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Mitochondrial transcription factor A (TFAM) plays a crucial role in mitochondrial fission beyond its canonical function in mtDNA maintenance. However, how TFAM regulates mitochondrial fission remains only partially understood. Fluorescence microscopy and TEM analyses showed that TFAM knockdown inhibited mitochondrial fission, whereas TFAM overexpression promoted mitochondrial fragmentation, and this mitochondrial morphology phenotype was supported by TEM-based ultrastructural observations in zebrafish embryos with tfam disruption. Depletion of Drp1 and MFF in TFAM-overexpressing cells led to elongated mitochondria, indicating that TFAM promotes Drp1- and MFF-dependent mitochondrial fission, which was further supported by the inhibitory effects of Mdivi-1 (Drp1 inhibitor) and Compound C (AMPK inhibitor) on TFAM-induced mitochondrial fission. Western blot and immunofluorescence analyses revealed that TFAM overexpression enhanced the mitochondrial localization and Sirt3-dependent mitochondrial protein deacetylation of Sirtuin 3 (Sirt3), increased phosphorylation of AMPK and MFF, and promoted mitochondrial recruitment of phosphorylated Drp1. Proteinase K protection and cycloheximide chase assays further supported intramitochondrial localization of Sirt3 and increased stability of mitochondrial Sirt3 upon TFAM overexpression. FRET imaging and co-immunoprecipitation demonstrated a direct TFAM-Sirt3 interaction mediated by TFAM’s HMG-box A domain. Targeted mutagenesis or deletion of the HMG-box A domain disrupted the TFAM-Sirt3 interaction, impaired Sirt3 mitochondrial localization and Sirt3-dependent mitochondrial protein deacetylation, and abolished TFAM-mediated mitochondrial fission. Analysis of TCGA data showed that high TFAM-SIRT3 co-expression is associated with overall survival across cancers, particularly in Kidney Renal Clear Cell Carcinoma (KIRC), where TFAM is downregulated (whereas SIRT3 is not). Together, these findings demonstrate that TFAM promotes mitochondrial fission via direct interaction with Sirt3, thereby activating the AMPK/MFF/Drp1 pathway.

The degradation of sandy land in Inner Mongolia presents a substantial threat to regional ecological security and the sustainable development of agriculture and animal husbandry. Planting alfalfa serves as a crucial recovery strategy; however, the inadequate capacity to retain water and nutrients impedes this process. The current reliance on a singular microbial remediation method has demonstrated limited effectiveness in addressing the challenges posed by sandy soil. While traditional sand-fixing agents can improve soil nutrients, they lack biological activity. Furthermore, the synergistic mechanisms between these approaches and their ecological impacts within a single season remain poorly understood. This study involved a pot experiment utilizing wind-sand soil as the substrate to evaluate the soil physicochemical properties, enzyme activities, and microbial community structure associated with the stress resistance of alfalfa. The results indicated that the medium concentration of sand-fixing agent (1:75) exhibited optimal water retention performance, thereby creating a conducive growth microenvironment for Trichoderma longibrachiatum and mitigating fluctuations in surface temperature and humidity. The combined treatment significantly improved the alpha diversity of soil microorganisms, thereby improving the stability and stress resistance of the system. Through the synergistic approach of “sand fixation and water retention–nutrient activation–improved stress resistance”, the microenvironment of sandy land was effectively improved, promoting alfalfa growth. This method offers “environmentally friendly and synergistic” technical support for the efficient cultivation and ecological restoration of alfalfa in sandy regions, while also contributing to the high-quality development of grassland animal husbandry.

