DeepICSH: a complex deep learning framework for identifying cell-specific silencers and their strength from the human genome.

Silencers are noncoding DNA sequence fragments located on the genome that suppress gene expression. The variation of silencers in specific cells is closely related to gene expression and cancer development. Computational approaches that exclusively rely on DNA sequence information for silencer identification fail to account for the cell specificity of silencers, resulting in diminished accuracy. Despite the discovery of several transcription factors and epigenetic modifications associated with silencers on the genome, there is still no definitive biological signal or combination thereof to fully characterize silencers, posing challenges in selecting suitable biological signals for their identification. Therefore, we propose a sophisticated deep learning framework called DeepICSH, which is based on multiple biological data sources. Specifically, DeepICSH leverages a deep convolutional neural network to automatically capture biologically relevant signal combinations strongly associated with silencers, originating from a diverse array of biological signals. Furthermore, the utilization of attention mechanisms facilitates the scoring and visualization of these signal combinations, whereas the employment of skip connections facilitates the fusion of multilevel sequence features and signal combinations, thereby empowering the accurate identification of silencers within specific cells. Extensive experiments on HepG2 and K562 cell line data sets demonstrate that DeepICSH outperforms state-of-the-art methods in silencer identification. Notably, we introduce for the first time a deep learning framework based on multi-omics data for classifying strong and weak silencers, achieving favorable performance. In conclusion, DeepICSH shows great promise for advancing the study and analysis of silencers in complex diseases. The source code is available at https://github.com/lyli1013/DeepICSH.

DeepITEH: a deep learning framework for identifying tissue-specific eRNAs from the human genome.

MOTIVATION: Enhancers are vital cis-regulatory elements that regulate gene expression. Enhancer RNAs (eRNAs), a type of long noncoding RNAs, are transcribed from enhancer regions in the genome. The tissue-specific expression of eRNAs is crucial in the regulation of gene expression and cancer development. The methods that identify eRNAs based solely on genomic sequence data have high error rates because they do not account for tissue specificity. Specific histone modifications associated with eRNAs offer valuable information for their identification. However, identification of eRNAs using histone modification data requires the use of both RNA-seq and histone modification data. Unfortunately, many public datasets contain only one of these components, which impedes the accurate identification of eRNAs. RESULTS: We introduce DeepITEH, a deep learning framework that leverages RNA-seq data and histone modification data from multiple samples of the same tissue to enhance the accuracy of identifying eRNAs. Specifically, deepITEH initially categorizes eRNAs into two classes, namely, regularly expressed eRNAs and accidental eRNAs, using histone modification data from multiple samples of the same tissue. Thereafter, it integrates both sequence and histone modification features to identify eRNAs in specific tissues. To evaluate the performance of DeepITEH, we compared it with four existing state-of-the-art enhancer prediction methods, SeqPose, iEnhancer-RD, LSTMAtt, and FRL, on four normal tissues and four cancer tissues. Remarkably, seven of these tissues demonstrated a substantially improved specific eRNA prediction performance with DeepITEH, when compared with other methods. Our findings suggest that DeepITEH can effectively predict potential eRNAs on the human genome, providing insights for studying the eRNA function in cancer. AVAILABILITY AND IMPLEMENTATION: The source code and dataset of DeepITEH have been uploaded to https://github.com/lyli1013/DeepITEH.

Long noncoding RNAs in human reproductive processes and diseases.

Infertility has become a global disease burden. Although assisted reproductive technologies are widely used, the assisted reproduction birth rate is no more than 30% worldwide. Therefore, understanding the mechanisms of reproduction can provide new strategies to improve live birth rates and clinical outcomes of enhanced implantation. Long noncoding RNAs (lncRNAs) have been reported to exert regulatory roles in various biological processes and diseases in many species. In this review, we especially focus on the role of lncRNAs in human reproduction. We summarize the function and mechanisms of lncRNAs in processes vital to reproduction, such as spermatogenesis and maturation, sperm motility and morphology, follicle development and maturation, embryo development and implantation. Then, we highlight the importance and diverse potential of lncRNAs as good diagnostic molecular biomarkers and therapeutic targets for infertility treatment.

