Metabolomics analysis of serum metabolites during endometrial transformation: association with recurrent implantation failure in hormonal replacement therapy-frozen embryo transfers cycles.

PURPOSE: The purpose of this study was to investigate alterations in serum metabolites during endometrial transformation and possible associations with recurrent implantation failure (RIF) in hormonal replacement therapy (HRT)-frozen embryo transfer (FET) cycles. METHODS: We performed a prospective study involving 100 patients scheduled for HRT-FET cycles during January 2022 to April 2022. Blood serum samples were collected on the day of progesterone administration (dPA) and on the third day of progesterone administration (d3PA). Gas chromatography-mass spectrometry (GC-MS) analysis was performed to identify and quantify serum metabolites. A nested case-control study including 19 RIF patients and 19 matching controls was conducted to explore the predictive value of serum metabolites for RIF. Partial least squares discriminant analysis (PLS-DA) and receiver operating characteristic (ROC) curve analysis were performed to establish prediction models. MAIN RESULTS: We identified 105 serum metabolites, with 76 of them exhibiting significant alterations during the initial 3 days of endometrial transformation. Metabolites involved in amino acid metabolism and tricarboxylic acid (TCA) cycle showed lower levels during endometrial transformation. In the nested case-control study, the prediction model based on the ratio of serum metabolites between d3PA and dPA showed the highest area under the ROC curve (AUC), accuracy, and R2 and Q2 values. Eight metabolites, including indol-3-propionic acid, beta-alanine, myristoleic acid, malic acid, indole, DL-isocitric acid, proline, and itaconic acid, exhibited high predictive values for RIF. CONCLUSION: This study demonstrates alterations in serum metabolites during endometrial transformation, particularly in amino acid metabolism and TCA cycle. The identified metabolites, especially indol-3-propionic acid and malic acid, show potential as predictive markers for RIF. These findings contribute to a better understanding of the metabolic changes associated with endometrial receptivity and provide insights for the development of personalized approaches to improve implantation outcomes in FET cycles.

Metabolomic profiling identifies hair as a robust biological sample for identifying women with cervical cancer.

Metabolomics serves as a useful tool for identifying biomarkers of disease and uncovering pathogenic mechanisms. However, most metabolomic studies use biological fluids such as blood and urine as biospecimens, which could be dramatically influenced by daily activities and dietary variation, resulting in measurement fluctuations. In contrast, hair may serve as a robust source of stable longitudinal metabolite information. Here, we conducted a pilot study to investigate the possibility of using hair as a biospecimen for the metabolomic analysis of cervical cancer. Hair, plasma, urine, and cervical tissue samples from cervical cancer and benign tumor patients were collected. Biospecimens were then tested using a gas chromatography-mass spectrometry-based metabolomic platform. The expressions of enzymatic genes related to metabolic changes were validated using qPCR. Statistical analyses were calculated via the R-console platform. Metabolite profiles in both hair and cervical tissue samples were significantly different between cancer and control groups, while no difference was observed in plasma and urine samples. Further analysis showed that most of the altered metabolites in hair were upregulated, and they had a negative correlation with those in the cervical tissue. Eight common metabolites showed an area under the Receiver Operating Characteristic curve greater than 0.95. These metabolites primarily participated in amino acid metabolism, cofactor synthesis, ferroptosis, and glycolysis. The gene expressions (IDH1, OGDH, GLUD1, ENO1, GSS, and GPX4) associated with the shortlisted metabolic pathways were also upregulated. Our study is the first to reveal metabolomic changes of hair in cervical cancer patients and demonstrates the potential for the hair metabolome to be used for biomarker identification in cervical cancer.

Evaluating Different Extraction Approaches for GC-MS Based Metabolomics Analysis of the Giant Pandas' Fur.