With the random discharging of industrial and agricultural wastewater, a large amount of cadmium (Cd) has accumulated in the soil, which seriously affects the growth of crops and people’s food safety. In this study, alfalfa was used as the material for studying the effects of the inoculation of Piriformospora indica (P. indica) on photosynthesis, osmoregulatory substances, and antioxidant enzymes of alfalfa seedlings at different Cd concentrations (0, 5, 10, 30, 50, and 100 mg/L) through hydroponic experiments. The results showed that with the increase in Cd concentration, the chlorophyll content, net photosynthetic rate (Pn), transpiration rate (Tr), and stomatal conductance (Gs) of alfalfa all decreased gradually, while the intercellular CO2 concentration (Ci) decreased at first and then increased. However, compared with non-inoculated control plants, the inoculation of P. indica improved the photosynthesis (41.97%) of alfalfa under Cd stress, increased the chlorophyll content (43.70%), and significantly increased the contents of proline (29.86%), soluble proteins (38.54%), and antioxidant enzyme activities. It was concluded that P. indica alleviates the negative effects of Cd on alfalfa plants to some extent. This is because P. indica can resist Cd stress and improve plant growth in cadmium-contaminated agricultural soil by alleviating membrane peroxidation damage, regulating osmotic regulatory substances, and enhancing enzyme activity to improve the antioxidant defense system. Thus, P. indica can be considered a biological fertilizer for improving plant growth and physiology in soils contaminated with cadmium.

A large-scale re-vegetation supported by the Grain for Green Project (GGP) has greatly changed local eco-hydrological systems, with an impact on soil moisture conditions for the Chinese Loess Plateau. It is important to know how, exactly, re-vegetation influences soil moisture conditions, which not only crucially constrain growth and distribution of vegetation, and hence, further re-vegetation, but also determine the degree of soil desiccation and, thus, erosion risk in the region. In this study, three eco-environmental factors, which are Soil Water Index (SWI), the Normalized Difference Vegetation Index (NDVI), and precipitation, were used to investigate the response of soil moisture in the one-meter layer of top soil to the re-vegetation during the GGP. SWI was estimated based on the backscatter coefficient produced by the European Remote Sensing Satellite (ERS-1/2) and Meteorological Operational satellite program (MetOp), while NDVI was derived from SPOT imageries. Two separate periods, which are 1998–2000 and 2008–2010, were selected to examine the spatiotemporal pattern of the chosen eco-environmental factors. It has been shown that the amount of precipitation in 1998–2000 was close to that of 2008–2010 (the difference being 13.10 mm). From 1998–2000 to 2008–2010, the average annual NDVI increased for 80.99%, while the SWI decreased for 72.64% of the area on the Loess Plateau. The average NDVI over the Loess Plateau increased rapidly by 17.76% after the 10-year GGP project. However, the average SWI decreased by 4.37% for two-thirds of the area. More specifically, 57.65% of the area on the Loess Plateau experienced an increased NDVI and decreased SWI, 23.34% of the area had an increased NDVI and SWI. NDVI and SWI decreased simultaneously for 14.99% of the area, and the decreased NDVI and increased SWI occurred at the same time for 4.02% of the area. These results indicate that re-vegetation, human activities, and climate change have impacts on soil moisture. However, re-vegetation, which consumes a large quantity of soil water, may be the major factor for soil moisture change in most areas of the Loess Plateau. It is, therefore, suggested that Soil Moisture Content (SMC) should be kept in mind when carrying out re-vegetation in China’s arid and semi-arid regions.

Remote sensing phenology retrieval can remedy the deficiencies in field investigations and has the advantage of catching the continuous characteristics of phenology on a large scale. However, there are some discrepancies in the results of remote sensing phenological metrics derived from different vegetation indices based on different extraction algorithms, and there are few studies that evaluate the impact of different vegetation indices on phenological metrics extraction. In this study, three satellite-derived vegetation indices (enhanced vegetation index, EVI; normalized difference vegetation index, NDVI; and normalized difference phenology index, NDPI; calculated using surface reflectance data from MOD09A1) and two algorithms were used to detect the start and end of growing season (SOS and EOS, respectively) in the Tibetan Plateau (TP). Then, the retrieved SOS and EOS were evaluated from different aspects. Results showed that the missing rates of both SOS and EOS based on the Seasonal Trend Decomposition by LOESS (STL) trendline crossing method were higher than those based on the seasonal amplitude method (SA), and the missing rate varied using different vegetation indices among different vegetation types. Also, the temporal and spatial stabilities of phenological metrics based on SA using EVI or NDPI were more stable than those from others. The accuracy assessment based on ground observations showed that phenological metrics based on SA had better agreements with ground observations than those based on STL, and EVI or NDVI may be more appropriate for monitoring SOS than NDPI in the TP, while EOS from NDPI had better agreements with ground-observed EOS. Besides, the phenological metrics over the complex terrain also presented worse performances than those over the flat terrain. Our findings suggest that previous results of inter-annual variability of phenology from a single data or method should be treated with caution.