Spatial-temporal dynamics and time series prediction of HFRS in mainland China: A long-term retrospective study.

Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China. The current study aims to characterize the spatial-temporal dynamics of HFRS in mainland China during a long-term period (1950-2018). A total of 1 665 431 cases of HFRS were reported with an average annual incidence of 54.22 cases/100 000 individuals during 1950-2018. The joint regression model was used to define the global trend of the HFRS cases with an increasing-decreasing-slightly increasing-decreasing-slightly increasing trend during the 68 years. Then spatial correlation analysis and wavelet cluster analysis were used to identify four types of clusters of HFRS cases located in central and northeastern China. Lastly, the prophet model outperforms auto-regressive integrated moving average model in the HFRS modeling. Our findings will help reduce the knowledge gap on the transmission dynamics and distribution patterns of the HFRS in mainland China and facilitate to take effective preventive and control measures for the high-risk epidemic area.

A mathematical model to simulate the release of Fe and Mn from sediments in a drinking water reservoir.

Fe and Mn release from sediments promotes the release of other chemicals and jointly affects downstream water safety, especially in drinking water reservoirs. Quantitative research on release processes and flux estimation methods for endogenous Fe and Mn in reservoirs is still limited. Static incubation experiments were designed to systematically explore the effects of water temperature (WT), dissolved oxygen (DO), pH, carbon sources, and microbial activity on Fe and Mn release. The results showed that increased WT and carbon source addition promoted the release of acid-extractable Fe and Mn from the sediments; hypoxia and acidification promoted the dissolution of reducible sediment Fe and Mn; and microorganisms participated in the cycling of Fe and Mn. Based on the experimental results, first-order kinetic equations for sediment Fe and Mn release to overlying water were proposed, and the relationships between release rate and environmental factors were mathematically represented by a surface equation (R2 = 0.88 and 0.86, respectively). A diffusion gradients in thin films (DGT) device based on the diffusion model was used in situ to obtain the diffusion fluxes of Fe (JFe = 13.93 mg m-2 d-1) and Mn (JMn = 3.48 mg m-2 d-1). When environmental factors obtained in the field were introduced into the established mathematical model, the modeled release fluxes of Fe and Mn were RFe = 20.92 mg m-2 d-1 and RMn = 13.12 mg m-2 d-1, respectively. The established model filled gaps in the diffusion model, which does not account for differences in release fluxes under changing physicochemical water conditions. This work serves as a reference for studying the release fluxes of endogenous chemicals in sediments.

Response of OC, TN, and TP deposition mediated by aquatic photosynthetic community structures in shallow karst surface waters under different land uses.

Land use change alters the hydrochemical features, nutrient outputs, and community structure of aquatic photosynthetic organisms in watersheds and has an important impact on C, N, and P biogeochemical processes. In shallow water environments, sediments are the most important burial sites for C, N, and P; however, the factors underlying the control of their deposition by land use changes remain unclear. In this study, the relationship among hydrochemical features, aquatic photosynthetic organism community structure, and C, N, and P deposition in surface waters associated with different land uses was studied at the Shawan Karst Water-Carbon Cycle Test Site, Puding, SW China, by combining field monitoring and laboratory experiments performed over a complete hydrological year from September 2018 to August 2019. The results indicate that (1) OC and TN deposition showed small differences among ponds associated with five land uses, while TP was significantly higher in ponds associated with shrubland and grassland than in ponds of cultivated land, bare soil, and bare rock. (2) Cultivated land increased OC and TN deposition by increasing N and P output and planktonic algae biomass in surface waters, while grassland and shrubland ponds mainly by increasing DIC output and macrophyte biomass. (3) Compared with cultivated land, grassland and shrubland significantly enhanced TP deposition by promoting the deposition of calcium-bound P and biogenic P from macrophytes and their epiphytic algae in surface waters. In conclusion, the shift of cultivated land and bare soil to grassland and shrubland may be conducive to the formation of benign aquatic ecosystems and stabilization of C, N, and P sinks in karst shallow surface waters.