Giant pandas in zoo captivity are situated in residential areas, where environmental pollutants and anthropogenic factors have an impact on their health. Hair metabolomics has been applied in numerous environmental toxicological studies. Therefore, the panda fur metabolome could be a reliable approach to reflect endogenous and exogenous metabolic changes related to environmental exposure. However, there is no established extraction protocol to study the fur metabolome of pandas. The aim of this research was to optimize the extraction of panda fur metabolome for high-throughput metabolomics analysis using gas chromatography-mass spectrometry. Fur samples were collected from five pandas. Eight different extraction methods were investigated and evaluated for their reproducibility, metabolite coverage, and extraction efficiency, particularly in relation to the biochemical compound classes such as amino acids, tricarboxylic acid cycle derivatives, fatty acids, and secondary metabolites. Our results demonstrated that HCl + ACN were the superior extraction solvents for amino acid and secondary metabolite extraction, and NaOH + MeOH was ideal for fatty acid extraction. Interestingly, the metabolomic analysis of panda fur was capable of discriminating the longitudinal metabolite profile between black and white furs. These extraction protocols can be used in future study protocols for the analysis of the fur metabolome in pandas.

Complex metabolic interactions between ovary, plasma, urine, and hair in ovarian cancer.

Ovarian cancer (OC) is the third most common malignant tumor of women accompanied by alteration of systemic metabolism, yet the underlying interactions between the local OC tissue and other system biofluids remain unclear. In this study, we recruited 17 OC patients, 16 benign ovarian tumor (BOT) patients, and 14 control patients to collect biological samples including ovary plasma, urine, and hair from the same patient. The metabolic features of samples were characterized using a global and targeted metabolic profiling strategy based on Gas chromatography-mass spectrometry (GC-MS). Principal component analysis (PCA) revealed that the metabolites display obvious differences in ovary tissue, plasma, and urine between OC and non-malignant groups but not in hair samples. The metabolic alterations in OC tissue included elevated glycolysis (lactic acid) and TCA cycle intermediates (malic acid, fumaric acid) were related to energy metabolism. Furthermore, the increased levels of glutathione and polyunsaturated fatty acids (linoleic acid) together with decreased levels of saturated fatty acid (palmitic acid) were observed, which might be associated with the anti-oxidative stress capability of cancer. Furthermore, how metabolite profile changes across differential biospecimens were compared in OC patients. Plasma and urine showed a lower concentration of amino acids (alanine, aspartic acid, glutamic acid, proline, leucine, and cysteine) than the malignant ovary. Plasma exhibited the highest concentrations of fatty acids (stearic acid, EPA, and arachidonic acid), while TCA cycle intermediates (succinic acid, citric acid, and malic acid) were most concentrated in the urine. In addition, five plasma metabolites and three urine metabolites showed the best specificity and sensitivity in differentiating the OC group from the control or BOT groups (AUC > 0.90) using machine learning modeling. Overall, this study provided further insight into different specimen metabolic characteristics between OC and non-malignant disease and identified the metabolic fluctuation across ovary and biofluids.

Diagnosis of the accurate genotype of HKαα carriers in patients with thalassemia using multiplex ligation-dependent probe amplification combined with nested polymerase chain reaction.

