focused on analyzing the species diversity, interspecific associations, community stability, and environmental factors of lithophytic moss at various elevations (989-1398 m). The findings revealed the presence of 58 species belonging to 27 genera and 13 families of lithophytic moss in the study area. Notably, the Brachytheciaceae and Pottiaceae emerged as dominant, exhibiting a broad ecological range and adaptation mechanisms, thereby playing a crucial role in the ecological environment of rocky desertification. The study observed that the highest species richness and dominance values of lithophytic moss were recorded at the N4 (1296-1398 m) elevation gradient, while the highest species diversity and uniformity values were observed at the N3 (1194-1295 m) elevation gradient, indicating a significant impact of altitude on lithobryophyte species diversity, particularly at middle and high altitudes. The analysis of interspecific associations and stability indicated a predominantly negative overall association within the lithophytic moss community, suggesting an early stage of succession, with weak interspecific associations and correlations among dominant pairs, tending towards relative independence. Only the communities at N2 (1092-1193 m) elevation exhibited stability, while the other communities were in an unstable stage, showing no significant correlation with species diversity. Furthermore, light intensity (182-129300 lux) exerted the greatest influence on community stability. Additionally, air humidity (36.5-52.3%) and altitude (998-1327 m) emerged as the primary environmental factors influencing community distribution, with a close and positive correlation between the two. These results hold significant reference value for promoting the succession and steady development of vegetation in rocky desertification areas and enhancing the conservation and restoration of vegetation community diversity in karst urban ecosystems.

Fine roots and absorptive roots play key roles in acquiring resources throughout soil profiles and determining plant functions along environmental gradients. Yet, the geographical pattern of carbon allocation in fine roots, particularly in absorptive roots, and their relations with plant sizes and evironment are less understood. We sampled 243 xerophytic shrubs from 63 species distributed along the latitudinal gradient (23°N to 32°N) in dry valleys of southwest China and synthetically measured biomass fractions of plant organs, especially fine roots and absorptive roots (1st to 3rd root order). We identified latitudinal patterns of biomass allocation fractions of organs and their relationships with plant sizes and environmental factors. The latitudinal patterns of both absorptive root and fine-root fractions followed weak unimodal distributions; stem biomass fraction increased with the latitude, while the leaf biomass fraction decreased. The fraction of fine-root biomass had negative relationships with plant height and root depth. The fractions of root, fine root, and absorptive root biomass were largely explained by soil moisture. Furthermore, fraction of fine-root biomass increased in a relatively humid environment. Overall, soil moisture was the most important factor in driving latitudinal patterns of biomass fraction. Our study highlighted that functional redistribution of root system biomass was the critical adaptive strategy along a latitudinal gradient.

Predicting soil heavy metal (SHM) content is crucial for understanding SHM pollution levels in urban residential areas and guide efforts to reduce pollution. However, current research indicates low SHM prediction accuracy in urban areas. Therefore, we employed a deep learning method (fully connected deep neural network) alongside four other methods (muti-layer perceptron, radial basis function neural network, multiple stepwise linear regression, and Kriging interpolation) to predict SHM content in the urban residential areas of Beijing and demonstrated the strength of deep learning in improving prediction accuracy. We found the contents of the evaluated heavy metals (Cd, Cu, Pb, and Zn) exhibited significant correlations with numerous other soil physicochemical properties and environmental factors. The prediction accuracy for Cu, Pb, and Zn contents was relatively high across different methods. Notably, deep learning showed considerable strength in predicting the contents of the four heavy metals, with the R2 for the test set of the model ranging from 0.75 to 0.91. Compared to other methods, deep learning achieved markedly higher prediction accuracy according to different accuracy evaluation indicators (e.g., deep learning showed increases in the cumulative R2 of the four heavy metals ranging from 53.16 % to 187.36 % compared to other methods). Our study indicates that deep learning can significantly improve SHM content prediction accuracy in urban areas and is highly applicable in urban residential areas with complex environmental influences.