The association between air pollutants, meteorological factors and tuberculosis cases in Beijing, China: A seven-year time series study.

BACKGROUND: Tuberculosis (TB) is a severe public health problem globally. Previous studies have revealed insufficient and inconsistent associations between air pollutants, meteorological factors and TB cases. Yet few studies have examined the associations between air pollutants, meteorological factors and TB cases in Beijing. OBJECTIVE: The purpose of this study was to explore the impact of air pollutants and meteorological factors on TB in Beijing, and to provide novel insights into public health managers to formulate control strategies of TB. METHODS: Data on the daily case of TB in Beijing during 2014-2020 were obtained from Chinese tuberculosis information management system. Concurrent data on the daily PM10, PM2.5, SO2, NO2, CO and O3, were obtained from the online publication platform of the Chinese National Environmental Monitoring Center. Daily average temperature, average wind speed, relative humidity, sunshine duration and total precipitation were collected from the China Meteorological Science Data Sharing Service System. A distributed lag non-linear model was fitted to identify the non-linear exposure-response relationship and the lag effects between air pollutions, meteorological factors and TB cases in Beijing. RESULTS: In the single-factor model, the excess risk (ER) of TB was significantly positively associated with every 10 µg/m3 increase in NO2 in lag 1 week (ER: 1.3%; 95% confidence interval [CI]: 0.4%, 2.3%) and every 0.1 m/s increase in average wind speed in lag 5 weeks (ER: 0.3%; 95% CI: 0.1%, 0.5%), and was negatively associated with every 10 µg/m3 increase in O3 in lag 1 week (ER: -1.2%; 95% CI: -1.8%, -0.5%), every 5 °C increase in average temperature (ER: -1.7%; 95% CI: -2.9%, -0.4%) and every 10% increase in average relative humidity (ER: -0.4%; 95% CI: -0.8%, -0.1%) in lag 10 weeks, respectively. In the multi-factor model, the lag effects between TB cases and air pollutants, meteorological factors were similar. The subgroup analysis suggests that the effects of NO2, O3, average wind speed and relative humidity on TB were greater in male or labor age subgroup, while the effect of CO was greater in the elderly. In addition, no significant associations were found between PM2.5, SO2, sunshine duration and TB cases. CONCLUSION: Our findings provide a better understanding of air pollutants and meteorological factors driving tuberculosis occurrence in Beijing, which enhances the capacity of public health manager to target early warning and disease control policy-making.

Characterization of the long noncoding RNA transcriptome in human preimplantation embryo development.

PURPOSE: Infertility remains a human health burden globally. Only a fraction of embryos produced via assisted reproductive technologies (ARTs) develop to the blastocyst stage in vitro. lncRNA abundance changes significantly during human early embryonic development, indicating vital regulatory roles of lncRNAs in this process. The aim of this study is to obtain insights into the transcriptional basis of developmental events. METHODS: scRNA-seq data and SUPeR-seq data were used to investigate the lncRNA profiles of human preimplantation embryos. The top 50 highly expressed unique and shared lncRNAs in each stage of preimplantation development were identified. Comparative analysis of the two datasets was used to verify the consistent expression patterns of the lncRNAs. Differentially expressed lncRNAs were identified and subjected to functional enrichment analysis. RESULTS: The lncRNA profiles of human preimplantation embryos in the E-MTAB-3929 dataset were similar to those in the GSE71318 dataset. The ratios of overlap among the top 50 highly expressed lncRNAs between two pairs of stages (2-cell stage vs. 4-cell stage and 8-cell stage vs. morula) were aberrantly low compared with those between other stages. Each stage of preimplantation development exhibited unique and shared lncRNAs among the top 50 highly expressed lncRNAs. Among the between-group comparisons, the 2-cell stage vs. 4-cell stage showed the highest number of differentially expressed lncRNAs. Functional enrichment analysis revealed that differentially expressed lncRNAs and their associated super enhancers and RNA binding proteins (RBPs) are closely involved in regulating embryonic development. These lncRNAs could function as important cell markers for distinguishing fetal germ cells. CONCLUSIONS: Our study paves the way for understanding the regulation of developmental events, which might be beneficial for improved reproductive outcomes.