BACKGROUND: Patients carrying the HongKongαα (HKαα) allele and -α/ααα could be misdiagnosed as -α/αα by the current conventional thalassemia detection methods, leading to inaccurate genetic counseling and an incorrect prenatal diagnosis. This study was aimed to accurately analyze the genotypes of HKαα carriers and -α/ααα. METHODS: Samples were collected in our hospital from July 2017 to October 2019. Twenty-four common types of Chinese thalassemia were screened by gap-polymerase chain reaction (Gap-PCR) and reverse dot blot (RDB). Anti-4.2 multiplex-PCR was used to confirm carriers of the ααα duplication with -α deletion. Two-round nested PCR and multiplex ligation-dependent probe amplification (MLPA) were applied to accurately identify and confirm their genotypes. For data analysis, we used descriptive statistics and Fisher's exact tests. RESULTS: Two thousand five hundred and forty-four cases were identified as thalassemia in 5488 peripheral blood samples. The results showed that α, ß, and αß compound thalassemia were identified in 1190 (46.78%), 1286 (50.55%), and 68 (2.67%) cases, respectively. A total of 227 samples from thalassemia patients were identified as -α/αα by Gap-PCR, and the genotypes of two samples were uncertain. There was a difference between Gap-PCR and combined groups (Gap-PCR combined with nested PCR and MLPA) in detecting HKαα (P < 0.05). Among the 229 patients, 20 patients were identified as HKαα carriers and one was identified as -α/ααα by two-round nested PCR and MLPA, including 15 patients with HKαα/αα, three with HKαα/αα and ß-thalassemia coinheritance, one with HKαα/--, one with HKαα/-α and ß-thalassemia coinheritance, and one with -α/ααα and ß-thalassemia coinheritance. CONCLUSIONS: ααα and HKαα genotypes of patients carrying -α need to be detected to reduce the misdiagnosis rate of patients carrying HKαα and -α3.7/ααα alleles. More accurate genetic counseling can be provided in the clinic using nested PCR combined with MLPA.

Amphiphilic Fullerenes Employed to Improve the Quality of Perovskite Films and the Stability of Perovskite Solar Cells.

Fullerene end-capped polyethylene glycol (C60-PEG) was introduced via an antisolvent method to fabricate the perovskite films. C60-PEG could enlarge the perovskite crystal size and passivate the defects of perovskite films, facilitating the carrier transport and hindering the carrier recombination. In consequence, the superior optoelectronic properties were attained with an improved power conversion efficiency of 17.71% for the perovskite device with C60-PEG treatment. Meanwhile, amphiphilic C60-PEG enhanced the resistance of perovskite films to moisture. After 40 days, the C60-PEG-based devices without encapsulation remained 93 and 86% of the original power conversion efficiency value under nitrogen and ambient conditions (25 °C temperature, 60% humidity), respectively.

[Analysis of NF1 gene mutations among eleven sporadic patients with neurofibromatosis type 1].

OBJECTIVE: To explore the genetic etiology for 11 sporadic patients with neurofibromatosis type 1. METHODS: Chip targeting capture and high-throughput sequencing were employed to detect potential mutations of NF1 and NF2 genes among the 11 patients. The data was filtered through multiple mutational databases and in-house whole exome sequence database. Sanger sequencing was used for analysis of family members of the patients. RESULTS: Eleven pathogenic variants were found among the 11 patients, which included two splicing mutations, one missense mutation, two nonsense mutations, and six frame-shifting mutations. None of the mutations was recorded by the public database or the in-house database generated from 1775 samples through whole exome sequencing. None of the unaffected parents carried the same mutation. Seven mutations were associated with neurofibromatosis type 1 previously, while the remaining four were discovered for the first time. Prenatal diagnosis of two high-risk pregnancies suggested that neither fetus has inherited the NF1 mutation from their affected parents. CONCLUSION: Identification of causative mutations in patients with sporadic-type neurofibromatosis type 1 has provided a basis for genetic counseling. The four novel mutations have enriched the spectrum of NF1 gene mutations.

Recent Progress on the Long-Term Stability of Perovskite Solar Cells.

As rapid progress has been achieved in emerging thin film solar cell technology, organic-inorganic hybrid perovskite solar cells (PVSCs) have aroused many concerns with several desired properties for photovoltaic applications, including large absorption coefficients, excellent carrier mobility, long charge carrier diffusion lengths, low-cost, and unbelievable progress. Power conversion efficiencies increased from 3.8% in 2009 up to the current world record of 22.1%. However, poor long-term stability of PVSCs limits the future commercial application. Here, the degradation mechanisms for unstable perovskite materials and their corresponding solar cells are discussed. The strategies for enhancing the stability of perovskite materials and PVSCs are also summarized. This review is expected to provide helpful insights for further enhancing the stability of perovskite materials and PVSCs in this exciting field.