OBJECTIVE: Celiac disease (CD) is a chronic autoimmune disorder caused by a complex interplay between genetic and environmental factors. The main goal of our case-control study was to analyse the association of environmental factors with the odds of CD development in a sample of the Slovak population.
METHODS: Data were collected from 1,226 respondents (534 CD patients and 692 controls) by a questionnaire. The impact of analysed parameters on the chance of disease development was assessed by multiple regression analysis and expressed as odds ratios (OR). Values of p < 0.05 were considered statistically significant.
RESULTS: In the patient group, celiac disease was significantly more prevalent in women than in men (OR = 1.52, p = 0.010). Respondents with a positive family history of CD showed 2.9-fold higher odds of CD compared to others (p < 0.001), and respondents with coexisting autoimmune diseases had 2.6-fold higher odds of CD (p < 0.001). Subjects who had taken antibiotics at least three times a year during childhood had 1.95-fold higher odds of developing CD compared to those who took them less frequently or not at all (p = 0.022). Conversely, individuals who were breastfed in infancy had lower odds of CD compared to non-breastfed respondents (OR = 0.53, p < 0.001). The mode of delivery (vaginal vs. caesarean section), overcoming severe infections, and the timing of gluten introduction in childhood did not show a statistically significant effect on the odds of developing CD.
CONCLUSIONS: Based on our data, being female, having a positive family history of CD, suffering from another autoimmune disease, and frequent use of antibiotics are factors associated with an increased chance of developing CD. On the other hand, breastfeeding in infancy seems to have a protective effect. Our findings highlight the importance of further research in understanding the complexities of this autoimmune condition and providing a foundation for prevention strategies.

To illuminate the temporal variations in the structure and functional groups of the root-associated fungal community associated with Mongolian pine Pinus sylvestris var. mongholica plantations in the Mu Us Sandy Land, P. sylvestris var. mongholica plantations with different stand ages （23, 33, and 44 a） were targeted. The community compositions and main drivers of root-associated fungi at different months and stand ages were identified using the Illumina high-throughput sequencing method. The results indicated that： ① There was a distinct temporal distribution in the root-associated fungal community, the sampling month had a significant effect on the diversity of root-associated fungi （P<0.05）, and the values were higher in May and July. The stand age had no significant effect on the diversity of root-associated fungi （P>0.05） and decreased gradually with increasing stand age. ② The dominant phylum of the root-associated fungal community was Ascomycota. The relative abundance of fungal function groups was different within each month and stand age, and the dominant groups were saprotroph-symbiotroph, undefined saprotroph, and ectomycorrhizal fungi. The indicator genera of ectomycorrhizal fungi in May, July, and September were Melanoleuca, Amphinema, and Tricholoma, respectively. ③ The temporal distribution of the root-associated fungal community was significantly affected by annual relative humidity, annual precipitation, soil porosity, ammonia nitrogen, annual sunshine duration, annual temperature, and soil water content （P<0.05）. Soil organic carbon content, soil porosity, annual precipitation, and annual relative humidity were the main factors that significantly affected the indicator genus of the root-associated fungal community. Our results demonstrated that the temporal distribution of the root-associated fungal community was shaped by climate and soil properties, whereas stand age contributed less. This improved information will provide a theoretical basis for the sustainable management of P. sylvestris var mongholica plantations.

Drought presents a significant abiotic stress that threatens crop productivity worldwide. Rhizosphere bacteria play pivotal roles in modulating plant growth and resilience to environmental stresses. Despite this, the extent to which rhizosphere bacteria are instrumental in plant responses to drought, and whether distinct cassava (Manihot esculenta Crantz) varieties harbor specific rhizosphere bacterial assemblages, remains unclear. In this study, we measured the growth and physiological characteristics, as well as the physical and chemical properties of the rhizosphere soil of drought-tolerant (SC124) and drought-sensitive (SC8) cassava varieties under conditions of both well-watered and drought stress. Employing 16S rDNA high-throughput sequencing, we analyzed the composition and dynamics of the rhizosphere bacterial community. Under drought stress, biomass, plant height, stem diameter, quantum efficiency of photosystem II (Fv/Fm), and soluble sugar of cassava decreased for both SC8 and SC124. The two varieties\' rhizosphere bacterial communities\' overall taxonomic structure was highly similar, but there were slight differences in relative abundance. SC124 mainly relied on Gamma-proteobacteria and Acidobacteriae in response to drought stress, and the abundance of this class was positively correlated with soil acid phosphatase. SC8 mainly relied on Actinobacteria in response to drought stress, and the abundance of this class was positively correlated with soil urease and soil saccharase. Overall, this study confirmed the key role of drought-induced rhizosphere bacteria in improving the adaptation of cassava to drought stress and clarified that this process is significantly related to variety.