Research on the purification enhancement of ecological ponds: Integrating water cycle optimization and plants layout.

The hydrodynamic conditions of ponds are generally poor, which seriously affects the long-term water quality guarantee. In this research, the numerical simulation method was used to establish an integrated model of hydrodynamics and water quality for the simulation of the plant purification effect in ponds. Based on the flushing time using the tracer method, the purification rate of plants was introduced to consider the purification effect of plants on water quality. In-situ monitoring was carried out at the Luxihe pond in Chengdu, and the model parameters such as the purification rate of typical plants were calibrated. The degradation coefficient of NH3-N in the non-vegetated area was 0.014 d-1 in August and 0.010 d-1 in November. In areas with vegetation, the purification rate of NH3-N was 0.10-0.20 g/(m2·d) in August and 0.06-0.12 g/(m2·d) in November. The comparison of the results in August and November showed that due to the higher temperature in August, the plant growth effect was better, and the degradation rate of pollutants and the purification rate of pollutants by plants were higher. The flushing time distribution of the proposed Baihedao pond under the conditions of terrain reconstruction, water replenishment, and plant layout was simulated, and the frequency distribution curve of flushing time was used to evaluate the results. Terrain reconstruction and water replenishment can significantly improve the water exchange capacity of ponds. The reasonable planting of plants can reduce the variability of the water exchange capacity. Based on this combined with the purification effect of plants on NH3-N, the layout plan of Canna, Cattails, and Thalia in ponds was proposed.

Field investigation on the change process of microbial community structure in large-deep reservoir during the initial impoundment.

During the initial impoundment of large-deep reservoir, the aquatic environment changed dramatically in various aspects such as water level, hydrological regime, and pollutants, which could alter microorganisms' community structure, break the balance of the aquatic ecosystem and even endanger the aquatic ecosystem. However, the interaction of microbial communities and water environment during the initial impoundment process of a large-deep reservoir remained unclear. To this end, in-situ monitoring and sampling analysis on water quality and microbial communities during the initial impoundment process of a typical large-deep reservoir named Baihetan were conducted so as to explore the response of microbial community structure to the changes of water environmental factors during the initial impoundment of large deep reservoir and reveal the key driving factors affecting microbial community structure. The spatio-temporal variation in water quality was analyzed, and the microbial community structure in the reservoir was investigated based on high-throughput sequencing. The results showed that the COD of each section increased slightly, and the water quality after impoundment was slightly poorer than that before the impoundment. Water temperature and pH were proved to be the key factors affecting the structure of bacterial and eukaryotic communities respectively during the initial impoundment. The research results revealed the role of microorganisms and their interaction with biogeochemical processes in the large-deep reservoir ecosystem, which was crucial for later operation and management of the reservoir and the protection of the reservoir water environment.

Alleviating eutrophication by reducing the abundance of Cyanophyta due to dissolved inorganic carbon fertilization: Insights from Erhai Lake, China.