Background This study addresses the degradation of shrub ecosystems and emphasizes the essential role that shrubs play within ecological systems. The use of advanced technological methods to swiftly and accurately capture information on shrub disturbance is crucial for preserving ecological security. Methods Utilizing the LandTrendr temporal segmentation algorithm on the Google Earth Engine cloud platform, and grounded in land cover data, we conducted dynamic monitoring of shrubland change across the Qinghai–Tibet Plateau from 1990 to 2022. Results From 1990 to 2022, the cumulative total area of shrub disturbance in the Qinghai–Tibet Plateau amounted to 372.23 km2, primarily concentrated in the eastern and southeastern regions, with an overall decreasing trend observed. The duration of shrub disturbance was predominantly concentrated within a 1–2‐year period, covering approximately 80.43% of the total disturbed area. Pixel‐scale validation indicated an overall accuracy of 95.71%, with a Kappa coefficient of 0.93. User's accuracy for each year surpassed 73.82% and producer's accuracy was above 70.08%. Shrub disturbance on the Tibetan Plateau is mainly concentrated in areas with an altitude of 2000–4000 m, a slope gradient of 15°−40°, and a shady slope aspect. Shrub disturbance shows a moderately significant negative correlation with temperature (r = −0.436, p < 0.05) and a weakly significant positive correlation with precipitation (r = 0.124, p < 0.05), respectively. Conclusions Incorporating contextual data, the study identified climate, and topography as primary factors driving shrub disturbance. This study offers valuable scientific evidence and methodological references for monitoring large‐scale shrub dynamics. This study utilized the LandTrendr algorithm to monitor shrub disturbances on the Qinghai‐Tibet Plateau from 1990 to 2022. The findings indicate that climate, topography, and grazing are the primary drivers of shrub disturbances, providing valuable scientific evidence for ecological monitoring.

This paper proposes a spatiotemporal fusion-based evapotranspiration inversion model (OL-SS) for grassland areas on the GEE platform. The model uses the OL processing strategy, with Landsat imagery being used as fine-resolution images and MCD43A4 imagery as coarse-resolution images, combined with GEE’s spatiotemporal fusion technology to generate 30 m resolution images. It then estimates the daily evapotranspiration of grasslands using the constant evaporation ratio method. The model was validated in the Xilin Gol League, Inner Mongolia, for grassland evapotranspiration inversion during the summer of 2015. The results show the following: 1. the OL-SS model can efficiently generate good spatiotemporal fusion results, but the fusion effect is poorer in some images due to cloud cover; 2. compared with the measured data from flux stations in grassland areas, the evapotranspiration inversion results show a good fit. The model demonstrates strong performance in grassland evapotranspiration monitoring and is suitable for the rapid estimation of daily evapotranspiration in certain grassland regions.