Sophora alopecuroides L., a perennial herb in the arid and semi-arid regions of northwest China, has the ecological functions of windbreaking and sand fixation and high medicinal value. In recent years, global warming and human activities have led to changes in suitable habitats for S. alopecuroides, which may affect the accumulation of natural products. In this study, MaxEnt 3.4 and ArcGIS 10.4 software were used to predict the distribution of potentially suitable habitats for S. alopecuroides in China under climate change. Furthermore, the geographical distribution of S. alopecuroides as affected by human activities, the differences in the content of natural products of S. alopecuroides between different suitable habitats, and the correlation between natural products and environmental factors were analyzed. The results showed that suitable habitats for S. alopecuroides were projected to expand in the future, and the major environmental factors were temperature (Bio1), rainfall (Bio18), and soil pH (pH). When Bio1, Bio18, and pH were 8.4283 °C, 7.1968 mm, and 9.9331, respectively, the distribution probability (P) of S. alopecuroides was the highest. After adding a human activity factor, the accuracy of the model prediction results was improved, and the area of suitable habitats was greatly reduced, showing a fragmented pattern. Meanwhile, habitat suitability had a specific effect on the content of natural products in S. alopecuroides. Specifically, the content of natural products in S. alopecuroides in wild habitats was higher than that in artificial cultivation, and highly suitable habitats showed higher contents than those in non-highly suitable habitats. The contents of total alkaloids and total flavonoids were positively correlated with human activities and negatively correlated with land use types. Among them, total alkaloids were negatively correlated with aspect, and total flavonoids were positively correlated with aspect. In addition, it is suggested that Xinjiang should be the priority planting area for S. alopecuroides in China, and priority should be given to protection measures in the Alashan area. Overall, this study provides an important foundation for the determination of priority planting areas and resource protection for S. alopecuroides.

Gestational diabetes mellitus (GDM) has been found to be a common complication in pregnant women, known to escalate the risk of negative obstetric outcomes. In our study, we genotyped 1,566 Chinese pregnant women for two single nucleotide polymorphisms (SNPs) in the LINGO2 gene and one SNP in the GLIS3 gene, utilizing targeted next-generation sequencing. The impact of two interacting genes, and the interaction of genes with the environment─including exposure to particulate matter (PM2.5), ozone (O3), and variations in prepregnancy body mass index (BMI)─on the incidence of GDM were analyzed using logistic regression. Our findings identify the variants LINGO2 rs10968576 (P = 0.022, OR = 1.224) and rs1412239 (P = 0.018, OR = 1.231), as well as GLIS3 rs10814916 (P = 0.028, OR = 1.172), as risk mutations significantly linked to increased susceptibility to GDM. Further analysis underscores the crucial role of gene-gene and gene-environment interactions in the development of GDM among Chinese women (P < 0.05). Particularly, the individuals carrying the rs10968576 G-rs1412239 G-rs10814916 C haplotype exhibit increased susceptibility to GDM during the prepregnancy period when interacting with PM2.5, O3, and BMI (P = 8.004 × 10-7, OR = 1.206; P = 6.3264 × 10-11, OR = 1.280; P = 9.928 × 10-7, OR = 1.334, respectively). In conclusion, our research emphasizes the importance of the interaction between specific gene variations─LINGO2 and GLIS3─and environmental factors in influencing GDM risk. Notably, we found significant associations between these gene variations and GDM risk across various environmental exposure periods.