The eutrophication of lakes is a global environmental problem. Regulating nitrogen (N) and phosphorus (P) on phytoplankton is considered to be the most important basis of lake eutrophication management. Therefore, the effects of dissolved inorganic carbon (DIC) on phytoplankton and its role in mitigating lake eutrophication have often been overlooked. In this study, the relationships between phytoplankton and DIC concentrations, carbon isotopic composition, nutrients (N and P), and hydrochemistry in the Erhai Lake (a karst lake) were investigated. The results showed that when the dissolved carbon dioxide (CO2(aq)) concentrations in the water were higher than 15 µmol/L, the productivity of phytoplankton was controlled by the concentrations of TP and TN, especially by that of TP. When the N and P were sufficient and the CO2(aq) concentrations were lower than 15 µmol/L, the phytoplankton productivity was controlled by the concentrations of TP and DIC, especially by that of DIC. Additionally, DIC significantly affected the composition of the phytoplankton community in the lake (p<0.05). When the CO2(aq) concentrations were higher than 15 µmol/L, the relative abundance of Bacillariophyta and Chlorophyta was much higher than those of harmful Cyanophyta. Thus, high concentrations of CO2(aq) can inhibit harmful Cyanophyta blooms. During lake eutrophication, when controlling N and P, an appropriate increase in CO2(aq) concentrations by land-use changes or pumping of industrial CO2 into water may reduce the proportion of harmful Cyanophyta and promote the growth of Chlorophyta and Bacillariophyta, which may provide effectively assist in mitigating water quality deterioration in surface waters.

Exertional rhabdomyolysis in newly enrolled cadets of a military academy.

INTRODUCTION/AIMS: Exertional rhabdomyolysis (ER) often occurs during prolonged intense exercise in hot environments, posing a threat to the health of military personnel. In this study we aimed to investigate possible risk factors for ER and provide further empirical data for prevention and clinical treatment strategies. METHODS: A retrospective investigation of 116 concurrent ER cases was conducted. Conditional logistic regression analyses were performed to assess the association between each potential risk (or protective) factor and ER. The clinical characteristics of the 71 hospitalized patients were analyzed descriptively. RESULTS: After screening, the following variables significantly increased the risk of ER: shorter length of service (recruits; odds ratios [OR], 7.49; 95% confidence interval [CI], 2.58-21.75); higher body mass index (BMI; OR, 1.14, 95% CI, 1.03-1.26); lack of physical exercise in the last half year (less than once per month; OR, 3.20; 95% CI, 1.08-9.44); and previous heat injury (OR, 2.94; 95% CI, 1.26-6.89). Frequent fruit consumption (OR, 0.57; 95% CI, 0.33-0.99), active hydration habit (OR, 0.37; 95% CI, 0.20-0.67), water replenishment of more than 2 L on the training day (OR, 0.15; 95% CI, 0.05-0.45), and water replenishment of at least 500 mL within 1 hour before training (OR, 0.33; 95% CI, 0.12-0.88) significantly decreased the risk of ER. Of the 71 hospitalized patients, 41 (57.7%) were diagnosed with hypokalemia on admission. DISCUSSION: In military training, emphasis should be placed on incremental adaptation training before more intense training, and close attention should be given to overweight and previously sedentary recruits. Fluid replenishment before exercise, increased fruit intake, and proper potassium supplementation may help prevent ER.

Longitudinal clinical trajectory analysis of individuals before and after diagnosis of Type 2 Diabetes Mellitus (T2DM) indicates that vascular problems start early.