With the random discharging of industrial and agricultural wastewater, a large amount of cadmium (Cd) has accumulated in the soil, which seriously affects the growth of crops and people's food safety. In this study, alfalfa was used as the material for studying the effects of the inoculation of Piriformospora indica (P. indica) on photosynthesis, osmoregulatory substances, and antioxidant enzymes of alfalfa seedlings at different Cd concentrations (0, 5, 10, 30, 50, and 100 mg/L) through hydroponic experiments. The results showed that with the increase in Cd concentration, the chlorophyll content, net photosynthetic rate (Pn), transpiration rate (Tr), and stomatal conductance (Gs) of alfalfa all decreased gradually, while the intercellular CO[sub.2] concentration (Ci) decreased at first and then increased. However, compared with non-inoculated control plants, the inoculation of P. indica improved the photosynthesis (41.97%) of alfalfa under Cd stress, increased the chlorophyll content (43.70%), and significantly increased the contents of proline (29.86%), soluble proteins (38.54%), and antioxidant enzyme activities. It was concluded that P. indica alleviates the negative effects of Cd on alfalfa plants to some extent. This is because P. indica can resist Cd stress and improve plant growth in cadmium-contaminated agricultural soil by alleviating membrane peroxidation damage, regulating osmotic regulatory substances, and enhancing enzyme activity to improve the antioxidant defense system. Thus, P. indica can be considered a biological fertilizer for improving plant growth and physiology in soils contaminated with cadmium.

Herein, we present a phosphorescent cationized cellulose derivative by simply introducing ionic structures, including cyanomethylimidazolium cations and chloride anions, into cellulose chains. The imidazolium cations with the cyano group and nitrogen element promote intersystem crossing. The cyano-containing cations, chloride anions and hydroxyl groups of cellulose form multiple hydrogen bonding interactions and electrostatic attraction interactions, effectively inhibiting the non-radiative transitions. The resultant cellulose-based RTP material is easily processed into phosphorescent films, fibers, coatings and patterns by using eco-friendly aqueous solution processing strategies. Furthermore, after we construct a cross-linking structure by adding a small amount of glutaraldehyde as the cross-linking agent, the as-fabricated phosphorescent patterns exhibit excellent antibacterial properties and water resistance. Therefore, considering the outstanding biodegradability and sustainability of cellulose materials, cellulose-based easy-to-process RTP materials can act as antibacterial, water-resistant, and eco-friendly phosphorescent patterns, coatings and bulk materials, which have enormous potential in advanced anti-counterfeiting, information encryption, disposable smart labels, etc. Organic room-temperature phosphorescence (RTP) materials often suffer from poor processability because of their crystalline or cross-linked nature. Here, the authors demonstrate phosphorescence in a processable cellulose derivative by introducing cationic groups such as imidazolium cations which are able to promote intersystem crossing and to form hydrogen bonds, inhibiting non-radiative transitions.

Background In the string correction problem, we are to transform one string into another using a set of prescribed edit operations. In string correction using the Damerau-Levenshtein (DL) distance, the permissible edit operations are: substitution, insertion, deletion and transposition. Several algorithms for string correction using the DL distance have been proposed. The fastest and most space efficient of these algorithms is due to Lowrance and Wagner. It computes the DL distance between strings of length m and n , respectively, in O ( m n ) time and O ( m n ) space. In this paper, we focus on the development of algorithms whose asymptotic space complexity is less and whose actual runtime and energy consumption are less than those of the algorithm of Lowrance and Wagner. Results We develop space- and cache-efficient algorithms to compute the Damerau-Levenshtein (DL) distance between two strings as well as to find a sequence of edit operations of length equal to the DL distance. Our algorithms require O ( s min{ m , n }+ m + n ) space, where s is the size of the alphabet and m and n are, respectively, the lengths of the two strings. Previously known algorithms require O ( m n ) space. The space- and cache-efficient algorithms of this paper are demonstrated, experimentally, to be superior to earlier algorithms for the DL distance problem on time, space, and enery metrics using three different computational platforms. Conclusion Our benchmarking shows that, our algorithms are able to handle much larger sequences than earlier algorithms due to the reduction in space requirements. On a single core, we are able to compute the DL distance and an optimal edit sequence faster than known algorithms by as much as 73.1% and 63.5%, respectively. Further, we reduce energy consumption by as much as 68.5%. Multicore versions of our algorithms achieve a speedup of 23.2 on 24 cores.