INTRODUCTION: Type 2 diabetes mellitus (T2DM) frequently associates with increasing multi-morbidity/treatment complexity. Some headway has been made to identify genetic and non-genetic risk factors for T2DM. However, longitudinal clinical histories of individuals both before and after diagnosis of T2DM are likely to provide additional insight into both diabetes aetiology/further complex trajectory of multi-morbidity. METHODS: This study utilised diabetes patients/controls enrolled in the DARE (Diabetes Alliance for Research in England) study where pre- and post-T2DM diagnosis longitudinal data was available for trajectory analysis. Longitudinal data of 281 individuals (T2DM n = 237 vs matched non-T2DM controls n = 44) were extracted, checked for errors and logical inconsistencies and then subjected to Trajectory Analysis over a period of up to 70 years based on calculations of the proportions of most prominent clinical conditions for each year. RESULTS: For individuals who eventually had a diagnosis of T2DM made, a number of clinical phenotypes were seen to increase consistently in the years leading up to diagnosis of T2DM. Of these documented phenotypes, the most striking were diagnosed hypertension (more than in the control group) and asthma. This trajectory over time was much less dramatic in the matched control group. Immediately prior to T2DM diagnosis, a greater indication of ischaemic heart disease proportions was observed. Post-T2DM diagnosis, the proportions of T2DM patients exhibiting hypertension and infection continued to climb rapidly before plateauing. Ischaemic heart disease continued to increase in this group as well as retinopathy, impaired renal function and heart failure. CONCLUSION: These observations provide an intriguing and novel insight into the onset and natural progression of T2DM. They suggest an early phase of potentially related disease activity well before any clinical diagnosis of diabetes is made. Further studies on a larger cohort of DARE patients are underway to explore the utility of establishing predictive risk scores.

Habitat-specificity and diversity of culturable cold-adapted yeasts of a cold-based glacier in the Tianshan Mountains, northwestern China.

Asian cold-based glacier yeasts with respect to their abundance, distribution, and taxonomy, in contrast to other continental cryosphere areas, have been little investigated. The present study reports the diversity and phylogeny of culturable cold-adapted yeasts in six cold habitats of the Glacier No.1 in the Tianshan Mountains (northwestern China). Of the total 591 yeast isolates, 401 were identified as basidiomycetous yeasts represented by 41 species of 15 genera, while 190 ascomycetous yeast isolates were assigned to the 8 species of 7 genera. The most prevalent species was Candida akabanensis with a 19.8% frequency of occurrence, followed by Vishniacozyma victoriae (16.4%) and Diutina rugosa (9.98%), of which V. victoriae was the only yeast species common to all six glacial habitats. Variability on the component and abundance of yeast taxa among glacial habitats primarily displayed in four dominant yeast genera, namely Candida, Vishniacozyma, Filobasidium, and Naganishia. However, network analysis illustrated that most of 32 rare yeast populations were habitat-specific, implying that the low-abundance yeast population was more easily influenced by the local habitat conditions (species sorting). Based on indicator species analyses, the subglacial habitat was characterized by psychrotolerant and/or psychrophilic yeast taxa.

Efficient nitrogen removal from synthetic domestic wastewater in a novel step-feed three-stage integrated anoxic/oxic biological aerated filter process through optimizing influent flow distribution ratio.

In this study, a novel step-feed three-stage integrated anoxic/oxic biological aerated filter (STIAOBAF) process was developed to enhance nitrogen removal from the synthetic domestic wastewater through optimizing influent flow distribution ratio (IFDR) for three stage reactors (R1, R2, R3). Long-term operation demonstrated that the maximum nitrogen removal efficiency was achieved at the IFDR of 30%:50%:20%. The corresponding effluent total nitrogen (TN) was less than 10 mg/L, superior to the first A grade discharge standard of China (Effluent TN < 15 mg/L). The IFDR was further optimized to 32%:49%:19% by response surface methodology (RSM) model, thus obtaining the highest TN removal efficiency of 81.4%. Nitrogen profiles suggested the 2nd stage reactor was the greatest significant contributor for nitrogen removal of the whole system. Microbial community analysis revealed that Chloroflexi, Bacteroidetes, Firmicutes, and Acidobacteria were abundant in anoxic zones, while Planctomycetes, Bacteroidetes and Verrucomicrobia were rich in oxic zones. Nitrogen removal-associated functional bacterial groups (Nitrospira, Thauera, Azospira and Candidatus Kuenenia) were also identified, supporting high-rate nitrogen removal through the combination of anoxic denitrification with aerobic simultaneous nitrification and denitrification (SND). The STIAOBAF will offer a compact and robust alternative for advanced nitrogen removal from the sewage.

Heterocumulene Sulfinyl Radical OCNSO.

Neutral five-atomic cumulenes formally consisting of two pseudohalogens (e.g., NCO, NNN, NSO) by sharing the central nitrogen atom are exotic species that have been barely studied. Through flash vacuum pyrolysis of CF3 S(O)NCO at ca. 1200 K, sulfinyl isocyanate, bearing resonance structures of O=C-N=S=O and O=C=N-S=O, has been generated in the gas phase and subsequently characterized in cryogenic matrices (Ar and N2 ). Its reversible conformational (syn and anti) interconversion and photodecomposition were observed.

Gas-Phase Generation and Decomposition of a Sulfinylnitrene into the Iminyl Radical OSN.

The dipolar oxathiazyne-like sulfinylnitrene RS(O)N, a highly reactive α-oxo nitrene, has been rarely investigated. Upon flash vacuum pyrolysis of sulfinyl azide CF3S(O)N3 at 350 °C, an elusive sulfinylnitrene CF3S(O)N was generated in the gas phase in its singlet ground state and was characterized by matrix-isolation IR spectroscopy. Further fragmentation of CF3S(O)N at 600 °C produced CF3 and a novel iminyl radical OSN, an SO2 analogue, which were unambiguously identified by IR spectroscopy. Consistent with the experimental observations, DFT calculations clearly support a stepwise decomposition mechanism of CF3S(O)N3.

Thermally persistent carbonyl nitrene: FC(O)N.

Transient carbonyl nitrenes RC(O)N, formed during thermal- or photoinduced decomposition of carbonyl azides RC(O)N3, are highly liable to the Curtius rearrangement, producing isocyanates RNCO in almost quantitative yield. Contrary to common belief, we found a thermally persistent triplet carbonyl nitrene, FC(O)N, that can be produced by flash pyrolysis of FC(O)N3 in 49% yield. The computed CBS-QB3 activation barrier for the thermal decomposition of FC(O)N3 to FC(O)N is 29 kJ mol(-1) lower than that for a concerted pathway producing FNCO.

SN2P2: a neutral five-membered sulfur-pnictogen(III) ring.

The novel aromatic ring compound 2,4-diphospha-3,5-diaza-thiole (cyclo-SNPNP) was synthesized via flash pyrolysis of SP(N3)3 and characterized by IR spectroscopy and (15)N isotope labeling. Quantum chemical computations indicate its formation by head-to-tail dimerization of SNP and subsequent elimination of a sulfur atom from the highly unstable boatlike six-membered-ring compound cyclo-SNPSNP.

Protein Modifications During Early Embryo Development.

BACKGROUND: Infertility is a global reproductive health burden. Assisted reproductive technologies (ARTs) have been widely used to help patients become pregnant. Few embryos develop to the blastocyst stage with ARTs, leading to relatively low live birth rates. Protein modifications play crucial roles in nearly every aspect of cell biology, including reproductive processes. The aim of this study was to explore the characteristics of protein modifications during embryonic development. METHODS: Proteomic data from humans and mice were acquired from the integrated proteome resources (iProX) of ProteomeXchange (PXD024267) and a tandem mass tag (TMT)-mass spectrometry dataset. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied for functional annotation. Protein-protein interactions (PPIs) of the modification-related genes were revealed by the STRING database. Modified proteins during mouse embryogenesis were visualized through heatmaps of hierarchically clustering using k-means. RESULTS: We identified modification-related proteins in human embryo development and characterized them through heatmaps, GO analysis, KEGG analysis, and PPI network analysis. We found that the 4-cell stage to the 8-cell stage might be the demarcation period for modification-related protein expression patterns during embryo development. Using quantitative mass spectrometry, we elucidated the methylation, acetylation, and ubiquitination events that occur during mouse embryogenesis to validate our findings in human embryonic development to some extent. CONCLUSIONS: The results of our study suggest that the posttranslational modifications (PTMs) of human preimplantation embryos might exhibit the same trends as those in mice to exert synergistic and fine-tuned regulatory effects during embryonic development.